Identification Of Putative Drug Targets Research Articles

In silico Identification of Putative Drug Targets in Mycobacterium ulcerans Virulence Proteins

Background: Buruli ulcer (BU), caused by Mycobacterium ulcerans is a neglected tropical disease characterized by necrotic skin lesions. Antibiotic therapy and excision of the lesions are the treatments for this chronic disease. During the management of the disease, the emergence of drug resistance in these bacilli is a major challenge. Therefore, there is a need to identify new drug targets against this important pathogen. Objective: The study aimed to investigate novel drug targets exploring virulence factors of M. ulcerans by in silico analysis. Methods: Virulence proteins encoded by the chromosome of Mycobacterium ulcerans strain Agy99 were retrieved and analyzed for their cellular localization, human non-homology and essentiality. Further, proteins were analyzed for their physio-chemical characterization, drug resistance analysis, protein interaction analysis, metabolic pathway prediction, and druggability prediction by various databases and online software to find their suitability as drug targets. The structure of the predicted drug targets was also modeled and validated. Among three predicted drug targets, MUL_4536 was subjected to molecular docking with some known inhibitor compounds also. Receptor-ligand complex with the highest binding energy was selected for molecular dynamic (MD) simulation to determine the structural stability of the complex. Results: Three virulence proteins MUL_4536, MUL_3640, and MUL_2329 encoding enzymes iso-citrate lyase, lysine-N-oxygenase, pup-protein ligase, respectively were predicted as a drug target against M. ulcerans. Isocitrate lyase has been identified as a potential drug target in many other mycobacterial and non-mycobacterial diseases. Lysine-N-oxygenase is the enzyme of mycobactin biosynthesis pathway and pup-protein ligase is associated with the pup-proteasome system. Proteins of these pathways have been studied as attractive drug targets in previous research works, which further support our predictions. Conclusion: Our computational analysis predicted new drug targets, which could be used to design drugs against M. ulcerans. However, these predicted proteins require further experimental validation for their potential use as drug targets.

Evolutionary potential ofthe monkeypox genome arising from interactions with human APOBEC3 enzymes.

APOBEC3, an enzyme subfamily that plays a role in virus restriction by generating mutations at particular DNA motifs or mutational 'hotspots', can drive viral mutagenesis with host-specific preferential hotspot mutations contributing to pathogen variation. While previous analysis of viral genomes from the 2022 Mpox (formerly Monkeypox) disease outbreak has shown a high frequency of C>T mutations at TC motifs, suggesting recent mutations are human APOBEC3-mediated, how emerging monkeypox virus (MPXV) strains will evolve as a consequence of APOBEC3-mediated mutations remains unknown. By measuring hotspot under-representation, depletion at synonymous sites, and a combination of the two, we analyzed APOBEC3-driven evolution in human poxvirus genomes, finding varying hotspot under-representation patterns. While the native poxvirus molluscum contagiosum exhibits a signature consistent with extensive coevolution with human APOBEC3, including depletion of TC hotspots, variola virus shows an intermediate effect consistent with ongoing evolution at the time of eradication. MPXV, likely the result of recent zoonosis, showed many genes with more TC hotspots than expected by chance (over-representation) and fewer GC hotspots than expected (under-representation). These results suggest the MPXV genome: (1) may have evolved in a host with a particular APOBEC GC hotspot preference, (2) has inverted terminal repeat (ITR) regions-which may be exposed to APOBEC3 for longer during viral replication-and longer genes likely to evolve faster, and therefore (3) has a heightened potential for future human APOBEC3-meditated evolution as the virus spreads in the human population. Our predictions of MPXV mutational potential can both help guide future vaccine development and identification of putative drug targets and add urgency to the task of containing human Mpox disease transmission and uncovering the ecology of the virus in its reservoir host.

Identification of Putative Drug Targets in Highly Resistant Gram-Negative Bacteria; and Drug Discovery Against Glycyl-tRNA Synthetase as a New Target.

Gram-negative bacterial infections are on the rise due to the high prevalence of multidrug-resistant bacteria, and efforts must be made to identify novel drug targets and then new antibiotics. In the upstream part, we retrieved the genome sequences of 4 highly resistant Gram-negative bacteria (e.g., Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterobacter cloacae). The core proteins were assessed to find common, cytoplasmic, and essential proteins with no similarity to the human proteome. Novel drug targets were identified using DrugBank, and their sequence conservancy was evaluated. Protein Data Bank files and STRING interaction networks were assessed. Finally, the aminoacylation cavity of glycyl-tRNA synthetase (GlyQ) was virtually screened to identify novel inhibitors using AutoDock Vina and the StreptomeDB library. Ligands with high binding affinity were clustered, and then the pharmacokinetics properties of therapeutic agents were investigated. A total of 6 common proteins (e.g., RP-L28, RP-L30, RP-S20, RP-S21, Rnt, and GlyQ) were selected as novel and widespread drug targets against highly resistant Gram-negative superbugs based on different criteria. In the downstream analysis, virtual screening revealed that Rimocidin, Flavofungin, Chaxamycin, 11,11'-O-dimethyl-14'-deethyl-14'-methylelaiophylin, and Platensimycin were promising hit compounds against GlyQ protein. Finally, 11,11'-O-dimethyl-14'-deethyl-14'-methylelaiophylin was identified as the best potential inhibitor of GlyQ protein. This compound showed high absorption capacity in the human intestine. The results of this study provide 6 common putative new drug targets against 4 highly resistant and Gram-negative bacteria. Moreover, we presented 5 different hit compounds against GlyQ protein as a novel therapeutic target. However, further in vitro and in vivo studies are needed to explore the bactericidal effects of proposed hit compounds against these superbugs.

Network approaches for modeling the effect of drugs and diseases.

The network approach is quickly becoming a fundamental building block of computational methods aiming at elucidating the mechanism of action (MoA) and therapeutic effect of drugs. By modeling the effect of drugs and diseases on different biological networks, it is possible to better explain the interplay between disease perturbations and drug targets as well as how drug compounds induce favorable biological responses and/or adverse effects. Omics technologies have been extensively used to generate the data needed to study the mechanisms of action of drugs and diseases. These data are often exploited to define condition-specific networks and to study whether drugs can reverse disease perturbations. In this review, we describe network data mining algorithms that are commonly used to study drug’s MoA and to improve our understanding of the basis of chronic diseases. These methods can support fundamental stages of the drug development process, including the identification of putative drug targets, the in silico screening of drug compounds and drug combinations for the treatment of diseases. We also discuss recent studies using biological and omics-driven networks to search for possible repurposed FDA-approved drug treatments for SARS-CoV-2 infections (COVID-19).

Thrombospondin-1 CD47 Signalling: From Mechanisms to Medicine.

Recent advances provide evidence that the cellular signalling pathway comprising the ligand-receptor duo of thrombospondin-1 (TSP1) and CD47 is involved in mediating a range of diseases affecting renal, vascular, and metabolic function, as well as cancer. In several instances, research has barely progressed past pre-clinical animal models of disease and early phase 1 clinical trials, while for cancers, anti-CD47 therapy has emerged from phase 2 clinical trials in humans as a crucial adjuvant therapeutic agent. This has important implications for interventions that seek to capitalize on targeting this pathway in diseases where TSP1 and/or CD47 play a role. Despite substantial progress made in our understanding of this pathway in malignant and cardiovascular disease, knowledge and translational gaps remain regarding the role of this pathway in kidney and metabolic diseases, limiting identification of putative drug targets and development of effective treatments. This review considers recent advances reported in the field of TSP1-CD47 signalling, focusing on several aspects including enzymatic production, receptor function, interacting partners, localization of signalling, matrix-cellular and cell-to-cell cross talk. The potential impact that these newly described mechanisms have on health, with a particular focus on renal and metabolic disease, is also discussed.

Modeling Novel Putative Drugs and Vaccine Candidates against Tick-Borne Pathogens: A Subtractive Proteomics Approach.

Ticks and tick-borne pathogens (TBPs) continuously causing substantial losses to the public and veterinary health sectors. The identification of putative drug targets and vaccine candidates is crucial to control TBPs. No information has been recorded on designing novel drug targets and vaccine candidates based on proteins. Subtractive proteomics is an in silico approach that utilizes extensive screening for the identification of novel drug targets or vaccine candidates based on the determination of potential target proteins available in a pathogen proteome that may be used effectively to control diseases caused by these infectious agents. The present study aimed to investigate novel drug targets and vaccine candidates by utilizing subtractive proteomics to scan the available proteomes of TBPs and predict essential and non-host homologous proteins required for the survival of these diseases causing agents. Subtractive proteome analysis revealed a list of fifteen essential, non-host homologous, and unique metabolic proteins in the complete proteome of selected pathogens. Among these therapeutic target proteins, three were excluded due to the presence in host gut metagenome, eleven were found to be highly potential drug targets, while only one was found as a potential vaccine candidate against TBPs. The present study may provide a foundation to design potential drug targets and vaccine candidates for the effective control of infections caused by TBPs.

