Systematic Validation of Protein Force Fields against Experimental Data

By K. Lindorff‐Larsen, Paul Maragakis, Stefano Piana, Michael P. Eastwood, Ron O. Dror, David E. Shaw. PLoS ONE, 2012

659 citations recorded by the source corpus.

Molecular dynamics simulations provide a vehicle for capturing the structures, motions, and interactions of biological macromolecules in full atomic detail. The accuracy of such simulations, however, is critically dependent on the force field—the mathematical model used to approximate the atomic-level forces acting on the simulated molecular system. Here we present a systematic and extensive evaluation of eight different protein force fields based on comparisons of experimental data with molecular dynamics simulations that reach a previously inaccessible timescale. First, through extensive comparisons with experimental NMR data, we examined the force fields' abilities to describe the structure and fluctuations of folded proteins. Second, we quantified potential biases towards different secondary structure types by comparing experimental and simulation data for small peptides that preferentially populate either helical or sheet-like structures. Third, we tested the force fields' abilities to fold two small proteins—one α-helical, the other with β-sheet structure. The results suggest that force fields have improved over time, and that the most recent versions, while not perfect, provide an accurate description of many structural and dynamical properties of proteins.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b2a9e19732bef38a27a7c5a911d48381a2fcb939

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Citations in the corpus

Protein structure prediction from sequence variation (2012, methodology): “…refinement meth-ods resulting in more accurate atomic coordinates (for example, using the molecular dynamics and refinement software Cystallography and NMR System (CNS) 42 , Rosetta 43 , the deformable elastic network (DEN) approach 44 or the Anton massively parallel special purpose computer 45 ).”
Structure of the Bacterial Cytoskeleton Protein Bactofilin by NMR Chemical Shifts and Sequence Variation. (2016, positive): “We expect that the improved accuracy afforded by better methods for determining molecular energy functions (45) and predicting contacts (18), as well as developments in techniques such as ssNMR(46),will expand the scope of our approach to other proteins for which classical structure determination ha”
Computational modeling of membrane proteins (2014, methodology): “227 The most commonly used are AMBER179 and OPLS,180 which have been used extensively for drug docking, and CHARMM.”
Developing a molecular dynamics force field for both folded and disordered protein states (2018, result): “Consistent with previous studies (2, 8), all force fields considered here considerably underestimated the cooperativity of both hairpin and helix formation.”