Cohen, Itay

Serine protease inhibitors of the Kunitz‐bovine pancreatic trypsin inhibitor (BPTI) family, such as tissue factor pathway inhibitor‐1 Kunitz domain 1 ( KD1 TFPI1) and amyloid precursor protein inhibitor (APPI), are biological regulators of proteolysis and serve as important scaffolds for developing therapeutics. Mesotrypsin is a unique human protease with cancer‐promoting properties which rapidly cleaves and inactivates serine protease inhibitors; because of this, it is a challenging therapeutic target and an excellent model for developing therapeutic inhibitors with improved proteolytic resistance. We hypothesize that stabilization of the Kunitz inhibitor binding loop by disulfide bond anchoring to the scaffold can reduce proteolytic susceptibility and improve binding efficacy. Here we have engineered a new disulfide bond into both KD1 TFPI1 and an APPI variant previously engineered for mesotrypsin affinity. The new disulfide bond anchors the binding loop to the scaffold, resulting in reduced mesotrypsin proteolytic cleavage by 17‐fold and 3‐fold, respectively. To gain insight into the structural basis for improved proteolytic stability, we crystallized mutant KD1 TFPI1 and APPI with mesotrypsin and solved these novel structures. We then performed all‐atom molecular dynamics simulations using these mesotrypsin‐mutant inhibitor complexes compared to models lacking the engineered disulfide bond. Our simulation results support our hypothesis that the cause of decreased proteolysis rates is dampened conformational fluctuations in the binding loop and minimized motion at the enzyme‐inhibitor interface. We also performed simulations using unbound inhibitors to show that stabilization of the binding loop to states similar to the bound configuration correlates with stronger binding affinity. Our disulfide engineering approach is potentially a useful tool in biopharmaceutical development for mesotrypsin, other serine proteases, and possibly for other enzyme targets. Support or Funding Information NIH grant R01CA154387 to E.S.R., European Research Council grant 336041 to N.P., US‐Israel Binational Science Foundation grant BSF2015134 to E.S.R. and N.P. Xray diffraction data were measured at the Berkeley Center for Structural Biology at the Advanced Light Source and at the European Synchrotron Radiation Facility. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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.

MMP ‐14 and MMP ‐9 are two well‐established cancer targets for which no specific clinically relevant inhibitor is available. Using a powerful combination of computational design and yeast surface display technology, we engineered such an inhibitor starting from a nonspecific MMP inhibitor, N‐ TIMP 2. The engineered purified N‐ TIMP 2 variants showed enhanced specificity toward MMP ‐14 and MMP ‐9 relative to a panel of off‐target MMP s. MMP ‐specific N‐ TIMP 2 sequence signatures were obtained that could be understood from the structural perspective of MMP /N‐ TIMP 2 interactions. Our MMP ‐9 inhibitor exhibited 1000‐fold preference for MMP ‐9 vs. MMP ‐14, which is likely to translate into significant differences under physiological conditions. Our results provide new insights regarding evolution of promiscuous proteins and optimization strategies for design of inhibitors with single‐target specificities.

Engineered protein therapeutics offer advantages, including strong target affinity, selectivity and low toxicity, but like natural proteins can be susceptible to proteolytic degradation, thereby limiting their effectiveness. A compelling therapeutic target is mesotrypsin, a protease up-regulated with tumour progression, associated with poor prognosis, and implicated in tumour growth and progression of many cancers. However, with its unique capability for cleavage and inactivation of proteinaceous inhibitors, mesotrypsin presents a formidable challenge to the development of biological inhibitors. We used a powerful yeast display platform for directed evolution, employing a novel multi-modal library screening strategy, to engineer the human amyloid precursor protein Kunitz protease inhibitor domain (APPI) simultaneously for increased proteolytic stability, stronger binding affinity and improved selectivity for mesotrypsin inhibition. We identified a triple mutant APPIM17G/I18F/F34V, with a mesotrypsin inhibition constant (Ki) of 89 pM, as the strongest mesotrypsin inhibitor yet reported; this variant displays 1459-fold improved affinity, up to 350 000-fold greater specificity and 83-fold improved proteolytic stability compared with wild-type APPI. We demonstrated that APPIM17G/I18F/F34V acts as a functional inhibitor in cell-based models of mesotrypsin-dependent prostate cancer cellular invasiveness. Additionally, by solving the crystal structure of the APPIM17G/I18F/F34V–mesotrypsin complex, we obtained new insights into the structural and mechanistic basis for improved binding and proteolytic resistance. Our study identifies a promising mesotrypsin inhibitor as a starting point for development of anticancer protein therapeutics and establishes proof-of-principle for a novel library screening approach that will be widely applicable for simultaneously evolving proteolytic stability in tandem with desired functionality for diverse protein scaffolds.