The Experts below are selected from a list of 47025 Experts worldwide ranked by ideXlab platform

Jurgen Pleiss - One of the best experts on this subject based on the ideXlab platform.

  • Expansin Engineering Database: A navigation and classification tool for expansins and homologues.
    Proteins, 2020
    Co-Authors: Caroline Lohoff, Patrick C. F. Buchholz, Marilize Le Roes-hill, Jurgen Pleiss
    Abstract:

    Expansins have the remarkable ability to loosen plant cell walls and cellulose material without showing catalytic activity and therefore have potential applications in biomass degradation. To support the study of sequence-structure-function relationships and the search for novel expansins, the Expansin Engineering Database (ExED, https://exed.biocatnet.de) collected sequence and structure data on expansins from Bacteria, Fungi, and Viridiplantae, and expansin-like homologues such as carbohydrate binding modules, glycoside hydrolases, loosenins, swollenins, cerato-platanins, and EXPNs. Based on global sequence alignment and protein sequence network analysis, the sequences are highly diverse. However, many similarities were found between the expansin domains. Newly created profile hidden Markov models of the two expansin domains enable standard numbering schemes, comprehensive conservation analyses, and genome annotation. Conserved key amino acids in the expansin domains were identified, a refined classification of expansins and carbohydrate binding modules was proposed, and new sequence motifs facilitate the search of novel candidate genes and the Engineering of expansins.

  • the short chain dehydrogenase reductase Engineering Database sdred a classification and analysis system for a highly diverse enzyme family
    Proteins, 2019
    Co-Authors: Maike Gräff, Patrick C. F. Buchholz, Peter Stockinger, Bettina Bommarius, Andreas S. Bommarius, Jurgen Pleiss
    Abstract:

    The Short-chain Dehydrogenases/Reductases Engineering Database (SDRED) covers one of the largest known protein families (168 150 proteins). Assignment to the superfamilies of Classical and Extended SDRs was achieved by global sequence similarity and by identification of family-specific sequence motifs. Two standard numbering schemes were established for Classical and Extended SDRs that allow for the determination of conserved amino acid residues, such as cofactor specificity determining positions or superfamily specific sequence motifs. The comprehensive sequence dataset of the SDRED facilitates the refinement of family-specific sequence motifs. The glycine-rich motifs for Classical and Extended SDRs were refined to improve the precision of superfamily classification. In each superfamily, the majority of sequences formed a tightly connected sequence network and belonged to a large homologous family. Despite their different sequence motifs and their different sequence length, the two sequence networks of Classical and Extended SDRs are not separate, but connected by edges at a threshold of 40% sequence similarity, indicating that all SDRs belong to a large, connected network. The SDRED is accessible at https://sdred.biocatnet.de/.

  • The Short-chain Dehydrogenase/Reductase Engineering Database (SDRED): A classification and analysis system for a highly diverse enzyme family.
    Proteins, 2019
    Co-Authors: Maike Gräff, Patrick C. F. Buchholz, Peter Stockinger, Bettina Bommarius, Andreas S. Bommarius, Jurgen Pleiss
    Abstract:

    The Short-chain Dehydrogenases/Reductases Engineering Database (SDRED) covers one of the largest known protein families (168 150 proteins). Assignment to the superfamilies of Classical and Extended SDRs was achieved by global sequence similarity and by identification of family-specific sequence motifs. Two standard numbering schemes were established for Classical and Extended SDRs that allow for the determination of conserved amino acid residues, such as cofactor specificity determining positions or superfamily specific sequence motifs. The comprehensive sequence dataset of the SDRED facilitates the refinement of family-specific sequence motifs. The glycine-rich motifs for Classical and Extended SDRs were refined to improve the precision of superfamily classification. In each superfamily, the majority of sequences formed a tightly connected sequence network and belonged to a large homologous family. Despite their different sequence motifs and their different sequence length, the two sequence networks of Classical and Extended SDRs are not separate, but connected by edges at a threshold of 40% sequence similarity, indicating that all SDRs belong to a large, connected network. The SDRED is accessible at https://sdred.biocatnet.de/.

  • the ω transaminase Engineering Database otaed a navigation tool in protein sequence and structure space
    Proteins, 2018
    Co-Authors: Oliver Bus, Patrick C. F. Buchholz, Maike Gräff, Peter Klausmann, Jens Rudat, Jurgen Pleiss
    Abstract:

    The ω-Transaminase Engineering Database (oTAED) was established as a publicly accessible resource on sequences and structures of the biotechnologically relevant ω-transaminases (ω-TAs) from Fold types I and IV. The oTAED integrates sequence and structure data, provides a classification based on fold type and sequence similarity, and applies a standard numbering scheme to identify equivalent positions in homologous proteins. The oTAED includes 67 210 proteins (114 655 sequences) which are divided into 169 homologous families based on global sequence similarity. The 44 and 39 highly conserved positions which were identified in Fold type I and IV, respectively, include the known catalytic residues and a large fraction of glycines and prolines in loop regions, which might have a role in protein folding and stability. However, for most of the conserved positions the function is still unknown. Literature information on positions that mediate substrate specificity and stereoselectivity was systematically examined. The standard numbering schemes revealed that many positions which have been described in different enzymes are structurally equivalent. For some positions, multiple functional roles have been suggested based on experimental data in different enzymes. The proposed standard numbering schemes for Fold type I and IV ω-TAs assist with analysis of literature data, facilitate annotation of ω-TAs, support prediction of promising mutation sites, and enable navigation in ω-TA sequence space. Thus, it is a useful tool for enzyme Engineering and the selection of novel ω-TA candidates with desired biochemical properties.

  • The ω‐transaminase Engineering Database (oTAED): A navigation tool in protein sequence and structure space
    Proteins, 2018
    Co-Authors: Oliver Buß, Patrick C. F. Buchholz, Maike Gräff, Peter Klausmann, Jens Rudat, Jurgen Pleiss
    Abstract:

    The ω-Transaminase Engineering Database (oTAED) was established as a publicly accessible resource on sequences and structures of the biotechnologically relevant ω-transaminases (ω-TAs) from Fold types I and IV. The oTAED integrates sequence and structure data, provides a classification based on fold type and sequence similarity, and applies a standard numbering scheme to identify equivalent positions in homologous proteins. The oTAED includes 67 210 proteins (114 655 sequences) which are divided into 169 homologous families based on global sequence similarity. The 44 and 39 highly conserved positions which were identified in Fold type I and IV, respectively, include the known catalytic residues and a large fraction of glycines and prolines in loop regions, which might have a role in protein folding and stability. However, for most of the conserved positions the function is still unknown. Literature information on positions that mediate substrate specificity and stereoselectivity was systematically examined. The standard numbering schemes revealed that many positions which have been described in different enzymes are structurally equivalent. For some positions, multiple functional roles have been suggested based on experimental data in different enzymes. The proposed standard numbering schemes for Fold type I and IV ω-TAs assist with analysis of literature data, facilitate annotation of ω-TAs, support prediction of promising mutation sites, and enable navigation in ω-TA sequence space. Thus, it is a useful tool for enzyme Engineering and the selection of novel ω-TA candidates with desired biochemical properties.

Michael Widmann - One of the best experts on this subject based on the ideXlab platform.

  • Structural classification by the Lipase Engineering Database: a case study of Candida antarctica lipase A
    BMC genomics, 2010
    Co-Authors: Michael Widmann, P. Benjamin Juhl, Jurgen Pleiss
    Abstract:

    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. 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. 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

  • the thiamine diphosphate dependent enzyme Engineering Database a tool for the systematic analysis of sequence and structure relations
    BMC Biochemistry, 2010
    Co-Authors: Michael Widmann, Robert Radloff, Jurgen Pleiss
    Abstract:

    Background Thiamine diphosphate (ThDP)-dependent enzymes form a vast and diverse class of proteins, catalyzing a wide variety of enzymatic reactions including the formation or cleavage of carbon-sulfur, carbon-oxygen, carbon-nitrogen, and especially carbon-carbon bonds. Although very diverse in sequence and domain organisation, they share two common protein domains, the pyrophosphate (PP) and the pyrimidine (PYR) domain. For the comprehensive and systematic comparison of protein sequences and structures the Thiamine diphosphate (ThDP)-dependent Enzyme Engineering Database (TEED) was established.

