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Abstract Background The Lipase Engineering Database (LED) integrates information on sequence, structure and function of lipases, esterases and related proteins with the α/β hydrolase fold. A new superfamily for Candida antarctica lipase A (CALA) was introduced including the recently published crystal structure of CALA. Since CALA has a highly divergent sequence in comparison to other α/β hydrolases, the Lipase Engineering Database was used to classify CALA in the frame of the already established classification system. This involved the comparison of CALA to similar structures as well as sequence-based comparisons against the content of the LED. Results The new release 3.0 (December 2009) of the Lipase Engineering Database contains 24783 sequence entries for 18585 proteins as well as 656 experimentally determined protein structures, including the structure of CALA. In comparison to the previous release 1 with 4322 protein and 167 structure entries this update represents a significant increase in data volume. By comparing CALA to representative structures from all superfamilies, a structure from the deacetylase superfamily was found to be most similar to the structure of CALA. While the α/β hydrolase fold is conserved in both proteins, the major difference is found in the cap region. Sequence alignments between both proteins show a sequence similarity of only 15%. A multisequence alignment of both protein families was used to create hidden Markov models for the cap region of CALA and showed that the cap region of CALA is unique among all other proteins of the α/β hydrolase fold. By specifically comparing the substrate binding pocket of CALA to other binding pockets of α/β hydrolases, the binding pocket of Candida rugosa lipase was identified as being highly similar. This similarity also applied to the lid of Candida rugosa lipase in comparison to the potential lid of CALA. Conclusion The LED serves as a valuable tool for the systematic analysis of single proteins or protein families. The updated release 3.0 was used for the evaluation of α/β hydrolases. The HTML version of the database with new features is available at http://www.led.uni-stuttgart.de and provides sequences, structures and a set of analysis tools including phylogenetic trees and HMM profiles

Abstract Background TEM β-lactamases are the main cause for resistance against β-lactam antibiotics. Sequence information about TEM β-lactamases is mainly found in the NCBI peptide database and TEM mutation table at http://www.lahey.org/Studies/temtable.asp. While the TEM mutation table is manually curated by experts in the lactamase field, who guarantee reliable and consistent information, the rapidly growing sequence and annotation information from the NCBI peptide database is sometimes inconsistent. Therefore, the Lactamase Engineering Database has been developed to collect the TEM β-lactamase sequences from the NCBI peptide database and the TEM mutation table, systematically compare sequence information and naming, identify inconsistencies, and thus provide a versatile tool for reconciliation of data and for an investigation of the sequence-function relationship. Description The LacED currently provides 2399 sequence entries and 37 structure entries. Sequence information on 150 different TEM β-lactamases was derived from the TEM mutation table which provides a unique number to each protein classified as TEM β-lactamase. 293 TEM-like proteins were found in the NCBI protein database, but only 113 TEM β-lactamase were common to both data sets. The 180 TEM β-lactamases from the NCBI protein database which have not yet been assigned to a TEM number fall in three classes: (1) 89 proteins from microbial organisms and 35 proteins from cloning or expression vectors had a new mutation profile; (2) 55 proteins had inconsistent annotation in terms of TEM assignment or reported mutation profile; (3) 39 proteins are fragments. The LacED is web accessible at http://www.LacED.uni-stuttgart.de and contains multisequence alignments, structure information and reconciled annotation of TEM β-lactamases. The LacED is weekly updated and supplies all data for download. Conclusion The Lactamase Engineering Database enables a systematic analysis of TEM β-lactamase sequence and annotation data from different data sources, and thus provides a valuable tool to identify inconsistencies in sequences from the NCBI peptide database, to detect TEM β-lactamases with a novel mutation profile, and to identify new amino acid positions at which mutations can occur.

Abstract Background The substitution of rare codons with more frequent codons is a commonly applied method in heterologous gene expression to increase protein yields. However, in some cases these substitutions lead to a decrease of protein solubility or activity. To predict these functionally relevant rare codons, a method was developed which is based on an analysis of multisequence alignments of homologous protein families. Results The method successfully predicts functionally relevant codons in fatty acid binding protein and chloramphenicol acetyltransferase which had been experimentally determined. However, the analysis of 16 homologous protein families belonging to the α/β hydrolase fold showed that functionally rare codons share no common location in respect to the tertiary and secondary structure. Conclusion A systematic analysis of multisequence alignments of homologous protein families can be used to predict rare codons with a potential impact on protein expression. Our analysis showed that most genes contain at least one putative rare codon rich region. Rare codons located near to those regions should be excluded in an approach of improving protein expression by an exchange of rare codons by more frequent codons.

Abstract Background In screening of libraries derived by expression cloning, expression of active proteins in E. coli can be limited by formation of inclusion bodies. In these cases it would be desirable to enrich gene libraries for coding sequences with soluble gene products in E. coli and thus to improve the efficiency of screening. Previously Wilkinson and Harrison showed that solubility can be predicted from amino acid composition (Biotechnology 1991, 9(5):443–448). We have applied this analysis to members of the alpha/beta hydrolase fold family to predict their solubility in E. coli. alpha/beta hydrolases are a highly diverse family with more than 1800 proteins which have been grouped into homologous families and superfamilies. Results The predicted solubility in E. coli depends on hydrolase size, phylogenetic origin of the host organism, the homologous family and the superfamily, to which the hydrolase belongs. In general small hydrolases are predicted to be more soluble than large hydrolases, and eukaryotic hydrolases are predicted to be less soluble in E. coli than prokaryotic ones. However, combining phylogenetic origin and size leads to more complex conclusions. Hydrolases from prokaryotic, fungal and metazoan origin are predicted to be most soluble if they are of small, medium and large size, respectively. We observed large variations of predicted solubility between hydrolases from different homologous families and from different taxa. Conclusion A comprehensive analysis of all alpha/beta hydrolase sequences allows more efficient screenings for new soluble alpha/beta hydrolases by the use of libraries which contain more soluble gene products. Screening of hydrolases from families whose members are hard to express as soluble proteins in E. coli should first be done in coding sequences of organisms from phylogenetic groups with the highest average of predicted solubility for proteins of this family. The tools developed here can be used to identify attractive target genes for expression using protein sequences published in databases. This analysis also directs the design of degenerate, family- specific primers to amplify new members from homologous families or superfamilies with a high probability of soluble alpha/beta hydrolases.

Background: The Lipase Engineering Database (LED) integrates information on sequence, structure and function of lipases, esterases and related proteins with the α/β hydrolase fold. A new superfamily for Candida antarctica lipase A (CALA) was introduced including the recently published crystal structure of CALA. Since CALA has a highly divergent sequence in comparison to other α/β hydrolases, the Lipase Engineering Database was used to classify CALA in the frame of the already established classification system. This involved the comparison of CALA to similar structures as well as sequence-based comparisons against the content of the LED. Results: The new release 3.0 (December 2009) of the Lipase Engineering Database contains 24783 sequence entries for 18585 proteins as well as 656 experimentally determined protein structures, including the structure of CALA. In comparison to the previous release [1] with 4322 protein and 167 structure entries this update represents a significant increase in data volume. By comparing CALA to representative structures from all superfamilies, a structure from the deacetylase superfamily was found to be most similar to the structure of CALA. While the α/β hydrolase fold is conserved in both proteins, the major difference is found in the cap region. Sequence alignments between both proteins show a sequence similarity of only 15%. A multisequence alignment of both protein families was used to create hidden Markov models for the cap region of CALA and showed that the cap region of CALA is unique among all other proteins of the α/β hydrolase fold. By specifically comparing the substrate binding pocket of CALA to other binding pockets of α/β hydrolases, the binding pocket of Candida rugosa lipase was identified as being highly similar. This similarity also applied to the lid of Candida rugosa lipase in comparison to the potential lid of CALA. Conclusion: The LED serves as a valuable tool for the systematic analysis of single proteins or protein families. The updated release 3.0 was used for the evaluation of α/β hydrolases. The HTML version of the database with new features is available at http://www.led.uni-stuttgart.de and provides sequences, structures and a set of analysis tools including phylogenetic trees and HMM profiles [ABSTRACT FROM AUTHOR]

Background: TEM β-lactamases are the main cause for resistance against β-lactam antibiotics. Sequence information about TEM β-lactamases is mainly found in the NCBI peptide database and TEM mutation table at http://www.lahey.org/Studies/temtable.asp. While the TEM mutation table is manually curated by experts in the lactamase field, who guarantee reliable and consistent information, the rapidly growing sequence and annotation information from the NCBI peptide database is sometimes inconsistent. Therefore, the Lactamase Engineering Database has been developed to collect the TEM β-lactamase sequences from the NCBI peptide database and the TEM mutation table, systematically compare sequence information and naming, identify inconsistencies, and thus provide a versatile tool for reconciliation of data and for an investigation of the sequence-function relationship. Description: The LacED currently provides 2399 sequence entries and 37 structure entries. Sequence information on 150 different TEM β-lactamases was derived from the TEM mutation table which provides a unique number to each protein classified as TEM β-lactamase. 293 TEM-like proteins were found in the NCBI protein database, but only 113 TEM β-lactamase were common to both data sets. The 180 TEM β-lactamases from the NCBI protein database which have not yet been assigned to a TEM number fall in three classes: (1) 89 proteins from microbial organisms and 35 proteins from cloning or expression vectors had a new mutation profile; (2) 55 proteins had inconsistent annotation in terms of TEM assignment or reported mutation profile; (3) 39 proteins are fragments. The LacED is web accessible at http://www.LacED.uni-stuttgart.de and contains multisequence alignments, structure information and reconciled annotation of TEM β-lactamases. The LacED is weekly updated and supplies all data for download. Conclusion: The Lactamase Engineering Database enables a systematic analysis of TEM β-lactamase sequence and annotation data from different data sources, and thus provides a valuable tool to identify inconsistencies in sequences from the NCBI peptide database, to detect TEM β-lactamases with a novel mutation profile, and to identify new amino acid positions at which mutations can occur. [ABSTRACT FROM AUTHOR]