Identification and characterization of potential druggable targets among hypothetical proteins of extensively drug resistant Mycobacterium tuberculosis (XDR KZN 605) through subtractive genomics approach

Computational Approaches for the Structure-Based Identification of Novel Inhibitors Targeting Nucleoid-Associated Proteins in Mycobacterium Tuberculosis

Implementation of computational tools in the identification of novel drug targets for Tuberculosis (TB) has been a promising area of research. TB has been a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb) localized primarily on the lungs and it has been one of the most successful pathogen in the history of mankind. Extensively arising drug resistivity in TB has made it a global challenge and need for new drugs has become utmost important.The involvement of Nucleoid-Associated Proteins (NAPs) in maintaining the structure of the genomic material and regulating various cellular processes like transcription, DNA replication, repair and recombination makes significant, has opened a new arena to find the drugs targeting Mtb. The current study aims to identify potential inhibitors of NAPs through a computational approach. In the present work we worked on the eight NAPs of Mtb, namely, Lsr2, EspR, HupB, HNS, NapA, mIHF and NapM. The structural modelling and analysis of these NAPs were carried out. Moreover, molecular interaction were checked and binding energy was identified for 2500 FDA-approved drugs that were selected for antagonist analysis to choose novel inhibitors targeting NAPs of Mtb. Drugs including Amikacin, streptomycin, kanamycin, and isoniazid along with eight FDA-approved molecules that were found to be potential novel targets for these mycobacterial NAPs and have an impact on their functions. The potentiality of several anti-tubercular drugs as therapeutic agents identified through computational modelling and simulation unlocks a new gateway for accomplishing the goal to treat TB.

Prediction of Essential Proteins of Klebsiella pneumoniae using Integrative Bioinformatics and Systems Biology Approach: Unveiling New Avenues for Drug Discovery

Klebsiella pneumoniae is an opportunistic multidrug-resistant bacterial pathogen responsible for various health care-associated infections. The prediction of proteins that are essential for the survival of bacterial pathogens can greatly facilitate the drug development and discovery pipeline toward target identification. To this end, the present study reports a comprehensive computational approach integrating bioinformatics and systems biology-based methods to identify essential proteins of K. pneumoniae involved in vital processes. From the proteome of this pathogen, we predicted a total of 854 essential proteins based on sequence, protein-protein interaction (PPI) and genome-scale metabolic model methods. These predicted essential proteins are involved in vital processes for cellular regulation such as translation, metabolism, and biosynthesis of essential factors, among others. Cluster analysis of the PPI network revealed the highly connected modules involved in the basic functionality of the organism. Further, the predicted consensus set of essential proteins of K. pneumoniae was evaluated by comparing them with existing resources (NetGenes and PATHOgenex) and literature. The findings of this study offer guidance toward understanding cell functionality, thereby facilitating the understanding of pathogen systems and providing a way forward to shortlist potential therapeutic candidates for developing novel antimicrobial agents against K. pneumoniae. In addition, the research strategy presented herein is a fusion of sequence and systems biology-based approaches that offers prospects as a model to predict essential proteins for other pathogens.

In silico identification and characterization of potential druggable targets among hypothetical proteins of Leptospira interrogans serovar Copenhageni: a comprehensive bioinformatics approach

Leptospirosis is one of the neglected zoonosis, affecting human and animal populations worldwide. Reliable effective therapeutics and concerns to look for more research into the molecular analysis of its genome is therefore needed. In the genomic pool of the Leptospira interrogans many hypothetical proteins are still uncharacterized. In the current research, we performed extensive in silico analysis to prioritize the potential hypothetical proteins of L. interrogans serovar Copenhageni via stepwise reducing the available hypothetical proteins (Total 3606) of the assembly to only 15, based on non-homologous to homosapien, essential, functional, virulent, cellular localization. Out of them, only two proteins WP_000898918.1 (Hypothetical Protein 1) & WP_001014594.1 (Hypothetical Protein 2) were found druggable and involved in protein-protein interaction network. The 3 D structures of these two target proteins were predicted via ab initio homology modeling followed by structures refinement and validation, as no structures were available till date. The analysis also revealed that the functional domains, families and protein-protein interacting partners identified in both proteins are crucial for the survival of the bacteria. The binding cavities were predicted for both the proteins through blind and specific protein-ligand docking with their respective ligands and inhibitors and were found to be in accordance with the druggable sites predicted by DoGSiteScorer. The docking interactions were found within the active functional domains for both the proteins while for Hypothetical Protein 2, the same residues were involved in interactions with Cytidine-5'-triphosphate in blind and specific docking. Furthermore, the simulations of molecular dynamics and free binding energy revealed the stable substrate binding and efficient binding energies, and were in accordance to our docking results. The work predicted two unique hypothetical proteins of L. interrogans as a potential druggable targets for designing of inhibitors for them.Communicated by Ramaswamy H. Sarma.

