Hybrid MM/CG Webserver: Automatic Set Up of Molecular Mechanics/Coarse-Grained Simulations for Human G Protein-Coupled Receptor/Ligand Complexes

Facilitating CG Simulations with MAD: The MArtini Database Server

The MArtini Database (MAD - https://mad.ibcp.fr) is a web server designed for the sharing of structures and topologies of molecules parametrized with the Martini coarse-grained (CG) force field. MAD can also convert atomistic structures into CG structures and prepare complex systems (including proteins, lipids, etc.) for molecular dynamics (MD) simulations at the CG level. It is dedicated to the generation of input files for Martini 3, the most recent version of this popular CG force field. Specifically, the MAD server currently includes tools to submit or retrieve CG models of a wide range of molecules (lipids, carbohydrates, nanoparticles, etc.), transform atomistic protein structures into CG structures and topologies, with fine control on the process and assemble biomolecules into large systems, and deliver all files necessary to start simulations in the GROMACS MD engine.

GPCRsignal: webserver for analysis of the interface between G-protein-coupled receptors and their effector proteins by dynamics and mutations

GPCRsignal (https://gpcrsignal.biomodellab.eu/) is a webserver devoted to signaling complexes of G-protein–coupled receptors (GPCRs). The recent improvement in cryo-electron microscopy resulted in the determination of a large number of high-resolution structures of GPCRs bound to their effector proteins: G proteins or arrestins. Analyzing the interfaces between receptor and an effector protein is of high importance since a selection of proper G protein or specific conformation of arrestin leads to changes of signaling that can significantly affect action of drugs. GPCRsignal provides a possibility of running molecular dynamics simulations of all currently available GPCR-effector protein complexes for curated structures: wild-type, with crystal/cryo-EM mutations, or with mutations introduced by the user. The simulations are performed in an implicit water-membrane environment, so they are rather fast. User can run several simulations to obtain statistically valid results. The simulations can be analyzed separately using dynamic FlarePlots for particular types of interactions. One can also compare groups of simulations in Interaction frequency analysis as HeatMaps and also in interaction frequency difference analysis as sticks, linking the interacting residues, of different color and size proportional to differences in contact frequencies.

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules

The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.

Structural dynamics bridge the gap between the genetic and functional levels of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly all physiological processes in the human body and represent an important drug targeting class. The genes encoding the different GPCR (sub)types determine their specific functionality, which can be altered by natural genetic variants and isoforms. Deciphering the molecular link between sequence diversity and its functional consequences is a current challenge and critical for the comprehension of the physiological response of GPCRs. It requires a global understanding of how protein sequence translates into protein structure, how this impacts the structural motions of the protein, and, finally, how all these factors determine the receptor functionality. Here, we discuss available resources and state-of-the-art computational approaches to address this question.

CGMD Platform: Integrated Web Servers for the Preparation, Running, and Analysis of Coarse-Grained Molecular Dynamics Simulations

Advances in coarse-grained molecular dynamics (CGMD) simulations have extended the use of computational studies on biological macromolecules and their complexes, as well as the interactions of membrane protein and lipid complexes at a reduced level of representation, allowing longer and larger molecular dynamics simulations. Here, we present a computational platform dedicated to the preparation, running, and analysis of CGMD simulations. The platform is built on a completely revisited version of our Martini coarsE gRained MembrAne proteIn Dynamics (MERMAID) web server, and it integrates this with other three dedicated services. In its current version, the platform expands the existing implementation of the Martini force field for membrane proteins to also allow the simulation of soluble proteins using the Martini and the SIRAH force fields. Moreover, it offers an automated protocol for carrying out the backmapping of the coarse-grained description of the system into an atomistic one.

Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-Based Hybrid Molecular Mechanics/Coarse-Grained Approach

Human G protein-coupled receptors (hGPCRs) are the most frequent targets of Food and Drug Administration (FDA)-approved drugs. Structural bioinformatics, along with molecular simulation, can support structure-based drug design targeting hGPCRs. In this context, several years ago, we developed a hybrid molecular mechanics (MM)/coarse-grained (CG) approach to predict ligand poses in low-resolution hGPCR models. The approach was based on the GROMOS96 43A1 and PRODRG united-atom force fields for the MM part. Here, we present a new MM/CG implementation using, instead, the Amber 14SB and GAFF all-atom potentials for proteins and ligands, respectively. The new implementation outperforms the previous one, as shown by a variety of applications on models of hGPCR/ligand complexes at different resolutions, and it is also more user-friendly. Thus, it emerges as a useful tool to predict poses in low-resolution models and provides insights into ligand binding similarly to all-atom molecular dynamics, albeit at a lower computational cost.