Subtractive genomics approach towards the identification of novel therapeutic targets against human Bartonella bacilliformis

Cryosphere: a frozen home of microbes and a potential source for drug discovery

The world is concerned about the emergence of pathogens and the occurrence and spread of antibiotic resistance among pathogens. Drug development requires time to combat these issues. Consequently, drug development from natural sources is unavoidable. Cryosphere represents a gigantic source of microbes that could be the bioprospecting source of natural products with unique scaffolds as molecules or drug templates. This review focuses on the novel source of drug discovery and cryospheric environments as a potential source for microbial metabolites having potential medicinal applications. Furthermore, the problems encountered in discovering metabolites from cold-adapted microbes and their resolutions are discussed. By adopting modern practical approaches, the discovery of bioactive compounds might fulfill the demand for new drug development.

The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials

Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.

Identification of repurposable drug targets in Mycoplasma pneumoniae using subtractive genomics, molecular docking and dynamics simulation

Mycoplasma pneumoniae is a significant causative agent of community-acquired pneumonia, causing acute inflammation in the upper and lower respiratory tract as well as extrapulmonary syndromes. In particular, the elderly and infants are at greater risk of developing severe, life-threatening pneumonia caused by M. pneumoniae. Yet, the global increase in antimicrobial resistance against antibiotics for the treatment of M. pneumoniae infection highlights the urgent need to explore novel drug targets. To this end, bioinformatics approaches, such as subtractive genomics, can be employed to identify specific metabolic pathways and essential proteins unique to the pathogen that could be potential targets for new drugs. In this study, we implemented a subtractive genomics approach to identify 61 metabolic pathways and 42 essential proteins that are unique to M. pneumoniae. A subsequent screening in the DrugBank database revealed three druggable proteins with similarity to FDA-approved small-molecule drugs, and finally, the compound CHEBI:97093 was identified as a promising novel putative drug target. These findings can provide crucial insights for the development of highly effective drugs that selectively inhibit the pathogen-specific metabolic pathways, leading to better management and treatment of M. pneumoniae infections.

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.

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.

Identification of a Potential Vaccine against Treponema pallidum Using Subtractive Proteomics and Reverse-Vaccinology Approaches

Syphilis, a sexually transmitted infection, is a deadly disease caused by Treponema pallidum. It is a Gram-negative spirochete that can infect nearly every organ of the human body. It can be transmitted both sexually and perinatally. Since syphilis is the second most fatal sexually transmitted disease after AIDS, an efficient vaccine candidate is needed to establish long-term protection against infections by T. pallidum. This study used reverse-vaccinology-based immunoinformatic pathway subtractive proteomics to find the best antigenic proteins for multi-epitope vaccine production. Six essential virulent and antigenic proteins were identified, including the membrane lipoprotein TpN32 (UniProt ID: O07950), DNA translocase FtsK (UniProt ID: O83964), Protein Soj homolog (UniProt ID: O83296), site-determining protein (UniProt ID: F7IVD2), ABC transporter, ATP-binding protein (UniProt ID: O83930), and Sugar ABC superfamily ATP-binding cassette transporter, ABC protein (UniProt ID: O83782). We found that the multiepitope subunit vaccine consisting of 4 CTL, 4 HTL, and 11 B-cell epitopes mixed with the adjuvant TLR-2 agonist ESAT6 has potent antigenic characteristics and does not induce an allergic response. Before being docked at Toll-like receptors 2 and 4, the developed vaccine was modeled, improved, and validated. Docking studies revealed significant binding interactions, whereas molecular dynamics simulations demonstrated its stability. Furthermore, the immune system simulation indicated significant and long-lasting immunological responses. The vaccine was then reverse-transcribed into a DNA sequence and cloned into the pET28a (+) vector to validate translational activity as well as the microbial production process. The vaccine developed in this study requires further scientific consensus before it can be used against T. pallidum to confirm its safety and efficacy.

Integrated Bioinformatics-Based Subtractive Genomics Approach to Decipher the Therapeutic Drug Target and Its Possible Intervention against Brucellosis

Brucella suis, one of the causative agents of brucellosis, is Gram-negative intracellular bacteria that may be found all over the globe and it is a significant facultative zoonotic pathogen found in livestock. It may adapt to a phagocytic environment, reproduce, and develop resistance to harmful environments inside host cells, which is a crucial part of the Brucella life cycle making it a worldwide menace. The molecular underpinnings of Brucella pathogenicity have been substantially elucidated due to comprehensive methods such as proteomics. Therefore, we aim to explore the complete Brucella suis proteome to prioritize the novel proteins as drug targets via subtractive proteo-genomics analysis, an effort to conjecture the existence of distinct pathways in the development of brucellosis. Consequently, 38 unique metabolic pathways having 503 proteins were observed while among these 503 proteins, the non-homologs (n = 421), essential (n = 350), drug-like (n = 114), virulence (n = 45), resistance (n = 42), and unique to pathogen proteins were retrieved from Brucella suis. The applied subsequent hierarchical shortlisting resulted in a protein, i.e., isocitrate lyase, that may act as potential drug target, which was finalized after the extensive literature survey. The interacting partners for these shortlisted drug targets were identified through the STRING database. Moreover, structure-based studies were also performed on isocitrate lyase to further analyze its function. For that purpose, ~18,000 ZINC compounds were screened to identify new potent drug candidates against isocitrate lyase for brucellosis. It resulted in the shortlisting of six compounds, i.e., ZINC95543764, ZINC02688148, ZINC20115475, ZINC04232055, ZINC04231816, and ZINC04259566 that potentially inhibit isocitrate lyase. However, the ADMET profiling showed that all compounds fulfill ADMET properties except for ZINC20115475 showing positive Ames activity; whereas, ZINC02688148, ZINC04259566, ZINC04232055, and ZINC04231816 showed hepatoxicity while all compounds were observed to have no skin sensitization. In light of these parameters, we recommend ZINC95543764 compound for further experimental studies. According to the present research, which uses subtractive genomics, proteins that might serve as therapeutic targets and potential lead options for eradicating brucellosis have been narrowed down.

Antimicrobial Compounds from Microorganisms

Antimicrobial resistance is an exigent public health concern owing to the emergence of novel strains of human resistant pathogens and the concurrent rise in multi-drug resistance. An influx of new antimicrobials is urgently required to improve the treatment outcomes of infectious diseases and save lives. Plant metabolites and bioactive compounds from chemical synthesis have found their efficacy to be dwindling, despite some of them being developed as drugs and used to treat human infections for several decades. Microorganisms are considered untapped reservoirs for promising biomolecules with varying structural and functional antimicrobial activity. The advent of cost-effective and convenient model organisms, state-of-the-art molecular biology, omics technology, and machine learning has enhanced the bioprospecting of novel antimicrobial drugs and the identification of new drug targets. This review summarizes antimicrobial compounds isolated from microorganisms and reports on the modern tools and strategies for exploiting promising antimicrobial drug candidates. The investigation identified a plethora of novel compounds from microbial sources with excellent antimicrobial activity against disease-causing human pathogens. Researchers could maximize the use of novel model systems and advanced biomolecular and computational tools in exploiting lead antimicrobials, consequently ameliorating antimicrobial resistance.

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.

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.

Genome-wide screening of vaccine targets prioritization and reverse vaccinology aided design of peptides vaccine to enforce humoral immune response against Campylobacter jejuni

Campylobacter jejuni, gram-negative bacteria, is an infectious agent of foodborne disease-causing bloody diarrhea, abdominal pain, fever, Guillain-Barré syndrome (GBS) and Miller Fisher syndrome in humans. Campylobacter spp. with multidrug resistance to fluoroquinolones, tetracycline, and erythromycin are reported. Hence, an effective vaccine candidate would provide long-term immunity against C. jejuni infections. Thus, we used a subtractive proteomics pipeline to prioritize essential proteins, which impart a critical role in virulence, replication and survival. Five proteins, i.e. Single-stranded DNA-binding protein, UPF0324 membrane protein Cj0999c, DNA translocase FtsK, 50S ribosomal protein L22, and 50S ribosomal protein L1 were identified as virulent proteins and selected for vaccine designing. We reported that the multi-epitopes subunit vaccine based on CTL, HTL and B-cell epitopes combination possess strong antigenic properties and associates no allergenic reaction. Further investigation revealed that the vaccine interacts with the immune receptor (TLR-4) and triggered the release of primary and secondary immune factors. Moreover, the CAI and GC contents obtained through codon optimization were reported to be 0.93 and 53% that confirmed a high expression in the selected vector. The vaccine designed in this study needs further scientific consensus and will aid in managing C. jejuni infections.

Target shortage and less explored multiple targeting: hurdles in the development of novel antifungals but overcome/addressed effectively through structural bioinformatics

Billions of people are affected by fungal infection worldwide, which is a major cause of morbidity and mortality in humans. Regardless of development in the field of antifungal therapeutics over the last three decades, multidrug resistance and limited efficacy of available antifungal drugs are very prominent and still a great hurdle in the patient treatment. The current antifungal pipeline is dry, which is needed to be strengthened. Although several strategies have been implemented over time to discover novel promising antifungal leads, but very little emphasis has been given to address the gap of fungal target identification. Undeniably, the need for identifying novel cellular fungal targets is as vital as discovering novel antifungal leads and a structural bioinformatics approach could be an effective strategy in this regard. To address the issue, we have performed in silico screening to identify a few potent multiple targeting ligands and their respective antifungal targets. Thus, we offer a perspective on the phenomena of 'target shortage' and least explored 'multiple targeting' being the most underrated challenges in antifungal drug discovery. 'Structural bioinformatics' could be an effective approach in the recognition of new/innovative antifungal target and identification/development of novel antifungal lead molecule aiming multiple molecular targets of the fungal pathogen.