Identification and characterization of potential drug targets by subtractive genome analyses of methicillin resistant Staphylococcus aureus

Subtractive genomics study for the identification of therapeutic targets against Cronobacter sakazakii: A threat to infants

Cronobacter sakazakii is an opportunistic pathogen that has been associated with severe infection in neonates such as necrotizing enterocolitis (NEC), neonatal meningitis, and bacteremia. This pathogen can survive in a relatively dry environment, especially in powdered infant formula (PIF). Unfortunately, conventional drugs that were once effective against C. sakazakii are gradually losing their efficacy due to rising antibiotic resistance. In this study, a subtractive genomic approach was followed in order to identify potential therapeutic targets in the pathogen. The whole proteome of the pathogen was filtered through a step-by-step process, which involved removing paralogous proteins, human homologs, sequences that are less essential for survival, proteins with shared metabolic pathways, and proteins that are located in cells other than the cytoplasmic membrane. As a result, nine novel drug targets were identified. Further, the analysis also unveiled that the FDA-approved drug Terbinafine can be repurposed against the Glutathione/l-cysteine transport system ATP-binding/permease protein CydC of C. sakazakii. Moreover, molecular docking and dynamics studies of Terbinafine and CydC suggested that this drug can be used to treat C. sakazakii infection in neonates. However, for clinical purposes further in vitro and in vivo studies are necessary.

Genome mining of Mycobacterium tuberculosis: targeting SufD as a novel drug candidate through in silico characterization and inhibitor screening

Tuberculosis (TB) stands as the second most fatal infectious disease globally, causing 1.3 million deaths in 2022. The resurgence of TB and the alarming rise of antibiotic resistance demand urgent call to develop novel antituberculosis drugs. Despite concerted efforts to control TB, the disease persists and spreads rapidly on a global scale. Targeting stress response pathways in Mycobacterium tuberculosis (Mtb) has become imperative to achieve complete eradication. This study employs subtractive genomics to identify and prioritize potential drug targets among the hypothetical proteins of Mtb, focusing on indispensable pathways. Amongst 177 essential hypothetical proteins, 152 were nonhomologous to human. These proteins participated in 34 pathways, and a 20-fold enrichment of SUF pathway genes led to its selection as a target pathway. Fe-S clusters are fundamental, widely distributed protein cofactors involved in vital cellular processes. The survival of Mtb in a hypoxic environment relies on the iron-sulfur (Fe-S) cluster biogenesis pathway for the repair of damaged Fe-S clusters. It also protects pathogen against drugs, ensuring controlled iron utilization and contributing to drug resistance. In Mtb, six proteins of Fe-S cluster assembly pathway are encoded by the suf operon. The present study was focused on SufD because of its role in iron acquisition and prevention of Fenton reaction. The research further delves into the in silico characterization of SufD, utilizing bioinformatics tools for sequence and structure based analysis. The protein's structural features, including the identification of conserved regions, motifs, and 3D structure prediction enhanced functional annotation. Target based virtual screening of compounds from the ChEMBL database resulted in 12 inhibitors with best binding affinities. Drug likeness and ADMET profiling of potential inhibitors identified promising compounds with favorable drug-like properties. The study also involved cloning in SUMO-pRSF-Duet1 expression vector, overexpression, and purification of recombinant SufD from E. coli BL21 (DE3) cells. Optimization of expression conditions resulted in soluble production, and subsequent purification highlighting the efficacy of the SUMO fusion system for challenging Mtb proteins in E. coli. These findings provide valuable insights into pharmacological targets for future experimental studies, holding promise for the development of targeted therapy against Mtb.

Antibiotic resistance in Neisseria gonorrhoeae: broad-spectrum drug target identification using subtractive genomics

Neisseria gonorrhoeae is a Gram-negative aerobic diplococcus bacterium that primarily causes sexually transmitted infections through direct human sexual contact. It is a major public health threat due to its impact on reproductive health, the widespread presence of antimicrobial resistance, and the lack of a vaccine. In this study, we used a bioinformatics approach and performed subtractive genomic methods to identify potential drug targets against the core proteome of N. gonorrhoeae (12 strains). In total, 12,300 protein sequences were retrieved, and paralogous proteins were removed using CD-HIT. The remaining sequences were analyzed for non-homology against the human proteome and gut microbiota, and screened for broad-spectrum analysis, druggability, and anti-target analysis. The proteins were also characterized for unique interactions between the host and pathogen through metabolic pathway analysis. Based on the subtractive genomic approach and subcellular localization, we identified one cytoplasmic protein, 2Fe-2S iron-sulfur cluster binding domain-containing protein (NGFG RS03485), as a potential drug target. This protein could be further exploited for drug development to create new medications and therapeutic agents for the treatment of N. gonorrhoeae infections.

