Zobrazeno 1 - 10
of 235
pro vyhledávání: '"Frank Noé"'
Autor:
Patrick Bryant, Frank Noé
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Proteins are dynamic molecules whose movements result in different conformations with different functions. Neural networks such as AlphaFold2 can predict the structure of single-chain proteins with conformations most likely to exist in the P
Externí odkaz:
https://doaj.org/article/26d9d0285df44aa2b0cb3c0eeaaa3966
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Protein-ligand docking is an established tool in drug discovery and development to narrow down potential therapeutics for experimental testing. However, a high-quality protein structure is required and often the protein is treated as fully o
Externí odkaz:
https://doaj.org/article/3e43b5cd6cf14369878e8dcfe1e4f995
Autor:
Patrick Bryant, Frank Noé
Publikováno v:
PLoS Computational Biology, Vol 20, Iss 7, p e1012253 (2024)
Structure prediction of protein complexes has improved significantly with AlphaFold2 and AlphaFold-multimer (AFM), but only 60% of dimers are accurately predicted. Here, we learn a bias to the MSA representation that improves the predictions by perfo
Externí odkaz:
https://doaj.org/article/65894245c1e047b0856b9c1ee653734a
Publikováno v:
Physical Review Research, Vol 6, Iss 4, p 043128 (2024)
Controlling the flow of energy and heat at the microscale is crucial to achieve energy-efficient quantum technologies, for on-chip thermal management, and to realize quantum heat engines and refrigerators. Yet, the efficiency of current quantum techn
Externí odkaz:
https://doaj.org/article/cbef8e06361742a78f00fdc5045053cf
Autor:
Maciej Majewski, Adrià Pérez, Philipp Thölke, Stefan Doerr, Nicholas E. Charron, Toni Giorgino, Brooke E. Husic, Cecilia Clementi, Frank Noé, Gianni De Fabritiis
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-13 (2023)
Abstract A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach
Externí odkaz:
https://doaj.org/article/7874019063c44680acebcb0eb6d2fbc6
Autor:
Daniëlle de Jong-Bolm, Mohsen Sadeghi, Cristian A Bogaciu, Guobin Bao, Gabriele Klaehn, Merle Hoff, Lucas Mittelmeier, F Buket Basmanav, Felipe Opazo, Frank Noé, Silvio O Rizzoli
Publikováno v:
PLoS Biology, Vol 21, Iss 12, p e3002427 (2023)
Multiplexed cellular imaging typically relies on the sequential application of detection probes, as antibodies or DNA barcodes, which is complex and time-consuming. To address this, we developed here protein nanobarcodes, composed of combinations of
Externí odkaz:
https://doaj.org/article/a0fe7e696f5542bd88b88b00a857d7ee
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022)
Modeling the dynamics of large proteins reveals a fundamental scaling problem. Here, the authors tackle this challenge by decomposing a large system into smaller independent subsystems, simultaneously modeling each subsystem’s kinetics and ensuring
Externí odkaz:
https://doaj.org/article/b3f2854b03e44df08778f18603f588c6
Autor:
Kalyan S. Chakrabarti, Simon Olsson, Supriya Pratihar, Karin Giller, Kerstin Overkamp, Ko On Lee, Vytautas Gapsys, Kyoung-Seok Ryu, Bert L. de Groot, Frank Noé, Stefan Becker, Donghan Lee, Thomas R. Weikl, Christian Griesinger
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022)
The authors provide a litmus test for the recognition mechanism of transiently binding proteins based on nuclear magnetic resonance and find a conformational selection binding mechanism through concentration-dependent kinetics of ubiquitin and SH3.
Externí odkaz:
https://doaj.org/article/e8ba332421814557b30a7a29637552f0
Publikováno v:
Physical Review Research, Vol 5, Iss 2, p L022017 (2023)
The full optimization of a quantum heat engine requires operating at high power, high efficiency, and high stability (i.e., low power fluctuations). However, these three objectives cannot be simultaneously optimized—as indicated by the so-called th
Externí odkaz:
https://doaj.org/article/0dd7537a5ada4994a6deb6170440c21b
Autor:
Paolo A. Erdman, Frank Noé
Publikováno v:
npj Quantum Information, Vol 8, Iss 1, Pp 1-11 (2022)
Abstract The optimal control of open quantum systems is a challenging task but has a key role in improving existing quantum information processing technologies. We introduce a general framework based on reinforcement learning to discover optimal ther
Externí odkaz:
https://doaj.org/article/cbf7e65018b84e138565ba241dff8564