Identification and characterization of repurposed small molecule inhibitors of Mycobacterium tuberculosis caseinolytic protease B (ClpB) as anti-mycobacterials.

Mycobacterium tuberculosis (Mtb) caseinolytic protease B (ClpB) is a chaperone possessing a unique ability to resolubilize the aggregated proteins in vivo. ClpB has been shown to be important for the survival of Mtb within the host. Thus, it appears to be a promising target to develop new therapeutic molecules against tuberculosis. In this study, we have screened FDA approved compounds in silico to identify inhibitors against Mtb ClpB. In our screen, several compounds interacted with ClpB. The top four compounds, namely framycetin, gentamicin, ribostamycin and tobramycin showing the highest binding energy were selected for further investigation. MD simulations and tryptophan-based quenching of ClpB-drug complexes established that the selected inhibitors stably interacted with the target protein. The inhibitor and protein complexes were found to be stabilized by hydrogen bonding, and hydrophobic interactions. Although, the compounds did not affect the ATPase activity of ClpB significantly, the protein resolubilization activity of ClpB was remarkably reduced in their presence. All four compounds potently inhibited the growth of Mtb H37Ra. The antimycobacterial activity of the compounds appears to be due the inhibition of functional ClpB oligomer formation, in turn affecting its chaperonic activity.

Computational exploration of the genomic assignments, molecular structure, and dynamics of the ccdABXn2 toxin-antitoxin homolog with its bacterial target, the DNA gyrase, in the entomopathogen Xenorhabdus nematophila.

Toxin-antitoxin (TA) modules, initially discovered on bacterial plasmids and subsequently identified within chromosomal contexts, hold a pivotal role in the realm of bacterial physiology. Among these, the pioneering TA system, ccd (Control of Cell Death), primarily localized on the F-plasmid, is known for its orchestration of plasmid replication with cellular division. Nonetheless, the precise functions of such systems within bacterial chromosomal settings remain a compelling subject that demands deeper investigation. To bridge this knowledge gap, our study focuses on exploring ccdABXn2, a chromosomally encoded TA module originating from the entomopathogenic bacterium Xenorhabdus nematophila. We meticulously delved into the system's genomic assignments, structural attributes, and functional interplay. Our findings uncovered intriguing patterns-CcdB toxin homologs exhibited higher conservation levels compared to their CcdA antitoxin counterparts. Moreover, we constructed secondary as well as tertiary models for both the CcdB toxin and CcdA antitoxin using threading techniques and subsequently validated their structural integrity. Our exploration extended to the identification of key interactions, including the peptide interaction with gyrase for the CcdB homolog and CcdB toxin interactions for the CcdA homolog, highlighting the intricate TA interaction network. Through docking and simulation analyses, we unequivocally demonstrated the inhibition of replication via binding the CcdB toxin to its target, DNA gyrase. These insights provide valuable knowledge about the metabolic and physiological roles of the chromosomally encoded ccdABXn2 TA module within the context of X. nematophila, significantly enhancing our comprehension of its functional significance within the intricate ecosystem of the bacterial host.Communicated by Ramaswamy H. Sarma.

Targeting of essential mycobacterial replication enzyme DnaG primase revealed Mitoxantrone and Vapreotide as novel mycobacterial growth inhibitors.

Tuberculosis (TB) is the second leading cause of mortality after COVID-19, with a global death toll of 1.6 million in 2021. The escalating situation of drug-resistant forms of TB has threatened the current TB management strategies. New therapeutics with novel mechanisms of action are urgently required to address the current global TB crisis. The essential mycobacterial primase DnaG with no structural homology to homo sapiens presents itself as a good candidate for drug targeting. In the present study, Mitoxantrone and Vapreotide, two FDA-approved drugs, were identified as potential anti-mycobacterial agents. Both Mitoxantrone and Vapreotide exhibit a strong Minimum Inhibitory Concentration (MIC) of ≤25µg/ml against both the virulent (M.tb-H37Rv) and avirulent (M.tb-H37Ra) strains of M.tb. Extending the validations further revealed the inhibitory potential drugs in ex vivo conditions. Leveraging the computational high-throughput multi-level docking procedures from the pool of ~2700 FDA-approved compounds, Mitoxantrone and Vapreotide were screened out as potential inhibitors of DnaG. Extensive 200 ns long all-atoms molecular dynamic simulation of DnaGDrugs complexes revealed that both drugs bind strongly and stabilize the DnaG during simulations. Reduced solvent exposure and confined motions of the active centre of DnaG upon complexation with drugs indicated that both drugs led to the closure of the active site of DnaG. From this study's findings, we propose Mitoxantrone and Vapreotide as potential anti-mycobacterial agents, with their novel mechanism of action against mycobacterial DnaG.

