1,051 research outputs found
SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.
To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours
SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules.
SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 version, which represents a major update in terms of underlying data, backend and web interface. The bioactivity data were updated, the model retrained and similarity thresholds redefined. In the new version, the predictions are performed by searching for similar molecules, in 2D and 3D, within a larger collection of 376 342 compounds known to be experimentally active on an extended set of 3068 macromolecular targets. An efficient backend implementation allows to speed up the process that returns results for a druglike molecule on human proteins in 15-20 s. The refreshed web interface enhances user experience with new features for easy input and improved analysis. Interoperability capacity enables straightforward submission of any input or output molecule to other on-line computer-aided drug design tools, developed by the SIB Swiss Institute of Bioinformatics. High levels of predictive performance were maintained despite more extended biological and chemical spaces to be explored, e.g. achieving at least one correct human target in the top 15 predictions for >70% of external compounds. The new SwissTargetPrediction is available free of charge (www.swisstargetprediction.ch)
Integrating radiomics into holomics for personalised oncology: from algorithms to bedside.
Radiomics, artificial intelligence, and deep learning figure amongst recent buzzwords in current medical imaging research and technological development. Analysis of medical big data in assessment and follow-up of personalised treatments has also become a major research topic in the area of precision medicine. In this review, current research trends in radiomics are analysed, from handcrafted radiomics feature extraction and statistical analysis to deep learning. Radiomics algorithms now include genomics and immunomics data to improve patient stratification and prediction of treatment response. Several applications have already shown conclusive results demonstrating the potential of including other "omics" data to existing imaging features. We also discuss further challenges of data harmonisation and management infrastructure to shed a light on the much-needed integration of radiomics and all other "omics" into clinical workflows. In particular, we point to the emerging paradigm shift in the implementation of big data infrastructures to facilitate databanks growth, data extraction and the development of expert software tools. Secured access, sharing, and integration of all health data, called "holomics", will accelerate the revolution of personalised medicine and oncology as well as expand the role of imaging specialists
Axillary Sentinel Lymph Node Biopsy for Breast Cancer and Melanoma Patients after Previous Axillary Surgery: A Systematic Review
Objective: Sentinel lymph node biopsy (SLNB) is a validated staging technique for breast carcinoma. Some women are exposed to have a second SLNB due to breast cancer recurrence or a second neoplasia (breast or other). Due to modi- fied anatomy, it has been claimed that previous axillary surgery represents a contra-indication to SLNB. Our objective was to analyse the literature to assess if a second SLNB is to be recommended or not. Methods: For the present study, we performed a review of all published data during the last 10 years on patients with previous axilla surgery and second SLNB. Results: Our analysis shows that second SLNB is feasible in 70%. Extra-axillary SNs rate (31%) was higher after radical lymph node dissection (ALND) (60% - 84%) than after SLNB alone (14% - 65%). Follow-up and com- plementary ALND following negative and positive second SLNB shows that it is a reliable procedure. Conclusion: The review of literature confirms that SLNB is feasible after previous axillary dissection. Triple technique for SN mapping is the best examination to highlight modified lymphatic anatomy and shows definitively where SLNB must be per- formed. Surgery may be more demanding as patients may have more frequently extra-axillary SN only, like internal mammary nodes. ALND can be avoided when second SLNB harvests negative SNs. These conclusions should however be taken with caution because of the heterogeneity of publications regarding SLNB and surgical technique
Inhibition of the shade avoidance response by formation of non-DNA binding bHLH heterodimers.
In shade-intolerant plants such as Arabidopsis, a reduction in the red/far-red (R/FR) ratio, indicative of competition from other plants, triggers a suite of responses known as the shade avoidance syndrome (SAS). The phytochrome photoreceptors measure the R/FR ratio and control the SAS. The phytochrome-interacting factors 4 and 5 (PIF4 and PIF5) are stabilized in the shade and are required for a full SAS, whereas the related bHLH factor HFR1 (long hypocotyl in FR light) is transcriptionally induced by shade and inhibits this response. Here we show that HFR1 interacts with PIF4 and PIF5 and limits their capacity to induce the expression of shade marker genes and to promote elongation growth. HFR1 directly inhibits these PIFs by forming non-DNA-binding heterodimers with PIF4 and PIF5. Our data indicate that PIF4 and PIF5 promote SAS by directly binding to G-boxes present in the promoter of shade marker genes, but their action is limited later in the shade when HFR1 accumulates and forms non-DNA-binding heterodimers. This negative feedback loop is important to limit the response of plants to shade
Systematic review of the use of granulocyte-macrophage colony-stimulating factor in patients with advanced melanoma.
Several immunomodulatory checkpoint inhibitors have been approved for the treatment of patients with advanced melanoma, including ipilimumab, nivolumab and pembrolizumab. Talimogene laherparepvec is the first oncolytic virus to gain regulatory approval in the USA; it is also approved in Europe. Talimogene laherparepvec expresses granulocyte-macrophage colony-stimulating factor (GM-CSF), and with other GM-CSF-expressing oncolytic viruses in development, understanding the clinical relevance of this cytokine in treating advanced melanoma is important. Results of trials of GM-CSF in melanoma have been mixed, and while GM-CSF has the potential to promote anti-tumor responses, some preclinical data suggest that GM-CSF may sometimes promote tumor growth. GM-CSF has not been approved as a melanoma treatment. We undertook a systematic literature review of studies of GM-CSF in patients with advanced melanoma (stage IIIB-IV). Of the 503 articles identified, 26 studies met the eligibility criteria. Most studies investigated the use of GM-CSF in combination with another treatment, such as peptide vaccines or chemotherapy, or as an adjuvant to surgery. Some clinical benefit was reported in patients who received GM-CSF as an adjuvant to surgery, or in combination with other treatments. In general, outcomes for patients receiving peptide vaccines were not improved with the addition of GM-CSF. GM-CSF may be a valuable therapeutic adjuvant; however, further studies are needed, particularly head-to-head comparisons, to confirm the optimal dosing regimen and clinical effectiveness in patients with advanced melanoma
Evolving impact of long-term survival results on metastatic melanoma treatment.
Melanoma treatment has been revolutionized over the past decade. Long-term results with immuno-oncology (I-O) agents and targeted therapies are providing evidence of durable survival for a substantial number of patients. These results have prompted consideration of how best to define long-term benefit and cure. Now more than ever, oncologists should be aware of the long-term outcomes demonstrated with these newer agents and their relevance to treatment decision-making. As the first tumor type for which I-O agents were approved, melanoma has served as a model for other diseases. Accordingly, discussions regarding the value and impact of long-term survival data in patients with melanoma may be relevant in the future to other tumor types. Current findings indicate that, depending on the treatment, over 50% of patients with melanoma may gain durable survival benefit. The best survival outcomes are generally observed in patients with favorable prognostic factors, particularly normal baseline lactate dehydrogenase and/or a low volume of disease. Survival curves from melanoma clinical studies show a plateau at 3 to 4 years, suggesting that patients who are alive at the 3-year landmark (especially in cases in which treatment had been stopped) will likely experience prolonged cancer remission. Quality-of-life and mixture-cure modeling data, as well as metrics such as treatment-free survival, are helping to define the value of this long-term survival. In this review, we describe the current treatment landscape for melanoma and discuss the long-term survival data with immunotherapies and targeted therapies, discussing how to best evaluate the value of long-term survival. We propose that some patients might be considered functionally cured if they have responded to treatment and remained treatment-free for at least 2 years without disease progression. Finally, we consider that, while there have been major advances in the treatment of melanoma in the past decade, there remains a need to improve outcomes for the patients with melanoma who do not experience durable survival
SwissTargetPrediction: a web server for target prediction of bioactive small molecules.
Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-molecular targets to modulate their activity, which in turn results in the observed phenotypic effects. For this reason, mapping the targets of bioactive small molecules is a key step toward unraveling the molecular mechanisms underlying their bioactivity and predicting potential side effects or cross-reactivity. Recently, large datasets of protein-small molecule interactions have become available, providing a unique source of information for the development of knowledge-based approaches to computationally identify new targets for uncharacterized molecules or secondary targets for known molecules. Here, we introduce SwissTargetPrediction, a web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. Predictions can be carried out in five different organisms, and mapping predictions by homology within and between different species is enabled for close paralogs and orthologs. SwissTargetPrediction is accessible free of charge and without login requirement at http://www.swisstargetprediction.ch
Lower bounds for the first eigenvalue of the magnetic Laplacian
We consider a Riemannian cylinder endowed with a closed potential 1-form A
and study the magnetic Laplacian with magnetic Neumann boundary conditions
associated with those data. We establish a sharp lower bound for the first
eigenvalue and show that the equality characterizes the situation where the
metric is a product. We then look at the case of a planar domain bounded by two
closed curves and obtain an explicit lower bound in terms of the geometry of
the domain. We finally discuss sharpness of this last estimate.Comment: Replaces in part arXiv:1611.0193
Response to MEK inhibition with trametinib and tyrosine kinase inhibition with imatinib in multifocal histiocytic sarcoma.
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