Biomolekylär strukturanalys
Why do we care about protein structure?
* Structure governs function and regulation
* Allows us to go from schematics to a molecular/atomic understanding
* Allow us to dissecthow changes in sequence often lead to changes in structure and function
* Proper folding is critical for function/ misfolding can have dire consequences
* MAcromolecules interact with other molecules using a variety of non-covalent innteraction. The specificity and affinity of these interactions are critical to biological function
Composition and functions: Protein
Atoms: C, H, N, O, S
Building blocks: Amino acids
Forms polymers, type of bind?: Yes peptide bonds
Intra-molecular interactions: Covalent (S-S), H-bonds, charge based, van der Waals.
Functional role in cells: Enzymes, structural proteins, sensors, receptors etc.
Composition and function: Nucleic acid
Atoms: C, H, N, O, P
Building blocks: Nucleotides
Forms polymers, type of bind?: Yes, Phosphodiester bonds
Intra-molecular interactions: H-bonds, Stacking interactions
Functional role in cells: Enzymes, Storage of genetic information, ribosomes.
Composition and function: Carbohydrates
Atoms: C, H, N, O
Building blocks: Simple sugars
Forms polymers, type of bind?: Yes, glycosidic linkages- of various types
Intra-molecular interactions: H-bonds
Functional role in cells: Storage of energy, structural, recognition, interactions.
Composition and function: Lipids
Atoms: C, H, O
Building blocks: Fatty Acids, glycerol
Forms polymers, type of bind?: No, forms various di-, tri- glycerides
Intra-molecular interactions: Van der Waals.
Functional role in cells: Membranes, signaling, energy storage, small molecule hormone
Structure is determined by several factors
* Covalent and non-covalent bonding govern the three-dimensional structures of proteins and nucleic acids which impacts functions.
* The amino acid sequence observed in nature are highly selected for biological function but do not necessarily adopt a unique folded structure.
* The sequence (and hence structure and function) of proteins and nucleic acid can be altered by alternative splicing, mutation or chemical modification. Sequences (and hence structure and function) of macromolecules can evolve to create altered or new biological activites.
Macromolecular interaction
* The interactions between macromolecules and other molecules rely on the ame weak, non-covalent interactions that play the mayor role in stabilising the 3D structures of the macromolecules themselves.
* The hydrophobic effect, ionic interactions and hydrogen bonding interactions are prominent.
* Structural organisation of interacting chemical groups in a binding site or an active site lends a hogh degree of specificity to these interactions.
* The specificity anf affinity of these interactions are critical to biological function
Interaactions in biological molecules: Covalent bonds
* Peptide
* Phosphodiester (nucleic acids)
* Disulfide
Interactions in biological molecules: Non-covalent interactions
* Hydrogen bonds
* Electrostatic/ionic
* Hydrophobic interaction
* Van der Waals
* Metal Coordination
* Pi based interaction (stacking)
Macromolecular structure is dynamic
* Macromolecular structure is dynamic over a wide range of time scales.
* The dynamic structural changes, large and small, are often critical for biological function
* Proteins can contain intrinsically unstructured domains. The lack of structure in solution may facilitate a function in which interactions must occur promiscuously with several other molecules
* The dynamic structure of macromolecules enables rapid changes that impact the homeostasis of biochemical and molecular biological processes.
Experimental data from the different methods
* X-ray crystallography
You get electron density from a structure of DNA.
* NRM
You get distance restraints and you can do calculation of protein folding. The restraints can be used o solve the strucutre of molecules.
*EM
You get the density of the overall ... of the protein. You can classify them and codefine them.
What is in the PDB?
* Coordinates and experimental data files.
* Details about sample preparation, data collection and structure solution.
* Sequence(s) of polymers (proteins and nucleic acids) in the structure.
* Information about ligands in the structure.
*Links to various resources that describes the sequence, function and other properties of the molecules.
* Classification of structures by sequence, structurem function and other criteria
Sample requirements for structural biology
* Size requirements/capabilities of differrent techniques
* Soluble (& folded) protein
* Pure sample
* Monodisperse
* Amount of sample needed (source: Natural, recombinant)
Why X-rays?
