BMC Bioinformatics 2005, 6(Suppl 4):S3 Protein Structure Prediction not a trivial matter Strict relation between protein function and structure Gap between known sequences and known tertiary structures is constantly increasing There is a need for automatic methods General methodology able to solve the problem has not yet been devised

Protein Structure Prediction not a trivial matter Protein structure prediction is a very difficult task Why?

Protein Structure Prediction not a trivial matter Complex interactions exist between intra- molecular atoms and between the protein and the surrounding environment. Number of interactions to track increases exponentially with molecule size The number of possible structures that proteins may possess is extremely large

Protein Structure Prediction not a trivial matter The physical basis of protein structural stability is not fully understood The primary sequence may not fully specify the tertiary structure (chaperones have the ability to induce proteins to fold in specific ways)

Protein Structure Prediction not a trivial matter Direct simulation of protein folding via methods such as molecular dynamics is not generally reliable for both practical and theoretical reasons Distributed computing projects are tackling such simulation difficulties

Protein Structure Prediction not a trivial matter Distributed computing projects: (Stanford University's Chemistry Department ) (Scripps Research Institute ) –Human Proteome Folding Project (part of World Community Grid run by IBM)

Protein Structure Prediction not a trivial matter Goal of protein structure prediction is to determine the 3D structure of proteins from their amino acid sequence Some approaches: –Comparative Protein Modeling: uses previously solved structures as starting points

Protein Structure Prediction not a trivial matter Comparative Protein Modeling: 2 methods –homology modeling –protein threading 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 of the unknown sequence (target sequence) to the known structure (template)

Protein Structure Prediction not a trivial matter Homology Modeling –Facilitated by the fact that 3D structure of proteins from the same family is more conserved than their primary sequences –Example: human hemoglobin and leghemoglobin (hemoglobin in legumes) If proteins are similar at the sequence level then structural similarity can usually be assumed

Protein Structure Prediction not a trivial matter Predicting structure from scratch –De novo structure prediction (or ab initio structure prediction) –Requires vast computational resources –Uses stochastic methods to search possible solutions –Finding the structure with the lowest free energy is the key element of this approach

Protein Structure Prediction not a trivial matter Distributed computing –Human Proteome Folding Project Employs the unused CPU cycles of personal computers worldwide to analyze scientific data

Protein Structure Prediction not a trivial matter Computational simulations of model proteins –most proteins are too large for current technology to simulate folding on an atom by atom basis –lattice proteins: highly simplified computer models of proteins, amino acid sequence behaves like a single functional unit (a bead)