Hossain Md Shahadat, Alom Md Siddik, Kader Mohammad Salauddin, Hossain Mohammed Akhter, Halim Mohammad A
Division of Infectious Diseases and Division of Computer Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka 1215, Bangladesh.
Department of Pharmacy, Faculty of Life Science, Mawlana Bhashani Science & Technology University, Tangail 1902, Bangladesh.
ACS Phys Chem Au. 2024 Jul 5;4(5):464-475. doi: 10.1021/acsphyschemau.4c00006. eCollection 2024 Sep 25.
HIV-1 integrase (IN), a major protein in the HIV life cycle responsible for integrating viral cDNA into the host DNA, represents a promising drug target. Small peptides have emerged as antiviral therapeutics for HIV because of their facile synthesis, highly selective nature, and fewer side effects. However, selecting the best candidates from a vast pool of peptides is a daunting task. In this study, multistep virtual screening was employed to identify potential peptides from a list of 280 HIV inhibitory peptides. Initially, 80 peptides were selected based on their minimum inhibitory concentrations (MIC). Then, molecular docking was performed to evaluate their binding scores compared to HIP000 and HIP00N which are experimentally validated HIV-1 integrase binding peptides that were used as a positive and negative control, respectively. The top-scoring docked complexes, namely, IN-HIP1113, IN-HIP1140, IN-HIP1142, IN-HIP678, IN-HIP776, and IN-HIP777, were subjected to initial 500 ns molecular dynamics (MD) simulations. Subsequently, HIP776, HIP777, and HIP1142 were selected for an in-depth mechanistic study of peptide interactions, with multiple simulations conducted for each complex spanning one microsecond. Independent simulations of the peptides, along with comparisons to the bound state, were performed to elucidate the conformational dynamics of the peptides. These peptides exhibit strong interactions with specific residues, as revealed by snapshot interaction analysis. Notably, LYS159, LYS156, VAL150, and GLU69 residues are prominently involved in these interactions. Additionally, residue-based binding free energy (BFE) calculations highlight the significance of HIS67, GLN148, GLN146, and SER147 residues within the binding pocket. Furthermore, the structure-activity relationship (SAR) analysis demonstrated that aromatic amino acids and the overall volume of peptides are the two major contributors to the docking scores. The best peptides will be validated experimentally by incorporating SAR properties, aiming to develop them as therapeutic agents and structural models for future peptide-based HIV-1 drug design, addressing the urgent need for effective HIV treatments.
HIV-1整合酶(IN)是HIV生命周期中的一种主要蛋白质,负责将病毒cDNA整合到宿主DNA中,是一个很有前景的药物靶点。小肽由于其易于合成、高度选择性且副作用较少,已成为治疗HIV的抗病毒药物。然而,从大量肽中筛选出最佳候选者是一项艰巨的任务。在本研究中,采用多步虚拟筛选从280种HIV抑制肽列表中鉴定潜在肽。最初,根据它们的最低抑菌浓度(MIC)选择了80种肽。然后,进行分子对接以评估它们与HIP000和HIP00N相比的结合分数,HIP000和HIP00N分别是经实验验证的HIV-1整合酶结合肽,用作阳性和阴性对照。得分最高的对接复合物,即IN-HIP1113、IN-HIP1140、IN-HIP1142、IN-HIP678、IN-HIP776和IN-HIP777,进行了初始500纳秒的分子动力学(MD)模拟。随后,选择HIP776、HIP777和HIP1142进行肽相互作用的深入机理研究,对每个复合物进行了长达一微秒的多次模拟。对肽进行独立模拟,并与结合状态进行比较,以阐明肽的构象动力学。如快照相互作用分析所示,这些肽与特定残基表现出强烈相互作用。值得注意的是,LYS159、LYS156、VAL150和GLU69残基显著参与这些相互作用。此外,基于残基的结合自由能(BFE)计算突出了结合口袋内HIS67、GLN148、GLN146和SER147残基的重要性。此外,结构-活性关系(SAR)分析表明,芳香族氨基酸和肽的总体积是对接分数的两个主要贡献因素。最佳肽将通过纳入SAR特性进行实验验证,旨在将它们开发为治疗剂和未来基于肽的HIV-1药物设计的结构模型,以满足有效治疗HIV的迫切需求。