Discovery of Natural Products as Novel and Potent FXR Antagonists by Virtual Screening

Farnesoid X receptor (FXR) is a member of nuclear receptor family involved in multiple physiological processes through regulating specific target genes. The critical role of FXR as a transcriptional regulator makes it a promising target for diverse diseases, especially those related to metabolic disorders such as diabetes and cholestasis. However, the underlying activation mechanism of FXR is still a blur owing to the absence of proper FXR modulators. To identify potential FXR modulators, an in-house natural product database (NPD) containing over 4,000 compounds was screened by structure-based virtual screening strategy and subsequent hit-based similarity searching method. After the yeast two-hybrid (Y2H) assay, six natural products were identified as FXR antagonists which blocked the CDCA-induced SRC-1 association. The IC50 values of compounds 2a, a diterpene bearing polycyclic skeleton, and 3a, named daphneone with chain scaffold, are as low as 1.29 and 1.79 μM, respectively. Compared to the control compound guggulsterone (IC50 = 6.47 μM), compounds 2a and 3a displayed 5- and 3-fold higher antagonistic activities against FXR, respectively. Remarkably, the two representative compounds shared low topological similarities with other reported FXR antagonists. According to the putative binding poses, the molecular basis of these antagonists against FXR was also elucidated in this report

Intelligent Online Selling Point Extraction for E-commerce Recommendation

In the past decade, automatic product description generation for e-commerce have witnessed significant advancement. As the services provided by e-commerce platforms become diverse, it is necessary to dynamically adapt the patterns of descriptions generated. The selling point of products is an important type of product description for which the length should be as short as possible while still conveying key information. In addition, this kind of product description should be eye-catching to the readers. Currently, product selling points are normally written by human experts. Thus, the creation and maintenance of these contents incur high costs. These costs can be significantly reduced if product selling points can be automatically generated by machines. In this paper, we report our experience developing and deploying the Intelligent Online Selling Point Extraction (IOSPE) system to serve the recommendation system in the JD.com e-commerce platform. Since July 2020, IOSPE has become a core service for 62 key categories of products (covering more than 4 million products). So far, it has generated more than 1.1 billion selling points, thereby significantly scaling up the selling point creation operation and saving human labour. These IOSPE generated selling points have increased the click-through rate (CTR) by 1.89% and the average duration the customers spent on the products by more than 2.03% compared to the previous practice, which are significant improvements for such a large-scale e-commerce platform

Automatic Product Copywriting for E-commerce

Product copywriting is a critical component of e-commerce recommendation platforms. It aims to attract users' interest and improve user experience by highlighting product characteristics with textual descriptions. In this paper, we report our experience deploying the proposed Automatic Product Copywriting Generation (APCG) system into the JD.com e-commerce product recommendation platform. It consists of two main components: 1) natural language generation, which is built from a transformer-pointer network and a pre-trained sequence-to-sequence model based on millions of training data from our in-house platform; and 2) copywriting quality control, which is based on both automatic evaluation and human screening. For selected domains, the models are trained and updated daily with the updated training data. In addition, the model is also used as a real-time writing assistant tool on our live broadcast platform. The APCG system has been deployed in JD.com since Feb 2021. By Sep 2021, it has generated 2.53 million product descriptions, and improved the overall averaged click-through rate (CTR) and the Conversion Rate (CVR) by 4.22% and 3.61%, compared to baselines, respectively on a year-on-year basis. The accumulated Gross Merchandise Volume (GMV) made by our system is improved by 213.42%, compared to the number in Feb 2021

Data_Sheet_1_Discovery of Natural Products as Novel and Potent FXR Antagonists by Virtual Screening.pdf

<p>Farnesoid X receptor (FXR) is a member of nuclear receptor family involved in multiple physiological processes through regulating specific target genes. The critical role of FXR as a transcriptional regulator makes it a promising target for diverse diseases, especially those related to metabolic disorders such as diabetes and cholestasis. However, the underlying activation mechanism of FXR is still a blur owing to the absence of proper FXR modulators. To identify potential FXR modulators, an in-house natural product database (NPD) containing over 4,000 compounds was screened by structure-based virtual screening strategy and subsequent hit-based similarity searching method. After the yeast two-hybrid (Y2H) assay, six natural products were identified as FXR antagonists which blocked the CDCA-induced SRC-1 association. The IC₅₀ values of compounds 2a, a diterpene bearing polycyclic skeleton, and 3a, named daphneone with chain scaffold, are as low as 1.29 and 1.79 μM, respectively. Compared to the control compound guggulsterone (IC₅₀ = 6.47 μM), compounds 2a and 3a displayed 5- and 3-fold higher antagonistic activities against FXR, respectively. Remarkably, the two representative compounds shared low topological similarities with other reported FXR antagonists. According to the putative binding poses, the molecular basis of these antagonists against FXR was also elucidated in this report.</p

Design, Synthesis, X‑ray Crystallographic Analysis, and Biological Evaluation of Thiazole Derivatives as Potent and Selective Inhibitors of Human Dihydroorotate Dehydrogenase

Human dihydroorotate dehydrogenase (<i>Hs</i>DHODH) is a flavin-dependent mitochondrial enzyme that has been certified as a potential therapeutic target for the treatment of rheumatoid arthritis and other autoimmune diseases. On the basis of lead compound <b>4</b>, which was previously identified as potential <i>Hs</i>DHODH inhibitor, a novel series of thiazole derivatives were designed and synthesized. The X-ray complex structures of the promising analogues <b>12</b> and <b>33</b> confirmed that these inhibitors bind at the putative ubiquinone binding tunnel and guided us to explore more potent inhibitors, such as compounds <b>44</b>, <b>46</b>, and <b>47</b> which showed double digit nanomolar activities of 26, 18, and 29 nM, respectively. Moreover, <b>44</b> presented considerable anti-inflammation effect in vivo and significantly alleviated foot swelling in a dose-dependent manner, which disclosed that thiazole-scaffold analogues can be developed into the drug candidates for the treatment of rheumatoid arthritis by suppressing the bioactivity of <i>Hs</i>DHODH