Dr. Rajni Garg
Dr. Rajni Garg
Research Associate Professor

Office: Science Hall 2-117
Phone: (760) 750-8069
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Rajni Garg received B.Sc. and M.Sc. (Organic Chemistry) degrees from Meerut  University, Meerut (India), in 1982 and 1984. She also received the M.Phil. (Chemistry) degree from the University of Delhi, Delhi (India) in 1988. She then received Ph.D. (Chemistry) degree from the Birla Institute of Technology and Science, Pilani (India) in 1996. She also served in the Chemistry department of the Birla Institute of Technology and Science, Pilani (India) as a Lecturer from January 1991 to July 1996.

From February 1997 to July 2002, she was a Postdoctoral Researcher in Chemistry Department at Pomona College, Claremont, CA.  From August  2002, she has been a research faculty with the Chemistry department at Clarkson University, Potsdam, NY. Since August 2006, she has been an research Associate Professor in the Chemistry & Biochemistry department at California State University San Marcos, CA. She is also an adjunct faculty in computational Science Research Center at San Diego State University, San Diego, CA.


  • Ph.D., Chemistry, 1996
    Birla Institute of Technology and Science, Pilani, India
    Thesis: Quantitative structure-activity relationship (QSAR) of anti-HIV-1 reverse transcriptase inhibitors.
  • M.Phil., Chemistry,1988
    University of Delhi, Delhi, India
    Dissertation: Synthesis and conformational studies on lysine oligopeptides.
  • B.Ed. (Bachelor of Education), 1986
    Meerut University, Meerut, India
  • M.Sc., Organic Chemistry, 1984
    Meerut University, Meerut, India
  • B.Sc., Chemistry, 1982
    Meerut University, Meerut, India

HONORS AND AWARDS:

  • ACS Cycle of Excellence Award for most accessed article (Chem. Rev. 104: 3751-3793, 2004), 2005
  • Invited member of QSAR expert panel for estrogen and androgen receptor, European Commission, Ispra, Italy 2004
  • Nominated for Hansch Award of QSAR and Modeling Society, 2001-2003
  • S R Palit Award of Indian Chemical Society, 1995
  • 3rd Rank in M.Phil., University of Delhi, India. 1988
  • 3rd Rank in B.Ed., Meerut University, India. 1984
  • National Merit Scholarship of Government of India, 1978-1984

My current research interests are in the area of computational chemistry and computer-assisted drug design, cheminformatics, bioinformatics, QSARomics and environmental toxicity as discussed below:                                                                                               

Computational chemistry and Computer-Assisted Drug Design:

Identification of potential drug molecules (i.e., lead discovery and optimization) accounts for about one-third of the drug development cost, besides the considerable amount of time. Computer-assisted drug design (CADD) techniques play a major role in the lead discovery and optimization as it significantly reduces the time and cost. Pharmaceutical companies are, therefore, investing resources in these techniques. QSAR (Quantitative Structure-Activity Relationship) analyses and receptor-ligand docking models are widely used CADD techniques. QSAR models have been applied to analyze/elucidate relationships between structure and activity of biologically active compounds.

In my research, we are studying HIV-protease inhibitors. Protease is one of the key viral enzymes needed for HIV reproduction.  Many drugs have successfully been developed to inhibit this enzyme.  However, the virus' fast reproduction cycle and tendency to mutate necessitates a constant development of new drugs.  We are developing linear and nonlinear QSAR models using statistical and machine learning techniques. The potential molecules identified using these models are further studied by using receptor-ligand docking. This research provides mechanistic insight about how a potential molecule (ligand) interacts with the receptor (protein). It also provides clues for further developing the candidate drug molecules for improved biological activity and pharmacokinetic profile. Using QSAR and receptor-ligand docking, we are also investigating estrogen receptor ligands that cause breast cancer.

Cheminformatics and Bioinformatics:

Cheminformatics and bioinformatics involve data mining, molecular modeling (docking), QSAR, pharmacophore mapping, structure/substructure searching etc. for predicting biological activity and other properties from chemical structure. Lately, many machine learning and engineering approaches such as artificial neural network (ANN), support vector machine (SVM), genetic algorithm (GA), principal component analysis (PCA), decision tree, data mining, pattern recognition, shape analysis and 3D graphics are also being increasingly applied for multi-modality data analysis in order to understand the drug-receptor interaction.

One of my projects is on development of quality assured (QA) databases for descriptor calculation, feature selection and model development. In another project, I am investigating development of new and traditional descriptors to create improved QSAR models that characterize and predict important biological responses. I am looking into topological, geometrical and chiral descriptors (with Dr. Basak, U. Minnesota, Duluth); and 3D-graphics, wavelet and shape related descriptors (with Prof. Kuo, USC Los Angeles; and Prof. Kumar, SDSU, San Diego). Once the descriptors have been determined and a predictive model has been built, thousands of new potential molecules, chemically similar to those of the benchmark data set, can be scanned from large databases and evaluated for their chemical properties based on the predictive model. The aim is to find a few novel molecules with potentially attractive pharmaceutical properties that can then be synthesized & tested further in the laboratory.

Combinatorial QSARomics:

I have recently initiated a project in which we are studying fusion/hybridization of machine learning techniques (i.e., GA and PCA for classification and feature selection followed by ANN or SVM techniques for pattern recognition), in combination with statistical regression analysis. We are developing robust computational models for rapid and reliable prediction of biological activity of HIV protease inhibitors. Comparative analysis of QSAR models developed using ANN/SVM with MLR/PLS analyses will bring out the similarities and differences in these models and provide lead for development of new drugs active against emerging mutant virus. The long-term objective of this research is to develop novel computational models as virtual screening tools for data mining of drug molecules from large databases.

Environmental Toxicity:

Computer-assisted procedures are effective in prescreening and prioritizing large numbers of compounds and in predicting their biological activity/toxicity rapidly and inexpensively. US EPA is very interested in developing quality assured (QA) databases for predicting the toxicity of endocrine disruptive agents (EDA). Both synthetic (pesticide, food anti-oxidants, polyphenols etc.) and natural (such as plant and mold metabolites) EDAs can interfere with the hormones in our system. One of my projects is on developing QA databases and predicting the activity/toxicity of these endocrine disruptive agents interacting with estrogen receptor (hormone in women responsible for breast cancer).  In this research, we plan to construct QA database of estrogen receptor ligands, calculate descriptor and develop models using various statistical and machine learning techniques.

Environmental toxicants in cigarette smoke are of great concern. Cigarette Mainstream Smoke (CMS) is a complex mixture and contains >500 polyaromatic hydrocarbons (PAH) which have been identified as carcinogenic by IARC. We have been collaborating with researchers at Lorillard Tobacco Company, Greensborough, NC, to develop molecular parameters and QSAR models for predicting carcinogenesis of these PAHs. In collaboration with Lorillard and USEPA health facility (UNC, Chapel Hill), we are also studying carbonyls in diesel exhaust. Many carbonyls are defined as irritants, mutagens and carcinogens. Several carbonyls are listed among the 188 hazardous air pollutants that the USEPA is required to control under the 1990 Clean Air Act.  Emitted from both mobile and non-mobile sources, diesel exhaust is a major contributor of carbonyls in the air. The goal of this project is to compute the molecular parameters and develop QSAR models to help in identifying toxicity of untested carbonyls.

My most recent project (with Prof. Partch, Clarkson Univ.) is on identification and development of ricin toxin inhibitors. Ricin is a potent cytotoxin easily isolated from the seeds of the castor plant. Its toxic dose for humans is in the microgram/kg, which ranks it among the most toxic substances known. This protein has been widely used in the design of therapeutic immunotoxins. Recently, governments and underground groups have used it as a poison. Thus, there is a great interest in identifying and designing effective inhibitor of the ricin A chain (RTA) protein. In our research we are calculating molecular parameters /descriptors of some potential RTA inhibitors. The molecules showing promising parameter values will be docked in the binding site of RTA to gain insight about the binding-interaction pattern. The outcome of this research can provide lead for further development of these molecules.

Book Chapter

R. Garg “Comparative QSAR and Cheminformatics” in Chemometrics and Chemoinformatics, Ed. B.K.Lavine, ACS symposium series 2004 (in press)  

Referred Journal Papers 

2006-2007

1.      R. Garg, P. Martin, B. Bhhatarai, R. D. Leverette, Prediction of Mutagenicity of α-β Unsaturated Aldehydes via QSAR,  Environ. Mole. Mutagen. (submitted)

2.      P. Martin, R. Garg, M. C. Madden and C. J. Smith, Toxicity-related molecular parameters calculated for aldehydes and ketones found in diesel exhaust and ambient air, Food Chem. Toxico. (in revision)

3.      C. J. Smith, T. A. Perfetti, R. Garg and C. Hansch, Utility of the mouse dermal promotion assay in comparing the tumorigenic potential of cigarette mainstream smoke, Food Chem. Toxico., 44: 1699-1706 (2006)

2005

4.      B. Bhhatarai and R. Garg, From SAR to comparative QSAR: role of hydrophobicity in the design of 4-hydroxy-5,6-dihydro pyranone HIV-1 protease inhibitors, Bioorg. Med. Chem. 13: 4078-4084 (2005).

