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Molecular Dynamics (MD) Simulation of GPR87-LPA Binding: Therapeutic Implications for Targeted Cancer Treatment
Mukta Rani1,2,3, Amit Kumar Sharma4, Anuradha Nischal2
1Department of Bioinformatics, National Institute for Plant Biotechnology, Indian Council of Agricultural Research, Pusa Campus, New Delhi, 110012, India.
Background:
GPR87 is an orphan G-protein-coupled receptor (GPCR) that represents a potential molecular target for developing novel drugs aimed at treating squamous cell carcinomas (SCCs) or adenocarcinomas of the lungs and bladder.
Objectives:
The present study aims to identify potential LPA analogues as inhibitors of the GPR87 protein through computational screening. To achieve this, the human GPR87 structure was modeled using template-based tools (Phyre2 and SWISS-MODEL), iterative threading (I-TASSER), and neural network-based de novo prediction (AlphaFold2). The modeled structures were then validated by assessing their quality against template structures using Verify-3D, ProSA, and ERRAT servers.
Methods:
We conducted a comprehensive structural and functional analysis of the target protein using various computational tools. Several computational techniques were employed to explore the structural and functional characteristics of the target, with LPA selected as the initial pharmacological candidate. A library of 2,605 LPA analogues was screened against orphan GPR87 through in-silico docking analysis to identify higher-affinity and more selective potential drugs.
Results:
Molecular dynamics (MD) simulations were performed to track structural changes and convergence during the simulations. Key metrics, including the root mean square fluctuation (RMSF) of Cα-atoms, radius of gyration, and RMSD of backbone atoms, were calculated for both the apo-form and the LPA-GPR87 complex structures. These studies on structure-based drug targeting could pave the way for the development of specific inhibitors for the treatment of squamous cell carcinomas.
Conclusion:
These findings may contribute to the design and development of new therapeutic compounds targeting GPR87 for the treatment of SCC.
Insights
Researchers computationally screened LPA analogues to find inhibitors for GPR87, a target for lung and bladder cancer drugs. This study identifies potential new treatments for squamous cell carcinomas (SCCs) by analyzing GPR87 protein structure and interactions.
Area of Science:
- Computational drug discovery
- Structural biology
- Oncology
Background:
- GPR87 is an orphan G-protein-coupled receptor (GPCR) and a potential drug target for lung and bladder cancers.
- Squamous Cell Carcinomas (SCCs) and adenocarcinomas represent significant therapeutic challenges.
Purpose of the Study:
- To computationally screen Lysophosphatidic acid (LPA) analogues for potential GPR87 inhibition.
- To model and validate the human GPR87 protein structure.
- To identify high-affinity GPR87 inhibitors for SCC treatment.
Main Methods:
- Protein structure prediction using Phyre2, SWISS-MODEL, ITASSER, and AlphaFold2.
- Structure validation via Verify-3D, ProSA, and ERRAT.
- In-silico molecular docking of 2,605 LPA analogues against GPR87.
- Molecular Dynamics (MD) simulations to analyze structural stability and dynamics.
Main Results:
- Successful modeling and validation of the human GPR87 protein structure.
- Identification of several LPA analogues with potential high affinity and selectivity for GPR87.
- MD simulations provided insights into apo- and holo-GPR87 complex dynamics.
Conclusions:
- Computational screening and structure-based drug design can identify novel GPR87 inhibitors.
- These findings support the development of targeted therapies for SCCs and other GPR87-associated cancers.
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