Shen Zheyuan, Chen Roufen, Gao Jian, Chi Xinglong, Zhang Qingnan, Bian Qingyu, Zhou Binbin, Che Jinxin, Dai Haibin, Dong Xiaowu
College of Pharmaceutical Sciences, Zhejiang University, HangzhouZhejiang310058, China.
Key Laboratory of Neuropsychiatric Drug Research of Zhejiang Province, School of Pharmacy, Hangzhou Medical College, HangzhouZhejiang310058, China.
J Chem Inf Model. 2025 Jan 13;65(1):7-14. doi: 10.1021/acs.jcim.4c01818. Epub 2024 Dec 18.
Structure-based virtual screening (SBVS) plays an indispensable role in the early phases of drug discovery, utilizing computational docking techniques to predict interactions between molecules and biological targets. During the SBVS process, selecting appropriate target structures and screening algorithms is crucial, as these choices significantly shape the outcomes. Typically, such selections require researchers to be proficient with multiple algorithms and familiar with evaluation and analysis processes, complicating their tasks. These algorithms' lack of graphical user interfaces (GUIs) further complicates it. To address these challenges, we introduced EvaluationMaster, the first GUI tool designed specifically to streamline and standardize the evaluation and decision-making processes in SBVS. It supports four docking algorithms' evaluation under multiple target structures and offers a comprehensive platform that manages the entire workflow─including the downloading of molecules, construction of decoy datasets, prediction of protein pockets, batch docking, and extensive data analysis. By automating complex evaluation tasks and providing clear visualizations of analysis results, EvaluationMaster significantly reduces the learning curve for researchers and boosts the efficiency of evaluations, potentially improving SBVS hit rates and accelerating the discovery and development of new therapeutic agents.
基于结构的虚拟筛选（SBVS）在药物发现的早期阶段发挥着不可或缺的作用，它利用计算对接技术来预测分子与生物靶点之间的相互作用。在SBVS过程中，选择合适的靶点结构和筛选算法至关重要，因为这些选择会显著影响结果。通常，这样的选择要求研究人员精通多种算法，并熟悉评估和分析过程，这使得他们的任务变得复杂。这些算法缺乏图形用户界面（GUI），进一步加剧了这一复杂性。为应对这些挑战，我们推出了EvaluationMaster，这是首个专门设计用于简化和规范SBVS评估及决策过程的GUI工具。它支持在多种靶点结构下对四种对接算法进行评估，并提供一个管理整个工作流程的综合平台，包括分子下载、诱饵数据集构建、蛋白质口袋预测、批量对接以及广泛的数据分析。通过自动化复杂的评估任务并提供清晰的分析结果可视化，EvaluationMaster显著降低了研究人员的学习曲线，提高了评估效率，有可能提高SBVS的命中率，并加速新治疗药物的发现和开发。
