[HTML][HTML] The role of ai in drug discovery: challenges, opportunities, and strategies

A Blanco-Gonzalez, A Cabezon, A Seco-Gonzalez… - Pharmaceuticals, 2023 - mdpi.com
Artificial intelligence (AI) has the potential to revolutionize the drug discovery process,
offering improved efficiency, accuracy, and speed. However, the successful application of AI …

Modeling conformational states of proteins with AlphaFold

D Sala, F Engelberger, HS Mchaourab… - Current Opinion in …, 2023 - Elsevier
Many proteins exert their function by switching among different structures. Knowing the
conformational ensembles affiliated with these states is critical to elucidate key mechanistic …

[HTML][HTML] AlphaFold2 and its applications in the fields of biology and medicine

Z Yang, X Zeng, Y Zhao, R Chen - Signal Transduction and Targeted …, 2023 - nature.com
Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind
that can predict three-dimensional (3D) structures of proteins from amino acid sequences …

Protein folds vs. protein folding: Differing questions, different challenges

SJ Chen, M Hassan, RL Jernigan… - Proceedings of the …, 2023 - National Acad Sciences
Protein fold prediction using deep-learning artificial intelligence (AI) has transformed the
field of protein structure prediction (1–3). By combining physical and geometric constraints …

[HTML][HTML] AlphaFold, allosteric, and orthosteric drug discovery: Ways forward

R Nussinov, M Zhang, Y Liu, H Jang - Drug Discovery Today, 2023 - Elsevier
Drug discovery is arguably a highly challenging and significant interdisciplinary aim. The
stunning success of the artificial intelligence-powered AlphaFold, whose latest version is …

Benchmarking refined and unrefined AlphaFold2 structures for hit discovery

Y Zhang, M Vass, D Shi, E Abualrous… - Journal of Chemical …, 2023 - ACS Publications
The recently developed AlphaFold2 (AF2) algorithm predicts proteins' 3D structures from
amino acid sequences. The open AlphaFold protein structure database covers the complete …

Towards predicting equilibrium distributions for molecular systems with deep learning

S Zheng, J He, C Liu, Y Shi, Z Lu, W Feng, F Ju… - arXiv preprint arXiv …, 2023 - arxiv.org
Advances in deep learning have greatly improved structure prediction of molecules.
However, many macroscopic observations that are important for real-world applications are …

[HTML][HTML] Protein structure and folding pathway prediction based on remote homologs recognition using PAthreader

K Zhao, Y Xia, F Zhang, X Zhou, SZ Li… - Communications …, 2023 - nature.com
Recognition of remote homologous structures is a necessary module in AlphaFold2 and is
also essential for the exploration of protein folding pathways. Here, we propose a method …

[HTML][HTML] Predicting equilibrium distributions for molecular systems with deep learning

S Zheng, J He, C Liu, Y Shi, Z Lu, W Feng… - Nature Machine …, 2024 - nature.com
Advances in deep learning have greatly improved structure prediction of molecules.
However, many macroscopic observations that are important for real-world applications are …

Advancing targeted protein degradation via multiomics profiling and artificial intelligence

M Duran-Frigola, M Cigler… - Journal of the American …, 2023 - ACS Publications
Only around 20% of the human proteome is considered to be druggable with small-molecule
antagonists. This leaves some of the most compelling therapeutic targets outside the reach …