  • The Thiamine diphosphate dependent Enzyme Engineering Database: A tool for the systematic analysis of sequence and structure relations
    BMC Biochemistry, 2010
    Co-Authors: Michael Widmann, Robert Radloff, Jurgen Pleiss
    Abstract:

    Background Thiamine diphosphate (ThDP)-dependent enzymes form a vast and diverse class of proteins, catalyzing a wide variety of enzymatic reactions including the formation or cleavage of carbon-sulfur, carbon-oxygen, carbon-nitrogen, and especially carbon-carbon bonds. Although very diverse in sequence and domain organisation, they share two common protein domains, the pyrophosphate (PP) and the pyrimidine (PYR) domain. For the comprehensive and systematic comparison of protein sequences and structures the Thiamine diphosphate (ThDP)-dependent Enzyme Engineering Database (TEED) was established. Description The TEED http://www.teed.uni-stuttgart.de contains 12048 sequence entries which were assigned to 9443 different proteins and 379 structure entries. Proteins were assigned to 8 different superfamilies and 63 homologous protein families. For each family, the TEED offers multisequence alignments, phylogenetic trees, and family-specific HMM profiles. The conserved pyrophosphate (PP) and pyrimidine (PYR) domains have been annotated, which allows the analysis of sequence similarities for a broad variety of proteins. Human ThDP-dependent enzymes are known to be involved in many diseases. 20 different proteins and over 40 single nucleotide polymorphisms (SNPs) of human ThDP-dependent enzymes were identified in the TEED. Conclusions The online accessible version of the TEED has been designed to serve as a navigation and analysis tool for the large and diverse family of ThDP-dependent enzymes.

Quan Ke Thai - One of the best experts on this subject based on the ideXlab platform.

  • SHV Lactamase Engineering Database: a reconciliation tool for SHV β-lactamases in public Databases
    BMC Genomics, 2010
    Co-Authors: Quan Ke Thai, Juergen Pleiss
    Abstract:

    Background SHV β-lactamases confer resistance to a broad range of antibiotics by accumulating mutations. The number of SHV variants is steadily increasing. 117 SHV variants have been assigned in the SHV mutation table ( http://www.lahey.org/Studies/ ). Besides, information about SHV β-lactamases can be found in the rapidly growing NCBI protein Database. The SHV β-Lactamase Engineering Database (SHVED) has been developed to collect the SHV β-lactamase sequences from the NCBI protein Database and the SHV mutation table. It serves as a tool for the detection and reconciliation of inconsistencies, and for the identification of new SHV variants and amino acid substitutions. Description The SHVED contains 200 protein entries with distinct sequences and 20 crystal structures. 83 protein sequences are included in the both the SHV mutation table and the NCBI protein Database, while 35 and 82 protein sequences are only in the SHV mutation table and the NCBI protein Database, respectively. Of these 82 sequences, 41 originate from microbial sources, and 22 of them are full-length sequences that harbour a mutation profile which has not been classified yet in the SHV mutation table. 27 protein entries from the NCBI protein Database were found to have an inconsistency in SHV name identification. These inconsistencies were reconciled using information from the SHV mutation table and stored in the SHVED. The SHVED is accessible at http://www.LacED.uni-stuttgart.de/classA/SHVED/ . It provides sequences, structures, and a multisequence alignment of SHV β-lactamases with the corrected annotation. Amino acid substitutions at each position are also provided. The SHVED is updated monthly and supplies all data for download. Conclusions The SHV β-Lactamase Engineering Database (SHVED) contains information about SHV variants with reconciled annotation. It serves as a tool for detection of inconsistencies in the NCBI protein Database, helps to identify new mutations resulting in new SHV variants, and thus supports the investigation of sequence-function relationships of SHV β-lactamases.

  • The Lactamase Engineering Database: a critical survey of TEM sequences in public Databases
    BMC genomics, 2009
    Co-Authors: Quan Ke Thai, Fabian Bös, Jurgen Pleiss
    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.

Jingde Cheng - One of the best experts on this subject based on the ideXlab platform.

  • ISEDS: An Information Security Engineering Database System Based on ISO Standards
    2008 Third International Conference on Availability Reliability and Security, 2008
    Co-Authors: Daisuke Horie, Noor Azimah, Shoichi Morimoto, Yuichi Goto, Jingde Cheng
    Abstract:

    Security facilities of information systems with high security requirements should be consistently and continuously developed, used, and maintained based on some common standards of information security. However, there is no Engineering environment that can support all tasks in security Engineering consistently and continuously. To construct a security Engineering environment, a Database that can manage all data concerning all tasks in security Engineering is indispensable. This paper presents an Information Security Engineering Database System, named "ISEDS," that we are developing based on ISO standards, and shows its some possible applications. ISEDS manages data of ISO standards of information security and various cases of system development and maintenance. We adopted the international standard ISO/IEC 15408 (Common Criteria) for information security evaluation as one of ISO standards to underlie ISEDS, and implemented major functions of ISEDS and its application tools to manage and use data oflSO/IEC 15408. Developers, users, and maintainers can create, correct, and verify specification documents of security facilities with the application tools.

  • ARES - ISEDS: An Information Security Engineering Database System Based on ISO Standards
    2008 Third International Conference on Availability Reliability and Security, 2008
    Co-Authors: Daisuke Horie, Noor Azimah, Shoichi Morimoto, Yuichi Goto, Jingde Cheng
    Abstract:

    Security facilities of information systems with high security requirements should be consistently and continuously developed, used, and maintained based on some common standards of information security. However, there is no Engineering environment that can support all tasks in security Engineering consistently and continuously. To construct a security Engineering environment, a Database that can manage all data concerning all tasks in security Engineering is indispensable. This paper presents an Information Security Engineering Database System, named "ISEDS," that we are developing based on ISO standards, and shows its some possible applications. ISEDS manages data of ISO standards of information security and various cases of system development and maintenance. We adopted the international standard ISO/IEC 15408 (Common Criteria) for information security evaluation as one of ISO standards to underlie ISEDS, and implemented major functions of ISEDS and its application tools to manage and use data oflSO/IEC 15408. Developers, users, and maintainers can create, correct, and verify specification documents of security facilities with the application tools.

Juergen Pleiss - One of the best experts on this subject based on the ideXlab platform.

  • SHV Lactamase Engineering Database: a reconciliation tool for SHV β-lactamases in public Databases
    BMC Genomics, 2010
    Co-Authors: Quan Ke Thai, Juergen Pleiss
    Abstract:

    Background SHV β-lactamases confer resistance to a broad range of antibiotics by accumulating mutations. The number of SHV variants is steadily increasing. 117 SHV variants have been assigned in the SHV mutation table ( http://www.lahey.org/Studies/ ). Besides, information about SHV β-lactamases can be found in the rapidly growing NCBI protein Database. The SHV β-Lactamase Engineering Database (SHVED) has been developed to collect the SHV β-lactamase sequences from the NCBI protein Database and the SHV mutation table. It serves as a tool for the detection and reconciliation of inconsistencies, and for the identification of new SHV variants and amino acid substitutions. Description The SHVED contains 200 protein entries with distinct sequences and 20 crystal structures. 83 protein sequences are included in the both the SHV mutation table and the NCBI protein Database, while 35 and 82 protein sequences are only in the SHV mutation table and the NCBI protein Database, respectively. Of these 82 sequences, 41 originate from microbial sources, and 22 of them are full-length sequences that harbour a mutation profile which has not been classified yet in the SHV mutation table. 27 protein entries from the NCBI protein Database were found to have an inconsistency in SHV name identification. These inconsistencies were reconciled using information from the SHV mutation table and stored in the SHVED. The SHVED is accessible at http://www.LacED.uni-stuttgart.de/classA/SHVED/ . It provides sequences, structures, and a multisequence alignment of SHV β-lactamases with the corrected annotation. Amino acid substitutions at each position are also provided. The SHVED is updated monthly and supplies all data for download. Conclusions The SHV β-Lactamase Engineering Database (SHVED) contains information about SHV variants with reconciled annotation. It serves as a tool for detection of inconsistencies in the NCBI protein Database, helps to identify new mutations resulting in new SHV variants, and thus supports the investigation of sequence-function relationships of SHV β-lactamases.

  • The Cytochrome P450 Engineering Database
    Bioinformatics (Oxford England), 2007
    Co-Authors: Markus Fischer, Michael Knoll, Demet Sirim, Florian Wagner, Sonja Funke, Juergen Pleiss
    Abstract:

    Summary: The Cytochrome P450 Engineering Database (CYPED) has been designed to serve as a tool for a comprehensive and systematic comparison of protein sequences and structures within the vast and diverse family of cytochrome P450 monooxygenases (CYPs). The CYPED currently integrates sequence and structure data of 3911 and 25 proteins, respectively. Proteins are grouped into homologous families and superfamilies according to Nelson's classification. Nonclassified CYP sequences are assigned by similarity. Functionally relevant residues are annotated. The web accessible version contains multisequence alignments, phylogenetic trees and HMM profiles. The CYPED is regularly updated and supplies all data for download. Thus, it provides a valuable data source for phylogenetic analysis, investigation of sequence–function relationships and the design of CYPs with improved biochemical properties. Abbreviations: Cytochrome P450 Engineering Database, CYPED; cytochrome P450 monooxygenase, CYP; Hidden Markov Model, HMM. Availability: www.cyped.uni-stuttgart.de Contact: Juergen.Pleiss@itb.uni-stuttgart.de