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Published on: June 23, 2026
Conformational selection in silico: loop latching motions and ligand binding in enzymes
Sergio Wong1, Matthew P Jacobson
1Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94158-2517, USA.
Predicting protein conformational changes upon ligand binding is crucial for drug design. This study introduces a computational method to model "loop latching" events, improving ligand binding predictions by identifying relevant protein structures.
Area of Science:
- Computational biology
- Structural biology
- Drug discovery
Background:
- Ligand binding often induces significant protein conformational changes.
- Predicting these changes is vital for structure-based drug design.
- The "conformational selection" hypothesis suggests holo states exist transiently in apo proteins.
Purpose of the Study:
- To test the conformational selection hypothesis for loop latching events.
- To develop a computational method for predicting ligand-induced loop conformations.
- To assess the accuracy of predicted conformations in ligand docking.
Main Methods:
- Utilized replica exchange molecular dynamics and a loop prediction algorithm.
- Generated low-energy loop structures for up to 15-residue loops.
- Employed molecular docking to evaluate predicted conformations against known ligands.
Main Results:
- Successfully generated holo-like loop conformations within 2 Å RMSD for six test proteins.
- Predicted loop conformations improved ligand ranking compared to apo structures in 5/6 cases.
- Accurate ligand poses were achieved in 4/6 cases using predicted conformations.
Conclusions:
- The developed method can predict relevant loop conformations for ligand binding.
- The findings support the conformational selection mechanism in loop latching.
- Further refinement is needed for optimal performance compared to experimental holo structures.
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