Biomedical subjects

An-Suei Yang

Publications and source records attributed to An-Suei Yang.

4 recordsLinked to original sources

PubMed2003

Local structure prediction with local structure-based sequence profiles.

MOTIVATION: A large body of experimental and theoretical evidence suggests that local structural determinants are frequently encoded in short segments of protein sequence. Although the local structural information, once recognized, is particularly useful in protein structural and functional analyses, it remains a difficult problem to identify embedded local structural codes based solely on sequence information. RESULTS: In this paper, we describe a local structure prediction method aiming at predicting the backbone structures of nine-residue sequence segments. Two elements are the keys for this local structure prediction procedure. The first key element is the LSBSP1 database, which contains a large number of non-redundant local structure-based sequence profiles for nine-residue structure segments. The second key element is the consensus approach, which identifies a consensus structure from a set of hit structures. The local structure prediction procedure starts by matching a query sequence segment of nine consecutive amino acid residues to all the sequence profiles in the local structure-based sequence profile database (LSBSP1). The consensus structure, which is at the center of the largest structural cluster of the hit structures, is predicted to be the native state structure adopted by the query sequence segment. This local structure prediction method is assessed with a large set of random test protein structures that have not been used in constructing the LSBSP1 database. The benchmark results indicate that the prediction capacities of the novel local structure prediction procedure exceed the prediction capacities of the local backbone structure prediction methods based on the I-sites library by a significant margin. AVAILABILITY: All the computational and assessment procedures have been implemented in the integrated computational system PrISM.1 (Protein Informatics System for Modeling). The system and associated databases for LINUX systems can be downloaded from the website: http://www.columbia.edu/~ay1/.

Amino Acid Sequence↗

PubMed2002

Local structure-based sequence profile database for local and global protein structure predictions.

MOTIVATION: A large body of evidence suggests that protein structural information is frequently encoded in local sequences-sequence-structure relationships derived from local structure/sequence analyses could significantly enhance the capacities of protein structure prediction methods. In this paper, the prediction capacity of a database (LSBSP2) that organizes local sequence-structure relationships encoded in local structures with two consecutive secondary structure elements is tested with two computational procedures for protein structure prediction. The goal is twofold: to test the folding hypothesis that local structures are determined by local sequences, and to enhance our capacity in predicting protein structures from their amino acid sequences. RESULTS: The LSBSP2 database contains a large set of sequence profiles derived from exhaustive pair-wise structural alignments for local structures with two consecutive secondary structure elements. One computational procedure makes use of the PSI-BLAST alignment program to predict local structures for testing sequence fragments by matching the testing sequence fragments onto the sequence profiles in the LSBSP2 database. The results show that 54% of the test sequence fragments were predicted with local structures that match closely with their native local structures. The other computational procedure is a filter system that is capable of removing false positives as possible from a set of PSI-BLAST hits. An assessment with a large set of non-redundant protein structures shows that the PSI-BLAST + filter system improves the prediction specificity by up to two-fold over the prediction specificity of the PSI-BLAST program for distantly related protein pairs. Tests with the two computational procedures above demonstrate that local sequence-structure relationships can indeed enhance our capacity in protein structure prediction. The results also indicate that local sequences encoded with strong local structure propensities play an important role in determining the native state folding topology.

Algorithms↗

PubMed2002

Structure-dependent sequence alignment for remotely related proteins.

MOTIVATION: The quality of a model structure derived from a comparative modeling procedure is dictated by the accuracy of the predicted sequence-template alignment. As the sequence-template pairs are increasingly remote in sequence relationship, the prediction of the sequence-template alignments becomes increasingly problematic with sequence alignment methods. Structural information of the template, used in connection with the sequence relationship of the sequence-template pair, could significantly improve the accuracy of the sequence-template alignment. In this paper, we describe a sequence-template alignment method that integrates sequence and structural information to enhance the accuracy of sequence-template alignments for distantly related protein pairs. RESULTS: The structure-dependent sequence alignment (SDSA) procedure was optimized for coverage and accuracy on a training set of 412 protein pairs; the structures for each of the training pairs are similar (RMSD< approximately 4A) but the sequence relationship is undetectable (average pair-wise sequence identity = 8%). The optimized SDSA procedure was then applied to extend PSI-BLAST local alignments by calculating the global alignments under the constraint of the residue pairs in the local alignments. This composite alignment procedure was assessed with a testing set of 1421 protein pairs, of which the pair-wise structures are similar (RMSD< approximately 4A) but the sequences are marginally related at best in each pair (average pair-wise sequence identity = 13%). The assessment showed that the composite alignment procedure predicted more aligned residues pairs with an average of 27% increase in correctly aligned residues over the standard PSI-BLAST alignments for the protein pairs in the testing set.

Algorithms↗

PubMed2001

Secondary structure of the human cardiac Na+ channel C terminus: evidence for a role of helical structures in modulation of channel inactivation.

Little is known about the structure of the C terminus of the human cardiac voltage-gated sodium channel alpha subunit (SCN5A), but disease-linked mutations within this 244-amino acid intracellular region of the channel have marked effects on channel inactivation. Here we report a structural analysis of the C-terminal tail of the cardiac Na(+) channel that sheds new light on mechanisms that control its inactivation gating. Homology modeling of the SCN5A C terminus predicts predominant alpha-helical structure (six helices) in the proximal half of this intracellular tail but little structure in the distal half. Circular dichroism of isolated and purified C terminus supports this prediction. Whole cell and single channel patch clamp recordings of wild type and mutant alpha subunits co-expressed with the hbeta(1) subunit in HEK 293 cells indicate that truncation of the distal, nonstructured, C terminus (L1921stop mutant) reduces current density but does not affect channel gating (n = 6). In contrast, truncation of the sixth helix containing a concentration of positively charged residues along with the distal C terminus (S1885stop mutant) also reduces current density but, in addition, has profound and selective effects on inactivation (no effect on activation). Channel availability is shifted (-11 +/- 0.6 mV), and there is a 10-fold increase in the percentage of channels that burst (fail to inactivate) during prolonged depolarization (0.025% S1885stop (n = 7) versus 0.0028% wild type (n = 9), p < 0.005). These results suggest that the charged structured region of the SCN5A C terminus plays a major role in channel inactivation, stabilizing the inactivated state.

Amino Acid Sequence↗