ZRANK: Reranking protein docking predictions with an optimized energy function

Bioinformatics Program, Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA.
Proteins Structure Function and Bioinformatics (Impact Factor: 2.92). 06/2007; 67(4):1078-86. DOI: 10.1002/prot.21373
Source: PubMed

ABSTRACT Protein-protein docking requires fast and effective methods to quickly discriminate correct from incorrect predictions generated by initial-stage docking. We have developed and tested a scoring function that utilizes detailed electrostatics, van der Waals, and desolvation to rescore initial-stage docking predictions. Weights for the scoring terms were optimized for a set of test cases, and this optimized function was then tested on an independent set of nonredundant cases. This program, named ZRANK, is shown to significantly improve the success rate over the initial ZDOCK rankings across a large benchmark. The amount of test cases with No. 1 ranked hits increased from 2 to 11 and from 6 to 12 when predictions from two ZDOCK versions were considered. ZRANK can be applied either as a refinement protocol in itself or as a preprocessing stage to enrich the well-ranked hits prior to further refinement.

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    • "Predicted changes in the interaction between the 51 kDa subunit and the WT or modified 75 kDa subunit were calculated using the ZDock algorithm (Chen and Weng, 2002). The ZRank scoring function was used to calculate the interaction energies of the resulting predicted protein complexes and represents a combination of van der Waals attractive and repulsive energies, short-and long-range repulsive and attractive energies, and desolvation (Pierce and Weng, 2007). Similarity of the predicted protein complexes to the crystal structure (3IAM) was determined by calculating and the root mean square deviation (RMSD) using the crystal structure as the reference. "
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    ABSTRACT: Mitochondrial oxidative stress and damage have been implicated in the etiology of temporal lobe epilepsy, but whether or not they have a functional impact on mitochondrial processes during epilepsy development (epileptogenesis) is unknown. One consequence of increased steady-state mitochondrial reactive oxygen species levels is protein post-translational modification (PTM). We hypothesize that complex I (CI), a protein complex of the mitochondrial electron transport chain, is a target for oxidant-induced PTMs, such as carbonylation, leading to impaired function during epileptogenesis. The goal of this study was to determine whether oxidative modifications occur and what impact they have on CI enzymatic activity in the rat hippocampus in response to kainate (KA)-induced epileptogenesis. Rats were injected with a single high dose of KA or vehicle and evidence for CI modifications was measured during the acute, latent, and chronic stages of epilepsy. Mitochondrial-specific carbonylation was increased acutely (48 h) and chronically (6 week), coincident with decreased CI activity. Mass spectrometry analysis of immunocaptured CI identified specific metal catalyzed carbonylation to Arg76 within the 75 kDa subunit concomitant with inhibition of CI activity during epileptogenesis. Computational-based molecular modeling studies revealed that Arg76 is in close proximity to the active site of CI and carbonylation of the residue is predicted to induce substantial structural alterations to the protein complex. These data provide evidence for the occurrence of a specific and irreversible oxidative modification of an important mitochondrial enzyme complex critical for cellular bioenergetics during the process of epileptogenesis.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 08/2012; 32(33):11250-8. DOI:10.1523/JNEUROSCI.0907-12.2012 · 6.75 Impact Factor
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    • "The energy minimised DNA was docked into the predicted binding pockets in the C-terminal domain of AIFM2 protein using rigid body docking program ZDOCK 2.1 (Rong and Zhiping, 2003).The generated docked complexes of AIFM2 – DNA were created by and re – ranked by ZRANK (Pierce and Weng, 2007). The ranking of the complexes is given by Z – score that is based on the pair – wise shape complementarity algorithm. "
    The Journal of Pharmacy 01/2012; 6(5):3099.
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    • "At the post-processing stage, a number of approaches are integrated with each docking module. These include biochemical information filtering, pair-wise root mean square deviation calculations and clustering using the MMTSB tool (Feig, 2004), energy minimization using the Amber molecular modeling package (Case, 2008), and rescoring using a variety of objective functions, i.e., ZRANK (Pierce, 2007), DFIRE (Zhang, 2004), EMPIRE (Liang, 2007), and MM-PB/GBSA (Onufriev, 2000). As an integrated pipeline, the PPDP provides a systematic platform to design and optimize different docking protocols for the applications of PPI studies. "
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    ABSTRACT: Knowledge of the three-dimensional (3D) structures of protein complexes provides a fundamental understanding of biological systems, as well as novel insights for antimicrobial drug and vaccine design. Protein-protein docking is used to predict the 3D structures of protein complexes from their components in silico. In this study, we developed a protein-protein docking pipeline (PPDP) that integrates a variety of state-of-the-art protein docking and structure prediction techniques, providing a systematic platform to predict large-scale protein-protein interactions (PPIs). The PPDP is deployed on high performance computing (HPC) clusters, thus enabling Department of Defense scientists to harness HPC resources to investigate the PPIs of biowarfare agents for the development of countermeasures. We applied the PPDP to investigate the binding interactions of Yersinia effector proteins with their chaperone and the underlying specificity of chaperone/effector interactions.
    High Performance Computing Modernization Program Users Group Conference (HPCMP-UGC), 2010 DoD; 07/2010
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