Module Details

Module Code: BIOT8014
Title: Protein Informatics
Long Title: Protein Informatics
NFQ Level: Advanced
Valid From: Semester 1 - 2017/18 ( September 2017 )
Duration: 1 Semester
Credits: 5
Field of Study: 4218 - Biotechnology
Module Delivered in: 2 programme(s)
Module Description: The aim of this module is to acquire a detailed knowledge of the processes shaping protein structure, function and evolution and to apply this knowledge to the design and development of new and improved protein based therapeutics.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Appraise the mechanisms underlying protein structure, function, evolution and engineering for therapeutic purposes.
LO2 Evaluate the classification systems underlying the main protein structural databases (CATH, SCOP, FSSP/DALI & PDB).
LO3 Critically appraise pattern and profile methods to identify protein analogues of low sequence identity (PROSITE, PRINTS, PFAM).
LO4 Analyse the most common empirical approaches to protein structure resolution (X-ray crystallography & NMR).
LO5 Apply in silico comparative modelling to resolve protein 3D structure and evaluate the accuracy of the resulting models using Ramachandran plots.
LO6 Critically assess the impact of protein research on biomedicine and biotechnology.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Classification of Protein Structure
An insight into the classification systems underlying the main structural databases (CATH, SCOP, FSSP/DALI).
Protein Domains, Folds and Motifs
A detailed overview of conserved protein domains and their role in protein identification and classification.
Prediction of Protein Secondary Structure & Function
An overview of the principal methods for the prediction of protein structure and interpretation of the results in terms of protein function.
Comparative Modelling
3D protein structure prediction. Specifically, the use of fold recognition and target-template alignment to detect structural, functional and evolutionary relationships.
Ramachandram Plots
The use of Ramachandran plots to obtain and convey information about favourable energy geometries in predicted protein models.
Protein Evolution
An introduction to evolutionary relationships which exist between given proteins, taking into account comparisons in sequence, structure and function.
Protein Engineering
The use of site directed mutagenesis to engineer improved protein therapeutics.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Multiple Choice Questions % of Total Mark 60
Timing Sem End Learning Outcomes 1,2,3,4,5,6
Assessment Description
50 MCQ questions
Assessment Type Presentation % of Total Mark 40
Timing Every Week Learning Outcomes 1,2,3,4,5,6
Assessment Description
Detailed case studies on key topics covered in class
No End of Module Formal Examination
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Class based instruction Every Week 2.00 2
Lecturer-Supervised Learning (Contact) Contact Presentations Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Self directed learning Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
This module has no Part Time workload.
 
Module Resources
Recommended Book Resources
  • Janusz M. Bujnicki. (2009), Prediction of Protein Structures, Functions, and Interactions, [ISBN: 9780470517673].
  • J. Rigden, Daniel (Ed.). (2017), From Protein Structure to Function with Bioinformatics, 2. Springer Netherlands, p.503, [ISBN: 978-94-024-10].
This module does not have any article/paper resources
This module does not have any other resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_SHERB_8 Bachelor of Science (Honours) in Herbal Science 8 Mandatory
CR_SPHBI_8 Bachelor of Science (Honours) in Pharmaceutical Biotechnology 8 Mandatory