scholarly journals Data Intensive Genome Level Analysis for Identifying Novel, Non-Toxic Drug Targets for Multi Drug Resistant Mycobacterium tuberculosis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Divneet Kaur ◽  
Rintu Kutum ◽  
Debasis Dash ◽  
Samir K. Brahmachari
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Discovery ◽  
Drug Targets ◽  
Systems Approach ◽  
Data Bank ◽  
Data Intensive ◽  
Synonymous Mutations ◽  
Starting Point ◽  
Genome Level ◽  
Level Analysis

Abstract We report the construction of a novel Systems Biology based virtual drug discovery model for the prediction of non-toxic metabolic targets in Mycobacterium tuberculosis (Mtb). This is based on a data-intensive genome level analysis and the principle of conservation of the evolutionarily important genes. In the 1623 sequenced Mtb strains, 890 metabolic genes identified through a systems approach in Mtb were evaluated for non-synonymous mutations. The 33 genes showed none or one variation in the entire 1623 strains, including 1084 Russian MDR strains. These invariant targets were further evaluated for their experimental and in silico essentiality as well as availability of their crystal structure in Protein Data Bank (PDB). Along with this, targets for the common existing antibiotics and the new Tb drug candidates were also screened for their variation across 1623 strains of Mtb for understanding the drug resistance. We propose that the reduced set of these reported targets could be a more effective starting point for medicinal chemists in generating new chemical leads. This approach has the potential of fueling the dried up Tuberculosis (Tb) drug discovery pipeline.

scholarly journals Erratum: Data Intensive Genome Level Analysis for Identifying Novel, Non-Toxic Drug Targets for Multi Drug Resistant Mycobacterium tuberculosis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Divneet Kaur ◽  
Rintu Kutum ◽  
Debasis Dash ◽  
Samir K. Brahmachari
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Targets ◽  
Drug Resistant ◽  
Data Intensive ◽  
Toxic Drug ◽  
Genome Level ◽  
Level Analysis

scholarly journals 194 Designing non-toxic ligands against TB using data intensive genome level analysis

2015 ◽  
Vol 33 (sup1) ◽  
pp. 128-128
Author(s):  
Divneet Kaur ◽  
S.K. Brahmachari
Keyword(s):  
Data Intensive ◽  
Genome Level ◽  
Using Data ◽  
Level Analysis

scholarly journals Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications

2020 ◽  
Vol 22 (1) ◽  
pp. 166
Author(s):  
Shen Chang ◽  
Jian-You Chen ◽  
Yung-Jen Chuang ◽  
Bor-Sen Chen
Keyword(s):  
Type 2 Diabetes ◽  
Drug Discovery ◽  
Signaling Pathways ◽  
Drug Targets ◽  
Regulatory Networks ◽  
Systems Approach ◽  
Pathogenic Mechanism ◽  
Detection Methods ◽  
Design Specifications

In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for type 2 diabetes (T2D) treatment. We first integrated databases to construct the genome-wide genetic and epigenetic networks (GWGENs), which consist of protein–protein interaction networks (PPINs) and gene regulatory networks (GRNs) for T2D and non-T2D (health), respectively. Second, the relevant “real GWGENs” are identified by system identification and system order detection methods performed on the T2D and non-T2D RNA-seq data. To simplify network analysis, principal network projection (PNP) was thereby exploited to extract core GWGENs from real GWGENs. Then, with the help of KEGG pathway annotation, core signaling pathways were constructed to identify significant biomarkers. Furthermore, in order to discover potential drugs for the selected pathogenic biomarkers (i.e., drug targets) from the core signaling pathways, not only did we train a deep neural network (DNN)-based drug–target interaction (DTI) model to predict candidate drug’s binding with the identified biomarkers but also considered a set of design specifications, including drug regulation ability, toxicity, sensitivity, and side effects to sieve out promising drugs suitable for T2D.

scholarly journals Recent Insights from Molecular Dynamics Simulations for G Protein-Coupled Receptor Drug Discovery

2019 ◽  
Vol 20 (17) ◽  
pp. 4237 ◽  
Author(s):  
Zou ◽  
Ewalt ◽  
Ng
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
G Protein ◽  
Drug Targets ◽  
Conformational Dynamics ◽  
Md Simulations ◽  
Data Bank ◽  
G Protein Coupled Receptor ◽  
Biased Signaling ◽  
G Protein Coupled

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. Some ligands that bind to GPCRs activate different downstream signaling pathways. G protein activation, or -arrestin biased signaling, involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. -arrestin biased signaling has become a hot target for structure-based drug discovery. However, challenges include that there are few crystal structures available in the Protein Data Bank and that GPCRs are highly dynamic. Hence, molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators’ interactions with receptors and ligands. Here, we highlight recent MD simulation studies and enhanced sampling methods used to study biased G protein-coupled receptor signaling and their conformational dynamics as well as applications to drug discovery.

scholarly journals Pangenome Analysis of Mycobacterium tuberculosis Reveals Core-Drug Targets and Screening of Promising Lead Compounds for Drug Discovery

Antibiotics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 819
Author(s):  
Hamza Arshad Dar ◽  
Tahreem Zaheer ◽  
Nimat Ullah ◽  
Syeda Marriam Bakhtiar ◽  
Tianyu Zhang ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Discovery ◽  
Drug Targets ◽  
Uridine Diphosphate ◽  
Lead Compounds ◽  
Diphosphate Glucose ◽  
Inhibitory Potential ◽  
Conserved Core ◽  
Effective Drugs ◽  
Novel Drug

Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), is one of the leading causes of human deaths globally according to the WHO TB 2019 report. The continuous rise in multi- and extensive-drug resistance in M. tuberculosis broadens the challenges to control tuberculosis. The availability of a large number of completely sequenced genomes of M. tuberculosis has provided an opportunity to explore the pangenome of the species along with the pan-phylogeny and to identify potential novel drug targets leading to drug discovery. We attempt to calculate the pangenome of M. tuberculosis that comprises a total of 150 complete genomes and performed the phylo-genomic classification and analysis. Further, the conserved core genome (1251 proteins) is subjected to various sequential filters (non-human homology, essentiality, virulence, physicochemical parameters, and pathway analysis) resulted in identification of eight putative broad-spectrum drug targets. Upon molecular docking analyses of these targets with ligands available at the DrugBank database shortlisted a total of five promising ligands with projected inhibitory potential; namely, 2′deoxy-thymidine-5′-diphospho-alpha-d-glucose, uridine diphosphate glucose, 2′-deoxy-thymidine-beta-l-rhamnose, thymidine-5′-triphosphate, and citicoline. We are confident that with further lead optimization and experimental validation, these lead compounds may provide a sound basis to develop safe and effective drugs against tuberculosis disease in humans.

scholarly journals Screening of Antitubercular Compound Library Identifies Inhibitors of Mur Enzymes in Mycobacterium tuberculosis

2019 ◽  
Vol 25 (1) ◽  
pp. 70-78 ◽  
Author(s):  
Kandasamy Eniyan ◽  
Jyoti Rani ◽  
Srinivasan Ramachandran ◽  
Rahul Bhat ◽  
Inshad Ali Khan ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Targets ◽  
Multidrug Resistant ◽  
Dynamics Simulation ◽  
Compound Library ◽  
Vitro Assay ◽  
Starting Point ◽  
Clinical Drugs ◽  
The Stability

The rapid rise in the emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis (Mtb) mandates the discovery of novel tuberculosis (TB) drugs. Mur enzymes, which are identified as essential proteins in Mtb and catalyze the cytoplasmic steps in the peptidoglycan biosynthetic pathway, are considered potential drug targets. However, none of the clinical drugs have yet been developed against these enzymes. Hence, the aim of this study was to identify novel inhibitors of Mur enzymes in Mycobacterium tuberculosis. We screened an antitubercular compound library of 684 compounds, using MurB and MurE enzymes of the Mtb Mur pathway as drug targets. For experimental validation, the top hits obtained on in silico screening were screened in vitro, using Mtb Mur enzyme-specific assays. In all, seven compounds were found to show greater than 50% inhibition, with the highest inhibition observed at 77%, and the IC50 for these compounds was found to be in the range of 28–50 μM. Compound 5175112 showed the lowest IC50 (28.69 ± 1.17 μM), and on the basis of (1) the binding affinity, (2) the stability of interaction noted on molecular dynamics simulation, and (3) an in vitro assay, MurE appeared to be its target enzyme. We believe that the overall strategy followed in this study and the results obtained are a good starting point for developing Mur enzyme-specific Mtb inhibitors.

