Best Practices in Mixed-Solvent Molecular Dynamics and Solvent-Site-Biased Docking

In this work, we present practical recommendations for the setup, analysis, and integration of mixed-solvent molecular dynamics (MixMD), solvent-biased docking (SSBD) workflows and pharmacophore analysis, drawing on more than a decade of accumulated experience in the field from multiple implementations and applications. Rather than providing a comprehensive review of all applications of MixMD, this Perspective focuses specifically on its use as a methodological foundation for deriving solvent sites that inform docking and pharmacophore-based strategies in structure-based drug design. Currently, mixed-solvent simulations and solvent-biased docking constitute a coherent, experimentally validated strategy for identifying and exploiting binding hot spots in proteins, and for translating solvent occupancy patterns into structurally interpretable pharmacophoric features and docking constraints. By standardizing best practices, and synthesizing previously published computational studies into a unified methodological framework, we aim to facilitate broader adoption of these methods within the structure-based drug design community, enabling more reliable identification of functional sites and accelerating rational ligand discovery.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2026-03-23
DOI
https://doi.org/10.1021/acs.jcim.6c00082
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

Best Practices in Mixed-Solvent Molecular Dynamics and Solvent-Site-Biased Docking

Juan Manuel Prieto, Marcelo A. Martí, Camila M. Clemente, Jose A.D Cuellar Estrada
Journal of Chemical Information and Modeling
Computational Drug Discovery Methods
article

Best Practices in Mixed-Solvent Molecular Dynamics and Solvent-Site-Biased Docking

Juan Manuel Prieto, Marcelo A. Martí, Camila M. Clemente, Jose A.D Cuellar Estrada
article en

Abstract

In this work, we present practical recommendations for the setup, analysis, and integration of mixed-solvent molecular dynamics (MixMD), solvent-biased docking (SSBD) workflows and pharmacophore analysis, drawing on more than a decade of accumulated experience in the field from multiple implementations and applications. Rather than providing a comprehensive review of all applications of MixMD, this Perspective focuses specifically on its use as a methodological foundation for deriving solvent sites that inform docking and pharmacophore-based strategies in structure-based drug design. Currently, mixed-solvent simulations and solvent-biased docking constitute a coherent, experimentally validated strategy for identifying and exploiting binding hot spots in proteins, and for translating solvent occupancy patterns into structurally interpretable pharmacophoric features and docking constraints. By standardizing best practices, and synthesizing previously published computational studies into a unified methodological framework, we aim to facilitate broader adoption of these methods within the structure-based drug design community, enabling more reliable identification of functional sites and accelerating rational ligand discovery.

Journal of Chemical Information and Modeling
Universidad de Flores (AR), Fundación Ciencias Exactas y Naturales (AR)
Openalex Percentile: Top 10%
Computational Drug Discovery Methods
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