scholarly journals Improving Biocatalyst Performance by Integrating Statistical Methods into Protein Engineering

2010 ◽  
Vol 76 (19) ◽  
pp. 6397-6403 ◽  
Author(s):  
Moran Brouk ◽  
Yuval Nov ◽  
Ayelet Fishman
Keyword(s):  
Statistical Analysis ◽  
Initial Data ◽  
Rational Design ◽  
Point Mutations ◽  
Enzymatic System ◽  
Wild Type ◽  
Initial Oxidation ◽  
Data Set ◽  
Highly Active ◽  
Average Activity

ABSTRACT Directed evolution and rational design were used to generate active variants of toluene-4-monooxygenase (T4MO) on 2-phenylethanol (PEA), with the aim of producing hydroxytyrosol, a potent antioxidant. Due to the complexity of the enzymatic system—four proteins encoded by six genes—mutagenesis is labor-intensive and time-consuming. Therefore, the statistical model of Nov and Wein (J. Comput. Biol. 12:247-282) was used to reduce the number of variants produced and evaluated in a lab. From an initial data set of 24 variants, with mutations at nine positions, seven double or triple mutants were identified through statistical analysis. The average activity of these mutants was 4.6-fold higher than the average activity of the initial data set. In an attempt to further improve the enzyme activity to obtain PEA hydroxylation, a second round of statistical analysis was performed. Nine variants were considered, with 3, 4, and 5 point mutations. The average activity of the variants obtained in the second statistical round was 1.6-fold higher than in the first round and 7.3-fold higher than that of the initial data set. The best variant discovered, TmoA I100A E214G D285Q, exhibited an initial oxidation rate of 4.4 ± 0.3 nmol/min/mg protein, which is 190-fold higher than the rate obtained by the wild type. This rate was also 2.6-fold higher than the activity of the wild type on the natural substrate toluene. By considering only 16 preselected mutants (out of ∼13,000 possible combinations), a highly active variant was discovered with minimum time and effort.

scholarly journals Improvement in Thermostability of an Achaetomium sp. Strain Xz8 Endopolygalacturonase via the Optimization of Charge-Charge Interactions

2015 ◽  
Vol 81 (19) ◽  
pp. 6938-6944 ◽  
Author(s):  
Tao Tu ◽  
Huiying Luo ◽  
Kun Meng ◽  
Yanli Cheng ◽  
Rui Ma ◽  
...  
Keyword(s):  
Rational Design ◽  
Residual Activity ◽  
Maximal Activity ◽  
Wild Type ◽  
Content Type ◽  
Highly Active ◽  
Wide Ph Range ◽  
Enzyme Thermal Stability ◽  
Ph Range ◽  
Charge Interactions

ABSTRACTImproving enzyme thermostability is of importance for widening the spectrum of application of enzymes. In this study, a structure-based rational design approach was used to improve the thermostability of a highly active, wide-pH-range-adaptable, and stable endopolygalacturonase (PG8fn) fromAchaetomiumsp. strain Xz8 via the optimization of charge-charge interactions. By using the enzyme thermal stability system (ETSS), two residues—D244 and D299—were inferred to be crucial contributors to thermostability. Single (D244A and D299R) and double (D244A/D299R) mutants were then generated and compared with the wild type. All mutants showed improved thermal properties, in the order D244A < D299R < D244A/D299R. In comparison with PG8fn, D244A/D299R showed the most pronounced shifts in temperature of maximum enzymatic activity (Tmax), temperature at which 50% of the maximal activity of an enzyme is retained (T50), and melting temperature (Tm), of about 10, 17, and 10.2°C upward, respectively, with the half-life (t1/2) extended by 8.4 h at 50°C and 45 min at 55°C. Another distinguishing characteristic of the D244A/D299R mutant was its catalytic activity, which was comparable to that of the wild type (23,000 ± 130 U/mg versus 28,000 ± 293 U/mg); on the other hand, it showed more residual activity (8,400 ± 83 U/mg versus 1,400 ± 57 U/mg) after the feed pelleting process (80°C and 30 min). Molecular dynamics (MD) simulation studies indicated that mutations at sites D244 and D299 lowered the overall root mean square deviation (RMSD) and consequently increased the protein rigidity. This study reveals the importance of charge-charge interactions in protein conformation and provides a viable strategy for enhancing protein stability.

scholarly journals Enhancing the Thermostability of Rhizomucor miehei Lipase with a Limited Screening Library by Rational-Design Point Mutations and Disulfide Bonds

2017 ◽  
Vol 84 (2) ◽  
Author(s):  
Guanlin Li ◽  
Xingrong Fang ◽  
Feng Su ◽  
Yuan Chen ◽  
Li Xu ◽  
...  
Keyword(s):  
Catalytic Activity ◽  
Disulfide Bonds ◽  
Rational Design ◽  
Single Point ◽  
Point Mutations ◽  
Rhizomucor Miehei ◽  
Wild Type ◽  
Content Type ◽  
Eukaryotic Protein ◽  
Screening Library

ABSTRACT Rhizomucor miehei lipase (RML), as a kind of eukaryotic protein catalyst, plays an important role in the food, organic chemical, and biofuel industries. However, RML retains its catalytic activity below 50°C, which limits its industrial applications at higher temperatures. Soluble expression of this eukaryotic protein in Escherichia coli not only helps to screen for thermostable mutants quickly but also provides the opportunity to develop rapid and effective ways to enhance the thermal stability of eukaryotic proteins. Therefore, in this study, RML was engineered using multiple computational design methods, followed by filtration via conservation analysis and functional region assessment. We successfully obtained a limited screening library (only 36 candidates) to validate thermostable single point mutants, among which 24 of the candidates showed higher thermostability and 13 point mutations resulted in an apparent melting temperature ( T m app ) of at least 1°C higher. Furthermore, both of the two disulfide bonds predicted from four rational-design algorithms were further introduced and found to stabilize RML. The most stable mutant, with T18K/T22I/E230I/S56C-N63C/V189C-D238C mutations, exhibited a 14.3°C-higher T m app and a 12.5-fold increase in half-life at 70°C. The catalytic efficiency of the engineered lipase was 39% higher than that of the wild type. The results demonstrate that rationally designed point mutations and disulfide bonds can effectively reduce the number of screened clones to enhance the thermostability of RML. IMPORTANCE R. miehei lipase, whose structure is well established, can be widely applied in diverse chemical processes. Soluble expression of R. miehei lipase in E. coli provides an opportunity to explore efficient methods for enhancing eukaryotic protein thermostability. This study highlights a strategy that combines computational algorithms to predict single point mutations and disulfide bonds in RML without losing catalytic activity. Through this strategy, an RML variant with greatly enhanced thermostability was obtained. This study provides a competitive alternative for wild-type RML in practical applications and further a rapid and effective strategy for thermostability engineering.

scholarly journals Packpred: Predicting the functional effect of missense mutations

2021 ◽  
Author(s):  
Kuan Pern Tan ◽  
Tejashree Rajaram Kanitkar ◽  
Kwoh Chee Keong ◽  
M.S. Madhusudhan
Keyword(s):  
Amino Acid ◽  
Single Point ◽  
Point Mutations ◽  
Substitution Matrix ◽  
Saturation Mutagenesis ◽  
Data Sets ◽  
Missense Mutations ◽  
Wild Type ◽  
Data Set ◽  
Functional Consequences

1.AbstractPredicting the functional consequences of single point mutations has relevance to protein function annotation and to clinical analysis/diagnosis. We developed and tested Packpred that makes use of a multi-body clique statistical potential in combination with a depth dependent amino acid substitution matrix (FADHM) and positional Shannon Entropy to predict the functional consequences of point mutations in proteins. Parameters were trained over a saturation mutagenesis data set of T4-lysozyme (1966 mutations). The method was tested over another saturation mutagenesis data set (CcdB; 1534 mutations) and the Missense3D data set (4099 mutations). The performance of Packpred was compared against those of six other contemporary methods. With MCC values of 0.42, 0.47 and 0.36 on the training and testing data sets respectively, Packpred outperforms all method in all data sets, with the exception of marginally underperforming to FADHM in the CcdB data set. On analyzing the results, we could build meta servers that chose best performing methods of wild type amino acids and for wild type-mutant amino acid pairs. This lead to an increase of MCC value of 0.40 and 0.51 for the two meta predictors respectively on the Missense3D data set. We conjecture that it is possible to improve accuracy with better meta predictors as among the 7 methods compared, at the least one method or another is able to correctly predict ∼99% of the data.

scholarly journals Packpred: Predicting the Functional Effect of Missense Mutations

2021 ◽  
Vol 8 ◽  
Author(s):  
Kuan Pern Tan ◽  
Tejashree Rajaram Kanitkar ◽  
Chee Keong Kwoh ◽  
Mallur Srivatsan Madhusudhan
Keyword(s):  
Amino Acid ◽  
Single Point ◽  
Point Mutations ◽  
Substitution Matrix ◽  
Saturation Mutagenesis ◽  
Data Sets ◽  
Missense Mutations ◽  
Wild Type ◽  
Data Set ◽  
Functional Consequences

Predicting the functional consequences of single point mutations has relevance to protein function annotation and to clinical analysis/diagnosis. We developed and tested Packpred that makes use of a multi-body clique statistical potential in combination with a depth-dependent amino acid substitution matrix (FADHM) and positional Shannon entropy to predict the functional consequences of point mutations in proteins. Parameters were trained over a saturation mutagenesis data set of T4-lysozyme (1,966 mutations). The method was tested over another saturation mutagenesis data set (CcdB; 1,534 mutations) and the Missense3D data set (4,099 mutations). The performance of Packpred was compared against those of six other contemporary methods. With MCC values of 0.42, 0.47, and 0.36 on the training and testing data sets, respectively, Packpred outperforms all methods in all data sets, with the exception of marginally underperforming in comparison to FADHM in the CcdB data set. A meta server analysis was performed that chose best performing methods of wild-type amino acids and for wild-type mutant amino acid pairs. This led to an increase in the MCC value of 0.40 and 0.51 for the two meta predictors, respectively, on the Missense3D data set. We conjecture that it is possible to improve accuracy with better meta predictors as among the seven methods compared, at least one method or another is able to correctly predict ∼99% of the data.

Maintenance of a Genetic Data Set on Multiple Data Base and Statistical Analysis Systems

1982 ◽  
Vol 61 (s109) ◽  
pp. 34-34
Author(s):  
Samuel J. Agronow ◽  
Federico C. Mariona ◽  
Frederick C. Koppitch ◽  
Kazutoshi Mayeda
Keyword(s):  
Statistical Analysis ◽  
Data Base ◽  
Genetic Data ◽  
Data Set ◽  
Multiple Data

Highly Active Modified Variants of Recombinant Phospholipase А2 from Streptomyces violaceoruber for Effective Biosynthesis in Yeasts

2019 ◽  
pp. 30-41 ◽  
Author(s):  
E.P. Sannikova ◽  
A.V. Malysheva ◽  
F.A. Klebanov ◽  
D.G. Kozlov
Keyword(s):  
New Technologies ◽  
Specific Activity ◽  
Point Mutations ◽  
Egg Yolk ◽  
Enzyme Preparations ◽  
Highly Active ◽  
High Calcium ◽  
Pla2 Enzyme ◽  
Streptomyces Violaceoruber ◽  
The Cost

The capacity of yeast to produce the highly active variants of PLA2 has been confirmed. The high-active variants were based on the original enzyme from the strain А-2688 of Streptomyces violaceoruber. To reduce the enzyme toxicity and to increase its expression, various approaches were tested including point mutations, construction of artificial N- and/or C-end pro-regions, hybridization with other proteins and engineering or inactivation of glycosylation sites. As a main result, the modified PLA2 enzymes were obtained which have the same secretion level as their low-active predecessors, but specific activity of which was at least tenfold higher. As the main feature, the selected mutants were characterized by a lower affinity for Ca2+ that probably accounts for their low toxicity (and high expression capacity) at the stage of biosynthesis and their ability to activate under special conditions, e.g. during the egg yolk fermentation. The data obtained can provide a basis for the cost reduction of highly active PLA2 enzyme preparations in industries where the application of high calcium concentrations is allowed. recombinant phospholipase А2, Streptomyces violaceoruber, yeasts, secretion, producer strain The work was initiated by the Innovation Center Biriuch - New Technologies, Ltd., and was supported within the framework of the State Assignment no. 595-00004-18 PR.

Interpretable SMILES-based QSAR model of inhibitory activity of sirtuins 1 and 2

2020 ◽  
Vol 23 ◽  
Author(s):  
Apilak Worachartcheewan ◽  
Alla P. Toropova ◽  
Andrey A. Toropov ◽  
Reny Pratiwi ◽  
Virapong Prachayasittikul ◽  
...  
Keyword(s):  
Histone Deacetylases ◽  
Rational Design ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Sirtuin 1 ◽  
Data Set ◽  
Functional Roles ◽  
Molecular Features ◽  
Oecd Principles ◽  
Qsar Models

Background: Sirtuin 1 (Sirt1) and sirtuin 2 (Sirt2) are NAD+ -dependent histone deacetylases which play important functional roles in removal of the acetyl group of acetyl-lysine substrates. Considering the dysregulation of Sirt1 and Sirt2 as etiological causes of diseases, Sirt1 and Sirt2 are lucrative target proteins for treatment, thus there has been great interest in the development of Sirt1 and Sirt2 inhibitors. Objective: This study compiled the bioactivity data of Sirt1 and Sirt2 for the construction of quantitative structure-activity relationship (QSAR) models in accordance with the OECD principles. Method: Simplified molecular input line entry system (SMILES)-based molecular descriptors were used to characterize the molecular features of inhibitors while the Monte Carlo method of the CORAL software was employed for multivariate analysis. The data set was subjected to 3 random splits in which each split separated the data into 4 subsets consisting of training, invisible training, calibration and external sets. Results: Statistical indices for the evaluation of QSAR models suggested good statistical quality for models of Sirt1 and Sirt2 inhibitors. Furthermore, mechanistic interpretation of molecular substructures that are responsible for modulating the bioactivity (i.e. promoters of increase or decrease of bioactivity) was extracted via the analysis of correlation weights. It exhibited molecular features involved Sirt1 and Sirt2 inhibitors. Conclusion: It is anticipated that QSAR models presented herein can be useful as guidelines in the rational design of potential Sirt1 and Sirt2 inhibitors for the treatment of Sirtuin-related diseases.

Rational Design of Colchicine Derivatives as anti-HIV Agents via QSAR and Molecular Docking

2019 ◽  
Vol 15 (4) ◽  
pp. 328-340 ◽  
Author(s):  
Apilak Worachartcheewan ◽  
Napat Songtawee ◽  
Suphakit Siriwong ◽  
Supaluk Prachayasittikul ◽  
Chanin Nantasenamat ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Rational Design ◽  
External Validation ◽  
Rational Drug Design ◽  
Support Vector ◽  
Data Set ◽  
Qsar Models ◽  
Anti Hiv Agents ◽  
Anti Hiv ◽  
Colchicine Derivatives

Background: Human immunodeficiency virus (HIV) is an infective agent that causes an acquired immunodeficiency syndrome (AIDS). Therefore, the rational design of inhibitors for preventing the progression of the disease is required. Objective: This study aims to construct quantitative structure-activity relationship (QSAR) models, molecular docking and newly rational design of colchicine and derivatives with anti-HIV activity. Methods: A data set of 24 colchicine and derivatives with anti-HIV activity were employed to develop the QSAR models using machine learning methods (e.g. multiple linear regression (MLR), artificial neural network (ANN) and support vector machine (SVM)), and to study a molecular docking. Results: The significant descriptors relating to the anti-HIV activity included JGI2, Mor24u, Gm and R8p+ descriptors. The predictive performance of the models gave acceptable statistical qualities as observed by correlation coefficient (Q2) and root mean square error (RMSE) of leave-one out cross-validation (LOO-CV) and external sets. Particularly, the ANN method outperformed MLR and SVM methods that displayed LOO−CV 2 Q and RMSELOO-CV of 0.7548 and 0.5735 for LOOCV set, and Ext 2 Q of 0.8553 and RMSEExt of 0.6999 for external validation. In addition, the molecular docking of virus-entry molecule (gp120 envelope glycoprotein) revealed the key interacting residues of the protein (cellular receptor, CD4) and the site-moiety preferences of colchicine derivatives as HIV entry inhibitors for binding to HIV structure. Furthermore, newly rational design of colchicine derivatives using informative QSAR and molecular docking was proposed. Conclusion: These findings serve as a guideline for the rational drug design as well as potential development of novel anti-HIV agents.

scholarly journals Facet-Dependent Reactivity of Ceria Nanoparticles Exemplified by CeO2-Based Transition Metal Catalysts: A Critical Review

Catalysts ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 452
Author(s):  
Michalis Konsolakis ◽  
Maria Lykaki
Keyword(s):  
Transition Metal ◽  
Co Oxidation ◽  
Critical Review ◽  
Rational Design ◽  
Metal Catalysts ◽  
Co2 Hydrogenation ◽  
Transition Metal Catalysts ◽  
Fine Tuning ◽  
Ceria Nanoparticles ◽  
Highly Active

The rational design and fabrication of highly-active and cost-efficient catalytic materials constitutes the main research pillar in catalysis field. In this context, the fine-tuning of size and shape at the nanometer scale can exert an intense impact not only on the inherent reactivity of catalyst’s counterparts but also on their interfacial interactions; it can also opening up new horizons for the development of highly active and robust materials. The present critical review, focusing mainly on our recent advances on the topic, aims to highlight the pivotal role of shape engineering in catalysis, exemplified by noble metal-free, CeO2-based transition metal catalysts (TMs/CeO2). The underlying mechanism of facet-dependent reactivity is initially discussed. The main implications of ceria nanoparticles’ shape engineering (rods, cubes, and polyhedra) in catalysis are next discussed, on the ground of some of the most pertinent heterogeneous reactions, such as CO2 hydrogenation, CO oxidation, and N2O decomposition. It is clearly revealed that shape functionalization can remarkably affect the intrinsic features and in turn the reactivity of ceria nanoparticles. More importantly, by combining ceria nanoparticles (CeO2 NPs) of specific architecture with various transition metals (e.g., Cu, Fe, Co, and Ni) remarkably active multifunctional composites can be obtained due mainly to the synergistic metalceria interactions. From the practical point of view, novel catalyst formulations with similar or even superior reactivity to that of noble metals can be obtained by co-adjusting the shape and composition of mixed oxides, such as Cu/ceria nanorods for CO oxidation and Ni/ceria nanorods for CO2 hydrogenation. The conclusions derived could provide the design principles of earth-abundant metal oxide catalysts for various real-life environmental and energy applications.

scholarly journals CHROMOSOMAL BASIS OF THE MEROZYGOSITY IN A PARTIALLY DIPLOID MUTANT OF PNEUMOCOCCUS

Genetics ◽  
1975 ◽  
Vol 80 (4) ◽  
pp. 667-678
Author(s):  
Mary Lee S Ledbetter ◽  
Rollin D Hotchkiss
Keyword(s):  
High Efficiency ◽  
Point Mutations ◽  
Resistant Mutant ◽  
Chromosomal Marker ◽  
Structural Abnormality ◽  
C Cells ◽  
Wild Type ◽  
Chromosomal Locus ◽  
Low Efficiency ◽  
Derivatives Of

ABSTRACT A sulfonamide-resistant mutant of pneumococcus, sulr-c, displays a genetic instability, regularly segregating to wild type. DNA extracts of derivatives of the strain possess transforming activities for both the mutant and wild-type alleles, establishing that the strain is a partial diploid. The linkage of sulr-c to strr-61, a stable chromosomal marker, was established, thus defining a chromosomal locus for sulr-c. DNA isolated from sulr-c cells transforms two mutant recipient strains at the same low efficiency as it does a wild-type recipient, although the mutant property of these strains makes them capable of integrating classical "low-efficiency" donor markers equally as efficiently as "high efficiency" markers. Hence sulr-c must have a different basis for its low efficiency than do classical low efficiency point mutations. We suggest that the DNA in the region of the sulr-c mutation has a structural abnormality which leads both to its frequent segregation during growth and its difficulty in efficiently mediating genetic transformation.

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