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Multivariate Analysis of Protein Polymorphism MAPP

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Multivariate Analysis of Protein Polymorphism MAPP

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    1. Multivariate Analysis of Protein Polymorphism (MAPP) Purpose and Basics Algorithm Outline and Performance How to view MAPP results in ProPhylER

    2. Multivariate Analysis of Protein Polymorphism (MAPP) Purpose and Basics

    3. The Impact of Amino Acid Variants

    4. MAPP Concept MAPP addresses specific variants in single positions of the protein sequence More specifically, it uses the evolutionary variation in single columns of the alignment for predictions of the impact of all possible variants on structure and function of the protein In contrast to ESF, which considers averages of neighboring sites, MAPP focuses on single sites and single variants Consider the variation in the two framed columns on the left Red-framed column has a lot of variation that does not appear to be constrained in obvious ways Blue-framed column has very little variation that preserves a certain characteristic (small size of side chain) MAPP quantifies the intuition that there are significant differences in constraint acting upon the red and blue columns, and generates predictions of functional impact of variants

    5. MAPP in ProPhylER

    6. MAPP Methodology: Rationale The observed variation is a sample that reflects specific structural or functional constraints on that position MAPP quantifies these constraints by converting the ‘letter’ information in each column into their corresponding physicochemical values Key concept The conversion allows calculating the mean and the variance in each column for each physicochemical property The variance is a statistical reflection of the tolerated variation The further a potential variant (polymorphism) is outside of the variance of the observed data, the more likely is it to be deleterious

    7. Multivariate Analysis of Protein Polymorphism (MAPP) Algorithm Outline and Performance

    8. MAPP Methodology: General Outline MAPP uses scales of six important physicochemical properties: Hydropathy Polarity Charge Volume of side chain Free energy in alpha helical conformation Free energy in beta sheet conformation The property scales are standardized so the values from different scales are comparable to one another MAPP also decorrelates the scales, which is necessary because certain scales (such as hydropathy and polarity) are correlated MAPP generates impact scores for all possible variants from the observed evolutionary variation MAPP impact scores are converted to P-values, which are displayed on the ProPhylER interface The lower the P-value, the higher the chance that the substitution will be deleterious for structure or function of the protein

    9. MAPP Methodology: Algorithm

    10. Test: Binary Predictions on Mutation Impact Data

    11. Prediction Accuracy for HIV Protease

    12. Multivariate Analysis of Protein Polymorphism (MAPP) How to view MAPP results in ProPhylER

    13. MAPP Track

    14. Physicochemical Property Importance

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