1,721,004 research outputs found
Is it possible docking and scoring new ligands with few experimental data? Preliminary results on estrogen receptor as a case study
No full textEstrogens are steroid hormones playing critical roles in several physiological processes, which bind the estrogen receptors ERα and ERÎ2. Aim of this work is to analyze, by different docking experiments, the behavior of a set of compounds, mimicking estrogens activity, in order to understand the relationship between ERα and such new ligands. Main goal is to verify, using a widely tested scoring software procedure applied on a set of 10 compounds, the possibility to produce new lead candidate molecules in lack of, or with few experimental data. Our preliminary results reveal the significance of HINT software as a scoring function in docking methodology and specifically, as a mean for assessing the consistency of docking solutions. © 2004 Elsevier SAS. All rights reserved
New in Silico Trends in Food Toxicology
No full textEver growing numbers of chemicals in food and drinking water make it impossible to address safety by classical approaches in toxicology. In silico chemical methods could be a first-line for hazard characterization, requiring food toxicology to expand the use of approaches currently well applied in medicinal chemistry
Molecular modelling methods in food safety: Bisphenols as case study
No full textBisphenol A (BPA), a synthetic compound widely used as a building block for polycarbonate plastics, has been declared in the European Union (EU) as a substance of very high concern (SVHC). A series of BPA alternatives and derivatives (bisphenols/BPs) with similar physical-chemical properties have been produced and used by companies for substituting it. To evaluate the estrogenic and androgenic binding activity of 26 BPs, a non-statistical in silico approach has been applied. The results of molecular docking analyses applied on six different nuclear receptors (NRs) have revealed that: i) some BPA metabolites could lower the harmful effects of BPA exposure; ii) BPS is a lower interactor for all NRs, but it does not appear safer at all for androgen receptor (AR), for which its binding activity is found similar to a pharmacological anti-androgen; iii) only a BP has been found as a safer compound for all NRs considered. Moreover, molecular dynamic simulation of three BPs on ERα have revealed that the presence of negative hydrophobic interactions could induce a decrease in receptor activity. Overall, the present results demonstrate that in silico methods could be a valid approach to screen estrogenic and androgenic activity of food contact materials (FCMs)
Novel allosteric effectors of the tryptophan synthase alpha2beta2 complex identified by computer-assisted molecular modeling
No full textSweet, umami and bitter taste receptors: State of the art of in silico molecular modeling approaches
No full textBackground: The human taste experience is the result of five basic taste qualities, namely sweet, salty, bitter, sour and umami. Sweet, bitter, and umami are mediated by G protein-coupled receptors (GPCRs), whereas sour and salt are modulated by specialized membrane channels. Taste perception starts with the interaction between a taste-active molecule (substance) and a specialized receptor located on the taste buds at the level of the cell membrane. Once the interaction has occurred, taste receptor cells are able to transduce the information content of the chemical stimulus into nerve signals directly to the brain. Therefore, the receptor-mediated recognition of taste molecules is the first episode leading to taste perception. Scope and approach: In this review, we provide a complete overview of in silico molecular modeling techniques applied to the study of umami, sweet, and bitter taste receptors. Structure-based computational tools, usually applied to investigate the binding mode of bioactive molecules into their targets and to rationally design new drug molecules, are proven equally useful in the field of chemical senses to shed light on the molecular acknowledgment of tastants. Key findings and conclusions: The recent computational advancements in the taste research field, and particularly the computation-driven investigations of the tastant-receptor binding, provided a better understanding of the molecular mechanisms underlying food tastants’ sensing and could have an impressive contribution to the identification of new taste modulators in the future
FIUMI: un dbase personale per la biotipizzazione dei fiumi del territorio italiano
No full textUniversità degli Studi di Parm
A Computational Workflow to Predict Biological Target Mutations: The Spike Glycoprotein Case Study
No full textThe biological target identification process, a pivotal phase in the drug discovery workflow, becomes particularly challenging when mutations affect proteins' mechanisms of action. COVID-19 Spike glycoprotein mutations are known to modify the affinity toward the human angiotensin-converting enzyme ACE2 and several antibodies, compromising their neutralizing effect. Predicting new possible mutations would be an efficient way to develop specific and efficacious drugs, vaccines, and antibodies. In this work, we developed and applied a computational procedure, combining constrained logic programming and careful structural analysis based on the Structural Activity Relationship (SAR) approach, to predict and determine the structure and behavior of new future mutants. "Mutations rules" that would track statistical and functional types of substitutions for each residue or combination of residues were extracted from the GISAID database and used to define constraints for our software, having control of the process step by step. A careful molecular dynamics analysis of the predicted mutated structures was carried out after an energy evaluation of the intermolecular and intramolecular interactions using the HINT (Hydrophatic INTeraction) force field. Our approach successfully predicted, among others, known Spike mutants
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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