Acellera
@acellera.com
AI-Driven Drug Engineering: Building a discovery factory.
www.acellera.com
www.acellera.com
Reposted by Acellera
Preprint release 😀 of "Speak to a Protein," an AI co-scientist that facilitates data gathering and analysis in an interactive collaborative session. It is quite amazing to use. Preprint: arxiv.org/abs/2510.17826
October 22, 2025 at 4:39 PM
Preprint release 😀 of "Speak to a Protein," an AI co-scientist that facilitates data gathering and analysis in an interactive collaborative session. It is quite amazing to use. Preprint: arxiv.org/abs/2510.17826
Reposted by Acellera
We’re announcing the publication of our latest research on a universal, machine-learned coarse-grained protein force field: www.nature.com/articles/s41...
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
Navigating protein landscapes with a machine-learned transferable coarse-grained model - Nature Chemistry
The development of a universal protein coarse-grained model has been a long-standing challenge. A coarse-grained model with chemical transferability has now been developed by combining deep-learning m...
www.nature.com
July 24, 2025 at 8:46 AM
We’re announcing the publication of our latest research on a universal, machine-learned coarse-grained protein force field: www.nature.com/articles/s41...
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
We’re announcing the publication of our latest research on a universal, machine-learned coarse-grained protein force field: www.nature.com/articles/s41...
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
Navigating protein landscapes with a machine-learned transferable coarse-grained model - Nature Chemistry
The development of a universal protein coarse-grained model has been a long-standing challenge. A coarse-grained model with chemical transferability has now been developed by combining deep-learning m...
www.nature.com
July 24, 2025 at 8:46 AM
We’re announcing the publication of our latest research on a universal, machine-learned coarse-grained protein force field: www.nature.com/articles/s41...
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
The approach demonstrates chemical transferability on diverse proteins, predicting metastable states, and relative folding free energies.
Acellera Therapeutics and Psivant Therapeutics to collaborate on transformative computational drug discovery, leveraging AI, quantum simulations, and physics-based methods to accelerate small molecule design.
Learn more: www.acellera.com/blog/aceller...
Learn more: www.acellera.com/blog/aceller...
Acellera and Psivant Collaborate to Develop Transformative Computational Drug Discovery Approaches Using AI and Quantum Simulations - Acellera Blog
www.acellera.com
January 29, 2025 at 2:27 PM
Acellera Therapeutics and Psivant Therapeutics to collaborate on transformative computational drug discovery, leveraging AI, quantum simulations, and physics-based methods to accelerate small molecule design.
Learn more: www.acellera.com/blog/aceller...
Learn more: www.acellera.com/blog/aceller...
AceForce 1.0 isn’t just for RBFE calculations—it’s also enabling advanced protein-ligand simulations using NNP/MM methodologies.
Discover how AceForce enhances accuracy and efficiency in computational drug discovery.
Discover how AceForce enhances accuracy and efficiency in computational drug discovery.
January 15, 2025 at 4:17 PM
AceForce 1.0 isn’t just for RBFE calculations—it’s also enabling advanced protein-ligand simulations using NNP/MM methodologies.
Discover how AceForce enhances accuracy and efficiency in computational drug discovery.
Discover how AceForce enhances accuracy and efficiency in computational drug discovery.
AceForce 1.0 is here.
Our neural network potential is designed to enhance drug discovery with quantum-level accuracy. AceForce 1.0 delivers precise predictions, reduces computational costs, and integrates seamlessly into workflows.
Discover more: acellera.com/blog/advanci...
#compchemsky
Our neural network potential is designed to enhance drug discovery with quantum-level accuracy. AceForce 1.0 delivers precise predictions, reduces computational costs, and integrates seamlessly into workflows.
Discover more: acellera.com/blog/advanci...
#compchemsky
Advancing Drug Discovery with AceForce 1.0 - Acellera Blog
acellera.com
January 7, 2025 at 10:07 AM
AceForce 1.0 is here.
Our neural network potential is designed to enhance drug discovery with quantum-level accuracy. AceForce 1.0 delivers precise predictions, reduces computational costs, and integrates seamlessly into workflows.
Discover more: acellera.com/blog/advanci...
#compchemsky
Our neural network potential is designed to enhance drug discovery with quantum-level accuracy. AceForce 1.0 delivers precise predictions, reduces computational costs, and integrates seamlessly into workflows.
Discover more: acellera.com/blog/advanci...
#compchemsky
ACEMD 4.0.0 is here! Now featuring seamless integration of Neural Network Potentials (NNP) with Molecular Mechanics (MM) for advanced hybrid simulations.
Key features: 🔹 Simplified NNP/MM simulations 🔹 Python API & backward compatibility
Explore more: www.acellera.com/blog/release...
Key features: 🔹 Simplified NNP/MM simulations 🔹 Python API & backward compatibility
Explore more: www.acellera.com/blog/release...
Release of ACEMD 4.0.0: Advancing Machine Learning for Molecular Dynamics Simulations - Acellera Blog
www.acellera.com
December 4, 2024 at 1:50 PM
ACEMD 4.0.0 is here! Now featuring seamless integration of Neural Network Potentials (NNP) with Molecular Mechanics (MM) for advanced hybrid simulations.
Key features: 🔹 Simplified NNP/MM simulations 🔹 Python API & backward compatibility
Explore more: www.acellera.com/blog/release...
Key features: 🔹 Simplified NNP/MM simulations 🔹 Python API & backward compatibility
Explore more: www.acellera.com/blog/release...
We recently presented our drug discovery methods in a CCPBioSim Industry Talk. Adrià Pérez, one of our computational chemists, showcased how MD simulations power conformational analysis, pose prediction, and free energy calculations.
Watch here: www.acellera.com/blog/aceller...
Watch here: www.acellera.com/blog/aceller...
Acellera CCPBioSim IndustryTalk: Applications of MD Simulations in Drug Discovery Pipelines - Acellera Blog
www.acellera.com
November 21, 2024 at 1:27 PM
We recently presented our drug discovery methods in a CCPBioSim Industry Talk. Adrià Pérez, one of our computational chemists, showcased how MD simulations power conformational analysis, pose prediction, and free energy calculations.
Watch here: www.acellera.com/blog/aceller...
Watch here: www.acellera.com/blog/aceller...
New work on neural network potentials for lightly coarse-grained systems. AMARO models.
AMARO: All Heavy-Atom Transferable Neural Network Potentials of Protein Thermodynamics
A novel machine-learning-based force field for protein thermodynamics. It uses an all-heavy-atom approach without hydrogens to simplify simulations while maintaining key dynamics.
pubs.acs.org/doi/10.1021/...
A novel machine-learning-based force field for protein thermodynamics. It uses an all-heavy-atom approach without hydrogens to simplify simulations while maintaining key dynamics.
pubs.acs.org/doi/10.1021/...
November 20, 2024 at 7:05 AM
New work on neural network potentials for lightly coarse-grained systems. AMARO models.