Journal of Chemical Sciences

, Volume 129, Issue 5, pp 515–531 | Cite as

Assessing therapeutic potential of molecules: molecular property diagnostic suite for tuberculosis \((\mathbf{MPDS}^{\mathbf{TB}})\)

  • Anamika Singh Gaur
  • Anshu Bhardwaj
  • Arun Sharma
  • Lijo John
  • M Ram Vivek
  • Neha Tripathi
  • Prasad V Bharatam
  • Rakesh Kumar
  • Sridhara Janardhan
  • Abhaysinh Mori
  • Anirban Banerji
  • Andrew M Lynn
  • Anmol J Hemrom
  • Anurag Passi
  • Aparna Singh
  • Asheesh Kumar
  • Charuvaka Muvva
  • Chinmai Madhuri
  • Chinmayee Choudhury
  • D Arun Kumar
  • Deepak Pandit
  • Deepak R. Bharti
  • Devesh Kumar
  • ER Azhagiya Singam
  • Gajendra PS Raghava
  • Hari Sailaja
  • Harish Jangra
  • Kaamini Raithatha
  • Karunakar Tanneeru
  • Kumardeep Chaudhary
  • M Karthikeyan
  • M Prasanthi
  • Nandan Kumar
  • N Yedukondalu
  • Neeraj K Rajput
  • P Sri Saranya
  • Pankaj Narang
  • Prasun Dutta
  • R Venkata Krishnan
  • Reetu Sharma
  • R Srinithi
  • Ruchi Mishra
  • S Hemasri
  • Sandeep Singh
  • Subramanian Venkatesan
  • Suresh Kumar
  • Uca Jaleel
  • Vijay Khedkar
  • Yogesh Joshi
  • G Narahari Sastry
Regular Article

Abstract

Molecular Property Diagnostic Suite (\(\text {MPDS}^{\mathrm{TB}}\)) is a web tool (http://mpds.osdd.net) designed to assist the in silico drug discovery attempts towards Mycobacterium tuberculosis (Mtb). \(\text {MPDS}^{\mathrm{TB}}\) tool has nine modules which are classified into data library (1–3), data processing (4–5) and data analysis (6–9). Module 1 is a repository of literature and related information available on the Mtb. Module 2 deals with the protein target analysis of the chosen disease area. Module 3 is the compound library consisting of 110.31 million unique molecules generated from public domain databases and custom designed search tools. Module 4 contains tools for chemical file format conversions and 2D to 3D coordinate conversions. Module 5 helps in calculating the molecular descriptors. Module 6 specifically handles QSAR model development tools using descriptors generated in the Module 5. Module 7 integrates the AutoDock Vina algorithm for docking, while module 8 provides screening filters. Module 9 provides the necessary visualization tools for both small and large molecules. The workflow-based open source web portal, \(\text {MPDS}^{\mathrm{TB}}\) 1.0.1 can be a potential enabler for scientists engaged in drug discovery in general and in anti-TB research in particular.

Graphical Abstract

SYNOPSIS: A web-based \(\text {MPDS}^{\mathrm{TB}}\) Galaxy tool is developed for assessing therapeutic potential of molecules. \(\text {MPDS}^{\mathrm{TB}}\) is categorized into Data Library, Data Processing and Data Analysis. It can be a potential enabler for scientists engaged in drug discovery in general and in anti-TB research in particular.

Keywords

Tuberculosis chemoinformatics open science neglected diseases drug discovery portal web-based technology 

Notes

Acknowledgements

We are thankful to OSDD, CSIR and Sir Dorabji TATA trust for providing TCOF fellowships to some of the authors in the study. CSIR \(12^{\mathrm{th}}\) five year program GENESIS (BSC 0121), Department of Science and Technology (New Delhi) and Department of Biotechnology (New Delhi) are also thanked for funding. Code development has taken about 5 years of time starting from 2012 and has witnessed 5 Workshops in IICT, IMTECH, OSDD centre, Bangalore, and NCL. Besides there were several exchange of students between various institutes. We thank CSIR OSDD consortium, NIPER, JNU, and BBAU for providing support. GNS thank J C Bose fellowship of DST. This manuscript is dedicated to the memory of Dr. Anirban Banerji and Dr. Pankaj Narang who have provided a lot of energy and enthusiasm during the kick-start stages of the MPDS teamwork.

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Copyright information

© Indian Academy of Sciences 2017

Authors and Affiliations

  • Anamika Singh Gaur
    • 1
  • Anshu Bhardwaj
    • 2
  • Arun Sharma
    • 2
  • Lijo John
    • 1
  • M Ram Vivek
    • 1
  • Neha Tripathi
    • 3
  • Prasad V Bharatam
    • 3
  • Rakesh Kumar
    • 2
  • Sridhara Janardhan
    • 1
  • Abhaysinh Mori
    • 3
  • Anirban Banerji
    • 1
  • Andrew M Lynn
    • 5
  • Anmol J Hemrom
    • 5
  • Anurag Passi
    • 2
  • Aparna Singh
    • 1
  • Asheesh Kumar
    • 7
  • Charuvaka Muvva
    • 4
  • Chinmai Madhuri
    • 6
  • Chinmayee Choudhury
    • 1
  • D Arun Kumar
    • 1
  • Deepak Pandit
    • 6
  • Deepak R. Bharti
    • 5
  • Devesh Kumar
    • 7
  • ER Azhagiya Singam
    • 4
  • Gajendra PS Raghava
    • 2
  • Hari Sailaja
    • 8
  • Harish Jangra
    • 3
  • Kaamini Raithatha
    • 8
  • Karunakar Tanneeru
    • 1
  • Kumardeep Chaudhary
    • 2
  • M Karthikeyan
    • 6
  • M Prasanthi
    • 1
  • Nandan Kumar
    • 1
  • N Yedukondalu
    • 1
  • Neeraj K Rajput
    • 2
  • P Sri Saranya
    • 1
  • Pankaj Narang
    • 5
  • Prasun Dutta
    • 8
  • R Venkata Krishnan
    • 3
  • Reetu Sharma
    • 1
  • R Srinithi
    • 1
  • Ruchi Mishra
    • 7
  • S Hemasri
    • 1
  • Sandeep Singh
    • 2
  • Subramanian Venkatesan
    • 4
  • Suresh Kumar
    • 7
  • Uca Jaleel
    • 8
  • Vijay Khedkar
    • 6
  • Yogesh Joshi
    • 6
  • G Narahari Sastry
    • 1
  1. 1.Centre for Molecular Modeling, CSIR-Indian Institute of Chemical TechnologyTarnaka, HyderabadIndia
  2. 2.Bioinformatics Centre, CSIR-Institute of Microbial TechnologyChandigarhIndia
  3. 3.Department of Medicinal ChemistryNational Institute of Pharmaceutical Education and Research (NIPER)MohaliIndia
  4. 4.Chemical LaboratoryCSIR-Central Leather Research InstituteChennaiIndia
  5. 5.School of Computational and Integrative SciencesJawaharlal Nehru UniversityNew DelhiIndia
  6. 6.Chemical Engineering and Process DevelopmentCSIR-National Chemical LaboratoryPuneIndia
  7. 7.Department of Applied PhysicsBabasaheb Bhimrao Ambedkar UniversityLucknowIndia
  8. 8.Open Source Drug Discovery ConsortiumNew DelhiIndia

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