Extracellular proteolysis in cancer: Proteases, substrates, and mechanisms in tumor progression and metastasis.

A vast ensemble of extracellular proteins influences the development and progression of cancer, shaped and reshaped by a complex network of extracellular proteases. These proteases, belonging to the distinct classes of metalloproteases, serine proteases, cysteine proteases, and aspartic proteases, play a critical role in cancer. They often become dysregulated in cancer, with increases in pathological protease activity frequently driven by loss of normal latency controls, diminished regulation by endogenous protease inhibitors, and changes in localization. Dysregulated proteases accelerate tumor progression and metastasis by degrading protein barriers within the extracellular matrix (ECM), stimulating tumor growth, reactivating dormant tumor cells, facilitating tumor cell escape from immune surveillance, and shifting stromal cells toward cancer-promoting behaviors through the precise proteolysis of specific substrates to alter their functions. These crucial substrates include ECM proteins and proteoglycans, soluble proteins secreted by tumor and stromal cells, and extracellular domains of cell surface proteins, including membrane receptors and adhesion proteins. The complexity of the extracellular protease web presents a significant challenge to untangle. Nevertheless, technological strides in proteomics, chemical biology, and the development of new probes and reagents are enabling progress and advancing our understanding of the pivotal importance of extracellular proteolysis in cancer.

Engineering Selective TIMPs Using a Counter-Selective Screening Strategy.

The yeast surface display platform provides a powerful approach for screening protein diversity libraries to identify binders with an enhanced affinity toward a binding partner. Here, we describe an adaptation of the approach to identify binders with enhanced specificity toward one among multiple closely related binding partners. Specifically, we describe methods for engineering selective matrix metalloproteinase (MMP) inhibitors via yeast surface display of a tissue inhibitor of metalloproteinase (TIMP) diversity library coupled with a counter-selective screening strategy. This protocol may also be employed for developing selective protein binders or inhibitors toward other targets.

Structure and computation-guided yeast surface display for the evolution of TIMP-based matrix metalloproteinase inhibitors.

The study of protein-protein interactions (PPIs) and the engineering of protein-based inhibitors often employ two distinct strategies. One approach leverages the power of combinatorial libraries, displaying large ensembles of mutant proteins, for example, on the yeast cell surface, to select binders. Another approach harnesses computational modeling, sifting through an astronomically large number of protein sequences and attempting to predict the impact of mutations on PPI binding energy. Individually, each approach has inherent limitations, but when combined, they generate superior outcomes across diverse protein engineering endeavors. This synergistic integration of approaches aids in identifying novel binders and inhibitors, fine-tuning specificity and affinity for known binding partners, and detailed mapping of binding epitopes. It can also provide insight into the specificity profiles of varied PPIs. Here, we outline strategies for directing the evolution of tissue inhibitors of metalloproteinases (TIMPs), which act as natural inhibitors of matrix metalloproteinases (MMPs). We highlight examples wherein design of combinatorial TIMP libraries using structural and computational insights and screening these libraries of variants using yeast surface display (YSD), has successfully optimized for MMP binding and selectivity, and conferred insight into the PPIs involved.

Designed Loop Extension Followed by Combinatorial Screening Confers High Specificity to a Broad Matrix MetalloproteinaseInhibitor.

Matrix metalloproteinases (MMPs) are key drivers of various diseases, including cancer. Development of probes and drugs capable of selectively inhibiting the individual members of the large MMP family remains a persistent challenge. The inhibitory N-terminal domain of tissue inhibitor of metalloproteinases-2 (N-TIMP2), a natural broad MMP inhibitor, can provide a scaffold for protein engineering to create more selective MMP inhibitors. Here, we pursued a unique approach harnessing both computational design and combinatorial screening to confer high binding specificity toward a target MMP in preference to an anti-target MMP. We designed a loop extension of N-TIMP2 to allow new interactions with the non-conserved MMP surface and generated an efficient focused library for yeast surface display, which was then screened for high binding to the target MMP-14 and low binding to anti-target MMP-3. Deep sequencing analysis identified the most promising variants, which were expressed, purified, and tested for selectivity of inhibition. Our best N-TIMP2 variant exhibited 29 pM binding affinity to MMP-14 and 2.4 µM affinity to MMP-3, revealing 7500-fold greater specificity than WT N-TIMP2. High-confidence structural models were obtained by including NGS data in the AlphaFold multiple sequence alignment. The modeling together with experimental mutagenesis validated our design predictions, demonstrating that the loop extension packs tightly against non-conserved residues on MMP-14 and clashes with MMP-3. This study demonstrates how introduction of loop extensions in a manner guided by target protein conservation data and loop design can offer an attractive strategy to achieve specificity in design of protein ligands.

