Biomedical subjects

Maricel G Kann

Publications and source records attributed to Maricel G Kann.

4 recordsLinked to original sources

PubMed2005

Predicting protein-protein interaction by searching evolutionary tree automorphism space.

MOTIVATION: Uncovering the protein-protein interaction network is a fundamental step in the quest to understand the molecular machinery of a cell. This motivates the search for efficient computational methods for predicting such interactions. Among the available predictors are those that are based on the co-evolution hypothesis "evolutionary trees of protein families (that are known to interact) are expected to have similar topologies". Many of these methods are limited by the fact that they can handle only a small number of protein sequences. Also, details on evolutionary tree topology are missing as they use similarity matrices in lieu of the trees. RESULTS: We introduce MORPH, a new algorithm for predicting protein interaction partners between members of two protein families that are known to interact. Our approach can also be seen as a new method for searching the best superposition of the corresponding evolutionary trees based on tree automorphism group. We discuss relevant facts related to the predictability of protein-protein interaction based on their co-evolution. When compared with related computational approaches, our method reduces the search space by approximately 3 x 10(5)-fold and at the same time increases the accuracy of predicting correct binding partners.

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PubMed2005

Histone structure and nucleosome stability.

Histone proteins play essential structural and functional roles in the transition between active and inactive chromatin states. Although histones have a high degree of conservation due to constraints to maintain the overall structure of the nucleosomal octameric core, variants have evolved to assume diverse roles in gene regulation and epigenetic silencing. Histone variants, post-translational modifications and interactions with chromatin remodeling complexes influence DNA replication, transcription, repair and recombination. The authors review recent findings on the structure of chromatin that confirm previous interparticle interactions observed in crystal structures.

Animals↗

PubMed2004

A structure-based method for protein sequence alignment.

MOTIVATION: With the continuing rapid growth of protein sequence data, protein sequence comparison methods have become the most widely used tools of bioinformatics. Among these methods are those that use position-specific scoring matrices (PSSMs) to describe protein families. PSSMs can capture information about conserved patterns within families, which can be used to increase the sensitivity of searches for related sequences. Certain types of structural information, however, are not generally captured by PSSM search methods. Here we introduce a program, Structure-based ALignment TOol (SALTO), that aligns protein query sequences to PSSMs using rules for placing and scoring gaps that are consistent with the conserved regions of domain alignments from NCBI's Conserved Domain Database. RESULTS: In most cases, the alignment scores obtained using the local alignment version follow an extreme value distribution. SALTO's performance in finding related sequences and producing accurate alignments is similar to or better than that of IMPALA; one advantage of SALTO is that it imposes an explicit gapping model on each protein family. AVAILABILITY: A stand-alone version of the program that can generate global or local alignments is available by ftp distribution (ftp://ftp.ncbi.nih.gov/pub/SALTO/), and has been incorporated to Cn3D structure/alignment viewer. CONTACT: bryant@ncbi.nlm.nih.gov.

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PubMed2002

Performance evaluation of a new algorithm for the detection of remote homologs with sequence comparison.

A detailed analysis of the performance of hybrid, a new sequence alignment algorithm developed by Yu and coworkers that combines Smith Waterman local dynamic programming with a local version of the maximum-likelihood approach, was made to access the applicability of this algorithm to the detection of distant homologs by sequence comparison. We analyzed the statistics of hybrid with a set of nonhomologous protein sequences from the SCOP database and found that the statistics of the scores from hybrid algorithm follows an Extreme Value Distribution with lambda approximately 1, as previously shown by Yu et al. for the case of artificially generated sequences. Local dynamic programming was compared to the hybrid algorithm by using two different test data sets of distant homologs from the PFAM and COGs protein sequence databases. The studies were made with several score functions in current use including OPTIMA, a new score function originally developed to detect remote homologs with the Smith Waterman algorithm. We found OPTIMA to be the best score function for both both dynamic programming and the hybrid algorithms. The ability of dynamic programming to discriminate between homologs and nonhomologs in the two sets of distantly related sequences is slightly better than that of hybrid algorithm. The advantage of producing accurate score statistics with only a few simulations may overcome the small differences in performance and make this new algorithm suitable for detection of homologs in conjunction with a wide range of score functions and gap penalties.

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