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Next-Gen Kinase Inhibitors 


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Structure-based drug design took nearly two decades of multiple, parallel technological improvements to arrive at its current mainstream position in medicinal chemistry. Developments in computer graphics, high-power radiation sources, computational processing power, refinement protocols, virtual screening and crystallography were all necessary to create the environment for rapid, iterative structure-based drug discovery. Given the crisis facing the pharmaceutical industry in the translation of early stage drug discovery results, a different set of tools, concerned with algorithms and methods for developing best in class drugs that engage biological targets with kinetically optimized potency and selectivity will need to be refined. In this conference, we bring to focus recent advancements in this field from an experienced faculty:

Keynote Address:

Event Video

David Swinney 

Binding Kinetics in Drug Discovery

David Swinney, Ph.D., CEO, Institute for Rare and Neglected Diseases Drug Discovery (iRND3)

Dr. Swinney has devoted the majority of his career to the identification of effective mechanisms of drug action, promising leads and clinical candidates to address unmet medical needs. He has also developed an expertise in the understanding and application of binding kinetics to drug discovery. Dr. Swinney has a PhD in medicinal chemistry from the University of Washington, Seattle, over 20 years of industrial experience (Roche, Syntex) and is currently CEO and co-founder of the non-profit, Institute for Rare and Neglected Diseases Drug Discovery (iRND3, www.irnd3.org). 

Themed Sessions:

  • Structure to Function
  • Free Energy Calculation and Molecular Dynamics Simulation
  • GPCR
  • Fragment-Based Design
  • Druggability and Kinetics-Based Drug Design
  • Trends and Advances 

Dinner Short Courses:

June 6, 2012  (6:00pm - 8:00pm)

First Principles in Binding Kinetics:Towards Predicting Structure-Kinetics Relationships*

Instructors:

David Swinney, Ph.D., CEO, Institute for Rare and Neglected Diseases Drug Discovery (iRND3)

Xavier Barril, Ph.D., ICREA Research Professor, Physical Chemistry Department, University of Barcelona

This course will address the questions on “why should I care about kinetics?” and “how can I understand and predict Structure-Kinetics relationships?”  We will first review the role of binding kinetics in drug action and then focus on the particular case of protein-ligand non-covalent complexes, reviewing what is known so far about the structural determinants of binding kinetics. This course will help you with a better understanding and increased awareness of current state of the chemistry and pharmacology of binding kinetics.

 

June 7, 2012  (6:30pm - 8:30pm)

PubChem Mining - From Small Molecule to Structures and Bioactivity *

Instructor:

Jun (Luke) Huan, Ph.D., Associate Professor, Electrical Engineering and Computer Science Department, University of Kansas
 

A number of universities recently started drug discovery centers. Among the list include Duke, University of North Carolina, Emory, Vanderbilt, Broad Institute, John Hopkins and many others. NIH has maintained its intramural drug discovery programs for a number of years. Recently NIH has started ambitious extramural funding programs to support academic-based drug discovery programs (with an estimated funding of ~$600M). With these new initiatives, huge volumes of data have been collected in an open and collaborative environment  and such data are shared with the public free of charge.
 
In this short course, the presenter will review the knowledge discovery and management needs in the drug discovery process. One part of the talk will focus on an introduction to PubChem, a public repository for small molecule structures and bioactivity data, where several components facilitating data mining of biological assays test results, including data organization, search of chemicals and analysis for assay development will be covered. On the second part, latest computing and modeling methodology development, primarily those from data mining and machine learning will be overviewed.

The primary targeted audience of the tutorial is cheminformatics researchers and practitioners who are interested in developing or applying advanced computing techniques to support knowledge discovery in drug discovery and drug development programs. It may also help drug development and drug post-market safety monitoring. General knowledge of cheminformatics and statistics is assumed.

*Separate registration is required to attend a short course.

 

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