Using Chemical Structure Databases in Drug Discovery CHEM5042
- Academic Session: 2022-23
- School: School of Chemistry
- Credits: 10
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: No
- Available to Erasmus Students: No
The drug discovery pipeline is now heavily dependent on the in silico screening of small molecule chemical library databases at a number of points along the route. This course will describe the biophysical and bioinformatics procedures used to identify lead and lead-like chemical compounds based upon their properties and interactions with protein target binding sites.
The course will run in one of the designated timetable blocks in Semester 2. Lecture/Seminar sessions of 1-3 hours duration several times per week; computer practical sessions of 1-3 hours several times per week.
Requirements of Entry
The course will be assessed entirely by coursework (100%). There will be three assessment components:
1. Report on a docking exercise, 750 words (30%) [ILOs 1,5]
2. Report on chemical database computing practical work, 1000 words (50%) [ILOs 2,3,4,5]
3. Set exercise demonstration of database construction and visualisation (20%) [ILOs 3,4,5]
This course aims to equip students with extensive, critical and integrative understanding of a portion of the drug discovery pipeline in which protein sequence and 3D structure data are integrated with small molecule chemical structures to inform drug design. The course will cover coding formats and organisational structure of chemical databases, interactions with such databases, identification of potential lead molecules for drug development, and the principles underlying manipulation of protein structures using docking algorithms to show molecular interactions. Students will have the chance to put many of these analysis concepts into practice during extensive computer lab practicals and will develop analytical skills, practical database construction and other computing skills and the ability to assess critically, and in the appropriate biological context, procedures for integrating structural data concerning proteins and small molecule ligands.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
1. Creatively apply and critically discuss the principles underlying prediction of protein/ligand interactions using molecular docking and other techniques, and the limitations of using modelling to predict protein structures and such interactions;
2. Critically evaluate and synthesise information about the key stages in the structure-aided drug discovery process.
3. Creatively apply and critically discuss the principles on which chemical databases are built, mechanisms for interacting with such databases, and approaches used when carrying out pharmacophore searches;
4. Use computers creatively to generate a virtual compound library in a database and query it for molecules with desired qualities;
5. Formulate rules for selection of protein ligands and design and implement a screening protocol to select candidate ligands from a library of chemical compounds, based on their likelihood of docking to a proposed target;
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.