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.
Combinatorial protein engineering of proteolytically resistant mesotrypsin inhibitors as candidates for cancer therapy
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.
Serine protease inhibitor Kazal type 1 (SPINK1) drives proliferation and anoikis resistance in a subset of ovarian cancers
PRSS3/mesotrypsin is an atypical isoform of trypsin, the up-regulation of which has been implicated in promoting tumour progression. Mesotrypsin inhibitors could potentially provide valuable research tools and novel therapeutics, but small-molecule trypsin inhibitors have low affinity and little selectivity, whereas protein trypsin inhibitors bind poorly and are rapidly degraded by mesotrypsin. In the present study, we use mutagenesis of a mesotrypsin substrate, APPI (amyloid precursor protein Kunitz protease inhibitor domain), and of a poor mesotrypsin inhibitor, BPTI (bovine pancreatic trypsin inhibitor), to dissect mesotrypsin specificity at the key P2′ position. We find that bulky and charged residues strongly disfavour binding, whereas acidic residues facilitate catalysis. Crystal structures of mesotrypsin complexes with BPTI variants provide structural insights into mesotrypsin specificity and inhibition. Through optimization of the P1 and P2′ residues of BPTI, we generate a stable high-affinity mesotrypsin inhibitor with an equilibrium binding constant Ki of 5.9 nM, a >2000-fold improvement in affinity over native BPTI. Using this engineered inhibitor, we demonstrate the efficacy of pharmacological inhibition of mesotrypsin in assays of breast cancer cell malignant growth and pancreatic cancer cell invasion. Although further improvements in inhibitor selectivity will be important before clinical potential can be realized, the results of the present study support the feasibility of engineering protein protease inhibitors of mesotrypsin and highlight their therapeutic potential.