Differential effects of disulfide bond formation in TEM-1 versus CTX-M-9 ß-lactamase.

To investigate how disulfide bonds can impact protein energy landscapes, we surveyed the effects of adding or removing a disulfide in two ß-lactamase enzymes, TEM-1 and CTX-M-9. The homologs share a structure and 38% sequence identity, but only TEM-1 contains a native disulfide bond. They also differ in thermodynamic stability and in the number of states populated at equilibrium: CTX-M-9 is two-state whereas TEM-1 has an additional intermediate state. We hypothesized that the disulfide bond is the major underlying determinant for these observed differences in their energy landscapes. To test this, we removed the disulfide bridge from TEM-1 and introduced a disulfide bridge at the same location in CTX-M-9. This modest change to sequence modulates the stabilities-and therefore populations-of TEM-1's equilibrium states and, more surprisingly, creates a novel third state in CTX-M-9. Unlike TEM-1's partially folded intermediate, this third state is a higher-order oligomer with reduced cysteines that retains the native fold and is fully active. Sub-denaturing concentrations of urea shifts the equilibrium to the monomeric form, allowing the disulfide bond to form. Interestingly, comparing the stability of the oxidized monomer with a variant lacking cysteines reveals the disulfide is neither stabilizing nor destabilizing in CTX-M-9, in contrast with the observed stabilization in TEM-1. Thus, we can conclude that engineering disulfide bonds is not always an effective stabilization strategy even when analogous disulfides exist in more stable structural homologs. This study also illustrates how homo-oligomerization can result from a small number of mutations, suggesting complex formation might be easily accessed during a protein family's evolution.

Natural and Synthetic Suppressor Mutations Defy Stability-Activity Tradeoffs.

Thermodynamic stability represents one important constraint on protein evolution, but the molecular basis for how mutations that change stability impact fitness remains unclear. Here, we demonstrate that a prevalent global suppressor mutation in TEM ß-lactamase, M182T, increases fitness by reducing proteolysis in vivo. We also show that a synthetic mutation, M182S, can act as a global suppressor and suggest that its absence from natural populations is due to genetic inaccessibility rather than fundamental differences in the protein's stability or activity.

Home Blood Pressure Monitoring.

Home blood pressure monitoring provides important diagnostic information beyond in-office blood pressure readings and offers similar results to ambulatory blood pressure monitoring. Home blood pressure monitoring involves patients independently measuring their blood pressure with an electronic device, whereas ambulatory blood pressure monitoring involves patients wearing a portable monitor for 24 to 48 hours. Although ambulatory blood pressure monitoring is the diagnostic standard for measurement, home blood pressure monitoring is more practical and accessible to patients, and its use is recommended by the U.S. Preventive Services Task Force and the American College of Cardiology/American Heart Association. Home blood pressure monitoring generally results in lower blood pressure readings than in-office measurements, can confirm the diagnosis of hypertension after an elevated office blood pressure reading, and can identify patients with white coat hypertension or masked hypertension. Best practices for home blood pressure monitoring include using an appropriately fitting upper-arm cuff on a bare arm, emptying the bladder, avoiding caffeinated beverages for 30 minutes before taking the measurement, resting for five minutes before taking the measurement, keeping the feet on the floor uncrossed and the arm supported with the cuff at heart level, and not talking during the reading. An average of multiple readings, ideally two readings in the morning and again in the evening separated by at least one minute each, is recommended for one week. Home blood pressure readings can be used in hypertension quality measures.

Cooperative Changes in Solvent Exposure Identify Cryptic Pockets, Switches, and Allosteric Coupling.

Proteins are dynamic molecules that undergo conformational changes to a broad spectrum of different excited states. Unfortunately, the small populations of these states make it difficult to determine their structures or functional implications. Computer simulations are an increasingly powerful means to identify and characterize functionally relevant excited states. However, this advance has uncovered a further challenge: it can be extremely difficult to identify the most salient features of large simulation data sets. We reasoned that many functionally relevant conformational changes are likely to involve large, cooperative changes to the surfaces that are available to interact with potential binding partners. To examine this hypothesis, we introduce a method that returns a prioritized list of potentially functional conformational changes by segmenting protein structures into clusters of residues that undergo cooperative changes in their solvent exposure, along with the hierarchy of interactions between these groups. We term these groups exposons to distinguish them from other types of clusters that arise in this analysis and others. We demonstrate, using three different model systems, that this method identifies experimentally validated and functionally relevant conformational changes, including conformational switches, allosteric coupling, and cryptic pockets. Our results suggest that key functional sites are hubs in the network of exposons. As a further test of the predictive power of this approach, we apply it to discover cryptic allosteric sites in two different ß-lactamase enzymes that are widespread sources of antibiotic resistance. Experimental tests confirm our predictions for both systems. Importantly, we provide the first evidence, to our knowledge, for a cryptic allosteric site in CTX-M-9 ß-lactamase. Experimentally testing this prediction did not require any mutations and revealed that this site exerts the most potent allosteric control over activity of any pockets found in ß-lactamases to date. Discovery of a similar pocket that was previously overlooked in the well-studied TEM-1 ß-lactamase demonstrates the utility of exposons.

Designing small molecules to target cryptic pockets yields both positive and negative allosteric modulators.

Allosteric drugs, which bind to proteins in regions other than their main ligand-binding or active sites, make it possible to target proteins considered "undruggable" and to develop new therapies that circumvent existing resistance. Despite growing interest in allosteric drug discovery, rational design is limited by a lack of sufficient structural information about alternative binding sites in proteins. Previously, we used Markov State Models (MSMs) to identify such "cryptic pockets," and here we describe a method for identifying compounds that bind in these cryptic pockets and modulate enzyme activity. Experimental tests validate our approach by revealing both an inhibitor and two activators of TEM ß-lactamase (TEM). To identify hits, a library of compounds is first virtually screened against either the crystal structure of a known cryptic pocket or an ensemble of structures containing the same cryptic pocket that is extracted from an MSM. Hit compounds are then screened experimentally and characterized kinetically in individual assays. We identify three hits, one inhibitor and two activators, demonstrating that screening for binding to allosteric sites can result in both positive and negative modulation. The hit compounds have modest effects on TEM activity, but all have higher affinities than previously identified inhibitors, which bind the same cryptic pocket but were found, by chance, via a computational screen targeting the active site. Site-directed mutagenesis of key contact residues predicted by the docking models is used to confirm that the compounds bind in the cryptic pocket as intended. Because hit compounds are identified from docking against both the crystal structure and structures from the MSM, this platform should prove suitable for many proteins, particularly targets whose crystal structures lack obvious druggable pockets, and for identifying both inhibitory and activating small-molecule modulators.

Prediction of New Stabilizing Mutations Based on Mechanistic Insights from Markov State Models.

Protein stabilization is fundamental to enzyme function and evolution, yet understanding the determinants of a protein's stability remains a challenge. This is largely due to a shortage of atomically detailed models for the ensemble of relevant protein conformations and their relative populations. For example, the M182T substitution in TEM ß-lactamase, an enzyme that confers antibiotic resistance to bacteria, is stabilizing but the precise mechanism remains unclear. Here, we employ Markov state models (MSMs) to uncover how M182T shifts the distribution of different structures that TEM adopts. We find that M182T stabilizes a helix that is a key component of a domain interface. We then predict the effects of other mutations, including a novel stabilizing mutation, and experimentally test our predictions using a combination of stability measurements, crystallography, NMR, and in vivo measurements of bacterial fitness. We expect our insights and methodology to provide a valuable foundation for protein design.

Evolutionary trend toward kinetic stability in the folding trajectory of RNases H.

Proper folding of proteins is critical to producing the biological machinery essential for cellular function. The rates and energetics of a protein's folding process, which is described by its energy landscape, are encoded in the amino acid sequence. Over the course of evolution, this landscape must be maintained such that the protein folds and remains folded over a biologically relevant time scale. How exactly a protein's energy landscape is maintained or altered throughout evolution is unclear. To study how a protein's energy landscape changed over time, we characterized the folding trajectories of ancestral proteins of the ribonuclease H (RNase H) family using ancestral sequence reconstruction to access the evolutionary history between RNases H from mesophilic and thermophilic bacteria. We found that despite large sequence divergence, the overall folding pathway is conserved over billions of years of evolution. There are robust trends in the rates of protein folding and unfolding; both modern RNases H evolved to be more kinetically stable than their most recent common ancestor. Finally, our study demonstrates how a partially folded intermediate provides a readily adaptable folding landscape by allowing the independent tuning of kinetics and thermodynamics.

