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      The Effect of Oligomerization on A Solid-Binding Peptide Binding to Silica-Based Materials

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          Abstract

          The bifunctional linker-protein G (LPG) fusion protein comprises a peptide (linker) sequence and a truncated form of Streptococcus strain G148 protein G (protein G). The linker represents a multimeric solid-binding peptide (SBP) comprising 4 × 21-amino acid sequence repeats that display high binding affinity towards silica-based materials. In this study, several truncated derivatives were investigated to determine the effect of the SBP oligomerization on the silica binding function of LPG (for the sake of clarity, LPG will be referred from here on as 4 × LPG). Various biophysical characterization techniques were used to quantify and compare the truncated derivatives against 4 × LPG and protein G without linker (PG). The derivative containing two sequence repeats (2 × LPG) showed minimal binding to silica, while the truncated derivative with only a single sequence (1 × LPG) displayed no binding. The derivative containing three sequence repeats (3 × LPG) was able to bind to silica with a binding affinity of K D = 53.23 ± 4.5 nM, which is 1.5 times lower than that obtained for 4 × LPG under similar experimental conditions. Circular dichroism (CD) spectroscopy and fluorescence spectroscopy studies indicated that the SBP degree of oligomerization has only a small effect on the secondary structure (the linker unravels the beginning of the protein G sequence) and chemical stability of the parent protein G. However, based on quartz crystal microbalance with dissipation monitoring (QCM-D), oligomerization is an important parameter for a strong and stable binding to silica. The replacement of three sequence repeats by a (GGGGS) 12 glycine-rich spacer indicated that the overall length rather than the SBP oligomerization mediated the effective binding to silica.

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          Most cited references 47

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          Understanding biophysicochemical interactions at the nano-bio interface.

          Rapid growth in nanotechnology is increasing the likelihood of engineered nanomaterials coming into contact with humans and the environment. Nanoparticles interacting with proteins, membranes, cells, DNA and organelles establish a series of nanoparticle/biological interfaces that depend on colloidal forces as well as dynamic biophysicochemical interactions. These interactions lead to the formation of protein coronas, particle wrapping, intracellular uptake and biocatalytic processes that could have biocompatible or bioadverse outcomes. For their part, the biomolecules may induce phase transformations, free energy releases, restructuring and dissolution at the nanomaterial surface. Probing these various interfaces allows the development of predictive relationships between structure and activity that are determined by nanomaterial properties such as size, shape, surface chemistry, roughness and surface coatings. This knowledge is important from the perspective of safe use of nanomaterials.
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            Estimation of protein secondary structure from circular dichroism spectra: comparison of CONTIN, SELCON, and CDSSTR methods with an expanded reference set.

             N Sreerama,  R D Woody (2000)
            We have expanded the reference set of proteins used in SELCON3 by including 11 additional proteins (selected from the reference sets of Yang and co-workers and Keiderling and co-workers). Depending on the wavelength range and whether or not denatured proteins are included in the reference set, five reference sets were constructed with the number of reference proteins varying from 29 to 48. The performance of three popular methods for estimating protein secondary structure fractions from CD spectra (implemented in software packages CONTIN, SELCON3, and CDSSTR) and a variant of CONTIN, CONTIN/LL, that incorporates the variable selection method in the locally linearized model in CONTIN, were examined using the five reference sets described here, and a 22-protein reference set. Secondary structure assignments from DSSP were used in the analysis. The performances of all three methods were comparable, in spite of the differences in the algorithms used in the three software packages. While CDSSTR performed the best with a smaller reference set and larger wavelength range, and CONTIN/LL performed the best with a larger reference set and smaller wavelength range, the performances for individual secondary structures were mixed. Analyzing protein CD spectra using all three methods should improve the reliability of predicted secondary structural fractions. The three programs are provided in CDPro software package and have been modified for easier use with the different reference sets described in this paper. CDPro software is available at the website: http://lamar.colostate.edu/ approximately sreeram/CDPro. Copyright 2000 Academic Press.
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              Molecular biomimetics: nanotechnology through biology.

              Proteins, through their unique and specific interactions with other macromolecules and inorganics, control structures and functions of all biological hard and soft tissues in organisms. Molecular biomimetics is an emerging field in which hybrid technologies are developed by using the tools of molecular biology and nanotechnology. Taking lessons from biology, polypeptides can now be genetically engineered to specifically bind to selected inorganic compounds for applications in nano- and biotechnology. This review discusses combinatorial biological protocols, that is, bacterial cell surface and phage-display technologies, in the selection of short sequences that have affinity to (noble) metals, semiconducting oxides and other technological compounds. These genetically engineered proteins for inorganics (GEPIs) can be used in the assembly of functional nanostructures. Based on the three fundamental principles of molecular recognition, self-assembly and DNA manipulation, we highlight successful uses of GEPI in nanotechnology.
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                Author and article information

                Journal
                Nanomaterials (Basel)
                Nanomaterials (Basel)
                nanomaterials
                Nanomaterials
                MDPI
                2079-4991
                30 May 2020
                June 2020
                : 10
                : 6
                Affiliations
                [1 ]Department of Molecular Sciences, Macquarie University, Sydney, NSW 2109, Australia; rachit.bansal@ 123456hdr.mq.edu.au (R.B.); sophia.goodchild@ 123456mq.edu.au (S.C.G.); andrew.care@ 123456mq.edu.au (A.C.); alison.rodger@ 123456mq.edu.au (A.R.)
                [2 ]ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, NSW 2109, Australia
                [3 ]Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2052, Australia; z.elgundi@ 123456unsw.edu.au (Z.E.); m.lord@ 123456unsw.edu.au (M.S.L.)
                [4 ]Biomolecular Discovery Research Centre, Macquarie University, Sydney, NSW 2109, Australia
                Author notes
                [* ]Correspondence: anwar.sunna@ 123456mq.edu.au ; Tel.: +612-9850-4220
                Article
                nanomaterials-10-01070
                10.3390/nano10061070
                7353425
                32486317
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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