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Sarker P, Mitro A, Hoque H, Hasan MN, Nurnabi Azad Jewel GM. Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach. Comput Biol Med 2023; 165:107436. [PMID: 37690289 DOI: 10.1016/j.compbiomed.2023.107436] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 07/08/2023] [Accepted: 08/28/2023] [Indexed: 09/12/2023]
Abstract
Elizabethkingia anophelis is a human pathogen responsible for severe nosocomial infections in neonates and immunocompromised patients. The significantly higher mortality rate from E. anophelis infections and the lack of available regimens highlight the critical need to explore novel drug targets. The current study investigated effective novel drug targets by employing a comprehensive in silico subtractive genomic approach integrated with pangenomic analysis of E. anophelis strains. A total of 2809 core genomic proteins were found by pangenomic analysis of non-paralogous proteins. Subsequently, 156 pathogen-specific, 442 choke point, 202 virulence factor, 53 antibiotic resistant and 119 host-pathogen interacting proteins were identified in E. anophelis. By subtractive genomic approach, at first 791 proteins were found to be indispensable for the survival of E. anophelis. 558 and 315 proteins were detected as non-homologous to human and gut microflora respectively. Following that 245 cytoplasmic, 245 novel, and 23 broad-spectrum targets were selected and finally four proteins were considered as potential therapeutic targets of E. anophelis based on highest degree score in PPI network. Among those, three proteins were subjected to molecular docking and subsequent MD simulation as one protein did not contain a plausible binding pocket with sufficient surface area and volume. All the complexes were found to be stable and compact in 100 ns molecular dynamics simulation studies as measured by RMSD, RMSF, and Rg. These three short-listed targets identified in this study may lead to the development of novel antimicrobials capable of curing infections and pave the way to prevent and control the disease progression caused by the deadly agent E. anophelis.
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Affiliation(s)
- Parth Sarker
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh; Computational Biology and Bioinformatics Lab, Dept. of GEB, SUST, Sylhet-3114, Bangladesh
| | - Arnob Mitro
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh; Computational Biology and Bioinformatics Lab, Dept. of GEB, SUST, Sylhet-3114, Bangladesh
| | - Hammadul Hoque
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh
| | - Md Nazmul Hasan
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh
| | - G M Nurnabi Azad Jewel
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh; Computational Biology and Bioinformatics Lab, Dept. of GEB, SUST, Sylhet-3114, Bangladesh.
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Kaur H, Modgil V, Chaudhary N, Mohan B, Taneja N. Computational Guided Drug Targets Identification against Extended-Spectrum Beta-Lactamase-Producing Multi-Drug Resistant Uropathogenic Escherichia coli. Biomedicines 2023; 11:2028. [PMID: 37509666 PMCID: PMC10377140 DOI: 10.3390/biomedicines11072028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/14/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
Urinary tract infections (UTIs) are one of the most frequent bacterial infections in the world, both in the hospital and community settings. Uropathogenic Escherichia coli (UPEC) are the predominant etiological agents causing UTIs. Extended-spectrum beta-lactamase (ESBL) production is a prominent mechanism of resistance that hinders the antimicrobial treatment of UTIs caused by UPEC and poses a substantial danger to the arsenal of antibiotics now in use. As bacteria have several methods to counteract the effects of antibiotics, identifying new potential drug targets may help in the design of new antimicrobial agents, and in the control of the rising trend of antimicrobial resistance (AMR). The public availability of the entire genome sequences of humans and many disease-causing organisms has accelerated the hunt for viable therapeutic targets. Using a unique, hierarchical, in silico technique using computational tools, we discovered and described potential therapeutic drug targets against the ESBL-producing UPEC strain NA114. Three different sets of proteins (chokepoint, virulence, and resistance genes) were explored in phase 1. In phase 2, proteins shortlisted from phase 1 were analyzed for their essentiality, non-homology to the human genome, and gut flora. In phase 3, the further shortlisted putative drug targets were qualitatively characterized, including their subcellular location, broad-spectrum potential, and druggability evaluations. We found seven distinct targets for the pathogen that showed no similarity to the human proteome. Thus, possibilities for cross-reactivity between a target-specific antibacterial and human proteins were minimized. The subcellular locations of two targets, ECNA114_0085 and ECNA114_1060, were predicted as cytoplasmic and periplasmic, respectively. These proteins play an important role in bacterial peptidoglycan biosynthesis and inositol phosphate metabolism, and can be used in the design of drugs against these bacteria. Inhibition of these proteins will be helpful to combat infections caused by MDR UPEC.
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Affiliation(s)
- Harpreet Kaur
- Department of Medical Microbiology, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India
| | - Vinay Modgil
- Department of Medical Microbiology, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India
| | - Naveen Chaudhary
- Department of Medical Microbiology, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India
| | - Balvinder Mohan
- Department of Medical Microbiology, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India
| | - Neelam Taneja
- Department of Medical Microbiology, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India
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Rivara-Espasandín M, Palumbo MC, Sosa EJ, Radío S, Turjanski AG, Sotelo-Silveira J, Fernandez Do Porto D, Smircich P. Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections. Front Pharmacol 2023; 14:1136321. [PMID: 37089958 PMCID: PMC10115950 DOI: 10.3389/fphar.2023.1136321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 03/28/2023] [Indexed: 04/09/2023] Open
Abstract
Introduction:Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches.Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development.Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery.
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Affiliation(s)
- Martin Rivara-Espasandín
- Departamento de Genómica, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
- Departamento de Genética, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Miranda Clara Palumbo
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Ezequiel J. Sosa
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - Santiago Radío
- Departamento de Genómica, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
| | - Adrián G. Turjanski
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - José Sotelo-Silveira
- Departamento de Genómica, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
- Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay
| | - Dario Fernandez Do Porto
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- *Correspondence: Dario Fernandez Do Porto, ; Pablo Smircich,
| | - Pablo Smircich
- Departamento de Genómica, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
- Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay
- *Correspondence: Dario Fernandez Do Porto, ; Pablo Smircich,
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Oarga A, Bannerman BP, Júlvez J. CONTRABASS: exploiting flux constraints in genome-scale models for the detection of vulnerabilities. Bioinformatics 2023; 39:7000333. [PMID: 36692133 PMCID: PMC9907045 DOI: 10.1093/bioinformatics/btad053] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 11/16/2022] [Accepted: 01/23/2023] [Indexed: 01/25/2023] Open
Abstract
MOTIVATION Despite the fact that antimicrobial resistance is an increasing health concern, the pace of production of new drugs is slow due to the high cost and uncertain success of the process. The development of high-throughput technologies has allowed the integration of biological data into detailed genome-scale models of multiple organisms. Such models can be exploited by means of computational methods to identify system vulnerabilities such as chokepoint reactions and essential reactions. These vulnerabilities are appealing drug targets that can lead to novel drug developments. However, the current approach to compute these vulnerabilities is only based on topological data and ignores the dynamic information of the model. This can lead to misidentified drug targets. RESULTS This work computes flux constraints that are consistent with a certain growth rate of the modelled organism, and integrates the computed flux constraints into the model to improve the detection of vulnerabilities. By exploiting these flux constraints, we are able to obtain a directionality of the reactions of metabolism consistent with a given growth rate of the model, and consequently, a more realistic detection of vulnerabilities can be performed. Several sets of reactions that are system vulnerabilities are defined and the relationships among them are studied. The approach for the detection of these vulnerabilities has been implemented in the Python tool CONTRABASS. Such tool, for which an online web server has also been implemented, computes flux constraints and generates a report with the detected vulnerabilities. AVAILABILITY AND IMPLEMENTATION CONTRABASS is available as an open source Python package at https://github.com/openCONTRABASS/CONTRABASS under GPL-3.0 License. An online web server is available at http://contrabass.unizar.es. SUPPLEMENTARY INFORMATION A glossary of terms are available at Bioinformatics online.
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Affiliation(s)
- Alexandru Oarga
- Department of Computer Science and Systems Engineering, University of Zaragoza, Zaragoza 50018, Spain
| | - Bridget P Bannerman
- Lucy Cavendish College, Biological Sciences, University of Cambridge, Cambridge CB3 0BU, UK.,Science Resources Foundation, Health Unit, London EC1V 2NX, UK
| | - Jorge Júlvez
- Department of Computer Science and Systems Engineering, University of Zaragoza, Zaragoza 50018, Spain
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Bannerman BP, Oarga A, Júlvez J. Mycobacterial metabolic model development for drug target identification. GIGABYTE 2023; 2023:gigabyte80. [PMID: 37153490 PMCID: PMC10154535 DOI: 10.46471/gigabyte.80] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 04/24/2023] [Indexed: 05/09/2023] Open
Abstract
Antibiotic resistance is increasing at an alarming rate, and three related mycobacteria are sources of widespread infections in humans. According to the World Health Organization, Mycobacterium leprae, which causes leprosy, is still endemic in tropical countries; Mycobacterium tuberculosis is the second leading infectious killer worldwide after COVID-19; and Mycobacteroides abscessus, a group of non-tuberculous mycobacteria, causes lung infections and other healthcare-associated infections in humans. Due to the rise in resistance to common antibacterial drugs, it is critical that we develop alternatives to traditional treatment procedures. Furthermore, an understanding of the biochemical mechanisms underlying pathogenic evolution is important for the treatment and management of these diseases. In this study, metabolic models have been developed for two bacterial pathogens, M. leprae and My. abscessus, and a new computational tool has been used to identify potential drug targets, which are referred to as bottleneck reactions. The genes, reactions, and pathways in each of these organisms have been highlighted; the potential drug targets can be further explored as broad-spectrum antibacterials and the unique drug targets for each pathogen are significant for precision medicine initiatives. The models and associated datasets described in this paper are available in GigaDB, Biomodels, and PatMeDB repositories.
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Affiliation(s)
- Bridget P. Bannerman
- Lucy Cavendish College, University of Cambridge, Lady Margaret Rd, Cambridge, CB3 0BU, UK
- Science Resources Foundation, 128 City Road, London, EC1V 2NX, UK
- Corresponding author. E-mail:
| | - Alexandru Oarga
- Department of Computer Science and Systems Engineering, University of Zaragoza, C/María de Luna n 1, 50018, Zaragoza, Spain
| | - Jorge Júlvez
- Department of Computer Science and Systems Engineering, University of Zaragoza, C/María de Luna n 1, 50018, Zaragoza, Spain
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Islam J, Sarkar H, Hoque H, Hasan MN, Jewel GNA. In-silico approach of identifying novel therapeutic targets against Yersinia pestis using pan and subtractive genomic analysis. Comput Biol Chem 2022; 101:107784. [DOI: 10.1016/j.compbiolchem.2022.107784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 10/30/2022] [Accepted: 11/01/2022] [Indexed: 11/06/2022]
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Joshi M, Purohit M, Shah DP, Patel D, Depani P, Moryani P, Krishnakumar A. Pathogenomic in silico approach identifies NSP-A and Fe-IIISBP as possible drug targets in Neisseria Meningitidis MC58 and development of pharmacophores as novel therapeutic candidates. Mol Divers 2022:10.1007/s11030-022-10480-y. [PMID: 35879631 DOI: 10.1007/s11030-022-10480-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/07/2022] [Indexed: 11/26/2022]
Abstract
Meningitis creates a life-threatening clinical crisis. Moreover, the administered antibiotics result into multi-drug resistance, thereby necessitating development of alternative therapeutic strategies. This study aimed at identifying novel-drug targets in Neisseria meningitidis and therapeutic molecules which can be exploited for the treatment of meningitis. Novel targets were identified by applying a pathogenomic approach involving protein data-set mining, subtractive channel analysis and subsequent qualitative analysis comprising of in silico pharmacokinetics, molecular docking and pharmacophore generation. Pathogenomic studies revealed Neisserial Surface Protein A (NSP-A) and Iron-III-Substrate Binding Protein (Fe-IIISBP) as potential targets. Two pharmacophore models comprising of 2-(biaryl) carbapenems, efavirenz, praziquantel and pyrimethamine for NSP-A and 2-(biaryl) carbapenems, trimipramine and pyrimethamine for Fe-IIISBP, showed successful docking, followed drug-likeness criteria and generated pharmacophore model with a score of 8.08 and 8.818, respectively, which had further been docked to the target stably. Thus, our study identifies NSP-A and Fe-IIISBP as novel targets in Neisseria meningitidis for which 2-(biaryl) carbapenems, efavirenz, praziquantel, trimipramine and pyrimethamine may be employed for effective treatment of meningitis.
