Engineering Tissue Inhibitors of Metalloproteinases Using Yeast Surface Display

Determining key residues of engineered scFv antibody variants with improved MMP-9 binding using deep sequencing and machine learning

Given the crucial role of specific matrix metalloproteinases (MMPs) in the extracellular matrix, an imbalance in the regulation of activation of matrix metalloproteinase-9 (MMP-9) zymogen and inhibition of the enzyme can result in various diseases, such as cancer, neurodegenerative, and gynecological diseases. Thus, developing novel therapeutics that target MMP-9 with single-chain antibody fragments (scFvs) is a promising approach. We used fluorescent-activated cell sorting (FACS) to screen a synthetic scFv antibody library displayed on yeast for enhanced binding to MMP-9. The screened scFv mutants demonstrated improved binding to MMP-9 compared to the natural inhibitor of MMPs, tissue inhibitor of metalloproteinases (TIMPs). To identify the molecular determinants of these engineered scFv variants that affect binding to MMP-9, we used next-generation DNA sequencing and computational protein structure analysis. Additionally, a deep-learning language model was trained on the screened scFv library of variants to predict the binding affinities of scFv variants based on their CDR-H3 sequences.

Elucidating key determinants of engineered scFv antibody in MMP-9 binding using high throughput screening and machine learning

An imbalance in matrix metalloproteinase-9 (MMP-9) regulation can lead to numerous diseases, including neurological disorders, cancer, and pre-term labor. Engineering single-chain antibody fragments (scFvs) Targeting MMP-9 to develop novel therapeutics for such diseases is desirable. We screened a synthetic scFv antibody library displayed on the yeast surface for binding improvement to MMP-9 using FACS (fluorescent-activated cell sorting). The scFv antibody clones isolated after FACS showed improvement in binding to MMP-9 compared to the endogenous inhibitor. To understand molecular determinants of binding between engineered scFv antibody variants and MMP-9, next-generation DNA sequencing, and computational protein structure analysis were used. Additionally, a deep-learning language model was trained on the synthetic library to predict the binding of scFv variants using their CDR-H3 sequences.

Engineering metalloproteinase inhibitors: tissue inhibitors of metalloproteinases or antibodies, that is the question

Targeting metalloproteinases (MPs) has been the center of attention for developing therapeutics due to their contribution to a wide range of diseases, including cancer, cardiovascular, neurodegenerative disease, and preterm labor. Protein-based MP inhibitors offer higher stability and selectivity, which is critical for developing efficient therapeutics with low off-target effects. Tissue inhibitors of metalloproteinases (TIMPs), natural inhibitors of MPs, and antibodies provide excellent protein scaffolds for engineering selective or multispecific MP inhibitors. Advances in protein engineering and design techniques, such as rational design and directed evolution using yeast display to develop potent MP inhibitors, are discussed, including but not limited to loop grafting, swapping, and counterselective selection.

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.

Engineering minimal tissue inhibitors of metalloproteinase targeting MMPs via gene shuffling and yeast surface display

Overexpression of specific matrix metalloproteinases (MMPs) has a key role in development of several diseases, such as cancer, neurological disorders, and cardiovascular diseases due to their critical role in degradation and remodeling of the extracellular matrix (ECM). Tissue inhibitors of metalloproteinases (TIMPs), a family of four in humans, are endogenous inhibitors of MMPs. TIMPs have a high level of sequence and structure homology, with a broad range of binding and inhibition to the family of MMPs. It is important to identify the key motifs of TIMPs responsible for inhibition of MMPs to develop efficient therapeutics targeting specific MMPs. We used DNA shuffling between the human TIMP family to generate a minimal TIMP hybrid library in yeast to identify the dominant minimal MMP inhibitory regions. The minimal TIMP variants screened toward MMP-3 and MMP-9 using fluorescent-activated cell sorting (FACS). Interestingly, several minimal TIMP variants selected after screening toward MMP-3cd or MMP-9cd, with lengths as short as 20 amino acids, maintained or improved binding to MMP-3 and MMP-9. The TIMP-MMP binding dissociation constant (KD ), in the nM range, and MMP inhibition constants (Ki ), in the pM range, of these minimal TIMP variants were similar to the N-terminal domain of TIMP-1 on the yeast surface and in solution indicating the potency of these minimal variants as MMP inhibitors. We further used molecular modeling simulation, and molecular docking of the minimal TIMP variants in complex with MMP-3cd to understand the binding and inhibition mechanism of these variants.

TIMP-1 Protects Tight Junctions of Brain Endothelial Cells From MMP-Mediated Degradation

OBJECTIVE

The blood-brain barrier (BBB) plays a critical role in central nervous system homeostasis, and the integrity of BBB is disrupted in many neurodegenerative diseases. Matrix metalloproteinases (MMPs) degrade the tight junctions (TJs) of endothelial cells and basement membrane components essential to BBB integrity, which leads to increased BBB permeability and allows inflammatory cells and neurotoxic substances to enter the brain. Tissue inhibitors of metalloproteinases (TIMPs), endogenous inhibitors of MMPs, regulate MMP activity, thereby maintaining BBB integrity.

METHODS

The disruptive impacts of MMP-3 and MMP-9 on BBB and protective effect of TIMP-1 were investigated in a simplified in vitro model of the BBB, which was generated using rat brain microvascular endothelial cells (RBMEC). The main features of BBB formation, including permeability and the trans-endothelial electrical resistance (TEER), were monitored over time after the addition of MMP-3 and MMP-9 and their complexes with TIMP-1 inhibitor.

RESULTS

Our results indicated that MMP-3 and MMP-9 caused a dose-dependent disruption of the BBB, with 1.5 µM MMPs resulting in an over threefold increase in permeability, while TIMP-1 inhibition protected the integrity of the BBB model and recovered TEER and permeability of RBMECs. The disruption and recovery of tight junction proteins of RBMECs after MMP and TIMP treatment were also detected using fluorescent microscopy.

CONCLUSION

MMP-9 and MMP-3 disrupt the BBB by degrading tight junctions in endothelial cells, and TIMP-1 could inhibit the disruptive effect of MMP-3 and MMP-9 by showing potential as therapeutic protein against MMP-related diseases where BBB disruption plays a role.