Computational approaches for drug discovery, such as quantitative structure-activity relationship, rely on structural similarities of small molecules to infer biological activity but are often ...limited to identifying new drug candidates in the chemical spaces close to known ligands. Here we report a biological activity-based modeling (BABM) approach, in which compound activity profiles established across multiple assays are used as signatures to predict compound activity in other assays or against a new target. This approach was validated by identifying candidate antivirals for Zika and Ebola viruses based on high-throughput screening data. BABM models were then applied to predict 311 compounds with potential activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Of the predicted compounds, 32% had antiviral activity in a cell culture live virus assay, the most potent compounds showing a half-maximal inhibitory concentration in the nanomolar range. Most of the confirmed anti-SARS-CoV-2 compounds were found to be viral entry inhibitors and/or autophagy modulators. The confirmed compounds have the potential to be further developed into anti-SARS-CoV-2 therapies.
Dietary supplements and natural products are often marketed as safe and effective alternatives to conventional drugs, but their safety and efficacy are not well regulated. To address the lack of ...scientific data in these areas, we assembled a collection of Dietary Supplements and Natural Products (DSNP), as well as Traditional Chinese Medicinal (TCM) plant extracts. These collections were then profiled in a series of in vitro high-throughput screening assays, including a liver cytochrome p450 enzyme panel, CAR/PXR signaling pathways, and P-glycoprotein (P-gp) transporter assay activities. This pipeline facilitated the interrogation of natural product–drug interaction (NaPDI) through prominent metabolizing pathways. In addition, we compared the activity profiles of the DSNP/TCM substances with those of an approved drug collection (the NCATS Pharmaceutical Collection or NPC). Many of the approved drugs have well-annotated mechanisms of action (MOAs), while the MOAs for most of the DSNP and TCM samples remain unknown. Based on the premise that compounds with similar activity profiles tend to share similar targets or MOA, we clustered the library activity profiles to identify overlap with the NPC to predict the MOAs of the DSNP/TCM substances. Our results suggest that many of these substances may have significant bioactivity and potential toxicity, and they provide a starting point for further research on their clinical relevance.
To generate drug molecules of desired properties with computational methods is the holy grail in pharmaceutical research. Here we describe an AI strategy, retro drug design, or RDD, to generate novel ...small molecule drugs from scratch to meet predefined requirements, including but not limited to biological activity against a drug target, and optimal range of physicochemical and ADMET properties. Traditional predictive models were first trained over experimental data for the target properties, using an atom typing based molecular descriptor system, ATP. Monte Carlo sampling algorithm was then utilized to find the solutions in the ATP space defined by the target properties, and the deep learning model of Seq2Seq was employed to decode molecular structures from the solutions. To test feasibility of the algorithm, we challenged RDD to generate novel drugs that can activate {\mu} opioid receptor (MOR) and penetrate blood brain barrier (BBB). Starting from vectors of random numbers, RDD generated 180,000 chemical structures, of which 78% were chemically valid. About 42,000 (31%) of the valid structures fell into the property space defined by MOR activity and BBB permeability. Out of the 42,000 structures, only 267 chemicals were commercially available, indicating a high extent of novelty of the AI-generated compounds. We purchased and assayed 96 compounds, and 25 of which were found to be MOR agonists. These compounds also have excellent BBB scores. The results presented in this paper illustrate that RDD has potential to revolutionize the current drug discovery process and create novel structures with multiple desired properties, including biological functions and ADMET properties. Availability of an AI-enabled fast track in drug discovery is essential to cope with emergent public health threat, such as pandemic of COVID-19.
Endometriosis is an estrogen dominant, chronic inflammatory disease characterized by the growth of endometrial-like tissue outside of the uterus. The most common symptoms experienced by patients ...include manifestations of chronic pelvic pain- such as pain with urination, menstruation, or defecation, and infertility. Alterations to Leukemia Inhibitory Factor (LIF), a cytokine produced by the luminal and glandular epithelium of the endometrium that is imperative for successful pregnancy, have been postulated to contribute to infertility. Conditions such as recurrent implantation failure, unexplained infertility, and infertility associated diseases such as adenomyosis and endometriosis, have demonstrated reduced LIF production in the endometrium of infertile patients compared to fertile counterparts. While this highlights the potential involvement of LIF in infertility, LIF is a multifaceted cytokine which plays additional roles in the maintenance of cell stemness and immunomodulation. Thus, we sought to explore the implications of LIF production within ectopic lesions on endometriosis pathophysiology. Through immunohistochemistry of an endometrioma tissue microarray and ELISA of tissue protein extract and peritoneal fluid samples, we identify LIF protein expression in the ectopic lesion microenvironment. Targeted RT qPCR for LIF and associated signaling transcripts, identify
to be significantly downregulated in the ectopic tissue compared to eutopic and control while its receptor,
, is upregulated, highlighting a discordance in ectopic protein and mRNA LIF expression.
treatment of endometriosis representative cell lines (12Z and hESC) with LIF increased production of immune-recruiting cytokines (MCP-1, MCP-3) and the angiogenic factor, VEGF, as well as stimulated tube formation in human umbilical vein endothelial cells (HUVECs). Finally, LIF treatment in a syngeneic mouse model of endometriosis induced both local and peripheral alterations to immune cell phenotypes, ultimately reducing immunoregulatory CD206
small peritoneal macrophages and T regulatory cells. These findings suggest that LIF is present in the ectopic lesions of endometriosis patients and could be contributing to lesion vascularization and immunomodulation.
Endometriosis is a chronic inflammatory disease in which endometrial-like tissue grows ectopically, resulting in pelvic pain and infertility. IL-23 is a key contributor in the development and ...differentiation of TH17 cells, driving TH17 cells toward a pathogenic profile. In a variety of inflammatory and autoimmune disorders, TH17 cells secrete proinflammatory cytokines, including IL-17, contributing to disease pathophysiology. Our studies and others have implicated IL-17 and TH17 cell dysregulation in endometriosis, which is associated with disease severity. In this article, we address whether IL-23-driven TH17 cells contribute to cardinal features of lesion proliferation, vascularization, and inflammation in endometriosis using patient samples, representative cell lines, and our established mouse model of endometriosis. The results indicated dysregulated expression of key genes in the IL-23/TH17 axis in patient ectopic and eutopic endometrial samples and increased IL-23 protein in patient plasma compared with controls. In vitro studies using primary human TH cells determined that rIL-23 mixture treatment increased pathogenic TH17 cell frequency. Similarly, rIL-23 treatment of cell lines (12Z cells, EECCs, HUVECs, and hESCs) representative of the endometriotic lesion microenvironment increased cytokines and growth factors, which play a role in lesion establishment and maintenance. In a syngeneic mouse model of endometriosis, rIL-23 treatment altered numbers of myeloid and T cell subsets in peritoneal fluid and increased giant cells within the lesion. Lesions from rIL-23-treated mice did not reveal significant alterations in proliferation/vascularization, although trends of increased proliferation and vascularization were observed. Collectively, these findings provide insights into the impact of the IL-23/TH17 axis on local immune dysfunction and broadly on endometriosis pathophysiology.
Communication, language, and discrimination Sachdev, Itesh; Ng, Sik Hung; Augoustinos, Martha ...
Journal of language and social psychology,
06/2007, Volume:
26, Issue:
2
Journal Article
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