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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2014/2015
- ARCHIVE as at 1 September 2014

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DRPS : Course Catalogue : School of Biological Sciences : Postgraduate

Postgraduate Course: In Silico Drug Discovery (PGBI11079)

Course Outline
SchoolSchool of Biological Sciences CollegeCollege of Science and Engineering
Course typeStandard AvailabilityNot available to visiting students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaPostgraduate Other subject areaNone
Course website None Taught in Gaelic?No
Course description**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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Course Delivery Information
Delivery period: 2014/15 Semester 1, Not available to visiting students (SS1) Learn enabled:  No Quota:  None
Web Timetable Web Timetable
Course Start Date 29/09/2014
Breakdown of 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 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
No Exam Information
Summary of Intended 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.
Assessment Information
50 % group assessment (including maximum 20% variation for Peer Assessment of contribution)

50 % electronic portfolio comprising learning log and contribution to Skills Profile
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsInSilico
Contacts
Course organiserDr Douglas Houston
Tel: (0131 6)50 7358
Email: DouglasR.Houston@ed.ac.uk
Course secretaryMiss Vicky Mactaggart
Tel: (0131 6)51 7052
Email: Vicky.Mactaggart@ed.ac.uk
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© Copyright 2014 The University of Edinburgh - 29 August 2014 4:27 am