Mostrant de 11 a 20 de 29 notícies disponibles
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Two anti-inflammatory drugs found that inhibit the Main protease (M-pro) from SARS-CoV-2
A study by the URV's Cheminformatics and Nutrition research group has shown that an anti-inflammatory drug for humans and another for animals inhibit a key enzyme in the replication and transcription of the COVID-19 virus. The results of the work have been validated by the initiative COVIDMoonshot which has carried out in vitro studies and assessed their bioactivity. The results have been published in the "International Journal of Molecular Sciences"
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Understanding the variability of the S1' pocket to improve matrix metalloproteinase inhibitor selectivity profiles.
Matrix metalloproteinases (MMPs) are a family of proteins involved in a range of pathologies. Given that MMP broad-spectrum inhibition is associated with severe adverse effects, selectivity has become a priority in the design of MMP inhibitors, and is often achieved by targeting the variable S1' pocket. However, the specific characteristics of the S1' pocket that determine inhibitor selectivity are often not described and, in many cases, challenging to identify. In this review, we investigate the variability of the S1' pocket across the MMP family, and propose explanations for the selectivity of previously described inhibitors. These analyses provide valuable insights into how to design novel inhibitors selective for a given MMP.
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Mining large databases to find new leads with low similarity to known actives: application to find new DPP-IV inhibitors.
Aim: Fragment-based drug design or bioisosteric replacement is used to find new actives with low (or no) similarity to existing ones but requires the synthesis of nonexisting compounds to prove their predicted bioactivity. Protein-ligand docking or pharmacophore screening are alternatives but they can become computationally expensive when applied to very large databases such as ZINC. Therefore, fast strategies are necessary to find new leads in such databases. Materials & methods: We designed a computational strategy to find lead molecules with very low (or no) similarity to existing actives and applied it to DPP-IV. Results: The bioactivity assays confirm that this strategy finds new leads for DPP-IV inhibitors. Conclusion: This computational strategy reduces the time of finding new lead molecules.
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A new review about virtual screening published by the Cheminformatics and Nutrition Research Group
The Light and Dark Sides of Virtual Screening: What Is There to Know? Gimeno A, Ojeda-Montes MJ, Tomás-Hernández S, Cereto-Massagué A, Beltrán-Debón R, Mulero M, Pujadas G, Garcia-Vallvé S. Int J Mol Sci. 2019 Mar 19;20(6). pii: E1375. doi: 10.3390/ijms20061375
Abstract
Virtual screening consists of using computational tools to predict potentially bioactive compounds from files containing large libraries of small molecules. Virtual screening is becoming increasingly popular in the field of drug discovery as in silico techniques are continuously being developed, improved, and made available. As most of these techniques are easy to use, both private and public organizations apply virtual screening methodologies to save resources in the laboratory. However, it is often the case that the techniques implemented in virtual screening workflows are restricted to those that the research team knows. Moreover, although the software is often easy to use, each methodology has a series of drawbacks that should be avoided so that false results or artifacts are not produced. Here, we review the most common methodologies used in virtual screening workflows in order to both introduce the inexperienced researcher to new methodologies and advise the experienced researcher on how to prevent common mistakes and the improper usage of virtual screening methodologies.
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Combined ligand- and receptor-based virtual screening methodology to identify structurally diverse PTP1B inhibitors.
Another of our articles has just been published:
Gimeno A, Ardid-Ruiz A, Ojeda-Montes MJ, Tomás-Hernández S, Cereto-Massagué A, Beltrán-Debón R, Mulero M, Valls C, Aragonès G, Suárez M, Pujadas G, Garcia-Vallvé S. Combined ligand- and receptor-based virtual screening methodology to identify structurally diverse PTP1B inhibitors. ChemMedChem. 2018 Jul 19. doi: 10.1002/cmdc.201800267.
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Activity and selectivity cliffs for DPP-IV inhibitors: Lessons we can learn from SAR studies and their application to virtual screening.
We have just published at Medicinal Research Reviews an excellent revision about DPP-IV inhibitors.
Activity and selectivity cliffs for DPP-IV inhibitors: Lessons we can learn from SAR studies and their application to virtual screening. Ojeda-Montes MJ, Gimeno A, Tomas-Hernández S, Cereto-Massagué A, Beltrán-Debón R, Valls C, Mulero M, Pujadas G, Garcia-Vallvé S. Med Res Rev. 2018 Apr 16. doi: 10.1002/med.21499
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A new article published at Molecular Nutrition and Food Research
Tomas-Hernández S, Blanco J, Rojas C, Roca-Martínez J, Ojeda-Montes MJ, Beltrán-Debón R, Garcia-Vallve S, Pujadas G, Arola L, Mulero M. Resveratrol Potently Counteracts Quercetin Starvation-Induced Autophagy and Sensitizes HepG2 Cancer Cells to Apoptosis. Mol Nutr Food Res. 2018 Jan 16. doi: 10.1002/mnfr.201700610.
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Our book chapter about PPARgamma polypharmacology has been just published
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A new article of the Cheminformatics & Nutrition Group published at Future Medicinal Chemistry
Our article "Ephedrine as a lead compound for the development of new DPP-IV inhibitors" has just been accepted at the "Future Medicinal Chemistry" journal. In this article we describe the activity of several compounds from Ephedra as DPP-IV inhibitors.
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Maria José Ojeda defended her PhD Thesis
