Recommender Systems in Antiviral Drug Discovery.
Ontology highlight
ABSTRACT:
SUBMITTER: Sosnina EA
PROVIDER: S-EPMC7315437 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Continued discovery and development of new antiviral medications are paramount for global human health, particularly as new pathogens emerge and old ones evolve to evade current therapeutic agents. Great success has been achieved in developing effective therapies to suppress human immunodeficiency virus (HIV) and hepatitis B virus (HBV); however, the therapies are not curative and therefore current efforts in HIV and HBV drug discovery are directed toward longer-acting therapies and/or developing new mechanisms of action that could potentially lead to cure, or eradication, of the virus. Recently, exciting early clinical data have been reported for novel antivirals targeting respiratory syncytial virus (RSV) and influenza (flu). Preclinical data suggest that these new approaches may be effective in treating high-risk patients afflicted with serious RSV or flu infections. In this review, we highlight new directions in antiviral approaches for HIV, HBV, and acute respiratory virus infections.
| S-EPMC4765712 | biostudies-other
Project description:BackgroundHealth recommender systems (HRSs) offer the potential to motivate and engage users to change their behavior by sharing better choices and actionable knowledge based on observed user behavior.ObjectiveWe aim to review HRSs targeting nonmedical professionals (laypersons) to better understand the current state of the art and identify both the main trends and the gaps with respect to current implementations.MethodsWe conducted a systematic literature review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and synthesized the results. A total of 73 published studies that reported both an implementation and evaluation of an HRS targeted to laypersons were included and analyzed in this review.ResultsRecommended items were classified into four major categories: lifestyle, nutrition, general health care information, and specific health conditions. The majority of HRSs use hybrid recommendation algorithms. Evaluations of HRSs vary greatly; half of the studies only evaluated the algorithm with various metrics, whereas others performed full-scale randomized controlled trials or conducted in-the-wild studies to evaluate the impact of HRSs, thereby showing that the field is slowly maturing. On the basis of our review, we derived five reporting guidelines that can serve as a reference frame for future HRS studies. HRS studies should clarify who the target user is and to whom the recommendations apply, what is recommended and how the recommendations are presented to the user, where the data set can be found, what algorithms were used to calculate the recommendations, and what evaluation protocol was used.ConclusionsThere is significant opportunity for an HRS to inform and guide health actions. Through this review, we promote the discussion of ways to augment HRS research by recommending a reference frame with five design guidelines.
| S-EPMC8278303 | biostudies-literature
Project description:One of the key questions in virology is how viruses, encoding relatively few genes, gain temporary or constant control over their hosts. To understand pathogenicity of a virus it is important to gain knowledge on the function of the individual viral proteins in the host cell, on their interactions with viral and cellular proteins and on the consequences of these interactions on cellular signaling pathways. A combination of transcriptomics, proteomics, high-throughput technologies and the bioinformatical analysis of the respective data help to elucidate specific cellular antiviral drug target candidates. In addition, viral and human interactome analyses indicate that different viruses target common, central human proteins for entering cellular signaling pathways and machineries which might constitute powerful broad-spectrum antiviral targets.
| S-EPMC7102765 | biostudies-literature
Project description:Structural biology has emerged during the last thirty years as a powerful tool for rational drug discovery. Crystal structures of biological targets alone and in complex with ligands and inhibitors provide essential insights into the mechanisms of actions of enzymes, their conformational changes upon ligand binding, the architectures and interactions of binding pockets. Structure-based methods such as crystallographic fragment screening represent nowadays invaluable instruments for the identification of new biologically active compounds. In this context, three-dimensional protein structures have played essential roles for the understanding of the activity and for the design of novel antiviral agents against several different viruses. In this review, the evolution in the resolution of viral structures is analysed, along with the role of crystal structures in the discovery and optimisation of new antivirals.
| S-EPMC7185576 | biostudies-literature
Project description:IntroductionThe highly pathogenic coronaviruses severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) are lethal zoonotic viruses that have emerged into human populations these past 15 years. These coronaviruses are associated with novel respiratory syndromes that spread from person-to-person via close contact, resulting in high morbidity and mortality caused by the progression to Acute Respiratory Distress Syndrome (ARDS). Areas covered: The risks of re-emergence of SARS-CoV from bat reservoir hosts, the persistence of MERS-CoV circulation, and the potential for future emergence of novel coronaviruses indicate antiviral drug discovery will require activity against multiple coronaviruses. In this review, approaches that antagonize viral nonstructural proteins, neutralize structural proteins, or modulate essential host elements of viral infection with varying levels of efficacy in models of highly pathogenic coronavirus disease are discussed. Expert opinion: Treatment of SARS and MERS in outbreak settings has focused on therapeutics with general antiviral activity and good safety profiles rather than efficacy data provided by cellular, rodent, or nonhuman primate models of highly pathogenic coronavirus infection. Based on lessons learned from SARS and MERS outbreaks, lack of drugs capable of pan-coronavirus antiviral activity increases the vulnerability of public health systems to a highly pathogenic coronavirus pandemic.
| S-EPMC7103675 | biostudies-literature
Project description:This research conducts an audit of Twitter's recommender system, aiming to examine the disparities between users' curated timelines and their subscription choices. Through the combined use of a browser extension and data collection via the Twitter API, our investigation reveals a high amplification of friends from the same community, a preference for amplifying emotionally charged and toxic tweets and an uneven algorithmic amplification across friends' political leaning. This audit emphasizes the importance of transparency, and increased awareness regarding the impact of algorithmic curation.
| S-EPMC10556069 | biostudies-literature
Project description:Human papillomavirus (HPV) infections are a major human health problem; they are the cause of recurrent benign warts and of several cancers of the anogenital tract and head and neck region. Although there are two prophylactic HPV vaccines that could, if used universally, prevent as many as two-thirds of HPV-induced cancers, as well as several cytotoxic and immunomodulatory agents for localized treatment of infections, there are currently no HPV antiviral drugs in our arsenal of therapeutic agents. This review examines the status of past and ongoing research into the development of HPV antivirals, focused primarily upon approaches targeting the replication of the viral genome. The only HPV enzyme, E1, is a DNA helicase that interfaces with the cellular DNA replication machinery to replicate the HPV genome. To date, searches for small molecule inhibitors of E1 for use as antivirals have met with limited success. The lack of other viral enzymes has meant that the search for antivirals has shifted to a large degree to the modulation of protein-protein interactions. There has been some success in identifying small molecule inhibitors targeting interactions between HPV proteins but with activity against a small subset of viral types only. As noted in this review, it is thought that targeting E1 interactions with cellular replication proteins may provide inhibitors with broader activity against multiple HPV types. Herein, we outline the steps in HPV DNA replication and discuss those that appear to provide the most advantageous targets for the development of anti-HPV therapeutics.
| S-EPMC4658057 | biostudies-other
Project description:BackgroundThe emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates. Here we present a method able to assess the general health of host cells based on morphological profiling, for untargeted phenotypic drug screening against viral infections.ResultsWe combine Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that this methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state.ConclusionsThe phenomics approach presented here, which makes use of a modified Cell Painting protocol by incorporating an anti-virus antibody stain, can be used for the unbiased morphological profiling of virus infection on host cells. The method can identify antiviral reference compounds, as well as novel antivirals, demonstrating its suitability to be implemented as a strategy for antiviral drug repurposing and drug discovery.
| S-EPMC8325993 | biostudies-literature
Project description:As one of the major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, the so-called item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. Interestingly, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely, these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs.
| S-EPMC4257537 | biostudies-literature
Project description:With the rapid growth of the Internet and overwhelming amount of information that people are confronted with, recommender systems have been developed to effectively support users' decision-making process in online systems. So far, much attention has been paid to designing new recommendation algorithms and improving existent ones. However, few works considered the different contributions from different users to the performance of a recommender system. Such studies can help us improve the recommendation efficiency by excluding irrelevant users. In this paper, we argue that in each online system there exists a group of core users who carry most of the information for recommendation. With them, the recommender systems can already generate satisfactory recommendation. Our core user extraction method enables the recommender systems to achieve 90% of the accuracy of the top-L recommendation by taking only 20% of the users into account. A detailed investigation reveals that these core users are not necessarily the large-degree users. Moreover, they tend to select high quality objects and their selections are well diversified.
| S-EPMC4139954 | biostudies-literature