Sparks of function by de novo protein design
Abstract Information in proteins flows from sequence to structure to function, with each step
causally driven by the preceding one. Protein design is founded on inverting this process …
causally driven by the preceding one. Protein design is founded on inverting this process …
A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation
Artificial intelligence (AI)-driven methods can vastly improve the historically costly drug
design process, with various generative models already in widespread use. Generative …
design process, with various generative models already in widespread use. Generative …
Artificial intelligence for science in quantum, atomistic, and continuum systems
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …
On the design fundamentals of diffusion models: A survey
Diffusion models are generative models, which gradually add and remove noise to learn the
underlying distribution of training data for data generation. The components of diffusion …
underlying distribution of training data for data generation. The components of diffusion …
Point cloud approach to generative modeling for galaxy surveys at the field level
We introduce a diffusion-based generative model to describe the distribution of galaxies in
our Universe directly as a collection of points in 3D space (coordinates) optionally with …
our Universe directly as a collection of points in 3D space (coordinates) optionally with …
[HTML][HTML] ProteinReDiff: Complex-based ligand-binding proteins redesign by equivariant diffusion-based generative models
Proteins, serving as the fundamental architects of biological processes, interact with ligands
to perform a myriad of functions essential for life. Designing functional ligand-binding …
to perform a myriad of functions essential for life. Designing functional ligand-binding …
[HTML][HTML] Structure-based protein and small molecule generation using EGNN and diffusion models: A comprehensive review
Recent breakthroughs in deep learning have revolutionized protein sequence and structure
prediction. These advancements are built on decades of protein design efforts, and are …
prediction. These advancements are built on decades of protein design efforts, and are …
Neural graph generator: Feature-conditioned graph generation using latent diffusion models
Graph generation has emerged as a crucial task in machine learning, with significant
challenges in generating graphs that accurately reflect specific properties. Existing methods …
challenges in generating graphs that accurately reflect specific properties. Existing methods …
Deep learning in template-free de novo biosynthetic pathway design of natural products
X **e, L Gui, B Qiao, G Wang, S Huang… - Briefings in …, 2024 - academic.oup.com
Natural products (NPs) are indispensable in drug development, particularly in combating
infections, cancer, and neurodegenerative diseases. However, their limited availability …
infections, cancer, and neurodegenerative diseases. However, their limited availability …
Transferable deep generative modeling of intrinsically disordered protein conformations
Intrinsically disordered proteins have dynamic structures through which they play key
biological roles. The elucidation of their conformational ensembles is a challenging problem …
biological roles. The elucidation of their conformational ensembles is a challenging problem …