Biomaterial Database

Coupled prediction of protein secondary and tertiary structure. 2003

Jens Meiler, and David Baker

Department of Biochemistry, University of Washington, Box 357350, Seattle, WA 98195-7350, USA.

The strong coupling between secondary and tertiary structure formation in protein folding is neglected in most structure prediction methods. In this work we investigate the extent to which nonlocal interactions in predicted tertiary structures can be used to improve secondary structure prediction. The architecture of a neural network for secondary structure prediction that utilizes multiple sequence alignments was extended to accept low-resolution nonlocal tertiary structure information as an additional input. By using this modified network, together with tertiary structure information from native structures, the Q3-prediction accuracy is increased by 7-10% on average and by up to 35% in individual cases for independent test data. By using tertiary structure information from models generated with the ROSETTA de novo tertiary structure prediction method, the Q3-prediction accuracy is improved by 4-5% on average for small and medium-sized single-domain proteins. Analysis of proteins with particularly large improvements in secondary structure prediction using tertiary structure information provides insight into the feedback from tertiary to secondary structure.

UI	MeSH Term	Description	Entries
D008958	Models, Molecular	Models used experimentally or theoretically to study molecular shape, electronic properties, or interactions; includes analogous molecules, computer-generated graphics, and mechanical structures.	Molecular Models,Model, Molecular,Molecular Model
D011506	Proteins	Linear POLYPEPTIDES that are synthesized on RIBOSOMES and may be further modified, crosslinked, cleaved, or assembled into complex proteins with several subunits. The specific sequence of AMINO ACIDS determines the shape the polypeptide will take, during PROTEIN FOLDING, and the function of the protein.	Gene Products, Protein,Gene Proteins,Protein,Protein Gene Products,Proteins, Gene
D003198	Computer Simulation	Computer-based representation of physical systems and phenomena such as chemical processes.	Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D017433	Protein Structure, Secondary	The level of protein structure in which regular hydrogen-bond interactions within contiguous stretches of polypeptide chain give rise to ALPHA-HELICES; BETA-STRANDS (which align to form BETA-SHEETS), or other types of coils. This is the first folding level of protein conformation.	Secondary Protein Structure,Protein Structures, Secondary,Secondary Protein Structures,Structure, Secondary Protein,Structures, Secondary Protein
D017434	Protein Structure, Tertiary	The level of protein structure in which combinations of secondary protein structures (ALPHA HELICES; BETA SHEETS; loop regions, and AMINO ACID MOTIFS) pack together to form folded shapes. Disulfide bridges between cysteines in two different parts of the polypeptide chain along with other interactions between the chains play a role in the formation and stabilization of tertiary structure.	Tertiary Protein Structure,Protein Structures, Tertiary,Tertiary Protein Structures
D017510	Protein Folding	Processes involved in the formation of TERTIARY PROTEIN STRUCTURE.	Protein Folding, Globular,Folding, Globular Protein,Folding, Protein,Foldings, Globular Protein,Foldings, Protein,Globular Protein Folding,Globular Protein Foldings,Protein Foldings,Protein Foldings, Globular