Boosting Drug Discovery: Expanding the Applicability of Fragment Dissolved Molecular Dynamics to Accelerate Binding Mode Elucidation

The use of small organic molecules has become one of the most popular strategies in computer-aided drug design (CADD) to facilitate the identification of potential drug-like compounds in the early stages of drug development. In this scenario, novel computational approaches such as the use of the fragment dissolved molecular dynamics (fdMD) methodology emerged as a new framework for the modeling of ligand-receptor interactions. Consisting of molecular dynamics (MD) simulations of the target protein solvated with multiple copies of the same fragment, the original approach is able to identify the most favorable binding site for the system studied in a reasonable simulation time scale (0.2-1 μs). In the present work, we have introduced the use of Gaussian accelerated molecular dynamics (GaMD) to facilitate system exploration, accelerate binding site identification and additionally enhance binding mode elucidation. For this purpose, up to 12 different systems with crystallographic information available have been employed for validation.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-11-24
DOI
https://doi.org/10.1021/acs.jcim.5c02122
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Boosting Drug Discovery: Expanding the Applicability of Fragment Dissolved Molecular Dynamics to Accelerate Binding Mode Elucidation

Maria Nuria Peralta-Moreno, María Santos Tomás Belenguer, José M. Granadino‐Roldán, J. Rubio
Journal of Chemical Information and Modeling
Computational Drug Discovery Methods
article

Boosting Drug Discovery: Expanding the Applicability of Fragment Dissolved Molecular Dynamics to Accelerate Binding Mode Elucidation

Maria Nuria Peralta-Moreno, María Santos Tomás Belenguer, José M. Granadino‐Roldán, J. Rubio
article en

Abstract

The use of small organic molecules has become one of the most popular strategies in computer-aided drug design (CADD) to facilitate the identification of potential drug-like compounds in the early stages of drug development. In this scenario, novel computational approaches such as the use of the fragment dissolved molecular dynamics (fdMD) methodology emerged as a new framework for the modeling of ligand-receptor interactions. Consisting of molecular dynamics (MD) simulations of the target protein solvated with multiple copies of the same fragment, the original approach is able to identify the most favorable binding site for the system studied in a reasonable simulation time scale (0.2-1 μs). In the present work, we have introduced the use of Gaussian accelerated molecular dynamics (GaMD) to facilitate system exploration, accelerate binding site identification and additionally enhance binding mode elucidation. For this purpose, up to 12 different systems with crystallographic information available have been employed for validation.

Journal of Chemical Information and ModelingVol. 65(23)
Universidad de Jaén (ES), Universitat de Barcelona (ES), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 64%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.