By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation and analyze site usage.
research & Development

Advancing Our Mission

Our research and development efforts are aimed at advancing our mission to transform drug discovery into a high-accuracy computable task.

We work closely with both public and private institutions, and we frequently publish our findings in reputable academic journals. In addition, we have initiated and continue to support various open access science and open source software projects.

We are always open to considering new collaborations.
Acellera ACEMD preview code
Open source projects

Molecular Modelling For Everyone

We lead and contribute to a number of open source molecular modeling and manipulation projects such as HTMD, MoleculeKit, OpenMM, ACEGEN, TorchMD and TorchMD-Net.
Open access

PlayMolecule.org – An Open Molecular Discovery Toolkit

PlayMolecule features a number of hosted apps for molecular discovery including a powerful online molecular viewer, system and ligand preparation tools and binding site and binding affinity prediction tools.
ACEMD, OPENMM and torchMD

Leaders in Molecular Dynamics

First launched in 2008, the ACEMD molecular simulation engine was the first biomolecular code to run on GPUs. Since 2020, ACEMD and OpenMM joined forces to innovate and deliver the most advanced molecular dynamics tools. We also contributed to TorchMD, a deep learning framework for molecular simulations.

Publications

>11,000
Papers citing Acellera's founders
>900
Papers citing ACEMD software
18
Years of know-how in computational drug discovery
Today, our software ACEMD has over 939 citations, and KDeep and Deepsite are among the most cited papers in the field of ML applied to drug discovery.
Showing
0
 results of
0
publications.

Enhancing Protein–Ligand Binding Affinity Predictions Using Neural Network Potentials

Sabanés Zariquiey, Francesc; Galvelis, Raimondas; Gallicchio, Emilio; Chodera, John D; Markland, Thomas E; De Fabritiis, Gianni;

Journal of Chemical Information and Modeling
2024
Applications

ACEGEN: Reinforcement learning of generative chemical agents for drug discovery

Albert Bou, Morgan Thomas, Sebastian Dittert, Carles Navarro Ramírez, Maciej Majewski, Ye Wang, Shivam Patel, Gary Tresadern, Mazen Ahmad, Vincent Moens, Woody Sherman, Simone Sciabola, Gianni De Fabritiis

arXiv preprint arXiv:2405.04657
2024
Applications

TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations

Pelaez, Raul P; Simeon, Guillem; Galvelis, Raimondas; Mirarchi, Antonio; Eastman, Peter; Doerr, Stefan; Thölke, Philipp; Markland, Thomas E; De Fabritiis, Gianni;

Journal of Chemical Theory and Computation
2024
Applications

PlayMolecule Viewer: a toolkit for the visualization of molecules and other data

Torrens-Fontanals, Mariona; Tourlas, Panagiotis; Doerr, Stefan; De Fabritiis, Gianni;

Journal of Chemical Information and Modeling
2024
Applications

TorchRL: A data-driven decision-making library for PyTorch

Bou, Albert; Bettini, Matteo; Dittert, Sebastian; Kumar, Vikash; Sodhani, Shagun; Yang, Xiaomeng; De Fabritiis, Gianni; Moens, Vincent;

ICLR 2024, arXiv preprint arXiv:2306.00577
2023
Applications

Machine Learning Small Molecule Properties in Drug Discovery

Schapin, Nikolai; Majewski, Maciej; Varela-Rial, Alejandro; Arroniz, Carlos; De Fabritiis, Gianni;

Artificial Intelligence Chemistry
2023
Molecular Simulations

Machine learning coarse-grained potentials of protein thermodynamics

Majewski, Maciej; Pérez, Adrià; Thölke, Philipp; Doerr, Stefan; Charron, Nicholas E; Giorgino, Toni; Husic, Brooke E; Clementi, Cecilia; Noé, Frank; De Fabritiis, Gianni;

Nature Communications
2023
Molecular Simulations

Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series

Sabanés Zariquiey, Francesc; Pérez, Adrià; Majewski, Maciej; Gallicchio, Emilio; De Fabritiis, Gianni

