Structure Modeling and Virtual Screening with HCAR3 to Discover Potential Therapeutic Molecules

<b>Background</b>: Hydroxycarboxylic acid receptor 3 (HCAR3) is a receptor that is mainly expressed in human adipose tissue. It can inhibit lipolysis through the inhibition of adenylyl cyclase; thus, it is closely related to the regulation of lipids in the human body. This makes HCAR3 a compelling target for developing drugs against dyslipidemia. Notably, the reported active compounds for HCAR3 are all carboxylic acids. This observation is in line with the fact that ARG111 has been reported as the key residue to anchor the active compound in a closely related homologous protein-HCAR2. <b>Methods</b>: In this study, we aim to discover new chemicals, through virtual screening, that may bind with HCAR3. As there are several choices for the receptor conformation, cross-docking was conducted and the root-mean-square deviation of the docking pose from the conformation of the crystal ligand was employed to determine the best receptor conformation for screening. Ligands from the ZINC20 database were screened through molecular docking, and 30 candidates were subjected to 100 ns MD simulations. Six stable complexes were further assessed by umbrella sampling to estimate binding affinity. <b>Results</b>: The homology model (<i>HCAR3_homology</i>) was selected as the receptor. Following the protocol determined by the retrospective docking process, prospective docking was conducted to screen the ligands from the ZINC20 database. Subsequently, the top 30 compounds with a good docking score and a good interaction with ARG111 were subjected to 100 ns molecular dynamics (MD) simulations, and their binding stability was analyzed based on the resulting trajectories. Finally, six compounds were chosen for binding free energy calculation using umbrella sampling; all showed negative binding affinities. <b>Conclusions:</b> All six compounds selected for umbrella sampling showed negative binding affinities, suggesting their potential as novel HCAR3 ligands for the development of drugs against dyslipidemia.

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Publication Details

Journal
Pharmaceuticals
Published
2025-08-28
DOI
https://doi.org/10.3390/ph18091290
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Structure Modeling and Virtual Screening with HCAR3 to Discover Potential Therapeutic Molecules

Bin Lin, Yi Peng, Ying‐Chih Chiang, Zhihao Zhao et al.
Pharmaceuticals
Computational Drug Discovery Methods
article

Structure Modeling and Virtual Screening with HCAR3 to Discover Potential Therapeutic Molecules

Bin Lin, Yi Peng, Ying‐Chih Chiang, Zhihao Zhao, Yulan Liu, Yilin Guo
article en

Abstract

<b>Background</b>: Hydroxycarboxylic acid receptor 3 (HCAR3) is a receptor that is mainly expressed in human adipose tissue. It can inhibit lipolysis through the inhibition of adenylyl cyclase; thus, it is closely related to the regulation of lipids in the human body. This makes HCAR3 a compelling target for developing drugs against dyslipidemia. Notably, the reported active compounds for HCAR3 are all carboxylic acids. This observation is in line with the fact that ARG111 has been reported as the key residue to anchor the active compound in a closely related homologous protein-HCAR2. <b>Methods</b>: In this study, we aim to discover new chemicals, through virtual screening, that may bind with HCAR3. As there are several choices for the receptor conformation, cross-docking was conducted and the root-mean-square deviation of the docking pose from the conformation of the crystal ligand was employed to determine the best receptor conformation for screening. Ligands from the ZINC20 database were screened through molecular docking, and 30 candidates were subjected to 100 ns MD simulations. Six stable complexes were further assessed by umbrella sampling to estimate binding affinity. <b>Results</b>: The homology model (<i>HCAR3_homology</i>) was selected as the receptor. Following the protocol determined by the retrospective docking process, prospective docking was conducted to screen the ligands from the ZINC20 database. Subsequently, the top 30 compounds with a good docking score and a good interaction with ARG111 were subjected to 100 ns molecular dynamics (MD) simulations, and their binding stability was analyzed based on the resulting trajectories. Finally, six compounds were chosen for binding free energy calculation using umbrella sampling; all showed negative binding affinities. <b>Conclusions:</b> All six compounds selected for umbrella sampling showed negative binding affinities, suggesting their potential as novel HCAR3 ligands for the development of drugs against dyslipidemia.

PharmaceuticalsVol. 18(9)
Shenyang Pharmaceutical University (CN), Chinese University of Hong Kong, Shenzhen (CN)
Chinese University of Hong Kong, Shenzhen Municipal Science and Technology Innovation Council
Openalex Percentile: Top 76%
Computational Drug Discovery Methods
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