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HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study.
Mei, Long-Can; Wang, Yu-Liang; Wu, Feng-Xu; Wang, Fan; Hao, Ge-Fei; Yang, Guang-Fu.
  • Mei LC; College of Chemistry, Central China Normal University.
  • Wang YL; College of Chemistry of CCNU.
  • Wu FX; College of Chemistry of CCNU.
  • Wang F; College of Chemistry of CCNU.
  • Hao GF; College of Chemistry of CCNU.
  • Yang GF; Pesticide Science from Nankai University, Tianjin, China.
Brief Bioinform ; 22(5)2021 09 02.
Article in English | MEDLINE | ID: covidwho-1012820
ABSTRACT
Protein-nucleic acid interactions play essential roles in many biological processes, such as transcription, replication and translation. In protein-nucleic acid interfaces, hotspot residues contribute the majority of binding affinity toward molecular recognition. Hotspot residues are commonly regarded as potential binding sites for compound molecules in drug design projects. The dynamic property is a considerable factor that affects the binding of ligands. Computational approaches have been developed to expedite the prediction of hotspot residues on protein-nucleic acid interfaces. However, existing approaches overlook hotspot dynamics, despite their essential role in protein function. Here, we report a web server named Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) to analyze hotspot residue dynamics by integrating molecular dynamics simulation and one-step free energy perturbation. HISNAPI is capable of not only predicting the hotspot residues in protein-nucleic acid interfaces but also providing insights into their intensity and correlation of dynamic motion. Protein dynamics have been recognized as a vital factor that has an effect on the interaction specificity and affinity of the binding partners. We applied HISNAPI to the case of SARS-CoV-2 RNA-dependent RNA polymerase, a vital target of the antiviral drug for the treatment of coronavirus disease 2019. We identified the hotspot residues and characterized their dynamic behaviors, which might provide insight into the target site for antiviral drug design. The web server is freely available via a user-friendly web interface at http//chemyang.ccnu.edu.cn/ccb/server/HISNAPI/ and http//agroda.gzu.edu.cn9999/ccb/server/HISNAPI/.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Nucleic Acids / Proteins / Computational Biology Type of study: Case report / Prognostic study Language: English Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Nucleic Acids / Proteins / Computational Biology Type of study: Case report / Prognostic study Language: English Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article