* Max resolution theoretically obtainable: 1/2 wavelength used for data collection
* To image atomic structure of molecules, wavelength needs to be on the same order of magnitude (<2Å), i.e wavelength in the range of atomic distance = X-Rays
* Wavelengths between 0.5-1.6 Å most suitable for X-ray crystallography: sufficient penetrating to study samples up to a mm in size, but scattered strongly by matter.
Which wavelengths?
* Depends on source.
* Usually 1.0 (synchrotron) pr 1.54 Å (Cu Kalpha radiation, home source)
* Wavelength of 1.0 Å = 12.394 keV -> very high energy
* At synchrotrons, you can tune the wavelength:
- anomalous scattering for phasing
- Identification of atomic species
Why X-ray crystallography?
* X-rays are scattered in all directions by the electron of every atom in the object with a magnitude proportional to the size of its electron complement (heavier atoms with more electrons scatter more - exploited in heavy atom phasing)
* Single molecules scatter too weakly, and would also be destroyed before obtaining atomic resolution data.
* Crystal lattice with many (10^12-10^15 molecules), scattering cooperatively, since all arranged the same way, yields amplified signal.
* Less of an impact if a fraction of the molecules is destroyed through radiation damage1
* No size restriction on molecules, as long as you can get crystals
* As much as possible of the scattered radiation is recorded. This makes the resulting image truly three-dimensional, with no special difference in representation or accuracy for different directions.
Pros/cons X-ray and solution NMR
* Advantage of NMR is you di it in solution
* NMR - Takes more time to get a structure, ,but unbeatable for dynamics
* In crystallography the difficult bit nowadays is not the dataprocessing or structure solution, but getting diffraction quality single crystals.
* Proteins trapped in a crystal lattice, restricted dynamics, since it is also average over all unit cells.
* X-ray more detailed, structures together with ligands, metals, etc
Protein crystallisation
* Rate limiting step
* Samle requirements
- Pure proteins of high conc 10-50 mg/ml
- Needs to be stable and ideally monodisperse
* Single point mutation can change behaviour during crystallisation
* Often hundreds to thousands of conditions need to be tested
Crystallisation = ordered aggregation
* The natural inclination of any system proceeding toward equlibrium is to maximize the extent of disorder, or entropy. At the same time there is a thermidynamic requirement to minimize the free energy (or Gibbs free energy) of the system.
* Crystal nucleation and growth must be dominated by noncovaent chemical and physical bonds arising in the crystalline state that either cannot be formed in solution or are stronger than those that can. These bonds are in fact what hld crystals togheter. Thet are the energetically favourable intermolecular interactions that drive crystal growth despite resistance to molecular constraints.
Weak non-covalent interactions between molecules
* High solvent content (average 50%, though it can vary from about 25-90%).
* The entire crystal is permeated with a network od solvent channels.
* Protein is surrounded by a hydration shell
* Can soak in ligands, substrated, etc
Mounting of protein crystals
* Mounted in cryoloops ( or capillaries) and flash frozen in liquid nitrogen.
* Need to prevent ice formation (would diffract) - add cryoprotectant to ensure vitrification during flash freezing.
* Frozen crystals can be stored and shipped in liquid nitrogen to the syncrothron.
* At the synhrothron, the crystals are mounted (by robot or more rarely manually).
* Over the laast 10 years or so technique development are enabled data collection from crystals in situ: No need to handle crystals at all, but requires many crystals.
* There are also laser set-ups for automated crystal harvesting using laser ablation - cutting out the crystal from the well and attach it to a pin to enable flash frozening, followed by automatic data collection.
Crystalls are mounted on a gonimeter for data collection.
* Mount on a gonimeter head - need to be centered in the X-ray beam.
* Then you rotate the crystal and collect data on a fixed detector.
* Robot mounting and beamline automation allows for remote data collection.
3D diffraction - many images needed to collect complete data set
* The complete diffraction pattern from a protein crystal is not limited to a single planar array.
* Each image corresponds to only a limited set of orientations of the crystal woth respect to the X-ray beam.
* In order to record the entire 3D X-ray diffraction pattern, a crystal must be aligned with respect to the X-ray beam in all orientation, and the resultant patterns recorded for each orientation.