Potential therapeutic targets for combating Mycoplasma genitalium

Mycoplasma genitalium (M. genitalium) has emerged as a sexually transmitted infection (STI) all over the world in the last three decades. It has been identified as a cause of male urethritis, and there is now evidence that it also causes cervicitis and pelvic inflammatory disease in women. However, the precise role of M. genitalium in diseases such as pelvic inflammatory disease, and infertility is unknown, and more research is required. It is a slow-growing organism, and with the advent of the nucleic acid amplification test (NAAT), more studies are being conducted and knowledge about the pathogenicity of this organism is being elucidated. The accumulation of data has improved our understanding of the pathogen and its role in disease transmission. Despite the widespread use of single-dose azithromycin in the sexual health field, M. genitalium is known to rapidly develop antibiotic resistance. As a result, the media frequently refer to this pathogen as the "new STI superbug." Despite their rarity, antibiotics available today have serious side effects. As the cure rates for first-line antimicrobials have decreased, it is now a challenge to determine the effective antimicrobial therapy. In this review, we summarise recent M. genitalium research and investigate potential therapeutic targets for combating this pathogen.

Identification of New Drug Target in Staphylococcus lugdunensis by Subtractive Genomics Analysis and Their Inhibitors through Molecular Docking and Molecular Dynamic Simulation Studies

Staphylococcus lugdunensis is a coagulase-negative, Gram-positive, and human pathogenic bacteria. S. lugdunensis is the causative agent of diseases, such as native and prosthetic valve endocarditis, meningitis, septic arthritis, skin abscesses, brain abscess, breast abscesses, spondylodiscitis, post-surgical wound infections, bacteremia, and peritonitis. S. lugdunensis displays resistance to beta-lactam antibiotics due to the production of beta-lactamases. This study aimed to identify potential novel essential, human non-homologous, and non-gut flora drug targets in the S. lugdunensis strain N920143, and to evaluate the potential inhibitors of drug targets. The method was concerned with a homology search between the host and the pathogen proteome. Various tools, including the DEG (database of essential genes) for the essentiality of proteins, the KEGG for pathways analysis, CELLO V.2.5 for cellular localization prediction, and the drug bank database for predicting the druggability potential of proteins, were used. Furthermore, a similarity search with gut flora proteins was performed. A DNA-binding response-regulator protein was identified as a novel drug target against the N920143 strain of S. lugdunensis. The three-dimensional structure of the drug target was modelled and validated with the help of online tools. Furthermore, ten thousand drug-like compounds were retrieved from the ZINC15 database. The molecular docking approach for the DNA-binding response-regulator protein identified ZINC000020192004 and ZINC000020530348 as the most favorable compounds to interact with the active site residues of the drug target. These two compounds were subjected to an MD simulation study. Our analysis revealed that the identified compounds revealed more stable behavior when bound to the drug target DNA-binding response-regulator protein than the apostate.

Leveraging big data bioinformatics approaches to extract knowledge from Staphylococcus aureus public omics data

Staphylococcus aureus is a notorious pathogen posing challenges in the medical industry due to drug resistance and biofilm formation. The horizon of knowledge on S. aureus pathogenesis has expanded with the advancement of data-driven bioinformatics techniques. Mining information from sequenced genomes and their expression data is an economic approach that alleviates wastage of resources and redundancy in experiments. The current review covers how big data bioinformatics has been used in the analysis of S. aureus from publicly available -omics data to uncover mechanisms of infection and inhibition. Particularly, advances in the past two decades in biomarker discovery, host responses, phenotype identification, consolidation of information, and drug development are discussed highlighting the challenges and shortcomings. Overall, the review summarizes the diverse aspects of scrupulous re-analysis of S. aureus proteomic and transcriptomic expression datasets retrieved from public repositories in terms of the efforts taken, benefits offered, and follow-up actions. The detailed review thus serves as a reference and aid for (i) Computational biologists by briefing the approaches utilized for bacterial omics re-analysis concerning S. aureus and (ii) Experimental biologists by elucidating the potential of bioinformatics in biological research to generate reliable postulates in a prompt and economical manner.

