Computational Biochemistry
Áreas Científicas |
Classificação |
Área Científica |
OFICIAL |
Biotecnologia |
Ocorrência: 2023/2024 - 1S
Ciclos de Estudo/Cursos
Sigla |
Nº de Estudantes |
Plano de Estudos |
Anos Curriculares |
Créditos UCN |
Créditos ECTS |
Horas de Contacto |
Horas Totais |
BINF |
17 |
Study Plan |
3 |
- |
5 |
52,5 |
148,5 |
Docência - Responsabilidades
Língua de trabalho
Portuguese
Objetivos
skills, focusing on structure modelling, protein modelling and protein interactions. Students will learn the validity
and applicability of molecular dynamics methods applied to biomolecular problemas – proteins, nucleic acid, and membranes.
Using the contents of this curricular unit students will be able to:
-Choose the appropriate technique to model problems relating to structural;
-Set-up and run the necessary calculations;
-Use the existing analysis tools or write their own, using the programming skills from previous UCs.
Students will learn the fundamental skills of structure simulation, with some exercise classes focused on learning
the details.
Resultados de aprendizagem e competências
-
Modo de trabalho
Presencial
Pré-requisitos (conhecimentos prévios) e co-requisitos (conhecimentos simultâneos)
This UC requires the capacity to write scripts, in any programming language but preferentially in Phyton, and analytical geometry skills, not covered in the UC; it also mobilizes Organic Chemistry and Biochemistry knowledge.
Programa
1. Introduction – atomic and molecular structure; bonds and interactions; general view of methods – classical, semi-empirical, DFT and ab initio – characteristics, applicability and limits. Force fields, thermostats, and barostats. Molecular dynamic best pratices.
2. Structure of proteins and nucleic acids – revision. Contribution of non covalent interactions for the structure and function of proteins and nucleic acids.
3. Modelling proteins and nucleic acids – molecular mechanics and dynamics applied to proteins; forcefields, application and limits.
4. Lipids and membranes – a molecular dynamics approach. Simulation of transmembrane proteins.
5. Protein-ligand interactions – docking, applicability and limits; post-docking analysis -molecular dynamics-based refining.
6. Protein interaction – the interactome; protein-protein docking tools.
Bibliografia Obrigatória
Bruce Alberts; Molecular Biology of the Cell, Garland Science, 2014. ISBN: 978-0815344643
Frank Jensen; Introduction to Computational Chemistry, Wiley, 2017. ISBN: 978-1118825990
Harvey Lodish, Arnold Berk, S Lawrence Zipursky, Paul Matsudaira, David Baltimore, and James Darnell; Molecular Cell Biology, WH Freeman, 2000. ISBN: 0-7167-3136-3
Atkins, Keeler, de Paula; Atkins' Physical Chemistry, Oxford University Press. ISBN: 9780198769866
Introduction to Computational Chemistry; GROMACS 2021.4 Manual (2021.4), 2021
Métodos de ensino e atividades de aprendizagem
Per week: 60 minutos T classes, describing theory and techniques, plus 120 minutes of hand-on computational classes for different simulation techniques focused on solving exercises, software use, work planning and result interepretation.
Software
AutoDock Vina - https://vina.scripps.edu/
GROningen MAchine for Chemical Simulations (GROMACS) - https://www.gromacs.org/
Visual Molecular Dynamics (VMD) - https://www.ks.uiuc.edu/Research/vmd/
Tipo de avaliação
Distributed evaluation with final exam
Componentes de Avaliação
Designation |
Peso (%) |
Teste |
40,00 |
Trabalho laboratorial |
60,00 |
Total: |
100,00 |
Componentes de Ocupação
Designation |
Tempo (Horas) |
Frequência das aulas |
45,00 |
Estudo autónomo |
65,00 |
Trabalho de investigação |
25,00 |
Total: |
135,00 |
Obtenção de frequência
Not applicable.
Fórmula de cálculo da classificação final
Continuous Assessment:
FC= 60% (average of 12 work) + 40% Test
Minimum classification of 6 in test.
Exam:
FC= 100 % Exam
Provas e trabalhos especiais
Continuous evaluation - 12 works wirh delivery spread over the semester (laboratory works), 3 tests about T classes and the lab works (L classes).
Trabalho de estágio/projeto
Not applicable.
Melhoria de classificação
By exam only. No previous evaluation items are considerable.