Turbo Analytics: Applications
of Big Data and HPC in Drug Discovery
Rajendra R. Joshi, Uddhavesh Sonavane, Vinod Jani, Amit Saxena,
Shruti Koulgi, Mallikarjunachari Uppuladinne, Neeru Sharma,
Sandeep Malviya, E. P. Ramakrishnan, Vivek Gavane,
Avinash Bayaskar, Rashmi Mahajan and Sudhir Pandey
Abstract In this current age of data-driven science, perceptive research is being
carried out in the areas of genomics, network and metabolic biology, human,
animal, organ and tissue models of drug toxicity, witnessing or capturing key
biological events or interactions for drug discovery. Drug designing and repurposing involves understanding of ligand orientations for proper binding to the target
molecules. The crucial requirement of finding right pose of small molecule in
ligand–protein complex is done using drug docking and simulation methods. The
domains of biology like genomics, biomolecular structure dynamics, and drug
discovery are capable of generating vast molecular data in range of terabytes to
petabytes. The analysis and visualization of this data pose a great challenge to the
researchers and needs to be addressed in an accelerated and efficient way. So there
is continuous need to have advanced analytics platform and algorithms which can
perform analysis of this data in a faster way. Big data technologies may help to
provide solutions for these problems of molecular docking and simulations.
Keywords Drug discovery Á Drug repurposing Á Hadoop Á Big data
Molecular dynamics simulations
Abbreviation
PCA
Principal component analysis
RMSD Root-mean-square deviation
RMSF Root-mean-square fluctuation
MR
MapReduce
R. R. Joshi (&) Á U. Sonavane Á V. Jani Á A. Saxena Á S. Koulgi
M. Uppuladinne Á N. Sharma Á S. Malviya Á E. P. Ramakrishnan
V. Gavane Á A. Bayaskar Á R. Mahajan Á S. Pandey
High Performance Computing-Medical & Bioinformatics Applications Group,
Centre for Development of Advanced Computing (C-DAC),
Savitribai Phule Pune University Campus, Pune 411007, India
e-mail: rajendra@cdac.in
© Springer Nature Switzerland AG 2019
C. G. Mohan (ed.), Structural Bioinformatics: Applications in Preclinical Drug
Discovery Process, Challenges and Advances in Computational Chemistry
and Physics 27, https://doi.org/10.1007/978-3-030-05282-9_11
347
of Big Data and HPC in Drug Discovery
Rajendra R. Joshi, Uddhavesh Sonavane, Vinod Jani, Amit Saxena,
Shruti Koulgi, Mallikarjunachari Uppuladinne, Neeru Sharma,
Sandeep Malviya, E. P. Ramakrishnan, Vivek Gavane,
Avinash Bayaskar, Rashmi Mahajan and Sudhir Pandey
Abstract In this current age of data-driven science, perceptive research is being
carried out in the areas of genomics, network and metabolic biology, human,
animal, organ and tissue models of drug toxicity, witnessing or capturing key
biological events or interactions for drug discovery. Drug designing and repurposing involves understanding of ligand orientations for proper binding to the target
molecules. The crucial requirement of finding right pose of small molecule in
ligand–protein complex is done using drug docking and simulation methods. The
domains of biology like genomics, biomolecular structure dynamics, and drug
discovery are capable of generating vast molecular data in range of terabytes to
petabytes. The analysis and visualization of this data pose a great challenge to the
researchers and needs to be addressed in an accelerated and efficient way. So there
is continuous need to have advanced analytics platform and algorithms which can
perform analysis of this data in a faster way. Big data technologies may help to
provide solutions for these problems of molecular docking and simulations.
Keywords Drug discovery Á Drug repurposing Á Hadoop Á Big data
Molecular dynamics simulations
Abbreviation
PCA
Principal component analysis
RMSD Root-mean-square deviation
RMSF Root-mean-square fluctuation
MR
MapReduce
R. R. Joshi (&) Á U. Sonavane Á V. Jani Á A. Saxena Á S. Koulgi
M. Uppuladinne Á N. Sharma Á S. Malviya Á E. P. Ramakrishnan
V. Gavane Á A. Bayaskar Á R. Mahajan Á S. Pandey
High Performance Computing-Medical & Bioinformatics Applications Group,
Centre for Development of Advanced Computing (C-DAC),
Savitribai Phule Pune University Campus, Pune 411007, India
e-mail: rajendra@cdac.in
© Springer Nature Switzerland AG 2019
C. G. Mohan (ed.), Structural Bioinformatics: Applications in Preclinical Drug
Discovery Process, Challenges and Advances in Computational Chemistry
and Physics 27, https://doi.org/10.1007/978-3-030-05282-9_11
347