Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis

Journal of Translational Medicine

Research

Mukta Sharma¹  Divneet Kaur¹  Samir K. Brahmachari²  Ashwin K. Jainanarayan³  Shalu Mathew⁴  Azitha Begum⁴  Chinchu G. S. Nair⁴ 

[1] CSIR-Institute of Genomics and Integrative Biology, New Delhi, India;CSIR-Institute of Genomics and Integrative Biology, New Delhi, India;Centre for Open Innovation-Indian Centre for Social Transformation, Bengaluru, Karnataka, India;Academy of Scientific and Innovative Research, New Delhi, India;CSIR-Open Source Drug Discovery Unit, New Delhi, India;CSIR-Institute of Genomics and Integrative Biology, New Delhi, India;Indian Institute of Science Education and Research (IISER), Mohali, India;Centre for Open Innovation-Indian Centre for Social Transformation, Bengaluru, Karnataka, India;

关键词: Drug development;    Drug resistance;    Mycobacterium tuberculosis;    Non-toxic targets;    Structural biology;    Systems biology;   

DOI  :  10.1186/s12967-017-1363-9

 received in 2017-08-06, accepted in 2017-12-08,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundThe problem of drug resistance and bacterial persistence in tuberculosis is a cause of global alarm. Although, the UN’s Sustainable Development Goals for 2030 has targeted a Tb free world, the treatment gap exists and only a few new drug candidates are in the pipeline. In spite of large information from medicinal chemistry to ‘omics’ data, there has been a little effort from pharmaceutical companies to generate pipelines for the development of novel drug candidates against the multi drug resistant Mycobacterium tuberculosis.MethodsIn the present study, we describe an integrated methodology; utilizing systems level information to optimize ligand selection to lower the failure rates at the pre-clinical and clinical levels. In the present study, metabolic targets (Rv2763c, Rv3247c, Rv1094, Rv3607c, Rv3048c, Rv2965c, Rv2361c, Rv0865, Rv0321, Rv0098, Rv0390, Rv3588c, Rv2244, Rv2465c and Rv2607) in M. tuberculosis, identified using our previous Systems Biology and data-intensive genome level analysis, have been used to design potential lead molecules, which are likely to be non-toxic. Various in silico drug discovery tools have been utilized to generate small molecular leads for each of the 15 targets with available crystal structures.ResultsThe present study resulted in identification of 20 novel lead molecules including 4 FDA approved drugs (droxidropa, tetroxoprim, domperidone and nemonapride) which can be further taken for drug repurposing. This comprehensive integrated methodology, with both experimental and in silico approaches, has the potential to not only tackle the MDR form of Mtb but also the most important persister population of the bacterium, with a potential to reduce the failures in the Tb drug discovery.ConclusionWe propose an integrated approach of systems and structural biology for identifying targets that address the high attrition rate issue in lead identification and drug development We expect that this system level analysis will be applicable for identification of drug candidates to other pathogenic organisms as well.

【 授权许可】

CC BY   
© The Author(s) 2017