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Computational predictions suggest that structural similarity in viral polymerases may lead to comparable allosteric binding sites.

ABSTRACT: The identification of ligand-binding sites is often the first step in drug targeting and design. To date there are numerous computational tools available to predict ligand binding sites. These tools can guide or mitigate the need for experimental methods to identify binding sites, which often require significant resources and time. Here, we evaluate four ligand-binding site predictor (LBSP) tools for their ability to predict allosteric sites within the Hepatitis C Virus (HCV) polymerase. Our results show that the LISE LBSP is able to identify all three target allosteric sites within the HCV polymerase as well as a known allosteric site in the Coxsackievirus polymerase. LISE was then employed to identify novel binding sites within the polymerases of the Dengue, West Nile, and Foot-and-mouth Disease viruses. Our results suggest that all three viral polymerases have putative sites that share structural or chemical similarities with allosteric pockets of the HCV polymerase. Thus, these binding locations may represent an evolutionarily conserved structural feature of several viral polymerases that could be exploited for the development of small molecule therapeutics.

SUBMITTER: Brown JA

PROVIDER: S-EPMC4969206 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Computational predictions suggest that structural similarity in viral polymerases may lead to comparable allosteric binding sites.

Brown Jodian A JA Espiritu Marie V MV Abraham Joel J Thorpe Ian F IF

Virus research 20160601

The identification of ligand-binding sites is often the first step in drug targeting and design. To date there are numerous computational tools available to predict ligand binding sites. These tools can guide or mitigate the need for experimental methods to identify binding sites, which often require significant resources and time. Here, we evaluate four ligand-binding site predictor (LBSP) tools for their ability to predict allosteric sites within the Hepatitis C Virus (HCV) polymerase. Our res ...[more]

PMID: 27262620

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Project description:Viruses are the most abundant and diverse biological entities on the planet and constitute a significant proportion of Earth's genetic diversity. Most of this diversity is not represented by isolated viral-host systems and has only been observed through sequencing of viral metagenomes (viromes) from environmental samples. Viromes provide snapshots of viral genetic potential, and a wealth of information on viral community ecology. These data also provide opportunities for exploring the biochemistry of novel viral enzymes. The in vitro biochemical characteristics of novel viral DNA polymerases were explored, testing hypothesized differences in polymerase biochemistry according to protein sequence phylogeny. Forty-eight viral DNA Polymerase I (PolA) proteins from estuarine viromes, hot spring metagenomes, and reference viruses, encompassing a broad representation of currently known diversity, were synthesized, expressed, and purified. Novel functionality was shown in multiple PolAs. Intriguingly, some of the estuarine viral polymerases demonstrated moderate to strong innate DNA strand displacement activity at high enzyme concentration. Strand-displacing polymerases have important technological applications where isothermal reactions are desirable. Bioinformatic investigation of genes neighboring these strand displacing polymerases found associations with SNF2 helicase-associated proteins. The specific function of SNF2 family enzymes is unknown for prokaryotes and viruses. In eukaryotes, SNF2 enzymes have chromatin remodeling functions but do not separate nucleic acid strands. This suggests the strand separation function may be fulfilled by the DNA polymerase for viruses carrying SNF2 helicase-associated proteins. Biochemical data elucidated from this study expands understanding of the biology and ecological behavior of unknown viruses. Moreover, given the numerous biotechnological applications of viral DNA polymerases, novel viral polymerases discovered within viromes may be a rich source of biological material for further in vitro DNA amplification advancements.

Project description:Transcription activator-like (TAL) effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs) that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open-source Java library Jstacs, and is freely available as a web-application and a command line program.

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Computational predictions suggest that structural similarity in viral polymerases may lead to comparable allosteric binding sites.

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Computational predictions suggest that structural similarity in viral polymerases may lead to comparable allosteric binding sites.

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