Modelling proteins' hidden conformations to predict antibiotic resistance.

TEM ß-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

Discovery of multiple hidden allosteric sites by combining Markov state models and experiments.

The discovery of drug-like molecules that bind pockets in proteins that are not present in crystallographic structures yet exert allosteric control over activity has generated great interest in designing pharmaceuticals that exploit allosteric effects. However, there have only been a small number of successes, so the therapeutic potential of these pockets--called hidden allosteric sites--remains unclear. One challenge for assessing their utility is that rational drug design approaches require foreknowledge of the target site, but most hidden allosteric sites are only discovered when a small molecule is found to stabilize them. We present a means of decoupling the identification of hidden allosteric sites from the discovery of drugs that bind them by drawing on new developments in Markov state modeling that provide unprecedented access to microsecond- to millisecond-timescale fluctuations of a protein's structure. Visualizing these fluctuations allows us to identify potential hidden allosteric sites, which we then test via thiol labeling experiments. Application of these methods reveals multiple hidden allosteric sites in an important antibiotic target--TEM-1 ß-lactamase. This result supports the hypothesis that there are many as yet undiscovered hidden allosteric sites and suggests our methodology can identify such sites, providing a starting point for future drug design efforts. More generally, our results demonstrate the power of using Markov state models to guide experiments.

Thermodynamic system drift in protein evolution.

Proteins from thermophiles are generally more thermostable than their mesophilic homologs, but little is known about the evolutionary process driving these differences. Here we attempt to understand how the diverse thermostabilities of bacterial ribonuclease H1 (RNH) proteins evolved. RNH proteins from Thermus thermophilus (ttRNH) and Escherichia coli (ecRNH) share similar structures but differ in melting temperature (T(m)) by 20 °C. ttRNH's greater stability is caused in part by the presence of residual structure in the unfolded state, which results in a low heat capacity of unfolding (ΔCp) relative to ecRNH. We first characterized RNH proteins from a variety of extant bacteria and found that Tm correlates with the species' growth temperatures, consistent with environmental selection for stability. We then used ancestral sequence reconstruction to statistically infer evolutionary intermediates along lineages leading to ecRNH and ttRNH from their common ancestor, which existed approximately 3 billion years ago. Finally, we synthesized and experimentally characterized these intermediates. The shared ancestor has a melting temperature between those of ttRNH and ecRNH; the T(m)s of intermediate ancestors along the ttRNH lineage increased gradually over time, while the ecRNH lineage exhibited an abrupt drop in Tm followed by relatively little change. To determine whether the underlying mechanisms for thermostability correlate with the changes in T(m), we measured the thermodynamic basis for stabilization--ΔCp and other thermodynamic parameters--for each of the ancestors. We observed that, while the T(m) changes smoothly, the mechanistic basis for stability fluctuates over evolutionary time. Thus, even while overall stability appears to be strongly driven by selection, the proteins explored a wide variety of mechanisms of stabilization, a phenomenon we call "thermodynamic system drift." This suggests that even on lineages with strong selection to increase stability, proteins have wide latitude to explore sequence space, generating biophysical diversity and potentially opening new evolutionary pathways.

Cleavable hydrophilic linker for one-bead-one-compound sequencing of oligomer libraries by tandem mass spectrometry.

We have developed a method for the rapid and unambiguous identification of sequences of hit compounds from one-bead-one-compound combinatorial libraries of peptide and peptoid ligands. The approach uses a cleavable linker that is hydrophilic to help reduce nonspecific binding to biological samples and allows for the attachment of a halogen tag, which greatly facilitates post-screening sequencing by tandem mass spectrometry (MS/MS). The linker is based on a tartaric acid unit, which, upon cleavage from resin, generates a C-terminal aldehyde. This aldehyde can then be derivatized with a bromine-containing amino-oxy compound that serves as an isotope tag for subsequent MS/MS analysis of y-ion fragments. We have applied this linker and method to the syntheses of a number of peptoids that vary in sequence and length and have also demonstrated single-bead sequencing of a peptoid pentamer. The linker is also shown to have very low levels of nonspecific binding to proteins.