Meet Inspiring Speakers and Experts at our 3000+ Global Conference Series Events with over 1000+ Conferences, 1000+ Symposiums
and 1000+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business.

Explore and learn more about Conference Series : World's leading Event Organizer

Back

Celerino Abad-Zapatero

University of Illinois at Chicago (UIC), USA

Title: Are SAR tables obsolete?

Biography

Biography: Celerino Abad-Zapatero

Abstract

The listing of the structures of compounds possessing biological activity (expressed as Ki, IC50 primarily) (structure-activity tables, SAR tables) for any drug discovery project is the core of any publication accross the medicinal chemistry scientific literature. It has been the standard way of reporting the progress of pharmaceutical discovery since the historical work of Erlich and coworkers in the early 1900'S. This summary was particularly important when the main variable driving drug discovery was potency. Nowadays, drug discovery teams have to examine a large number of variables simultaneously and pay a very close atention to the physicochemical properties (primarly size, polarity/hydrophobicity) of the chemical entities being pursued. Presenting and summarizing all this information in an effective manner is of the utmost importance. ‘Alternative variables combining the affinity of the ligands with relevant physico-chemical properties of the compounds have been introduced in various ways in the literature and are being cited in the literature, particularly as ligand efficiency indices. Controversy over the usage and utility of these variables to drive drug discovery is still prevalent in the community. The presentation will discuss certain formulations of ‘Ligand Efficiency Indices’ that permit the complete mapping of chemico-biological space (CBS) in efficiency planes (AltasCBS: https://www.ebi.ac.uk/chembl/ atlascbs/), which allows a direct two-dimensional representation of the information presented in the SAR tables in a graphic manner. The proposed representation permits an easy and effective understanding of the multiparameter optimization variables involved, and intuitvely suggest the most efficient strategies to optimize the drug-like properties of the compounds.