Discovery of an Unexpected Similarity in Ligand Binding Between BRD4 and PPARγ

2019 ◽  
Author(s):  
Lina Humbeck ◽  
Jette Pretzel ◽  
Saskia Spitzer ◽  
Oliver Koch
Keyword(s):  
Cancer Therapy ◽  
Drug Targets ◽  
Synergistic Effects ◽  
Complex Structure ◽  
Peroxisome Proliferator ◽  
Resistance Development ◽  
Peroxisome Proliferator Activated Receptor ◽  
Starting Point ◽  
Fundamental Research ◽  
Important Drug

Knowledge about interrelationships between different proteins is crucial in fundamental research for the elucidation of protein networks and pathways. Furthermore, it is especially critical in chemical biology to identify further key regulators of a disease and to take advantage of polypharmacology effects. A comprehensive scaffold-based analysis uncovered an unexpected relationship between bromodomain-containing protein 4 (BRD4) and peroxisome-proliferator activated receptor gamma (PPARγ). They are both important drug targets for cancer therapy and many more important diseases. Both proteins share binding site similarities near a common hydrophobic subpocket which should allow the design of a polypharmacology-based ligand targeting both proteins. Such a dual-BRD4-PPARγ-modulator could show synergistic effects with a higher efficacy or delayed resistance development in, for example, cancer therapy. Thereon, a complex structure of sulfasalazine was obtained that involves two bromodomains and could be a potential starting point for the design of a bivalent BRD4 inhibitor.

Adenylating Enzymes in Mycobacterium tuberculosis as Drug Targets

2012 ◽  
Vol 12 (7) ◽  
pp. 766-796 ◽  
Author(s):  
Benjamin P. Duckworth ◽  
Kathryn M. Nelson ◽  
Courtney C. Aldrich
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Targets

Exploration of Ion Channels in Mycobacterium tuberculosis: Implication on Drug Discovery and Potent Drug Targets Against Tuberculosis

2020 ◽  
Vol 14 (1) ◽  
pp. 14-29
Author(s):  
Manish Dwivedi
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Targets ◽  
Cell Envelope ◽  
Intracellular Pathogen ◽  
Host Immune System ◽  
Transporter Proteins ◽  
Channel Proteins ◽  
Medical Importance ◽  
Potent Drug ◽  
Emergence Of Resistance

Scientific interest in mycobacteria has been sparked by the medical importance of Mycobacterium tuberculosis (Mtb) that is known to cause severe diseases in mammals, i.e. tuberculosis and by properties that distinguish them from other microorganisms which are notoriously difficult to treat. The treatment of their infections is difficult because mycobacteria fortify themselves with a thick impermeable cell envelope. Channel and transporter proteins are among the crucial adaptations of Mycobacterium that facilitate their strength to combat against host immune system and anti-tuberculosis drugs. In previous studies, it was investigated that some of the channel proteins contribute to the overall antibiotic resistance in Mtb. Moreover, in some of the cases, membrane proteins were found responsible for virulence of these pathogens. Given the ability of M. tuberculosis to survive as an intracellular pathogen and its inclination to develop resistance to the prevailing anti-tuberculosis drugs, its treatment requires new approaches and optimization of anti-TB drugs and investigation of new targets are needed for their potential in clinical usage. Therefore, it is imperative to investigate the survival of Mtb. in stressed conditions with different behavior of particular channel/ transporter proteins. Comprehensive understanding of channel proteins and their mechanism will provide us direction to find out preventive measures against the emergence of resistance and reduce the duration of the treatment, eventually leading to plausible eradication of tuberculosis.

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