Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …
Key topics in molecular docking for drug design
PHM Torres, ACR Sodero, P Jofily… - International journal of …, 2019 - mdpi.com
Molecular docking has been widely employed as a fast and inexpensive technique in the
past decades, both in academic and industrial settings. Although this discipline has now had …
past decades, both in academic and industrial settings. Although this discipline has now had …
Comparison of descriptor-and fingerprint sets in machine learning models for ADME-Tox targets
The screening of compounds for ADME-Tox targets plays an important role in drug design.
QSPR models can increase the speed of these specific tasks, although the performance of …
QSPR models can increase the speed of these specific tasks, although the performance of …
Property-unmatched decoys in docking benchmarks
Enrichment of ligands versus property-matched decoys is widely used to test and optimize
docking library screens. However, the unconstrained optimization of enrichment alone can …
docking library screens. However, the unconstrained optimization of enrichment alone can …
DeepCancerMap: a versatile deep learning platform for target-and cell-based anticancer drug discovery
Discovering new anticancer drugs has been widely concerned and remains an open
challenge. Target-and phenotypic-based experimental screening represent two mainstream …
challenge. Target-and phenotypic-based experimental screening represent two mainstream …
A multi-task FP-GNN framework enables accurate prediction of selective PARP inhibitors
PARP (poly ADP-ribose polymerase) family is a crucial DNA repair enzyme that responds to
DNA damage, regulates apoptosis, and maintains genome stability; therefore, PARP …
DNA damage, regulates apoptosis, and maintains genome stability; therefore, PARP …
Ligand-and structure-based identification of novel CDK9 inhibitors for the potential treatment of leukemia
H Zhang, J Huang, R Chen, H Cai, Y Chen, S He… - Bioorganic & Medicinal …, 2022 - Elsevier
Abstract Cyclin-dependent kinase 9 (CDK9) plays a vital role in controlling cell transcription
and has been an attractive target for cancer treatment. Herein, ten predictive models derived …
and has been an attractive target for cancer treatment. Herein, ten predictive models derived …
[HTML][HTML] Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning
The world is facing the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome
Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were …
Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were …
Novel covalent and non-covalent complex-based pharmacophore models of SARS-CoV-2 main protease (Mpro) elucidated by microsecond MD simulations
Y Hayek-Orduz, AF Vásquez, MF Villegas-Torres… - Scientific Reports, 2022 - nature.com
As the world enters its second year of the pandemic caused by SARS-CoV-2, intense efforts
have been directed to develop an effective diagnosis, prevention, and treatment strategies …
have been directed to develop an effective diagnosis, prevention, and treatment strategies …
Machine learning enables accurate and rapid prediction of active molecules against breast cancer cells
Breast cancer (BC) has surpassed lung cancer as the most frequently occurring cancer, and
it is the leading cause of cancer-related death in women. Therefore, there is an urgent need …
it is the leading cause of cancer-related death in women. Therefore, there is an urgent need …