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Updated: Jul 19, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
Published on: January 26, 2024
Coupled atomic charge selectivity for optimal ligand-charge distributions at protein binding sites
Sathesh Bhat1, Traian Sulea, Enrico O Purisima
1Department of Biochemistry, McGill University, 3655 Sir William Osler, Montreal, Quebec H3G 1Y6, Canada.
This study introduces a new method to analyze how atomic charges in molecules affect binding. The findings reveal significant differences in charge selectivity when considering coupled atomic charge changes, impacting molecular design.
Area of Science:
- Computational chemistry
- Molecular modeling
- Drug design
Background:
- Charge optimization is crucial for understanding and improving molecular binding electrostatics.
- Existing methods for charge selectivity analysis do not account for coupled charge changes.
Purpose of the Study:
- To develop and apply a novel method for characterizing charge selectivity in a concerted manner.
- To analyze the coupled charge selectivity of celecoxib binding to COX2 and CAII.
Main Methods:
- Developed a novel approach for calculating concerted charge selectivity.
- Applied the method to celecoxib, a ligand binding to cyclooxygenase 2 (COX2) and carbonic anhydrase II (CAII).
- Compared uncoupled and coupled charge selectivity profiles.
Main Results:
- The novel method accounts for coupled changes in atomic charges, unlike previous approaches.
- Celecoxib exhibits distinct charge selectivity profiles when binding to COX2 versus CAII.
- Coupled charge selectivity calculations yield significantly different results compared to uncoupled methods.
Conclusions:
- Concerted charge selectivity analysis provides a more accurate representation of ligand-protein interactions.
- The findings offer insights into the cross-reactivity of celecoxib and can guide future molecular design.
- This approach enhances the understanding of binding electrostatics and molecular recognition.
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