Abstract
Mycobacterium tuberculosis (MTB) is the principal pathogen which causes tuberculosis (TB), a disease that remains as one of the most alarming health problems worldwide. An active area for the search of new anti-TB therapies is concerned with the use of computational approaches based on Chemoinformatics and/or Bioinformatics toward the discovery of new and potent anti-TB agents. These approaches consider only small series of structurally related compounds and the studies are generally realized for only one target like a protein. This fact constitutes an important limitation. The present work is an effort to overcome this problem. We introduce here the first chemo-bioinformatic approach by developing a multi-target (mt) QSAR discriminant model, for the in silico design and virtual screening of anti-TB agents against six proteins in MTB. The mt-QSAR model was developed by employing a large and heterogeneous database of compounds and substructural descriptors. The model correctly classified more than 90% of active and inactive compounds in both, training and prediction series. Some fragments were extracted from the molecules and their contributions to anti-TB activity through inhibition of the six proteins, were calculated. Several fragments were identified as responsible for anti-TB activity and new molecular entities were designed from those fragments with positive contributions, being suggested as possible anti-TB agents.
Keywords: Anti-TB activity, bioinformatics, chemoinformatics, fragment contributions, linear discriminant analysis, mt- QSAR, inhibitors, protein sequence, tuberculosis, anti-TB drugs
Combinatorial Chemistry & High Throughput Screening
Title:In Silico Discovery and Virtual Screening of Multi-Target Inhibitors for Proteins in Mycobacterium tuberculosis
Volume: 15 Issue: 8
Author(s): Alejandro Speck-Planche, Valeria V. Kleandrova, Feng Luan and M. Natalia D.S. Cordeiro
Affiliation:
Keywords: Anti-TB activity, bioinformatics, chemoinformatics, fragment contributions, linear discriminant analysis, mt- QSAR, inhibitors, protein sequence, tuberculosis, anti-TB drugs
Abstract: Mycobacterium tuberculosis (MTB) is the principal pathogen which causes tuberculosis (TB), a disease that remains as one of the most alarming health problems worldwide. An active area for the search of new anti-TB therapies is concerned with the use of computational approaches based on Chemoinformatics and/or Bioinformatics toward the discovery of new and potent anti-TB agents. These approaches consider only small series of structurally related compounds and the studies are generally realized for only one target like a protein. This fact constitutes an important limitation. The present work is an effort to overcome this problem. We introduce here the first chemo-bioinformatic approach by developing a multi-target (mt) QSAR discriminant model, for the in silico design and virtual screening of anti-TB agents against six proteins in MTB. The mt-QSAR model was developed by employing a large and heterogeneous database of compounds and substructural descriptors. The model correctly classified more than 90% of active and inactive compounds in both, training and prediction series. Some fragments were extracted from the molecules and their contributions to anti-TB activity through inhibition of the six proteins, were calculated. Several fragments were identified as responsible for anti-TB activity and new molecular entities were designed from those fragments with positive contributions, being suggested as possible anti-TB agents.
Export Options
About this article
Cite this article as:
Speck-Planche Alejandro, V. Kleandrova Valeria, Luan Feng and Natalia D.S. Cordeiro M., In Silico Discovery and Virtual Screening of Multi-Target Inhibitors for Proteins in Mycobacterium tuberculosis, Combinatorial Chemistry & High Throughput Screening 2012; 15 (8) . https://dx.doi.org/10.2174/138620712802650487
DOI https://dx.doi.org/10.2174/138620712802650487 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
Call for Papers in Thematic Issues
Artificial Intelligence Methods for Biomedical, Biochemical and Bioinformatics Problems
Recently, a large number of technologies based on artificial intelligence have been developed and applied to solve a diverse range of problems in the areas of biomedical, biochemical and bioinformatics problems. By utilizing powerful computing resources and massive amounts of data, methods based on artificial intelligence can significantly improve the ...read more
Eco-friendly Agents for Biological Control of Pathogenic Diseases
The discovery of an alternative biological approach to disease management includes work on medicinal products derived from natural sources as a starting point for the development of eco-friendly agents for these diseases and the injuries they cause, as well as reducing human contact with hazardous chemicals and their residues. We ...read more
Emerging trends in diseases mechanisms, noble drug targets and therapeutic strategies: focus on immunological and inflammatory disorders
Recently infectious and inflammatory diseases have been a key concern worldwide due to tremendous morbidity and mortality world Wide. Recent, nCOVID-9 pandemic is a good example for the emerging infectious disease outbreak. The world is facing many emerging and re-emerging diseases out breaks at present however, there is huge lack ...read more
Exploring Spectral Graph Theory in Combinatorial Chemistry
Scope of the Thematic Issue: Combinatorial chemistry involves the synthesis and analysis of a large number of diverse compounds simultaneously. Traditional methods rely on brute force experimentation, which can be time-consuming and resource-intensive. Spectral Graph Theory, a branch of mathematics dealing with the properties of graphs in relation to the ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Polymorphisms of Human N-Acetyltransferases and Cancer Risk
Current Drug Metabolism Interactions Between Proteins and Platinum-Containing Anti-Cancer Drugs
Mini-Reviews in Medicinal Chemistry Resistant TB: Newer Drugs and Community Approach
Recent Patents on Anti-Infective Drug Discovery Neurocysticercosis: The Enigmatic Disease
Central Nervous System Agents in Medicinal Chemistry Imidazole and 1,2,4-Triazole-based Derivatives Gifted with Antitubercular Activity: Cytotoxicity and Computational Assessment
Current Topics in Medicinal Chemistry Artificial Neural Network Methods Applied to Drug Discovery for Neglected Diseases
Combinatorial Chemistry & High Throughput Screening Genomic and Genetic Approaches for the Identification of Antifungal Drug Targets
Infectious Disorders - Drug Targets Recent Opportunities and Challenges in Selective C-H Functionalization of Methyl Azaarenes: A Highlight from 2010 to 2020 Studies
Current Organic Synthesis Sphingolipid Metabolism and Leukemia: A Potential for Novel Therapeutic Approaches
Anti-Cancer Agents in Medicinal Chemistry New Anti-Tuberculosis Drugs with Novel Mechanisms of Action
Current Medicinal Chemistry Is Targeting microRNAs the Philosopher’s Stone for Vascular Disease?
Current Vascular Pharmacology Targeted Drug Delivery Across the Blood Brain Barrier in Alzheimer’s Disease
Current Pharmaceutical Design Red Blood Cells as Modulators of T Cell Growth and Survival
Current Pharmaceutical Design Synthesis, In vitro and In silico Studies of Benzothiazole Azo-Ester Derivatives as Anti-TB Agents
Anti-Infective Agents Nutrition in Infancy
Current Pediatric Reviews A Mathematical Approach for the Simultaneous In Vitro Spectrophotometric Analysis of Rifampicin and Isoniazid from Modified-Release Anti-TB Drug Delivery Systems
Current Drug Delivery Pyrazinamide and Pyrazinoic Acid Derivatives Directed to Mycobacterial Enzymes Against Tuberculosis
Current Protein & Peptide Science Clinical and Forensic Aspects of Pharmacobezoars
Current Drug Research Reviews Anti-TNF and Pouch Surgery for Ulcerative Colitis: The Ones who Blame for More Complications?
Current Drug Targets Thiocoumarins and Dithiocoumarins: Advances in Synthesis and Pharmacological Activity
Current Organic Chemistry