Computer-aided drug design and drug discovery: a prospective analysis
In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges
as a transformative force, bridging the realms of biology and technology. This paper …
as a transformative force, bridging the realms of biology and technology. This paper …
Automated model building and protein identification in cryo-EM maps
Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high
levels of expertise and labour-intensive manual intervention in three-dimensional computer …
levels of expertise and labour-intensive manual intervention in three-dimensional computer …
Novel artificial intelligence-based approaches for ab initio structure determination and atomic model building for cryo-electron microscopy
Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method
for near-atomic structure determination, shedding light on the important molecular …
for near-atomic structure determination, shedding light on the important molecular …
Steering masked discrete diffusion models via discrete denoising posterior prediction
Generative modeling of discrete data underlies important applications spanning text-based
agents like ChatGPT to the design of the very building blocks of life in protein sequences …
agents like ChatGPT to the design of the very building blocks of life in protein sequences …
Evaluating representation learning on the protein structure universe
We introduce ProteinWorkshop, a comprehensive benchmark suite for representation
learning on protein structures with Geometric Graph Neural Networks. We consider large …
learning on protein structures with Geometric Graph Neural Networks. We consider large …
Protein fitness prediction is impacted by the interplay of language models, ensemble learning, and sampling methods
Advances in machine learning (ML) and the availability of protein sequences via high-
throughput sequencing techniques have transformed the ability to design novel diagnostic …
throughput sequencing techniques have transformed the ability to design novel diagnostic …
Integrating Embeddings from Multiple Protein Language Models to Improve Protein O-GlcNAc Site Prediction
O-linked β-N-acetylglucosamine (O-GlcNAc) is a distinct monosaccharide modification of
serine (S) or threonine (T) residues of nucleocytoplasmic and mitochondrial proteins. O …
serine (S) or threonine (T) residues of nucleocytoplasmic and mitochondrial proteins. O …
Fast protein structure searching using structure graph embeddings
Comparing and searching protein structures independent of primary sequence has proved
useful for remote homology detection, function annotation and protein classification. With the …
useful for remote homology detection, function annotation and protein classification. With the …
Functional protein dynamics directly from sequences
The sequence correlations within a protein multiple sequence alignment are routinely being
used to predict contacts within its structure, but here we point out that these data can also be …
used to predict contacts within its structure, but here we point out that these data can also be …
TAFPred: Torsion Angle Fluctuations Prediction from Protein Sequences
Simple Summary This study aimed to create an intelligent computer model called TAFPred
to predict how proteins move and twist by looking at their sequences. By analyzing different …
to predict how proteins move and twist by looking at their sequences. By analyzing different …