Editorial [Hot Topic: Computational Applications in Medicinal Chemistry Executive (Editor: Stefano Moro)]

The very foundations of drug discovery research are being rapidly transformed by high throughput systems, automated assays, robotics and advanced computational applications in medicinal chemistry. Costs are dropping, the time to complete a cycle of discovery and compound characterization is lessening, and all the while the ability to assess a compound's possible therapeutic role is improving. Indeed, the drive to increase the speed and efficiency of drug discovery, from hit identification all the way through to the creation of development candidates has seen huge investments by major pharmaceutical companies in many new technologies, with the primary aim of synthesizing more compounds and screening them faster; all at reduced cost per compound or assay. Nowadays, computational medicinal chemistry brings together the most powerful concepts in modern chemistry, biology and pharmacology, linking medicinal chemistry with genomics and proteomics. However, following our experience, both ligand-based and structure-based approaches to drug discovery in the absence, but probably also in the presence, of the real 3D-structures require a multidisciplinary approach, where molecular models represent a structural context to efficiently integrate experimental data and inferences derived from molecular biological, biophysical, bioinformatic, pharmacological and organic chemical methods. Although not always achievable, the success of a synergistic effect among these disciplines is highly dependent on the experimental design. Synergy is best achieved when mutations are structurally interpretable, structural hypotheses are experimentally testable, ligands are well characterized pharmacologically, and the necessary chemical modifications of the ligands are feasible. The present edition opens with the interesting report by Silvio Tosatto and Stefano Toppo [1] on the large scale prediction of protein structure and function from primary sequence obtained by the state of art chemioinformatics methodologies. This is an instance of a likely future contribution of bioinformatics research towards an improvement in the druggable target structure and function prediction. Giovanna Scapin [2] recalls the crucial role of macromolecular crystallography in structural determination and structural-based drug design (SBDD) approach. This process has been aided by recent technological innovations such as high-throughput crystallization, high performance synchrotron beamlines, and new methods in structural bioinformatics and computational chemistry prompted by the structural genomics effort. Alfonso Pozzan [3] updates the role of molecular descriptors and methods for ligand based virtual high throughput screening in drug discovery. Christoph Steinbeck, Christian Hoppe, Stefan Kuhn, Matteo Floris, Rajarshi Guha and Egon L. Willighagen [4] deal with the potentiality of Java applications in molecular informatics. The Authors outline the perspective to develop chemoinformatics tools, such as Chemistry Development Kit (CDK), with the aim to speed up the drug discovery process. Nohad Gresh [5] reports about the development, validation, and applications of anisotropic polarizable molecular mechanics to study ligand and drug-receptor interactions. In fact, considering molecular docking one of the most useful application in structural-based drug design (SBDD) approach, a correct representation of intermolecular interaction energies is necessary for reliable drug-receptor docking studies. Gabriele Costantino [6] introduces the role of in silico approaches towards the understanding of the structurefunction relationships in metabotropic glutamate receptors (mGluRs) and other family C GPRCs. The present review will discuss the evolution of our perception in family C GPCRs structure and function as emerged from the critical comparison of in silico methods with molecular biology and crystallographic experiments Francesca Deflorian, Magdalena Bacilieri, Giampiero Spalluto and myself [7], address the concept of receptor multi-conformational state applied to G-protein coupled receptors (GPCRs). Particularly, we define ligand-based homology modeling as new approach to simulate the reorganization of the receptor induced by the ligand binding. Finally, we discuss its possible application in new GPCR ligand discovery. 2066 Current Pharmaceutical Design, 2006, Vol. 12, No. 17 Computational Applications in Medicinal Chemistry References [1] Tosatto SCE, Toppo S. Large-Scale Prediction of Protein Structure and Function from Sequence. Curr Pharm Design 2006; 12(17): 2067-2086. [2] Scapin G. Structural Biology and Drug Discovery. Curr Pharm Design 2006; 12(17): 2087-2097. [3] Pozzan A. Molecular Descriptors and Methods for Ligand Based Virtual High Throughput Screening in Drug Discovery. Curr Pharm Design 2006; 12(17): 2099-2110......