Science

Since 2006, Acellera supports applied research for the development of biomedical simulation methods and machine learning predictors via agreements with academic institutions.

Furthermore, we create new software and hardware infrastructure for performing biomolecular simulations in high-throughput. Salient examples are ACEMD, HTMD or Metrocubo.

We would be happy to consider scientific collaborations with interested parties to demonstrate the potential of biomolecular simulations and deep learning. We are open to research projects (e.g. European projects) as well as other collaboration formats. Do not hesitate to contact us today.

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Science

Publications

Keywords

ACEMD/HTMD/AceCloud Applications Conformational Studies Fragment Based Drug Discovery Membrane Proteins Protein-Ligand Binding Theory

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publications.

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

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

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

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

Machine Learning Coarse-Grained Potentials of Protein Thermodynamics

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

Structure based virtual screening: Fast and slow

TorchMD: A deep learning framework for molecular simulations

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

SkeleDock: a web application for scaffold docking in PlayMolecule

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

Small molecule modulation of intrinsically disordered proteins using molecular dynamics simulations

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

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

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

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

DeltaDelta neural networks for lead optimization of small molecule potency

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

Shape-based generative modeling for de novo drug design

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

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

Dopamine D3 receptor antagonist reveals a cryptic pocket in aminergic GPCRs

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

PathwayMap: molecular pathway association with self-normalizing neural networks

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

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

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

Dimensionality reduction methods for molecular simulations

Optimizing Proteins and Ligands for Computerized Drug Discovery

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

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

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

HTMD: high-throughput molecular dynamics for molecular discovery

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

Binding kinetics in drug discovery

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

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

AceCloud: molecular dynamics simulations in the cloud

Insights from fragment hit binding assays by molecular simulations

Reranking docking poses using molecular simulations and approximate free energy methods

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

Membrane lipids are key modulators of the endocannabinoid-hydrolase FAAH

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

Kinetic modulation of a disordered protein domain by phosphorylation

Identification of slow molecular order parameters for Markov model construction

Visualizing the induced binding of SH2-phosphopeptide

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

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

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

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

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

Optimized potential of mean force calculations for standard binding free energies

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

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

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

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

ACEMD: Accelerating biomolecular dynamics in the microsecond time scale

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