Computational characterization and analysis of molecular sequence data of Elizabethkingia meningoseptica

OBJECTIVE

Elizabethkingia meningoseptica is a multidrug resistance strain which primarily causes meningitis in neonates and immunocompromised patients. Being a nosocomial infection causing agent, less information is available in literature, specifically, about its genomic makeup and associated features. An attempt is made to study them through bioinformatics tools with respect to compositions, embedded periodicities, open reading frames, origin of replication, phylogeny, orthologous gene clusters analysis and pathways.

RESULTS

Complete DNA and protein sequence pertaining to E. meningoseptica were thoroughly analyzed as part of the study. E. meningoseptica G4076 genome showed 7593 ORFs it is GC rich. Fourier based analysis showed the presence of typical three base periodicity at the genome level. Putative origin of replication has been identified. Phylogenetically, E. meningoseptica is relatively closer to E. anophelis compared to other Elizabethkingia species. A total of 2606 COGs were shared by all five Elizabethkingia species. Out of 3391 annotated proteins, we could identify 18 unique ones involved in metabolic pathway of E. meningoseptica and this can be an initiation point for drug designing and development. Our study is novel in the aspect in characterizing and analyzing the whole genome data of E. meningoseptica.

Identification of Putative Vaccine and Drug Targets against the Methicillin-Resistant Staphylococcus aureus by Reverse Vaccinology and Subtractive Genomics Approaches

Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic pathogen and responsible for causing life-threatening infections. The emergence of hypervirulent and multidrug-resistant (MDR) S. aureus strains led to challenging issues in antibiotic therapy. Consequently, the morbidity and mortality rates caused by S. aureus infections have a substantial impact on health concerns. The current worldwide prevalence of MRSA infections highlights the need for long-lasting preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine candidates and drug target proteins against the 16 strains of MRSA using reverse vaccinology and subtractive genomics approaches. Using the reverse vaccinology approach, 4 putative antigenic proteins were identified; among these, PrsA and EssA proteins were found to be more promising vaccine candidates. We applied a molecular docking approach of selected 8 drug target proteins with the drug-like molecules, revealing that the ZINC4235426 as potential drug molecule with favorable interactions with the target active site residues of 5 drug target proteins viz., biotin protein ligase, HPr kinase/phosphorylase, thymidylate kinase, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate-L-lysine ligase, and pantothenate synthetase. Thus, the identified proteins can be used for further rational drug or vaccine design to identify novel therapeutic agents for the treatment of multidrug-resistant staphylococcal infection.

An integrated in silico based subtractive genomics and reverse vaccinology approach for the identification of novel vaccine candidate and chimeric vaccine against XDR Salmonella typhi H58

Salmonella typhi is notorious for causing enteric fever which is also known as typhoid fever. It emerged as an extreme drug resistant strain that requires urgent attention to prevent its global spread. Statistically, about 11-17 million typhoid illnesses are reported worldwide annually. The only alternative approach for the control of this illness is proper vaccination. However, available typhoid vaccine has certain limitations such as poor long-term efficacy, and non-recommendation for below 6 years children, which opens the avenues for designing new vaccines to overcome such limitations. Computational-based reverse vaccinology along with subtractive genomics analysis is one of the robust approaches used for the prioritization of vaccine candidates through direct screening of genome sequence assemblies. In the current study, we have successfully designed a peptide-based novel antigen chimeric vaccine candidate against the XDR strain of S. typhi H58. The pipeline revealed four peptides from WP_001176621.1 i.e., peptidoglycan-associated lipoprotein Pal and two peptides from WP_000747548.1 i.e., OmpA family lipoprotein as promising target for the induction of immune response against S. typhi. The six epitopes from both proteins were found as immunogenic, antigenic, virulent, highly conserved, nontoxic, and non-allergenic among whole Salmonella H58 proteome. Furthermore, the binding interaction between a chimeric vaccine and human population alleles was unveiled through structure-based studies. So far, these proteins have never been characterized as vaccine targets against S. typhi. The current study proposed that construct V2 could be a significant vaccine candidate against S. typhi H58. However, to ascertain this, future experimental holistic studies are recommended as follow-up.

Potential Drug Targets Identification Against Clostridioides Difficile (CD) and Characterization of Indispensable Proteins by a Subtractive Genomics Approach Followed by Virtual Screening

Background:

Clostridioides difficile (CD) is an enteric multi-drug resistant pathogenic bacterium. CD-associated infections are the leading cause of nosocomial diarrhea that can further lead to pseudomembranous colitis, toxic mega-colon or sepsis with greater mortality and morbidity risks. CD infection possesses higher rates of recurrence due to its greater resistance to antibiotics. Considering its higher rates of recurrence, it has become a major burden on healthcare facilities. Therefore, there is a dire need to identify novel drug targets to combat antibiotic resistance of Clostridioides difficile.

Objective:

To identify and propose new and novel drug targets against the Clostridioides difficile.

Methods:

In the current study, a computational subtractive genomics approach was applied to obtain a set of potential drug targets that exist in the multi-drug resistant strain of Clostridioides difficile. Here, the uncharacterized proteins were studied as potential drug targets. The methodology involved several bioinformatics databases and tools. The druggable proteins sequences were retrieved based on non-homology with host proteome and essentiality for the survival of the pathogen. The uncharacterized proteins were functionally characterized using different computational tools, and sub-cellular localization was also predicted. The metabolic pathways were analyzed using the KEGG database. Eventually, the druggable proteome has been fetched using sequence similarity with the already available drug targets present in the DrugBank database. These druggable proteins were further explored for the structural details to identify drug candidates.

Results :

A priority list of potential drug targets was provided with the help of the applied method on the complete proteome set of the C. difficile. Moreover, the drug-like compounds have been screened against the potential drug targets to prioritize potential drug candidates. To facilitate the need for drug targets and therapies, the study proposed five potential protein drug targets, out of which three proposed drug targets were subjected to homology modeling to explore their structural and functional activities

Conclusion:

In conclusion, we proposed three unique, unexplored drug targets against C. difficile. The structure-based methods were applied and resulted in a list of top-scoring compounds as potential inhibitors to proposed drug targets.

Integrated bioinformatics based subtractive genomics approach to decipher the therapeutic function of hypothetical proteins from Salmonella typhi XDR H-58 strain

Purpose

The efficacy of drugs against Salmonella infection have compromised due to emerging XDR H58 strain. There is a dire need to find novel antimicrobial drug targets as well as drug candidates to cure by the XDR strain of Salmonella. It is observed that the complete genome sequence of the XDR H58 strain contains a large number of hypothetical proteins with unknown cellular and biological functions. Hence, it is indispensable to annotate these proteins functionally as well as structurally to identify novel drug targets.

Methods

In the current study, a comparative genomics and proteomics based approach was applied to find the novel drug targets in XDR strain while comparing the MDR and NR strains of Salmonella typhi.

Results

The characterization of ~ 350 hypothetical proteins were performed through determination of their physio-chemical properties, sub-cellular localization, functional annotation, and structure-based studies. As a result, only five proteins were prioritized as essential, druggable, and virulent proteins. Moreover, only one protein i.e. WP_000916613.1 was functionally annotated with high confidence and subjected to further structure-based analysis.

Conclusion

The current study presents a hypothetical protein from the XDR S. typhi proteome as a potential pharmacological target against which novel therapeutic candidates may be predicted. The outcome of the current study may lead to formulate a general set of pipelines for better understanding of the role of hypothetical proteins in pathogenesis of not only Salmonella but also for other pathogens.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10529-021-03219-6.

Identification of a Novel Therapeutic Target against XDR Salmonella Typhi H58 Using Genomics Driven Approach Followed Up by Natural Products Virtual Screening

Typhoid fever is caused by a pathogenic, rod-shaped, flagellated, and Gram-negative bacterium known as Salmonella Typhi. It features a polysaccharide capsule that acts as a virulence factor and deceives the host immune system by protecting phagocytosis. Typhoid fever remains a major health concern in low and middle-income countries, with an estimated death rate of ~200,000 per annum. However, the situation is exacerbated by the emergence of the extensively drug-resistant (XDR) strain designated as H58 of S. Typhi. The emergence of the XDR strain is alarming, and it poses serious threats to public health due to the failure of the current therapeutic regimen. A relatively newer computational method called subtractive genomics analyses has been widely applied to discover novel and new drug targets against pathogens, particularly drug-resistant ones. The method involves the gradual reduction of the complete proteome of the pathogen, leading to few potential and novel drug targets. Thus, in the current study, a subtractive genomics approach was applied against the Salmonella XDR strain to identify potential drug targets. The current study predicted four prioritized proteins (i.e., Colanic acid biosynthesis acetyltransferase wcaB, Shikimate dehydrogenase aroE, multidrug efflux RND transporter permease subunit MdtC, and pantothenate synthetase panC) as potential drug targets. Though few of the prioritized proteins are treated in the literature as the established drug targets against other pathogenic bacteria, these drug targets are identified here for the first time against S. Typhi (i.e., S. Typhi XDR). The current study aimed at drawing attention to new drug targets against S. Typhi that remain largely unexplored. One of the prioritized drug targets, i.e., Colanic acid biosynthesis acetyltransferase, was predicted as a unique, new drug target against S. Typhi XDR. Therefore, the Colanic acid was further explored using structure-based techniques. Additionally, ~1000 natural compounds were docked with Colanic acid biosynthesis acetyltransferase, resulting in the prediction of seven compounds as potential lead candidates against the S. Typhi XDR strain. The ADMET properties and binding energies via the docking program of these seven compounds characterized them as novel drug candidates. They may potentially be used for the development of future drugs in the treatment of Typhoid fever.

Prioritization of potential drug targets and antigenic vaccine candidates against Klebsiella aerogenes using the computational subtractive proteome-driven approach

Klebsiella aerogenes is a multidrug-resistant Gram-negative bacterium that causes nosocomial infections. The organism showed resistance to most of the conventional antibiotics available. Because of the high resistance of the species, the treatment of K. aerogenes is difficult. These species are resistant to third-generation cephalosporins due to the production of chromosomal beta-lactams with cephalosporin activity. The lack of better treatment and the development of therapeutic resistance in hospitals hinders better/new broad-spectrum-based treatment against this pathogen. This study identifies potential drug targets/vaccine candidates through a computational subtractive proteome-driven approach. This method is used to predict proteins that are not homologous to humans and human symbiotic intestinal flora. The resultant proteome of K. aerogenes was further searched for proteins, which are essential, virulent, and determinants of antibiotic/drug resistance. Subsequently, their druggability properties were also studied. The data set was reduced based on its presence in the pathogen-specific metabolic pathways. The subtractive proteome analysis predicted 13 proteins as potential drug targets for K. aerogenes. Furthermore, these target proteins were annotated based on their spectrum of activity, cellular localization, and antigenicity properties, which ensured that they are potent candidates for broad-spectrum antibiotic and vaccine design. The results open up new opportunities for designing and manufacturing powerful antigenic vaccines against K. aerogenes and the detection and release of new and active drugs against K. aerogenes without altering the gut microbiome.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-021-00068-9.

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.

Core proteome mediated therapeutic target mining and multi-epitope vaccine design for Helicobacter pylori

Helicobacter pylori is a Gram-negative spiral-shaped bacterium that infects half of the human population worldwide and causes chronic inflammation. In the present study, we used the art of computational biology for therapeutic drug targets identification and a multi-epitope vaccine against multi-strains of H. pylori. For drug target identification, we used different tools and softwares to identify human non-homologous but pathogen essential proteins, with virulent properties and involved in unique metabolic pathways of H. pylori. For this purpose, the core proteome of 84 strains of H. pylori was retrieved from EDGAR 2.3 database. There were 59,808 proteins sequences in these strains. Duplicates and paralogous protein sequence removal was followed by human non-homologous protein miningPathogen essential and virulent proteins were subjected to pathway analysis Subcellular localization of the virulent proteins was predicted and druggability was also checked, leading to 30 druggable targets based on their similarity with the approved drug targets in Drugbank. For immunoinformatics analysis, we selected two outer membrane proteins (HPAKL86_RS06305 and HPSNT_RS00950) and subjected to determined immunogenic B and T-Cell epitopes. The B and T-Cell overlapped epitopes were selected to design 9 different vaccine constructs by using linkers and adjuvants. Least allergenic and most antigenic construct (C-8) was selected as a promiscuous vaccine to elicit host immune response. Cloning and in silico expression of the constructed vaccine (C-8) was done to produce a clone having the desired (gene) vaccine construct. In conclusion, the prioritized therapeutic targets for 84 strains of H.pylori will be useful for future therapy design. Vaccine design may also prove useful in the quest for targeting multi-strains of H. pylori in patients.

