skip to main content


Title: Modeling CAPRI targets 110‐120 by template‐based and free docking using contact potential and combined scoring function
Abstract

The paper presents analysis of our template‐based and free docking predictions in the joint CASP12/CAPRI37 round. A new scoring function for template‐based docking was developed, benchmarked on the Dockgroundresource, and applied to the targets. The results showed that the function successfully discriminates the incorrect docking predictions. In correctly predicted targets, the scoring function was complemented by other considerations, such as consistency of the oligomeric states among templates, similarity of the biological functions, biological interface relevance, etc. The scoring function still does not distinguish well biological from crystal packing interfaces, and needs further development for the docking of bundles of α‐helices. In the case of the trimeric targets, sequence‐based methods did not find common templates, despite similarity of the structures, suggesting complementary use of structure‐ and sequence‐based alignments in comparative docking. The results showed that if a good docking template is found, an accurate model of the interface can be built even from largely inaccurate models of individual subunits. Free docking however is very sensitive to the quality of the individual models. However, our newly developed contact potential detected approximate locations of the binding sites.

 
more » « less
NSF-PAR ID:
10042858
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Proteins: Structure, Function, and Bioinformatics
Volume:
86
Issue:
S1
ISSN:
0887-3585
Page Range / eLocation ID:
p. 302-310
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Comparative docking is based on experimentally determined structures of protein‐protein complexes (templates), following the paradigm that proteins with similar sequences and/or structures form similar complexes. Modeling utilizing structure similarity of target monomers to template complexes significantly expands structural coverage of the interactome. Template‐based docking by structure alignment can be performed for the entire structures or by aligning targets to the bound interfaces of the experimentally determined complexes. Systematic benchmarking of docking protocols based on full and interface structure alignment showed that both protocols perform similarly, with top 1 docking success rate 26%. However, in terms of the models' quality, the interface‐based docking performed marginally better. The interface‐based docking is preferable when one would suspect a significant conformational change in the full protein structure upon binding, for example, a rearrangement of the domains in multidomain proteins. Importantly, if the same structure is selected as the top template by both full and interface alignment, the docking success rate increases 2‐fold for both top 1 and top 10 predictions. Matching structural annotations of the target and template proteins for template detection, as a computationally less expensive alternative to structural alignment, did not improve the docking performance. Sophisticated remote sequence homology detection added templates to the pool of those identified by structure‐based alignment, suggesting that for practical docking, the combination of the structure alignment protocols and the remote sequence homology detection may be useful in order to avoid potential flaws in generation of the structural templates library.

     
    more » « less
  2. Abstract

    As a participant in the joint CASP13‐CAPRI46 assessment, the ClusPro server debuted its new template‐based modeling functionality. The addition of this feature, called ClusPro TBM, was motivated by the previous CASP‐CAPRI assessments and by the proven ability of template‐based methods to produce higher‐quality models, provided templates are available. In prior assessments, ClusPro submissions consisted of models that were produced via free docking of pre‐generated homology models. This method was successful in terms of the number of acceptable predictions across targets; however, analysis of results showed that purely template‐based methods produced a substantially higher number of medium‐quality models for targets for which there were good templates available. The addition of template‐based modeling has expanded ClusPro's ability to produce higher accuracy predictions, primarily for homomeric but also for some heteromeric targets. Here we review the newest additions to the ClusPro web server and discuss examples of CASP‐CAPRI targets that continue to drive further development. We also describe ongoing work not yet implemented in the server. This includes the development of methods to improve template‐based models and the use of co‐evolutionary information for data‐assisted free docking.

     
    more » « less
  3. Abstract

    Structural characterization of protein‐protein interactions is essential for our ability to study life processes at the molecular level. Computational modeling of protein complexes (protein docking) is important as the source of their structure and as a way to understand the principles of protein interaction. Rapidly evolving comparative docking approaches utilize target/template similarity metrics, which are often based on the protein structure. Although the structural similarity, generally, yields good performance, other characteristics of the interacting proteins (eg, function, biological process, and localization) may improve the prediction quality, especially in the case of weak target/template structural similarity. For the ranking of a pool of models for each target, we tested scoring functions that quantify similarity of Gene Ontology (GO) terms assigned to target and template proteins in three ontology domains—biological process, molecular function, and cellular component (GO‐score). The scoring functions were tested in docking of bound, unbound, and modeled proteins. The results indicate that the combined structural and GO‐terms functions improve the scoring, especially in the twilight zone of structural similarity, typical for protein models of limited accuracy.

     
    more » « less
  4. ABSTRACT

    Protein‐protein interactions are either through direct contacts between two binding partners or mediated by structural waters. Both direct contacts and water‐mediated interactions are crucial to the formation of a protein‐protein complex. During the recent CAPRI rounds, a novel parallel searching strategy for predicting water‐mediated interactions is introduced into our protein‐protein docking method, MDockPP. Briefly, a FFT‐based docking algorithm is employed in generating putative binding modes, and an iteratively derived statistical potential‐based scoring function, ITScorePP, in conjunction with biological information is used to assess and rank the binding modes. Up to 10 binding modes are selected as the initial protein‐protein complex structures for MD simulations in explicit solvent. Water molecules near the interface are clustered based on the snapshots extracted from independent equilibrated trajectories. Then, protein‐ligand docking is employed for a parallel search for water molecules near the protein‐protein interface. The water molecules generated by ligand docking and the clustered water molecules generated by MD simulations are merged, referred to as the predicted structural water molecules. Here, we report the performance of this protocol for CAPRI rounds 28–29 and 31–35 containing 20 valid docking targets and 11 scoring targets. In the docking experiments, we predicted correct binding modes for nine targets, including one high‐accuracy, two medium‐accuracy, and six acceptable predictions. Regarding the two targets for the prediction of water‐mediated interactions, we achieved models ranked as “excellent” in accordance with the CAPRI evaluation criteria; one of these two targets is considered as a difficult target for structural water prediction. Proteins 2017; 85:424–434. © 2016 Wiley Periodicals, Inc.

     
    more » « less
  5. Abstract

    We report the performance of the protein docking prediction pipeline of our group and the results for Critical Assessment of Prediction of Interactions (CAPRI) rounds 38‐46. The pipeline integrates programs developed in our group as well as other existing scoring functions. The core of the pipeline is the LZerD protein‐protein docking algorithm. If templates of the target complex are not found in PDB, the first step of our docking prediction pipeline is to run LZerD for a query protein pair. Meanwhile, in the case of human group prediction, we survey the literature to find information that can guide the modeling, such as protein‐protein interface information. In addition to any literature information and binding residue prediction, generated docking decoys were selected by a rank aggregation of statistical scoring functions. The top 10 decoys were relaxed by a short molecular dynamics simulation before submission to remove atom clashes and improve side‐chain conformations. In these CAPRI rounds, our group, particularly the LZerD server, showed robust performance. On the other hand, there are failed cases where some other groups were successful. To understand weaknesses of our pipeline, we analyzed sources of errors for failed targets. Since we noted that structure refinement is a step that needs improvement, we newly performed a comparative study of several refinement approaches. Finally, we show several examples that illustrate successful and unsuccessful cases by our group.

     
    more » « less