Postgraduate Course: Computer-Aided Drug Design (CHEM11048)
Course Outline
| School | School of Chemistry |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | An online distance-learning course covering key areas of computational chemistry methods as applied to the modelling of biological processes and to rational drug design, building on students' knowledge of theoretical chemistry. The course comprises lecture courses and interactive sessions on: cheminformatics, biophysics and protein-ligand interactions, medicinal chemistry, molecular simulations and case studies highlighting recent successes. |
| Course description |
Not entered
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | At least a 2:1 BSc (Hons) degree or equivalent in chemistry, physics, or other cognate discipline. Formal enrolment only for PG students on the distance learning PG Cert programme. Not available as formal credit-bearing courses to Tier 4 visa students or to other visiting students. |
| Additional Costs | Students must have regular and reliable access to the internet. |
Course Delivery Information
|
| Academic year 2014/15, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Please contact the School directly for a breakdown of Learning and Teaching Activities |
| Assessment (Further Info) |
Written Exam
25 %,
Coursework
75 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
The course is assessed on the basis of coursework and an 'open-book' online exam. Written Exam 25 %, Coursework 75 %. |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
At the end of this course students will be able to:
- describe the drug development pipeline and understand where computational chemistry fits in
- discuss informatics approaches to the prediction of chemical properties
- understand the importance of drug-like properties and their prediction
- describe the use of lead candidates and database representations
- understand the use of classifier algorithms and quantum/classical descriptors
- describe relations between thermodynamic properties and protein-ligand binding and structure
- describe protein-ligand docking and the empirical/knowledge-based scoring functions employed
- discuss empirical scoring, de-novo design and virtual screening
- describe simulations of ligand binding thermodynamics
- appreciate protein sequence searches, homology and loop modelling, protein-protein docking, and describe biologics design
- describe the relation between IC50 and Kd, and discuss biophysical methods used
- know how to use software such as KNIME, CDK, AutoDock and Sire.
Learning outcomes specific to attainment of a pass at Level 11 include:
- ability to integrate all, or most, of the main areas of the course
- development of original and creative responses to problems and issues within the course
- application of critical analysis, evaluation and synthesis to issues at the forefront of the subject area.
|
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Carole Morrison
Tel: (0131 6)50 4725
Email: Carole.Morrison@ed.ac.uk |
Course secretary | Dr David Michael Rogers
Tel: (0131 6)50 7748
Email: David.Rogers@ed.ac.uk |
|
© Copyright 2014 The University of Edinburgh - 12 January 2015 3:37 am
|
University Homepage