Biomolecular structure and modeling

The course is available as a singular or elective course independent of study program, also to exchange students. The course is offered on condition that a minimum number of students register for the course.

This course offers a comprehensive exploration into the structural and computational principles governing biomolecules, with a focus on proteins and key classes of biological macromolecules. Students will gain an integrated understanding of how molecular structure dictates biological function and how computational modeling, structural biology techniques, and artificial intelligence (AI) approaches unravel these relationships. Content spans atomic-level insights into proteins, the physicochemical forces dictating their three-dimensional structure, and the application of modern computational techniques to investigate dynamics, folding, ligand binding, enzyme catalysis, and AI-driven structure prediction.

Key topics include:

• Fundamental principles of protein structure (amino acids, secondary, tertiary, and quaternary architecture, motifs, folds, and structure-function relationships)
• Intramolecular and intermolecular forces, protein stability, and factors influencing biomolecular conformation
• Experimental and computational methods for structure elucidation, including X-ray crystallography, NMR spectroscopy, and use of structure databases
• Core computational methods: molecular mechanics, energy minimization, molecular dynamics and free energy methods
• Applications of artificial intelligence and machine learning for biomolecular structure prediction, functional annotation, and dynamic modeling
• Practical skills in biomolecular modeling, analysis, and visualization, including hands-on use of molecular modeling software, with integration of AI tools

Required:

A bachelor degree in chemistry, biotechnology or equivalent, with a grade C or better in the Norwegian grading system

Application code 9371 - singular courses at Master's level.

After passing the course, the student can

Knowledge

• describe and explain chemical, structural, and computational properties of biomolecules, especially proteins.
• describe and explain the fundamental principles and limitations of key biophysical, computational modeling, and AI-based methods.
• describe and explain structure-based classification and the mechanistic basis of ligand binding, enzyme activity, macromolecular interactions, and AI-driven predictions.

Skills

• independently perform and critically analyze biomolecular modeling, including AI-enhanced structure prediction, energy minimization, molecular dynamics, and structure-function analysis.
• relate molecular structure to biological function through interpretation of experimental, computational, and AI-generated data.
• discuss, present, and communicate theoretical and practical biomolecular modeling results, including concise report writing and oral presentation.
• employ AI tools to supplement traditional modeling approaches, including structural data interpretation and predictive modeling.

General competence

• communicate subject matter effectively with both specialists and non-specialists, verbally and in writing.
• plan and carry out assignments independently and responsibly within given timeframes.
• adapt knowledge and skills to new and varied academic contexts as appropriate.
• evaluate and take some responsibility for the quality of their own work and that of collaborative projects.

If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:

• KJE-3402 Protein Structure 5 ects
• KJE-3106 Biomolecular modelling 5 ects

Language of instruction and examination

Schedule

This course is open to incoming exchange students.

Study level: Master’s

Admission prerequisites:
This course has admission prerequisites, which are listed under the Admission requirements section. Please review this information carefully before adding the course to your Learning Agreement.

For details on how to apply for exchange, course selection guidelines, or to contact the Incoming Admissions Team, please visit: Admissions for Student Exchange.

More info about the coursework requirements

Re-sit examination