Biomedical subjects

C Bystroff

Publications and source records attributed to C Bystroff.

12 recordsLinked to original sources

PubMed2000

HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins.

We describe a hidden Markov model, HMMSTR, for general protein sequence based on the I-sites library of sequence-structure motifs. Unlike the linear hidden Markov models used to model individual protein families, HMMSTR has a highly branched topology and captures recurrent local features of protein sequences and structures that transcend protein family boundaries. The model extends the I-sites library by describing the adjacencies of different sequence-structure motifs as observed in the protein database and, by representing overlapping motifs in a much more compact form, achieves a great reduction in parameters. The HMM attributes a considerably higher probability to coding sequence than does an equivalent dipeptide model, predicts secondary structure with an accuracy of 74.3 %, backbone torsion angles better than any previously reported method and the structural context of beta strands and turns with an accuracy that should be useful for tertiary structure prediction.

Amino Acid Motifs↗

PubMed1999

Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins.

We describe the development of a scoring function based on the decomposition P(structure/sequence) proportional to P(sequence/structure) *P(structure), which outperforms previous scoring functions in correctly identifying native-like protein structures in large ensembles of compact decoys. The first term captures sequence-dependent features of protein structures, such as the burial of hydrophobic residues in the core, the second term, universal sequence-independent features, such as the assembly of beta-strands into beta-sheets. The efficacies of a wide variety of sequence-dependent and sequence-independent features of protein structures for recognizing native-like structures were systematically evaluated using ensembles of approximately 30,000 compact conformations with fixed secondary structure for each of 17 small protein domains. The best results were obtained using a core scoring function with P(sequence/structure) parameterized similarly to our previous work (Simons et al., J Mol Biol 1997;268:209-225] and P(structure) focused on secondary structure packing preferences; while several additional features had some discriminatory power on their own, they did not provide any additional discriminatory power when combined with the core scoring function. Our results, on both the training set and the independent decoy set of Park and Levitt (J Mol Biol 1996;258:367-392), suggest that this scoring function should contribute to the prediction of tertiary structure from knowledge of sequence and secondary structure.

Models, Statistical↗

PubMed1998

Prediction of local structure in proteins using a library of sequence-structure motifs.

We describe a new method for local protein structure prediction based on a library of short sequence pattern that correlate strongly with protein three-dimensional structural elements. The library was generated using an automated method for finding correlations between protein sequence and local structure, and contains most previously described local sequence-structure correlations as well as new relationships, including a diverging type-II beta-turn, a frayed helix, and a proline-terminated helix. The query sequence is scanned for segments 7 to 19 residues in length that strongly match one of the 82 patterns in the library. Matching segments are assigned the three-dimensional structure characteristic of the corresponding sequence pattern, and backbone torsion angles for the entire query sequence are then predicted by piecing together mutually compatible segment predictions. In predictions of local structure in a test set of 55 proteins, about 50% of all residues, and 76% of residues covered by high-confidence predictions, were found in eight-residue segments within 1.4 A of their true structures. The predictions are complementary to traditional secondary structure predictions because they are considerably more specific in turn regions, and may contribute to ab initio tertiary structure prediction and fold recognition.

Algorithms↗

PubMed1998

Prediction and structural characterization of an independently folding substructure in the src SH3 domain.

Previous studies of the conformations of peptides spanning the length of the alpha-spectrin SH3 domain suggested that SH3 domains lack independently folding substructures. Using a local structure prediction method based on the I-sites library of sequence-structure motifs, we identified a seven residue peptide in the src SH3 domain predicted to adopt a native-like structure, a type II beta-turn bridging unpaired beta-strands, that was not contained intact in any of the SH3 domain peptides studied earlier. NMR characterization confirmed that the isolated peptide, FKKGERL, adopts a structure similar to that adopted in the native protein: the NOE and 3JNHalpha coupling constant patterns were indicative of a type II beta-turn, and NOEs between the Phe and the Leu side-chains suggest that they are juxtaposed as in the prediction and the native structure. These results support the idea that high-confidence I-sites predictions identify protein segments that are likely to form native-like structures early in folding.

