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

Genomic and Computational Analysis Unveils Bacteriocin Based Therapeutics against Clinical Mastitis Pathogens in Dairy Cows

Clinical mastitis (CM) remains a critical challenge in dairy production, exacerbated by the global rise of antibiotic-resistant pathogens, which threatens herd health and productivity. This study pioneers a dual genomic-computational strategy to develop bacteriocin-based therapeutics-a promising alternative to conventional antibiotics-by targeting conserved virulence mechanisms in CM-causing pathogens. We aimed to (i) identify essential core proteins in CM-causing pathogens of dairy cows using the genomic approach; and (ii) assess the efficacy of bacteriocin peptides (BPs) as novel therapeutic agents targeting the selected core proteins for sustainable management of mastitis. Through pan-genomic analysis of 16 clinically relevant pathogens, including Staphylococcus aureus, S. warneri, Streptococcus agalactiae, S. uberis, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, P. putida, and P. asiatica, we identified 65 evolutionarily conserved core proteins. Prioritization based on essentiality, virulence, and resistance potential revealed Rho (transcription termination factor) and HupB (nucleoid-associated protein) as high-value therapeutic targets due to their critical roles in bacterial survival and pathogenicity. A computational screen of 70 BPs identified 14 candidates with high binding affinity for both Rho and HupB proteins. Molecular dynamics simulations demonstrated that BP8, a novel dual-action bacteriocin, competitively inhibits Rho-mediated transcription termination and disrupts HupB-DNA interactions, effectively crippling bacterial replication and virulence. BP8 exhibited superior structural stability and binding efficacy compared to other candidates, positioning it as a potent broad-spectrum agent against diverse CM pathogens, including multidrug-resistant strains. Our study underscores the untapped potential of bacteriocins in veterinary medicine, offering a sustainable solution to mitigate antibiotic overuse and resistance. The computational validation of BP8 provides a foundational framework for developing targeted therapies, with implications for reducing dairy industry losses and improving animal welfare. Further in vitro and in vivo studies are warranted to translate these insights into practical therapeutics.

Identification of novel drug targets and small molecule discovery for MRSA infections

Introduction

The topmost deadliest microorganism, namely, methicillin-resistant Staphylococcus aureus (MRSA), causes dreadful infections like bacteremia, pneumonia, endocarditis, and systemic inflammations. The virulence factors associated with MRSA exhibit multidrug-resistant characteristics, complicating treatment choices. So, the primary objective of this study is to identify the MRSA virulence factors and inhibiting its activity utilizing bioinformatic approaches.

Methods

The screening of novel therapeutic MRSA targets was conducted based on the predictions retrieved from non-homologous, physicochemical analysis, subcellular localization, druggability, and virulence factor examinations. Following that, flavonoid compounds were docked against specific MRSA targets using AutoDock Vina. Further, molecular dynamic simulations and binding free energy calculations were performed using simulation software.

Results

After examining 2,640 virulence factors that presented in MRSA, the heme response regulator R (HssR) was found to be a novel protein that greatly controls the levels of heme in MRSA infections. Subsequently, the binding energy calculations for flavonoid compounds and HssR revealed that the catechin provided -7.9 kcal/mol, which surpassed the standard drug, namely, vancomycin (-5.9 kcal/mol). Further, the results were validated by evaluating molecular dynamic simulation parameters like RMSD, RMSF, ROG, SASA, and PCA. Through analyzing these parameters, catechin provided a more stable, compact nature and less solvent exposure with HssR than vancomycin. Moreover, the predicted binding free energy for HssR-catechin was found to be -23.0 kcal/mol, which was less compared to the HssR-vancomycin (-16.91 kcal/mol) complex. The results suggested that the catechin was able to modulate the activity of the HssR protein effectively.

Conclusion

These potential findings revealed that heme response regulator R as a promising therapeutic target while the flavonoid compound catechin could act as alternative therapeutic inhibitor that target MRSA infections.

Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach

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.

