Fast parameterized methods such as density-functional tight-binding (DFTB) facilitate realistic calculations of large molecular systems, which can be accelerated by the fragment molecular orbital (FMO) method. Fragmentation facilitates interaction analyses between functional parts of molecular systems. In addition to DFTB, other parameterized methods combined with FMO are also described. Applications of FMO methods to biochemical and inorganic systems are reviewed.

1.
R. A.
Shaw
and
J. G.
Hill
, “
A linear-scaling method for noncovalent interactions: An efficient combination of absolutely localized molecular orbitals and a local random phase approximation approach
,”
J. Chem. Theory Comput.
15
,
5352
5369
(
2019
).
2.
L. O.
Jones
,
M. A.
Mosquera
,
G. C.
Schatz
, and
M. A.
Ratner
, “
Embedding methods for quantum chemistry: Applications from materials to life sciences
,”
J. Am. Chem. Soc.
142
,
3281
3295
(
2020
).
3.
M. S.
Gordon
,
D. G.
Fedorov
,
S. R.
Pruitt
, and
L. V.
Slipchenko
, “
Fragmentation methods: A route to accurate calculations on large systems
,”
Chem. Rev.
112
,
632
672
(
2012
).
4.
A. D.
Becke
, “
Perspective: Fifty years of density-functional theory in chemical physics
,”
J. Chem. Phys.
140
,
18A301
(
2014
).
5.
As of November 24, 2022, https://scholar.google.com/ produced 13 900 hits for “ab initio DFT,” 50 hits for “ab initio DFT,” 673 hits for “semi-empirical DFT,” 771 hits for “semiempirical DFT,” 3 hits for “semi-empiric DFT,” and 3 hits for “semiempiric DFT.” Exit vox populi.
6.
Y.
Xu
,
R.
Friedman
,
W.
Wu
, and
P.
Su
, “
Understanding intermolecular interactions of large systems in ground state and excited state by using density functional based tight binding methods
,”
J. Chem. Phys.
154
,
194106
(
2021
).
7.
P.
Otto
and
J.
Ladik
, “
Investigation of the interaction between molecules at medium distances: I. SCF LCAO MO supermolecule, perturbational and mutually consistent calculations for two interacting HF and CH2O molecules
,”
Chem. Phys.
8
,
192
200
(
1975
).
8.
J.
Gao
, “
Toward a molecular orbital derived empirical potential for liquid simulations
,”
J. Phys. Chem. B
101
,
657
663
(
1997
).
9.
N.
Komoto
,
T.
Yoshikawa
,
Y.
Nishimura
, and
H.
Nakai
, “
Large-scale molecular dynamics simulation for ground and excited states based on divide-and-conquer long-range corrected density-functional tight-binding method
,”
J. Chem. Theory Comput.
16
,
2369
2378
(
2020
).
10.
B.
Thapa
and
K.
Raghavachari
, “
Energy decomposition analysis of protein–ligand interactions using molecules-in-molecules fragmentation-based method
,”
J. Chem. Inf. Model.
59
,
3474
3484
(
2019
).
11.
K.-Y.
Liu
and
J. M.
Herbert
, “
Energy-screened many-body expansion: A practical yet accurate fragmentation method for quantum chemistry
,”
J. Chem. Theory Comput.
16
,
475
487
(
2020
).
12.
T.
Fang
,
Y.
Li
, and
S.
Li
, “
Generalized energy-based fragmentation approach for modeling condensed phase systems
,”
Wiley Interdiscip. Rev.: Comput. Mol. Sci.
7
,
e1297
(
2017
).
13.
Y.
Kim
,
Y.
Bui
,
R. N.
Tazhigulov
,
K. B.
Bravaya
, and
L. V.
Slipchenko
, “
Effective fragment potentials for flexible molecules: Transferability of parameters and amino acid database
,”
J. Chem. Theory Comput.
16
,
7735
7747
(
2020
).
14.
U.
Bozkaya
and
B.
Ermiş
, “
Linear-scaling systematic molecular fragmentation approach for perturbation theory and coupled-cluster methods
,”
J. Chem. Theory Comput.
18
,
5349
5359
(
2022
).
15.
K.
Kitaura
,
E.
Ikeo
,
T.
Asada
,
T.
Nakano
, and
M.
Uebayasi
, “
Fragment molecular orbital method: An approximate computational method for large molecules
,”
Chem. Phys. Lett.
313
,
701
706
(
1999
).
16.
D. G.
Fedorov
, “
The fragment molecular orbital method: Theoretical development, implementation in GAMESS, and applications
,”
Wiley Interdiscip. Rev.: Comput. Mol. Sci.
7
,
e1322
(
2017
).
17.
Recent Advances of the Fragment Molecular Orbital Method
, edited by
Y.
Mochizuki
,
S.
Tanaka
, and
K.
Fukuzawa
(
Springer
,
Singapore
,
2021
).
18.
K.
Fukuzawa
and
S.
Tanaka
, “
Fragment molecular orbital calculations for biomolecules
,”
Curr. Opin. Struct. Biol.
72
,
127
134
(
2022
).
19.
D. G.
Fedorov
and
K.
Kitaura
, “
The importance of three-body terms in the fragment molecular orbital method
,”
J. Chem. Phys.
120
,
6832
6840
(
2004
).
20.
T.
Nakano
,
Y.
Mochizuki
,
K.
Yamashita
,
C.
Watanabe
,
K.
Fukuzawa
,
K.
Segawa
,
Y.
Okiyama
,
T.
Tsukamoto
, and
S.
Tanaka
, “
Development of the four-body corrected fragment molecular orbital (FMO4) method
,”
Chem. Phys. Lett.
523
,
128
133
(
2012
).
21.
D. G.
Fedorov
,
N.
Asada
,
I.
Nakanishi
, and
K.
Kitaura
, “
The use of many-body expansions and geometry optimizations in fragment-based methods
,”
Acc. Chem. Res.
47
,
2846
2856
(
2014
).
22.
S. P.
Veccham
,
J.
Lee
, and
M.
Head-Gordon
, “
Making many-body interactions nearly pairwise additive: The polarized many-body expansion approach
,”
J. Chem. Phys.
151
,
194101
(
2019
).
23.
T.
Ishikawa
, “
Ab initio quantum chemical calculation of electron density, electrostatic potential, and electric field of biomolecule based on fragment molecular orbital method
,”
Int. J. Quantum Chem.
118
,
e25535
(
2018
).
24.
D. G.
Fedorov
, “
Electron density from the fragment molecular orbital method combined with density-functional tight-binding
,”
Chem. Phys. Lett.
780
,
138900
(
2021
).
25.
S.
Tsuneyuki
,
T.
Kobori
,
K.
Akagi
,
K.
Sodeyama
,
K.
Terakura
, and
H.
Fukuyama
, “
Molecular orbital calculation of biomolecules with fragment molecular orbitals
,”
Chem. Phys. Lett.
476
,
104
108
(
2009
).
26.
D. G.
Fedorov
and
K.
Kitaura
, “
Many-body expansion of the Fock matrix in the fragment molecular orbital method
,”
J. Chem. Phys.
147
,
104106
(
2017
).
27.
T.
Watanabe
,
Y.
Inadomi
,
H.
Umeda
,
K.
Fukuzawa
,
S.
Tanaka
,
T.
Nakano
, and
U.
Nagashima
, “
Fragment molecular orbital (FMO) and FMO-MO calculations of DNA: Accuracy validation of energy and interfragment interaction energy
,”
J. Comput. Theor. Nanosci.
6
,
1328
1337
(
2009
).
28.
D. G.
Fedorov
, “
Partition analysis for density-functional tight-binding
,”
J. Phys. Chem. A
124
,
10346
10358
(
2020
).
29.
T.
Nakano
,
T.
Kaminuma
,
T.
Sato
,
Y.
Akiyama
,
M.
Uebayasi
, and
K.
Kitaura
, “
Fragment molecular orbital method: Application to polypeptides
,”
Chem. Phys. Lett.
318
,
614
618
(
2000
).
30.
D. G.
Fedorov
,
J. H.
Jensen
,
R. C.
Deka
, and
K.
Kitaura
, “
Covalent bond fragmentation suitable to describe solids in the fragment molecular orbital method
,”
J. Phys. Chem. A
112
,
11808
11816
(
2008
).
31.
Y.
Nishimoto
and
D. G.
Fedorov
, “
Adaptive frozen orbital treatment for the fragment molecular orbital method combined with density-functional tight-binding
,”
J. Chem. Phys.
148
,
064115
(
2018
).
32.
Y.
Komeiji
,
Y.
Inadomi
, and
T.
Nakano
, “
PEACH 4 with ABINIT-MP: A general platform for classical and quantum simulations of biological molecules
,”
Comput. Biol. Chem.
28
,
155
161
(
2004
).
33.
G. M. J.
Barca
,
C.
Bertoni
,
L.
Carrington
,
D.
Datta
,
N.
De Silva
,
J. E.
Deustua
,
D. G.
Fedorov
,
J. R.
Gour
,
A. O.
Gunina
,
E.
Guidez
,
T.
Harville
,
S.
Irle
,
J.
Ivanic
,
K.
Kowalski
,
S. S.
Leang
,
H.
Li
,
W.
Li
,
J. J.
Lutz
,
I.
Magoulas
,
J.
Mato
,
V.
Mironov
,
H.
Nakata
,
B. Q.
Pham
,
P.
Piecuch
,
D.
Poole
,
S. R.
Pruitt
,
A. P.
Rendell
,
L. B.
Roskop
,
K.
Ruedenberg
,
T.
Sattasathuchana
,
M. W.
Schmidt
,
J.
Shen
,
L.
Slipchenko
,
M.
Sosonkina
,
V.
Sundriyal
,
A.
Tiwari
,
J. L.
Galvez Vallejo
,
B.
Westheimer
,
M.
Włoch
,
P.
Xu
,
F.
Zahariev
, and
M. S.
Gordon
, “
Recent developments in the general atomic and molecular electronic structure system
,”
J. Chem. Phys.
152
,
154102
(
2020
).
34.
D. G.
Fedorov
,
R. M.
Olson
,
K.
Kitaura
,
M. S.
Gordon
, and
S.
Koseki
, “
A new hierarchical parallelization scheme: Generalized distributed data interface (GDDI), and an application to the fragment molecular orbital method (FMO)
,”
J. Comput. Chem.
25
,
872
880
(
2004
).
35.
S. R.
Pruitt
,
H.
Nakata
,
T.
Nagata
,
M.
Mayes
,
Y.
Alexeev
,
G.
Fletcher
,
D. G.
Fedorov
,
K.
Kitaura
, and
M. S.
Gordon
, “
Importance of three-body interactions in molecular dynamics simulations of water demonstrated with the fragment molecular orbital method
,”
J. Chem. Theory Comput.
12
,
1423
1435
(
2016
).
36.
J. C.
Kromann
,
A. S.
Christensen
,
C.
Steinmann
,
M.
Korth
, and
J. H.
Jensen
, “
A third-generation dispersion and third-generation hydrogen bonding corrected PM6 method: PM6-D3H+
,”
PeerJ
2
,
e449
(
2014
).
37.
M.
Gaus
,
Q.
Cui
, and
M.
Elstner
, “
DFTB3: Extension of the self-consistent-charge density-functional tight-binding method (SCCDFTB)
,”
J. Chem. Theory Comput.
7
,
931
948
(
2011
).
38.
M.
Gaus
,
Q.
Cui
, and
M.
Elstner
, “
Density functional tight binding: Application to organic and biological molecules
,”
Wiley Interdiscip. Rev.: Comput. Mol. Sci.
4
,
49
61
(
2014
).
39.
T. J.
Giese
,
H.
Chen
,
T.
Dissanayake
,
G. M.
Giambaşu
,
H.
Heldenbrand
,
M.
Huang
,
E. R.
Kuechler
,
T.-S.
Lee
,
M. T.
Panteva
,
B. K.
Radak
, and
D. M.
York
, “
A variational linear-scaling framework to build practical, efficient next-generation orbital-based quantum force fields
,”
J. Chem. Theory Comput.
9
,
1417
1427
(
2013
).
40.
Y.
Nishimoto
,
D. G.
Fedorov
, and
S.
Irle
, “
Density-functional tight-binding combined with the fragment molecular orbital method
,”
J. Chem. Theory Comput.
10
,
4801
4812
(
2014
).
41.
Y.
Nishimoto
,
D. G.
Fedorov
, and
S.
Irle
, “
Third-order density-functional tight-binding combined with the fragment molecular orbital method
,”
Chem. Phys. Lett.
636
,
90
96
(
2015
).
42.
V. Q.
Vuong
,
Y.
Nishimoto
,
D. G.
Fedorov
,
B. G.
Sumpter
,
T. A.
Niehaus
, and
S.
Irle
, “
The fragment molecular orbital method based on long-range corrected density-functional tight-binding
,”
J. Chem. Theory Comput.
15
,
3008
3020
(
2019
).
43.
M. T. d. N.
Varella
,
L.
Stojanović
,
V. Q.
Vuong
,
S.
Irle
,
T. A.
Niehaus
, and
M.
Barbatti
, “
How the size and density of charge-transfer excitons depend on heterojunction’s architecture
,”
J. Phys. Chem. C
125
,
5458
5474
(
2021
).
44.
Y.
Nishimoto
and
D. G.
Fedorov
, “
Three-body expansion of the fragment molecular orbital method combined with density-functional tight-binding
,”
J. Comput. Chem.
38
,
406
418
(
2017
).
45.
C.
Bannwarth
,
E.
Caldeweyher
,
S.
Ehlert
,
A.
Hansen
,
P.
Pracht
,
J.
Seibert
,
S.
Spicher
, and
S.
Grimme
, “
Extended tight-binding quantum chemistry methods
,”
Wiley Interdiscip. Rev.: Comput. Mol. Sci.
11
,
e1493
(
2021
).
46.
N.
Goldman
,
S.
Goverapet Srinivasan
,
S.
Hamel
,
L. E.
Fried
,
M.
Gaus
, and
M.
Elstner
, “
Determination of a density functional tight binding model with an extended basis set and three-body repulsion for carbon under extreme pressures and temperatures
,”
J. Phys. Chem. C
117
,
7885
7894
(
2013
).
47.
Z.
Bodrog
and
B.
Aradi
, “
Possible improvements to the self-consistent-charges density-functional tight-binding method within the second order
,”
Phys. Status Solidi B
249
,
259
269
(
2012
).
48.
C.
Köhler
,
G.
Seifert
,
U.
Gerstmann
,
M.
Elstner
,
H.
Overhof
, and
T.
Frauenheim
, “
Approximate density-functional calculations of spin densities in large molecular systems and complex solids
,”
Phys. Chem. Chem. Phys.
3
,
5109
5114
(
2001
).
49.
F.
Trani
,
G.
Scalmani
,
G.
Zheng
,
I.
Carnimeo
,
M. J.
Frisch
, and
V.
Barone
, “
Time-dependent density functional tight binding: New formulation and benchmark of excited states
,”
J. Chem. Theory Comput.
7
,
3304
3313
(
2011
).
50.
Y.
Nishimoto
and
D. G.
Fedorov
, “
The fragment molecular orbital method combined with density-functional tight-binding and periodic boundary conditions
,”
J. Chem. Phys.
154
,
111102
(
2021
).
51.
T.
Nagata
,
K.
