1. What is Protein Folding? Implications of Misfolding Computational Techniques Background image: Staphylococcal protein A, Z Domain (http://www-nmr.cabm.rutgers.edu/photogallery/structures/html/page16.html) http://en.wikipedia.org/wiki/Prion http://www.faseb.org/opar/protfold/fundstru.html http://faq.distributed.net/bags/compute-cluster.png Proteins are a sequence of unbranched amino acids, which make the protein unique. If folded wrongly, they do not function properly and can cause human and animal diseases. Protein folding is the process in which and amino acid sequence assumes a functional three dimensional structure by folding and coiling. There are four protein structures: Two possible tertiary structures: Protein in α-helix structure Protein in β-sheet structure Two conformations of PrP (Prion): Left: normal PrP C Right: proposed model of abnormal PrP Sc Primary structure: Secondary structure: Tertiary structure: Quaternary structure:  The amino acid sequence of a protein  Codes for its Native confirmation  Consists of α-helices and β-sheets  Necessary to obtain tertiary structure  Native confirmation of the protein  Held together by covalent bonds between two cysteine residues and electrostatic interactions  Final assemblage  Overall structure consisting of several folded proteins Formation of helices and sheets Actual folding process optional Misfolding of proteins can cause a variety of diseases: Human: Animal:  Creutzfeld-Jakob Disease (CJD)  Cystic Fibrosis  Alzheimer’s Disease  many cancers  Mad Cow Disease  Bovine Spongiform Encephalopathy CJD and Mad Cow Disease are caused by the misfolding of Prion. Protein Structure Prediction Distributed Computing: Query from a single computer using resources from other computers and providing the results. Distributed Computing Projects Distributed computing projects use computing resources banded together throughout the world. Everyone can participate by downloading and installing the corresponding software and providing the own unused CPU cycles to the network.  Folding@home : - By Stanford University’s Chemistry Department - Second largest distributed computing project after SETI@home (searching for extraterrestrial intelligence) - Perform computationally intensive simulations of protein folding - Aims to study the dynamics of protein folding - Uses own networking infrastructure, but makes transition to BOINC - Results are made publicly available  Predictor@home: - By Scripps Research Institute - perform computationally intensive simulations of protein folding - Aims to specify what the tertiary structure of a protein will be - Based on BOINC (Berkeley Open Infrastructure for Network Computing, originally designed for SETI@home)  Human Proteome Folding Project: - Part of World Community Grid: Largest public computing grid Run by IBM Supports many different humanitarian projects Several computing techniques to simplify and study the folding of proteins have been developed. Here are the most important examples, some utilize others. http://www.bio.davidson.edu/Courses/Molbio/MolStudents/spring2003/Kogoy/protein.html Background image: Staphylococcal protein A, Z Domain (http://www-nmr.cabm.rutgers.edu/photogallery/structures/html/page16.html) Computational Simulations of Model Proteins: The Lattice Model - Lattice proteins are highly simplified models of proteins - Amino Acid sequence behave like single functional units - Molecule folds to its least energy consuming state Cartoon of a hypothetical crystalline lattice The goal is to predict three-dimensional structure of proteins from an amino acid sequence.  Comparative Protein Modeling : - Uses previously solved structures as starting points - In nature there are about 2000 distinct protein folding motifs that can be used as templates - Two approaches: Homology Modeling and Protein Threading - Homology Modeling: Based on the assumption that two homologous protein will share very similar structures Given a solved amino acid structure from a homologous protein, it is mutated into the unsolved structure - Protein Threading: Scans the amino acid sequence of an unknown structure against a database of solved structures A scoring function is used to assess the compatibility  De Novo Structure Prediction: - Tries to establish three-dimensional protein structure from scratch - Requires vast computational resources - Based on stochastic methods to search possible solutions - Requires supercomputers or distributed computing Blake BolingTamara Schneider