Amino Acid Sequence↗

PubMed1997

Blind predictions of local protein structure in CASP2 targets using the I-sites library.

Blind predictions of the local structure of nine CASP2 targets were made using the I-sites library of short sequence--structure motifs, revealing strengths and weaknesses in this new knowledge-based method. Many turns between secondary structural elements were accurately predicted. Estimates of the confidence of prediction correlated well with the accuracy over the whole set. Bias toward structures used to develop the library was minimal, probably because of the extensive use of cross-validation. However, helix positions were better predicted by the PHD program. The method is likely to be sensitive to the quality of the sequence alignment. A general measure for evaluating local structure predictions is suggested.

Binding Sites↗

PubMed1997

Three-dimensional structures and contexts associated with recurrent amino acid sequence patterns.

We have used cluster analysis to identify recurring sequence patterns that transcend protein family boundaries. A subset of these patterns occur predominantly in a single type of local structure in proteins. Here we characterize the three-dimensional structures and contexts in which these sequence patterns occur, with particular attention to the interactions responsible for their structural selectivity.

Algorithms↗

PubMed1996

Local sequence-structure correlations in proteins.

Considerable progress has been made in understanding the relationship between local amino acid sequence and local protein structure. Recent highlights include numerous studies of the structures adopted by short peptides, new approaches to correlating sequence patterns with structure patterns, and folding simulations using simple potentials.

Amino Acid Sequence↗

PubMed1994

Macromolecular chelation as an improved mechanism of protease inhibition: structure of the ecotin-trypsin complex.

The 2.4 A crystal structure (R = 0.180) of the serine protease inhibitor ecotin was determined in a complex with trypsin. Ecotin's dimer structure provides a second discrete and distal binding site for trypsin and, as shown by modelling experiments, other serine proteases. The second site is approximately 45 A from the reactive/active site of the complex and features 13 hydrogen bonds, including six that involve carbonyl oxygen atoms and four bridged by water molecules. Contacts ecotin makes with trypsin's active site are similar to, though more extensive than, those found between trypsin and basic pancreatic trypsin inhibitor. The side chain of ecotin Met84 is found in the substrate binding pocket of trypsin where it makes few contacts, but also does not disrupt the solvent structure or cause misalignment of the scissile bond. This first case of protein dimerization being used to augment binding energy and allow chelation of a target protein provides a new model for protein-protein interactions and for protease inhibition.

Bacterial Proteins↗

PubMed1992

The crystal structure of the Bacillus lentus alkaline protease, subtilisin BL, at 1.4 A resolution.

The crystal structure of subtilisin BL, an alkaline protease from Bacillus lentus with activity at pH 11, has been determined to 1.4 A resolution. The structure was solved by molecular replacement starting with the 2.1 A structure of subtilisin BPN' followed by molecular dynamics refinement using X-PLOR. A final crystallographic R-factor of 19% overall was obtained. The enzyme possesses stability at high pH, which is a result of the high pI of the protein. Almost all of the acidic side-chains are involved in some type of electrostatic interaction (ion pairs, calcium binding, etc.). Furthermore, three of seven tyrosine residues have potential partners for forming salt bridges. All of the potential partners are arginine with a pK around 12. Lysine would not function well in a salt bridge with tyrosine as it deprotonates at around the same pH as tyrosine ionizes. Stability at high pH is acquired in part from the pI of the protein, but also from the formation of salt bridges (which would affect the pI). The overall structure of the enzyme is very similar to other subtilisins and shows that the subtilisin fold is more highly conserved than would be expected from the differences in amino acid sequence. The amino acid side-chains in the hydrophobic core are not conserved, though the inter-residue interactions are. Finally, one third of the serine side-chains in the protein have multiple conformations. This presents an opportunity to correlate computer simulations with observed occupancies in the crystal structure.

