Repurposing proteins for new bioinorganic functions

2017 ◽  
Vol 61 (2) ◽  
pp. 245-258 ◽  
Author(s):  
Lewis A. Churchfield ◽  
Athira George ◽  
F. Akif Tezcan
Keyword(s):  
Synthetic Biology ◽  
Supramolecular Chemistry ◽  
Protein Design ◽  
Chemical Properties ◽  
Bioinorganic Chemistry ◽  
Design Principles ◽  
Protein Scaffolds ◽  
Materials Engineering ◽  
Physico Chemical ◽  
Protein Design And Engineering

Inspired by the remarkable sophistication and complexity of natural metalloproteins, the field of protein design and engineering has traditionally sought to understand and recapitulate the design principles that underlie the interplay between metals and protein scaffolds. Yet, some recent efforts in the field demonstrate that it is possible to create new metalloproteins with structural, functional and physico-chemical properties that transcend evolutionary boundaries. This essay aims to highlight some of these efforts and draw attention to the ever-expanding scope of bioinorganic chemistry and its new connections to synthetic biology, biotechnology, supramolecular chemistry and materials engineering.

scholarly journals Exploring protein sequence and functional spaces using adversarial autoencoder

2020 ◽  
Author(s):  
Tristan Bitard-Feildel
Keyword(s):  
Protein Design ◽  
Protein Sequence ◽  
Functional Organization ◽  
Chemical Properties ◽  
Protein Sequences ◽  
Generative Models ◽  
Physico Chemical ◽  
Latent Space ◽  
Data Points ◽  
New Protein

AbstractShedding light on the relationship between protein sequences and their functions is a challenging task with implications for our understanding of protein evolution, diseases, or protein design. However, due to its complexity, protein sequence/function space is hard to comprehend with potential numerous human bias. Generative models help to decipher complex systems due to their abilities to learn and recreate data specificity. Applied to protein sequences, they can help to pointing out relationships between protein positions and functions or to capture the different sequence patterns associated to functions. In this study, an unsupervised generative approach based on auto-encoder (AE) is proposed to generate and explore new protein sequences with respect to their functions. AE is tested on three protein families known for their multiple functions, with manually curated annotations for one family. Functional labeling of encoded sequences on a two dimensional latent space computed by AE for each family shows a good agreement regarding the ability of the latent space to capture the functional organization and specificity of the sequences. Furthermore, arithmetic between latent spaces and latent space interpolations between encoded sequences are tested as a way to generate new intermediate protein sequences sharing sequential and functional properties of sequences issued of families with different sequences and functions. Using structural homology modeling and assessment, it can be observed that the new protein sequences generated using latent space arithmetic display intermediate physico-chemical properties and energies when compared to the original sequences of the families. Finally, protein sequences generated by interpolation between data points of the latent space show the ability of the AE to smoothly generalize and to produce meaningful biological sequences from an uncharted area of the latent space.Code and data used for this study are freely available at https://github.com/T-B-F/aae4seq.

scholarly journals The Surfactin-Like Lipopeptides From Bacillus spp.: Natural Biodiversity and Synthetic Biology for a Broader Application Range

2021 ◽  
Vol 9 ◽  
Author(s):  
Ariane Théatre ◽  
Carolina Cano-Prieto ◽  
Marco Bartolini ◽  
Yoann Laurin ◽  
Magali Deleu ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Biological Activities ◽  
Chemical Properties ◽  
Large Set ◽  
Application Range ◽  
Peptide Synthetases ◽  
Peptide Moiety ◽  
Physico Chemical ◽  
Bacillus Spp ◽  
First Time

Surfactin is a lipoheptapeptide produced by several Bacillus species and identified for the first time in 1969. At first, the biosynthesis of this remarkable biosurfactant was described in this review. The peptide moiety of the surfactin is synthesized using huge multienzymatic proteins called NonRibosomal Peptide Synthetases. This mechanism is responsible for the peptide biodiversity of the members of the surfactin family. In addition, on the fatty acid side, fifteen different isoforms (from C12 to C17) can be incorporated so increasing the number of the surfactin-like biomolecules. The review also highlights the last development in metabolic modeling and engineering and in synthetic biology to direct surfactin biosynthesis but also to generate novel derivatives. This large set of different biomolecules leads to a broad spectrum of physico-chemical properties and biological activities. The last parts of the review summarized the numerous studies related to the production processes optimization as well as the approaches developed to increase the surfactin productivity of Bacillus cells taking into account the different steps of its biosynthesis from gene transcription to surfactin degradation in the culture medium.

Decoration of specific sites on freeze-fractured membranes

1978 ◽  
Vol 36 (2) ◽  
pp. 140-141
Author(s):  
H. Gross ◽  
H. Moor
Keyword(s):  
Pure Water ◽  
Freeze Fracture ◽  
Chemical Properties ◽  
Surface Forces ◽  
Sulfate Pentahydrate ◽  
Copper Sulfate Pentahydrate ◽  
Physico Chemical ◽  
Water Of Hydration ◽  
Small Container ◽  
Binding Forces

Fracturing under ultrahigh vacuum (UHV, p ≤ 10-9 Torr) produces membrane fracture faces devoid of contamination. Such clean surfaces are a prerequisite foe studies of interactions between condensing molecules is possible and surface forces are unequally distributed, the condensate will accumulate at places with high binding forces; crystallites will arise which may be useful a probes for surface sites with specific physico-chemical properties. Specific “decoration” with crystallites can be achieved nby exposing membrane fracture faces to water vopour. A device was developed which enables the production of pure water vapour and the controlled variation of its partial pressure in an UHV freeze-fracture apparatus (Fig.1a). Under vaccum (≤ 10-3 Torr), small container filled with copper-sulfate-pentahydrate is heated with a heating coil, with the temperature controlled by means of a thermocouple. The water of hydration thereby released enters a storage vessel.

Physico-Chemical Properties of Recombinant Desulphatohirudin

1990 ◽  
Vol 63 (03) ◽  
pp. 499-504 ◽  
Author(s):  
A Electricwala ◽  
L Irons ◽  
R Wait ◽  
R J G Carr ◽  
R J Ling ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Gel Filtration ◽  
Chemical Properties ◽  
Alpha Helix ◽  
Apparent Molecular Weight ◽  
Correlation Spectroscopy ◽  
Nmr Studies ◽  
Recombinant Hirudin ◽  
Physico Chemical ◽  
Recombinant Molecule

SummaryPhysico-chemical properties of recombinant desulphatohirudin expressed in yeast (CIBA GEIGY code No. CGP 39393) were reinvestigated. As previously reported for natural hirudin, the recombinant molecule exhibited abnormal behaviour by gel filtration with an apparent molecular weight greater than that based on the primary structure. However, molecular weight estimation by SDS gel electrophoresis, FAB-mass spectrometry and Photon Correlation Spectroscopy were in agreement with the theoretical molecular weight, with little suggestion of dimer or aggregate formation. Circular dichroism studies of the recombinant molecule show similar spectra at different pH values but are markedly different from that reported by Konno et al. (13) for a natural hirudin-variant. Our CD studies indicate the presence of about 60% beta sheet and the absence of alpha helix in the secondary structure of recombinant hirudin, in agreement with the conformation determined by NMR studies (17)

Physico-chemical properties of the rare-earth metals, scandium, and yttrium

1963 ◽  
Vol 79 (2) ◽  
pp. 263-293 ◽  
Author(s):  
E.M. Savitskii ◽  
V.F. Terekhova ◽  
O.P. Naumkin
Keyword(s):  
Rare Earth ◽  
Rare Earth Metals ◽  
Chemical Properties ◽  
Physico Chemical ◽  
The Rare Earth

Physico chemical properties and gas adsorption separation characteristics of Itaya zeolite and its modified products.

1990 ◽  
Vol 39 (442) ◽  
pp. 996-1000 ◽  
Author(s):  
Ayao TAKASAKA ◽  
Hideyuki NEMOTO ◽  
Hirohiko KONO ◽  
Yoshihiro MATSUDA
Keyword(s):  
Gas Adsorption ◽  
Chemical Properties ◽  
Physico Chemical

Development of Ketchup from Sudanese Red karkade (Hibiscus sabdariffa L.) byproduct

Food Biology ◽  
1970 ◽  
pp. 19-23
Author(s):  
Nawal Abdel-Gayoum Abdel-Rahman
Keyword(s):  
Sensory Quality ◽  
Chemical Properties ◽  
Storage Period ◽  
Gum Arabic ◽  
Raw Material ◽  
Soluble Solids ◽  
Hibiscus Sabdariffa ◽  
Overall Acceptability ◽  
Physico Chemical ◽  
Tomato Ketchup

The aim of this study is to use of karkede (Hibiscus sabdariffa L.) byproduct as raw material to make ketchup instead of tomato. Ketchup is making of various pulps, but the best type made from tomatoes. Roselle having adequate amounts of macro and micro elements, and it is rich in source of anthocyanine. The ketchup made from pulped of waste of soaked karkede, and homogenized with starch, salt, sugar, ginger (Zingiber officinale), kusbara (Coriandrum sativum) and gum Arabic. Then processed and filled in glass bottles and stored at two different temperatures, ambient and refrigeration. The total solids, total soluble solids, pH, ash, total titratable acidity and vitamin C of ketchup were determined. As well as, total sugars, reducing sugars, colour density, and sodium chloride percentage were evaluated. The sensory quality of developed product was determined immediately and after processing, which included colour, taste, odour, consistency and overall acceptability. The suitability during storage included microbial growth, physico-chemical properties and sensory quality. The karkede ketchup was found free of contaminants throughout storage period at both storage temperatures. Physico-chemical properties were found to be significantly differences at p?0.05 level during storage. There were no differences between karkade ketchup and market tomato ketchup concerning odour, taste, odour, consistency and overall acceptability. These results are encouraging for use of roselle cycle as a raw material to make acceptable karkade ketchup.

Graph Neural Networks for Prediction of Fuel Ignition Quality

2020 ◽  
Author(s):  
Artur Schweidtmann ◽  
Jan Rittig ◽  
Andrea König ◽  
Martin Grohe ◽  
Alexander Mitsos ◽  
...  
Keyword(s):  
Neural Networks ◽  
Octane Number ◽  
Molecular Graph ◽  
Chemical Properties ◽  
Graph Representation ◽  
Structure Property ◽  
Oxygenated Hydrocarbons ◽  
Physico Chemical ◽  
Ignition Quality ◽  
Graph Neural Networks

<div>Prediction of combustion-related properties of (oxygenated) hydrocarbons is an important and challenging task for which quantitative structure-property relationship (QSPR) models are frequently employed. Recently, a machine learning method, graph neural networks (GNNs), has shown promising results for the prediction of structure-property relationships. GNNs utilize a graph representation of molecules, where atoms correspond to nodes and bonds to edges containing information about the molecular structure. More specifically, GNNs learn physico-chemical properties as a function of the molecular graph in a supervised learning setup using a backpropagation algorithm. This end-to-end learning approach eliminates the need for selection of molecular descriptors or structural groups, as it learns optimal fingerprints through graph convolutions and maps the fingerprints to the physico-chemical properties by deep learning. We develop GNN models for predicting three fuel ignition quality indicators, i.e., the derived cetane number (DCN), the research octane number (RON), and the motor octane number (MON), of oxygenated and non-oxygenated hydrocarbons. In light of limited experimental data in the order of hundreds, we propose a combination of multi-task learning, transfer learning, and ensemble learning. The results show competitive performance of the proposed GNN approach compared to state-of-the-art QSPR models making it a promising field for future research. The prediction tool is available via a web front-end at www.avt.rwth-aachen.de/gnn.</div>

Sign in / Sign up

Export Citation Format

Share Document