CRDS: Consensus Reverse Docking System for target fishing.

Identification of putative drug targets is a critical step for explaining the mechanism of drug action against multiple targets, finding new therapeutic indications for existing drugs and unveiling the adverse drug reactions. One important approach is to use the molecular docking. However, its widespread utilization has been hindered by the lack of easy-to-use public servers. Therefore, it is vital to develop a streamlined computational tool for target prediction by molecular docking on a large scale. We present a fully automated web tool named Consensus Reverse Docking System (CRDS), which predicts potential interaction sites for a given drug. To improve hit rates, we developed a strategy of consensus scoring. CRDS carries out reverse docking against 5254 candidate protein structures using three different scoring functions (GoldScore, Vina and LeDock from GOLD version 5.7.1, AutoDock Vina version 1.1.2 and LeDock version 1.0, respectively), and those scores are combined into a single score named Consensus Docking Score (CDS). The web server provides the list of top 50 predicted interaction sites, docking conformations, 10 most significant pathways and the distribution of consensus scores. The web server is available at http://pbil.kaist.ac.kr/CRDS. Supplementary data are available at Bioinformatics online.

Proteome Mining for the Identification of Putative Drug Targets For Human Pathogen Clostridium Tetani

Background: Clostridium tetani are rod-like, anaerobic types of pathogenic bacteria of the genus Clostridium. It is Gram-positive in nature and appears as a tennis racket or drumsticks on staining with the dye. Tetanus is a neuromuscular disease wherein the Clostridium tetani exotoxin produces muscle fits in the host. Tetanus is the second leading cause of worldwide deaths occurring from the family of immunization-preventable diseases. Methods: In this research, subtractive proteome analysis of C. tetani was performed to identify putative drug targets. The proteins were subjected to blast analysis against Homo sapiens to exclude homologous proteins. The database of Essential Genes was used to determine the essential proteins of the pathogen. These basic proteins were additionally analyzed to anticipate the corresponding metabolic pathways. Results: Cellular localization analysis was carried out to determine the possibility of the protein presence in the outer membrane. The study has recognized 29 essential genes and 20 unique pathways of 2314 proteins as potential drug targets. There are 29 essential proteins, out of which, 3 membrane proteins were also identified as putative drug targets. Conclusion: Virtual screening in contrast to these proteins can be valuable in the identification of novel clinical compounds for the C. tetani infections in Homo sapiens.

Recent Aspects on the Pathogenesis Mechanism, Animal Models and Novel Therapeutic Interventions for Middle East Respiratory Syndrome Coronavirus Infections.

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is an emerging zoonotic virus considered as one of the major public threat with a total number of 2 298 laboratory-confirmed cases and 811 associated deaths reported by World Health Organization as of January 2019. The transmission of the virus was expected to be from the camels found in Middle Eastern countries via the animal and human interaction. The genome structure provided information about the pathogenicity and associated virulent factors present in the virus. Recent studies suggested that there were limited insight available on the development of novel therapeutic strategies to induce immunity against the virus. The severities of MERS-CoV infection highlight the necessity of effective approaches for the development of various therapeutic remedies. Thus, the present review comprehensively and critically illustrates the recent aspects on the epidemiology of the virus, the structural and functional features of the viral genome, viral entry and transmission, major mechanisms of pathogenesis and associated virulent factors, current animal models, detection methods and novel strategies for the development of vaccines against MERS-CoV. The review further illustrates the molecular and computational virtual screening platforms which provide insights for the identification of putative drug targets and novel lead molecules toward the development of therapeutic remedies.

An in silico approach in identification of drug targets in Leishmania: A subtractive genomic and metabolic simulation analysis

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.

Prioritizing and modelling of putative drug target proteins of Candida albicans by systems biology approach.

