Acellera News
News
- Beyond one billion tokens per day: a small experiment in AI for drug discovery
- Does better electrostatics improve RBFE?
- From PDB to Simulation-Ready: Expanding What Molecular System Preparation Can Handle
- Evaluating AceProp on public Polaris benchmarks
- An AceProp submission to the PXR Blind Challenge
- AceFF™-2: Bridging the Gap Between Speed and Accuracy in Drug Discovery
- From Conversation to Computation: PlayMolecule AI Calls Molecular Workflows
- Stop Searching, Start Asking: Introducing "Speak to a Protein"
- Acellera and Psivant Collaborate to Develop Transformative Computational Drug Discovery Approaches Using AI and Quantum Simulations
- Advancing Drug Discovery with AceFF™ 1.0
- Release of ACEMD 4.0.0: Advancing Machine Learning for Molecular Dynamics Simulations
- Acellera CCPBioSim IndustryTalk: Applications of MD Simulations in Drug Discovery Pipelines
- Professor Andrew White Joins Acellera Therapeutics’ Advisory Board
- ACEGEN: A Reinforcement Learning Toolkit for Generative Drug Design
- Exploring the Complexities of PURA Syndrome: Insights from Molecular Dynamics
- A published RBFE study and a call for collaborators
- PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data
- Acellera receives ISO 27001 certification in information security
- OpenMM 8 with Integrated Machine Learning Potentials
- Machine Learning Small Molecule Properties in Drug Discovery: A Glimpse into Acellera's Innovations
- Top-Down Machine Learning of Coarse-Grained Protein Force Fields
- Machine learning coarse-grained potentials of protein thermodynamics
- NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics
- Exploring the Alchemical Transfer Method
- SPICE Dataset Released
- Workshop “Methods In Molecular Simulations And Machine Learning” 14-16/07/22 Barcelona
- New Tutorial: Using PlayMolecule® AceProfiler To Identify Homologs In The Protein Data Bank
- Pocket Detection, Docking And Molecular Dynamics For Binding Mode Prediction.
- CrypticScout Redesigned To Improve Fragment Screening Analysis
- C4X Discovery And Acellera Collaborate To Shed Light On The Mechanisms Of Action Of Anti-Cancer Drugs
- Acellera and Chemotargets collaborate on AI and physics based drug discovery
- New Tutorial: Using PlayMolecule Apps To Run A Drug Discovery Campaign
- New Tutorial: Predicting Ligand Binding Affinities With KDeep And KDeep Trainer
- Release Of ACEMD 3.5
- New Tutorial: AceDock, Protein-Ligand Docking And Virtual Screening.
- Release Of ACEMD 3.4
- TorchMD – A Deep Learning Framework For Molecular Simulations
- New Tutorial: Using CrypticScout To Find Binding Pockets In A Protein
- ACEMD And OpenMM Unite To Tackle New Challenges In Molecular Simulations
- How We Did On D3R Grand Challenge 4