Amide Rotation Hindrance Predicts Proteolytic Resistance of Cystine-Knot Peptides

Abstract

Cystine-knot peptides have remarkable stability against protease degradation, and are attractive scaffolds for peptide-based therapeutic and diagnostic agents. In this work, by studying the hydrolysis reaction of a cystine-knot inhibitor MCTI-A and its variants with ab initio QM/MM molecular dynamics simulations, we have elucidated an amide rotation hindrance mechanism for proteolysis resistance: the proteolysis of MCTI-A is retarded due to the higher free energy cost during the rotation of NH group around scissile peptide bond at the tetrahedral intermediate of acylation, and covalent constraint provided by disulfide bonds is the key factor to hinder this rotation. A nearly linear correlation has been revealed between free energy barriers of the peptide hydrolysis reaction and the amide rotation free energy changes at the protease-peptide Michaelis complex state. This suggests that amide rotation hindrance could be one useful feature to estimate peptide proteolysis stability.

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

“…It may be that for the specific case of cleavage by mesotrypsin, the ratedetermining step is shifted from deacylation to acylation; this would be consistent with evidence that mesotrypsin accelerates canonical inhibitor cleavage via mutations that disrupt primed side substrate interactions, facilitating acyl-enzyme hydrolysis (23,24,54). Alternatively, the energy landscape for cleavage of Kunitz domains may differ from that of chymotrypsin inhibitor 2, such that acylation should be reconsidered as a rate-determining step in cleavage of Kunitz domains more generally, as has been suggested by other computational studies (51,52). It remains to be further explored how each step in the catalytic cycle may be impacted by the differential flexibility of Kunitz domains on the fast (nanosecond-microsecond) time scale and by consequent differential access to rare conformational states on the time scale of proteolysis.…”

“…Constrained dynamics during cleavage of these and other canonical serine protease inhibitors have been linked to their relative proteolytic resistance (20,51,52). For cleavage of chymotrypsin inhibitor 2 by subtilisin, we found that acylation occurred rapidly (within milliseconds) but reversibly, leading to an equilibrium favoring the intact peptide bond, and that a later step presumed to be acyl-enzyme hydrolysis was rate-limiting (20,28).…”

Recognition and Cleavage of Human tRNA Methyltransferase TRMT1 by the SARS-CoV-2 Main Protease

“…Comparing nsp4/5-, nsp8/9-, and TRMT1-bound M pro crystal structures, the scissile amide bond that links substrate residues P1 and P1′ are positioned almost identically in the active site and located at similar distances from the Cys145Ala residue ( Figure S6A ). Likewise, deviations away from 180 degrees in the dihedral angle of the scissile amide bond in these M pro -peptide structures, which could indicate ground state destabilization and help explain accelerated proteolysis for nsp4/5 (60), are also inconsistent with the observed trends in peptide cleavage rates ( Figure S6B ). Molecular dynamics simulations of nsp4/5 and TRMT1 peptide substrates bound to M pro support the observation that the unique P3′- in conformation is favored for TRMT1 binding, but that only subtle differences in geometry are present at the nucleophilic Cys145 residue and scissile peptide bond in the M pro -substrate complexes, which cannot account for the order of magnitude differences in observed cleavage kinetics between ns4/5 and TRMT1 substrates.…”

Two symmetric arginine residues play distinct roles in Thermus thermophilus Argonaute DNA guide strand-mediated DNA target cleavage

“…We employed B3LYP/6-31G(d) QM/MM-MD (56, 74) simulations with umbrella sampling (65,75,76), a computational tour de force to study biochemical reactions. This state-of-the-art computational approach provides a first-principles description of chemical bond formation/breaking and dynamics of the enzyme active site while properly incorporating the effects of heterogeneous and fluctuating protein environment, and has been demonstrated to be powerful in characterizing the reaction mechanism for a number of complex systems (64,74,(77)(78)(79)(80)(81)(82)(83)(84)(85)(86)(87). In addition, we also performed classic MD simulations for selective mutants of reactant and pentacovalent intermediate to identify the catalytic roles of key charged residues near the active site.…”