Unravelling the potential of Triflusal as an anti-TB repurposed drug by targeting replication protein DciA.

The increasing prevalence of drug-resistant Tuberculosis (TB) is imposing extreme difficulties in controlling the TB infection rate globally, making treatment critically challenging. To combat the prevailing situation, it is crucial to explore new anti-TB drugs with a novel mechanism of action and high efficacy. The Mycobacterium tuberculosis (M.tb)DciA is an essential protein involved in bacterial replication and regulates its growth. DciA interacts with DNA and provides critical help in binding other replication machinery proteins to the DNA. Moreover, the lack of any structural homology of M.tb DciA with human proteins makes it an appropriate target for drug development. In this study, FDA-approved drugs were virtually screened against M.tb DciA to identify potential inhibitors. Four drugs namely Lanreotide, Risedronate, Triflusal, and Zoledronic acid showed higher molecular docking scores. Further, molecular dynamics simulations analysis of DciA-drugs complexes reported stable interaction, more compactness, and reduced atomic motion. The anti-TB activity of drugs was further evaluated under in vitro and ex vivo conditions where Triflusal was observed to have the best possible activity with the MIC of 25 µg/ml. Our findings present novel DciA inhibitors and anti-TB activity of Triflusal. Further investigations on the use of Triflusal may lead to the discovery of a new anti-TB drug.

Atosiban and Rutin exhibit anti-mycobacterial activity - An integrated computational and biophysical insight toward drug repurposing strategy against Mycobacterium tuberculosis targeting its essential enzyme HemD.

With the advancements of high throughput computational screening procedures, drug repurposing became the privileged framework for drug discovery. The structure-based drug discovery is the widely used method of drug repurposing, consisting of computational screening of compounds and testing them in-vitro. This current method of repurposing leaves room for mechanistic insights into how these screened hits interact with and influence their targets. We addressed this gap in the current study by integrating highly sensitive biophysical methods into existing computational repurposing methods. We also corroborated our computational and biophysical findings on H37Rv for the anti-mycobacterial action of selected drugs in-vitro and ex-vivo conditions. Atosiban and Rutin were screened as highly interacting hits against HemD through multi-stage docking and were cross-validated in biophysical studies. The affinity of these drugs (K ~ 106 M-1) was quantified using fluorescence quenching studies. Differential Scanning Fluorimetry (DSF) and urea-based chemical denaturation studies revealed a destabilizing effect of these drugs on target which was further validated using MD simulations. Conformational rearrangements of secondary structures were established using CD spectra and intrinsic fluorescence. Furthermore, Atosiban and Rutin inhibited M.tb growth in-vitro and ex-vivo while remaining non-toxic to mice peritoneal macrophages.

Role of a substrate binding pocket in the amino terminal domain of Mycobacterium tuberculosis caseinolytic protease B (ClpB) in its function.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis when infects the host encounters several stresses within the host, resulting in aggregation of its proteins. To resolve this problem Mtb uses chaperones to either repair the damage or degrade the aggregated proteins. Mtb caseinolytic protein B (ClpB) helps in the prevention of aggregation and also resolubilization of aggregated proteins in bacteria, which is important for the survival of Mtb in the host. To function optimally, ClpB associates with its co-partners DnaK, DnaJ, and GrpE. The role of N-terminal domain (NTD) of Mtb ClpB in its function is not well understood. In this context, we investigated the interaction of three substrate mimicking peptides with the NTD of Mtb ClpB in silico. A substrate binding pocket, within the NTD of ClpB comprising of residues L136, R137, E138, K142, R144, R148, V149, Y158, and Y162 forming an ɑ-helix was thus identified. The residues L136 and R137 of the ɑ-helix were found to be important for the interaction of DnaK to ClpB. Further, nine single alanine recombinant variants of the identified residues were generated. As compared to the wild-type Mtb ClpB all the Mtb ClpB variants generated in this study were found to have reduced ATPase and protein refolding activity indicating the importance of the substrate binding pocket in ClpB function. The study demonstrates that the NTD of Mtb ClpB is important for its substrate interaction activity, and the substrate binding pocket identified in this study plays a crucial role in this interaction.Communicated by Ramaswamy H. Sarma.

