Ilatovskiy Andrey V, Abagyan Ruben, Kufareva Irina
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA, 92093 ; Division of Molecular and Radiation Biophysics, Konstantinov Petersburg Nuclear Physics Institute, NRC Kurchatov Institute, Gatchina, Russia, 188300.
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA, 92093.
Int J Quantum Chem. 2013 Jun 15;113(12):1669-1675. doi: 10.1002/qua.24400.
The rapid growth of the available crystallographic information about proteins and binding pockets creates remarkable opportunities for enriching the drug research pipelines with computational prediction of novel protein-ligand interactions. While quantum mechanical approaches are known to provide unprecedented accuracy in structure-based binding energy calculations, they are limited to only small systems of dozens of atoms. In the structural chemogenomics era, it is critical that new approaches are developed that enable application of QM methodologies to non-covalent interactions in systems as large as protein-ligand complexes and conformational ensembles. This perspective highlights recent advances towards bridging the gap between high accuracy and high volume computations in drug research.
关于蛋白质和结合口袋的现有晶体学信息的快速增长,为通过计算预测新型蛋白质-配体相互作用来丰富药物研究流程创造了显著机遇。虽然量子力学方法在基于结构的结合能计算中具有前所未有的准确性,但它们仅限于由几十个原子组成的小系统。在结构化学基因组学时代,开发新方法以使量子力学方法能够应用于蛋白质-配体复合物和构象集合等大系统中的非共价相互作用至关重要。本文观点突出了在药物研究中弥合高精度和高容量计算之间差距的最新进展。