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000306286 0247_ $$2doi$$a10.1042/BCJ20180070
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000306286 0247_ $$2ISSN$$a0306-3283
000306286 0247_ $$2ISSN$$a0264-6021
000306286 0247_ $$2ISSN$$a0306-3275
000306286 0247_ $$2ISSN$$a1470-8728
000306286 037__ $$aDKFZ-2025-02512
000306286 041__ $$aEnglish
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000306286 1001_ $$aCohen, Itay$$b0
000306286 245__ $$aPre-equilibrium competitive library screening for tuning inhibitor association rate and specificity toward serine proteases.
000306286 260__ $$aLondon$$bPortland Press$$c2018
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000306286 520__ $$aHigh structural and sequence similarity within protein families can pose significant challenges to the development of selective inhibitors, especially toward proteolytic enzymes. Such enzymes usually belong to large families of closely similar proteases and may also hydrolyze, with different rates, protein- or peptide-based inhibitors. To address this challenge, we employed a combinatorial yeast surface display library approach complemented with a novel pre-equilibrium, competitive screening strategy for facile assessment of the effects of multiple mutations on inhibitor association rates and binding specificity. As a proof of principle for this combined approach, we utilized this strategy to alter inhibitor/protease association rates and to tailor the selectivity of the amyloid β-protein precursor Kunitz protease inhibitor domain (APPI) for inhibition of the oncogenic protease mesotrypsin, in the presence of three competing serine proteases, anionic trypsin, cationic trypsin and kallikrein-6. We generated a variant, designated APPIP13W/M17G/I18F/F34V, with up to 30-fold greater specificity relative to the parental APPIM17G/I18F/F34V protein, and 6500- to 230 000-fold improved specificity relative to the wild-type APPI protein in the presence of the other proteases tested. A series of molecular docking simulations suggested a mechanism of interaction that supported the biochemical results. These simulations predicted that the selectivity and specificity are affected by the interaction of the mutated APPI residues with nonconserved enzyme residues located in or near the binding site. Our strategy will facilitate a better understanding of the binding landscape of multispecific proteins and will pave the way for design of new drugs and diagnostic tools targeting proteases and other proteins.
000306286 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000306286 650_7 $$2Other$$adirected evolution
000306286 650_7 $$2Other$$aprotease inhibitor
000306286 650_7 $$2Other$$aprotein engineering
000306286 650_7 $$2Other$$aprotein–protein interactions (PPIs)
000306286 650_7 $$2Other$$aserine proteases
000306286 650_7 $$2NLM Chemicals$$aAPP protein, human
000306286 650_7 $$2NLM Chemicals$$aAmyloid beta-Protein Precursor
000306286 650_7 $$2NLM Chemicals$$aPeptide Library
000306286 650_7 $$2NLM Chemicals$$aProtease Inhibitors
000306286 650_7 $$0EC 3.4.21.4$$2NLM Chemicals$$aTrypsin
000306286 650_2 $$2MeSH$$aAmyloid beta-Protein Precursor: chemistry
000306286 650_2 $$2MeSH$$aAmyloid beta-Protein Precursor: genetics
000306286 650_2 $$2MeSH$$aAmyloid beta-Protein Precursor: metabolism
000306286 650_2 $$2MeSH$$aBinding, Competitive
000306286 650_2 $$2MeSH$$aHumans
000306286 650_2 $$2MeSH$$aModels, Molecular
000306286 650_2 $$2MeSH$$aMolecular Docking Simulation
000306286 650_2 $$2MeSH$$aPeptide Library
000306286 650_2 $$2MeSH$$aProtease Inhibitors: chemistry
000306286 650_2 $$2MeSH$$aProtease Inhibitors: metabolism
000306286 650_2 $$2MeSH$$aSubstrate Specificity
000306286 650_2 $$2MeSH$$aTrypsin: genetics
000306286 650_2 $$2MeSH$$aTrypsin: metabolism
000306286 7001_ $$aNaftaly, Si$$b1
000306286 7001_ $$aBen-Zeev, Efrat$$b2
000306286 7001_ $$aHockla, Alexandra$$b3
000306286 7001_ $$aRadisky, Evette S$$b4
000306286 7001_ $$aPapo, Niv$$b5
000306286 773__ $$0PERI:(DE-600)1473095-9$$a10.1042/BCJ20180070$$gVol. 475, no. 7, p. 1335 - 1352$$n7$$p1335 - 1352$$tBiochemical journal$$v475$$x0006-2936$$y2018
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