scholarly journals Solubility-Weighted Index: fast and accurate prediction of protein solubility

2020 ◽  
Author(s):  
Bikash K. Bhandari ◽  
Paul P. Gardner ◽  
Chun Shen Lim
Keyword(s):  
Protein Expression ◽  
Protein Production ◽  
Protein Solubility ◽  
Region Of Interest ◽  
Structural Flexibility ◽  
Web Interface ◽  
Solubility Prediction ◽  
Prediction Tools ◽  
Weighted Index ◽  
Link Type

ABSTRACTMotivationRecombinant protein production is a widely used technique in the biotechnology and biomedical industries, yet only a quarter of target proteins are soluble and can therefore be purified.ResultsWe have discovered that global structural flexibility, which can be modeled by normalised B-factors, accurately predicts the solubility of 12,216 recombinant proteins expressed in Escherichia coli. We have optimised B-factors, and derived a new set of values for solubility scoring that further improves prediction accuracy. We call this new predictor the ‘Solubility-Weighted Index’ (SWI). Importantly, SWI outperforms many existing protein solubility prediction tools. Furthermore, we have developed ‘SoDoPE’ (Soluble Domain for Protein Expression), a web interface that allows users to choose a protein region of interest for predicting and maximising both protein expression and solubility.AvailabilityThe SoDoPE web server and source code are freely available at https://tisigner.com/sodope and https://github.com/Gardner-BinfLab/TISIGNER-ReactJS, respectively. The code and data for reproducing our analysis can be found at https://github.com/Gardner-BinfLab/SoDoPE_paper2020.

scholarly journals Solubility-Weighted Index: fast and accurate prediction of protein solubility

2020 ◽  
Vol 36 (18) ◽  
pp. 4691-4698 ◽  
Author(s):  
Bikash K Bhandari ◽  
Paul P Gardner ◽  
Chun Shen Lim
Keyword(s):  
Protein Expression ◽  
Protein Production ◽  
Protein Solubility ◽  
Region Of Interest ◽  
Supplementary Information ◽  
Structural Flexibility ◽  
Web Interface ◽  
Solubility Prediction ◽  
Prediction Tools ◽  
Weighted Index

Abstract Motivation Recombinant protein production is a widely used technique in the biotechnology and biomedical industries, yet only a quarter of target proteins are soluble and can therefore be purified. Results We have discovered that global structural flexibility, which can be modeled by normalized B-factors, accurately predicts the solubility of 12 216 recombinant proteins expressed in Escherichia coli. We have optimized these B-factors, and derived a new set of values for solubility scoring that further improves prediction accuracy. We call this new predictor the ‘Solubility-Weighted Index’ (SWI). Importantly, SWI outperforms many existing protein solubility prediction tools. Furthermore, we have developed ‘SoDoPE’ (Soluble Domain for Protein Expression), a web interface that allows users to choose a protein region of interest for predicting and maximizing both protein expression and solubility. Availability and implementation The SoDoPE web server and source code are freely available at https://tisigner.com/sodope and https://github.com/Gardner-BinfLab/TISIGNER-ReactJS, respectively. The code and data for reproducing our analysis can be found at https://github.com/Gardner-BinfLab/SoDoPE_paper_2020. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Improving recombinant protein production using TISIGNER.com

2020 ◽  
Author(s):  
Bikash K. Bhandari ◽  
Chun Shen Lim ◽  
Paul P. Gardner
Keyword(s):  
Web Services ◽  
Recombinant Protein ◽  
Protein Expression ◽  
Translation Initiation ◽  
Recombinant Protein Production ◽  
Protein Production ◽  
Recombinant Protein Expression ◽  
Accurate Prediction ◽  
Coding Region ◽  
Link Type

ABSTRACTPlanning experiments using accurate prediction algorithms could mitigate failures in recombinant protein production. We have developed TISIGNER.com with the aim of addressing the technical challenges in recombinant protein production. We offer two web services, TIsigner (Translation Initiation coding region designer) and SoDoPE (Soluble Domain for Protein Expression), which are specialised in prediction/optimisation of recombinant protein expression and solubility, respectively. Importantly, TIsigner and SoDoPE are linked, which allows users to switch between the tools when optimising their genes of interest.

scholarly journals Mitigation of deleterious phenotypes in chloroplast-engineered plants accumulating high levels of foreign proteins

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Jennifer A. Schmidt ◽  
Lubna V. Richter ◽  
Lisa A. Condoluci ◽  
Beth A. Ahner
Keyword(s):  
Protein Expression ◽  
Protein Production ◽  
Biomass Accumulation ◽  
Cellulase Production ◽  
Protein Yield ◽  
Total Soluble Protein ◽  
Foreign Protein ◽  
Active Components ◽  
Dwarf Phenotype ◽  
Mutant Phenotypes

Abstract Background The global demand for functional proteins is extensive, diverse, and constantly increasing. Medicine, agriculture, and industrial manufacturing all rely on high-quality proteins as major active components or process additives. Historically, these demands have been met by microbial bioreactors that are expensive to operate and maintain, prone to contamination, and relatively inflexible to changing market demands. Well-established crop cultivation techniques coupled with new advancements in genetic engineering may offer a cheaper and more versatile protein production platform. Chloroplast-engineered plants, like tobacco, have the potential to produce large quantities of high-value proteins, but often result in engineered plants with mutant phenotypes. This technology needs to be fine-tuned for commercial applications to maximize target protein yield while maintaining robust plant growth. Results Here, we show that a previously developed Nicotiana tabacum line, TetC-cel6A, can produce an industrial cellulase at levels of up to 28% of total soluble protein (TSP) with a slight dwarf phenotype but no loss in biomass. In seedlings, the dwarf phenotype is recovered by exogenous application of gibberellic acid. We also demonstrate that accumulating foreign protein represents an added burden to the plants’ metabolism that can make them more sensitive to limiting growth conditions such as low nitrogen. The biomass of nitrogen-limited TetC-cel6A plants was found to be as much as 40% lower than wildtype (WT) tobacco, although heterologous cellulase production was not greatly reduced compared to well-fertilized TetC-cel6A plants. Furthermore, cultivation at elevated carbon dioxide (1600 ppm CO2) restored biomass accumulation in TetC-cel6A plants to that of WT, while also increasing total heterologous protein yield (mg Cel6A plant−1) by 50–70%. Conclusions The work reported here demonstrates that well-fertilized tobacco plants have a substantial degree of flexibility in protein metabolism and can accommodate considerable levels of some recombinant proteins without exhibiting deleterious mutant phenotypes. Furthermore, we show that the alterations to protein expression triggered by growth at elevated CO2 can help rebalance endogenous protein expression and/or increase foreign protein production in chloroplast-engineered tobacco.

scholarly journals SOLart: a structure-based method to predict protein solubility and aggregation

2019 ◽  
Author(s):  
Qingzhen Hou ◽  
Jean Marc Kwasigroch ◽  
Marianne Rooman ◽  
Fabrizio Pucci
Keyword(s):  
Solvent Accessibility ◽  
Pearson Correlation ◽  
Protein Solubility ◽  
Independent Set ◽  
Supplementary Information ◽  
Training Dataset ◽  
Solubility Prediction ◽  
High Concentration ◽  
Structural Genomic ◽  
Genomic Studies

Abstract Motivation The solubility of a protein is often decisive for its proper functioning. Lack of solubility is a major bottleneck in high-throughput structural genomic studies and in high-concentration protein production, and the formation of protein aggregates causes a wide variety of diseases. Since solubility measurements are time-consuming and expensive, there is a strong need for solubility prediction tools. Results We have recently introduced solubility-dependent distance potentials that are able to unravel the role of residue–residue interactions in promoting or decreasing protein solubility. Here, we extended their construction by defining solubility-dependent potentials based on backbone torsion angles and solvent accessibility, and integrated them, together with other structure- and sequence-based features, into a random forest model trained on a set of Escherichia coli proteins with experimental structures and solubility values. We thus obtained the SOLart protein solubility predictor, whose most informative features turned out to be folding free energy differences computed from our solubility-dependent statistical potentials. SOLart performances are very good, with a Pearson correlation coefficient between experimental and predicted solubility values of almost 0.7 both in cross-validation on the training dataset and in an independent set of Saccharomyces cerevisiae proteins. On test sets of modeled structures, only a limited drop in performance is observed. SOLart can thus be used with both high-resolution and low-resolution structures, and clearly outperforms state-of-art solubility predictors. It is available through a user-friendly webserver, which is easy to use by non-expert scientists. Availability and implementation The SOLart webserver is freely available at http://babylone.ulb.ac.be/SOLART/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals PaRSnIP: sequence-based protein solubility prediction using gradient boosting machine

2017 ◽  
Vol 34 (7) ◽  
pp. 1092-1098 ◽  
Author(s):  
Reda Rawi ◽  
Raghvendra Mall ◽  
Khalid Kunji ◽  
Chen-Hsiang Shen ◽  
Peter D Kwong ◽  
...  
Keyword(s):  
Protein Solubility ◽  
Gradient Boosting ◽  
Solubility Prediction ◽  
Gradient Boosting Machine

scholarly journals Insights into the role of electrostatics in temperature adaptation: a comparative study of psychrophilic, mesophilic, and thermophilic subtilisin-like serine proteases

RSC Advances ◽  
2018 ◽  
Vol 8 (52) ◽  
pp. 29698-29713 ◽  
Author(s):  
Yuan-Ling Xia ◽  
Jian-Hong Sun ◽  
Shi-Meng Ai ◽  
Yi Li ◽  
Xing Du ◽  
...  
Keyword(s):  
Comparative Study ◽  
Serine Proteases ◽  
Protein Solubility ◽  
Temperature Adaptation ◽  
Structural Flexibility ◽  
Charged Surface ◽  
Surface Patches

Differently charged surface patches contribute to temperature adaptation of subtilisin-like serine proteases through affecting/modulating the protein solubility and thermostability and the structural flexibility/rigidity/stability.

Rapid protein expression analysis with an interferometric biosensor for monitoring protein production

2007 ◽  
Vol 387 (5) ◽  
pp. 1921-1932 ◽  
Author(s):  
Christian Hoffmann ◽  
Katrin Schmitt ◽  
Albrecht Brandenburg ◽  
Steffen Hartmann
Keyword(s):  
Protein Expression ◽  
Expression Analysis ◽  
Protein Production ◽  
Interferometric Biosensor
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