Multi-epitope vaccine against drug-resistant strains of Mycobacterium tuberculosis: a proteome-wide subtraction and immunoinformatics approach

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, one of the most deadly infections in humans. The emergence of multidrug-resistant and extensively drug-resistant Mtb strains presents a global challenge. Mtb has shown resistance to many frontline antibiotics, including rifampicin, kanamycin, isoniazid, and capreomycin. The only licensed vaccine, Bacille Calmette-Guerin, does not efficiently protect against adult pulmonary tuberculosis. Therefore, it is urgently necessary to develop new vaccines to prevent infections caused by these strains. We used a subtractive proteomics approach on 23 virulent Mtb strains and identified a conserved membrane protein (MmpL4, NP_214964.1) as both a potential drug target and vaccine candidate. MmpL4 is a non-homologous essential protein in the host and is involved in the pathogen-specific pathway. Furthermore, MmpL4 shows no homology with anti-targets and has limited homology to human gut microflora, potentially reducing the likelihood of adverse effects and cross-reactivity if therapeutics specific to this protein are developed. Subsequently, we constructed a highly soluble, safe, antigenic, and stable multi-subunit vaccine from the MmpL4 protein using immunoinformatics. Molecular dynamics simulations revealed the stability of the vaccine-bound Toll-like receptor-4 complex on a nanosecond scale, and immune simulations indicated strong primary and secondary immune responses in the host. Therefore, our study identifies a new target that could expedite the design of effective therapeutics, and the designed vaccine should be validated. Future directions include an extensive molecular interaction analysis, in silico cloning, wet-lab experiments, and evaluation and comparison of the designed candidate as both a DNA vaccine and protein vaccine.

Molecular dynamics and simulation analysis against superoxide dismutase (SOD) target of Micrococcus luteus with secondary metabolites from Bacillus licheniformis recognized by genome mining approach

Micrococcus luteus, also known as M. luteus, is a bacterium that inhabits mucous membranes, human skin, and various environmental sources. It is commonly linked to infections, especially among individuals who have compromised immune systems. M. luteus is capable of synthesizing the enzyme superoxide dismutase (SOD) as a component of its protective response to reactive oxygen species (ROS). This enzyme serves as a promising target for drug development in various diseases. The current study utilized a subtractive genomics approach to identify potential therapeutic targets from M. luteus. Additionally, genome mining was employed to identify and characterize the biosynthetic gene clusters (BGCs) responsible for the production of secondary metabolites in Bacillus licheniformis (B. licheniformis), a bacterium known for its production of therapeutically relevant secondary metabolites. Subtractive genomics resulted in identification of important extracellular protein SOD as a drug target that plays a crucial role in shielding cells from damage caused by ROS. Genome mining resulted in identification of five potential ligands (secondary metabolites) from B. licheniformis such as, Bacillibactin (BAC), Paenibactin (PAE), Fengycin (FEN), Surfactin (SUR) and Lichenysin (LIC). Molecular docking was used to predict and analyze the binding interactions between these five ligands and target protein SOD. The resulting protein-ligand complexes were further analyzed for their motions and interactions of atoms and molecules over 250 ns using molecular dynamics (MD) simulation analysis. The analysis of MD simulations suggests, Bacillibactin as the probable candidate to arrest the activities of SOD. All the five compounds reported in this study were found to act by directly/indirectly interacting with ROS molecules, such as superoxide radicals (O2-) and hydrogen peroxide (H2O2), and transforming them into less reactive species. This antioxidant activity contributes to its protective effects against oxidative stress-induced damage in cells making them likely candidate for various applications, including in the development of antioxidant-based therapies, nutraceuticals, and functional foods.

