The transformational role of GPU computing and deep learning in drug discovery
Deep learning has disrupted nearly every field of research, including those of direct
importance to drug discovery, such as medicinal chemistry and pharmacology. This …
importance to drug discovery, such as medicinal chemistry and pharmacology. This …
Deep learning-based advances in protein structure prediction
Obtaining an accurate description of protein structure is a fundamental step toward
understanding the underpinning of biology. Although recent advances in experimental …
understanding the underpinning of biology. Although recent advances in experimental …
Accurate prediction of protein structural flexibility by deep learning integrating intricate atomic structures and Cryo-EM density information
X Song, L Bao, C Feng, Q Huang, F Zhang… - Nature …, 2024 - nature.com
The dynamics of proteins are crucial for understanding their mechanisms. However,
computationally predicting protein dynamic information has proven challenging. Here, we …
computationally predicting protein dynamic information has proven challenging. Here, we …
Machine‐Learning Microstructure for Inverse Material Design
Metallurgy and material design have thousands of years' history and have played a critical
role in the civilization process of humankind. The traditional trial‐and‐error method has …
role in the civilization process of humankind. The traditional trial‐and‐error method has …
Applications of deep learning in electron microscopy
We review the growing use of machine learning in electron microscopy (EM) driven in part
by the availability of fast detectors operating at kiloHertz frame rates leading to large data …
by the availability of fast detectors operating at kiloHertz frame rates leading to large data …
Low-data interpretable deep learning prediction of antibody viscosity using a biophysically meaningful representation
BK Rai, JR Apgar, EM Bennett - Scientific Reports, 2023 - nature.com
Deep learning, aided by the availability of big data sets, has led to substantial advances
across many disciplines. However, many scientific problems of practical interest lack …
across many disciplines. However, many scientific problems of practical interest lack …
A robust normalized local filter to estimate compositional heterogeneity directly from cryo-EM maps
Cryo electron microscopy (cryo-EM) is used by biological research to visualize biomolecular
complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated …
complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated …
[HTML][HTML] Machine learning and artificial intelligence in therapeutics and drug development life cycle
In recent years, the pharmaceutical business has seen a considerable increase in data
digitization. With digitization, however, comes the challenge of obtaining, analyzing, and …
digitization. With digitization, however, comes the challenge of obtaining, analyzing, and …
Comprehensive strategies of machine-learning-based quantitative structure-activity relationship models
Early quantitative structure-activity relationship (QSAR) technologies have unsatisfactory
versatility and accuracy in fields such as drug discovery because they are based on …
versatility and accuracy in fields such as drug discovery because they are based on …
Integrating model simulation tools and cryo‐electron microscopy
JG Beton, T Cragnolini, M Kaleel… - Wiley …, 2023 - Wiley Online Library
The power of computer simulations, including machine‐learning, has become an
inseparable part of scientific analysis of biological data. This has significantly impacted the …
inseparable part of scientific analysis of biological data. This has significantly impacted the …