Amino Acid Sequence↗

PubMed1991

Crystal structure of unliganded Escherichia coli dihydrofolate reductase. Ligand-induced conformational changes and cooperativity in binding.

The crystal structure of unliganded dihydrofolate reductase (DHFR) from Escherichia coli has been solved and refined to an R factor of 19% at 2.3-A resolution in a crystal form that is nonisomorphous with each of the previously reported E. coli DHFR crystal structures [Bolin, J. T., Filman, D. J., Matthews, D. A., Hamlin, B. C., & Kraut, J. (1982) J. Biol. Chem. 257, 13650-13662; Bystroff, C., Oatley, S. J., & Kraut, J. (1990) Biochemistry 29, 3263-3277]. Significant conformational changes occur between the apoenzyme and each of the complexes: the NADP+ holoenzyme, the folate-NADP+ ternary complex, and the methotrexate (MTX) binary complex. The changes are small, with the largest about 3 A and most of them less than 1 A. For simplicity a two-domain description is adopted in which one domain contains the NADP+ 2'-phosphate binding site and the binding sites for the rest of the coenzyme and for the substrate lie between the two domains. Binding of either NADP+ or MTX induces a closing of the PABG-binding cleft and realignment of alpha-helices C and F which bind the pyrophosphate of the coenzyme. Formation of the ternary complex from the holoenzyme does not involve further relative domain shifts but does involve a shift of alpha-helix B and a floppy loop (the Met-20 loop) that precedes alpha B. These observations suggest a mechanism for cooperativity in binding between substrate and coenzyme wherein the greatest degree of cooperativity is expressed in the transition-state complex. We explore the idea that the MTX binary complex in some ways resembles the transition-state complex.

Amino Acid Sequence↗

PubMed1990

Crystal structures of Escherichia coli dihydrofolate reductase: the NADP+ holoenzyme and the folate.NADP+ ternary complex. Substrate binding and a model for the transition state.

The crystal structure of dihydrofolate reductase (EC 1.5.1.3) from Escherichia coli has been solved as the binary complex with NADP+ (the holoenzyme) and as the ternary complex with NADP+ and folate. The Bragg law resolutions of the structures are 2.4 and 2.5 A, respectively. The new crystal forms are nonisomorphous with each other and with the methotrexate binary complex reported earlier [Bolin, J. T., Filman, D. J., Matthews, D. A., Hamlin, R. C., & Kraut, J. (1982) J. Biol. Chem. 257, 13650-13662]. In general, NADP+ and folate binding conform to predictions, but the nicotinamide moiety of NADP+ is disordered in the holoenzyme and ordered in the ternary complex. A mobile loop (residues 16-20) involved in binding the nicotinamide is also disordered in the holoenzyme. We report a detailed analysis of the binding interactions for both ligands, paying special attention to several apparently strained interactions that may favor the transition state for hydride transfer. Hypothetical models are presented for the binding of 7,8-dihydrofolate in the Michaelis complex and for the transition-state complex.

Catalysis↗

PubMedDate not supplied

Detection of protein coding sequences using a mixture model for local protein amino acid sequence.

Locating protein coding regions in genomic DNA is a critical step in accessing the information generated by large scale sequencing projects. Current methods for gene detection depend on statistical measures of content differences between coding and noncoding DNA in addition to the recognition of promoters, splice sites, and other regulatory sites. Here we explore the potential value of recurrent amino acid sequence patterns 3-19 amino acids in length as a content statistic for use in gene finding approaches. A finite mixture model incorporating these patterns can partially discriminate protein sequences which have no (detectable) known homologs from randomized versions of these sequences, and from short (< or = 50 amino acids) non-coding segments extracted from the S. cerevisiea genome. The mixture model derived scores for a collection of human exons were not correlated with the GENSCAN scores, suggesting that the addition of our protein pattern recognition module to current gene recognition programs may improve their performance.

Algorithms↗