Trends in Microbiology
ReviewComputational databases, pathway and cheminformatics tools for tuberculosis drug discovery
Section snippets
New drugs for tuberculosis
Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), infects approximately one-third of the world's population and annually 1.7–1.8 million people die from this disease [1]. The past decade has witnessed the growing menace of both increasing numbers of cases of drug-sensitive and drug-resistant strains and the recognition that fighting this global health pandemic requires a multifaceted research effort from both academia and industry. Infection with drug-sensitive TB can
Databases for TB
We are aware of over 300 000 compounds screened against Mtb in one laboratory alone, so it is likely that several million compounds have been examined cumulatively to date by all groups. It was not until recently that a central location for these screening results was developed. The advantage of collating such data is that it might prevent repetition of screening by different groups, while also allowing large scale analysis of molecular properties of compounds with antitubercular whole cell
Pathway tools and technologies
It has been suggested that an integrated analysis of metabolic pathways, small molecule screening and structural databases will facilitate anti-TB screening efforts [12], which reflects more of a systems biology (see Glossary) and computer aided drug discovery approach. Systems biology approaches based on predictive networks will be increasingly developed at the interface of cheminformatics and bioinformatics, with applications for target selection and discovery 13, 14 alongside other target
Applications of systems biology to TB
One example of TB systems biology research is a study using gene expression data to identify stress response networks before and after treatment with different drugs [17]. The research combined the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCyc metabolic pathway databases with previously published gene expression data and a k-shortest path algorithm. It was found that gene expression networks for isoniazid treatment indicated a generic stress response. This type of approach could
Computational cheminformatic tools and their uses
Computational approaches applied to TB have predominantly implemented standard commercially available cheminformatic methods, as will be described in the following section. These methods have been generally used by specialists focused on a single target or series of compounds, and rarely in combination with other computational tools. Owing to space limitations, we have focused our analysis of cheminformatics tools used in TB research within the past 5 years.
Gap analysis for computational methods in TB drug discovery
The computational methods previously described are widely used in workflows by many project teams in the pharmaceutical industry. We found several gaps when we looked at how computational methods could be used in TB drug discovery (Figure 1) compared with the various reported efforts to date. Beginning with the recent popularity of high-throughput, whole-cell phenotypic screening of large commercial libraries, we noted limited use of filtering of the library input or resulting hit lists for
Conclusions and future perspectives
In the TB community, there appears to be a disparity between the generation and utilization of computational models and the entire drug discovery process. TB models are not well disseminated, shared or even reused, and serve an isolated purpose for publication or comprehending a very limited structure–activity relation. At present, these computational models are in the hands of cheminformatics experts, and insufficient efforts have been made in their dissemination on publicly accessible
Conflicts of interest
S.E. is a consultant for Collaborative Drug Discovery. The other authors have no conflicts of interest.
Acknowledgments
S.E. acknowledges Dr Barry A. Bunin and colleagues for developing the CDD TB database as well as the many TB research collaborators. The CDD TB database along with introductory training was provided freely to Mtb researchers until the end of October 2010 thanks to funding from the Bill and Melinda Gates Foundation (Grant number 49852 Collaborative Drug Discovery for TB Through a Novel Database of SAR Data Optimized to Promote Data Archiving and Sharing). The project described was supported by
References (100)
Rising standards for tuberculosis drug development
Trends Pharmacol. Sci.
(2008)Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
Adv. Drug Del. Rev.
(1997)Use of genomics and combinatorial chemistry in the development of new antimycobacterial drugs
Biochem. Pharmacol.
(2000)Antituberculosis activity of the molecular libraries screening center network library
Tuberculosis
(2009)High-throughput screening for inhibitors of Mycobacterium tuberculosis H37Rv
Tuberculosis
(2009)- et al.
Troubleshooting computational methods in drug discovery
J. Pharmacol. Toxicol. Methods
(2010) Search of chemical scaffolds for novel antituberculosis agents
J. Biomol. Screen
(2005)Docking and chemoinformatic screens for new ligands and targets
Curr. Opin. Biotechnol.
(2009)Discovery of potential new InhA direct inhibitors based on pharmacophore and 3D-QSAR analysis followed by in silico screening
Eur. J. Med. Chem.
(2009)Evaluation of the amino acid binding site of Mycobacterium tuberculosis glutamine synthetase for drug discovery
Bioorg. Med. Chem.
(2008)
Novel web-based tools combining chemistry informatics, biology and social networks for drug discovery
Drug Disc. Today
TBrowse: an integrative genomics map of Mycobacterium tuberculosis
Tuberculosis (Edinburgh, Scotland)
Learning from the genome sequence of Mycobacterium tuberculosis H37Rv
FEBS Lett.
The TB structural genomics consortium: a resource for Mycobacterium tuberculosis biology
Tuberculosis
Potential drug targets in Mycobacterium tuberculosis through metabolic pathway analysis
Comput. Biol. Chem.
Synthesis, anti-tuberculosis activity, and 3D-QSAR study of ring-substituted-2/4-quinolinecarbaldehyde derivatives
Bioorg. Med. Chem.
