Contact inhibition of locomotion and mechanical cross-talk between cell-cell and cell-substrate adhesion determines the pattern of junctional tension in epithelial cell aggregates

We generated a computational approach to analyze the biomechanics of epithelial cell aggregates, either island or stripes or entire monolayers, that combines both vertex and contact-inhibition-of-locomotion models to include both cell-cell and cell-substrate adhesion. Examination of the distribution of cell protrusions (adhesion to the substrate) in the model predicted high order profiles of cell organization that agree with those previously seen experimentally. Cells acquired an asymmetric distribution of basal protrusions, traction forces and apical aspect ratios that decreased when moving from the edge to the island center. Our in silico analysis also showed that tension on cell-cell junctions and apical stress is not homogeneous across the island. Instead, these parameters are higher at the island center and scales up with island size, which we confirmed experimentally using laser ablation assays and immunofluorescence. Without formally being a 3-dimensional model, our approach has the minimal elements necessary to reproduce the distribution of cellular forces and mechanical crosstalk as well as distribution of principal stress in cells within epithelial cell aggregates. By making experimental testable predictions, our approach would benefit the mechanical analysis of epithelial tissues, especially when local changes in cell-cell and/or cell-substrate adhesion drive collective cell behavior.Comment: 39 pages, 8 Figures. Supplementary Information is include

Data-driven discovery of molecular photoswitches with multioutput Gaussian processes

Photoswitchable molecules display two or more isomeric forms that may be accessed using light. Separating the electronic absorption bands of these isomers is key to selectively addressing a specific isomer and achieving high photostationary states whilst overall red-shifting the absorption bands serves to limit material damage due to UV-exposure and increases penetration depth in photopharmacological applications. Engineering these properties into a system through synthetic design however, remains a challenge. Here, we present a data-driven discovery pipeline for molecular photoswitches underpinned by dataset curation and multitask learning with Gaussian processes. In the prediction of electronic transition wavelengths, we demonstrate that a multioutput Gaussian process (MOGP) trained using labels from four photoswitch transition wavelengths yields the strongest predictive performance relative to single-task models as well as operationally outperforming time-dependent density functional theory (TD-DFT) in terms of the wall-clock time for prediction. We validate our proposed approach experimentally by screening a library of commercially available photoswitchable molecules. Through this screen, we identified several motifs that displayed separated electronic absorption bands of their isomers, exhibited red-shifted absorptions, and are suited for information transfer and photopharmacological applications. Our curated dataset, code, as well as all models are made available at https://github.com/Ryan-Rhys/The-Photoswitch-Dataset

Tunable spin-state bistability in a spin crossover molecular complex

The spin crossover (SCO) transitions at both the surface and over the entire volume of the [Fe{H2B(pz)2}2(bipy)] polycrystalline films on Al2O3 substrates have been studied, where pz  =  pyrazol-1-yl and bipy  =  2,2'-bipyridine. For [Fe{H2B(pz)2}2(bipy)] films of hundreds of nm thick, magnetometry and x-ray absorption spectroscopy measurements show thermal hysteresis in the SCO transition with temperature, although the transition in bulk [Fe{H2B(pz)2}2(bipy)] occurs in a non-hysteretic fashion at 157 K. While the size of the crystallites in those films are similar, the hysteresis becomes more prominent in thinner films, indicating a significant effect of the [Fe{H2B(pz)2}2(bipy)]/Al2O3 interface. Bistability of spin states, which can be inferred from the thermal hysteresis, was directly observed using temperature-dependent x-ray diffraction; the crystallites behave as spin-state domains that coexist during the transition. The difference between the spin state of molecules at the surface of the [Fe{H2B(pz)2}2(bipy)] films and that of the molecules within the films, during the thermal cycle, indicates that both cooperative (intermolecular) effects and coordination are implicated in perturbations to the SCO transition

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

From Fertilisation to Implantation in Mammalian Pregnancy-Modulation of Early Human Reproduction by the Endocannabinoid System.

