Khalid Mohammad, H Alqarni Mohammed, Foudah Ahmed I, Saad Al Oraby Mishary
Department of Pharmacognosy College of Pharmacy, Prince Sattam Bin Abdulaziz University Alkharj, Saudi Arabia.
Forensic Toxicology, Specialized Comprehensive Clinics for Security Forces in Taif, Security Forces Hospital, Makkah Region, Taif, Saudi Arabia.
J Biomol Struct Dyn. 2025 Mar 26:1-12. doi: 10.1080/07391102.2025.2483963.
Poly (ADP-ribose) polymerase 1 (PARP1) is a nuclear protein that plays a pivotal role in DNA repair and has emerged as a promising target for cancer therapy. Repurposing existing FDA-approved drugs for PARP1 inhibition offers an accelerated route to drug discovery. Here, we present an integrated approach to drug repurposing for PARP1 inhibition while utilizing an integrated approach involving structure-based virtual screening and molecular dynamics (MD) simulations. First, a curated library of 3648 FDA-approved drugs from DrugBank was screened to identify potential candidates capable of binding to the PARP1. Our study reveals a subset of drug molecules with favorable binding profiles and stable interactions within the PARP1 active site. The standout candidate, Nilotinib, was selected based on its drug profile and subjected to a detailed analysis, including interaction studies and 500 ns all-atom MD simulations. By integrating multiple computational approaches, we provide a rational framework for the selection of Nilotinib, demonstrating its PARP1 binding features and potential for therapeutic development after further experimentation. This study highlights the power of computational methods in accelerating drug repurposing efforts, offering an efficient strategy for identifying novel therapeutic options for PARP1-associated diseases.
聚(ADP - 核糖)聚合酶1(PARP1)是一种核蛋白,在DNA修复中起关键作用,并且已成为癌症治疗的一个有前景的靶点。重新利用美国食品药品监督管理局(FDA)批准的现有药物来抑制PARP1为药物研发提供了一条加速途径。在此,我们提出一种用于PARP1抑制的药物重新利用的综合方法,同时利用一种涉及基于结构的虚拟筛选和分子动力学(MD)模拟的综合方法。首先,对来自DrugBank的3648种FDA批准药物的精选文库进行筛选,以识别能够与PARP1结合的潜在候选药物。我们的研究揭示了一部分在PARP1活性位点具有良好结合特征和稳定相互作用的药物分子。基于其药物特性选择了突出的候选药物尼罗替尼,并对其进行详细分析,包括相互作用研究和500纳秒的全原子MD模拟。通过整合多种计算方法,我们为尼罗替尼的选择提供了一个合理的框架,展示了其PARP1结合特征以及经过进一步实验后用于治疗开发的潜力。这项研究突出了计算方法在加速药物重新利用工作中的作用,为识别PARP1相关疾病的新型治疗选择提供了一种有效策略。