TOPICS IN COMPUTER MODELLING - 2022/3
Module code: CHE3053
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
To provide practical experience in modern computer graphics and modelling techniques for the chemical industry and research.
HOWLIN Brendan (Chemistry)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 6
JACs code: I450
Module cap (Maximum number of students): N/A
Overall student workload
Workshop Hours: 15
Independent Learning Hours: 100
Guided Learning: 20
Captured Content: 15
Prerequisites / Co-requisites
Indicative content includes:
Introduction to bioinformatics
Internet resources for bioinformatics
Examining protein structure
Using MOE for molecular modelling of proteins
Protein-ligand docking in pharmaceutical drug design
Examples of protein modelling using pharmaceutical examples e.g. GPCRs and plant proteins
Further analysis of protein structure using molecular dynamics
Point mutation and mutational analysis
Introduction to Chemometrics
Basic statistical concepts
Introduction to Multivariate Data Analysis
Principal Component Analysis
Multivariant Regression: MLR, PCR and PLS
Examples of applications to current research
Introduction to quantum chemical calculations: Schrödinger equation, Born-Oppenheimer approximation, Hartree-Fock method, DFT method
Wave functions, basis sets
Closed shell and open shell systems, self-consistent field
Optimisation techniques, gradients, Hessian matrix
Post-Hartree-Fock concepts: many-body perturbation theory, configuration interaction. QM/MM methods, density functional theory
Use of ab initio program package GAUSSIAN. Structure of input and output files
Interpretation of the results of ab initio calculations: geometries and energies
Interpretation of the results of ab initio calculations: molecular properties
Interpretation of the results of ab initio calculations: molecular orbitals
|Assessment type||Unit of assessment||Weighting|
|School-timetabled exam/test||PRACTICAL IN CLASS TEST (1 HOUR)||50|
|Examination Online||ONLINE OPEN BOOK EXAM||50|
The assessment strategy is designed to provide students with the opportunity to demonstrate
Practical skills in Molecular Modelling and knowledge of the underlying theory.
Thus, the summative assessment for this module consists of:
Practical in class test, 1 hour, 50% (meets learning outcomes 1,2,4)
Formal examination, 1.5 hours, 50% (meets learning outcomes 3 and 5)
A 'mock' practical exam will be held and the results discussed
Individual and in class feedback will be given on the in class mock test
- To discuss the theory and practice of modelling as applied to pharmaceuticals and proteins.
- To provide the background necessary for students to comprehend and criticise the results of simulation on the above systems.
- To give students the opportunity to carry out and comment on the results of a simulation
- To cover a range of selected topics in molecular orbital calculations appropriate to research.
- To cover a range of selected topics in chemometrics appropriate to research.
- To introduce students to advanced techniques of molecular modelling applied to both small molecules and proteins, and the use of a range of databases in these studies.
|001||Confidently carry out and comment on the results of a protein modelling simulation.||KCPT|
|002||Comprehend and analyse the results of simulation of a QSAR.||KC|
|003||Systematically understand the process of molecular modelling.||KCP|
|004||Have the ability to apply appropriate chemometric techniques to solve multivariate and complex data analysis and modelling problems.||KCP|
|005||Have a deep understanding of modern molecular orbital methods.||KCP|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
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 (30 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.
Upon accessing the reading list, please search for the module using the module code: CHE3053
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 2022/3 academic year.