Workshop in Computational Structural Biology 2015 81855 & 81813, 4 points Ora Schueler-Furman TA: Orly Marcu

Introduction – When, Where, How? Thursdays, Givat Ram Lecture: 14:00-15:45, Sprinzak 25 Exercise: 16:00-18:45, Sprinzak computer class #2 Lectures & exercises available in moodle How: Make sure you have an account in CS ✓ Exercises Submit 7/10 exercises Due within 2 weeks Submit by email to orly.marcu@gmail.com 1/3 of grade Contact: Ora 87094 oraf@ekmd.huji.ac.il, or Orly 87063 orly.marcu@gmail.com Acknowledgements: Sources of figures and slides include slides from Branden & Tooze; some slides have been adapted from members of the Rosetta Community, especially from Jens Meiler Exercises in Pyrosetta have been adapted from teaching material by Jeff Gray

What will we learn: Part I: Protein structure in the eye of the computational biologist 1. Introduction to computational structural biology The basics of protein structure Challenges in computational biology and bioinformatics Protein structure prediction and design  

Part I: Protein structure in the eye of the computational biologist 2. Introduction to Rosetta and structural modeling Approaches for structural modeling of proteins The Rosetta framework and its prediction modes Cartesian and polar coordinates Sampling (find the structure) and Scoring (select the structure) 3. Optimization techniques Energy minimization Monte Carlo (MC) Sampling MC with minimization (MCM)

Part II: Protein modeling and design 4. Ab initio modeling: Principles and approaches 5. Full-atom refinement Local optimization Side chain modeling The representation of side chains as rotamers Rotamer and off-rotamer sampling Finding minimum energy rotamer combinations

Part II: Protein modeling and design 6. Homology modeling Selection of template and alignment of query sequence to template Loop modeling approaches (modeling of unaligned regions) 7. Protein design The theoretical basis of protein design; how different design goals are achieved Success and challenge in computational design  

Part III: Protein interactions 8. Protein-protein docking Challenges and approaches in protein docking The theoretical basis of low-resolution and high-resolution docking 9. Interface analysis and design Determinants of binding affinity and specificity Identification of interface residue hotspots: Computational alanine scanning Success and challenge in interface design 10. Summary  

What will we learn: Exercises Exercises will span a variety of subjects and involve both Rosetta and other widely-used protocols Basic introduction: how to look at proteins Protein structure evaluation and classification: What does my protein do, how good is its structure? Structure comparison Running Rosetta Pyrosetta and Rosettascripts: running and programming ab initio modeling Homology modeling Structure refinement Modeling side chains Loop modeling Protein docking Interface analysis – Computational alanine scanning Protein design and protein interface design

1. Introduction to Computational Structural Biology The Basics of Protein Structure

The central dogma

The code: 4 bases, 64 triplets, 20 amino acids

4 Hierarchies of protein structure Anfinsen: sequence determines structure

The building blocks: 20 amino acids Differ in size, polarity, charge, secondary structure propensity …

Special amino acids N CO C H The simplest aa No sc Very flexible bb N H2C Cyclic aa sc Connects bb N Very constrained bb

Aliphatic amino acids sc contains only carbon and hydrogen atoms hydrophobic

Amino acids with hydroxyl group

Negatively charged amino acids Asp does not like alpha and beta, glu does not like beta Alpha: Ala, Leu, Arg, Met, Lys, Gln, Glu, Ile, Trp, Ser, Tyr, Phe, Val, His, Asn, Thr, Cys, Asp, Gly Beta: Tyr, Thr, Ile, Phe, Trp, Val, Ser, Met, Cys, Leu, Arg, Asn, His, Gln, Lys, Glu, Ala, Asp, Gly, Pro Different size → different tendency for 2. structure

Amide amino acids

Positively charged amino acids pKa 11.1 pKa 12 large sc

Aromatic amino acids pKa 7 benzene ring sc contains aromatic ring

Amino acids with sulfur

Cystine Oxidation of Sulfur atoms creates covalent disulfide bond (S-S bond) between two cysteines

S-S bonds stabilize the protein A chain G I V E Q C C A S V C S L Y Q L E N E N Y C N s s s s B chain F V N Q H L C G S H L V E A L Y L V C G E R G F.. s s N Insulin A chain C B chain

Post-translational modifications Processing (pro-insulin/insulin) control of protein activity Glycosylation protein trafficking Phosphorylation (Tyr, Ser, Thr) regulation of signaling Methylation, Acetylation histone tagging ….

Metal binding proteins aa: HCDE Fe, Zn, Mg, Ca Fe blood: red hemoglobin electro-transfer: cytochrome c Zn in DNA-binding “Zn-finger” proteins Alcohol dehydrogenase: oxidation of alcohol

Important bonds for protein folding and stability Dipole moments attract each other by van der Waals force (transient and very weak: 0.1-0.2 kcal.mol) Hydrophobic interaction –hydrophobic groups/ molecules tend to cluster together and shield themselves from the hydrophilic solvent

Hydrogen bonding potential of amino acids

Primary sequence: concatenated amino acids

Primary sequence: concatenated amino acids

Formation of a peptide bond H O || +H3N Ca C O- R CPK = Corey, Pauling, Kultin. Condensation or dehydration synthesis reaction cpk colors O - oxygen H - hydrogen N - nitrogen C - carbon

The geometry of the peptide backbone The peptide bond is planar & polar: W=180o (trans) or 0o (cis) W W W Peptide bond length and angles do not change Peptide dihedral angles define structure

