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Protein Mutational Analysis Using Statistical Geometry Methods

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Protein Mutational Analysis Using Statistical Geometry Methods Majid Masso mmasso_at_gmu.edu http://mason.gmu.edu/~mmasso Bioinformatics and Computational Biology – PowerPoint PPT presentation

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Title: Protein Mutational Analysis Using Statistical Geometry Methods


1
Protein Mutational Analysis Using Statistical
Geometry Methods
  • Majid Masso
  • mmasso_at_gmu.edu
  • http//mason.gmu.edu/mmasso
  • Bioinformatics and Computational Biology
  • George Mason University

2
Protein Basics
  • formed by linearly linking amino acid residues
    (aas are the building blocks of proteins)
  • 20 distinct aa types
  • A,C,D,E,F,G,H,I,K,L,M,N,P,Q,R,S,T,V,W,Y

3
Amino Acid Groups
  • Brandon/Tooze (affinity for water)
  • hydrophobic aas A,V,L,I,M,P,F
  • hydrophilic aas
  • polar N,Q,W,S,T,G,C,H,Y
  • charged D,E,R,K
  • Dayhoff (similar wrt structure or function)
  • (A,S,T,G,P),(V,L,I,M),(R,K,H),(D,E,N,Q),(F,Y,W),(C
    )
  • conservative substitution replacement with an
    amino acid from within the same class
  • non-conservative substitution interclass
    replacement

4
Protein Basics
  • genes code, or blueprint
  • proteins product, or building
  • protein structure gives rise to function
  • why do things go wrong?
  • mistakes in blueprint
  • incorrectly built, or nonexistent buildings
  • Protein Data Bank (PDB) repository of protein
    structural data, including 3D coords. of all
    atoms (www.rcsb.org/pdb/)

PDB ID 1REZ Structure reference Muraki M.,
Harata K., Sugita N., Sato K., Origin of
carbohydrate recognition specificity of human
lysozyme revealed by affinity labeling,
Biochemistry 35 (1996)
5
Computational Geometry Approach to Protein
Structure Prediction
  • Tessellation
  • protein structure represented as a set of points
    in 3D, using Ca coordinates
  • Voronoi tessellation convex polyhedra, each
    contains one Ca , all interior points closer to
    this Ca than any other
  • Delaunay tessellation connect four Ca whose
    Voronoi polyhedra meet at a common vertex
  • vertices of Delaunay simplices objectively define
    a set of four nearest-neighbor residues
    (quadruplets)
  • 5 classes of Delaunay simplices
  • Quickhull algorithm (qhull program), Barber et
    al., UMN Geometry Center

Voronoi/Delaunay tessellation in 2D space.
Voronoi tessellation-dashed line, Delaunay
tessellation-solid line (Adapted from Singh R.K.,
et al. J. Comput. Biol., 1996, 3, 213-222.)
Five classes of Delaunay simplices. (Adapted from
Singh R.K., et al. J. Comput. Biol., 1996, 3,
213-222.)
6
Counting Quadruplets
  • assuming order independence among residues
    comprising Delaunay simplices, the maximum number
    of all possible combinations of quadruplets
    forming such simplices is 8855

7
Residue Environment Scores
  • log-likelihood
  • normalized frequency of quadruplets
    containing residues i,j,k,l in a representative
    training set of high-resolution protein
    structures with low primary sequence identity
  • i.e., total number of quadruplets in
    dataset containing only residues i,j,k,l divided
    by total number of observed quadruplets
  • frequency of random occurrence of the
    quadruplet (multinomial)
  • i.e.,
  • total number of occurrences of residue i
    divided by total number of residues in the
    dataset
  • , where n number of distinct
    residue types in the
  • quadruplet, and t i is the
    number of residues of type i.

8
Residue Environment Scores
  • total statistical potential (topological score)
    of protein sum the log-likelihoods of all
    quadruplets forming the Delaunay simplices
  • individual residue potentials sum the
    log-likelihoods of all quadruplets in which the
    residue participates (yields a 3D-1D potential
    profile)

PDB ID 3phv HIV-1 Protease Monomer 99 amino
acids (total potential 27.93)
Structure reference R. Lapatto, T. Blundell, A.
Hemmings, et al., X-ray analysis of HIV-1
proteinase at 2.7 Å resolution confirms
structural homology among retroviral enzymes,
Nature 342 (1989) 299-302.
9
Properties of HIV-1 Protease
  • functional as a homodimer
  • 99 residues per subunit
  • monomers form an intermolecular two-fold axis of
    symmetry
  • approximate intramolecular two-fold axis of
    symmetry
  • dimer interface N and C termini (P1-T4
    C95-F99, respectively) form a four-stranded beta
    sheet
  • active site triad D25-T26-G27
  • h-phobic flaps (M46-V56) are also G-rich,
    providing flexibility
  • accommodate / interact with substrate molecule
  • Figure adapted from URL
  • http//mcl1.ncifcrf.gov/hivdb/Informative/Facts/fa
    cts.html

10
HIV-1 Protease Comprehensive Mutational Profile
(CMP)
  • mutate 19 times the residue present at each of
    the 99 positions in the primary sequence
  • get total potential and potential profile of each
    artificially created mutant protein
  • create 20x99 matrix containing total potentials
    of all the single residue mutants
  • columns labeled with residues in the primary
    sequence of wild-type (WT) HIV-1 protease
    monomer, and rows labeled with the 20 naturally
    occurring amino acids
  • subtract WT total potential (TP) from each cell,
    then average columns to get CMP
  • CMPj (mutant TP)ij-(WT TP)
    (mutant TP)ij-27.93 , j1,,99

11
Mean Change in Total Protein Potential
Residue
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15
Experimental Data
  • 536 single point missense mutations
  • 336 published mutants Loeb D.D., Swanstrom R.,
    Everitt L., Manchester M., Stamper S.E.,
    Hutchison III C.A. Complete mutagenesis of the
    HIV-1 protease. Nature, 1989, 340, 397-400
  • 200 mutants provided by R. Swanstrom (UNC)
  • each mutant placed in one of 3 phenotypic
    categories, positive, negative, or intermediate,
    based on activity
  • mutant activity to be compared with change in
    sequence-structure compatibility elucidated by
    potential data

16
Experimental Data
17
Observations
  • set of mutants with unaffected protease activity
    exhibit minimal (negative) change in potential
  • set of mutants that inactivate protease exhibit
    large negative change in potential, weighted
    heavily by NC
  • set of mutants with intermediate phenotypes
    exhibit moderate negative change in potential
    (similar among C and NC) wide range for
    intermediate phenotype in the experiments

18
Evolutionarily Conserved Residue Positions
19
  • Apply chi-square test statistic on tables above,
    with the null hypothesis being no association
    between residue position conservation and level
    of sensitivity to mutation
  • LHS table (1 df) ?2 10.44, reject null with p
    lt 0.01
  • RHS table (2 df) ?2 75.49, reject null with p
    lt 0.001

20
Mutagenesis at the Dimer Interface
  • Q2, T4, T96, and N98 are polar and side chains
    directed outward P1, I3, L97, and F99 are
    hydrophobic and side chains directed toward body
  • F99 in one subunit makes extensive contacts with
    I3, V11, L24, I66, C67, I93, C95, and H96 in the
    complementary chain

21
Mutagenesis at the Dimer Interface
  • Alanine scan conducted on interface residues
    individually and in pairs, in one subunit and in
    both chains activity of mutants measured by
    cleavage of ß-galactosidase containing a protease
    cleavage site
  • S. Choudhury, L. Everitt, S.C. Pettit, A.H.
    Kaplan, Mutagenesis of the dimer interface
    residues of tethered and untethered HIV-1
    protease result in differential activity and
    suggest multiple mechanisms of compensation,
    Virology 307 (2003) 204-212.
  • Results Good correlation between cleavage
    (protease activity) and topological scores
    (protease sequence-structure compatibility)

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24
Conformational Changes Due to Dimerization and/or
Ligand Binding
  • PDB ID 1g35
  • HIV-1 Protease Dimer with Inhibitor aha024
  • monomer in a dimeric configuration with an
    inhibitor obtain profile for 1g35, plot 3D-1D
    only for g35A
  • isolated monomer eliminate all PDB coordinate
    lines in 1g35 except those for 1g35A, obtain
    profile, plot 3D-1D
  • plot interface difference between the 1g35A
    3D-1Ds in the dimer and monomer configurations

Structure reference W. Schaal, A. Karlsson, G.
Ahlsen, et al., Synthesis and comparative
molecular field analysis (CoMFA) of symmetric and
nonsymmetric cyclic sulfamide HIV-1 protease
inhibitors, J. Med. Chem. 44 (2001) 155-169
25
Observations
  • majority of residues forming both dimer interface
    and flap region exhibit increase in stability
    following dimerization Q2, T4, I47-I54, T96,
    L97, and F99
  • all h-phobic except Q2
  • increase in stability due to inhibitor binding
    evident for the active site residues D25, T26,
    and G27 also true for the surrounding h-phobic
    residues L24 and A28

26
Significance of Hydrophobic Residues in HIV-1
Protease
  • 35/99 amino acids with scores exceeding 1.0
  • 27 of these are hydrophobic
  • altogether, 44/99 amino acids in protease are
    hydrophobic
  • Assuming h-phobic residues no more likely than
    others (polar/charged) to have scoregt1.0
  • expect (35/99)x44, i.e. 15 or 16 h-phobics gt1.0
  • P(27 h-phobicsgt1.0)
    lt 0.001, yet this is exactly what we observe!
  • What about other cut-off scores, and other
    proteins?
  • applied similar test to all 996 proteins in the
    training setwhile varying cut-off between
    0.0-5.0 in 0.25 increments, binomial
    probabilities were calculated for each protein.
    For a given p-value, of proteins with a lower
    significance level at each cut-off score was
    tabulated

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Significance of Hydrophobic Residues
  • optimal cut-off score for rejection of the null
    is clearly distinct for each of the individual
    proteins.
  • Ex. 827 proteins reject a null with 2.0 cut-off
    score at p 0.05, but 918 proteins reject the
    null at the same significance level if all
    cut-off scores considered.
  • alternate approach 92,343 h-phobic amino acids
    and 136,329 others (polar/charged), total of
    228,672 residues in the 996 proteins assuming no
    differ. in the mean of the scores in both groups,
    apply t-test.
  • Result t126.48, with 228,670 df gt reject null!

29
Acknowledgements
  • Iosif Vaisman (Ph.D. advisor, first to apply
    Delaunay to protein structure)
  • Zhibin Lu (Java programs for calculating
    statistical potentials from tessellations)
  • Ronald Swanstrom (experimental HIV-1 protease
    mutants and activity measure)
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