5.      R. Garg and D. Patel, Hydrophobicity in the design of P2/P2′ tetrahydropyrimidinone HIV protease inhibitors, Bioorg. Med. Chem. Letters, 13: 3767-3770 (2005).

2004

6.      C. J. Smith, T. A. Perfetti, R. Garg. The mouse dermal promotion assay and cancer risk in cigarette smokers. Food Chem. Toxico,. 42: 9-15 (2004).

7.      R. Garg and B. Bhhatarai, A mechanistic study of 3-aminoindazole cyclic urea HIV-1 protease inhibitors using comparative QSAR, Bioorg. Med. Chem., 12: 5817-5831 (2004).

8.      D. Hadjipavlou-Litina,, R. Garg and C. Hansch, Comparative quantitative structure-activity relationship studies (QSAR) on non-benzodiazepines compounds binding to BZR, Chem. Rev., 104: 3751-3793 (2004).

9.      C. J. Smith, T. A. Perfetti, R. Garg, P. Martin, C. Hansch. Percutaneous penetration enhancers in cigarette mainstream smoke. Food Chem. Toxico. 42: 9-15 (2004).

2003

10. C.D. Selassie, R. Garg, S. Mekapati. A mechanism-based approach to the study of the toxicity of endocrine disruptive agents. Pure and Applied Chemistry, 75: 2363-2374(2003)

11. C. J. Smith, T. A. Perfetti, R. Garg, C. Hansch. IARC carcinogens reported in cigarette mainstream smoke and their calculated logP values. Food  Chem. Toxico 41: 807-817 (2003).

12. C. Hansch, A. Jazirehi, S. B. Mekapati, R. Garg, B. Bonavida. QSAR of apoptosis function in various cancer cells. Bioorg. Med. Chem. 10: 3015-3019 (2003).

13. R. Garg, A. Kurup, S. B. Mekapati, C. Hansch. Searching for allosteric effects via QSAR II. Bioorg.  Med. Chem. 11: 621-628 (2003)

14. R. Garg, A. Kurup, S. B. Mekapati, C. Hansch. Cyclooxygenase (COX) inhibitors: A comparative QSAR analyses. Chem. Rev. 103: 703-731 (2003).

15. C. Hansch, R. Garg, A. Kurup, S. B. Mekapati. Allosteric interactions and QSAR: On the role of ligand hydrophobicity. Bioorg. Med. Chem. 11: 2075-2084 (2003).

16. A. Kurup, S. B. Mekapati, R. Garg, C. Hansch. HIV-1 protease inhibitors: A comparative QSAR study. Current Med. Chem. 10: 1819-1828 (2003).

2002

17. C. J. Smith, T. A. Perfetti, M. J. Morton, A. Rodgman, R. Garg, C. D. Selassie, C. Hansch. The relative toxicity of substituted phenols reported in cigarette mainstream smoke. Tox. Sci. 69:265-278 (2002)

18. C. D. Selassie, R. Garg, S. Kapur, A. Kurup, R.P. Verma, S. B. Mekapati, C. Hansch. Comparative QSAR and the Radical Toxicity of Various Functional Groups. Chem. Rev. 102: 2585-2605 (2002).

2001

19. R. Garg, A. Kurup, C. Hansch. Possible allosteric effects in anticancer compounds. Bioorg. Med. Chem. 9: 3161-3164 (2001).

20. A. Kurup, R. Garg, D. J. Carini, C. Hansch. Comparative QSAR: Angiotensin II inhibitors. Chem. Rev. 101: 2727-2750 (2001).

21. A. Kurup, R. Garg, C. Hansch. Comparative QSAR study of tyrosine kinase inhibitors. Chem. Rev. 101: 2573-2600 (2001).

22. C. Hansch, R. Garg. Comparative QSAR and radical toxicology: the aromatic CH2OH moiety. Perkin Trans. 2: 476-479 (2001).

23. C. Hansch, A. Kurup, R. Garg, H. Gao. Chem-Bioinformatics and QSAR. A review of QSAR lacking positive hydrophobic terms. Chem. Rev. 101: 619-672 (2001).