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Affiliation(s)
- Madhavi Joshi
- Institute of Science, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad, Gujarat, 382 481, India
| | - Maitree Purohit
- Institute of Science, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad, Gujarat, 382 481, India
| | - Dhriti P Shah
- Institute of Science, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad, Gujarat, 382 481, India
| | - Devanshi Patel
- Institute of Science, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad, Gujarat, 382 481, India
| | - Preksha Depani
- Institute of Science, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad, Gujarat, 382 481, India
| | - Premkumar Moryani
- Institute of Science, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad, Gujarat, 382 481, India
| | - Amee Krishnakumar
- Institute of Science, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad, Gujarat, 382 481, India.
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Xie Y, Wang S, Wu S, Gao S, Meng Q, Wang C, Lan J, Luo L, Zhou X, Xu J, Gu X, He R, Yang Z, Peng X, Hu S, Yang G. Genome of the Giant Panda Roundworm Illuminates Its Host Shift and Parasitic Adaptation. GENOMICS, PROTEOMICS & BIOINFORMATICS 2022; 20:366-381. [PMID: 34487863 PMCID: PMC9684166 DOI: 10.1016/j.gpb.2021.08.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 08/17/2021] [Accepted: 08/25/2021] [Indexed: 01/05/2023]
Abstract
Baylisascaris schroederi, a roundworm (ascaridoid) parasite specific to the bamboo-feeding giant panda (Ailuropoda melanoleuca), represents a leading cause of mortality in wild giant panda populations. Here, we present a 293-megabase chromosome-level genome assembly of B. schroederi to infer its biology, including host adaptations. Comparative genomics revealed an evolutionary trajectory accompanied by host-shift events in ascaridoid parasite lineages after host separations, suggesting their potential for transmission and rapid adaptation to new hosts. Genomic and anatomical lines of evidence, including expansion and positive selection of genes related to the cuticle and basal metabolisms, indicate that B. schroederi undergoes specific adaptations to survive in the sharp-edged bamboo-enriched gut of giant pandas by structurally increasing its cuticle thickness and efficiently utilizing host nutrients through gut parasitism. Additionally, we characterized the secretome of B. schroederi and predicted potential drug and vaccine targets for new control strategies. Overall, this genome resource provides new insights into the host adaptation of B. schroederi to the giant panda as well as the host-shift events in ascaridoid parasite lineages. Our findings on the unique biology of B. schroederi will also aid in the development of prevention and treatment measures to protect giant panda populations from roundworm parasitism.
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Affiliation(s)
- Yue Xie
- Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu 611130, China
| | - Sen Wang
- Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Shuangyang Wu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; Department of Oncology and Pathology, Karolinska Institutet, Stockholm 17164, Sweden
| | - Shenghan Gao
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qingshu Meng
- Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Chengdong Wang
- Chengdu Research Base of Giant Panda Breeding, Chengdu 610081, China
| | - Jingchao Lan
- Chengdu Research Base of Giant Panda Breeding, Chengdu 610081, China
| | - Li Luo
- Chengdu Research Base of Giant Panda Breeding, Chengdu 610081, China
| | - Xuan Zhou
- Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu 611130, China; Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jing Xu
- Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaobin Gu
- Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu 611130, China
| | - Ran He
- Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu 611130, China
| | - Zijiang Yang
- Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20740, USA
| | - Xuerong Peng
- Department of Chemistry, College of Life and Basic Science, Sichuan Agricultural University, Chengdu 611130, China
| | - Songnian Hu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Guangyou Yang
- Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu 611130, China.
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Serral F, Pardo AM, Sosa E, Palomino MM, Nicolás MF, Turjanski AG, Ramos PIP, Fernández Do Porto D. Pathway Driven Target Selection in Klebsiella pneumoniae: Insights Into Carbapenem Exposure. Front Cell Infect Microbiol 2022; 12:773405. [PMID: 35174104 PMCID: PMC8841789 DOI: 10.3389/fcimb.2022.773405] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 01/07/2022] [Indexed: 12/13/2022] Open
Abstract
Carbapenem-resistant Klebsiella pneumoniae (CR-KP) represents an emerging threat to public health. CR-KP infections result in elevated morbidity and mortality. This fact, coupled with their global dissemination and increasingly limited number of therapeutic options, highlights the urgency of novel antimicrobials. Innovative strategies linking genome-wide interrogation with multi-layered metabolic data integration can accelerate the early steps of drug development, particularly target selection. Using the BioCyc ontology, we generated and manually refined a metabolic network for a CR-KP, K. pneumoniae Kp13. Converted into a reaction graph, we conducted topological-based analyses in this network to prioritize pathways exhibiting druggable features and fragile metabolic points likely exploitable to develop novel antimicrobials. Our results point to the aptness of previously recognized pathways, such as lipopolysaccharide and peptidoglycan synthesis, and casts light on the possibility of targeting less explored cellular functions. These functions include the production of lipoate, trehalose, glycine betaine, and flavin, as well as the salvaging of methionine. Energy metabolism pathways emerged as attractive targets in the context of carbapenem exposure, targeted either alone or in conjunction with current therapeutic options. These results prompt further experimental investigation aimed at controlling this highly relevant pathogen.
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Affiliation(s)
- Federico Serral
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (UBA), Buenos Aires, Argentina
| | - Agustin M. Pardo
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (UBA), Buenos Aires, Argentina
| | - Ezequiel Sosa
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina
| | - María Mercedes Palomino
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina
- Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Universidad de Buenos Aires, Cdad. Universitaria, Buenos Aires, Argentina
| | - Marisa F. Nicolás
- Laboratório de Bioinformática (LABINFO), Laboratório Nacional de Computação Científica (LNCC), Petrópolis, Brazil
| | - Adrian G. Turjanski
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina
- Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Universidad de Buenos Aires, Cdad. Universitaria, Buenos Aires, Argentina
| | - Pablo Ivan P. Ramos
- Centro de Integração de Dados e Conhecimentos para a Saúde (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz - Bahia), Salvador, Brazil
- *Correspondence: Darío Fernández Do Porto, ; Pablo Ivan P. Ramos,
| | - Darío Fernández Do Porto
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (UBA), Buenos Aires, Argentina
- Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Universidad de Buenos Aires, Cdad. Universitaria, Buenos Aires, Argentina
- *Correspondence: Darío Fernández Do Porto, ; Pablo Ivan P. Ramos,
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Bannerman BP, Júlvez J, Oarga A, Blundell TL, Moreno P, Floto RA. Integrated human/SARS-CoV-2 metabolic models present novel treatment strategies against COVID-19. Life Sci Alliance 2021; 4:e202000954. [PMID: 34353886 PMCID: PMC8343166 DOI: 10.26508/lsa.202000954] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 07/26/2021] [Accepted: 07/27/2021] [Indexed: 01/20/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic caused by the new coronavirus (SARS-CoV-2) is currently responsible for more than 3 million deaths in 219 countries across the world and with more than 140 million cases. The absence of FDA-approved drugs against SARS-CoV-2 has highlighted an urgent need to design new drugs. We developed an integrated model of the human cell and SARS-CoV-2 to provide insight into the virus' pathogenic mechanism and support current therapeutic strategies. We show the biochemical reactions required for the growth and general maintenance of the human cell, first, in its healthy state. We then demonstrate how the entry of SARS-CoV-2 into the human cell causes biochemical and structural changes, leading to a change of cell functions or cell death. A new computational method that predicts 20 unique reactions as drug targets from our models and provides a platform for future studies on viral entry inhibition, immune regulation, and drug optimisation strategies. The model is available in BioModels (https://www.ebi.ac.uk/biomodels/MODEL2007210001) and the software tool, findCPcli, that implements the computational method is available at https://github.com/findCP/findCPcli.
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Affiliation(s)
- Bridget P Bannerman
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK
- The Center for Research and Interdisciplinarity, Paris, France
| | - Jorge Júlvez
- Department of Computer Science and Systems Engineering, University of Zaragoza, Zaragoza, Spain
| | - Alexandru Oarga
- Department of Computer Science and Systems Engineering, University of Zaragoza, Zaragoza, Spain
| | - Tom L Blundell
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Pablo Moreno
- EMBL-EBI, European Bioinformatics Institute, Hinxton, UK
| | - R Andres Floto
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK
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11
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Chiappino-Pepe A, Pandey V, Billker O. Genome reconstructions of metabolism of Plasmodium RBC and liver stages. Curr Opin Microbiol 2021; 63:259-266. [PMID: 34461385 DOI: 10.1016/j.mib.2021.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 08/09/2021] [Accepted: 08/15/2021] [Indexed: 11/18/2022]
Abstract
Genome scale metabolic models (GEMs) offer a powerful means of integrating genome and biochemical information on an organism to make testable predictions of metabolic functions at different conditions and to systematically predict essential genes that may be targeted by drugs. This review describes how Plasmodium GEMs have become increasingly more accurate through the integration of omics and experimental genetic data. We also discuss how GEMs contribute to our increasing understanding of how Plasmodium metabolism is reprogrammed between life cycle stages.
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Affiliation(s)
- Anush Chiappino-Pepe
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Wyss Institute for Biologically Inspired Engineering, Boston, MA 02115, USA; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Vikash Pandey
- Department of Molecular Biology, Umeå University, Umeå, 90187, Sweden; The Laboratory for Molecular Infection Medicine Sweden, Umeå, 90187, Sweden
| | - Oliver Billker
- Department of Molecular Biology, Umeå University, Umeå, 90187, Sweden; The Laboratory for Molecular Infection Medicine Sweden, Umeå, 90187, Sweden
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12
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Serral F, Castello FA, Sosa EJ, Pardo AM, Palumbo MC, Modenutti C, Palomino MM, Lazarowski A, Auzmendi J, Ramos PIP, Nicolás MF, Turjanski AG, Martí MA, Fernández Do Porto D. From Genome to Drugs: New Approaches in Antimicrobial Discovery. Front Pharmacol 2021; 12:647060. [PMID: 34177572 PMCID: PMC8219968 DOI: 10.3389/fphar.2021.647060] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 05/17/2021] [Indexed: 01/31/2023] Open
Abstract
Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline.
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Affiliation(s)
- Federico Serral
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Florencia A Castello
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Ezequiel J Sosa
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - Agustín M Pardo
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - Miranda Clara Palumbo
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Carlos Modenutti
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - María Mercedes Palomino
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - Alberto Lazarowski
- Departamento de Bioquímica Clínica, Instituto de Investigaciones en Fisiopatología y Bioquímica Clínica (INFIBIOC), Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Jerónimo Auzmendi
- Departamento de Bioquímica Clínica, Instituto de Investigaciones en Fisiopatología y Bioquímica Clínica (INFIBIOC), Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Pablo Ivan P Ramos
- Centro de Integração de Dados e Conhecimentos para Saúde (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Brazil
| | - Marisa F Nicolás
- Laboratório Nacional de Computação Científica (LNCC), Petrópolis, Brazil
| | - Adrián G Turjanski
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - Marcelo A Martí
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.,Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Buenos Aires, Argentina
| | - Darío Fernández Do Porto
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
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13
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Vedithi SC, Malhotra S, Acebrón-García-de-Eulate M, Matusevicius M, Torres PHM, Blundell TL. Structure-Guided Computational Approaches to Unravel Druggable Proteomic Landscape of Mycobacterium leprae. Front Mol Biosci 2021; 8:663301. [PMID: 34026836 PMCID: PMC8138464 DOI: 10.3389/fmolb.2021.663301] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 04/12/2021] [Indexed: 02/02/2023] Open
Abstract
Leprosy, caused by Mycobacterium leprae (M. leprae), is treated with a multidrug regimen comprising Dapsone, Rifampicin, and Clofazimine. These drugs exhibit bacteriostatic, bactericidal and anti-inflammatory properties, respectively, and control the dissemination of infection in the host. However, the current treatment is not cost-effective, does not favor patient compliance due to its long duration (12 months) and does not protect against the incumbent nerve damage, which is a severe leprosy complication. The chronic infectious peripheral neuropathy associated with the disease is primarily due to the bacterial components infiltrating the Schwann cells that protect neuronal axons, thereby inducing a demyelinating phenotype. There is a need to discover novel/repurposed drugs that can act as short duration and effective alternatives to the existing treatment regimens, preventing nerve damage and consequent disability associated with the disease. Mycobacterium leprae is an obligate pathogen resulting in experimental intractability to cultivate the bacillus in vitro and limiting drug discovery efforts to repositioning screens in mouse footpad models. The dearth of knowledge related to structural proteomics of M. leprae, coupled with emerging antimicrobial resistance to all the three drugs in the multidrug therapy, poses a need for concerted novel drug discovery efforts. A comprehensive understanding of the proteomic landscape of M. leprae is indispensable to unravel druggable targets that are essential for bacterial survival and predilection of human neuronal Schwann cells. Of the 1,614 protein-coding genes in the genome of M. leprae, only 17 protein structures are available in the Protein Data Bank. In this review, we discussed efforts made to model the proteome of M. leprae using a suite of software for protein modeling that has been developed in the Blundell laboratory. Precise template selection by employing sequence-structure homology recognition software, multi-template modeling of the monomeric models and accurate quality assessment are the hallmarks of the modeling process. Tools that map interfaces and enable building of homo-oligomers are discussed in the context of interface stability. Other software is described to determine the druggable proteome by using information related to the chokepoint analysis of the metabolic pathways, gene essentiality, homology to human proteins, functional sites, druggable pockets and fragment hotspot maps.
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Affiliation(s)
- Sundeep Chaitanya Vedithi
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom,*Correspondence: Sundeep Chaitanya Vedithi,
| | - Sony Malhotra
- Rutherford Appleton Laboratory, Science and Technology Facilities Council, Oxon, United Kingdom
| | | | | | - Pedro Henrique Monteiro Torres
- Laboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Tom L. Blundell
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom,Tom L. Blundell,
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14
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Aromolaran O, Aromolaran D, Isewon I, Oyelade J. Machine learning approach to gene essentiality prediction: a review. Brief Bioinform 2021; 22:6219158. [PMID: 33842944 DOI: 10.1093/bib/bbab128] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/04/2021] [Accepted: 03/17/2021] [Indexed: 12/17/2022] Open
Abstract
Essential genes are critical for the growth and survival of any organism. The machine learning approach complements the experimental methods to minimize the resources required for essentiality assays. Previous studies revealed the need to discover relevant features that significantly classify essential genes, improve on the generalizability of prediction models across organisms, and construct a robust gold standard as the class label for the train data to enhance prediction. Findings also show that a significant limitation of the machine learning approach is predicting conditionally essential genes. The essentiality status of a gene can change due to a specific condition of the organism. This review examines various methods applied to essential gene prediction task, their strengths, limitations and the factors responsible for effective computational prediction of essential genes. We discussed categories of features and how they contribute to the classification performance of essentiality prediction models. Five categories of features, namely, gene sequence, protein sequence, network topology, homology and gene ontology-based features, were generated for Caenorhabditis elegans to perform a comparative analysis of their essentiality prediction capacity. Gene ontology-based feature category outperformed other categories of features majorly due to its high correlation with the genes' biological functions. However, the topology feature category provided the highest discriminatory power making it more suitable for essentiality prediction. The major limiting factor of machine learning to predict essential genes conditionality is the unavailability of labeled data for interest conditions that can train a classifier. Therefore, cooperative machine learning could further exploit models that can perform well in conditional essentiality predictions. SHORT ABSTRACT Identification of essential genes is imperative because it provides an understanding of the core structure and function, accelerating drug targets' discovery, among other functions. Recent studies have applied machine learning to complement the experimental identification of essential genes. However, several factors are limiting the performance of machine learning approaches. This review aims to present the standard procedure and resources available for predicting essential genes in organisms, and also highlight the factors responsible for the current limitation in using machine learning for conditional gene essentiality prediction. The choice of features and ML technique was identified as an important factor to predict essential genes effectively.
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Affiliation(s)
- Olufemi Aromolaran
- Department of Computer and Information Sciences, Covenant University, Ota, Ogun State, Nigeria.,Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
| | - Damilare Aromolaran
- Department of Computer and Information Sciences, Covenant University, Ota, Ogun State, Nigeria.,Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
| | - Itunuoluwa Isewon
- Department of Computer and Information Sciences, Covenant University, Ota, Ogun State, Nigeria.,Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
| | - Jelili Oyelade
- Department of Computer and Information Sciences, Covenant University, Ota, Ogun State, Nigeria.,Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
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15
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Strategies for drug target identification in Mycobacterium leprae. Drug Discov Today 2021; 26:1569-1573. [PMID: 33798649 DOI: 10.1016/j.drudis.2021.03.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 03/01/2021] [Accepted: 03/23/2021] [Indexed: 11/22/2022]
Abstract
Hansen's disease (HD), or leprosy, continues to be endemic in many parts of the world. Although multidrug therapy (MDT) is successful in curing a large number of patients, some of them abandon it because it is a long-term treatment. Therefore, identification of new drug targets in Mycobacterium leprae is considered of high importance. Here, we introduce an overview of in silico and in vitro studies that might be of help in this endeavor. The essentiality of M. leprae proteins is reviewed with discussion of flux balance analysis, gene expression, and knockout articles. Finally, druggability techniques are proposed for the validation of new M. leprae protein targets (see Fig. 1).
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16
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Childs LM, Larremore DB. Network Models for Malaria: Antigens, Dynamics, and Evolution Over Space and Time. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11512-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
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17
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Kaur H, Kalia M, Singh V, Modgil V, Mohan B, Taneja N. In silico identification and characterization of promising drug targets in highly virulent uropathogenic Escherichia coli strain CFT073 by protein-protein interaction network analysis. INFORMATICS IN MEDICINE UNLOCKED 2021. [DOI: 10.1016/j.imu.2021.100704] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
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18
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Sinha S, Lynn AM, Desai DK. Implementation of homology based and non-homology based computational methods for the identification and annotation of orphan enzymes: using Mycobacterium tuberculosis H37Rv as a case study. BMC Bioinformatics 2020; 21:466. [PMID: 33076816 PMCID: PMC7574302 DOI: 10.1186/s12859-020-03794-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 10/01/2020] [Indexed: 02/06/2023] Open
Abstract
Background Homology based methods are one of the most important and widely used approaches for functional annotation of high-throughput microbial genome data. A major limitation of these methods is the absence of well-characterized sequences for certain functions. The non-homology methods based on the context and the interactions of a protein are very useful for identifying missing metabolic activities and functional annotation in the absence of significant sequence similarity. In the current work, we employ both homology and context-based methods, incrementally, to identify local holes and chokepoints, whose presence in the Mycobacterium tuberculosis genome is indicated based on its interaction with known proteins in a metabolic network context, but have not been annotated. We have developed two computational procedures using network theory to identify orphan enzymes (‘Hole finding protocol’) coupled with the identification of candidate proteins for the predicted orphan enzyme (‘Hole filling protocol’). We propose an integrated interaction score based on scores from the STRING database to identify candidate protein sequences for the orphan enzymes from M. tuberculosis, as a case study, which are most likely to perform the missing function. Results The application of an automated homology-based enzyme identification protocol, ModEnzA, on M. tuberculosis genome yielded 56 novel enzyme predictions. We further predicted 74 putative local holes, 6 choke points, and 3 high confidence local holes in the genome using ‘Hole finding protocol’. The ‘Hole-filling protocol’ was validated on the E. coli genome using artificial in-silico enzyme knockouts where our method showed 25% increased accuracy, compared to other methods, in assigning the correct sequence for the knocked-out enzyme amongst the top 10 ranks. The method was further validated on 8 additional genomes. Conclusions We have developed methods that can be generalized to augment homology-based annotation to identify missing enzyme coding genes and to predict a candidate protein for them. For pathogens such as M. tuberculosis, this work holds significance in terms of increasing the protein repertoire and thereby, the potential for identifying novel drug targets.
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Affiliation(s)
- Swati Sinha
- Bioinformatics Institute, Agency for Science, Technology, and Research (A*Star), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore
| | - Andrew M Lynn
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
| | - Dhwani K Desai
- Department of Biology and Department of Pharmacology, Dalhousie University, Halifax, NS, B3H4R2, Canada. .,School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
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19
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Pal S, Sarker N, Qaria M, Tandon K, Akhter Y, Ahmed N. Design of an inhibitor of Helicobacter pylori cholesteryl-α-glucoside transferase critical for bacterial colonization. Helicobacter 2020; 25:e12720. [PMID: 32668502 DOI: 10.1111/hel.12720] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/23/2020] [Accepted: 06/08/2020] [Indexed: 12/09/2022]
Abstract
BACKGROUND Fifty percent of the world's population surves as a host for Helicobacter pylori, gastric cancer causing bacteria, that colonizes the gastric region of digestive tract. It has a remarkable capacity to infect the host stomach for the entire lifetime despite an activated host immune response. METHODS In this study, we have performed the virtual screening analysis of protein-inhibitor binding between the glycosyl transferase enzymes of Helicobacter pylori (CapJ or HP0421) and a corresponding library of inhibitors in the known substrate-binding pockets. We have docked our library of ligands consisting of cholesterol backbone with CapJ protein and identified several ligands' interacting amino acid residues present in active site pocket(s) of the protein. RESULTS In most of the cases, the ligands showed an interaction with the residues of the same pocket of the enzyme. Top three (03) hits were filtered out from the whole data set, which might act as potent inhibitors of the enzyme-substrate reaction. CONCLUSIONS This study describes a new possibility by which colonization of H. pylori can be limited. The reported evidence suggests that comprehensive knowledge and wet laboratory validation of these inhibitors are needed in order to develop them as lead molecules.
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Affiliation(s)
- Soumiya Pal
- Department of Biotechnology, Babasaheb Bhimrao Ambedkar University, Lucknow, India
| | - Nishat Sarker
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka
| | - Majjid Qaria
- Department of Biotechnology and Bioinformatics, University of Hyderabad, Hyderabad, India
| | - Kshitij Tandon
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
| | - Yusuf Akhter
- Department of Biotechnology, Babasaheb Bhimrao Ambedkar University, Lucknow, India
| | - Niyaz Ahmed
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka.,Department of Biotechnology and Bioinformatics, University of Hyderabad, Hyderabad, India
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20
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Ibrahim KA, Helmy OM, Kashef MT, Elkhamissy TR, Ramadan MA. Identification of Potential Drug Targets in Helicobacter pylori Using In Silico Subtractive Proteomics Approaches and Their Possible Inhibition through Drug Repurposing. Pathogens 2020; 9:E747. [PMID: 32932580 PMCID: PMC7558524 DOI: 10.3390/pathogens9090747] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 09/07/2020] [Accepted: 09/10/2020] [Indexed: 12/24/2022] Open
Abstract
The class 1 carcinogen, Helicobacter pylori, is one of the World Health Organization's high priority pathogens for antimicrobial development. We used three subtractive proteomics approaches using protein pools retrieved from: chokepoint reactions in the BIOCYC database, the Kyoto Encyclopedia of Genes and Genomes, and the database of essential genes (DEG), to find putative drug targets and their inhibition by drug repurposing. The subtractive channels included non-homology to human proteome, essentiality analysis, sub-cellular localization prediction, conservation, lack of similarity to gut flora, druggability, and broad-spectrum activity. The minimum inhibitory concentration (MIC) of three selected ligands was determined to confirm anti-helicobacter activity. Seventeen protein targets were retrieved. They are involved in motility, cell wall biosynthesis, processing of environmental and genetic information, and synthesis and metabolism of secondary metabolites, amino acids, vitamins, and cofactors. The DEG protein pool approach was superior, as it retrieved all drug targets identified by the other two approaches. Binding ligands (n = 42) were mostly small non-antibiotic compounds. Citric, dipicolinic, and pyrophosphoric acid inhibited H. pylori at an MIC of 1.5-2.5 mg/mL. In conclusion, we identified potential drug targets in H. pylori, and repurposed their binding ligands as possible anti-helicobacter agents, saving time and effort required for the development of new antimicrobial compounds.
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Affiliation(s)
- Kareem A. Ibrahim
- Department of Microbiology & Immunology, Faculty of Pharmacy, Egyptian Russian University, Cairo 11829, Egypt; (K.A.I.); (T.R.E.)
| | - Omneya M. Helmy
- Department of Microbiology & Immunology, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt; (M.T.K.); (M.A.R.)
| | - Mona T. Kashef
- Department of Microbiology & Immunology, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt; (M.T.K.); (M.A.R.)
| | - Tharwat R. Elkhamissy
- Department of Microbiology & Immunology, Faculty of Pharmacy, Egyptian Russian University, Cairo 11829, Egypt; (K.A.I.); (T.R.E.)
| | - Mohammed A. Ramadan
- Department of Microbiology & Immunology, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt; (M.T.K.); (M.A.R.)
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21
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Garg A, Singhal N, Kumar M. Discerning novel drug targets for treating Mycobacterium avium ss. paratuberculosis-associated autoimmune disorders: an in silico approach. Brief Bioinform 2020; 22:5902595. [PMID: 32895696 DOI: 10.1093/bib/bbaa195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/24/2020] [Accepted: 07/30/2020] [Indexed: 11/13/2022] Open
Abstract
Mycobacterium avium subspecies paratuberculosis (MAP) exhibits 'molecular mimicry' with the human host resulting in several autoimmune diseases such as multiple sclerosis, type 1 diabetes mellitus (T1DM), Hashimoto's thyroiditis, Crohn's disease (CD), etc. The conventional therapy for autoimmune diseases includes immunosuppressants or immunomodulators that treat the symptoms rather than the etiology and/or causative mechanism(s). Eliminating MAP-the etiopathological agent might be a better strategy to treat MAP-associated autoimmune diseases. In this case study, we conducted a systematic in silico analysis to identify the metabolic chokepoints of MAP's mimicry proteins and their interacting partners. The probable inhibitors of chokepoint proteins were identified using DrugBank. DrugBank molecules were stringently screened and molecular interactions were analyzed by molecular docking and 'off-target' binding. Thus, we identified 18 metabolic chokepoints of MAP mimicry proteins and 13 DrugBank molecules that could inhibit three chokepoint proteins viz. katG, rpoB and narH. On the basis of molecular interaction between drug and target proteins finally eight DrugBank molecules, viz. DB00609, DB00951, DB00615, DB01220, DB08638, DB08226, DB08266 and DB07349 were selected and are proposed for treatment of three MAP-associated autoimmune diseases namely, T1DM, CD and multiple sclerosis. Because these molecules are either approved by the Food and Drug Administration or these are experimental drugs that can be easily incorporated in clinical studies or tested in vitro. The proposed strategy may be used to repurpose drugs to treat autoimmune diseases induced by other pathogens.
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22
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Curran DM, Grote A, Nursimulu N, Geber A, Voronin D, Jones DR, Ghedin E, Parkinson J. Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets. eLife 2020; 9:e51850. [PMID: 32779567 PMCID: PMC7419141 DOI: 10.7554/elife.51850] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 07/14/2020] [Indexed: 12/17/2022] Open
Abstract
The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia-present in many filariae-which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.
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Affiliation(s)
- David M Curran
- Program in Molecular Medicine, Hospital for Sick ChildrenTorontoCanada
| | - Alexandra Grote
- Department of Biology, Center for Genomics and Systems Biology, New York UniversityNew YorkUnited States
| | - Nirvana Nursimulu
- Program in Molecular Medicine, Hospital for Sick ChildrenTorontoCanada
- Department of Computer Science, University of TorontoTorontoCanada
| | - Adam Geber
- Department of Biology, Center for Genomics and Systems Biology, New York UniversityNew YorkUnited States
| | | | - Drew R Jones
- Department of Biochemistry and Molecular Pharmacology, New York University School of MedicineNew YorkUnited States
| | - Elodie Ghedin
- Department of Biology, Center for Genomics and Systems Biology, New York UniversityNew YorkUnited States
- Department of Epidemiology, School of Global Public Health, New York UniversityNew YorkUnited States
| | - John Parkinson
- Program in Molecular Medicine, Hospital for Sick ChildrenTorontoCanada
- Department of Computer Science, University of TorontoTorontoCanada
- Department of Biochemistry, University of TorontoTorontoCanada
- Department of Molecular Genetics, University of TorontoTorontoCanada
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23
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Farfán-López M, Espinoza-Culupú A, García-de-la-Guarda R, Serral F, Sosa E, Palomino MM, Fernández Do Porto DA. Prioritisation of potential drug targets against Bartonella bacilliformis by an integrative in-silico approach. Mem Inst Oswaldo Cruz 2020; 115:e200184. [PMID: 32785422 PMCID: PMC7416641 DOI: 10.1590/0074-02760200184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 07/22/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Carrion's disease (CD) is a neglected biphasic illness caused by Bartonella bacilliformis, a Gram-negative bacteria found in the Andean valleys. The spread of resistant strains underlines the need for novel antimicrobials against B. bacilliformis and related bacterial pathogens. OBJECTIVE The main aim of this study was to integrate genomic-scale data to shortlist a set of proteins that could serve as attractive targets for new antimicrobial discovery to combat B. bacilliformis. METHODS We performed a multidimensional genomic scale analysis of potential and relevant targets which includes structural druggability, metabolic analysis and essentiality criteria to select proteins with attractive features for drug discovery. FINDINGS We shortlisted seventeen relevant proteins to develop new drugs against the causative agent of Carrion's disease. Particularly, the protein products of fabI, folA, aroA, trmFO, uppP and murE genes, meet an important number of desirable features that make them attractive targets for new drug development. This data compendium is freely available as a web server (http://target.sbg.qb.fcen.uba.ar/). MAIN CONCLUSION This work represents an effort to reduce the costs in the first phases of B. bacilliformis drug discovery.
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Affiliation(s)
- Mariella Farfán-López
- Laboratorio de Microbiología Molecular y Biotecnología, Facultad de Ciencias Biológicas, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Abraham Espinoza-Culupú
- Laboratorio de Microbiología Molecular y Biotecnología, Facultad de Ciencias Biológicas, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Ruth García-de-la-Guarda
- Laboratorio de Microbiología Molecular y Biotecnología, Facultad de Ciencias Biológicas, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Federico Serral
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Ezequiel Sosa
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - María Mercedes Palomino
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Darío A Fernández Do Porto
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
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24
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Riaz MR, Preston GM, Mithani A. MAPPS: A Web-Based Tool for Metabolic Pathway Prediction and Network Analysis in the Postgenomic Era. ACS Synth Biol 2020; 9:1069-1082. [PMID: 32347714 DOI: 10.1021/acssynbio.9b00397] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Comparative and evolutionary analyses of metabolic networks have a wide range of applications, ranging from research into metabolic evolution through to practical applications in drug development, synthetic biology, and biodegradation. We present MAPPS: Metabolic network Analysis and Pathway Prediction Server (https://mapps.lums.edu.pk), a web-based tool to study functions and evolution of metabolic networks using traditional and 'omics data sets. MAPPS provides diverse functionalities including an interactive interface, graphical visualization of results, pathway prediction and network comparison, identification of potential drug targets, in silico metabolic engineering, host-microbe interactions, and ancestral network building. Importantly, MAPPS also allows users to upload custom data, thus enabling metabolic analyses on draft and custom genomes, and has an 'omics pipeline to filter pathway results, making it relevant in today's postgenomic era.
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Affiliation(s)
- Muhammad Rizwan Riaz
- Department of Biology, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), DHA, Lahore 54792, Pakistan
| | - Gail M. Preston
- Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, U.K
| | - Aziz Mithani
- Department of Biology, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), DHA, Lahore 54792, Pakistan
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25
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Genome-wide screening and in silico gene knockout to predict potential candidates for drug designing against Candida albicans. INFECTION GENETICS AND EVOLUTION 2020; 80:104196. [PMID: 31954918 DOI: 10.1016/j.meegid.2020.104196] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2019] [Revised: 01/13/2020] [Accepted: 01/15/2020] [Indexed: 12/16/2022]
Abstract
C. albicans infections are increasingly becoming a threat to public health with emergence of drug resistant strains. It emphasizes the need to look for alternate drug targets through genome-wide screening. In the present study, whole proteome of C. albicans SC5314 was analyzed in single click target mining workflow of TiDv2. A protein-protein interaction network (PPI) for the resulting putative targets was generated based on String database. Ninety four proteins with higher connectivity (degree ≥ 10) in the network are noted as hub genes. Among them, 24 are observed to be known targets while 70 are novel ones. Further, chokepoint analysis revealed FAS2, FOL1 and ERG5 as chokepoint enzymes in their respective pathways. Subsequently, the chokepoints were selected as prior interest for in silico gene knockout via MATLAB and COBRA Toolbox. In silico gene knockout pointed that FAS2 inhibition reduced the growth rate of pathogen from 0.2879 mmol.gDW-1.h-1 to zero. Furthermore, enzyme inhibition assay of FAS2 with cerulenin strengthen the computational outcome with MIC 1.25 μg/mL. Hence, the study establishes FAS2 as a promising target to design therapeutics against C. albicans.