Candida albicans (Candida albicans) is one of the major sources of nosocomial infections in humans which may prove fatal in 30% of cases. The hospital acquired infection is very difficult to treat affectively due to the presence of drug resistant pathogenic strains, therefore there is a need to find alternative drug targets to cure this infection. In silico and computational level frame work was used to prioritize and establish antifungal drug targets of Candida albicans. The identification of putative drug targets was based on acquiring 5090 completely annotated genes of Candida albicans from available databases which were categorized into essential and non-essential genes. The result indicated that 9% of proteins were essential and could become potential candidates for intervention which might result in pathogen eradication. We studied cluster of orthologs and the subtractive genomic analysis of these essential proteins against human genome was made as a reference to minimize the side effects. It was seen that 14% of Candida albicans proteins were evolutionary related to the human proteins while 86% are non-human homologs. In the next step of compatible drug target selections, the non-human homologs were sequentially compared to the human microbiome data to minimize the potential effects against gut flora which accumulated to 38% of the essential genome. The sub-cellular localization of these candidate proteins in fungal cellular systems indicated that 80% of them are cytoplasmic, 10% are mitochondrial and the remaining 10% are associated with the cell wall. The role of these non-human and non-gut flora putative target proteins in Candida albicans biological pathways was studied. Due to their integrated and critical role in Candida albicans replication cycle, four proteins were selected for molecular modeling. For drug designing and development, four high quality and reliable protein models with more than 70% sequence identity were constructed. These proteins are used for the docking studies of the known and new ligands (unpublished data). Our study will be an effective framework for drug target identifications of pathogenic microbial strains and development of new therapies against the infections they cause.

Identification of putative drug targets and annotation of unknown proteins in Tropheryma whipplei

Tropheryma whipplei (T. whipplei) is the causative agent of Whipple’s disease and blood culture-negative endocarditis. Due to the variability of symptoms, the disease is often poorly diagnosed.Treatment for this bacterial infection is often lengthy, and improper uptake of antibiotics has resulted in relapses in many patients. In the present study, using available bioinformatic tools and databases such as the Cluster Database at High Identity with Tolerance (CD-HIT), the Basic Local Alignment Search Tool for proteins (BLASTp), the Database of Essential Genes (DEG), and the DrugBank database, 13 putative drug targets were identified in T. whipplei by subtractive genome analysis that could be targeted with currently available drugs (experimental or approved). Further, a 3D model was generated for one of these putative drug targets, the T. whipplei DNA ligase, and in silico docking was performed with pyridochromanone and adenosine-derived inhibitors using the AutoDock Vina. Additionally, many of the T. whipplei protein sequences in the National Center for Biotechnology Information (NCBI) protein database were unknown/uncurated. Using available web servers e.g. the KEGG Automatic Annotation Server (KAAS), the BLASTp, the Conserved Domain Architecture Retrieval Tool (CDAT) and the Protein families (Pfam), the function/remote/domain homology for nearly 80% of these uncurated protein sequences were annotated. The data obtained in the present study will aid physicians and researchers alike in curbing this bacterial infection.

Novel Bioengineered Three-Dimensional Human Intestinal Model for Long-Term Infection of Cryptosporidium parvum.

Cryptosporidium spp. are apicomplexan parasites of global importance that cause human diarrheal disease. In vitro culture models that may be used to study this parasite and that have physiological relevance to in vivo infection remain suboptimal. Thus, the pathogenesis of cryptosporidiosis remains poorly characterized, and interventions for the disease are limited. In this study, we evaluated the potential of a novel bioengineered three-dimensional (3D) human intestinal tissue model (which we developed previously) to support long-term infection by Cryptosporidium parvum Infection was assessed by immunofluorescence assays and confocal and scanning electron microscopy and quantified by quantitative reverse transcription-PCR. We found that C. parvum infected and developed in this tissue model for at least 17 days, the extent of the study time used in the present study. Contents from infected scaffolds could be transferred to fresh scaffolds to establish new infections for at least three rounds. Asexual and sexual stages and the formation of new oocysts were observed during the course of infection. Additionally, we observed ablation, blunting, or distortion of microvilli in infected epithelial cells. Ultimately, a 3D model system capable of supporting continuous Cryptosporidium infection will be a useful tool for the study of host-parasite interactions, identification of putative drug targets, screening of potential interventions, and propagation of genetically modified parasites.