Brorsen
,
D. G.
Fedorov
,
K.
Kitaura
, and
M. S.
Gordon
, “
Fully analytic energy gradient in the fragment molecular orbital method
,”
J. Chem. Phys.
134
,
124115
(
2011
).
52.
H.
Nakata
,
Y.
Nishimoto
, and
D. G.
Fedorov
, “
Analytic second derivative of the energy for density-functional tight-binding combined with the fragment molecular orbital method
,”
J. Chem. Phys.
145
,
044113
(
2016
).
53.
Y.
Nishimoto
,
H.
Nakata
,
D. G.
Fedorov
, and
S.
Irle
, “
Large-scale quantum-mechanical molecular dynamics simulations using density-functional tight-binding combined with the fragment molecular orbital method
,”
J. Phys. Chem. Lett.
6
,
5034
5039
(
2015
).
54.
T.
Nakano
,
T.
Kaminuma
,
T.
Sato
,
K.
Fukuzawa
,
Y.
Akiyama
,
M.
Uebayasi
, and
K.
Kitaura
, “
Fragment molecular orbital method: Use of approximate electrostatic potential
,”
Chem. Phys. Lett.
351
,
475
480
(
2002
).
55.
D. G.
Fedorov
,
K.
Kitaura
,
H.
Li
,
J. H.
Jensen
, and
M. S.
Gordon
, “
The polarizable continuum model (PCM) interfaced with the fragment molecular orbital method (FMO)
,”
J. Comput. Chem.
27
,
976
985
(
2006
).
56.
H.
Nakata
and
D. G.
Fedorov
, “
Simulations of infrared and Raman spectra in solution using the fragment molecular orbital method
,”
Phys. Chem. Chem. Phys.
21
,
13641
13652
(
2019
).
57.
Y.
Nishimoto
and
D. G.
Fedorov
, “
The fragment molecular orbital method combined with density-functional tight-binding and the polarizable continuum model
,”
Phys. Chem. Chem. Phys.
18
,
22047
22061
(
2016
).
58.
D. G.
Fedorov
, “
Analysis of solute-solvent interactions using the solvation model density combined with the fragment molecular orbital method
,”
Chem. Phys. Lett.
702
,
111
116
(
2018
).
59.
C.
Friedl
,
D. G.
Fedorov
, and
T.
Renger
, “
Towards a quantitative description of excitonic couplings in photosynthetic pigment–protein complexes: Quantum chemistry driven multiscale approaches
,”
Phys. Chem. Chem. Phys.
24
,
5014
5038
(
2022
).
60.
D. G.
Fedorov
and
K.
Kitaura
, “
Energy decomposition analysis in solution based on the fragment molecular orbital method
,”
J. Phys. Chem. A
116
,
704
719
(
2012
).
61.
Y.
Okiyama
,
C.
Watanabe
,
K.
Fukuzawa
,
Y.
Mochizuki
,
T.
Nakano
, and
S.
Tanaka
, “
Fragment molecular orbital calculations with implicit solvent based on the Poisson–Boltzmann equation: II. Protein and its ligand-binding system studies
,”
J. Phys. Chem. B
123
,
957
973
(
2019
).
62.
D. G.
Fedorov
, “
Solvent screening in zwitterions analyzed with the fragment molecular orbital method
,”
J. Chem. Theory Comput.
15
,
5404
5416
(
2019
).
63.
Y.
Xu
,
S.
Zhang
,
E.
Lindahl
,
R.
Friedman
,
W.
Wu
, and
P.
Su
, “
A general tight-binding based energy decomposition analysis scheme for intermolecular interactions in large molecules
,”
J. Chem. Phys.
157
,
034104
(
2022
).
64.
R. M.
Parrish
and
C. D.
Sherrill
, “
Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition
,”
J. Chem. Phys.
141
,
044115
(
2014
).
65.
P.
Su
and
H.
Li
, “
Energy decomposition analysis of covalent bonds and intermolecular interactions
,”
J. Chem. Phys.
131
,
014102
(
2009
).
66.
Q.
Ge
,
Y.
Mao
, and
M.
Head-Gordon
, “
Energy decomposition analysis for exciplexes using absolutely localized molecular orbitals
,”
J. Chem. Phys.
148
,
064105
(
2018
).
67.
K.
Hengphasatporn
,
P.
Wilasluck
,
P.
Deetanya
,
K.
Wangkanont
,
W.
Chavasiri
,
P.
Visitchanakun
,
A.
Leelahavanichkul
,
W.
Paunrat
,
S.
Boonyasuppayakorn
,
T.
Rungrotmongkol
,
S.
Hannongbua
, and
Y.
Shigeta
, “
Halogenated baicalein as a promising antiviral agent toward SARS-CoV-2 main protease
,”
J. Chem. Inf. Model.
62
,
1498
1509
(
2022
).
68.
H.
Nakata
,
D. G.
Fedorov
,
T.
Nagata
,
K.
Kitaura
, and
S.
Nakamura
, “
Simulations of chemical reactions with the frozen domain formulation of the fragment molecular orbital method
,”
J. Chem. Theory Comput.
11
,
3053
3064
(
2015
).
69.
K. A.
Kistler
and
S.