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26
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Oyelade J, Isewon I, Aromolaran O, Uwoghiren E, Dokunmu T, Rotimi S, Aworunse O, Obembe O, Adebiyi E. Computational Identification of Metabolic Pathways of Plasmodium falciparum using the k-Shortest Path Algorithm. Int J Genomics 2019; 2019:1750291. [PMID: 31662957 PMCID: PMC6791207 DOI: 10.1155/2019/1750291] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 11/28/2018] [Accepted: 07/29/2019] [Indexed: 02/02/2023] Open
Abstract
Plasmodium falciparum, a malaria pathogen, has shown substantial resistance to treatment coupled with poor response to some vaccines thereby requiring urgent, holistic, and broad approach to prevent this endemic disease. Understanding the biology of the malaria parasite has been identified as a vital approach to overcome the threat of malaria. This study is aimed at identifying essential proteins unique to malaria parasites using a reconstructed iPfa genome-scale metabolic model (GEM) of the 3D7 strain of Plasmodium falciparum by filling gaps in the model with nineteen (19) metabolites and twenty-three (23) reactions obtained from the MetaCyc database. Twenty (20) currency metabolites were removed from the network because they have been identified to produce shortcuts that are biologically infeasible. The resulting modified iPfa GEM was a model using the k-shortest path algorithm to identify possible alternative metabolic pathways in glycolysis and pentose phosphate pathways of Plasmodium falciparum. Heuristic function was introduced for the optimal performance of the algorithm. To validate the prediction, the essentiality of the reactions in the reconstructed network was evaluated using betweenness centrality measure, which was applied to every reaction within the pathways considered in this study. Thirty-two (32) essential reactions were predicted among which our method validated fourteen (14) enzymes already predicted in the literature. The enzymatic proteins that catalyze these essential reactions were checked for homology with the host genome, and two (2) showed insignificant similarity, making them possible drug targets. In conclusion, the application of the intelligent search technique to the metabolic network of P. falciparum predicts potential biologically relevant alternative pathways using graph theory-based approach.
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Affiliation(s)
- Jelili Oyelade
- Department of Computer & Information Sciences, Covenant University, Ota, Nigeria
- Covenant University Bioinformatics Research Cluster (CUBRe), Ota, Nigeria
| | - Itunuoluwa Isewon
- Department of Computer & Information Sciences, Covenant University, Ota, Nigeria
- Covenant University Bioinformatics Research Cluster (CUBRe), Ota, Nigeria
| | - Olufemi Aromolaran
- Department of Computer & Information Sciences, Covenant University, Ota, Nigeria
- Covenant University Bioinformatics Research Cluster (CUBRe), Ota, Nigeria
| | - Efosa Uwoghiren
- Department of Computer & Information Sciences, Covenant University, Ota, Nigeria
- Covenant University Bioinformatics Research Cluster (CUBRe), Ota, Nigeria
| | - Titilope Dokunmu
- Covenant University Bioinformatics Research Cluster (CUBRe), Ota, Nigeria
- Department of Biochemistry, Covenant University, Ota, Nigeria
| | - Solomon Rotimi
- Covenant University Bioinformatics Research Cluster (CUBRe), Ota, Nigeria
- Department of Biochemistry, Covenant University, Ota, Nigeria
| | | | - Olawole Obembe
- Department of Biological Sciences, Covenant University, Ota, Nigeria
| | - Ezekiel Adebiyi
- Department of Computer & Information Sciences, Covenant University, Ota, Nigeria
- Covenant University Bioinformatics Research Cluster (CUBRe), Ota, Nigeria
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27
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Gupta R, Verma R, Pradhan D, Jain AK, Umamaheswari A, Rai CS. An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira. PLoS One 2019; 14:e0221446. [PMID: 31430340 PMCID: PMC6701809 DOI: 10.1371/journal.pone.0221446] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 08/06/2019] [Indexed: 11/18/2022] Open
Abstract
Leptospirosis is one of the leading zoonotic infections worldwide. As with other infectious diseases, report of antimicrobial resistance to existing therapeutic arsenal poses challenges in the management of disease. Hence, identification of novel drug targets for the pathogen deems essential. Present study used combined approach of comparative and subtractive genomics to identify putative drug targets. Crucial genes of 16 pathogenic Leptospira strains were filtered and subjected to homology search via target identification tool "TiD". Thereafter, comparative analysis was performed for non-homologous, essential genes to accomplish the broad-spectrum drug target. Consequently, 37 essential genes were found to be conserved in at least 10 strains of Leptospira. Further, prioritization of resultant set of genes revealed 18 were hubs in protein-protein interaction network. Sixteen putative targets among the hub genes were conserved in all strains of Leptospira. Out of sixteen, fourteen were enzymes while 8 were novel and 4 were involved in virulence mechanism. In addition, genome scale metabolic network reconstruction and choke point analysis revealed cobA (porphyrin and chlorophyll metabolism) and thiL (thiamine metabolism) as chokepoints in their respective metabolic pathways. The proposed hub genes could act as putative broad-spectrum drug targets for Leptospira species, however, these putative targets should be validated to ensure them as real one prior to utilizing them for target based lead discovery.
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Affiliation(s)
- Reena Gupta
- University School of Information, Communication & Technology, Guru Gobind Singh Indraprastha University, New Delhi, India
| | - Rashi Verma
- Biomedical Informatics Centre, National Institute of Pathology-Indian Council of Medical Research, New Delhi, India
| | - Dibyabhaba Pradhan
- Computational Genomics Centre, Indian Council of Medical Research, Campus—All India Institute of Medical Sciences, New Delhi, India
| | - Arun Kumar Jain
- Biomedical Informatics Centre, National Institute of Pathology-Indian Council of Medical Research, New Delhi, India
| | - Amineni Umamaheswari
- Department of Bioinformatics, Sri Venkateswara Institute of Medical Sciences, Tirupati, Andhra Pradesh, India
| | - Chandra Shekhar Rai
- University School of Information, Communication & Technology, Guru Gobind Singh Indraprastha University, New Delhi, India
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28
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Sosa EJ, Burguener G, Lanzarotti E, Defelipe L, Radusky L, Pardo AM, Marti M, Turjanski AG, Fernández Do Porto D. Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens. Nucleic Acids Res 2019; 46:D413-D418. [PMID: 29106651 PMCID: PMC5753371 DOI: 10.1093/nar/gkx1015] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 10/16/2017] [Indexed: 12/20/2022] Open
Abstract
Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request.
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Affiliation(s)
- Ezequiel J Sosa
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Germán Burguener
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Esteban Lanzarotti
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Lucas Defelipe
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Leandro Radusky
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Agustín M Pardo
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Marcelo Marti
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Adrián G Turjanski
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
| | - Darío Fernández Do Porto
- IQUIBICEN-CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina.,Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA Ciudad de Buenos Aires, Argentina
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29
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Identification of small molecule enzyme inhibitors as broad-spectrum anthelmintics. Sci Rep 2019; 9:9085. [PMID: 31235822 PMCID: PMC6591293 DOI: 10.1038/s41598-019-45548-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 06/06/2019] [Indexed: 11/18/2022] Open
Abstract
Targeting chokepoint enzymes in metabolic pathways has led to new drugs for cancers, autoimmune disorders and infectious diseases. This is also a cornerstone approach for discovery and development of anthelmintics against nematode and flatworm parasites. Here, we performed omics-driven knowledge-based identification of chokepoint enzymes as anthelmintic targets. We prioritized 10 of 186 phylogenetically conserved chokepoint enzymes and undertook a target class repurposing approach to test and identify new small molecules with broad spectrum anthelmintic activity. First, we identified and tested 94 commercially available compounds using an in vitro phenotypic assay, and discovered 11 hits that inhibited nematode motility. Based on these findings, we performed chemogenomic screening and tested 32 additional compounds, identifying 6 more active hits. Overall, 6 intestinal (single-species), 5 potential pan-intestinal (whipworm and hookworm) and 6 pan-Phylum Nematoda (intestinal and filarial species) small molecule inhibitors were identified, including multiple azoles, Tadalafil and Torin-1. The active hit compounds targeted three different target classes in humans, which are involved in various pathways, including carbohydrate, amino acid and nucleotide metabolism. Last, using representative inhibitors from each target class, we demonstrated in vivo efficacy characterized by negative effects on parasite fecundity in hamsters infected with hookworms.
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30
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Nayak S, Pradhan D, Singh H, Reddy MS. Computational screening of potential drug targets for pathogens causing bacterial pneumonia. Microb Pathog 2019; 130:271-282. [PMID: 30914386 DOI: 10.1016/j.micpath.2019.03.024] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 03/15/2019] [Accepted: 03/19/2019] [Indexed: 12/24/2022]
Abstract
Streptococcus pneumoniae is widely recognized as the main cause of bacterial pneumonia among all age groups. Other important gram-positive, gram-negative and atypical bacteria causing pneumonia majorly infect children and infants. Despite abundant occurrence of bacterial pneumonia, there is no specific antibiotic therapy available. On the other hand non-specific therapies are less effective and may influence bacterial resistance. Therefore, search for novel drug targets for pathogen is highly necessary. The current study suggested novel potential drug targets through the subtractive and comparative genomics approach. Putative drug targets were identified from highly virulent strain of Streptococcus pneumoniae using target identification (TiD) software and compared with other 12 pneumonia causing pathogens. The putative targets were prioritized through druggability analysis, virulence analysis, metabolic pathway enrichment followed by functional annotations and interactome network. Prioritization of 74 drug targets revealed that 42 of them were enzymes which included 29 new targets and seven chokepoint enzymes. Twenty (out of 74) potential targets are proposed as hub genes through interactome analysis and explored their significance in survival of the pathogen. Comparative analysis of 20 hub genes represents that 15 are enzymes and five are non-enzymes. Functional annotation of two chokepoint hub enzymes namely, peptidoglycan bridge formation alanyltransferase MurN (fibB) and PTS mannitol transporter subunit IIA (mltF) were significantly enriched in peptidoglycan biosynthesis and phosphotransferase system (PTS) respectively. Therefore these enzymes would be of prior interest for rational design of targeted therapy against bacterial pneumonia.
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Affiliation(s)
- Subhalaxmi Nayak
- Department of Biotechnology, Thapar Institute of Engineering & Technology, Patiala, Punjab 147004, India; ICMR - AIIMS Computational Genomics Centre, ISRM, Indian Council of Medical Research (ICMR), Ansari Nagar, New Delhi 110029, India
| | - Dibyabhaba Pradhan
- ICMR - AIIMS Computational Genomics Centre, ISRM, Indian Council of Medical Research (ICMR), Ansari Nagar, New Delhi 110029, India
| | - Harpreet Singh
- ICMR - AIIMS Computational Genomics Centre, ISRM, Indian Council of Medical Research (ICMR), Ansari Nagar, New Delhi 110029, India
| | - M Sudhakara Reddy
- Department of Biotechnology, Thapar Institute of Engineering & Technology, Patiala, Punjab 147004, India.
