Chem 130B Spring 2007

 

Syllabus

 

This course will examine case studies that provide real-life examples of various concepts discussed in Pharmaceutical Chemistry 1.

It will also provide hands-on experience with modern computational methods used in the drug design process.

Two class periods each week will be devoted to discussion of various aspects of the drug development process as it played out for that week's drug(s) of choice. The third class period each week will involve hands-on experience using modern computational software. Each week a different computational method will be described and then it will be applied using real-life drugs and related molecules.

 

Recommended Text:

Richard B. Silverman, The Organic Chemistry of Drug Design and Drug Action, 2nd Edition, Elsevier/Academic Press, 2004, ISBN 0-12-643732-7.

 

Expectations:

This class is not about memorization. It is about developing analytical thinking and problem-solving skills.

It will utilize and expand upon most everything covered in 130A!

 

Guest Speakers:

Dr. Susan Bernhard, Elan Pharmaceuticals
Dr. Sundeep Dugar, SAI Advantium
Dr. Todd Elworthy, Roche Biosciences
Prof. Bruce Hammock, UC Davis, Department of Entomology
Dr. Sung Hee Hwang, UC Davis, Department of Entomology
Prof. Mark Kurth, UC Davis, Department of Chemistry
Dr. Katerina Leftheris, Bristol-Myers-Squibb
Prof. Claude Meares, UC Davis, Department of Chemistry
Dr. Dave Smith, Roche Biosciences
Prof. Heike Wulff, UC Davis, Medical Pharmacology and Toxicology

 

Course Requirements:

mini lab reports

weekly questionnaires

drug design project

The first task is to find a family of drugs or drug candidates that have been described in the primary literature and are of interest to you. The “drug family” you choose must have either: (A) at least three drugs or drug candidates that interact with the same protein, or (B) at least three drugs or drug candidates that are similar in structure but that have different biological targets.

The second task is to design a new drug candidate and make predictions about its activity and other properties using the computational tools that you learned about earlier in the quarter.

In short, imagine you are a modeler working at a pharmaceutical company and a co-worker who is a medicinal chemist comes to you for advice because he is having a bad day—he’s out of ideas for new potential drug candidates to synthesize and test. His project involves the target of the “drug family” you’ve chosen and he is looking for a suggestion for a new drug candidate to synthesize and test. From what is known about your drug family, and what you can discover using the computational tools that have been available to you, you must propose a NEW drug candidate; the molecule you propose cannot be a known molecule—i.e. it must not have been described previously in the literature. You must turn in a final report in which you explain in detail why you think that your proposed drug candidate shows promise. Your argument must be supported by computational evidence that you obtain yourself. In your final report, you must clearly describe the computations that you used and the results you obtained. You should also describe your level of confidence in these results—i.e. which do you feel are most reliable and which are more tentative.

 
 

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