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Chemogenomics and in silico repurposing as an innovative approach for rapid drug discovery in tuberculosis

Periodic Reporting for period 1 - iCHEMGENODRUGS_TB (Chemogenomics and in silico repurposing as an innovative approach for rapid drug discovery in tuberculosis)

Reporting period: 2018-09-01 to 2020-08-31

Tuberculosis (TB) remains a serious Public Health problem in many countries, causing millions of deaths per year. The World Health Organization launched the “End TB” strategy, which aims to reduce TB deaths by 95% and to cut new cases by 90% between 2015 and 2035. Although there has been a decrease in global TB incidence rates and mortality, the present rate of such decline is insufficient to meet the 2035 goals. Treatment of multidrug resistant TB (MDRTB) is extremely difficult since it requires more expensive drugs with a higher toxicity profile, during a longer period (up to 24 months), resulting in patient non-compliance and poorer outcomes. Therefore, there is a need to identify new drugs and new combined therapies that are better tolerated with the possibility to treat both drug-susceptible and drug-resistant TB alike, more quickly and efficiently.
In general, conventional drug discovery strategies are usually costly and time-consuming and, frequently, with low success rates. An alternative approach to accelerate and cheapen drug discovery is to find new uses for existing approved drugs, a practice known as drug repurposing. Since a repurposed drug does not trail through the research phase, it can follow directly to preclinical testing and clinical trials, thus reducing time, costs and risk.
This project used drug repurposing combined with comparative chemogenomics to identify drugs that target proteins involved in energy metabolism and membrane transport of Mycobacterium tuberculosis. This strategy identified 18 potential M. tuberculosis targets and 23 approved drugs. A group of selected compounds was evaluated using different in vitro methodologies, in order to identify the most promising drugs. This project contributed to the development of a new paradigm for the design of new drugs and new therapeutic strategies to be used in the fight against TB.
Bioinformatic analysis predicted 18 potential M. tuberculosis targets that are expected to interact with 23 approved drugs. These drugs are expected to target several proteins involved in energy metabolism and membrane transport in M. tuberculosis. Most of the identified drugs are approved for a variety of indications, such as arrhythmia, epilepsy, chronic immune thrombocytopenia, and cancer and may serve as lead compounds for the development of new anti-TB drugs. The identified drugs were: bedaquiline (anti-TB drug - proof of concept), doxorubicin, fostamatinib, thiabendazole, valproic acid, ouabain, metformin, omeprazole, pantoprazole, acetyldigitoxin, bretylium, deslanoside, dexlansoprazole, enasidenib, esomeprazole, ethacrynic acid, fomepizole, halothane, isoflurane, ivosidenib, levoleucovorin, rabeprazole and tipiracil.
A group of selected drugs (deslanoside, doxorubicin, fostamatinib, thiabendazole and valproic acid) were sequentially evaluated using an algorithm consisting of different in vitro methodologies, in order to identify the most promising drugs with potential application against mycobacteria. Doxorubicin showed the most effective antimycobacterial activity with a minimum inhibitory concentration (MIC) < 20 µM. However, the confirmation of the predicted target of doxorubicin in M. tuberculosis through the selection of resistant mutants in the presence of the compound was inconclusive. The other four compounds showed a MIC ≥ 20 µM. The most promising was valproic acid that showed synergistic interactions with the antibiotic clarithromycin. However, even if a given drug proved itself to be promising after these studies, the issue of toxicity had to be addressed. Therefore, evaluation of drug cytotoxicity was carried out in human macrophages. Some compounds presented cytotoxicity at the MIC, in particular doxorubicin and deslanoside. The results obtained during this project generated one peer reviewed publication and were presented in several congresses and conferences. Moreover, this work will bring the opportunity to develop future projects and collaborations that will further explore these drugs as lead compounds for the development and optimization of new effective drugs.
This project applied a new strategy for the development of anti-TB drugs using in silico drug repurposing. This approach can greatly improve drug discovery by reducing costs, risk and time and, when combined with in silico computer-aided drug design strategies, can help identify promising drug leads.
Concerning the identified potential anti-TB drugs, the ones with most promising activities could become important starting points for lead identification and optimization and, ultimately, for the development of new antimycobacterials. Future studies will continue to explore the usefulness and usage of these compounds.
Ending the TB epidemic by 2030 is one of the health targets of the United Nations Sustainable Development Goals (UN-SDGs). TB is a disease that also causes a major economic and social burden, being a significant drain on a society’s resources. Therefore, this project impacts on health, social and economic aspects by searching for new effective drugs that can tackle the problem of drug resistance and reduce the costs of TB treatment (via drug repurposing).
The experiences and results gained in this project will contribute to further advance in silico and computer-aided drug design strategies that will help to achieve the rapid discovery of novel, effective and safe drugs and ultimately decrease the global burden of TB and, thus, contributing to achieve the 2030 UN-SDGs.
Graphical Abstract