[HTML][HTML] Exploring new horizons: Empowering computer-assisted drug design with few-shot learning

SS Mendonça, AR de Sousa Vitória, TW de Lima… - Artificial Intelligence in …, 2023 - Elsevier
Computational approaches have revolutionized the field of drug discovery, collectively
known as Computer-Assisted Drug Design (CADD). Advancements in computing power …

Machine-learning-based similarity meets traditional QSAR:“q-RASAR” for the enhancement of the external predictivity and detection of prediction confidence outliers …

A Banerjee, K Roy - Chemometrics and Intelligent Laboratory Systems, 2023 - Elsevier
Recently, the concept of quantitative Read-Across Structure-Activity Relationship (q-RASAR)
has been introduced by using various Machine Learning (ML)-derived similarity functions in …

Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease

V Kumar, A Banerjee, K Roy - Chemometrics and Intelligent Laboratory …, 2024 - Elsevier
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) …

[图书][B] Computational modeling of drugs against Alzheimer's disease

K Roy - 2023 - books.google.com
This second edition volume expands on the previous edition with updated descriptions on
different computational methods encompassing ligand-based, structure-based, and …

Identification of Novel Quinolone and Quinazoline Alkaloids as Phosphodiesterase 10A Inhibitors for Parkinson's Disease through a Computational Approach

I Ahmad, H Khalid, A Perveen, M Shehroz, U Nishan… - ACS …, 2024 - ACS Publications
Phosphodiesterases (PDEs) are vital in signal transduction, specifically by hydrolyzing
cAMP and cGMP. Within the PDE family, PDE10A is notable for its prominence in the …

Quantitative Read-Across (q-RA) and Quantitative Read-Across Structure–Activity Relationships (q-RASAR)—Genesis and Model Development

K Roy, A Banerjee - q-RASAR: A Path to Predictive Cheminformatics, 2024 - Springer
Recently the concept of read-across has been applied to machine-learning-based
supervised predictions for quantitative-read-across (q-RA) which have shown superior …

Deep Learning-Based Sentiment Analysis for the Prediction of Alzheimer's Drugs

P Mansingh, BK Pattanayak, B Pati - Computación y Sistemas, 2023 - scielo.org.mx
A growing public health concern, Alzheimer's disease (AD) affects millions of people
globally and has a yearly economic impact of billions of dollars. We examine the pipeline of …

QSAR model to develop newer generation GSK-3β inhibitors targeting Alzheimer

S Saha, V Jakhmola, AK Mahato, PK Ashok… - Moroccan Journal of …, 2023 - revues.imist.ma
In the year 2022 most of the patients affected by the disease was around 65 year age.
Among total number of patients, 73% were near 75 year or older age. It was also stated that …

Protein-protein interaction network analysis for the identification of novel multi-target inhibitors and target miRNAs against Alzheimer's disease.

V Kumar, K Roy - Advances in Protein Chemistry and Structural …, 2024 - europepmc.org
This study presents a strategy for extracting significant gene complexes and then provides
prospective therapeutics for AD. In this research, a total of 7905 reports published from 1981 …

[PDF][PDF] Constructing 4-hydroxythiazole-5-carboxamide building blocks in one pot

Y Xu, J Shu, Y Wang, Z Lu, YQ Yang… - ARKIVOC: Online Journal …, 2023 - arkat-usa.org
Hydroxythiazole-5-carboxamide units have been found in many bioactive compounds.
However, the yield for its overall synthetic method is as low as 10%, which limits its further …