Antimicrobial resistance in Klebsiella pneumoniae: identification of bacterial DNA adenine methyltransferase as a novel drug target from hypothetical proteins using subtractive genomics

Klebsiella pneumoniae is a gram-negative bacterium that is known for causing infection innosocomial settings. As reported by the World Health Organization, carbapenem-resistantEnterobacteriaceae, a category that includes K. pneumoniae, are classified as an urgentthreat, and the greatest concern is that these bacterial pathogens may acquire genetictraits that make them resistant towards antibiotics. The last class of antibiotics, carbapenems, are not able to combat these bacterial pathogens, allowing them to clonally expandantibiotic-resistant strains. Most antibiotics target essential pathways of bacterial cells;however, these targets are no longer susceptible to antibiotics. Hence, in our study, we focused on a hypothetical protein in K. pneumoniae that contains a DNA methylation proteindomain, suggesting a new potential site as a drug target. DNA methylation regulates theattenuation of bacterial virulence. We integrated computational-aided drug design by using a bioinformatics approach to perform subtractive genomics, virtual screening, and fingerprint similarity search. We identified a new potential drug, koenimbine, which could bea novel antibiotic.

F, Sterba J, Kaprelyants A. Shotgun proteomic profiling of dormant, ‘non-culturable’ Mycobacterium tuberculosis

Dormant cells of Mycobacterium tuberculosis, in addition to low metabolic activity and a high level of drug resistance, are characterized by ‘non-culturability’–a specific reversible state of the inability of the cells to grow on solid media. The biochemical characterization of this physiological state of the pathogen is only superficial, pending clarification of the metabolic processes that may exist in such cells. In this study, applying LC-MS proteomic profiling, we report the analysis of proteins accumulated in dormant, ‘non-culturable’ M. tuberculosis cells in an in vitro model of self-acidification of mycobacteria in the post-stationary phase, simulating the in vivo persistence conditions—the raw data are available via ProteomeXchange with identifier PXD028849. This approach revealed the preservation of 1379 proteins in cells after 5 months of storage in dormancy; among them, 468 proteins were statistically different from those in the actively growing cells and bore a positive fold change (FC). Differential analysis revealed the proteins of the pH-dependent regulatory system PhoP and allowed the reconstruction of the reactions of central carbon/glycerol metabolism, as well as revealing the salvaged pathways of mycothiol and UMP biosynthesis, establishing the cohort of survival enzymes of dormancy. The annotated pathways mirror the adaptation of the mycobacterial metabolic machinery to life within lipid-rich macrophages: especially the involvement of the methyl citrate and glyoxylate pathways. Thus, the current in vitro model of M. tuberculosis self-acidification reflects the biochemical adaptation of these bacteria to persistence in vivo. Comparative analysis with published proteins displaying antigenic properties makes it possible to distinguish immunoreactive proteins among the proteins bearing a positive FC in dormancy, which may include specific antigens of latent tuberculosis. Additionally, the biotransformatory enzymes (oxidoreductases and hydrolases) capable of prodrug activation and stored up in the dormant state were annotated. These findings may potentially lead to the discovery of immunodiagnostic tests for early latent tuberculosis and trigger the discovery of efficient drugs/prodrugs with potency against non-replicating, dormant populations of mycobacteria.

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.

The Epidemiological and Pangenome Landscape of Staphylococcus aureus and Identification of Conserved Novel Candidate Vaccine Antigens

Background and Objective:

Staphylococcus aureus (S. aureus) is a gram-positive bacterium and one of the major nosocomial pathogen. It has the ability to acquire resistance against almost all available classes of antibiotics; Methicillin-Resistant S. aureus (MRSA) is a well-known antibiotic resistance. S. aureus is a globally distributed pathogen that need in-depth epidemiological and genomic level investigation for proper treatment and prevention.

Methods:

To explore the genomic epidemiology of S. aureus in-silico Multi Locus Sequence Typing (MLST) was carried out for 355 complete genomes. Diversity within the species was investigated through pan-genome analysis and subtractive genomic approach was employed for identification of core immunogenic targets.

Results:

Epidemiological study identified 62 different sequence types (STs) of S. aureus distributed worldwide, in which ST-8, ST-5, ST-398, ST-239, and ST-30 are the most dominant STs comprising more than 50% of the isolates. The pan-genome of S. aureus is still open with 7,199 genes and there is a major contribution (80%) of MRSA strains in the S. aureus species pangenome. The core genome (2,025 genes) of S. aureus is almost stable (comprises of 72% of S. aureus genome size) while accessory and unique genes (28% of S. aureus genome size) are gradually increasing. Screening of 2,025 core genes identified putative vaccine candidates. The best scoring and dominant B-cell and T-cell epitopes were predicted out of the selected potential vaccine candidate proteins with the help of a multi-step screening procedure.

Conclusion:

We believe that the current study will provide insight into the genetic epidemiology and diversity of S. aureus and the predicted epitopes against the pathogen can be tested further for its immunological responses within the host and may provide both humoral and cellular immunity against the disease.

Core-Proteomics-Based Annotation of Antigenic Targets and Reverse-Vaccinology-Assisted Design of Ensemble Immunogen against the Emerging Nosocomial Infection-Causing Bacterium Elizabethkingia meningoseptica

Elizabethkingia meningoseptica is a ubiquitous Gram-negative emerging pathogen that causes hospital-acquired infection in both immunocompromised and immunocompetent patients. It is a multi-drug-resistant bacterium; therefore, an effective subunit immunogenic candidate is of great interest to encounter the pathogenesis of this pathogen. A protein-wide annotation of immunogenic targets was performed to fast-track the vaccine development against this pathogen, and structural-vaccinology-assisted epitopes were predicted. Among the total proteins, only three, A0A1T3FLU2, A0A1T3INK9, and A0A1V3U124, were shortlisted, which are the essential vaccine targets and were subjected to immune epitope mapping. The linkers EAAK, AAY, and GPGPG were used to link CTL, HTL, and B-cell epitopes and an adjuvant was also added at the N-terminal to design a multi-epitope immunogenic construct (MEIC). The computationally predicted physiochemical properties of the ensemble immunogen reported a highly antigenic nature and produced multiple interactions with immune receptors. In addition, the molecular dynamics simulation confirmed stable binding and good dynamic properties. Furthermore, the computationally modeled immune response proposed that the immunogen triggered a strong immune response after several doses at different intervals. Neutralization of the antigen was observed on the 3rd day of injection. Conclusively, the immunogenic construct produces protection against Elizabethkingia meningoseptica; however, further immunological testing is needed to unveil its real efficacy.

Genomic Analysis of Multidrug-Resistant Mycobacterium tuberculosis Strains From Patients in Kazakhstan

Tuberculosis (TB) is an infectious disease that remains an essential public health problem in many countries. Despite decreasing numbers of new cases worldwide, the incidence of antibiotic-resistant forms (multidrug resistant and extensively drug-resistant) of TB is increasing. Next-generation sequencing technologies provide a high-throughput approach to identify known and novel potential genetic variants that are associated with drug resistance in Mycobacterium tuberculosis (Mtb). There are limited reports and data related to whole-genome characteristics of drug-resistant Mtb strains circulating in Kazakhstan. Here, we report whole-genome sequencing and analysis results of eight multidrug-resistant strains collected from TB patients in Kazakhstan. Genotyping and validation of all strains by MIRU-VNTR and spoligotyping methodologies revealed that these strains belong to the Beijing family. The spectrum of specific and potentially novel genomic variants (single-nucleotide polymorphisms, insertions, and deletions) related to drug resistance was identified and annotated. ResFinder, CARD, and CASTB antibiotic resistance databases were used for the characterization of genetic variants in genes associated with drug resistance. Our results provide reference data and genomic profiles of multidrug-resistant isolates for further comparative studies and investigations of genetic patterns in drug-resistant Mtb strains.