Journal of Chemical Information and Modeling
2023
Applications

Top-Down Machine Learning of Coarse-Grained Protein Force Fields

Navarro, Carles; Majewski, Maciej; De Fabritiis, Gianni;

Journal of Chemical Theory and Computation
2023
Molecular Simulations

NNP/MM: Accelerating molecular dynamics simulations with machine learning potentials and molecular mechanics

Galvelis, Raimondas; Varela-Rial, Alejandro; Doerr, Stefan; Fino, Roberto; Eastman, Peter; Markland, Thomas E; Chodera, John D; De Fabritiis, Gianni;

Journal of chemical information and modeling
2023
ACEMD/HTMD/AceCloud

Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series

Sabanés Zariquiey, Francesc; Pérez, Adrià; Majewski, Maciej; Gallicchio, Emilio; De Fabritiis, Gianni;

Journal of chemical information and modeling
2023
Applications

Openmm 8: Molecular dynamics simulation with machine learning potentials

Eastman, Peter; Galvelis, Raimondas; Peláez, Raúl P; Abreu, Charlles RA; Farr, Stephen E; Gallicchio, Emilio; Gorenko, Anton; Henry, Michael M; Hu, Frank; Huang, Jing;

The Journal of Physical Chemistry B
2023
Molecular Simulations

TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials

Thölke, Philipp; De Fabritiis, Gianni

International Conference on Learning Representations
2022
Applications

PlayMolecule glimpse: Understanding protein–ligand property predictions with interpretable neural networks

Varela-Rial, Alejandro; Maryanow, Iain; Majewski, Maciej; Doerr, Stefan; Schapin, Nikolai; Jiménez-Luna, José; De Fabritiis, Gianni

Journal of chemical information and modeling
2022
Applications

Structure based virtual screening: Fast and slow

Varela‐Rial, Alejandro; Majewski, Maciej; De Fabritiis, Gianni

Wiley Interdisciplinary Reviews: Computational Molecular Science
2022
Protein-Ligand Binding

TorchMD: A deep learning framework for molecular simulations

Doerr, Stefan; Majewski, Maciej; Pérez, Adrià; Kramer, Andreas; Clementi, Cecilia; Noe, Frank; Giorgino, Toni; De Fabritiis, Gianni

Journal of chemical theory and computation
2021
Applications

PlayMolecule CrypticScout: predicting protein cryptic sites using mixed-solvent molecular simulations

Martinez-Rosell, Gerard; Lovera, Silvia; Sands, Zara A; De Fabritiis, Gianni

Journal of Chemical Information and Modeling
2020
Applications

SkeleDock: a web application for scaffold docking in PlayMolecule

Varela-Rial, Alejandro; Majewski, Maciej; Cuzzolin, Alberto; Martínez-Rosell, Gerard; De Fabritiis, Gianni

Journal of Chemical Information and Modeling
2020
Applications

Characterization of partially ordered states in the intrinsically disordered N-terminal domain of p53 using millisecond molecular dynamics simulations

Herrera-Nieto, Pablo; Pérez, Adrià; De Fabritiis, Gianni

Scientific reports
2020
Applications

Small molecule modulation of intrinsically disordered proteins using molecular dynamics simulations

Herrera-Nieto, Pablo; Pérez, Adrià; De Fabritiis, Gianni

Journal of Chemical Information and Modeling
2020
Applications

AdaptiveBandit: A Multi-armed Bandit Framework for Adaptive Sampling in Molecular Simulations

Adrià Pérez, Pablo Herrera-Nieto, Stefan Doerr, and Gianni De Fabritiis

J. Chem. Theory Comput.
2020
Applications

A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning

Galvelis, Raimondas; Doerr, Stefan; Damas, João M; Harvey, Matt; De Fabritiis, Gianni

Journal of chemical information and modeling
2019
Applications

From target to drug: generative modeling for the multimodal structure-based ligand design

