Lipase Engineering Database Research Articles

EP-Pred: A Machine Learning Tool for Bioprospecting Promiscuous Ester Hydrolases.

When bioprospecting for novel industrial enzymes, substrate promiscuity is a desirable property that increases the reusability of the enzyme. Among industrial enzymes, ester hydrolases have great relevance for which the demand has not ceased to increase. However, the search for new substrate promiscuous ester hydrolases is not trivial since the mechanism behind this property is greatly influenced by the active site’s structural and physicochemical characteristics. These characteristics must be computed from the 3D structure, which is rarely available and expensive to measure, hence the need for a method that can predict promiscuity from sequence alone. Here we report such a method called EP-pred, an ensemble binary classifier, that combines three machine learning algorithms: SVM, KNN, and a Linear model. EP-pred has been evaluated against the Lipase Engineering Database together with a hidden Markov approach leading to a final set of ten sequences predicted to encode promiscuous esterases. Experimental results confirmed the validity of our method since all ten proteins were found to exhibit a broad substrate ambiguity.

The limitations of the current protein classification tools in identifying lipolytic features in putative bacterial lipase sequences

Metagenomics sequencing has generated millions of new protein sequences, most of them with unknown functions. A relatively quick first step for function assignment is to use the existing public protein databases and their scanning tools. However, to date these tools are not able to identify all sequence features like conserved motifs or patterns. In this study we evaluated the capability of several protein public databases (e.g., InterPro, PROSITE, ESTHER, pfam, AlphaFold etc) and their scanning tools for identifying lipolytic features in 78 putative cold-adapted bacterial lipase sequences. Novel lipases that can tolerate extreme conditions have great biotechnological importance. We obtained the putative cold-adapted lipolytic sequences from the metagenomic study of anaerobic psychrophilic microbial community treating domestic wastewater at 4 and 15 ℃. Both newer and conventional protein classifiers failed to find lipolytic features for most of the putative lipases. InterProScan predicted lipase family membership for only 18 of the putative lipase sequences. For more than half of them (41 out of 78) InterProScan could not predict any protein family membership, let alone find lipolytic features in them. However, when the Lipase Engineering Database and AlphaFold were used, half of those sequences were classified. Conventional databases like PROSITE could find lipolytic patterns for 9 of the putative lipolytic sequences of which only one was identified by InterProScan as a lipase. Moreover, different scanning tools made different and inconsistent predictions for a certain putative lipase sequence. Even InterProScan, which integrates predictions from 13 protein member databases, did not have a consensus prediction for a certain lipase sequence. Our study shows that there is lack of information in public protein databases about bacterial lipase sequences and this limits their lipolytic feature prediction and biotechnological application. The integration of AlphaFold within the InterPro can improve the lipase identification and classification significantly.

Bioinformatic characterization of a triacylglycerol lipase produced by Aspergillus flavus isolated from the decaying seed of Cucumeropsis mannii

Lipases are enzymes of industrial importance responsible for the hydrolysis of ester bonds of triglycerides. A lipolytic fungus was isolated and subsequently identified based on the ITS sequence analysis as putative Aspergillus flavus with accession number LC424503. The gene coding for extracellular triacylglycerol lipase was isolated from Aspergillus flavus species, sequenced, and characterised using bioinformatics tools. An open reading frame of 420 amino acid sequence was obtained and designated as Aspergillus flavus lipase (AFL) sequence. Alignment of the amino acid sequence with other lipases revealed the presence GHSLG sequence which is the lipase consensus sequence Gly-X1-Ser-X2-Gly indicating that it a classical lipase. A catalytic active site lid domain composed of TYITDTIIDLS amino acids sequence was also revealed. This lid protects the active site, control the catalytic activity and substrate selectivity in lipases. The 3-Dimensional structural model shared 34.08% sequence identity with a lipase from Yarrowia lipolytica covering 272 amino acid residues of the template model. A search of the lipase engineering database using AFL sequence revealed that it belongs to the class GX-lipase, superfamily abH23 and homologous family abH23.02, molecular weight and isoelectric point values of 46.95 KDa and 5.7, respectively. N-glycosylation sites were predicted at residues 164, 236 and 333, with potentials of 0.7250, 0.7037 and 0.7048, respectively. O-glycosylation sites were predicted at residues 355, 358, 360 and 366. A signal sequence of 37 amino acids was revealed at the N-terminal of the polypeptide. This is a short peptide sequence that marks a protein for transport across the cell membrane and indicates that AFL is an extracellular lipase. The findings on the structural and molecular properties of Aspergillus flavus lipase in this work will be crucial in future studies aiming at engineering the enzyme for biotechnology applications. Communicated by Ramaswamy H. Sarma

The modular structure of α/β-hydrolases.

The α/β-hydrolase fold family is highly diverse in sequence, structure and biochemical function. To investigate the sequence-structure-function relationships, the Lipase Engineering Database (https://led.biocatnet.de) was updated. Overall, 280638 protein sequences and 1557 protein structures were analysed. All α/β-hydrolases consist of the catalytically active core domain, but they might also contain additional structural modules, resulting in 12 different architectures: core domain only, additional lids at three different positions, three different caps, additional N- or C-terminal domains and combinations of N- and C-terminal domains with caps and lids respectively. In addition, the α/β-hydrolases were distinguished by their oxyanion hole signature (GX-, GGGX- and Y-types). The N-terminal domains show two different folds, the Rossmann fold or the β-propeller fold. The C-terminal domains show a β-sandwich fold. The N-terminal β-propeller domain and the C-terminal β-sandwich domain are structurally similar to carbohydrate-binding proteins such as lectins. The classification was applied to the newly discovered polyethylene terephthalate (PET)-degrading PETases and MHETases, which are core domain α/β-hydrolases of the GX- and the GGGX-type respectively. To investigate evolutionary relationships, sequence networks were analysed. The degree distribution followed a power law with a scaling exponent γ=1.4, indicating a highly inhomogeneous network which consists of a few hubs and a large number of less connected sequences. The hub sequences have many functional neighbours and therefore are expected to be robust toward possible deleterious effects of mutations. The cluster size distribution followed a power law with an extrapolated scaling exponent τ=2.6, which strongly supports the connectedness of the sequence space of α/β-hydrolases. DATABASE: Supporting data about domains from other proteins with structural similarity to the N- or C-terminal domains of α/β-hydrolases are available in Data Repository of the University of Stuttgart (DaRUS) under doi: https://doi.org/10.18419/darus-458.

Probing role of key residues in the divergent evolution of Yarrowia lipolytica lipase 2 and Aspergillus niger eruloyl esterase A

Yarrowia lipolytica lipase 2 (YLLip2) and Aspergillus niger feruloyl esterase A (AnFaeA) are enzymes of similar structures but with different functions. They are both classified into the same homologous family in Lipase Engineering Database (LED). The major difference between the two enzymes is that YLLip2 exhibits interfacial activity while AnFaeA does not. In order to better understand the interfacial activation mechanisms of YLLip2, structure guided site-directed mutagenesis were performed, mutants were constructed, kinetics parameters and lipase properties were detected. Mutant enzymes showed enhanced catalytic efficiency towards p-nitrophenyl butyrin (pNPB) but their catalytic efficiency decreased towards p-nitrophenyl palmitate (pNPP), their catalysis behavior was more close to feruloyl esterase. Moreover, the mutant enzymes exhibited enhanced thermostability compared with their wild type. These results indicate that I100 and F129 are probably cut-off point of divergent functions between the two enzymes during evolution.

Compositional profile of α / β-hydrolase fold proteins in mangrove soil metagenomes: prevalence of epoxide hydrolases and haloalkane dehalogenases in oil-contaminated sites.

The occurrence of genes encoding biotechnologically relevant α/β-hydrolases in mangrove soil microbial communities was assessed using data obtained by whole-metagenome sequencing of four mangroves areas, denoted BrMgv01 to BrMgv04, in São Paulo, Brazil. The sequences (215 Mb in total) were filtered based on local amino acid alignments against the Lipase Engineering Database. In total, 5923 unassembled sequences were affiliated with 30 different α/β-hydrolase fold superfamilies. The most abundant predicted proteins encompassed cytosolic hydrolases (abH08; ∼ 23%), microsomal hydrolases (abH09; ∼ 12%) and Moraxella lipase-like proteins (abH04 and abH01; < 5%). Detailed analysis of the genes predicted to encode proteins of the abH08 superfamily revealed a high proportion related to epoxide hydrolases and haloalkane dehalogenases in polluted mangroves BrMgv01-02-03. This suggested selection and putative involvement in local degradation/detoxification of the pollutants. Seven sequences that were annotated as genes for putative epoxide hydrolases and five for putative haloalkane dehalogenases were found in a fosmid library generated from BrMgv02 DNA. The latter enzymes were predicted to belong to Actinobacteria, Deinococcus-Thermus, Planctomycetes and Proteobacteria. Our integrated approach thus identified 12 genes (complete and/or partial) that may encode hitherto undescribed enzymes. The low amino acid identity (< 60%) with already-described genes opens perspectives for both production in an expression host and genetic screening of metagenomes.

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

BackgroundThe 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.ResultsThe 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.ConclusionThe 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

Aspergillus niger lipase: Heterologous expression in Pichia pastoris, molecular modeling prediction and the importance of the hinge domains at both sides of the lid domain to interfacial activation

Aspergillus niger lipase (ANL) is an important biocatalyst in the food processing industry. However, there is no report of its detailed three-dimensional structure because of difficulties in crystallization. In this article, based on experimental data and bioinformational analysis results, the structural features of ANL were simulated. Firstly, two recombinant ANLs expressed in Pichia pastoris were purified to homogeneity and their corresponding secondary structure compositions were determined by circular dichroism spectra. Secondly, the primary structure, the secondary structure and the three-dimensional structure of ANL were modeled by comparison with homologous lipases with known three-dimensional structures using the BioEdit software, lipase engineering database (http://www.led.uni-stuttgart.de/), PSIPRED server and SwissModel server. The predicted molecular structure of ANL presented typical features of the alpha/beta hydrolase fold including positioning of the putative catalytic triad residues and the GXSXG signature motif. Comparison of the predicted three-dimensional structure of ANL with the X-ray three-dimensional structure of A. niger feruloyl esterase showed that the functional difference of interfacial activation between lipase and esterase was concerned with the difference in position of the lid. Our three-dimensional model of ANL helps to modify lipase structure by protein engineering, which will further expand the scope of application of ANL.

Rational design of a new one-step purification strategy for Candida antarctica lipase B by ion-exchange chromatography

A fast and efficient one-step method for purification of lipase B from Candida antarctica by ion-exchange chromatography was developed by rational design. The electrostatic properties of the enzyme were calculated and validated by isoelectric focusing and measurement of the titration curve. C. antarctica lipase B shows an unusual pH profile with a broad isoelectric region from pH 4 to 8. At pH 3 C. antarctica lipase B can be bound to a cation-exchange chromatography column and was purified to homogeneity with a purification factor of 2.4. It was stable at pH 3, the residual activity was still 80% after 6 days incubation at 20 °C. The broad isoelectric region of C. antarctica lipase B is unique as compared to almost all other α/β-hydrolases which have a well-defined isoelectric point. A search in the lipase engineering database resulted in only one further α/β-hydrolase, the Fusarium solani cutinase, which also has a broad isoelectric region.

DWARF--a data warehouse system for analyzing protein families.