A bioinformatic approach to identify pathogenic variants for Stevens-Johnson syndrome

Stevens-Johnson syndrome (SJS) produces a severe hypersensitivity reaction caused by Herpes simplex virus or mycoplasma infection, vaccination, systemic disease, or other agents. Several studies have investigated the genetic susceptibility involved in SJS. To provide further genetic insights into the pathogenesis of SJS, this study prioritized high-impact, SJS-associated pathogenic variants through integrating bioinformatic and population genetic data. First, we identified SJS-associated single nucleotide polymorphisms from the genome-wide association studies catalog, followed by genome annotation with HaploReg and variant validation with Ensembl. Subsequently, expression quantitative trait locus (eQTL) from GTEx identified human genetic variants with differential gene expression across human tissues. Our results indicate that two variants, namely rs2074494 and rs5010528, which are encoded by the HLA-C (human leukocyte antigen C) gene, were found to be differentially expressed in skin. The allele frequencies for rs2074494 and rs5010528 also appear to significantly differ across continents. We highlight the utility of these population-specific HLA-C genetic variants for genetic association studies, and aid in early prognosis and disease treatment of SJS.

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.

Molecular docking and simulation studies against nucleoside diphosphate kinase (NDK) of Pseudomonas aeruginosa with secondary metabolite identified by genome mining from paenibacillusehimensis

Pseudomonas aeruginosa is one of the leading opportunistic pathogens that causes nosocomial pneumonia and mostly in people with cystic fibrosis. In the present study, an in-silicoapproach was adopted to identify the novel drug target against Pseudomonas aeruginosa by employing subtractive genomics and molecular docking studies. Each step in the subtractive genomics scrutinized the bacterial proteome and determined a potential drug target against Pseudomonas aeruginosa. 71 essential proteins were obtained from the subcellular localization method that resides in the extracellular region. Metabolic pathways were studied to elucidate the unique pathways where the involvement of proteins present in the pathogen was predicted and a total of 6 unique pathways were determined. By, Genome mining of the source organism Paenibacillusehimensis, 9 ligands were obtained. The molecular docking analysis between the binding site of target protein NDK and ligands was carried out by employing the AutoDock Vina tool. Based on the highest binding affinity, Paenibactin, AnabaenopeptinNZ857 and Nostamide A complex with NDK protein with a lower binding energy of -7.5 kcal/mol, -7.4and -7.2 kcal/molrespectively were considered for the simulation studies. Molecular dynamics simulation studies showed the ligand in complex with protein was highly stable and rigid for a duration of 150 ns. For Paenibactin, AnabaenopeptinNZ857 and Nostamide Acomplex with protein, RMSD plot showed a deviation of ∼0.2-0.3 nm till ∼30ns/50 ns-110ns and further stabilized. The radius of the gyration plot clearly showed that the values stayed at ∼1.45 nm- 1.55 nm showing compactness and stability. The SASA stayed at the range ∼80nm2 and at least one total number of hydrogen bonds was shown throughout the 150 ns simulation for all three possible ligand-protein complexes. In the RMSF plot, the maximum fluctuation was ranged from ∼0.4-0.42 nm at the range between ∼57ns-60ns.The Paenibactin, AnabaenopeptinNZ857 and Nostamide A complex with NDK protein showed a stable, rigid and compact interaction throughout the simulation of duration 150 ns.Communicated by Ramaswamy H. Sarma.

Computer-aided genomic data analysis of drug-resistant Neisseria gonorrhoeae for the Identification of alternative therapeutic targets

Neisseria gonorrhoeae is an emerging multidrug resistance pathogen that causes sexually transmitted infections in men and women. The N. gonorrhoeae has demonstrated an emerging antimicrobial resistance against reported antibiotics, hence fetching the attention of researchers to address this problem. The present in-silico study aimed to find putative novel drug and vaccine targets against N. gonorrhoeae infection by the application of bioinformatics approaches. Core genes set of 69 N. gonorrhoeae strains was acquired from complete genome sequences. The essential and non-homologous metabolic pathway proteins of N. gonorrhoeae were identified. Moreover, different bioinformatics databases were used for the downstream analysis. The DrugBank database scanning identified 12 novel drug targets in the prioritized list. They were preferred as drug targets against this bacterium. A viable vaccine is unavailable so far against N. gonorrhoeae infection. In the current study, two outer-membrane proteins were prioritized as vaccine candidates via reverse vaccinology approach. The top lead B and T-cells overlapped epitopes were utilized to generate a chimeric vaccine construct combined with immune-modulating adjuvants, linkers, and PADRE sequences. The top ranked prioritized vaccine construct (V7) showed stable molecular interaction with human immune cell receptors as inferred during the molecular docking and MD simulation analyses. Considerable response for immune cells was interpreted by in-silico immune studies. Additional tentative validation is required to ensure the effectiveness of the prioritized vaccine construct against N. gonorrhoeae infection. The identified proteins can be used for further rational drug and vaccine designing to develop potential therapeutic entities against the multi-drug resistant N. gonorrhoeae.

