Potential Drug Targets Identification against Clostridioides difficile (CD) and Characterization of Indispensable Proteins by a Subtractive Genomics Approach Followed by Virtual Screening

Background: Clostridioides difficile (CD) is a multi-drug resistant, enteric pathogenic bacterium. The CD associated infections are the leading cause of nosocomial diarrhea that can further lead to pseudomembranous colitis up to a toxic mega-colon or sepsis with greater mortality and morbidity risks. The CD infection possess higher rates of recurrence due to its greater resistance against antibiotics. Considering its higher rates of recurrence, it has become a major burden on the healthcare facilities. Therefore, there is a dire need to identify novel drug targets to combat with the antibiotic resistance of Clostridioides difficile. Objective: To identify and propose new and novel drug targets against the Clostridioides difficile. Methods: In the current study, a computational subtractive genomics approach was applied to obtain a set of potential drug targets that exists in the multi-drug resistant strain of Clostridioides difficile. Here, the uncharacterized proteins were studied as potential drug targets. The methodology involved several bioinformatics databases and tools. The druggable proteins sequences were retrieved based on non-homology with host proteome and essentiality for the survival of the pathogen. The uncharacterized proteins were functionally characterized using different computational tools and sub-cellular localization was also predicted. The metabolic pathways were analyzed using KEGG database. Eventually, the druggable proteome has been fetched using sequence similarity with the already available drug targets present in DrugBank database. These druggable proteins were further explored for the structural details to identify drug candidates. Results : A priority list of potential drug targets was provided with the help of the applied method on complete proteome set of the C. difficile. Moreover, the drug like compounds have been screened against the potential drug targets to prioritize potential drug candidates. To facilitate the need for drug targets and therapies, the study proposed five potential protein drug targets out of which three proposed drug targets were subjected to homology modeling to explore their structural and functional activities. Conclusion: In conclusion, we proposed three unique, unexplored drug targets against C. difficile. The structure-based methods were applied and resulted in a list of top scoring compounds as potential inhibitors to proposed drug targets.

Genome Subtraction and Comparison for the Identification of Novel Drug Targets against Mycobacterium avium subsp. hominissuis

Mycobacterium avium complex (MAC) is a major cause of non-tuberculous pulmonary and disseminated diseases worldwide, inducing bronchiectasis, and affects HIV and immunocompromised patients. In MAC, Mycobacterium avium subsp. hominissuis is a pathogen that infects humans and mammals, and that is why it is a focus of this study. It is crucial to find essential drug targets to eradicate the infections caused by these virulent microorganisms. The application of bioinformatics and proteomics has made a significant impact on discovering unique drug targets against the deadly pathogens. One successful bioinformatics methodology is the use of in silico subtractive genomics. In this study, the aim was to identify the unique, non-host and essential protein-based drug targets of Mycobacterium avium subsp. hominissuis via in silico a subtractive genomics approach. Therefore, an in silico subtractive genomics approach was applied in which complete proteome is subtracted systematically to shortlist potential drug targets. For this, the complete dataset of proteins of Mycobacterium avium subsp. hominissuis was retrieved. The applied subtractive genomics method, which involves the homology search between the host and the pathogen to subtract the non-druggable proteins, resulted in the identification of a few prioritized potential drug targets against the three strains of M. avium subsp. Hominissuis, i.e., MAH-TH135, OCU466 and A5. In conclusion, the current study resulted in the prioritization of vital drug targets, which opens future avenues to perform structural as well as biochemical studies on predicted drug targets against M. avium subsp. hominissuis.

Identification of potential candidates for drug designing against Klebsiella Pneumoniae among hypothetical proteins of DNA Adenine Methyltransferase through subtractive genomics approach

ABSTRACTKlebsiella Pneumoniae is a gram-negative bacterium that is known for causing infection in nosocomial settings. As reported by WHO, this bacterial pathogen is classified as an urgent threat our most concern is that these bacterial pathogens acquired genetic traits that make them resistant towards antibiotics. The last class of antibiotics; carbapenems are not able to combat these bacterial pathogens allowing them to clonally expand their antibiotic-resistant strain. Most antibiotics target the essential pathways of the bacteria cell however these targets are no longer susceptible to the antibiotic. Hence in our study, we focus on Klebsiella Pneumoniae bacterial strains that contain DNA Adenine Methyltransferase domain which suggests a new potential site for a drug target. DNA methylation is seen to regulate the attenuation of bacterial virulence. In this study, all hypothetical proteins of Klebsiella Pneumoniae containing N6 DNA Adenine Methyltransferase domain were analysed for a potential drug target. About 32 hypothetical proteins were retrieved from Uniprot. 19 proteins were selected through a step-wise subtractive genomics approach like a selection of non-homologus proteins against the human host, selection of bacterial proteins contains an essential gene, broad-spectrum analysis, druggability analysis, Non-homology analysis against gut microbiota. Through drug target prioritization like sub-cellular analysis, drug property analysis, anti-target non-homology analysis, virulence factor analysis and protein-protein interaction analysis one drug target protein (Uniprot ID: A0A2U0NNR3) was prioritized. Identified drug target docked with potential inhibitors like are mahanine (PubChem ID: 375151), curcumin (PubChem ID: 969516), EGCG (PubChem ID: 65064), nanaomycin A (PubChem ID: 40586), parthenolide (PubChem ID: 7251185), quercetin (PubChem ID: 5280343) and trimethylaurintricarboxylic acid. Based on the moelcular docking analysis, mahanine has the highest binding affinity. In order to identify novel natural inhibitor based on mahanine fingerprint search is performed against NPASS (Natural Product Activity and Species Source databases) and Koenimbine was identified as a novel natural inhibitor based on virtual screening.