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Nebojsa Mirkovic, Carles Ferrer-Costa, Marc A. Marti-Renom, Alvaro N.A. Monteiro, Andrej Sali

Functional Consequences of the SNPs : BRCA1, Membrane Transporters and More. Nebojsa Mirkovic, Carles Ferrer-Costa, Marc A. Marti-Renom, Alvaro N.A. Monteiro, Andrej Sali. Single Nucleotide Polymorphisms (SNPs).

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Nebojsa Mirkovic, Carles Ferrer-Costa, Marc A. Marti-Renom, Alvaro N.A. Monteiro, Andrej Sali

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  1. Functional Consequences of the SNPs : BRCA1, Membrane Transporters and More Nebojsa Mirkovic, Carles Ferrer-Costa, Marc A. Marti-Renom, Alvaro N.A. Monteiro, Andrej Sali

  2. Single Nucleotide Polymorphisms (SNPs) • single base pair replacements of appreciable allelic frequency in the population ( >1% ); • predominant form of human genetic variation (90%); • number predicted to range from one to several million per genome; • predicted frequency: 1/1000bp; • predicted number per gene: 4-12 on average (limited datasets); • classification by genomic location: ncSNPs, cSNPs (synonymous, non-synonymous: 24,000-40,000 per genome).

  3. Significance of SNP Analysis • identify gene(s) that underlie numerous genetic disorders and multifactorial traits (eg, pharmacological response); • SNPs are probably the biggest class of pathogenic changes in the human genome (coding and regulatory regions); • several genetic variants connected to genetic disorders (E4 allele of APOE with Alzheimer disease, FV Leiden allele with deep-venuos thrombosis, and CCR532 with resistance to HIV infection); • numerous indirect evidence of functional impact; • markers of choice in genetic studies.

  4. Br Br 42 * Br 32 Identification of Sequence Variants in Genes of Interest

  5. Project Goal What is the likelihood that a given SNP destroys the function of a protein? • Approach • design a classification function that can predict functional impact of a particular SNP and relies on a combination of sequence, structure and genetic properties from a well-characterized set of nsSNPs; • build ModSNP, a structural database of SNPs, containing protein structure models for all known nsSNPs; • apply the classification function to a number of specific examples and to all the SNPs in ModSNP.

  6. BRCA1 Project

  7. RING BRCT NLS Globular regions 200aa Nonglobular regions BRCA1 BRCT repeats Human BRCA1 Tandem BRCT Repeats Williams, Green, Glover. Nat.Struct.Biol. 8, 838, 2001

  8. Missense Mutations in BRCT Domains by Function cancer associated not cancer associated unknown F1761S M1775E M1775K L1780P I1807S V1833E A1843T L1705PS1715NS1722FF1734LG1738EG1743RA1752PF1761I M1652K L1657P E1660G H1686Q R1699Q K1702EY1703HF1704S C1697R R1699W A1708E S1715R P1749R M1775R no transcription activation V1665M D1692N G1706A D1733G M1775V P1806A transcription activation M1652I A1669S M1652T V1653M L1664P T1685A T1685I M1689R D1692Y F1695L V1696L R1699L G1706E W1718C W1718S T1720A W1730S F1734S E1735K V1736A G1738R D1739E D1739G D1739YV1741G H1746N R1751P R1751Q R1758G L1764P I1766S P1771LT1773S P1776S D1778G D1778H D1778N M1783T C1787S G1788D G1788V G1803A V1804D V1808A V1809A V1809F V1810G Q1811R P1812S N1819S A1823T V1833M W1837R W1837G S1841N A1843P T1852S P1856T P1859R unknown

