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

Whole proteome-integrated and vaccinomics-based next generation mRNA vaccine design against Pseudomonas aeruginosa-A hierarchical subtractive proteomics approach

Pseudomonas aeruginosa (P. aeruginosa) is a multidrug-resistant opportunistic pathogen responsible for chronic obstructive pulmonary disease (COPD), cystic fibrosis, and ventilator-associated pneumonia (VAP), leading to cancer. Developing an efficacious vaccine remains the most promising strategy for combating P. aeruginosa infections. In this study, we employed an advanced in silico strategy to design a highly efficient and stable mRNA vaccine using immunoinformatics tools. Whole proteome data were utilized to identify highly immunogenic vaccine candidates using subtractive proteomics. Three extracellular proteins were prioritized for T- and linear B-cell epitope prediction. Beta-definsin protein sequence was incorporated as an adjuvant at the N-terminus of the construct. A total of 3 CTL, 3 HTL, and 3 linear B cell highly immunogenic epitopes were combined using specific linkers to design this multi-peptide construct. The 5' and 3' UTR sequences, Kozak sequence with a stop codon, and signal peptides followed by a poly-A tail were incorporated into the above vaccine construct to create our final mRNA vaccine. The vaccines exhibited antigenicity scores >0.88, ensuring high antigenicity with no allergenic or toxic. Physiochemical properties analysis revealed high solubility and thermostability. Three-dimensional structural analysis determined high-quality structures. Vaccine-receptor docking and molecular dynamic simulations demonstrated strong molecular interactions, stable binding affinities, dynamic nature, and structural stability of this vaccine, with significant immunogenic responses of the immune system against the vaccine. The immunological simulation indicates successful cellular and humoral immune responses to defend against P. aeruginosa infection. Validation of the study outcomes necessitates both experimental and clinical testing.

In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation

Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs.

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.

Vaccinomics-aided next-generation novel multi-epitope-based vaccine engineering against multidrug resistant Shigella Sonnei: Immunoinformatics and chemoinformatics approaches

Shigella sonnei is a gram-negative bacterium and is the primary cause of shigellosis in advanced countries. An exceptional rise in the prevalence of the disease has been reported in Asia, the Middle East, and Latin America. To date, no preventive vaccine is available against S. sonnei infections. This pathogen has shown resistances towards both first- and second-line antibiotics. Therefore, an effective broad spectrum vaccine development against shigellosis is indispensable. In the present study, vaccinomics-aided immunoinformatics strategies were pursued to identify potential vaccine candidates from the S. sonnei whole proteome data. Pathogen essential proteins that are non-homologous to human and human gut microbiome proteome set, are feasible candidates for this purpose. Three antigenic outer membrane proteins were prioritized to predict lead epitopes based on reverse vaccinology approach. Multi-epitope-based chimeric vaccines was designed using lead B- and T-cell epitopes combined with suitable linker and adjuvant peptide sequences to enhance immune responses against the designed vaccine. The SS-MEVC construct was prioritized based on multiple physicochemical, immunological properties, and immune-receptors docking scores. Immune simulation analysis predicted strong immunogenic response capability of the designed vaccine construct. The Molecular dynamic simulations analysis ensured stable molecular interactions of lead vaccine construct with the host receptors. In silico restriction and cloning analysis predicted feasible cloning capability of the SS-MEVC construct within the E. coli expression system. The proposed vaccine construct is predicted to be more safe, effective and capable of inducing robust immune responses against S. sonnei infections and may be worthy of examination via in vitro/in vivo assays.

Comparative Proteomics and Genome-Wide Druggability Analyses Prioritized Promising Therapeutic Targets against Drug-Resistant Leishmania tropica

Leishmania tropica is a tropical parasite causing cutaneous leishmaniasis (CL) in humans. Leishmaniasis is a serious public health threat, affecting an estimated 350 million people in 98 countries. The global rise in antileishmanial drug resistance has triggered the need to explore novel therapeutic strategies against this parasite. In the present study, we utilized the recently available multidrug resistant L. tropica strain proteome data repository to identify alternative therapeutic drug targets based on comparative subtractive proteomic and druggability analyses. Additionally, small drug-like compounds were scanned against novel targets based on virtual screening and ADME profiling. The analysis unveiled 496 essential cellular proteins of L. tropica that were nonhomologous to the human proteome set. The druggability analyses prioritized nine parasite-specific druggable proteins essential for the parasite's basic cellular survival, growth, and virulence. These prioritized proteins were identified to have appropriate binding pockets to anchor small drug-like compounds. Among these, UDPase and PCNA were prioritized as the top-ranked druggable proteins. The pharmacophore-based virtual screening and ADME profiling predicted MolPort-000-730-162 and MolPort-020-232-354 as the top hit drug-like compounds from the Pharmit resource to inhibit L. tropica UDPase and PCNA, respectively. The alternative drug targets and drug-like molecules predicted in the current study lay the groundwork for developing novel antileishmanial therapies.

