Extracting thermodynamic properties from van 't Hoff plots with emphasis on temperature-sensing ion channels.

Transient receptor potential (TRP) ion channels are among the most well-studied classes of temperature-sensing molecules. Yet, the molecular mechanism and thermodynamic basis for the temperature sensitivity of TRP channels remains to this day poorly understood. One hypothesis is that the temperature-sensing mechanism can simply be described by a difference in heat capacity between the closed and open channel states. While such a two-state model may be simplistic it nonetheless has descriptive value, in the sense that it can be used to compare overall temperature sensitivity between different channels and mutants. Here, we introduce a mathematical framework based on the two-state model to reliably extract temperature-dependent thermodynamic potentials and heat capacities from measurements of equilibrium constants at different temperatures. Our framework is implemented in an open-source data analysis package that provides a straightforward way to fit both linear and nonlinear van 't Hoff plots, thus avoiding some of the previous, potentially erroneous, assumptions when extracting thermodynamic variables from TRP channel electrophysiology data.

Specificity, synergy, and mechanisms of splice-modifying drugs.

Drugs that target pre-mRNA splicing hold great therapeutic potential, but the quantitative understanding of how these drugs work is limited. Here we introduce mechanistically interpretable quantitative models for the sequence-specific and concentration-dependent behavior of splice-modifying drugs. Using massively parallel splicing assays, RNA-seq experiments, and precision dose-response curves, we obtain quantitative models for two small-molecule drugs, risdiplam and branaplam, developed for treating spinal muscular atrophy. The results quantitatively characterize the specificities of risdiplam and branaplam for 5' splice site sequences, suggest that branaplam recognizes 5' splice sites via two distinct interaction modes, and contradict the prevailing two-site hypothesis for risdiplam activity at SMN2 exon 7. The results also show that anomalous single-drug cooperativity, as well as multi-drug synergy, are widespread among small-molecule drugs and antisense-oligonucleotide drugs that promote exon inclusion. Our quantitative models thus clarify the mechanisms of existing treatments and provide a basis for the rational development of new therapies.

Protein dynamics underlying allosteric regulation.

Allostery is the mechanism by which information and control are propagated in biomolecules. It regulates ligand binding, chemical reactions, and conformational changes. An increasing level of experimental resolution and control over allosteric mechanisms promises a deeper understanding of the molecular basis for life and powerful new therapeutics. In this review, we survey the literature for an up-to-date biological and theoretical understanding of protein allostery. By delineating five ways in which the energy landscape or the kinetics of a system may change to give rise to allostery, we aim to help the reader grasp its physical origins. To illustrate this framework, we examine three systems that display these forms of allostery: allosteric inhibitors of beta-lactamases, thermosensation of TRP channels, and the role of kinetic allostery in the function of kinases. Finally, we summarize the growing power of computational tools available to investigate the different forms of allostery presented in this review.

Structure-function analysis suggests that the photoreceptor LITE-1 is a light-activated ion channel.

Sensation of light is essential for all organisms. The eye-less nematode Caenorhabditis elegans detects UV and blue light to evoke escape behavior. The photosensor LITE-1 absorbs UV photons with an unusually high extinction coefficient, involving essential tryptophans. Here, we modeled the structure and dynamics of LITE-1 using AlphaFold2-multimer and molecular dynamics (MD) simulations and performed mutational and behavioral assays in C. elegans to characterize its function. LITE-1 resembles olfactory and gustatory receptors from insects, recently shown to be tetrameric ion channels. We identified residues required for channel gating, light absorption, and mechanisms of photo-oxidation, involving a likely binding site for the peroxiredoxin PRDX-2. Furthermore, we identified the binding pocket for a putative chromophore. Several residues lining this pocket have previously been established as essential for LITE-1 function. A newly identified critical cysteine pointing into the pocket represents a likely chromophore attachment site. We derived a model for how photon absorption, via a network of tryptophans and other aromatic amino acids, induces an excited state that is transferred to the chromophore. This evokes conformational changes in the protein, possibly leading to a state receptive to oxidation of cysteines and, jointly, to channel gating. Electrophysiological data support the idea that LITE-1 is a photon and H2O2-coincidence detector. Other proteins with similarity to LITE-1, specifically C. elegans GUR-3, likely use a similar mechanism for photon detection. Thus, a common protein fold and assembly, used for chemoreception in insects, possibly by binding of a particular compound, may have evolved into a light-activated ion channel.

Conformational heterogeneity and probability distributions from single-particle cryo-electron microscopy.

Single-particle cryo-electron microscopy (cryo-EM) is a technique that takes projection images of biomolecules frozen at cryogenic temperatures. A major advantage of this technique is its ability to image single biomolecules in heterogeneous conformations. While this poses a challenge for data analysis, recent algorithmic advances have enabled the recovery of heterogeneous conformations from the noisy imaging data. Here, we review methods for the reconstruction and heterogeneity analysis of cryo-EM images, ranging from linear-transformation-based methods to nonlinear deep generative models. We overview the dimensionality-reduction techniques used in heterogeneous 3D reconstruction methods and specify what information each method can infer from the data. Then, we review the methods that use cryo-EM images to estimate probability distributions over conformations in reduced subspaces or predefined by atomistic simulations. We conclude with the ongoing challenges for the cryo-EM community.

Ensemble Reweighting Using Cryo-EM Particle Images.

Cryo-electron microscopy (cryo-EM) has recently become a leading method for obtaining high-resolution structures of biological macromolecules. However, cryo-EM is limited to biomolecular samples with low conformational heterogeneity, where most conformations can be well-sampled at various projection angles. While cryo-EM provides single-molecule data for heterogeneous molecules, most existing reconstruction tools cannot retrieve the ensemble distribution of possible molecular conformations from these data. To overcome these limitations, we build on a previous Bayesian approach and develop an ensemble refinement framework that estimates the ensemble density from a set of cryo-EM particle images by reweighting a prior conformational ensemble, e.g., from molecular dynamics simulations or structure prediction tools. Our work provides a general approach to recovering the equilibrium probability density of the biomolecule directly in conformational space from single-molecule data. To validate the framework, we study the extraction of state populations and free energies for a simple toy model and from synthetic cryo-EM particle images of a simulated protein that explores multiple folded and unfolded conformations.

What Makes a Kinase Promiscuous for Inhibitors?

ATP-competitive kinase inhibitors often bind several kinases due to the high conservation of the ATP binding pocket. Through clustering analysis of a large kinome profiling dataset, we found a cluster of eight promiscuous kinases that on average bind more than five times more kinase inhibitors than the other 398 kinases in the dataset. To understand the structural basis of promiscuous inhibitor binding, we determined the co-crystal structure of the receptor tyrosine kinase DDR1 with the type I inhibitors dasatinib and VX-680. Surprisingly, we find that DDR1 binds these type I inhibitors in an inactive conformation typically reserved for type II inhibitors. Our computational and biochemical studies show that DDR1 is unusually stable in this inactive conformation, giving a mechanistic explanation for inhibitor promiscuity. This phenotypic clustering analysis provides a strategy to obtain functional insights not available by sequence comparison alone.

An Open Library of Human Kinase Domain Constructs for Automated Bacterial Expression.

Kinases play a critical role in cellular signaling and are dysregulated in a number of diseases, such as cancer, diabetes, and neurodegeneration. Therapeutics targeting kinases currently account for roughly 50% of cancer drug discovery efforts. The ability to explore human kinase biochemistry and biophysics in the laboratory is essential to designing selective inhibitors and studying drug resistance. Bacterial expression systems are superior to insect or mammalian cells in terms of simplicity and cost effectiveness but have historically struggled with human kinase expression. Following the discovery that phosphatase coexpression produced high yields of Src and Abl kinase domains in bacteria, we have generated a library of 52 His-tagged human kinase domain constructs that express above 2 µg/mL of culture in an automated bacterial expression system utilizing phosphatase coexpression (YopH for Tyr kinases and lambda for Ser/Thr kinases). Here, we report a structural bioinformatics approach to identifying kinase domain constructs previously expressed in bacteria and likely to express well in our protocol, experiments demonstrating our simple construct selection strategy selects constructs with good expression yields in a test of 84 potential kinase domain boundaries for Abl, and yields from a high-throughput expression screen of 96 human kinase constructs. Using a fluorescence-based thermostability assay and a fluorescent ATP-competitive inhibitor, we show that the highest-expressing kinases are folded and have well-formed ATP binding sites. We also demonstrate that these constructs can enable characterization of clinical mutations by expressing a panel of 48 Src and 46 Abl mutations. The wild-type kinase construct library is available publicly via Addgene.

A dynamic mechanism for allosteric activation of Aurora kinase A by activation loop phosphorylation.

Many eukaryotic protein kinases are activated by phosphorylation on a specific conserved residue in the regulatory activation loop, a post-translational modification thought to stabilize the active DFG-In state of the catalytic domain. Here we use a battery of spectroscopic methods that track different catalytic elements of the kinase domain to show that the ~100 fold activation of the mitotic kinase Aurora A (AurA) by phosphorylation occurs without a population shift from the DFG-Out to the DFG-In state, and that the activation loop of the activated kinase remains highly dynamic. Instead, molecular dynamics simulations and electron paramagnetic resonance experiments show that phosphorylation triggers a switch within the DFG-In subpopulation from an autoinhibited DFG-In substate to an active DFG-In substate, leading to catalytic activation. This mechanism raises new questions about the functional role of the DFG-Out state in protein kinases.

Heat activation is intrinsic to the pore domain of TRPV1.

The TRPV1 channel is a sensitive detector of pain-producing stimuli, including noxious heat, acid, inflammatory mediators, and vanilloid compounds. Although binding sites for some activators have been identified, the location of the temperature sensor remains elusive. Using available structures of TRPV1 and voltage-activated potassium channels, we engineered chimeras wherein transmembrane regions of TRPV1 were transplanted into the Shaker Kv channel. Here we show that transplanting the pore domain of TRPV1 into Shaker gives rise to functional channels that can be activated by a TRPV1-selective tarantula toxin that binds to the outer pore of the channel. This pore-domain chimera is permeable to Na+, K+, and Ca2+ ions, and remarkably, is also robustly activated by noxious heat. Our results demonstrate that the pore of TRPV1 is a transportable domain that contains the structural elements sufficient for activation by noxious heat.

Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale.

The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (super)families, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences-from a single sequence to an entire superfamily-and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest), reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics-such as Markov state models (MSMs)-which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human tyrosine kinase family, using all available kinase catalytic domain structures from any organism as structural templates. Ensembler is free and open source software licensed under the GNU General Public License (GPL) v2. It is compatible with Linux and OS X. The latest release can be installed via the conda package manager, and the latest source can be downloaded from https://github.com/choderalab/ensembler.

Engineering vanilloid-sensitivity into the rat TRPV2 channel.

The TRPV1 channel is a detector of noxious stimuli, including heat, acidosis, vanilloid compounds and lipids. The gating mechanisms of the related TRPV2 channel are poorly understood because selective high affinity ligands are not available, and the threshold for heat activation is extremely high (>50°C). Cryo-EM structures of TRPV1 and TRPV2 reveal that they adopt similar structures, and identify a putative vanilloid binding pocket near the internal side of TRPV1. Here we use biochemical and electrophysiological approaches to investigate the resiniferatoxin(RTx) binding site in TRPV1 and to explore the functional relationships between TRPV1 and TRPV2. Collectively, our results support the interaction of vanilloids with the proposed RTx binding pocket, and demonstrate an allosteric influence of a tarantula toxin on vanilloid binding. Moreover, we show that sensitivity to RTx can be engineered into TRPV2, demonstrating that the gating and permeation properties of this channel are similar to TRPV1.

Modeling error in experimental assays using the bootstrap principle: understanding discrepancies between assays using different dispensing technologies.

All experimental assay data contains error, but the magnitude, type, and primary origin of this error is often not obvious. Here, we describe a simple set of assay modeling techniques based on the bootstrap principle that allow sources of error and bias to be simulated and propagated into assay results. We demonstrate how deceptively simple operations--such as the creation of a dilution series with a robotic liquid handler--can significantly amplify imprecision and even contribute substantially to bias. To illustrate these techniques, we review an example of how the choice of dispensing technology can impact assay measurements, and show how large contributions to discrepancies between assays can be easily understood and potentially corrected for. These simple modeling techniques--illustrated with an accompanying IPython notebook--can allow modelers to understand the expected error and bias in experimental datasets, and even help experimentalists design assays to more effectively reach accuracy and imprecision goals.

Modeling Suggests TRPC3 Hydrogen Bonding and Not Phosphorylation Contributes to the Ataxia Phenotype of the Moonwalker Mouse.

A gain-of-function mutation (T635A) in the transient receptor potential (TRP) channel TRPC3 results in abnormal channel gating and causes cerebellar ataxia in the dominant Moonwalker (Mwk) mouse mutant. However, the underlying molecular and structural mechanisms are unclear. Here, we used a combined approach of computational modeling and functional characterization of proposed TRPC3 mutants. Our findings support a mechanism by which the hydrogen bonding capability of threonine 635 plays a significant role in maintaining a stable, closed state channel. This capability is lost in the Mwk mutant, suggesting a structural basis for the disease-causing phenotype in the Mwk mouse.

Capsaicin interaction with TRPV1 channels in a lipid bilayer: molecular dynamics simulation.

Transient receptor potential vanilloid subtype 1 (TRPV1) is a heat-sensitive ion channel also involved in pain sensation, and is the receptor for capsaicin, the active ingredient of hot chili peppers. The recent structures of TRPV1 revealed putative ligand density within the S1 to S4 voltage-sensor-like domain of the protein. However, questions remain regarding the dynamic role of the lipid bilayer in ligand binding to TRPV1. Molecular dynamics simulations were used to explore behavior of capsaicin in a 1-palmitoyl-2-oleoyl phosphatidylcholine bilayer and with the target S1-S4 transmembrane helices of TRPV1. Equilibrium simulations reveal a preferred interfacial localization for capsaicin. We also observed a capsaicin molecule flipping from the extracellular to the intracellular leaflet, and subsequently able to access the intracellular TRPV1 binding site. Calculation of the potential of mean force (i.e., free energy profile) of capsaicin along the bilayer normal confirms that it prefers an interfacial localization. The free energy profile indicates that there is a nontrivial but surmountable barrier to the flipping of capsaicin between opposing leaflets of the bilayer. Molecular dynamics of the S1-S4 transmembrane helices of the TRPV1 in a lipid bilayer confirm that Y511, known to be crucial to capsaicin binding, has a distribution along the bilayer normal similar to that of the aromatic group of capsaicin. Simulations were conducted of the TRPV1 S1-S4 transmembrane helices in the presence of capsaicin placed in the aqueous phase, in the lipid, or docked to the protein. No stable interaction between ligand and protein was seen for simulations initiated with capsaicin in the bilayer. However, interactions were seen between TRPV1 and capsaicin starting from the cytosolic aqueous phase, and capsaicin remained stable in the majority of simulations from the docked pose. We discuss the significance of capsaicin flipping from the extracellular to the intracellular leaflet and mechanisms of binding site access by capsaicin.

Packing of the extracellular domain hydrophobic core has evolved to facilitate pentameric ligand-gated ion channel function.

Protein function depends on conformational flexibility and folding stability. Loose packing of hydrophobic cores is not infrequent in proteins, as the enhanced flexibility likely contributes to their biological function. Here, using experimental and computational approaches, we show that eukaryotic pentameric ligand-gated ion channels are characterized by loose packing of their extracellular domain ß-sandwich cores, and that loose packing contributes to their ability to rapidly switch from closed to open channel states in the presence of ligand. Functional analyses of GABA(A) receptors show that increasing the ß-core packing disrupted GABA-mediated currents, with impaired GABA efficacy and slowed GABA current activation and desensitization. We propose that loose packing of the hydrophobic ß-core developed as an evolutionary strategy aimed to facilitate the allosteric mechanisms of eukaryotic pentameric ligand-gated ion channels.

Reactant stationary approximation in enzyme kinetics.

In the application of the quasi-steady-state approximation, it is generally assumed that there is an initial transient during which the substrate concentration remains approximately constant while the complex concentration builds up. In this paper, we address the assumption that the substrate concentration does not change significantly during this initial transient and name it the reactant stationary approximation. For the single enzyme, single substrate reaction, the reactant stationary approximation is generally considered a sufficient condition to apply the quasi-steady-state approximation. Studying the dynamic behavior of this reaction with endogenous substrate, we show that the quasi-steady-state approximation and reactant stationary approximation are two separate approximations. We discuss the consequence of this result for the determination of reaction parameters in enzyme catalyzed reactions.

A test for measuring the effects of enzyme inactivation.

In the single-enzyme, single-substrate reaction with non-mechanism-based enzyme inactivation, the formation of the product and inactivation of the enzyme occur independently. For this reaction, we show that the steady-state hypothesis is applicable even when degradation of the enzyme occurs. An equation for the rate of product formation has been derived and it shows Michaelis-Menten kinetics with an apparent Michaelis-Menten constant K(M)(app)=K(M)+K(delta) where K(delta) is the enzyme inactivation constant. Use of a Lineweaver-Burk plot yields values for K(M)(app), which can be used to estimate K(delta) and, consequently, the degree of enzyme inactivation in a particular experiment. We employ this methodology to estimate the inactivation constant for the arsenate reductase catalyzed production of arsenite with appreciable enzyme inactivation.