Structure Based in Silico Screening Revealed a Potent Acinetobacter Baumannii Ftsz Inhibitor From Asinex Antibacterial Library

The superbug Acinetobacter baumannii is an increasingly prevalent pathogen of the intensive care units where its treatment is challenging. The identification of newer drug targets and the development of propitious therapeutics against this pathogen is of utmost importance. A drug target, cell division enzyme (FtsZ), involved in A. baumannii cytokinesis is a promising avenue for antibacterial therapy. Structure based virtual screening illustrated a lead-like molecule from Asinex antibacterial library to have the best binding affinity for the FtsZ active pocket. Computational pharmacokinetics predicted the compound to have the safest pharmacokinetics profile, thus maximizing the chances of the molecule reaching the market with enhanced efficacy and lesser toxicity. Molecular dynamics simulations in an aqueous environment revealed the flexibility of protein loop regions, and upward extension followed by the backward movement of the inhibitor N, N-dimethylpyridazin-3-amine ring on its axis. The active pocket residue Thr310 demonstrated to play significant role in inhibitor binding. The binding free energy predicted by MM/GBSA and MM/PBSA reflected system stability with a total value of -62.15 kcal/mol and -10.60 kcal/mol, respectively. The absolute binding free energy estimated by WaterSwap was -16 kcal/mol that validates and affirms complex stability. The inhibitor represents a promising scaffold as a lead optimization for the FtsZ enzyme.

Subtractive genomics profiling for potential drug targets identification against Moraxella catarrhalis

Moraxella catarrhalis (M. catarrhalis) is a gram-negative bacterium, responsible for major respiratory tract and middle ear infection in infants and adults. The recent emergence of the antibiotic resistance M. catarrhalis demands the prioritization of an effective drug target as a top priority. Fortunately, the failure of new drugs and host toxicity associated with traditional drug development approaches can be avoided by using an in silico subtractive genomics approach. In the current study, the advanced in silico genome subtraction approach was applied to identify potential and pathogen-specific drug targets against M. catarrhalis. We applied a series of subtraction methods from the whole genome of pathogen based on certain steps i.e. paralogous protein that have extensive homology with humans, essential, drug like, non-virulent, and resistant proteins. Only 38 potent drug targets were identified in this study. Eventually, one protein was identified as a potential new drug target and forwarded to the structure-based studies i.e. histidine kinase (UniProt ID: D5VAF6). Furthermore, virtual screening of 2000 compounds from the ZINC database was performed against the histidine kinase that resulted in the shortlisting of three compounds as the potential therapeutic candidates based on their binding energies and the properties exhibited using ADMET analysis. The identified protein gives a platform for the discovery of a lead drug candidate that may inhibit it and may help to eradicate the otitis media caused by drug-resistant M. catarrhalis. Nevertheless, the current study helped in creating a pipeline for drug target identification that may assist wet-lab research in the future.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

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.

An in silico study to unveil potential drugs and vaccine chimera for HBV capsid assembly protein: combined molecular docking and dynamics simulation approach

Humans are a major reservoir of the hepatitis B virus (HBV), therefore promising treatment and control vaccination strategies are needed to eradicate the virus. Though promising drugs and vaccines are available against HBV, still efforts are required to enrich the therapy options. Herein, the HBV assembly protein was explored to identify novel targets for future use against HBV. Computer-aided drug designing and immune-informatics techniques were employed for the identification of putative inhibitors and vaccine ensemble against HBV using capsid assembly protein. The identified drug molecule binds with high affinity to the active pocket of the protein, and several epitopes are scanned in the protein sequence. The drug molecule, besides being a good putative inhibitor, has acceptable drug-like properties. A multi-epitope vaccine is also constructed to overcome the limitations of weakly immunogenic epitopes. In contrast to the MHC II level, the set of predicted epitopes has been recognized to interact with significant numbers of HLA alleles of MHC I. Selected epitopes are extremely virulent, antigenic, nontoxic, nonallergic, have suitable affinity to bind with the prevailing DRB*0101 allele, and also spectacle 86% mediocre population coverage. A multi-epitope peptide-based vaccine chimera having 73 amino acids was designed. It emerged as substantially immunogenic, thermally stable, robust in producing cellular as well as humoral immune responses, and had competent physicochemical properties to analyze in vitro and in vivo studies. The capsid assembly protein is a in more stable nature in the presence of the drug molecule compared to the TLR3 receptor in the vaccine presence. These particulars were confirmed by exposing the docked molecules to absolute and relative binding free energy approaches of MMGBSA/PBSA. The purpose to investigate the interactions between the vaccine and a representative TLR3 immune receptor can reveal the intermolecular affinity and possible presentation mechanism of the vaccine by TLR3 to the host immune system. It was revealed that the vaccine is showing a very good affinity of binding for the TLR3 and forming a network of hydrophobic and hydrophilic interactions. Overall, the findings of this study are promising and might be useful for further experimental validations.

