Biomedical subjects

Michael L Sierk

Publications and source records attributed to Michael L Sierk.

3 recordsLinked to original sources

PubMed2005

The limits of protein sequence comparison?

Modern sequence alignment algorithms are used routinely to identify homologous proteins, proteins that share a common ancestor. Homologous proteins always share similar structures and often have similar functions. Over the past 20 years, sequence comparison has become both more sensitive, largely because of profile-based methods, and more reliable, because of more accurate statistical estimates. As sequence and structure databases become larger, and comparison methods become more powerful, reliable statistical estimates will become even more important for distinguishing similarities that are due to homology from those that are due to analogy (convergence). The newest sequence alignment methods are more sensitive than older methods, but more accurate statistical estimates are needed for their full power to be realized.

Algorithms↗

PubMed2004

Déjà vu all over again: finding and analyzing protein structure similarities.

Structure comparison is a crucial aspect of structural biology today. The field of structure comparison is developing rapidly, with the development of new algorithms, similarity scores, and statistical scores. The predicted large increase of experimental structures and structural models made possible by high-throughput efforts means that structural comparison and searching of structural databases using automated methods will become increasingly common. This Ways & Means article is meant to guide the structural biologist in the basics of structural alignment, and to provide an overview of the available software tools. The main purpose is to encourage users to gain some understanding of the strengths and limitations of structural alignment, and to take these factors into account when interpreting the results of different programs.

Algorithms↗

PubMed2004

Sensitivity and selectivity in protein structure comparison.

Seven protein structure comparison methods and two sequence comparison programs were evaluated on their ability to detect either protein homologs or domains with the same topology (fold) as defined by the CATH structure database. The structure alignment programs Dali, Structal, Combinatorial Extension (CE), VAST, and Matras were tested along with SGM and PRIDE, which calculate a structural distance between two domains without aligning them. We also tested two sequence alignment programs, SSEARCH and PSI-BLAST. Depending upon the level of selectivity and error model, structure alignment programs can detect roughly twice as many homologous domains in CATH as sequence alignment programs. Dali finds the most homologs, 321-533 of 1120 possible true positives (28.7%-45.7%), at an error rate of 0.1 errors per query (EPQ), whereas PSI-BLAST finds 365 true positives (32.6%), regardless of the error model. At an EPQ of 1.0, Dali finds 42%-70% of possible homologs, whereas Matras finds 49%-57%; PSI-BLAST finds 36.9%. However, Dali achieves >84% coverage before the first error for half of the families tested. Dali and PSI-BLAST find 9.2% and 5.2%, respectively, of the 7056 possible topology pairs at an EPQ of 0.1 and 19.5, and 5.9% at an EPQ of 1.0. Most statistical significance estimates reported by the structural alignment programs overestimate the significance of an alignment by orders of magnitude when compared with the actual distribution of errors. These results help quantify the statistical distinction between analogous and homologous structures, and provide a benchmark for structure comparison statistics.

Computational Biology↗