Скачать презентацию Physicochemical Methods for Protein Function Prediction Mary Jo Скачать презентацию Physicochemical Methods for Protein Function Prediction Mary Jo

79d474ae8e1cf3bbff9a8a02fca96309.ppt

  • Количество слайдов: 39

Physicochemical Methods for Protein Function Prediction Mary Jo Ondrechen Dept of Chemistry & Chemical Physicochemical Methods for Protein Function Prediction Mary Jo Ondrechen Dept of Chemistry & Chemical Biology Northeastern University Boston, MA 02115

THEMATICS Genomics and proteomics n About titration curves n Method for active site location THEMATICS Genomics and proteomics n About titration curves n Method for active site location and characterization n Examples n Future directions and conclusions n

The post-genomic path n n n Genome sequence Protein structure Protein function Active site The post-genomic path n n n Genome sequence Protein structure Protein function Active site location and characterization, drug design, understanding protein function, normal and disease processes

PROTEOMICS Structural genomics – rapidly discovering new protein structures, many of unknown function The PROTEOMICS Structural genomics – rapidly discovering new protein structures, many of unknown function The Next Frontier: Characterizing the 106 proteins for which genes hold the code.

Predicting Protein Function Protein structure and protein function are not well correlated. Need – Predicting Protein Function Protein structure and protein function are not well correlated. Need – methods to predict function from structure (or sequence). THEMATICS “Theoretical Microscopic Titration Curves” – a reliable way to locate and characterize enzyme active sites.

Typical Experimental Titration Curve Typical Experimental Titration Curve

In the absence of a field, acids obey Henderson-Hasselbalch p. H = p. Ka In the absence of a field, acids obey Henderson-Hasselbalch p. H = p. Ka + log 10{[A-]/[HA]} which may be rewritten in terms of the average charge as a function of p. H: _ C = 10 p. H / (10 p. H + 10 p. Ka) OR C = 10 p. Ka / (10 p. H + 10 p. Ka) where C is the mean net charge

C(p. H) for a typical residue C(p. H) for a typical residue

Typical weak acid/base – narrow window of reactivity When the p. H is close Typical weak acid/base – narrow window of reactivity When the p. H is close to the p. Ka, a weak acid/base is available to act as both an acid and a base By definition of a catalyst, the enzyme must regenerate itself before one cycle is over. for: HA + B A + HB, reaction proceeds both ways if HA and HB have matched p. Ka‘s

A common catalysis - st 1 step in enzyme Deprotonate a C-H bond: C-H A common catalysis - st 1 step in enzyme Deprotonate a C-H bond: C-H + B: C + HB+ What is required of B? n n It must be a strong enough base It must be deprotonated at neutral p. H Mutually contradictory requirements (for a Henderson-Hasselbalch acid/base)

A better way … Catalytic base Lysine 39 is a very strong base AND A better way … Catalytic base Lysine 39 is a very strong base AND is partially deprotonated at neutral p. H!

Perturbed titration curves n n Enable residue to act as acid/base over a wide Perturbed titration curves n n Enable residue to act as acid/base over a wide p. H range Precise p. H adjustment not needed Precise p. Ka match not required Enable residue to have right mix of chemical properties: n n acid (or base) strength right protonation state at neutrality

Perturbed curves Have been noticed before (in titration curves obtained computationally for proteins) We Perturbed curves Have been noticed before (in titration curves obtained computationally for proteins) We now understand are significant: n n Are markers of chemical reactivity Can be used to locate active site M. J. Ondrechen, J. G. Clifton and D. Ringe, Proc. Natl. Acad Sci USA 98, 12473 -12478 (2001)

THEMATICS Theoretical Microscopic Titration Curves n Conceptually simple n Require a known structure n THEMATICS Theoretical Microscopic Titration Curves n Conceptually simple n Require a known structure n Can be computed n Highly reliable identifier of active site n Characterize enzyme active site

Complementary to other methods THEMATICS complements well other methods that predict, or provide clues Complementary to other methods THEMATICS complements well other methods that predict, or provide clues about, function: Evolutionary history; sequence relationships; sequence homology; domain fusion; conservation of gene position; gene coinheritance; geometric motif search; cleft search; small molecule docking; energetics; flexibility Characterize function by chemical reactivity

THEMATICS COMPUTATION n n Start with protein structure Solve Poisson-Boltzmann equations for electrical potential THEMATICS COMPUTATION n n Start with protein structure Solve Poisson-Boltzmann equations for electrical potential function Obtain C(p. H) by Monte Carlo method [Boltzmann-weighted populations] Plot C(p. H) and find perturbed curves

Which curves are perturbed? n n Visual inspection Mathematical analysis (H. Yang) n n Which curves are perturbed? n n Visual inspection Mathematical analysis (H. Yang) n n Statistical analysis Fit to parametrized sigmoid function Neural networks / Support Vector Machines (W. Tong) Only small fraction (~3 -7%) of all ionizable residues are perturbed n

Ionizable residues Arg Asp Cys Glu His Lys Tyr + termini A cluster of Ionizable residues Arg Asp Cys Glu His Lys Tyr + termini A cluster of two or more perturbed residues in physical proximity is a reliable predictor of active site location Success in finding active site is not particularly sensitive to selection criteria

THEMATICS – A unique predictive tool for Proteomics n n n Gives chemical information THEMATICS – A unique predictive tool for Proteomics n n n Gives chemical information Indicates why a particular residue may be involved in catalysis Highly reliable for identifying active sites Conceptually simple Computationally (relatively) fast