Subtractive genomics and molecular docking approach to identify drug targets against Stenotrophomonas maltophilia

Stenotrophomonas maltophilia is a multidrug resistant pathogen associated with high mortality and morbidity in patients having compromised immunity. The efflux systems of S. maltophilia include SmeABC and SmeDEF proteins, which assist in acquisition of multiple-drug-resistance. In this study, proteome based mapping was utilized to find out the potential drug targets for S. maltophilia strain k279a. Various tools of computational biology were applied to remove the human-specific homologous and pathogen-specific paralogous sequences from the bacterial proteome. The CD-HIT analysis selected 4315 proteins from total proteome count of 4365 proteins. Geptop identified 407 essential proteins, while the BlastP revealed approximately 85 non-homologous proteins in the human genome. Moreover, metabolic pathway and subcellular location analysis were performed for essential bacterial genes, to describe their role in various cellular processes. Only two essential proteins (Acyl-[acyl-carrier-protein]—UDP-N acetyl glucosamine O-acyltransferase and D-alanine-D-alanine ligase) as candidate for potent targets were found in proteome of the pathogen, in order to design new drugs. An online tool, Swiss model was employed to model the 3D structures of both target proteins. A library of 5000 phytochemicals was docked against those proteins through the molecular operating environment (MOE). That resulted in to eight inhibitors for both proteins i.e. enterodiol, aloin, ononin and rhinacanthinF for the Acyl-[acyl-carrier-protein]—UDP-N acetyl glucosamine O-acyltransferase, and rhazin, alkannin beta, aloesin and ancistrocladine for the D-alanine-D-alanine ligase. Finally the ADMET was done through ADMETsar. This study supported the development of natural as well as cost-effective drugs against S. maltophilia. These inhibitors displayed the effective binding interactions and safe drug profiles. However, further in vivo and in vitro validation experiment might be performed to check their drug effectiveness, biocompatibility and their role as effective inhibitors.

Computational identification of putative common genomic drug and vaccine targets in Mycoplasma genitalium

Mycoplasma genitalium is an obligate intracellular bacterium that is responsible for several sexually transmitted infections, including non-gonococcal urethritis in men and several inflammatory reproductive tract syndromes in women. Here, we applied subtractive genomics and reverse vaccinology approaches for in silico prediction of potential vaccine and drug targets against five strains of M. genitalium. We identified 403 genes shared by all five strains, from which 104 non-host homologous proteins were selected, comprising of 44 exposed/secreted/membrane proteins and 60 cytoplasmic proteins. Based on the essentiality, functionality, and structure-based binding affinity, we finally predicted 19 (14 novel) putative vaccine and 7 (2 novel) candidate drug targets. The docking analysis showed six molecules from the ZINC database as promising drug candidates against the identified targets. Altogether, both vaccine candidates and drug targets identified here may contribute to the future development of therapeutic strategies to control the spread of M. genitalium worldwide.

