Development of High Affinity and High Specificity Inhibitors of Matrix Metalloproteinase 14 through Computational Design and Directed Evolution

Valeria Arkadash,Gal Yosef,Jason Shirian,Itay Cohen,Yuval Horev,Moran Grossman,Irit Sagi,Evette S Radisky,Julia M Shifman,Niv Papo

doi:10.1074/jbc.m116.756718

Abstract

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.

Highlights

Degradation of the extracellular matrices in the human body is controlled by matrix metalloproteinases (MMPs), a family of more than 20 homologous enzymes
Combinatorial Library Design Based on Computational Saturation Mutagenesis Analysis—To maximize our chances of selecting the best MMP-14 inhibitors, we designed a focused library of N-TIMP2 mutants that contained mutations at seven positions with the highest probability of mutations for enhancing affinity and specificity of N-TIMP2 toward the catalytic domain of MMP-14 (MMP-14CAT)
All seven positions lie in the direct binding interface of N-TIMP1⁄7MMP complexes, and six of them are coupled in pairs as a result of close proximity to one another (35 and 38, 68 and 71, and 97 and 99), suggesting that a mutation at one such position is likely to influence the effect of a mutation at another position

Summary

Edited by Norma Allewell

Degradation of the extracellular matrices in the human body is controlled by matrix metalloproteinases (MMPs), a family of more than 20 homologous enzymes. Due to the limit in transformation efficiency, YSD technology is confined to exploring ϳ108 various protein binder sequences, meaning that only 6 –7 binder positions can be fully randomized with all 20 amino acids To overcome this limitation and to increase our chances of success in evolving a potent MMP-14 inhibitor, here we have designed a focused combinatorial library of the most promising N-TIMP2 mutants, based on our previous computational analysis of N-TIMP2/MMP interactions [40]. Our prior computational results serve as a launching-off point for designing a YSD library that very efficiently samples the most relevant areas of sequence space; this formidable combination of computational and YSD methodologies succeeds in producing highly selective N-TIMP2 mutants capable of serving as potent and specific inhibitors of MMP-14 in vitro and in vivo

Results

Spi ecificityb

Discussion

KD nM

Experimental Procedures