The Next Frontier for Designing Switchable Proteins: Rational Enhancement of Kinetics

Abstract

Designing proteins that can switch between active (ON) and inactive (OFF) conformations in response to signals such as ligand binding and incident light has been a tantalizing endeavor in protein engineering for over a decade. While such designs have yielded novel biosensors, therapeutic agents, and smart biomaterials, the response times (times for switching ON and OFF) of many switches have been too slow to be of practical use. Among the defining properties of such switches, the kinetics of switching has been the most challenging to optimize. This is largely due to the difficulty of characterizing the structures of transient states, which are required for manipulating the height of the effective free energy barrier between the ON and OFF states. We share our perspective of the most promising new experimental and computational strategies over the past several years for tackling this next frontier for designing switchable proteins.

An overview of the vaccine platforms to combat COVID-19 with a focus on the subunit vaccines

“…The S protein's glycan shield helps the virus evade the human immune response by providing a thick sugar-coated barrier against any antibody ( Ghorbani et al, 2021 ). More specifically, the SARS-CoV-2 spike has 22 predicted N-glycosylation sites per protomer ( Bogetti et al, 2021 ), and at least two predicted O-glycosylation sites ( Q. Wang et al, 2021 ). The O-linked glycosylation pattern flanking the S1/S2 cleavage site is suggested to regulate the S protein activation during the viral infection ( Andersen et al, 2020 ), ( Sanda et al, 2020 ).…”

Enhancing response of a protein conformational switch by using two disordered ligand binding domains

“…One aspect of AFF switching is that the fold shift can be slow (seconds to hours depending on the protein). This is because the switching rate is typically limited by unfolding of the N-fold (or CPfold) which can be slow for stable proteins (Stratton and Loh, 2010;DeGrave et al, 2018;Bogetti et al, 2021). To determine the turn-on rate of Bn-AFF, we mixed the I96*G mutant with FK506, added RNA substrate at various times, and recorded the initial velocities.…”