Lecture 8. Thursday, September 21. Calculating Sequence Similarity Scores

Lecture 8. Thursday, September 21. Calculating Sequence Similarity Scores

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Restricted: For students enrolled in Chem130/MCB100A, UC Berkeley, Fall 2006 ONLY 1 John Kuriyan : University of California, Berkeley Chem 130/MCB 100A, Fall 2006, Lecture 8 SEQUENCE IDENTITY & STRUCTURAL VARIATION The level of sequence identity between two sequences still remains a useful metric when comparing proteins because it is simple to understand what is meant by it. However, as we have seen, it can be a poor predictor of structural similarity. When two proteins have diverged from a common ancestor, they retain a common structural core:
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Restricted: For students enrolled in Chem130/MCB100A, UC Berkeley, Fall 2006 ONLY 2 When can we be certain that two proteins have similar structure, based on sequence identity alone?
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Restricted: For students enrolled in Chem130/MCB100A, UC Berkeley, Fall 2006 ONLY 3 The thermodynamic hypothesis: PROTEIN PROTEIN SEQUENCE STRUCTURE But, the protein folding codes is degenerate: Many different sequences can fold into very similar protein structures. Some of these sequences may share very little sequence similarity (e.g., < 15%). Myoglobin vs. Hemoglobin α vs. Hemoglobin β : 28 out of 150 amino acids are identical.
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Restricted: For students enrolled in Chem130/MCB100A, UC Berkeley, Fall 2006 ONLY 4 The question is, how de we evaluate the degree of similarity between sequences? Amino acid substitution matrices assign scores for substitution of one amino acid by another: This matrix allows us to assign a score to any given alignment:
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Restricted: For students enrolled in Chem130/MCB100A, UC Berkeley, Fall 2006 ONLY 5 What does this score mean? Consider the probability or likelihood that one type of amino acid is replaced by another and survives natural selection. This is a statistical property based on studying the sequences of proteins that are known to be related to each other.
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Lecture 8. Thursday, September 21. Calculating Sequence Similarity Scores

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