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@ARTICLE{Cohen:306286,
author = {I. Cohen and S. Naftaly and E. Ben-Zeev and A. Hockla and
E. S. Radisky and N. Papo},
title = {{P}re-equilibrium competitive library screening for tuning
inhibitor association rate and specificity toward serine
proteases.},
journal = {Biochemical journal},
volume = {475},
number = {7},
issn = {0006-2936},
address = {London},
publisher = {Portland Press},
reportid = {DKFZ-2025-02512},
pages = {1335 - 1352},
year = {2018},
note = {#DKFZ-MOST-GR-2495#},
abstract = {High 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.},
keywords = {Amyloid beta-Protein Precursor: chemistry / Amyloid
beta-Protein Precursor: genetics / Amyloid beta-Protein
Precursor: metabolism / Binding, Competitive / Humans /
Models, Molecular / Molecular Docking Simulation / Peptide
Library / Protease Inhibitors: chemistry / Protease
Inhibitors: metabolism / Substrate Specificity / Trypsin:
genetics / Trypsin: metabolism / directed evolution (Other)
/ protease inhibitor (Other) / protein engineering (Other) /
protein–protein interactions (PPIs) (Other) / serine
proteases (Other) / APP protein, human (NLM Chemicals) /
Amyloid beta-Protein Precursor (NLM Chemicals) / Peptide
Library (NLM Chemicals) / Protease Inhibitors (NLM
Chemicals) / Trypsin (NLM Chemicals)},
ddc = {540},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:29535275},
pmc = {pmc:PMC5929103},
doi = {10.1042/BCJ20180070},
url = {https://inrepo02.dkfz.de/record/306286},
}