Potential Repurposed Drug Candidates for Tuberculosis Treatment: Progress and Update of Drugs Identified in Over a Decade.

The devastating impact of Tuberculosis (TB) has been a menace to mankind for decades. The World Health Organization (WHO) End TB Strategy aims to reduce TB mortality up to 95% and 90% of overall TB cases worldwide, by 2035. This incessant urge will be achieved with a breakthrough in either a new TB vaccine or novel drugs with higher efficacy. However, the development of novel drugs is a laborious process involving a timeline of almost 20-30 years with huge expenditure; on the other hand, repurposing previously approved drugs is a viable technique for overcoming current bottlenecks in the identification of new anti-TB agents. The present comprehensive review discusses the progress of almost all the repurposed drugs that have been identified to the present day (∼100) and are in the development or clinical testing phase against TB. We have also emphasized the efficacy of repurposed drugs in combination with already available frontline anti-TB medications along with the scope of future investigations. This study would provide the researchers a detailed overview of nearly all identified anti-TB repurposed drugs and may assist them in selecting the lead compounds for further in vivo/clinical research.

Computational analysis of RNA methyltransferase Rv3366 as a potential drug target for combating drug-resistant Mycobacterium tuberculosis.

Mycobacterium tuberculosis (M.tb) remains a formidable global health threat. The increasing drug resistance among M.tb clinical isolates is exacerbating the current tuberculosis (TB) burden. In this study we focused on identifying novel repurposed drugs that could be further investigated as potential anti-TB drugs. We utilized M.tb RNA methyltransferase Rv3366 (spoU) as a potential drug target due to its imperative activity in RNA modification and no structural homology with human proteins. Using computational modeling approaches the structure of Rv3366 was determined followed by high throughput virtual screening of Food and Drug Administration (FDA) approved drugs to screen potential binders of Rv3366. Molecular dynamics (MD) simulations were performed to assess the drug-protein binding interactions, complex stability and rigidity. Through this multi-step structure-based drug repurposing workflow two promising inhibitors of Rv3366 were identified, namely, Levodopa and Droxidopa. This study highlights the significance of targeting M.tb RNA methyltransferases to combat drug-resistant M.tb. and proposes Levodopa and Droxidopa as promising inhibitors of Rv3366 for future pre-clinical investigations.

The Mycobacterium tuberculosis PE_PGRS Protein Family Acts as an Immunological Decoy to Subvert Host Immune Response.

Mycobacterium tuberculosis (M.tb) is a successful pathogen that can reside within the alveolar macrophages of the host and can survive in a latent stage. The pathogen has evolved and developed multiple strategies to resist the host immune responses. M.tb escapes from host macrophage through evasion or subversion of immune effector functions. M.tb genome codes for PE/PPE/PE_PGRS proteins, which are intrinsically disordered, redundant and antigenic in nature. These proteins perform multiple functions that intensify the virulence competence of M.tb majorly by modulating immune responses, thereby affecting immune mediated clearance of the pathogen. The highly repetitive, redundant and antigenic nature of PE/PPE/PE_PGRS proteins provide a critical edge over other M.tb proteins in terms of imparting a higher level of virulence and also as a decoy molecule that masks the effect of effector molecules, thereby modulating immuno-surveillance. An understanding of how these proteins subvert the host immunological machinery may add to the current knowledge about M.tb virulence and pathogenesis. This can help in redirecting our strategies for tackling M.tb infections.

Multifaceted role of drugs: a potential weapon to outsmart Mycobacterium tuberculosis resistance by targeting its essential ThyX.

