Protein Structure Prediction in CASP13 Using AWSEM-Suite

Abstract

Recently several techniques have emerged that significantly enhance the quality of predictions of protein tertiary structures. In this study, we describe the performance of AWSEM-Suite, an algorithm that incorporates template-based modeling and coevolutionary restraints with a realistic coarse-grained force field, AWSEM. With its roots in neural networks, AWSEM contains both physical and bioinformatical energies that have been optimized using energy landscape theory. AWSEM-Suite participated in CASP13 as a server predictor and generated reliable predictions for most targets. AWSEM-Suite ranked eighth in both the free-modeling category and the hard-to-model category and in one case provided the best submitted prediction. Here we critically discuss the prediction performance of AWSEM-Suite using several examples from different categories in CASP13. Structure prediction tests on these selected targets, two of them being hard-to-model targets, show that AWSEM-Suite can achieve high-resolution structure prediction after incorporating both template guidances and coevolutionary restraints even when homology is weak. For targets with reliable templates (template-easy category), introducing coevolutionary restraints sometimes damages the overall quality of the predictions. Free energy profile analyses demonstrate, however, that the incorporations of both of these evolutionarily informed terms effectively increase the funneling of the landscape toward native-like structures while still allowing sufficient flexibility to correct for discrepancies between the correct target structure and the provided guidance. In contrast to other predictors that are exclusively oriented toward structure prediction, the connection of AWSEM-Suite to a statistical mechanical basis and affiliated molecular dynamics and importance sampling simulations makes it suitable for functional explorations.

OpenAWSEM with Open3SPN2: a fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

“…ij (17) where N is the total number of residues, i and j are sequence positions, r ij is the distance between the CA of residue i and the CA of residue j. r N ij is the distance between CA of residue i and CA of residue j in native structure, σ ij = (1 + |i − j| 0.15 )Å. For Q water , N is the number of residues outside of the membrane, and the sum is taken over all of those residues.…”

“…It has also performed quite well in recent CASP competitions. [17] Nucleic acids are important partners with proteins in biology and it is desirable to study their dynamics with compatible computational tools. 3SPN.2 is a Coarse Grained DNA model developed by the de Pablo group that models the DNA molecule using 3-sites-per-nucleotide: a particle for the phosphate group, a particle for the sugar and a particle for the nucleobase [18].…”

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules

“…Given the additional computational gain provided by its discontinuous potentials, PRIME was instead extensively exploited to investigate the behavior of large-scale systems, especially in the context of aggregation of fibrils in presence or absence of fibrillation seeds or inhibitors ( Nguyen and Hall, 2004 ; Cheon et al, 2011 ; Wang et al, 2017 ; Wang and Hall, 2018 ). In addition to protein folding ( Jin et al, 2020 ), applications of AWSEM include the investigation of protein-protein association ( Zheng et al, 2012 ) and fibrillar aggregation processes ( Zheng et al, 2016 ; Chen et al, 2020 ), as well as the analysis of the static and dynamic behavior of intrinsically disordered proteins ( Wu et al, 2018 ; Lin et al, 2019 ). The incorporation of an implicit membrane potential in AWSEM enabled it to provide insight on the folding behavior of transmembrane proteins ( Lu et al, 2018 ) and protein assemblies ( Truong et al, 2015 ).…”

Exploring the folding energy landscapes of heme proteins using a hybrid AWSEM-heme model

“…AWSEM has already successfully surveyed many aspects of protein folding and function. It has been used not only for protein structure prediction [ 31 ], but also to study aggregation [ 32 ], and protein-DNA binding [ 33 ], and has been used for very large assemblies [ 34 ]. In these studies, coarse-grained models have already been used to explore the mechanism of heme protein folding.…”