[HTML][HTML] Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics
With more than 5 million fatalities and close to 300 million reported cases, COVID-19 is the
first documented pandemic due to a coronavirus that continues to be a major health …
first documented pandemic due to a coronavirus that continues to be a major health …
Drug design and disease diagnosis: the potential of deep learning models in biology
S Sreeraman, MP Kannan… - Current …, 2023 - ingentaconnect.com
Early prediction and detection enable reduced transmission of human diseases and provide
healthcare professionals ample time to make subsequent diagnoses and treatment …
healthcare professionals ample time to make subsequent diagnoses and treatment …
Deepbindgcn: Integrating molecular vector representation with graph convolutional neural networks for protein–ligand interaction prediction
The core of large-scale drug virtual screening is to select the binders accurately and
efficiently with high affinity from large libraries of small molecules in which non-binders are …
efficiently with high affinity from large libraries of small molecules in which non-binders are …
[HTML][HTML] Bibliometric analysis of artificial intelligence in healthcare research: Trends and future directions
Objective The presence of artificial intelligence (AI) in healthcare is a powerful and game-
changing force that is completely transforming the industry as a whole. Using sophisticated …
changing force that is completely transforming the industry as a whole. Using sophisticated …
[HTML][HTML] Advancements and novel approaches in modified autodock vina algorithms for enhanced molecular docking
Molecular docking plays a crucial role in modern drug discovery by facilitating the prediction
of interactions between small molecules and biomolecular targets. AutoDock Vina (Vina) …
of interactions between small molecules and biomolecular targets. AutoDock Vina (Vina) …
The application of artificial intelligence to accelerate G protein‐coupled receptor drug discovery
The application of artificial intelligence (AI) approaches to drug discovery for G protein‐
coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at …
coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at …
Small-Molecule Inhibitors of TIPE3 Protein Identified through Deep Learning Suppress Cancer Cell Growth In Vitro
Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a
transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human …
transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human …
Identifying Potent Fat Mass and Obesity-Associated Protein Inhibitors Using Deep Learning-Based Hybrid Procedures
K Mayuri, D Varalakshmi, M Tharaheswari… - …, 2024 - mdpi.com
The fat mass and obesity-associated (FTO) protein catalyzes metal-dependent modifications
of nucleic acids, namely the demethylation of methyl adenosine inside mRNA molecules …
of nucleic acids, namely the demethylation of methyl adenosine inside mRNA molecules …
[HTML][HTML] AI's role in pharmaceuticals: assisting drug design from protein interactions to drug development
S Bechelli, J Delhommelle - Artificial Intelligence Chemistry, 2024 - Elsevier
Developing new pharmaceutical compounds is a lengthy, costly, and intensive process. In
recent years, the development of Artificial Intelligence (AI), Machine Learning (ML), and …
recent years, the development of Artificial Intelligence (AI), Machine Learning (ML), and …
Advances in Deep Learning Assisted Drug Discovery Methods: A Self-review
H Zhang, KM Saravanan - Current Bioinformatics, 2024 - benthamdirect.com
Artificial Intelligence is a field within computer science that endeavors to replicate the
intricate structures and operational mechanisms inherent in the human brain. Machine …
intricate structures and operational mechanisms inherent in the human brain. Machine …