Protein-protein interactions are integral to virtually all biological pathways. Many important interactions occur in weak, transient complexes that will not be amenable to direct experimental analysis, even when both proteins can be isolated and their structures determined. Thus, it is important to develop computational docking methods which, starting from the structures of component proteins, can determine the structure of their complexes. We have developed a multistage docking algorithm that provided the best results in the latest rounds of the CAPRI (Critical Assessment of Predicted Interactions) worldwide docking experiment. In addition, our docking server ClusPro was the best among automated servers. Although the CAPRI results demonstrate progress, a number of major problems remain unsolved. First, docking homology models is a challenge and all methods used in CAPRI performed poorly for such targets. Docking unbound structures is also difficult if binding is accompanied by substantial backbone conformational change. Second, it is not clear whether a model generated by docking represents a specific and stable complex. Third, the interface may include regions that are disordered in the separate proteins, challenging docking methods. We address these problems by pursuing three specific aims. First, we develop a novel algorithm for docking homology models and proteins with substantial backbone flexibility. The method is based on the hypothesis that the interface in complexes is sequentially and structurally more conserved than the rest of the proteins. Since such regions are frequently sufficient for recognition, identification and correct docking of the key segments can yield near-native docked structures. For homology models this implies that one can dock the regions that can be reliably modeled, and then expand the models by adding back the removed parts using the docked structures as constraints. The problem of docking """"""""difficult cases"""""""" with substantial backbone conformational change can also be addressed by identifying and docking the structurally most conserved regions. Once clusters of the docked rigid fragments are obtained, the models are expanded by rebuilding the more flexible parts. Second, we use a two-step approach to examine the stability of protein complexes, first by removing small and hence unlikely clusters of low energy docked structures, and then by calculating dissociation rates by stochastic roadmap simulation. The method will be validated on a benchmark set that includes models of real protein complexes and decoys generated by docking non-interacting protein pairs. The approach will also be used to determine whether complex structures deposited to the PDB are biologically relevant. Third, we consider the problem of determining the structure of flexible loops and/or disordered regions when they become parts of a protein- protein interface. Rather than attempting to predict and to dock the most likely conformation of the flexible fragment, we build their bound structure directly into binding hot spots of the partner protein. Flexible peptide docking methods will be used to expand the docked fragments by adding further residues.

Public Health Relevance

Many biologically important interactions occur in weak, transient complexes that are not amenable to direct experimental analysis, and hence it is important to develop computational docking methods that, starting from the structures of unbound proteins, can determine the structure of their complexes. The goal of this proposal is to solve some of the most important outstanding problems of protein docking, i.e., docking homology models and flexible proteins, and predicting the stability of complexes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM061867-12
Application #
8439227
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
2000-09-01
Project End
2017-02-28
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
12
Fiscal Year
2013
Total Cost
$284,681
Indirect Cost
$104,681
Name
Boston University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215
Mamonov, Artem B; Moghadasi, Mohammad; Mirzaei, Hanieh et al. (2016) Focused grid-based resampling for protein docking and mapping. J Comput Chem 37:961-70
Vajda, Sandor; Yueh, Christine; Beglov, Dmitri et al. (2016) New Additions to the ClusPro Server Motivated by CAPRI. Proteins :
Im, Wonpil; Liang, Jie; Olson, Arthur et al. (2016) Challenges in structural approaches to cell modeling. J Mol Biol 428:2943-64
Lukose, Vinita; Luo, Lingqi; Kozakov, Dima et al. (2015) Conservation and Covariance in Small Bacterial Phosphoglycosyltransferases Identify the Functional Catalytic Core. Biochemistry 54:7326-34
Xia, Bing; Mamonov, Artem; Leysen, Seppe et al. (2015) Accounting for observed small angle X-ray scattering profile in the protein-protein docking server ClusPro. J Comput Chem 36:1568-72
Mirzaei, Hanieh; Zarbafian, Shahrooz; Villar, Elizabeth et al. (2015) Energy Minimization on Manifolds for Docking Flexible Molecules. J Chem Theory Comput 11:1063-76
Moghadasi, Mohammad; Mirzaei, Hanieh; Mamonov, Artem et al. (2015) The impact of side-chain packing on protein docking refinement. J Chem Inf Model 55:872-81
Bohnuud, Tanggis; Kozakov, Dima; Vajda, Sandor (2014) Evidence of conformational selection driving the formation of ligand binding sites in protein-protein interfaces. PLoS Comput Biol 10:e1003872
Yakubovskaya, Elena; Guja, Kip E; Eng, Edward T et al. (2014) Organization of the human mitochondrial transcription initiation complex. Nucleic Acids Res 42:4100-12
Mottarella, Scott E; Beglov, Dmitri; Beglova, Natalia et al. (2014) Docking server for the identification of heparin binding sites on proteins. J Chem Inf Model 54:2068-78

Showing the most recent 10 out of 60 publications