Designing of inhibitors against drug tolerant Mycobacterium tuberculosis (H37Rv).
ABSTRACT: BACKGROUND: Mycobacterium tuberculosis (M.tb) is the causative agent of tuberculosis, killing ~1.7 million people annually. The remarkable capacity of this pathogen to escape the host immune system for decades and then to cause active tuberculosis disease, makes M.tb a successful pathogen. Currently available anti-mycobacterial therapy has poor compliance due to requirement of prolonged treatment resulting in accelerated emergence of drug resistant strains. Hence, there is an urgent need to identify new chemical entities with novel mechanism of action and potent activity against the drug resistant strains. RESULTS: This study describes novel computational models developed for predicting inhibitors against both replicative and non-replicative phase of drug-tolerant M.tb under carbon starvation stage. These models were trained on highly diverse dataset of 2135 compounds using four classes of binary fingerprint namely PubChem, MACCS, EState, SubStructure. We achieved the best performance Matthews correlation coefficient (MCC) of 0.45 using the model based on MACCS fingerprints for replicative phase inhibitor dataset. In case of non-replicative phase, Hybrid model based on PubChem, MACCS, EState, SubStructure fingerprints performed better with maximum MCC value of 0.28. In this study, we have shown that molecular weight, polar surface area and rotatable bond count of inhibitors (replicating and non-replicating phase) are significantly different from non-inhibitors. The fragment analysis suggests that substructures like hetero_N_nonbasic, heterocyclic, carboxylic_ester, and hetero_N_basic_no_H are predominant in replicating phase inhibitors while hetero_O, ketone, secondary_mixed_amine are preferred in the non-replicative phase inhibitors. It was observed that nitro, alkyne, and enamine are important for the molecules inhibiting bacilli residing in both the phases. In this study, we introduced a new algorithm based on Matthews correlation coefficient called MCCA for feature selection and found that this algorithm is better or comparable to frequency based approach. CONCLUSION: In this study, we have developed computational models to predict phase specific inhibitors against drug resistant strains of M.tb grown under carbon starvation. Based on simple molecular properties, we have derived some rules, which would be useful in robust identification of tuberculosis inhibitors. Based on these observations, we have developed a webserver for predicting inhibitors against drug tolerant M.tb H37Rv available at http://crdd.osdd.net/oscadd/mdri/.
Project description:BACKGROUND: Identification of drug-like molecules is one of the major challenges in the field of drug discovery. Existing approach like Lipinski rule of 5 (Ro5), Operea have their own limitations. Thus, there is a need to develop computational method that can predict drug-likeness of a molecule with precision. In addition, there is a need to develop algorithm for screening chemical library for their drug-like properties. RESULTS: In this study, we have used 1347 approved and 3206 experimental drugs for developing a knowledge-based computational model for predicting drug-likeness of a molecule. We have used freely available PaDEL software for computing molecular fingerprints/descriptors of the molecules for developing prediction models. Weka software has been used for feature selection in order to identify the best fingerprints. We have developed various classification models using different types of fingerprints like Estate, PubChem, Extended, FingerPrinter, MACCS keys, GraphsOnlyFP, SubstructureFP, Substructure FPCount, Klekota-RothFP, Klekota-Roth FPCount. It was observed that the models developed using MACCS keys based fingerprints, discriminated approved and experimental drugs with higher precision. Our model based on one hundred fifty nine MACCS keys predicted drug-likeness of the molecules with 89.96% accuracy along with 0.77 MCC. Our analysis indicated that MACCS keys (ISIS keys) 112, 122, 144, and 150 were highly prevalent in the approved drugs. The screening of ZINC (drug-like) and ChEMBL databases showed that around 78.33% and 72.43% of the compounds present in these databases had drug-like potential. CONCLUSION: It was apparent from above study that the binary fingerprints could be used to discriminate approved and experimental drugs with high accuracy. In order to facilitate researchers working in the field of drug discovery, we have developed a webserver for predicting, designing, and screening novel drug-like molecules (http://crdd.osdd.net/oscadd/drugmint/).
Project description:α-Isopropylmalate Synthase (α-IPMS) encoded by leuA in Mycobacterium tuberculosis (M.tb) is involved in the leucine biosynthesis pathway and is extremely critical for the synthesis of branched-chain amino acids (leucine, isoleucine and valine). α-IPMS activity is required not only for the proliferation of M.tb but is also indispensable for its survival during the latent phase of infection. It is absent in humans and is widely regarded as one of the validated drug targets against Tuberculosis (TB). Despite its essentiality, any study on designing of potential chemical inhibitors against α-IPMS has not been reported so far. In the present study, in silico identification of putative inhibitors against α-IPMS exploring three chemical databases i.e. NCI, DrugBank and ChEMBL is reported through structurebased drug design and filtering of ligands based on the pharmacophore feature of the actives. In the absence of experimental results of any inhibitor against α-IPMS, a stringent validation of docking results is done by comparing with molecular mechanics/Poisson- Boltzmann surface area (MM/PBSA) calculations by investigating two more proteins for which experimental results are known.
Project description:Multi-drug resistant in Mycobacterium tuberculosis (M.tb) is considered as major bottleneck in the treatment and cure of tuberculosis (TB). Several anti-tubercular drugs fail in its efficacy due to drug-resistant M.tb developed mechanism for resistance. So, research across globe has been carried out to develop effective anti-TB drugs to improve the treatment of these strains. Traditional drug development methods have been proved unsuccessful as it fails to develop a broad-spectrum drug due to lack of structure based approach. Several studies have been conducted in this regard and identified several drug target sites that influence drug-resistant M.tb strains. In this study, the attempt was to study the interaction between the protein Arabinosyltransferase C with the two existing drugs (Ethambutol and Isoniazid) and five modified molecules derived from Ethambutol by calculating their binding affinity and mode of binding through molecular docking study using AutoDock 4. From the comparison study of the existing drug (EMB and INH) and the five proposed modified molecules (Emb1, Emb2, Emb3, Emb4 and Emb5), it is analysed that Emb1 and Emb3 with binding affinities -5.77 kcal/mol and -5.13 kcal/mol respectively can be considered as potential inhibitors of Arabinosyltransferase C in Mycobacterium tuberculosis which is responsible for cell wall synthesis. The facts provided may be further verified experimentally for future drug discovery process to make a stand against tuberculosis and contribute an advance research for worthy antimycobacterial strategies.
Project description:HIV-1 protease plays an important role in the processing of virus infection. Protease is an effective therapeutic target for the treatment of HIV-1. Our data set is based on a selection of 4855 HIV-1 protease inhibitors (PIs) from ChEMBL. A series of 15 classification models for predicting the active inhibitors were built by machine learning methods, including k-nearest neighors (K-NN), decision tree (DT), random forest (RF), support vector machine (SVM), and deep neural network (DNN). The molecular structures were characterized by (1) fingerprint descriptors including MACCS fingerprints and PubChem fingerprints and (2) physicochemical descriptors calculated by CORINA Symphony. The prediction accuracies of all of the models are more than 70% on the test set; the best accuracy of 83.07% was obtained by model 4A, which was built by the SVM method based on MACCS fingerprint descriptors. Nine consensus models were built with three kinds of different descriptors, which combined all of the machine learning methods using the "consensus prediction". Model C3a developed with MACCS fingerprint descriptors showed the highest accuracy on both training set (91.96%) and test set (83.15%). An external validation set including 35 989 compounds from DUD database and 239 active inhibitors from the recent literature was used to verify the performance of our model. The best prediction accuracy of 98.37% was obtained by model 3C, which was built by RF based on CORINA Symphony descriptors. In addition, from the analysis of molecular descriptors, it shows that the aromatic system and atoms related to hydrogen bonding provide important contributions to the bioactivity of PIs.
Project description:Tuberculosis (TB) is a leading cause of death worldwide and its impact has intensified due to the emergence of multi drug-resistant (MDR) and extensively drug-resistant (XDR) TB strains. Protein phosphorylation plays a vital role in the virulence of Mycobacterium tuberculosis (M.tb) mediated by protein kinases. Protein tyrosine phosphatase A (MptpA) undergoes phosphorylation by a unique tyrosine-specific kinase, protein tyrosine kinase A (PtkA), identified in the M.tb genome. PtkA phosphorylates PtpA on the tyrosine residues at positions 128 and 129, thereby increasing PtpA activity and promoting pathogenicity of MptpA. In the present study, we performed an extensive investigation of the conformational behavior of the intrinsically disordered domain (IDD) of PtkA using replica exchange molecular dynamics simulations. Long-term molecular dynamics (MD) simulations were performed to elucidate the role of IDD on the catalytic activity of kinase core domain (KCD) of PtkA. This was followed by identification of the probable inhibitors of PtkA using drug repurposing to block the PtpA-PtkA interaction. The inhibitory role of IDD on KCD has already been established; however, various analyses conducted in the present study showed that IDDPtkA had a greater inhibitory effect on the catalytic activity of KCDPtkA in the presence of the drugs esculin and inosine pranobex. The binding of drugs to PtkA resulted in formation of stable complexes, indicating that these two drugs are potentially useful as inhibitors of M.tb.
Project description:A screen of a eukaryotic kinase inhibitor library in an established intracellular infection model identified a set of drug candidates enabling intracellular killing of Mycobacterium tuberculosis (M.tb). Screen validity was confirmed internally by a Z' = 0.5 and externally by detecting previously reported host-targeting anti-M.tb compounds. Inhibitors of the CHK kinase family, specifically checkpoint kinase 2 (CHK2), showed the highest inhibition and lowest toxicity of all kinase families. The screen identified and validated DDUG, a CHK2 inhibitor, as a novel bactericidal anti-M.tb compound. CHK2 inhibition by RNAi phenocopied the intracellular inhibitory effect of DDUG. DDUG was active intracellularly against M.tb, but not other mycobacteria. DDUG also had extracellular activity against 4 of 12 bacteria tested, including M.tb. Combined, these observations suggest DDUG acts in tandem against both host and pathogen. Importantly, DDUG's validation highlights the screening and analysis methodology developed for this screen, which identified novel host-directed anti-M.tb compounds.
