Presentation is loading. Please wait.

Presentation is loading. Please wait.

Protein Structure Prediction. Why do we want to know protein structure? Classification Functional Prediction.

Similar presentations


Presentation on theme: "Protein Structure Prediction. Why do we want to know protein structure? Classification Functional Prediction."— Presentation transcript:

1 Protein Structure Prediction

2 Why do we want to know protein structure? Classification Functional Prediction

3 What is protein structure? Primary - chains of amino acids Secondary - interaction between groups of amino acids Tertiary - the organization in three dimensions of all the atoms in a polypeptide Quaternary - the conformation assumed by a multimeric protein

4 Proteins are chains of amino acids joined by peptide bonds The N-C-C sequence is repeated throughout the protein, forming the backbone The bonds on each side of the C atom are free to rotate within spatial constrains, the angles of these bonds determine the conformation of the protein backbone The R side chains also play an important structural role Polypeptide chain The structure of two amid acids Primary Structure

5 Interactions that occur between the C=O and N-H groups on amino acids Much of the protein core comprises  helices and  sheets, folded into a three- dimensional configuration: - regular patterns of H bonds are formed between neighboring amino acids - the amino acids have similar angles - the formation of these structures neutralizes the polar groups on each amino acid - the secondary structures are tightly packed in a hydrophobic environment - Each R side group has a limited volume to occupy and a limited number of interactions with other R side groups  helix  sheet Secondary Structure

6  helix  sheet Secondary Structure

7 Other Secondary structure elements (no standardized classification) - loop - random coil - others (e.g helix, -hairpin, paperclip) Super-secondary structure - In addition to secondary structure elements that apply to all proteins (e.g. helix, sheet) there are some simple structural motifs in some proteins - These super-secondary structures (e.g. transmembrane domains, coiled coils, helix-turn-helix, signal peptides) can give important hints about protein function Secondary Structure

8 Structural classification of proteins (SCOP) Class 1: mainly alpha Class 4: few secondary structures Class 2: mainly beta Class 3: alpha/beta Classification

9 Alternative SCOP Class  : only  helices Class  : antiparallel  sheetsClass  /  : mainly  sheets with intervening  helices Class  +  : mainly segregated  helices with antiparallel  sheets Membrane structure: hydrophobic  helices with membrane bilayers Multidomain: contain more than one class More Classification

10 Q: If we have all the Psi and Phi angles in a protein, do we then have enough information to describe the 3-D structure? Tertiary structure A: No, because the detailed packing of the amino acid side chains is not revealed from this information. However, the Psi and Phi angles do determine the entire secondary structure of a protein Protein Structure Review

11 Secondary-Structure Prediction Programs * PSI-pred * JPRED Consensus prediction (includes many of the methods given below)JPRED * DSC * PREDATOR * PHD * ZPRED * nnPredict * BMERC PSA * SSP

12 The tertiary structure describes the organization in three dimensions of all the atoms in the polypeptide The tertiary structure is determined by a combination of different types of bonding (covalent bonds, ionic bonds, h-bonding, hydrophobic interactions, Van der Waal’s forces) between the side chains Many of these bonds are very week and easy to break, but hundreds or thousands working together give the protein structure great stability If a protein consists of only one polypeptide chain, this level then describes the complete structure Tertiary Structure

13 Proteins can be divided into two general classes based on their tertiary structure: - Fibrous proteins have elongated structure with the polypeptide chains arranged in long strands. This class of proteins serves as major structural component of cells Examples: silk, keratin, collagen - Globular proteins have more compact, often irregular structures. This class of proteins includes most enzymes and most proteins involved in gene expression and regulation Tertiary Structure

14 The quaternary structure defines the conformation assumed by a multimeric protein. The individual polypeptide chains that make up a multimeric protein are often referred to as protein subunits. Subunits are joined by ionic, H and hydrophobic interactions Example: Haemoglobin (4 subunits) Quaternary Structures

15 Common displays are (among others) cartoon, spacefill, and backbone cartoon spacefill backbone Structure Displays

16 Software RasMol Cn3D Jmol (Chime)

17 Classic Approach to Determining Structure? Determine biochemical and cellular role of protein Purify protein Experimentally determine 3D structure Clone cDNA encoding protein Obtain protein By expression Infer function, mechanism of action

18 Structural Genomics Approach? genomic DNA sequences predict protein- coding genes Obtain protein by expression Obtain protein In silico Experimentally determine 3D structure Predict 3D structure Determine biochemical and cellular role of protein homology searches (PSI-BLAST)

19 3-D macromolecular structures stored in databases The most important database: the Protein Data Bank (PDB) The PDB is maintained by the Research Collaboratory for Structural Bioinformatics (RCSB) and can be accessed at three different sites (plus a number of mirror sites outside the USA): - (Rutgers University) - (San Diego Supercomputer Center) - (National Institute for Standards and Technology) It is the very first “bioinformatics” database ever build Sources of Protein Structure Information?

20 Researches have been working for decades to develop procedures for predicting protein structure that are not so time consuming and not hindered by size and solubility constrains. As protein sequences are encoded in DNA, in principle, it should therefore be possible to translate a gene sequence into an amino acid sequence, and to predict the three-dimensional structure of the resulting chain from this amino acid sequence Computational Modeling Structural Prediction

21 How to predict the protein structure? Ab initio prediction of protein structure from sequence: not yet. Problem: the information contained in protein structures lies essentially in the conformational torsion angles. Even if we only assume that every amino-acid residue has three such torsion angles, and that each of these three can only assume one of three "ideal" values (e.g., 60, 180 and -60 degrees), this still leaves us with 27 possible conformations per residue. For a typical 200-amino acid protein, this would give (roughly 1.87 x ) possible conformations! If we were able to evaluate 10 9 conformations per second, this would still keep us busy 4 x times the current age of the universe There are optimized ab initio prediction algorithms available as well as fold recognition algorithms that use threading (compares protein folds with know fold structures from databases), but the results are still very poor Q: Can’t we just generate all these conformations, calculate their energy and see which conformation has the lowest energy? Computational Modeling

22 Homology (comparative) modeling attempts to predict structure on the strength of a protein’s sequence similarity to another protein of known structure Basic idea: a significant alignment of the query sequence with a target sequence from PDB is evidence that the query sequence has a similar 3-D structure (current threshold ~ 40% sequence identity). Then multiple sequence alignment and pattern analysis can be used to predict the structure of the protein Homology Modeling

23 Computational modeling: summary Partial or full sequences predicted through gene finding Similarity search against proteins in PDB Alignment can be used to position the amino acids of the query sequence in the same approximate 3-D structure Find structures that have a significant level of structural similarity (but not necessarily significant sequence similarity) If member of a family with a predicted structural fold, multiple alignment can be used for structural modeling Infer structural information (e.g. presence of small amino acid motifs; spacing and arrangement of amino acids; certain typical amino acid combinations associated with certain types of secondary structure) can provide clues as to the presence of active sites and regions of secondary structure Structural analyses in the lab (X-ray crystallography, NMR) How do we do this?

24 3D Comparative Modeling Profile Methods - match sequences to folds by describing each fold in terms of the environment of each residue in the structure Threading Methods - match sequences to structure by considering pairwise interactions for each residue, rather than averaging them into an environmental class HMM Methods - the equivalent state corresponds to one structurally aligned position in a structural fold, including gaps

25 Structural HMM


Download ppt "Protein Structure Prediction. Why do we want to know protein structure? Classification Functional Prediction."

Similar presentations


Ads by Google