Protein Modeling and Molecular Dynamics Simulations
- Description
- Curriculum
- FAQ
- Announcement
- Reviews
The Protein Modeling and Simulations course offers hands-on training in a specific research area. Students will learn about the structural features and stability of protein structures, as well as model mutations using single and multiple amino acid substitutions. The effects of these mutations on protein structure will be studied using state-of-the-art Molecular Dynamics simulations. Additionally, the course covers the interaction of target proteins with specific ligand molecules, such as inhibitors or activators. Overall, this course provides a comprehensive understanding of protein structure and function through simulations and analysis.
- 1
Protein Data Bank (PDB), RCSB, UNIPROT - 2Relationship between sequence and 3D structure of a protein
- 3Alignment of protein sequences for homology modeling
- 4
Needleman-Wunsch alignment methodHere is an overview of the Needleman-Wunsch alignment method:
- Define the sequences to be aligned: The Needleman-Wunsch algorithm requires two sequences to be aligned. These can be DNA, RNA, or protein sequences.
- Define the scoring matrix: The scoring matrix is used to assign a score to each possible alignment between elements in the two sequences. For example, a match between two identical elements might be scored higher than a mismatch. Gaps in one of the sequences may also be penalized.
- Construct the alignment matrix: The alignment matrix is a two-dimensional matrix that represents the alignment between the two sequences. Each element in the matrix represents the alignment between a pair of elements in the two sequences.
- Fill in the alignment matrix: Starting at the top left corner of the matrix, the algorithm progresses through each element in the matrix and compares the alignment options for each element. The algorithm chooses the alignment with the highest score and adds it to the matrix.
- Traceback: Once the matrix is complete, the algorithm traces back through the matrix to determine the optimal alignment. This involves starting at the bottom right corner of the matrix and following the path with the highest scores until the top left corner is reached.
- Output the alignment: The optimal alignment is output as two strings, with the elements in each sequence aligned with each other and gaps inserted where necessary to align the elements.
The Needleman-Wunsch algorithm is a powerful tool for comparing biological sequences, but it can be computationally intensive and may not be suitable for very large sequences. There are also variations of the algorithm that have been developed to address specific needs, such as the Smith-Waterman algorithm, which is used for local alignment rather than global alignment.
- 5Multiple sequence alignments (MSA)
- 6Homology modeling of proteins
- 7Refinement of the homology model
- 8Model validation
- 9CHARM & AMBER & VMD
- 10Simulation using GROMACS
- This course is intended for anyone interested in learning molecular modeling.
- This course is aimed at beginners, so no previous experience with bioinformatics is required.
