Drug Discovery Using Chemical Systems Biology: Repositioning the Safe Medicine Comtan to Treat Multi-Drug and Extensively Drug Resistant Tuberculosis

By Sarah L. Kinnings, Nina Liu, N. Buchmeier, P. Tonge, Lei Xie, Philip E. Bourne. PLoS Comput. Biol., 2009

330 citations recorded by the source corpus.

The rise of multi-drug resistant (MDR) and extensively drug resistant (XDR) tuberculosis around the world, including in industrialized nations, poses a great threat to human health and defines a need to develop new, effective and inexpensive anti-tubercular agents. Previously we developed a chemical systems biology approach to identify off-targets of major pharmaceuticals on a proteome-wide scale. In this paper we further demonstrate the value of this approach through the discovery that existing commercially available drugs, prescribed for the treatment of Parkinson's disease, have the potential to treat MDR and XDR tuberculosis. These drugs, entacapone and tolcapone, are predicted to bind to the enzyme InhA and directly inhibit substrate binding. The prediction is validated by in vitro and InhA kinetic assays using tablets of Comtan, whose active component is entacapone. The minimal inhibition concentration (MIC99) of entacapone for Mycobacterium tuberculosis (M.tuberculosis) is approximately 260.0 µM, well below the toxicity concentration determined by an in vitro cytotoxicity model using a human neuroblastoma cell line. Moreover, kinetic assays indicate that Comtan inhibits InhA activity by 47.0% at an entacapone concentration of approximately 80 µM. Thus the active component in Comtan represents a promising lead compound for developing a new class of anti-tubercular therapeutics with excellent safety profiles. More generally, the protocol described in this paper can be included in a drug discovery pipeline in an effort to discover novel drug leads with desired safety profiles, and therefore accelerate the development of new drugs.

Subfields: Computational Theory and Mathematics, Infectious Diseases, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9bc6a6a3137ed69b52e7ccf896d602e1a2835bc7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Infectious Diseases

In Molecular Biology

Citations in the corpus

Exploiting drug-disease relationships for computational drug repositioning (2011, methodology): “[29] employed molecular docking in a chemical systems biology approach to reposition Entacapone, a catechol-O-methyl transferase (COMT) inhibitor used to treat Parkinson’s disease, as a treatment for multi-drug resistant (MDR) tuberculosis.”
Docking & Chemoinformatic Screens for New Ligands and Targets (2009, background): “Other studies, which return to a more structure-based method for predicting off-target effects, including docking, have also revealed new off-targets, though these efforts remain at an earlier stage than the chemoinformatics approaches [52].”
Computational Drug Repositioning: From Data to Therapeutics (2013, methodology): “46 Because not all protein structures have been resolved, methods utilizing the structural or physiochemical properties of the ligands were developed, 47,48 impressively validating 23 of 30 novel drug-target predictions.”
Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction (2016, neutral): “In general, traditional computational methods proposed for DTI prediction can be categorized into two main groups: docking simulation approaches and ligand-based approaches [6–8].”
Discovery and preclinical validation of drug indications using compendia of public gene expression data (2011, background): “…approaches to the discovery of novel biological targets for approved drugs have been developed to overcome the high costs and other logistical limitations associated with experimental HTS approaches, allowing for greatly expanded searches for novel repositioning opportunities ( 5 – 10 ).”
Molecular Docking: Shifting Paradigms in Drug Discovery (2019, background): “Their results allowed the identification of entacapone as a promising lead compound against resistant strains of Mycobacterium tuberculosis [51].”
Automatic construction of a large-scale and accurate drug-side-effect association knowledge base from biomedical literature (2014, background): “The majority of these approaches leverage on known drug properties such as chemical similarity [15], molecular activity similarity [20], molecular docking [17], and gene expression profile similarity [13, 24].”
PREDICT: a method for inferring novel drug indications with application to personalized medicine (2011, neutral): “Table is supplemented as an Excel file.”
Structure-based Systems Biology for Analyzing Off-target Binding (2011, background): “In another study, the pharmaceutical Comtan (entacapone), which is a COMT methyltransferase inhibitor used to treat Parkinson’s disease, has shown direct inhibition of InhA, one of the most used drug targets against tuberculosis [46].”