Current advances in disulfide connectivity predictions

Pavadai, Elumalai; Wu, Josephine W.; Liu, Hsuan‐Liang

doi:10.1016/j.jtice.2010.05.011

Cited by 2 publications

(1 citation statement)

References 63 publications

(102 reference statements)

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“…They are dissimilar in their physio-chemical properties [ 19 ]. A disulfide bond is covalently formed between two half-cysteine residues by an oxidation reaction which contributes to the stability of a protein structure [ 20 ]. However, a free cysteine residue is capable of forming hydrogen bond with the carbonyl groups of other residues [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Directed Evolution of Recombinant C-Terminal Truncated Staphylococcus epidermidis Lipase AT2 for the Enhancement of Thermostability

Veno

Leow

Ali

et al. 2017

IJMS

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In the industrial processes, lipases are expected to operate at temperatures above 45 °C and could retain activity in organic solvents. Hence, a C-terminal truncated lipase from Staphylococcus epidermis AT2 (rT-M386) was engineered by directed evolution. A mutant with glycine-to-cysteine substitution (G210C) demonstrated a remarkable improvement of thermostability, whereby the mutation enhanced the activity five-fold when compared to the rT-M386 at 50 °C. The rT-M386 and G210C lipases were purified concurrently using GST-affinity chromatography. The biochemical and biophysical properties of both enzymes were investigated. The G210C lipase showed a higher optimum temperature (45 °C) and displayed a more prolonged half-life in the range of 40–60 °C as compared to rT-M386. Both lipases exhibited optimal activity and stability at pH 8. The G210C showed the highest stability in the presence of polar organic solvents at 50 °C compared to the rT-M386. Denatured protein analysis presented a significant change in the molecular ellipticity value above 60 °C, which verified the experimental result on the temperature and thermostability profile of G210C.

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Section: Discussionmentioning

confidence: 99%

Directed Evolution of Recombinant C-Terminal Truncated Staphylococcus epidermidis Lipase AT2 for the Enhancement of Thermostability

Veno

Leow

Ali

et al. 2017

IJMS

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On the Relevance of Sophisticated Structural Annotations for Disulfide Connectivity Pattern Prediction

2013

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Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix) together with the CSP (cysteine separation profile) are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of on the benchmark dataset SPX, which corresponds to improvement over the state of the art. A web-application is available at http://m24.giga.ulg.ac.be:81/x3CysBridges.

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Current advances in disulfide connectivity predictions

Cited by 2 publications

References 63 publications

Directed Evolution of Recombinant C-Terminal Truncated Staphylococcus epidermidis Lipase AT2 for the Enhancement of Thermostability

Directed Evolution of Recombinant C-Terminal Truncated Staphylococcus epidermidis Lipase AT2 for the Enhancement of Thermostability

On the Relevance of Sophisticated Structural Annotations for Disulfide Connectivity Pattern Prediction

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