Fold Family-Regularized Bayesian Optimization for Directed Protein Evolution

Directed Evolution (DE) is a technique for protein engineering that involves iterative rounds of mutagenesis and screening to search for sequences that optimize a given property (ex. binding affinity to a specified target). Unfortunately, the underlying optimization problem is under-determined, and so mutations introduced to improve the specified property may come at the expense of unmeasured, but nevertheless important properties (ex. subcellular localization). We seek to address this issue by incorporating a fold-specific regularization factor into the optimization problem. The regularization factor biases the search towards designs that resemble sequences from the fold family to which the protein belongs. We applied our method to a large library of protein GB1 mutants with binding affinity measurements to IgG-Fc. Our results demonstrate that the regularized optimization problem produces more native-like GB1 sequences with only a minor decrease in binding affinity. Specifically, the log-odds of our designs under a generative model of the GB1 fold family are between 41-45% higher than those obtained without regularization, with only a 7% drop in binding affinity. Thus, our method is capable of making a trade-off between competing traits. Moreover, we demonstrate that our active-learning driven approach reduces the wet-lab burden to identify optimal GB1 designs by 67%, relative to recent results from the Arnold lab on the same data

A Probability-Based Similarity Measure for Saupe Alignment Tensors with Applications to Residual Dipolar Couplings in NMR Structural Biology

High-throughput NMR structural biology and NMR structural genomics pose a fascinating set of geometric challenges. A key bottleneck in NMR structural biology is the resonance assignment problem. We seek to accelerate protein NMR resonance assignment and structure determination by exploiting a priori structural information. In particular, a method known as Nuclear Vector Replacement (NVR) has been proposed as a method for solving the assignment problem given a priori structural information [24,25]. Among several different kinds of input data, NVR uses a particular type of NMR data known as residual dipolar couplings (RDCs). The basic physics of residual dipolar couplings tells us that the data should be explainable by a structural model and set of parameters contained within the Saupe alignment tensor. In the NVR algorithm, one estimates the Saupe alignment tensors and then proceeds to refine those estimates. We would like to quantify the accuracy of such estimates, where we compare the estimated Saupe matrix to the correct Saupe matrix. In this work, we propose a way to quantify this comparison. Given a correct Saupe matrix and an estimated Saupe matrix, we compute an upper bound on the probability that a randomly rotated Saupe tensor would have an error smaller than the estimated Saupe matrix. This has the advantage of being a quantified upper bound which also has a clear interpretation in terms of geometry and probability. While the specific application of our rotation probability results is given to NVR, our novel methods can be used for any RDC-based algorithm to bound the accuracy of the estimated alignment tensors. Furthermore, they could also be used in X-ray crystallography or molecular docking to quantitate the accuracy of calculated rotations of proteins, protein domains, nucleic acids, or small molecules

Bitopic binding mode of an M1 muscarinic acetylcholine receptor agonist associated with adverse clinical trial outcomes

The realisation of the therapeutic potential of targeting the M1 muscarinic acetylcholine receptor (M1 mAChR) for the treatment of cognitive decline in Alzheimer's disease has prompted the discovery of M1 mAChR ligands showing efficacy in alleviating cognitive dysfunction in both rodents and humans. Among these is GSK1034702, described previously as a potent M1 receptor allosteric agonist, which showed pro-cognitive effects in rodents and improved immediate memory in a clinical nicotine withdrawal test but induced significant side-effects. Here we provide evidence using ligand binding, chemical biology and functional assays to establish that rather than the allosteric mechanism claimed, GSK1034702 interacts in a bitopic manner at the M1 mAChR such that it can concomitantly span both the orthosteric and an allosteric binding site. The bitopic nature of GSK1034702 together with the intrinsic agonist activity and a lack of muscarinic receptor subtype selectivity reported here, all likely contribute to the adverse effects of this molecule in clinical trials. We conclude that these properties, whilst imparting beneficial effects on learning and memory, are undesirable in a clinical candidate due to the likelihood of adverse side effects. Rather, our data supports the notion that "pure" positive allosteric modulators showing selectivity for the M1 mAChR with low levels of intrinsic activity would be preferable to provide clinical efficacy with low adverse responses

Monoclonal anti-β1-adrenergic receptor antibodies activate G protein signaling in the absence of β-arrestin recruitment

Thermostabilized G protein-coupled receptors used as antigens for in vivo immunization have resulted in the generation of functional agonistic anti-β1-adrenergic (β1AR) receptor monoclonal antibodies (mAbs). The focus of this study was to examine the pharmacology of these antibodies to evaluate their mechanistic activity at β1AR. Immunization with the β1AR stabilized receptor yielded five stable hybridoma clones, four of which expressed functional IgG, as determined in cell-based assays used to evaluate cAMP stimulation. The antibodies bind diverse epitopes associated with low nanomolar agonist activity at β1AR, and they appeared to show some degree of biased signaling as they were inactive in an assay measuring signaling through β-arrestin. In vitro characterization also verified different antibody-receptor interactions reflecting the different epitopes on the extracellular surface of β1AR to which the mAbs bind. The anti-β1AR mAbs only demonstrated agonist activity when in dimeric antibody format, but not as the monomeric Fab format, suggesting that agonist activation may be mediated through promoting receptor dimerization. Finally, we have also shown that at least one of these antibodies exhibits in vivo functional activity at a therapeutically-relevant dose producing an increase in heart rate consistent with β1AR agonism

Evaluation of expression and function of the H+/myo-inositol transporter HMIT;

BACKGROUND: The phosphoinositide (PIns) signalling pathway regulates a series of neuronal processes, such as neurotransmitter release, that are thought to be altered in mood disorders. Furthermore, mood-stabilising drugs have been shown to inhibit key enzymes that regulate PIns production and alter neuronal growth cone morphology in an inositol-reversible manner. Here, we describe analyses of expression and function of the recently identified H+/myo-inositol transporter (HMIT) investigated as a potential regulator of PIns signalling. RESULTS: We show that HMIT is primarily a neuronal transporter widely expressed in the rat and human brain, with particularly high levels in the hippocampus and cortex, as shown by immunohistochemistry. The transporter is localised at the Golgi apparatus in primary cultured neurones. No HMIT-mediated electrophysiological responses were detected in rat brain neurones or slices; in addition, inositol transport and homeostasis were unaffected in HMIT targeted null-mutant mice. CONCLUSION: Together, these data do not support a role for HMIT as a neuronal plasma membrane inositol transporter, as previously proposed. However, we observed that HMIT can transport inositol triphosphate, indicating unanticipated intracellular functions for this transporter that may be relevant to mood control

Positive allosteric modulation of the muscarinic M1 receptor improves efficacy of antipsychotics in mouse glutamatergic deficit models of behavior

Current antipsychotics are effective in treating the positive symptoms associated with schizophrenia, but they remain suboptimal in targeting cognitive dysfunction. Recent studies have suggested that positive allosteric modulation of the M1 muscarinic acetylcholine receptor (mAChR) may provide a novel means of improving cognition. However, very little is known about the potential of combination therapies in extending coverage across schizophrenic symptom domains. This study investigated the effect of the M1 mAChR positive allosteric modulator BQCA [1-(4-methoxybenzyl)-4-oxo-1,4-dihydroquinoline-3-carboxylic acid], alone or in combination with haloperidol (a first-generation antipsychotic), clozapine (a second-generation atypical antipsychotic), or aripiprazole (a third-generation atypical antipsychotic), in reversing deficits in sensorimotor gating and spatial memory induced by the N-methyl-d-aspartate receptor antagonist, MK-801 [(5R,10S)-(+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine]. Sensorimotor gating and spatial memory induction are two models that represent aspects of schizophrenia modeled in rodents. In prepulse inhibition (an operational measure of sensorimotor gating), BQCA alone had minimal effects but exhibited different levels of efficacy in reversing MK-801–induced prepulse inhibition disruptions when combined with a subeffective dose of each of the three (currently prescribed) antipsychotics. Furthermore, the combined effect of BQCA and clozapine was absent in M1−/− mice. Interestingly, although BQCA alone had no effect in reversing MK-801–induced memory impairments in a Y-maze spatial test, we observed a reversal upon the combination of BQCA with atypical antipsychotics, but not with haloperidol. These findings provide proof of concept that a judicious combination of existing antipsychotics with a selective M1 mAChR positive allosteric modulator can extend antipsychotic efficacy in glutamatergic deficit models of behavior

Directive 02-14: Tax Obligations of Persons Purchasing Cigarettes in Interstate Commerce for which the Massachusetts Cigarette Excise Has Not Been Paid

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications.</p