Accelerating reliable multiscale quantum refinement of protein–drug systems enabled by machine learning

Yan，Zeyin; Wei，Dacong; Li，Xin; Chung，Lung Wa

2024-12-01

10.1038/s41467-024-48453-4

Nature Communications   影响因子和分区

2041-1723

Biomacromolecule structures are essential for drug development and biocatalysis. Quantum refinement (QR) methods, which employ reliable quantum mechanics (QM) methods in crystallographic refinement, showed promise in improving the structural quality or even correcting the structure of biomacromolecules. However, vast computational costs and complex quantum mechanics/molecular mechanics (QM/MM) setups limit QR applications. Here we incorporate robust machine learning potentials (MLPs) in multiscale ONIOM(QM:MM) schemes to describe the core parts (e.g., drugs/inhibitors), replacing the expensive QM method. Additionally, two levels of MLPs are combined for the first time to overcome MLP limitations. Our unique MLPs+ONIOM-based QR methods achieve QM-level accuracy with significantly higher efficiency. Furthermore, our refinements provide computational evidence for the existence of bonded and nonbonded forms of the Food and Drug Administration (FDA)-approved drug nirmatrelvir in one SARS-CoV-2 main protease structure. This study highlights that powerful MLPs accelerate QRs for reliable protein–drug complexes, promote broader QR applications and provide more atomistic insights into drug development.

英语

第一 ; 通讯

2-s2.0-85193532885

Scopus

Shenzhen Grubbs Institute,Department of Chemistry and Guangdong Provincial Key Laboratory of Catalysis,Southern University of Science and Technology,Shenzhen,518055,China

Yan，Zeyin,Wei，Dacong,Li，Xin,等. Accelerating reliable multiscale quantum refinement of protein–drug systems enabled by machine learning[J]. Nature Communications,2024,15(1).

Yan，Zeyin,Wei，Dacong,Li，Xin,&Chung，Lung Wa.(2024).Accelerating reliable multiscale quantum refinement of protein–drug systems enabled by machine learning.Nature Communications,15(1).

Yan，Zeyin,et al."Accelerating reliable multiscale quantum refinement of protein–drug systems enabled by machine learning".Nature Communications 15.1(2024).