COMPUTER MODELLING IN CHEMISTRY - 2020/1

Module Overview

To provide introductory practical experience in modern computer graphics and modelling techniques for the chemical industry and research.

Module provider

Chemistry

Module Leader

HOWLIN Brendan (Chemistry)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

None

Module content

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.

• the use of MOE for visualising structures.

• introduction to the use of MOE databases

• designing QSAR equations using MOE

• practical exercise on Nicotinic inhibitors using MOE

• designing new drugs using QSAR

• Lipinski’s rule of Five

Assessment pattern

Alternative Assessment

No alternative

Assessment Strategy

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 1, 3)

Module aims

• 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.

Learning outcomes

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).

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: CHE2043

Other information

None

Programmes this module appears in

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 2020/1 academic year.