Project description:RATIONALE:Understanding mechanisms of resistance to M. tuberculosis (M.tb) infection in humans could identify novel therapeutic strategies as it has for other infectious diseases, such as HIV. OBJECTIVES:To compare the early transcriptional response of M.tb-infected monocytes between Ugandan household contacts of tuberculosis patients who demonstrate clinical resistance to M.tb infection (cases) and matched controls with latent tuberculosis infection. METHODS:Cases (n = 10) and controls (n = 18) were selected from a long-term household contact study in which cases did not convert their tuberculin skin test (TST) or develop tuberculosis over two years of follow up. We obtained genome-wide transcriptional profiles of M.tb-infected peripheral blood monocytes and used Gene Set Enrichment Analysis and interaction networks to identify cellular processes associated with resistance to clinical M.tb infection. MEASUREMENTS AND MAIN RESULTS:We discovered gene sets associated with histone deacetylases that were differentially expressed when comparing resistant and susceptible subjects. We used small molecule inhibitors to demonstrate that histone deacetylase function is important for the pro-inflammatory response to in-vitro M.tb infection in human monocytes. CONCLUSIONS:Monocytes from individuals who appear to resist clinical M.tb infection differentially activate pathways controlled by histone deacetylase in response to in-vitro M.tb infection when compared to those who are susceptible and develop latent tuberculosis. These data identify a potential cellular mechanism underlying the clinical phenomenon of resistance to M.tb infection despite known exposure to an infectious contact.
Project description:BACKGROUND: Mycobacterium tuberculosis (M.tb), the pathogen that causes tuberculosis, is capable of staying asymptomatically in a latent form, persisting for years in very low replicating state, before getting reactivated to cause active infection. It is therefore important to study M.tb chromosome replication, specifically its initiation and regulation. While the region between dnaA and dnaN gene is capable of autonomous replication, little is known about the interaction between DnaA initiator protein, oriC origin of replication sequences and their negative effectors of replication. METHODOLOGY/PRINCIPAL FINDINGS: By KMnO(4) mapping assays the sequences involved in open complex formation within oriC, mediated by M.tb DnaA protein, were mapped to position -500 to -518 with respect to the dnaN gene. Contrary to E. coli, the M.tb DnaA in the presence of non-hydrolysable analogue of ATP (ATPgammaS) was unable to participate in helix opening thereby pointing to the importance of ATP hydrolysis. Interestingly, ATPase activity in the presence of supercoiled template was higher than that observed for DnaA box alone. M.tb rRv1985c, a homologue of E.coli IciA (Inhibitor of chromosomal initiation) protein, could inhibit DnaA-mediated in-vitro helix opening by specifically binding to A+T rich region of oriC, provided the open complex formation had not initiated. rIciA could also inhibit in-vitro replication of plasmid carrying the M.tb origin of replication. CONCLUSIONS/SIGNIFICANCE: These results have a bearing on the functional role of the important regulator of M.tb chromosomal replication belonging to the LysR family of bacterial regulatory proteins in the context of latency.
Project description:One third of the world's population is infected with Mycobacterium tuberculosis (M.tb). A vaccine that would prevent progression to TB disease will have a dramatic impact on the global TB burden. We propose that antigens of M.tb that are preferentially expressed during latent infection will be excellent candidates for post-exposure vaccination. We therefore assessed human T cell recognition of two such antigens, Rv2660 and Rv2659. Expression of these was shown to be associated with non-replicating persistence in vitro. After six days incubation of PBMC from persons with latent tuberculosis infection (LTBI) and tuberculosis (TB) disease, Rv2660 and Rv2659 induced IFN-? production in a greater proportion of persons with LTBI, compared with TB diseased patients. Persons with LTBI also had increased numbers of viable T cells, and greater specific CD4(+) T cell proliferation and cytokine expression capacity. Persons with LTBI preferentially recognize Rv2659 and Rv2660, compared with patients with TB disease. These results suggest promise of these antigens for incorporation into post-exposure TB vaccines.
Project description:The emergence of multi- and extensively drug-resistant tuberculosis (MDR-TB and XDR-TB, respectively) has intensified the critical public health implications of this global disease. The fitness of Mycobacterium tuberculosis (M.tb.) strains exhibiting MDR and XDR phenotypes is of fundamental importance in predicting whether the MDR-/XDR-TB epidemic will be sustained across the human population. Here we describe a potential mechanism of M.tb. resistance to the TB drug isoniazid (INH) conferred by loss of a sigma factor, SigI. We demonstrate that the gain of INH resistance in the M.tb. ?sigI mutant might not diminish the organism's fitness for causing disease. These findings have significant implications when considering the ability of drug-resistant M.tb. strains to initiate untreatable TB epidemics, as it is possible that loss or alteration of SigI function could have a role in the generation of MDR and XDR M.tb. strains of suitable fitness to spread in a community setting.