Matsika
, “
Solvatochromic shifts of uracil and cytosine using a combined multireference configuration interaction/molecular dynamics approach and the fragment molecular orbital method
,”
J. Phys. Chem. A
113
,
12396
12403
(
2009
).
70.
D. G.
Fedorov
and
K.
Kitaura
, “
Pair interaction energy decomposition analysis
,”
J. Comput. Chem.
28
,
222
237
(
2007
).
71.
D. G.
Fedorov
and
K.
Kitaura
, “
Pair interaction energy decomposition analysis for density functional theory and density-functional tight-binding with an evaluation of energy fluctuations in molecular dynamics
,”
J. Phys. Chem. A
122
,
1781
1795
(
2018
).
72.
D. G.
Fedorov
, “
Three-body energy decomposition analysis based on the fragment molecular orbital method
,”
J. Phys. Chem. A
124
,
4956
4971
(
2020
).
73.
A. K.
Das
,
L.
Urban
,
I.
Leven
,
M.
Loipersberger
,
A.
Aldossary
,
M.
Head-Gordon
, and
T.
Head-Gordon
, “
Development of an advanced force field for water using variational energy decomposition analysis
,”
J. Chem. Theory Comput.
15
,
5001
5013
(
2019
).
74.
S.
Naseem-Khan
,
N.
Gresh
,
A. J.
Misquitta
, and
J.-P.
Piquemal
, “
Assessment of SAPT and supermolecular EDA approaches for the development of separable and polarizable force fields
,”
J. Chem. Theory Comput.
17
,
2759
2774
(
2021
).
75.
D. G.
Fedorov
, “
Polarization energies in the fragment molecular orbital method
,”
J. Comput. Chem.
43
,
1094
1103
(
2022
).
76.
K.
Kitaura
and
K.
Morokuma
, “
A new energy decomposition scheme for molecular interactions within the Hartree-Fock approximation
,”
Int. J. Quantum Chem.
10
,
325
340
(
1976
).
77.
W.
Chen
and
M. S.
Gordon
, “
Energy decomposition analyses for many-body interaction and applications to water complexes
,”
J. Phys. Chem.
100
,
14316
14328
(
1996
).
78.
V.
Sladek
and
D. G.
Fedorov
, “
The importance of charge transfer and solvent screening in the interactions of backbones and functional groups in amino acid residues and nucleotides
,”
Int. J. Mol. Sci.
23
,
13514
(
2022
).
79.
D. G.
Fedorov
and
K.
Kitaura
, “
Subsystem analysis for the fragment molecular orbital method and its application to protein–ligand binding in solution
,”
J. Phys. Chem. A
120
,
2218
2231
(
2016
).
80.
D. G.
Fedorov
and
T.
Nakamura
, “
Free energy decomposition analysis based on the fragment molecular orbital method
,”
J. Phys. Chem. Lett.
13
,
1596
1601
(
2022
).
81.
D. G.
Fedorov
, “
Partitioning of the vibrational free energy
,”
J. Phys. Chem. Lett.
12
,
6628
6633
(
2021
).
82.
A. L. P.
Nguyen
,
T. G.
Mason
,
B. D.
Freeman
, and
E. I.
Izgorodina
, “
Prediction of lattice energy of benzene crystals: A robust theoretical approach
,”
J. Comput. Chem.
42
,
248
260
(
2021
).
83.
H.
Yamada
,
Y.
Mochizuki
,
K.
Fukuzawa
,
Y.
Okiyama
, and
Y.
Komeiji
, “
Fragment molecular orbital (FMO) calculations on DNA by a scaled third-order Møller-Plesset perturbation (MP2.5) scheme
,”
Comput. Theor. Chem.
1101
,
46
54
(
2017
).
84.
R.
Sure
and
S.
Grimme
, “
Corrected small basis set Hartree-Fock method for large systems
,”
J. Comput. Chem.
34
,
1672
1685
(
2013
).
85.
D. G.
Fedorov
,
J. C.
Kromann
, and
J. H.
Jensen
, “
Empirical corrections and pair interaction energies in the fragment molecular orbital method
,”
Chem. Phys. Lett.
706
,
328
333
(
2018
).
86.
S.
Grimme
,
S.
Ehrlich
, and
L.
Goerigk
, “
Effect of the damping function in dispersion corrected density functional theory
,”
J. Comput. Chem.
32
,
1456
1465
(
2011
).
87.
H.
Nakata
,
D. G.
Fedorov
,
S.
Yokojima
,
K.
Kitaura
, and
S.
Nakamura
, “
Simulations of Raman spectra using the fragment molecular orbital method
,”
J. Chem. Theory Comput.
10
,
3689
3698
(
2014
).
88.
D. G.
Fedorov
,
T.
Ishida
,
M.
Uebayasi
, and
K.
Kitaura
, “
The fragment molecular orbital method for geometry optimizations of polypeptides and proteins
,”
J. Phys. Chem. A
111
,
2722
2732
(
2007
).
89.
H.
Nakata
and
D. G.
Fedorov
, “
Analytic first and second derivatives of the energy in the fragment molecular orbital method combined with molecular mechanics
,”
Int. J. Quantum Chem.
120
,
e26414
(
2020
).
90.
K.
Kříž
and
J.
Řezáč
, “
Benchmarking of semiempirical quantum-mechanical methods on systems relevant to computer-aided drug design
,”
J. Chem. Inf. Model.
60
,
1453
1460
(
2020
).
91.
I.
Morao
,
D. G.
Fedorov
,
R.
Robinson
,
M.
Southey
,
A.
Townsend-Nicholson
,
M. J.
Bodkin
, and
A.
Heifetz
, “
Rapid and accurate assessment of GPCR–ligand interactions using the fragment molecular orbital-based density-functional tight-binding method
,”
J. Comput. Chem.
38
,
1987
1990
(
2017
).
92.
R.
González
,
C. F.
Suárez
,
H. J.
Bohórquez
,
M. A.
Patarroyo
, and
M. E.
Patarroyo
, “
Semi-empirical quantum evaluation of peptide—MHC class II binding
,”
Chem. Phys. Lett.
668
,
29
34
(
2017
).
93.
C. A.
Ortiz-Mahecha
,
H. J.
Bohórquez
,
W. A.
Agudelo
,
M. A.
Patarroyo
,
M. E.
Patarroyo
, and
C. F.
Suárez
, “
Assessing peptide binding to MHC II: An accurate semiempirical quantum mechanics based proposal
,”
J. Chem. Inf. Model.
59
,
5148
5160
(
2019
).
94.
S.
Monteleone
,
D. G.
Fedorov
,
A.
Townsend-Nicholson
,
M.
Southey
,
M.
Bodkin
, and
A.
Heifetz
, “
Hotspot identification and drug design of protein–protein interaction modulators using the fragment molecular orbital method
,”
J. Chem. Inf. Model.
62
,
3784
3799
(
2022
).
95.
N.
Okimoto
,
T.
Otsuka
,
Y.
Hirano
, and
M.
Taiji
, “
Use of the multilayer fragment molecular orbital method to predict the rank order of protein–ligand binding affinities: A case study using tankyrase 2 inhibitors
,”
ACS Omega
3
,
4475
4485
(
2018
).
96.
T.
Nakamura
,
T.
Yokaichiya
, and
D. G.
Fedorov
, “
Quantum-mechanical structure optimization of protein crystals and analysis of interactions in periodic systems
,”
J. Phys. Chem. Lett.
12
,
8757
8762
(
2021
).
97.
See www.dftb.org for DFTB homepage.
98.
M.
Gaus
,
A.
Goez
, and
M.
Elstner
, “
Parametrization and benchmark of DFTB3 for organic molecules
,”
J. Chem. Theory Comput.
9
,
338
354
(
2013
).
99.
M.
Suenaga
, “
Development of GUI for GAMESS/FMO calculation
,”
J. Comput. Chem., Jpn.
7
,
33
54
(
2008
).
100.
O. S.
Kolovskaya
,
T. N.
Zamay
,
G. S.
Zamay
,
V. A.
Babkin
,
E. N.
Medvedeva
,
N. A.
Neverova
,
A. K.
Kirichenko
,
S. S.
Zamay
,
I. N.
Lapin
,
E. V.
Morozov
,
A. E.
Sokolov
,
A. A.
Narodov
,
D. G.
Fedorov
,
F. N.
Tomilin
,
V. N.
Zabluda
,
Y.
Alekhina
,
K. A.
Lukyanenko
,
Y. E.
Glazyrin
,
V. A.
Svetlichnyi
,
M. V.
Berezovski
, and
A. S.
Kichkailo
, “
Aptamer-conjugated superparamagnetic ferroarabinogalactan nanoparticles for targeted magnetodynamic therapy of cancer
,”
Cancers
12
,
216
(
2020
).
101.
D.
Morozov
,
V.
Mironov
,
R. V.
Moryachkov
,
I. A.
Shchugoreva
,
P. V.
Artyushenko
,
G. S.
Zamay
,
O. S.
Kolovskaya
,
T. N.
Zamay
,
A. V.
Krat
,
D. S.
Molodenskiy
,
V. N.
Zabluda
,
D. V.
Veprintsev
,
A. E.
Sokolov
,
R. A.
Zukov
,
M. V.
Berezovski
,
F. N.
Tomilin
,
D. G.
Fedorov
,
Y.
Alexeev
, and
A. S.
Kichkailo
, “
The role of SAXS and molecular simulations in 3D structure elucidation of a DNA aptamer against lung cancer
,”
Mol. Ther.–Nucleic Acids
25
,
316
327
(
2021
).
102.
V.
Mironov
,
I. A.
Shchugoreva
,
P. V.
Artyushenko
,
D.
Morozov
,
N.
Borbone
,
G.
Oliviero
,
T. N.
Zamay
,
R. V.
Moryachkov
,
O. S.
Kolovskaya
,
K. A.
Lukyanenko
,
Y.
Song
,
I. A.
Merkuleva
,
V. N.
Zabluda
,
G.
Peters
,
L. S.
Koroleva
,
D. V.
Veprintsev
,
Y. E.
Glazyrin
,
E. A.
Volosnikova
,
S. V.
Belenkaya
,
T. I.
Esina
,
A. A.
Isaeva
,
V. S.
Nesmeyanova
,
D. V.
Shanshin
,
A. N.
Berlina
,
N. S.
Komova
,
V. A.
Svetlichnyi
,
V. N.
Silnikov
,
D. N.
Shcherbakov
,
G. S.
Zamay
,
S. S.
Zamay
,
T.
Smolyarova
,
E. P.
Tikhonova
,
K. H.
Chen
,
U. S.
Jeng
,
G.
Condorelli
,
V.
de Franciscis
,
G.
Groenhof
,
C.
Yang
,
A. A.
Moskovsky
,
D. G.
Fedorov
,
F. N.
Tomilin
,
W.
Tan
,
Y.
Alexeev
,
M. V.
Berezovski
, and
A. S.
Kichkailo
, “
Structure- and interaction-based design of anti-SARS-CoV-2 aptamers
,”
Chem. - Eur. J.
28
,
e202104481
(
2022
).
103.
F. N.
Tomilin
,
A. V.
Rogova
,
L. P.
Burakova
,
O. N.
Tchaikovskaya
,
P. V.
Avramov
,
D. G.
Fedorov
, and
E. S.
Vysotski
, “
Unusual shift in the visible absorption spectrum of an active ctenophore photoprotein elucidated by time-dependent density functional theory
,”
Photochem. Photobiol. Sci.
20
,
559
570
(
2021
).
104.
A. V.
Ozerskaya
,
T. N.
Zamay
,
O. S.
Kolovskaya
,
N. A.
Tokarev
,
K. V.
Belugin
,
N. G.
Chanchikova
,
O. N.
Badmaev
,
G. S.
Zamay
,
I. A.
Shchugoreva
,
R. V.
Moryachkov
,
V. N.
Zabluda
,
V. A.
Khorzhevskii
,
N.
Shepelevich
,
S. V.
Gappoev
,
E. A.
Karlova
,
A. S.
Saveleva
,
A. A.
Volzhentsev
,
A. N.
Blagodatova
,
K. A.
Lukyanenko
,
D. V.
Veprintsev
,
T. E.
Smolyarova
,
F. N.
Tomilin
,
S. S.
Zamay
,
V. N.
Silnikov
,
M. V.
Berezovski
, and
A. S.
Kichkailo
, “
11C-radiolabeled aptamer for imaging of tumors and metastases using positron emission tomography-computed tomography
,”
Mol. Ther.–Nucleic Acids
26
,
1159
1172
(
2021
).
105.
R.
González
and
M. A.
Mroginski
, “
Fully quantum chemical treatment of chromophore–protein interactions in phytochromes
,”
J. Phys. Chem. B
123
,
9819
9830
(
2019
).
106.
M. A.
Hameedi
,
E. T.
Prates
,
M. R.
Garvin
,
I. I.
Mathews
,
B. K.
Amos
,
O.
Demerdash
,
M.
Bechthold
,
M.
Iyer
,
S.
Rahighi
,
D. W.
Kneller
,
A.
Kovalevsky
,
S.
Irle
,
V.-Q.
Vuong
,
J. C.
Mitchell
,
A.
Labbe
,
S.
Galanie
,
S.
Wakatsuki
, and
D.
Jacobson
, “
Structural and functional characterization of NEMO cleavage by SARS-CoV-2 3CLpro
,”
Nat. Commun.
13
,
5285
(
2022
).
107.
H.
Lim
,
A.
Baek
,
J.
Kim
,
M. S.
Kim
,
J.
Liu
,
K.-Y.
Nam
,
J.
Yoon
, and
K. T.
No
, “
Hot spot profiles of SARS-CoV-2 and human ACE2 receptor protein protein interaction obtained by density functional tight binding fragment molecular orbital method
,”
Sci. Rep.
10
,
16862
(
2020
).
108.
S.-H.
Baek
,
S.
Hwang
,
T.
Park
,
Y.-J.
Kwon
,
M.
Cho
, and
D.
Park
, “
Evaluation of selective COX-2 inhibition and in silico study of kuwanon derivatives isolated from Morus alba
,”
Sci. Rep.
22
,
3659
(
2021
).
109.
J.
Kim
,
H.
Lim
,
S.
Moon
,
S. Y.
Cho
,
M.
Kim
,
J. H.
Park
,
H. W.
Park
, and
K. T.
No
, “
Hot spot analysis of YAP-TEAD protein-protein interaction using the fragment molecular orbital method and its application for inhibitor discovery
,”
Cancers
13
,
4246
(
2021
).
110.
H.
Lim
,
H.
Hong
,
S.
Hwang
,
S. J.
Kim
,
S. Y.
Seo
, and
K. T.
No
, “
Identification of novel natural product inhibitors against matrix metalloproteinase 9 using quantum mechanical fragment molecular orbital-based virtual screening methods
,”
Int. J. Mol. Sci.
23
,
4438
(
2022
).
111.
S.
Hwang
,
S.-H.
Baek
, and
D.
Park
, “
Interaction analysis of the spike protein of delta and omicron variants of SARS-CoV-2 with hACE2 and eight monoclonal antibodies using the fragment molecular orbital method
,”
J. Chem. Inf. Model.
62
,
1771
1782
(
2022
).
112.
V.
Sladek
,
Y.
Yamamoto
,
R.
Harada
,
M.
Shoji
,
Y.
Shigeta
, and
V.
Sladek
, “
pyProGA—A PyMOL plugin for protein residue network analysis
,”
PLoS One
16
,
e0255167
(
2021
).
