Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions

Zhou, Hufeng; Gao, Shumei; Nguyen, Nam Ninh; Fan, Mengyuan; Jin, Jingjing; Liu, Bing; Zhao, Liang; Geng, Xin; Tan, Min; Li, Shijun; Wong, Limsoon

doi:10.1186/1745-6150-9-5

Cited by 66 publications

(59 citation statements)

References 71 publications

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“…Additionally, potential drug targets of the pathogen that interact with the host have been identified to understand the infection mechanism using a dataset obtained from a computational prediction of Homo sapiens-Mycobacterium tuberculosis H37Rv protein-protein interactions [25]. This dataset is thought as a golden dataset for host-pathogen interaction.…”

Section: Resultsmentioning

confidence: 99%

Comparative Genome and Network Centrality Analysis to Identify Drug Targets ofMycobacterium tuberculosis H37Rv

Melak

Gakkhar

2015

BioMed Research International

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Potential drug targets of Mycobacterium tuberculosis H37Rv were identified through systematically integrated comparative genome and network centrality analysis. The comparative analysis of the complete genome of Mycobacterium tuberculosis H37Rv against Database of Essential Genes (DEG) yields a list of proteins which are essential for the growth and survival of the pathogen. Those proteins which are nonhomologous with human were selected. The resulting proteins were then prioritized by using the four network centrality measures: degree, closeness, betweenness, and eigenvector. Proteins whose centrality value is close to the centre of gravity of the interactome network were proposed as a final list of potential drug targets for the pathogen. The use of an integrated approach is believed to increase the success of the drug target identification process. For the purpose of validation, selective comparisons have been made among the proposed targets and previously identified drug targets by various other methods. About half of these proteins have been already reported as potential drug targets. We believe that the identified proteins will be an important input to experimental study which in the way could save considerable amount of time and cost of drug target discovery.

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Section: Resultsmentioning

confidence: 99%

Comparative Genome and Network Centrality Analysis to Identify Drug Targets ofMycobacterium tuberculosis H37Rv

Melak

Gakkhar

2015

BioMed Research International

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“…In the future work, author would extend the application of the proposed method on improving the works of Zhou et al those are related to computational biology [44], [45], [46].…”

Section: Discussionmentioning

confidence: 99%

Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

2014

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ContextOver the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem.ObjectiveThis paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment.MethodThe proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships.ResultsThe result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively.ConclusionThe primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

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“…There are several way to functionally and structurally annotate/predict important residues (Zhou et al 2013).…”

Section: Identification Of Functionally and Structurally Important Rementioning

confidence: 99%

Functional Exposed Amino Acids of BauA as Potential Immunogen Against Acinetobacter baumannii

et al. 2015

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Multidrug-resistant Acinetobacter baumannii is recognized to be among the most difficult antimicrobial-resistant gram negative bacilli to control and treat. One of the major challenges that the pathogenic bacteria face in their host is the scarcity of freely available iron. To survive under such conditions, bacteria express new proteins on their outer membrane and also secrete iron chelators called siderophores. Antibodies directed against these proteins associated with iron uptake exert a bacteriostatic or bactericidal effect against A. baumanii in vitro, by blocking siderophore mediated iron uptake pathways. Attempts should be made to discover peptides that could mimic protein epitopes and possess the same immunogenicity as the whole protein. Subsequently, theoretical methods for epitope prediction have been developed leading to synthesis of such peptides that are important for development of immunodiagnostic tests and vaccines. The present study was designed to in silico resolving the major obstacles in the control or in prevention of the diseases caused by A. baumannii. We exploited bioinformatic tools to better understand and characterize the Baumannii acinetobactin utilization structure of A. baumannii and select appropriate regions as effective B cell epitopes. In conclusion, amino acids 26-191 of cork domain and 321-635 of part of the barrel domain including L4-L9, were selected as vaccine candidates. These two regions contain functional exposed amino acids with higher score of B cell epitopes properties. Majority of amino acids are hydrophilic, flexible, accessible, and favorable for B cells from secondary structure point of view.

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Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions

Cited by 66 publications

References 71 publications

Comparative Genome and Network Centrality Analysis to Identify Drug Targets ofMycobacterium tuberculosis H37Rv

Comparative Genome and Network Centrality Analysis to Identify Drug Targets ofMycobacterium tuberculosis H37Rv

Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

Functional Exposed Amino Acids of BauA as Potential Immunogen Against Acinetobacter baumannii

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