Niv Papo

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.

Protein Engineering by Combined Computational and In Vitro Evolution Approaches

Two alternative strategies are commonly used to study protein-protein interactions (PPIs) and to engineer protein-based inhibitors. In one approach, binders are selected experimentally from combinatorial libraries of protein mutants that are displayed on a cell surface. In the other approach, computational modeling is used to explore an astronomically large number of protein sequences to select a small number of sequences for experimental testing. While both approaches have some limitations, their combination produces superior results in various protein engineering applications. Such applications include the design of novel binders and inhibitors, the enhancement of affinity and specificity, and the mapping of binding epitopes. The combination of these approaches also aids in the understanding of the specificity profiles of various PPIs.

Development of high affinity and high specificity inhibitors of matrix metalloproteinase 14 through computational design and directed evolution

Degradation of the extracellular matrices in the human body is controlled by matrix metalloproteinases (MMPs), a family of more than 20 homologous enzymes. Imbalance in MMP activity can result in many diseases, such as arthritis, cardiovascular diseases, neurological disorders, fibrosis, and cancers. Thus, MMPs present attractive targets for drug design and have been a focus for inhibitor design for as long as 3 decades. Yet, to date, all MMP inhibitors have failed in clinical trials because of their broad activity against numerous MMP family members and the serious side effects of the proposed treatment. In this study, we integrated a computational method and a yeast surface display technique to obtain highly specific inhibitors of MMP-14 by modifying the natural non-specific broad MMP inhibitor protein N-TIMP2 to interact optimally with MMP-14. We identified an N-TIMP2 mutant, with five mutations in its interface, that has an MMP-14 inhibition constant (Ki) of 0.9 pm, the strongest MMP-14 inhibitor reported so far. Compared with wild-type N-TIMP2, this variant displays ∼900-fold improved affinity toward MMP-14 and up to 16,000-fold greater specificity toward MMP-14 relative to other MMPs. In an in vitro and cell-based model of MMP-dependent breast cancer cellular invasiveness, this N-TIMP2 mutant acted as a functional inhibitor. Thus, our study demonstrates the enormous potential of a combined computational/directed evolution approach to protein engineering. Furthermore, it offers fundamental clues into the molecular basis of MMP regulation by N-TIMP2 and identifies a promising MMP-14 inhibitor as a starting point for the development of protein-based anticancer therapeutics.

Constitutive Association of Tie1 and Tie2 with Endothelial Integrins is Functionally Modulated by Angiopoietin-1 and Fibronectin.

Functional cross-talk between Tie2 and Integrin signaling pathways is essential to coordinate endothelial cell adhesion and migration in response to the extracellular matrix, yet the mechanisms behind this phenomenon are unclear. Here, we examine the possibility that receptor cross-talk is driven through uncharacterized Tie-integrin interactions on the endothelial surface. Using a live cell FRET-based proximity assay, we monitor Tie-integrin receptor recognition and demonstrate that both Tie1 and Tie2 readily associate with integrins α5ß1 and αVß3 through their respective ectodomains. Although not required, Tie2-integrin association is significantly enhanced in the presence of the extracellular component and integrin ligand fibronectin. In vitro binding assays with purified components reveal that Tie-integrin recognition is direct, and further demonstrate that the receptor binding domain of the Tie2 ligand Ang-1, but not the receptor binding domain of Ang-2, can independently associate with α5ß1 or αVß3. Finally, we reveal that cooperative Tie/integrin interactions selectively stimulate ERK/MAPK signaling in the presence of both Ang-1 and fibronectin, suggesting a molecular mechanism to sensitize Tie2 to extracellular matrix. We provide a mechanistic model highlighting the role of receptor localization and association in regulating distinct signaling cascades and in turn, the angiogenic switch.

Matrix metalloproteinase protein inhibitors: highlighting a new beginning for metalloproteinases in medicine

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Combinatorial and computational approaches to identify interactions of macrophage colony stimulating factor (M-CSF) and its receptor c-fms

Background: Identifying residues crucial for M-CSF·c-FMS binding remains difficult. Results: Using a combination of experimental and computational methods, we identified mutations on M-CSF that reduce affinity to c-FMS. Conclusion: Affinity-reducing mutations are located both inside and outside of the binding interface. Significance: Knowledge of the critical residues will facilitate a better understanding of the M-CSF mechanism and facilitate drug design. The molecular interactions between macrophage colony-stimulating factor (M-CSF) and the tyrosine kinase receptor c-FMS play a key role in the immune response, bone metabolism, and the development of some cancers. Because no x-ray structure is available for the human M-CSF·c-FMS complex, the binding epitope for this complex is largely unknown. Our goal was to identify the residues that are essential for binding of the human M-CSF to c-FMS. For this purpose, we used a yeast surface display (YSD) approach. We expressed a combinatorial library of monomeric M-CSF (M-CSFM) single mutants and screened this library to isolate variants with reduced affinity for c-FMS using FACS. Sequencing yielded a number of single M-CSFM variants with mutations both in the direct binding interface and distant from the binding site. In addition, we used computational modeling to map the identified mutations onto the M-CSFM structure and to classify the mutations into three groups as follows: those that significantly decrease protein stability; those that destroy favorable intermolecular interactions; and those that decrease affinity through allosteric effects. To validate the YSD and computational data, M-CSFM and three variants were produced as soluble proteins; their affinity and structure were analyzed; and very good correlations with both YSD data and computational predictions were obtained. By identifying the M-CSFM residues critical for M-CSF·c-FMS interactions, we have laid down the basis for a deeper understanding of the M-CSF·c-FMS signaling mechanism and for the development of target-specific therapeutic agents with the ability to sterically occlude the M-CSF·c-FMS binding interface.

Identifying Residues that Determine SCF Molecular-Level Interactions through a Combination of Experimental and In silico Analyses

The stem cell factor (SCF)/c-Kit receptor tyrosine kinase complex-with its significant roles in hematopoiesis and angiogenesis-is an attractive target for rational drug design. There is thus a need to map, in detail, the SCF/c-Kit interaction sites and the mechanisms that modulate this interaction. While most residues in the direct SCF/c-Kit binding interface can be identified from the existing crystal structure of the complex, other residues that affect binding through protein unfolding, intermolecular interactions, allosteric or long-distance electrostatic effects cannot be directly inferred. Here, we describe an efficient method for protein-wide epitope mapping using yeast surface display. A library of single SCF mutants that span the SCF sequence was screened for decreased affinity to soluble c-Kit. Sequencing of selected clones allowed the identification of mutations that reduce SCF binding affinity to c-Kit. Moreover, the screening of these SCF clones for binding to a structural antibody helped identify mutations that result in small or large conformational changes in SCF. Computational modeling of the experimentally identified mutations showed that these mutations reduced the binding affinity through one of the three scenarios: through SCF destabilization, through elimination of favorable SCF/c-Kit intermolecular interactions, or through allosteric changes. Eight SCF variants were expressed and purified. Experimentally measured in vitro binding affinities of these mutants to c-Kit confirmed both the yeast surface display selection results and the computational predictions. This study has thus identified the residues crucial for c-Kit/SCF binding and has demonstrated the advantages of using a combination of computational and combinatorial methods for epitope mapping.

An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis.

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. Although considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here, we examine the importance of substrate dynamics in the cleavage of Kunitz-bovine pancreatic trypsin inhibitor protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4-Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals a dramatic conformational change in the substrate upon proteolysis. By using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning 3 orders of magnitude, we identify global and local dynamic features of substrates on the nanosecond-microsecond time scale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substrate-like and product-like states, linking substrate dynamics on the nanosecond-microsecond time scale with large collective substrate motions on the much slower time scale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis.

A computational combinatorial approach identifies a protein inhibitor of superoxide dismutase 1 misfolding, aggregation, and cytotoxicity

Molecular agents that specifically bind and neutralize misfolded and toxic superoxide dismutase 1 (SOD1) mutant proteins may find application in attenuating the disease progression of familial amyotrophic lateral sclerosis. However, high structural similarities between the wild-type and mutant SOD1 proteins limit the utility of this approach. Here we addressed this challenge by converting a promiscuous natural human IgG-binding domain, the hyperthermophilic variant of protein G (HTB1), into a highly specific aggregation inhibitor (designated HTB1M) of two familial amyotrophic lateral sclerosis–linked SOD1 mutants, SOD1G93A and SOD1G85R. We utilized a computational algorithm for mapping protein surfaces predisposed to HTB1 intermolecular interactions to construct a focused HTB1 library, complemented with an experimental platform based on yeast surface display for affinity and specificity screening. HTB1M displayed high binding specificity toward SOD1 mutants, inhibited their amyloid aggregation in vitro, prevented the accumulation of misfolded proteins in living cells, and reduced the cytotoxicity of SOD1G93A expressed in motor neuron–like cells. Competition assays and molecular docking simulations suggested that HTB1M binds to SOD1 via both its α-helical and β-sheet domains at the native dimer interface that becomes exposed upon mutated SOD1 misfolding and monomerization. Our results demonstrate the utility of computational mapping of the protein–protein interaction potential for designing focused protein libraries to be used in directed evolution. They also provide new insight into the mechanism of conversion of broad-spectrum immunoglobulin-binding proteins, such as HTB1, into target-specific proteins, thereby paving the way for the development of new selective drugs targeting the amyloidogenic proteins implicated in a variety of human diseases.

Engineering a monomeric variant of macrophage colony-stimulating factor (M‑CSF) that antagonizes the c-FMS receptor

Enhanced activation of the signaling pathways that mediate the differentiation of mononuclear monocytes into osteoclasts is an underlying cause of several bone diseases and bone metastasis. In particular, dysregulation and overexpression of macrophage colony-stimulating factor (M-CSF) and its c-FMS tyrosine kinase receptor, proteins that are essential for osteoclast differentiation, are known to promote bone metastasis and osteoporosis, making both the ligand and its receptor attractive targets for therapeutic intervention. With this aim in mind, our starting point was the previously held concept that the potential of the M-CSFC31S mutant as a therapeutic is derived from its inability to dimerize and hence to act as an agonist. The current study showed, however, that dimerization is not abolished in M-CSFC31S and that the protein retains agonistic activity toward osteoclasts. To design an M-CSF mutant with diminished dimerization capabilities, we solved the crystal structure of the M-CSFC31S dimer complex and used structure-based energy calculations to identify the residues responsible for its dimeric form. We then used that analysis to develop M-CSFC31S,M27R, a ligand-based, high-affinity antagonist for c-FMS that retained its binding ability but prevented the ligand dimerization that leads to receptor dimerization and activation. The monomeric properties of M-CSFC31S,M27R were validated using dynamic light scattering and small-angle X-ray scattering analyses. It was shown that this mutant is a functional inhibitor of M-CSF-dependent c-FMS activation and osteoclast differentiation in vitro Our study, therefore, provided insights into the sequence-structure-function relationships of the M-CSF/c-FMS interaction and of ligand/receptor tyrosine kinase interactions in general.