Dataset Information

Recent Trends and Applications of Molecular Modeling in GPCR?Ligand Recognition and Structure-Based Drug Design.

ABSTRACT: G protein-coupled receptors represent the largest family of human membrane proteins and are modulated by a variety of drugs and endogenous ligands. Molecular modeling techniques, especially enhanced sampling methods, have provided significant insight into the mechanism of GPCR?ligand recognition. Notably, the crucial role of the membrane in the ligand-receptor association process has earned much attention. Additionally, docking, together with more accurate free energy calculation methods, is playing an important role in the design of novel compounds targeting GPCRs. Here, we summarize the recent progress in the computational studies focusing on the above issues. In the future, with continuous improvement in both computational hardware and algorithms, molecular modeling would serve as an indispensable tool in a wider scope of the research concerning GPCR?ligand recognition as well as drug design targeting GPCRs.

SUBMITTER: Yuan X

PROVIDER: S-EPMC6073596 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Recent Trends and Applications of Molecular Modeling in GPCR⁻Ligand Recognition and Structure-Based Drug Design.

Yuan Xiaojing X Xu Yechun Y

International journal of molecular sciences 20180720 7

G protein-coupled receptors represent the largest family of human membrane proteins and are modulated by a variety of drugs and endogenous ligands. Molecular modeling techniques, especially enhanced sampling methods, have provided significant insight into the mechanism of GPCR⁻ligand recognition. Notably, the crucial role of the membrane in the ligand-receptor association process has earned much attention. Additionally, docking, together with more accurate free energy calculation methods, is pla ...[more]

PMID: 30036949

Similar Datasets

Project description:Purpose G Protein-Coupled Receptors (GPCRs) are a large family of therapeutically important proteins and as diverse X-ray structures become available it is increasingly possible to leverage structural information for rational drug design. We present herein approaches that use explicit water networks combined with energetic surveys of the binding site (GRID), providing an enhanced druggability and ligand design approach, with structural understanding of ligand binding, including a ‘magic’ methyl and binding site mutations, and a fast new approach to generate and score waters. Methods The GRID program was used to identify lipophilic and hydrogen bonding hotspots. Explicit full water networks were generated and scored for (pseudo)apo structures and ligand-protein complexes using a new approach, WaterFLAP (Molecular Discovery), together with WaterMap (Schrödinger) for (pseudo)apo structures. A scoring function (MetaScore) was developed using a fast computational protocol based on several short adiabatic biased MD simulations followed by multiple short well-tempered metadynamics runs. Results Analysis of diverse ligands binding to the adenosine A2A receptor together with new structures for the ?/?/? opioid and CCR5 receptors confirmed the key role of lipophilic hotspots in driving ligand binding and thus design; the displacement of ‘unhappy’ waters generally found in these regions provides a key binding energy component. Complete explicit water networks could be robustly generated for protein-ligand complexes using a WaterFLAP based approach. They provide a structural understanding of structure-activity relationships such as a ‘magic methyl’ effect and with the metadynamics approach a useful estimation of the binding energy changes resulting from active site mutations. Conclusions The promise of full structure-based drug design (SBDD) for GPCRs is now possible using a combination of advanced experimental and computational data. The conformational thermostabilisation of StaR® proteins provide the ability to easily generate biophysical screening data (binding including fragments, kinetics) and to get crystal structures with both potent and weak ligands. Explicit water networks for apo and ligand-complex structures are a critical ‘third dimension’ for SBDD and are key for understanding ligand binding energies and kinetics. GRID lipophilic hotspots are found to be key drivers for binding. In this context ‘high end’ GPCR ligand design is now enabled. Electronic supplementary material The online version of this article (doi:10.1186/2193-9616-1-23) contains supplementary material, which is available to authorized users.

Dataset Information

Recent Trends and Applications of Molecular Modeling in GPCR?Ligand Recognition and Structure-Based Drug Design.

Publications

Recent Trends and Applications of Molecular Modeling in GPCR⁻Ligand Recognition and Structure-Based Drug Design.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets