The Thiamine diphosphate dependent Enzyme Engineering Database: A tool for the systematic analysis of sequence and structure relations

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Description</p> <p>The TEED <url>http://www.teed.uni-stuttgart.de</url> 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.</p> <p>Conclusions</p> <p>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.</p

Structural classification by the Lipase Engineering Database: a case study of Candida antarctica lipase A

<p>Abstract</p> <p>Background</p> <p>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 <it>Candida antarctica </it>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.</p> <p>Results</p> <p>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 <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> 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 <it>Candida rugosa </it>lipase was identified as being highly similar. This similarity also applied to the lid of <it>Candida rugosa </it>lipase in comparison to the potential lid of CALA.</p> <p>Conclusion</p> <p>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 <url>http://www.led.uni-stuttgart.de</url> and provides sequences, structures and a set of analysis tools including phylogenetic trees and HMM profiles</p

Prediction and analysis of the modular structure of cytochrome P450 monooxygenases

<p>Abstract</p> <p>Background</p> <p>Cytochrome P450 monooxygenases (CYPs) form a vast and diverse family of highly variable sequences. They catalyze a wide variety of oxidative reactions and are therefore of great relevance in drug development and biotechnological applications. Despite their differences in sequence and substrate specificity, the structures of CYPs are highly similar. Although being in research focus for years, factors mediating selectivity and activity remain vague.</p> <p>Description</p> <p>This systematic comparison of CYPs based on the Cytochrome P450 Engineering Database (<it>CYPED</it>) involved sequence and structure analysis of more than 8000 sequences. 31 structures have been applied to generate a reliable structure-based HMM profile in order to predict structurally conserved regions. Therefore, it was possible to automatically transfer these modules on CYP sequences without any secondary structure information, to analyze substrate interacting residues and to compare interaction sites with redox partners.</p> <p>Conclusions</p> <p>Functionally relevant structural sites of CYPs were predicted. Regions involved in substrate binding were analyzed in all sequences among the <it>CYPED</it>. For all CYPs that require a reductase, two reductase interaction sites were identified and classified according to their length. The newly gained insights promise an improvement of engineered enzyme properties for potential biotechnological application. The annotated sequences are accessible on the current version of the <it>CYPED</it>. The prediction tool can be applied to any CYP sequence via the web interface at <url>http://www.cyped.uni-stuttgart.de/cgi-bin/strpred/dosecpred.pl</url>.</p

Analysis of the distribution of functionally relevant rare codons

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

The PHA Depolymerase Engineering Database: A systematic analysis tool for the diverse family of polyhydroxyalkanoate (PHA) depolymerases

<p>Abstract</p> <p>Background</p> <p>Polyhydroxyalkanoates (PHAs) can be degraded by many microorganisms using intra- or extracellular PHA depolymerases. PHA depolymerases are very diverse in sequence and substrate specificity, but share a common α/β-hydrolase fold and a catalytic triad, which is also found in other α/β-hydrolases.</p> <p>Results</p> <p>The PHA Depolymerase Engineering Database (DED, <url>http://www.ded.uni-stuttgart.de</url>) has been established as a tool for systematic analysis of this enzyme family. The DED contains sequence entries of 587 PHA depolymerases, which were assigned to 8 superfamilies and 38 homologous families based on their sequence similarity. For each family, multiple sequence alignments and profile hidden Markov models are provided, and functionally relevant residues are annotated.</p> <p>Conclusion</p> <p>The DED is a valuable tool which can be applied to identify new PHA depolymerase sequences from complete genomes <it>in silico</it>, to classify PHA depolymerases, to predict their biochemical properties, and to design enzyme variants with improved properties.</p

Alteration of the Route to Menaquinone towards Isochorismate-Derived Metabolites

Chorismate and isochorismate constitute branch-point intermediates in the biosynthesis of many aromatic metabolites in microorganisms and plants. To obtain unnatural compounds, we modified the route to menaquinone in Escherichia coli. We propose a model for the binding of isochorismate to the active site of MenD ((1R,2S, 5S,6S)-2-succinyl-5-enolpyruvyl-6-hydroxycyclohex-3-ene-1-carboxylate (SEPHCHC) synthase) that explains the outcome of the native reaction with α-ketoglutarate. We have rationally designed variants of MenD for the conversion of several isochorismate analogues. The double-variant Asn117Arg–Leu478Thr preferentially converts (5S,6S)-5,6-dihydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHD), the hydrolysis product of isochorismate, with a >70-fold higher ratio than that for the wild type. The single-variant Arg107Ile uses (5S,6S)-6-amino-5-hydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHA) as substrate with >6-fold conversion compared to wild-type MenD. The novel compounds have been made accessible in vivo (up to 5.3 g L−1). Unexpectedly, as the identified residues such as Arg107 are highly conserved (>94 %), some of the designed variations can be found in wild-type SEPHCHC synthases from other bacteria (Arg107Lys, 0.3 %). This raises the question for the possible natural occurrence of as yet unexplored branches of the shikimate pathway.Fil: Fries, Alexander Erich. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina. Albert Ludwigs University of Freiburg; AlemaniaFil: Mazzaferro, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina. Albert Ludwigs University of Freiburg; AlemaniaFil: Grüning, Björn. Albert Ludwigs University of Freiburg; AlemaniaFil: Bisel, Philippe. Albert Ludwigs University of Freiburg; AlemaniaFil: Stibal, Karin. Albert Ludwigs University of Freiburg; AlemaniaFil: Buchholz, Patrick C. F.. University of Stuttgart; AlemaniaFil: Pleiss, Jürgen. Universität Stuttgart;Fil: Sprenger, Georg A.. Universität Stuttgart;Fil: Müller, Michael. Albert Ludwigs University of Freiburg; Alemani

Harnessing Interpretable and Unsupervised Machine Learning to Address Big Data from Modern X-ray Diffraction

The information content of crystalline materials becomes astronomical when collective electronic behavior and their fluctuations are taken into account. In the past decade, improvements in source brightness and detector technology at modern x-ray facilities have allowed a dramatically increased fraction of this information to be captured. Now, the primary challenge is to understand and discover scientific principles from big data sets when a comprehensive analysis is beyond human reach. We report the development of a novel unsupervised machine learning approach, XRD Temperature Clustering (X-TEC), that can automatically extract charge density wave (CDW) order parameters and detect intra-unit cell (IUC) ordering and its fluctuations from a series of high-volume X-ray diffraction (XRD) measurements taken at multiple temperatures. We apply X-TEC to XRD data on a quasi-skutterudite family of materials, (Ca$_x$Sr$_{1-x}$)$_3$Rh$_4$Sn$_{13}$, where a quantum critical point arising from charge order is observed as a function of Ca concentration. We further apply X-TEC to XRD data on the pyrochlore metal, Cd$_2$Re$_2$O$_7$, to investigate its two much debated structural phase transitions and uncover the Goldstone mode accompanying them. We demonstrate how unprecedented atomic scale knowledge can be gained when human researchers connect the X-TEC results to physical principles. Specifically, we extract from the X-TEC-revealed selection rule that the Cd and Re displacements are approximately equal in amplitude, but out of phase. This discovery reveals a previously unknown involvement of $5d^2$ Re, supporting the idea of an electronic origin to the structural order. Our approach can radically transform XRD experiments by allowing in-operando data analysis and enabling researchers to refine experiments by discovering interesting regions of phase space on-the-fly

The Isoelectric Region of Proteins: A Systematic Analysis

Background: Binding of proteins in ion exchange chromatography is dominated by electrostatic interactions and can be tuned by adjusting pH and ionic strength of the solvent. Therefore, the isoelectric region (IER), the pH region of almost zero charge near the pI, has been used to predict the binding properties of proteins. Principal findings: Usually the IER is small and binding and elution is carried out at pH values near to the pI. However, some proteins with an extended IER have been shown to bind and elute far away from its pI. To analyze factors that mediate the size of the IER and to identify proteins with an extended IER, two protein families consisting of more than 7000 proteins were systematically investigated. Most proteins were found to have a small IER and thus are expected to bind or elute near to their pI, while only a small fraction of less than 2 % had a large IER. Conclusions: Only four factors, the number of histidines, the pI, the number of titratable amino acids and the ratio of acidic to basic residues, are sufficient to reliably classify proteins by their IER based on their sequence only, and thus to predict their binding and elution behaviour in ion exchange chromatography

Selective targeting of microglia by quantum dots

<p>Abstract</p> <p>Background</p> <p>Microglia, the resident immune cells of the brain, have been implicated in brain injury and various neurological disorders. However, their precise roles in different pathophysiological situations remain enigmatic and may range from detrimental to protective. Targeting the delivery of biologically active compounds to microglia could help elucidate these roles and facilitate the therapeutic modulation of microglial functions in neurological diseases.</p> <p>Methods</p> <p>Here we employ primary cell cultures and stereotaxic injections into mouse brain to investigate the cell type specific localization of semiconductor quantum dots (QDs) in vitro and in vivo. Two potential receptors for QDs are identified using pharmacological inhibitors and neutralizing antibodies.</p> <p>Results</p> <p>In mixed primary cortical cultures, QDs were selectively taken up by microglia; this uptake was decreased by inhibitors of clathrin-dependent endocytosis, implicating the endosomal pathway as the major route of entry for QDs into microglia. Furthermore, inhibiting mannose receptors and macrophage scavenger receptors blocked the uptake of QDs by microglia, indicating that QD uptake occurs through microglia-specific receptor endocytosis. When injected into the brain, QDs were taken up primarily by microglia and with high efficiency. In primary cortical cultures, QDs conjugated to the toxin saporin depleted microglia in mixed primary cortical cultures, protecting neurons in these cultures against amyloid beta-induced neurotoxicity.</p> <p>Conclusions</p> <p>These findings demonstrate that QDs can be used to specifically label and modulate microglia in primary cortical cultures and in brain and may allow for the selective delivery of therapeutic agents to these cells.</p