Postgraduate Course: Molecular Modelling and Database Mining (PGBI11023)
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 | This course will expose the student to the computational methods involved in structure-based drug design. The student will work on a small project and carry out the different steps with a high degree of independence. Supervision will be provided on an introductory basis as well as ad hoc. |
| Course description |
Principles of Molecular recognition
The protein-ligand universe, classification of protein structures, molecular descriptors, Lipinski's rules
Structural and Molecular Databases
Analysis of available structural data stored in the publicly available databases including PDB (protein database), CCDB (crystallographic database), ACD (available chemicals database)
Molecular Mechanics and Force Fields
Descriptions of theoretical molecular structures and energy terms describing bonded and non-bonded (inter)molecular interactions
Principles of template-based ligand design
Use of molecular graphics software to build novel 'drug leads'
Database Mining in 2D and 3D; Virtual Screening
Use of databases and software used to extract small molecules with required physical and chemical properties.
Use of 3D docking packages in lead discovery
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | A good working knowledge of chemical principles corresponding to at least one year of a University course is expected. Degrees in biochemistry, molecular biology, biophysics, and pharmacology will probably satisfy this requirement. Students with other backgrounds, for example in physics, computer science or informatics, should contact the Course Organiser. |
Course Delivery Information
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| Academic year 2021/22, Not available to visiting students (SS1)
|
Quota: 55 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 10,
Seminar/Tutorial Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
A two part exercise to assess the availability and quality of sequence and structural data available in a parasite/human metabolic pathway will be done to prepare for the essay (worth 25% of the course assessment).
Short project report/essay (3000 words) to be handed in at the end of Semester One. This is worth 75% of the course assessment.
|
| Feedback |
The exercise involving selection of protein targets for the main assessment, provides feedback on the correctness/appropriateness of student protein selections. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Describe the computational approaches in current use for protein modelling and structure-based drug design.
- Analyse and critically assess a macromolecular/ ligand interaction
- Analyse a protein databank structure and assess its quality and utility in molecular modelling.
- Apply molecular graphics tools to analyse molecular interactions
- Describe the use of molecular force field methods in the analysis of and creation of molecular models and understand the use and limitations of homology models.
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Reading List
There is no formal course book, but students may find Hoeltje,Sippl, Rogna and Folkers, Molecular Modelling, Basic Principles and Applications
ISBN 978-0-471-47878-2 useful. |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | MMDB |
Contacts
| Course organiser | Dr Paul Taylor
Tel: (0131 6)50 7058
Email: p.taylor@ed.ac.uk |
Course secretary | Mrs Claire Black
Tel: (0131 6)50 8637
Email: Claire.Black@ed.ac.uk |
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