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WO2003007187A1 - Procede d'evaluation de ligand et utilisation de ce procede - Google Patents

Procede d'evaluation de ligand et utilisation de ce procede Download PDF

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Publication number
WO2003007187A1
WO2003007187A1 PCT/JP2002/007057 JP0207057W WO03007187A1 WO 2003007187 A1 WO2003007187 A1 WO 2003007187A1 JP 0207057 W JP0207057 W JP 0207057W WO 03007187 A1 WO03007187 A1 WO 03007187A1
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Prior art keywords
binding molecule
protein
amino acid
residue
ligand
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Japanese (ja)
Inventor
Hiroshi Inooka
Yoshio Yamamoto
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Takeda Pharmaceutical Co Ltd
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Takeda Chemical Industries Ltd
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    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/435—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans
    • C07K14/705—Receptors; Cell surface antigens; Cell surface determinants

Definitions

  • the present invention relates to a method for predicting a binding molecule of an unknown binding molecule protein, a method for producing a medicine using the prediction method, and a computer for predicting a binding molecule of the unknown binding molecule protein.
  • a medicine using the method for predicting a binding molecule or a type of a binding molecule of an unknown protein of a binding molecule from information on the amino acid sequence (or sequence alignment) of the protein and the type of the binding molecule or the type of the binding molecule.
  • a medicine using the method and the method It relates to a computer used for.
  • the present invention relates to a method for predicting the function of a protein whose binding molecule is unknown through prediction of the binding molecule and the type of the binding molecule.
  • the protein examples include a protein that binds a low-molecular substance, an enzyme that has catalytic activity for a low-molecular or high-molecular substance, and a protein that binds a high-molecular substance.
  • an enzyme that has catalytic activity for a low-molecular or high-molecular substance
  • a protein that binds a high-molecular substance there are a very large number of drugs that target proteins that bind low molecular substances.
  • Proteins of particular interest as target molecules include G protein-coupled receptor proteins involved in signal transduction as membrane proteins.
  • GPCR Geneincouplederecrecint
  • GPCRs have an N-terminal outside the cell, have a topology with a C-terminal inside the cell via a seven transmembrane domain, and the ligand binds to the N-terminal region or transmembrane region depending on the type. It is also known that G protein binds to the intracellular C-terminal part and intracellular loop 2. To date, the only crystal structure of oral dopsin, a member of the GP CR family, has been analyzed (Palczewski et al., Science, Vol. 289, pp.
  • GPCR activation occurs as follows. That is, (i) the ligand binds to the receptor and the structure of the GPCR changes. (Ii) Conjugation changes of the GPCR are transmitted to the conjugated G protein, and a part of the G protein is released. (Iiii) Information (signal) is transmitted into cells. Molecules that specifically bind to the receptor are called ligands.
  • known ligand molecules include living amines such as dopamine, serotonin, melatonin, and histamine, lipid derivatives such as prostaglandins and leukotrienes, amino acids such as nucleic acid and glutamine, angiotensin, secretin, and somatosutin. And physiologically active peptides such as
  • the G protein functions as a transducer in the signal transduction system, and is composed of three subunits, i, ⁇ , and ⁇ .
  • the ⁇ subunit has the activity of binding to GTP and hydrolyzing G ⁇ ⁇ , and is a subunit unique to each G protein. That is, the function of GPCR is determined by the type of Ga protein to be conjugated.
  • Go Go; G s and G or G as proteins. And Gt have been isolated and purified, and their properties have been investigated.
  • G protein-coupled receptor protein is present on the surface of each functional cell in living cells and organs, and is a target for molecules that regulate the function of those cells and organs, such as hormones, neurotransmitters, and biologically active substances. Plays a physiologically important role.
  • the receptor transmits a signal into the cell via binding to a physiologically active substance, and this signal causes various reactions such as suppression of activation and activation of the cell.
  • G protein-coupled receptor Yuichi proteins To clarify the relationship between substances that regulate complex functions in various cells and organs and their specific receptor proteins, especially G protein-coupled receptor Yuichi proteins, it is important to clarify the complex functions in various cells and organs. Will provide a very important tool for drug development closely related to these functions.
  • G protein-coupled receptors Not all G protein-coupled receptors have been found, and even at this time, there are many unknown G protein-coupled receptors and so-called orphan receptors for which no corresponding ligand has been identified. It is present, and the search for new G protein-coupled receptors and the elucidation of their functions are eagerly awaited.
  • Methods for predicting binding molecules and functions from sequence information include, for example, mutations of amino acids (and their mutation positions) that are considered to be involved in determining the type of G protein to be coupled to a limited number of known GPCRs.
  • mutations of amino acids (and their mutation positions) that are considered to be involved in determining the type of G protein to be coupled to a limited number of known GPCRs.
  • a method for predicting the site involved in binding of a ligand to its GPCR by analyzing mutations in both GPCR and ligand amino acids that is, a correlated mutation analysis (CMA) method was developed (Singer et al., Receptors and channels, 3: 89-95 (1995)), there is no report that a GPCR sequence alone was used to select unknown GPCR binding molecules (and / or types of binding molecules).
  • CMA correlated mutation analysis
  • GPCRs it is not known how to predict molecules or types of molecules that bind (or conjugate) to GPCR directly from the sequence information of GPCR, and predict the function. Not been.
  • GPCRs if a new GPCR is discovered, in order to manufacture a drug using the GPCR, it must bind to (or conjugate to) the GPCR after understanding the function of the GPCR. There is a problem that it is necessary to grasp the molecule or the kind of the molecule through experiments or the like, which requires enormous cost and labor. Disclosure of the invention
  • the present invention relates to a method for simply and accurately predicting a molecule or the like that can bind to sequence information of unknown function, a method for producing a medicine using the method, and a computer used for the method.
  • a binding molecule unknown protein prediction method for predicting a binding molecule that binds to a binding molecule unknown protein, wherein the amino acid sequence and the binding molecule are known obtaining a binding molecule known protein classification information in which the sequence alignment of the binding molecule known protein is associated with the type of the binding molecule or the binding molecule; and using the binding molecule known protein classification information, the binding molecule known protein. Specifying one or more binding molecule-determining residue positions that are assumed to be involved in determining a binding molecule among the sequence alignment positions of the amino acid sequence; and aminos at the binding molecule-determining residue positions.
  • binding molecule determining residues By associating acid residues (binding molecule determining residues) with binding molecules or types of binding molecules Obtaining a binding molecule-determining residue-binding molecule classification information indicating a correlation between the binding molecule-determining residue and the binding molecule or the type of the binding molecule; and for a binding molecule unknown protein of the same type as the binding molecule-known protein.
  • the binding molecule is any one of a ligand, a regulator, an effector, and a coenzyme.
  • the binding protein unknown protein is any one of a G protein-coupled receptor, a kinase, a lipase, a transporter, a protease, and an ion channel according to any of (1) to (3) above; Method for predicting binding molecules of unknown proteins.
  • the one or more binding molecule-determining residue positions are identified from amino acid residues constituting the sequence alignment and types of binding molecules.
  • the method for predicting a binding molecule of an unknown protein according to any one of (1) to (4).
  • Binding molecule prediction method determining the position of the binding molecule-determining residue using at least one of Formulas 3, 4, and 5; and determining the position of the unknown binding molecule protein according to any one of (1) to (4) above. Binding molecule prediction method.
  • the step of obtaining the ligand-determined residue-ligand classification information extracts the amino acid residues of the ligand-known protein at the position of the ligand-determined residue with the smallest value of the function f 3 (n). Determining the number (A) of ligand-determined residues that match the extracted ligand-determined residues among the ligand-known proteins listed in the ligand-determined residue-ligand classification information; Obtaining a number (B) of the known ligand proteins which correspond to the extracted ligand-determining residues among the known ligand proteins, wherein the type of the ligand or the ligand matches that of the known ligand protein; and Among the amino acid residues of known proteins, the value of the function f3 (n) is the second smallest or the Xth (where X represents an integer greater than 2 and less than 100).
  • Extracting the one at the position of the smallest ligand-determined residue, and the ligand-known protein listed in the ligand-determined residue-ligand classification information Determining the number (C) of the extracted ligand-determining residues that match the extracted ligand-determining residues; and matching the extracted ligand-determining residues among the ligand-known proteins listed in the ligand-determining residue-ligand classification information.
  • binding in which the sequence alignment of the binding protein known protein is associated with the binding molecule or the type of binding molecule A step of obtaining information on the classification of known protein molecules, and a binding molecule which is a position assumed to be involved in determining a binding molecule in the sequence alignment of the known binding molecules using the classification information on known binding molecules.
  • a binding molecule which is a position assumed to be involved in determining a binding molecule in the sequence alignment of the known binding molecules using the classification information on known binding molecules.
  • the binding molecule determination residue indicating the correlation between the binding molecule determination residue and the binding molecule.
  • the binding molecule classification information includes the binding molecule unknown protein of the same type as the binding molecule known protein.
  • this method it is possible to predict the binding molecule or the type of the binding molecule only by obtaining information on the amino acid sequence of the protein whose binding molecule is unknown and the sequence alignment obtained using Z or the amino acid sequence. .
  • This makes it much faster than conventional molecular modeling methods that predict even three-dimensional structures. It can predict the binding molecule (ligand etc.) at a low cost.
  • it is possible to predict the binding molecule or the type of the binding molecule for a protein in which various types of binding molecules are unknown.
  • it is possible to predict the binding molecule or the kind of the binding molecule easily and quickly than by experimenting whether or not any candidate binding molecule actually binds to the protein whose binding molecule is unknown.
  • Determining residue of binding molecule By obtaining the classification information of one binding molecule, the sequence is applied only to the sequence alignment of the unknown protein, and the information is applied to the table, and the type of the binding molecule or binding molecule that binds to the unknown protein. Can be easily predicted.
  • a method for producing a medicament comprising the step of:
  • the binding molecule in the position of the sequence alignment of the protein with the known binding molecule is used.
  • Molecule binding residue which is an amino acid residue at a position supposed to be involved in the determination of the binding molecule (binding molecule determining residue position), and a binding molecule determination residue indicating the correlation between the binding molecule or the type of the binding molecule.
