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MCB 124

M2 Midterm 2

Resolution Defined as the minimum center to center distance at which two spherical objects can be distinguished as being “two”. Smaller numbers are better. Quantitative measure of the level of detail that can be discerned in an image of an object.
Noise Random degradation of an image due to local fluctuations in the measured intensity at individual coordinates. Should average to zero if truly “random”.
negative stain the electron beam primarily interacts with the stain. When stain is added to a sample, the stain surrounds the sample but is excluded from the volume occupied by the sample;
negative stain 2 a well-stained sample is uniformly covered by the stain. When the electron beam (arrows) passes through the sample, it will be deflected by its interactions with the sample and stain.
negative stain 3 Since the protein sample excludes stain, the deflection of the electron beam through protein (center arrow) is less than that through stain rich regions (outer arrows). Electrons that are highly deflected
negative stain 4 by the stain are then filtered out by the objective aperture located below the sample. Depending on the size of the aperture, the quantity of electrons that are culled out will vary and determine the contrast and resolution of the image.
negative stain 5 A negative staining technique uses heavy metal salts to enhance the contrast between the background and the image.
Metal Shadowing a thin layer of evaporated metal, such as platinum, is laid at an angle on a biological sample. An acid bath dissolves the biological material, leaving a metal replica of its surface, which can then be examined in the transmission electron microscope.
Nano-Gold Labeling specificity of gold nanoparticle-fusion tag couples provides a means of labeling individual proteins in multisubunit, macromolecular complexes or structures with gold particles of different sizes
Cryo-TEM (3D from 2D) techniques that look at Proteins in Buffer Solution on Carbon-Film in -180 C. Place sample on copper-grid with holey carbon film. allows the observation of specimens that have not been stained or fixed in any way, showing them in their native environment.
X-ray crystallography (1) 1) Yields a 3-D picture of the electron density in crystals => since atoms have electrons around them, this gives the locations of all of the atoms in the structure.
x-ray crystallography (2) 2) Is the primary means by which protein structural geometry is known.
x-ray crystallography (3) 3) Structures are determined to • understand how proteins fold and are stabilized • elucidate enzyme mechanisms • understand the basis for specific molecular recognition
X-ray crystallography (advantages) 1) describes structures in the greatest detail 2) gives the entire picture all at once 3) is now highly automatable 4) no size limitations, up to virus sized molecules
X-ray crystallography (disadvantages) 1) requires crystals high protein concentrations, mono-disperse 2) crystals must be “frozen” in vitreous ice 3) is crystal state relevant? (YES, for the most part) 4) Gives no information about mobile atoms (rmsd = 1Å)
x-ray crystallography (phasing fix) Perturb the system – Multiple Isomorphous Replacement (MIR) (Position of few heavy atoms) – Multiple-wavelength Anomalous Dispersion (MAD) (Anomalous scatterers) Guess the phase – Molecular Replacement - Good model - 6-D problem - Mathematical Function
Image Averaging Reduces random noise by cancellation
delta-Cp for Folding Proportional to surface area difference between F and U states
cold unfolding a result of the large negative delta-Cp for folding
Hydrophobic Effect major driving force for polypeptide compaction
Molten Globule a stable partially-folded, fluctuating protein structure
Cosy Data used to assign NMR spectrum peaks to particular protein proteins
Protein Stability Difference in free energy between folded and unfolded states
Circular Dichroism Optical technique that measures the amount of secondary structure
NOESY NMR experiment that identifies proton pairs within 5-Angstrom of each other
Strain Energy Penalty for unfavorable interatomic interactions
Simulated Anealing A simulation run initially at a high temperature followed by gradual cooling
Molecular Dynamics Simulation of atomic motions in a molecule
transfer free energy Free energy difference between aqueous and non-polar environments
AFM An imaging technique that yields a topographic map of the sample to angstrom vertical resolution
Disulfide bridge Stabilizes proteins by reducing the U-State entropy
chain entropy Always unfavorably changed when a protein folds
Cm Denaturant concentration at which proteins delta-Gf = 0
R-Factor Measures agreement between an atomic model and observed diffraction data
phase Required to solve an X-Ray crystal structure
Tm At this temperature, folded and unfolded states are in equal amounts
Force Field A mathematical description of interatomic forces used in energy calculations
Resolution The minimum distance between two objects that can be distinguished in an imaging technique
Cryo - Single Particle CryoElectron Microscopy, AFM, 2DX (2-D Electron Crystallography) Technique(s) where the primary data from an experiment is an image of the macromolecule
X-Ray Chrystallography Technique that most accurately determines atom positions in a macromolecule
NMR Technique(s) that can be used to determine the pkas of protein side chains
AFM Easiest way to visualize the location of a bound protein on a large DNA molecule
NMR Technique(s) that can determine whether an ion pair stabilizes a protein or not.
NMR Technique(s) that is (are) limited by the size of the protein.
NMR Atomic structures are derived by determining which atoms are close to each other in 3-D space.
X-Ray, 2DX Technique(s) that require(s) ordered macromolecule arrays (e.g crystals)
AFM Technique(s) that visualize(s) macromolecules by their topography.
Cryo (single particle cryoelectron microscopy) Technique(s) that yield(s) a low solution 3-D structure by taking many different low quality views of individual protein particles.
2.0A, 3.0A, 4.0A (X-Ray Crystallography) Which resolution is the "highest" resolution?
2.0A, 3.0A, 4.0A (X-Ray Crystallography) Which resolution would give the most accuracy in atomic positions?
2.0A, 3.0A, 4.0A (X-Ray Crystallography) Which resolution would give reliable hydrogen bond distances?
2.0A, 3.0A, 4.0A (X-Ray Crystallography) Which resolution would NOT be sufficient to determine the positions of individual atoms?
2.0A, 3.0A, 4.0A (X-Ray Crystallography) Which resolution should give the lowest FREE R-Factor?
2.0A, 3.0A, 4.0A (X-Ray Crystallography) - Larger density correspond to 4.0A resolution. Tighter density correspond to 2.0A. Three electron density maps for a bound UTP ligand were calculated from each of the data sets. Label the resolution of the data set for each panel.
1-H, 13-C, 31-P, 15-N These isotopes have intrinsic magnetic moments that randomly oriented without magnetic field. With Bo, they tend to align with or against the field according to nuclear spin quantum number (+-1/2).
1-H, 13-C, 31-P, 15-N (Precess frequency: 600 MHZ, 125 MHZ, ?, 60 MHZ At 600 mhz Bo, Match up the precess frequency to these isotopes
Chemical Shift in NMR delta-E depends on Global Environment (External field, Bo), local environment (nearby electrons can modulate external field shielding). Frequency differences is VERY small (1 millionth of resonant freq.)
Chemical Shift in NMR is the resonant frequency of a set of protons relative to standard (usually TMS for protons), measured in ppm of the resonant frequency
Chemical Shift in NMR Characteristic for specific protons on amino acid or nucleotides. Modulated through space by nearby electrons and spin. Dependent on the bonding environment
Chemical Shift in NMR Most shielded are aliphatic (CH4) protons (lowest shift). Shielding decreases with the Proximity to electronegative atoms (higher shifts). Ring systems decrease shielding for atoms at edge, increases for atoms near center.
FT - Fourier Transorm Spectroscopy Excite all freq. simultaneous via short hard pulse. Systems resonate at many different freq. Frequency analyzes to yield component frequencies.
Cosy-Scalar (J) Coupling (A type of interactions btw nuclei...the transfer of magnetization through spin-spin coupling.) Mediated thru overlap of electronic orbitals. "through bond" coupling (atoms 1,2,3 bonds) away are J-coupled. Useful for assigning particular peaks to particular protons and determine covalent structure of the protein molecule.
Dipolar Coupling - NOESY (A type of interactions btw nuclei...the transfer of magnetization through spin-spin coupling.) Results from interaction of dipolar fields of nuclei. "thru space" coupling (within 5 angstom distance, r-6 distance dependence. detect non-covalent structure (folded shape) of molecule.
Uses of NMR Structures, side chains pKa measurements, ligand binding, folding, Dynamics: line-shape analysis and H-D exchanges.
NMR Structure Determination Molecular modeling with energy function. find lowest value of E-total, generate family of structure, resolution is not good as x-ray but better reflection of molecules in-vivo.
NMR Basics Assign all peaks using Cosy. ID all cross peaks btw assigned diagnal peaks on NOESY. Convert NOESY cross-peak to distance constraints btw corresponding protons. find 3D structure that satisfied distance constraint and protein stereochemistry.
Compactness Polymers tend to form spheres due to surface tension. Water forced hydrophobic molecules to burry inside. Main-Chain H-Bondings must be satisfied. Polarity is located on the outside which help maintain solubility.
consequence of unfolding exposed hydrophobic surfaces of thermally unfolded proteins tend to promote intramolecular interactions that form stable insoluble aggregates in which the hydrophobic parts are not in contact with water.
Protein stability The free energy difference btw the folded form of a protein and the ensemble of unfolded states, under a given set of temperature and solvent conditions where the folding of a protein is completely reversible.
Magnitude Protein Stability Depended on conditions such as temperature, salt concentration, pH and other factors. Low pH, salt, and [protein] are needed to prevent irreversible processes (aggregation).
Equilibrium constant for folding Kf=[F]/[U]
unfolded states lack of activity, prone to aggregation, cellular degradation
delta - H (enthalpy) Changes in internal energy of the system, which is the sum of covalent and noncovalent interactions, torsional energies, and bond deformations.
delta - S (Entropy) statistical term that takes into the account the number of possitive states that can be occupied or degrees of freedom. The greater the increase the number of states or degree of freedom, the more positive and more favarable. Hi temp. favors more states.
Hydrophobic Effect Water interaction with non-polar surfaces...
Minimization Generates a model that best agrees with restraints and constraints and is closest to the original model. Model parameters always move towards optimal values.