Utilizing genetic code expansion to modify N-TIMP2 specificity towards MMP-2, MMP-9, and MMP-14.

Matrix metalloproteinases (MMPs) regulate the degradation of extracellular matrix (ECM) components in biological processes. MMP activity is controlled by natural tissue inhibitors of metalloproteinases (TIMPs) that non-selectively inhibit the function of multiple MMPs via interaction with the MMPs' Zn2+-containing catalytic pocket. Recent studies suggest that TIMPs engineered to confer MMP specificity could be exploited for therapeutic purposes, but obtaining specific TIMP-2 inhibitors has proved to be challenging. Here, in an effort to improve MMP specificity, we incorporated the metal-binding non-canonical amino acids (NCAAs), 3,4-dihydroxyphenylalanine (L-DOPA) and (8-hydroxyquinolin-3-yl)alanine (HqAla), into the MMP-inhibitory N-terminal domain of TIMP2 (N-TIMP2) at selected positions that interact with the catalytic Zn2+ ion (S2, S69, A70, L100) or with a structural Ca2+ ion (Y36). Evaluation of the inhibitory potency of the NCAA-containing variants towards MMP-2, MMP-9 and MMP-14 in vitro revealed that most showed a significant loss of inhibitory activity towards MMP-14, but not towards MMP-2 and MMP-9, resulting in increased specificity towards the latter proteases. Substitutions at S69 conferred the best improvement in selectivity for both L-DOPA and HqAla variants. Molecular modeling provided an indication of how MMP-2 and MMP-9 are better able to accommodate the bulky NCAA substituents at the intermolecular interface with N-TIMP2. The models also showed that, rather than coordinating to Zn2+, the NCAA side chains formed stabilizing polar interactions at the intermolecular interface with MMP-2 and MMP-9. Our findings illustrate how incorporation of NCAAs can be used to probe-and possibly exploit-differential tolerance for substitution within closely related protein-protein complexes as a means to improve specificity.

The roles of proteases in prostate cancer.

Since the proposition of the pro-invasive activity of proteolytic enzymes over 70 years ago, several roles for proteases in cancer progression have been established. About half of the 473 active human proteases are expressed in the prostate and many of the most well-characterized members of this enzyme family are regulated by androgens, hormones essential for development of prostate cancer. Most notably, several kallikrein-related peptidases, including KLK3 (prostate-specific antigen, PSA), the most well-known prostate cancer marker, and type II transmembrane serine proteases, such as TMPRSS2 and matriptase, have been extensively studied and found to promote prostate cancer progression. Recent findings also suggest a critical role for proteases in the development of advanced and aggressive castration-resistant prostate cancer (CRPC). Perhaps the most intriguing evidence for this role comes from studies showing that the protease-activated transmembrane proteins, Notch and CDCP1, are associated with the development of CRPC. Here, we review the roles of proteases in prostate cancer, with a special focus on their regulation by androgens.

Utilizing genetic code expansion to modify N-TIMP2 specificity towards MMP-2, MMP-9, and MMP-14.

Matrix metalloproteinases (MMPs) regulate the degradation of extracellular matrix (ECM) components in biological processes. MMP activity is controlled by natural tissue inhibitors of metalloproteinases (TIMPs) that non-selectively inhibit the function of multiple MMPs via interaction with the MMPs' Zn 2+ -containing catalytic pocket. Recent studies suggest that TIMPs engineered to confer MMP specificity could be exploited for therapeutic purposes, but obtaining specific TIMP-2 inhibitors has proved to be challenging. Here, in an effort to improve MMP specificity, we incorporated the metal-binding non-canonical amino acids (NCAAs), 3,4-dihydroxyphenylalanine (L-DOPA) and (8-hydroxyquinolin-3-yl)alanine (HqAla), into the MMP-inhibitory N-terminal domain of TIMP2 (N-TIMP2) at selected positions that interact with the catalytic Zn 2+ ion (S2, S69, A70, L100) or with a structural Ca 2+ ion (Y36). Evaluation of the inhibitory potency of the NCAA-containing variants towards MMP-2, MMP-9 and MMP-14 in vitro revealed that most showed a significant loss of inhibitory activity towards MMP-14, but not towards MMP-2 and MMP-9, resulting in increased specificity towards the latter proteases. Substitutions at S69 conferred the best improvement in selectivity for both L-DOPA and HqAla variants. Molecular modeling revealed how MMP-2 and MMP-9 are better able to accommodate the bulky NCAA substituents at the intermolecular interface with N-TIMP2. The models also showed that, rather than coordinating to Zn 2+ , the NCAA side chains formed stabilizing polar interactions at the intermolecular interface with MMP-2 and MMP-9. The findings illustrate how incorporation of NCAAs can be used to probe and exploit differential tolerance for substitution within closely related protein-protein complexes to achieve improved specificity.

Aberrant TIMP-1 overexpression in tumor-associated fibroblasts drives tumor progression through CD63 in lung adenocarcinoma.

Tissue inhibitor of metalloproteinase-1 (TIMP-1) is an important regulator of extracellular matrix turnover that has been traditionally regarded as a potential tumor suppressor owing to its inhibitory effects of matrix metalloproteinases. Intriguingly, this interpretation has been challenged by the consistent observation that increased expression of TIMP-1 is associated with poor prognosis in virtually all cancer types including lung cancer, supporting a tumor-promoting function. However, how TIMP-1 is dysregulated within the tumor microenvironment and how it drives tumor progression in lung cancer is poorly understood. We analyzed the expression of TIMP-1 and its cell surface receptor CD63 in two major lung cancer subtypes: lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), and defined the tumor-promoting effects of their interaction. We found that TIMP-1 is aberrantly overexpressed in tumor-associated fibroblasts (TAFs) in ADC compared to SCC. Mechanistically, TIMP-1 overexpression was mediated by the selective hyperactivity of the pro-fibrotic TGF-ß1/SMAD3 pathway in ADC-TAFs. Likewise, CD63 was upregulated in ADC compared to SCC cells. Genetic analyses revealed that TIMP-1 secreted by TGF-ß1-activated ADC-TAFs is both necessary and sufficient to enhance growth and invasion of ADC cancer cells in culture, and that tumor cell expression of CD63 was required for these effects. Consistently, in vivo analyses revealed that ADC cells co-injected with fibroblasts with reduced SMAD3 or TIMP-1 expression into immunocompromised mice attenuated tumor aggressiveness compared to tumors bearing parental fibroblasts. We also found that high TIMP1 and CD63 mRNA levels combined define a stronger prognostic biomarker than TIMP1 alone. Our results identify an excessive stromal TIMP-1 within the tumor microenvironment selectively in lung ADC, and implicate it in a novel tumor-promoting TAF-carcinoma crosstalk, thereby pointing to TIMP-1/CD63 interaction as a novel therapeutic target in lung cancer.

Activity-based protein profiling reveals active serine proteases that drive malignancy of human ovarian clear cell carcinoma.

Ovarian clear cell carcinoma (OCCC) is an understudied poor prognosis subtype of ovarian cancer lacking in effective targeted therapies. Efforts to define molecular drivers of OCCC malignancy may lead to new therapeutic targets and approaches. Among potential targets are secreted proteases, enzymes which in many cancers serve as key drivers of malignant progression. Here, we found that inhibitors of trypsin-like serine proteases suppressed malignant phenotypes of OCCC cell lines. To identify the proteases responsible for malignancy in OCCC, we employed activity-based protein profiling to directly analyze enzyme activity. We developed an activity-based probe featuring an arginine diphenylphosphonate warhead to detect active serine proteases of trypsin-like specificity and a biotin handle to facilitate affinity purification of labeled proteases. Using this probe, we identified active trypsin-like serine proteases within the complex proteomes secreted by OCCC cell lines, including two proteases in common, tissue plasminogen activator and urokinase-type plasminogen activator. Further interrogation of these proteases showed that both were involved in cancer cell invasion and proliferation of OCCC cells and were also detected in in vivo models of OCCC. We conclude the detection of tissue plasminogen activator and urokinase-type plasminogen activator as catalytically active proteases and significant drivers of the malignant phenotype may point to these enzymes as targets for new therapeutic strategies in OCCC. Our activity-based probe and profiling methodology will also serve as a valuable tool for detection of active trypsin-like serine proteases in models of other cancers and other diseases.

Engineering of tissue inhibitor of metalloproteinases TIMP-1 for fine discrimination between closely related stromelysins MMP-3 and MMP-10.

Matrix metalloproteinases (MMPs) have long been known as key drivers in the development and progression of diseases, including cancer and neurodegenerative, cardiovascular, and many other inflammatory and degenerative diseases, making them attractive potential drug targets. Engineering selective inhibitors based upon tissue inhibitors of metalloproteinases (TIMPs), endogenous human proteins that tightly yet nonspecifically bind to the family of MMPs, represents a promising new avenue for therapeutic development. Here, we used a counter-selective screening strategy for directed evolution of yeast-displayed human TIMP-1 to obtain TIMP-1 variants highly selective for the inhibition of MMP-3 in preference over MMP-10. As MMP-3 and MMP-10 are the most similar MMPs in sequence, structure, and function, our results thus clearly demonstrate the capability for engineering full-length TIMP proteins to be highly selective MMP inhibitors. We show using protein crystal structures and models of MMP-3-selective TIMP-1 variants bound to MMP-3 and counter-target MMP-10 how structural alterations within the N-terminal and C-terminal TIMP-1 domains create new favorable and selective interactions with MMP-3 and disrupt unique interactions with MMP-10. While our MMP-3-selective inhibitors may be of interest for future investigation in diseases where this enzyme drives pathology, our platform and screening strategy can be employed for developing selective inhibitors of additional MMPs implicated as therapeutic targets in disease.

Avidity observed between a bivalent inhibitor and an enzyme monomer with a single active site.

Although myriad protein-protein interactions in nature use polyvalent binding, in which multiple ligands on one entity bind to multiple receptors on another, to date an affinity advantage of polyvalent binding has been demonstrated experimentally only in cases where the target receptor molecules are clustered prior to complex formation. Here, we demonstrate cooperativity in binding affinity (i.e., avidity) for a protein complex in which an engineered dimer of the amyloid precursor protein inhibitor (APPI), possessing two fully functional inhibitory loops, interacts with mesotrypsin, a soluble monomeric protein that does not self-associate or cluster spontaneously. We found that each inhibitory loop of the purified APPI homodimer was over three-fold more potent than the corresponding loop in the monovalent APPI inhibitor. This observation is consistent with a suggested mechanism whereby the two APPI loops in the homodimer simultaneously and reversibly bind two corresponding mesotrypsin monomers to mediate mesotrypsin dimerization. We propose a simple model for such dimerization that quantitatively explains the observed cooperativity in binding affinity. Binding cooperativity in this system reveals that the valency of ligands may affect avidity in protein-protein interactions including those of targets that are not surface-anchored and do not self-associate spontaneously. In this scenario, avidity may be explained by the enhanced concentration of ligand binding sites in proximity to the monomeric target, which may favor rebinding of the multiple ligand binding sites with the receptor molecules upon dissociation of the protein complex.

Climbing Up and Down Binding Landscapes through Deep Mutational Scanning of Three Homologous Protein-Protein Complexes.

Protein-protein interactions (PPIs) have evolved to display binding affinities that can support their function. As such, cognate and noncognate PPIs could be highly similar structurally but exhibit huge differences in binding affinities. To understand this phenomenon, we study three homologous protease-inhibitor PPIs that span 9 orders of magnitude in binding affinity. Using state-of-the-art methodology that combines protein randomization, affinity sorting, deep sequencing, and data normalization, we report quantitative binding landscapes consisting of ΔΔGbind values for the three PPIs, gleaned from tens of thousands of single and double mutations. We show that binding landscapes of the three complexes are strikingly different and depend on the PPI evolutionary optimality. We observe different patterns of couplings between mutations for the three PPIs with negative and positive epistasis appearing most frequently at hot-spot and cold-spot positions, respectively. The evolutionary trends observed here are likely to be universal to other biological complexes in the cell.

Attacking COVID-19 Progression Using Multi-Drug Therapy for Synergetic Target Engagement.

COVID-19 is a devastating respiratory and inflammatory illness caused by a new coronavirus that is rapidly spreading throughout the human population. Over the past 12 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, has already infected over 160 million (>20% located in United States) and killed more than 3.3 million people around the world (>20% deaths in USA). As we face one of the most challenging times in our recent history, there is an urgent need to identify drug candidates that can attack SARS-CoV-2 on multiple fronts. We have therefore initiated a computational dynamics drug pipeline using molecular modeling, structure simulation, docking and machine learning models to predict the inhibitory activity of several million compounds against two essential SARS-CoV-2 viral proteins and their host protein interactors-S/Ace2, Tmprss2, Cathepsins L and K, and Mpro-to prevent binding, membrane fusion and replication of the virus, respectively. All together, we generated an ensemble of structural conformations that increase high-quality docking outcomes to screen over >6 million compounds including all FDA-approved drugs, drugs under clinical trial (>3000) and an additional >30 million selected chemotypes from fragment libraries. Our results yielded an initial set of 350 high-value compounds from both new and FDA-approved compounds that can now be tested experimentally in appropriate biological model systems. We anticipate that our results will initiate screening campaigns and accelerate the discovery of COVID-19 treatments.