  • a sequence alignment input means for inputting information on the sequence alignment of the protein; an amino acid sequence or sequence alignment of the binding molecule known protein input by the sequence alignment input means; and a binding molecule or a binding molecule.
  • a sequence alignment binding molecule storage means for storing information on the type; an amino acid sequence or sequence alignment of the binding molecule known protein stored by the sequence alignment binding molecule storage means; and a type of the binding molecule or the binding molecule.
  • a binding molecule determining residue position determining means for determining the binding molecule determining residue position using information; an amino acid residue (binding molecule determining residue) at the binding molecule determining residue position; Type and By associating, the binding molecule determination residue-binding molecule classification information obtaining means for obtaining the binding molecule determination residue-binding molecule classification information indicating the correlation between the binding molecule determination residue and the binding molecule or the type of the binding molecule; Information on the sequence alignment of the unknown binding molecule protein obtained by aligning the sequence of the unknown binding molecule protein with respect to the sequence alignment between the unknown binding molecule proteins for the same type of unknown binding molecule protein as the known binding molecule protein Inputting sequence alignment input means, and using the information on the sequence alignment of unknown binding molecule proteins input by the sequence alignment input means as the binding molecule determination residue-binding molecule classification information.
  • Bound molecule unknown protein Binding molecule or to predict the kind of binding molecules, binding molecules unknown evening protein computer for predicting the binding molecule,
  • the binding molecule-determining residue position determining means predicts the binding molecule of the binding molecule unknown protein according to (14) using at least one of the functions of Formula 9 and Formula 10 or both functions.
  • the binding molecule-determining residue position determining means uses the function represented by Formula 9 to predict the binding molecule of the binding molecule unknown protein described in (15) or (16) above.
  • a computer for predicting a binding molecule of a binding molecule unknown protein wherein the computer is a sequence alignment of a binding molecule known protein having the same type as the binding molecule unknown protein and a binding molecule known.
  • the binding And a binding molecule determining residue position that is assumed to be involved in determining a molecule that binds to a known protein, and a binding molecule determination that is an amino acid residue of the binding molecule known protein at the binding molecule determining residue position.
  • Sequence alignment input means for inputting information on the sequence alignment of the unknown binding molecule protein obtained by aligning the sequence of the unknown binding molecule protein with the sequence alignment between the binding molecule known proteins.
  • Information and storage means for the entered sequence alignment
  • a binding molecule determining means for determining the binding molecule or the type of the binding molecule of the unknown binding molecule protein from the stored information; and displaying the determined binding molecule or the type of the binding molecule binding to the determined unknown binding molecule protein.
  • Display means the information relating to the sequence alignment of the unknown protein of the binding molecule input by the sequence alignment input means, and the binding molecule determination residue and the binding molecule determination residue stored in the storage means.
  • the binding molecule determination unit predicts the binding molecule or the type of the binding molecule of the unknown binding molecule protein, and is predicted by the binding molecule determination unit. Display the binding molecule or the type of the binding molecule of the unknown binding molecule by the display means.
  • Computer for predicting the binding molecules of the child unknown protein - is even. According to such a computer, it is possible to obtain binding molecule-determined residue-binding molecule classification information based on the sequence alignment of the binding molecule known proteins, and thereby to obtain the sequence alignment of the binding molecule unknown protein. Only by obtaining, the binding molecule or the type of the binding molecule can be easily predicted.
  • a computer is connected to a sequence alignment input means for inputting information on the sequence alignment of the known binding molecule protein, and the amino acid sequence or the amino acid sequence of the binding molecule known protein input by the sequence alignment input means.
  • Sequence alignment and binding molecules or types of binding molecules Sequence-binding molecule storage means for storing information on the amino acid sequence or sequence alignment of a known binding molecule protein stored by the sequence alignment-binding molecule storage means, and information on the type of the binding molecule or the binding molecule.
  • a binding molecule-determining residue position determining means for determining the binding molecule-determining residue position using: a binding molecule determining residue position; an amino acid residue (binding molecule determining residue) at the binding molecule determining residue position; By associating the type with the binding molecule determining residue and the binding molecule or the type of the binding molecule, the binding molecule representing the correlation between the binding molecule determining residue and the type of the binding molecule is obtained. And the above step, for the unknown binding molecule protein of the same type as the known binding molecule protein. Sequence alignment input means for inputting information on sequence alignment of unknown binding molecules obtained by aligning sequences of unknown binding molecules with respect to sequence alignment between known proteins of combined molecules. program,
  • Binding molecule-determining residue position that is supposed to be involved in the binding molecule; binding molecule-determining residue that is an amino acid residue of a binding molecule known protein at the binding molecule-determining residue position; Storage means for storing information on the binding molecule or the type of binding molecule of the binding molecule known protein corresponding to the group; and a sequence alignment between the binding molecule known protein for the same type of binding molecule unknown protein as the binding molecule known protein.
  • Unknown protein obtained by aligning the sequence of unknown protein to And Sequence ⁇ Line Instrument input means for inputting information about the Sequence alignment of Park protein, input Sequence ⁇ Line ment Information storage means the binding molecule from the information stored in the unknown protein
  • FIG. 1 shows a process chart from creation of ligand-determined residue-ligand classification information of the present invention.
  • FIG. 2 is a process chart showing one embodiment of the ligand-determining residue position specifying step of the present invention.
  • FIG. 3 is a process chart showing another embodiment of the ligand-determining residue position specifying step of the present invention.
  • FIG. 4 shows the results of sequence alignment between silodopsin and TGR 23-1.
  • FIG. 5 shows the activity of increasing the intracellular Ca ion concentration of TGR23-1-expressing CHO cells with various concentrations of human TGR23.2 ligand (1-20) measured using FLIPR.
  • FIG. 6 shows the activity of increasing the intracellular Ca ion concentration of TGR23-2 expressing CHO cells by various concentrations of human TGR23-2 ligand (112) measured using FLIPR.
  • the present invention relates to a known binding molecule protein whose amino acid sequence and binding molecule are known, wherein the binding alignment is performed by associating at least two or more binding molecule known proteins with the binding molecule or the type of the binding molecule.
  • One or more determined residue positions Determining the binding molecule-determining residue and the binding molecule or the binding molecule by associating the amino acid residue (binding molecule determination residue) at the binding molecule-determining residue position with the type of the binding molecule or the binding molecule.
  • the binding molecule-determining residue-binding molecule classification information indicating the correlation with the type of the binding molecule; and a sequence alignment between the binding molecule unknown proteins of the same type as the binding molecule unknown protein. Aligning the sequence of the unknown binding molecule protein to obtain a sequence alignment of the unknown binding molecule protein, and obtaining information on the binding molecule determining residue in the sequence alignment of the unknown binding molecule protein.
  • the present invention relates to a method for predicting a binding molecule of an unknown protein, which predicts the type of the binding molecule.
  • a binding molecule known protein means a protein for which a biomolecule that binds to the protein is known.
  • it refers to a protein to which a biological molecule specifically binds, such as a receptor whose ligand is known.
  • An unknown binding molecule protein refers to a protein of the same type as a known binding molecule protein, wherein the binding molecule is unknown.
  • a sequence alignment of the unknown binding molecule protein obtained by aligning the sequence of the unknown binding molecule protein with respect to the sequence alignment between the known binding molecule proteins with respect to the same type of unknown binding molecule protein as the known binding molecule protein.
  • the insertion taking into account the substitution, insertion, and deletion, A gap was inserted at the position corresponding to the deletion, and the entire sequence was juxtaposed.
  • unknown binding molecule proteins and known binding molecule proteins examples include G protein-coupled receptors (GPCRs), kinases, lipases, transporters, proteases, and ion channels. Of these, the present invention can be preferably applied to G protein-coupled receptors (GPCRs) and kinases.
  • GPCRs G protein-coupled receptors
  • the unknown binding molecule protein and the known binding molecule protein are G protein-coupled receptors (GPCRs)
  • the unknown binding molecule protein is also called an orphan receptor.
  • the unknown binding molecule protein and the known binding molecule protein are of the same type. For example, if the protein whose binding molecule is unknown is a GPCR, the protein whose binding molecule is known is also a GPCR.
  • the binding molecule known protein classification information means a table in which sequence alignment of at least two or more binding molecule known proteins is associated with the binding molecule (and Z or the type of the binding molecule).
  • This table is not particularly limited as long as it is in a form that can be stored electronically and visually recognized as a table, not only on paper.
  • the binding molecule determining residue position means a position of a sequence alignment of a protein having a known binding molecule, which is assumed to be involved in determining a binding molecule.
  • the number of ligand-determining residue positions is not particularly limited as long as it is 1 or more, preferably 1 or more and 10 or less, more preferably 2 or more and 6 or less, and particularly preferably 2 or more.
  • more than 100 kinds of ligands are known, so that if there is only one ligand-determining residue position, all ligands cannot be associated with ligand-determining residues.
  • the prediction accuracy increases as the number of ligand determination residue positions increases.
  • p is the number of classifications
  • the classification of the ligand of the unknown protein belongs to which classification the number of ligands (value of ⁇ ) is small.
  • amino acids at two or more ligand-determining residue positions are generally The prediction accuracy becomes higher when the type of ligand is predicted by combining acid residues.
  • the binding molecule determining residue means an amino acid residue at the binding molecule determining residue position.
  • specific residue positions (one or two or more) of a plurality of types of binding molecules and a plurality of types of amino acid residues may be combined with a known protein of the binding molecule to be used as a residue for determining a binding molecule.
  • the second and eighth amino acid residue positions in the sequence alignment are taken as examples of the binding molecule-determining residue positions
  • the ninth and eleventh amino acid residues in the sequence alignment are taken as other examples. This is the case. Combining different binding molecule determining residue positions in this manner makes it possible to improve the accuracy of predicting the binding molecule or the type of the binding molecule.
  • the information on the binding molecule determining residue means information on the amino acid residue at the binding molecule determining residue position. For example, if the second and eighth positions in the sequence alignment of the protein are binding molecule determinant residue positions, the second and eighth positions in the sequence alignment are information on the positions of the binding molecule determinant residues. Then, in the sequence alignment, information on the types of the second and eighth amino acid residues and information on the position of the binding molecule determining residue are combined to provide information on the binding molecule determining residue.
  • the binding molecule determining residue-binding molecule classification information is a table showing the correlation between the binding molecule determining residue and the binding molecule or the type of the binding molecule. This table is not particularly limited as long as it is in a form that can be stored electronically and visually recognized as a table as well as on paper.
  • the binding molecule is not particularly limited as long as the correspondence between the binding molecule determining residue and the type of the binding molecule or the binding molecule can be recognized.
  • the binding molecule is not particularly limited as long as it can bind to known binding molecule proteins and unknown binding molecule proteins that are biopolymers.
  • ligands that bind to receptor proteins and GPCRs G ⁇ protein that binds. [Type of binding molecule]
  • the type of binding molecule is a type in which, when a plurality of binding molecules exist in the same type of known binding molecule protein, they are classified according to their functions and properties. For example, there are cases where GPCR ligands are classified into monoamines, lipids, and peptides.
  • the computer of the present invention is not particularly limited as long as it is an electronic device capable of performing a certain calculation or the like.
  • a known computer such as a personal computer, a super computer, and a mobile may be used. You may.
  • a computer equipped with a browser is particularly preferable because it can be connected to the Internet and can access a well-known Web (Web) site.
  • Web Web
  • FIG. 1 shows an example of a process from the generation of ligand-determined residue-ligand classification information, which comprises the following steps. That is, the step of obtaining information on sequence alignment and ligand (and / or ligand type) for at least two or more binding molecule known proteins whose amino acid sequence and ligand (and / or ligand type) are known ( S 101), sequence alignment and ligand (and type of Z or ligand) are associated, and sequence alignment ligand classification information obtaining step for obtaining binding protein known protein classification information (S 102), sequence alignment ligand classification information obtaining The ligand-determining residue positions, which are assumed to be involved in determining the ligand (and / or the type of ligand) in the sequence alignment of the known binding molecule proteins using the information on the classification of the known binding molecule proteins obtained by the process, are described.
  • S104 gand determining residue-ligand classification step
  • the sequence alignment and ligand (and type of Z or ligand) for at least two or more binding molecule known proteins whose amino acid sequence and ligand are known are described.
  • Information is acquired (S101).
  • information on the amino acid sequence and ligand (and / or type of ligand) is obtained for a plurality of known binding molecule proteins, but sequence alignment may be obtained from the amino acid sequence, or a plurality of known binding molecule proteins may be obtained. If sequence alignment has already been requested for, information on the sequence alignment may be obtained directly.
  • the method for obtaining sequence alignment and information on ligands (and Z or the type of ligand) for proteins with known binding molecules is not particularly limited.
  • the database is preferably a database that contains information on sequence alignments and ligands (and / or types of ligands) of at least 100 or more types of known binding molecules, and more preferably 500 or more. It is particularly preferable to record 1000 or more. This is because the greater the number of proteins with known binding molecules, the higher the accuracy of the ligand-determined residue-ligand classification information.
  • the known database is not particularly limited as long as it describes the sequence alignment and ligand (and Z or the type of ligand) of the binding molecule known protein.
  • GPCRDB ht tp: / /www.GPCR.org/7tm/.
  • Sequence alignment can also be obtained by a known calculation method.
  • Known calculation methods for sequence alignment include, for example, Clus tal W and BLAST, but may be calculated manually.
  • a classification for the ligand is created in advance, and if the information on the ligand is input, the type of the ligand is automatically obtained. If the information on the ligand is obtained, the information on the type of the ligand is also obtained. You may make it available. [Step 1 0 2]
  • sequence alignment and the information on the ligand (and the type of Z or ligand) for the two or more binding molecule known proteins obtained in step 101, and the sequence alignment and the information on the ligand (and type of Z or ligand) are obtained.
  • classification information of the binding molecule known protein sequence alignment ligand classification information obtaining step: S102.
  • sequence alignment and ligand (and / or ligand type) information on one or more known binding molecules is obtained from a database or the like, the sequence alignment and the ligand (and / or ligand) have already been performed. If the type is associated with the sequence alignment, the information may be obtained with the sequence alignment and the ligand (and the type of Z or ligand) associated with each other.
  • the ligand (and the type of ligand or ligand) in the sequence alignment of the binding molecule known protein is determined using the binding molecule known protein classification information obtained in the sequence alignment ligand classification information acquisition step of step 102.
  • One or more ligand-determining residue positions, which are assumed to be involved in the above, are specified (ligand-determining residue position specifying step: S103).
  • one or more ligand-determining residue positions are specified by combining preferred functions according to the type and properties of the target protein. A preferred embodiment of this step will be described later.
  • the ligand (and / or the type of ligand) is associated with the amino acid residue (ligand-determining residue) at the ligand-determining residue position specified in the ligand-determining residue position specifying step.
  • ligand-determined residue-ligand classification information indicating the correlation between the ligand and the ligand (ligand determined residue-ligand classification step: S104).
  • information on the ligand-determined residue positions, ligand-determined residues, and ligands (and / or types of ligands) is obtained from the sequence alignment ligand classification information for each GPCR, and the ligand-determined residue-one ligand is obtained. Obtain classification information.
  • ligand-determining residue position identification step S103
  • This step is for the case where the number of ligand-determining residue positions is one.
  • Ligands are classified into!) Types and classified into XI to Xp, respectively.
  • the information on all sequence alignments and ligands (and / or types of ligands) of known binding molecule proteins present in the classification information on binding molecules known in step 102 is input to the following equation 15 and the function fl Since the value of (n) is small, it is determined as a candidate for a ligand-determined residue position (a candidate ligand-determined residue position selection step: S201).
  • the ligand-determined residue positions are determined. It is preferable not to adopt as a ligand-determining residue position
  • n fl (n) as an evaluation function for the nth amino acid residue in the sequence alignment of the binding molecule known protein
  • Res represents the amino acid residue.
  • XQ and Xr represent ligands, Q represents an integer from 1 to p-1, r represents an integer greater than Q and less than or equal to p, p represents the number of ligands, and N ( Res, XQ) represents the number of proteins in which the nth amino acid residue in the sequence alignment is Res and the ligand is among the known binding molecule proteins present in the binding molecule known protein classification information, N (Res, Xr) is the number of proteins whose binding amino acid residue is Res and the ligand is Xr among known binding molecule proteins in the binding molecule known protein classification information.
  • the number of candidate ligand-determining residue positions in the ligand-determining residue position candidate selecting step is not particularly limited, but is preferably 1 or more and 100 or less, more preferably 1 or more and 10 or less. It is particularly preferable that the value is not less than 5 and not more than 5. This is because if there are too many candidate ligand-determined residue positions, the subsequent step of confirming the reliability of candidate ligand-determined residue positions becomes difficult.
  • the candidate ligand-determined residue position selected in the candidate ligand-determined residue position selecting step in step 201 may be used as it is as the ligand-determined residue position candidate. It is more preferable to use and study.
  • Step of examining reliability of candidate ligand-determined residue position S202).
  • the reliability of candidate ligand-determined residue positions is examined using the following equation (16). The smaller the obtained value of f 2 (n), the more suitable the position of the ligand-determining residue.
  • f 2 (n) ⁇ (N (Res, XI) xN (Res, X2) X N (Res, Xp)) Equation 16
  • n represents that f 2 (n) is an evaluation function for the nth amino acid residue in the sequence alignment of the binding molecule known protein, and Res represents the amino acid residue.
  • Res represents the amino acid residue.
  • XI to 3 ⁇ 4 represent the ligand or the type of ligand
  • p represents the number of the ligand or the type of ligand
  • N (Res, X) represents the known binding molecule obtained in step 102.
  • this indicates the number of proteins in which the n-th amino acid residue in the sequence alignment is Res and the ligand is X.
  • the position of a ligand-determining residue is identified (ligand-determining residue position identification step: S 203).
  • the position of the obtained f 2 (ii) having the smallest value may be determined as the ligand-determining residue position, and the product of ⁇ (n) and the value of f 2 (n) that is the smallest may be determined as the ligand-determining residue position.
  • the smallest sum of the values of ⁇ (n) and f 2 (n) may be used as the ligand-determining residue position.
  • the positions of fl (n) are ranked in ascending order, and further, f 2 (n) May be similarly ranked, and both ranks may be multiplied, and the lowest one may be used as the ligand-determining residue position.
  • the sequence alignment at the obtained ligand-determined residue position is not sequence-alignable (indicated by-), but is present in 3% or more of all GPCRs, the ligand-determined residue position is determined by the ligand. It is preferable not to adopt it as a residue position.
  • Step S103 Another preferred embodiment of the ligand-determining residue locating step (S103) will be described.
  • This step is for the case of two ligand-determining residue positions.
  • All sequence alignments of known binding molecule proteins present in the binding molecule known protein classification information obtained in step 102 and information on the ligand or the type of ligand are input to Equation 1, and the ligand-determined residue position is entered.
  • Step for selecting candidate residue position for determining ligand S301).
  • the number of candidate ligand-determining residue positions in the ligand-determining residue position candidate selecting step is not particularly limited, but is preferably 1 or more and 100 or less, more preferably 1 or more and 20 or less, and 2 or more It is more preferably 10 or less, particularly preferably 2 or more and 6 or less. This is because if the number of candidate ligand-determined residue positions is large, the reliability confirmation process of the candidate ligand-determined residue positions becomes difficult, and if the number of candidate candidates is one, it cannot cope with various ligand types.
  • Step of examining reliability of candidate ligand determination residue position S302
  • the process may proceed to step 303 after step 301.
  • step of examining the reliability of the position of the ligand-determined residue at least the amino acid residue position including the candidate position of the ligand-determined residue is input to equation 2 with the sequence alignment of the known binding molecule protein and the ligand. Small value of function f2 (n) The residue is suitable as a residue position for determining a ligand.
  • the position of the ligand-determining residue may be selected from those with the smallest value of the function f 2 (n), or the product of the smallest value of f 1 (n) and ⁇ 2 (n) is determined as the position of the ligand-determining residue. Or the one with the smallest sum of the values of fl (n) and f2 (n) may be selected as the ligand-determining residue position.
  • the amino acid residue positions of the known binding molecule proteins present in the information on the classification of known binding molecules obtained in step 102 are ranked from the one with the lowest f 1 (n), and further the f 2 (n n) may be ranked in the same manner, and both ranks may be multiplied to select a ligand-determining residue position from the lower one. If the sequence alignment at the obtained ligand-determining residue position cannot be sequence-aligned (indicated by-), but is present in 3% or more of the GPCRs described in the information on the classification of known binding molecules, the ligand is determined. It is preferred that residue positions are not employed as residue determining residue positions.
  • a candidate pair for the ligand-determined residue positions is given (step of selecting a pair of ligand-determined residue positions: S303).
  • a candidate pair of ligand-determined residue positions a combination consisting of all candidate ligand-determined residue positions may be used, or a preferred ligand-determined residue position of ⁇ (n) and other residue positions may be used.
  • a candidate pair of ligand-determined residue positions may be given by the combination of
  • a pair of ligand-determined residue positions is identified (pair identification step of ligand-determined residue positions: S304).
  • f 3 (m, n) ⁇ (number of amino acid residue pair types) / wX + wlx (2 cross residue pair types) + w2 X (3 cross residue pair types) tens...
  • wp-1 p cross Number of types of residue pairs
  • wA X number of non-alignable amino acid residues
  • wB X number of non-alignable amino acid residues
  • (m, n) is f 3 (m, n) where the binding molecule is a known protein:
  • the number of types of amino acid residue pairs indicates the number of types of combinations of the mth and nth amino acid residues in the sequence alignment of proteins with known binding molecules.
  • the number of 3 crossing residue pairs means the number of 2 and 3 ligands, respectively, of the combination of the mth and nth amino acid residues in the sequence alignment of the binding molecule known protein.
  • the number of pairs of p-crossing residue pairs is determined by the sequence alignment of known binding molecules, the ligand of which is the combination of the mth and nth amino acid residues!
  • One of the m-th and n-th amino acid residues in the sequence alignment of a protein with a known binding molecule has favorable homology.
  • the number of amino acid residue pairs that cannot be sequence-aligned in order to obtain, and the number of amino acid residue pairs that cannot be sequence-aligned means that both the mth and nth amino acid residues in the sequence alignment of the binding molecule known protein are WX is a positive constant or a distribution function with the number of amino acid pair types as variables, and the number of amino acid pair types is 400 or less in order to obtain favorable homology.
  • WX may be a positive constant, a Gaussian function, or a distribution function.
  • a positive constant although not particularly limited, 1 is preferable.
  • wX is a positive constant or a distribution function with the number of amino acid pair types as a variable, and means a distribution function that gives the maximum value when the number of amino acid pair types is 400 or less.
  • a Gaussian function using the number of types of amino acid pairs as a variable a mouth-to-Lenz function, etc.
  • the maximum value is not particularly limited as long as it is a positive number.
  • the value of the variable that gives the maximum value of is preferably 400 or less, more preferably 20 to 200, and even more preferably 40 to 140. This value indicates that the total number of ligand-determining amino acid pairs is 20 or less.
  • X 20 400, based on experience It is determined because prediction with 40 to 140 amino acid pairs gives the best results.
  • the full width at half maximum of the distribution function is preferably 10 or more and 100 or less, and 20 or more and 7 or less. It is more preferably 0 or less, more preferably 30 or more and 50 or less.
  • the maximum value of the distribution function is preferably 1, although it depends on the relationship with other weights.
  • the value of the weight is not particularly limited as long as it is a positive number. However, for example, when 3 pairs of residue pairs exist, 2 intersection residues It is preferable that the value of w2 is larger than the value of wl because it is more unfavorable in predicting the ligand than the base pair, for example, when the number of ligands is three, there may be more than three crossing residue pairs. There are no combinations of weights in this case: wl is 2, w2 is 5, wA and wB are 1.
  • ligand-determined residue-ligand classification information in which pairs of ligand-determined residue positions are arbitrarily combined.
  • the combination is not particularly limited, but the combination of the function i3 (n) having the smallest value and the second and / or Xth (where X is greater than 2 and less than 100) Represents an integer.) Is combined with a smaller one.
  • the value of the function i3 (m, ⁇ ) is the Xth smallest and the yth (where y is different from X and is greater than 2 and greater than 100) It represents a small integer.
  • the value of the f3 ( ⁇ ) function can be arbitrarily combined with the ligand-determining residues up to the 29th.
  • the X-th and y-th Xs and y's may be input to the computer in advance, or the computer may receive input information from the user and create a combination of ligand-determined residues.
  • the combination of the smallest and the second smallest f 3 (m, n) function limits the number of ligand-locating residues that can predict ligand and / or ligand type.
  • X and y above Is preferably larger than 2 and smaller than 100, more preferably smaller than 50, even more preferably smaller than 30 and particularly preferably smaller than 20.
  • the amino acid residue at the ligand-determining residue position where the value of the function ⁇ 3 (ffl, n) is the smallest is extracted.
  • the number of those that match the extracted ligand-determined residues is determined. Further, among these, the number of the ligands or the types of the ligands corresponding to the ligand-known protein is determined.
  • the value obtained in this manner is expressed as N: ((Ligand-determined residues—the number of ligand-identified proteins listed in the ligand classification information that match the extracted ligand-determined residues. ) / (Number of ligands or ligands whose type matches the ligand-known protein))). Then, N is similarly obtained for the ligand-determining residue position where the value of the function f 3 (m, ii) is the second smallest. Then, the denominator of N and the numerator at the position of the first and second smallest ligand-determining residue of the function i3 (m, n) are added. In this manner, the ligand-determined residue-ligand classification information obtained by arbitrarily combining the pairs of the ligand-determined residue positions is obtained.
  • Each of the steps described above may be performed manually, but is particularly preferably performed by a computer having a predetermined medium or program installed.
  • this computer is connected to the Internet and can access an external device.
  • Such a computer includes at least a sequence alignment input means for inputting information on sequence alignment of the unknown binding molecule protein, an amino acid sequence or sequence alignment of the binding molecule known protein input by the sequence alignment input means.
  • Sequence alignment binding molecule storage means for storing information on the binding molecule or the type of binding molecule; and the amino acid sequence or sequence alignment of the binding molecule known protein or the binding molecule stored by the sequence alignment binding molecule storage means.
  • the position of the binding molecule-determining residue is predicted using information on the type of the binding molecule.
  • a binding molecule or a type of binding molecule by associating the amino acid residue (binding molecule determining residue) at the binding molecule determining residue position with the binding molecule or the type of the binding molecule.
  • a binding molecule-determining residue-binding molecule classification information obtaining means for obtaining binding molecule-determining residue-binding molecule classification information indicating a correlation between the binding molecule and the type of the binding molecule.
  • binding molecule determination residue locating means the sequence alignment of known binding molecule proteins and information on the binding molecule or the type of the binding molecule are described by the ⁇ ( ⁇ ), ⁇ 2 ( ⁇ ), and f3 (m, n) functions described above. Any or any combination thereof is determined to determine the position of the binding molecule determining residue.
  • the ligand-determined residue-ligand classification information may constitute a unique database, or may be configured as a relational database based on the binding molecule known protein classification information obtained in step 102. If the ligand-determined residue-ligand classification information is configured as a relational database based on the binding molecule known protein classification information, if the sequence alignment of the unknown protein and its ligand are confirmed, It is preferable because it can be easily re-evaluated at the position of the ligand-determining residue by incorporating it into the information on the classification of known binding molecules.
  • the binding molecule or the type of the binding molecule can be easily predicted by inputting the sequence alignment of the binding molecule unknown protein into the binding molecule determination residue-binding molecule classification information.
  • the computer of the present invention has the binding molecule determining residue-binding molecule classification information preliminarily installed, and the sequence alignment input means for inputting the protein sequence alignment is used to execute the sequence alignment of the unknown protein. It may be a computer that predicts the type of the binding molecule and / or the binding molecule by inputting the data. Even with such a computer, it is easy to predict the binding molecule or the type of the binding molecule by inputting the sequence alignment of the unknown binding protein to the binding molecule determination residue-binding molecule classification information. Becomes possible.
  • Table 1 is an example of hypothetical binding molecule known protein classification information.
  • Ligands are divided into three categories: P, A, and N.
  • P, A, and N When determining the position of a ligand-determining residue based on the type of ligand, P, A, and N correspond to XI, X2, and X3 in Formulas 1 and 2, respectively.
  • ⁇ X, XX, and ⁇ ⁇ correspond to XI, 11, and X3 in Formulas 1 and 2, respectively.
  • sequence alignment of the first known binding molecule protein is TLMRK
  • binding molecule (ligand) is ⁇
  • type of ligand of ligand I is ⁇ .
  • f2 (l) ⁇ (N (Res, XI) XN (Res, X2) XN (Res, X3))
  • n is in the order of 2, 4, 3, 5, 1.
  • Amino acid residue positions that give a small value of ⁇ ( ⁇ ) are candidates for ligand-determined residue positions.
  • the second, fourth, and third amino acid residue positions are candidates for ligand-determined residue positions. How many amino acid residue positions are candidates for ligand-determining residue positions may be determined in advance. Since the value of f2 (n) at these amino acid residue positions is smaller than the value of ⁇ 2 ( ⁇ ) at the first and fifth amino acid residue positions, the second, fourth and third amino acid residue positions Is a desirable candidate as a candidate for a ligand-determining residue position.
  • Two cross-residue pairs when there are two ligands for a pair of ligand-determined residue positions and three cross-residue pairs when there are three ligands for a pair of ligand-determined residue positions .
  • candidate pairs of ligand-determined residue positions In this example, three types (2, 3), (2,4), (3, 4) Pair candidates.
  • the candidate pairs (2, 3) for the ligand-determined residue positions are examined.
  • the combination of the second and third amino acid residues in the sequence alignment is (L, M), (M, M), (C, M), (L, L), and (M, L). is there. Therefore, the “number of kinds of amino acid residue pairs” to which the present invention belongs is 5.
  • the corresponding ligand for each of the combinations of these five types of amino acid residues is uniquely determined, so there are no two-crossing residue pair species and three-crossing residue pair species. From this, the value of f 3 (2, 3) is 5. Similarly, the value of f3 (2, 4) is 4, and the value of ⁇ 3 (3, 4) is 5. Therefore, a pair of residue positions (2, 4) is the most preferable, and is a pair of ligand-determining residue positions.
