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Marcin von Grotthuss

dblp:64/4929 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2006
0000-0002-2850-1152ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular informatics › cheminformatics
chemical similarity search
0.012003
Ligand-Info, Searching for Similar Small Compounds Using Index Profiles · Bioinform. 2003
Bioinformatics and computational biology › molecular informatics
cheminformatics
0.012003
Ligand-Info, Searching for Similar Small Compounds Using Index Profiles · Bioinform. 2003

Methods — techniques the papers use, named apart from their topics

index profiles · 0.0
YearPublicationVenuePosition
2006 PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics
abstract
BACKGROUND: The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. RESULTS: Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins (with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0), for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. CONCLUSION: We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file. AVAILABILITY: http://paradox.harvard.edu/PDB-UF and http://bioinfo.pl/PDB-UF.
Marcin von Grotthuss, Dariusz Plewczynski, Krzysztof Ginalski, Leszek Rychlewski, Eugene I. Shakhnovich
BMC Bioinform.1
2003 Ligand-Info, Searching for Similar Small Compounds Using Index Profiles
abstract
MOTIVATION: The Ligand-Info system is based on the assumption that small molecules with similar structure have similar functional (binding) properties. The developed system enables a fast and sensitive index based search for similar compounds in large databases. Index profiles, constructed by averaging indexes of related molecules are used to increase the specificity of the search. The utilization of index profiles helps to focus on frequent, common features of a family of compounds. RESULTS: A Java-based tool for clustering and scanning of small molecules has been created. The tool can interactively cluster sets of molecules and create index profiles on the user side and automatically download similar molecules from a databases of 250 000 compounds. The results of the application of index profiles demonstrate that the profile based search strategy can increase the quality of the selection process. AVAILABILITY: The system is available at http://Ligand.Info. The application requires the Java Runtime Environment 1.4, which can be automatically installed during the first use on desktop systems, which support it. A standalone version of the program is available from the authors upon request.
Marcin von Grotthuss, Jakub Pas, Leszek Rychlewski
Bioinform.1