• Computer Aided Drug Design
    • School of Life Sciences & Biotechnology
    • Credit. 2
    • BI436
    • Enroll
    • Fall , 2015
    • 4020
    • Course Description:
    • ( Exchange Programme )
    • This is a course for senior undergraduate students to apply bioinformatics in rational drug design. Computer aided drug design uses pharmacophore models quantum mechanics, molecular dynamics, the quantitative structure-activity relationship (QSAR), etc, on enzyme or receptor, so as to achieve the purpose of drug design. With the human genome project completed, the rapid development of proteomics, and a large number of genes associated with human disease found, target macromolecules of drugs was predicted to be grow rapidly; at the same time, with rapid advances of the computer technology, computer aided drug design has made progress greatly in recent years. It is necessary for students to understand and master the basic skills, the latest development and application examples.
      This course has lectures on theory of molecular simulations, QSAR, and various models of the three-dimensional structures of the drugs, as well as structure based design methods, virtual high throughput screening, so as to introduce the ideas and methods of computer aided drug design methods to the students. We emphasize on heuristic teaching and quality education in this course. Computer aided drug design (CADD) is an interdisciplinary science with rapid updates of new knowledge and new methods. Therefore, we focus on introduction of the process of new drug discovery and the growth of new rules and new technologies. Although some of them are still controversial, they can help students gradually develop independent thinking and creativity. We emphasize on the emerging new methods and technologies like combinatorial chemistry and high throughput screening, so as to show the frontier of this field to the students, inspire their thinking, and improve their understanding on this course. In addition, multimedia teaching and project practice could improve students' practical ability of researches.
    • Course Syllabus:
    • After completing the course, students should:
      1. understand and master the basic concepts of protein structure prediction, molecular docking, molecular dynamics simulations, pharmocophore, QSAR, de novo drug design and other techniques of structure based rational drug design;
      2. get familiar with paper reading and searching and learn about the new developments in computer-aided drug design;
      3. apply the knowledge in practical research, finish a project independently or in teams after class
    • Schedule:
    • Topics / Credit hours / Teaching methodology / Tasks / Intended learning outcomes / Assessment methods

      1.Introduction of CADD/4 Credit hours/Lectures/NA/Understand related concepts/ NA
      2.Sequence analysis/2 Credit hours/Lectures/NA/Understand related concepts/NA
      3.Protein structure prediction/4 Credit hours/Lectures and labs/NA/Familiar with popular softwares/NA
      4.Structural databases of proteins/2 Credit hours/Lectures/homework/Familiar with popular databases/One page report
      5.Molecular dynamics simulations/4 Credit hours/Lectures/NA/Understand related concepts/ NA
      6.New developments in CADD/2 Credit hours/In class discussion/After class paper reading/Learn new developments in CADD/Presentations and one page report
      7.Molecular docking/4 Credit hours/Lectures/NA/Understand related concepts/NA
      8.QSAR/2 Credit hours/Lectures/NA/Understand related concepts/NA
      9.Pharmacophore/2 Credit hours/Lectures/NA/Understand related concepts/NA
      10.Structural based drug design/4 Credit hours/Lectures and labs/NA/Understand related concepts/NA
      11.Applications of CADD in Bioresearch/2 Credit hours/In class discussion/After class project/Practically use CADD to solve a specific question /Presentations and more than 10 pages report
  • Reading list
  • Other Materials
  • Discussion
  • Homework download/submit
    • Wei Dongqing
    • Read more
    • Male
    • E-mail:
    • dqwei@sjtu.edu.cn
    • Profile
    • Xu Qin
    • Professor
    • Read more
    • Male
    • E-mail:
    • xuqin523@sjtu.edu.cn
    • Profile
    • Research interests:
      1.Study microscopic details in structures or mechanisms of biological macromolecules like enzymes and membrane proteins, using computational simulations, especially molecular dynamics simulations.
      2.Improve computer-aided drug design and innovations based on structures and interactions between drugs and targets, especially focused on drugs/drug combinations, multi-target receptors, and databases of natural products/drug-like compounds/leads, using bioinformatics and biostatistics.
  • Prerequisite Course:

    Biochemistry or molecular biology

  • Textbooks:

    1. Textbook of Drug Design and Discovery,Third Edition,edited by Povl Krogsgaard-Larsen, Tommy Liljefors, Ulf Madsen,published by Taylor & Francis,2002
    2. Computational Medicinal Chemistry for Drug Discovery, edited by Patrick Bultinck, Jan P Tollenaere, Hans de Winter, Wilfried Langenaeker,published by Marcel Dekker, 2003
    3. Molecular Modelling for Beginners,by Alan Hinchliffe,published by John
  • Grading:

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