AWSEM-Suite: a protein structure prediction server based on template- guided, coevolutionary-enhanced optimized folding landscapes

SK Jin and VG Contessoto and MC Chen and NP Schafer and W Lu and X Chen and C Bueno and A Hajitaheri and BJ Sirovetz and A Davtyan and GA Papoian and MY Tsai and PG Wolynes, NUCLEIC ACIDS RESEARCH, 48, W25-W30 (2020).

DOI: 10.1093/nar/gkaa356

The accurate and reliable prediction of the 3D structures of proteins and their assemblies remains difficult even though the number of solved structures soars and prediction techniques improve. In this study, a free and open access web server, AWSEM-Suite, whose goal is to predict monomeric protein tertiary structures from sequence is described. The model underlying the server's predictions is a coarse-grained protein force field which has its roots in neural network ideas that has been optimized using energy landscape theory. Employing physically motivated potentials and knowledge-based local structure biasing terms, the addition of homologous template and co-evolutionary restraints to AWSEM- Suite greatly improves the predictive power of pure AWSEM structure prediction. From the independent evaluation metrics released in the CASP13 experiment, AWSEM-Suite proves to be a reasonably accurate algorithm for free modeling, standing at the eighth position in the free modeling category of CASP13. The AWSEM-Suite server also features a front end with a user-friendly interface. The AWSEM-Suite server is a powerful tool for predicting monomeric protein tertiary structures that is most useful when a suitable structure template is not available.

Return to Publications page