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M. von Itzstein, W. Y. Wu, G. B. Kok, M. S. Pegg, J. C. Dyason, B. Jin, T. V. Phan, M. L. Smythe, H. F. White, S. W. Oliver, P. M. Colman, J. N. Varghese, D. M. Ryan, J. M. Woods, R. C. Bethell, V. J. Hotham, J. M. Cameron and C. R. Penn, “Rational Design of Potent SialidaseBased Inhibitors of Influenza Virus Replication,” Nature, Vol. 363, No. 6428, 1993, pp. 418-423. doi:10.1038/363418a0

has been cited by the following article:

• TITLE: Computer-Aided Drug Design: An Innovative Tool for Modeling

  AUTHORS: Pranita P. Kore, Madhavi M. Mutha, Rishikesh V. Antre, Rajesh J. Oswal, Sandip S. Kshirsagar

  KEYWORDS: CADD; HTS; Software for General Purpose Molecular Modeling; SBDD

  JOURNAL NAME: Open Journal of Medicinal Chemistry, Vol.2 No.4, December 31, 2012

  ABSTRACT: Strategies for CADD vary depending on the extent of structural and other information available regarding the target (enzyme/receptor) and the ligands. Computer-aided drug design (CADD) is an exciting and diverse discipline where various aspects of applied and basic research merge and stimulate each other. In the early stage of a drug discovery process, researchers may be faced with little or no structure activity relationship (SAR) information. The process by which a new drug is brought to market stage is referred to by a number of names most commonly as the development chain or “pipeline” and consists of a number of distinct stages. To design a rational drug, we must firstly find out which proteins can be the drug targets in pathogenesis. In present review we reported a brief history of CADD, DNA as target, receptor theory, structure optimization, structure-based drug design, virtual high-throughput screening (vHTS), graph machines.