Computational approaches streamlining drug discovery

AV Sadybekov, V Katritch - Nature, 2023 - nature.com
Computer-aided drug discovery has been around for decades, although the past few years
have seen a tectonic shift towards embracing computational technologies in both academia …

Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)

HW Loh, CP Ooi, S Seoni, PD Barua, F Molinari… - Computer Methods and …, 2022 - Elsevier
Background and objectives Artificial intelligence (AI) has branched out to various
applications in healthcare, such as health services management, predictive medicine …

Targeting ferroptosis opens new avenues for the development of novel therapeutics

S Sun, J Shen, J Jiang, F Wang, J Min - Signal transduction and …, 2023 - nature.com
Ferroptosis is an iron-dependent form of regulated cell death with distinct characteristics,
including altered iron homeostasis, reduced defense against oxidative stress, and abnormal …

m6A modification: recent advances, anticancer targeted drug discovery and beyond

LJ Deng, WQ Deng, SR Fan, MF Chen, M Qi, WY Lyu… - Molecular cancer, 2022 - Springer
Abstract Abnormal N6-methyladenosine (m6A) modification is closely associated with the
occurrence, development, progression and prognosis of cancer, and aberrant m6A …

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

R Gupta, D Srivastava, M Sahu, S Tiwari, RK Ambasta… - Molecular …, 2021 - Springer
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

The role of artificial intelligence in healthcare: a structured literature review

S Secinaro, D Calandra, A Secinaro… - BMC medical informatics …, 2021 - Springer
Abstract Background/Introduction Artificial intelligence (AI) in the healthcare sector is
receiving attention from researchers and health professionals. Few previous studies have …

Artificial intelligence aids in development of nanomedicines for cancer management

P Tan, X Chen, H Zhang, Q Wei, K Luo - Seminars in cancer biology, 2023 - Elsevier
Over the last decade, the nanomedicine has experienced unprecedented development in
diagnosis and management of diseases. A number of nanomedicines have been approved …

Amelioration of Alzheimer's disease pathology by mitophagy inducers identified via machine learning and a cross-species workflow

C Xie, XX Zhuang, Z Niu, R Ai, S Lautrup… - Nature Biomedical …, 2022 - nature.com
A reduced removal of dysfunctional mitochondria is common to aging and age-related
neurodegenerative pathologies such as Alzheimer's disease (AD). Strategies for treating …

Drug discovery with explainable artificial intelligence

J Jiménez-Luna, F Grisoni, G Schneider - Nature Machine Intelligence, 2020 - nature.com
Deep learning bears promise for drug discovery, including advanced image analysis,
prediction of molecular structure and function, and automated generation of innovative …

Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR

A Tropsha, O Isayev, A Varnek, G Schneider… - Nature Reviews Drug …, 2024 - nature.com
Quantitative structure–activity relationship (QSAR) modelling, an approach that was
introduced 60 years ago, is widely used in computer-aided drug design. In recent years …