  9. Mapping of the Mutations on the Surface of BRCA1 BRCT Domains R1699Q/W G1743R K1702F L1657P D1692N D1773G E1660G

  10. Location of Putative BRCT-Protein Interaction Site RMSMVVSGLTPEEFMLVYKFARKHHITLTNLITEETTHVVMKTDAEFVCERTLKYFLGIAGGKWVVSYFWVTQSIKERKMLNEHDFEVRGDVVNGRNHQGPKRARESQDRKIFRGLEICCYGPFTNMPTDQLEWMVQLCGASVVKELSSFTLGTGVHPIVVVQPDAWTEDNGFHAIGQMCEAPVVTREWVLDSVALYQCQELDTYLIPQIP RMSMVVSGLTPEEFMLVYKFARKHHITLTNLITEETTHVVMKTDAEFVCERTLKYFLGIAGGKWVVSYFWVTQSIKERKMLNEHDFEVRGDVVNGRNHQGPKRARESQDRKIFRGLEICCYGPFTNMPTDQLEWMVQLCGASVVKELSSFTLGTGVHPIVVVQPDAWTEDNGFHAIGQMCEAPVVTREWVLDSVALYQCQELDTYLIPQIP

  11. Mutation Features

  12. START “Decision” Tree for Predicting Functional Impact of Genetic Variants buried exposed buriedness buriedness buriedness buriedness neighborhood rigidity neighborhood rigidity neighborhood rigidity functional site functional site non-rigid (≥-0.7) rigid (<-0.7) YES residue rigidity residue rigidity residue rigidity non-rigid (≥-0.7) rigid (<-0.7) volume change volume change volume change volume change volume change volume change ≥30A3 NO ≥90A3 ≥60A3 <30A3 - - <90A3 - <60A3 - - charge change charge change charge change charge change YES NO - 2 class polarity change polarity change polarity change 0 or 1 class mutation likelihood mutation likelihood mutation likelihood ≥0 <0 - 0 non 0 phylogenetic entropy phylogenetic entropy phylogenetic entropy - other information (helix breaker, turn breaker) other information (helix breaker, turn breaker) other information (helix breaker, turn breaker) YES + + + + NO

  13. Rationalization of Functionally Characterized Mutants Prediction of Function of Uncharacterized Mutants

  14. SNP Web Server

  15. Membrane Transporter Project

  16. Domain Organization and Structure of E.Coli ABC Transporter MsbA 1 582 A C B transmembrane nucleotide binding transmembrane intracellular extracellular A Walker motif A (375-383) B Walker motif B (501-505) C ABC transporter signature (481-489) crystalized not crystalized Eco-msbA dimer, 1jsq Chang, Roth. Science 293, 1793, 2001

  17. PMT Database • a database of in-site detected and/or verified polymorphisms in various mammalian membrane transporters with ample population genetics data (allelic frequencies, ethnic distribution); • 59 proteins divided in two groups (24 and 25 proteins respectively) depending on the SNP-detection approach; • 10 ABC transporters, 5 with SNPs reported so far (BSEP, MDR1, MDR3, MRP1, MRP2).

  18. http://guitar.rockefeller.edu/modbase Pieper et al., Nucl. Acids Res. 2002.

  19. ModPipe Results for Transmembrane Proteins from the PMT Database • 49 proteins submitted; • 11 proteins could not be modeled; • 15 proteins have bad fold assessment; • 8 proteins have good fold assessment, but bad model score; • 15 proteins have good fold assessment and good model score. Coverage of ABC Transporters

  20. Predicted Domain Organization and Structure Model of Human ABC Transporter MDR1 1 1280 repeat 1 repeat 2 1jj7A (383-625) 1g291 (1034-1274) modeled intracellular, extracellular ATP-binding loop transmembrane helix ATP-binding cassette not modeled Modeled regions of MDR1 383 1034 625 1274

  21. Sequence and structure features of SNPs

  22. Significance • a comprehensive structural study of the functional impact of mutations focused on a particular protein family; • a large and informative mutation set used; • rationalization of the characterized mutation set used to develop a predictive tool; • possible contribution to genetic studies (eg, candidate gene approach) and medical practice (with other methods).

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