Immunoinformatics and Immunogenetics-Based Design of Immunogenic Peptides Vaccine against the Emerging Tick-Borne Encephalitis Virus (TBEV) and Its Validation through In Silico Cloning and Immune Simulation

Pegivirus, HPgV, earlier known as Gb virus and hepatitis G virus, is an enveloped, positive-stranded RNA and lymphotropic virus classified into the Flaviviridae family. The transmission routes primarily involve blood products, with infections worldwide, leading up to 25% of persistent infections. To date, no effective therapeutic means are available to resolve Pegivirus infections. Effective vaccine therapeutics are the best alternative to manage this disease and any associated potential pandemic. Thus, whole proteome-based mining of immunogenic peptides, i.e., CTL (cytotoxic T lymphocytes), HTL (helper T lymphocytes) and B cell epitopes were mapped to design a vaccine ensemble. Our investigation revealed that 29 different epitopes impart a critical role in immune response induction, which was also validated by exploring its physiochemical properties and experimental feasibility. In silico expression and host immune simulation using an agent-based modeling approach confirmed the induction of both primary and secondary immune factors such as IL, cytokines and antibodies. The current study warrants further lab experiments to demonstrate its efficacy and safety.

Comprehensive review on mechanism of action, resistance and evolution of antimycobacterial drugs

Tuberculosis is one of the deadliest infectious diseases existing in the world since ancient times and still possesses serious threat across the globe. Each year the number of cases increases due to high drug resistance shown by Mycobacterium tuberculosis (Mtb). Available antimycobacterial drugs have been classified as First line, Second line and Third line antibiotics depending on the time of their discoveries and their effectiveness in the treatment. These antibiotics have a broad range of targets ranging from cell wall to metabolic processes and their non-judicious and uncontrolled usage in the treatment for years has created a significant problem called multi-drug resistant (MDR) tuberculosis. In this review, we have summarized the mechanism of action of all the classified antibiotics currently in use along with the resistance mechanisms acquired by Mtb. We have focused on the new drug candidates/repurposed drugs, and drug in combinations, which are in clinical trials for either treating the MDR tuberculosis more effectively or involved in reducing the time required for the chemotherapy of drug sensitive TB. This information is not discussed very adequately on a single platform. Additionally, we have discussed the recent technologies that are being used to discover novel resistance mechanisms acquired by Mtb and for exploring novel drugs. The story of intrinsic resistance mechanisms and evolution in Mtb is far from complete. Therefore, we have also discussed intrinsic resistance mechanisms of Mtb and their evolution with time, emphasizing the hope for the development of novel antimycobacterial drugs for effective therapy of tuberculosis.

Proteome wide vaccine targets prioritization and designing of antigenic vaccine candidate to trigger the host immune response against the Mycoplasma genitalium infection

Mycoplasma genitalium is a small size, sexually transmitted bacterial pathogen that causes urethritis in males and cervicitis in females. Being resistant to antibiotics, difficulty in diagnosis, treatment, and control of this cosmopolitan infection, vaccination is the alternating method for its effective management. Herein, this study was conducted to computationally design a multi-epitope vaccine to boost host immune responses against M. genitalium. To achieve the study aim, immunoinformatics approaches were applied to the said pathogen's proteomics sequence data. B and T cell epitopes were projected from the three shortlisted vaccine proteins; MG014, MG015, Hmw3MG317. The final vaccine ensemble comprises cytotoxic and helper T cell epitopes fused through appropriate linkers. The epitopes peptide is then liked to an adjuvant for efficient recognition and processing by the host immune system. The various physicochemical parameters such as allergenicity, antigenicity, theoretical pI, GRAVY, and molecular weight of the vaccine were checked and found safe and effective to be used in post-experimental studies. The stability and binding affinity of the vaccine with the TLR1/2 heterodimer were ensured by performing molecular docking. The best-docked complex was considered, ranked top having the lowest binding energy and strong intermolecular binding and stability. Finally, the vaccine constructs better expression was obtained by in silico cloning into the pET28a (+) vector in Escherichia coli K-12 strain, and immune simulation validated the immune response. In a nutshell, all these approaches lead to developing a multi-epitope vaccine that possessed the ability to induce cellular and antibody-mediated immune responses against the pathogen used.