Genome Subtraction and Comparison for the Identification of Novel Drug Targets against Mycobacterium avium subsp. hominissuis

Mycobacterium avium complex (MAC) is a major cause of non-tuberculous pulmonary and disseminated diseases worldwide, inducing bronchiectasis, and affects HIV and immunocompromised patients. In MAC, Mycobacterium avium subsp. hominissuis is a pathogen that infects humans and mammals, and that is why it is a focus of this study. It is crucial to find essential drug targets to eradicate the infections caused by these virulent microorganisms. The application of bioinformatics and proteomics has made a significant impact on discovering unique drug targets against the deadly pathogens. One successful bioinformatics methodology is the use of in silico subtractive genomics. In this study, the aim was to identify the unique, non-host and essential protein-based drug targets of Mycobacterium avium subsp. hominissuis via in silico a subtractive genomics approach. Therefore, an in silico subtractive genomics approach was applied in which complete proteome is subtracted systematically to shortlist potential drug targets. For this, the complete dataset of proteins of Mycobacterium avium subsp. hominissuis was retrieved. The applied subtractive genomics method, which involves the homology search between the host and the pathogen to subtract the non-druggable proteins, resulted in the identification of a few prioritized potential drug targets against the three strains of M. avium subsp. Hominissuis, i.e., MAH-TH135, OCU466 and A5. In conclusion, the current study resulted in the prioritization of vital drug targets, which opens future avenues to perform structural as well as biochemical studies on predicted drug targets against M. avium subsp. hominissuis.

A comparative proteomic approach using metabolic pathways for the identification of potential drug targets against Helicobacter pylori

BACKGROUND

Helicobacter pylori is the most highlighted pathogen across the globe especially in developing countries. Severe gastric problems like ulcers, cancers are associated with H. pylori and its prevalence is widespread. Evolution in the genome and cross-resistance with different antibiotics are the major reason of its survival and pandemic resistance against current regimens.

OBJECTIVES

To prioritize potential drug target against H. pylori by comparing metabolic pathways of its available strains.

METHODS

We used various computational tools to extract metabolic sets of all available (61) strains of H. pylori and performed pan genomics and subtractive genomics analysis to prioritize potential drug target. Additionally, the protein interaction and detailed structure-based studies were performed for further characterization of protein.

RESULTS

We found 41 strains showing similar set of metabolic pathways. However, 19 strains were found with unique set of metabolic pathways. The metabolic set of these 19 strains revealed 83 unique proteins and BLAST against human proteome further funneled them to 38 non-homologous proteins. The druggability and essentiality testing further converged our findings to a single unique protein as a potential drug target against H. pylori.

CONCLUSION

We prioritized one protein-based drug target which upon subject to applied protocol was found as close homolog of the Saccharopine dehydrogenase. Our study has opened further avenues of research regarding the discovery of new drug targets against H. pylori.

Identification of novel drug targets for humans and potential vaccine targets for cattle by subtractive genomic analysis of Brucella abortus strain 2308

Brucella abortus is the causative agent of brucellosis, a neglected endemic zoonotic disease. It causes devastating economic losses in low income and developing countries. Clinical symptoms of infected cows include abortion, poor weight, reduced fertility gain and reduction in milk production. Transmission of the zoonotic disease from cattle to human can occur through direct contact with infected cows, their tissues (e.g. placenta or aborted tissues), or their products (e.g. dairy) whereas human-to-human transmission can occur transplacentally or via breastfeeding. Malaise, fatigue, fever, arthritis are some clinical symptom of the disease in humans. Recent studies have revealed that Brucella abortus show resistance to several antibiotics. There are worldwide concerns about rising levels of antibiotic resistance resulting in the treatment failure as well as the reduced usefulness of older broad-spectrum antibiotics. Hence, a rather novel method has been in use to combat resistant pathogens since the last decade. To overcome this challenge, subtractive genomic analysis has been successfully carried out with the whole proteome of Brucella abortus strain 2308 using various bioinformatic tools and servers. Proteins nonhomologous to cattle and human were selected for metabolic analysis. Only three membrane proteins (ABC transporter permease, acriflavine resistance protein B, penicillin-binding protein 2) were found to be potential novel vaccine candidates with cattle as the host whereas one membrane protein (ABC transporter permease) was selected as novel drug target with human as the host. Development of novel vaccines and therapeutics through targeting inhibition of the functions of any of these essential proteins can lead to disruption of pathogen-specific metabolic pathways and thereby to the destruction and the eradication of this pathogen from respective hosts. The results of this study could facilitate the discovery and release of new and effective drugs and help in designing and producing potent vaccines against Brucella abortus strain 2308.