Hypothetical protein FoDbp40 influences the growth and virulence of Fusarium oxysporum by regulating the expression of isocitrate lyase

Fungal growth is closely related to virulence. Finding the key genes and pathways that regulate growth can help elucidate the regulatory mechanisms of fungal growth and virulence in efforts to locate new drug targets. Fusarium oxysporum is an important plant pathogen and human opportunistic pathogen that has research value in agricultural and medicinal fields. A mutant of F. oxysporum with reduced growth was obtained by Agrobacterium tumefaciens-mediated transformation, the transferred DNA (T-DNA) interrupted gene in this mutant coded a hypothetical protein that we named FoDbp40. FoDbp40 has an unknown function, but we chose to explore its possible functions as it may play a role in fungal growth regulatory mechanisms. Results showed that F. oxysporum growth and virulence decreased after FoDbp40 deletion. FOXG_05529 (NCBI Gene ID, isocitrate lyase, ICL) was identified as a key gene that involved in the reduced growth of this mutant. Deletion of FoDbp40 results in a decrease of more than 80% in ICL expression and activity, succinate level, and energy level, plus a decrease in phosphorylated mammalian target of rapamycin level and an increase in phosphorylated 5′-adenosine monophosphate activated protein kinase level. In summary, our study found that the FoDbp40 regulates the expression of ICL at a transcriptional level and affects energy levels and downstream related pathways, thereby regulating the growth and virulence of F. oxysporum.

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.

Pangenomic and functional investigations for dormancy and biodegradation features of an organic pollutant-degrading bacterium Rhodococcus biphenylivorans TG9

Environmental bacteria contain a wealth of untapped potential in the form of biodegradative genes. Leveraging this potential can often be confounded by a lack of understanding of fundamental survival strategies, like dormancy, for environmental stress. Investigating bacterial dormancy-to-degradation relationships enables improvement of bioremediation. Here, we couple genomic and functional assessment to provide context for key attributes of the organic pollutant-degrading strain Rhodococcus biphenylivorans TG9. Whole genome sequencing, pangenome analysis and functional characterization were performed to elucidate important genes and gene products, including antimicrobial resistance, dormancy, and degradation. Rhodococcus as a genus has strong potential for degradation and dormancy, which we demonstrate using R. biphenylivorans TG9 as a model. We identified four Resuscitation-promoting factor (Rpf) encoding genes in TG9 involved in dormancy and resuscitation. We demonstrate that R. biphenylivorans TG9 grows on fourteen typical organic pollutants, and exhibits a robust ability to degrade biphenyl and several congeners of polychlorinated biphenyls. We further induced TG9 into a dormant state and demonstrated pronounced differences in morphology and activity. Together, these results expand our understanding of the genus Rhodococcus and the relationship between dormancy and biodegradation in the presence of environmental stressors.

Comparative Metabolic Pathways Analysis and Subtractive Genomics Profiling to Prioritize Potential Drug Targets Against Streptococcus pneumoniae

Streptococcus pneumoniae is a notorious pathogen that affects ∼450 million people worldwide and causes up to four million deaths per annum. Despite availability of antibiotics (i.e., penicillin, doxycycline, or clarithromycin) and conjugate vaccines (e.g., PCVs), it is still challenging to treat because of its drug resistance ability. The rise of antibiotic resistance in S. pneumoniae is a major source of concern across the world. Computational subtractive genomics is one of the most applied techniques in which the whole proteome of the bacterial pathogen is gradually reduced to a limited number of potential therapeutic targets. Whole-genome sequencing has greatly reduced the time required and provides more opportunities for drug target identification. The goal of this work is to evaluate and analyze metabolic pathways in serotype 14 of S. pneumonia to identify potential drug targets. In the present study, 47 potent drug targets were identified against S. pneumonia by employing the computational subtractive genomics approach. Among these, two proteins are prioritized (i.e., 4-oxalocrotonate tautomerase and Sensor histidine kinase uniquely present in S. pneumonia) as novel drug targets and selected for further structure-based studies. The identified proteins may provide a platform for the discovery of a lead drug candidate that may be capable of inhibiting these proteins and, therefore, could be helpful in minimizing the associated risk related to the drug-resistant S. pneumoniae. Finally, these enzymatic proteins could be of prime interest against S. pneumoniae to design rational targeted therapy.

Prediction of Potential Drug Targets and Vaccine Candidates Against Antibiotic-Resistant Pseudomonas aeruginosa

Pseudomonas aeruginosa is one of the leading causes of nosocomial infections, characterized by increasing antibiotic resistance, severity and mortality. Therefore, numerous efforts have been made nowadays to identify new therapeutic targets. This study aimed to find potential drug targets and vaccine candidates in drug-resistant strains of P. aeruginosa. Extensive antibiotic-resistant and carbapenem-resistant strains of P. aeruginosa with complete genome were selected and ten common hypothetical proteins (HPs) containing more than 200 amino acids were obtained. The structural, functional and immunological predictions of these HPs were performed with the utility of bioinformatics approaches. Two common HPs (Gene ID: 2877781645 and 2877781936) among other investigated proteins were revealed as potential candidates for pharmaceutical and vaccine purposes based on structural and physicochemical properties, functional domains, subcellular localizations, signal peptides, toxicity, virulence factor, antigenicity, allergenicity and immunoinformatic predictions. The consequence of this predictive study will assist in novel drug and vaccine design through experimental investigations.

In Silico Core Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Streptococcus pyogenes

Streptococcus pyogenes is a significant pathogen that causes skin and upper respiratory tract infections and non-suppurative complications, such as acute rheumatic fever and post-strep glomerulonephritis. Multidrug resistance has emerged in S. pyogenes strains, making them more dangerous and pathogenic. Hence, it is necessary to identify and develop therapeutic methods that would present novel approaches to S. pyogenes infections. In the current study, a subtractive proteomics approach was employed to core proteomes of four strains of S. pyogenes using several bioinformatic software tools and servers. The core proteome consists of 1324 proteins, and 302 essential proteins were predicted from them. These essential proteins were analyzed using BLASTp against human proteome, and the number of potential targets was reduced to 145. Based on subcellular localization prediction, 46 proteins with cytoplasmic localization were chosen for metabolic pathway analysis. Only two cytoplasmic proteins, i.e., chromosomal replication initiator protein DnaA and two-component response regulator (TCR), were discovered to have the potential to be novel drug target candidates. Three-dimensional (3D) structure prediction of target proteins was carried out via the Swiss Model server. Molecular docking approach was employed to screen the library of 1000 phytochemicals against the interacting residues of the target proteins through the MOE software. Further, the docking studies were validated by running molecular dynamics simulation and highly popular binding free energy approaches of MM-GBSA and MM-PBSA. The findings revealed a promising candidate as a novel target against S. pyogenes infections.

Subtractive Genomics Approach for Identification of Novel Therapeutic Drug Targets in Mycoplasma genitalium

Mycoplasma genitalium infection is a sexually transmitted infection that causes urethritis, cervicitis, and pelvic inflammatory disease (PID) in men and women. The global rise in antimicrobial resistance against recommended antibiotics for the treatment of M. genitalium infection has triggered the need to explore novel drug targets against this pathogen. The application of a bioinformatics approach through subtractive genomics has proven highly instrumental in predicting novel therapeutic targets against a pathogen. This study aimed to identify essential and non-homologous proteins with unique metabolic pathways in the pathogen that could serve as novel drug targets. Based on this, a manual comparison of the metabolic pathways of M. genitalium and the human host was done, generating nine pathogen-specific metabolic pathways. Additionally, the analysis of the whole proteome of M. genitalium using different bioinformatics databases generated 21 essential, non-homologous, and cytoplasmic proteins involved in nine pathogen-specific metabolic pathways. The further screening of these 21 cytoplasmic proteins in the DrugBank database generated 13 druggable proteins, which showed similarity with FDA-approved and experimental small-molecule drugs. A total of seven proteins that are involved in seven different pathogen-specific metabolic pathways were finally selected as novel putative drug targets after further analysis. Therefore, these proposed drug targets could aid in the design of potent drugs that may inhibit the functionality of these pathogen-specific metabolic pathways and, as such, lead to the eradication of this pathogen.

Cinnamaldehyde inhibits the growth of Phytophthora capsici through disturbing metabolic homoeostasis

Background

Phytophthora capsici Leonian (P. capsici) can cause wilting and roots rotting on pepper and other cash crops. The new fungicide cinnamaldehyde (CA) has high activity against this pathogen. However, its potential mechanism is still unknown.

Methods

In order to gain insights into the mechanism, isobaric tags for relative and absolute quantification (iTRAQ)-based quantitative proteomics was used to analyze P. capsici treated with CA. The iTRAQ results were evaluated by parallel reaction monitoring (PRM) analysis and quantitative real-time PCR (qRT-PCR) analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to speculate the biochemical pathways that the agent may act on.

