Dataset Information

Associative memory Hamiltonians for structure prediction without homology: alpha/beta proteins.

ABSTRACT: We describe a method for predicting the structure of alpha beta class proteins in the absence of information from homologous structures. The method is based on an associative memory model for short to intermediate range in sequence contacts and a contact potential for long range in sequence contacts. The coefficients in the energy function are chosen to maximize the ratio of the folding temperature to the glass transition temperature. We use the resulting optimized model to predict the structure of three alpha beta protein domains ranging in length from 81 to 115 residues. The resulting predictions align with low rms deviations to large portions of the native state. We have also calculated the free energy as a function of similarity to the native state for one of these three domains, and we show that, as expected from the optimization criteria, the free energy surface resembles a rough funnel to the native state. Finally, we briefly demonstrate the effect of roughness in the energy landscape on the dynamics.

SUBMITTER: Hardin C

PROVIDER: S-EPMC149892 | biostudies-literature | 2003 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Associative memory Hamiltonians for structure prediction without homology: alpha/beta proteins.

Hardin Corey C Eastwood Michael P MP Prentiss Michael C MC Luthey-Schulten Zadia Z Wolynes Peter G PG

Proceedings of the National Academy of Sciences of the United States of America 20030128 4

We describe a method for predicting the structure of alpha beta class proteins in the absence of information from homologous structures. The method is based on an associative memory model for short to intermediate range in sequence contacts and a contact potential for long range in sequence contacts. The coefficients in the energy function are chosen to maximize the ratio of the folding temperature to the glass transition temperature. We use the resulting optimized model to predict the structure ...[more]

PMID: 12554830

Similar Datasets

Project description:BACKGROUND: Automated function prediction has played a central role in determining the biological functions of bacterial proteins. Typically, protein function annotation relies on homology, and function is inferred from other proteins with similar sequences. This approach has become popular in bacterial genomics because it is one of the few methods that is practical for large datasets and because it does not require additional functional genomics experiments. However, the existing solutions produce erroneous predictions in many cases, especially when query sequences have low levels of identity with the annotated source protein. This problem has created a pressing need for improvements in homology-based annotation. RESULTS: We present an automated method for the functional annotation of bacterial protein sequences. Based on sequence similarity searches, BLANNOTATOR accurately annotates query sequences with one-line summary descriptions of protein function. It groups sequences identified by BLAST into subsets according to their annotation and bases its prediction on a set of sequences with consistent functional information. We show the results of BLANNOTATOR's performance in sets of bacterial proteins with known functions. We simulated the annotation process for 3090 SWISS-PROT proteins using a database in its state preceding the functional characterisation of the query protein. For this dataset, our method outperformed the five others that we tested, and the improved performance was maintained even in the absence of highly related sequence hits. We further demonstrate the value of our tool by analysing the putative proteome of Lactobacillus crispatus strain ST1. CONCLUSIONS: BLANNOTATOR is an accurate method for bacterial protein function prediction. It is practical for genome-scale data and does not require pre-existing sequence clustering; thus, this method suits the needs of bacterial genome and metagenome researchers. The method and a web-server are available at http://ekhidna.biocenter.helsinki.fi/poxo/blannotator/.

Project description:The thermodynamic hypothesis of Anfinsen postulates that structures and stabilities of globular proteins are determined by their amino acid sequences. Chain topology, however, is known to influence the folding reaction, in that motifs with a preponderance of local interactions typically fold more rapidly than those with a larger fraction of nonlocal interactions. Together, the topology and sequence can modulate the energy landscape and influence the rate at which the protein folds to the native conformation. To explore the relationship of sequence and topology in the folding of beta alpha-repeat proteins, which are dominated by local interactions, we performed a combined experimental and simulation analysis on two members of the flavodoxin-like, alpha/beta/alpha sandwich fold. Spo0F and the N-terminal receiver domain of NtrC (NT-NtrC) have similar topologies but low sequence identity, enabling a test of the effects of sequence on folding. Experimental results demonstrated that both response-regulator proteins fold via parallel channels through highly structured submillisecond intermediates before accessing their cis prolyl peptide bond-containing native conformations. Global analysis of the experimental results preferentially places these intermediates off the productive folding pathway. Sequence-sensitive G?-model simulations conclude that frustration in the folding in Spo0F, corresponding to the appearance of the off-pathway intermediate, reflects competition for intra-subdomain van der Waals contacts between its N- and C-terminal subdomains. The extent of transient, premature structure appears to correlate with the number of isoleucine, leucine, and valine (ILV) side chains that form a large sequence-local cluster involving the central beta-sheet and helices alpha2, alpha 3, and alpha 4. The failure to detect the off-pathway species in the simulations of NT-NtrC may reflect the reduced number of ILV side chains in its corresponding hydrophobic cluster. The location of the hydrophobic clusters in the structure may also be related to the differing functional properties of these response regulators. Comparison with the results of previous experimental and simulation analyses on the homologous CheY argues that prematurely folded unproductive intermediates are a common property of the beta alpha-repeat motif.

Dataset Information

Associative memory Hamiltonians for structure prediction without homology: alpha/beta proteins.

Publications

Associative memory Hamiltonians for structure prediction without homology: alpha/beta proteins.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure