Molecular Dynamics (MD) Simulation of GPR87-LPA Binding: Therapeutic Implications for Targeted Cancer Treatment

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.

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.

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.

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.

These findings may contribute to the design and development of new therapeutic compounds targeting GPR87 for the treatment of SCC.