113.
H.
Lim
,
H.-N.
Jeon
,
S.
Lim
,
Y.
Jang
,
T.
Kim
,
H.
Cho
,
J.-G.
Pan
, and
K. T.
No
, “
Evaluation of protein descriptors in computer-aided rational protein engineering tasks and its application in property prediction in SARS-CoV-2 spike glycoprotein
,”
Comput. Struct. Biotechnol. J.
20
,
788
798
(
2022
).
114.
A.
Acharya
,
R.
Agarwal
,
M. B.
Baker
,
J.
Baudry
,
D.
Bhowmik
,
S.
Boehm
,
K. G.
Byler
,
S. Y.
Chen
,
L.
Coates
,
C. J.
Cooper
,
O.
Demerdash
,
I.
Daidone
,
J. D.
Eblen
,
S.
Ellingson
,
S.
Forli
,
J.
Glaser
,
J. C.
Gumbart
,
J.
Gunnels
,
O.
Hernandez
,
S.
Irle
,
D. W.
Kneller
,
A.
Kovalevsky
,
J.
Larkin
,
T. J.
Lawrence
,
S.
LeGrand
,
S.-H.
Liu
,
J. C.
Mitchell
,
G.
Park
,
J. M.
Parks
,
A.
Pavlova
,
L.
Petridis
,
D.
Poole
,
L.
Pouchard
,
A.
Ramanathan
,
D. M.
Rogers
,
D.
Santos-Martins
,
A.
Scheinberg
,
A.
Sedova
,
Y.
Shen
,
J. C.
Smith
,
M. D.
Smith
,
C.
Soto
,
A.
Tsaris
,
M.
Thavappiragasam
,
A. F.
Tillack
,
J. V.
Vermaas
,
V. Q.
Vuong
,
J.
Yin
,
S.
Yoo
,
M.
Zahran
, and
L.
Zanetti-Polzi
, “
Supercomputer-based ensemble docking drug discovery pipeline with application to Covid-19
,”
J. Chem. Inf. Model.
60
,
5832
5852
(
2020
).
115.
I.
Morao
,
A.
Heifetz
, and
D. G.
Fedorov
, “
Accurate scoring in seconds with the fragment molecular orbital and density-functional tight-binding methods
,” in
Quantum Mechanics in Drug Discovery
, edited by
A.
Heifetz
(
Springer
,
New York
,
2020
), Vol. 2114, pp.
143
148
.
116.
S.
Ito
,
D. G.
Fedorov
,
Y.
Okamoto
, and
S.
Irle
, “
Implementation of replica-exchange umbrella sampling in GAMESS
,”
Comput. Phys. Commun.
228
,
152
162
(
2018
).
117.
T.
Nakamura
,
T.
Yokaichiya
, and
D. G.
Fedorov
, “
Analysis of guest adsorption on crystal surfaces based on the fragment molecular orbital method
,”
J. Phys. Chem. A
126
,
957
969
(
2022
).
118.
T.
Nakamura
and
D. G.
Fedorov
, “
The catalytic activity and adsorption in faujasite and ZSM-5 zeolites: The role of differential stabilization and charge delocalization
,”
Phys. Chem. Chem. Phys.
24
,
7739
7747
(
2022
).
119.
H.
Kitoh-Nishioka
,
K.
Welke
,
Y.
Nishimoto
,
D. G.
Fedorov
, and
S.
Irle
, “
Multiscale simulations on charge transport in covalent organic frameworks including dynamics of transfer integrals from the FMO-DFTB/LCMO approach
,”
J. Phys. Chem. C
121
,
17712
17726
(
2017
).
120.
J.
Rigby
,
S.
Barrera Acevedo
, and
E. I.
Izgorodina
, “
Novel SCS-IL-MP2 and SOS-IL-MP2 methods for accurate energetics of large-scale ionic liquid clusters
,”
J. Chem. Theory Comput.
11
,
3610
3616
(
2015
).
121.
L.
Goerigk
,
C. A.
Collyer
, and
J. R.
Reimers
, “
Recommending Hartree–Fock theory with London-dispersion and basis-set-superposition corrections for the optimization or quantum refinement of protein structures
,”
J. Phys. Chem. B
118
,
14612
14626
(
2014
).
122.
K.
Kato
,
T.
Masuda
,
C.
Watanabe
,
N.
Miyagawa
,
H.
Mizouchi
,
S.
Nagase
,
K.
Kamisaka
,
K.
Oshima
,
S.
Ono
,
H.
Ueda
,
A.
Tokuhisa
,
R.
Kanada
,
M.
Ohta
,
M.
Ikeguchi
,
Y.
Okuno
,
K.
Fukuzawa
, and
T.
Honma
, “
High-precision atomic charge prediction for protein systems using fragment molecular orbital calculation and machine learning
,”
J. Chem. Inf. Model.
60
,
3361
3368
(
2020
).
123.
K.
Okuwaki
,
H.
Doi
,
K.
Fukuzawa
, and
Y.
Mochizuki
, “
Folding simulation of small proteins by dissipative particle dynamics (DPD) with non-empirical interaction parameters based on fragment molecular orbital calculations
,”
Appl. Phys. Express
13
,
017002
(
2020
).
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