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31
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Kumar H, Kehrer J, Singer M, Reinig M, Santos JM, Mair GR, Frischknecht F. Functional genetic evaluation of DNA house-cleaning enzymes in the malaria parasite: dUTPase and Ap4AH are essential in Plasmodium berghei but ITPase and NDH are dispensable. Expert Opin Ther Targets 2019; 23:251-261. [PMID: 30700216 DOI: 10.1080/14728222.2019.1575810] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 01/25/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND Cellular metabolism generates reactive oxygen species. The oxidation and deamination of the deoxynucleoside triphosphate (dNTP) pool results in the formation of non-canonical, toxic dNTPs that can cause mutations, genome instability, and cell death. House-cleaning or sanitation enzymes that break down and detoxify non-canonical nucleotides play major protective roles in nucleotide metabolism and constitute key drug targets for cancer and various pathogens. We hypothesized that owing to their protective roles in nucleotide metabolism, these house-cleaning enzymes are key drug targets in the malaria parasite. METHODS Using the rodent malaria parasite Plasmodium berghei we evaluate here, by gene targeting, a group of conserved proteins with a putative function in the detoxification of non-canonical nucleotides as potential antimalarial drug targets: they are inosine triphosphate pyrophosphatase (ITPase), deoxyuridine triphosphate pyrophosphatase (dUTPase) and two NuDiX hydroxylases, the diadenosine tetraphosphate (Ap4A) hydrolase and the nucleoside triphosphate hydrolase (NDH). RESULTS While all four proteins are expressed constitutively across the intraerythrocytic developmental cycle, neither ITPase nor NDH are required for parasite viability. dutpase and ap4ah null mutants, on the other hand, are not viable suggesting an essential function for these proteins for the malaria parasite. CONCLUSIONS Plasmodium dUTPase and Ap4A could be drug targets in the malaria parasite.
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Affiliation(s)
- Hirdesh Kumar
- a Integrative Parasitology, Department of Infectious Diseases , University of Heidelberg Medical School , Heidelberg , Germany
| | - Jessica Kehrer
- a Integrative Parasitology, Department of Infectious Diseases , University of Heidelberg Medical School , Heidelberg , Germany
| | - Mirko Singer
- a Integrative Parasitology, Department of Infectious Diseases , University of Heidelberg Medical School , Heidelberg , Germany
| | - Miriam Reinig
- a Integrative Parasitology, Department of Infectious Diseases , University of Heidelberg Medical School , Heidelberg , Germany
| | - Jorge M Santos
- b Instituto de Medicina Molecular , Faculdade de Medicina da Universidade de Lisboa , Lisbon , Portugal
| | - Gunnar R Mair
- a Integrative Parasitology, Department of Infectious Diseases , University of Heidelberg Medical School , Heidelberg , Germany
- b Instituto de Medicina Molecular , Faculdade de Medicina da Universidade de Lisboa , Lisbon , Portugal
- c Department of Biomedical Sciences , 2008 College of Veterinary Medicine, Iowa State University , Ames , IA USA
| | - Friedrich Frischknecht
- a Integrative Parasitology, Department of Infectious Diseases , University of Heidelberg Medical School , Heidelberg , Germany
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32
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Chellapandi P, Prathiviraj R, Prisilla A. Deciphering structure, function and mechanism of Plasmodium IspD homologs from their evolutionary imprints. J Comput Aided Mol Des 2019; 33:419-436. [DOI: 10.1007/s10822-019-00191-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 02/12/2019] [Indexed: 12/17/2022]
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33
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Rout S, Mahapatra RK. Plasmodium falciparum: Multidrug resistance. Chem Biol Drug Des 2019; 93:737-759. [DOI: 10.1111/cbdd.13484] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 01/05/2019] [Accepted: 01/09/2019] [Indexed: 12/25/2022]
Affiliation(s)
- Subhashree Rout
- School of BiotechnologyKIIT University Bhubaneswar Odisha India
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34
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Kabra R, Chauhan N, Kumar A, Ingale P, Singh S. Efflux pumps and antimicrobial resistance: Paradoxical components in systems genomics. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2019; 141:15-24. [PMID: 30031023 PMCID: PMC7173168 DOI: 10.1016/j.pbiomolbio.2018.07.008] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 07/10/2018] [Accepted: 07/15/2018] [Indexed: 01/01/2023]
Abstract
Efflux pumps play a major role in the increasing antimicrobial resistance rendering a large number of drugs of no use. Large numbers of pathogens are becoming multidrug resistant due to inadequate dosage and use of the existing antimicrobials. This leads to the need for identifying new efflux pump inhibitors. Design of novel targeted therapies using inherent complexity involved in the biological network modeling has gained increasing importance in recent times. The predictive approaches should be used to determine antimicrobial activities with high pathogen specificity and microbicidal potency. Antimicrobial peptides, which are part of our innate immune system, have the ability to respond to infections and have gained much attention in making resistant strain sensitive to existing drugs. In this review paper, we outline evidences linking host-directed therapy with the efflux pump activity to infectious disease.
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Affiliation(s)
- Ritika Kabra
- National Centre for Cell Science, NCCS Complex, Ganeshkhind, SP Pune University Campus, Pune 411007, India
| | - Nutan Chauhan
- National Centre for Cell Science, NCCS Complex, Ganeshkhind, SP Pune University Campus, Pune 411007, India
| | - Anurag Kumar
- National Centre for Cell Science, NCCS Complex, Ganeshkhind, SP Pune University Campus, Pune 411007, India
| | - Prajakta Ingale
- National Centre for Cell Science, NCCS Complex, Ganeshkhind, SP Pune University Campus, Pune 411007, India
| | - Shailza Singh
- National Centre for Cell Science, NCCS Complex, Ganeshkhind, SP Pune University Campus, Pune 411007, India.
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35
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Meshram RJ, Goundge MB, Kolte BS, Gacche RN. An in silico approach in identification of drug targets in Leishmania: A subtractive genomic and metabolic simulation analysis. Parasitol Int 2018; 69:59-70. [PMID: 30503238 DOI: 10.1016/j.parint.2018.11.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 10/17/2018] [Accepted: 11/28/2018] [Indexed: 12/26/2022]
Abstract
Leishmaniasis is one of the major health issue in developing countries. The current therapeutic regimen for this disease is less effective with lot of adverse effects thereby warranting an urgent need to develop not only new and selective drug candidates but also identification of effective drug targets. Here we present subtractive genomics procedure for identification of putative drug targets in Leishmania. Comprehensive druggability analysis has been carried out in the current work for identified metabolic pathways and drug targets. We also demonstrate effective metabolic simulation methodology to pinpoint putative drug targets in threonine biosynthesis pathway. Metabolic simulation data from the current study indicate that decreasing flux through homoserine kinase reaction can be considered as a good therapeutic opportunity. The data from current study is expected to show new avenue for designing experimental strategies in search of anti-leishmanial agents.
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Affiliation(s)
- Rohan J Meshram
- Bioinformatics Centre, Savitribai Phule Pune University, Pune 411007, India.
| | - Mayuri B Goundge
- Bioinformatics Centre, Savitribai Phule Pune University, Pune 411007, India
| | - Baban S Kolte
- Bioinformatics Centre, Savitribai Phule Pune University, Pune 411007, India; Department of Biotechnology, Savitribai Phule Pune University, Pune 411007, India
| | - Rajesh N Gacche
- Department of Biotechnology, Savitribai Phule Pune University, Pune 411007, India
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Ramos PIP, Fernández Do Porto D, Lanzarotti E, Sosa EJ, Burguener G, Pardo AM, Klein CC, Sagot MF, de Vasconcelos ATR, Gales AC, Marti M, Turjanski AG, Nicolás MF. An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets. Sci Rep 2018; 8:10755. [PMID: 30018343 PMCID: PMC6050338 DOI: 10.1038/s41598-018-28916-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 06/27/2018] [Indexed: 02/07/2023] Open
Abstract
Klebsiella pneumoniae (Kp) is a globally disseminated opportunistic pathogen that can cause life-threatening infections. It has been found as the culprit of many infection outbreaks in hospital environments, being particularly aggressive towards newborns and adults under intensive care. Many Kp strains produce extended-spectrum β-lactamases, enzymes that promote resistance against antibiotics used to fight these infections. The presence of other resistance determinants leading to multidrug-resistance also limit therapeutic options, and the use of 'last-resort' drugs, such as polymyxins, is not uncommon. The global emergence and spread of resistant strains underline the need for novel antimicrobials against Kp and related bacterial pathogens. To tackle this great challenge, we generated multiple layers of 'omics' data related to Kp and prioritized proteins that could serve as attractive targets for antimicrobial development. Genomics, transcriptomics, structuromic and metabolic information were integrated in order to prioritize candidate targets, and this data compendium is freely available as a web server. Twenty-nine proteins with desirable characteristics from a drug development perspective were shortlisted, which participate in important processes such as lipid synthesis, cofactor production, and core metabolism. Collectively, our results point towards novel targets for the control of Kp and related bacterial pathogens.
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Affiliation(s)
- Pablo Ivan Pereira Ramos
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Bahia, Brazil
- Laboratório Nacional de Computação Científica, Petrópolis, Rio de Janeiro, Brazil
| | - Darío Fernández Do Porto
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Esteban Lanzarotti
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Ezequiel J Sosa
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Germán Burguener
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Agustín M Pardo
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Cecilia C Klein
- Inria Grenoble Rhône-Alpes, Grenoble, France
- Université Claude Bernard Lyon 1, Lyon, France
- Centre for Genomic Regulation (CRG), Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia and Institut de Biomedicina (IBUB), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Marie-France Sagot
- Inria Grenoble Rhône-Alpes, Grenoble, France
- Université Claude Bernard Lyon 1, Lyon, France
| | | | - Ana Cristina Gales
- Laboratório Alerta. Division of Infectious Diseases, Department of Internal Medicine. Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Marcelo Marti
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Adrián G Turjanski
- Plataforma de Bioinformática Argentina (BIA), Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina.
- Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Ciudad Universitaria, Pabellón 2, C1428EHA, Ciudad de Buenos Aires, Argentina.
| | - Marisa F Nicolás
- Laboratório Nacional de Computação Científica, Petrópolis, Rio de Janeiro, Brazil.
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Identification of Antifungal Targets Based on Computer Modeling. J Fungi (Basel) 2018; 4:jof4030081. [PMID: 29973534 PMCID: PMC6162656 DOI: 10.3390/jof4030081] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 06/24/2018] [Accepted: 06/29/2018] [Indexed: 01/07/2023] Open
Abstract
Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host⁻pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.
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Katiyar A, Singh H, Azad KK. Identification of Missing Carbon Fixation Enzymes as Potential Drug Targets in Mycobacterium Tuberculosis. J Integr Bioinform 2018; 15:/j/jib.2018.15.issue-3/jib-2017-0041/jib-2017-0041.xml. [PMID: 30218604 PMCID: PMC6340126 DOI: 10.1515/jib-2017-0041] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2017] [Accepted: 02/08/2018] [Indexed: 01/22/2023] Open
Abstract
Metabolic adaptation to the host environment has been recognized as an essential mechanism of pathogenicity and the growth of Mycobacterium tuberculosis (Mtb) in the lungs for decades. The Mtb uses CO2 as a source of carbon during the dormant or non-replicative state. However, there is a lack of biochemical knowledge of its metabolic networks. In this study, we investigated the CO2 fixation pathways (such as ko00710 and ko00720) most likely involved in the energy production and conversion of CO2 in Mtb. Extensive pathway evaluation of 23 completely sequenced strains of Mtb confirmed the existence of a complete list of genes encoding the relevant enzymes of the reductive tricarboxylic acid (rTCA) cycle. This provides the evidence that an rTCA cycle may function to fix CO2 in this bacterium. We also proposed that as CO2 is plentiful in the lungs, inhibition of CO2 fixation pathways (by targeting the relevant CO2 fixation enzymes) could be used in the expansion of new drugs against the dormant Mtb. In support of the suggested hypothesis, the CO2 fixation enzymes were confirmed as a potential drug target by analyzing a number of attributes necessary to be a good bacterial target.
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Affiliation(s)
- Amit Katiyar
- ICMR-AIIMS Computational Genomics Centre, Indian Council of Medical Research, Ansari Nagar, New Delhi-110029, India.,Department of Biophysics, All India Institute of Medical Sciences, Ansari Nagar, New Delhi-110029, India
| | - Harpreet Singh
- ICMR-AIIMS Computational Genomics Centre, Indian Council of Medical Research, Ansari Nagar, New Delhi-110029, India.,Division of Informatics Systems and Research Management, Indian Council of Medical Research, Ansari Nagar, New Delhi-110029, India, Phone: +91-11-26589556, Fax: +91-11-26588662
| | - Krishna Kant Azad
- Division of Informatics Systems and Research Management, Indian Council of Medical Research, Ansari Nagar, New Delhi-110029, India
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Hossain MU, Omar TM, Alam I, Das KC, Mohiuddin AKM, Keya CA, Salimullah M. Pathway based therapeutic targets identification and development of an interactive database CampyNIBase of Campylobacter jejuni RM1221 through non-redundant protein dataset. PLoS One 2018; 13:e0198170. [PMID: 29883471 PMCID: PMC5993290 DOI: 10.1371/journal.pone.0198170] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 05/15/2018] [Indexed: 11/19/2022] Open
Abstract
The bacterial species Campylobacter jejuni RM1221 (CjR) is the primary cause of campylobacteriosis which poses a global threat for human health. Over the years the efficacy of antibiotic treatment is becoming more fruitless due to the development of multiple drug resistant strains. Therefore, identification of new drug targets is a valuable tool for the development of new treatments for affected patients and can be obtained by targeting essential protein(s) of CjR. We conducted this in silico study in order to identify therapeutic targets by subtractive CjR proteome analysis. The most important proteins of the CjR proteome, which includes chokepoint enzymes, plasmid, virulence and antibiotic resistant proteins were annotated and subjected to subtractive analyses to filter out the CjR essential proteins from duplicate or human homologous proteins. Through the subtractive and characterization analysis we have identified 38 eligible therapeutic targets including 1 potential vaccine target. Also, 12 potential targets were found in interactive network, 5 targets to be dealt with FDA approved drugs and one pathway as potential pathway based drug target. In addition, a comprehensive database 'CampyNIBase' has also been developed. Besides the results of this study, the database is enriched with other information such as 3D models of the identified targets, experimental structures and Expressed Sequence Tag (EST) sequences. This study, including the database might be exploited for future research and the identification of effective therapeutics against campylobacteriosis. URL: (http://nib.portal.gov.bd/site/page/4516e965-8935-4129-8c3f-df95e754c562#Banner).
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Affiliation(s)
- Mohammad Uzzal Hossain
- Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Taimur Md. Omar
- Department of Biotechnology and Genetic Engineering, Life Science Faculty, Mawlana Bhashani Science and Technology University, Santosh, Tangail, Bangladesh
| | - Iftekhar Alam
- Plant Biotechnology Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Keshob Chandra Das
- Molecular Biotechnology Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - A. K. M. Mohiuddin
- Department of Biotechnology and Genetic Engineering, Life Science Faculty, Mawlana Bhashani Science and Technology University, Santosh, Tangail, Bangladesh
| | - Chaman Ara Keya
- Department of Biochemistry and Microbiology, North south University, Bashundhara, Dhaka, Bangladesh
| | - Md. Salimullah
- Molecular Biotechnology Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
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40
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In Silico Knockout Screening of Plasmodium falciparum Reactions and Prediction of Novel Essential Reactions by Analysing the Metabolic Network. BIOMED RESEARCH INTERNATIONAL 2018; 2018:8985718. [PMID: 29789805 PMCID: PMC5896307 DOI: 10.1155/2018/8985718] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 02/04/2018] [Accepted: 02/19/2018] [Indexed: 01/18/2023]
Abstract
Malaria is an infectious disease that affects close to half a million individuals every year and Plasmodium falciparum is a major cause of malaria. The treatment of this disease could be done effectively if the essential enzymes of this parasite are specifically targeted. Nevertheless, the development of the parasite in resisting existing drugs now makes discovering new drugs a core responsibility. In this study, a novel computational model that makes the prediction of new and validated antimalarial drug target cheaper, easier, and faster has been developed. We have identified new essential reactions as potential targets for drugs in the metabolic network of the parasite. Among the top seven (7) predicted essential reactions, four (4) have been previously identified in earlier studies with biological evidence and one (1) has been with computational evidence. The results from our study were compared with an extensive list of seventy-seven (77) essential reactions with biological evidence from a previous study. We present a list of thirty-one (31) potential candidates for drug targets in Plasmodium falciparum which includes twenty-four (24) new potential candidates for drug targets.
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41
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Sakharkar MK, Rajamanickam K, Chandra R, Khan HA, Alhomida AS, Yang J. Identification of novel drug targets in bovine respiratory disease: an essential step in applying biotechnologic techniques to develop more effective therapeutic treatments. Drug Des Devel Ther 2018; 12:1135-1146. [PMID: 29765203 PMCID: PMC5944452 DOI: 10.2147/dddt.s163476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Bovine Respiratory Disease (BRD) is a major problem in cattle production which causes substantial economic loss. BRD has multifactorial aetiologies, is multi-microbial, and several of the causative pathogens are unknown. Consequently, primary management practices such as metaphylactic antimicrobial injections for BRD prevention are used to reduce the incidence of BRD in feedlot cattle. However, this poses a serious threat in the form of development of antimicrobial resistance and demands an urgent need to find novel interventions that could reduce the effects of BRD drastically and also delay/prevent bacterial resistance. MATERIALS AND METHODS We have employed a subtractive genomics approach that helps delineate essential, host-specific, and druggable targets in pathogens responsible for BRD. We also proposed antimicrobials from FDA green and orange book that could be repositioned for BRD. RESULTS We have identified 107 putative targets that are essential, selective and druggable. We have also confirmed the susceptibility of two BRD pathogens to one of the proposed antimicrobials - oxytetracycline. CONCLUSION This approach allows for repositioning drugs known for other infections to BRD, predicting novel druggable targets for BRD infection, and providing a new direction in developing more effective therapeutic treatments for BRD.
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Affiliation(s)
- Meena Kishore Sakharkar
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada
- Correspondence: Meena Kishore Sakharkar; Jian Yang, College of Pharmacy and Nutrition, University of Saskatchewan, 107 Wiggins Road, Saskatoon, SK S7N 5E5, Canada, Email ;
| | - Karthic Rajamanickam
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada
| | - Ramesh Chandra
- Department of Chemistry, University of Delhi, Delhi, India
| | - Haseeb A Khan
- Department of Biochemistry, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Abdullah S Alhomida
- Department of Biochemistry, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Jian Yang
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada
- Correspondence: Meena Kishore Sakharkar; Jian Yang, College of Pharmacy and Nutrition, University of Saskatchewan, 107 Wiggins Road, Saskatoon, SK S7N 5E5, Canada, Email ;
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Cesur MF, Abdik E, Güven-Gülhan Ü, Durmuş S, Çakır T. Computational Systems Biology of Metabolism in Infection. EXPERIENTIA SUPPLEMENTUM (2012) 2018; 109:235-282. [PMID: 30535602 DOI: 10.1007/978-3-319-74932-7_6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
A systems approach to elucidate the effect of infection on cell metabolism provides several opportunities from a better understanding of molecular mechanisms to the identification of potential biomarkers and drug targets. This is obvious from the fact that we have witnessed the accelerated use of computational systems biology in the last five years to study metabolic changes in pathogen and/or host cells in response to infection. In this chapter, we aim to present a comprehensive review of the recent research by focusing on genome-scale metabolic network models of pathogen-host systems and genome-wide metabolomics and fluxomics analysis of infected cells.
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Affiliation(s)
- Müberra Fatma Cesur
- Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey
| | - Ecehan Abdik
- Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey
| | - Ünzile Güven-Gülhan
- Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey
| | - Saliha Durmuş
- Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey
| | - Tunahan Çakır
- Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey.
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Carey MA, Papin JA, Guler JL. Novel Plasmodium falciparum metabolic network reconstruction identifies shifts associated with clinical antimalarial resistance. BMC Genomics 2017; 18:543. [PMID: 28724354 PMCID: PMC5518114 DOI: 10.1186/s12864-017-3905-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 06/27/2017] [Indexed: 02/06/2023] Open
Abstract
Background Malaria remains a major public health burden and resistance has emerged to every antimalarial on the market, including the frontline drug, artemisinin. Our limited understanding of Plasmodium biology hinders the elucidation of resistance mechanisms. In this regard, systems biology approaches can facilitate the integration of existing experimental knowledge and further understanding of these mechanisms. Results Here, we developed a novel genome-scale metabolic network reconstruction, iPfal17, of the asexual blood-stage P. falciparum parasite to expand our understanding of metabolic changes that support resistance. We identified 11 metabolic tasks to evaluate iPfal17 performance. Flux balance analysis and simulation of gene knockouts and enzyme inhibition predict candidate drug targets unique to resistant parasites. Moreover, integration of clinical parasite transcriptomes into the iPfal17 reconstruction reveals patterns associated with antimalarial resistance. These results predict that artemisinin sensitive and resistant parasites differentially utilize scavenging and biosynthetic pathways for multiple essential metabolites, including folate and polyamines. Our findings are consistent with experimental literature, while generating novel hypotheses about artemisinin resistance and parasite biology. We detect evidence that resistant parasites maintain greater metabolic flexibility, perhaps representing an incomplete transition to the metabolic state most appropriate for nutrient-rich blood. Conclusion Using this systems biology approach, we identify metabolic shifts that arise with or in support of the resistant phenotype. This perspective allows us to more productively analyze and interpret clinical expression data for the identification of candidate drug targets for the treatment of resistant parasites. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3905-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Maureen A Carey
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, School of Medicine, Charlottesville, USA
| | - Jason A Papin
- Department of Biomedical Engineering, University of Virginia, Charlottesville, USA.
| | - Jennifer L Guler
- Department of Biology, University of Virginia, Charlottesville, USA. .,Division of Infectious Diseases and International Health, University of Virginia, School of Medicine, Charlottesville, USA.
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Okombo J, Chibale K. Insights into Integrated Lead Generation and Target Identification in Malaria and Tuberculosis Drug Discovery. Acc Chem Res 2017. [PMID: 28636311 PMCID: PMC5518282 DOI: 10.1021/acs.accounts.6b00631] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
New, safe and effective drugs are urgently needed to treat and control malaria and tuberculosis, which affect millions of people annually. However, financial return on investment in the poor settings where these diseases are mostly prevalent is very minimal to support market-driven drug discovery and development. Moreover, the imminent loss of therapeutic lifespan of existing therapies due to evolution and spread of drug resistance further compounds the urgency to identify novel effective drugs. However, the advent of new public-private partnerships focused on tropical diseases and the recent release of large data sets by pharmaceutical companies on antimalarial and antituberculosis compounds derived from phenotypic whole cell high throughput screening have spurred renewed interest and opened new frontiers in malaria and tuberculosis drug discovery. This Account recaps the existing challenges facing antimalarial and antituberculosis drug discovery, including limitations associated with experimental animal models as well as biological complexities intrinsic to the causative pathogens. We enlist various highlights from a body of work within our research group aimed at identifying and characterizing new chemical leads, and navigating these challenges to contribute toward the global drug discovery and development pipeline in malaria and tuberculosis. We describe a catalogue of in-house efforts toward deriving safe and efficacious preclinical drug development candidates via cell-based medicinal chemistry optimization of phenotypic whole-cell medium and high throughput screening hits sourced from various small molecule chemical libraries. We also provide an appraisal of target-based screening, as invoked in our laboratory for mechanistic evaluation of the hits generated, with particular focus on the enzymes within the de novo pyrimidine biosynthetic and hemoglobin degradation pathways, the latter constituting a heme detoxification process and an associated cysteine protease-mediated hydrolysis of hemoglobin. We further expound on the recombinant enzyme assays, heme fractionation experiments, and genomic and chemoproteomic methods that we employed to identify Plasmodium falciparum falcipain 2 (PfFP2), hemozoin formation, phosphatidylinositol 4-kinase (PfPI4K) and Mycobacterium tuberculosis cytochrome bc1 complex as the targets of the antimalarial chalcones, pyrido[1,2-a]benzimidazoles, aminopyridines, and antimycobacterial pyrrolo[3,4-c]pyridine-1,3(2H)-diones, respectively. In conclusion, we argue for the expansion of chemical space through exploitation of privileged natural product scaffolds and diversity-oriented synthesis, as well as the broadening of druggable spaces by exploiting available protein crystal structures, -omics data, and bioinformatics infrastructure to explore hitherto untargeted spaces like lipid metabolism and protein kinases in P. falciparum. Finally, we audit the merits of both target-based and whole-cell phenotypic screening in steering antimalarial and antituberculosis chemical matter toward populating drug discovery pipelines with new lead molecules.
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Affiliation(s)
- John Okombo
- Department
of Chemistry, University of Cape Town, Rondebosch 7701, South Africa
| | - Kelly Chibale
- Department
of Chemistry, University of Cape Town, Rondebosch 7701, South Africa
- South
African Medical Research Council Drug Discovery and Development Research
Unit, Drug Discovery and Development Centre (H3D), Department of Chemistry
and Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Rondebosch 7701, South Africa
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Hossain MU, Khan MA, Hashem A, Islam MM, Morshed MN, Keya CA, Salimullah M. Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration. Front Microbiol 2016; 7:1817. [PMID: 27920755 PMCID: PMC5118456 DOI: 10.3389/fmicb.2016.01817] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Accepted: 10/28/2016] [Indexed: 11/13/2022] Open
Abstract
Background:Shigella flexneri is a gram negative bacteria that causes the infectious disease “shigellosis.” S. flexneri is responsible for developing diarrhea, fever, and stomach cramps in human. Antibiotics are mostly given to patients infected with shigella. Resistance to antibiotics can hinder its treatment significantly. Upon identification of essential therapeutic targets, vaccine and drug could be effective therapy for the treatment of shigellosis. Methods: The study was designed for the identification and qualitative characterization for potential drug targets from S. flexneri by using the subtractive proteome analysis. A set of computational tools were used to identify essential proteins those are required for the survival of S. flexneri. Total proteome (13,503 proteins) of S. flexneri was retrieved from NCBI and further analyzed by subtractive channel analysis. After identification of the metabolic proteins we have also performed its qualitative characterization to pave the way for the identification of promising drug targets. Results: Subtractive analysis revealed that a list of 53 targets of S. flexneri were human non-homologous essential metabolic proteins that might be used for potential drug targets. We have also found that 11 drug targets are involved in unique pathway. Most of these proteins are cytoplasmic, can be used as broad spectrum drug targets, can interact with other proteins and show the druggable properties. The functionality and drug binding site analysis suggest a promising effective way to design the new drugs against S. flexneri. Conclusion: Among the 53 therapeutic targets identified through this study, 13 were found highly potential as drug targets based on their physicochemical properties whilst only one was found as vaccine target against S. flexneri. The outcome might also be used as module as well as circuit design in systems biology.
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Affiliation(s)
- Mohammad Uzzal Hossain
- Department of Biotechnology and Genetic Engineering, Life Science Faculty, Mawlana Bhashani Science and Technology University Tangail, Bangladesh
| | - Md Arif Khan
- Department of Science and Humanities, Military Institute of Science and Technology, Mirpur Cantonment Dhaka, Bangladesh
| | - Abu Hashem
- Microbial Biotechnology Division, National Institute of Biotechnology Savar, Bangladesh
| | - Md Monirul Islam
- Department of Biotechnology and Genetic Engineering, Life Science Faculty, Mawlana Bhashani Science and Technology University Tangail, Bangladesh
| | - Mohammad Neaz Morshed
- Department of Science and Humanities, Military Institute of Science and Technology, Mirpur Cantonment Dhaka, Bangladesh
| | - Chaman Ara Keya
- Department of Biochemistry and Microbiology, North South University Bashundhara, Dhaka, Bangladesh
| | - Md Salimullah
- Molecular Biotechnology Division, National Institute of Biotechnology Savar, Bangladesh
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Wallqvist A, Fang X, Tewari SG, Ye P, Reifman J. Metabolic host responses to malarial infection during the intraerythrocytic developmental cycle. BMC SYSTEMS BIOLOGY 2016; 10:58. [PMID: 27502771 PMCID: PMC4977726 DOI: 10.1186/s12918-016-0291-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2016] [Accepted: 06/16/2016] [Indexed: 12/23/2022]
Abstract
BACKGROUND The malarial parasite Plasmodium falciparum undergoes a complex life cycle, including an intraerythrocytic developmental cycle, during which it is metabolically dependent on the infected human red blood cell (RBC). To describe whole cell metabolic activity within both P. falciparum and RBCs during the asexual reproduction phase of the intraerythrocytic developmental cycle, we developed an integrated host-parasite metabolic modeling framework driven by time-dependent gene expression data. RESULTS We validated the model by reproducing the experimentally determined 1) stage-specific production of biomass components and their precursors in the parasite and 2) metabolite concentration changes in the medium of P. falciparum-infected RBC cultures. The model allowed us to explore time- and strain-dependent P. falciparum metabolism and hypothesize how host cell metabolism alters in response to malarial infection. Specifically, the metabolic analysis showed that uninfected RBCs that coexist with infected cells in the same culture decrease their production of 2,3-bisphosphoglycerate, an oxygen-carrying regulator, reducing the ability of hemoglobin in these cells to release oxygen. Furthermore, in response to parasite-induced oxidative stress, infected RBCs downgraded their glycolytic flux by using the pentose phosphate pathway and secreting ribulose-5-phosphate. This mechanism links individually observed experimental phenomena, such as glycolytic inhibition and ribulose-5-phosphate secretion, to the oxidative stress response. CONCLUSIONS Although the metabolic model does not incorporate regulatory mechanisms per se, alterations in gene expression levels caused by regulatory mechanisms are manifested in the model as altered metabolic states. This provides the model the capability to capture complex multicellular host-pathogen metabolic interactions of the infected RBC culture. The system-level analysis revealed complex relationships such as how the parasite can reduce oxygen release in uninfected cells in the presence of infected RBCs as well as the role of different metabolic pathways involved in the oxidative stress response of infected RBCs.
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Affiliation(s)
- Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD, 21702, USA
| | - Xin Fang
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD, 21702, USA
| | - Shivendra G Tewari
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD, 21702, USA
| | - Ping Ye
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD, 21702, USA
| | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD, 21702, USA.
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Drug Target Identification and Prioritization for Treatment of Ovine Foot Rot: An In Silico Approach. Int J Genomics 2016; 2016:7361361. [PMID: 27379247 PMCID: PMC4917682 DOI: 10.1155/2016/7361361] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 05/16/2016] [Indexed: 02/06/2023] Open
Abstract
Ovine foot rot is an infection of the feet of sheep, mainly caused by Dichelobacter nodosus. In its virulent form, it is highly contagious and debilitating, causing significant losses in the form of decline in wool growth and quality and poor fertility. Current methods of treatment are ineffective in complete eradication. Effective antibiotic treatment of foot rot is hence necessary to ensure better outcomes during control phases by reduction in culling count and the possibility of carriers of the infection. Using computational approaches, we have identified a set of 297 proteins that are essential to the D. nodosus and nonhomologous with sheep proteins. These proteins may be considered as potential vaccine candidates or drug targets for designing antibiotics against the bacterium. This core set of drug targets have been analyzed for pathway annotation to identify 67 proteins involved in unique bacterial pathways. Choke-point analysis on the drug targets identified 138 choke-point proteins, 29 involved in unique bacterial pathways. Subcellular localization was also predicted for each target to identify the ones that are membrane associated or secreted extracellularly. In addition, a total of 13 targets were identified that are common in at least 10 pathogenic bacterial species.
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Preston S, Jabbar A, Gasser RB. A perspective on genomic-guided anthelmintic discovery and repurposing using Haemonchus contortus. INFECTION GENETICS AND EVOLUTION 2016; 40:368-373. [DOI: 10.1016/j.meegid.2015.06.029] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Revised: 06/28/2015] [Accepted: 06/29/2015] [Indexed: 02/02/2023]
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Gupta M, Prasad Y, Sharma SK, Jain CK. Identification of Phosphoribosyl-AMP cyclohydrolase, as drug target and its inhibitors in Brucella melitensis bv. 1 16M using metabolic pathway analysis. J Biomol Struct Dyn 2016; 35:287-299. [DOI: 10.1080/07391102.2015.1137229] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Money Gupta
- Department of Biotechnology, Jaypee Institute of Information Technology, A-10, Sector-62, Noida, Uttar Pradesh 201307, India
| | - Yamuna Prasad
- Department of Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi 110016, India
| | - Sanjeev Kumar Sharma
- Department of Biotechnology, Jaypee Institute of Information Technology, A-10, Sector-62, Noida, Uttar Pradesh 201307, India
| | - Chakresh Kumar Jain
- Department of Biotechnology, Jaypee Institute of Information Technology, A-10, Sector-62, Noida, Uttar Pradesh 201307, India
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50
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Gasser RB, Schwarz EM, Korhonen PK, Young ND. Understanding Haemonchus contortus Better Through Genomics and Transcriptomics. ADVANCES IN PARASITOLOGY 2016; 93:519-67. [PMID: 27238012 DOI: 10.1016/bs.apar.2016.02.015] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Parasitic roundworms (nematodes) cause substantial mortality and morbidity in animals globally. The barber's pole worm, Haemonchus contortus, is one of the most economically significant parasitic nematodes of small ruminants worldwide. Although this and related nematodes can be controlled relatively well using anthelmintics, resistance against most drugs in common use has become a major problem. Until recently, almost nothing was known about the molecular biology of H. contortus on a global scale. This chapter gives a brief background on H. contortus and haemonchosis, immune responses, vaccine research, chemotherapeutics and current problems associated with drug resistance. It also describes progress in transcriptomics before the availability of H. contortus genomes and the challenges associated with such work. It then reviews major progress on the two draft genomes and developmental transcriptomes of H. contortus, and summarizes their implications for the molecular biology of this worm in both the free-living and the parasitic stages of its life cycle. The chapter concludes by considering how genomics and transcriptomics can accelerate research on Haemonchus and related parasites, and can enable the development of new interventions against haemonchosis.
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Affiliation(s)
- R B Gasser
- The University of Melbourne, Parkville, VIC, Australia
| | - E M Schwarz
- The University of Melbourne, Parkville, VIC, Australia; Cornell University, Ithaca, NY, United States
| | - P K Korhonen
- The University of Melbourne, Parkville, VIC, Australia
| | - N D Young
- The University of Melbourne, Parkville, VIC, Australia
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