Comparative genomics study for identification of putative drug targets in Salmonella typhi Ty2

Typhoid presents a major health concern in developing countries with an estimated annual infection rate of 21 million. The disease is caused by Salmonella typhi, a pathogenic bacterium acquiring multiple drug resistance. We aim to identify proteins that could prove to be putative drug targets in the genome of S. typhi str. Ty2. We employed comparative and subtractive genomics to identify targets that are absent in humans and are essential to S. typhi Ty2. We concluded that 46 proteins essential to pathogen are absent in the host genome. Filtration on the basis of drug target prioritization singled out 20 potentially therapeutic targets. Their absence in the host and specificity to S. typhi Ty2 makes them ideal targets for treating typhoid in Homo sapiens. 3D structures of two of the final target enzymes, MurA and MurB have been predicted via homology modeling which are then used for a docking study.

Identification of putative drug targets in Vancomycin-resistant Staphylococcus aureus (VRSA) using computer aided protein data analysis

Vancomycin-resistant Staphylococcus aureus (VRSA) is a Gram-positive, facultative aerobic bacterium which is evolved from the extensive exposure of Vancomycin to Methicillin resistant S. aureus (MRSA) that had become the most common cause of hospital and community-acquired infections. Due to the emergence of different antibiotic resistance strains, there is an exigency to develop novel drug targets to address the provocation of multidrug-resistant bacteria. In this study, in-silico genome subtraction methodology was used to design potential and pathogen specific drug targets against VRSA. Our study divulged 1987 proteins from the proteome of 34,549 proteins, which have no homologues in human genome after sequential analysis through CD-HIT and BLASTp. The high stringency analysis of the remaining proteins against database of essential genes (DEG) resulted in 169 proteins which are essential for S. aureus. Metabolic pathway analysis of human host and pathogen by KAAS at the KEGG server sorted out 19 proteins involved in unique metabolic pathways. 26 human non-homologous membrane-bound essential proteins including 4 which were also involved in unique metabolic pathway were deduced through PSORTb, CELLO v.2.5, ngLOC. Functional classification of uncharacterized proteins through SVMprot derived 7 human non-homologous membrane-bound hypothetical essential proteins. Study of potential drug target against Drug Bank revealed pbpA-penicillin-binding protein 1 and hypothetical protein MQW_01796 as the best drug target candidate. 2D structure was predicted by PRED-TMBB, 3D structure and functional analysis was also performed. Protein–protein interaction network of potential drug target proteins was analyzed by using STRING. The identified drug targets are expected to have great potential for designing novel drugs against VRSA infections and further screening of the compounds against these new targets may result in the discovery of novel therapeutic compounds that can be effective against Vancomycin resistant S. aureus.

Identification of putative drug targets for human sperm-egg interaction defect using protein network approach.

BackgroundSperm-egg interaction defect is a significant cause of in-vitro fertilization failure for infertile cases. Numerous molecular interactions in the form of protein-protein interactions mediate the sperm-egg membrane interaction process. Recent studies have demonstrated that in addition to experimental techniques, computational methods, namely protein interaction network approach, can address protein-protein interactions between human sperm and egg. Up to now, no drugs have been detected to treat sperm-egg interaction disorder, and the initial step in drug discovery research is finding out essential proteins or drug targets for a biological process. The main purpose of this study is to identify putative drug targets for human sperm-egg interaction deficiency and consider if the detected essential proteins are targets for any known drugs using protein-protein interaction network and ingenuity pathway analysis.ResultsWe have created human sperm-egg protein interaction networks with high confidence, including 106 nodes and 415 interactions. Through topological analysis of the network with calculation of some metrics, such as connectivity and betweenness centrality, we have identified 13 essential proteins as putative drug targets. The potential drug targets are from integrins, fibronectins, epidermal growth factor receptors, collagens and tetraspanins protein families. We evaluated these targets by ingenuity pathway analysis, and the known drugs for the targets have been detected, and the possible effective role of the drugs on sperm-egg interaction defect has been considered. These results showed that the drugs ocriplasmin (Jetrea©), gefitinib (Iressa©), erlotinib hydrochloride (Tarceva©), clingitide, cetuximab (Erbitux©) and panitumumab (Vectibix©) are possible candidates for efficacy testing for the treatment of sperm-egg interaction deficiency. Further experimental validation can be carried out to confirm these results.ConclusionWe have identified the first potential list of drug targets for human sperm-egg interaction defect using the protein interaction network approach. The essential proteins or potential drug targets were found using topological analysis of the protein network. These putative targets are promising for further experimental validation. These study results, if validated, may develop drug discovery techniques for sperm-egg interaction defect and also improve assisted reproductive technologies to avoid in-vitro fertilization failure.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0186-7) contains supplementary material, which is available to authorized users.

