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Abstract The RGD (Arg-Gly-Asp)-binding integrins αvβ6 and αvβ8 are clinically validated cancer and fibrosis targets of considerable therapeutic importance. Compounds that can discriminate between homologous αvβ6 and αvβ8 and other RGD integrins, stabilize specific conformational states, and have high thermal stability could have considerable therapeutic utility. Existing small molecule and antibody inhibitors do not have all these properties, and hence new approaches are needed. Here we describe a generalized method for computationally designing RGD-containing miniproteins selective for a single RGD integrin heterodimer and conformational state. We design hyperstable, selective αvβ6 and αvβ8 inhibitors that bind with picomolar affinity. CryoEM structures of the designed inhibitor-integrin complexes are very close to the computational design models, and show that the inhibitors stabilize specific conformational states of the αvβ6 and the αvβ8 integrins. In a lung fibrosis mouse model, the αvβ6 inhibitor potently reduced fibrotic burden and improved overall lung mechanics, demonstrating the therapeutic potential of de novo designed integrin binding proteins with high selectivity.

Discussion forums are a key component of online learning platforms, allowing learners to ask for help, provide help to others, and connect with others in the learning community. Analyzing patterns of forum usage and their association with course outcomes can provide valuable insight into how learners actually use discussion forums, and suggest strategies for shaping forum dynamics to improve learner experiences and outcomes. However, the fine-grained coding of forum posts required for this kind of analysis is a manually intensive process that can be challenging for large datasets, e.g., those that result from popular MOOCs. To address this issue, we propose an AI-assisted labeling process that uses advanced natural language processing techniques to train machine learning models capable of labeling a large dataset while minimizing human annotation effort. We fine-tune pretrained transformer-based deep learning models on category, structure, and emotion classification tasks. The transformer-based models outperform a more traditional baseline that uses support vector machines and a bag-of-words input representation. The transformer-based models also perform better when we augment the input features for an individual post with additional context from the post's thread (e.g., the thread title). We validate model quality through a combination of internal performance metrics, human auditing, and common-sense checks. For our Python MOOC dataset, we find that annotating approximately 1% of the forum posts achieves performance levels that are reliable for downstream analysis. Using labels from the validated AI models, we investigate the association of learner and course attributes with thread resolution and various forms of forum participation. We find significant differences in how learners of different age groups, gender, and course outcome status ask for help, provide help, and make posts with emotional (positive or negative) sentiment.

The first total synthesis of phenethylamine alkaloid based natural products discolin A, B, E and bacillimidazole B is reported, which were isolated from marine sea bacteria Tenacibaculum discolor sv11 and marine sponge. Total syntheses of discolin A, B, E and bacillimidazole B are achieved in two linear steps including condensation reaction and N-alkylation reaction with an overall yield of 68%, 35%, 65%, and 32%, respectively. A total of 24 analogues are prepared with moderate to excellent yield. All the natural products and their analogues were screened for antibacterial activity. The most active compound showed an IC50 of 122.1 nM against P. aeruginosa. [ABSTRACT FROM AUTHOR]

BackgroundCustomized fetal growth charts assume birthweight at term to be normally distributed across the population with a constant coefficient of variation at earlier gestational ages. Thus, standard deviation used for computing percentiles (e.g., 10th, 90th) is assumed to be proportional to the customized mean, although this assumption has never been formally tested.MethodsIn a secondary analysis of NICHD Fetal Growth Studies-Singletons (12 U.S. sites, 2009-2013) using longitudinal sonographic biometric data (n = 2288 pregnancies), we investigated the assumptions of normality and constant coefficient of variation by examining behavior of the mean and standard deviation, computed following the Gardosi method. We then created a more flexible model that customizes both mean and standard deviation using heteroscedastic regression and calculated customized percentiles directly using quantile regression, with an application in a separate study of 102, 012 deliveries, 37-41 weeks.ResultsAnalysis of term optimal birthweight challenged assumptions of proportionality and that values were normally distributed: at different mean birthweight values, standard deviation did not change linearly with mean birthweight and the percentile computed with the normality assumption deviated from empirical percentiles. Composite neonatal morbidity and mortality rates in relation to birthweight < 10th were higher for heteroscedastic and quantile models (10.3% and 10.0%, respectively) than the Gardosi model (7.2%), although prediction performance was similar among all three (c-statistic 0.52-0.53).ConclusionsOur findings question normality and constant coefficient of variation assumptions of the Gardosi customization method. A heteroscedastic model captures unstable variance in customization characteristics which may improve detection of abnormal growth percentiles.Trial registrationClinicalTrials.gov identifier: NCT00912132.

Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be tested computationally and experimentally in order to find stable ones, which is expensive in terms of time and resources. Here we use a high-throughput, low-fidelity assay to experimentally evaluate the stability of approximately 200,000 novel proteins. These include a wide range of sequence perturbations, providing a baseline for future work in the field. We build a neural network model that predicts protein stability given only sequences of amino acids, and compare its performance to the assayed values. We also report another network model that is able to generate the amino acid sequences of novel stable proteins given requested secondary sequences. Finally, we show that the predictive model—despite weaknesses including a noisy data set—can be used to substantially increase the stability of both expert-designed and model-generated proteins.

Tyrosinase is a copper‐containing enzyme involved in the biosynthesis of melanin pigment. While the excess production of melanin causes hyperpigmentation of human skin, hypopigmentation results in medical conditions like vitiligo. Tyrosinase inhibitors could be used as efficient skin whitening agents and tyrosinase agonists could be used for enhanced melanin synthesis and skin protection from UV exposure. Among a wide range of tyrosinase‐regulating compounds, natural and synthetic derivatives of furochromenones, such as 8‐methoxypsoralen (8‐MOP), are known to both activate and inhibit tyrosinase. We recently reported a synthetic approach to generate a variety of dihydrofuro[3,2‐c]chromenones and furo[3,2‐c]chromenones in a metal‐free condition. In the present study, we investigated these compounds for their potential as antagonists or agonists of tyrosinase. Using fungal tyrosinase‐based in vitro biochemical assay, we obtained one compound (3k) which could inhibit tyrosinase activity, and the other compound (4f) that stimulated tyrosinase activity. The kinetic studies revealed that compound 3k caused 'mixed' type tyrosinase inhibition and 4f stimulated the catalytic efficiency. Studying the mechanisms of these compounds may provide a basis for the development of new effective tyrosinase inhibitors or activators. [ABSTRACT FROM AUTHOR]

The mitochondrial electron transport chain is a major source of reactive oxygen species (ROS) and is also a target of ROS, with an implied role in the stabilization of hypoxia-inducible factor (HIF) and induction of the AMPK pathway. Here we used varying doses of two agents, Mito-Paraquat and Mito-Metformin, that have been conjugated to cationic triphenylphosphonium (TPP+) moiety to selectively target them to the mitochondrial matrix compartment, thereby resulting in the site-specific generation of ROS within mitochondria. These agents primarily induce superoxide (O2•–) production by acting on complex I. In Raw264.7 macrophages, C2C12 skeletal myocytes, and HCT116 adenocarcinoma cells, we show that mitochondria-targeted oxidants can induce ROS (O2•– and H2O2). In all three cell lines tested, the mitochondria-targeted agents disrupted membrane potential and activated calcineurin and the Cn-dependent retrograde signaling pathway. Hypoxic culture conditions also induced Cn activation and HIF1α activation in a temporally regulated manner, with the former appearing at shorter exposure times. Together, our results indicate that mitochondrial oxidant-induced retrograde signaling is driven by disruption of membrane potential and activation of Ca2+/Cn pathway and is independent of ROS-induced HIF1α or AMPK pathways.

Summary: This study shows that multiple modes of mitochondrial stress generated by partial mtDNA depletion or cytochrome c oxidase disruption cause ryanodine receptor channel (RyR) dysregulation, which instigates the release of Ca2+ in the cytoplasm of C2C12 myoblasts and HCT116 carcinoma cells. We also observed a reciprocal downregulation of IP3R channel activity and reduced mitochondrial uptake of Ca2+. Ryanodine, an RyR antagonist, abrogated the mitochondrial stress-mediated increase in [Ca2+]c and the entire downstream signaling cascades of mitochondrial retrograde signaling. Interestingly, ryanodine also inhibited mitochondrial stress-induced invasive behavior in mtDNA-depleted C2C12 cells and HCT116 carcinoma cells. In addition, co-immunoprecipitation shows reduced FKBP12 protein binding to RyR channel proteins, suggesting the altered function of the Ca2+ channel. These results document how the endoplasmic reticulum-associated RyR channels, in combination with inhibition of the mitochondrial uniporter system, modulate cellular Ca2+ homeostasis and signaling under mitochondrial stress conditions.

Background: Survival of Mycobacterium leprae, the causative bacteria for leprosy, in the human host is dependent to an extent on the ways in which its genome integrity is retained. DNA repair mechanisms protect bacterial DNA from damage induced by various stress factors. The current study is aimed at understanding the sequence and functional annotation of DNA repair genes in M. leprae. Methods: T he genome of M. leprae was annotated using sequence alignment tools to identify DNA repair genes that have homologs in Mycobacterium tuberculosis and Escherichia coli. A set of 96 genes known to be involved in DNA repair mechanisms in E. coli and Mycobacteriaceae were chosen as a reference. Among these, 61 were identified in M. leprae based on sequence similarity and domain architecture. The 61 were classified into 36 characterized gene products (59%), 11 hypothetical proteins (18%), and 14 pseudogenes (23%). All these genes have homologs in M. tuberculosis and 49 (80.32%) in E. coli. A set of 12 genes which are absent in E. coli were present in M. leprae and in Mycobacteriaceae. These 61 genes were further investigated for their expression profiles in the whole transcriptome microarray data of M. leprae which was obtained from the signal intensities of 60bp probes, tiling the entire genome with 10bp overlaps. Results: It was noted that transcripts corresponding to all the 61 genes were identified in the transcriptome data with varying expression levels ranging from 0.18 to 2.47 fold (normalized with 16SrRNA). The mRNA expression levels of a representative set of seven genes ( four annotated and three hypothetical protein coding genes) were analyzed using quantitative Polymerase Chain Reaction (qPCR) assays with RNA extracted from skin biopsies of 10 newly diagnosed, untreated leprosy cases. It was noted that RNA expression levels were higher for genes involved in homologous recombination whereas the genes with a low level of expression are involved in the direct repair pathway. Conclusion: This study provided preliminary information on the potential DNA repair pathways that are extant in M. leprae and the associated genes.

Herein, we describe the successful construction of composite DNA nanostructures by the self-assembly of complementary symmetrical 2,6,14-triptycenetripropiolic acid (TPA)–DNA building blocks and zinc protoporphyrin IX (Zn PpIX). DNA–organic molecule scaffolds for the composite DNA nanostructure were constructed through covalent conjugation of TPA with 5′-C12-amine-terminated modified single strand DNA (ssDNA) and its complementary strand. The repeated covalent conjugation of TPA with DNA was confirmed by using denaturing polyacrylamide gel electrophoresis (PAGE), reverse-phase high-performance liquid chromatography (RP-HPLC) and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF). The biologically relevant photosensitizer Zn PpIX was used to direct the hybridization-mediated self-assembly of DNA–TPA molecular building blocks as well as a model guest molecule within the DNA–TPA supramolecular self-assembly. The formation of fiber-like composite DNA nanostructures was observed. Native PAGE, circular dichroism (CD) and atomic force microscopy (AFM) have been utilized for analyzing the formation of DNA nanofibers after the coassembly. Computational methods were applied to discern the theoretical dimension of the DNA–TPA molecular building block of the nanofibers. A notable change in photocatalytic efficiency of Zn PpIX was observed when it was inside the TPA–DNA scaffold. The significant increase in ROS generation by Zn PpIX when trapped in this biocompatible DNA–TPA hybrid nanofiber may be an effective tool to explore photodynamic therapy (PDT) applications as well as photocatalytic reactions.