Long QT syndrome–associated mutations in KCNQ1 most often destabilize the protein, leading to mistrafficking and degradation.

The voltage-gated potassium channel KCNQ1 (KV7.1) assembles with the KCNE1 accessory protein to generate the slow delayed rectifier current, IKS, which is critical for membrane repolarization as part of the cardiac action potential. Loss-of-function (LOF) mutations in KCNQ1 are the most common cause of congenital long QT syndrome (LQTS), type 1 LQTS, an inherited genetic predisposition to cardiac arrhythmia and sudden cardiac death. A detailed structural understanding of KCNQ1 is needed to elucidate the molecular basis for KCNQ1 LOF in disease and to enable structure-guided design of new anti-arrhythmic drugs. In this work, advanced structural models of human KCNQ1 in the resting/closed and activated/open states were developed by Rosetta homology modeling guided by newly available experimentally-based templates: X. leavis KCNQ1 and various resting voltage sensor structures. Using molecular dynamics (MD) simulations, the capacity of the models to describe experimentally established channel properties including state-dependent voltage sensor gating charge interactions and pore conformations, PIP2 binding sites, and voltage sensor–pore domain interactions were validated. Rosetta energy calculations were applied to assess the utility of each model in interpreting mutation-evoked KCNQ1 dysfunction by predicting the change in protein thermodynamic stability for 50 experimentally characterized KCNQ1 variants with mutations located in the voltage-sensing domain. Energetic destabilization was successfully predicted for folding-defective KCNQ1 LOF mutants whereas wild type-like mutants exhibited no significant energetic frustrations, which supports growing evidence that mutation-induced protein destabilization is an especially common cause of KCNQ1 dysfunction. The new KCNQ1 Rosetta models provide helpful tools in the study of the structural basis for KCNQ1 function and can be used to generate hypotheses to explain KCNQ1 dysfunction.

Dynamic nuclear polarization (DNP) of a biomolecule tagged with a polarizing agent has the potential to not only increase NMR sensitivity but also to provide spectroscopy specificity towards the tagging...

Tauopathies are a class of neurodegenerative disorders characterized by the accumulation of tau protein filaments in the brain. On the basis of isoforms with three or four microtubule-binding repeats (3R or 4R) that constitute tau filaments, tauopathies can be divided into 3R, 4R, and 3R/4R tauopathies. [18F]­PI-2620 is a tau-positron emission tomography (PET) tracer that detects tau filaments in the 3R/4R tauopathy Alzheimer’s disease (AD) and the 4R tauopathies corticobasal degeneration (CBD) and progressive supranuclear palsy (PSP) with differential binding characteristics. A multiscale simulation workflow, including molecular docking, molecular dynamics simulation, metadynamics, and Brownian dynamics, was applied to uncover the molecular basis for the different binding properties of [18F]­PI-2620 in these tauopathies. The energetically best binding sites of [18F]­PI-2620 in the AD-tau filament are located in the C-shaped groove of the filament core structure that is accessible to the outside. The most favorable binding sites in CBD-tau and PSP-tau filaments are localized to cavities in the inner filament core. Sites on the outer surface have higher binding free energies, and interaction of [18F]­PI-2620 at these sites was short-lived in the molecular dynamics simulations. Computationally predicted associated rates of [18F]­PI-2620 with the groove sites in the AD-tau filament were higher than association rates with the cavity sites in the CBD- and PSP-tau filaments. The results indicate that tau filaments in AD combine favorable energetic and kinetic properties with regard to tracer binding, while the binding of [18F]­PI-2620 to filaments in CBD and PSP is kinetically restricted. Our findings reveal that distinct structural, energetic, and kinetic properties of tau filaments from AD, CBD, and PSP govern their interaction with PET tracers, which highlights the possibility to achieve tau isoform specificity in future tracer developments.

The function of the voltage-gated KCNQ1 potassium channel is regulated by co-assembly with KCNE auxiliary subunits. KCNQ1-KCNE1 channels generate the slow delayed rectifier current, IKs, which contributes to the repolarization phase of the cardiac action potential. A three amino acid motif (F57-T58-L59, FTL) in KCNE1 is essential for slow activation of KCNQ1-KCNE1 channels. However, how this motif interacts with KCNQ1 to control its function is unknown. Combining computational modeling with electrophysiological studies, we developed structural models of the KCNQ1-KCNE1 complex that suggest how KCNE1 controls KCNQ1 activation. The FTL motif binds at a cleft between the voltage-sensing and pore domains and appears to affect the channel gate by an allosteric mechanism. Comparison with the KCNQ1-KCNE3 channel structure suggests a common transmembrane-binding mode for different KCNEs and illuminates how specific differences in the interaction of their triplet motifs determine the profound differences in KCNQ1 functional modulation by KCNE1 versus KCNE3.

The recently discovered metagenomic-derived polyester hydrolase PHL7 is able to efficiently degrade amorphous polyethylene terephthalate (PET) in post-consumer plastic waste. We present the cocrystal structure of this hydrolase with its hydrolysis product terephthalic acid and elucidate the influence of 17 single mutations on the PET-hydrolytic activity and thermal stability of PHL7. The substrate-binding mode of terephthalic acid is similar to that of the thermophilic polyester hydrolase LCC and deviates from the mesophilic IsPETase. The subsite I modifications L93F and Q95Y, derived from LCC, increased the thermal stability, while exchange of H185S, derived from IsPETase, reduced the stability of PHL7. The subsite II residue H130 is suggested to represent an adaptation for high thermal stability, whereas L210 emerged as the main contributor to the observed high PET-hydrolytic activity. Variant L210T showed significantly higher activity, achieving a degradation rate of 20 µm h−1 with amorphous PET films.

Computational methods that produce accurate protein structure models from limited experimental data, for example, from nuclear magnetic resonance (NMR) spectroscopy, hold great potential for biomedical research. The NMR‐assisted modeling challenge in CASP13 provided a blind test to explore the capabilities and limitations of current modeling techniques in leveraging NMR data which had high sparsity, ambiguity, and error rate for protein structure prediction. We describe our approach to predict the structure of these proteins leveraging the Rosetta software suite. Protein structure models were predicted de novo using a two‐stage protocol. First, low‐resolution models were generated with the Rosetta de novo method guided by nonambiguous nuclear Overhauser effect (NOE) contacts and residual dipolar coupling (RDC) restraints. Second, iterative model hybridization and fragment insertion with the Rosetta comparative modeling method was used to refine and regularize models guided by all ambiguous and nonambiguous NOE contacts and RDCs. Nine out of 16 of the Rosetta de novo models had the correct fold (global distance test total score > 45) and in three cases high‐resolution models were achieved (root‐mean‐square deviation < 3.5 å). We also show that a meta‐approach applying iterative Rosetta + NMR refinement on server‐predicted models which employed non‐NMR‐contacts and structural templates leads to substantial improvement in model quality. Integrating these data‐assisted refinement strategies with innovative non‐data‐assisted approaches which became possible in CASP13 such as high precision contact prediction will in the near future enable structure determination for large proteins that are outside of the realm of conventional NMR.

The voltage-gated potassium channel KCNQ1 (KV7.1) assembles with the KCNE1 accessory protein to generate the slow delayed rectifier current, IKS, which is critical for membrane repolarization as part of the cardiac action potential. Loss-of-function (LOF) mutations in KCNQ1 are the most common cause of congenital long QT syndrome (LQTS), type 1 LQTS, an inherited genetic predisposition to cardiac arrhythmia and sudden cardiac death. A detailed structural understanding of KCNQ1 is needed to elucidate the molecular basis for KCNQ1 LOF in disease and to enable structure-guided design of new anti-arrhythmic drugs. In this work, advanced structural models of human KCNQ1 in the resting/closedand activated/open states were developed by Rosetta homology modeling guided by newly available experimentally-based templates: X. leavis KCNQ1 and resting voltage sensor structures. Using molecular dynamics (MD) simulations, the models' capability to describe experimentally established channel properties including state-dependent voltage sensor gating charge interactions and pore conformations, PIP2 binding sites, and voltage sensorpore domain interactions were validated. Rosetta energy calculations were applied to assess the models' utility in interpreting mutation-evoked KCNQ1 dysfunction by predicting the change in protein thermodynamic stability for 50 characterized KCNQ1 variants with mutations located in the voltage-sensing domain. Energetic destabilization was successfully predicted for folding-defective KCNQ1 LOF mutants whereas wild type-like mutants had no significant energetic frustrations, which supports growing evidence that mutation-induced protein destabilization is an especially common cause of KCNQ1 dysfunction. The new KCNQ1 Rosetta models provide helpful tools in the study of the structural mechanisms of KCNQ1 function and can be used to generate structurebased hypotheses to explain KCNQ1 dysfunction. Author SummaryCardiac rhythm is maintained by synchronized electrical impulses conducted throughout the heart. The potassium ion channel KCNQ1 is important for the repolarization phase of the cardiac action potential that underlies these electrical impulses. Heritable mutations in KCNQ1 can lead to channel loss-offunction (LOF) and predisposition to a life-threatening cardiac arrhythmia. Knowledge of the threedimensional structure of KCNQ1 is important to understand how mutations lead to LOF and to support structurally-guided design of new anti-arrhythmic drugs. In this work, we present the development and validation of molecular models of human KCNQ1 inferred by homology from the structure of frog KCNQ1.Models were developed for the open channel state in which potassium ions can pass through the channel and the closed state in which the channel is not conductive. Using molecular dynamics simulations, interactions in the voltage-sensing and pore domain of KCNQ1 and with the membrane lipid PIP2 were analyzed. Energy calculations for KCNQ1 mutations in the voltage-sensing domain reveled that most of 3 the mutations t...