Research Signpost 37/661 (2), Fort P.O., Trivandrum-695 023, Kerala, India

New Perspectives in Medicinal Chemistry, 2009, Vol.1: 13-23 ISBN: 978-81-308-0321-0 Editor: Stefano Alcaro

2 Pharmacophore modeling: A continuously evolving tool for computational drug design

Andrea Tafi, Luca Bellucci, Simone Brogi, Fabiana Caporuscio and Stefania Olla Dipartimento Farmaco Chimico Tecnologico, Polo Scientifico Universitario San Miniato, Università degli Studi Di Siena, Via Aldo Moro 2, I-53100 Siena Italy

Abstract In the latest two or three years progressive applications of pharmacophore modeling continue to appear in literature. Pharmacophore based parallel screening, for instance, has been introduced in 2006. Moreover, in 2008, a survey discussing the prospective impact of virtual screening techniques in the discovery of bioactive natural products has been published. Finally, virtual screening techniques from the drug discovery field are beginning to be used for profiling the bioactivity of chemicals

Correspondence/Reprint request: Prof. Andrea Tafi, Dipartimento Farmaco Chimico Tecnologico, Polo Scientifico Universitario San Miniato, Università degli Studi Di Siena, Via Aldo Moro 2, I-53100 Siena Italy. E-mail: tafi@unisi.it

Andrea Tafi et al. 14

(especially those of potential environmental concern) with the aim of prioritizing compounds for further testing using more complex systems and reducing and ultimately replacing the use of animals in regulatory testing. Pharmacophore modeling might be extremely helpful to allow full achievement of all the above mentioned goals. In this contribution we report a couple of case studies where pharmacophore generation and handling played a pivotal role. In particular, in the first example, the development of a novel computational pre-screening approach to be used as an in silico filtering tool for natural products is described, applied to the estrogen receptor-α subtype. In the second study, differently, the validation of a preexisting pharmacophore by the prediction of the antifungal activities of new azole compounds is discussed. In this case, it comes to light the importance and utility of adding excluded volumes to a pharmacophore, to increase its predictivity. Introduction Pharmacophore Modeling (PM) is a three-dimensional computational approach largely exploited in drug design, mainly to rationalize distributions of activities within groups of molecules exhibiting a similar pharmacological profile and supposed to be recognized by the same site of a target protein. According to the definition elaborated by an IUPAC working party leaded by Camille G. Wermuth: a pharmacophore is the ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger (or block) its biological response [1]. This “structure-based” definition, as a matter of fact, directly relates pharmacophores to the microscopic phenomenon of molecular recognition of bioactive compounds (potential drugs) by their biological targets and enlightens about the main utility of PM in drug design. In accordance with the early definition by Paul Ehrlich, however, pharmacophores have long been related only indirectly to drug-receptor interactions by means of changeable macroscopic measured activity descriptors (IC50, MIC, and so on). A pharmacophore, in fact, was firstly described as: a molecular framework that carries the essential features responsible for a drug’s biological activity, with no reference to any microscopic biological target [2]. Peter Gund [3] and more effectively Garland Marshall with its Active Analog Approach (AAA) [4], settled in the late seventies the basis of present computational three-dimensional “ligand-based” pharmacophore modeling, by developing computer programs that facilitated the process of determining putative pharmacophoric patterns in different congeneric series of a drug [5].