Tuberculosis (TB) is one of the prominent cause of deaths across the world and multidrug-resistant and extensively drug-resistant TB continues to pose challenges for clinicians and public health centers. The risk of death is extremely high in individuals who have compromised immune systems, HIV infection, or diabetes. Research institutes and pharmaceutical companies have been working on repurposing existing drugs as effective therapeutic options against TB. The identification of suitable drugs with multi-target affinity profiles is a widely accepted way to combat the development of resistance. Flavin-dependent thymidylate synthase (FDTS), known as ThyX, is in the class of methyltransferases and is a possible target in the discovery of novel anti-TB drugs. In this study, we aimed to repurpose existing drugs approved by Food and Drug Administration (FDA) that could be used in the treatment of TB. An integrated screening was performed based on computational procedures: high-throughput molecular docking techniques, followed by molecular dynamics simulations of the target enzyme, ThyX. After performing in silico screening using a library of 3,967 FDA-approved drugs, the two highest-scoring drugs, Carglumic acid and Mesalazine, were selected as potential candidates that could be repurposed to treat TB.Communicated by Ramaswamy H. Sarma.

Dual inhibition of SARS-CoV-2 spike and main protease through a repurposed drug, rutin.

The global health emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to alarming numbers of fatalities across the world. So far the researchers worldwide have not been able to discover a breakthrough in the form of a potent drug or an effective vaccine. Therefore, it is imperative to discover drugs to curb the ongoing menace. In silico approaches using FDA approved drugs can expedite the drug discovery process by providing leads that can be pursued. In this report, two drug targets, namely the spike protein and main protease, belonging to structural and non-structural class of proteins respectively, were utilized to carry out drug repurposing based screening. The exposed nature of the spike protein on the viral surface along with its instrumental role in host infection and the involvement of main protease in processing of polyproteins along with no human homologue make these proteins attractive drug targets. Interestingly, the screening identified a common high efficiency binding molecule named rutin. Further, molecular dynamics simulations in explicit solvent affirmed the stable and sturdy binding of rutin with these proteins. The decreased Rg value (4 nm for spike-rutin and 2.23 nm for main protease-rutin) and stagnant SASA analysis (485 nm/S2/N in spike-rutin and 152 nm/S2/N in main protease-rutin) for protein surface and its orientation in the exposed and buried regions suggests a strong binding interaction of the drug. Further, cluster analysis and secondary structure analysis of complex trajectories validated the conformational changes due to binding of rutin.

Insights into the mutations leading to capreomycin resistance in S-adenosyl-L-methionine binding motif in TlyA from Mycobacterium tuberculosis.

Capreomycin is a second line antibiotic used for the treatment of drug resistant Tuberculosis (TB), primary reason of death from a solo infectious organism, Mycobacterium tuberculosis (M.tb). Capreomycin targets the ribosome of bacteria and is known to bind at the interface where the large and small ribosomal subunits interact in M.tb using an S-Adenosyl Methionine (SAM) dependent methyltransferase, TlyA (Rv1794). Besides the methyltransferase activity, TlyA has also been found to show substantial haemolytic activity. The dual activity of TlyA highlights its crucial role in pathogenesis and virulence of M.tb. In the present study, docking and molecular dynamics (MD) simulations were carried out to explore the impact of mutations in a conserved SAM binding motif, 90GASTG94, on the affinity of TlyA enzyme for SAM. Two already reported mutations, A91E and S92L, and the remaining wild type residues, Gly90, Thr93, Gly94 mutated to alanine were taken into consideration resulting in a total of six systems, wild type + SAM, G90A + SAM, A91E + SAM, S92L + SAM, T93A + SAM and G94A + SAM that were subjected to 100 ns MD simulations. Docking scores and MD simulations analyses revealed that in contrast to wild type, mutants reduced the affinity of SAM for TlyA with most prominent effect observed in case of alanine mutants. Mutations also led to the loss of hydrogen bond and hydrophobic interactions and large-scale movement of atoms evident from the principal component analyses indicating their destabilizing impact on TlyA. The present study gives insights into influence of mutations on binding of SAM to TlyA in M.tb and promoting capreomycin resistance.Communicated by Ramaswamy H. Sarma.

PGRS Domain of Rv0297 of Mycobacterium tuberculosis Functions in A Calcium Dependent Manner.

Mycobacterium tuberculosis (M.tb), the pathogen causing tuberculosis, is a major threat to human health worldwide. Nearly 10% of M.tb genome encodes for a unique family of PE/PPE/PGRS proteins present exclusively in the genus Mycobacterium. The functions of most of these proteins are yet unexplored. The PGRS domains of these proteins have been hypothesized to consist of Ca2+ binding motifs that help these intrinsically disordered proteins to modulate the host cellular responses. Ca2+ is an important secondary messenger that is involved in the pathogenesis of tuberculosis in diverse ways. This study presents the calcium-dependent function of the PGRS domain of Rv0297 (PE_PGRS5) in M.tb virulence and pathogenesis. Tandem repeat search revealed the presence of repetitive Ca2+ binding motifs in the PGRS domain of the Rv0297 protein (Rv0297PGRS). Molecular Dynamics simulations and fluorescence spectroscopy revealed Ca2+ dependent stabilization of the Rv0297PGRS protein. Calcium stabilized Rv0297PGRS enhances the interaction of Rv0297PGRS with surface localized Toll like receptor 4 (TLR4) of macrophages. The Ca2+ stabilized binding of Rv0297PGRS with the surface receptor of macrophages enhances its downstream consequences in terms of Nitric Oxide (NO) production and cytokine release. Thus, this study points to hitherto unidentified roles of calcium-modulated PE_PGRS proteins in the virulence of M.tb. Understanding the pathogenic potential of Ca2+ dependent PE_PGRS proteins can aid in targeting these proteins for therapeutic interventions.

An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins.

Tuberculosis is one the oldest known affliction of mankind caused by the pathogen Mycobacterium tuberculosis. Till date, there is no absolute single treatment available to deal with the pathogen, which has acquired a great potential to develop drug resistance rapidly. BCG is the only anti-tuberculosis vaccine available till date which displays limited global efficacy due to genetic variation and concurrent pathogen infections. Extracellular vesicles or exosomes vesicle (EVs) lie at the frontier cellular talk between pathogen and the host, and therefore play a significant role in establishing pathogenesis. In the present study, an in-silico approach has been adopted to construct a multi-epitope vaccine from selected immunogenic EVs proteins to elicit a cellular as well as a humoral immune response. Our designed vaccine has wide population coverage and can effectively compensate for the genetic variation among different populations. For maximum efficacy and minimum adverse effects possibilities the antigenic, non-allergenic and non-toxic B-cell, HTL and CTL epitopes from experimentally proven EVs proteins were selected for the vaccine construct. TLR4 agonist RpfE served as an adjuvant for the vaccine construct. The vaccine construct structure was modelled, refined and docked on TLR4 immune receptor. The designed vaccine construct displayed safe usage and exhibits a high probability to elicit the critical immune regulators, like B cells, T-cells and memory cells as displayed by the in-silico immunization assays. Therefore, it can be further corroborated using in vitro and in vivo assays to fulfil the global need for a more efficacious anti-tuberculosis vaccine.

Predicting phosphorylation sites using machine learning by integrating the sequence, structure, and functional information of proteins.

BACKGROUND: Post-translational modification (PTM) is a biological process that alters proteins and is therefore involved in the regulation of various cellular activities and pathogenesis. Protein phosphorylation is an essential process and one of the most-studied PTMs: it occurs when a phosphate group is added to serine (Ser, S), threonine (Thr, T), or tyrosine (Tyr, Y) residue. Dysregulation of protein phosphorylation can lead to various diseases-most commonly neurological disorders, Alzheimer's disease, and Parkinson's disease-thus necessitating the prediction of S/T/Y residues that can be phosphorylated in an uncharacterized amino acid sequence. Despite a surplus of sequencing data, current experimental methods of PTM prediction are time-consuming, costly, and error-prone, so a number of computational methods have been proposed to replace them. However, phosphorylation prediction remains limited, owing to substrate specificity, performance, and the diversity of its features. METHODS: In the present study we propose machine-learning-based predictors that use the physicochemical, sequence, structural, and functional information of proteins to classify S/T/Y phosphorylation sites. Rigorous feature selection, the minimum redundancy/maximum relevance approach, and the symmetrical uncertainty method were employed to extract the most informative features to train the models. RESULTS: The RF and SVM models generated using diverse feature types in the present study were highly accurate as is evident from good values for different statistical measures. Moreover, independent test sets and benchmark validations indicated that the proposed method clearly outperformed the existing methods, demonstrating its ability to accurately predict protein phosphorylation. CONCLUSIONS: The results obtained in the present work indicate that the proposed computational methodology can be effectively used for predicting putative phosphorylation sites further facilitating discovery of various biological processes mechanisms.

