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Ferrari, I. V.

Publications and source records attributed to Ferrari, I. V..

2 recordsLinked to original sources

Important Docking study of Structure of Plasmodium falciparum thioredoxin reductase-thioredoxin complex: the case of potent drug Telatinib, a small molecule angiogenesis inhibitor

BackgroundOver the last decades, malaria parasites have been rapidly developing resistance against antimalarial drugs, which underlines the need for novel drug targets. Thioredoxin reductase (TrxR) is crucially involved in redox homeostasis and essential for Plasmodium falciparum. In this communication, we report first time important Docking study by in Silico approach, using AutoDock Vina. After a selective analysis of over 300 drugs, processed with Pyrx (a Virtual Screening software into the active site of protein (ID PDB 4J56 Thioredoxin reductase 2 Chain A), we noticed excellent value of Binding Energy of Telatinib estimated by Pyrx software. These results are comparable to the crystallized ligand FAD (FLAVIN-ADENINE DINUCLEOTIDE) completed in the above-mentioned protein. Indeed, from the results of Autodock Vina, Telatinib an inhibitor of tyrosine kinases, has excellent a Binding affinity value, ca. -12 kcal/mol.

bioinformatics↗

Open access in silico tools to predict the ADMET profiling and PASS (Prediction of Activity Spectra for Substances of Bioactive compounds of Garlic (Allium sativum L.)

BackgroundGarlic (Allium sativum L.) is a common spice with many health benefits, mainly due to its diverse bioactive compounds, (see below) such as organic sulphides, saponins, phenolic compounds, and polysaccharides. Several studies have demonstrated its functions such as anti-inflammatory, antibacterial, and antiviral, antioxidant, cardiovascular protective and anticancer property. In this work we have investigated the main bioactive components of garlic through a bioinformatics approach. Indeed, we are in an era of bioinformatics where we can predict data in the fields of medicine. Approaches with open access in silico tools have revolutionized disease management due to early prediction of the absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles of the chemically designed and eco-friendly next-generation drugs. MethodsThis paper encompasses the fundamental functions of open access in silico prediction tools, as PASS database (Prediction of Activity Spectra for Substances) that it estimates the probable biological activity profiles for compounds. This paper also aims to help support new researchers in the field of drug design and to investigate best bioactive compounds in garlic. Resultsscreening through each of pharmacokinetic criteria resulted in identification of Garlic compounds that adhere to all the ADMET properties. ConclusionsIt was established an open-access database (PASS database, available bioinformatics tool SwissADME, PreADMET pkCSM database) servers were employed to determine the ADMET (metabolism, distribution, excretion, absorption, and toxicity) attributes of garlic molecules and to enable identification of promising molecules that follow ADMET properties. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/452815v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@1344e43org.highwire.dtl.DTLVardef@fe1674org.highwire.dtl.DTLVardef@1742577org.highwire.dtl.DTLVardef@47a966_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