Postgraduate Course: In Silico Drug Discovery (PGBI11079)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | **Online Distance Learning Course**
A major contributor of new leads to the drug discovery process is the large scale, normally database driven, calculation based on modelling ligand/macromolecular interactions or searches based on properties derived from pre-existing chemical entities. In this course these database mining techniques, along with allied chemical fragment based approaches will be explored. |
| Course description |
Not entered
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2014/15, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 1 |
| Course Start Date |
29/09/2014 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Online Activities 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
50 % group assessment (including maximum 20% variation for Peer Assessment of contribution)
50 % electronic portfolio comprising learning log and contribution to Skills Profile
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| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
At the end of this course students should be able to:
¿ Describe the major aspects of a virtual screening application, including the methods for initial site point generation, and the various approaches to pose fitting.
¿ Distinguish between force field/enthalpy based and knowledge based pose scoring methods.
¿ Understand the properties that increase the value of compound databases.
¿ Have a clear understanding of the values and problems associated with multiconformer vs single conformer chemical databases.
¿ Describe the major classes of similarity searching algorithms, and understand the types of problem that such programs can be applied to.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | InSilico |
Contacts
| Course organiser | Dr Douglas Houston
Tel: (0131 6)50 7358
Email: DouglasR.Houston@ed.ac.uk |
Course secretary | Miss Vicky Mactaggart
Tel: (0131 6)51 7052
Email: Vicky.Mactaggart@ed.ac.uk |
|
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