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Bridging the dimensions: Seamless integration of 3D structure-based design and 2D structure-activity relationships to guide medicinal chemistry

Wednesday, 23 March 2016 16:46
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Matt Segall

Matt Segall gave this presentation at the ACS Spring National Meeting & Exposition held in San Diego, USA on 13th March 2016.

Abstract

The effective use of software can have a major impact on timelines and innovation in drug discovery. However, the traditional split between computational modellers and synthetic chemists has been blurred and software must be accessible across disciplines to quickly understand and predict structure-activity relationships (SAR). There has been a similar divide between tools for three-dimensional (3D) structure-based design and those for analysis of SAR based on a two-dimensional (2D) compound structure. Seamless integration between these approaches would enable all of the available structural knowledge to be used to guide the efficient design of high quality, active compounds.



In this talk we will illustrate how information from 2D models of key physicochemical and absorption, distribution, metabolism, elimination and toxicity (ADMET) properties can be superimposed on 3D views of protein-ligand complexes. The influence of each atom or functional group on these properties can be highlighted and combined with visualization of the atomistic contributions to binding affinity, enabling development of optimization strategies that balance potency with the ADMET properties required in a safe and efficacious drug.

Furthermore, 2D analyses, such as activity cliff detection and matched molecular pair analyses, are commonly used to explore compound data sets and quickly identify important SAR within a chemical series or library. We will demonstrate how a seamless, highly visual link between the results of these analyses and related 3D structural information helps to understand and rationalize this SAR. This enables the efficient design of compounds with improved target affinity in a truly multi-parameter optimization environment. .

You can download this presentation as a PDF.

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Last Updated on Friday, 08 April 2016 12:44  
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