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A semimechanistic pharmacokinetic (PK)/receptor occupancy (RO) model was constructed to differentiate a next generation anti-NKG2A monoclonal antibody (KSQ mAb) from monalizumab, an immune checkpoint inhibitor in multiple clinical trials for the treatment of solid tumors. A three-compartment model incorporating drug PK, biodistribution, and NKG2A receptor interactions was parameterized using monalizumab PK, in vitro affinity measurements for both monalizumab and KSQ mAb, and receptor burden estimates from the literature. Following calibration against monalizumab PK data in patients with rheumatoid arthritis, the model successfully predicted the published PK and RO observed in gynecological tumors and in patients with squamous cell carcinoma of the head and neck. Simulations predicted that the KSQ mAb requires a 10-fold lower dose than monalizumab to achieve a similar RO over a 3-week period following q3w intravenous (i.v.) infusion dosing. A global sensitivity analysis of the model indicated that the drug-target binding affinity greatly affects the tumor RO and that an optimal affinity is needed to balance RO with enhanced drug clearance due to target mediated drug disposition. The model predicted that the KSQ mAb can be dosed over a less frequent regimen or at lower dose levels than the current monalizumab clinical dosing regimen of 10 mg/kg q2w. Either dosing strategy represents a competitive advantage over the current therapy. The results of this study demonstrate a key role for mechanistic modeling in identifying optimal drug parameters to inform and accelerate progression of mAb to clinical trials., (© 2021 KSQ therapeutics, Inc. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Amyloid appearance is a rare event that is promoted in the presence of other aggregated proteins. These aggregates were thought to act by templating the formation of an assembly-competent nucleation seed, but we find an unanticipated role for them in enhancing the persistence of amyloid after it arises. Specifically, Saccharomyces cerevisiae Rnq1 amyloid reduces chaperone-mediated disassembly of Sup35 amyloid, promoting its persistence in yeast. Mathematical modeling and corresponding in vivo experiments link amyloid persistence to the conformationally defined size of the Sup35 nucleation seed and suggest that amyloid is actively cleared by disassembly below this threshold to suppress appearance of the [PSI + ] prion in vivo. Remarkably, this framework resolves multiple known inconsistencies in the appearance and curing of yeast prions. Thus, our observations establish the size of the nucleation seed as a previously unappreciated characteristic of prion variants that is key to understanding transitions between prion states.

A myriad of cellular events are regulated by allostery; therefore, evolution of this process is of fundamental interest. Here, we use ancestral sequence reconstruction to resurrect ancestors of two colocalizing proteins, Aurora A kinase and its allosteric activator TPX2 (targeting protein for Xklp2), to experimentally characterize the evolutionary path of allosteric activation. Autophosphorylation of the activation loop is the most ancient activation mechanism; it is fully developed in the oldest kinase ancestor and has remained stable over 1 billion years of evolution. As the microtubule-associated protein TPX2 appeared, efficient kinase binding to TPX2 evolved, likely owing to increased fitness by virtue of colocalization. Subsequently, TPX2-mediated allosteric kinase regulation gradually evolved. Surprisingly, evolution of this regulation is encoded in the kinase and did not arise by a dominating mechanism of coevolution., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

The self-assembly of alternative conformations of normal proteins into amyloid aggregates has been implicated in both the acquisition of new functions and in the appearance and progression of disease. However, while these amyloidogenic pathways are linked to the emergence of new phenotypes, numerous studies have uncoupled the accumulation of aggregates from their biological consequences, revealing currently underappreciated complexity in the determination of these traits. Here, to explore the molecular basis of protein-only phenotypes, we focused on the Saccharomyces cerevisiae Sup35/[PSI(+)] prion, which confers a translation termination defect and expression level-dependent toxicity in its amyloid form. Our studies reveal that aggregated Sup35 retains its normal function as a translation release factor. However, fluctuations in the composition and size of these complexes specifically alter the level of this aggregate-associated activity and thereby the severity and toxicity of the amyloid state. Thus, amyloid heterogeneity is a crucial contributor to protein-only phenotypes.

The dominant theory on the mechanism of response regulators activation in two-component bacterial signaling systems is the "Y-T coupling" mechanism, wherein the χ1 rotameric state of a highly conserved aromatic residue correlates with the activation of the protein via structural rearrangements coupled to a conserved tyrosine. In this paper, we present evidence that, in the receiver domain of the response regulator nitrogen regulatory protein C (NtrC(R)), the interconversion of this tyrosine (Y101) between its rotameric states is actually faster than the rate of inactive/active conversion and is not correlated to the activation process. Data gathered from NMR relaxation dispersion experiments show that a subset of residues surrounding the conserved tyrosine sense a process that is occurring at a faster rate than the inactive/active conformational transition. We show that this process is related to χ1 rotamer exchange of Y101 and that mutation of this aromatic residue to a leucine eliminated this second faster process without affecting activation. Computational simulations of NtrC(R) in its active conformation further demonstrate that the rotameric state of Y101 is uncorrelated with the global conformational transition during activation. Moreover, the tyrosine does not appear to be involved in the stabilization of the active form upon phosphorylation and is not essential in propagating the signal downstream for ATPase activity of the central domain. Our data provide experimental evidence against the generally accepted "Y-T coupling" mechanism of activation in NtrC(R)., (Copyright © 2013. Published by Elsevier Ltd.)

To study microsecond processes by relaxation dispersion NMR spectroscopy, low power deposition and short pulses are crucial and encourage the development of experiments that employ (1)H Carr-Purcell-Meiboom-Gill (CPMG) pulse trains. Herein, a method is described for the comprehensive study of microsecond to millisecond time scale dynamics of methyl groups in proteins, exploiting their high abundance and favorable relaxation properties. In our approach, protein samples are produced using [(1)H, (13)C]-d-glucose in ∼100% D(2)O, which yields CHD(2) methyl groups for alanine, valine, threonine, isoleucine, leucine, and methionine residues with high abundance, in an otherwise largely deuterated background. Methyl groups in such samples can be sequence-specifically assigned to near completion, using (13)C TOCSY NMR spectroscopy, as was recently demonstrated (Otten, R.; et al. J. Am. Chem. Soc. 2010, 132, 2952-2960). In this Article, NMR pulse schemes are presented to measure (1)H CPMG relaxation dispersion profiles for CHD(2) methyl groups, in a vein similar to that of backbone relaxation experiments. Because of the high deuteration level of methyl-bearing side chains, artifacts arising from proton scalar coupling during the CPMG pulse train are negligible, with the exception of Ile-δ1 and Thr-γ2 methyl groups, and a pulse scheme is described to remove the artifacts for those residues. Strong (13)C scalar coupling effects, observed for several leucine residues, are removed by alternative biochemical and NMR approaches. The methodology is applied to the transcriptional activator NtrC(r), for which an inactive/active state transition was previously measured and the motions in the microsecond time range were estimated through a combination of backbone (15)N CPMG dispersion NMR spectroscopy and a collection of experiments to determine the exchange-free component to the transverse relaxation rate. Exchange contributions to the (1)H line width were detected for 21 methyl groups, and these probes were found to collectively report on a local structural rearrangement around the phosphorylation site, with a rate constant of (15.5 ± 0.5) × 10(3) per second (i.e., τ(ex) = 64.7 ± 1.9 μs). The affected methyl groups indicate that, already before phosphorylation, a substantial, transient rearrangement takes place between helices 3 and 4 and strands 4 and 5. This conformational equilibrium allows the protein to gain access to the active, signaling state in the absence of covalent modification through a shift in a pre-existing dynamic equilibrium. Moreover, the conformational switching maps exactly to the regions that differ between the solution NMR structures of the fully inactive and active states. These results demonstrate that a cost-effective and quantitative study of protein methyl group dynamics by (1)H CPMG relaxation dispersion NMR spectroscopy is possible and can be applied to study functional motions on the microsecond time scale that cannot be accessed by backbone (15)N relaxation dispersion NMR. The use of methyl groups as dynamics probes extends such applications also to larger proteins.

While ground state structures combined with chemical tools and enzyme kinetics deliver useful information on possible chemical mechanisms of enzyme catalysis, they do not unravel the finely balanced energy inventory to explain the impressive rate enhancement of enzymes. For this goal, a complete description of enzyme catalysis in the form of an energy landscape is needed. Since the rate of catalysis is determined by the climb over a sequence of energy barriers, we focus here on the critical question of transition pathways. A combination of time-resolved NMR and simulation deliver a glimpse into how proteins can so efficiently move within the ensemble of the native conformations while avoiding unfolding during that journey. The loss of energy due to breakage of native contacts is compensated by non-native transient hydrogen bonds during the transition thereby 'holding on' to the energy until the new native contacts form that define the alternate functional state. The use of kinetic isotope effects (KIE) to study the chemical step show that coordinated atomic fluctuations of the protein component dictate the probability of 'correct' distance and orientation, due to its extreme sensitivity to distance. The examples here stress the point that highly choreographed conformational sampling together with chemical integrity is a prerequisite for efficient enzyme catalysis., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Phosphorylation is a common mechanism for activating proteins within signaling pathways. Yet, the molecular transitions between the inactive and active conformational states are poorly understood. Here we quantitatively characterize the free-energy landscape of activation of a signaling protein, nitrogen regulatory protein C (NtrC), by connecting functional protein dynamics of phosphorylation-dependent activation to protein folding and show that only a rarely populated, pre-existing active conformation is energetically stabilized by phosphorylation. Using nuclear magnetic resonance (NMR) dynamics, we test an atomic scale pathway for the complex conformational transition, inferred from molecular dynamics simulations (Lei et al., 2009). The data show that the loss of native stabilizing contacts during activation is compensated by non-native transient atomic interactions during the transition. The results unravel atomistic details of native-state protein energy landscapes by expanding the knowledge about ground states to transition landscapes.