Results

The results showed that 1502 differentially expressed proteins were identified, annotated and classified into 209 different terms (like metabolic process, cellular process, single-organism process) based on Gene Ontology (GO) functional enrichment analysis and nine different pathways (glyoxylate and dicarboxylate metabolism, fatty acid metabolism and so on) based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. This study suggested that CA disordered fatty acid metabolism, polysaccharide metabolism and leucine metabolism. Based on PRM analysis, five proteins including CAMK/CAMK1 protein kinase, glucan 1,3-beta-glucosidase, 1,3-beta-glucanosyltransferase, methylcrotonoyl-CoA carboxylase subunit alpha and isovaleryl-CoA dehydrogenase were down-regulated in P. capsici treated with CA. Furthermore, the qRT-PCR analysis showed that the gene expression level of the interested proteins was consistent with the protein expression level, except for CAMK/CAMK1 protein kinase, acetyl-CoA carboxylase and fatty acid synthase subunit alpha.

Conclusions

CA destroyed the metabolic homoeostasisof P. capsici, which led to cell death. This is the first proteomic analysis of P. capsici treated with CA, which may provide an important information for exploring the mechanism of the fungicide CA against P. capsici.

Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. According to the WHO, the disease is one of the top 10 causes of death of people worldwide. Mycobacterium tuberculosis is an intracellular pathogen with an unusually thick, waxy cell wall and a complex life cycle. These factors, combined with M. tuberculosis ability to enter prolonged periods of latency, make the bacterium very difficult to eradicate. The standard treatment of TB requires 6-20months, depending on the drug susceptibility of the infecting strain. The need to take cocktails of antibiotics to treat tuberculosis effectively and the emergence of drug-resistant strains prompts the need to search for new antitubercular compounds. This review provides a perspective on how modern -omic technologies facilitate the drug discovery process for tuberculosis treatment. We discuss how methods of DNA and RNA sequencing, proteomics, and genetic manipulation of organisms increase our understanding of mechanisms of action of antibiotics and allow the evaluation of drugs. We explore the utility of mathematical modeling and modern computational analysis for the drug discovery process. Finally, we summarize how -omic technologies contribute to our understanding of the emergence of drug resistance.

Mycobacterium tuberculosis Rv0580c Impedes the Intracellular Survival of Recombinant Mycobacteria, Manipulates the Cytokines, and Induces ER Stress and Apoptosis in Host Macrophages via NF-κB and p38/JNK Signaling

The Mycobacterium tuberculosis (M. tb) genome encodes a large number of hypothetical proteins, which need to investigate their role in physiology, virulence, pathogenesis, and host interaction. To explore the role of hypothetical protein Rv0580c, we constructed the recombinant Mycobacterium smegmatis (M. smegmatis) strain, which expressed the Rv0580c protein heterologously. We observed that Rv0580c expressing M. smegmatis strain (Ms_Rv0580c) altered the colony morphology and increased the cell wall permeability, leading to this recombinant strain becoming susceptible to acidic stress, oxidative stress, cell wall-perturbing stress, and multiple antibiotics. The intracellular survival of Ms_Rv0580c was reduced in THP-1 macrophages. Ms_Rv0580c up-regulated the IFN-γ expression via NF-κB and JNK signaling, and down-regulated IL-10 expression via NF-κB signaling in THP-1 macrophages as compared to control. Moreover, Ms_Rv0580c up-regulated the expression of HIF-1α and ER stress marker genes via the NF-κB/JNK axis and JNK/p38 axis, respectively, and boosted the mitochondria-independent apoptosis in macrophages, which might be lead to eliminate the intracellular bacilli. This study explores the crucial role of Rv0580c protein in the physiology and novel host-pathogen interactions of mycobacteria.

In Silico Subtractive Proteomics Approach for Identification of Potential Drug Targets in Staphylococcus saprophyticus

Staphylococcus saprophyticus is a uropathogenic bacteria responsible for acute urinary tract infections (UTIs) mainly in young female patients. Patients suffering from urinary catheterization, pregnant patients, the elderly as well as those with nosocomial UTIs are at greater risk of the colonizing S. saprophyticus infection. The causative factors include benign prostatic hyperplasia, indwelling catheter, neurogenic bladder, pregnancy, and history of frequent UTIs. Recent findings have exhibited that S. saprophyticus is resistant to several antimicrobial agents. Moreover, there is a global concern regarding the increasing level of antimicrobial resistance, which leads to treatment failure and reduced effectiveness of broad-spectrum antimicrobials. Therefore, a novel approach is being utilized to combat resistant microbes since the past few years. Subtractive proteome analysis has been performed with the entire proteome of S. saprophyticus strain American Type Culture Collection (ATCC) 15305 using several bioinformatics servers and software. The proteins that were non-homologous to humans and bacteria were identified for metabolic pathway analysis. Only four cytoplasmic proteins were found possessing the potential of novel drug target candidates. The development of innovative therapeutic agents by targeting the inhibition of any essential proteins may disrupt the metabolic pathways specific to the pathogen, thus causing destruction as well as eradication of the pathogen from a particular host. The identified targets can facilitate in designing novel and potent drugs against S. saprophyticus strain ATCC 15305.

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.