Novel Strategy for Protein Exploration: High-throughput Screening Assisted with Fuzzy Neural Network

Kato, Ryuji; Nakano, Hideo; Konishi, Hiroyuki; Kato, Katsuya; Koga, Yuchi; Yamané, Tsuneo; Kobayashi, Takeshi; Honda, Hiroyuki

doi:10.1016/j.jmb.2005.05.026

Cited by 23 publications

(20 citation statements)

References 29 publications

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“…The remaining datasets, modeling datasets A1, were newly split into four datasets again and subjected to 4-fold cross-validation (CV), using three datasets as training data and one dataset for validation. Through this 4-fold CV, the best combination of input parameters, which provides the best predictive accuracy as an average throughout the CV, was selected by the use of the parameter-increasing method (PIM) (13). Blind dataset A1 was evaluated with this parameter combination, and the model's accuracy (designated as accuracy A1) was obtained.…”

Section: Methodsmentioning

confidence: 99%

“…It has been shown that high predictive accuracies can be obtained in the analysis of various data derived from complex phenomena, such as bioprocess factors and fermentation efficiency (12), protein structure information and protein enantioselectivity (13), expression profiles of microarray data and the diagnosis of disease development (14), and the prediction of peptide binding to MHC class II (9). As compared with ANN, FNN has an advantage: the fuzzy layer.…”

Section: Introductionmentioning

confidence: 99%

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Computationally Assisted Screening and Design of Cell-Interactive Peptides by a Cell-Based Assay Using Peptide Arrays and a Fuzzy Neural Network Algorithm

et al. 2008

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We developed a method of effective peptide screening that combines experiments and computational analysis. The method is based on the concept that screening efficiency can be enhanced from even limited data by use of a model derived from computational analysis that serves as a guide to screening and combining the model with subsequent repeated experiments. Here we focus on cell-adhesion peptides as a model application of this peptide-screening strategy. Cell-adhesion peptides were screened by use of a cell-based assay of a peptide array. Starting with the screening data obtained from a limited, random 5-mer library (643 sequences), a rule regarding structural characteristics of cell-adhesion peptides was extracted by fuzzy neural network (FNN) analysis. According to this rule, peptides with unfavored residues in certain positions that led to inefficient binding were eliminated from the random sequences. In the restricted, second random library (273 sequences), the yield of cell-adhesion peptides having an adhesion rate more than 1.5-fold to that of the basal array support was significantly high (31%) compared with the unrestricted random library (20%). In the restricted third library (50 sequences), the yield of cell-adhesion peptides increased to 84%. We conclude that a repeated cycle of experiments screening limited numbers of peptides can be assisted by the rule-extracting feature of FNN.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computationally Assisted Screening and Design of Cell-Interactive Peptides by a Cell-Based Assay Using Peptide Arrays and a Fuzzy Neural Network Algorithm

et al. 2008

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“…This amino acid had been previously described to be important for enzyme activity, and it was expected that mutations at this position could generate variants displaying different catalytic activities. 1,2,21 Storage microplates were inoculated with 8 colonies of each mutant, 16 colonies of wild-type BCL (which will be used as reference), and 8 colonies of negative control. The last 8 wells were filled with culture medium and not inoculated to check the absence of growth.…”

Section: Validation Of the Screening Protocolmentioning

confidence: 99%

“…A NUMBER OF STUDIES have described successful engineering of lipases for enantioselectivity specificity, [1][2][3][4][5] but few of them are concerned with the lipase from Burkholderia cepacia ATCC21808 (BCL; triacylglycerol acylhydrolases, EC 3.1.1.3). Although this enzyme is very attractive for deracemization of valuable organic intermediates, [6][7][8][9][10][11] combinatorial engineering is limited by problems of expression.…”

Section: Introductionmentioning

confidence: 99%

Small-Scale Production of Burkholderia cepacia ATCC21808 Lipase Adapted to High-Throughput Screening

Puech-Guenot¹,

Lafaquière²,

Guieysse³

et al. 2008

SLAS Discovery

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“…Directed evolution or rational design techniques have proven to be successful for the development of lipases with either enhanced or inverted enantioselectivity compared to their parental enzymes. [5][6][7] Amongst lipases used for racemic resolution, lipase from Burk-A C H T U N G T R E N N U N G holderia cepacia (BCL) has proven to be very useful for the resolution of racemic mixtures of primary and secondary alcohols [8] and carboxylic acids. [9,10] In a previous study [11,12] focused on the understanding of the factors involved in racemic resolution of 2-substituted carboxylic acids, it was suggested that given the topology of BCL active site, which is located at the bottom of a narrow 17 pocket, the enzyme ligand affinity and, by extension enantioselectivity, could be affected by the accessibility of the substrate to the catalytic site and the difficulty encountered by the substrate in adopting a productive conformation at the reaction site.…”

Section: Introductionmentioning

confidence: 99%

Control of Lipase Enantioselectivity by Engineering the Substrate Binding Site and Access Channel

et al. 2009

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Lipase from Burkholderia cepacia (BCL) has proven to be a very useful biocatalyst for the resolution of 2-substituted racemic acid derivatives, which are important chiral building blocks. Our previous work showed that enantioselectivity of the wild-type BCL could be improved by chemical engineering of the substrate's molecular structure. From this earlier study, three amino acids (L17, V266 and L287) were proposed as targets for mutagenesis aimed at tailoring enzyme enantioselectivity. In the present work, a small library of 57 BCL single mutants targeted on these three residues was constructed and screened for enantioselectivity towards (R,S)-2-chloro ethyl 2-bromophenylacetate. This led to the fast isolation of three single mutants with a remarkable tenfold enhanced or reversed enantioselectivity. Analysis of substrate docking and access trajectories in the active site was then performed. From this analysis, the construction of 13 double mutants was proposed. Among them, an outstanding improved mutant of BCL was isolated that showed an E value of 178 and a 15-fold enhanced specific activity compared to the parental enzyme; thus, this study demonstrates the efficiency of the semirational engineering strategy.

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Novel Strategy for Protein Exploration: High-throughput Screening Assisted with Fuzzy Neural Network

Cited by 23 publications

References 29 publications

Computationally Assisted Screening and Design of Cell-Interactive Peptides by a Cell-Based Assay Using Peptide Arrays and a Fuzzy Neural Network Algorithm

Computationally Assisted Screening and Design of Cell-Interactive Peptides by a Cell-Based Assay Using Peptide Arrays and a Fuzzy Neural Network Algorithm

Small-Scale Production of Burkholderia cepacia ATCC21808 Lipase Adapted to High-Throughput Screening

Control of Lipase Enantioselectivity by Engineering the Substrate Binding Site and Access Channel

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