Improving geometric validation metrics and ensuring consistency with experimental data through TrioSA: an NMR re？nement protocol = 실험 데이터와 일관성을 보장하고 TrioSA를 통한 NMR 정제 프로토콜을 통해 기하학적 검증 지표를 개선하는 방법

Abstract

Protein model re？nement a the crucial step in improving the quality of a predicted protein model. This study presents an NMR re？nement protocol called TrioSA (torsion-angle and implicit-solvation-optimized simulated annealing) that improves the accuracy of backbone/sidechain conformations and the overall structural quality of proteins. TrioSA was applied to a subset of 3752 solution NMR protein structures accompanied by experimental NMR data: distance and dihedral angle restraints. We compared the initial NMR structures with the TrioSA-re？ned structures and found signi？cant improvements in structural quality. In particular, we observed a reduction in both the maximum and number of NOE (nuclear Overhauser effect) violations, indicating better agreement with experimental NMR data. TrioSA improved geometric validation metrics of NMR protein structure, including backbone accuracy and the secondary structure ratio. We evaluated the contribution of each re？nement element and found that the torsional angle potential played a signi？cant role in improving the geometric validation metrics. In addition, we investigated protein-ligand docking to determine if TrioSA can improve biological outcomes. TrioSA structures exhibited better binding prediction compared to the initial NMR structures. This study suggests that further development and research in computational re？nement methods could improve biomolecular NMR structural determination.