Complete iteration Calculate all possibilities and score them all to find best.
Simulation Samples configurations by simulating “reasonable” atomic movement based on scoring function
Monte Carlo sampling Randomly sample configurations and determine probability for moving to the new configuration-make moves based on “dice roll”
Genetic algorithm Sparsely sample configurations, identify best subset, expand test set by introducing variation, score, identify best subset, expand, etc.
Scoring Functions Empirically based on observed geometries. “Energy” based on chemistry theory. Agreement with real data (NMR, X-ray, Raman). Ad-hoc function (Energy + empirical terms + data)
Some Common force fields in Computational Biology ENCAD. AMBER (Peter Kollman, UCSF; David Case, Scripps) CHARMM (Martin Karplus, Harvard). OPLS (Bill Jorgensen, Yale). MM2/MM3/MM4 (Norman Allinger, U. Georgia). ECEPP (Harold Scheraga, Cornell). GROMOS (Van Gunsteren, ETH, Zurich)
computational structural biology Essentially the goal is make educated Prediction how a molecule will behave: model biomolecular structures and their behaviors in a realistic way. can be used to - design or guide “wet” design experiments - engineer function or processes
Typical uses of computations 1 Predict the structure of an entire biomolecule or a region (active site) -based on another structure -de novo
Typical uses of computations 2 Predict interactions with ligands -protein/small molecule -protein/protein, RNA, DNA.
Typical uses of computations 3 Predict dynamic behavior -catalysis -binding -folding.
Typical uses of computations WHY? •predict function or properties •engineer structure •find drugs •predict new biologically- relevant interactions *probe potential influences. model for interactions with ligands & Predict dynamic behavior
All applications have similar general computational requirements: identify and evaluate favorable configuration(s) (mechanics) or trajectories (dynamics). Fundamental issue: SPEED vs “ACCURACY”
Energy Functions-Force Fields (Molecule definition) Treated as an object under the influences of forces like those in classical mechanics.
Atomic interactions of force fields vdW interactions - dipole-dipole, dipole-induces dipole, two instanteous dipoles (dispersion forces); Electrostatics interactions - between cations and anions; Accessible Surface Area Potential (hydrophobic potential)
Strong bonded interactions All chemical bonds (2 bodies). Angle between chemical bonds (3 bodies). Preferred conformations for Torsion angles: - ω angle of the main chain - χ angles of the sidechains (aromatic, ...). 4 bodies...
Force fields (FF) BOTTOM LINE: NEVER accurately calculate energies. binding/folding interaction energies are less than 1% of the total energy calculated. too many terms, small errors accumulate
Force fields (FF) BOTTOM LINE 2: Usually further simplified to increase speed. Quantum calculations are too slow and also not accurate. FF an give reasonable relative estimates, eliminate bad configurations. can help pin down critical structural parameters
Statistical Potentials in Force Field Knowledge-based propensities for certain relationships with or between residue types. Can describe distances and/or conformation Can be rapidly calculated. Quality depends on library size. May be poor (weak, overly-specific) constraints
Force Fields Basic When comparing configurations using force field calculations, they should be at their lowest energies => FF are very sensitive to position => energy needs to be first minimized
Molecular Dynamics “Wandering”: on the potential energy surface in a molecule searching for the minimum. kinetic energy terms allow escape from local minima. energy function is constantly changing. constraint to molecule-prevents trapping in false minima
Minimization terative process of making moves towards the function minimum, recalculating direction at every step. finds the local function minimum Parameter shift directions are determined from the derivative (gradient) of the energy function
Homology Modeling Modeling a protein on the framework of another protein with similar sequences (accuracy ~ “0.5-1 Å” in good regions, bad in regions with low similarity)
Threading/Fold recognition Identifying folds based on how compatible a sequence is with the 3-D templates of another protein (accuracy falls off with sequence identity, but fold is often accurately determined even for 5-10% identity
Ab-initio Methods Using “first principles” to simulate folding or sample likely folded states. No similarity required.(Accuracy mixed).
HOMOLOGY MODELLING Steps Identify homolog by sequence comparison: Align sequences. Swap side chains in regions with “good”sequence alignment. Determine side-chain positions. Minimize energy (repeat)
DOCKING Predicting the likely orientations of two interacting molecules based on energetic modeling
Hot Tm the point above Tmax at which the protein is half unfolded.
Cold Tm the point below Tmax at which the protein is half unfolded.
Tmax The temperature of maximum protein stability
Area between Cold Tm and Hot Tm The temperature range where protein folding is favorable.
ii. At temperatures below (B-Cold Tm) what is believed to be the driving force for folding? Intramolecular interactions in the folded state, and the favorable entropy of solvent release from the hydrophobic effect.
iii. At temperatures above (A-Hot Tm) what is believed to be the driving force for folding? Intramolecular interactions in the folded state, and the favorable enthalpy change on burying hydrophobic groups- that hydrophobic water has poorer interactions than in liquid water, and the entropy of water release.
Created by: 100002158790713