Exploring the potential of structural modeling and molecular docking for efficient siRNA screening: A promising approach to Combat viral mutants, with a focus on HIV-1

Biochem Biophys Res Commun. 2024 May 14:708:149769. doi: 10.1016/j.bbrc.2024.149769. Epub 2024 Mar 11.

Abstract

RNA interference (RNAi) holds immense potential for sequence-specific downregulation of disease-related genes. Small interfering RNA (siRNA) therapy has made remarkable strides, with FDA approval for treating specific human diseases, showcasing its promising future in disease treatment. Designing highly efficient siRNAs is a critical step in this process. Previous studies have introduced various algorithms and parameters for siRNA design and scoring. However, these attempts have often fallen short of meeting all essential criteria or required modifications, resulting in variable and unclear effectiveness of screened siRNAs, particularly against viral mutants with non-conserved short sequences. In this study, we present a fully optimized siRNA screening system considering all necessary parameters. Notably, we highlight the critical role of molecular docking simulations between siRNA and two functional domains of the Argonaute protein (PAZ and PIWI) in identifying the most efficient siRNAs, since the appropriate interaction between the guide siRNA strand and the RISC complex is crucial. Through our stringent method, we designed approximately 50 potential siRNAs targeting the HIV-1 vpr gene. Evaluation through XTT, qRT-PCR, and flow cytometry analysis on RAW 264.7 macrophage stable cells revealed negligible cytotoxicity and exceptional gene-silencing efficiency at both the transcriptional and translational levels for the top-ranked screened siRNAs. Given the growing interest in siRNA-based therapeutics, we anticipate that the insights from this study will contribute to improving treatment strategies against mutant viruses, particularly HIV-1.

Keywords: HIV-1 vpr; Molecular docking; Mutation studies; RAW 264.7 cells; siRNA screening.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Silencing
  • HIV-1* / genetics
  • HIV-1* / metabolism
  • Humans
  • Molecular Docking Simulation
  • RNA Interference
  • RNA, Small Interfering / metabolism

Substances

  • RNA, Small Interfering