Dihedral angles c1-c4 define side chain Dihedral angle: defines geometry of 4 consecutive atoms (given bond lengths and angles) From wikipedia

Ramachandran plot  F All except Glycine Glycine: flexible backbone

Ramachandran plot  F

Secondary structure: local interactions

Secondary structure – built from backbone hydrogen bonds

a helix discovered 1951 by Pauling 5-40 aa long average: 10aa right handed Oi-NHi+4 : bb atoms satisfied p helix: i - i+5 310 helix: i - i+3 1.5Å/res Favored: Ala, Leu, Arg, Met, Lys Disfavored: Asn, Thr, Cys, Asp, Gly

a helix: dipole binds negative charges at N-terminus Specific binding through bb binds negative charges at N-terminus

a helix: side chains point out View down one helical turn

Frequent amino acids at the N-terminus of a helices Ncap, N1, N2, N3 …….Ccap Pro Blocks the continuation of the helix by its side chain Asn, Ser Block the continuation of the helix by hydrogen bonding with the donor (NH) of N3

Helices of different character buried partially exposed exposed

Representation: helical wheel buried partially exposed: amphipathic helix exposed

b-sheet Involves several regions in sequence Oi-NHj Parallel and anti-parallel sheets Favored: Tyr, Thr, Ile, Phe, Trp Disfavored: Glu, Ala, Asp, Gly, Pro

Antiparallel b-sheet Parallel Hbonds Residue side chains point up/down/up .. Pleated

Parallel b-sheet less stable than antiparallel sheet angled hbonds

Connecting elements of secondary structure define tertiary structure

Loops connect helices and strands at surface of molecule more flexible contain functional sites

Hairpin Loops (b turns) Connect strands in antiparallel sheet G,N,D G G S,T 70% of beta hairpins <7aa long; mostly 2res long; Type I'.The first residue in this turn adopts the left-handed a-helical conformation and therefore shows preference for glycine, asparagine or aspartate. These residues can adopt conformations with positive F angles due to the absence of a side chain with glycine and because of hydrogen bonds between the side chain and main chain in the case of asparagine or aspartate. The second residue of a type I' turn is nearly always glycine as the required F and Y angles are well outside the allowed regions of the Ramachandran plot for amino acids with side chains. Were another type of amino acid to occur here there would be steric hindrance between its side chain and the carbonyl oxygen of the preceding residue. Type II'. The first residue of these turns has a conformation which can only be adopted by glycine. The second residue shows a preference for polar amino acids such as serine and threonine.

Super secondary structures – Greek Key Motif Most common topology for 2 hairpins Staphylococcus nuclease

Super Secondary Structures- b-a-b Motif connects strands in parallel sheet always right-handed In certain proteins the loop linking the carboxy terminal end of the first b-strand to the amino terminal end of the helix is involved in binding of ligands or substrates.

Repeated b-a-b motif creates b-meander: TIM barrel TIM – triose phosphate isomerase

Tertiary structure defines protein function

The quaternary structure of a protein defines its biological functional unit

Quaternary structure: Hemoglobin consists of 4 distinct chains

Quaternary structure: assembly of protein domains (from two distinct protein chains, or two domains in one protein sequence) Glyceraldehyde phosphate dehydrogenase: domain 1 binds the substance for being metabolized, domain 2 binds a cofactor

1. Introduction to Computational Structural Biology Experimental determination of protein structure: X-ray diffraction and NMR

Experimental determination of structure X-ray crystallography Determines electron density – positions of atoms in structure Highly accurate Static: depends on crystal NMR Determines constraints between labeled spins Allows measure of structure in solution Resolution not defined: more constraints – better defined structure

X-ray diffraction

X-ray diffraction If direction is such that -> Constructive addition -> Reflection spot in the diffraction pattern Wavelength of x-ray ~ crystal plane separations Rotation of crystal relative to beam allows recording of different diffractions Diffraction maps are translated to electron density maps using Fourier Transform Path length difference: 2d sin theta Resolution measures diffraction angles (high angle peaks – high resolution data)

X-ray diffraction Iterative refinement allows improvement of structure R-factor measures quality Fo – observed Fc - calculated

X-ray diffraction 1950’s first protein structure solved by Kendrew & Perutz: sperm whale myoglobin Today: ~107’000 structures solved, most by x-ray crystallography Challenges Grow crystal Determine phase

NMR (Nuclear Magnetic Resonance) NMR-active nuclei (w spins) 1H, 13C Application of magnetic field reorients spins – measure resonance between close nuclei Extract constraints & determine structure Spin: odd number of protons and/or neutrons

1. Introduction to Computational Structural Biology Challenges in Computational Structural Biology

Protein structure prediction and design Protein sequence Protein structure FASTA >2180 hSERT METTPLNSQKQ…… PDB ATOM 490 N GLN A 31 52.013 -87.359 -8.797 1.00 7.06 N ATOM 491 CA GLN A 31 52.134 -87.762 -10.201 1.00 8.67 C ATOM 492 C GLN A 31 51.726 -89.222 -10.343 1.00 10.90 C ATOM 493 O GLN A 31 51.015 -89.601 -11.275 1.00 9.63 O ….. …. Protein Design

Additional topics in computational structural biology Nucleic acids - Prediction of binding and structure RNA stem & loops, pseudoknots; protein-RNA binding DNA curvature; protein-DNA binding Prediction of macromolecular structures Reconstruction of protein assemblies from low-resolution cryo-EM maps Protein-ligand interactions Docking of small ligands Design of inhibitors … and many many more!