The trRosetta server for fast and accurate protein structure prediction

Z Du, H Su, W Wang, L Ye, H Wei, Z Peng… - Nature protocols, 2021‏ - nature.com
The trRosetta (transform-restrained Rosetta) server is a web-based platform for fast and
accurate protein structure prediction, powered by deep learning and Rosetta. With the input …

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

KM Jablonka, Q Ai, A Al-Feghali, S Badhwar… - Digital discovery, 2023‏ - pubs.rsc.org
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists.
Recent studies suggested that these models could be useful in chemistry and materials …

[HTML][HTML] DeePMD-kit v2: A software package for deep potential models

J Zeng, D Zhang, D Lu, P Mo, Z Li, Y Chen… - The Journal of …, 2023‏ - pubs.aip.org
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics
simulations using machine learning potentials known as Deep Potential (DP) models. This …

ColabFold: making protein folding accessible to all

M Mirdita, K Schütze, Y Moriwaki, L Heo… - Nature …, 2022‏ - nature.com
ColabFold offers accelerated prediction of protein structures and complexes by combining
the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold's 40− 60 …

PROTAC-DB 2.0: an updated database of PROTACs

G Weng, X Cai, D Cao, H Du, C Shen… - Nucleic acids …, 2023‏ - academic.oup.com
Proteolysis targeting chimeras (PROTACs), which harness the ubiquitin-proteasome system
to selectively induce targeted protein degradation, represent an emerging therapeutic …

CASTp 3.0: computed atlas of surface topography of proteins

W Tian, C Chen, X Lei, J Zhao, J Liang - Nucleic acids research, 2018‏ - academic.oup.com
Geometric and topological properties of protein structures, including surface pockets, interior
cavities and cross channels, are of fundamental importance for proteins to carry out their …

Generative design of de novo proteins based on secondary-structure constraints using an attention-based diffusion model

B Ni, DL Kaplan, MJ Buehler - Chem, 2023‏ - cell.com
We report two generative deep-learning models that predict amino acid sequences and 3D
protein structures on the basis of secondary-structure design objectives via either the overall …

HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA

G Weng, E Wang, Z Wang, H Liu, F Zhu… - Nucleic acids …, 2019‏ - academic.oup.com
Protein–protein interactions (PPIs) play an important role in the different functions of cells,
but accurate prediction of the three-dimensional structures for PPIs is still a notoriously …

GPS 6.0: an updated server for prediction of kinase-specific phosphorylation sites in proteins

M Chen, W Zhang, Y Gou, D Xu, Y Wei… - Nucleic acids …, 2023‏ - academic.oup.com
Protein phosphorylation, catalyzed by protein kinases (PKs), is one of the most important
post-translational modifications (PTMs), and involved in regulating almost all of biological …

Improvements to the APBS biomolecular solvation software suite

E Jurrus, D Engel, K Star, K Monson, J Brandi… - Protein …, 2018‏ - Wiley Online Library
Abstract The Adaptive Poisson–Boltzmann Solver (APBS) software was developed to solve
the equations of continuum electrostatics for large biomolecular assemblages that have …