Zhou, Guangfeng Rusnac, Domnita-Valeria Park, Hahnbeom Canzani, Daniele Nguyen, Hai Minh Stewart, Lance Bush, Matthew F. Nguyen, Phuong Tran Wulff, Heike Yarov-Yarovoy, Vladimir Zheng, Ning Dimaio, Frank 2024-10-02T10:00:11Z 2024-10-02T10:00:11Z 2024-10-02 2024-09 https://pubs.kist.re.kr/handle/201004/150697 Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel NaV1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to NaV1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery. The authors in this work introduce RosettaVS, an AI-accelerated open-source drug discovery platform. They apply this tool to multi-billion compound libraries, where it was able to identify compounds that bind important targets KLHDC2 and NaV1.7. English Nature Publishing Group An artificial intelligence accelerated virtual screening platform for drug discovery Article 10.1038/s41467-024-52061-7 1 Nature Communications, v.15, no.1 Nature Communications 15 1 Y scie scopus 001307964900005 2-s2.0-85203419978 Multidisciplinary Sciences Science & Technology - Other Topics Article FAST INACTIVATION ACCURATE DOCKING POSE PREDICTION SMALL MOLECULES SODIUM-CHANNEL DOMAIN 4 PROTEIN BINDING GLIDE OPTIMIZATION