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Maciej Majewski
Maciej Majewski
在 sanofi.com 的电子邮件经过验证
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TorchMD: A deep learning framework for molecular simulations
S Doerr, M Majewski, A Pérez, A Kramer, C Clementi, F Noe, T Giorgino, ...
Journal of chemical theory and computation 17 (4), 2355-2363, 2021
1612021
Coarse graining molecular dynamics with graph neural networks
BE Husic, NE Charron, D Lemm, J Wang, A Pérez, M Majewski, A Krämer, ...
The Journal of chemical physics 153 (19), 2020
1532020
Cap analogs modified with 1, 2-dithiodiphosphate moiety protect mRNA from decapping and enhance its translational potential
M Strenkowska, R Grzela, M Majewski, K Wnek, J Kowalska, ...
Nucleic acids research 44 (20), 9578-9590, 2016
792016
An investigation of structural stability in protein-ligand complexes reveals the balance between order and disorder
M Majewski, S Ruiz-Carmona, X Barril
Communications Chemistry 2 (1), 110, 2019
562019
Structure based virtual screening: Fast and slow
A Varela‐Rial, M Majewski, G De Fabritiis
Wiley Interdisciplinary Reviews: Computational Molecular Science 12 (2), e1544, 2022
362022
Machine learning coarse-grained potentials of protein thermodynamics
M Majewski, A Pérez, P Thölke, S Doerr, NE Charron, T Giorgino, ...
Nature communications 14 (1), 5739, 2023
342023
Structural stability predicts the binding mode of protein–ligand complexes
M Majewski, X Barril
Journal of Chemical Information and Modeling 60 (3), 1644-1651, 2020
142020
PlayMolecule glimpse: understanding protein–ligand property predictions with interpretable neural networks
A Varela-Rial, I Maryanow, M Majewski, S Doerr, N Schapin, ...
Journal of chemical information and modeling 62 (2), 225-231, 2022
132022
SkeleDock: a web application for scaffold docking in PlayMolecule
A Varela-Rial, M Majewski, A Cuzzolin, G Martínez-Rosell, G De Fabritiis
Journal of chemical information and modeling 60 (6), 2673-2677, 2020
92020
Fragment-to-lead tailored in silico design
M Rachman, S Piticchio, M Majewski, X Barril
Drug Discovery Today: Technologies 40, 44-57, 2021
82021
Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series
F Sabanés Zariquiey, A Pérez, M Majewski, E Gallicchio, G De Fabritiis
Journal of chemical information and modeling 63 (8), 2438-2444, 2023
72023
Dynamic undocking: a novel method for structure-based drug discovery
M Majewski, S Ruiz-Carmona, X Barril
Rational Drug Design: Methods and Protocols, 195-215, 2018
62018
Nucleotide-decorated AuNPs as probes for nucleotide-binding proteins
O Perzanowska, M Majewski, M Strenkowska, P Głowala, ...
Scientific Reports 11 (1), 15741, 2021
52021
Navigating protein landscapes with a machine-learned transferable coarse-grained model
NE Charron, F Musil, A Guljas, Y Chen, K Bonneau, AS Pasos-Trejo, ...
arXiv preprint arXiv:2310.18278, 2023
42023
Machine learning small molecule properties in drug discovery
N Schapin, M Majewski, A Varela-Rial, C Arroniz, G De Fabritiis
Artificial Intelligence Chemistry, 100020, 2023
42023
Top-down machine learning of coarse-grained protein force fields
C Navarro, M Majewski, G De Fabritiis
Journal of Chemical Theory and Computation 19 (21), 7518-7526, 2023
32023
AceGen: A TorchRL-based toolkit for reinforcement learning in generative chemistry
A Bou, M Thomas, S Dittert, CN Ramírez, M Majewski, Y Wang, S Patel, ...
ICLR 2024 Workshop on Generative and Experimental Perspectives for …, 0
2*
Implications of Structural Stability for Drug Design
M Majewski
Universitat de Barcelona, 2020
2020
Supplementary Information SkeleDock: A Web Application for Scaffold Docking in PlayMolecule
A Varela-Rial, M Majewski, A Cuzzolin, G Martınez-Rosell, G De Fabritiis
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