Fear of the human 'super predator' in native marsupials and introduced deer in Australia.

Recent experiments have demonstrated that carnivores and ungulates in Africa, Asia, Europe and North America fear the human 'super predator' far more than other predators. Australian mammals have been a focus of research on predator naiveté because it is suspected they show atypical antipredator responses. To experimentally test if mammals in Australia also most fear humans, we quantified the responses of four native marsupials (eastern grey kangaroo, Bennett's wallaby, Tasmanian pademelon, common brushtail possum) and introduced fallow deer to playbacks of predator (human, dog, Tasmanian devil, wolf) or non-predator control (sheep) vocalizations. Native marsupials most feared the human 'super predator', fleeing humans 2.4 times more often than the next most frightening predator (dogs), and being most, and significantly, vigilant to humans. These results demonstrate that native marsupials are not naïve to the peril humans pose, substantially expanding the taxonomic and geographic scope of the growing experimental evidence that wildlife worldwide generally perceive humans as the planet's most frightening predator. Introduced fallow deer fled humans, but not more than other predators, which we suggest may result from their being introduced. Our results point to both challenges concerning marsupial conservation and opportunities for exploiting fear of humans as a wildlife management tool.

Fragment-Based Discovery of Allosteric Inhibitors of SH2 Domain-Containing Protein Tyrosine Phosphatase-2 (SHP2).

The ubiquitously expressed protein tyrosine phosphatase SHP2 is required for signaling downstream of receptor tyrosine kinases (RTKs) and plays a role in regulating many cellular processes. Genetic knockdown and pharmacological inhibition of SHP2 suppresses RAS/MAPK signaling and inhibit the proliferation of RTK-driven cancer cell lines. Here, we describe the first reported fragment-to-lead campaign against SHP2, where X-ray crystallography and biophysical techniques were used to identify fragments binding to multiple sites on SHP2. Structure-guided optimization, including several computational methods, led to the discovery of two structurally distinct series of SHP2 inhibitors binding to the previously reported allosteric tunnel binding site (Tunnel Site). One of these series was advanced to a low-nanomolar lead that inhibited tumor growth when dosed orally to mice bearing HCC827 xenografts. Furthermore, a third series of SHP2 inhibitors was discovered binding to a previously unreported site, lying at the interface of the C-terminal SH2 and catalytic domains.

Prognostic Value of Multiplexed Assays of Variant Effect and Automated Patch-clamping for KCNH2-LQTS Risk Stratification.

Background: Long QT syndrome (LQTS) is a lethal arrhythmia condition, frequently caused by rare loss-of-function variants in the cardiac potassium channel encoded by KCNH2. Variant-based risk stratification is complicated by heterogenous clinical data, incomplete penetrance, and low-throughput functional data. Objective: To test the utility of variant-specific features, including high-throughput functional data, to predict cardiac events among KCNH2 variant heterozygotes. Methods: We quantified cell-surface trafficking of 18,323 variants in KCNH2 and recorded potassium current densities for 506 KCNH2 variants. Next, we deeply phenotyped 1150 KCNH2 missense variant patients, including ECG features, cardiac event history (528 total cardiac events), and mortality. We then assessed variant functional, in silico, structural, and LQTS penetrance data to stratify event-free survival for cardiac events in the study cohort. Results: Variant-specific current density (HR 0.28 [0.13-0.60]) and estimates of LQTS penetrance incorporating MAVE data (HR 3.16 [1.59-6.27]) were independently predictive of severe cardiac events when controlling for patient-specific features. Risk prediction models incorporating these data significantly improved prediction of 20 year cardiac events (AUC 0.79 [0.75-0.82]) over patient-only covariates (QTc and sex) (AUC 0.73 [0.70-0.77]). Conclusion: We show that high-throughput functional data, and other variant-specific features, meaningfully contribute to both diagnosis and prognosis of a clinically actionable monogenic disease.

Enabling synthesis in fragment-based drug discovery (FBDD): microscale high-throughput optimisation of the medicinal chemist's toolbox reactions.

Miniaturised high-throughput experimentation (HTE) is widely employed in industrial and academic laboratories for rapid reaction optimisation using material-limited, multifactorial reaction condition screening. In fragment-based drug discovery (FBDD), common toolbox reactions such as the Suzuki-Miyaura and Buchwald-Hartwig cross couplings can be hampered by the fragment's intrinsic heteroatom-rich pharmacophore which is required for ligand-protein binding. At Astex, we are using microscale HTE to speed up reaction optimisation and prevent target down-prioritisation. By identifying catalyst/base/solvent combinations which tolerate unprotected heteroatoms we can rapidly optimise key cross-couplings and expedite route design by avoiding superfluous protecting group manipulations. However, HTE requires extensive upfront training, and this modern automated synthesis technique largely differs to the way organic chemists are traditionally trained. To make HTE accessible to all our synthetic chemists we have developed a semi-automated workflow enabled by pre-made 96-well screening kits, rapid analytical methods and in-house software development, which is empowering chemists at Astex to run HTE screens independently with minimal training.

Accelerated Chemical Reaction Optimization Using Multi-Task Learning.

Functionalization of C-H bonds is a key challenge in medicinal chemistry, particularly for fragment-based drug discovery (FBDD) where such transformations require execution in the presence of polar functionality necessary for protein binding. Recent work has shown the effectiveness of Bayesian optimization (BO) for the self-optimization of chemical reactions; however, in all previous cases these algorithmic procedures have started with no prior information about the reaction of interest. In this work, we explore the use of multitask Bayesian optimization (MTBO) in several in silico case studies by leveraging reaction data collected from historical optimization campaigns to accelerate the optimization of new reactions. This methodology was then translated to real-world, medicinal chemistry applications in the yield optimization of several pharmaceutical intermediates using an autonomous flow-based reactor platform. The use of the MTBO algorithm was shown to be successful in determining optimal conditions of unseen experimental C-H activation reactions with differing substrates, demonstrating an efficient optimization strategy with large potential cost reductions when compared to industry-standard process optimization techniques. Our findings highlight the effectiveness of the methodology as an enabling tool in medicinal chemistry workflows, representing a step-change in the utilization of data and machine learning with the goal of accelerated reaction optimization.

Human disease-associated calmodulin mutations alter calcineurin function through multiple mechanisms.

Calmodulin (CaM) is a ubiquitous, calcium-sensing protein that regulates a multitude of processes throughout the body. In response to changes in [Ca2+], CaM modifies, activates, and deactivates enzymes and ion channels, as well as many other cellular processes. The importance of CaM is highlighted by the conservation of an identical amino acid sequence in all mammals. Alterations to CaM amino acid sequence were once thought to be incompatible with life. During the last decade modifications to the CaM protein sequence have been observed in patients suffering from life-threatening heart disease (calmodulinopathy). Thus far, inadequate or untimely interaction between mutant CaM and several proteins (LTCC, RyR2, and CaMKII) have been identified as mechanisms underlying calmodulinopathy. Given the extensive number of CaM interactions in the body, there are likely many consequences for altering CaM protein sequence. Here, we demonstrate that disease-associated CaM mutations alter the sensitivity and activity of the Ca2+-CaM-enhanced serine/threonine phosphatase calcineurin (CaN). Biophysical characterization by circular dichroism, solution NMR spectroscopy, stopped-flow kinetic measurements, and MD simulations provide mechanistic insight into mutation dysfunction as well as highlight important aspects of CaM Ca2+ signal transduction. We find that individual CaM point mutations (N53I, F89L, D129G, and F141L) impair CaN function, however, the mechanisms are not the same. Specifically, individual point mutations can influence or modify the following properties: CaM binding, Ca2+ binding, and/or Ca2+kinetics. Moreover, structural aspects of the CaNCaM complex can be altered in manners that indicate changes to allosteric transmission of CaM binding to the enzyme active site. Given that loss of CaN function can be fatal, as well as evidence that CaN modifies ion channels already associated with calmodulinopathy, our results raise the possibility that altered CaN function contributes to calmodulinopathy.

Top predator restricts the niche breadth of prey: effects of assisted colonization of Tasmanian devils on a widespread omnivorous prey.

Few landscape-scale experiments test the effects of predators on the abundance and distribution of prey across habitat gradients. We use the assisted colonization of a top predator, the Tasmanian devil (Sarcophilus harrisii), to test the impacts of predation on the abundance, habitat use and temporal activity of a widespread prey species, the omnivorous common brushtail possum (Trichosurus vulpecula). Before introduction of devils to Maria Island, Tasmania, Australia, in 2012, possums were abundant in open grasslands as well as forests. Predation by devils caused high mortality of possums in grasslands, but individuals with access to trees had a higher survival probability. Possum abundance declined across the whole island from 2012-2016, as possums disappeared almost completely from grasslands and declined in drier forests with more open understorey. Abundance remained stable in wet forests, which are not preferred habitat for possums but provide better refuge from devils. Abundance and habitat use of possums remained unchanged at a control site on the adjacent Tasmanian mainland, where the devil population was low and stable. This study demonstrates how spatial variation in predator-caused mortality can limit both abundance and habitat breadth in generalist prey species, excluding them entirely from certain habitats.

A Brief Introduction to Chemical Reaction Optimization.

From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

Fragment-to-Lead Medicinal Chemistry Publications in 2020.

Fragment-based drug discovery (FBDD) continues to evolve and make an impact in the pharmaceutical sciences. We summarize successful fragment-to-lead studies that were published in 2020. Having systematically analyzed annual scientific outputs since 2015, we discuss trends and best practices in terms of fragment libraries, target proteins, screening technologies, hit-optimization strategies, and the properties of hit fragments and the leads resulting from them. As well as the tabulated Fragment-to-Lead (F2L) programs, our 2020 literature review identifies several trends and innovations that promise to further increase the success of FBDD. These include developing structurally novel screening fragments, improving fragment-screening technologies, using new computer-aided design and virtual screening approaches, and combining FBDD with other innovative drug-discovery technologies.

A Review of Calcineurin Biophysics with Implications for Cardiac Physiology.

Calcineurin, also known as protein phosphatase 2B, is a heterodimeric serine threonine phosphatase involved in numerous signaling pathways. During the past 50 years, calcineurin has been the subject of extensive investigation. Many of its cellular and physiological functions have been described, and the underlying biophysical mechanisms are the subject of active investigation. With the abundance of techniques and experimental designs utilized to study calcineurin and its numerous substrates, it is difficult to reconcile the available information. There have been a plethora of reports describing the role of calcineurin in cardiac disease. However, a physiological role of calcineurin in healthy cardiomyocyte function requires clarification. Here, we review the seminal biophysical and structural details that are responsible for the molecular function and inhibition of calcineurin. We then focus on literature describing the roles of calcineurin in cardiomyocyte physiology and disease.

Non-Canonical Interaction between Calmodulin and Calcineurin Contributes to the Differential Regulation of Plant-Derived Calmodulins on Calcineurin.

Calmodulin (CaM) serves as an important Ca2+ signaling hub that regulates many protein signaling pathways. Recently, it was demonstrated that plant CaM homologues can regulate mammalian targets, often in a manner that opposes the impact of the mammalian CaM (mCaM). However, the molecular basis of how CaM homologue mutations differentially impact target activation is unclear. To understand these mechanisms, we examined two CaM isoforms found in soybean plants that differentially regulate a mammalian target, calcineurin (CaN). These CaM isoforms, sCaM-1 and sCaM-4, share >90 and ∼78% identity with the mCaM, respectively, and activate CaN with comparable or reduced activity relative to mCaM. We used molecular dynamics (MD) simulations and fluorometric assays of CaN-dependent dephosphorylation of MUF-P to probe whether calcium and protein-protein binding interactions are altered by plant CaMs relative to mCaM as a basis for differential CaN regulation. In the presence of CaN, we found that the two sCaMs' Ca2+ binding properties, such as their predicted coordination of Ca2+ and experimentally measured EC50 [Ca2+] values are comparable to mCaM. Furthermore, the binding of CaM to the CaM binding region (CaMBR) in CaN is comparable among the three CaMs, as evidenced by MD-predicted binding energies and experimentally measured EC50 [CaM] values. However, mCaM and sCaM-1 exhibited binding with a secondary region of CaN's regulatory domain that is weakened for sCaM-4. We speculate that this secondary interaction affects the turnover rate (kcat) of CaN based on our modeling of enzyme activity, which is consistent with our experimental data. Together, our data describe how plant-derived CaM variants alter CaN activity through enlisting interactions other than those directly influencing Ca2+ binding and canonical CaMBR binding, which may additionally play a role in the differential regulation of other mammalian targets.

Relative demographic susceptibility does not explain the extinction chronology of Sahul's megafauna.

The causes of Sahul's megafauna extinctions remain uncertain, although several interacting factors were likely responsible. To examine the relative support for hypotheses regarding plausible ecological mechanisms underlying these extinctions, we constructed the first stochastic, age-structured models for 13 extinct megafauna species from five functional/taxonomic groups, as well as 8 extant species within these groups for comparison. Perturbing specific demographic rates individually, we tested which species were more demographically susceptible to extinction, and then compared these relative sensitivities to the fossil-derived extinction chronology. Our models show that the macropodiformes were the least demographically susceptible to extinction, followed by carnivores, monotremes, vombatiform herbivores, and large birds. Five of the eight extant species were as or more susceptible than the extinct species. There was no clear relationship between extinction susceptibility and the extinction chronology for any perturbation scenario, while body mass and generation length explained much of the variation in relative risk. Our results reveal that the actual mechanisms leading to the observed extinction chronology were unlikely related to variation in demographic susceptibility per se, but were possibly driven instead by finer-scale variation in climate change and/or human prey choice and relative hunting success.

Structure-Based Design of Potent and Orally Active Isoindolinone Inhibitors of MDM2-p53 Protein-Protein Interaction.

Inhibition of murine double minute 2 (MDM2)-p53 protein-protein interaction with small molecules has been shown to reactivate p53 and inhibit tumor growth. Here, we describe rational, structure-guided, design of novel isoindolinone-based MDM2 inhibitors. MDM2 X-ray crystallography, quantum mechanics ligand-based design, and metabolite identification all contributed toward the discovery of potent in vitro and in vivo inhibitors of the MDM2-p53 interaction with representative compounds inducing cytostasis in an SJSA-1 osteosarcoma xenograft model following once-daily oral administration.

Accidents alter animal fitness landscapes.

Animals alter their habitat use in response to the energetic demands of movement ('energy landscapes') and the risk of predation ('the landscape of fear'). Recent research suggests that animals also select habitats and move in ways that minimise their chance of temporarily losing control of movement and thereby suffering slips, falls, collisions or other accidents, particularly when the consequences are likely to be severe (resulting in injury or death). We propose that animals respond to the costs of an 'accident landscape' in conjunction with predation risk and energetic costs when deciding when, where, and how to move in their daily lives. We develop a novel theoretical framework describing how features of physical landscapes interact with animal size, morphology, and behaviour to affect the risk and severity of accidents, and predict how accident risk might interact with predation risk and energetic costs to dictate movement decisions across the physical landscape. Future research should focus on testing the hypotheses presented here for different real-world systems to gain insight into the relative importance of theorised effects in the field.

The effects of weather variability on patterns of genetic diversity in Tasmanian bettongs.

While the effects of climate (long-term, prevailing weather) on species abundance, range and genetic diversity have been widely studied, short-term, localized variations in atmospheric conditions (i.e., weather) can also rapidly alter species' geographical ranges and population sizes, but little is known about how they affect genetic diversity. We investigated the relationship between weather and range-wide genetic diversity in a marsupial, Bettongia gaimardi, using dynamic species distribution models (SDMs). Genetic diversity was lower in parts of the range where the weather-based SDM predicted high variability in probability of B. gaimardi occurrence during 1950-2009. This is probably an effect of lower population sizes and extinction-recolonization cycles in places with highly variable weather. Spatial variation in genetic diversity was also better predicted by mean probabilities of B. gaimardi occurrence from weather- than climate-based SDMs. Our results illustrate the importance of weather in driving population dynamics and species distributions on decadal timescales and thereby in affecting genetic diversity. Modelling the links between changing weather patterns, species distributions and genetic diversity will allow researchers to better forecast biological impacts of climate change.

A triple threat: high population density, high foraging intensity and flexible habitat preferences explain high impact of feral cats on prey.

Alien mammalian carnivores have contributed disproportionately to global loss of biodiversity. In Australia, predation by the feral cat and red fox is one of the most significant causes of the decline of native vertebrates. To discover why cats have greater impacts on prey than native predators, we compared the ecology of the feral cat to a marsupial counterpart, the spotted-tailed quoll. Individual prey are 20-200 times more likely to encounter feral cats, because of the combined effects of cats' higher population densities, greater intensity of home-range use and broader habitat preferences. These characteristics also mean that the costs to the prey of adopting anti-predator behaviours against feral cats are likely to be much higher than adopting such behaviours in response to spotted-tailed quolls, due to the reliability and ubiquity of feral cat cues. These results help explain the devastating impacts of cats on wildlife in Australia and other parts of the world.

Fragment-to-Lead Medicinal Chemistry Publications in 2019.

Fragment-based drug discovery (FBDD) has grown and matured to a point where it is valuable to keep track of its extent and details of application. This Perspective summarizes successful fragment-to-lead stories published in 2019. It is the fifth in a series that started with literature published in 2015. The analysis of screening methods, optimization strategies, and molecular properties of hits and leads are presented in the hope of informing best practices for FBDD. Moreover, FBDD is constantly evolving, and the latest technologies and emerging trends are summarized. These include covalent FBDD, FBDD for the stabilization of proteins or protein-protein interactions, FBDD for enzyme activators, new screening technologies, and advances in library design and chemical synthesis.