Search results for "DISCOVERY"
showing 10 items of 4119 documents
A Simple Method to Predict Blood-Brain Barrier Permeability of Drug- Like Compounds Using Classification Trees
2017
Background: To know the ability of a compound to penetrate the blood-brain barrier (BBB) is a challenging task; despite the numerous efforts realized to predict/measure BBB passage, they still have several drawbacks. Methods: The prediction of the permeability through the BBB is carried out using classification trees. A large data set of 497 compounds (recently published) is selected to develop the tree model. Results: The best model shows an accuracy higher than 87.6% for training set; the model was also validated using 10-fold cross-validation procedure and through a test set achieving accuracy values of 86.1% and 87.9%, correspondingly. We give a brief explanation, in structural terms, o…
Recent advances on CDK inhibitors: An insight by means of in silico methods
2017
The cyclin dependent kinases (CDKs) are a small family of serine/threonine protein kinases that can act as a potential therapeutic target in several proliferative diseases, including cancer. This short review is a survey on the more recent research progresses in the field achieved by using in silico methods. All the "armamentarium" available to the medicinal chemists (docking protocols and molecular dynamics, fragment-based, de novo design, virtual screening, and QSAR) has been employed to the discovery of new, potent, and selective inhibitors of cyclin dependent kinases. The results cited herein can be useful to understand the nature of the inhibitor-target interactions, and furnish an ins…
Molecular topology: A new strategy for antimicrobial resistance control
2017
The control of antimicrobial resistance (AMR) seems to have come to an impasse. The use and abuse of antibacterial drugs has had major consequences on the genetic mutability of both pathogenic and nonpathogenic microorganisms, leading to the development of new highly resistant strains. Because of the complexity of this situation, an in silico strategy based on QSAR molecular topology was devised to identify synthetic molecules as antimicrobial agents not susceptible to one or several mechanisms of resistance such as: biofilms formation (BF), ionophore (IA) activity, epimerase (EI) activity or SOS system (RecA inhibition). After selecting a group of 19 compounds, five of them showed signific…
Transcription factor NRF2 as a therapeutic target for chronic diseases: a systems medicine approach
2018
Systems medicine has a mechanism-based rather than a symptom- or organ-based approach to disease and identifies therapeutic targets in a nonhypothesis-driven manner. In this work, we apply this to transcription factor nuclear factor (erythroid-derived 2)-like 2 (NRF2) by cross-validating its position in a protein-protein interaction network (the NRF2 interactome) functionally linked to cytoprotection in low-grade stress, chronic inflammation, metabolic alterations, and reactive oxygen species formation. Multiscale network analysis of these molecular profiles suggests alterations of NRF2 expression and activity as a common mechanism in a subnetwork of diseases (the NRF2 diseasome). This netw…
Biopiracy of natural products and good bioprospecting practice
2016
Made available in DSpace on 2018-11-26T16:27:45Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-02-15 Deutsche Forschungsgemeinschaft Background: Biopiracy mainly focuses on the use of biological resources and/or knowledge of indigenous tribes or communities without allowing them to share the revenues generated out of economic exploitation or other non-monetary incentives associated with the resource/knowledge. Methods: Based on collaborations of scientists from five continents, we have created a communication platform to discuss not only scientific topics, but also more general issues with social relevance. This platform was termed 'PhytCancer -Phytotherapy to Fight Cancer' (www.phy…
An RNA toolbox for cancer immunotherapy.
2018
Cancer immunotherapy has revolutionized oncology practice. However, current protein and cell therapy tools used in cancer immunotherapy are far from perfect, and there is room for improvement regarding their efficacy and safety. RNA-based structures have diverse functions, ranging from gene expression and gene regulation to pro-inflammatory effects and the ability to specifically bind different molecules. These functions make them versatile tools that may advance cancer vaccines and immunomodulation, surpassing existing approaches. These technologies should not be considered as competitors of current immunotherapies but as partners in synergistic combinations and as a clear opportunity to r…
Antimicrobial and Antibiofilm Activity of a Recombinant Fragment of β-Thymosin of Sea Urchin Paracentrotus lividus
2018
With the aim to obtain new antimicrobials against important pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa, we focused on antimicrobial peptides (AMPs) from Echinoderms. An example of such peptides is Paracentrin 1 (SP1), a chemically synthesised peptide fragment of a sea urchin thymosin. In the present paper, we report on the biological activity of a Paracentrin 1 derivative obtained by recombination. The recombinant paracentrin RP1, in comparison to the synthetic SP1, is 22 amino acids longer and it was considerably more active against the planktonic forms of S. aureus ATCC 25923 and P. aeruginosa ATCC 15442 at concentrations of 50 µ
Discovering discriminative graph patterns from gene expression data
2016
We consider the problem of mining gene expression data in order to single out interesting features characterizing healthy/unhealthy samples of an input dataset. We present an approach based on a network model of the input gene expression data, where there is a labelled graph for each sample. To the best of our knowledge, this is the first attempt to build a different graph for each sample and, then, to have a database of graphs for representing a sample set. Our main goal is that of singling out interesting differences between healthy and unhealthy samples, through the extraction of "discriminative patterns" among graphs belonging to the two different sample sets. Differently from the other…
Antibodies Responses to SARS-CoV-2 in a Large Cohort of Vaccinated Subjects and Seropositive Patients
2021
COVID-19 is a current global threat, and the characterization of antibody response is vitally important to update vaccine development and strategies. In this study we assessed SARS-CoV-2 antibody concentrations in SARS-CoV-2 positive patients (N = 272) and subjects vaccinated with the BNT162b2 m-RNA COVID-19 vaccine (N = 1256). For each participant, socio-demographic data, COVID-19 vaccination records, serological analyses, and SARS-CoV-2 infection status were collected. IgG antibodies against S1/S2 antigens of SARS-CoV-2 were detected. Almost all vaccinated subjects (99.8%) showed a seropositivity to anti-SARS-COV-2 IgG and more than 80% of vaccinated subjects had IgG concentrations >
Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.
2021
Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2′-o-ribose methyltransferase). Supported by…