Subtractive proteomics approach to Unravel the druggable proteins of the emerging pathogen Waddlia chondrophila and drug repositioning on its MurB protein

Waddlia chondrophila is an emerging pathogen that has been implicated in numerous unpropitious pregnancy events in humans and ruminants. Taking into account its association with abortigenic events, possible modes of transmission, and future risk, immediate clinical measures are required to prevent widespread damage caused by this organism and hence this study. Here, a subtractive proteomics approach was employed to identify druggable proteins of W. chondrophila. Considering the essential genes, antibiotic resistance proteins, and virulence factors, 676 unique important proteins were initially identified for this bacterium. Afterward, NCBI BLASTp performed against human proteome identified 223 proteins that were further pushed into KEGG Automatic Annotation Server (KAAS) for automatic annotation. Using the information from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database 14 Waddlia specific metabolic pathways were identified with respect to humans. Analyzing the data from KAAS and KEGG databases, forty-eight metabolic pathway-dependent, and seventy metabolic pathway independent proteins were identified. Standalone BLAST search against DrugBank FDA approved drug targets revealed eight proteins that are finally considered druggable proteins. Prediction of three-dimensional structures was done for the eight proteins through homology modeling and the Ramachandran plot model showed six models as a valid prediction. Finally, virtual screening against MurB protein was performed using FDA approved drugs to employ the drug repositioning strategy. Three drugs showed promising docking results that can be used for therapeutic purposes against W. chondrophila following the clinical validation of the study.

Computational/in silico methods in drug target and lead prediction

Drug-like compounds are most of the time denied approval and use owing to the unexpected clinical side effects and cross-reactivity observed during clinical trials. These unexpected outcomes resulting in significant increase in attrition rate centralizes on the selected drug targets. These targets may be disease candidate proteins or genes, biological pathways, disease-associated microRNAs, disease-related biomarkers, abnormal molecular phenotypes, crucial nodes of biological network or molecular functions. This is generally linked to several factors, including incomplete knowledge on the drug targets and unpredicted pharmacokinetic expressions upon target interaction or off-target effects. A method used to identify targets, especially for polygenic diseases, is essential and constitutes a major bottleneck in drug development with the fundamental stage being the identification and validation of drug targets of interest for further downstream processes. Thus, various computational methods have been developed to complement experimental approaches in drug discovery. Here, we present an overview of various computational methods and tools applied in predicting or validating drug targets and drug-like molecules. We provide an overview on their advantages and compare these methods to identify effective methods which likely lead to optimal results. We also explore major sources of drug failure considering the challenges and opportunities involved. This review might guide researchers on selecting the most efficient approach or technique during the computational drug discovery process.

Prioritisation of potential drug targets against Bartonella bacilliformis by an integrative in-silico approach

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.

Design of a Novel Multi Epitope-Based Vaccine for Pandemic Coronavirus Disease (COVID-19) by Vaccinomics and Probable Prevention Strategy against Avenging Zoonotics

The emergence and rapid expansion of the coronavirus disease (COVID-19) require the development of effective countermeasures especially a vaccine to provide active acquired immunity against the virus. This study presented a comprehensive vaccinomics approach applied to the complete protein data published so far in the National Center for Biotechnological Information (NCBI) coronavirus data hub. We identified non-structural protein 8 (Nsp8), 3C-like proteinase, and spike glycoprotein as potential targets for immune responses to COVID-19. Epitopes prediction illustrated both B-cell and T-cell epitopes associated with the mentioned proteins. The shared B and T-cell epitopes: DRDAAMQRK and QARSEDKRA of Nsp8, EDMLNPNYEDL and EFTPFDVVR of 3C-like proteinase, and VNNSYECDIPI of the spike glycoprotein are regions of high potential interest and have a high likelihood of being recognized by the human immune system. The vaccine construct of the epitopes shows stimulation of robust primary immune responses and high level of interferon gamma. Also, the construct has the best conformation with respect to the tested innate immune receptors involving vigorous molecular mechanics and solvation energy. Designing of vaccination strategies that target immune response focusing on these conserved epitopes could generate immunity that not only provide cross protection across Betacoronaviruses but additionally resistant to virus evolution.

Prioritization of Mur family drug targets against A. baumannii and identification of their homologous proteins through molecular phylogeny, primary sequence, and structural analysis

Background

The World Health Organization (WHO) report stated that Acinetobacter baumannii had been classified as one of the most important pathogenic bacteria causing nosocomial infection in hospital patients due to multi-drug resistance (MDR). It is vital to find out new bacterial drug targets and annotated their structure and function for the exploration of new anti-bacterial agents. The present study utilized a systematic route to prioritize the potential drug targets that belong to Mur family of Acinetobacter baumannii and identify their homologous proteins using a computational approach such as sequence similarity search, multiple sequence alignment, phylogenetic analysis, protein sequence, and protein structure analysis.

