A novel in silico approach to identify potential therapeutic targets in human bacterial pathogens

An immuno-informatics approach for annotation of hypothetical proteins and multi-epitope vaccine designed against the Mpox virus

A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.

Identification, prioritization, and evaluation of RlpA protein as a target against multidrug-resistant Pseudomonas aeruginosa

According to the World Health Organization, infectious diseases, particularly those caused by multidrug-resistant bacteria (MDR), are projected to claim the lives of 15 million people by 2050. Septicemia carries a higher morbidity and mortality rate than infections caused by susceptible Pseudomonas aeruginosa, and MDR-mediated ocular infections can lead to impaired vision and blindness. To identify and develop a potential drug against MDR P. aeruginosa, we employed in silico reverse genetics-based target mining, drug prioritization, and evaluation. Rare Lipoprotein A (RlpA) was selected as the target protein, and its crystal structure was geometrically optimized. Molecular docking and virtual screening analyses revealed that RlpA exhibits strong binding affinity with 11 compounds. Among these, 3-chlorophthalic acid was evaluated, and subsequent in vitro assays demonstrated significant anti-Pseudomonas activity with negligible cytotoxicity. The compound was further evaluated against both drug-susceptible and MDR P. aeruginosa strains in vitro, with cytotoxicity assessed using an MTT assay. The study demonstrated that 3-chlorophthalic acid exhibits potent anti-Pseudomonas activity with minimal toxicity to host cells. Consequently, this compound emerges as a promising candidate against MDR P. aeruginosa, warranting further investigation.

An insight into MDR Acinetobacter baumannii infection and its pathogenesis: Potential therapeutic targets and challenges

Acinetobacter baumannii is observed as a common species of Gram-negative bacteria that exist in soil and water. Despite being accepted as a typical component of human skin flora, it has become an important opportunistic pathogen, especially in healthcare settings. The pathogenicity of A. baumannii is attributed to its virulence factors, which include adhesins, pili, lipopolysaccharides, outer membrane proteins, iron uptake systems, autotransporter, secretion systems, phospholipases etc. These elements provide the bacterium the ability to cling to and penetrate host cells, get past the host immune system, and destroy tissue. Its infection is a major contributor to human pathophysiological conditions including pneumonia, bloodstream infections, urinary tract infections, and surgical site infections. It is challenging to treat infections brought on by this pathogen since this bacterium has evolved to withstand numerous drugs and further emergence of drug-resistant A. baumannii results in higher rates of morbidity and mortality. The long-term survival of this bacterium on surfaces of medical supplies and hospital furniture facilitates its frequent spread in humans from one habitat to another. There is a need for urgent investigations to find effective drug targets for A. baumannii as well as designing novel drugs to reduce the survival and spread of infection. In the current review, we represent the specific features, pathogenesis, and molecular intricacies of crucial drug targets of A. baumannii. This would also assist in proposing strategies and alternative therapies for the prevention and treatment of A. baumannii infections and their spread.

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Structural and Functional Annotation and Molecular Docking Analysis of a Hypothetical Protein from Neisseria gonorrhoeae: An In-Silico Approach

Background

Worldwide, Neisseria gonorrhoeae-related sexually transmitted infections (STIs) continue to be of significant public health concern. This obligate-human pathogen has developed a number of defenses against both innate and adaptive immune responses during infection, some of which are mediated by the pathogen's proteins. Hence, the uncharacterized proteins of N. gonorrhoeae can be annotated to get insight into the unique functions of this organism related to its pathogenicity and to find a more efficient therapeutic target.

Methods

In this study, a hypothetical protein (HP) of N. gonorrhoeae was chosen for analysis and an in-silico approach was used to explore various properties such as physicochemical characteristics, subcellular localization, secondary structure, 3D structures, and functional annotation of that HP. Finally, a molecular docking analysis was performed to design an epitope-based vaccine against that HP.

Results

This study has identified the potential role of the chosen HP of N. gonorrhoeae in plasmid transfer, cell cycle control, cell division, and chromosome partitioning. Acidic nature, thermal stability, cytoplasmic localization of the protein, and some of its other physicochemical properties have also been identified through this study. Molecular docking analysis has demonstrated that one of the T cell epitopes of the protein has a significant binding affinity with the human leukocyte antigen HLA-B∗15 : 01.

Conclusions

The in-silico characterization of this protein will help us understand molecular mechanism of action of N. gonorrhoeae and get an insight into novel therapeutic identification processes. This research will, therefore, enhance our knowledge to find new medications to tackle this potential threat to humankind.

Pathogenomic in silico approach identifies NSP-A and Fe-IIISBP as possible drug targets in Neisseria Meningitidis MC58 and development of pharmacophores as novel therapeutic candidates

Meningitis creates a life-threatening clinical crisis. Moreover, the administered antibiotics result into multi-drug resistance, thereby necessitating development of alternative therapeutic strategies. This study aimed at identifying novel-drug targets in Neisseria meningitidis and therapeutic molecules which can be exploited for the treatment of meningitis. Novel targets were identified by applying a pathogenomic approach involving protein data-set mining, subtractive channel analysis and subsequent qualitative analysis comprising of in silico pharmacokinetics, molecular docking and pharmacophore generation. Pathogenomic studies revealed Neisserial Surface Protein A (NSP-A) and Iron-III-Substrate Binding Protein (Fe-IIISBP) as potential targets. Two pharmacophore models comprising of 2-(biaryl) carbapenems, efavirenz, praziquantel and pyrimethamine for NSP-A and 2-(biaryl) carbapenems, trimipramine and pyrimethamine for Fe-IIISBP, showed successful docking, followed drug-likeness criteria and generated pharmacophore model with a score of 8.08 and 8.818, respectively, which had further been docked to the target stably. Thus, our study identifies NSP-A and Fe-IIISBP as novel targets in Neisseria meningitidis for which 2-(biaryl) carbapenems, efavirenz, praziquantel, trimipramine and pyrimethamine may be employed for effective treatment of meningitis.

Proteomic Characterization and Target Identification Against Streptococcus mutans Under Bacitracin Stress Conditions Using LC-MS and Subtractive Proteomics

The aim of the present study, is to identify potential targets against the highly pathogenic bacteria Streptococcus mutans that causes dental caries as well as the deadly infection of endocarditis. The powerful and highly sensitive technique of liquid chromatography-mass spectrometry (LC–MS/MS) identified 321 proteins of S. mutans when grown under stressful conditions induced by the antibiotic bacitracin. These 321 proteins were subjected to the insilico method of subtractive proteomics to screen out potential targets by utilizing different analyses like CD-HIT, non-homologous sequence screening, KEGG pathway, essentiality screening, gut-flora non-homology, and codon usage analysis. A database of essential proteins was employed to find sequence homology of non-paralogous proteins to determine proteins which are essential for bacterial survival. Cellular localization analysis of the selected proteins was done to localize them inside the cell along with physico-chemical characterization and druggability analysis. Using computational tools, 22 proteins out of 321, that are functionally distinguishable from their human counterparts and passed the criterion of a potential therapeutic candidate were identified. The selected proteins comprise central energy metabolic proteins, virulence factors, proteins of the sortase family, and essentiality factors. The presented analyses identified proteins of the sortase family, which appear as key therapeutic targets against caries infection. These proteins regulate a number of virulence factors, thus can be simultaneously inhibited to obstruct multiple virulence pathways.

Comparative proteomic analysis to annotate the structural and functional association of the hypothetical proteins of S. maltophilia k279a and predict potential T and B cell targets for vaccination

Stenotrophomonas maltophilia is a multidrug-resistant bacterium with no precise clinical treatment. This bacterium can be a vital cause for death and different organ failures in immune-compromised, immune-competent, and long-time hospitalized patients. Extensive quorum sensing capability has become a challenge to develop new drugs against this pathogen. Moreover, the organism possesses about 789 proteins which function, structure, and pathogenesis remain obscured. In this piece of work, we tried to enlighten the aforementioned sectors using highly reliable bioinformatics tools validated by the scientific community. At first, the whole proteome sequence of the organism was retrieved and stored. Then we separated the hypothetical proteins and searched for the conserved domain with a high confidence level and multi-server validation, which resulted in 24 such proteins. Furthermore, all of their physical and chemical characterizations were performed, such as theoretical isoelectric point, molecular weight, GRAVY value, and many more. Besides, the subcellular localization, protein-protein interactions, functional motifs, 3D structures, antigenicity, and virulence factors were also evaluated. As an extension of this work, 'RTFAMSSER' and 'PAAPQPSAS' were predicted as potential T and B cell epitopes, respectively. We hope our findings will help in better understating the pathogenesis and smoothen the way to the cure.

Computational Identification of Essential Enzymes as Potential Drug Targets in Shigella flexneri Pathogenesis Using Metabolic Pathway Analysis and Epitope Mapping

Shigella flexneri is a facultative intracellular pathogen that causes bacillary dysentery in humans. Infection with S. flexneri can result in more than a million deaths yearly and most of the victims are children in developing countries. Therefore, identifying novel and unique drug targets against this pathogen is instrumental to overcome the problem of drug resistance to the antibiotics given to patients as the current therapy. In this study, a comparative analysis of the metabolic pathways of the host and pathogen was performed to identify this pathogen's essential enzymes for the survival and propose potential drug targets. First, we extracted the metabolic pathways of the host, Homo sapiens, and pathogen, S. flexneri, from the KEGG database. Next, we manually compared the pathways to categorize those that were exclusive to the pathogen. Further, all enzymes for the 26 unique pathways were extracted and submitted to the Geptop tool to identify essential enzymes for further screening in determining the feasibility of the therapeutic targets that were predicted and analyzed using PPI network analysis, subcellular localization, druggability testing, gene ontology and epitope mapping. Using these various criteria, we narrowed it down to prioritize 5 novel drug targets against S. flexneri and one vaccine drug targets against all strains of Shigella. Hence, we suggest the identified enzymes as the best putative drug targets for the effective treatment of S. flexneri.

hTLR2 interacting peptides of pathogenic leptospiral outer membrane proteins

To adapt into the host system from moist environment Leptospira alter their gene expression by inducing differential expression of the genes encoding virulence factors. Knowledge about the molecular pathogenesis and virulent evolution remains limited to Leptospira. The pathogenic organism sense the environmental changes mainly through their outer membrane proteins that in-turn activates the signal transduction pathways to overcome the stress to adaptation into host system and to evade immunity. In this present study, we analyzed the expression profile of virulence associated OMPs regulated under various stress conditions like temperatures, iron deprivation, osmotic stress and low to high passages in single scale and characterized the selected proteins by MALDI-TOF MS/MS and their role in pathogenesis were predicted by implying in-silico analysis. To identify differential expression profile, the extracted OMPs were resolved through 2DE and compared the OMPs profile from various in-vivo like conditions in single scale and found 61 upregulated OMPs and three potentially virulent proteins were earmarked for their significance in pathogenesis. Further, the in-silico analysis revealed that differentially expressed protein has MHC-I T-cell, MHC-II T-cell and B-cell epitopes which showed an interaction between human TLR2 proteins confirmed by CABS docking and interaction network unveiled to understand the leptospiral virulent mechanism and host adaptation.

Identification of novel therapeutic target and epitopes through proteome mining from essential hypothetical proteins in Salmonella strains: An In silico approach towards antivirulence therapy and vaccine development

Salmonella strains are responsible for a huge mortality rate through foodborne ailment in the world that necessitated the discovery of novel drugs and vaccines. Essential hypothetical proteins (EHPs), whose structures and functions were previously unknown, could serve as potential therapeutic and vaccine targets. Antivirulence therapy shall emerge as a superior therapeutic approach that uses virulence factors as drug targets. This study annotated the biological functions of 96 out of total 106 essential hypothetical proteins in five strains of Salmonella and classified into nine important protein categories. 34 virulence factors were predicted among the EHPs, out of which, 11 were identified to be pathogen specific potential drug targets for antivirulence therapy. These targets were non-homologous to both human and gut microbiota proteome to avoid cross-reactivity with them. Seven identified targets had druggable property, while the rest four targets were novel targets. Four identified targets (DEG10320148, DEG10110027, DEG10110040 and DEG10110142) had antigenic properties and were further classified as: two membrane-bound Lipid-binding transmembrane proteins, a Zinc-binding membrane protein and an extracellular glycosylase. These targets could be potentially used for the development of subunit vaccines. The study further identified 11 highly conserved and exposed epitope sequences from these 4 vaccine targets. The three-dimensional structures of the vaccine targets were also elucidated along with highlighting the conformation of the epitopes. This study identified potential therapeutic targets for antivirulence therapy against Salmonella. It would therefore instigate in novel drug designing as well as provide important leads to new Salmonella vaccine development.

Identification of potential therapeutic targets in Neisseria gonorrhoeae by an in-silico approach

Neisseria gonorrhoeae is a gram negative diplococcus bacterium and the causative agent of the sexually transmitted disease Gonorrhea. It has been recently given the status of "superbug" by World Health Organization because of the increasing antibiotic resistance and unavailability of a viable vaccine candidate. Over recent years, there have been increasing reports about the use of subtractive genomics to identify potential drug and vaccine targets. Our study utilizes codon biasing, a tool to identify the essential genes, in N. gonorrhoeae that could be utilized as novel therapeutic targets for drug or vaccine development. Through the screening of 2350 total genes, we present a list of 29 such drug candidate genes based on codon adaptation. Through the data-mining with BLAST2GO and InterProScan databases, we could predict the function of these 29 genes. These genes are involved in pivotal cellular functions like DNA replication, energy synthesis and metabolites production. This study also shortlists the essential genes of N. gonorrhoeae that could be used to target Neisseria. We identified a molecule/drug which can be used to target essential protein DapD (succinyltransferase).

In Silico Identification of Probable Drug and Vaccine Candidates Against Antibiotic-Resistant Acinetobacter baumannii

Acinetobacter baumannii is known as a Gram-negative bacterium that has become one of the most important health problems due to antibiotic resistance. Today, numerous efforts are being made to find new antibiotics against this nosocomial pathogen. As an alternative solution, finding bacterial target(s), necessary for survival and spread of most resistant strains, can be a benefit exploited in drug and vaccine design. In this study, a list of extensive drug-resistant and carbapenem-resistant (multidrug resistant) A. bumannii strains with complete sequencing of genome were prepared and common hypothetical proteins (HPs) composed of more than 200 amino acids were selected. Then, a number of bioinformatics tools were combined for functional assignments of HPs using their sequence. Overall, among 18 in silico investigated proteins, the results showed that 7 proteins implicated in transcriptional regulation, pilus assembly, protein catabolism, fatty acid biosynthesis, adhesion, urea catalysis, and hydrolysis of phosphate monoesters have theoretical potential of involvement in successful survival and pathogenesis of A. baumannii. In addition, immunological analyses with prediction softwares indicated 4 HPs to be probable vaccine candidates. The outcome of this work will be helpful to find novel vaccine design candidates and therapeutic targets for A. baumannii through experimental investigations.

In silico characterization of hypothetical proteins from Orientia tsutsugamushi str. Karp uncovers virulence genes

Scrub typhus also known as bush typhus is a disease with symptoms similar to Chikungunya infection. It is caused by a gram-negative bacterium Orientia tsutsugamushi which resides in its vertebrate host, Mites. The genome of Orientia tsutsugamushi str. Karp encodes for 1,563 proteins, of which 344 are characterized as hypothetical ones. In the present study, we tried to identify the probable functions of these 344 hypothetical proteins (HPs). All the characterized hypothetical proteins (HPs) belong to the various protein classes like enzymes, transporters, binding proteins, metabolic process and catalytic activity and kinase activity. These hypothetical proteins (HPs) were further analyzed for virulence factors with 62 proteins identified as the most virulent proteins among these hypothetical proteins (HPs). In addition, we studied the protein sequence similarity network for visualizing functional trends across protein superfamilies from the context of sequence similarity and it shows great potential for generating testable hypotheses about protein structure-function relationships. Furthermore, we calculated toplogical properties of the network and found them to obey network power law distributions showing a fractal nature. We also identifed two highly interconnected modules in the main network which contained five hub proteins (KJV55465, KJV56211, KJV57212, KJV57203 and KJV57216) having 1.0 clustering coefficient. The structural modeling (2D and 3D structure) of these five hub proteins was carried out and the catalytic site essential for its functioning was analyzed. The outcome of the present study may facilitate a better understanding of the mechanism of virulence, pathogenesis, adaptability to host and up-to-date annotations will make unknown genes easy to identify and target for experimentation. The information on the functional attributes and virulence characteristic of these hypothetical proteins (HPs) are envisaged to facilitate effective development of novel antibacterial drug targets of Orientia tsutsugamushi.

Structure-based drug target prioritisation and rational drug design for targeting Chlamydia trachomatis eye infections

Chlamydia trachomatis (C.t) is a major causative of infectious blindness in world. It is a real challenge to combat Chlamydial infection as it is an intracellular pathogen. Hence, it is essential to determine the most potential targets of C.t in order to inhibit or suppress its virulence during its infectious phase. Thus, in this study, the highly expressed-cum-most essential genes reported through our earlier study were reprioritized by structure-based comparative binding site analysis with host proteome. Therefore, computational approaches involving molecular modelling, large-scale binding site prediction and comparison, molecular dynamics simulation studies were performed to narrow down the most potential targets. Furthermore, high-throughput virtual screening and ADMETox were also performed to identify potential hits that shall efficiently inhibit the prioritised targets. Hence, by this study we report Pyruvoyl-dependent arginine decarboxylase (PvlArgDC), DNA-repair protein (RecO) and porin (outer membrane protein) as the most viable targets of C.t which can be potentially targeted by compounds, NSC_13086, MFCD00276409, MFCD05662003, respectively. AbbreviationsC.tChlamydia trachomatisSTDSexually transmitted diseaseHTVSHigh-throughput virtual screeningADMEToxAbsorption, Distribution, Metabolism, Excretion and ToxicityPMPocketMatchMDMolecular Dynamics simulationSPStandard precisionXPExtra precisionMMGBSAMolecular mechanics energies combined with generalised Born and surface area continuum solvationOMPOuter membrane proteinPvlArgDCPyruvoyl-dependent arginine decarboxylaseRecORecombination protein O.Communicated by Ramaswamy H. Sarma.