  • f3 (l, 5) is determined using a combination of amino acid residue positions 1 and 5 to indicate that an unfavorable combination of amino acid residue positions increases the value of f3.
  • the amino acid residue at the position of the ligand-determined residue of the binding molecule unknown protein (the binding molecule with unknown ligand) is determined, and the ligand determined residue-ligand classification is performed.
  • the information on the classification of the ligand-determined residue-ligand as described above can be obtained, the amino acid residue at the position of the ligand-determined residue of the binding molecule unknown protein (the binding molecule with unknown ligand) is determined, and the ligand determined residue-ligand classification is performed.
  • the information on the classification of the ligand-determined residue-ligand as described above can be obtained, the amino acid residue at the position of the ligand-determined residue of the binding molecule unknown protein (the binding molecule with unknown ligand) is determined, and the ligand determined residue-ligand classification is performed.
  • the ligand of the unknown protein of the binding molecule For example, a sequence alignment of a certain unknown binding molecule protein is determined by a known method. If the second and fourth amino acid residues in the sequence alignment are M
  • the prediction method of the present invention is also useful for developing a novel medicine.
  • a ligand was described.
  • the present invention can predict not only a ligand but also a molecule that binds to a known binding molecule protein.
  • the binding molecule known protein is GPCR
  • a G protein that binds to the GPCR can also be predicted.
  • the use of the method for predicting binding molecules of unknown binding molecules of the present invention makes it possible to predict, for example, the type of ligand and Z or ligand of GPCR. If the ligand of the GPCR and / or the type of the ligand can be predicted, the function of the GPCR in vivo can be predicted. And, for example, using information on a GPCR whose function is predicted and whose ligand and / or ligand type is predicted, It is possible to easily produce a prophylactic or therapeutic drug for a disease or the like involving the GPCR.
  • this method is particularly suitable for the manufacture of either or both prophylactic agents and / or therapeutic agents for central diseases, inflammatory diseases, cardiovascular diseases, cancer, metabolic diseases, immune system diseases or digestive system diseases.
  • prophylactic agents and / or therapeutic agents for central diseases, inflammatory diseases, cardiovascular diseases, cancer, metabolic diseases, immune system diseases or digestive system diseases.
  • the invention will be used effectively.
  • sequence numbers in the sequence listing in the present specification indicate the following sequences.
  • FIG. 1 shows the amino acid sequence of rat TGR23-2 ligand (1-15).
  • Fig. 3 shows the amino acid sequence of mouse TGR 23-2 ligand (1-18).
  • Figure 3 shows the amino acid sequence of mouse TGR 23-2 ligand (1-15).
  • Figure 3 shows the amino acid sequence of mouse TGR 23-2 ligand (1-14).
  • Figure 3 shows the amino acid sequence of mouse TGR 23-2 ligand (1-20).
  • FIG. 2 shows the nucleotide sequence of cDNA encoding a part of rat TGR23-2 ligand precursor.
  • [SEQ ID NO: 25] 2 shows the amino acid sequence of rat TGR 23-2 ligand (1-20).
  • Rat TGR 23 Shows the nucleotide sequence of cDNA encoding the precursor of ligand 2
  • FIG. 2 shows the amino acid sequence of rat TGR 23-2 ligand precursor.
  • TGR 23-1 human TGR 23-1).
  • TGR 23-2 human TGR 23-2).
  • Example 1 shows the nucleotide sequence of cDNA encoding human-derived G protein-coupled receptor protein TGR23-2.
  • GPCR is mentioned as a protein with a known binding molecule and a protein with an unknown binding molecule, but the present invention is not limited to these without departing from the gist thereof.
  • P P ?? Peptides (peptide), C emokines (chemokine), Glycoproteins (glycoprotein) A ⁇ Monoamines, (adrenaline, acetylcholine, dopamine, serotonin, histamine)
  • a candidate having a small product of the value of the f l (n) function and the value of the f2 (n) function is selected as the ligand residue position candidate. Among them, if any of them could not be sequence aligned (-), 3% or more of them were excluded from candidate ligand-determined residue positions. In this manner, 20 ligand residue position candidates were selected.
  • Table 3 shows the evaluation values and ranks of the function ⁇ ( ⁇ ) and the function f2 (n) for the more preferable six candidate ligand residue positions among them. Table 3 Evaluation results and ranks of function i l (n) and function f 2 (n) for six preferred candidate ligand residue positions f l (n) f2 (n)
  • the 86th and 90th amino acid residue types and the number of ligand types were extracted from the sequence alignment of GPCR from the binding molecule known protein classification information to obtain ligand-determined residue-ligand classification information.
  • Table 4 shows the excerpts. From Table 4, for example, of the 1152 types of GPCRs, there are 86 types in which the amino acids at amino acid residue positions 86 and 90 are A and G, respectively, and their ligands are all N (lipid). It can be seen that it is classified as Thus, it can be seen that most GPCRs can predict their ligands by the amino acids at the 86th and 90th amino acid positions.
  • Table 4 Ligand-determined residue-ligand classification table (Binding molecule-determined residue-binding molecule classification table)
  • the (86, 90) th amino acid residue (position of the residue determining the binding molecule) has a sequence of I and M, respectively.
  • the binding molecule known GPC R1152 types in the binding molecule classification residue-binding molecule classification information there are 32 types in which the (86, 90) th amino acid residues are I and M, respectively. All 32 types of ligands are peptides.
  • this GPR 2 is not included in the 1152 known binding molecules of GPCR, the actual ligand type is a peptide, which is consistent with the predicted ligand type.
  • the amino acid residue at the position (209, 211) determined by the binding molecule is V and F, respectively.
  • Table 5 shows that the binding molecule-determining residue positions (86, 90) are the most preferable binding molecule-determining residue positions among the three types. Furthermore, according to Table 5, it can be seen that the type of the ligand can be predicted with high accuracy.
  • the binding molecule determining residues of GPR2 (86, 90), and N (1112 types of GPCRs) at (209, 211), the binding molecule determining residues were identical to GPR2.
  • the number of ligands with the same type of ligand are 3 2/3 2 and 4/26, respectively. Add these up to 36/58.
  • Example 2 (Method of predicting the type of binding G a protein that binds to GPCR)
  • the binding G ⁇ protein which is a binding molecule of GPCR, was classified into three types, G i, Gq, and G s. This is a categorization of the binding G ⁇ protein into the 2000 Receptor & Ion channel Nomenclature Supplement of Trends in pharmacological sciences (TIPS). For simplicity, Gi / o is Gi and GQ / 11 is GQ in the 2000 Receptor & Ion channel Nomenclature Supplement of TIPS.
  • proteins listed in the 2000 Receptor & Ion channel Nomenclature Supplement of TIPS those binding to two or more G proteins, and Gi / al, 3, and Gi / a2, 3 were excluded as exceptions. In this way, information on about 600 types of GPCR and its sequence alignment, and the binding G ⁇ protein that binds to it, and its type were obtained.
  • sequence alignment of GPCR and information on the type of binding Ga protein that binds to the G protein were input to a computer.
  • the inputted sequence information of the GPCR and the information on the type of the binding Gcu protein were selected by means of a candidate selecting residue position for determining a binding molecule using the f1 (n) function and the f2 (n) function.
  • two pairs of binding residue positions (177, 178) and (82, 230) were determined.
  • binding molecule determination residue position candidate selecting means a candidate having a small product of the value of the ⁇ ( ⁇ ) function and the value of the ⁇ 2 ( ⁇ ) function is selected as the candidate binding molecule residue position. Among them, if any of them could not be sequence-aligned (-), 3% or more of them were excluded from candidate ligand-determining residue positions. In this way, candidate ligand residue positions were selected.
  • Ga protein that binds to multiple GPCRs was obtained from the literature. Then, the binding Go; how the protein was obtained was determined by Ca influx, Arachidonic acid release: by arachidonic acid release, by PTX (pertussis toxin sensitive), and by cyclic adenosine. Phosphoric acid was used, and Ca, AA, PTX, and cAMP were used, respectively. In addition, GQ is determined only by Ca Were excluded because the bound Ga protein could be something else. In this way, a GPCR was selected.
  • APJ G L 2/2 ST 0/0 Gi (cAMP) Gi For example, GPR5 in Table 6 will be described.
  • the type of binding G a protein of GPR5 is Gi, which was obtained by PTX.
  • the 177th and 178th sequence alignments of GPR5 are R and S.
  • Nine GPCRs have such a sequence alignment, and it can be seen that the type of conjugated Gcu protein is Gi.
  • GPR5, GPR13, GPR14, GPR16, GPR24, and AP; [6] are predicting the binding Go; protein. From the above, it can be seen that according to the present invention, it is possible to predict the binding Ga protein with high accuracy.
  • TGR23 which is the G protein-coupled receptor protein represented by SEQ ID NO: 37 and SEQ ID NO: 39
  • FIG. 4 shows the results of sequence alignment of TGR2311 and ⁇ silodopsin.
  • the amino acids at residues (86, 90), (209, 211) and (86, 236) in TGR 23-1 are (Q, L), (D , F) and (Q, N).
  • N the number of 1152 types of GPCRs in which the binding molecule-determining residue coincided with TGR 23 and the type of ligand were the same
  • 52/52 and the combined evaluation of (86, 90) and (86, 236) SDM pairs with a wide range of estimated GPCR numbers estimated that the ligand type was peptide.
  • the following reference examples show that the ligand of TGR23 (TGR23_1 and TGR23-2) is actually a peptide. [Reference Example 1] ⁇
  • a substance exhibiting a ligand activity specific to TGR 23-2 was purified from rat whole brain using cGR production promoting activity on CGR cells expressing TGR 23-2 as an index.
  • High performance liquid chromatography (HPLC) fraction of rat whole brain extract was prepared by the method described below. Immediately after sequentially extracting 400 g (200 cats) of the whole brain of an 8-week-old Wistar rat purchased from Charles River Japan Co., Ltd., it was thrown into distilled water (300 ml) boiled in 25 pets and boiled for 10 min. did. Immediately after boiling, cool on ice, combine 200 heads (2.4 L), add 180 ml of acetic acid to a final concentration of 1.0 M, and use Polytron (10,000 rpm, 2 minutes) at low temperature. Crushed. The crushed liquid is centrifuged (8,000 rpm, 30 minutes), and the supernatant is collected.
