AWSEM-MD: Protein Structure Prediction Using Coarse-grained Physical Potentials and Bioinformatically Based Local Structure Biasing

By N. Schafer, Weihua Zheng, Cecilia Clementi, Peter G. Wolynes, G. Papoian. 2012

305 citations recorded by the source corpus.

The Associative memory, Water mediated, Structure and Energy Model (AWSEM) is a coarse-grained protein force field. AWSEM contains physically motivated terms, such as hydrogen bonding, as well as a bioinformatically based local structure biasing term, which efficiently takes into account many-body effects that are modulated by the local sequence. When combined with appropriate local or global alignments to choose memories, AWSEM can be used to perform de novo protein structure prediction. Herein we present structure prediction results for a particular choice of local sequence alignment method based on short residue sequences called fragments. We demonstrate the model’s structure prediction capabilities for three levels of global homology between the target sequence and those proteins used for local structure biasing, all of which assume that the structure of the target sequence is not known. When there are no homologs in the database of structures used for local structure biasing, AWSEM calculations produce structural predictions that are somewhat improved compared with prior works using related approaches. The inclusion of a small number of structures from homologous sequences improves structure prediction only marginally but when the fragment search is restricted to only homologous sequences, AWSEM can perform high resolution structure prediction and can be used for kinetics and dynamics studies.

Subfields: Ecology, Evolution, Behavior and Systematics, Plant Science, Soil Science

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Citations in the corpus

Coevolutionary information, protein folding landscapes, and the thermodynamics of natural selection (2014, methodology): “We also compared the two Hamiltonian values as a function of the fraction of native contacts, Q, for partially folded structures from a folding simulation of the repressor CI protein (PDB ID code 1R69) (32) sampled using AWSEM.”
The power of coarse graining in biomolecular simulations (2013, methodology): “It has been successfully used to predict protein structures both de novo and using homology models, 112 as well as dimeric protein interfaces.”