DR. . YENAMANDRA S. PRABHAKAR
 
...
 Medicinal Chemistry Division
Central Drug Research Institute
Lucknow - 226 031, INDIA.
 
E- mail yenpra[at]yahoo dot com
Educational qualifications M.Sc. (A.U., Visakhapatnam), Ph.D. (B.I.T.S., Pilani).
Date of Birth

10-8-1959

 Dr. Y.S. Prabhakar’s specialization is application of QSAR and molecular modeling in drug research. He is actively involved in the antimalarial and anti-TB drug discover program of the institute. Dr. Prabhakar is also versatile in development of new chemometric tools and software. He developed a variable selection approach by name CP-MLR (Combinatorial Protocol in Multiple Linear Regression) and introduced new concepts in feature selection. He critically appraised the role of artificial neural networks in QSAR models. This has led to a thought provoking publication “Is Feature Selection Essential for ANN Modeling?” in as SCI journal. He also made some seminal contribution in the understanding of ‘disease’ in terms of Ayurvedic principles. He has passion for reading/ writing science and philosophy. He draws inspiration from adversity.
 
RESEARCH INTERESTS AND EXPERTISE
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Theoretical aspects of drug design and modeling of compounds of biological interest;
Physicochemical aspects of organic compounds;
Theoretical organic chemistry;
Software development for chemistry and drug research;
Informatics.
Ph.D. Students 2
 
SELECTED PUBLICATIONS
 
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 Consensus features of CP-MLR and GA in modeling HIV-1 RT inhibitory activity of 4- benzyl/benzoylpyridin-2-one analogues. S. Deshpandea, R. Singha, M. Goodarzi, S.B. Kattia and Y.S. Prabhakar J Enzyme Inhibition and Med Chem, 26(5), 696-705 (2011)
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 CoMFA and CoMSIA Analysis of Tetrahydroquinolines as Potential Antimalarial Agents. S. Deshpande, S. Jaiswal, S.B. Katti, Y.S. Prabhakar. SAR QSAR Environ. Res., 22(5-6) 473-488, (2011)
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 Chemometric descriptors in modeling the carbonic anhydrase inhibition activity of sulfonamide and sulfamate derivatives. B. K. Sharma, P. Pilania, K. Sarbhai, P. Singh and Y. S. Prabhakar. Molecular Diversity,14(2), 371-384 (2010)
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 Is Feature Selection Essential for ANN Modeling? M. Goodarzi, S. Deshpande, V. Murugesan, S.B. Katti and Y.S. Prabhakar. QSAR and Combinatorial Science, 28(11-12), 1487–1499(2009).
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 Chemical Structure Indices in In Silico Molecular Design, Y.S. Prabhakar and M.K. Gupta. Sci Pharm. 76, 101-132 (2008)
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 C-3 alkyl /arylalkyl-2,3-dideoxy hex-2-enopyranosides as antitubercular agents: synthesis, biological evaluation and QSAR study, M. Saquib, M.K. Gupta, Ram Sagar, Y.S. Prabhakar, A.K. Shaw, R. Kumar, P.R. Maulik, A.N. Gaikwad, S. Sinha, A.K. Srivastava, V. Chaturvedi, R. Srivastava and B.S. Srivastava, J. Med. Chem. 50(13),  2942 – 2950 (2007).
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 Topological Descriptors in Modeling the Antimalarial Activity of 4-(3’, 5’-Disubstitutedanilino)quinolines, M.K. Gupta and Y S. Prabhakar J. Chem. Inf. Modeling, 46(1), 93-102 (2006).
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 A Simple Algorithm for Unique Representation of Chemical Structures - Cyclic/ Acyclic Functionalized Achiral Molecules, Y.S. Prabhakar and K. Balasubramanian. J. Chem. Inf. Modeling, 46(1), 52-56 (2006).
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 CP-MLR Directed QSAR Studies on the Antimycobacterial Activity of Functionalised Alkenols - Topological Descriptors in Modeling the Activity MK. Gupta, R. Sagar, AK. Shaw and YS. Prabhakar , Bioorg. Med. Chem, 13, 343-351(2005)
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 A Combinatorial Protocol in Multiple Linear Regression to Model Gas Chromatographic Response Factor of Organophosphonate Esters, YS Prabhakar. Internet Electron. J. Mol. Des. 3, 150–162 (2004), http://www.biochempress.com
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 A Combinatorial Approach to the Variable Selection in Multiple Linear Regression: Analysis of Selwood et al Data Set - A Case Study. Y.S. Prabhakar. QSAR and Combinatorial Science, (2003), 22, 583-595.
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 Analysis of Tetrahedral Carbon in QSAR Studies. A Case Study Using HMGR Inhibitors. Y.S. Prabhakar. J. Chem. Inf. Comp. Sciences, 1999, 39, 650-653.
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A theoretical study of hydrophobic fragment and factor constants of Hansch and Leo: Estimation of a few non-available fragments and factors. Y.S. Prabhakar, Ind. J.Biochem. Biophys., 1996, 33, 72-75.

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 A model to quantify disease state based on the ayurvedic concept of tridosa. Y.S. Prabhakar and D.S. Kumar. Bull. Ind. Inst. Hist. Med., 1993, 23, 1-19.