INSILICO PROTEOME SCREENING TO IDENTIFY PROSPECTIVE DRUG TARGETS IN BACILLUS ANTHRACIS

Various Insilico based genome screening methods helped us in identifying the key drug targets for a pathogen. The accuracy of the predictions are systematically based on the benchmarks at different stages of methodology and the kind of dataset which is considered for the study. In the current study, we made an effort to screen the entire proteome of Bacillus anthracis for identification of putative drug targets. B. anthracis is the causautive agent for anthrax disease. Instead of genome sequence, the metabolically classified proteome of B. anthracis from JCVI-CMR database was considered for the present study. The entire proteome is been categorized into 25 different metabolisms and in each sub-categorised metabolisms respective protein sequences were retrieved and subjected to screening against Database of Essential Genes (DEG) and Human-Basic Local Alignment Search Tool (H-BLAST) databases. In total 136 essential genes/proteins were obtained from the DEGp (protein) screening whereas 145 Non-Human Homologs (NHHs) were predicted. The identified 145 NHHs are further subjected to criteria based selection to identify the most suitable, functional, putative drug targets. The 8 common hits of both DEG and H-BLAST were considered to be better potential targets as they justify the criteria of being an essential gene/protein, non-human homolog, availability of the 3D structure in PDB and having a significant functional role in the cellular biochemical processes.

Complete genome-wide screening and subtractive genomic approach revealed new virulence factors, potential drug targets against bio-war pathogen Brucella melitensis 16M

Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes) to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50%) to Silicibacter pomeroyi DUF1285 family protein (2RE3). A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the glycerol structural analogs from the PubChem database. We identified five best inhibitors with strong affinities, stable interactions, and also with reliable drug-like properties. Hence, these leads might be used as the most effective inhibitors of modeled protein. The outcome of the present work of virtual screening of putative gene targets might facilitate design of potential drugs for better treatment against brucellosis.

Identification of Putative Drug Targets and Vaccine Candidates for Pathogens Causing Atherosclerosis

Atherosclerosis is a chronic inflammatory artery disease, responsible for both cardiovascular (heart) and cerebrovascular (brain) stroke with high morbidity and mortality worldwide. Infectious pathogens such as Chlamydophila pneumoniae, Porphyromonas gingivalis and Helicobacter pylori are shown to be associated with the disease in recent epidemiological studies. Therefore, identification of common drug targets and vaccine candidates against these three pathogens would be vital towards therapy and management of atherosclerosis. Chlamydophila pneumonia was selected as a reference organism due to its predominant role in atherosclerosis. Implementing comparative genomic approach, subtractive genomic approach, metabolic pathway analysis, non-homologous gut flora analysis and domain search analysis, 35 common putative drug targets were identified against pathogens of atherosclerosis. Subcellular localization studies were performed and identified UvrABC protein as vaccine candidate. Metabolic pathway analysis has showed that, out of 35 drug targets, 14 enzymes were participating in key pathways linked to pathogen’s survival, proliferation and pathogenesis without any alternative mechanism to synthesize the product. The gut microbiota analysis was performed to identify the drug targets which do not affect the microbiota in the humans. Domain search was performed for the identified 14 drug targets using Pfam and SMART databases and protein network analysis was carried out using STRING and Cytoscape v3.2.0. The drug targets and vaccine candidates proposed in the present study would serve as basis to design potent inhibitors and subunit vaccines through in silico approach for combating atherosclerosis caused by infectious pathogens.

An interactomic approach for identification of putative drug targets in Listeria monocytogenes.

A wide variety of human population is infected with Listeria monocytogenes, which causes listeriosis, a deadly disease with mortality rate of about 30%. The major hindrance to cure listeriosis is the unavailability of specific or selectable drug targets. At present, antibiotics used to cure the disease are not specific and insufficient to manage the disease efficiently. Therefore, in order to search specific drugs, here, we used interactome analysis to search specific drug targets which may provide novel templates for drug designing having better efficacy without any potential adverse effects. The complete genome of L. monocytogenes having 2846 proteins has been analysed. We found 11 proteins as putative drug targets. The sequence and interactome analyses revealed that 11 proteins are non-homologous to human, but essential for pathogen and hence may be considered as potential therapeutic targets.