1
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Swain A, Pan A. Protein Therapeutic Target Candidates Against Acinetobacter baumannii, a Pathogen of Concern to Planetary Health: A Network-Based Integrative Omics Drug Discovery Approach. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2023; 27:62-74. [PMID: 36735546 DOI: 10.1089/omi.2022.0180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Acinetobacter baumannii, an opportunistic gram-negative pathogen responsible for several nosocomial infections, has developed resistance to various antibiotics. Proteins involved in the two-component system (TCS), virulence, and antibiotic resistance (AR), help this pathogen in regulating antibiotic susceptibility and virulence mechanisms. The present study reports a network-based integrative omics approach to drug discovery to identify key regulatory proteins as therapeutic candidates against A. baumannii. We collected data on the TCS, virulence, and AR proteins from various databases (P2CS, VFDB, ARDB, and PAIDB), which were subjected to network, host-pathogen, and gene expression data analysis. Network analysis identified 43 hubs, and 10 proteins were found to be interacting with human proteins associated with vital pathways. Of the 53 (43 + 10) pathogen proteins, 46 had no orthologs in the human host. Twelve proteins, namely, RpfC, Wzc, OmpR, EnvZ, BfmS, PilG, histidine kinase, ABC 3 transport family protein, outer membrane porin OprD family, CsuD, Pgm, and LpxA, were differentially expressed in the resistant strain. We propose these proteins as key regulators that warrant evaluation as therapeutic target candidates in the future. Furthermore, structure prediction of ABC 3 transport family protein was performed as a case study. The findings from this study are poised to facilitate and inform drug discovery and development against A. baumannii.
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Affiliation(s)
- Aishwarya Swain
- Department of Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, India
| | - Archana Pan
- Department of Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, India
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2
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Priyamvada P, Debroy R, Anbarasu A, Ramaiah S. A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements. World J Microbiol Biotechnol 2022; 38:153. [PMID: 35788443 DOI: 10.1007/s11274-022-03343-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 06/21/2022] [Indexed: 12/11/2022]
Abstract
In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.
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Affiliation(s)
- P Priyamvada
- Medical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), 632014, Vellore, India.,Department of Bio-Sciences, SBST, VIT, 632014, Vellore, India
| | - Reetika Debroy
- Medical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), 632014, Vellore, India.,Department of Bio-Medical Sciences, SBST, VIT, 632014, Vellore, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), 632014, Vellore, India.,Department of Biotechnology, SBST, VIT, 632014, Vellore, India
| | - Sudha Ramaiah
- Medical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), 632014, Vellore, India. .,Department of Bio-Sciences, SBST, VIT, 632014, Vellore, India. .,School of Biosciences and Technology VIT, 632014, Vellore, Tamil Nadu, India.
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3
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Wangkheimayum J, Baishya S, Choudhury MD, Bhattacharjee A. Secondary resistome in bacteria: a potential biomarker for future antimicrobial resistance diagnostics. Future Microbiol 2022; 17:573-576. [PMID: 35392663 DOI: 10.2217/fmb-2022-0008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
| | - Somorita Baishya
- Department of Life Science & Bioinformatics, Assam University, Silchar, Assam, India.,Department of Zoology, Cachar College Silchar, Assam, India
| | | | - Amitabha Bhattacharjee
- Department of Microbiology, Assam University, Silchar, Assam, India.,Department of Zoology, Cachar College Silchar, Assam, India
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4
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Ashok G, Miryala SK, Anbarasu A, Ramaiah S. Integrated systems biology approach using gene network analysis to identify the important pathways and new potential drug targets for Neuroblastoma. GENE REPORTS 2021. [DOI: 10.1016/j.genrep.2021.101101] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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5
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Miryala SK, Anbarasu A, Ramaiah S. Role of SHV-11, a Class A β-Lactamase, Gene in Multidrug Resistance Among Klebsiella pneumoniae Strains and Understanding Its Mechanism by Gene Network Analysis. Microb Drug Resist 2020; 26:900-908. [DOI: 10.1089/mdr.2019.0430] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Affiliation(s)
- Sravan Kumar Miryala
- Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT, Vellore, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT, Vellore, India
| | - Sudha Ramaiah
- Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT, Vellore, India
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6
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Naha A, Kumar Miryala S, Debroy R, Ramaiah S, Anbarasu A. Elucidating the multi-drug resistance mechanism of Enterococcus faecalis V583: A gene interaction network analysis. Gene 2020; 748:144704. [DOI: 10.1016/j.gene.2020.144704] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 04/16/2020] [Accepted: 04/21/2020] [Indexed: 12/12/2022]
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7
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Miryala SK, Anbarasu A, Ramaiah S. Gene interaction network approach to elucidate the multidrug resistance mechanisms in the pathogenic bacterial strain Proteus mirabilis. J Cell Physiol 2020; 236:468-479. [PMID: 32542649 DOI: 10.1002/jcp.29874] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 05/11/2020] [Accepted: 05/29/2020] [Indexed: 12/24/2022]
Abstract
Proteus mirabilis is one among the most frequently identified pathogen in patients with the urinary tract infection. The multidrug resistance exhibited by P. mirabilis renders the treatment ineffective, and new progressive strategies are needed to overcome the antibiotic resistance (AR). We have analyzed the evolutionary relationship of 29 P. mirabilis strains available in the National Center for Biotechnology Information-Genome database. The antimicrobial resistance genes of P. mirabilis along with the enriched pathways and the Gene Ontology terms are analyzed using gene networks to understand the molecular basis of AR. The genes rpoB, tufB, rpsl, fusA, and rpoA could be exploited as potential drug targets as they are involved in regulating the vital functions within the bacterium. The drug targets reported in the present study will aid researchers in developing new strategies to combat multidrug-resistant P. mirabilis.
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Affiliation(s)
- Sravan K Miryala
- Medical and Biological Computing Laboratory, Department of Bio-Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, Department of Bio-Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Sudha Ramaiah
- Medical and Biological Computing Laboratory, Department of Bio-Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
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8
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Debroy R, Miryala SK, Naha A, Anbarasu A, Ramaiah S. Gene interaction network studies to decipher the multi-drug resistance mechanism in Salmonella enterica serovar Typhi CT18 reveal potential drug targets. Microb Pathog 2020; 142:104096. [PMID: 32097747 DOI: 10.1016/j.micpath.2020.104096] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 02/21/2020] [Accepted: 02/21/2020] [Indexed: 01/13/2023]
Abstract
Salmonella enterica subsp. enterica serovar Typhi, a human enteric pathogen causing typhoid fever, developed resistance to multiple antibiotics over the years. The current study was dedicated to understand the multi-drug resistance (MDR) mechanism of S. enterica serovar Typhi CT18 and to identify potential drug targets that could be exploited for new drug discovery. We have employed gene interaction network analysis for 44 genes which had 275 interactions. Clustering analysis resulted in three highly interconnecting clusters (C1-C3). Functional enrichment analysis revealed the presence of drug target alteration and three different multi-drug efflux pumps in the bacteria that were associated with antibiotic resistance. We found seven genes (arnA,B,C,D,E,F,T) conferring resistance to Cationic Anti-Microbial Polypeptide (CAMP) molecules by membrane Lipopolysaccharide (LPS) modification, while macB was observed to be an essential controlling hub of the network and played a crucial role in MacAB-TolC efflux pump. Further, we identified five genes (mdtH, mdtM, mdtG, emrD and mdfA) which were involved in Major Facilitator Superfamily (MFS) efflux system and acrAB contributed towards AcrAB-TolC efflux pump. All three efflux pumps were seen to be highly dependent on tolC gene. The five genes, namely tolC, macB, acrA, acrB and mdfA which were involved in multiple resistance pathways, can act as potential drug targets for successful treatment strategies. Therefore, this study has provided profound insights into the MDR mechanism in S. Typhi CT18. Our results will be useful for experimental biologists to explore new leads for S. enterica.
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Affiliation(s)
- Reetika Debroy
- Medical and Biological Computing Laboratory, School of Bio-Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India
| | - Sravan Kumar Miryala
- Medical and Biological Computing Laboratory, School of Bio-Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India
| | - Aniket Naha
- Medical and Biological Computing Laboratory, School of Bio-Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, School of Bio-Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India
| | - Sudha Ramaiah
- Medical and Biological Computing Laboratory, School of Bio-Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India.
