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Related Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...

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Modeling Ligands into Maps Derived from Electron Cryomicroscopy
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Comparative Evaluation of Explicit Solvent Models for RNA-Ligand Docking.

Laura Almena Rodriguez1, Christian Kersten1,2

  • 1Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz, Staudingerweg 5, 55128 Mainz, Germany.

Journal of Chemical Information and Modeling
|May 21, 2026
PubMed
Summary

Including explicit solvent in RNA-ligand docking improves accuracy, especially for low-resolution structures. Computational solvation models like 3D-RISM show robust results, enhancing virtual screening potential for drug discovery.

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Targeting RNA with small molecules is a growing area in drug discovery.
  • Structure-based RNA-ligand docking faces challenges like conformational changes, ions, and solvation.
  • Few studies have explored structure-based approaches due to these difficulties.

Purpose of the Study:

  • To investigate the impact of explicit solvent inclusion on RNA-ligand docking performance.
  • To evaluate different computational solvation models and docking software.
  • To assess the effectiveness of solvent consideration for virtual screening.

Main Methods:

  • Performed redocking studies on 92 RNA-ligand complexes.
  • Utilized crystallographic water sites and computational solvation models (3D-RISM, GalaxyWater-CNN, waterdock_fxx).
  • Employed docking software: FlexX, FlexX with HYDE rescoring, GOLD, and LeadIT.

Main Results:

  • Solvent inclusion benefits are target-specific and resolution-dependent, improving average pose prediction accuracy.
  • Computational models enhanced success rates, particularly for low-resolution structures (up to 30% with 3D-RISM and LeadIT).
  • NMR and ion-free structures presented greater docking challenges than ion-containing X-ray structures.

Conclusions:

  • Explicit solvent consideration, especially using 3D-RISM, significantly advances RNA-ligand docking accuracy.
  • Hydrated docking improved cross-docking studies, highlighting RNA dynamics as a challenge.
  • Optimized solvent inclusion strategies hold great potential for prospective RNA-targeted virtual screenings.