* From many 2D arrays of reflections, corresponding to cross section through diffraction space, the entire 3D diffraction pattern composed of ten to thousands of reflections is compiled.
Diffraction image
Can be understod based on the works of Braggs:
*Diffraction of X-rays by the set of lattice planes in the crystal.
*The atoms in the crystals can be seen as sitting in planes, that repeat regularly in all three dimensions.
*Each individual spot in a diffractoin image represents a single reflection from each set of these crystal planes.
Diffraction is a wave phenomenon
* When light passes through a small opening, comparable in size to the wavelenght of the light, in an otherwise opaque obstacle, the wavefront on the other side of the opening resemble a curve with high and lows.
* The light spread around the edges of the obstacle. This is the phenomenon of diffraction.
*Diffraction is a wave phenomenon and is also observed with water waves in a ripple bank.
Symmetry operations
* An object is symmetrical if, after som e operations have been carried out, the result in indistinguishable from the original object.
* Types of symmetry:
- Rotation
-Mirror (plane)
-Inversion
* Since macromolecules are chiral, only rotational symmetry is possible, leaving 65 spacegroups (of 230 total).
Crystal lattice
* The unit cell is the basic repeating unit of the crystal, repeated in all three directions, with no empty spaced allowed.
* Lattice translations in all three directions based on the distance of the repeating unit will reproduce an identical crystal.
Asymmetric unit
* Has no self-symmetry, smallest building block.
* A set of symmetry operators, here three mutually perpendicular twofold axes, called space groups, is applied to the asymmetric unit to produce a small, closed set of asymmetric units.
* A parallelepiped of minimum volume, called the unit cell, is chosen so that it encloses a full complement of the asymmetric units, and reflects the symmetry properties of the space group.
Unit cell
* A parallelepiped of minimum volume that encloses a full complement of the asymmetric units, and reflects the symmetry properties of the space group.
* The symmetry operations allowed within a unit cell include twofold, threefold, fourfolf and sixfold rotation and screw axis.
* The space group shown here is called ans orthorhombic unit cell.
* the unit cell and its contetns are repeated in a periodic manner aling the unit cell axis. These translations are called the lattice translation, or lattice vectors, and the corners of the unit cells, define a point lattice.
Families of parallel planes in the crystal
* Let us define families of planes of equal interplanar spacing that include all of the points in the lattice.
* The most readily apparent sets of planes in na crystalline lattice are those determined by the faces of the unit cells.
* Any set, or family, of planes can be uniquely characterized by the number of times it would intercept each cell edge over the course of one unit cell.
Miller indices hkl
* The three integers that uniquely define a given family of planes are known as the Miller indices.
* They are designated hkl.
* If the unit cell dimension and interaxial angles are known for a particular crystal, the interplanar spacing d for any set of Miller indices hkl can be directly calculated.
* The families of planes also may be thought os as sampling the contents of the unit cells at regular inteervals, liek serial cross sections in microscopy.
* By analogy of one knew what lay on each plane, by interpolation one could reconstruct the contents of the unit cell:
- For families of large interplanar spacing (low Miller indices), this would yield rather poor results i.e it would give a very low-resolution image of the unit cell contents.
- For families of small interplanar spacing (With high Miller indexes), this interpolation would be much better.
Braggs Law - diffraction from sets of planes
* Large unit cells, with large spacing, give small angles of diffraction and hence produce many refkections that fall within a convenient angle from the incident beam,
* On the other hand, small unit cells give large angles of diffraction, producing fewer measurable reflections.
Ewald sphere construction
All lattice points that touch the sphere obey Braggs Law
Calculation of unit cell parameters from the diffraction pattern
Because reciprocal-lattice spacings are the inverse of real-lattice spacings, the unit cell dimensions are inverserly proportional to the spacing of reflactions on planes in reciprocal space, and determining unit cell dimensions from reciprocal-lattice soacing is a remarkably simple geometric problem.
Determination of resolution
Basic geometry of your diffraction experiment will tell you the max resolution at the edge of the detector (normally you choose the distance of the detector based on the resolution of your crystal).
Crystal diffraction data set
* Position and geometry of spots = unit cell dimensions (space group symmetry).
* The more order of diffraction you observe, the higher the resolution.
* The intensities of the spots reflect the scatter density from that particulat plane = reflecting the unit cell contents.
