Structural Biology: What does 3D tell us? Stephen J Everse University of Vermont

Outline Determining a 3D structure –X-ray crystallography Structural elements Modeling a 3D structure

PrimarySecondaryTertiaryQuaternary Amino acid sequence. Alpha helices & Beta sheets, Loops. Arrangement of secondary elements in 3D space. Packing of several polypeptide chains. Given an amino acid sequence, we are interested in its secondary structures, and how they are arranged in higher structures. Protein Structures

Secondary Structural Elements Alpha-helixBeta-strandBeta-turns

Viewing Structures C  or CA Ball-and-stickCPK It’s often as important to decide what to omit as it is to decide what to include What you omit depends on what you want to emphasize

Ribbon and Topology Diagrams Representations of Secondary Structures  -helix  -strand N C

GRASP Graphical Representation and Analysis of Structural Properties Red = negative surface charge Blue = positive surface charge

Consurf The ConSurf server enables the identification of functionally important regions on the surface of a protein or domain, of known three-dimensional (3D) structure, based on the phylogenetic relations between its close sequence homologues; A multiple sequence alignment (MSA) is used to build a phylogenetic tree consistent with the MSA and calculates conservation scores with either an empirical Bayesian or the Maximum Likelihood method.

Tools for Viewing Structures Jmol – PyMOL – Swiss PDB viewer – Mage/KiNG – – Rasmol –

Where can you learn about protein structures? RCSB (PDB) –Lots of hyperlinks out –Educational info (proteins of the month) Proteopedia

RCSB

PDB – View of Biology

Proteopedia

How do we show 3-D? Stereo pairs –Rely on the way the brain processes left- and right-eye images –If we allow our eyes to go slightly wall- eyed or crossed, the image appears three-dimensional Dynamics: rotation of flat image Movies

Stereo pair: Release factor 2/3 Klaholz et al, Nature (2004) 427:862

Protein structures in the PDB The last 15 years have witnessed an explosion in the number of known protein structures. How do we make sense of all this information? blue bars: yearly total red bars: cumulative total N=75,105 Non-redundant ~ 42,938

Classification of Protein Structures The explosion of protein structures has led to the development of hierarchical systems for comparing and classifying them. Effective protein classification systems allow us to address several fundamental and important questions: If two proteins have similar structures, are they related by common ancestry, or did they converge on a common theme from two different starting points? How likely is that two proteins with similar structures have the same function? Put another way, if I have experimental knowledge of, or can somehow predict, a protein’s structure, I can fit into known classification systems. How much do I then know about that protein? Do I know what other proteins it is homologous to? Do I know what its function is?

Definition of Domain “A polypeptide or part of a polypeptide chain that can independently fold into a stable tertiary structure...” from Introduction to Protein Structure, by Branden & Tooze “Compact units within the folding pattern of a single chain that look as if they should have independent stability.” from Introduction to Protein Architecture, by Lesk Thus, domains: can be built from structural motifs; independently folding elements; functional units; separable by proteases. Two domains of a bifunctional enzyme

Proteins Can Be Made From One or More Domains Proteins often have a modular organization Single polypeptide chain may be divisible into smaller independent units of tertiary structure called domains Domains are the fundamental units of structure classification Different domains in a protein are also often associated with different functions carried out by the protein, though some functions occur at the interface between domains activation domain sequence-specific DNA binding domain tetramer- ization domain non-specific DNA-binding domain domain organization of P53 tumor suppressor

Rates of Change Not all proteins change at the same rate; Why? Functional pressures –Surface residues are observed to change most frequently; –Interior less frequently;

Sequence  Structure  Function Many sequences can give same structure  Side chain pattern more important than sequence When homology is high (>50%), likely to have same structure and function (Structural Genomics)  Cores conserved  Surfaces and loops more variable *3-D shape more conserved than sequence* *There are a limited number of structural frameworks* W. Chazin © 2003

Degree of Evolutionary Conservation Less conserved Information poor More conserved Information rich DNA seqProtein seqStructureFunction ACAGTTACAC CGGCTATGTA CTATACTTTG HDSFKLPVMS KFDWEMFKPC GKFLDSGKLG S. Lovell © 2002

Protein Principles Proteins reflect millions of years of evolution. Most proteins belong to large evolutionary families. 3D structure is better conserved than sequence during evolution. Similarities between sequences or between structures may reveal information about shared biological functions of a protein family.

How is a 3D structure determined ? 1. Experimental methods (Best approach): X-rays crystallography - stable fold, good quality crystals. NMR - stable fold, not suitable for large molecule. 2. In-silico methods (partial solutions - based on similarity): Sequence or profile alignment - uses similar sequences, limited use of 3D information. Threading - needs 3D structure, combinatorial complexity. Ab-initio structure prediction - not always successful.

