Synthesis and crystal structure of phosphonic acid and bisphosphoramidate derivatives: QSAR studies of their anti-fungal potential on Macrophomina Phaseolina (Tassi) Goid

Article abstract of DOI:10.1007/s13738-020-02133-4

A series of phosphonic acid and bisphosphoramidate derivatives were synthesized and characterized. The bioactivities against the fungal pathogen Macrophomina phaseolina and human acetylcholinesterase AChE enzyme were studied using QSAR based on multiple linear regression. L17, with (p-Cl–C₆H₄–NH) (p-Cl–C₆H₄)C(H)P(O)(OC₂H₅)₂ skeleton, demonstrated a great mortality on the M. phaseolina mycelial growth by 83% inhibition at 150 mg/L; the other tested derivative showed moderate to weak antifungal activity against the fungus. QSAR model based on the GA-MLR method revealed the importance of 3D descriptors (De, Mor18e, H8m, and Mor30p) on the antifungal activity. It showed good capability in predicting the fungicidal activity of the studied molecules. Another derivative, L5, with (m-CH₃–NC₅H₄–NH)(m-CH₃–C₆H₄)C(H)P(O)(OCH₃)₂ skeleton displays the most potent anti-AChE activity. The electronic parameters, ΔE_L-H, and E_LUMO, have the highest contribution of human AChE. The authors suggest that these models could be usefully employed in designing more effective crop protection compounds without side effects on non-target organisms.

Full text of DOI:10.1007/s13738-020-02133-4

Journal of the Iranian Chemical Society
https://doi.org/10.1007/s13738-020-02133-4
ORIGINAL PAPER
Synthesis and crystal structure of phosphonic acid
and bisphosphoramidate derivatives: QSAR studies of their anti‑fungal
potential on Macrophomina Phaseolina (Tassi) Goid
Khodayar Gholivand1 · Mohsen Abbod2 · Ali Asghar Ebrahimi Valmoozi3 · Omolbanin Barzegar1 ·
Hadis Nasrollah Tabar1 · Rouhollah Yaghoubi1 · Mahdieh Hosseini1 · Naser Safaie2 · Maryam Rahimzadeh Dashtaki1 ·
Michal Dusek4 · Ahmad Mani‑Varnosfaderani1
Received: 11 April 2020 / Accepted: 29 November 2020
© Iranian Chemical Society 2021
Abstract
A series of phosphonic acid and bisphosphoramidate derivatives were synthesized and characterized. The bioactivities against
the fungal pathogen Macrophomina phaseolina and human acetylcholinesterase AChE enzyme were studied using QSAR
based on multiple linear regression. L17, with (p-Cl–C6H4–NH) (p-Cl–C6H4)C(H)P(O)(OC2H5)2 skeleton, demonstrated
a great mortality on the M. phaseolina mycelial growth by 83% inhibition at 150 mg/L; the other tested derivative showed
moderate to weak antifungal activity against the fungus. QSAR model based on the GA-MLR method revealed the impor-
tance of 3D descriptors (De, Mor18e, H8m, and Mor30p) on the antifungal activity. It showed good capability in predicting
the fungicidal activity of the studied molecules. Another derivative, L5, with (m-CH3–NC5H4–NH)(m-CH3–C6H4)C(H)
P(O)(OCH3)2 skeleton displays the most potent anti-AChE activity. The electronic parameters, ΔEL-H, and ELUMO, have the
highest contribution of human AChE. The authors suggest that these models could be usefully employed in designing more
efective crop protection compounds without side efects on non-target organisms.
Keywords Bisphosphoramidate · Phosphonic acid · Anti-fungal agents · Anti-AchE · Structure–activity relationships
Introduction
hazards on the environment and non-target organisms [1].
The excessive use of traditional pesticides leads to the emer-
gence of new strains of pests difcult to control [1–4]. Since
the 1950s, there has been a rapid rise in using phosphoric
acid ester derivatives in insecticide chemistry [5]. In con-
trast, a few of organophosphorus compounds were developed
to be used as fungicides [5] compared to organic compounds
used to control the plant diseases [6]. In terms of the mode
of action, acetylcholinesterase enzyme does not constitute
a target for fungicides like within the organophosphorus
insecticides. This may help develop new organophosphorus
fungicides that do not interact with human cholinesterase
leading to more safe agrochemicals [1].
Old methods of pesticide development like random synthesis
are no longer used due to their high consumption of time and
money [1]. Nowadays, eforts have been made to fnd new
and alternative chemicals for pest control with minimum
Supplementary Information The online version contains
supplementary material available at https://doi.org/10.1007/s1373
8-020-02133-4.
* Khodayar Gholivand
gholi_kh@modares.ac.ir
1
2
3
4
It is well known that the development of a new pesti-
cide is a costly process, and the recent main concern is
to minimize the cost and time of these procedures [7, 8].
Computer-aided drug design (CADD) technique potentially
ofers a further means to probe structure–bioactivity rela-
tionships [9]. The quantitative structure–activity/property
relationships (QSAR/QSPR) approaches were employed to
explore the most efective physio-chemical parameters in
Department of Chemistry, Faculty of Basic Sciences, Tarbiat
Modares University, P.O.Box: 14115-175, Tehran, Iran
Department of Plant Pathology, Faculty of Agriculture,
Tarbiat Modares University, Tehran, Iran
Department of Advanced Materials, Technical Engineering
Faculty, Imam Hossein University, Tehran, Iran
Institute of Physics of the ASCR, v.v.i., Na Slovance 2,
182 21 Praha 8, Czech Republic
Vol.:(0123456789)
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Journal of the Iranian Chemical Society
binding interactions between drugs and their target sites [10,
11]. Descriptors used in QSAR have been classifed into
diferent categories, including constitutional, geometrical,
topological, quantum chemical, and so on [12–14]. Also,
several variable selection methods, including multiple linear
regression (MLR) and genetic algorithm (GA), were used
[15]. These approaches were previously applied to explore
the binding interactions between the phosphonic acid and
bisphosphoramidate derivatives and the AChE and fungal
enzymes [16].
Crystal structure determination
Single-crystal X-ray data of L1 and L11 were collected on
a Bruker APEX-II difractometer with CCD area detec-
tor [22] using graphite monochromated Mo–Ka radiations
(λ=0.71073 Å). Xcalibur, Eos, Gemini ultra and Xcalibur,
Atlas, Gemini ultra difractometers were used for L1 and
L11. The CCD detector, software package CrysAlis171 (L1)
and CrysAlisPRO (L11) were also applied. [23] The struc-
tures were refned by full-matrix least-squares on F2 using
the Jana2006 package (L11) and SHELXL-2014 (L1) [24].
CCDC numbers: 1564405 (L1) and 1,560,706 (L11) con-
tain the supplementary crystallographic data for these two
compounds. These data can be obtained free of charge via
http://www.ccdc.cam.ac.uk/conts/retrieving.html, or from
the Cambridge Crystallographic Data Centre, 12 Union
Road, Cambridge CB2 1EZ, UK; Fax: (+44)1223–336-033;
or email: deposit@ccdc.cam.ac.uk.
In this work, several phosphonic acids and bisphospho-
ramidate derivatives were synthesized and characterized.
The fungicidal activity of synthesized compounds was deter-
mined on Macrophomina phaseolina (Tassi) Goid, a plant
pathogenic fungus. Also, they were tested against acetylcho-
linesterase (AChE) enzyme. The results were then used to
generate QSAR models to describe the relationship between
these activities and the physicochemical properties of the
synthesized compounds within mathematical equations.
Synthesis
Materials and methods
General procedure for compounds L1–L17 Compounds L1–
L8 were prepared by 1 mmol benzaldehyde, 1.1 mmol of
the primary amine, and trimethyl phosphite in the presence
of 2 mmol of LiClO4. The expected aminophosphonate was
produced in 92% yield after 24 h at 50 °C in dichlorometh-
ane (Scheme 1). Compounds L9–L17 were prepared by the
reaction of 1 mmol aldehyde and 1.1 mmol of the primary
amine in glycerol at 80 °C. After 4 h of stirring 1 mmol of
diethyl phosphite was added and after 12 h the product was
washed with water and ethyl acetate (Scheme 1).
Chemicals and instruments
Triton X-100, bovine serum albumin, acetylthiocholine
iodide (ATCH), 5,5′-dithiobis(2-nitrobenzoic acid) (DTNB),
alpha-naphthyl acetate, beta-naphthyl acetate, fast blue RR,
DMSO, Na2HPO4 (99%), NaH2PO4 (99%), sodium dode-
cyl sulfate (SDS) were all bought from Sigma-Aldrich and
1
Methanol form Merck. H, and, 31P NMR spectra were
1
recorded on a Bruker Avance DRX 500 spectrometer. H
and 13C chemical shifts were determined relative to inter-
nal TMS, and 31P chemical shifts relative to 85% H3PO4 as
an external standard. Infrared (IR) spectra were recorded
on a Shimadzu model IR-60 spectrometer using KBr pel-
lets. Melting points were obtained with an electrothermal
instrument. UV/Visible Spectrophotometer was performed
using a PerkinElmer Lambda 25. The fuorescence quench-
ing studies were carried out using the PerkinElmer LS 45
fuorescence spectrophotometer.
(C6H5)(NC5H4–NH)C(H)P(O)(OCH3)2 (L1) Mp: 138 °C.
1H NMR (250.13 MHz, d-DMSO, ppm): δ=3.48 (d,
3JP–H =10.5 Hz, 3H, Me), 3.61 (d, 3JP–H =10.5 Hz, 3H, Me),
2
3
5.87 (dd, JP–H =22.5 Hz, JH–H =8.3 Hz, 1H, CH), 6.51
(t, 3JH–H =6.3 Hz, 1H, Hb-py), 6.78 (d, 3JH–H =8.5 Hz, 1H,
Hd-py), 7.25–7.51 (m, 7H, Ph), 7.93 (d, 3JH–H =4.5 Hz, 1H,
Ha-py). 31P NMR (121.49 MHz, d-DMSO, ppm): δ=26.5
ppm. IR data (KBr, cm−1): 3299 s (υN–H); 3026w, 2945w,
2848w (υAliph); 1601 s (υpy); 1482 s (υAr); 1230 s (υP=O);
1031 s (υP–O).
Software
(p‑Cl–C6H4)(NC5H4–NH)C(H)P(O)(OCH3)2 (L2) Mp: 171
1
The three-dimensional structures of molecules were drawn
using the HyperChem software [17]. Dragon (version 3.0)
was used for calculation of molecular descriptors [18].
Gaussian 09 suite of programs was used for the calculation
of quantum descriptors [19]. Windows-based SPSS software
was utilized for the MLR analysis [20]. GA and MLR regres-
sion, and other calculations were performed in the MAT-
LAB 7.10.0 environment [21].
°C. H NMR (500.13 MHz, d-DMSO, ppm): δ = 3.51 (d,
3
3JP–H = 10.6 Hz, 3H, Me), 3.62 (d, JP–H = 10.6 Hz, 3H,
2
3
Me), 5.85 (dd, JP–H = 22.9 Hz, JP–H = 9.9 Hz, 1H, CH),
3
3
6.52 (t, JP–H = 5.9 Hz, 1H, Hb-py), 6.77 (d, JP–H = 8.4
3
Hz, 1H, Hd-py), 7.39 (m, 3H, Ph-py), 7.50 (d, JP–H = 7.5
3
3
Hz, 1H, C6H4),7.54 (dd, JP–H = 8.9 Hz, JP–H = 3.1 Hz,
1H, NH), 7.92 (d, JP–H = 4.4 Hz, 1H, Ha-py). 31P NMR
3
(202.45 MHz, d-DMSO, ppm): δ = 25.5 ppm. IR data
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Journal of the Iranian Chemical Society
Scheme 1 Reactions diagram for the synthesis of compounds L1–L22, L28 and L29
(KBr, cm–1): 3299 s (υN–H); 2951w, 2854w (υAliph); 1605
s (υpy); 1525w, 1483 s (υAr); 1233 s (υP=O); 1029 s (υP–O).
(o‑NC5H4–NH)(m‑CH3–C6H4)C(H)P(O)(OCH3)2 (L4) Mp: 117
°C. 1H NMR (500.13 MHz, d-DMSO, ppm): δ = 2.28
3
(s, 3H, Me’’), 3.48 (d, JP–H = 10.5 Hz, 3H, Me), 3.61
3
2
(m‑Br–C6H4)(NC5H4–NH)C(H)P(O)(OCH3)2 (L3) Mp: 112
(d, JP–H = 10.5 Hz, 3H, Me), 5.83 (dd, JP–H = 22.6 Hz,,
1
3
°C. H NMR (500.13 MHz, d-DMSO, ppm): δ = 3.53 (d,
3JP–H = 10.1 Hz, 1H, CH), 6.50 (t, JP–H = 6.2 Hz, 1H,
3
3
3JP–H = 10.6 Hz, 3H, Me), 3.63 (d, JP–H = 10.6 Hz, 3H,
Hb-py), 6.77 (d, JP–H = 8.4 Hz, 1H, Hd-py), 7.06 (d,
Me), 5.87 (dd, 2JP–H = 22.9 Hz, 3JH–H = 10.0 Hz, 1H, CH),
3JP–H = 7.4 Hz, 1H, Hg-C6H4), 7.21 (ps-t, JP–H = 7.6 Hz,
3
6.53 (t, 3JP–H = 5.8 Hz, 1H, Hb-py), 6.77 (d, 3JP–H = 8.5 Hz,
1H, Hf-C6H4), 7.28 (d, 3JP–H = 7.6 Hz, 1H, He-C6H4), 7.30
3
3
1H, Hd-py), 7.29 (t, JP–H = 7.9 Hz, 1H, Hc-py), 7.40 (ps-
(s, 1H, Hh-C6H4), 7.37 (t, JP–H = 7.7 Hz, 1H, Hc-py),
3
3
3
t, JP–H = 7.7 Hz, 1H, Hf-C6H4), 7.47 (m, 2H, He,g-C6H4),
7.47 (dd, JP–H = 9.8 Hz, JP–H = 2.7 Hz, 1H, NH), 7.93
3
3
3
7.56 (dd, JP–H = 9.9 Hz, JP–H = 3.5 Hz, 1H, NH), 7.71
(d, JP–H = 4.9 Hz, 1H, Ha-py). 31P NMR (202.45 MHz,
(s, 1H, Hh-C6H4), 7.93 (d, 3JP–H = 3.8 Hz, 1H, Ha-py). 31
P
d-DMSO, ppm): δ = 25.4 ppm. IR data (KBr, cm–1): 3390
m; 3286 s (υN–H); 3018w, 2941w, 2853w (υAliph); 1601 s
(υpy); 1481 s (υAr); 1230 s (υP=O); 1062 s, 1035 (υP–O).
NMR (202.45 MHz, d-DMSO, ppm): δ = 24.7 ppm. IR
data (KBr, cm–1): 3390 m; 3298 s (υN–H); 2943w (υAliph);
1596 s (υpy); 1474 s (υAr); 1234 s (υP=O); 1034 s (υP–O).
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Journal of the Iranian Chemical Society
(m‑CH3–NC5H4–NH)(m‑CH3–C6H4)C(H)P(O)(OCH3)2 (L5) Mp:
Hz, 1H, CH), 4.12 (q, 3JH–H =7.0 Hz, 2H, CH2–OEt1), 3.93
1
3
3
142 °C. H NMR (500.13 MHz, d-DMSO, ppm): δ=2.30
(q, JH–H =10.3 Hz, 1H, CH2–OEt2), 3.69 (q, JH–H =8.4
3
3
(s, 3H, Me’), 3.50 (d, JP–H =10.6 Hz, 3H, Me), 3.67 (d,
Hz, 1H, CH2–OEt2), 1.29 (t, JH–H =6.5 Hz, 3H, CH3–
3
3JP–H =10.7 Hz, 3H, Me),4.16 (s, 3H, Me"), 5.34 (dd,
3JP–H =23.9 Hz, 3JP–H =9.8 Hz, 1H, CH), 7.12 (d, 3JP–H =7.6
Hz, 1H, Hg-C6H4), 7.26 (ps-t, 3JP–H =7.6 Hz, 1H, Hf-C6H4),
7.33 (d, 1H, 3JP–H =10 Hz, He-C6H4), 7.34 (s, 1H, Hh-C6H4),
OEt1), 1.11 (t, JH–H =7.0 Hz, 3H, CH3–OEt2). 31P NMR
(202.45 MHz, CDCl3, ppm): δ=22.1 ppm. IR data (KBr,
cm–1): υ=3325 m (N–H); 2950w, 2900w (C–Halph.); 1500
m (C=Carm.); 1239 s (P=O); 1055 m;1030 s (P–O).
3
3
7.73 (dd, JP–H =8.8 Hz, JP–H =5.7 Hz, 1H, Hc-py), 7.83
3
3
(d, JP–H =8.5 Hz, 1H, Hd-py), 8.04 (dd, JP–H =9.7 Hz,
3JP–H =5.4 Hz, 1H, NH), 8.12 (d, 3JP–H =5.5 Hz, 1H, Hb-py),
8.34 (s, 1H, Ha-py). 31P NMR (202.45 MHz, d-DMSO,
ppm): δ=23.5 ppm. IR data (KBr, cm–1): 3356w; 3275 m
(υN–H); 3103w, 2957w, 2851w; 1628 m, 1597 (υpy); 1516 m,
1458ws (υAr); 1231 s (υP=O); 1062 s, 1043 s, 1016 s (υP–O).
(p‑F–C6H4–NH)(C6H5)C(H)P(O)(OC2H5)2 (L10) Mp: 100–105
1
°C; H NMR (250.13 MHz, CDCl3, ppm): δ=7.48 (d,
3JH–H =6.3 Hz, 2H, o-Ph), 7.35–7.26 (m, 3H, m-Ph, p-Ph),
6.79 (st, 3JH–H/F–H =8.4 Hz, 2H, C6H4), 6.67 (m, 2H, C6H4),
4.10 (m, 2H, CH2–OEt1), 3.97 (q, 3JH–H =6.9 Hz, 1H, CH2–
3
OEt2), 3.81 (q, JH–H =7.5 Hz, 1H, CH2–OEt2), 1.26 (t,
3JH–H =6.9 Hz, 3H, CH3–OEt1), 1.14 (t, 3JH–H =7.2 Hz, 3H,
CH3–OEt2). 31P NMR (121.49 MHz, CDCl3, ppm): δ=25.2
ppm. IR data (KBr, cm–1): υ=3294 s (N–H); 2984w, 2912w
(C–Halph.); 1511 s; 1446w (C=Carm.); 1233 s (P=O); 1029
s; 973 s.
(NC5H4–NH)P(O)(OCH3)2C(H)(C6H4)C(H)–(NC5H4–NH)
P(O)(OCH3)2 (L6) Mp: 196 °C. 1H NMR (250.13 MHz,
3
d-DMSO, ppm): δ=3.47 (d, JP–H =10.3 Hz, 6H, Me),
3
2
3.60 (d, JP–H =10.3 Hz, 6H, Me), 5.87 (dd, JP–H =24.0
3
3
Hz, JP–H =7.5 Hz, 1H, CH), 6.49 (t, JP–H =6.3 Hz, 2H,
3
Hb-py), 6.75 (d, JP–H =8.3 Hz, 2H, Hd-py), 7.34–7.45 (m,
(p‑Cl–C6H4–NH)(C6H5)C(H)P(O)(OC2H5)2 (L11) Mp: 110–115
3
1
6H, Hc-py), 7.91 (d, JP–H =4.3 Hz, 1H, Ha-py). 31P NMR
°C; H NMR (500.13 MHz, CDCl3, ppm): δ=7.49 (d,
3
(121.49 MHz, d-DMSO, ppm): δ=26.5 ppm. IR data (KBr,
cm–1): 3294 m (υN–H); 2953w, 2926w, 2851w (υAliph); 1602
s (υpy); 1481 s (υAr); 1238 s (υP=O); 1060 s, 1030 s (υP–O).
3JH–H =7.4 Hz, 2H, o-Ph), 7.30 (t, JH–H =7.1 Hz, 2H, m-
Ph), 7.23 (d, 3JH–H =7.2 Hz, 1H, p-Ph), 7.00 (d, 3JH–H =8.5
3
Hz, 2H, C6H4), 6.79 (d, 2H, JH–H =8.7 Hz, C6H4), 6.59
2
3
(m, 1H, NH), 5.00 (dd, JP–H =25.0 Hz, JH–H =9.9 Hz,
1H, CH), 4.02 (q, 3JH–H =8.2 Hz, 2H, CH2–OEt1), 3.95 (q,
3JH–H =7.2 Hz, 1H, CH2–OEt2), 3.81 (q, 3JH–H =7.8 Hz, 1H,
(C6H5NH)P(O)(OCH3)2C(H)(C6H4)C(H)–(C6H5NH)P(O)(OCH3)2
(L7) Mp: 120 °C. 1H NMR (500.13 MHz, d-DMSO, ppm):
δ=3.38 (m, 6H, Me+solvent), 3.62 (d, 3JP–H =10.4 Hz, 6H,
3
CH2–OEt2), 1.16 (t, JH–H =7.0 Hz, 3H, CH3–OEt1), 1.02
Me), 5.07 (dd, JP–H =24.2 Hz, JH–H =10.1 Hz, 1H, CH),
(t, 3JH–H =7.0 Hz, 3H, CH3–OEt2). 31P NMR (202.45 MHz,
CDCl3, ppm): δ=22.7 ppm. IR data (KBr, cm–1): υ=3291
s (N–H); 2980 s, 2905w (C–Halph.); 1597 s; 1496 s, 1448 m
(C=Carm.); 1239 s (P=O); 1027 s; 971 s.
2
3
3
3
6.32 (dd, JP–H =9.9 Hz, JP–H =6.0 Hz, 2H, NH), 6.50 (t,
3JP–H =7.2 Hz, 2H, p-Ph), 6.75 (d, 3JP–H =8.1 Hz, 4H, o-Ph),
6.97 (t, JP–H =7.5 Hz, 4H, m-Ph), 7.46 (s, 4H, C6H4). 31P
3
NMR (202.45 MHz, d-DMSO, ppm): δ=25.1 ppm. IR data
(KBr, cm–1): 3377 m (υN–H); 3055w, 2955w, 2853w (υAliph);
1599 s; 1508 s, 1438w (υAr); 1248 s (υP=O); 1055 s, 1020 s
(υP–O).
(p‑Br–C6H4–NH)(C6H5)C(H)P(O)(OC2H5)2 (L12) Mp: 120–123
1
°C; H NMR (250.13 MHz, CDCl3, ppm): δ=7.49 (d,
3JH–H =6.9 Hz, 2H, o-Ph), 7.36–7.27 (m, 3H, m-Ph, p-Ph),
7.14 (d, 3JH–H =8.4 Hz, 2H, C6H4), 6.63 (d, 2H, 3JH–H =8.4
Hz, C6H4), 4.10 (m, 2H, CH2–OEt1), 3.95 (q, 3JH–H =7.8 Hz,
(C6H5)(3,5–(CH3)2–N2C4H–NH)C(H)P(O)(OCH3)2
(L8) Mp:
1
3
142 °C. H NMR (250.13 MHz, d-DMSO, ppm): δ=3.51
1H, CH2–OEt2), 3.81 (q, JH–H =7.2 Hz, 1H, CH2–OEt2),
(ps-t, JP–H =11.3 Hz, 6H, Me), 5.84 (dd, JP–H =22.5
1.26 (t, 3JH–H =6.9 Hz, 3H, CH3–OEt1), 1.15 (t, 3JH–H =6.9
Hz, 3H, CH3–OEt2). 31P NMR (121.49 MHz, CDCl3, ppm):
δ=23.4 ppm. IR data (KBr, cm–1): υ=3291 s (N–H); 2922
m (C–Halph.); 1593 m; 1490 s (C=Carm.); 1239 s (P=O);
1027 s; 973 s.
3
2
3
Hz, JH–H =7.0 Hz, 1H, CH), 6.42 (s, 1H, Hb), 7.26–7.35
3
(m, 3H, p,m-Ph), 7.54 (d, JH–H =6.7 Hz, 2H, o-Ph), 7.76
3
(d, JP–H =10.0 Hz, 1H, NH). 31P NMR (121.49 MHz,
d-DMSO, ppm): δ=25.9 ppm. IR data (KBr, cm–1): 3294
m (υN–H); 2952w, 2852w (υAliph); 1566 s (υpy); 1450 s (υAr);
1245 s (υP=O); 1027 s (υP–O).
(p‑I–C6H4–NH)(C6H5)C(H)P(O)(OC2H5)2 (L13) Mp: 130–133
1
°C; H NMR (500.13 MHz, CDCl3, ppm): δ=7.54–7.26
(C6H5–NH)(C6H5)C(H)P(O)(OC2H5)2 (L9) Mp: 80–85 °C; 1H
(m, Ar), 6.49 (m،NH), 4.75 (dd, 1H, CH), 4.29 (q, 4.02 (q,
2H, 3JH–H =8.2 Hz, CH2–OEt1), 3.95 (q, 3JH–H =7.2 Hz, 1H,
CH2–OEt2), 3.81 (q, CH2–OEt (Inpurity)), 4.131 (q, 2H, CH2–
OEt), 3.94 (q, 1H, CH2–OEt2), 3.66 (q, 1H, CH2–OEt2),
1.39 (t, CH3–OEtInpurity), 1.29 (t, 3H, CH3–OEt1), 1.16 (t,
3
NMR (500.13 MHz, CDCl3, ppm): δ=7.48 (d, JH–H =7.2
Hz, 2H, o-Ph’), 7.35–7.26 (m, 3H, m-Ph’, p-Ph’), 7.12 (t,
3
3JH–H =7.3 Hz, 2H, m-Ph), 6.73 (t, JH–H =7.2 Hz, 2H, p-
Ph), 6.66 (d, 3JH–H =7.1 Hz, 2H, o-Ph), 4.76 (d, 2JP–H =23.3
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Journal of the Iranian Chemical Society
CH3–OEtInpurity), 1.10 (t, 3H, CH3–OEt2). 31P NMR (202.45
MHz, CDCl3, ppm): δ=21.4, –1.2 (Inpurity) ppm. IR data
(KBr, cm–1): υ=3293 s (N–H); 2975 s, 29185w (C–Halph.);
1496 s, 1445 m (C=Carm.); 1235 s (P=O); 1028 s; 973 s.
υ=3288 m (N–H); 2997w, 2923w (C–Halph.); 1514 s; 1444
s, (C=Carm.); 1232 s (P=O); 1020 s; 980 m.
General procedure for compound L18–L22, L28, and L29
(p‑NO2–C6H4–NH)(C6H5)C(H)P(O)(OC2H5)2 (L14) Mp: 111
Compounds L18–L22, L28, and L29 were prepared by a Man-
nich-type reaction according to the procedure previously
described [25]. The corresponding amine (1 mmol) was
mixed with 37% hydrochloric acid (5 mL), deionized water
(5 mL) and phosphorous acid (3 mmol). The mixture was
allowed to refux at 100–120 °C for 1.5 h, then paraformal-
dehyde (4 mmol) was added in small portions over a period
of 1 h, and the mixture was refuxed for an additional hour,
a white powder was yielded after removing the solvents.
1
°C; H NMR (500.13 MHz, CDCl3, ppm): δ=8.01 (d,
3
3JH–H =9.1 Hz, 2 H, C6H4), 7.45 (d, JH–H =7.4 Hz, 2H, o-
Ph), 7.37 (t, 3JH–H =7.7 Hz, 2H, m-Ph), 7.32 (d, 3JH–H =6.8
Hz, 1H, p-Ph), 6.58 (d, 3JH–H =9.2 Hz, 2H, C6H4), 6.79 (d,
3
2H, JH–H =8.7 Hz, C6H4), 6.58 (m, 1H, NH), 4.80 (dd,
2JP–H =24.1 Hz, 1H, CH), 4.14 (q, 3JH–H =8.3 Hz, 2H, CH2–
OEt1), 3.90 (q, 3JH–H =9.82 Hz, 1H, CH2–OEt2), 3.61 (q, 1H,
3
CH2–OEt2), 1.31 (t, JH–H =5.6 Hz, 3H, CH3–OEt1), 1.10
(t, 3JH–H =7.0 Hz, 3H, CH3–OEt2). 31P NMR (202.45 MHz,
CDCl3, ppm): δ=21.3 ppm. IR data (KBr, cm–1): υ=3285
m (N–H); 2977w, 2922w, 1530 s; 1348 s, (C=Carm.); 1232 s
(P=O); 1016 s; 971 m.
(C6H5)2–CH–N–[(CH2)P(O)(OH)2]2 (L18) Mp: 204 °C. 31P
1
NMR (202.46 MHz, D2O): δ=7.48 ppm. H NMR(500.13
MHz, D2O): δ=3.19 ppm (CH, s, 1H), 3.35 (CH2, d, 4H,
2JP,H =12.23 Hz), 7.36–7.40 (Ar–H, m). IR (KBr, cm−1):
υ = 3419 (w,NH+), 2926 (s, CH), 2856 (s, CH), 2358 (s),
1636 (m), 1081–1176 (s, PO3), 921 (s, PO3), 783 (s, P–C),
553 (s,p=o), 481 (m).
(p‑Cl–C6H4–NH)(p‑F–C6H4)C(H)P(O)(OC2H5)2
(L15) Mp:
1
78–82 °C; H NMR (500.13 MHz, CDCl3, ppm): δ=7.84
(d, Ar), 7.53–7.03 (m, Ar), 6.51 (d, Ar), 4.70 (d, 2JP–H =23.6
Hz, 1H, CH),6.72(br 4.11 (m, 2H, CH2–OEt1), 3.95 (q,
3JH–H =10.1 Hz, 1H, CH23–OEt2), 3.65 (q, JH–H =8.5 Hz,
(m‑NC5H4)(CH2)–N–[(CH2)P(O)(OH)2]2 (L19) Mp: 248 °C. 31P
NMR (202.46 MHz, D2O): δ=8.11 ppm. 1H NMR (500.13
3
1H, CH2–OEt2), 1.29 (t, JH–H =6.2 Hz, 1H, CH3–OEt1),
3
2
1.11 (t, JH–H =7.0 Hz, 1H, CH3–OEt2). 31P NMR (202.45
MHz, D2O): δ=3.37 ppm (CH2, d, 4H, JP,H =12.35 Hz),
MHz, CDCl3, ppm): δ=22.3 s, 21.6w ppm. IR data (KBr,
cm–1): υ=3290 m (N–H); 2983w, 2909w (C–Halph.); 1520
s; 1440 s, (C=Carm.); 1236 s (P=O); 10125 s; 9673 m.
4.85 (–CH2, s, 2H), 8.05–9.01 (m, 4H). IR (KBr, cm−1): υ
3405 (w, NH+), 2965 (s, CH), 2845 (s, CH), 2720 (s, P–
=
OH), 2545 (s), 1284 (m, C–N), 1166–1229 (s, PO3), 935–
1008 (s, PO3), 746 (s, P–C), 573 (s, p=o), 485 (m), 421 (m).
(p‑Cl‑C6H4‑NH)(NC5H4)C(H)P(O)(OC2H5)2 (L16) Mp: 106–108
1
°C; H NMR (500.13 MHz, CDCl3, ppm): δ=8.59 (d,
(p‑F–C6H4)–(CH2)–N–[(CH2)P(O)(OH)2]2 (L20) Mp: 227 °C. 31P
3
3JH–H =4.5 Hz, 1H, py), 7.70 (t, JH–H =7.5 Hz, 1H, py),
NMR (202.46 MHz, D2O): δ=7.62 ppm. 1H NMR (500.13
3
2
7.50 (d, JH–H =7.6 Hz, 1H, py), 7.24 (t-br, 1H, py), 7.06
MHz, D2O): δ=3.36 (CH2, d, 4H, JP,H =12.66 Hz), 4.60
3
3
(d, JH–H =8.6 Hz, 1H, C6H4), 6.61 (d, JH–H =8.6 Hz, 1H,
(CH2, s, 2H), 7.29–7.53 (Ar–H, m, 4H). IR (KBr, cm−1): υ
2
C6H4), 5.35 (br, 1 H, NH), 4.98 (d, JP–H =21.6 Hz, 1 H,
3415 (w, NH+), 3040 (m, CH), 2870 (m, CH), 2775 (m,
=
CH), 4.12 (m, 2H, CH2–OEt1), 4.03 (m, 1H, CH2–OEt2),
P–OH), 2590 (m), 1450 (w), 1237 (m, C–N), 1161–1200 (s,
PO3), 940–1004 (s, PO3), 744 (w, P–C), 575 (m), 493 (m),
405 (m).
3.905 (m, 1H, CH2–OEt2), 1.27 (t, 3JH–H =6.2 Hz, 1H, CH3–
OEt1), 1.15 (t, JH–H =7.0 Hz, 1H, CH3–OEt2). 31P NMR
3
(202.45 MHz, CDCl3, ppm): δ=20.7 s, 21.6w ppm. IR data
(KBr, cm–1): υ=3285 s (N–H); 2985w, 2911w (C–Halph.);
1493 s; 1434w, (C=Carm.); 1239 s (P=O); 1029 s; 968 m.
(OH)2(O)P(CH2)NC5H9(CH2)3C5H9N(CH2)P(O)(OH)2 (L21) Mp:
1
257 °C. 31P NMR (202.46 MHz, D2O): δ=7.33 ppm. H
NMR (500.13 MHz, D2O): δ=1.14–1.544 (CH2, m, 2H),
1.82 (CH2, m, 2H), 2.92 (CH2, m, 2H), 3.11 (CH2, d,
4H,2JP,H =11.0 Hz), 3.23 (CH2, 2H), 3.57 (CH2, m, 2H). IR
(p‑Cl–C6H4–NH)(p–Cl–C6H4)C(H)P(O)(OC2H5)2
(L17) Mp:
103–106 °C; 1H NMR (500.13 MHz, CDCl3, ppm): δ=7.40
(d, 3JH–H =6.6 Hz, 2H, C6H4`), 7.30 (d, 3JH–H =8.1 Hz, 2H,
(KBr, cm−1): υ 3415 (w, NH+), 3040 (m, CH), 2870 (m,
=
3
C6H4`), 6.82 (st, JH–H =8.5 Hz, 2H, C6H4`), 7.24 (t-br,
CH), 2775 (m, P–OH), 2590 (m), 1450 (w), 1237 (m, C–N),
1161–1200 (s, PO3), 940–1004 (s, PO3), 744 (w, P–C), 575
(m), 493 (m), 405 (m).
2
1H, py), 6.57 (m, 2H, C6H4`), 4.66 (d, JP–H =23.8 Hz,
1H, CH), 4.12 (q, 2H, 3JH–H =7.2 Hz, CH2–OEt1), 3.98 (q,
3JH–H =9.8 Hz, 2H, CH2–OEt2), 3.80 (q, 3JH-H =8.0 Hz, 1H,
3
CH2-OEt2),1.29 (t, 2H, JH-H =7.0 Hz, 1H,CH3-OEt1), 1.16
C6H5–CH2–N–[(CH2)P(O)(OH)2]2 (L22) Mp: 209 °C. 31P NMR
(t, 3JH-H =7.0 Hz, 1 H, CH3–OEt2), 31P NMR (202.45 MHz,
CDCl3, ppm): δ=21.4 s, 21.6w ppm. IR data (KBr, cm–1):
(202.46 MHz, D2O): δ=6.20 ppm. 1H NMR (500.13 MHz,
2
D2O): δ=281 3.06 ppm (CH2, d, 4H, JP,H =12.1), 4.20
1 3

Journal of the Iranian Chemical Society
3
(CH2, s, 2H), 7.31–7.48 (Ar–H, m, 5H). IR (KBr, cm−1):
υ=3405(w, NH+), 2965 (s, CH), 2876 (282 s, CH), 2348
(s), 1633 (m), 1071–1186 (s, PO3), 283 930 (s, PO3), 756 (s,
P–C), 553 (s, p=o), 476 (m).
(m, 8H, CH2); 1.54 (s, 2H, CH); 2.48 (t, JH–H =1.65 Hz,
4H, CH2); 5.18 (m, 2H, NH), 7.42–7.49 (m, 8H, C6H5),
7.6–7.7 (m, 4H, C6H5), 7.71–7.77 (m, 8H, C6H5) ppm. 31P
NMR (202.45 MHz, d-DMSO, ppm): δ=21.47 ppm. IR
data (KBr, cm–1): 3432 s, 3198 (υN–H); 2914 m (υC–Halph.);
2852; 1435 s (υAr); 1185 s (υP=O); 1067 s (υP–N); 723; 697.
(o‑CO2H)–C5H9N)(CH2)P(O)(OH)2(L28) Mp: 221 °C. 31P NMR
(202.46 MHz, D2O): δ=7.36 ppm. 1H NMR (500.13 MHz,
D2O): δ=1.87–2.40 (CH2, m), 3.18 (CH2, d, 2H, 2JP,H =11.9
Hz), 3.39 (CH, m) 3.77 (CH, s) 4.26 (CH, m). IR (KBr,
cm−1): υ = 3435(w, NH+), 2980 (m, CH), 2755 (m, P–OH),
2295 (m), 1274 (m, C–N), 1078–1192 (s, PO3), 913–1015
(s, PO3), 759 (w, P–C), 521 (s, p=o), 461 (m), 411 (m).
(C2H5O)2P(S)(NH)2C(O)(NH)2P(S)(OC2H5)2 (L24) Mp: 187 °C.
1H NMR (500.13 MHz, CDCl3, ppm): δ=1.33 (t, 2JH–H =7
Hz, 12H, Me), 4.13–4.19 (m, 8H, CH2), 6.86 (br, 2H, N–
Hβ), 7.26 (s, 2H, NHamide). 31P NMR (202.45 MHz, CDCl3,
ppm): δ=69.33 ppm. IR data (KBr, cm–1): 3294 s (υN–H);
1667 s (υC=O); 2983w (υC–Halph); 1521 s (υAliphatic); 1023 s
(υN–N); 966 s (υP–N); 811 s (υP=S).
[(p‑OH)(o–CO2H)C5H8N](CH2)P(O)(OH)2 (L29) Mp: 237 °C. 31P
1
NMR(202.46 MHz, D2O): δ=7.21 ppm. H NMR(500.13
MHz, D2O): δ=1.99–2.40 (CH2, m), 3.18 (CH2, d, 2H,
2JP,H =12.3 Hz), 3.54 (CH, m) 3.66 (CH, s) 4.16 (CH, m).
IR (KBr, cm−1): υ = 3395 (w, NH+), 3000 (m, CH), 2870
(m, CH), 2735 (m, P–OH), 2570 (m), 1420 (w), 1259 (m,
C–N), 1173–1231 (s, PO3), 928–1000 (s, PO3), 784 (w,
P–C), 595 (m), 552 (m), 509 (m).
(C6H5O)2P(O)–NH–NH–C(O)–NH–NH–P(O)(OC6H5)2
(L25) Mp: 190 °C. 1H NMR (250.13 MHz, d-DMSO, ppm):
δ=5.89 (dd, 2JP–H =23 Hz, 3JH–H =8.8 Hz, 2H, NHα), 7.18
2
(m, 2H, NHβ), 7.39 (d, JP–H =7 Hz, 4H, N–Haniline), 7.46
(m, 8H, C6H5). 7.52 (m, 4H, C6H5), 7.8(m, 8H, C6H5). 31P
NMR (121.49 MHz, d-DMSO, ppm): δ=22.16 ppm. IR
data (KBr, cm–1): 3223 s, 3061 (υN–H); 1685 s (υC=O); 1529
s (υAr); 1207 s (υP=O); 1030 s (υP–O); 1051 s (υN–N); 944 m
(υP=N); 749 m.
General procedure for compound L32
This compound was prepared by adding a solution of the
(thio)hydrazide compound (1 mmol) and triethylamine (1
mmol) in THF at 0 °C to a solution of (C6H5–NH)2P(O)
Cl (1 mmol) in THF. After stirring for 4 h, the solvent was
removed under vacuum, and the resulting product was
washed with distilled water.
(C6H5)2P(O)–HN–(C6H10)–CH2–(C6H10)–HN–P(O)(C6H5)2
(L26) Mp: 122 °C. 1H NMR (250.13 MHz, d-DMSO, ppm):
0.77 (m, 2H, CH2); 0.89 (m, 2H, CH); 1.3–1.4 (m, 8H, CH2),
1.62–2.01 (m, 8H, CH2), 2.76 (m, 2H, CH); 7.35 (m, 2H,
NH), 7.45–7.52 (m, 8H, C6H5), 7.54–7.56 (m, 4H,C6H5),
7.76–7.87 (m, 8H, C6H5) ppm. 31P NMR (121.49 MHz,
MeOD, ppm): δ=25.24 ppm. IR data (KBr, cm–1): 3399w,
3197 (υN–H); 2926 (υC–Halph); 2856 m (υAliphatic); 1442 s (υAr);
1262 m, 1189vs (υP=O); 1115vs (υP–O); 898 m (υP–N); 697.
(o‑S‑C4H3)C(O)NH–NHP(O)(NH–C6H5)2 (L32) Mp: 224 °C. 1H
NMR (500.13 MHz, MeOD, ppm): 7.04 (dd, 2JH–H =3.8 Hz,
2
1H, HThio), 7.13 (d, JPNH =8.54 Hz, 1H, N–Hα), 7.3–7.49
2
(br, m, 4H, HPh), 7.52 (d, JH–H =2.7 Hz, 1H, HThio), 7.55
(m, 2H, HPh), 7.67–7.8 (br, m,4H, HPh); 7.84 (d, 2JH–H =4.8
(C6H5O)2P(O)–NH–C6H10–O–P(O)(OC6H5)2 (L27) Mp: 127
2
1
Hz,1H, HThio);7.99 (d, JPNH =6.1 Hz, 2H, N–Haniline);
°C. H NMR (500.13 MHz, CDCl3, ppm): 1.17–1.35 (m,
8.27 (s, 1H, NHβ); 31P NMR (202.45 MHz, MeOD, ppm):
δ=26.61 ppm. IR data (KBr, cm–1): 3273 s, 3229 s (υN–H);
3054 m; 1647 s (υC=O); 1497 s; 1409 m, 1295 m, 1212 s (vs,
υP=O); 1071 s (υN–N); 956 s (υP–N), 905 s, 724 m.
4H, CH2), 1.89–2.04 (m, 4H, CH2), 3.20 (m, 1H, CH), 3.55
(m, 1H, CH), 7.07–7.17 (m, 8H, C6H5), 7.19–7.27 (m, 4H,
2
C6H5), 7.29–7.34 (m, 8H, C6H5), 7.39 (dd, 1H, JPH =7.7
3
Hz, JHH =3.5 Hz, NH). 31P NMR (202.45 MHz, CDCl3,
ppm): δ=–1.8 (PP–N), –11.27 (PP=O) ppm. IR data (KBr,
cm–1): 3233, 3064 (υN–H); 2933 (υC–Halph); 2682 (υaliphatic);
1591 s (υAliphatic); 1488 s (υAr); 1193vs+1111 s (υP=O); 1074
m+1022 (υP–O); 937vs (υP–N).
General procedure for compounds L23–L27, and L33
A solution of amine or diamine (1 mmol) and triethylamine
(2 mmol) in hydrated THF were added at 50 °C to a solu-
tion of (R)2P(X=O, S)Cl (2 mmol) in hydrated THF. After
8 h refuxing, the solvent was removed in vacuum and the
resulting white powder was washed with distilled water and
recrystallized at room temperature.
1
(OEt)2(O)P–NH–C6H4–NH–P(S)(OEt)2 (L33) Mp: 169 °C. H
NMR (500.13 MHz, d-DMSO, ppm): δ=1.17 (t, 12H,
3JP–H = 7.0 Hz, 4CH3), 3.93 (m, 4H, CH2), 3.99 (m, 4H,
2
CH2), 6.8–6.9 (m, 4H, C6H4), 7.72 (d, 1H, JP–H =9.2 Hz,
2
NHP=O), 8.04 (d, 1H, JP–H =15.10 Hz, NHP=S). 31P NMR
(C6H5)2P(O)–NH–CH2–C6H10–CH2–NH–P(O)(C6H5)2 (L23) Mp:
209 °C. 1H NMR (500.13 MHz, d-DMSO, ppm): 1.22–1.36
(202.45 MHz, d-DMSO, ppm): δ=65.17 (P=S), 3.5
(P=O) ppm. IR data (KBr, cm–1): 3426 m+3265 m (υN–H),
1 3

Journal of the Iranian Chemical Society
2975+2916 (υAliphatic); 1509 m (υAr); 1276 (υP=O); 1216
(υP–O); 1034 s+961 s (υP–N); 808 m (υP=S).
where C is the diameter of the fungal colony (mean) in
control, and T is the diameter of the fungal colony (mean)
in the presence of the synthesized compound.
AChE enzymes assay
Descriptor calculation
Absorbance assay Human AChE activity measurements
were taken essentially according to Ellman’s method [26].
Reactions were carried out at 37 °C in 70 mM phosphate
bufer (Na2HPO4/NaH2PO4, pH=7.4) containing the AChE
(human erythrocyte; Sigma, Cat. No. C0663) enzyme (10
µl volume, diluted 100 times in phosphate bufer, pH=7.4),
DTNB (concentration=10–4 M and ATCh (concentra-
tion=1.35×10–4 M). Each compound was dissolved in
isopropanol and then added to the bufer for in vitro ChE
assays. The absorbance changes at 37 °C were monitored
with the spectrophotometer at 412 nm for 3 min, and three
replicates were run in each experiment. In the absence of
an inhibitor, the absorbance change was directly propor-
tional to the enzyme level. The reaction mixtures for deter-
mination of IC50 values (the median inhibitory concentra-
tion) consisted of DTNB solution, 100 μl; inhibitor, x μl;
acetylthiocholine iodide (ATCh) solution, 40 μl; phosphate
bufer (850 − x) μl and hAChE solution, 10 μl. The plot of
VI/V0 (VI and V0 are the activity of the enzyme in the pres-
ence and absence of inhibitors, respectively) against log[I],
where [I] is the inhibitor concentration, gave the IC50 values
of L1–L16 (Table 2).
A total number of 1497 descriptors of (0D), mono-dimen-
sional (1D), bi-dimensional (2D), and three-dimensional
(3D) were generated using E-Dragon software [18]. The
descriptors’ total was computed after removing invari-
able descriptors for all molecules and correlated descrip-
tors (R>0.9). The electronic and structural descriptors are
obtained by either the quantum chemical calculations, theo-
retical and experimental studies. All the quantum chemi-
cal calculations were carried out by using the Gaussian 09
program package [19]. The electronic descriptors include
the energy of frontier orbitals (EHOMO and ELUMO), hydro-
gen bonding energy (EHB), electrophilicity (ω), polarizabil-
ity (PL), and the net atomic charges (Q). Moreover, dipole
moment (μ), molar refractivity (Mr), surface area (SA), and
the molecular volume (Mv) are the structural descriptors.
The bioactivities of organophosphorus analogs and associa-
tion constants are expressed in terms of I%, log(I), and p(1/
IC50) (Table 2).
Data processing and modeling
Multiple linear regression (MLR) analysis
Antifungal assay
MLR is a method used for linear relationship modeling
between a dependent variable and an independent variable
[29]. In our study, the dependent variable is the compound
bioactivity values, and the independent variable is the
molecular descriptors. The values of regression coefcients
are calculated using MLR by applying the least-squares
curve ftting method. Regression equation takes the form
below:
We used Macrophomina phaseolina Mph44, which was pre-
viously isolated and identifed by Mahdizadeh and Safaie
2011 [27]. The isolate was originally obtained from melons
with charcoal rot disease in Khorasan. For evaluating the
efect of each compound on mycelial growth of M. pha-
seolina, the poisoned food technique was used [28]. The
synthesized compounds have been tested in vitro by transfer-
ring a specifc volume of each compound into a Petri dish
containing 20–25 ml melted warm PDA medium, and they
were gently shaken for mixing (Compounds fnal concentra-
tion=150 mg/L). The PDA plates were aseptically inocu-
lated by transferring a 6 mm diameter agar disc of 7-day-
old culture of the pathogen to the center of the Petri dish.
Three replications were maintained for each treatment. The
basal medium (PDA) without synthetic compounds served
as control. The inoculated plates were incubated at 25 °C
and colony diameter was measured and recorded after 3–7
days. The percentage of mycelial growth inhibition is given
by the following equation:
Y = b0 + b1X1 + b2X2 + … + bnXn + e
where Y is the dependent variable, X1, X2, …, Xk are inde-
pendent variables (descriptors), e is a random error and b0,
b1, b2, …, bk are the regression coefcients [29].
Genetic algorithm (GA)
GA is a searching procedure rooted in Darwin’s theory of
natural selection and evolution. It has three basic operations
(selection, crossover, and mutation). Because of its sim-
plicity and efectiveness, GA has been used as a promising
method for variable selection [30]. In our study, the genetic
[
]
Mycelial growth inhibition%(I%) = (C−T)∕C × 100
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Journal of the Iranian Chemical Society
Algorithm was used to select the main descriptors that
A mixture of chloroform/hexane (4:1) was used for L1 and
chloroform/methanol (2:1) for L11. The crystallographic data
and the details of the X-ray analysis for these compounds
are given in Table 1. Phosphorus atoms have a slightly dis-
torted tetrahedral confguration with the bond angles in the
range of 123.2° to 101.2° around the P atoms in L1 and L11
(Fig. 1). The P=O and P–O angles are 1.478 and 1.570 Å,
respectively. The phosphorus atoms have a slightly distorted
tetrahedral confguration with the bond angles in the range
101.94°–116.47° around the P atoms. The P=O and P–O
afected the fungicidal activity of the studied compounds.
Results and discussion
Spectral study
Phosphorus chemical shifts δ(31P) for L1–L16 were observed
in the range of 20.7 ppm (L16) to 26.5 ppm (L6). However,
phosphorus chemical shifts for L26–L35 were appeared in a
vast range (from –1.80 ppm for L34 to 69.83 ppm for L27).
This splitting pattern arises from spin couplings between the
phosphorus nucleus and the NH protons. The 1H NMR spec-
tra of L1–L8 showed two signals for the CH3O protons, while
in the case of L9–L16, two triplets and two quartets were seen
for OC2H5 protons. Protons of the C(H)–NH appeared in the
range of 4.66–5.87 ppm, and CH–N(H) protons appeared
from 5.14 to 8.04 ppm. The IR analysis spectra indicated that
the fundamental υP=O stretching modes for all the derivatives
appeared in 1230–1247 cm–1. N–H vibration of CH–N(H)
for all the compounds was seen in the range 3275–3377
cm–1. Stretching vibrations of υC=O were in the range of
1677 (L24) to 1687 cm–1 (L25).
distances are 1.467 and 1.574 Å, respectively. The RX
Z
( )
graph–set notation is descriptive of a Z–membered ringYpro-
duced by the X hydrogen bonds between the Y donor–accep-
tor units [31]. Polymeric chains formed in the crystal lattice
2( )
with cyclic R2 8 motifs via P=O…H–N (d=3.012 Å for
L1 and d=2.952 Å for L11) hydrogen bonds (Figs. 2, 3, 4).
Interestingly, each methanol molecule in the crystal network
of L1 is surrounded by six neighboring molecules via C–H…
O–C hydrogen interactions. These interactions are estab-
lished with diferent donor–acceptor distances of C–O(6)…
H(7)–C (d = 2.478 Å) to C–O(6)…H(2)–C (d = 2.707 Å)
(Fig. 5).
Anti‑AChE assay
AChE enzyme hydrolyzes acetylthiocholine to produce
thiocholine, which reacts with the DTNB (5,5′–dithiobis(2-
nitrobenzoic acid)) to produce 2-nitrobenzoate-5-mercap-
tothiocholine and 5-thio-2-nitrobenzoate. The inhibition
constant (log(1/IC50)) values of AChE against compounds
Crystal structure
Compounds L1 and L11 were recrystallized at room tem-
perature to obtain suitable crystals for the X-ray analysis.
Table 1 Crystallographic data
Forms
L1
L11
of compounds L1 and L11
Empirical formula
Formula weight
Temperature (K)
Crystal system
space group
a (Å)
C15H20N2O3PClO4
406.75
173 (2)
Monoclinic
P21/c
8.6749 (9)
11.0093 (8)
19.5372 (16)
90
C17H21N1O3PCl1
353.80
100 (2)
Monoclinic
P21/c
9.466 (10)
23.632 (3)
7.927 (7)
b (Å)
c (Å)
α (°)
90
β (°)
132.005 (2)
90
1851.6(3)
16, 1.459
848
92.706 (8)
90
1771.6(3)
4, 1.326
744
γ (°)
V (Å3)
Z, Calculated density (Mg m−3
F(000)
)
Crystal size (mm)
0.20×0.30×0.40
3.5–29.1
7340 / 3958, [R(int)=0.109]
R1 =0.1825, wR2 =0.4692
1.71 and –0.57
0.12×0.13×0.24
3.1–29.5
7395/ 4119, [R(int)=0.042]
R1 =0.5, wR2 =0.1160
0.46 and –0.54
θ range for data collection (°)
Refections collected / unique
Final R indices
Largest dif. peak and hole (e Å−3
)
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Journal of the Iranian Chemical Society
Fig.1 ORTEP representation of compounds L1 and L11
Fig. 2 P–O···H–N hydrogen bonds in L1 and L11
L1–L16 were in the range of –0.81 (L5) to 0.11 (L9)
(Table 2). In L3 and L4 with skeleton R(NC5H4–NH)C(H)
P(O)(OCH3)2, the inhibitory activity of L4 in which R=m-
CH3–C6H4 was higher than that in L3 with R=m-Br–C6H4
[p(1/IC50)=–0.77 and –0.40, respectively]. L5 with the skel-
eton (m-CH3–NC5H4–NH)(m-CH3–C6H4)C(H)P(O)(OCH3)2
versus AChE displayed the most potent inhibitory activity.
In L10, L11, and L12 with the skeleton (p-R–C6H4–NH)(Ph)
C(H)P(O)(OC2H5)2 and R = F, Cl, and Br, the inhibitory
of L10 is higher than the other two ligands. The presence
of fluorine electron acceptor connected to the aromatic
group increases the inhibitory potential of phosphoric acid
derivatives. To get a better understanding of the inhibitory
potential of the synthesized compounds, QSAR method was
used to examine the interaction between the phosphoric acid
derivatives and the AChE structures.
Anti‑fungal assay
Mycelial growth inhibition was measured using the poi-
soned food technique at 150 mg/L, in which the inhibi-
tion ratios ranged between 0 to 83%. L17 (p-Cl–C6H4–NH)
(p-Cl–C6H4)C(H)P(O)(OC2H5)2 was the most active com-
pound against the fungus with 83% inhibition of the myce-
lial growth and full inhibition of the microsclerotia repro-
duction as compared to the control, the compound L16,
(p-Cl–C6H4–NH)(NC5H4)C(H)P(O)(OC2H5)2, exhibited
up to 41% mycelial growth inhibition, and the formation of
the microsclerotia bodies was entirely inhibited. Both L2
and L3 with skeletons (p-Cl–C6H4)(NC5H4–NH)C(H)P(O)
(OCH3)2 and (m-Br–C6H4)(NC5H4–NH)C(H)P(O)(OCH3)2
showed reasonable antifungal activity by 49% and 46%
1 3

Journal of the Iranian Chemical Society
Fig. 3 Packing diagram of L1, formed by N–H···O–P hydrogen bonds
Fig. 4 Packing diagram of L11, formed by N–H···O–P hydrogen bond
respectively, the microsclerotia formation was signif-
cantly inhibited by both compounds even after 7 days of
treatment as well. Moreover, (C6H5)2–CH–N–[(CH2)P(O)
(OH)2]2 (L18) illustrated the moderate inhibition activity
with 33% growth inhibition, respectively. L10 with fuorine
substituent (p-F–C6H4–NH)(C6H5)C(H)P(O)(OC2H5)2,
showed a 22% inhibition ratio. Other compounds showed
relatively weak bioactivity on both mycelial growth and
microsclerotia production, as given in Table 2. The results
of the fungicidal assays were used to generate the QSAR
model as described below:
QSAR study
QSAR models of Anti‑AChE activity
QSAR studies were done in order to recognize the efect
of descriptors on the activity of AChE. The stepwise MLR
procedure was used for model selection, which is a com-
mon method used in QSAR studies, where n is the num-
ber of compounds, r is the correlation coefcient, R2 is the
determination coefcient of regression, Sreg is the standard
1 3

Journal of the Iranian Chemical Society
Fig. 5 Weak interactions around
the methanol molecule in L1
deviation of regression, and Fstatistic is the Fisher’s statistic
structures were drawn and pre-optimized using molecular
[29] (Eq. 1):
mechanics force felds (MM+) embedded in HyperChem
log(1/IC50) = −9.789ΔEL−H + 8.617ELUMO − 5.059QC − 3.077QN − 0.116ꢀ
− 0.003Mv − 0.733
(1)
n = 16;R2 = 0.937;Sreg = 0.298;Fstatistic = 22.375
In this equation, the inhibitory potency of AChE is mainly
infuenced by the electronic parameters (as frontier molecu-
lar orbital energies). Compared with the structural param-
eters, ΔEL-H and ELUMO with the coefcient values of –9.789
and +8.617 have a higher contribution in log(1/IC50) consid-
erably. The positive and negative signs of ΔEL-H and ELUMO
in log(1/IC50) disclose that the compound with the higher
energy diference between LUMO and HOMO (ΔEL–H) and
lower molecular orbital (ELUMO) has higher toxicity against
AChE enzyme.
program [17]. The three-dimensional molecular geom-
etries were refned using AM1 semi-empirical quantum-
chemical method procedure with a root-mean-square gra-
dient of 0.01 kcal mol–1. For the modeling job, a wide
set of theoretical molecular descriptors [18] were used to
capture and magnify distinct aspects of chemical struc-
tures. 1214 descriptors were computed out of 1497 using
E-Dragon 3.0 software [18] after removing invariable
descriptors for all molecules and correlated descriptors
(R > 0.9). The list of these descriptors, their meaning, and
the calculation procedures were provided with related ref-
erences by the E-Dragon [18, 32]. The genetic algorithm
[30] combined with multiple linear regression (GA-MLR)
was used to select the main set of descriptors from all
those that perform good predictions with minimum error
in comparison with the experimental data [33]. The ft-
ness function applied in this study was the leave-one-out
cross-validated correlation coefcient (Q2LOO) [34]. The
GA-MLR program is implemented in MATLAB 7.10.0
software [21]. The genetic algorithm method was applied
QSAR models of anti‑fungal activity
The dataset consists of 26 compounds from the organo-
phosphorus derivatives that showed diferent fungicidal
activity levels against the plant pathogenic fungus, M.
phaseolina (Table 2). The logarithmic values of mycelial
growth inhibition percentages were calculated and con-
sidered as the dependent variable for the feature selec-
tion and the QSAR analysis’s endpoints. The compounds’
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Journal of the Iranian Chemical Society
Table 2 The experimental and predicted bioactivity of the tested compounds by QSAR study
Compounds name and structure
Absorbance
Anti-fungal
Ref
assay(AChE)
assay
R
R’
p(1/IC50)
% I Log (I)exp
Log (I)pr Log
(I)pr.Loo
L1
L2
L3
L4
L5
L6
L7
L8
(o–NC5H4)
(C6H5)
–0.60
–0.40
–0.40
–0.77
–0.81
–0.26
–0.70
–0.20
–
–
–
–
–
–
–
–
–
–
–
–
(o–NC5H4)
(o–NC5H4)
(o–NC5H4)
(m-CH3–NC5H4)
(o-NC5H4)
(C6H5)
(p-Cl–C6H4)
(m-Br–C6H4)
(m-CH3–C6H4)
(m-CH3–C6H4)
(p-CHO–C6H4)
(p-CHO–C6H4)
(C6H5)
49.0 1.690
46.0 1.663
13.0 1.114
1.671
1.68
1.284
–
1.012
–
1.667
1.761
1.307
–
0.976
–
–
–
12.0 1.079
–
7.0 0.845
–
[3,5–(CH3)2–
0.963
0.978
2,6(N)2C4H]
R
R’
L9
(C6H5)
(C6H5)
(C6H5)
(C6H5)
(C6H5)
(C6H5)
(C6H5)
(p-F–C6H4)
(o-N–C5H4)
(p-Cl–C6H4)
0.11
–0.08
0.02
0.10
–0.74
–0.65
–0.08
–0.08
–
–
–
–
–
–
–
–
–
–
–
–
–
L10
L11
L12
L13
L14
L15
L16
L17
(p-F–C6H4)
(p-Cl–C6H4)
(p-Br–C6H4)
(p-I–C6H4)
(p-NO2–C6H4)
(p-Cl–C6H4)
(p-Cl–C6H4)
(p-Cl–C6H4)
R
22.0 1.342
1.250
–
–
–
–
–
1.239
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
41.0 1.613
83.0 1.919
1.597
1.936
1.593
1.974
L18
L19
L20
L21
L22
(C6H5)2–CH
(m-NC5H4)–(CH2)
(p-F–C6H4)–(CH2)
C5H9(CH2)3C5H9
C6H5–CH2
–
–
–
–
–
33.0 1.519
16 1.204
8.0 0.903
13.0 1.114
13 1.114
1.446
1.020
1.173
1.086
1.084
1.430
0.988
1.211
1.077
1.08
–
–
–
–
–
X
Y
Z
L23
NH(CH2)(C6H10)
(CH2)NH
O
C6H5
–
6.0 0.778
0.651
0.585
–
L24
L25
L26
(NH)2C(O)(NH)2
(NH)2C(O)(NH)2
S
O
O
OC2H5
OC6H5
C6H5
–
–
–
14.0 1.146
12.0 1.079
19.0 1.279
1.094
1.152
1.297
1.077
1.274
1.308
–
–
–
NH(C6H10)–CH2–
(C6H10)NH
L27
NH–C6H10–O–
R
O
OC6H5
–
0.0
–
–
–
–
L28
L29
(o-CO2H)–C5H9-
–
–
7.0 0.845
10.0 1.00
0.979
0.888
0.999
0.848
–
–
(p-OH)(o–CO2H)
C5H8–
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Journal of the Iranian Chemical Society
Table 2 (continued)
Compounds name and structure
Absorbance
Anti-fungal
assay
Ref
assay(AChE)
L30
–
5.0 0.699
0.564
0.939
0.518
0.919
[48]
L31
–
11.0 1.041
16.0 1.204
[49]
–
L32
–
1.082
1.075
L33
L34
–
–
4.0 0.602
1.0 0.000
0.71
0.728
0.231
–
0.114
[49]
L35
–
–
5.0 0.699
2.0 0.301
0.792
–
0.815
–
[50]
[51]
L36
L37
–
9.0 0.954
0.98
0.989
Log (I)exp. =experimental log I values of the studied compounds
Log (I)pr. =predicted log I values of the studied compounds
Log (I)pr.Loo. =predicted log I after applying in the leave-one-out cross-validated correlation coefcient (Q2
)
LOO
to select the best subset of descriptors. The GA-MLR
model and its statistical parameters are presented as Eq. 2:
R2 is the squared correlation coefficient; RMSE is
the root-mean-square error, Q2
shows the squared
LOO
Log I% = 4.1693 + 0.0363(T(P..Cl))−8.3494(De) + 3.3914(H8m) + 0.3867(Mor18e)
+ 0.3544(GGI4) + 6.0164(R1p+)
(2)
n = 26, R2 = 0.9237; RMSELOO = 0.1411; Q2LOO = 0.8718
1 3

Journal of the Iranian Chemical Society
cross-validation coefcients for leave-one-out. GGI4 from
Galves topological charge indices [18, 32, 35], and T(P..
Cl) from the topological descriptors [18, 32, 36] showed a
positive efect on the fungicidal activity. As demonstrated
in Eq. 2, the topological distance between P and Cl atoms
afects the studied compounds’ activity.
De belongs to the VHIM descriptors [37, 38], the
descriptor with the highest negative coefcient has a sig-
nifcant efect on the studied compounds’ inhibition ratio
values. Mor18e belongs to the 3D-MoRSE descriptors
(3D-Molecule Representation of Structures based on Elec-
tron difraction descriptors), which were described in 1996
[39, 40], and widely used in QSAR studies [41–43]. Other
3D-descriptors [18] are H8m and R1p + that belong to the
GETAWAY descriptors [44, 45] that have a good capa-
bility in QSAR/QSPR studies [46]. The two descriptors
showed a signifcant positive efect on the fungicidal activ-
ity of the tested molecules with a coefcient of +3.3914
and +6.0164, respectively.
Fig. 6 The plot represents the predicted log (I%) [Log (I)pr.Loo.)] val-
ues by the GA-MLR modeling against the experimental ones[Log
(I)exp.]. Good correlation can be seen between the predicted and the
experimental values with Q2LOO =0.8718
3D-descriptors showed good predictive ability com-
pared with 2D ones [47]. In our GA-MLR model, four of
six selected descriptors (De, Mor18e, H8m, and Mor30p)
belong to the 3D-descriptors [32], which may reveal the
importance of theses parameters in prediction the fungi-
cidal activity of our phosphoramidate derivatives. Table 3
shows the selected descriptors and their meanings. Table 2
shows the predicted values of the antifungal activity by this
model compared with the experimental ones. The plot of
the predicted against the experimental values is represented
in Fig. 6. It is clear that the predicted values are in good
agreement with the experimental ones. The cross-validation
results show that the generated GA-MLR model is valid, and
it can be set to calculate the inhibition ratio of these types of
organophosphorus compounds.
their bioactivities against Macrophomina phaseolina fungal
pathogen. Two compounds (p-Cl–C6H4–NH)(p-Cl–C6H4)
C(H)P(O)(OC2H5)2 (L17) and (p-Cl–C6H4)(NC5H4–NH)
C(H)P(O)(OCH3)2 (L2) had the most mortality on the M.
phaseolina. The cyclic motifs of L1 and L11 were further
determined by X-ray crystallography determination. The
biological activity on human acetylcholinesterase (AChE)
enzyme was determined and showed that L5 with (m-
CH3–NC5H4–NH)(m-CH3–C6H4)C(H)P(O)(OCH3)2 skel-
eton displays the most potent anti-AChE activity and the
electronic parameters ΔEL-H and ELUMO have the highest
contribution of human AChE. L17 was the most active com-
pound against the fungus with 83% inhibition of the mycelial
growth; the other tested compounds showed moderate to
weak antifungal activity. QSAR study showed the role of
3D-descriptors, especially 3D-MoRSE, VHIM, and GET-
AWAY descriptors in the fungicidal activity of the tested
Conclusions
Herein, QSAR has been performed using multiple linear
regressions (MLR) to investigate the relationship between
the phosphonic acid and bisphosphoramidate derivatives and
Table 3 The descriptors selected by GA-MLR method for antifungal activity
Descriptors
Chemical meanings
Descriptor group
T(P..Cl)
De
H8m
Mor18e
GGI4
Sum of topological distance between P..Cl
D total accessibility index/ weighted by atomic Sanderson electronegativities
H autocorrelation of lag 8/ weighted by atomic Masses
3D-MoRSE – signal18 / weighted by atomic Sanderson electronegativities
Topological charge index of order 4
Topological descriptors
WHIM descriptors
GETAWAY descriptors
3D-MoRSE descriptors
Galves topological charge
indices
R1p+
R maximal autocorrelation of lag 1/ weighted by atomic polarizabilities
GETAWAY descriptors
1 3

Journal of the Iranian Chemical Society
benzoylurea for the control of rice sheath blight. Pest Manag. Sci.
74(7), 1736–1746 (2018)
compounds. Further studies need to be done in terms of
these compounds’ bioactivities on both target and non-target
organisms to use them as a start point in fungicides design.
12. C. Hansch, T. Fujita, Classical and Three-Dimensional QSAR in
Agrochemistry (American Chemical Society, Washington, DC,
1995), pp. 1–12
Acknowledgements Financial support of this work by Iran National
Science Foundation: INSF and Tarbiat Modares University is grate-
fully acknowledged.
13. M. Karelson, V.S. Lobanov, A.R. Katritzky, Quantum-chemical
descriptors in QSAR/QSPR studies. Chem. Rev. 96(3), 1027–1044
(1996)
14. J. Devillers, A.T. Balaban, Topological Indices and Related
Descriptors in QSAR and QSPAR (CRC Press, Boca Raton, 2000).
15. R. Karbakhsh, R. Sabet, Application of diferent chemometric
tools in QSAR study of azolo-adamantanes against infuenza A
virus. Res. Pharm. Sci. 6(1), 23 (2011)
Authors contributions Gholivand, Valmoozi, Hosseini, Barzegar,
Nasrollah Tabar, and Yaghoubi participated in the synthesis of the
compounds and crystal structure analysis, Abbod provided the anti-
fungal assay and the GA-MLR QSAR study of the fungicidal activity
and wrote the related sections. Valmoozi were the major contributors
in writing the manuscript, Safaie participated in the antifungal assay,
Valmoozi provided the anti-AChE assay and related QSAR study. All
authors read and approved the fnal manuscript.
16. M. de Candia, L. Summo, A. Carrieri, C. Altomare, A. Nardec-
chia, S. Cellamare, A. Carotti, Investigation of platelet aggrega-
tion inhibitory activity by phenyl amides and esters of piperidine-
carboxylic acids. Bioorg. Med. Chem. 11(7), 1439–1450 (2003)
17. HyperChem, Hypercube, Inc., http://www.hyper.com
18. R. Todeschini, V. Consonni, A. Mauri, M. Pavan, Software
Dragon: Calculation of Molecular Descriptors (Department of
Environmental Sciences, University of Milano-Bicocca, Milan,
2003).
Funding This work was supported by Tarbiat Modares University.
Availability of data and materials All data generated or analyzed during
this study are included in article main text and supplementary material.
19. M.J. Frisch, G.W. Trucks, H.B. Schlegel, G.E. Scuseria, M.A.
Robb, J.R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci,
G.A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H.P. Hratch-
ian, A.F. Izmaylov, J. Bloino, G. Zheng, J.L. Sonnenberg, M.
Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida,
T. Nakajima, Y. Honda, O. Kitao, H. Nakai, T. Vreven, J.A.
Montgomery Jr., J.E. Peralta, F. Ogliaro, M. Bearpark, J.J.
Heyd, E. Brothers, K.N. Kudin, V.N. Staroverov, T. Keith, R.
Kobayashi, J. Normand, K. Raghavachari, A. Rendell, J.C.
Burant, S.S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J.M. Mil-
lam, M. Klene, J.E. Knox, J.B. Cross, V. Bakken, C. Adamo,
J. Jaramillo, R. Gomperts, R.E. Stratmann, O. Yazyev, A.J.
Austin, R. Cammi, C. Pomelli, J.W. Ochterski, R.L. Martin,
K. Morokuma, V.G. Zakrzewski, G.A. Voth, Dannenberg JJ.
Salvador, S. Dapprich, A.D. Daniels, O. Farkas, J.B. Foresman,
J.V. Ortiz, J. Cioslowski, D.J. Fox, Gaussian 09, Revision D.01
(Gaussian Inc., Wallingford, CT, 2013).
Compliance with Ethical standards
Conflict of interest The authors declare that they have no confict of
interests.
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