Cytotoxic T-lymphocyte elicited vaccine against SARS-CoV-2 employing immunoinformatics framework.

Development of effective counteragents against the novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains, requires clear insights and information for understanding the immune responses associated with it. This global pandemic has pushed the healthcare system and restricted the movement of people and succumbing of the available therapeutics utterly warrants the development of a potential vaccine to contest the deadly situation. In the present study, highly efficacious, immunodominant cytotoxic T-lymphocyte (CTL) epitopes were predicted by advanced immunoinformatics assays using the spike glycoprotein of SARS-CoV2, generating a robust and specific immune response with convincing immunological parameters (Antigenicity, TAP affinity, MHC binder) engendering an efficient viral vaccine. The molecular docking studies show strong binding of the CTL construct with MHC-1 and host membrane specific TLR2 receptors. The molecular dynamics simulation in an explicit system confirmed the stable and robust binding of CTL epitope with TLR2. Steep magnitude RMSD variation and compelling residual fluctuations existed in terminal residues and various loops of the ß linker segments of TLR2-epitope (residues 105-156 and 239-254) to about 0.4 nm. The reduced Rg value (3.3 nm) and stagnant SASA analysis (275 nm/S2/N after 8 ns and 5 ns) for protein surface and its orientation in the exposed and buried regions suggests more compactness due to the strong binding interaction of the epitope. The CTL vaccine candidate establishes a high capability to elicit the critical immune regulators, like T-cells and memory cells as proven by the in silico immunization assays and can be further corroborated through in vitro and in vivo assays.

PGRS Domain of Rv0297 of Mycobacterium tuberculosis Is Involved in Modulation of Macrophage Functions to Favor Bacterial Persistence.

Mycobacterium tuberculosis (M. tb) Rv0297-encoded PE_PGRS5 has been known to be expressed at the later stages of infection and in acidified phagosomes during transcriptome and proteomic studies. The possible role of Rv0297 in the modulation of phagosomal maturation and in providing protection against a microbicidal environment has been hypothesized. We show that Rv0297PGRS is involved in modulating the calcium homeostasis of macrophages followed by impedance of the phagolysosomal acidification process. This is evident from the downregulation of the late endosomal markers (Rab7 and cathepsin D) in the macrophages infected with recombinant Mycobacterium smegmatis (rM.smeg)-M.smeg_Rv0297 and M.smeg_Rv0297PGRS-or treated with recombinant Rv0297PGRS protein. Macrophages infected with rM.smeg expressing Rv0297 produce nitric oxide and undergo apoptosis, which may aid in the dissemination of pathogen in the later stages of infection. Rv0297 was also found to be involved in rescuing the bacterium from oxidative and hypoxic stress employed by macrophages and augmented the survivability of the recombinant bacterium. These results attribute to the functional significance of this protein in M.tb virulence mechanism. The fact that this protein gets expressed at the later stages of lung granulomas during M.tb infection suggests that the bacterium possibly employs Rv0297 as its dissemination and survival strategy.

Author Correction: Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis.

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (M.tb), causes highest number of deaths globally for any bacterial disease necessitating novel diagnosis and treatment strategies. High-throughput sequencing methods generate a large amount of data which could be exploited in determining multi-drug resistant (MDR-TB) associated mutations. The present work is a computational framework that uses artificial intelligence (AI) based machine learning (ML) approaches for predicting resistance in the genes rpoB, inhA, katG, pncA, gyrA and gyrB for the drugs rifampicin, isoniazid, pyrazinamide and fluoroquinolones. The single nucleotide variations were represented by several sequence and structural features that indicate the influence of mutations on the target protein coded by each gene. We used ML algorithms - naïve bayes, k nearest neighbor, support vector machine, and artificial neural network, to build the prediction models. The classification models had an average accuracy of 85% across all examined genes and were evaluated on an external unseen dataset to demonstrate their application. Further, molecular docking and molecular dynamics simulations were performed for wild type and predicted resistance causing mutant protein and anti-TB drug complexes to study their impact on the conformation of proteins to confirm the observed phenotype.