Global landscape of patents related to human coronaviruses.
Ontology highlight
ABSTRACT:
SUBMITTER: Liu K
PROVIDER: S-EPMC8071764 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The fundamental goal of small molecule discovery is to generate chemicals with target functionality. While this often proceeds through structure-based methods, we set out to investigate the practicality of orthogonal methods that leverage the extensive corpus of chemical literature. We hypothesize that a sufficiently large text-derived chemical function dataset would mirror the actual landscape of chemical functionality. Such a landscape would implicitly capture complex physical and biological interactions given that chemical function arises from both a molecule's structure and its interacting partners. To evaluate this hypothesis, we built a Chemical Function (CheF) dataset of patent-derived functional labels. This dataset, comprising 631K molecule-function pairs, was created using an LLM- and embedding-based method to obtain functional labels for approximately 100K molecules from their corresponding 188K unique patents. We carry out a series of analyses demonstrating that the CheF dataset contains a semantically coherent textual representation of the functional landscape congruent with chemical structural relationships, thus approximating the actual chemical function landscape. We then demonstrate that this text-based functional landscape can be leveraged to identify drugs with target functionality using a model able to predict functional profiles from structure alone. We believe that functional label-guided molecular discovery may serve as an orthogonal approach to traditional structure-based methods in the pursuit of designing novel functional molecules.
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Project description:Human immunodeficiency virus (HIV) has a small genome and therefore relies heavily on the host cellular machinery to replicate. Identifying which host proteins and complexes come into physical contact with the viral proteins is crucial for a comprehensive understanding of how HIV rewires the host's cellular machinery during the course of infection. Here we report the use of affinity tagging and purification mass spectrometry to determine systematically the physical interactions of all 18 HIV-1 proteins and polyproteins with host proteins in two different human cell lines (HEK293 and Jurkat). Using a quantitative scoring system that we call MiST, we identified with high confidence 497 HIV-human protein-protein interactions involving 435 individual human proteins, with ?40% of the interactions being identified in both cell types. We found that the host proteins hijacked by HIV, especially those found interacting in both cell types, are highly conserved across primates. We uncovered a number of host complexes targeted by viral proteins, including the finding that HIV protease cleaves eIF3d, a subunit of eukaryotic translation initiation factor 3. This host protein is one of eleven identified in this analysis that act to inhibit HIV replication. This data set facilitates a more comprehensive and detailed understanding of how the host machinery is manipulated during the course of HIV infection.
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Project description:Bats are a unique group of mammals of the order Chiroptera. They are highly diversified and are the group of mammals with the second largest number of species. Such highly diversified cell types and receptors facilitate them to be potential hosts of a large variety of viruses. Bats are the only group of mammals capable of sustained flight, which enables them to disseminate the viruses they harbor and enhance the chance of interspecies transmission. This article aims at reviewing the various aspects of the global epidemiology of bat coronaviruses (CoVs). Before the SARS epidemic, bats were not known to be hosts for CoVs. In the last 15 years, bats have been found to be hosts of >30 CoVs with complete genomes sequenced, and many more if those without genome sequences are included. Among the four CoV genera, only alphaCoVs and betaCoVs have been found in bats. As a whole, both alphaCoVs and betaCoVs have been detected from bats in Asia, Europe, Africa, North and South America and Australasia; but alphaCoVs seem to be more widespread than betaCoVs, and their detection rate is also higher. For betaCoVs, only those from subgenera Sarbecovirus, Merbecovirus, Nobecovirus and Hibecovirus have been detected in bats. Most notably, horseshoe bats are the reservoir of SARS-CoV, and several betaCoVs from subgenus Merbecovirus are closely related to MERS-CoV. In addition to the interactions among various bat species themselves, bat⁻animal and bat⁻human interactions, such as the presence of live bats in wildlife wet markets and restaurants in Southern China, are important for interspecies transmission of CoVs and may lead to devastating global outbreaks.
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Project description:BackgroundThe isolation of artemisinin in 1971 heralded the beginning of a new era in antimalarial drug therapy, and artemisinin-based combination therapies are currently the mainstay of malaria treatment worldwide. Artemisinin-related studies have been extensively and intensively executed in the last few decades. However, although many purely technological reviews have been completed in this field, studies on artemisinin from the perspective of patents are still very limited. In terms of the importance of patents for academic research and commercial development, this study aims to reveal the overall patent landscape of artemisinin in the temporal, spatial, and technological dimensions. This work may provide a useful reference for relevant decision-making by researchers, investors, and policymakers.MethodsAll available patent data relevant to artemisinin derivatives and artemisinin-based drug combinations developed for use in various therapeutic areas were collected from the Derwent Innovation database. Descriptive statistics and citation analyses were used to analyze the patent landscape.ResultsA total of 4594 patent documents and 1450 simple patent families from 1986 to 2019 were analyzed. A comprehensive patent landscape of artemisinin is presented from the aspects of time trends, filing countries, patent ownership, co-patents, technological categories, therapeutic areas, and citation networks and pathways.ConclusionsChina and the United States are mainly responsible for the dramatic increase of artemisinin patents over the last three decades. From the point of view of patents, notable technological issues on artemisinin are chemical and biological synthesis, novel combinations, new formulations and administration routes, drug repositioning, and minimizing the resistance. Furthermore, a critical challenge lies in how to stimulate the industry to develop artemisinin-related drugs by government regulation and public-private partnership.
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Project description:Environmental factors could influence the epidemic of virus in human; however, the association remains intricate, and the evidence is still not clear in human coronaviruses (HCoVs). We aimed to explore and compare the associations between HCoVs' epidemic and environmental factors globally. Four common HCoVs' data were collected by a systematic literature review, and data of MERS, SARS, and COVID-19 were collected from the World Health Organization's reports. Monthly positive rates of common HCoVs and incidence rates of MERS, SARS, and COVID-19 were calculated. Geographical coordinates were used to link virus data and environmental data. Generalized additive models (GAMs) were used to quantitatively estimate the association of environmental factors with HCoVs' epidemic. We found that there are wide associations between HCoVs and environmental factors on a global scale, and some of the associations were nonlinear. In addition, COVID-19 has the most similarities in associations' direction with common HCoVs, especially for HCoV-HKU1 in four environmental factors including the significantly negative associations with average temperature, precipitation, vegetation coverage (p<0.05), and the U-shaped association with temperature range. This study strengthened the relevant research evidences and provided significant insights into the epidemic rules of HCoVs in general. The similarities between COVID-19 and common HCoVs indicated that it is critically important to strengthen surveillance on common HCoVs and pay more attention to environmental factors' role in surveillance and early warning of HCoVs' epidemic.
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Project description:Cytokines are cell-to-cell signaling proteins that play a central role in immune development, pathogen responses, and diseases. Cytokines are highly regulated at the transcriptional level by combinations of transcription factors (TFs) that recruit cofactors and the transcriptional machinery. Here, we mined through three decades of studies to generate a comprehensive database, CytReg, reporting 843 and 647 interactions between TFs and cytokine genes, in human and mouse respectively. By integrating CytReg with other functional datasets, we determined general principles governing the transcriptional regulation of cytokine genes. In particular, we show a correlation between TF connectivity and immune phenotype and disease, we discuss the balance between tissue-specific and pathogen-activated TFs regulating each cytokine gene, and cooperativity and plasticity in cytokine regulation. We also illustrate the use of our database as a blueprint to predict TF-disease associations and identify potential TF-cytokine regulatory axes in autoimmune diseases. Finally, we discuss research biases in cytokine regulation studies, and use CytReg to predict novel interactions based on co-expression and motif analyses which we further validated experimentally. Overall, this resource provides a framework for the rational design of future cytokine gene regulation studies.
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Project description:BACKGROUND:In these trying times, we developed an R package about bibliographic references on coronaviruses. Working with reproducible research principles based on open science, disseminating scientific information, providing easy access to scientific production on this particular issue, and offering a rapid integration in researchers' workflows may help save time in this race against the virus, notably in terms of public health. OBJECTIVE:The goal is to simplify the workflow of interested researchers, with multidisciplinary research in mind. With more than 60,500 medical bibliographic references at the time of publication, this package is among the largest about coronaviruses. METHODS:This package could be of interest to epidemiologists, researchers in scientometrics, biostatisticians, as well as data scientists broadly defined. This package collects references from PubMed and organizes the data in a data frame. We then built functions to sort through this collection of references. Researchers can also integrate the data into their pipeline and implement them in R within their code libraries. RESULTS:We provide a short use case in this paper based on a bibliometric analysis of the references made available by this package. Classification techniques can also be used to go through the large volume of references and allow researchers to save time on this part of their research. Network analysis can be used to filter the data set. Text mining techniques can also help researchers calculate similarity indices and help them focus on the parts of the literature that are relevant for their research. CONCLUSIONS:This package aims at accelerating research on coronaviruses. Epidemiologists can integrate this package into their workflow. It is also possible to add a machine learning layer on top of this package to model the latest advances in research about coronaviruses, as we update this package daily. It is also the only one of this size, to the best of our knowledge, to be built in the R language.
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Project description:A response to Pervasive sequence patents cover the entire human genome by J Rosenfeld and C Mason. Genome Med 2013, 5:27. See related Correspondence by Rosenfeld and Mason, http://genomemedicine.com/content/5/3/27 and related letter by Rosenfeld and Mason, http://genomemedicine.com/content/6/2/15.
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