  • HPLC high performance liquid chromatography
  • the column was washed with 400 ml of 1.0 M acetic acid and eluted with 500 ml of 60% acetonitrile containing 0.1% trifluoroacetic acid.
  • the eluate was concentrated under reduced pressure to remove the solvent, and the concentrate was freeze-dried.
  • 1.2 g of the obtained white powder was dissolved in 30 ml of 10% acetonitrile containing 0.1% trifluoroacetic acid, and 12.5 ml of each powder was dissolved in an ODS column (Tosoichi, TSKgel ODS-80TS (2.
  • the sample was subjected to preparative HP LC using a gradient elution method of acetonitrile containing 10% to 60% of 0.1% trifluoroacetic acid using 5 ⁇ X 300 mm)).
  • the HP LC was performed twice, and the eluate was divided into 60 fractions every 2 minutes, and the two eluates were combined. Each fraction was concentrated and dried under reduced pressure, and 0.4 ml of dimethyl sulfoxide (DMSO) was added to the residue, and then completely dissolved using a Portex mixer and an ultrasonic washer.
  • DMSO dimethyl sulfoxide
  • the DMSO solution of the HPLC fraction obtained above was administered to CHO cells expressing TGR23-2 according to the method described in Reference Example 3, and the amount of intracellular cAMP production was measured. And 22 to 23 showed remarkable cAMP production promoting activity.
  • a similar sample was examined for arachidonic acid metabolite releasing activity according to a known method. As a result, remarkable activity was confirmed.
  • the three active fractions obtained were further purified by the following methods (a) to (c), respectively.
  • the receptor-specific intracellular calcium release activity was also confirmed by FLIPR (Molecular Devices). Was done. Therefore, in confirming the activity in the subsequent purification steps, intracellular calcium release activity by FLIPR was used as an indicator, and it was appropriately confirmed that the fraction showing the activity exhibited cAMP production promoting activity.
  • fraction No. 18 dissolve in 10 ml of 1 OmM ammonium formate containing 10% acetonitrile, and use a cation exchange column (Tosoichi, TSKgel SP-5PW (20 mm ⁇ X 15 Omm)) After elution, elution was carried out with a concentration gradient of 10 mM to 1.0 M ammonium formate containing 10% acetonitrile. The activity was recovered at around 0.4M ammonium formate.
  • a cation exchange column Tosoichi, TSKgel SP-5PW (20 mm ⁇ X 15 Omm
  • the obtained active fraction was lyophilized, dissolved in 0.1 lm of DMSO, further added with 0.7 ml of 0.1% acetofluorobutyric acid in 10% acetonitrile, and added to an ODS column (Wako Pure Chemical Industries, Ltd.). Wakosii-II 3C18H G (2. ⁇ ⁇ X 15 Omm)) and eluted with a concentration gradient of 10% to 37.5% acetonitrile containing 0.1% heptafluorobutyric acid. It was manually collected every time. The activity was observed around 26% of acetonitrile.
  • the active fraction was further added with 0.7 ml of 0.1% trifluoroacetic acid containing 0.1% acetonitrile, applied to a QDS column (Wako Pure Chemical Industries, Wakosite II 3C18HG), and then purified with 0.1% trifluoroacetic acid. Elution was carried out with a gradient of 10% to 20% acetonitrile containing acetic acid, and the eluate was manually collected for each peak. The activity was obtained as a single peak around 11% of acetonitrile. The structure of the active substance contained in this fraction was determined as shown in Reference Example 5 below.
  • the resulting active fraction was lyophilized, dissolved in 0.1 lm of DMS 0, and further added with 0.7 ml of 10% acetonitrile containing 0.1% trifluoroacetic acid, followed by ODS column (Wako Pure Chemical Industries, Wakosil- II 3C18HG (2. ⁇ X 150mm)) and eluted with a concentration gradient of 10% to 20% acetonitrile containing 0.1% trifluoroacetic acid, and the eluate was manually separated for each peak . The activity was obtained as a single peak around 15% of acetonitrile.
  • Fraction Nos. 22-23 were dissolved in 10 ml of 1 OmM ammonium formate containing 10% acetonitrile and applied to a cation exchange column (TOSOKI, TSKgel SP-5PW (2 ⁇ X 150 mm)). Elution was carried out with a concentration gradient of 1.0 M ammonium formate, 1 OmM force containing 10% acetonitrile. The activity was recovered at around 0.4M ammonium formate. After freeze-drying the active fraction, dissolve it in 0.8 ml of 10% acetonitrile containing 0.1% trifluoroacetic acid and attach to a CN column (Nomura Chemical, Develosil CN-UG-5 (4. ⁇ X 250 mm)).
  • the sample was manually collected for each work. Activity was observed around 16% of acetonitrile.
  • To the active fraction 0.7 ml of 10% acetonitrile containing 0.1% heptanofluorbutyric acid was further added, and the mixture was applied to an ODS column (Wako Pure Chemical Industries, Wakosil-II 3C18HG). Elution was performed with a gradient of 10% to 37.5% acetonitrile containing heptafluorobutyric acid, and the eluate was manually collected for each peak. The activity was obtained as a single peak around 28% of acetonitrile.
  • the structure of the active substance contained in this fraction was determined as shown in Reference Example 4 below.
  • protease Type XIV (P5147)) was used to determine whether the active substance was proteinaceous.
  • Rat whole brain extract HP LC active fraction (fraction No. 18, 20, and 22 to 23) Add 4-1 each to 0.2 M ammonium acetate 1001, and add 3 ig pronase to this After incubation at 37 ° C for 2 hours, the added pronase was inactivated by heating in boiling water for 10 minutes. Distilled water (lm1) containing BSAO. 05mg and CHAPS 0.05mg was added thereto and freeze-dried. The freeze-dried sample was added to CHO cells expressing TGR23-2 according to a known method, and the activity of promoting intracellular cAMP production was measured.
  • any of the active substances exhibiting an intracellular cAMP production promoting activity on CHO cells expressing TGR23-2 in a rat whole brain extract is a protein or a peptide.
  • Thermo Fiimigan LCQ ion trap mass spectrometer (ThermoQuest) equipped with a nanospray ion source (Pro evening).
  • the result was calculated from the amino acid sequence of SEQ ID NO: 1. (Measured value: 1954.9, calculated value: 1954.2).
  • the active substance which specifically exhibits cAMP production promoting activity on TGR2-3-expressing CHO cells obtained from fraction number 20 of rat whole brain extract has the amino acid sequence shown in SEQ ID NO: 1. It was determined to have.
  • the active substance that specifically exhibits cAMP production promoting activity on TGR23-2 expressing CHO cells obtained from fraction numbers 22 to 23 of rat whole brain extract is the amino acid shown in SEQ ID NO: 2. It was determined to have a sequence.
  • the same eluate was used to perform mass spectrometry using a Thermo Finnigan LCQ ion trap mass spectrometer (SammoQuest) equipped with a nanospray ion source (protana).
  • the mass was calculated from the amino acid sequence of SEQ ID NO: 3. The following mass values were obtained (actual value: 144.1, calculated value: 1423.6).
  • the active substance that specifically exhibits cAMP production promoting activity on TGR23-2 expressing CHO cells obtained from fractional number 18 of rat whole brain extract
  • rat TGR23 To clone the cDNA encoding the precursor of the human homolog (sometimes referred to as human TGR23-2 ligand in this specification) of the human hypolog, A PCR was performed using the cDNA as a type II. Using the following synthetic DNA primers, cDNA derived from the human hypothalamus was converted to type III and amplified by the PCR method.
  • the composition of the reaction solution was human hypothalamus Marathon-Ready cDNA (CLONTECH) 0.8 ⁇ , SEQ ID NO: 4 and SEQ ID NO: 5, each of the synthetic DNA primers 1.0 M, 0.2 mM dNTPs, ET aq (Takara Shuzo) 0.1 II 1 and the ExTaq buffer attached to the enzyme, and the total reaction volume was 201.
  • the amplification cycle was performed using a thermal cycler (PE Biosystems) at 94 ° C for 300 seconds, followed by 94 ° C for 10 seconds, 55 ° C for 30 seconds, 72 ° C for 30 seconds. A cycle of 35 seconds was repeated 35 times, and finally, the mixture was kept at 72 ° C for 5 minutes.
  • a PCR reaction solution 2 n 1 which was diluted 50-fold with DNase and RNase Free distilled water, synthetic DNA primers of SEQ ID NO: 4 and SEQ ID NO: 6, 1.0 M and 0.2 mM dNTPs, respectively ExT aq polymerase (Takara Shuzo) 0.11 and ExTaq buffer attached to the enzyme to make the total reaction volume 201, and heat it for 94 ⁇ 300 seconds using a thermocycler (PE Biosystems). Thereafter, a cycle of 94 ° C ⁇ 10 seconds, 55 ° C ⁇ 30 seconds, and 72 ° C ⁇ 30 seconds was repeated 35 times, and finally, the temperature was kept at 72 ° C for 5 minutes.
  • the nucleotide sequence of the DNA represented by SEQ ID NO: 7 includes the amino acid sequence of rat TGR23-2 ligand obtained from whole rat brain represented by SEQ ID NO: 1, SEQ ID NO: 2 and SEQ ID NO: 3. The presence of a frame encoding an amino acid sequence very similar to that of was predicted to be cDNA encoding the precursor of human TGR23-2 ligand or a part thereof.
  • An ATG which is predicted to be the initiation codon for protein translation, is located 5 'upstream of the amino acid sequence translated from SEQ ID NO: 7 in a frame encoding an amino acid sequence considered to be a human TGR 23-2 ligand.
  • SEQ ID NO: 8 The amino acid sequence of the human TGR 23-2 ligand precursor deduced as described above is shown in SEQ ID NO: 8.
  • the amino acid sequence of human TGR23-2 ligand is the amino acid sequence of rat TGR23-2 ligand obtained from rat whole brain extract; SEQ ID NO: 1 [rat TGR23-2 ligand (1-18) )], SEQ ID NO: 2 [rat TGR23-2 ligand (1-15)] and SEQ ID NO: 3 [rat TGR23-2 ligand (1-114)], SEQ ID NO: 9 [ Human TGR23_2 ligand (111)], SEQ ID NO: 10 [human TGR23-2 ligand (1-15)] and SEQ ID NO: 11 [human TGR23-2 ligand ( 11-14)] and an amino acid sequence represented by SEQ ID NO: 9 with two residues extended to the C-terminal side of SEQ ID NO: 9 [SEQ ID NO: 12] [amino acid sequence represented by human TGR 23-2 ligand (1 20)].
  • the sequence of human TGR 23-2 ligand is TGR 23-2 ligand and rat Unlike the sequence of TGR 23-2 ligand, the sequence has a G 1 nA rg sequence instead of an Arg-A rg sequence, so the 16 residues shown in SEQ ID NO: 26
  • the amino acid sequence [human TGR 23-2 ligand (1-16)] was also deduced to be the ligand sequence.
  • Mouse homologue of rat TGR23-2 ligand obtained from rat whole brain extract (referred to as mouse TGR23-2 ligand in this specification)
  • PCR was performed using type I cDNA from the whole mouse brain.
  • Amplification by PCR was performed using the following synthetic DNA primers and cDNA of mouse whole brain as type II.
  • the composition of the reaction solution was as follows: Mouse whole brain Marathon-Ready cDNA (CLONTECH) 0.8 Synthetic DNA primers of SEQ ID NO: 13 and SEQ ID NO: 14: 1.0 0, 0.2 mM dNTPs, ExT a ⁇ (Takara Shuzo) 0.1 H1 and ExTaQ buffer attached to the enzyme, and the total reaction volume was 201.
  • the amplification cycle was performed using a thermal cycler (PE Biosystems) at 94 ° C for 5 minutes, followed by a cycle of 94 ° C for 10 seconds, 65 ° C for 30 seconds, and 72 and 30 seconds.
  • the test was repeated 5 times, and finally kept at 72 ° C for 5 minutes.
  • the PCR reaction solution 21 which was diluted 100 times with DNase and RNase Free distilled water, the synthetic DNA primers of SEQ ID NO: 13 and SEQ ID NO: 15 were each 1.0 M and 0.2 mM dN.
  • TP s, ExTaQ polymerase (Takara Shuzo) 0.1 1 and EXT aq buffer attached to the enzyme the total reaction volume was 201, and the temperature was 94 ° C After heating for 5 minutes, a cycle of 94 ° C for 10 seconds, 60 hours, 30 seconds, and 72 ° C for 30 seconds was repeated 30 times, and finally, the temperature was kept at 72 ° C for 5 minutes.
  • the nucleotide sequence of DNA represented by SEQ ID NO: 16 includes the amino acid sequence of rat TGR23_2 ligand obtained from whole rat brain represented by SEQ ID NO: 1, SEQ ID NO: 2 and SEQ ID NO: 3. Since a frame encoding a very similar amino acid sequence was present, it was presumed to be a cDNA encoding the precursor of mouse TGR 23-2 ligand or a part thereof.
  • SEQ ID NO: 17 shows the amino acid sequence of the mouse TGR23-2 ligand precursor deduced as described above.
  • the N-terminal of the amino acid sequence considered to correspond to the mouse TGR 23-2 ligand has a Lys-Arg sequence (Seidah, NG), which is usually considered to be a bioactive peptide cleaved from its precursor protein. et al., Ann. NY Acad. Sci., 839, 9-24, 1998).
  • NG Lys-Arg sequence
  • a termination codon was present at the C-terminal side, but two more residues were present between the sequence corresponding to the rat TGR23_2 ligand of SEQ ID NO: 1.
  • the amino acid sequence of mouse TGR23-2 ligand was extracted from rat whole brain Amino acid sequence of rat TGR23-2 ligand obtained from the product; SEQ ID NO: 1 [rat TGR23-2 ligand (1-18)], SEQ ID NO: 2 [rat TGR23-2 ligand (1-15) ] And SEQ ID NO: 3 [rat TGR 23-2 ligand (1-114)], corresponding to each, SEQ ID NO: 18 [mouse TGR 23-2 ligand (1-1 8)], SEQ ID NO: 19 [Mouse TGR 23-2 ligand (1-15)] and the amino acid sequence represented by SEQ ID NO: 20 [mouse TGR 23-2 ligand (1-14)], and further, at the C-terminal side of SEQ ID NO: 18 It was presumed to be the amino acid sequence represented by SEQ ID NO: 21 extended by 2 residues [mouse TGR 23-2 ligand (1-20)].
  • PCR was performed using cDNA from rat whole brain as type II.
  • cDNA derived from whole rat brain was used as type II and amplified by the PCR method.
  • the composition of the reaction solution was rat whole brain Marathon-Ready cDNA (CLONTECH) 0.81, SEQ ID NO: 22 and SEQ ID NO: 14, each of the synthetic DNA primers 1.0 / iM, 0.2mM dNTPs, E xT aq (Takara Shuzo) 0.1 a 1 and the ExTaQ buffer attached to the enzyme, the total reaction volume was 20 n 1.
  • the amplification cycle is performed using a thermal cycler (PE Biosystems) at 94 ° C for 5 minutes, followed by a cycle at 94 ° C for 10 seconds, 65 ° C for 30 seconds, and 72 ° C for 30 seconds. Was repeated 35 times, and finally kept at 72 ° C for 5 minutes.
  • PCR reaction solution 2n1 diluted 100 times with DNase and RNase Free distilled water, primer 1.0M of SEQ ID NO: 22, synthetic DNA primer of SEQ ID NO: 15 2 xM, 0.2 mM dNTPs, ExTaQ polymerase (Takara Shuzo) 0.1 x 1 and ExTaq buffer supplied with the enzyme, the total reaction volume is 201, and the total cycler is PE Biosystems.
  • a clone having a cDNA insert is selected on an LB agar medium containing ampicillin and X-ga1, and the white clone is selected. Only one was isolated using a sterilized toothpick to obtain a transformant. Each clone was cultured overnight in LB medium containing ampicillin, and plasmid DNA was prepared using QIAwell 8 Plasmid Kit (Qiagen).
  • the reaction for determining the nucleotide sequence was performed using the BigDye Terminator Cycle Seauencing Ready Reaction Kit (PE Biosystems), followed by decoding using a fluorescent automatic sequencer to obtain the DNA sequence represented by SEQ ID NO: 23. Was.
  • the nucleotide sequence of the DNA represented by SEQ ID NO: 23 includes the amino acid sequence of rat TGR23_2 ligand obtained from whole rat brain represented by SEQ ID NO: 1, SEQ ID NO: 2 and SEQ ID NO: 3. There was a frame to code. When the DNA sequence was translated using this frame as a reading frame, the amino acid sequence represented by SEQ ID NO: 24 was obtained. By comparing this sequence with the amino acid sequence of the mouse TGR23-2 ligand precursor obtained in Reference Example 7 (SEQ ID NO: 16), this sequence was found to be a part of the rat TGR23-2 ligand precursor. It was presumed to correspond to a sequence consisting of 54 amino acids at the C-terminal side.
  • a termination codon was present downstream of the sequence encoding rat TGR 23-2 ligand.
  • the N-terminal side of the amino acid sequence of rat TGR 23-2 ligand has a Lys-Arg sequence (Seidah, N.G. et al., Ann. NY Acad. Sci., 839, 9-24, 1998).
  • a termination codon was present on the C-terminal side, but two more residues were present between the sequence of the rat TGR23-2 ligand of SEQ ID NO: 1.
  • the amino acid sequence of rat TGR 23-2 ligand was obtained from SEQ ID NO: 1 [rat TGR 23-2 ligand (1-18)] obtained from rat whole brain extract, Amino acid sequence represented by SEQ ID NO: 2 [rat TGR 23-2 ligand (1-15)] and SEQ ID NO: 3 [rat TGR 23-2 ligand (1-14)], and further SEQ ID NO: 1 It was presumed to be the amino acid sequence [rat TGR 23-2 ligand (1-20)] represented by SEQ ID NO: 25, which was extended to the C-terminal side by 2 residues.
  • cDNA derived from rat whole brain was subjected to amplification by PCR using type III.
  • the composition of the reaction solution was rat whole brain Marathon-Ready cDNA (CLONTECH) 0.8 / 1, SEQ ID NO: 27 and SEQ ID NO: 28, each of the synthetic DNA primers 1.0 M, 0.2 mM dNTPs, E xT aq (Takara Shuzo) 0.11 and ExT aq buffer attached to the enzyme, the total reaction volume was 201.
  • the amplification cycle was performed using a thermocycler (PE Biosystems) at 94 ° C for 5 minutes, followed by a cycle at 94 ° C for 10 seconds, 65 ° C for 30 seconds, and a cycle of 72 ° C for 30 seconds. Was repeated 35 times, and finally, the mixture was kept at 72 ° C for 5 minutes.
  • PE Biosystems PE Biosystems
  • PCR reaction solution 2 ⁇ i1 a primer of SEQ ID NO: 29, 1.0 M, and a synthetic DNA primer of SEQ ID NO: 28, diluted 50-fold with distilled water of DNase and RNA Free 0.2 M, 0.2 mM dNTPs, ExTaQ polymerase (Takara Shuzo) 0.1 x 1 and the ExTaq buffer attached to the enzyme to a total reaction volume of 20 n1.
  • PCR reaction solution 2 ⁇ i1 a primer of SEQ ID NO: 29, 1.0 M
  • a synthetic DNA primer of SEQ ID NO: 28 diluted 50-fold with distilled water of DNase and RNA Free 0.2 M, 0.2 mM dNTPs, ExTaQ polymerase (Takara Shuzo) 0.1 x 1 and the ExTaq buffer attached to the enzyme to a total reaction volume of 20 n1.
  • Each clone was cultured once in LB medium containing ampicillin, and plasmid DNA was prepared using QIAwell 8 Plasmid Kit (Qiagen).
  • the reaction for determining the nucleotide sequence was carried out using a BigDye Terminator Cycle Sequencing Ready Reaction Kit (PE Biosystems), and was decoded using a fluorescent automatic sequencer to obtain a DNA sequence represented by SEQ ID NO: 30.
  • the nucleotide sequence of cDNA represented by SEQ ID NO: 30 is a further 5 'of the DNA sequence (SEQ ID NO: 23) encoding a part of the rat TGR23-2 ligand precursor obtained in Reference Example 8. The sequence was extended to the side. This sequence is constructed using a frame encoding an amino acid sequence corresponding to the amino acid sequence of rat TGR 23-2 ligand obtained from whole rat brain represented by SEQ ID NO: 1, SEQ ID NO: 2 or SEQ ID NO: 3.
  • TGR23-1 Human TGR23-1 is sometimes simply referred to as TGR23_1
  • TGR23_1 Human TGR23-1 is sometimes simply referred to as TGR23_1
  • Plasmid pTB2173 containing a DNA fragment having the nucleotide sequence represented by SEQ ID NO: 38 encoding TGR 23-1 was designated as type I, and the Sa1I recognition sequence was A PCR reaction was performed using the added primer 1 (SEQ ID NO: 32) and the primer 2 (SEQ ID NO: 33) added with a SpeI recognition sequence.
  • the composition of the reaction solution in the reaction was as follows: 10 ng of the above plasmid was used as type III, PiU Turbo DNA Polymerase (Stratagene) 2.5 U, primer 1 (SEQ ID NO: 32) and primer 1 (SEQ ID NO: 2).
  • coli TOP 10 (Invitrogen), and a clone containing the cDNA of TGR23-1 contained in pTB2173 was selected in an LB agar medium containing kanamycin.
  • the insert DNA was excised from an agarose gel after electrophoresis, and then recovered using a Gel Extraction Kit (Qiagen).
  • Vector plasmid pAKKO—111H for expression of animal cells obtained by cutting this insert DNA with Sa1I and SpeI (Hinuma, S. et al. Biochim. Biophys. Acta, Vol. 1219, pp. 251-259 (1994), the same vector plasmid as pAKKO l.11H), and ligated using DNA Ligation Kit ver.2 (Takara Shuzo) to obtain a plasmid pAKKO-TGR23 for protein expression. -1 was constructed. After culturing E. coli TOP10 transformed with this pAKKO-TGR23-1, plasmid DNA of pAKKO-TGR23-1 was prepared using Plasmid Miniprep Kit (Bio-Rad).
  • Hamster CHOZd hfr_ cells were placed on a falcon dish (3.5 cm in diameter) in an a-MEM medium (with ribonucleosides and deoxyribozyme leosides, GIBC0, Cat. No. 12571) containing 10% fetal serum. 1 0 and five seeding, 5% C0 2 The cells were cultured at 37 ° C overnight in an incubator.
  • the expression plasmid pAKKO-TGR23-1GRA2Xg was transfected using Transiection Reagent FuGENE 6 (Roche) according to the method described in the attached instruction manual. After culturing for 18 hours, the medium was replaced with a fresh growth medium.
  • the transfected cells were collected by trypsin-EDTA treatment, and selected medium (Hi-MEM medium containing 10% dialyzed fetal calf serum (without ribonucleosides and deoxyribonucleosides, GIBC0, Cat. No. 12561) )) was used to inoculate 10 flat bottom 96-well plates. Culture was continued while changing the selection medium every 3 to 4 days, and after 2 to 3 weeks, 81 DHF R + cell clones that had grown in a colony were obtained.
  • selected medium Hi-MEM medium containing 10% dialyzed fetal calf serum (without ribonucleosides and deoxyribonucleosides, GIBC0, Cat. No. 12561)
  • RNAs were prepared using an RNeasy 96 Kit (Qiagen). A reverse transcription reaction was performed on 50 to 200 ng of the obtained total RNA using a TadMan Gold RT-PCR Kit (PE Biosystems).
  • the standard cDNA is prepared by measuring the absorbance at 260 nm of the plasmid PTB2174 containing the DNA fragment having the nucleotide sequence represented by SEQ ID NO: 40, calculating the concentration, calculating the exact copy number, and then including ImM EDTA. It was diluted with a 10 mM Tris-HCI (pH 8.0) solution to prepare 2 ⁇ 10 6 copies of a standard cDNA solution from 2 copies.
  • the probe and primer for TaciMan PCR are P Designed by rimer Express (Version 1.0) (PE Biosystems). The expression level was calculated using ABI PRISM 7700 SDS software.
  • the number of cycles at the moment when the fluorescence intensity of the reporter reached the set value was plotted on the vertical axis, and the logarithmic value of the initial concentration of the standard cDNA was plotted on the horizontal axis, to create a standard curve.
  • the initial concentration of each reverse transcript product was calculated from the standard curve, and the amount of TGR23-1 gene expression per total RNA of each clone was determined.
  • one CH ⁇ cell line having high expression of TGR23-1 was selected and cultured in a 24-well plate. For these cells, the expression level of TGR 23-1 was re-examined.
  • Total RNA was prepared using RNeasy Mini Kits (Qiagen), and then treated with RNase-free DNase Set (Qiagen).
  • a reverse transcription reaction was performed from the obtained total RNA in the same manner as described above, and the expression level of the TGR23-1 gene per total RNA of each clone was determined by TaQMan PCR. As a result, it was found that CHO cell lines clones 49 and 52 expressing TGR23-1 showed high expression levels.
  • Boc- Ser (Bzl) - a 0CH 2 -PAM resin is input to the reaction vessel of the peptide synthesizer ACT 90, the B oc swelling after TFA was removed in DCM, and neutralized with DI EA. This resin was suspended in NMP, and Boc-Lys (Cl-Z) was condensed with HOBt-DIPCI. After the reaction, the presence of free amino groups was examined by a ninhydrin test. When the ninhydrin test was positive, the same amino acid was condensed again. Even after the recondensation, when the ninhydrin test was positive, acetylation was performed with acetic anhydride.
  • the human TGR 23-2 ligand (1-20) obtained in Reference Example 12 was administered at various concentrations to TGR 23-1 -expressing CHO cells and TGR 23-2 -expressing CHO cells at various concentrations according to a known method.
  • human TGR23-2 ligand (1-20) was found to be dependent on the concentration of TGR23-1 expressing CHO cells and TGR23-2 expressing CH0. Increased intracellular Ca ion concentration in cells. The results are shown in FIGS.
  • polypeptide having the amino sequence represented by SEQ ID NO: 12 increased the intracellular Ca ion concentration of TGR 23-1 and TGR 23-2. It is clear that it has activity.
  • binding molecule or a type of a binding molecule only by obtaining information on an amino acid sequence of a protein whose binding molecule is unknown (and / or a sequence alignment obtained using the amino acid sequence). Becomes possible. This makes it possible to predict binding molecules (ligands, etc.) much faster than conventional molecular modeling methods that predict even three-dimensional structures.
  • the present invention it is possible to predict the binding molecule or the type of the binding molecule for a protein for which various types of binding molecules are unknown. Further, it is possible to predict the binding molecule or the kind of the binding molecule easily and quickly rather than experimenting whether or not any binding molecule actually binds to the protein whose binding molecule is unknown.
  • binding molecule or the type of the binding molecule of a binding molecule unknown protein such as an orphan G protein-coupled receptor. It is possible to easily produce a prophylactic or therapeutic drug for a disease or the like involving a binding molecule unknown protein.

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Abstract

La présente invention concerne un procédé permettant, sur la base des données séquentielles du récepteur couplé à la protéine G, d'estimer un ligand ou un type de ligand se liant ou se couplant directement au récepteur couplé à la protéine G, et par voie de conséquences, d'évaluer sa fonction. L'invention concerne plus particulièrement un procédé permettant d'évaluer un ligand d'une protéine avec un ligand inconnu. A cet effet, on se procure les données de classification des protéines à ligands connus pour lesquels les alignements des protéines avec les ligands connus correspondent, suivant le cas, aux ligands ou aux types de ligands. On se procure également données de classification des ligands de résidus déterminants pour les ligands, et qui font apparaître les corrélations entre résidus déterminants pour les ligands et ligands ou types de ligands, de façon à avoir les alignements des protéines avec les ligands inconnus. On prend les données concernant au moins les résidus déterminants pour les ligands dans les alignements des protéines avec les ligands tels que décrit précédemment, et on les applique aux données de classification des ligands de résidus déterminants pour les ligands, ce qui permet d'évaluer le ligand ou type de ligand de protéine portant le ligand inconnu.
PCT/JP2002/007057 2001-07-12 2002-07-11 Procede d'evaluation de ligand et utilisation de ce procede Ceased WO2003007187A1 (fr)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2004056866A1 (fr) * 2002-12-20 2004-07-08 Geneos Oy Locus de susceptibilite a l'asthme
WO2004076487A1 (fr) * 2003-02-28 2004-09-10 Takeda Pharmaceutical Company Limited Anticorps et utilisation de celui-ci
EP1433849A4 (fr) * 2001-09-14 2005-08-17 Takeda Pharmaceutical Nouveau polypeptide, adn associe et utilisation de ce polypeptide

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
MARCHESE A., GEORGE S.R., O'DOWD B.F.: "Novel GPCRs and their endogenous ligands: expanding the boundaries of physiology and pharmacology", TRENDS IN PHARMACOLOGICAL SCIENCES, vol. 20, no. 9, 1999, pages 370 - 375, XP002187420 *
STADEL J.M., BERGSMA D.J.: "Orphan G protein-coupled receptors: a neglecteed opportunity for pioneer", TRENDS IN PHARMACOLOGICAL SCIENCES, vol. 18, no. 11, November 1997 (1997-11-01), pages 430 - 437, XP004096215 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1433849A4 (fr) * 2001-09-14 2005-08-17 Takeda Pharmaceutical Nouveau polypeptide, adn associe et utilisation de ce polypeptide
US7323541B2 (en) 2001-09-14 2008-01-29 Takeda Pharmaceutical Company Limited Polypeptide DNA thereof and use of the same
WO2004056866A1 (fr) * 2002-12-20 2004-07-08 Geneos Oy Locus de susceptibilite a l'asthme
WO2004076487A1 (fr) * 2003-02-28 2004-09-10 Takeda Pharmaceutical Company Limited Anticorps et utilisation de celui-ci

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