COMPUTER MODELLING OF DRUGS AND BIOMOLECULES - 2018/9
Module code: CHE2032
HOWLIN BJ Dr (Chemistry)
Number of Credits
FHEQ Level 5
Module cap (Maximum number of students)
Overall student workload
Independent Study Hours: 117
|Assessment type||Unit of assessment||Weighting|
N/A - Retake Coursework
Prerequisites / Co-requisites
To provide introductory practical experience in modern computer graphics and modelling techniques for the chemical industry and research.
To introduce students to the techniques of molecular modelling applied to both small molecules and proteins and the use of a range of databases in these studies.
To examine simple quantum mechanical calculations.
To gain practical experience in homology modelling of proteins.
To introduce the concepts behind chemoinformatics.
To describe the representation of structural and chemical data.
To introduce the use of 2-dimensional reduction, for specifying chemical structures.
To study the use of databases to store and retrieve structural and chemical data.
|1||Be familiar with the wide range of modelling techniques as a precursor to applying these to the Industrial Research Year and beyond||K|
|2||Have an in-depth appreciation of how to carry out practical projects requiring teamwork and initiative to use the most advanced methods to store and retrieve 3-dimensional data in a database and to display it in a variety of ways.||CPT|
|3||Critically understand the science behind how to reduce a 3-dimensional structure to a 2-D format.||KC|
|4||Have an in-depth understanding of how to carry out QSAR analysis on pharmaceutical compounds.||KPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Indicative content includes:
Introduction to molecular modelling and computational chemistry.
Simple theory of molecular mechanics and molecular orbital calculations. Energy expressions and minimisation techniques.
Small Molecule Modelling.
Practical applications using MOE and GAUSSIAN on PCs with GAUSSVIEW.
Conformations in molecules and conformational analysis.
Using GAUSSIAN to predict and animate IR and NMR spectra of simple molecules
Protein Modelling and Databases
Introduction to protein three-dimensional structure covering amino acids, codes for amino acids, sequence analysis, primary, secondary, tertiary and quaternary structure.
The Protein Database for protein X-ray structures and using the Web Browser.
Protein structure prediction, use of artificial intelligence (the EMBL Predict-Protein programme) and other internet resources.
The use of MOE for visualising structures.
Introduction to chemoinformatics, what it is, what it can do.
3D-2D reduction- the SMILES string
Introduction to the use of MOE databases
Designing QSAR equations using MOE
Practical exercise on Nicotinic inhibitors using MOE
Designing new drugs using QSAR
Does it exist? Validating results
Lipinski’s rule of Five
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
Give the student both practical and theoretical knowledge of modern molecular modelling
The learning and teaching methods include:
A hands on workshop approach will be taken to the computational modelling in the computing laboratory (33 hours).
The assessment strategy is designed to provide students with the opportunity to demonstrate
Practical skills in computer modelling
Thus, the summative assessment for this module consists of:
Coursework on protein modelling, 50% (meets learning outcomes 1,2)
Coursework on QSAR, 50% (meets learning outcomes 3 and 4)
Hands on guidance to the coursework will be given
Individual and in class feedback will be given on the progress in modelling
Programmes this module appears in
|Chemistry MChem||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Chemistry with Forensic Investigation MChem||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Chemistry BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Chemistry with Forensic Investigation BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2018/9 academic year.