Artificial intelligence in molecular de novo design: Integration with experiment
In this mini review, we capture the latest progress of applying artificial intelligence (AI)
techniques based on deep learning architectures to molecular de novo design with a focus …
techniques based on deep learning architectures to molecular de novo design with a focus …
Lead/drug discovery from natural resources
Z Xu, B Eichler, EA Klausner, J Duffy-Matzner, W Zheng - Molecules, 2022 - mdpi.com
Natural products and their derivatives have been shown to be effective drug candidates
against various diseases for many years. Over a long period of time, nature has produced an …
against various diseases for many years. Over a long period of time, nature has produced an …
[图书][B] Antimalarial natural products
DGI Kingston, MB Cassera - 2022 - Springer
Natural products have made a crucial and unique contribution to human health, and this is
especially true in the case of malaria, where the natural products quinine and artemisinin …
especially true in the case of malaria, where the natural products quinine and artemisinin …
On the best way to cluster NCI-60 molecules
S Hernández-Hernández, PJ Ballester - Biomolecules, 2023 - mdpi.com
Machine learning-based models have been widely used in the early drug-design pipeline.
To validate these models, cross-validation strategies have been employed, including those …
To validate these models, cross-validation strategies have been employed, including those …
QSARtuna: An Automated QSAR Modeling Platform for Molecular Property Prediction in Drug Design
Machine-learning (ML) and deep-learning (DL) approaches to predict the molecular
properties of small molecules are increasingly deployed within the design–make–test …
properties of small molecules are increasingly deployed within the design–make–test …
2D-quantitative structure–activity relationships model using PLS method for anti-malarial activities of anti-haemozoin compounds
PTV Nguyen, T Van Dat, S Mizukami, DLH Nguyen… - Malaria Journal, 2021 - Springer
Background Emergence of cross-resistance to current anti-malarial drugs has led to an
urgent need for identification of potential compounds with novel modes of action and anti …
urgent need for identification of potential compounds with novel modes of action and anti …
Salicylic acid derivatives as potential α-glucosidase inhibitors: drug design, molecular docking and pharmacokinetic studies
Background Diabetes mellitus (DM) is one of the most defying health risk in the twenty-first
century promoting a high rate of morbidity and mortality that could possibly increase if no …
century promoting a high rate of morbidity and mortality that could possibly increase if no …
Boosting Sinh Cosh Optimizer and arithmetic optimization algorithm for improved prediction of biological activities for indoloquinoline derivatives
Abstract Quantitative Structure Activity Relation (QSAR) models are mathematical
techniques used to link structural characteristics with biological activities, thus considered a …
techniques used to link structural characteristics with biological activities, thus considered a …
Ligand-based drug design, molecular docking and pharmacokinetic studies of some series of 1, 4-dihydropyridines derivatives as human intestinal maltase …
Abstract Quantitative Structure Activity Relationship (QSAR) was employed to predict the
inhibitory activities of some series of 1, 4–dihydropyridines derivatives as potent C-terminal …
inhibitory activities of some series of 1, 4–dihydropyridines derivatives as potent C-terminal …
Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids
Identification of lead compounds with the traditional laboratory approach is expensive and
time-consuming. Nowadays, in silico techniques have emerged as a promising approach for …
time-consuming. Nowadays, in silico techniques have emerged as a promising approach for …