A New Prediction Protein Structure Method Based on Genetic Algorithm and Coarse-Grained Protein Model

Author(s):  
Cai-Yun Wang ◽  
Hao-Dong Zhu ◽  
Le-Cai Cai
Genes ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 601 ◽  
Author(s):  
Eshel Faraggi ◽  
Pawel Krupa ◽  
Magdalena Mozolewska ◽  
Adam Liwo ◽  
Andrzej Kloczkowski

Ranking protein structure models is an elusive problem in bioinformatics. These models are evaluated on both the degree of similarity to the native structure and the folding pathway. Here, we simulated the use of the coarse-grained UNited RESidue (UNRES) force field as a tool to choose the best protein structure models for a given protein sequence among a pool of candidate models, using server data from the CASP11 experiment. Because the original UNRES was optimized for Molecular Dynamics simulations, we reoptimized UNRES using a deep feed-forward neural network, and we show that introducing additional descriptive features can produce better results. Overall, we found that the reoptimized UNRES performs better in selecting the best structures and tracking protein unwinding from its native state. We also found a relatively poor correlation between UNRES values and the model’s Template Modeling Score (TMS). This is remedied by reoptimization. We discuss some cases where our reoptimization procedure is useful. The reoptimized version of UNRES (OUNRES) is available at http://mamiris.com and http://www.unres.pl.


2003 ◽  
Vol 53 (S6) ◽  
pp. 424-429 ◽  
Author(s):  
Bruno Contreras-Moreira ◽  
Paul W. Fitzjohn ◽  
Marc Offman ◽  
Graham R. Smith ◽  
Paul A. Bates

2019 ◽  
Vol 79 ◽  
pp. 6-15 ◽  
Author(s):  
Md. Lisul Islam ◽  
Swakkhar Shatabda ◽  
Mahmood A. Rashid ◽  
M.G.M. Khan ◽  
M. Sohel Rahman

2019 ◽  
Vol 47 (W1) ◽  
pp. W471-W476 ◽  
Author(s):  
Rasim Murat Aydınkal ◽  
Onur Serçinoğlu ◽  
Pemra Ozbek

AbstractProSNEx (Protein Structure Network Explorer) is a web service for construction and analysis of Protein Structure Networks (PSNs) alongside amino acid flexibility, sequence conservation and annotation features. ProSNEx constructs a PSN by adding nodes to represent residues and edges between these nodes using user-specified interaction distance cutoffs for either carbon-alpha, carbon-beta or atom-pair contact networks. Different types of weighted networks can also be constructed by using either (i) the residue-residue interaction energies in the format returned by gRINN, resulting in a Protein Energy Network (PEN); (ii) the dynamical cross correlations from a coarse-grained Normal Mode Analysis (NMA) of the protein structure; (iii) interaction strength. Upon construction of the network, common network metrics (such as node centralities) as well as shortest paths between nodes and k-cliques are calculated. Moreover, additional features of each residue in the form of conservation scores and mutation/natural variant information are included in the analysis. By this way, tool offers an enhanced and direct comparison of network-based residue metrics with other types of biological information. ProSNEx is free and open to all users without login requirement at http://prosnex-tool.com.


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