Handling the Hurdles on the Way to Anti-tuberculosis Drug Development

The global epidemic of tuberculosis (TB) imposes a sustained epidemiologic vigilance and investments in research by governments. Mycobacterium tuberculosis, the main causative agent of TB in human beings, is a very successful pathogen, being the main cause of death in the population among infectious agents. In 2018, ~10 million individuals were contaminated with this bacillus and became ill with TB, and about 1.2 million succumbed to the disease. Most of the success of the M. tuberculosis to linger in the population comes from its ability to persist in an asymptomatic latent state into the host and, in fact, the majority of the individuals are unaware of being contaminated. Even though TB is a treatable disease and is curable in most cases, the treatment is lengthy and laborious. In addition, the rise of resistance to first-line anti-TB drugs elicits a response from TB research groups to discover new chemical entities, preferably with novel mechanisms of action. The pathway to find a new TB drug, however, is arduous and has many barriers that are difficult to overcome. Fortunately, several approaches are available today to be pursued by scientists interested in anti-TB drug development, which goes from massively testing chemical compounds against mycobacteria, to discovering new molecular targets by genetic manipulation. This review presents some difficulties found along the TB drug development process and illustrates different approaches that might be used to try to identify new molecules or targets that are able to impair M. tuberculosis survival.

Mining the Proteome of Streptococcus mutans for Putative Drug Targets

BACKGROUND

Dental caries is the most common and one of the prevalent diseases in the world. Streptococcus mutans is one of the major oral pathogens that cause dental caries by forming a biofilm on dental tissues, degrading dental enamel and consequent cavitation in the tissue. In vitro selection of drug targets is a laborious and expensive process and therefore, computational methods are preferable for target identification at the initial stage.

OBJECTIVE

The present research aims to find new drug targets in S. mutans by using subtractive proteomics analysis, which implements various bioinformatics tools and databases.

METHODS

The proteome of S. mutans UA159 was mined for novel drug targets using computational tools and databases such as: CD-HIT, BLASTP, DEG, KAAS and CELL2GO.

RESULTS

Out of 1953 proteins of S. mutans UA159, proteins that are redundant, homologous to human and non-essential to the pathogen were eliminated. Around 178 proteins already available in drug target repositories were also eliminated. Possible functions and subcellular localization of 32 uncharacterized proteins were predicted. Substantially, 13 proteins were identified as novel drug targets in S. mutans UA159 that can be targeted by various drugs against dental caries.

CONCLUSION

This study will effectuate the development of novel therapeutic agents against dental caries and other Streptococcal infections.

A systematic strategy for the investigation of vaccines and drugs targeting bacteria

Infectious and epidemic diseases induced by bacteria have historically caused great distress to people, and have even resulted in a large number of deaths worldwide. At present, many researchers are working on the discovery of viable drug and vaccine targets for bacteria through multiple methods, including the analyses of comparative subtractive genome, core genome, replication-related proteins, transcriptomics and riboswitches, which plays a significant part in the treatment of infectious and pandemic diseases. The 3D structures of the desired target proteins, drugs and epitopes can be predicted and modeled through target analysis. Meanwhile, molecular dynamics (MD) analysis of the constructed drug/epitope-protein complexes is an important standard for testing the suitability of these screened drugs and vaccines. Currently, target discovery, target analysis and MD analysis are integrated into a systematic set of drug and vaccine analysis strategy for bacteria. We hope that this comprehensive strategy will help in the design of high-performance vaccines and drugs.

Proteome-wide subtractive approach to prioritize a hypothetical protein of XDR-Mycobacterium tuberculosis as potential drug target

BACKGROUND

Among the resistant isolates of MTB, multidrug resistant tuberculosis (MDR-TB) and extensively drug resistant tuberculosis (XDR-TB) have been the areas of growing concern. The genomic analysis showed that the respective genomic pool of the XDR-MTB proteome contains more than 30% of the hypothetical proteins for which no functions have been annotated yet. This class of proteins presumably have their own importance to complete genome and proteome information. The bioinformatics advancements have helped to annotate those hypothetical proteins by using various computational tools and have potential to classify them functionally.

OBJECTIVE

The objective of this study was to propose a new and unique drug target against the deadly Mycobacterium tuberculosis using Bioinformatics approaches to characterize the hypothetical proteins.

RESULTS

We stepwise reduced the hypothetical proteins (total number: 1256) out of the complete proteome to only 26 essential hypothetical proteins. Out of those 26 proteins, the protein WP_003401246.1 was computationally characterized as the druggable target.