Identification of putative non-host essential genes and novel drug targets against Acinetobacter baumannii by in silico comparative genome analysis

Acinetobacter baumannii, the gram-negative bacteria emerged as an extremely critical pathogen causing nosocomial and different kinds of infections. A. baumannii exhibit resistivity towards various classes of antibiotics that shows that there is a dire need to search more drug targets by exploiting the full genome of the bacteria. In doing so, a strategy is made with the combination of computational biology, pathogen informatics and cheminformatics. Comparative genomics analysis, modeling and docking studies have been performed for the prediction of non-host essential genes and novel drug candidates against A. baumannii. Among 37 unique and 82 common metabolic pathways, 92 genes were predicted as non-host genes. Similarly, using homology search between A. baumannii genome and essential genes of different bacteria, 293 genes were predicted as essential genes of A. baumannii. Among these predicted non-host and essential genes, 86 genes were predicted as non-host essential genes which could serve as potential novel drug and vaccine targets. Additional drug-target like physicochemical properties were estimated such as the molecular weight, subcellular localization and druggability potential. On the structural part, the crystal structures of all the non-host essential genes of A. baumannii were found except the three genes. Out of these three, a homology model of Undecaprenyl-diphosphatase was built using a PDB template by MODELLER [version 9.18]. The quality of the model was assessed by the ProSA and RAMPAGE. The built model was subjected as a receptor for the molecular docking with Adenosine diphosphate (ADP) as a ligand. The molecular docking was performed by AutoDock4 and the best conformation with lowest binding energy (-4.39 kcal/mol) was obtained. The LigPlot was used to identify the close interactions between the ligand the receptor's residues. This study will further aid for the selection of putative inhibitors against a novel drug target identified against A. baumannii and hence could lead to the better therapeutics.

Reverse vaccinology and subtractive genomics-based putative vaccine targets identification for Burkholderia pseudomallei Bp1651

The Burkholderia pseudomallei is a unique bio-threat and causative agent of melioidosis. The B. pseudomallei Bp1651 strain has been isolated from a chronic cystic fibrosis patient. The genome-level DNA sequences information of this strain has recently been published. Unfortunately, there is no commercial vaccine available till date to combat B. pseudomallei infection. The genome-wide prioritization approaches are widely used for the identification of potential therapeutic candidates against pathogens. In the present study, we utilized the recently available annotated genomic information of B. pseudomallei Bp1651 through subtractive genomics and reverse-vaccinology strategies to identify its potential vaccine targets. The analyses identified more than 60 pathogen-specific, human host non-homologous proteins that may prioritize in future studies to investigate therapeutic targets for B. pseudomallei Bp1651. The potential B and T-cells antigenic determinant peptides from these pathogen-specific proteins were cataloged using antigenicity and epitope prediction tools. The analyses unveiled a promising antigenic peptide "FQWEFSLSV" from protein-export membrane protein (SecF) of Bp1651 strain, which was predicted to interact with multiple class I and class II MHC alleles with IC₅₀ value < 100 nM. The molecular docking analysis verified favorable molecular interaction of this lead antigenic peptide with the ligand-binding pocket residues of HLA A*02:06 human host immune cell surface receptor. This peptide is predicted to be a suitable epitope capable to elicit the cell-mediated immune response against the B. pseudomallei pathogen. The putative epitopes and proteins identified in this study may be promising vaccine targets against Bp1651 as well as other pathogenic strains of B. pseudomallei.

