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rino.ragno@uniroma1.it
Rino Ragno
Professore Ordinario
Struttura:
DIPARTIMENTO DI CHIMICA E TECNOLOGIE DEL FARMACO
E-mail:
rino.ragno@uniroma1.it
Pagina istituzionale corsi di laurea
Curriculum Sapienza
Publications
Title
Published on
Year
Essential Oils as Antimicrobials against Acinetobacter baumannii: Experimental and Literature Data to Definite Predictive Quantitative Composition–Activity Relationship Models Using Machine Learning Algorithms
JOURNAL OF CHEMICAL INFORMATION AND MODELING
2025
Nuovi approcci metodologici applicati a Cencelle (Tarquinia, VT) - New methodological approaches applied to Cencelle (Tarquinia, VT)
SPOLIA
2024
(Heteroarylmethyl)benzoic Acids as a New Class of Bacterial Cystathionine γ-Lyase Inhibitors: Synthesis, Biological Evaluation, and Molecular Modeling
ACS INFECTIOUS DISEASES
2024
Pyrimidine thioethers: A novel class of antidepressant agents, endowed with anxiolytic, performance enhancing and nootropic activity
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
2023
Bcl-2 family inhibitors sensitize human cancer models to therapy
CELL DEATH & DISEASE
2023
Effect of different soil treatments on production and chemical composition of essential oils extracted from Foeniculum vulgare Mill., Origanum vulgare L. and Thymus vulgaris L
PLANTS
2023
Molecular Docking Assessment of Cathinones as 5-HT2AR Ligands: Developing of Predictive Structure-Based Bioactive Conformations and Three-Dimensional Structure-Activity Relationships Models for Future Recognition of Abuse Drugs
MOLECULES
2023
Essential Oils from Mediterranean Plants Inhibit In Vitro Monocyte Adhesion to Endothelial Cells from Umbilical Cords of Females with Gestational Diabetes Mellitus
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
2023
An Undefined Interaction between Polyamines and Heat Shock Proteins Leads to Cellular Protection in Plasmodium falciparum and Proliferating Cells in Various Organisms
MOLECULES
2023
Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening
MACHINE LEARNING
2023
In Vitro Antioxidant and In Vivo Antigenotoxic Features of a Series of 61 Essential Oils and Quantitative Composition–Activity Relationships Modeled through Machine Learning Algorithms
ANTIOXIDANTS
2023
In vivo antiphytoviral and aphid repellency activity of essential oils and hydrosols from Mentha suaveolens and Foeniculum vulgare to control zucchini yellow mosaic virus and its vector Aphis gossypii
PLANTS
2023
Chemical Composition and Anti-Candida Activity of Mentha suaveolens Ehrh. Essential Oils Obtained by Different Distillation Processes
MOLECULES
2023
Sviluppo di nanosistemi sostenibili per l’incapsulamento di oli essenziali e dei loro principi attivi per la conservazione dei beni culturali di origine lignea
NATURAL 1
2023
Inhibition of PKCθ Improves Dystrophic Heart Phenotype and Function in a Novel Model of DMD Cardiomyopathy
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
2022
Foeniculum vulgare miller, a new chemotype from Montenegro
PLANTS
2022
Transcriptomic and genomic studies classify NKL54 as a histone deacetylase inhibitor with indirect influence on MEF2-dependent transcription
NUCLEIC ACIDS RESEARCH
2022
Human estrogen receptor α antagonists, part 2: Synthesis driven by rational design, in vitro antiproliferative, and in vivo anticancer evaluation of innovative coumarin-related antiestrogens as breast cancer suppressants
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
2022
Targeting the anti-apoptotic Bcl-2 family proteins: Machine learning virtual screening and biological evaluation of new small molecules
THERANOSTICS
2022
Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients
MICROORGANISMS
2022
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ERC
LS1_13
LS2_11
PE4_13
PE5_18
KET
Life-science technologies & biotechnologies
Interessi di ricerca
Keywords
drug design
drug design and discovery
computational chemistry
essential oil active components (EO-ACs)
essential oil
Molecular docking
drug repurposing
quantitative composition-activity relationships
Progetti di Ricerca
Verso la progettazione di oli essenziali bioattivi. Impiego di tecniche di "machine learning" con l'utilizzo massivo di dati di letteratura e sperimentali.
Gli oli essenziali quali potenziali sorgente di informazioni per combattere patologie per l'uomo, gli animali e le piante. Caratterizzazione chimica e biologica di nuovi oli essenziali e commerciali per lo sviluppo di un nuovo portale scientifico a...
Il ritorno all'uso di rimedi che non tramontano mai: gli oli essenziali. Acquisizione di dati sperimentali chimici, farmacologici, (micro)biologici e biochimici da elaborare con algoritmi "machine learning" per individuare nuovi composti bioattivi e...
Glli oli essenziali come potenziali farmaci o "drug enhancers". Estrazione e caratterizzazione chimica, biochimica, antibatterica e antibiofilm e applicazione di algoritmi di intelligenza artificiale al fine di individuare i componenti maggiormente ...
Laboratori di ricerca
3D-QSAR PORTAL Prof. RAGNO RINO
© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma