Guiding Protein Docking With Geometric and Evolutionary Information

Hashmi, Irina; Akbal-Delibas, Bahar; Haspel, Nurit; Shehu, Amarda

doi:10.1142/s0219720012420085

Cited by 12 publications

(18 citation statements)

References 36 publications

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“…In order to test our multimeric refinement method, we used docked dimeric structures provided by Shehu et al [24] with the following PDB IDs: 1BDJ, 1C1Y, 1CSE, 1DS6, 1OHZ, 1TX4 and 1WQ1. In addition to these dimers, we produced multimeric input structures by running the Multi-LZerD multimeric docking program without refinement [11] for protein complexes with the following PDB IDs: 1I3O, 1JYO, 1LOG, 1QGW, 1VCB, 1W88, 1WWW, 2BBK, 2PRG and 6RLX.…”

Section: Methodsmentioning

confidence: 99%

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A conservation and biophysics guided stochastic approach to refining docked multimeric proteins

Akbal-Delibas

Haspel

2013

BMC Structural Biology

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BackgroundWe introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units.ResultsOur results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures.ConclusionsEvolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

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Section: Methodsmentioning

confidence: 99%

“…We recently developed a docking refinement method that uses a scoring function based on evolutionary conservation [23,24], in addition to the usual VdW energy term. It employs a novel Evolutionary Trace (ET)-based [25,26] conservation scoring function.…”

Section: Introductionmentioning

confidence: 99%

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins

Akbal-Delibas

Haspel

2013

BMC Structural Biology

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“…Our results suggest that HopDock is efficient, competitive, and samples many near-native configurations. These characteristics make it a promising search algorithm to use in the context of docking protocols, particularly if more powerful energy functions are used and if the generated decoys are further selected and refined at greater detail and with more computational resources [27,28]. …”

Section: Introductionmentioning

confidence: 99%

HopDock: a probabilistic search algorithm for decoy sampling in protein-protein docking

Hashmi

Shehu

2013

Proteome Sci

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BackgroundElucidating the three-dimensional structure of a higher-order molecular assembly formed by interacting molecular units, a problem commonly known as docking, is central to unraveling the molecular basis of cellular activities. Though protein assemblies are ubiquitous in the cell, it is currently challenging to predict the native structure of a protein assembly in silico.MethodsThis work proposes HopDock, a novel search algorithm for protein-protein docking. HopDock efficiently obtains an ensemble of low-energy dimeric configurations, also known as decoys, that can be effectively used by ab-initio docking protocols. HopDock is based on the Basin Hopping (BH) framework which perturbs the structure of a dimeric configuration and then follows it up with an energy minimization to explicitly sample a local minimum of a chosen energy function. This process is repeated in order to sample consecutive energy minima in a trajectory-like fashion. HopDock employs both geometry and evolutionary conservation analysis to narrow down the interaction search space of interest for the purpose of efficiently obtaining a diverse decoy ensemble.Results and conclusionsA detailed analysis and a comparative study on seventeen different dimers shows HopDock obtains a broad view of the energy surface near the native dimeric structure and samples many near-native configurations. The results show that HopDock has high sampling capability and can be employed to effectively obtain a large and diverse ensemble of decoy configurations that can then be further refined in greater structural detail in ab-initio docking protocols.

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“…Docking methods have exploited knowledge of interaction interfaces in guiding the search towards native-like configurations [18,26,33,34,36,62]. Recent work by us has extended geometrybased methods to directly sample rigid-body transformations that match geometrically-complementary and evolutionary-conserved surface regions [19,20,22]. However, evolutionary conservation is probably one of many features characterizing interaction interfaces.…”

Section: Introductionmentioning

confidence: 99%

Informatics-driven Protein-protein Docking

Hashmi

Shehu

2013

Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics

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Predicting the structure of protein assemblies is fundamental to our ability to understand the molecular basis of biological function. The basic protein-protein docking problem involving two protein units docking onto each-other remains challenging. One direction of research is exploring probabilistic search algorithms with high exploration capability, but these algorithms are limited by errors in current energy functions. A complementary direction is choosing to understand what constitutes true interaction interfaces. In this paper we present a method that combines the two directions and advances research into computationally-efficient yet highaccuracy docking. We present an informatics-driven probabilistic search algorithm for rigid protein-protein docking. The algorithm builds upon the powerful basin hopping framework, which we have shown in many settings in molecular modeling to have high exploration capability. Rather than operate de novo, the algorithm employs information on what constitutes a native interaction interface. A predictive machine learning model is built and trained a priori on known dimeric structures to learn features correlated with a true interface. The model is fast, accurate, and replaces expensive physics-based energy functions in scoring sampled configurations. A sophisticated energy function is used to refine only high-scoring configurations. The result is an ensemble of high-quality decoy configurations that we show here to approach the known native dimeric structure better than other state-of-the-art docking methods. We believe the proposed method advances computationally-efficient highaccuracy docking.

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Guiding Protein Docking With Geometric and Evolutionary Information

Cited by 12 publications

References 36 publications

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins

HopDock: a probabilistic search algorithm for decoy sampling in protein-protein docking

Informatics-driven Protein-protein Docking

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