Protein science : a publication of the Protein Society · 2023
Large library docking for novel SARS-CoV-2 main protease non-covalent and covalent inhibitors.
СтатьяПоддержка NIH: внешняя программаПоддержка правительства СШАПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Fink Elissa A, Bardine Conner, Gahbauer Stefan, Singh Isha, Detomasi Tyler C, White Kris, Gu Shuo, Wan Xiaobo, Chen Jun, Ary Beatrice, Glenn Isabella, O'Connell Joseph, O'Donnell Henry, Fajtová Pavla, Lyu Jiankun, Vigneron Seth, Young Nicholas J, Kondratov Ivan S, Alisoltani Arghavan, Simons Lacy M, Lorenzo-Redondo Ramon, Ozer Egon A, Hultquist Judd F, O'Donoghue Anthony J, Moroz Yurii S, Taunton Jack, Renslo Adam R, Irwin John J, García-Sastre Adolfo, Shoichet Brian K, Craik Charles S
Аннотация
Antiviral therapeutics to treat SARS-CoV-2 are needed to diminish the morbidity of the ongoing COVID-19 pandemic. A well-precedented drug target is the main viral protease (MPro ), which is targeted by an approved drug and by several investigational drugs. Emerging viral resistance has made new inhibitor chemotypes more pressing. Adopting a structure-based approach, we docked 1.2 billion non-covalent lead-like molecules and a new library of 6.5 million electrophiles against the enzyme structure. From these, 29 non-covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC50 of 29 and 20 μM, respectively. Several series were optimized, resulting in low micromolar inhibitors. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. While the new chemotypes may aid further optimization of MPro inhibitors for SARS-CoV-2, the modest success rate also reveals weaknesses in our approach for challenging targets like MPro versus other targets where it has been more successful, and versus other structure-based techniques against MPro itself.