BackgroundThe emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families.DescriptionThe data warehouse system DWARF integrates data on sequence, structure, and functional annotation for protein fold families. The underlying relational data model consists of three major sections representing entities related to the protein (biochemical function, source organism, classification to homologous families and superfamilies), the protein sequence (position-specific annotation, mutant information), and the protein structure (secondary structure information, superimposed tertiary structure). Tools for extracting, transforming and loading data from public available resources (ExPDB, GenBank, DSSP) are provided to populate the database. The data can be accessed by an interface for searching and browsing, and by analysis tools that operate on annotation, sequence, or structure. We applied DWARF to the family of α/β-hydrolases to host the Lipase Engineering database. Release 2.3 contains 6138 sequences and 167 experimentally determined protein structures, which are assigned to 37 superfamilies 103 homologous families.ConclusionDWARF has been designed for constructing databases of large structurally related protein families and for evaluating their sequence-structure-function relationships by a systematic analysis of sequence, structure and functional annotation. It has been applied to predict biochemical properties from sequence, and serves as a valuable tool for protein engineering.

Sequence and structure of epoxide hydrolases: A systematic analysis

Epoxide hydrolases (EC 3.3.2.3) are ubiquitous enzymes that catalyze the hydrolysis of epoxides to the corresponding vicinal diols. More than 100 epoxide hydrolases (EH) have been identified or predicted, and 3 structures are available. Although they catalyze the same chemical reaction, sequence similarity is low. To identify conserved regions, all EHs were aligned. Phylogenetic analysis identified 12 homologous families, which were grouped into 2 major superfamilies: the microsomal EH superfamily, which includes the homologous families of Mammalian, Insect, Fungal, and Bacterial EHs, and the cytosolic EH superfamily, which includes Mammalian, Plant, and Bacterial EHs. Bacterial EHs show a high sequence diversity. Based on structure comparison of three known structures from Agrobacterium radiobacter AD1 (cytosolic EH), Aspergillus niger (microsomal EH), Mus musculus (cytosolic EH), and multisequence alignment and phylogenetic analysis of 95 EHs, the modular architecture of this enzyme family was analyzed. Although core and cap domain are highly conserved, the structural differences between the EHs are restricted to only two loops: the NC-loop connecting the core and the cap and the cap-loop, which is inserted into the cap domain. EHs were assigned to either of three clusters based on loop length. By using this classification, core and cap region of all EHs, NC-loops and cap-loops of 78% and 89% of all EHs, respectively, could be modeled. Representative models are available from the Lipase Engineering Database, http://www.led.uni-stuttgart.de.

Lipase 유전자의 보존적 영역 탐색

Lipase 유전자들의 보존적 영역을 탐색하기 위해 LED(Lipase Engineering Database)와 COG (Clusters of Orthologous Groups of proteins)를 통하여 각각 132개와 24개의 서열을 얻어 분석하였다. Lipase 유전자의 염기서열은 아주 다양하였고 LED의 각 상동성그룹 (homologous family) 별로 독특한 아미노산 서열이 보존적인 것을 확인 할 수 있었다. COG0657에 속하는 lipase들은 LED의 Moraxella lipase 1 homologous group과 유사한 아미노산 보존적 영역이 있음을 확인하였다. 다양한 반응 조건에 적응하는 혹은 높은 활성을 갖는 새로운 lipase 유전자를 원핵생물에서 탐색하기 위하여 다양한 시도들이 수행되어 왔지만 그들은 모두 배양가능한 미생물에 국한되어 있었다. 배양할 수 없는 세균의 유전자원을 포함하는 메타게놈에 대한 유용성 역시 최근에 널리 인식되고 있다. Lipase 유전자의 다양성으로 보았을 때 메타게놈을 이용한 새로운 lipase 유전자를 찾는 작업도 가능할 것으로 사료되어 lipase유전자 일부를 (222∼713 bp) 증폭시키는 총 10개의 PCR primer를 설계하였으며 그 가능성을 NCBI의 BLAST를 통하여 검증하였다. Lipase 유전자의 염기서열은 아미노산 서열보다 아주 다양하여 비교적 많은 수의 primer set이 필요하였다. 각 primer set의 증폭효율은 각 LED group의 16.7%와 60.0% 사이였고 개별적인 primer set을 이용할 때 보다 3.6배 효율이 높은 것으로 드러났다. Lipase 유전자의 다양성은 설계된 primer set들을 이용하여 새로운 lipase 유전자를 검출할 가능성을 높이는 것으로 사료되었다. For the investigation of conserved regions in lipase genes, 132 and 24 sequences were obtained from LED (Lipase Engineering Database) and COG (Clusters of Orthologous Groups of proteins), respectively. There was high diversity in lipase genes and peculiar amino acid sequences were conserved for each homologous family of LED. Similar conserved amino acid sequences were detected from COG0657 and Moraxella lipase 1 homologous group of LED. Although many studies have attempted to detect new lipase genes in procaryotes, they have been limited culturable bacteria. The importance of metagenome, including DNA from non-culturable bacteria, is known. Due to the high diversity, we assumed it might be possible to detect new lipase gene from metagenome. Due to the high diversity of nucleotide sequences in lipase genes, 10 primer sets were designed. Designed primer sets were inspected in BLAST of NCBI and they could amplify a part of the lipase gene from 222 to 713 bp. They can amplify 16.7%∼60.0% of each lipase homologous group which was 3.6 fold higher than each sets. They might offer a high probability of detecting new lipase genes, owing to high efficiency and the diversity of lipase genes.

The Lipase Engineering Database: a navigation and analysis tool for protein families.

The Lipase Engineering Database (LED) (http://www.led.uni-stuttgart.de) integrates information on sequence, structure, and function of lipases, esterases, and related proteins. Sequence data on 806 protein entries are assigned to 38 homologous families, which are grouped into 16 superfamilies with no global sequence similarity between each other. For each family, multisequence alignments are provided with functionally relevant residues annotated. Pre-calculated phylogenetic trees allow navigation inside superfamilies. Experimental structures of 45 proteins are superposed and consistently annotated. The LED has been applied to systematically analyze sequence-structure-function relationships of this vast and diverse enzyme class. It is a useful tool to identify functionally relevant residues apart from the active site residues, and to design mutants with desired substrate specificity.

Lipase engineering database: Understanding and exploiting sequence–structure–function relationships

The Lipase Engineering Database is a WWW-accessible resource on sequence–structure–function relationships of microbial lipases. Sequences of 92 microbial lipases and homologous serine hydrolases were assigned to 32 homologous families and 15 superfamilies. Multisequence alignments of all homologous families and superfamilies are provided. Functionally relevant amino acids are annotated. The catalytic serine is part of the conserved nucleophilic elbow and was identified in all sequences by its conserved signature GxSxG. The complete catalytic machinery (catalytic triad and two oxyanion hole residues) could be annotated in 91% of LED sequence entries. Published mutants and their properties are provided. The X-ray structures of 22 lipases were superposed and consistently annotated. Sequence and structure data were applied to study the role of the first oxyanion hole residues. Although the backbone amides contribute to the oxyanion hole rather than side chains, the residues are well conserved. Two sequence signatures including the first oxyanion hole residue were identified: G X and GG GX. In the G X type, the position of the first oxyanion hole residue X is stabilized by one or several anchor residues. If X is hydrophilic, it is hydrogen bonded to hydrophilic anchor residues, while hydrophobic oxyanion hole residues bind to hydrophobic pockets. The GG GX type includes short chain length specific lipases and carboxylesterases. The first oxyanion hole residue G is stabilized by interaction of the dipeptide GX with the side chain of the second oxyanion hole residues, which is a conserved alanine as C-terminal neighbour of the catalytic serine. Thus, short chain specific lipases and carboxylesterase can be identified by combining the signatures GGGX and GxSAG. Consistently annotated aligned sequences and superimposed structures of microbial lipases help to understand the functional role of individual amino acids and thus the LED is a useful tool for protein engineering. The Lipase Engineering Database is available at http://www.led.uni-stuttgart.de/.