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9
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Miryala SK, Anbarasu A, Ramaiah S. Evolutionary Relationship of Penicillin-Binding Protein 2 Coding penA Gene and Understanding the Role in Drug-Resistance Mechanism Using Gene Interaction Network Analysis. LECTURE NOTES ON MULTIDISCIPLINARY INDUSTRIAL ENGINEERING 2020. [DOI: 10.1007/978-981-13-7968-0_2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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10
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Miryala SK, Anbarasu A, Ramaiah S. Systems biology studies in Pseudomonas aeruginosa PA01 to understand their role in biofilm formation and multidrug efflux pumps. Microb Pathog 2019; 136:103668. [DOI: 10.1016/j.micpath.2019.103668] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2019] [Revised: 04/24/2019] [Accepted: 08/12/2019] [Indexed: 11/29/2022]
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11
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Chernov VM, Chernova OA, Mouzykantov AA, Medvedeva ES, Baranova NB, Malygina TY, Aminov RI, Trushin MV. Antimicrobial resistance in mollicutes: known and newly emerging mechanisms. FEMS Microbiol Lett 2019; 365:5057471. [PMID: 30052940 DOI: 10.1093/femsle/fny185] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Accepted: 07/21/2018] [Indexed: 12/13/2022] Open
Abstract
This review is devoted to the mechanisms of antibiotic resistance in mollicutes (class Bacilli, subclass Mollicutes), the smallest self-replicating bacteria, that can cause diseases in plants, animals and humans, and also contaminate cell cultures and vaccine preparations. Research in this area has been mainly based on the ubiquitous mollicute and the main contaminant of cell cultures, Acholeplasma laidlawii. The omics technologies applied to this and other bacteria have yielded a complex picture of responses to antimicrobials, including their removal from the cell, the acquisition of antibiotic resistance genes and mutations that potentially allow global reprogramming of many cellular processes. This review provides a brief summary of well-known resistance mechanisms that have been demonstrated in several mollicutes species and, in more detail, novel mechanisms revealed in A. laidlawii, including the least explored vesicle-mediated transfer of short RNAs with a regulatory potency. We hope that this review highlights new avenues for further studies on antimicrobial resistance in these bacteria for both a basic science and an application perspective of infection control and management in clinical and research/production settings.
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Affiliation(s)
- Vladislav M Chernov
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS 2/31 Lobachevsky Str., Kazan, 420111, Russian Federation.,Kazan (Volga region) Federal University, 18 Kremlyovskaya Str., Kazan, 420008, Russian Federation
| | - Olga A Chernova
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS 2/31 Lobachevsky Str., Kazan, 420111, Russian Federation.,Kazan (Volga region) Federal University, 18 Kremlyovskaya Str., Kazan, 420008, Russian Federation
| | - Alexey A Mouzykantov
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS 2/31 Lobachevsky Str., Kazan, 420111, Russian Federation.,Kazan (Volga region) Federal University, 18 Kremlyovskaya Str., Kazan, 420008, Russian Federation
| | - Elena S Medvedeva
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS 2/31 Lobachevsky Str., Kazan, 420111, Russian Federation.,Kazan (Volga region) Federal University, 18 Kremlyovskaya Str., Kazan, 420008, Russian Federation
| | - Natalia B Baranova
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS 2/31 Lobachevsky Str., Kazan, 420111, Russian Federation.,Kazan (Volga region) Federal University, 18 Kremlyovskaya Str., Kazan, 420008, Russian Federation
| | - Tatiana Y Malygina
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS 2/31 Lobachevsky Str., Kazan, 420111, Russian Federation
| | - Rustam I Aminov
- School of Medicine and Dentistry, University of Aberdeen, Aberdeen AB25 2ZD, United Kingdom
| | - Maxim V Trushin
- Kazan (Volga region) Federal University, 18 Kremlyovskaya Str., Kazan, 420008, Russian Federation
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12
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Miryala SK, Ramaiah S. Exploring the multi-drug resistance in Escherichia coli O157:H7 by gene interaction network: A systems biology approach. Genomics 2019; 111:958-965. [DOI: 10.1016/j.ygeno.2018.06.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 06/08/2018] [Accepted: 06/11/2018] [Indexed: 12/27/2022]
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13
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Miryala SK, Anbarasu A, Ramaiah S. Impact of bedaquiline and capreomycin on the gene expression patterns of multidrug‐resistant
Mycobacterium tuberculosis
H37Rv strain and understanding the molecular mechanism of antibiotic resistance. J Cell Biochem 2019; 120:14499-14509. [DOI: 10.1002/jcb.28711] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 03/06/2019] [Accepted: 03/15/2019] [Indexed: 01/03/2023]
Affiliation(s)
- Sravan Kumar Miryala
- Department of Bio‐Sciences, Medical and Biological Computing Laboratory, School of Bio Sciences and Technology Vellore Institute of Technology Vellore Tamil Nadu India
| | - Anand Anbarasu
- Department of Bio‐Sciences, Medical and Biological Computing Laboratory, School of Bio Sciences and Technology Vellore Institute of Technology Vellore Tamil Nadu India
| | - Sudha Ramaiah
- Department of Bio‐Sciences, Medical and Biological Computing Laboratory, School of Bio Sciences and Technology Vellore Institute of Technology Vellore Tamil Nadu India
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14
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Chernov VM, Chernova OA, Mouzykantov AA, Lopukhov LL, Aminov RI. Omics of antimicrobials and antimicrobial resistance. Expert Opin Drug Discov 2019; 14:455-468. [DOI: 10.1080/17460441.2019.1588880] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Vladislav M. Chernov
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS, Kazan, Russian Federation
- Institute of Fundamental Medicine and Biology, Kazan (Volga region) Federal University, Kazan, Russian Federation
| | - Olga A. Chernova
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS, Kazan, Russian Federation
- Institute of Fundamental Medicine and Biology, Kazan (Volga region) Federal University, Kazan, Russian Federation
| | - Alexey A. Mouzykantov
- Kazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS, Kazan, Russian Federation
- Institute of Fundamental Medicine and Biology, Kazan (Volga region) Federal University, Kazan, Russian Federation
| | - Leonid L. Lopukhov
- Institute of Fundamental Medicine and Biology, Kazan (Volga region) Federal University, Kazan, Russian Federation
| | - Rustam I. Aminov
- Institute of Fundamental Medicine and Biology, Kazan (Volga region) Federal University, Kazan, Russian Federation
- Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK
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15
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Miryala SK, Anbarasu A, Ramaiah S. Discerning molecular interactions: A comprehensive review on biomolecular interaction databases and network analysis tools. Gene 2017; 642:84-94. [PMID: 29129810 DOI: 10.1016/j.gene.2017.11.028] [Citation(s) in RCA: 98] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Revised: 10/17/2017] [Accepted: 11/08/2017] [Indexed: 12/12/2022]
Abstract
Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks.
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Affiliation(s)
- Sravan Kumar Miryala
- Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT University, Vellore 632014, Tamil Nadu, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT University, Vellore 632014, Tamil Nadu, India
| | - Sudha Ramaiah
- Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT University, Vellore 632014, Tamil Nadu, India.
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16
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Thillainayagam M, Anbarasu A, Ramaiah S. Comparative molecular field analysis and molecular docking studies on novel aryl chalcone derivatives against an important drug target cysteine protease in Plasmodium falciparum. J Theor Biol 2016; 403:110-128. [DOI: 10.1016/j.jtbi.2016.05.019] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Revised: 05/03/2016] [Accepted: 05/10/2016] [Indexed: 01/08/2023]
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17
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Suganya S, Nandagopal B, Anbarasu A. Natural Inhibitors of HMG-CoA Reductase-An Insilico Approach Through Molecular Docking and Simulation Studies. J Cell Biochem 2016; 118:52-57. [PMID: 27216569 DOI: 10.1002/jcb.25608] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2016] [Accepted: 05/20/2016] [Indexed: 01/09/2023]
Abstract
Plant products have always been considered for many important metabolic disorders due to its abundant medicinal properties. Alarming adverse effects of overuse of statins has been reported for patients with dyslipidemia. This study was aimed to identify compounds with potent anti-dyslipidemic property from selected plants and analyze them for their efficiency in binding with HMG-CoA reductase, a key enzyme in lipid metabolism. The docking studies indicate rutin as the best compound that can inhibit HMG-CoA reductase as it had strong binding affinity to the enzyme. The molecular dynamics simulation studies confirmed the stability of the HMG-CoA reductase-rutin complex. RMSD, RMSF, Rg, H-bond results indicated that the HMG-CoA reductase-rutin complex is highly stable. Presently, statins are not preferred for individuals with pre-existing liver disease. Our study identified rutin as a promising lead compound which could be further developed into an anti-dyslipidemic molecule. Our results will be a good starting point for future experimental and clinical studies and if the results from such studies match international standards plant derived rutin might emerge as a good alternative to statins. J. Cell. Biochem. 118: 52-57, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Subramanian Suganya
- Sri Sakthi Amma Institute of Biomedical Research, Sri Narayani Hospital and Research Centre, Sripuram, Vellore, 632 055, Tamil Nadu, India.,Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT University, Vellore, 632 014, Tamil Nadu, India