There is an increasing recognition that the endocannabinoid system is the crucial cytokine-hormone system regulating early human pregnancy. The synchronous development of the fertilized embryo and the endometrium to ensure timely implantation has been shown to be one of the pivotal steps to successful implantation. This development is thought to be regulated by a finely balanced relationship between various components of the endocannabinoid system in the endometrium, the embryo and the Fallopian tube. In addition, this system has also been shown to be involved in the regulation of the development and maturation of the gametes prior to fertilization. In this review, we will examine the evidence from animal and human studies to support the role of the endocannabinoid system in gametogenesis, fertilization, implantation, early pregnancy maintenance, and in immunomodulation of pregnancy. We will discuss the role of the cannabinoid receptors and the enzymes involved in the synthesis and degradation of the key endocannabinoid ligands (e.g., anandamide and 2-arachinoylglycerol) in early reproduction

Turning high-throughput structural biology into predictive inhibitor design

A common challenge in drug design pertains to finding chemical modifications to a ligand that increases its affinity to the target protein. An underutilized advance is the increase in structural biology throughput, which has progressed from an artisanal endeavor to a monthly throughput of hundreds of different ligands against a protein in modern synchrotrons. However, the missing piece is a framework that turns high-throughput crystallography data into predictive models for ligand design. Here, we designed a simple machine learning approach that predicts protein–ligand affinity from experimental structures of diverse ligands against a single protein paired with biochemical measurements. Our key insight is using physics-based energy descriptors to represent protein–ligand complexes and a learning-to-rank approach that infers the relevant differences between binding modes. We ran a high-throughput crystallography campaign against the SARS-CoV-2 main protease (MPro), obtaining parallel measurements of over 200 protein–ligand complexes and their binding activities. This allows us to design one-step library syntheses which improved the potency of two distinct micromolar hits by over 10-fold, arriving at a noncovalent and nonpeptidomimetic inhibitor with 120 nM antiviral efficacy. Crucially, our approach successfully extends ligands to unexplored regions of the binding pocket, executing large and fruitful moves in chemical space with simple chemistry

Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors

INTRODUCTION COVID-19 became a global pandemic partially as a result of the lack of easily deployable, broad-spectrum oral antivirals, which complicated its containment. Even endemically, and with effective vaccinations, it will continue to cause acute disease, death, and long-term sequelae globally unless there are accessible treatments. COVID-19 is not an isolated event but instead is the latest example of a viral pandemic threat to human health. Therefore, antiviral discovery and development should be a key pillar of pandemic preparedness efforts. RATIONALE One route to accelerate antiviral drug discovery is the establishment of open knowledge bases, the development of effective technology infrastructures, and the discovery of multiple potent antivirals suitable as starting points for the development of therapeutics. In this work, we report the results of the COVID Moonshot—a fully open science, crowdsourced, and structure-enabled drug discovery campaign—against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). This collaboration may serve as a roadmap for the potential development of future antivirals. RESULTS On the basis of the results of a crystallographic fragment screen, we crowdsourced design ideas to progress from fragment to lead compounds. The crowdsourcing strategy yielded several key compounds along the optimization trajectory, including the starting compound of what became the primary lead series. Three additional chemically distinct lead series were also explored, spanning a diversity of chemotypes. The collaborative and highly automated nature of the COVID Moonshot Consortium resulted in >18,000 compound designs, >2400 synthesized compounds, >490 ligand-bound x-ray structures, >22,000 alchemical free-energy calculations, and >10,000 biochemical measurements—all of which were made publicly available in real time. The recently approved antiviral ensitrelvir was identified in part based on crystallographic data from the COVID Moonshot Consortium. This campaign led to the discovery of a potent [median inhibitory concentration (IC50) = 37 ± 2 nM] and differentiated (noncovalent and nonpeptidic) lead compound that also exhibited potent cellular activity, with a median effective concentration (EC50) of 64 nM in A549-ACE2-TMPRSS2 cells and 126 nM in HeLa-ACE2 cells without measurable cytotoxicity. Although the pharmacokinetics of the reported compound is not yet optimal for therapeutic development, it is a promising starting point for further antiviral discovery and development. CONCLUSION The success of the COVID Moonshot project in producing potent antivirals, building open knowledge bases, accelerating external discovery efforts, and functioning as a useful information-exchange hub is an example of the potential effectiveness of open science antiviral discovery programs. The open science, patent-free nature of the project enabled a large number of collaborators to provide in-kind support, including synthesis, assays, and in vitro and in vivo experiments. By making all data immediately available and ensuring that all compounds are purchasable from Enamine without the need for materials transfer agreements, we aim to accelerate research globally along parallel tracks. In the process, we generated a detailed map of the structural plasticity of Mpro, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data to spur further research into antivirals and discovery methodologies. We hope that this can serve as an alternative model for antiviral discovery and future pandemic preparedness. Further, the project also showcases the role of machine learning, computational chemistry, and high-throughput structural biology as force multipliers in drug design. Artificial intelligence and machine learning algorithms help accelerate chemical synthesis while balancing multiple competing molecular properties. The design-make-test-analyze cycle was accelerated by these algorithms combined with planetary-scale biomolecular simulations of protein-ligand interactions and rapid structure determination

