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J Chem Inf Model ; 64(13): 5151-5160, 2024 Jul 08.
Article in English | MEDLINE | ID: mdl-38907694

ABSTRACT

Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.


Subject(s)
Algorithms , Cryoelectron Microscopy , Molecular Dynamics Simulation , Cryoelectron Microscopy/methods , Protein Conformation
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