Simulations of the regulatory ACT domain of human phenylalanine hydroxylase (PAH) unveil its mechanism of phenylalanine binding

Phenylalanine hydroxylase (PAH) regulates phenylalanine (Phe) levels in mammals to prevent neurotoxicity resulting from high Phe concentrations as observed in genetic disorders leading to hyperphenylalaninemia and phenylketonuria. PAH senses elevated Phe concentrations by transient allosteric Phe binding to a protein-protein interface between ACT domains of di…

Read more

Site-Specific Immuno-PET Tracer to Image PD-L1

The rapid ascension of immune checkpoint blockade treatments has placed an emphasis on the need for viable, robust, and noninvasive imaging methods for immune checkpoint proteins, which could be of diagnostic value. Immunoconjugate-based positron emission tomography (immuno-PET) allows for sensitive and quantitative imaging of target levels and has promising p…

Read more

Reconciling Simulated Ensembles of Apomyoglobin with Experimental Hydrogen/Deuterium Exchange Data Using Bayesian Inference and Multiensemble Markov State Models

Hydrogen/deuterium exchange (HDX) is a powerful technique to investigate protein conformational dynamics at amino acid resolution. Because HDX provides a measurement of solvent exposure of backbone hydrogens, ensemble-averaged over potentially slow kinetic processes, it has been challenging to use HDX protection factors to refine structural ensembles obtained …

Read more

Metal-Binding Q-Proline Macrocycles

We introduce the efficient Fmoc-SPPS and peptoid synthesis of Q-proline-based, metal-binding macrocycles (QPMs), which bind metal cations and display nine functional groups. Metal-free QPMs are disordered, evidenced by NMR and a crystal structure of QPM-3 obtained through racemic crystallization. Upon addition of metal cations, QPMs adopt ordered struct…

Read more

A tutorial on building markov state models with MSMBuilder and coarse-graining them with BACE

Markov state models (MSMs) are a powerful means of (1) making sense of molecular simulations, (2) making a quantitative connection between simulation and experiment, and (3) driving efficient simulations. A Markov model can be thought of as a map of the conformational space a molecule explores. Instead of having towns and cities connected with roads labeled with speed limits, a Markov model has conformational states and probabilities of transitioning between pairs of these states. Thi…

Read more

Quantitative comparison of alternative methods for coarse-graining biological networks

Markov models and master equations are a powerful means of modeling dynamic processes like protein conformational changes. However, these models are often difficult to understand because of the enormous number of components and connections between them. Therefore, a variety of methods have been developed to facilitate understanding by coarse-graining these complex models. Here, we employ Bayesian model comparison to determine which of these coarse-graining methods provides the models …

Read more

Extensive conformational heterogeneity within protein cores

Basic principles of statistical mechanics require that proteins sample an ensemble of conformations at any nonzero temperature. However, it is still common to treat the crystallographic structure of a protein as the structure of its native state, largely because high-resolution structural characterization of protein flexibility remains a profound challenge. To assess the typical degree of conformational heterogeneity within folded proteins, we construct Markov state models describing …

Read more