COMPUTER MODELLING IN CHEMISTRY - 2023/4

Module Overview

his module is intended to further develop knowledge and practice of Molecular modelling (started in the MOE part of module CHE1040) and introduce the students to modern computational drug design as an opportunity to gain these skills on their own but also as a precursor to the CHE3053 module in the final year where more advanced aspects of these techniques will be developed. The module also serves to help students gain skills and experience that they may want to develop further in the final year project modules (CHE3047 and CHEM029)

Module provider

Chemistry and Chemical Engineering

Module Leader

HOWLIN Brendan (Chst Chm Eng)

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 (Molecular Operating Environment) and GAUSSIAN on PCs (persnal computers) 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 (Quantitative Strucutre Activity Relationships) 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 allow students to demonstrate: 

A personally guided investigation into 2 aspects of drug design which are currently a protein modelling exercise and a Quantitative Structure activity relationships exercise which cover both aspects of modern drug design (digital capabilities). Students work though the exercises week by week, building models and evaluating their success and the coursework aspect of the assessment requires the students to research the literature, calculate and evaluate results and present a scientific report that answers questions and presents scientifically supported conclusions (resourcefulness and reliability) 

Why are we doing this? 

The assessment strategy is designed to allow students to develop and test their knowledge and their skills in a manner that not only enhances their understanding of the topic, but also allows them to situate it within the wider context of the subject area, thereby contributing to the coherency of their learning journey. The assessments therefore contain valuable employability components and test a range of transferable skills.  

 

The assessment strategy also allows for assessment to take place in a supportive context through a hands-on workshop that is supported by the lecturer and the demonstrator and that can be applied to assessments in other modules. Such an approach contributes to the development of students as independent learners by empowering them to self-evaluate, and reflect on, their own performance in relation to others.  

 

Other elements of the assessment strategy allow students to test their performance in relation to ‘real-life’ scenarios and authentic documentation production, and to critically engage with the latest academic knowledge in relation to the subject area.  

All aspects of the assessment strategy allow students to receive feedback from expert staff. 

  Thus, the summative assessment for this module consists of: 

 

Coursework on protein modelling, (meets learning outcomes 1,2) 

Coursework on QSAR, (meets learning outcomes 1, 3) 

 

  Formative assessment 

 

Hands-on guidance to the coursework will be given.  

 

 Feedback 

 

Individual and in-class feedback will be given on the progress in modelling. 

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

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/organized separately to taught content and will be published on to student personal timetables, where they apply to taken modules as soon as they are finalized by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester. The learning and teaching strategy for this module is designed to: 

 

provide students with the opportunity to demonstrate practical skills in computer modelling by using modern graphics software in a computer laboratory to solve 2 real world problems in drug design with support from the academic and demonstrator, Students are encouraged to go beyond the brief and develop their own theories and ideas about drug design. Students with these skills are highly employable in the pharmaceutical industry 
 

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

The School of Chemistry and Chemical Engineering is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas: As the module concentrates on using computers it will enhance the Digital capabilities of students, the hands-on problem-solving approach will increase the Resourcefulness and resilience of students, both the use of computers and the ability to solve problems are particularly attractive to employers hence enhancing the Employability of students

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 2023/4 academic year.