CONCLUSION

The study proposed a hypothetical protein from complete proteome of the XDR-MTB as a new drug target against which new drug candidates can be proposed. Hence, the study opens up the new avenues in the areas of drug discovery against deadly M. tuberculosis.

Comparative genome-scale modelling of the pathogenic Flavobacteriaceae species Riemerella anatipestifer in China

Riemerella anatipestifer (RA) is a gram-negative bacterium that has a high potential to infect waterfowl. Although more and more genomes of RA have been generated comparaed to genomic analysis of RA still remains at the level of individual species. In this study, we analysed the pan-genome of 27 RA virulent isolates to reveal the intraspecies genomic diversity from various aspects. The multi-locus sequence typing (MLST) analysis suggests that the geographic origin of R. anatipestifer is Guangdong province, China. Results of pan-genome analysis revealed an open pan-genome for all 27 species with the sizes of 2967 genes. We identified 387 genes among 555 unique genes originated by horizontal gene transfer. Further studies showed 204 strain-specific HGT genes were predicted as virulent proteins. Screening the 1113 core genes in RA through subtractive genomic approach, 70 putative vaccine targets out of 125 non-cytoplasmic proteins have been predicted. Further analysis of these non A. platyrhynchos homologous proteins predicted that 56 essential proteins as drug target with more interaction partners were involved in unique metabolic pathways of RA. In conclusion, the present study indicated the essence and the diversity of RA and also provides useful information for identification of vaccine and drugs candidates in future.

Gallic Acid Potentiates the Antimicrobial Activity of Tulathromycin Against Two Key Bovine Respiratory Disease (BRD) Causing-Pathogens

Bovine respiratory disease (BRD) is the most common infectious disease in dairy and beef cattle. It is associated with significant morbidity and mortality and causes a huge economic loss each year. In western Canada, a one-time injection of tulathromycin is commonly used as a metaphylactic procedure to reduce BRD incidence and eliminate potential BRD outbreak. With increased global concern on antimicrobial usage in dairy and beef products and bacterial resistance to antimicrobials, it is important to develop a novel strategy to eliminate the usage or decrease the dosage of antimicrobials. In this study, we showed that gallic acid was active against both Mannheimia haemolytica and Pasteurella multocida, two key BRD associated-pathogens, with the minimum inhibitory concentration (MIC) measured at 250 and 500 μg/mL, respectively. Co-administration of tulathromycin and gallic acid exhibited a strong additive or weak synergistic effect toward both M. haemolytic and P. multocida. Tulathromycin, gallic acid and their combination were also effective against the mixed culture of M. haemolytic and P. multocida. Furthermore, we showed that pre-exposure to tulathromycin generated bacterial resistance to the antimicrobial in M. haemolytica but not in P. multocida.

Subtractive Genomics, Molecular Docking and Molecular Dynamics Simulation Revealed LpxC as a Potential Drug Target Against Multi-Drug Resistant Klebsiella pneumoniae

The emergence and dissemination of pan drug resistant clones of Klebsiella pneumoniae are great threat to public health. In this regard new therapeutic targets must be highlighted to pave the path for novel drug discovery and development. Subtractive proteomic pipeline brought forth UDP-3-O-[3-hydroxymyristoyl] N-acetylglucosamine deacetylase (LpxC), a Zn⁺² dependent cytoplasmic metalloprotein and catalyze the rate limiting deacetylation step of lipid A biosynthesis pathway. Primary sequence analysis followed by 3-dimensional (3-D) structure elucidation of the protein led to the detection of K. pneumoniae LpxC (KpLpxC) topology distinct from its orthologous counterparts in other bacterial species. Molecular docking study of the protein recognized receptor antagonist compound 106, a uridine-based LpxC inhibitory compound, as a ligand best able to fit the binding pocket with a Gold Score of 67.53. Molecular dynamics simulation of docked KpLpxC revealed an alternate binding pattern of ligand in the active site. The ligand tail exhibited preferred binding to the domain I residues as opposed to the substrate binding hydrophobic channel of subdomain II, usually targeted by inhibitory compounds. Comparison with the undocked KpLpxC system demonstrated ligand induced high conformational changes in the hydrophobic channel of subdomain II in KpLpxC. Hence, ligand exerted its inhibitory potential by rendering the channel unstable for substrate binding.

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.