Durdagi Serdar, Sayyah Ehsan, Ulug Muhammet Eren, Durdağı Serdar
Bahcesehir University, School of Medicine, Biophysics, Besiktas, 34353, Istanbul, TURKEY.
Bahçeşehir Üniversitesi: Bahcesehir Universitesi, Computational Drug Design Center, Istanbul, Turkey, Istanbul, 34353, Istanbul, TURKEY.
ChemMedChem. 2025 Apr 27:e202500210. doi: 10.1002/cmdc.202500210.
Ubiquitin-specific protease 7 (USP7) is a key deubiquitinating enzyme involved in tumor suppression, DNA repair, and epigenetic regulation. Given its critical role in cancer progression, USP7 has emerged as an attractive therapeutic target. In this study, we employed a multi-tier computational approach, integrating ligand-based virtual screening, molecular docking, MD simulations, MM/GBSA binding free energy calculations, binary QSAR modeling, and steered MD simulations to identify and optimize novel USP7 inhibitors. Using SwissSimilarity-based ligand screening, we selected structurally related analogs of previously identified and validated hit compounds by our research group and performed grid-based docking simulations, prioritizing molecules with high binding affinity (docking scores < -8.0 kcal/mol). The top-ranked candidates were refined through long-term MD simulations and MM/GBSA free energy calculations to assess their structural stability and interaction patterns with key USP7 residues. Binary QSAR analysis further evaluated the anticancer potential of these compounds, filtering those with high predicted therapeutic activity (normalized therapeutic activity value > 0.5). Furthermore, to investigate selectivity of the potent compounds, we performed cross-docking against multiple USP family members. Finally, sMD simulations provided insights into the mechanical stability of ligand-protein interactions. The identified candidates hold promise for further in vitro studies, advancing USP7-targeted therapies for cancer treatment.
泛素特异性蛋白酶7(USP7)是一种关键的去泛素化酶,参与肿瘤抑制、DNA修复和表观遗传调控。鉴于其在癌症进展中的关键作用,USP7已成为一个有吸引力的治疗靶点。在本研究中,我们采用了一种多层次的计算方法,整合基于配体的虚拟筛选、分子对接、分子动力学(MD)模拟、MM/GBSA结合自由能计算、二元定量构效关系(QSAR)建模和引导MD模拟,以识别和优化新型USP7抑制剂。通过基于SwissSimilarity的配体筛选,我们选择了与我们研究小组先前鉴定和验证的活性化合物结构相关的类似物,并进行了基于网格的对接模拟,优先考虑具有高结合亲和力的分子(对接分数< -8.0 kcal/mol)。排名靠前的候选物通过长期MD模拟和MM/GBSA自由能计算进行优化,以评估其结构稳定性以及与USP7关键残基的相互作用模式。二元QSAR分析进一步评估了这些化合物的抗癌潜力,筛选出具有高预测治疗活性的化合物(归一化治疗活性值> 0.5)。此外,为了研究强效化合物的选择性,我们对多个USP家族成员进行了交叉对接。最后,引导MD模拟提供了关于配体-蛋白质相互作用机械稳定性的见解。所鉴定的候选物有望进一步进行体外研究,推动针对USP7的癌症治疗方法的发展。