QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS IN COMPUTER AIDED MOLECULAR DESIGN

Authors

  • Hentabli Hamza Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Naomie Salim Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Faisal Saeed Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v78.9723

Keywords:

Computer aided molecular design, CAMD, Quantitative Structure Activity Relationship, QSAR, Drug design, Chemical dataset, molecular design, and Biological activity

Abstract

The drug development process requires the complete evaluation and identification of the chosen substance as well as its properties. It involves extensive chemical examination to achieve the best therapeutic effects which demands huge expenditure both in terms of time and money. Computer aided molecular design (CAMD) allows the production of new substances with pre-decided properties. Additionally, in order to illustrate and determine the interrelationship between the chemical structure of a compound and its biological activity, Quantitative Structure Activity Relationship (QSAR) is applied by employing a mathematical model and arranging molecular descriptors. This paper presents review of CAMD and QSAR techniques. The most common chemometric techniques are also emphasized. CAMD and QSAR are considered to be extremely efficient instruments in molecular design and accelerate the initial steps of drug development process. Furthermore, they enhance the effectiveness and reduce the cost of newly developed drugs.  

References

Martin, Y. C. 1978. Quantitative Drug Design: A Critical Introduction. Marcel Dekker: New York.

Sanz, F., Martín, M., Pérez, J., Turmo, J., Mitjana, A., Moreno, V., Dearden, J. C. (Eds.). 1983. Quantitative Approaches to Drug Design. Elsevier: Amsterdam,

Franke, R. (Ed.). 1984. Theoretical Drug Design Methods. Elsevier: Amsterdam.

Barakat, Khaled. 2014. Computer-Aided Drug Design. Journal of Pharmaceutical Care & Health Systems.

Werth, Barry. 2013. The Billion-dollar Molecule: The Quest for the Perfect Drug. Simon and Schuster,

Vaidya, Ankur, Sourabh Jain, Shweta Jain, Abhishek K. Jain, and Ram K. Agrawal. 2014. Quantitative Structure-Activity Relationships: A Novel Approach of Drug Design and Discovery. Journal of Pharmaceutical Sciences and Pharmacology. 1(3): 219-232.

Singh, Kunwar P., Shikha Gupta, and Premanjali Rai. 2013. Predicting Acute Aquatic Toxicity Of Structurally Diverse Chemicals In Fish Using Artificial Intelligence Approaches. Ecotoxicology And Environmental Safety. 95: 221-233.

Eriksson, L., Jaworska, J., Worth, A. P., Cronin, M. T. D., McDowell, R. M., Gramatica, P. 2003. Methods For Reliability And Uncertainty Assessment And Applicability Evaluations Of Classification Regression-Based And Qsars. Environ. Health Perspect. 111: 1361-1375.

Muster, Wolfgang, Alexander Breidenbach, Holger Fischer, Stephan Kirchner, Lutz Müller, and Axel Pähler. 2008. Computational Toxicology In Drug Development. Drug Discovery Today. 13(7): 303-310.

Winkler, David A., Enrico Mombelli, Antonio Pietroiusti, Lang Tran, Andrew Worth, Bengt Fadeel, and Maxine J. McCall. 2013. Applying Quantitative Structure–Activity Relationship Approaches To Nanotoxicology: Current Status And Future Potential. Toxicology. 313(1): 15-23.

Cronin, M. T. D. 2000. Computational Methods For The Prediction Of Drug Toxicity. Curr. Opinion in Drug Discovery and Development. 3: 292-297.

Muster, Wolfgang, Alexander Breidenbach, Holger Fischer, Stephan Kirchner, Lutz Müller, and Axel Pähler. 2008. Computational Toxicology In Drug Development. Drug Discovery Today. 13(7): 303-310.

Enoch, S. J., M. T. D. Cronin, Terry W. Schultz, and J. C. Madden. 2008. An Evaluation Of Global QSAR Models For The Prediction Of The Toxicity Of Phenols To Tetrahymena Pyriformis. Chemosphere. 71(7): 1225-1232.

Nantasenamat, C., Isarankura-Na-Ayudhya, C., Naenna, T., & Prachayasittikul, V. 2009. A Practical Overview Of Quantitative Structure-Activity Relationship. EXCLI J. 8(7).

Nantasenamat, C., Isarankura-Na-Ayudhya, C., & Prachayasittikul, V. 2010. Advances In Computational Methods To Predict The Biological Activity Of Compounds. Expert Opinion On Drug Discovery. 5(7): 633-654.

Chapman, N., ed. 2012. Advances In Linear Free Energy Relationships. Springer Science & Business Media.

