Atsushi Tokuhisa
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Explore the profile of Atsushi Tokuhisa including associated specialties, affiliations and a list of published articles.
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15
Citations
57
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Recent Articles
1.
Waida H, Yamazaki K, Tokuhisa A, Wada M, Wada Y
Neural Netw
. 2024 Dec;
184:106966.
PMID: 39700824
Self-supervised learning for image denoising problems in the presence of denaturation for noisy data is a crucial approach in machine learning. However, theoretical understanding of the performance of the approach...
2.
Kanada R, Tokuhisa A, Nagasaka Y, Okuno S, Amemiya K, Chiba S, et al.
J Chem Theory Comput
. 2023 Dec;
20(1):7-17.
PMID: 38148034
In all-atom (AA) molecular dynamics (MD) simulations, the rugged energy profile of the force field makes it challenging to reproduce spontaneous structural changes in biomolecules within a reasonable calculation time....
3.
Tokuhisa A, Akinaga Y, Terayama K, Okamoto Y, Okuno Y
J Chem Inf Model
. 2022 Jul;
62(14):3352-3364.
PMID: 35820663
Femtosecond X-ray pulse lasers are promising probes for the elucidation of the multiconformational states of biomolecules because they enable snapshots of single biomolecules to be observed as coherent diffraction images....
4.
Takaba K, Watanabe C, Tokuhisa A, Akinaga Y, Ma B, Kanada R, et al.
J Comput Chem
. 2022 Jun;
43(20):1362-1371.
PMID: 35678372
Fragment molecular orbital (FMO) method is a powerful computational tool for structure-based drug design, in which protein-ligand interactions can be described by the inter-fragment interaction energy (IFIE) and its pair...
5.
Kanada R, Terayama K, Tokuhisa A, Matsumoto S, Okuno Y
J Chem Theory Comput
. 2022 Mar;
18(4):2062-2074.
PMID: 35325529
Compared to all-atom molecular dynamics (AA-MD) simulations, coarse-grained (CG) MD simulations can significantly reduce calculation costs. However, existing CG-MD methods are unsuitable for sampling structures that depart significantly from the...
6.
Miyaguchi I, Sato M, Kashima A, Nakagawa H, Kokabu Y, Ma B, et al.
Sci Rep
. 2021 Dec;
11(1):23599.
PMID: 34880321
Low-resolution electron density maps can pose a major obstacle in the determination and use of protein structures. Herein, we describe a novel method, called quality assessment based on an electron...
7.
Kato K, Masuda T, Watanabe C, Miyagawa N, Mizouchi H, Nagase S, et al.
J Chem Inf Model
. 2020 Jun;
60(7):3361-3368.
PMID: 32496771
Here, we have constructed neural network-based models that predict atomic partial charges with high accuracy at low computational cost. The models were trained using high-quality data acquired from quantum mechanics...
8.
Tokuhisa A, Kanada R, Chiba S, Terayama K, Isaka Y, Ma B, et al.
J Chem Inf Model
. 2020 May;
60(6):2803-2818.
PMID: 32469517
Biomolecular imaging using X-ray free-electron lasers (XFELs) has been successfully applied to serial femtosecond crystallography. However, the application of single-particle analysis for structure determination using XFELs with 100 nm or...
9.
Kanada R, Tokuhisa A, Tsuda K, Okuno Y, Terayama K
Biomolecules
. 2020 Apr;
10(3).
PMID: 32245275
Accompanied with an increase of revealed biomolecular structures owing to advancements in structural biology, the molecular dynamics (MD) approach, especially coarse-grained (CG) MD suitable for macromolecules, is becoming increasingly important...
10.
Tokuhisa A
Biophys Physicobiol
. 2020 Jan;
16:430-443.
PMID: 31984195
An attainable structural resolution of single particle imaging is determined by the characteristics of X-ray diffraction intensity, which depend on the incident X-ray intensity density and molecule size. To estimate...