Experimental Determination of Atomic Resolution Structures X-ray X-rays Diffraction Pattern  Direct detection of atom positions  Crystals NMR RF Resonance H0H0  Indirect detection of H-H distances  In solution

Position Signal Resolving Power: The ability to see two points that are separated by a given distance as distinct Resolution of two points separated by a distance d requires radiation with a wavelength on the order of d or shorter: d wavelength Mark Rould © 2007 Resolving Power

Lenses require a difference in refractive index between the air and lens material in order to 'bend' and redirect light (or any other form of electromagnetic radiation.) The refractive index for x-rays is almost exactly 1.00 for all materials. ∆ There are no lenses for xrays. n air n glass n air Mark Rould © 2007 X-ray Microscopes?

Scattering = Fourier Transform of specimen Lens applies a second Fourier Transform to the scattered rays to give the image Mark Rould © 2007 Light Scattering and Lenses are Described by Fourier Transforms Since X-rays cannot be focused by lenses and refractive index of X-rays in all materials is very close to 1.0 how do we get an atomic image?

X-ray Diffraction with “The Fourier Duck” Images by Kevin Cowtan The molecule The diffraction pattern

Animal Magic Images by Kevin Cowtan The CAT (molecule) The diffraction pattern

X-Ray Detector Computer Mark Rould © 2007 Solution: Measure Scattered Rays, Use Fourier Transform to Mimic Lens Transforms

A single molecule is a very weak scatterer of X-rays. Most of the X-rays will pass through the molecule without being diffracted. Those rays which are diffracted are too weak to be detected. Solution: Analyzing diffraction from crystals instead of single molecules. A crystal is made of a three-dimensional repeat of ordered molecules (10 14 ) whose signals reinforce each other. The resulting diffracted rays are strong enough to be detected. A Problem… Sylvie Doublié © D repeating lattice; Unit cell is the smallest unit of the lattice; Come in all shapes and sizes. Crystals come from slowly precipitating the biological molecule out of solution under conditions that will not damage or denature it (sometimes). A Crystal

X-rays Computer Crystallographer Electron density map Model Scattered rays Detector Object Putting it all together: X-ray diffraction Sylvie Doublié © 2000 Diffraction pattern is a collection of diffraction spots (reflections) Rubisco diffraction pattern

3-D view of macromolecules at near atomic resolution. The result of a successful structural project is a “structure” or model of the macromolecule in the crystal. You can assign: - secondary structure elements - position and conformation of side chains - position of ligands, inhibitors, metals etc. A model allows you: - to understand biochemical and genetic data (i.e., structural basis of functional changes in mutant or modified macromolecule). - generate hypotheses regarding the roles of particular residues or domains What information does structure give you? Sylvie Doublié © 2000

What did I just say????!!! A structure is a “MODEL”!! What does that mean? –It is someone’s interpretation of the primary data!!!

So what happens when we can’t get an NMR or X-ray structure?

2˚ & 3˚ Structure Prediction

Secondary (2 o ) Structure

Secondary Structure Prediction One of the first fields to emerge in bioinformatics (~1967) Grew from a simple observation that certain amino acids or combinations of amino acids seemed to prefer to be in certain secondary structures Subject of hundreds of papers and dozens of books, many methods…

Simplified C-F Algorithm Select a window of 7 residues Calculate average P  over this window and assign that value to the central residue Repeat the calculation for P  and P c Slide the window down one residue and repeat until sequence is complete Analyze resulting “plot” and assign secondary structure (H, B, C) for each residue to highest value

Best of the Best PredictProtein-PHD (72%) – Jpred (73-75%) – jpred/index.html SAM-T08 (75%) – query.html PSIpred (77%) –

Structure Prediction Threading –A protein fold recognition technique that involves incrementally replacing the sequence of a known protein structure with a query sequence of unknown structure. Why threading? –Secondary structure is more conserved than primary structure –Tertiary structure is more conserved than secondary structure T H R E A D

3D Threading Servers Generate 3D models or coordinates of possible models based on input sequence PredictProtein-PHDacc – PredAcc – bin/portal.py?form=PredAcc Loopp (version 2) – Phyre – SwissModel – All require addresses since the process may take hours to complete

Ab Initio Folding Two Central Problems –Sampling conformational space ( ) –The energy minimum problem The Sampling Problem (Solutions) –Lattice models, off-lattice models, simplified chain methods, parallelism The Energy Problem (Solutions) –Threading energies, packing assessment, topology assessment

Lattice Folding

Critical Assessment of protein Structure Prediction (CASP)

For the gamers out there…

Print & Online Resources Crystallography Made Crystal Clear, by Gale Rhodes Online tutorial with interactive applets and quizzes. Nice pictures demonstrating Fourier transforms Cool movies demonstrating key points about diffraction, resolution, data quality, and refinement. Notes from a macromolecular crystallography course taught in Cambridge