Mannhold, R., Krogsgaard-Larsen, P., & Timmerman, H. 2008. QSAR: Hansch Analysis And Related Approaches (Vol. 1). H. Kubinyi (Ed.). John Wiley & Sons.

Cramer III, R. D., Paterson, D. E., Bunce, J. D. 1988. Comparative Molecular Field Analysis (Comfa). Effect Of Shape On Binding Of Steroids To Carrier Proteins. J. Am. Chem. Soc. 110: 5959-5967.

Kubinyi, H. (Ed.). 1993. 3D QSAR in Drug Design. Theory, Methods and Applications. Leiden: ESCOM.

Good, A. C., So, S. S., Richards, W. G. 1993. Structure-Activity Relationships From Molecular Similarity Matrices. J. Med. Chem. 36: 433-438

Good, A. C., Peterson, S. J., Richards, W. G. 1993. QSAR’s From Similarity Matrices. Technique Validation And Application In The Comparison Of Different Similarity Evaluation Methods. J. Med. Chem. 36: 2929-2937

Good, A. C., Richards, W. G. 1996. The Extension And Application Of Molecular Similarity To Drug Design. Drug Information Journal. 30: 371-388.

Vedani, A., McMasters, D. R., Dobler, M. 2000. Multi-Conformational Ligand Representation In 4D–QSAR: Reducing The Bias Associated With Ligand Alignment. Quant. Struct.-Act. Relat. 19: 149-161.

Vedani, A., Briem, H., Dobler, M., Dollinger, H., McMasters, D. R. 2000. Multiple Conformation And Protonation-State Representation In 4D–QSAR: The Neurokinin–1 Receptor System. J. Med.Chem. 43: 4416-4427.

Vedani, A., Dobler, M. 2002. Multidimensional QSAR: Moving From Three- To Five-Dimensional Concepts. Quant. Struct.-Act. Relat. 21: 382-390.

Vedani, A., Dobler, M. 2002. 5D-QSAR: The Key For Simulating Induced Fit? J. Med. Chem. 45: 2139-2149.

Downs, G. M. 2004. Molecular Descriptors. In Computational Medicinal Chemistry for Drug Discovery. Bultinck, P., De Winter, H., Langenaeker, W., Tollenaere, J. P. (Eds.). Marcel Dekker; New York. 515-538.

Devillers, J., Balaban, A. T. 1999. Topological Indices and Related Descriptors in QSAR and QSPR. Gordon Breach Scientific Publishers: Amsterdam. 811.

Verma, J., Khedkar, V. M., & Coutinho, E. C. 2010. 3D-QSAR In Drug Design-A Review. Current Topics In Medicinal Chemistry. 10(1): 95-115.

Karelson, M. 2000. Molecular Descriptors in QSAR/QSPR. Wiley-InterScience; New York,

Stuper, A. J., Jurs, P. C. ADAPT: A Computer System For Auto-Mated Data Analysis Using Pattern Recognition Techniques. J. Chem. Inf. Comput. Sci. 16: 197699-105.

Mekenyan, O., Bonchev, D. 1986. OASIS Method For Predicting Bio-Logical Activity Of Chemical Compounds. Acta Pharm. Jugosl. 36: 225-237.

Van de Waterbeemd, H., B. Testa, and B. Testa. 1987. Advances in Drug Research. Academic, New York. 16: 85-225.

Purcell, W. P. G. E. Bass, and J. M. Clayton. 1973. Strategy of Drug Design.

Todeschini, Roberto, and Viviana Consonni. 2009. Molecular Descriptors for Chemoinformatics. John Wiley & Sons. 41(2).

Todeschini, Roberto, and Viviana Consonni. 2008. Handbook Of Molecular Descriptors. Vol. 11. John Wiley & Sons.

Kier, Lemont. 2012. Molecular Orbital Theory In Drug Research. Vol. 10. Elsevier,

Balaban, Alexandru T., ed. 2006. From Chemical Topology To Three-Dimensional Geometry. Springer Science & Business Media.

Silipo, C. Vittoria, A. 1990. Three-Dimensional Structure of Drugs. In Comprehensive Medicinal Chemistry. Vol 4. Quantitive Drug Design. Hansch, C. Sammes, P. G., Taylor, J. B., eds. Pergamon Press, New York. 154-204.

Downloads

Published

2016-09-28

How to Cite

QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS IN COMPUTER AIDED MOLECULAR DESIGN. (2016). Jurnal Teknologi, 78(9-3). https://doi.org/10.11113/jt.v78.9723