24. C. Hansch, R. Garg, A. Kurup. Searching for allosteric effects via QSAR. Bioorg. Med. Chem. 9: 283-289 (2001).

25. R. Garg, A. Kurup, C. Hansch. Comparative QSAR. on the toxicology of the phenolic OH moiety. Crit. Rev. Toxico. 31(2): 223-245 (2001).

2000

26. 22. R. Garg, S. Kapur, C. Hansch. Radical toxicity of phenols. A reference point for obtaining perspective in the formulation of QSAR. Med. Res. Rev. 21: 73-82 (2000).

27. 23. R. Garg, W.A. Denny, C. Hansch. Comaparative QSAR studies on substituted bis-(acridines) and bis-(phenazines)-carboxamides: a new class of anticancer agents. Bioorg. Med. Chem. 8: 1835-1839(2000).

28. 24. A. Kurup, R. Garg, C. Hansch. Comparative QSAR analysis Of 5a-reductase inhibitors. Chem. Rev. 100: 909-924 (2000).

1999

29. 25. R. Garg, S.P. Gupta, H. Gao, M.S. Babu, A.K. Debnath, C. Hansch. Comparative quantitative structure-activity relationship studies on anti-HIV drugs. Chem. Rev. 99: 3525-3601 (1999).

30. 26. H. Gao, John A. Katzenellenbogen, R. Garg, C. Hansch. Comparative QSAR analysis of estrogen receptor ligands. Chem.Rev. 99: 723-745 (1999).

1996-1998

31. H. Gao, W.A. Denny, R. Garg, C. Hansch. Quantitative structure-activity relationship (QSAR) of anilinoacridines: a comparative analysis. Chem.- Bio. Interac.116: 157-180 (1998).

32. S.P. Gupta, M.S. Babu,. R. Garg, S. Sowmya. Quantitative structure-activity relationship studies on cyclic urea-based HIV-protease inhibitors. J. Enzyme Inh. 13: 399-407 (1998).

33. R. Garg, S.P. Gupta. Quantitative structure-activity relationship studies on some anti-human-immunodeficiency-virus-1 (anti-HIV-1) drugs: viral reverse transcriptase inhibitors. J. Enzyme Inh. 12: 1-12 (1997).

34. R. Garg, A. Kurup, S.P. Gupta. Quantitative structure-activity relationship studies on  some acyclouridine derivatives acting as anti-HIV-1 drugs. Quant. Struc.- Act. Relat. 16: 20-24 (1997).

35. S.P. Gupta, R. Garg. Quantitative structure-activity relationship studies on  some viral reverse transcriptase inhibitors acting as anti-HIV-1 agents. J. Enzyme Inh. 11:171-181 (1997).

36. S.P. Gupta, R. Garg. Quantitative structure-activity relationship studies on anti-HIV-1 TIBO derivatives as inhibitors of viral reverse transcriptase. J. Enzyme Inh. 11: 23-32 (1996).

Conference Papers

1.       B. Bhhatarai, S. Reddy Alla, R. Garg and S. Kumar. A novel cheminformatics study of non-peptidic HIV protease inhibitors using machine learning and statistical tools. 233rd American Chemical Society National Meeting, Chicago, March 25-29, 2007.

2.       R. C. Kasara, B. Bhhatarai and R. Garg. Pharmacokinetic modeling of anti-HIV protease ritonavir analogues. 233rd American Chemical Society National Meeting, Chicago, March 25-29, 2007.

3.      

4.       A. S. Reddy, R. Garg, S. Kumar, G. N. Sastry. Probing the energetic and structural role of non-covalent (cation-aromatic) interactions in HIB protease. 233rd American Chemical Society National Meeting, Chicago, March 25-29, 2007.

5.       C. Bernier, B. Bhhatarai, S. Kumar, and R. Garg, Feed-forward neural network models of potential sulfonamide-substituted cycloalkylpyranone HIV protease inhibitors, 232nd American Chemical Society National Meeting, San Francisco, CA, September 10-14, 2006.

6.       R. C. Kasara, B. Bhhatarai and R. Garg, QSAR Studies of anti-HIV ritonavir analogs, 232nd American Chemical Society National Meeting, San Francisco, CA, September 10-14, 2006.

7.       B. Bhhatarai and R. Garg, Multivariate analysis of pyranone based HIV protease inhibitors: cheminformatics approach. 232nd American Chemical Society National Meeting, San Francisco, CA, September 10-14, 2006.

