Protein ScienceEvolutionary BiologyPeer-reviewed journal article
High-throughput amino acid-level characterization of the interactions of plasminogen activator inhibitor-1 with variably divergent proteases
Laura M. HaynesiD, Matthew L. HoldingiD, Hannah DiGiovanni, David R. Siemieniak, David GinsburgiD
Abstract
While members of large paralogous protein families share structural features, their functional niches often diverge significantly. Serine protease inhibitors (SERPINs), whose members typically function as covalent inhibitors of serine proteases, are one such family. Plasminogen activator inhibitor-1 (PAI-1) is a prototypic SERPIN, which canonically inhibits tissue-and urokinase-type plasminogen activators (tPA and uPA) to regulate fibrinolysis. PAI-1 has been shown to also inhibit other serine proteases, including coagulation factor XIIa (FXIIa) and transmembrane serine protease 2 (TMPRSS2). The structural determinants of PAI-1 inhibitory function toward these non-canonical protease targets, and the biological significance of these functions, are unknown. We applied deep mutational scanning (DMS) to assess the effects of [~]80% of all possible single amino acid substitutions in PAI-1 on its ability to inhibit three putative serine protease targets (uPA, FXIIa, and TMPRSS2). Selection with each target protease generated a unique PAI-1 mutational landscape, with the determinants of protease specificity distributed throughout PAI-1s primary sequence. Next, we conducted a comparative analysis of extant orthologous sequences, demonstrating that key residues modulating PAI-1 inhibition of uPA and FXIIa, but not TMPRSS2, are maintained by purifying selection. PAI-1s activity toward FXIIa may reflect how protease evolutionary relationships predict SERPIN functional divergence, which we support via a cophylogenetic analysis of all secreted SERPINs and their cognate serine proteases. This work provides insight into the functional diversification of SERPINs and lays the framework for extending these studies to other proteases and their regulators.
- organism: human
- assay: proteomics
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
- Citations
- 5
- FWCI
- 1.62
- Field percentile
- top 18%
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