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Discovering critical residues in glutathione reductase bioinformatics_GR_presentation.ppt Donnie Berkholz.

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Presentation on theme: "Discovering critical residues in glutathione reductase bioinformatics_GR_presentation.ppt Donnie Berkholz."— Presentation transcript:

1 Discovering critical residues in glutathione reductase http://dev.gentoo.org/~spyderous/ bioinformatics_GR_presentation.ppt Donnie Berkholz

2 What and How ● Role – Reduced thiols – Oxidative stress – DNA precursors – H + transport ● Mechanism – Flavoprotein – NADPH – Disulfide

3 Goals ● Figure out the best programs and methods for this analysis ● Search for unknown critical residues ● Verify whether residues already thought critical are actually conserved ● Check for potential differences in function and specificity among subfamilies (Podar et al.)

4 Multiple sequence alignments

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7 ClustalWDialign-TMuscleProbCons

8 ● “Probabilistic consistency” ● Pair-HMM based ● Three-way alignment consistency ● Parameters derived from training ● Maximized accuracy ProbCons

9 How to find important residues? ● Principal component analysis (PCA) – Each sequence becomes a vector – Successive dimensions grow less significant ● Evolutionary trace and friends – Divide tree into groups, then check them – So, first we need trees

10 Trees ● Maximum likelihood – ProML (PHYLIP) – Gamma distribution + invariant sites – Approximate with 5 rate categories ● Bayesian – MrBayes – Gamma distribution + invariant sites – MCMC: Markov chain Monte Carlo – Mixed: sample with probability -> WAG – Try variable-rate models

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12 ConSurf ● Calculates evolutionary conservation (Bayesian) ● Maps onto protein structure ● Input flexibility – PDB -> seq. -> PSI-BLAST -> MSA -> NJ -> CS ● Can't yet analyze subfamilies

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14 NADPH environment

15 Disulfide environment

16 Catalytic: H467+D472

17 Structure without function?

18 Surface: F354+D22

19 Surface: D316+T321

20 FAD binding

21 Stabilizing the phosphate

22 Structural stability

23 What next? ● Check for validity of tree model ● Tree-determinant residues ● Experimental functional determination

24 Summary ● ProbCons is great for MSA's ● Bayesian trees take forever, but they provide confidence values (no bootstrap!) ● ConSurf maps sequence conservation onto protein structures ● Supports catalytic hypothesis ● New putative functional roles: – Interactions? F354+D22, D316+T321 – Binding: I26, R218 – Structure: H434 etc

25 References ClustalW: Chenna et al. NAR 31: 3497 (2003). Muscle: Edgar. NAR 32: 1792 (2004). Dialign-T: Morgenstern. NAR 32: W33 (2004). ProbCons: Chuong et al. Genome Res. 15: 330 (2005) Jalview: Clamp et al. Bioinform. 12: 426 (2004). PHYLIP: Felsenstein. Distributed by author (2005). MrBayes: Ronquist and Huelsenbeck. Bioinform. 19: 1572 (2003). ConSurf: Landau et al. NAR 33: W299 (2005). PyMol: DeLano. www.pymol.org (2005).


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