| Title: |
Statistical Molecular Interaction Fields: A Fast and Informative Tool for Characterizing RNA and Protein-Binding Pockets |
| Authors: |
Morera, Diego Barquero; Mattiotti, Giovanni; Kocev, Alexandar; Rousselot, Amshuman; Meuret, Louis; Rouaud, Lucas; Santuz, Hubert; Baaden, Marc; Taly, Antoine; Pasquali, Samuela |
| Contributors: |
Unité de Biologie Fonctionnelle et Adaptative (BFA (UMR_8251 / U1133)); Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité); Institut de Chimie des Substances Naturelles (ICSN); Institut de Chimie - CNRS Chimie (INC-CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS); Laboratoire de biochimie théorique Paris (LBT (UMR_8266)); Institut de biologie physico-chimique (IBPC (FR_550)); Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie - CNRS Chimie (INC-CNRS)-Centre National de la Recherche Scientifique (CNRS); ANR-11-LABX-0011,DYNAMO,Dynamique des membranes transductrices d'énergie : biogénèse et organisation supramoléculaire.(2011); ANR-11-EQPX-0008,CACSICE,Centre d'analyse de systèmes complexes dans les environnements complexes(2011); ANR-22-CE45-0032,MERLIN,Exploration multi-échelle du polymorphisme des ARN pour al conception des médicaments(2022); ANR-21-CE45-0014,PIRATE,Pharmacophore Interactif grace à la Réalité AugmenTéE(2021) |
| Source: |
ISSN: 1549-9618. |
| Publisher Information: |
CCSD; American Chemical Society |
| Publication Year: |
2025 |
| Subject Terms: |
[CHIM]Chemical Sciences |
| Description: |
International audience ; Developing a physical understanding of the interactions between a macromolecular target and its ligands is a crucial step in structure-based drug design. Although many tools exist to characterize protein-binding pockets in silico, this is not yet the case for RNA, which has only recently been recognized as a suitable target for small ligands. Molecular Interaction Fields (MIF) are a useful tool to characterize the interactions of a given binding pocket. However, classical MIFs heavily rely on the use of probes, which makes their calculation accurate but very specific to the binding partners in question. We develop here a simple version of MIF, that we call Statistical Molecular Interaction Fields (SMIF), based on functional forms inspired by coarse-grained models and parametrized based on PDB structures. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1021/acs.jctc.5c00688 |
| Availability: |
https://hal.science/hal-05236200; https://hal.science/hal-05236200v1/document; https://hal.science/hal-05236200v1/file/Fields_final.pdf; https://doi.org/10.1021/acs.jctc.5c00688 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.1036F29D |
| Database: |
BASE |