MMP1 drives tumor progression in large cell carcinoma of the lung through fibroblast senescence.

Large cell carcinoma (LCC) is a rare and aggressive lung cancer subtype with poor prognosis and no targeted therapies. Tumor-associated fibroblasts (TAFs) derived from LCC tumors exhibit premature senescence, and coculture of pulmonary fibroblasts with LCC cell lines selectively induces fibroblast senescence, which in turn drives LCC cell growth and invasion. Here we identify MMP1 as overexpressed specifically in LCC cell lines, and we show that expression of MMP1 by LCC cells is necessary for induction of fibroblast senescence and consequent tumor promotion in both cell culture and mouse models. We also show that MMP1, in combination with TGF-ß1, is sufficient to induce fibroblast senescence and consequent LCC promotion. Furthermore, we implicate PAR-1 and oxidative stress in MMP1/TGF-ß1-induced TAF senescence. Our results establish an entirely new role for MMP1 in cancer, and support a novel therapeutic strategy in LCC based on targeting senescent TAFs.

Targeting an autocrine IL-6-SPINK1 signaling axis to suppress metastatic spread in ovarian clear cell carcinoma.

A major clinical challenge of ovarian cancer is the development of malignant ascites accompanied by widespread peritoneal metastasis. In ovarian clear cell carcinoma (OCCC), a challenging subtype of ovarian cancer, this problem is compounded by near-universal primary chemoresistance; patients with advanced stage OCCC thus lack effective therapies and face extremely poor survival rates. Here we show that tumor-cell-expressed serine protease inhibitor Kazal type 1 (SPINK1) is a key driver of OCCC progression and metastasis. Using cell culture models of human OCCC, we find that shRNA silencing of SPINK1 sensitizes tumor cells to anoikis and inhibits proliferation. Knockdown of SPINK1 in OCCC cells also profoundly suppresses peritoneal metastasis in mouse implantation models of human OCCC. We next identify a novel autocrine signaling axis in OCCC cells whereby tumor-cell-produced interleukin-6 (IL-6) regulates SPINK1 expression to stimulate a common protumorigenic gene expression pattern leading to anoikis resistance and proliferation of OCCC cells. We further demonstrate that this signaling pathway can be successfully interrupted with the IL-6Rα inhibitor tocilizumab, sensitizing cells to anoikis in vitro and reducing metastasis in vivo. These results suggest that clinical trials of IL-6 pathway inhibitors in OCCC may be warranted, and that SPINK1 might offer a candidate predictive biomarker in this population.

Quantitative mapping of binding specificity landscapes for homologous targets by using a high-throughput method.

To facilitate investigations of protein-protein interactions (PPIs), we developed a novel platform for quantitative mapping of protein binding specificity landscapes, which combines the multi-target screening of a mutagenesis library into high- and low-affinity populations with sophisticated next-generation sequencing analysis. Importantly, this method generates accurate models to predict affinity and specificity values for any mutation within a protein complex, and requires only a few experimental binding affinity measurements using purified proteins for calibration. We demonstrated the utility of the approach by mapping quantitative landscapes for interactions between the N-terminal domain of the tissue inhibitor of metalloproteinase 2 (N-TIMP2) and three matrix metalloproteinases (MMPs) having homologous structures but different affinities (MMP-1, MMP-3, and MMP-14). The binding landscapes for N-TIMP2/MMP-1 and N-TIMP2/MMP-3 showed the PPIs to be almost fully optimized, with most single mutations giving a loss of affinity. In contrast, the non-optimized PPI for N-TIMP2/MMP-14 was reflected in a wide range of binding affinities, where single mutations exhibited a far more attenuated effect on the PPI. Our new platform reliably and comprehensively identified not only hot- and cold-spot residues, but also specificity-switch mutations that shape target affinity and specificity. Thus, our approach provides a methodology giving an unprecedentedly rich quantitative analysis of the binding specificity landscape, which will broaden the understanding of the mechanisms and evolutionary origins of specific PPIs and facilitate the rational design of specific inhibitors for structurally similar target proteins.

FAM111A protects replication forks from protein obstacles via its trypsin-like domain.

Persistent protein obstacles on genomic DNA, such as DNA-protein crosslinks (DPCs) and tight nucleoprotein complexes, can block replication forks. DPCs can be removed by the proteolytic activities of the metalloprotease SPRTN or the proteasome in a replication-coupled manner; however, additional proteolytic mechanisms may exist to cope with the diversity of protein obstacles. Here, we show that FAM111A, a PCNA-interacting protein, plays an important role in mitigating the effect of protein obstacles on replication forks. This function of FAM111A requires an intact trypsin-like protease domain, the PCNA interaction, and the DNA-binding domain that is necessary for protease activity in vivo. FAM111A, but not SPRTN, protects replication forks from stalling at poly(ADP-ribose) polymerase 1 (PARP1)-DNA complexes trapped by PARP inhibitors, thereby promoting cell survival after drug treatment. Altogether, our findings reveal a role of FAM111A in overcoming protein obstacles to replication forks, shedding light on cellular responses to anti-cancer therapies.

Mirolysin structures open a window on gum disease.

Guevara, Rodriguez-Banqueri et al. [(2020), IUCrJ, 7, 18-29] determine crystal structures of mirolysin, a metalloprotease that helps oral pathogen Tannerella forsythia evade the human immune response. The structures provide insight into the regulation and specificity of mirolysin, and hint at how it might be inhibited for therapeutic effect.

Trypsin activity governs increased susceptibility to pancreatitis in mice expressing human PRSS1R122H.

Currently, an effective targeted therapy for pancreatitis is lacking. Hereditary pancreatitis (HP) is a heritable, autosomal-dominant disorder with recurrent acute pancreatitis (AP) progressing to chronic pancreatitis (CP) and a markedly increased risk of pancreatic cancer. In 1996, mutations in PRSS1 were linked to the development of HP. Here, we developed a mouse model by inserting a full-length human PRSS1R122H gene, the most commonly mutated gene in human HP, into mice. Expression of PRSS1R122H protein in the pancreas markedly increased stress signaling pathways and exacerbated AP. After the attack of AP, all PRSS1R122H mice had disease progression to CP, with similar histologic features as those observed in human HP. By comparing PRSS1R122H mice with PRSS1WT mice, as well as enzymatically inactivated Dead-PRSS1R122H mice, we unraveled that increased trypsin activity is the mechanism for R122H mutation to sensitize mice to the development of pancreatitis. We further discovered that trypsin inhibition, in combination with anticoagulation therapy, synergistically prevented progression to CP in PRSS1R122H mice. These animal models help us better understand the complex nature of this disease and provide powerful tools for developing and testing novel therapeutics for human pancreatitis.

Directed evolution of the metalloproteinase inhibitor TIMP-1 reveals that its N- and C-terminal domains cooperate in matrix metalloproteinase recognition.

Tissue inhibitors of metalloproteinases (TIMPs) are natural inhibitors of matrix metalloproteinases (MMPs), enzymes that contribute to cancer and many inflammatory and degenerative diseases. The TIMP N-terminal domain binds and inhibits an MMP catalytic domain, but the role of the TIMP C-terminal domain in MMP inhibition is poorly understood. Here, we employed yeast surface display for directed evolution of full-length human TIMP-1 to develop MMP-3-targeting ultrabinders. By simultaneously incorporating diversity into both domains, we identified TIMP-1 variants that were up to 10-fold improved in binding MMP-3 compared with WT TIMP-1, with inhibition constants (Ki ) in the low picomolar range. Analysis of individual and paired mutations from the selected TIMP-1 variants revealed cooperative effects between distant residues located on the N- and C-terminal TIMP domains, positioned on opposite sides of the interaction interface with MMP-3. Crystal structures of MMP-3 complexes with TIMP-1 variants revealed conformational changes in TIMP-1 near the cooperative mutation sites. Affinity was strengthened by cinching of a reciprocal "tyrosine clasp" formed between the N-terminal domain of TIMP-1 and proximal MMP-3 interface and by changes in secondary structure within the TIMP-1 C-terminal domain that stabilize interdomain interactions and improve complementarity to MMP-3. Our protein engineering and structural studies provide critical insight into the cooperative function of TIMP domains and the significance of peripheral TIMP epitopes in MMP recognition. Our findings suggest new strategies to engineer TIMP proteins for therapeutic applications, and our directed evolution approach may also enable exploration of functional domain interactions in other protein systems.