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Maximum Entropy Optimized Force Field for Intrinsically Disordered Proteins
journal contribution
posted on 2019-12-12, 22:44 authored by Andrew
P. Latham, Bin ZhangIntrinsically disordered proteins (IDPs) constitute a
significant
fraction of eukaryotic proteomes. High-resolution characterization
of IDP conformational ensembles can help elucidate their roles in
a wide range of biological processes but remains challenging both
experimentally and computationally. Here, we present a generic algorithm
to improve the accuracy of coarse-grained IDP models using a diverse
set of experimental measurements. It combines maximum entropy optimization
and least-squares regression to systematically adjust model parameters
and improve the agreement between simulation and experiment. We successfully
applied the algorithm to derive a transferable force field, which
we term the maximum entropy optimized force field (MOFF), for de novo
prediction of IDP structures. Statistical analysis of force field
parameters reveals features of amino acid interactions not captured
by potentials designed to work well for folded proteins. We anticipate
its combination of efficiency and accuracy will make MOFF useful for
studying the phase separation of IDPs, which drives the formation
of various biological compartments.
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force field parametersStatistical analysisproteincoarse-grained IDP modelsphase separationMOFFentropy optimized force fieldaccuracyHigh-resolution characterizationMaximum Entropy Optimized Force Fieldleast-squares regressionacid interactionseukaryotic proteomesentropy optimizationalgorithmforce fieldmodel parametersIDP structuresIntrinsically Disordered Proteins Intrinsically
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