A5019195809- Computational Drug Discovery Methods
- Metabolomics and Mass Spectrometry Studies
- Microbial Metabolic Engineering and Bioproduction
- Receptor Mechanisms and Signaling
- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
- Analytical Chemistry and Chromatography
- Free Radicals and Antioxidants
- Biochemical effects in animals
- Pharmacogenetics and Drug Metabolism
- Cholinesterase and Neurodegenerative Diseases
- Monoclonal and Polyclonal Antibodies Research
- Machine Learning in Materials Science
- Advanced Glycation End Products research
- Advanced Graph Neural Networks
- Neuropeptides and Animal Physiology
- Natural Antidiabetic Agents Studies
- Pancreatic function and diabetes
- Ginger and Zingiberaceae research
- Statistical Methods in Clinical Trials
- Aldose Reductase and Taurine
- Academic Writing and Publishing
- Pharmacological Receptor Mechanisms and Effects
- Biomedical Text Mining and Ontologies
- Biosimilars and Bioanalytical Methods
University of Milan
2016-2025
Abstract The purpose of the article is to offer an overview latest release VEGA suite programs. This software has been constantly developed and freely released during last 20 years now reached a significant diffusion technology level as confirmed by about 22 500 registered users. While being primarily for drug design studies, package includes cheminformatics modeling features, which can be fruitfully utilized in various contexts computational chemistry. To glimpse remarkable potentials...
Predicting the structures of metabolites formed in humans can provide advantageous insights for development drugs and other compounds. Here we present GLORYx, which integrates machine learning-based site metabolism (SoM) prediction with reaction rule sets to predict rank that could potentially be by phase 1 and/or 2 metabolism. GLORYx extends approach from our previously developed tool GLORY, predicted metabolite cytochrome P450-mediated only. A robust ranking is attained using SoM...
In this work we present the third generation of FAst MEtabolizer (FAME 3), a collection extra trees classifiers for prediction sites metabolism (SoMs) in small molecules such as drugs, druglike compounds, natural products, agrochemicals, and cosmetics. FAME 3 was derived from MetaQSAR database ( Pedretti et al. J. Med. Chem. 2018 , 61 1019 ), recently published data resource on xenobiotic that contains more than 2100 substrates annotated with 6300 experimentally confirmed SoMs related to...
Docking simulations are very popular approaches able to assess the capacity of a given ligand interact with target. usually focused on single best complex even though many studies showed that ligands retain significant mobility within binding pocket by assuming different modes all which may contribute monitored affinity. The present study describes an innovative concept, space, allows exploration simultaneously considering several poses as generated docking simulations. multiple and relative...
Hempseed (Cannabis sativa) protein is an important source of bioactive peptides. H3 (IGFLIIWV), a transepithelial transported intestinal peptide obtained from the hydrolysis hempseed with pepsin, carries out antioxidant and anti-inflammatory activities in HepG2 cells. In this study, main aim was to assess its hypocholesterolemic effects at cellular level mechanisms behind health-promoting activity. The results showed that inhibited 3-hydroxy-3-methylglutaryl co-enzyme A reductase (HMGCoAR)...
Accurate determination of the metabolic fate xenobiotics is essential for ensuring their safety and efficacy. While in vivo vitro methods remain gold standard assessing properties, they are both costly time-consuming. In silico metabolism prediction models offer complementary solutions to tackle challenging task improving a compound's stability without compromising its desired biological activity. This paper introduces aweSOM, novel graph neural network (GNN)-based site-of-metabolism (SOM)...
Computational models predicting the sites of metabolism (SOM) small organic molecules have become invaluable tools for studying and optimizing metabolic properties xenobiotics. However, performance SOM predictors has shown signs plateauing in recent years, primarily due to limited availability training data. While vast amounts biotransformation data form substrate-metabolite pairs exist, their potential prediction remains largely untapped absence annotations. Annotating SOMs requires expert...
Accurate determination of the metabolic fate xenobiotics is essential for ensuring their safety and efficacy. While in vivo vitro methods remain gold standard assessing properties, they are both costly time-consuming. In silico metabolism prediction models offer complementary solutions to tackle challenging task improving a compound's stability without compromising its desired biological activity. This paper introduces aweSOM, novel graph neural network (GNN)-based site-of-metabolism (SOM)...
Computational models predicting the sites of metabolism (SOM) small or- ganic molecules have become invaluable tools for studying and optimizing metabolic properties xenobiotics. However, performance SOM predic- tors has shown signs plateauing in recent years, primarily due to limited availability training data. While vast amounts biotransformation data form substrate-metabolite pairs exist, their potential prediction remains largely untapped absence annotations. Annotating SOMs requires...
The ability to pinpoint and predict sites of metabolism (SoMs) is essential for designing optimizing effective safe bioactive small molecules, such as drugs. However, the number molecules with annotated SoMs in public domain pharmaceutical industry limited, hindering advancement data-driven methods like machine learning prediction. Here, we provide a comprehensive characterization SoM data obtained from readouts human hepatocyte assay conducted at AstraZeneca Gothenburg. We explore new...
Structure-based drug design can potentially accelerate the development of new therapeutics. In this study, a cocrystal structure acetylcholine binding protein (AChBP) from Capitella teleta (Ct) in complex with cyclopropane-containing selective α4β2-nicotinic receptor (nAChR) partial agonist (compound 5) was acquired. The structural determinants required for ligand obtained AChBP X-ray were used to refine previous model human α4β2-nAChR, thus possibly providing better understanding receptor....
Aim: The inhibition of protein carbonylation can play therapeutic roles in several oxidative-based diseases and direct carbonyl quenching appears the most effective strategies. l-carnosine derivatives are selective quenchers toward 4-hydroxy-2-nonenal even though their activity was never investigated a fully comparable way. Results: reported results revealed that anserine, homocarnosine carnosinamide retain remarkable combined with satisfactory selectivity. In silico analyses confirmed key...
The study describes the MetaQSAR tool, a new database engine specifically tailored to collect and analyze metabolic data. This is plug-in embedded in VEGA suite of programs (freely downloadable at www.vegazz.net ) takes advantage from all cheminformatics features implemented software with additional tools aimed perform statistical analyses, similarity searches, physicochemical profiling stored molecules. also implements novel metabolism classification, which groups reactions 101 classes can...
DNA methylation plays key roles in mammalian cells and is modulated by a set of proteins which recognize symmetrically methylated nucleotides. Among them, the protein MECP2 shows multifunctional repressing and/or activating genes binding to both unmethylated regions genome. The interest for this markedly increased from observation that its mutations are primary cause Rett syndrome, neurodevelopmental disorder causes mental retardation young females. Thus, present study aimed investigate...
The study proposes a novel consensus strategy based on linear combinations of different docking scores to be used in the evaluation virtual screening campaigns. models are generated by applying recently proposed Enrichment Factor Optimization (EFO) method, which develops equations exhaustively combining available and optimizing resulting enrichment factors. performances such were evaluated simulating entire Directory Useful Decoys (DUD datasets). In detail, poses initially PLANTS program...
The ability to determine and predict metabolically labile atom positions in a molecule (also called "sites of metabolism" or "SoMs") is high interest the design optimization bioactive compounds, such as drugs, agrochemicals, cosmetics. In recent years, several silico models for SoM prediction have become available, many which include machine-learning component. bottleneck advancing these approaches coverage distinct environments rare complex biotransformation events with high-quality...
The Advanced Glycation and Lipoxidation End products (AGEs ALEs) are a heterogeneous class of compounds derived from the non-enzymatic glycation or protein adduction by lipoxidation break-down products. receptor for AGEs (RAGE) is involved in progression chronic diseases based on persistent inflammatory state oxidative stress. RAGE pattern recognition (PRR) inhibition interaction with its ligands ligand accumulation have potential therapeutic effect. N-terminal domain RAGE, V domain, major...