Skalic, Miha; Sabbadin, Davide; Sattarov, Boris; Sciabola, Simone; De Fabritiis, Gianni

Molecular pharmaceutics
2019
Applications

LigVoxel: inpainting binding pockets using 3D-convolutional neural networks

Skalic, Miha; Varela-Rial, Alejandro; Jiménez, José; Martínez-Rosell, Gerard; De Fabritiis, Gianni

Bioinformatics
2019
Applications

DeltaDelta neural networks for lead optimization of small molecule potency

Jiménez-Luna, José; Pérez-Benito, Laura; Martinez-Rosell, Gerard; Sciabola, Simone; Torella, Rubben; Tresadern, Gary; De Fabritiis, Gianni

Chemical science
2019
Applications

Reconstruction of apo A2A receptor activation pathways reveal ligand-competent intermediates and state-dependent cholesterol hotspots

Lovera, Silvia; Cuzzolin, Alberto; Kelm, Sebastian; De Fabritiis, Gianni; Sands, Zara A

Scientific Reports
2019
Applications

Shape-based generative modeling for de novo drug design

Skalic, Miha; Jiménez, José; Sabbadin, Davide; De Fabritiis, Gianni

Journal of chemical information and modeling
2019
Applications

K deep: protein–ligand absolute binding affinity prediction via 3d-convolutional neural networks

Jiménez, José; Skalic, Miha; Martinez-Rosell, Gerard; De Fabritiis, Gianni

Journal of chemical information and modeling
2018
Applications

Molecular-simulation-driven fragment screening for the discovery of new CXCL12 inhibitors

Martinez-Rosell, Gerard; Harvey, Matt J; De Fabritiis, Gianni

Journal of chemical information and modeling
2018
Fragment Based Drug Discovery

Dopamine D3 receptor antagonist reveals a cryptic pocket in aminergic GPCRs

Ferruz, Noelia; Doerr, Stefan; Vanase-Frawley, Michelle A; Zou, Yaozhong; Chen, Xiaomin; Marr, Eric S; Nelson, Robin T; Kormos, Bethany L; Wager, Travis T; Hou, Xinjun; Villalobos, Anabella; Sciabola, Simone; De Fabritiis, Gianni

Scientific reports
2018
Protein-Ligand Binding

PlayMolecule BindScope: Large scale CNN-based virtual screening on the web

Skalic, Miha; Martínez-Rosell, Gerard; Jiménez, José; De Fabritiis, Gianni

Bioinformatics
2018
Applications

PathwayMap: molecular pathway association with self-normalizing neural networks

Jimenez, Jose; Sabbadin, Davide; Cuzzolin, Alberto; Martinez-Rosell, Gerard; Gora, Jacob; Manchester, John; Duca, Jose; De Fabritiis, Gianni

Journal of chemical information and modeling
2018
Applications

Complete protein–protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling

Plattner, Nuria; Doerr, Stefan; De Fabritiis, Gianni; Noé, Frank

Nature chemistry
2017
Conformational Studies

High-throughput automated preparation and simulation of membrane proteins with HTMD

Doerr, Stefan; Giorgino, Toni; Martínez-Rosell, Gerard; Damas, Joao M; De Fabritiis, Gianni

Journal of Chemical Theory and Computation
2017
ACEMD/HTMD/AceCloud

DeepSite: protein-binding site predictor using 3D-convolutional neural networks

Jiménez, José; Doerr, Stefan; Martínez-Rosell, Gerard; Rose, Alexander S; De Fabritiis, Gianni

Bioinformatics
2017
Applications

Dimensionality reduction methods for molecular simulations

Doerr, Stefan; Ariz-Extreme, Igor; Harvey, Matthew J; De Fabritiis, Gianni

arXiv preprint arXiv:1710.10629
2017
Molecular Simulations

Optimizing Proteins and Ligands for Computerized Drug Discovery

Damas, João; Cuzzolin, Alberto; Galvelis, Raimondas; Doerr, Stefan; Martínez-Rosell, Gerard; Harvey, Matt; De Fabritiis, Gianni

2017
Applications

PlayMolecule ProteinPrepare: a web application for protein preparation for molecular dynamics simulations

Martínez-Rosell, Gerard; Giorgino, Toni; De Fabritiis, Gianni

Journal of chemical information and modeling
2017
Applications

Drug discovery and molecular dynamics: methods, applications and perspective beyond the second timescale

Martinez-Rosell, Gerard; Giorgino, Toni; Harvey, Matt J; de Fabritiis, Gianni

Current topics in medicinal chemistry
2017
Applications

The pathway of ligand entry from the membrane bilayer to a lipid G protein-coupled receptor

Stanley, Nathaniel; Pardo, Leonardo; De Fabritiis, Gianni

Scientific reports
2016
Membrane Proteins

HTMD: high-throughput molecular dynamics for molecular discovery

Doerr, S; Harvey, MJ; Noé, Frank; De Fabritiis, G

Journal of chemical theory and computation
2016
ACEMD/HTMD/AceCloud

Multibody cofactor and substrate molecular recognition in the myo-inositol monophosphatase enzyme

Ferruz, Noelia; Tresadern, Gary; Pineda-Lucena, Antonio; De Fabritiis, Gianni

Scientific reports
2016
Protein-Ligand Binding

Binding kinetics in drug discovery

Ferruz, Noelia; De Fabritiis, Gianni

Molecular Informatics
2016
Protein-Ligand Binding

HTMD: A complete software workspace for simulation-guided drug design

Doerr, Stefan; Harvey, Matt; De Fabritiis, Gianni

ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
2015
ACEMD/HTMD/AceCloud

Detection of new biased agonists for the serotonin 5-HT2A receptor: modeling and experimental validation

Martí-Solano, Maria; Iglesias, Alba; de Fabritiis, Gianni; Sanz, Ferran; Brea, José; Loza, M Isabel; Pastor, Manuel; Selent, Jana

Molecular pharmacology
2015
Fragment Based Drug Discovery

AceCloud: molecular dynamics simulations in the cloud

Harvey, Matt J; De Fabritiis, Gianni

Journal of Chemical Information and Modeling
2015
ACEMD/HTMD/AceCloud

Insights from fragment hit binding assays by molecular simulations

Ferruz, Noelia; Harvey, Matthew J; Mestres, Jordi; De Fabritiis, Gianni

Journal of chemical information and modeling
2015
Fragment Based Drug Discovery

Reranking docking poses using molecular simulations and approximate free energy methods

Lauro, G; Ferruz, Noelia; Fulle, Simone; Harvey, Matt J; Finn, Paul W; De Fabritiis, Gianni

Journal of chemical information and modeling
2014
Molecular Simulations

On-the-fly learning and sampling of ligand binding by high-throughput molecular simulations

Doerr, S; De Fabritiis, G

Journal of chemical theory and computation
2014
ACEMD/HTMD/AceCloud

Membrane lipids are key modulators of the endocannabinoid-hydrolase FAAH

Dainese, Enrico; De Fabritiis, Gianni; Sabatucci, Annalaura; Oddi, Sergio; Angelucci, Clotilde Beatrice; Di Pancrazio, Chiara; Giorgino, Toni; Stanley, Nathaniel; Del Carlo, Michele; Cravatt, Benjamin F

Biochemical Journal
2014
Applications

Kinetic characterization of fragment binding in AmpC β-lactamase by high-throughput molecular simulations

Bisignano, Paola; Doerr, Stefan; Harvey, Matt J; Favia, Angelo D; Cavalli, Andrea; De Fabritiis, Gianni

Journal of Chemical Information and Modeling
2014
Conformational Studies

Kinetic modulation of a disordered protein domain by phosphorylation

Stanley, Nathaniel; Esteban-Martín, Santiago; De Fabritiis, Gianni

Nature communications
2014
Conformational Studies

Identification of slow molecular order parameters for Markov model construction

Pérez-Hernández, Guillermo; Paul, Fabian; Giorgino, Toni; De Fabritiis, Gianni; Noé, Frank

The Journal of chemical physics
2013
ACEMD/HTMD/AceCloud

Visualizing the induced binding of SH2-phosphopeptide

Giorgino, T; Buch, I; De Fabritiis, G

Journal of chemical theory and computation
2012
Protein-Ligand Binding

Thumbs down for HIV: domain level rearrangements do occur in the NNRTI-bound HIV-1 reverse transcriptase

Wright, David W; Sadiq, S Kashif; De Fabritiis, Gianni; Coveney, Peter V

Journal of the American Chemical Society
2012
Conformational Studies

High-throughput molecular dynamics: the powerful new tool for drug discovery

Harvey, Matthew J; De Fabritiis, Gianni

Drug discovery today
2012
Molecular Simulations

Kinetic characterization of the critical step in HIV-1 protease maturation

Sadiq, S Kashif; Noé, Frank; De Fabritiis, Gianni

Proceedings of the National Academy of Sciences
2012
Conformational Studies

Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations

Buch, Ignasi; Giorgino, Toni; De Fabritiis, Gianni

Proceedings of the National Academy of Sciences
2011
Protein-Ligand Binding

A high-throughput steered molecular dynamics study on the free energy profile of ion permeation through gramicidin A

Giorgino, Toni; De Fabritiis, Gianni

Journal of Chemical Theory and Computation
2011
Applications

Optimized potential of mean force calculations for standard binding free energies

Buch, Ignasi; Sadiq, S Kashif; De Fabritiis, Gianni

Journal of Chemical Theory and Computation
2011
Applications

High-throughput all-atom molecular dynamics simulations using distributed computing

Buch, I; Harvey, Matt J; Giorgino, T; Anderson, DP; De Fabritiis, G

Journal of chemical information and modeling
2010
Applications

Induced effects of sodium ions on dopaminergic G-protein coupled receptors

Selent, Jana; Sanz, Ferran; Pastor, Manuel; De Fabritiis, Gianni

PLoS Computational Biology
2010
Membrane Proteins

Explicit solvent dynamics and energetics of HIV‐1 protease flap opening and closing

Sadiq, S Kashif; De Fabritiis, Gianni

Proteins: Structure, Function, and Bioinformatics
2010
Conformational Studies

An implementation of the smooth particle mesh Ewald method on GPU hardware

Harvey, MJ; De Fabritiis, G

Journal of Chemical Theory and Computation
2009
Conformational Studies

ACEMD: Accelerating biomolecular dynamics in the microsecond time scale

Harvey, MJ; Giupponi, G; De Fabritiis, G

Journal of Chemical Theory and Computation
2009
ACEMD/HTMD/AceCloud

The impact of accelerator processors for high-throughput molecular modeling and simulation

Giupponi, G; Harvey, MJ; De Fabritiis, G

Drug discovery today
2008
Molecular Simulations
International And EU Funded Projects
A cloud application platform for rational drug discovery using high throughput molecular dynamics.
European SME innovation Associate(H2020-INNOSUP-02-2016, Grant Agreement 739649)
Computer-Centric Fragment Based Ligand Discovery for the Development of candidate molecules targeting the chemkine system.
Nuclis d’Innovació Tecnològica 2014. Acció, Generalitat de Catalunya. Nuclis Transnacionals Programa Bilateral Catalunya-Israel, Project nr. RDIS14-1-0002. 2014-2016
Feasibility assessment of a cloud application platform for rational drug design using high-throughput.
H2020 SME Instrument 2014, Grant Agreement nr. 674659. 2015
A Centre of Excellence in Computational Biomedicine.
H2020-EINFRA-2015-1, Grant Agreement nr. 675451. 2016-2019
A Centre of Excellence in Computational Biomedicine.
H2020-INFRAEDI-02-2018, Grant Agreement nr. 823712. 2019-2023