Subtractive genome analysis for in silico identification and characterization of novel drug targets in Streptococcus pneumonia strain JJA

Streptococcus pneumoniae (pneumococcus) is a Gram-positive bacterium. Humans are the major target for the pneumococcus. The pneumococcus is a common etiological agent of many different diseases such as bacterial meningitis, pneumonia, otitis media (OM), sinusitis, and conjunctivitis. According to the WHO, the pneumococcus is responsible for causing 1 million deaths each year. In 2000, over 14 million children worldwide under the age of 5 years were diagnosed with a pneumococcal disease, with the highest incidence seen in Africa. The human population most susceptible to pneumococcal infections is that of children due to their immature immune system. A sensational increase in antibiotic resistance among S. pneumoniae has been witnessed in different parts of the world since 1980s. The increase of resistance of S. pneumoniae to antibiotics is of major concern throughout the world. Worldwide, there are concerns about rising levels of antibiotic resistance and fears that the efficacy of antimicrobial therapy may be compromised, resulting in treatment failure and reduced utility of older antibiotics, a comparatively novel method has been used to defeat the resistant pathogens since last decade. The computational subtractive genomics approach is one of them, in which the bacterial pathogen complete proteins is gradually rock-bottom to a small number of likely drug targets. In this approach the steps which are used to find human non-homologs targets, proteins that are essential to the disease causing agent and participation of the selected proteins in pathogen metabolic pathways which are necessary for the survival of bacteria. We used computational subtractive genomics on consummate proteins of the of S. pneumonia strain JJA in this study and concluded with 2 proteins that can be used as potent drug targets against which new dynamic molecules can be planned to make better the action to treat the disease which is related with pathogen.

Application of the Subtractive Genomics and Molecular Docking Analysis for the Identification of Novel Putative Drug Targets against Salmonella enterica subsp. enterica serovar Poona

The emergence of novel pathogenic strains with increased antibacterial resistance patterns poses a significant threat to the management of infectious diseases. In this study, we aimed at utilizing the subtractive genomic approach to identify novel drug targets against Salmonella enterica subsp. enterica serovar Poona strain ATCC BAA-1673. We employed in silico bioinformatics tools to subtract the strain-specific paralogous and host-specific homologous sequences from the bacterial proteome. The sorted proteome was further refined to identify the essential genes in the pathogenic bacterium using the database of essential genes (DEG). We carried out metabolic pathway and subcellular location analysis of the essential proteins of the pathogen to elucidate the involvement of these proteins in important cellular processes. We found 52 unique essential proteins in the target proteome that could be utilized as novel targets to design newer drugs. Further, we investigated these proteins in the DrugBank databases and 11 of the unique essential proteins showed druggability according to the FDA approved drug bank databases with diverse broad-spectrum property. Molecular docking analyses of the novel druggable targets with the drugs were carried out by AutoDock Vina option based on scoring functions. The results showed promising candidates for novel drugs against Salmonella infections.

Active site analysis of sortase A from Staphylococcus simulans indicates function in cleavage of putative cell wall proteins

Sortase mediated transpeptidation reactions play a significant role in covalent attachment of surface proteins to the cell wall of Gram-positive bacteria. Earlier studies have shown that sortase A (StrA) is required for the virulence of Staphylococci. The human pathogen Staphylococcus simulans CJ16 carries a putative sortase A (SsiStrA) encoding gene, but neither transpeptidation activity nor biochemical characteristics of SsiStrA have been investigated. Here, we identified and characterized StrA from coagulase-negative Staphylococci. SsiStrA was cloned and overexpressed in Escherichia coli BL21 in a soluble form. Size-exclusion chromatography, cross-linking and dynamic light scattering demonstrated that SsiStrA existed as monomer-dimer equilibrium in vitro. We further demonstrated that SsiStrA has sortase activity, and it recognized and cleaved the sorting motif LXPTG. H117, C180 and R193 residues were critical for enzyme activity, and calcium ions enhanced activity.

To Hit or Not to Hit, That Is the Question - Genome-wide Structure-Based Druggability Predictions for Pseudomonas aeruginosa Proteins

Pseudomonas aeruginosa is a Gram-negative bacterium known to cause opportunistic infections in immune-compromised or immunosuppressed individuals that often prove fatal. New drugs to combat this organism are therefore sought after. To this end, we subjected the gene products of predicted perturbative genes to structure-based druggability predictions using DrugPred. Making this approach suitable for large-scale predictions required the introduction of new methods for calculation of descriptors, development of a workflow to identify suitable pockets in homologous proteins and establishment of criteria to obtain valid druggability predictions based on homologs. We were able to identify 29 perturbative proteins of P. aeruginosa that may contain druggable pockets, including some of them with no or no drug-like inhibitors deposited in ChEMBL. These proteins form promising novel targets for drug discovery against P. aeruginosa.