* The probem we have with collecting diffraction data:
we only observe the position and intensity of the spots, not their time of arrival = the phase information is lost (which is needed to be able to calculate the electron density).
Wave equations and Fourier series
* Even the most intricate periodic functions can be described as the sum of simple sine and cosinee functions = Fourier series
* Step function = Target
* Can be described by a fourier synthesis of multiple Fourier terms.
* Low-frequency terms like f1 approximate gross features, while higher frequency terms like f3 improve the approximation by filling in the finer details.
Structure factors <-FT-> Electron density
* Structure factors = wave description of X-ray reflections
* Electron density - What scatters in real space in the unit cell
Intensity distribution of diffraction pattern is related to the electron density distribution in the crystal
Electron density - end result from experiment
* Result of the experiment is the electron density map, telling us how the electrons are distributed in the unit cell.
* Based on the primary sequence of the protein that wa scrystallised we can then go on to build the model.
* Nowadays, depending on resolution of the data, models are autobuilt and "just" need to be checked manually via careful inspection.
* Need to see connectivity of electron density to be able to trace the main chain. Also the higher the resolution the easier it is to identify each amino acid.
Methods to overcome the phase problem
* Direct methods: Requires very high resolution and small proteins, very rare for proteins, but common for small molecules.
* Molecular replacment: Requires prior information, i.e structural information from experimental structures of homologous protein or good homology models
* Experimental phasing:
- Heavy-atom derivatives pf you protein (SIR, MIR, MIRAS, SIRAS)
- SeMet derivative of your protein - collect anomalous dispersion data (SAD, MAD)
Heavy atom derivative
* If heavy atoms dont bind, or are unordered - no intensity difference = no signal
* Binding of heavy atom can cause protein to shift in unit cell and/or unit cell dimensions to change
Anomalous scattering
* X-ray photon interacts with the electrons in the atoms of the sample. Atomic scatterinf factor f proportional lto the atomic number, Z, of atoms (exploited when using HEAVY atoms)
* At photon energies close to the absorption edge of a given atom, sattering from the atom is no longer normal: While many photons are scattered normally, a fraction is absorbed by the atom and re-emitted with altered phase -> anomalous scattering.
* Absorption edges for anomalous scattering
- The light atoms of N, C and O do not have any absorption edge in the enrgy range used for crystallography -> Need other elements in crystal taht can be exploited.
SAD/MAD phasing
* Introduce a small number of anomalously scattering atoms into crystals.
- Usual choice: SeMet-labelled protein, S-SAD, Zn2+
- Heavy atoms can also be exploited for this.
* During anomalous scattering Friedels law breaks down --> Need to collect bith F+ and F- at one or more wavelength.
* Derive anomalous and ( if more than one wavelenght) dispersive differences
* Use these differences to locate anomalously scattering atoms.
* Use these position to initiate phase calculations.
Molecular replacement
* Need structure of close enough homolog >30%
* Ideally you should have search models representing the majority of your scattering "mass" in the crystal.
* If you have multidomain or multi-component complexes, you might need to divide into multiple search models and search individually, one by one (inter-domain rearranhements)
* Important to trim flexible and/or divergent part from your search model
Improving inital phases - density modificatio
* Initial maps usually quite noisy, especially from SAD/SIT whit phase ambiguity
* Use knowledge about electron density distribution to obtain improved phases by density modification.
- Solvent flattening/flipping
- Histogram matching
- NCS averaging
How do we know that our phasing experiment has worked?
Interpretability of the electron density map is the best metric.
* Clear solvent/protein regions.
* Connectivity of electron density.
* Recognizable shape for side chains.
Map interpretation - obtaining an atomic model
* The quality of the electron density map tp be interpreted depends both on the resolution and quality of tha phases.
* If high enough resolution, atomatic model building will get far.
* Initial, automatic map interpretations (skeletonization, building of poly-Ala or sequence assigned (partial) models need to be followed up by manual inspection and model building, iterated with refinments.)
* Bulky side-chains, proline, methionines/cysteines can act as sequence markers during model building.
* Possibly (automatic) placment of (ideal) alfa-helices or strands.
When starting from MR, atomic model already available, needs adjusting.