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DRPS : Course Catalogue : School of Biological Sciences : Postgraduate

Postgraduate Course: Research Project in Next Generation Drug Discovery (PGBI11075)

Course Outline
SchoolSchool of Biological Sciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits60 ECTS Credits30
Summary**Online Distance Learning Course**

The MSc research project will be undertaken by students in their third year of the course. Utilizing group learning strategies the students will progress through all the initial stages of the standard pharmaceutical industry drug discovery pipeline.
Arranged into groups, the students will be provided with a list of possible drug targets for a range of related organisms, for example, the kinomes of all pathogenic protozoan parasites. Each student will choose their unique gene based on their research into its relevance to aspects of parasite survival, for example virulence or drug resistance, using techniques learned during the preceding two years of the course. This research will cover the initial two stages of the drug discovery pipeline, and allow each student to build their own Target Validation Dossier which will form part of their dissertation.
Once the search for a suitable target is complete, students will be required to commence the search for inhibitors of that target. A search for a crystal or NMR structure of the target will be undertaken, and if none is available the construction of a homology model will be required. In either case, a close analysis of the quality of the protein model will be expected using methodologies demonstrated during the Molecular Modeling and Protein Structure modules.
The next phase of the project will mimic the hit identification step of the drug discovery process. Utilizing our virtual screening software package CODASS the students will each perform their own high throughput compound screen in silico to discover possible inhibitors of their target enzyme.
Finally, a detailed analysis of the hits generated will be required, with considerations such as solubility, ligand efficiency and Lipinski rule conformation enabling each student to make conclusions about the suitability of each compound for progression to the lead identification phase of the process. Ultimately, compounds that meet all the prerequisites and appear sufficiently promising could potentially be acquired and tested using in vitro binding studies in the Centre for Translational and Chemical Biology, Edinburgh.
In summary, the project will give the students hands-on experience, in a virtual context, of all the early phases of an industrial drug discovery program. The collaborative nature of the work might also enable a ¿crowd-sourcing¿ strategy to collate a pool of data from which larger conclusions can be drawn, which may potentiate future publications in the data mining and chemoinformatics fields.
Course description Not entered
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2016/17, Not available to visiting students (SS1) Quota:  None
Course Start Full Year
Course Start Date 19/09/2016
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 600 ( Dissertation/Project Supervision Hours 20, Programme Level Learning and Teaching Hours 12, Directed Learning and Independent Learning Hours 568 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Research Project Dissertation = 70%
Pebblepad Webfolio = 30%
Feedback Not entered
No Exam Information
Learning Outcomes
Students are expected to achieve hands-on experience, in a virtual context, of all the early phases of an industrial drug discovery program.
Reading List
Additional Information
Graduate Attributes and Skills Not entered
Course organiserDr Douglas Houston
Tel: (0131 6)50 7358
Course secretaryMrs Claire Black
Tel: (0131 6)50 8637
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