AlphaFold, artificial intelligence (AI), and allostery
R Nussinov, M Zhang, Y Liu, H Jang - The Journal of Physical …, 2022 - ACS Publications
AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of
biological sequence data and artificial intelligence (AI). AlphaFold has appended projects …
biological sequence data and artificial intelligence (AI). AlphaFold has appended projects …
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery
W Wilman, S Wróbel, W Bielska… - Briefings in …, 2022 - academic.oup.com
Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to developing and designing these molecules are …
therapeutics. Computational approaches to developing and designing these molecules are …
ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction
Predicting the functional sites of a protein from its structure, such as the binding sites of small
molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two …
molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two …
DeepRank-GNN: a graph neural network framework to learn patterns in protein–protein interfaces
Motivation Gaining structural insights into the protein–protein interactome is essential to
understand biological phenomena and extract knowledge for rational drug design or protein …
understand biological phenomena and extract knowledge for rational drug design or protein …
Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology
Artificial intelligence (AI) uses data and algorithms to aim to draw conclusions that are as
good as, or even better than, those drawn by humans. AI is already part of our daily life; it is …
good as, or even better than, those drawn by humans. AI is already part of our daily life; it is …
DeepRank: a deep learning framework for data mining 3D protein-protein interfaces
Abstract Three-dimensional (3D) structures of protein complexes provide fundamental
information to decipher biological processes at the molecular scale. The vast amount of …
information to decipher biological processes at the molecular scale. The vast amount of …
A new age in protein design empowered by deep learning
The rapid progress in the field of deep learning has had a significant impact on protein
design. Deep learning methods have recently produced a breakthrough in protein structure …
design. Deep learning methods have recently produced a breakthrough in protein structure …
Protein docking model evaluation by graph neural networks
Physical interactions of proteins play key functional roles in many important cellular
processes. To understand molecular mechanisms of such functions, it is crucial to determine …
processes. To understand molecular mechanisms of such functions, it is crucial to determine …
Structure‐Based Drug Discovery with Deep Learning
Artificial intelligence (AI) in the form of deep learning has promise for drug discovery and
chemical biology, for example, to predict protein structure and molecular bioactivity, plan …
chemical biology, for example, to predict protein structure and molecular bioactivity, plan …
Open-source machine learning in computational chemistry
A Hagg, KN Kirschner - Journal of Chemical Information and …, 2023 - ACS Publications
The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …