CACHE Challenge #1: Docking with GNINA Is All You Need

作者：Ian Dunn, Somayeh Pirhadi, Yao Wang, Smmrithi Ravindran, Carter Concepcion, David Ryan Koes · 发表于：Journal of Chemical Information and Modeling · 年份：2024 · DOI：10.1021/acs.jcim.4c01429 · 被引用次数：19 · 研究领域：Computational Drug Discovery Methods、Protein Degradation and Inhibitors、Statistical Methods in Clinical Trials

We describe our winning submission to the first Critical Assessment of Computational Hit-Finding Experiments (CACHE) challenge. In this challenge, 23 participants employed a diverse array of structure-based methods to identify hits to a target with no known ligands. We utilized two methods, pharmacophore search and molecular docking, to identify our initial hit list and compounds for the hit expansion phase. Unlike many other participants, we limited ourselves to using docking scores in identifying and ranking hits. Our resulting best hit series tied for first place when evaluated by a panel of expert judges. Here, we report our top-performing open-source workflow and results.