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[HTML][HTML] Revolutionizing medicinal chemistry: the application of artificial intelligence (AI) in early drug discovery
Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical
industry and research, where it has been utilized to efficiently identify new chemical entities …
industry and research, where it has been utilized to efficiently identify new chemical entities …
[HTML][HTML] Advances in Artificial Intelligence (AI)-assisted approaches in drug screening
Artificial intelligence (AI) is revolutionizing the current process of drug design and
development, addressing the challenges encountered in its various stages. By utilizing AI …
development, addressing the challenges encountered in its various stages. By utilizing AI …
Deep learning tools to accelerate antibiotic discovery
Introduction As machine learning (ML) and artificial intelligence (AI) expand to many
segments of our society, they are increasingly being used for drug discovery. Recent deep …
segments of our society, they are increasingly being used for drug discovery. Recent deep …
Discovery of multitarget inhibitors against insect chitinolytic enzymes via machine learning-based virtual screening
Multitarget inhibitors of insect chitinolytic enzymes are promising sources of green
insecticides. Machine learning (ML) is an emerging virtual screening method that can …
insecticides. Machine learning (ML) is an emerging virtual screening method that can …
Tidal: topology-inferred drug addiction learning
Z Zhu, B Dou, Y Cao, J Jiang, Y Zhu… - Journal of chemical …, 2023 - ACS Publications
Drug addiction is a global public health crisis, and the design of antiaddiction drugs remains
a major challenge due to intricate mechanisms. Since experimental drug screening and …
a major challenge due to intricate mechanisms. Since experimental drug screening and …
Artificial Intelligence Agents for Materials Sciences
ON Oliveira Jr, L Christino, MCF Oliveira… - Journal of Chemical …, 2023 - ACS Publications
The artificial intelligence (AI) tools based on large-language models may serve as a
demonstration that we are reaching a groundbreaking new paradigm in which machines …
demonstration that we are reaching a groundbreaking new paradigm in which machines …
From NMR to AI: designing a novel chemical representation to enhance machine learning predictions of physicochemical properties
A novel approach to the utilization of nuclear magnetic resonance (NMR) spectroscopy data
in the prediction of logD through machine learning algorithms is shown. In the analysis, a …
in the prediction of logD through machine learning algorithms is shown. In the analysis, a …
[HTML][HTML] Artificial intelligence for drug repurposing against infectious diseases
A Singh - Artificial Intelligence Chemistry, 2024 - Elsevier
Traditional drug discovery struggles to keep pace with the ever-evolving threat of infectious
diseases. New viruses and antibiotic-resistant bacteria, all demand rapid solutions. Artificial …
diseases. New viruses and antibiotic-resistant bacteria, all demand rapid solutions. Artificial …
Proteome-informed machine learning studies of cocaine addiction
No anti-cocaine addiction drugs have been approved by the Food and Drug Administration
despite decades of effort. The main challenge is the intricate molecular mechanisms of …
despite decades of effort. The main challenge is the intricate molecular mechanisms of …
[HTML][HTML] Mind the gap—deciphering GPCR pharmacology using 3D pharmacophores and artificial intelligence
T Noonan, K Denzinger, V Talagayev, Y Chen, K Puls… - Pharmaceuticals, 2022 - mdpi.com
G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and
well-studied protein targets, yet unanswered questions in the field leave significant gaps in …
well-studied protein targets, yet unanswered questions in the field leave significant gaps in …