| | - Balaji Nandagopal
- Sri Sakthi Amma Institute of Biomedical Research, Sri Narayani Hospital and Research Centre, Sripuram, Vellore, 632 055, Tamil Nadu, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, School of Biosciences and Technology, VIT University, Vellore, 632 014, Tamil Nadu, India
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18
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Molecular Docking and Molecular Dynamics Studies to Identify Potential OXA-10 Extended Spectrum β-Lactamase Non-hydrolysing Inhibitors for Pseudomonas aeruginosa. Cell Biochem Biophys 2016; 74:141-55. [DOI: 10.1007/s12013-016-0735-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 05/18/2016] [Indexed: 01/17/2023]
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19
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Chen Y, Su Z. Reveal genes functionally associated with ACADS by a network study. Gene 2015; 569:294-302. [PMID: 26045367 DOI: 10.1016/j.gene.2015.05.069] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 05/22/2015] [Accepted: 05/28/2015] [Indexed: 02/05/2023]
Abstract
Establishing a systematic network is aimed at finding essential human gene-gene/gene-disease pathway by means of network inter-connecting patterns and functional annotation analysis. In the present study, we have analyzed functional gene interactions of short-chain acyl-coenzyme A dehydrogenase gene (ACADS). ACADS plays a vital role in free fatty acid β-oxidation and regulates energy homeostasis. Modules of highly inter-connected genes in disease-specific ACADS network are derived by integrating gene function and protein interaction data. Among the 8 genes in ACADS web retrieved from both STRING and GeneMANIA, ACADS is effectively conjoined with 4 genes including HAHDA, HADHB, ECHS1 and ACAT1. The functional analysis is done via ontological briefing and candidate disease identification. We observed that the highly efficient-interlinked genes connected with ACADS are HAHDA, HADHB, ECHS1 and ACAT1. Interestingly, the ontological aspect of genes in the ACADS network reveals that ACADS, HAHDA and HADHB play equally vital roles in fatty acid metabolism. The gene ACAT1 together with ACADS indulges in ketone metabolism. Our computational gene web analysis also predicts potential candidate disease recognition, thus indicating the involvement of ACADS, HAHDA, HADHB, ECHS1 and ACAT1 not only with lipid metabolism but also with infant death syndrome, skeletal myopathy, acute hepatic encephalopathy, Reye-like syndrome, episodic ketosis, and metabolic acidosis. The current study presents a comprehensible layout of ACADS network, its functional strategies and candidate disease approach associated with ACADS network.
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Affiliation(s)
- Yulong Chen
- Molecular Medicine Research Center, West China Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China
| | - Zhiguang Su
- Molecular Medicine Research Center, West China Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China.
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20
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Gene network analysis reveals the association of important functional partners involved in antibiotic resistance: A report on an important pathogenic bacterium Staphylococcus aureus. Gene 2015; 575:253-63. [PMID: 26342962 DOI: 10.1016/j.gene.2015.08.068] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Revised: 07/30/2015] [Accepted: 08/31/2015] [Indexed: 12/27/2022]
Abstract
Staphylococcus aureus (S. aureus) is an emerging concern in hospital settings as it causes serious human infections. The multidrug resistance (MDR) in S. aureus is a complicated problem that is difficult to overcome due to the presence of numerous antibiotic resistance genes and it exhibit resistance to most of the currently available antibiotics. Presently, the resistance mechanisms of these genes/proteins are not completely understood. Therefore, identifying and understanding the functional relationship between the antibiotic resistant genes and their associated proteins might provide necessary information on resistance mechanisms and thereby help in designing successful drugs to combat the antibiotic resistance. In this study, we propose a model based on protein/gene network to identify genes/proteins associated with drug resistance in S. aureus. We filtered 50 functional partners in NorA, aacA-aphD (aac6ie), aad9ib (ant), aadd (knt), baca (uppP), bl2a_pc (blaZ), ble, ermA, SAV0052 (ermb), ermc, fosB, mecA (mecI), mecR (mecr1), mepA, msrA1, qacA, vraR (str), tet38 and tetM while 40 functional partners are identified in tet and aphA-3 (aph3iiia). The average shortest path length and betweenness centrality of functional partners in the clusters are calculated and they are functionally enriched with the Gene Ontology (GO) terms with a p-value cut-off ≤0.05. Interestingly, the constructed network reveals many associated antibiotic resistant genes and proteins and their role in resistance mechanisms. Thus, our results might provide a better understanding of the molecular mechanisms of action and their mode of drug resistance that will be useful for researchers exploring in the field of antibiotic resistance mechanisms.
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Handelman SK, Aaronson JM, Seweryn M, Voronkin I, Kwiek JJ, Sadee W, Verducci JS, Janies DA. Cladograms with Path to Event (ClaPTE): a novel algorithm to detect associations between genotypes or phenotypes using phylogenies. Comput Biol Med 2015; 58:1-13. [PMID: 25577610 PMCID: PMC4331246 DOI: 10.1016/j.compbiomed.2014.12.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2014] [Revised: 12/09/2014] [Accepted: 12/15/2014] [Indexed: 12/20/2022]
Abstract
BACKGROUND Associations between genotype and phenotype provide insight into the evolution of pathogenesis, drug resistance, and the spread of pathogens between hosts. However, common ancestry can lead to apparent associations between biologically unrelated features. The novel method Cladograms with Path to Event (ClaPTE) detects associations between character-pairs (either a pair of mutations or a mutation paired with a phenotype) while adjusting for common ancestry, using phylogenetic trees. METHODS ClaPTE tests for character-pairs changing close together on the phylogenetic tree, consistent with an associated character-pair. ClaPTE is compared to three existing methods (independent contrasts, mixed model, and likelihood ratio) to detect character-pair associations adjusted for common ancestry. Comparisons utilize simulations on gene trees for: HIV Env, HIV promoter, and bacterial DnaJ and GuaB; and case studies for Oseltamavir resistance in Influenza, and for DnaJ and GuaB. Simulated data include both true-positive/associated character-pairs, and true-negative/not-associated character-pairs, used to assess type I (frequency of p-values in true-negatives) and type II (sensitivity to true-positives) error control. RESULTS AND CONCLUSIONS ClaPTE has competitive sensitivity and better type I error control than existing methods. In the Influenza/Oseltamavir case study, ClaPTE reports no new permissive mutations but detects associations between adjacent (in primary sequence) amino acid positions which other methods miss. In the DnaJ and GuaB case study, ClaPTE reports more frequent associations between positions both from the same protein family than between positions from different families, in contrast to other methods. In both case studies, the results from ClaPTE are biologically plausible.
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Affiliation(s)
- Samuel K Handelman
- Department of Pharmacology, Ohio State University College of Medicine, 5072 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210, United States; Mathematical Biosciences Institute, The Ohio State University, Jennings Hall 3rd Floor, 1735 Neil Avenue, Columbus, OH 43210, United States.
| | - Jacob M Aaronson
- Department of Biomedical Informatics, Ohio State University College of Medicine, 3190 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210, United States
| | - Michal Seweryn
- Mathematical Biosciences Institute, The Ohio State University, Jennings Hall 3rd Floor, 1735 Neil Avenue, Columbus, OH 43210, United States
| | - Igor Voronkin
- Department of Biomedical Informatics, Ohio State University College of Medicine, 3190 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210, United States
| | - Jesse J Kwiek
- Department of Microbial Infection & Immunity and Department of Microbiology, The Ohio State University, 788 Biomedical Research Tower, 460 West 12th Avenue, Columbus, OH 43210, United States
| | - Wolfgang Sadee
- Department of Pharmacology, Ohio State University College of Medicine, 5072 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210, United States
| | - Joseph S Verducci
- Department of Statistics, The Ohio State University, 404 Cockins Hall, 1958 Neil Avenue, Columbus, OH 43210-1247, United States
| | - Daniel A Janies
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223-0001, United States
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Bag S, Anbarasu A. Revealing the Strong Functional Association of adipor2 and cdh13 with adipoq: A Gene Network Study. Cell Biochem Biophys 2014; 71:1445-56. [DOI: 10.1007/s12013-014-0367-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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