Comparative assessment of the therapeutic drug targets of C. botulinum ATCC 3502 and C. difficile str. 630 using in silico subtractive proteomics approach

Growing antimicrobial resistance of the pathogens against multiple drugs posed a serious threat to the human health worldwide. This fueled the need of identifying the novel therapeutic targets that can be used for developing new class of the drugs. Recently, there is a substantial rise in the rate of Clostridium infections as well as in the emergence of virulent and antibiotic resistant strains. Hence, there is an urgent need for the identification of potential therapeutic targets and the development of new drugs for the treatment and prevention of Clostridium infections. In the present study, a combinatorial approach involving systems biology and comparative genomics strategy was tested against Clostridium botulinum ATCC 3502 and Clostridium difficile str. 630 pathogens, to render potential therapeutic target at qualitative and quantitative level. This resulted in the identification of five common (present in both the pathogens, 34 in C. botulinum ATCC 3502 and 42 in C. difficile str. 630) drug targets followed by virtual screening-based identification of potential inhibitors employing molecular docking and molecular dynamics simulations. The identified targets will provide a solid platform for the designing of novel wide-spectrum lead compounds capable of inhibiting their catalytic activities against multidrug-resistant Clostridium in the near future.

Genome-wide codon usage profiling of ocular infective Chlamydia trachomatis serovars and drug target identification

Chlamydia trachomatis (C.t) is a Gram-negative obligate intracellular bacteria and is a major causative of infectious blindness and sexually transmitted diseases. Among the varied serovars of this organism, A, B and C are reported as prominent ocular pathogens. Genomic studies of these strains shall aid in deciphering potential drug targets and genomic influence on pathogenesis. Hence, in this study we performed deep statistical profiling of codon usage in these serovars. The overall base composition analysis reveals that these serovars are over biased to AU than GC. Similarly, relative synonymous codon usage also showed preference towards A/U ending codons. Parity Rule 2 analysis inferred unequal distribution of AT and GC, indicative of other unknown factors acting along with mutational pressure to influence codon usage bias (CUB). Moreover, absolute quantification of CUB also revealed lower bias across these serovars. The effect of natural selection on CUB was also confirmed by neutrality plot, reinforcing natural selection under mutational pressure turned to be a pivotal role in shaping the CUB in the strains studied. Correspondence analysis (COA) clarified that, C.t C/TW-3 to show a unique trend in codon usage variation. Host influence analysis on shaping the codon usage pattern also inferred some speculative relativity. In a nutshell, our finding suggests that mutational pressure is the dominating factor in shaping CUB in the strains studied, followed by natural selection. We also propose potential drug targets based on cumulative analysis of strand bias, CUB and human non-homologue screening.

Drug Target Identification and Elucidation of Natural Inhibitors for Bordetella petrii: An In Silico Study

Environmental microbes like Bordetella petrii has been established as a causative agent for various infectious diseases in human. Again, development of drug resistance in B. petrii challenged to combat against the infection. Identification of potential drug target and proposing a novel lead compound against the pathogen has a great aid and value. In this study, bioinformatics tools and technology have been applied to suggest a potential drug target by screening the proteome information of B. petrii DSM 12804 (accession No. PRJNA28135) from genome database of National Centre for Biotechnology information. In this regards, the inhibitory effect of nine natural compounds like ajoene (Allium sativum), allicin (A. sativum), cinnamaldehyde (Cinnamomum cassia), curcumin (Curcuma longa), gallotannin (active component of green tea and red wine), isoorientin (Anthopterus wardii), isovitexin (A. wardii), neral (Melissa officinalis), and vitexin (A. wardii) have been acknowledged with anti-bacterial properties and hence tested against identified drug target of B. petrii by implicating computational approach. The in silico studies revealed the hypothesis that lpxD could be a potential drug target and with recommendation of a strong inhibitory effect of selected natural compounds against infection caused due to B. petrii, would be further validated through in vitro experiments.

Genome analysis of Chlamydia trachomatis for functional characterization of hypothetical proteins to discover novel drug targets

C. trachomatis is a Gram-negative bacterium that causes trachoma and sexually transmitted disease (STD) Chlamydia in humans. Chlamydial genital infections are the most frequent among all communicable diseases. The D/UW-3/Cx strain of C. trachomatis contains 935 genes and three pseudogenes. Out of these genes, 887 genes code for proteins while six for rRNA, 37 tRNA, and three genes translate into other RNAs. The proteome of C. trachomatis made of 887 proteins contains 269 Hypothetical proteins (HPs) that are subjected to functional characterization. This study suggests some known methods of functional characterization of such HPs. All of these methods are explicitly used to assign functions to the HPs with the accuracy of more than 90%. After extensive analysis of all the HPs, we have successfully assigned functions to 89 HPs with high precision. In the newly assigned HPs, there are enzymes, transporters, binding proteins, proteins involved in biosynthesis and regulatory processes and proteins with miscellaneous functions. The study suggests that the functionally annotated HPs may play a vital role in the growth and pathogenesis of this organism. Therefore, they can be considered potential drug targets.

Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration

Background:Shigella flexneri is a gram negative bacteria that causes the infectious disease “shigellosis.” S. flexneri is responsible for developing diarrhea, fever, and stomach cramps in human. Antibiotics are mostly given to patients infected with shigella. Resistance to antibiotics can hinder its treatment significantly. Upon identification of essential therapeutic targets, vaccine and drug could be effective therapy for the treatment of shigellosis.

Methods: The study was designed for the identification and qualitative characterization for potential drug targets from S. flexneri by using the subtractive proteome analysis. A set of computational tools were used to identify essential proteins those are required for the survival of S. flexneri. Total proteome (13,503 proteins) of S. flexneri was retrieved from NCBI and further analyzed by subtractive channel analysis. After identification of the metabolic proteins we have also performed its qualitative characterization to pave the way for the identification of promising drug targets.

Results: Subtractive analysis revealed that a list of 53 targets of S. flexneri were human non-homologous essential metabolic proteins that might be used for potential drug targets. We have also found that 11 drug targets are involved in unique pathway. Most of these proteins are cytoplasmic, can be used as broad spectrum drug targets, can interact with other proteins and show the druggable properties. The functionality and drug binding site analysis suggest a promising effective way to design the new drugs against S. flexneri.

Conclusion: Among the 53 therapeutic targets identified through this study, 13 were found highly potential as drug targets based on their physicochemical properties whilst only one was found as vaccine target against S. flexneri. The outcome might also be used as module as well as circuit design in systems biology.

Structural and functional annotation of human FAM26F: A multifaceted protein having a critical role in the immune system

BACKGROUND

Human immune system is a complex amalgam of a greatly diverse ensemble comprising of various cellular and non-cellular components, including proteins. FAM26F (family with sequence similarity 26, member F) is a relatively recently identified gene reported to play important role in diverse immune responses. Numerous studies have reported FAM26F to be differentially expressed in several viral, bacterial and parasitic infections, in certain pathophysiological conditions such as heart and liver transplantation, and in several cancers. FAM26F has also been found to be upregulated by various stimulants such as polyI:C, LPS, INF gamma and TNF alpha, and via various anticipated pathways including TLR3, TLR4 IFN-β and Dectin-1. Moreover, the synergistic expression of FAM26F on both NK-cells and myeloid dendritic cells is required to activate NK-cells against tumors via its cytoplasmic tail, thus emphasizing the therapeutic potential of FAM26F for NK sensitive tumors. Although a considerable amount of evidence is present regarding the potential role of FAM26F in immune modulation, the exact function and modulatory pathways of this gene are yet to be elucidated. We aimed to completely characterize FAM26F in order to apprehend its function and role in the immune responses.

RESULTS

The results revealed human FAM26F to be located at chromosomal position 6q22.1. FAM26F mRNA contains 1141bp coding region encoding a 315 amino acid long, stable protein that has been well-conserved throughout evolution. It is a signal peptide deprived transmembrane protein that is secreted through non-classical pathway. The presence of a single well-conserved Ca_hom_mod domain indicated FAM26F to be a cation channel involved in the transport of molecules. A potential N-glycosylation and 14 phosphorylation sites were also predicted, along with four interacting partners of FAM26F. The secondary and tertiary structures of FAM26F were determined. Moreover, the presence of an immunoglobulin-like fold in FAM26F emphasized its role in immune responses.

CONCLUSION

This is the first in silico structural and functional characterization of FAM26F which will be helpful in better understanding the role of FAM26F in the context of the immune system and may also lead to the identification of novel therapeutic targets.

Classification and Functional Analyses of Putative Conserved Proteins from Chlamydophila pneumoniae CWL029

Chlamydophila pneumoniae, a Gram-negative bacterium belongs to the family Chlamydiaceae, is known to cause community-acquired pneumonia and bronchitis. There is a need for genomic analyses of C. pneumoniae as its chronic infections result in reactive airway disease, lung cancer and asthma. Recent advancement in the sequencing techniques led to the generation of large genomic data. In order to utilize these data, sequence-based function predictions were used for annotating the uncharacterized genes. The genome of C. pneumoniae encodes 1052 proteins, which include a group of 366 functionally uncharacterized proteins, known as "hypothetical proteins" (HPs). Functions of these HPs were predicted by utilizing an integrated approach that combines varieties of bioinformatics tools. The functions of 142 proteins were successfully predicted and categorized into different classes of enzymes, transport proteins, binding proteins and virulence factors. Among these functionally annotated HPs, we were able to identify 12 virulent HPs. Furthermore, the HP with the highest virulence score was subjected to molecular dynamics (MD) simulations to better understand their dynamical behavior in explicit water conditions. These analyses could be utilized for an in-depth understanding of virulence mechanism. The functional knowledge of these proteins could be useful in drug design and discovery process of infections caused by C. pneumoniae.

Identification of functional candidates amongst hypothetical proteins of Treponema pallidum ssp. pallidum

Syphilis is a globally occurring venereal disease, and its infection is propagated through sexual contact. The causative agent of syphilis, Treponema pallidum ssp. pallidum, a Gram-negative sphirochaete, is an obligate human parasite. Genome of T. pallidum ssp. pallidum SS14 strain (RefSeq NC_010741.1) encodes 1,027 proteins, of which 444 proteins are known as hypothetical proteins (HPs), i.e., proteins of unknown functions. Here, we performed functional annotation of HPs of T. pallidum ssp. pallidum using various database, domain architecture predictors, protein function annotators and clustering tools. We have analyzed the sequences of 444 HPs of T. pallidum ssp. pallidum and subsequently predicted the function of 207 HPs with a high level of confidence. However, functions of 237 HPs are predicted with less accuracy. We found various enzymes, transporters, binding proteins in the annotated group of HPs that may be possible molecular targets, facilitating for the survival of pathogen. Our comprehensive analysis helps to understand the mechanism of pathogenesis to provide many novel potential therapeutic interventions.

Identification of functional candidates amongst hypothetical proteins of Mycobacterium leprae Br4923, a causative agent of leprosy

Mycobacterium leprae is an intracellular obligate parasite that causes leprosy in humans, and it leads to the destruction of peripheral nerves and skin deformation. Here, we report an extensive analysis of the hypothetical proteins (HPs) from M. leprae strain Br4923, assigning their functions to better understand the mechanism of pathogenesis and to search for potential therapeutic interventions. The genome of M. leprae encodes 1604 proteins, of which the functions of 632 are not known (HPs). In this paper, we predicted the probable functions of 312 HPs. First, we classified all HPs into families and subfamilies on the basis of sequence similarity, followed by domain assignment, which provides many clues for their possible function. However, the functions of 320 proteins were not predicted because of low sequence similarity with proteins of known function. Annotated HPs were categorized into enzymes, binding proteins, transporters, and proteins involved in cellular processes. We found several novel proteins whose functions were unknown for M. leprae. These proteins have a requisite association with bacterial virulence and pathogenicity. Finally, our sequence-based analysis will be helpful for further validation and the search for potential drug targets while developing effective drugs to cure leprosy.

Genome subtraction for the identification of potential antimicrobial targets in Xanthomonas oryzae pv. oryzae PXO99A pathogenic to rice

In pathogenic bacteria, identification of essential proteins which are non-homologous to the host plants represents potential antimicrobial targets. We applied subtractive genomics approach for the identification of novel antimicrobial targets in Xanthomonas oryzae pv. oryzae PXO99A, the causative agent of bacterial blight in rice. Comparative analysis was performed through BLAST available with the NCBI. The analysis revealed that 27 essential protein sequences out of 4,988 sequences of X. oryzae pv. oryzae PXO99A are non-homologous to Oryza sativa. Subsequent analysis of 27 essential proteins revealed their involvement in different metabolic activities such as transport activity, DNA binding, structural constituent of ribosome, cell division, translation, and plasma membrane. These 27 proteins were analyzed for virulence and novelty and out of 27, three essential non-homologous proteins were found to be the novel antimicrobial targets.

Functional annotation of conserved hypothetical proteins from Haemophilus influenzae Rd KW20

Haemophilus influenzae is a Gram negative bacterium that belongs to the family Pasteurellaceae, causes bacteremia, pneumonia and acute bacterial meningitis in infants. The emergence of multi-drug resistance H. influenzae strain in clinical isolates demands the development of better/new drugs against this pathogen. Our study combines a number of bioinformatics tools for function predictions of previously not assigned proteins in the genome of H. influenzae. This genome was extensively analyzed and found 1,657 functional proteins in which function of 429 proteins are unknown, termed as hypothetical proteins (HPs). Amino acid sequences of all 429 HPs were extensively annotated and we successfully assigned the function to 296 HPs with high confidence. We also characterized the function of 124 HPs precisely, but with less confidence. We believed that sequence of a protein can be used as a framework to explain known functional properties. Here we have combined the latest versions of protein family databases, protein motifs, intrinsic features from the amino acid sequence, pathway and genome context methods to assign a precise function to hypothetical proteins for which no experimental information is available. We found these HPs belong to various classes of proteins such as enzymes, transporters, carriers, receptors, signal transducers, binding proteins, virulence and other proteins. The outcome of this work will be helpful for a better understanding of the mechanism of pathogenesis and in finding novel therapeutic targets for H. influenzae.

Identification of druggable targets for Acinetobacter baumannii via subtractive genomics and plausible inhibitors for MurA and MurB

Emergence of the multidrug-resistant pathogens has rendered the current therapies ineffective thereby, resulting in the need for new drugs and drug targets. The accumulating protein sequence data has initiated a drift from classical drug discovery protocols to structure-based drug designing. In the present study, in silico subtractive genomics approach was implemented to find a set of potential drug targets present in an opportunist bacterial pathogen, Acinetobacter baumannii (A. baumannii). Out of the 43 targets identified, further studies for protein model building and lead-inhibitor identification were carried out on two cell-essential targets, MurA and MurB enzymes (of A. baumannii designated as MurAAb and MurBAb) involved in the peptidoglycan biosynthesis pathway of bacteria. The homology model built for each of them was further refined and validated using various available programs like PROCHECK, Errat, ProSA energy plots, etc. Compounds showing activity against MurA and MurB enzymes of other organisms were collected from the literature and were docked into the active site of MurAAb and MurBAb enzymes. Three inhibitors namely, T6361, carbidopa, and aesculin, showed maximum Glide score, hydrogen bonding interactions with the key amino acid residues of both the enzymes and acceptable ADME properties. Furthermore, molecular dynamics simulation studies on MurAAb-T6361 and MurBAb-T6361 complexes suggested that the ligand has a high binding affinity with both the enzymes and the hydrogen bonding with the key residues were stable in the dynamic condition also. Therefore, these ligands have been propsed as dual inhibitors and promising lead compounds for the drug design against MurAAb and MurBAb enzymes.

Identification and characterization of potential therapeutic candidates in emerging human pathogen Mycobacterium abscessus: a novel hierarchical in silico approach

Mycobacterium abscessus, a non-tuberculous rapidly growing mycobacterium, is recognized as an emerging human pathogen causing a variety of infections ranging from skin and soft tissue infections to severe pulmonary infections. Lack of an optimal treatment regimen and emergence of multi-drug resistance in clinical isolates necessitate the development of better/new drugs against this pathogen. The present study aims at identification and qualitative characterization of promising drug targets in M. abscessus using a novel hierarchical in silico approach, encompassing three phases of analyses. In phase I, five sets of proteins were mined through chokepoint, plasmid, pathway, virulence factors, and resistance genes and protein network analysis. These were filtered in phase II, in order to find out promising drug target candidates through subtractive channel of analysis. The analysis resulted in 40 therapeutic candidates which are likely to be essential for the survival of the pathogen and non-homologous to host, human anti-targets, and gut flora. Many of the identified targets were found to be involved in different metabolisms (viz., amino acid, energy, carbohydrate, fatty acid, and nucleotide), xenobiotics degradation, and bacterial pathogenicity. Finally, in phase III, the candidate targets were qualitatively characterized through cellular localization, broad spectrum, interactome, functionality, and druggability analysis. The study explained their subcellular location identifying drug/vaccine targets, possibility of being broad spectrum target candidate, functional association with metabolically interacting proteins, cellular function (if hypothetical), and finally, druggable property. Outcome of the present study could facilitate the identification of novel antibacterial agents for better treatment of M. abscesses infections.