Updates on the biofunctionalization of gold nanoparticles for the rapid and sensitive multiplatform diagnosis of SARS-CoV-2 virus and its proteins: from computational …
RE Ionescu - International Journal of Molecular Sciences, 2023 - mdpi.com
Since the outbreak of the pandemic respiratory virus SARS-CoV-2 (COVID-19), academic
communities and governments/private companies have used several detection techniques …
communities and governments/private companies have used several detection techniques …
Breaking the Barriers: Machine-Learning-Based c-RASAR Approach for Accurate Blood–Brain Barrier Permeability Prediction
The intricate nature of the blood–brain barrier (BBB) poses a significant challenge in
predicting drug permeability, which is crucial for assessing central nervous system (CNS) …
predicting drug permeability, which is crucial for assessing central nervous system (CNS) …
Prediction of the solubility of acid gas hydrogen sulfide in green solvent ionic liquids via quantitative structure–property relationship models based on the molecular …
T Liu, Z Dong, W Zhu, Y Chen, M Zhou… - ACS Sustainable …, 2023 - ACS Publications
Ionic liquids (ILs) can be used as capturing acidic gases that damage the environment. By
establishing a quantitative structure–property relationship (QSPR) model of the IL structure …
establishing a quantitative structure–property relationship (QSPR) model of the IL structure …
Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease
In the present research, we present the application of a novel approach, termed the Machine
Learning (ML)-Based q-RASAR (quantitative read-across structure-activity relationship) …
Learning (ML)-Based q-RASAR (quantitative read-across structure-activity relationship) …
Multi-target QSAR modeling for the identification of novel inhibitors against Alzheimer's disease
Alzheimer's disease (AD) is an age-related neurodegenerative disorder, which is the most
common cause of dementia in elderly individuals. It is characterized by selective neuronal …
common cause of dementia in elderly individuals. It is characterized by selective neuronal …
Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CLpro enzyme for COVID-19 therapy: a computer-aided …
Abstract Small molecules such as 9, 10-dihydrophenanthrene derivatives have remarkable
activity toward inhibition of SARS-CoV-2 3CLpro and COVID-19 proliferation, which show a …
activity toward inhibition of SARS-CoV-2 3CLpro and COVID-19 proliferation, which show a …
Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model
As the rate of discovery of new antibacterial compounds for multidrug-resistant bacteria is
declining, there is an urge for the search for molecules that could revert this tendency …
declining, there is an urge for the search for molecules that could revert this tendency …
Computational Screening of Approved Drugs for Inhibition of the Antibiotic Resistance Gene mecA in Methicillin-Resistant Staphylococcus aureus (MRSA) Strains
B Otarigho, MO Falade - BioTech, 2023 - mdpi.com
Antibiotic resistance is a critical problem that results in a high morbidity and mortality rate.
The process of discovering new chemotherapy and antibiotics is challenging, expensive …
The process of discovering new chemotherapy and antibiotics is challenging, expensive …
Dicoumarol is an effective post-exposure prophylactic for SARS-CoV-2 Omicron infection in human airway epithelium
Y Peng, S Chen, Z Wang, Z Zhou, J Sun… - … and Targeted Therapy, 2023 - nature.com
Repurposing existing drugs to inhibit SARS-CoV-2 infection in airway epithelial cells (AECs)
is a quick way to find novel treatments for COVID-19. Computational screening has found …
is a quick way to find novel treatments for COVID-19. Computational screening has found …
Innovative strategies for the quantitative modeling of blood–brain barrier (BBB) permeability: harnessing the power of machine learning-based q-RASAR approach
In the current research, we have unveiled an advanced technique termed the quantitative
read-across structure–activity relationship (q-RASAR) framework to harness the power of …
read-across structure–activity relationship (q-RASAR) framework to harness the power of …