Alanine Racemase n n n Used by bacteria in cell wall construction A target Alanine Racemase n n n Used by bacteria in cell wall construction A target for antibiotics (and for drugs to treat tuberculosis) Vitamin B 6 – dependent Active as a dimer Active site located at dimer interface

Alanine Racemase catalysis n n Catalyzes interconversion of D-Ala and L -Ala Reaction occurs Alanine Racemase catalysis n n Catalyzes interconversion of D-Ala and L -Ala Reaction occurs on a Schiff base intermediate (alanine + pyridoxal phosphate) First step on Schiff base: remove alpha. H atom from Ala moiety K 39 and Y 265’ are the catalytic bases

Alanine Racemase Lysines 39 A-234 A K 39 is the catalytic base for D-to-L Alanine Racemase Lysines 39 A-234 A K 39 is the catalytic base for D-to-L

Tyrosines in Alanine racemase Tyrosines in Alanine racemase

Results for Alanine Racemase Full results for Alanine racemase: n [R 219, C 311, Results for Alanine Racemase Full results for Alanine racemase: n [R 219, C 311, K 39, Y 43, Y 265, Y 284, Y 354, C 358], [R 366], [D 68] Bold = known active site residue Italics = “second shell” False positives – tend to be isolated

THEMATICS results THEMATICS has succeeded in finding the active site for several dozen proteins THEMATICS results THEMATICS has succeeded in finding the active site for several dozen proteins with a variety of folds and chemistries. Occasionally, get two or more clusters Occasionally, when visual inspection has not found a positive cluster, statistical analysis has.

Human Adenosine Kinase n n n Catalyzes the transfer of phosphate from ATP to Human Adenosine Kinase n n n Catalyzes the transfer of phosphate from ATP to a nucleoside analogue Unique fold – an - three-layer sandwich plus a smaller - two-layer domain Antiviral and anticancer drug target

Human Adenosine Kinase n n n One of two proteins to date where the Human Adenosine Kinase n n n One of two proteins to date where the human observer was unable to locate the active site Statistical analysis successful in finding the active site (H. Yang) Perturbations in predicted titration curves are subtle, but statistically significant

Aspartates in Human AK D 300 has slightly perturbed curve Aspartates in Human AK D 300 has slightly perturbed curve

Colicin E 3 – important test case n n Nuclease - cleaves a phosphodiester Colicin E 3 – important test case n n Nuclease - cleaves a phosphodiester linkage in the RNA of the ribosome Used by e coli to kill rival bacteria Unique fold – cannot infer active site location from other RNAases Structure provided by Prof. M. Shoham (CWR) prior to publication

THEMATICS results Colicin E 3 n n [E 517, H 526, R 495, R THEMATICS results Colicin E 3 n n [E 517, H 526, R 495, R 545, Y 519] Calculation was performed on the structure of the catalytic fragment Active site found prior to completion of the biochemical characterization Active site correctly located by THEMATICS

HIV-1 protease n n n Acid protease Cathepsin D fold Active as a dimer HIV-1 protease n n n Acid protease Cathepsin D fold Active as a dimer D 25 and D 25’ are the catalytic groups THEMATICS – human observer found D 25 and D 25’ …

HIV-1 Protease Aspartates Note shape of D 25 HIV-1 Protease Aspartates Note shape of D 25

THEMATICS on HIV-1 Protease n n n Human observer finds: [D 25, D 25’] THEMATICS on HIV-1 Protease n n n Human observer finds: [D 25, D 25’] Statistical analysis finds: [D 25, D 25’, R 87] R 8 and R 87 are believed to be involved in substrate recognition: Bardi, J. S. , I. Luque, E. Freire, Structure-based thermodynamic analysis of HIV-1 protease inhibitors. Biochemistry, 1997. 36: p. 6588 -6596

Conclusions n n n THEMATICS – simple, computationally fast, and reliable Simple connection with Conclusions n n n THEMATICS – simple, computationally fast, and reliable Simple connection with chemistry A cluster of two or more positive residues is predictive of active sites Has been automated Characterizes residues (reactivity) Positive clusters well conserved

Conclusions - continued n n Perturbed curves result from the polyprotic nature of proteins Conclusions - continued n n Perturbed curves result from the polyprotic nature of proteins Working hypotheses about perturbed titration curves n n Afford catalytic advantage Afford advantage in reversible binding at recognition sites

Thanks n n David Budil, Leo Murga, Terry Yang, Ying Wei, Alissa Bologna, Katie Thanks n n David Budil, Leo Murga, Terry Yang, Ying Wei, Alissa Bologna, Katie Boino, Wenxu Tong, Bob Futrelle, Ron Williams (Northeastern) Jaeju Ko (IUP) Ihsan Shehadi (UAEU) Dagmar Ringe & Jim Clifton (Brandeis)

Support Acknowledged National Science Foundation Institute for Complex Scientific Software (ICSS) - Northeastern Support Acknowledged National Science Foundation Institute for Complex Scientific Software (ICSS) - Northeastern

mjo@neu. edu M. J. Ondrechen, J. G. Clifton and D. Ringe, Proc. Natl. Acad [email protected] edu M. J. Ondrechen, J. G. Clifton and D. Ringe, Proc. Natl. Acad Sci USA 98, 1247312478 (2001) I. A. Shehadi, H. Yang and M. J. Ondrechen, Mol. Biol. Rpts 29, 329335 (2002)