Synthesis of novel 5-aryl-2-thio-1,3,4-oxadiazoles and the study of their structure-anti-mycobacterial activities
Bioorg. Med. Chem.
3D-QSAR studies on antitubercular thymidine monophosphate kinase inhibitors based on different alignment methods
Bioorg. Med. Chem. Lett.
Quantitative structure-activity relationship studies on nitrofuranyl anti-tubercular agents
Bioorg. Med. Chem.
Synthesis, anti-tuberculosis activity, and 3D-QSAR study of 4-(adamantan-1-yl)-2-substituted quinolines
Bioorg. Med. Chem.
3D-QSAR study of ring-substituted quinoline class of anti-tuberculosis agents
Bioorg. Med. Chem.
NAD+-dependent DNA Ligase (Rv3014c) from Mycobacterium tuberculosis. Crystal structure of the adenylation domain and identification of novel inhibitors
J. Biol. Chem.
New small-molecule synthetic antimycobacterials
Antimicrob. Agents Chemother.
The magic bullets and tuberculosis drug targets
Annu. Rev. Pharmacol. Toxicol.
Virtual screening: an endless staircase?
Nat. Rev. Drug Discov.
Computational systems approach for drug target discovery
Expert Opin. Drug Disc.
Current status of some antituberculosis drugs and the development of new antituberculous agents with special reference to their in vitro and in vivo antimicrobial activities
Curr. Pharm. Des.
Structure-based approaches to drug discovery against tuberculosis
Curr. Protein Pept. Sci.
Isoniazid is not a lead compound for its pyridyl ring derivatives, isonicotinoyl amides, hydrazides, and hydrazones: a critical review
Curr. Med. Chem.
Structural bioinformatic approaches to the discovery of new antimycobacterial drugs
Curr. Pharm. Des.
targetTB: a target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis
BMC Syst. Biol.
A Collaborative Database And Computational Models For Tuberculosis Drug Discovery
Mol. Biosyst.
Tuberculosis
BMJ
Systems biology: applications in drug discovery
Computers and systems biology for Pharmaceutical Research and Development
Prioritizing genomic drug targets in pathogens: application to Mycobacterium tuberculosis
PLoS Comput. Biol.
Differential network expression during drug and stress response
Bioinformatics
Strategies for efficient disruption of metabolism in Mycobacterium tuberculosis from network analysis
Mol. Biosyst.
A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis
Mol. Biosyst.
Fishing the target of antitubercular compounds: in silico target deconvolution model development and validation
J. Proteome Res.
Drug discovery using chemical systems biology: repositioning the safe medicine Comtan to treat multi-drug and extensively drug resistant tuberculosis
PLoS Comput. Biol.
New frontiers in the therapy of tuberculosis: fighting with the global menace
Mini Rev. Med.
Prediction of hydrophobic (lipophilic) properties of small organic molecules using fragmental methods: an analysis of ALOGP and CLOGP methods
J. Phys. Chem.
Physicochemical properties of antibacterial compounds: implications for drug discovery
J. Med. Chem.
Drugs for bad bugs: confronting the challenges of antibacterial discovery
Nat. Rev. Drug Disc.
Analysis of the calculated physicochemical properties of respiratory drugs: can we design for inhaled drugs yet?
J. Chem. Inf. Model.
Analysis and hit filtering of a very large library of compounds screened against Mycobacterium tuberculosis
Mol. Biosyst.
Developing an antituberculosis compounds database and data mining in the search of a motif responsible for the activity of a diverse class of antituberculosis agents
J. Chem. Inf. Model.
Design of novel antituberculosis compounds using graph-theoretical and substructural approaches
Mol. Divers.
Cited by (79)
Recent advances in CADD
2022, Computer Aided Drug Design (CADD): From Ligand-Based Methods to Structure-Based ApproachesStructure-aided optimization of non-nucleoside M. tuberculosis thymidylate kinase inhibitors
2021, European Journal of Medicinal ChemistryDesign, synthesis, and biological evaluation of benzo[d]imidazole-2-carboxamides as new anti-TB agents
2021, Bioorganic ChemistryMapping genomes by using bioinformatics data and tools
2021, Chemoinformatics and Bioinformatics in the Pharmaceutical SciencesAnti-tubercular profile of new selenium-menadione conjugates against Mycobacterium tuberculosis H37Rv (ATCC 27294) strain and multidrug-resistant clinical isolates
2021, European Journal of Medicinal ChemistryCitation Excerpt :According to the importance of estimating the distribution and diffusion of drugs to across the cell membrane and tissue and their solubilization in an aqueous medium, the CLogP was calculated. In particular, it has been well established that the lipophilicity of anti-TB drug candidates is positively correlated with their ability to permeate through M. tuberculosis cell wall [55]. As reported in Table 2, the compounds 8a-i showed CLogP values in the range of 4.31–6.88.
Synthesis and structure-activity relationships for tetrahydroisoquinoline-based inhibitors of Mycobacterium tuberculosis
2020, Bioorganic and Medicinal Chemistry
- *
Present address: Medicinal Chemistry, Institut Pasteur Korea, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea.