Polyphenols are natural molecules of crucial importance in many applications, of which tannic acid (TA) is one of the most abundant and established. Most high-value applications require precise control of TA interactions with the system of interest. However, the molecular structure of TA is still not comprehended at the atomic level, of which all electronic and reactivity properties depend. Here, we combine an enhanced sampling global optimization method with density functional theory (DFT)-based calculations to explore the conformational space of TA assisted by unsupervised machine learning visualization and then investigate its lowest energy conformers. We study the external environment’s effect on the TA structure and properties. We find that vacuum favors compact structures by stabilizing peripheral atoms’ weak interactions, while in water, the molecule adopts more open conformations. The frontier molecular orbitals of the conformers with the lowest harmonic vibrational free energy have a HOMO–LUMO energy gap of 2.21 (3.27) eV, increasing to 2.82 (3.88) eV in water, at the DFT generalized gradient approximation (and hybrid) level of theory. Structural differences also change the distribution of potential reactive sites. We establish the fundamental importance of accurate structural consideration in determining TA and related polyphenol interactions in relevant technological applications.

1.
S.
Quideau
,
D.
Deffieux
,
C.
Douat-Casassus
, and
L.
Pouységu
,
Angew. Chem., Int. Ed.
50
,
586
(
2011
).
2.
H.
Wang
,
C.
Wang
,
Y.
Zou
,
J.
Hu
,
Y.
Li
, and
Y.
Cheng
,
Giant
3
,
100022
(
2020
).
3.
F.
Reitzer
,
M.
Allais
,
V.
Ball
, and
F.
Meyer
,
Adv. Colloid Interface Sci.
257
,
31
(
2018
).
4.
H. A. M.
Bacelo
,
S. C. R.
Santos
, and
C. M. S.
Botelho
,
Chem. Eng. J.
303
,
575
(
2016
).
5.
J.
Zhou
,
Z.
Lin
,
Y.
Ju
,
M. A.
Rahim
,
J. J.
Richardson
, and
F.
Caruso
,
Acc. Chem. Res.
53
,
1269
(
2020
).
6.
P.
Chowdhury
,
P. K. B.
Nagesh
,
E.
Hatami
,
S.
Wagh
,
N.
Dan
,
M. K.
Tripathi
,
S.
Khan
,
B. B.
Hafeez
,
B.
Meibohm
,
S. C.
Chauhan
 et al.,
J. Colloid Interface Sci.
535
,
133
(
2019
).
7.
Z.
Xia
,
W.
Kiratitanavit
,
P.
Facendola
,
S.
Thota
,
S.
Yu
,
J.
Kumar
,
R.
Mosurkal
, and
R.
Nagarajan
,
Polym. Degrad. Stab.
153
,
227
(
2018
).
9.
T.
Zhang
,
L.
Fang
,
N.
Lin
,
J.
Wang
,
Y.
Wang
,
T.
Wu
, and
P.
Song
,
Green Chem.
21
,
5405
(
2019
).
10.
M.
Shin
,
H.-A.
Lee
,
M.
Lee
,
Y.
Shin
,
J.-J.
Song
,
S.-W.
Kang
,
D.-H.
Nam
,
E. J.
Jeon
,
M.
Cho
,
M.
Do
 et al.,
Nat. Biomed. Eng.
2
,
304
(
2018
).
11.
T.
Liu
,
M.
Zhang
,
W.
Liu
,
X.
Zeng
,
X.
Song
,
X.
Yang
,
X.
Zhang
, and
J.
Feng
,
ACS Nano
12
,
3917
(
2018
).
12.
İ.
Gülçin
,
Z.
Huyut
,
M.
Elmastaş
, and
H. Y.
Aboul-Enein
,
Arabian J. Chem.
3
,
43
(
2010
).
13.
G.
Shen
,
R.
Xing
,
N.
Zhang
,
C.
Chen
,
G.
Ma
, and
X.
Yan
,
ACS Nano
10
,
5720
(
2016
).
14.
E.
Shin
,
J.
Yoo
,
G.
Yoo
,
Y.-J.
Kim
, and
Y. S.
Kim
,
Chem. Eng. J.
358
,
170
(
2019
).
15.
J.
Yeo
,
J.
Lee
,
S.
Yoon
, and
W. J.
Kim
,
Biomater. Sci.
8
,
1148
(
2020
).
16.
H.
Peng
,
D.
Wang
, and
S.
Fu
,
Chem. Eng. J.
384
,
123288
(
2020
).
17.
B.
Akkaya
,
B.
Çakiroğlu
, and
M.
Özacar
,
ACS Sustainable Chem. Eng.
6
,
3805
(
2018
).
18.
S.
Zhao
,
S.
Xie
,
Z.
Zhao
,
J.
Zhang
,
L.
Li
, and
Z.
Xin
,
ACS Sustainable Chem. Eng.
6
,
7652
(
2018
).
19.
X.
An
,
Y.
Kang
, and
G.
Li
,
Chem. Phys.
520
,
100
(
2019
).
20.
S.
Ok
and
A.
Altun
,
Eur. Polym. J.
108
,
472
(
2018
).
21.
L.
Zou
,
P.
Shao
,
K.
Zhang
,
L.
Yang
,
D.
You
,
H.
Shi
,
S. G.
Pavlostathis
,
W.
Lai
,
D.
Liang
, and
X.
Luo
,
Chem. Eng. J.
364
,
160
(
2019
).
22.
V.
Lukeš
,
D.
Darvasiová
,
K.
Furdíková
,
I.
Hubertová
, and
P.
Rapta
,
J. Solid State Electrochem.
19
,
2533
(
2015
).
23.
C.
Bannwarth
,
S.
Ehlert
, and
S.
Grimme
,
J. Chem. Theory Comput.
15
,
1652
(
2019
).
24.
S.
Grimme
,
J. Chem. Theory Comput.
15
,
2847
(
2019
).
25.
A.
Barducci
,
M.
Bonomi
, and
M.
Parrinello
,
Wiley Interdiscip. Rev.: Comput. Mol. Sci.
1
,
826
(
2011
).
26.
G.
Bussi
and
A.
Laio
,
Nat. Rev. Phys.
2
,
200
(
2020
).
28.
P.
Pracht
,
F.
Bohle
, and
S.
Grimme
,
Phys. Chem. Chem. Phys.
22
,
7169
(
2020
).
29.
National Center for Biotechnology Information
, PubChem Compound Summary for CID 16129778, Tannic Acid,
2007
.
30.
D.
Bashford
and
D. A.
Case
,
Annu. Rev. Phys. Chem.
51
,
129
(
2000
).
31.
S.
Spicher
and
S.
Grimme
,
J. Chem. Theory Comput.
17
,
1701
(
2021
).
32.
O.
Isayev
,
D.
Fourches
,
E. N.
Muratov
,
C.
Oses
,
K.
Rasch
,
A.
Tropsha
, and
S.
Curtarolo
,
Chem. Mater.
27
,
735
(
2015
).
33.
S.
De
,
A. P.
Bartók
,
G.
Csányi
, and
M.
Ceriotti
,
Phys. Chem. Chem. Phys.
18
,
13754
(
2016
).
34.
G. R.
Schleder
,
A. C. M.
Padilha
,
C. M.
Acosta
,
M.
Costa
, and
A.
Fazzio
,
J. Phys.: Mater.
2
,
032001
(
2019
).
35.
G. R.
Schleder
,
A. C. M.
Padilha
,
A.
Reily Rocha
,
G. M.
Dalpian
, and
A.
Fazzio
,
J. Chem. Inf. Model.
60
,
452
(
2020
).
36.
F.
Giustino
,
J. H.
Lee
,
F.
Trier
,
M.
Bibes
,
S. M.
Winter
,
R.
Valentí
,
Y.-W.
Son
,
L.
Taillefer
,
C.
Heil
,
A. I.
Figueroa
,
B.
Plaçais
,
Q.
Wu
,
O. V.
Yazyev
,
E. P. A. M.
Bakkers
,
J.
Nygård
,
P.
Forn-Díaz
,
S.
De Franceschi
,
J. W.
McIver
,
L. E. F. F.
Torres
,
T.
Low
,
A.
Kumar
,
R.
Galceran
,
S. O.
Valenzuela
,
M. V.
Costache
,
A.
Manchon
,
E.-A.
Kim
,
G. R.
Schleder
,
A.
Fazzio
, and
S.
Roche
,
J. Phys.: Mater.
3
,
042006
(
2021
).
37.
H.
Huo
and
M.
Rupp
, “
Unified representation of molecules and crystals for machine learning
,” arXiv:1704.06439 [physics.chem-ph] (
2018
).
38.
L.
Himanen
,
M. O. J.
Jäger
,
E. V.
Morooka
,
F.
Federici Canova
,
Y. S.
Ranawat
,
D. Z.
Gao
,
P.
Rinke
, and
A. S.
Foster
,
Comput. Phys. Commun.
247
,
106949
(
2020
).
39.
M.
Melander
,
K.
Laasonen
, and
H.
Jónsson
,
J. Chem. Theory Comput.
11
,
1055
(
2015
).
40.
P.
Hohenberg
and
W.
Kohn
,
Phys. Rev.
136
,
B864
(
1964
).
41.
W.
Kohn
and
L. J.
Sham
,
Phys. Rev.
140
,
A1133
(
1965
).
42.
J.
VandeVondele
,
M.
Krack
,
F.
Mohamed
,
M.
Parrinello
,
T.
Chassaing
, and
J.
Hutter
,
Comput. Phys. Commun.
167
,
103
(
2005
).
43.
J. P.
Perdew
,
K.
Burke
, and
M.
Ernzerhof
,
Phys. Rev. Lett.
77
,
3865
(
1996
).
44.
Y.
Zhang
and
W.
Yang
,
Phys. Rev. Lett.
80
,
890
(
1998
).
45.
M.
Krack
,
Theor. Chem. Acc.
114
,
145
(
2005
).
46.
A. D.
Becke
and
E. R.
Johnson
,
J. Chem. Phys.
123
,
154101
(
2005
).
47.
S.
Grimme
,
S.
Ehrlich
, and
L.
Goerigk
,
J. Comput. Chem.
32
,
1456
(
2011
).
48.
S.
Ehrlich
,
J.
Moellmann
, and
S.
Grimme
,
Acc. Chem. Res.
46
,
916
(
2013
).
49.
G. R.
Schleder
,
A.
Fazzio
, and
J. T.
Arantes
,
J. Comput. Chem.
38
,
2675
(
2017
).
50.
C.
Dupont
,
O.
Andreussi
, and
N.
Marzari
,
J. Chem. Phys.
139
,
214110
(
2013
).
51.
K.
Fukui
,
T.
Yonezawa
, and
H.
Shingu
,
J. Chem. Phys.
20
,
722
(
1952
).
53.
R. G.
Parr
and
W.
Yang
,
J. Am. Chem. Soc.
106
,
4049
(
1984
).
54.
P. W.
Ayers
and
M.
Levy
,
Theor. Chem. Acc.
103
,
353
(
2000
).
55.
T. C.
Allison
and
Y. J.
Tong
,
Electrochim. Acta
101
,
334
(
2013
).
56.
R. K.
Roy
,
S.
Pal
, and
K.
Hirao
,
J. Chem. Phys.
110
,
8236
(
1999
).
57.
R.
Kinkar Roy
,
K.
Hirao
, and
S.
Pal
,
J. Chem. Phys.
113
,
1372
(
2000
).
58.
J.
Chen
,
W.
Im
, and
C. L.
Brooks
,
J. Am. Chem. Soc.
128
,
3728
(
2006
).
59.
C.
Baldauf
and
M.
Rossi
,
J. Phys.: Condens. Matter
27
,
493002
(
2015
).
60.
V.
Kapil
,
E.
Engel
,
M.
Rossi
, and
M.
Ceriotti
,
J. Chem. Theory Comput.
15
,
5845
(
2019
).
61.
J.
Heyd
,
G. E.
Scuseria
, and
M.
Ernzerhof
,
J. Chem. Phys.
118
,
8207
(
2003
).
62.
J.
Heyd
and
G. E.
Scuseria
,
J. Chem. Phys.
121
,
1187
(
2004
).
63.
J.
Heyd
,
G. E.
Scuseria
, and
M.
Ernzerhof
,
J. Chem. Phys.
124
,
219906
(
2006
).
64.
A. V.
Krukau
,
O. A.
Vydrov
,
A. F.
Izmaylov
, and
G. E.
Scuseria
,
J. Chem. Phys.
125
,
224106
(
2006
).
65.
R. B.
Woodward
and
R.
Hoffmann
,
Angew. Chem., Int. Ed. Engl.
8
,
781
(
1969
).
66.
H.
Fujimoto
and
K.
Fukui
,
Adv. Quantum Chem.
6
,
177
(
1972
).
67.
R. G.
Parr
and
R. G.
Pearson
,
J. Am. Chem. Soc.
105
,
7512
(
1983
).

Supplementary Material

You do not currently have access to this content.