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The Protein Folding Problem Bionanotechnology Protein folding is “one of the great unsolved problems of science” Alan Fersht protein folding can be seen as a connection between the genome (sequence) and what the proteins actually do (their function). Protein folding problem ● ● Prediction of three dimensional structure from its amino acid sequence Translate “Linear” DNA Sequence data to spatial information Why solve the folding problem? ● ● ● Acquisition of sequence data relatively quick Acquisition of experimental structural information slow Limited to proteins that crystallize or stable in solution for NMR Protein folding dynamics Electrostatics, hydrogen bonds and van der Waals forces hold a protein together. Hydrophobic effects force global protein conformation. Peptide chains can be cross-linked by disulfides, Zinc, heme or other liganding compounds. Zinc has a complete d orbital , one stable oxidation state and forms ligands with sulfur, nitrogen and oxygen. Proteins refold very rapidly and generally in only one stable conformation. Random search and the Levinthal paradox ● The initial stages of folding must be nearly random, but if the entire process was a random search it would require too much time. Consider a 100 residue protein. If each residue is considered to have just 3 possible conformations the total number of conformations of the protein is 3100. Conformational changes occur on a time scale of 10-13 seconds i.e. the time required to sample all possible conformations would be 3100 x 10-13 seconds which is about 1027 years. Even if a significant proportion of these conformations are sterically disallowed the folding time would still be astronomical. Proteins are known to fold on a time scale of seconds to minutes and hence energy barriers probably cause the protein to fold along a definite pathway. Physical nature of protein folding ● ● Denatured protein makes many interactions with the solvent water During folding transition exchanges these noncovalent interactions with others it makes with itself What happens if proteins don't fold correctly? ● Diseases such as Alzheimer's disease, cystic fibrosis, Mad Cow disease, an inherited form of emphysema, and even many cancers are believed to result from protein misfolding Protein folding is a balance of forces ● Proteins are only marginally stable ● Free energies of unfolding ~5-15 kcal/mol ● ● The protein fold depends on the summation of all interaction energies between any two individual atoms in the native state Also depends on interactions that individual atoms make with water in the denatured state Protein denaturation ● Can be denatured depending on chemical environment – Heat – Chemical denaturant – pH – High pressure The Protein Folding Folding Problem The Protein Problem A major hurdle must be crossed before bionanotechnology will have general applicability: We must be able to predict the folded structure of a protein starting only with its chemical sequence. Without this ability, we will merely shadow evolution, poking and prodding existing proteins until they are changed into something that we want. The Protein Folding Problem The protein folding problem poses grave difficulties for two reasons. 1. The first is the sheer magnitude of the problem. Typical proteins have several hundred amino acids. Each is connected to its neighbors through two flexible linkages that may adopt a range of stable conformations. In addition, each amino acid has a flexible side chain that can adopt a number of stable local conformations. Together, these many levels of torsional freedom define a staggeringly large conformational space that is beyond all current computational prediction methods. The Protein Folding Problem The protein folding problem poses grave difficulties for two reasons. 2. The second problem lies in the method used to estimate the stability of each trial conformation during a prediction experiment. Folded proteins have thousands of internal contacts, each of which adds a tiny increment of stabilization to the entire structure. The Protein Folding Problem The protein folding problem poses grave difficulties for two reasons. 2. Many water molecules are freed as proteins fold, as the protein chains shelter their carbon-rich portions inside. This freeing of water is a strong force pushing proteins toward a folded structure. Entropy, on the other hand, works against the favorable energies of internal contacts and water release. Protein Structure Prediction ● ● ● Why ? Type of protein structure predictions – Sec Str. Pred – Homology Modelling – Fold Recognition – Ab Initio Secondary structure prediction – Why – History – Performance – Usefullness Why do we need structure prediction? ● 3D structure give clues to function: – active sites, binding sites, conformational changes... – structure and function conserved more than sequence – 3D structure determination is difficult, slow and expensive – Intellectual challenge, Nobel prizes etc... – Engineering new proteins The Use of Structure The Use of Structure The Use of Structure It's not that simple... ● ● ● Amino acid sequence contains all the information for 3D structure (experiments of Anfinsen, 1970's) But, there are thousands of atoms, rotatable bonds, solvent and other molecules to deal with... Levinthal's paradox Structure prediction Summary of the four main approaches to structure prediction. Note that there are overlaps between nearly all categories. Approac h Difficulty Usefulness Compar ative Proteins of modelling known (Homolog y structure modelling) Identify related structure with sequence methods, copy 3D coords and modi fy where necessary Relatively easy Very, if sequence identity drug design Fold recognition Proteins of known structure Same as above, but use more sophisticated methods to find related structure Medium Limited due to poor models Secondary structure prediction Sequencestructure statistics Forget 3D arrangeme nt and Medium predict where the helices/strands are Can improve align ments, fold recognition, ab initio ab initio tertiary structure prediction Energy functions, statistics Simulat e folding, or generate lots Very hard of structures and try to pick the correct one Not really Method Knowledge Secondary structure predictions ● Ignore 3D, it's too hard! ● Usually concentrate on helix, strand and ``coil''. Pattern recognition, but which patterns? – ● ● ● ● some amino acids have preferences for helix or strand; due to geometry and hydrogen bonding spatial (along sequence) patterns, alternating hydrophobics (helical wheel) conservation (down alignment) in different members of protein family; insertions and deletions Three main generations/stages in SSP method development since 1970's. What is ``known secondary structure''? ● Of critical importance in training/assessment of SSP methods ● Can be defined: ● visually by structural biologist ● by geometric and chemical criteria (, angles, distances between atoms, hydrogen bonds...) by programs like DSSP and STRIDE Secondary structures -Helix Secondary Structure - Sheet Secondary structure - turns Other secondary structure prediction methods ● turn prediction ● transmembrane helix prediction ● coiled coil ● Dissorder predictions ● contact prediction, disulphides What use is it? ● ● ● No 3D means no clues to detailed function, so... Accurate secondary structure predictions help sequence analysis: finding homologues, aligning homologues, identifying domain boundaries. Can help true 3D prediction Future improvements to SSP ● Long range information – ● Baker Folding pathway and/or 3D-information