i3Drefine Software for Protein 3D Structure Refinement and Its Assessment in CASP10

Bhattacharya, Debswapna; Cheng, Jianlin
July 2013
PLoS ONE;Jul2013, Vol. 8 Issue 7, p1
Academic Journal
Protein structure refinement refers to the process of improving the qualities of protein structures during structure modeling processes to bring them closer to their native states. Structure refinement has been drawing increasing attention in the community-wide Critical Assessment of techniques for Protein Structure prediction (CASP) experiments since its addition in 8th CASP experiment. During the 9th and recently concluded 10th CASP experiments, a consistent growth in number of refinement targets and participating groups has been witnessed. Yet, protein structure refinement still remains a largely unsolved problem with majority of participating groups in CASP refinement category failed to consistently improve the quality of structures issued for refinement. In order to alleviate this need, we developed a completely automated and computationally efficient protein 3D structure refinement method, i3Drefine, based on an iterative and highly convergent energy minimization algorithm with a powerful all-atom composite physics and knowledge-based force fields and hydrogen bonding (HB) network optimization technique. In the recent community-wide blind experiment, CASP10, i3Drefine (as ‘MULTICOM-CONSTRUCT’) was ranked as the best method in the server section as per the official assessment of CASP10 experiment. Here we provide the community with free access to i3Drefine software and systematically analyse the performance of i3Drefine in strict blind mode on the refinement targets issued in CASP10 refinement category and compare with other state-of-the-art refinement methods participating in CASP10. Our analysis demonstrates that i3Drefine is only fully-automated server participating in CASP10 exhibiting consistent improvement over the initial structures in both global and local structural quality metrics. Executable version of i3Drefine is freely available at http://protein.rnet.missouri.edu/i3drefine/.


Related Articles

  • Serverification of Molecular Modeling Applications: The Rosetta Online Server That Includes Everyone (ROSIE) Lyskov, Sergey; Chou, Fang-Chieh; Conchúir, Shane Ó.; Der, Bryan S.; Drew, Kevin; Kuroda, Daisuke; Xu, Jianqing; Weitzner, Brian D.; Renfrew, P. Douglas; Sripakdeevong, Parin; Borgo, Benjamin; Havranek, James J.; Kuhlman, Brian; Kortemme, Tanja; Bonneau, Richard; Gray, Jeffrey J.; Das, Rhiju // PLoS ONE;May2013, Vol. 8 Issue 5, p1 

    The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and...

  • CGAP-Align: A High Performance DNA Short Read Alignment Tool. Chen, Yaoliang; Hong, Ji; Cui, Wanyun; Zaneveld, Jacques; Wang, Wei; Gibbs, Richard; Xiao, Yanghua; Chen, Rui // PLoS ONE;Apr2013, Vol. 8 Issue 4, p1 

    Background: Next generation sequencing platforms have greatly reduced sequencing costs, leading to the production of unprecedented amounts of sequence data. BWA is one of the most popular alignment tools due to its relatively high accuracy. However, mapping reads using BWA is still the most time...

  • Molecular Surface Representation Using 3D Zernike Descriptors for Protein Shape Comparison and Docking. Kihara, Daisuke; Sael, Lee; Chikhi, Rayan; Esquivel-Rodriguez, Juan // Current Protein & Peptide Science;Sep2011, Vol. 12 Issue 6, p520 

    The tertiary structures of proteins have been solved in an increasing pace in recent years. To capitalize the enormous efforts paid for accumulating the structure data, efficient and effective computational methods need to be developed for comparing, searching, and investigating interactions of...

  • Accelerated protein structure comparison using TM-score-GPU. Hung, Ling-Hong; Samudrala, Ram // Bioinformatics;Aug2012, Vol. 28 Issue 16, p2191 

    Motivation: Accurate comparisons of different protein structures play important roles in structural biology, structure prediction and functional annotation. The root-mean-square-deviation (RMSD) after optimal superposition is the predominant measure of similarity due to the ease and speed of...

  • PconsFold: improved contact predictions improve protein models. Michel, Mirco; Hayat, Sikander; Skwark, Marcin J.; Sander, Chris; Marks, Debora S.; Elofsson, Arne // Bioinformatics;Sep2014, Vol. 30 Issue 17, pi482 

    Motivation: Recently it has been shown that the quality of protein contact prediction from evolutionary information can be improved significantly if direct and indirect information is separated. Given sufficiently large protein families, the contact predictions contain sufficient information to...

  • Fast learning optimized prediction methodology (FLOPRED) for protein secondary structure prediction. Saraswathi, S.; Fernández-Martínez, J.; Kolinski, A.; Jernigan, R.; Kloczkowski, A. // Journal of Molecular Modeling;Sep2012, Vol. 18 Issue 9, p4275 

    Computational methods are rapidly gaining importance in the field of structural biology, mostly due to the explosive progress in genome sequencing projects and the large disparity between the number of sequences and the number of structures. There has been an exponential growth in the number of...

  • Efficient Sampling in Fragment-Based Protein Structure Prediction Using an Estimation of Distribution Algorithm. Simoncini, David; Zhang, Kam Y. J. // PLoS ONE;Jul2013, Vol. 8 Issue 7, p1 

    Fragment assembly is a powerful method of protein structure prediction that builds protein models from a pool of candidate fragments taken from known structures. Stochastic sampling is subsequently used to refine the models. The structures are first represented as coarse-grained models and then...

  • Machine Learning Algorithms for Predicting Protein Folding Rates and Stability of Mutant Proteins: Comparison with Statistical Methods. Gromiha, M. Michael; Huang, Liang-Tsung // Current Protein & Peptide Science;Sep2011, Vol. 12 Issue 6, p490 

    Machine learning algorithms have wide range of applications in bioinformatics and computational biology such as prediction of protein secondary structures, solvent accessibility, binding site residues in protein complexes, protein folding rates, stability of mutant proteins, and discrimination...

  • Insights into the Evolution of the CSP Gene Family through the Integration of Evolutionary Analysis and Comparative Protein Modeling Kulmuni, Jonna; Havukainen, Heli // PLoS ONE;May2013, Vol. 8 Issue 5, p1 

    Insect chemical communication and chemosensory systems rely on proteins coded by several gene families. Here, we have combined protein modeling with evolutionary analysis in order to study the evolution and structure of chemosensory proteins (CSPs) within arthropods and, more specifically, in...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics