Drug Design, Development and Therapy, 2018 Isnatin Miladiyah,1,2 Jumina Jumina,3 Sofia Mubarika Haryana,4 Mustofa Mustofa5 1Pharmacology Department, Faculty of Medicine, Islamic University of Indonesia, 2Doctorate Program of Medical Science and Health, Faculty of Medicine, 3Chemistry Department,
Miladiyah I +3 more
doaj
A Quantitative Structure–Activity Relationship Study of the Anabolic Activity of Ecdysteroids
ComputationPhytoecdysteroids represent a class of naturally occurring substances known for their diverse biological functions, particularly their strong ability to stimulate protein anabolism.
Durbek Usmanov +4 more
doaj +1 more source
Protective activity of aromatic amines and imines against oxidative nerve cell death [PDF]
, 2001 Oxidative stress is a widespread phenomenon in the pathology of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.
Behl, Christian +3 more
core +1 more source
Prediction of Terpenoid Toxicity Based on a Quantitative Structure–Activity Relationship Model
Foods, 2019 Terpenoids, including monoterpenoids (C10), norisoprenoids (C13), and sesquiterpenoids (C15), constitute a large group of plant-derived naturally occurring secondary metabolites with highly diverse chemical structures.
R. Perestrelo +3 more
semanticscholar +1 more source
A working model for cytoplasmic assembly of H/ACA snoRNPs
FEBS Letters, EarlyView.Dyskerin is the component of nuclear H/ACA ribonucleoproteins (RNPs) endowed with pseudouridine synthase catalytic activity. Two isoforms of human dyskerin have been characterized: the abundant Iso1, mainly nuclear, and the shorter Iso3, mainly cytoplasmic but occasionally imported into nuclei.
Alberto Angrisani, Maria Furia
wiley +1 more source
Predicting Skin Permeability by means of Computational Approaches : Reliability and Caveats in Pharmaceutical Studies [PDF]
, 2019 © 2019 American Chemical Society.The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters.
Almerico, Anna Maria +5 more
core +2 more sources
Multi-task learning with a natural metric for quantitative structure activity relationship learning
Journal of Cheminformatics, 2019 The goal of quantitative structure activity relationship (QSAR) learning is to learn a function that, given the structure of a small molecule (a potential drug), outputs the predicted activity of the compound.
Noureddin M. Sadawi +8 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu +12 more
wiley +1 more source
Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and artificial intelligence models [PDF]
, 2015 [Abstract] The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological ...
García, Rafael +4 more
core +2 more sources
Review on: quantitative structure activity relationship (QSAR) modeling
, 2018 Quantitative structure – activity relationship (QSAR) modeling pertains to the construction of predictive models of biological activities as a function of structural and molecular information of a compound library.
U. Muhammad, A. Uzairu, D. Arthur
semanticscholar +1 more source