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

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.

Protein structure prediction: making AWSEM AWSEM-ER by adding evolutionary restraints.

Protein sequences have evolved to fold into functional structures, resulting in families of diverse protein sequences that all share the same overall fold. One can harness protein family sequence data to infer likely contacts between pairs of residues. In the current study, we combine this kind of inference from coevolutionary information with a coarse-grained protein force field ordinarily used with single sequence input, the Associative memory, Water mediated, Structure and Energy Model (AWSEM), to achieve improved structure prediction.

Water Mediated Interactions and the Protein Folding Phase Diagram in the Temperature-Pressure Plane.

The temperature-pressure behavior of two proteins, ubiquitin and λ-repressor, is explored using a realistically coarse-grained physicochemical model, the associative memory, water mediated, structure and energy model (AWSEM). The phase diagram across the temperature-pressure plane is obtained by perturbing the water mediated interactions in the Hamiltonian systematically. The phase diagrams calculated with direct simulations along with an extended bridge sampling estimator show the main features found experimentally, including both cold- and pressure-denaturation.