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HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study
Long-Can Mei1, Yu-Liang Wang2, Feng-Xu Wu2
1College of Chemistry, Central China Normal University.
Briefings in Bioinformatics
|January 6, 2021
Summary
We developed HISNAPI, a new tool to analyze hotspot residue dynamics in protein-nucleic acid interactions. This method aids in identifying drug targets by considering the crucial role of protein dynamics in molecular recognition.
Area of Science:
- Biochemistry and Structural Biology
- Computational Biology and Cheminformatics
- Drug Discovery and Development
Background:
- Protein-nucleic acid interactions are fundamental to biological processes like transcription and translation.
- Hotspot residues at these interfaces are key for molecular recognition and potential drug-binding sites.
- Existing computational methods for hotspot prediction often neglect the significant impact of residue dynamics on binding affinity.
Purpose of the Study:
- To introduce HISNAPI, a novel web server for analyzing hotspot residue dynamics at protein-nucleic acid interfaces.
- To integrate molecular dynamics simulations and free energy perturbation for comprehensive hotspot analysis.
- To provide insights into hotspot intensity and correlated dynamic motions for improved drug design.
Main Methods:
- Development of the Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) web server.
- Integration of molecular dynamics (MD) simulations to capture protein and nucleic acid dynamics.
- Application of one-step free energy perturbation (FEP) to quantify binding affinities and hotspot contributions.
Main Results:
- HISNAPI successfully predicts hotspot residues and characterizes their dynamic properties, including intensity and motion correlation.
- The study highlights the importance of considering dynamics in hotspot identification for protein-nucleic acid interactions.
- Application to SARS-CoV-2 RNA-dependent RNA polymerase identified key residues and their dynamics relevant for antiviral drug design.
Conclusions:
- HISNAPI offers a valuable computational approach to analyze hotspot residue dynamics in protein-nucleic acid interactions.
- Understanding residue dynamics enhances the prediction of binding sites and facilitates rational drug design.
- The tool provides crucial insights for developing targeted antiviral therapies, exemplified by its application to SARS-CoV-2 targets.
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