Introduction to Biomolecular Simulation
Objectives
The proposed course aims to introduce students to the field of biomolecular simulation. By the end of this course unit, it is expected that students will:
i) Have acquired theoretical and practical skills concerning protein structure files, techniques used in biomolecule simulation and of protein structure prediction tools.
ii) Understand and master the visualization of 3D protein structures, their preparation, and utilization in molecular simulation.
iii) Gain familiarity with multi-scale computational methods, ranging from quantum mechanics to coarse-grained approaches.
Develop the capability to use protein structures, conduct simulations at the atomistic scale, and analyze the resulting outcomes.
General characterization
Code
13321
Credits
6.0
Responsible teacher
Arménio Jorge Moura Barbosa, Pedro António de Brito Tavares
Hours
Weekly - 4
Total - 4
Teaching language
Português
Prerequisites
Available soon
Bibliography
- Leach, A. (2001) Molecular Modelling: Principles and Applications. Prentice Hall, Englewood Cliffs.
- Paul Bauer, Berk Hess, & Erik Lindahl. (2023). GROMACS 2022.6 Manual (2022.6). Zenodo. https://doi.org/10.5281/zenodo.8134358
- Tozzini V. Multiscale modeling of proteins. Acc Chem Res. 2010 Feb 16;43(2):220-30. doi: 10.1021/ar9001476.
Teaching method
The theoretical classes will be conducted using a data projector and will be supplemented with additional bibliography provided on CLIP. Practical sessions will take place in a computer laboratory where students will apply their knowledge in practical tutorials. All used software will be freely accessible to allow students unrestricted access, future use and application.
The practical classes will cover the following topics:
i) Sequence and structural databases;
ii) 3D visualization of proteins;
iii) Homology models and AI tools for protein structure prediction;
iv) Preparation of protein structures for simulation;
v) Geometry optimization/energy minimization of protein structures;
vi) Preparation of small molecule structures and biopharmaceuticals for protein-ligand and protein-protein docking;
vii) Molecular dynamics simulation of proteins, parameter selection, force field, script preparation for calculation;
viii) Analysis and treatment of trajectories from molecular dynamics simulations.
The practical tutorials will lead to a mini project developed during the practical classes of the course.
Evaluation method
1. General Conditions for Participation, Attendance, and Evaluation of the Course:
- The course consists of theoretical (T) and practical computer lab sessions (P).
- Attendance in P sessions is mandatory.
- Evaluation includes assessments for both T and P components
2. Attendance Requirement:
- The maximum allowable absences in practical sessions will be aligned with current legislation.
3. Course Evaluation:
A. Evaluation of T and P Components - 60% of the final grade.
- Continuous assessment through one theoretical test and one practical test.
- Or through a final exam.
B. Evaluation of Practical Component Integrated with Theoretical Component - 40% of the final grade.
- Evaluation is based on presentation of a project/poster or report at the semester''s end.
- The minimum grade for component B is 9.5.
- Component B grade cannot be improved in the resit exam.
- To pass the course, students need a grade higher than 9.5 in component A and B.
Important Notes:
- Grades for all assessment elements are not rounded; they will be used in the final calculation as they are.
- Students who haven''t passed through continuous assessment are not allowed to sit for the resit exam. To pass, the grade in this exam needs to be 9.5 or higher.
- Improvement of the final grade is done only in the resit exam and limited to component A.
The course instructor reserves the right to conduct an oral exam for final approval for any student enrolled in the course.
Subject matter
- Revision: Basic concepts of protein structures, databases, and biomolecule visualization.
- Protein Structure Prediction - Homology models and AI tools for structure prediction.
- Introduction to protein simulation and modeling: from quantum mechanics to molecular mechanics.
- Introduction to molecular interaction prediction techniques: protein-ligand docking and protein-protein interactions.
- Introduction to Molecular Dynamics Simulations: protocols, ensembles, potentials, short and long-range interactions, force fields.
- Analysis of protein simulation results.
- Coarse-grained models and simulations of biomolecular systems.