# US 12,002,551 B2 · Method to distinguish peroxisome proliferator-activated receptor gamma full agonist, partial agonist and antagonist with different activities and identification thereof

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- Number: US 12,002,551 B2
- Document ID: US12002551B2
- Status: Granted
- Kind: B2
- Application number: 16/816,306
- Filed: 2020-03-12
- Published: 2020-11-26
- Granted: 2024-06-04
- Earliest claimed: 2019-05-21
- Assignees: Nanjing University
- Applicants: Nanjing University
- Inventors: Hongling Liu; Laihao Shi
- Web page: https://patentgrep.com/patent/US12002551B2

## CPC

- G16C 20/50: Molecular design, e.g. of drugs
- C07K 1/00: General methods for the preparation of peptides {, i.e. processes for the organic chemical preparation of peptides or proteins of any length}
- C07K 1/04: on carriers {(C07K1/003, C07K1/006 take precedence)}
- C07K 14/70567: {Nuclear receptors, e.g. retinoic acid receptor [RAR], RXR, nuclear orphan receptors}
- G16B 5/00: ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
- G16B 15/00: ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
- G16B 15/30: Drug targeting using structural data; Docking or binding prediction
- G16C 20/70: Machine learning, data mining or chemometrics
- G16C 10/00: Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like
- G16C: COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- C07K: PEPTIDES (peptides in foodstuffs A23; obtaining protein compositions for foodstuffs, working-up proteins for foodstuffs A23J; preparations for medicinal purposes A61K; peptides containing beta-lactam rings C07D; cyclic dipeptides not having in their molecule any other peptide link than those which form their ring, e.g. piperazine-2,5-diones, C07D; ergot alkaloids of the cyclic peptide type C07D519/02; macromolecular compounds having statistically distributed amino acid units in their molecules, i.e. when the preparation does not provide for a specific; but for a random sequence of the amino acid units, homopolyamides and block copolyamides derived from amino acids C08G69/00; macromolecular products derived from proteins C08H1/00; preparation of glue or gelatine C09H; single cell proteins, enzymes C12N; genetic engineering processes for obtaining peptides C12N15/00; compositions for measuring or testing processes involving enzymes C12Q; investigation or analysis of biological material G01N33/00)
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY

## Abstract

The present invention discloses a method of constructing a pharmacophore to determine whether a molecule is a peroxisome proliferator-activated receptor γ full agonist, partial agonist or antagonist in terms of a binding energy or a free energy surface comprising: providing a protein receptor mimicking said peroxisome proliferator-activated receptor γ and a corresponding ligand; docking the corresponding ligand and the protein receptor to form a docked conformation; performing at least two rounds of molecular dynamic simulation to obtain at least one trajectory and at least one free energy surface; inputting the trajectory to construct at least one pharmacophore and obtaining the binding energy of the corresponding ligand; comparing the molecule with the corresponding ligand in terms of the binding energy thereof to the protein receptor in order to determine whether the molecule is the peroxisome proliferator-activated receptor γ full agonist, partial agonist or antagonist.

## Claims

### Claim 1

A method of identifying endocrine disrupting chemicals by determining whether a molecule of interest is a peroxisome proliferator-activated receptor γ full agonist, partial agonist or antagonist by analyzing a binding energy, the method comprising:
providing a simulated protein receptor mimicking said peroxisome proliferator-activated receptor γ and a simulation of the molecule of interest;
docking the simulation of the molecule of interest and the simulated protein receptor to form a docked conformation;
performing at least two rounds of molecular dynamic simulation to obtain at least one trajectory and at least one free energy surface, wherein one of the at least two rounds of molecular dynamic simulation comprises adopting a collective variable (CV) 1 and a CV2, wherein the CV1 is a first distance between Cα of Tyr473 on H12 and Cα of Leu453 on H11 of the peroxisome proliferator-activated receptor γ, and CV2 is a second distance between Cα of Tyr473 on H12 and Ca of Lys319 on H4 of the peroxisome proliferator-activated receptor γ;
inputting the trajectory to construct at least one pharmacophore and obtaining a binding energy diagram of the simulation of the molecule of interest docked on the simulated protein receptor; and
analyzing the binding energy diagram of simulation of the molecule of interest docked on the simulated protein in order to determine whether the molecule of interest is the peroxisome proliferator-activated receptor γ full agonist, partial agonist or antagonist;
wherein if the molecule of interest is a full agonist, the binding energy diagram shows one low energy area; and if the molecule of interest is an antagonist or a partial agonist, the binding energy diagram shows multiple low energy areas.

### Claim 2 (depends on 1)

The method of claim 1, wherein said providing the simulated protein receptor comprises removing at least one small molecule mekt21 in a A chain and a B chain from said simulated protein receptor; removing at least one water molecule to form a remaining B chain protein, wherein the remaining B chain protein after removal of the at least one small molecule mekt21 and the at least one water molecule is saved as a template for a homology modeling prior to said performing at least two rounds of simulation.

### Claim 3 (depends on 1)

The method of claim 1, wherein said docking simulation of the molecule of interest and the simulated protein receptor to form the docked conformation comprises searching a binding pocket with a threshold value of 0.5 and a bloat value of 0.