Expanding the repertoire of low‐molecular‐weight pentafluorosulfanyl‐substituted scaffolds

The pentafluorosulfanyl (-SF5) functional group is of increasing interest as a bioisostere in medicinal chemistry. A library of SF5-containing compounds, including amide, isoxazole, and oxindole derivatives, was synthesised using a range of solution-based and solventless methods, including microwave and ball-mill techniques. The library was tested against targets including human dihydroorotate dehydrogenase (HDHODH). A subsequent focused approach led to synthesis of analogues of the clinically used disease modifying anti-rheumatic drugs (DMARDs), Teriflunomide and Leflunomide, considered for potential COVID-19 use, where SF5 bioisostere deployment led to improved inhibition of HDHODH compared with the parent drugs. The results demonstrate the utility of the SF5 group in medicinal chemistry

2021 Taxonomic Update Of Phylum Negarnaviricota (Riboviria: Orthornavirae), Including The Large Orders Bunyavirales And Mononegavirales:Negarnaviricota Taxonomy Update 2021

Unfortunately, the inclusion of original names (in non-Latin script) of the following authors caused problems with author name indexing in PubMed. Therefore, these original names were removed from XML data to correct the PubMed record. Mengji Cao, Yuya Chiaki, Hideki Ebihara, Jingjing Fu, George Fú Gāo, Tong Han, Jiang Hong, Ni Hong, Seiji Hongo, Masayuki Horie, Dàohóng Jiāng, Fujio Kadono, Hideki Kondō, Kenji Kubota, Shaorong Li, Longhui Li, Jiànróng Lǐ, Huazhen Liu, Tomohide Natsuaki, Sergey V. Netesov, Anna Papa, Sofia Paraskevopoulou, Liying Qi, Takahide Sasaya, Mang Shi, Xiǎohóng Shí, Zhènglì Shí, Yoshifumi Shimomoto, Jin‑Won Song, Ayato Takada, Shigeharu Takeuchi, Yasuhiro Tomitaka, Keizō Tomonaga, Shinya Tsuda, Changchun Tu, Tomio Usugi, Nikos Vasilakis, Jiro Wada, Lin‑Fa Wang, Guoping Wang, Yanxiang Wang, Yaqin Wang, Tàiyún Wèi, Shaohua Wen, Jiangxiang Wu, Lei Xu, Hironobu Yanagisawa, Caixia Yang, Zuokun Yang, Lifeng Zhai, Yong‑Zhen Zhang, Song Zhang, Jinguo Zhang, Zhe Zhang, Xueping Zhou. In addition, the publication call-out in the supplementary material was updated from issue 11 to issue 12. The original article has been corrected