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      A Versatile and Robust Serine Protease Inhibitor Scaffold from Actinia tenebrosa

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          Abstract

          Serine proteases play pivotal roles in normal physiology and a spectrum of patho-physiological processes. Accordingly, there is considerable interest in the discovery and design of potent serine protease inhibitors for therapeutic applications. This led to concerted efforts to discover versatile and robust molecular scaffolds for inhibitor design. This investigation is a bioprospecting study that aims to isolate and identify protease inhibitors from the cnidarian Actinia tenebrosa. The study isolated two Kunitz-type protease inhibitors with very similar sequences but quite divergent inhibitory potencies when assayed against bovine trypsin, chymostrypsin, and a selection of human sequence-related peptidases. Homology modeling and molecular dynamics simulations of these inhibitors in complex with their targets were carried out and, collectively, these methodologies enabled the definition of a versatile scaffold for inhibitor design. Thermal denaturation studies showed that the inhibitors were remarkably robust. To gain a fine-grained map of the residues responsible for this stability, we conducted in silico alanine scanning and quantified individual residue contributions to the inhibitor’s stability. Sequences of these inhibitors were then used to search for Kunitz homologs in an A. tenebrosa transcriptome library, resulting in the discovery of a further 14 related sequences. Consensus analysis of these variants identified a rich molecular diversity of Kunitz domains and expanded the palette of potential residue substitutions for rational inhibitor design using this domain.

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          Most cited references56

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          Methods for the directed evolution of proteins.

          Directed evolution has proved to be an effective strategy for improving or altering the activity of biomolecules for industrial, research and therapeutic applications. The evolution of proteins in the laboratory requires methods for generating genetic diversity and for identifying protein variants with desired properties. This Review describes some of the tools used to diversify genes, as well as informative examples of screening and selection methods that identify or isolate evolved proteins. We highlight recent cases in which directed evolution generated enzymatic activities and substrate specificities not known to exist in nature.
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            Increasing the precision of comparative models with YASARA NOVA--a self-parameterizing force field.

            One of the conclusions drawn at the CASP4 meeting in Asilomar was that applying various force fields during refinement of template-based models tends to move predictions in the wrong direction, away from the experimentally determined coordinates. We have derived an all-atom force field aimed at protein and nucleotide optimization in vacuo (NOVA), which has been specifically designed to avoid this problem. NOVA resembles common molecular dynamics force fields but has been automatically parameterized with two major goals: (i) not to make high resolution X-ray structures worse and (ii) to improve homology models built by WHAT IF. Force-field parameters were not required to be physically correct; instead, they were optimized with random Monte Carlo moves in force-field parameter space, each one evaluated by simulated annealing runs of a 50-protein optimization set. Errors inherent to the approximate force-field equation could thus be canceled by errors in force-field parameters. Compared with the optimization set, the force field did equally well on an independent validation set and is shown to move in silico models closer to reality. It can be applied to modeling applications as well as X-ray and NMR structure refinement. A new method to assign force-field parameters based on molecular trees is also presented. A NOVA server is freely accessible at http://www.yasara.com/servers Copyright 2002 Wiley-Liss, Inc.
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              Protein sequence alignments: a strategy for the hierarchical analysis of residue conservation.

              An algorithm is described for the systematic characterization of the physico-chemical properties seen at each position in a multiple protein sequence alignment. The new algorithm allows questions important in the design of mutagenesis experiments to be quickly answered since positions in the alignment that show unusual or interesting residue substitution patterns may be rapidly identified. The strategy is based on a flexible set-based description of amino acid properties, which is used to define the conservation between any group of amino acids. Sequences in the alignment are gathered into subgroups on the basis of sequence similarity, functional, evolutionary or other criteria. All pairs of subgroups are then compared to highlight positions that confer the unique features of each subgroup. The algorithm is encoded in the computer program AMAS (Analysis of Multiply Aligned Sequences) which provides a textual summary of the analysis and an annotated (boxed, shaded and/or coloured) multiple sequence alignment. The algorithm is illustrated by application to an alignment of 67 SH2 domains where patterns of conserved hydrophobic residues that constitute the protein core are highlighted. The analysis of charge conservation across annexin domains identifies the locations at which conserved charges change sign. The algorithm simplifies the analysis of multiple sequence data by condensing the mass of information present, and thus allows the rapid identification of substitutions of structural and functional importance.
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                Author and article information

                Journal
                Mar Drugs
                Mar Drugs
                marinedrugs
                Marine Drugs
                MDPI
                1660-3397
                12 December 2019
                December 2019
                : 17
                : 12
                : 701
                Affiliations
                [1 ]Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD 4059, Australia; xingchen.chen@ 123456connect.qut.edu.au (X.C.); darren.leahy@ 123456hdr.qut.edu.au (D.L.); j.vanhaeften@ 123456qut.edu.au (J.V.H.); chloe.vanderburg@ 123456connect.qut.edu.au (C.A.v.d.B.); a.pavasovic@ 123456qut.edu.au (A.P.)
                [2 ]School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD 4000, Australia; p.hartfield@ 123456qut.edu.au
                [3 ]School of Earth, Environmental and Biological Sciences, Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4000, Australia; p.prentis@ 123456qut.edu.au
                [4 ]Institute for Future Environments, Queensland University of Technology, Brisbane, QLD 4000, Australia
                [5 ]Institute for Molecular Bioscience, University of Queensland, St Lucia, QLD 4072, Australia; b.madio@ 123456uq.edu.au (B.M.); glenn.king@ 123456imb.uq.edu.au (G.F.K.)
                [6 ]Centre for Advanced Imaging, University of Queensland, St Lucia, QLD 4072, Australia; b.hamilton@ 123456uq.edu.au (B.R.H.); eivind.a.b.undheim@ 123456ntnu.no (E.A.B.U.)
                [7 ]Centre for Biodiversity Dynamics, Department of Biology, Norwegian University of Science and Technology, 7491 Trondheim, Norway
                [8 ]Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, PO Box 1066 Blindern, 0316 Oslo, Norway
                [9 ]Department of Medical Biosciences, Umeå University, 901 87 Umeå, Sweden; maria.brattsand@ 123456umu.se
                Author notes
                [* ]Correspondence: j2.harris@ 123456qut.edu.au ; Tel.: +61-7-3138-6186; Fax: +61-7-3138-6030
                Author information
                https://orcid.org/0000-0001-6587-8875
                https://orcid.org/0000-0002-2308-2200
                https://orcid.org/0000-0002-8667-3999
                https://orcid.org/0000-0001-7175-1336
                Article
                marinedrugs-17-00701
                10.3390/md17120701
                6950308
                31842369
                142a1aa3-b4cb-416b-85c8-ada856d2e7a7
                © 2019 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/).

                History
                : 29 October 2019
                : 10 December 2019
                Categories
                Article

                Pharmacology & Pharmaceutical medicine
                actinia tenebrosa,kallikrein-related peptidases,kunitz inhibitor,serine protease,mass spectrometry imaging,molecular dynamics simulation

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