8.       R. Garg and L. Streeter, Analysis of estradiolic ligand binding to the estrogen receptor using QSAR approach (Poster), QSAR 2006: 12th International workshop on Quantitative structure-activity relationships in environmental toxicology, Lyon, France, May 8-12, 2006.

9.       D. Patel, B. Bhhatarai and R. Garg, Computational analysis of HIV protease cyclic urea inhibitors (Poster), 7th Annual SURE Symposium, Clarkson University, April 12, 2006.

10.   L. Streeter and R. Garg, Analysis of estradiolic ligands of estrogen receptor, 7th Annual SURE Symposium, Clarkson University, April 12, 2006.

11.   C. Bernier, B. Bhhatarai, S. Kumar, and R. Garg, Probabilistic neural networks: predicting good HIV protease inhibitors, 231st American Chemical Society National Meeting, Atlanta, GA, March 26-April 1, 2006.

12.   B. Bhhatarai and R. Garg, No one size fits all - different pocket sizes for different mutants of HIV-PI: QSAR as a cheminformatics approach, 231st American Chemical Society National Meeting, Atlanta, GA, March 26-April 1, 2006.

13.   D. Patel, B. Bhhatarai and R. Garg, Investigation of HIV protease cyclic urea inhibitors using computational approach, 231st American Chemical Society National Meeting, Atlanta, GA, March 26-April 1, 2006.

14.   L. Streeter and R. Garg, Using QSAR Techniques: analysis of estradiolic ligand binding to the estrogen receptor (ER), 231st American Chemical Society National Meeting,Atlanta, GA, March 26-April 1, 2006.

15.   R. Garg and B. Bhhatarai., Digging the past for a clue: A novel in-silico approach for new leads on 4-hydroxy-pyran-2-ones HIV protease inhibitors, 230th American Chemical Society National Meeting, Washington, DC, Aug 26- 30, 2005.

16.   R. Garg and B. Bhhatarai, A New Series of dihydro-pyranone HIV-PI based on QSAR and molecular modeling studies, Gordon Research Conference on Computer-Aided Drug Design, Tiliton, NH, July 31-Aug 5, 2005.

17.   L. Streeter, B. Bhhatarai and R. Garg, Application of quantitative structure-activity relationship (QSAR) approach in drug design, 6th Annual Symposium of Undergraduate Research Experience (SURE), Clarkson University, April 8, 2005.

18.   D. Patel, B. Bhhatarai and R. Garg, Role of QSAR in the design of novel HIV protease inhibitors (Poster). 6th Annual SURE Symposium, Clarkson University, April 8, 2005.

19.   R. Garg and B. Bhhatarai, Comparative QSAR as a cheminformatics tool in the design of HIV-1 protease inhibitors (Poster), 229th American Chemical Society National Meeting, San Diego, CA, USA, March 13-March 17, 2005.

20.   B. Bhhatarai and R. Garg, Role of quantitative structure activity relationship (QSAR) in understanding HIV-1 binding domain and designing protease inhibitors (Poster), 229th American Chemical Society National Meeting, San Diego, CA, USA, March 13-March 17, 2005.

21.   P. Martin, R. Garg, M. C. Madden and C. J. Smith, Toxicity-related molecular parameters calculated for aldehydes and ketones found in diesel exhaust (Oral), 44th Annual Meeting of Society of Toxicology, New Orleans, Louisiana, March 6-10, 2005.

22.   P. Martin, C. J. Smith, R. Garg, G. A. Long, B. Bhhatarai and C. Hansch, Molecular parameters calculated for a series of polycyclic aromatic hydrocarbons (PAHs) (Oral), 58th Tobacco Science Research Conference, Winston-Salem NC, September19-22, 2004.

23.   B. Bhhatarai and R. Garg, Role of hydrophobicity in the design of 4-hydroxy-5,6-dihydropyrones HIV-1 protease inhibitors using comparative QSAR (CQSAR) (Poster), 15th European Symposium on Quantitative Structure-Activity Relationships & Molecular Modeling, Istanbul, Turkey. September 5-10, 2004.

24.   R. Garg and B. Bhhatarai, Comparative quantitative structure-activity relationship (QSAR) studies on cyclic urea HIV-1 protease inhibitors (poster), 11th International Workshop on Quantitative Structure-Activity Relationship (QSAR) in the Human Health and Environmental Sciences, Liverpool, UK. May 9-13, 2004.

25.   R. Garg,, Quantitative structure-activity relationship (QSAR) studies on cyclic urea 3-aminoindazole HIV-1 protease inhibitors (oral), 227th American Chemical Society National Meeting, Anaheim, CA, USA, March 27-April1, 2004.

26.   B. Thomas and R. Garg, QSAR studies of HIV integrase inhibitors(Oral), SURE Symposium, Clarkson University, July 31, 2003.

27.   R. Garg, Quantitative structure-activity relationship studies (QSAR) on cyclic urea HIV-1 protease inhibitors, Gordon Research Conference on Computer-Aided Drug Design, Tilton, NH, USA, July 20-25, 2003.

28.   C. J. Smith, T. A. Perfetti, R. Garg, P. Martin and C. Hansch., Percutaneous penetration enhancers in cigarette mainstream smoke, 57th Tobacco Science Research Conference, Norfolk, VA, September 22-27, 2003.

29.   C.D. Selassie and R. Garg, A mechanism-based approach to the study of the toxicity of endocrine disruptive agent (Invited Lecture), SCOPE/IUPAC Project on Endocrine Active Substances Workshop, Yokohama, November 17-21, 2002.

30.   C. J. Smith, T. A. Perfetti, M. J. Morton, A. Rodgman, R. Garg, C. D. Selassie and C. Hansch, The relative toxicity of substituted phenols reported in cigarette mainstream smoke CORSETA Congress, New Orleans, USA, September 22-27, 2002.

31.   R. Garg, A. Kurup and C. Hansch, Possible allosteric efects in anticancer compounds: A QSAR study (poster), 221st American Chemical Society National Meeting, San Diego, CA, USA, April 1-5, 2001.

32.   S. B. Mekapati, R. Garg, A. Kurup and C. Hansch, Comparative QSAR studies on topoisomerase-I inhibitors: Bi and Ter- Benzimidazoles (poster), 221st American Chemical Society National Meeting, San Diego, CA, USA, April 1-5, 2001.

33.   S. B. Mekapati, R. Garg, A. Kurup and C. Hansch, QSAR and the toxicology of aromatic nitro group (poster), 221st American Chemical Society National Meeting, San Diego, CA, USA, April 1-5, 2001.

34.   A. Kurup, R. Garg and C. Hansch, QSAR study on some tyrosine kinase inhibitors (poster), 221st American Chemical Society National Meeting, San Diego, CA, USA, April 1-5, 2001.

35.   R. Garg and C. Hansch, QSAR on anti-HIV drugs: A comparative study (poster), 219th American Chemical Society National Meeting, San Francisco, CA, USA, March 26-30, 2000.

36.   R. Garg and C. Hansch, Comparative QSAR studies on anti-HIV HEPT derivatives (poster), 217th American Chemical Society National Meeting, Anaheim, CA, USA, March 21-25, 1999.

37.   R. Garg and C. Hansch, Comparative QSAR studies on anti-HIV-1 nevirapine analogs (oral), 217th American Chemical Society National Meeting, Anaheim, CA, USA, March 21-25, 1999.

38.   R. Garg and S.P. Gupta, QSAR studies on some anti-AIDS drugs (oral), 84th Indian Science Congress, New Delhi, India, January 3-8, 1997.

39.   S. B. Mekapati, R. Garg and S.P. Gupta, QSAR studies on some anti-HIV-1 reverse transcriptase inhibitors (oral), 33rd Annual Convention of Chemists, Coimbatore, India, December 26-29, 1996.

40.   R. Garg and S.P. Gupta, A Quantitative structure-activity relationship studies on some inhibitors of HIV-1 reverse transcriptase inhibitors (oral), 65th Annual Session of National Academy of Sciences, Tirupati, India, November 3-5, 1995.

41.   R. Garg and S. P. Gupta, Quantitative structure-activity relationships study on some HIV-1 reverse transcriptase inhibitors (oral), 32nd Annual Convention of Chemists, Jaipur, India, December 2-4, 1995.


AFFILIATIONS:

  • Member of American Chemical Society (ACS)
  • Life Member of Indian Science Congress Association (ISCA)
  • Fellow of Indian Chemical Society (ICS)
  • Member International Society of Computational Biologist (ISCB)
  • Member American Association for the Advancement of Science (AAAS)
  • Member QSAR and Modeling Society


REVIEWER RESPONSIBILITY:

  • Reviewed research grant proposals for National Science Foundation
  • Reviewed book entitled "QSAR Study Guide" of Academic Press
  • Reviewer for Mini-Reviews in Medicinal Chemistry, and Current Medicinal Chemistry