Results

From the results of protein sequence analysis of eight Mur family proteins, they divided into three main enzymatic classes namely transferases (MurG, MurA and MraY), ligases (MurC, MurD, MurE, and MurF), and oxidoreductase (MurB). Based on the results of intra-comparative protein sequence analysis and enzymatic classification, we have chosen MurB, MurE, and MurG as the prioritized drug targets from A. baumannii and subjected them for further detailed studies of inter-species comparison. This inter-species comparison help us to explore the sequential and structural properties of homologous proteins in other species and hence, opens a gateway for new target identification and using common inhibitor for different bacterial species caused by various diseases. The pairwise sequence alignment results between A. baumannii’s MurB with A. calcoaceticus’s MurB, A. baumannii’s MurE with A. seifertii’s MurE, and A. baumannii’s MurG with A. pittii’s MurG showed that every group of the proteins are highly similar with each other and they showed sequence identity of 95.7% and sequence similarity of 97.2%.

Conclusion

Together with the results of secondary and three-dimensional structure predictions explained that three selected proteins (MurB, MurE, and MurG) from A. baumannii and their related proteins (AcMurB, AsMurE, and ApMurG) belong to mixed αβ class and they are very similar.

In silico screening of antigenic B-cell derived T-cell epitopes and designing of a multi-epitope peptide vaccine for Acinetobacter nosocomialis

Globally, antibiotic-resistant and tolerated bacterial isolates of Acinetobacter species are imposing high financial cost on health care systems and as such, molecular targets with promising immune protection could provide substantive benefits to human healthcare. Here, we performed an in silico based proteome-wide screening for antigenic B-cell derived T-cell epitopes and their following use to design a multi-epitope peptide vaccine that can effectively engage the host immune system against Acinetobacter nosocomialis SSA3 strain. Epitopes of the fimbrial biogenesis outer membrane usher FimD protein: YQQGINNYL and YRTNYTTVG were revealed appropriate for multi-epitope peptide construct designing. This protein has no homology to the host, essential to the pathogen survival and is localized at the pathogen surface. The predicted epitopes have high affinity for the highly expressed DRB*0101 allele in humans based on the lowest IC50 value in MHCPred and have an exo-membrane topology for efficient immune system recognition. The designed multi-epitope peptide vaccine is composed of the mentioned shortlisted antigenic epitopes linked to each other through a GPGPG linker, and an EAAAK linker that joined the multi-epitope peptide to the Cholera B subunit from Vibrio cholera as an adjuvant to increase vaccine construct antigenicity. The vaccine construct was docked and simulated with a transmembrane toll-like receptor (TLR4) that revealed construct stable binding with the TLR4 through the adjuvant, allowing the epitopes exposed to the host immune system essential for generating effective innate and long-lasting adaptive immunity. The designed multi-epitope peptide vaccine may prompt the development of a vaccine to control refractory and deleterious A. nosocomialis infections.

Identification of potential drug targets and vaccine candidates in Clostridium botulinum using subtractive genomics approach

A subtractive genomic approach has been utilized for the identification of potential drug targets and vaccine candidates in Clostridium botulinum, the causative agent of flaccid paralysis in humans. The emergence of drug-resistant pathogenic strains has become a significant global public health threat. Treatment with antitoxin can target the neurotoxin at the extracellular level, however, can't converse the paralysis caused by botulism. Therefore, identification of drug targets and vaccine candidates in C. botulinum would be crucial to overcome drug resistance to existing antibiotic therapy. A total of 1729 crucial proteins, including chokepoint, virulence, plasmid and resistance proteins were mined and used for subtractive channel of analysis. This analysis disclosed 15 potential targets, which were non-similar to human, gut micro flora, and anti-targets in the host. The cellular localization of 6 targets was observed in the cytoplasm and might be used as a drug target, whereas 9 targets were localized in extracellular and membrane bound proteins and can be used as vaccine candidates. Furthermore, 4 targets were observed to be homologous to more than 75 pathogens and hence are considered as broad-spectrum antibiotic targets. The identified drug and vaccine targets in this study would be useful in the design and discovery of novel therapeutic compounds against botulism.

Identification of novel drug targets in bovine respiratory disease: an essential step in applying biotechnologic techniques to develop more effective therapeutic treatments

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.