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The “ETA” Indices in QSAR/QSPR/QSTR Research
θ
Table 2. A representative list of endpoints modeled using TAU scheme indices
Endpoints Addressed Type of Chemicals Used Ref.
Narcosis of barnacle larvae in tomato plant and red spider
Inhibitory activity of Mycobacterium tuberculosis Substituted bromophenols Pal et al., 1989 Amoebicidal action against Entamoeba histolytica Polymethylene primary diamines Pal et al., 1990 Fuel property in terms of research octane number
(RON) and performance number (PN) Narcosis to tadpoles Diverse functional acyclic compounds Roy et al., 1999 General anesthetic activity Aliphatic hydrocarbons, halocarbons and ethers Roy et al., 2001 Heat of formation and heat of atomization Diverse functional acyclic compounds Roy & Saha, 2003a Lipid–Water Partition Coefficient Diverse functional acyclic compounds Roy & Saha, 2003b Aqueous solubility Diverse functional acyclic compounds Roy & Saha, 2003c Molar refractivity Diverse functional acyclic compounds Roy & Saha, 2005
Vapor toxicity of alkanols Pal et al., 1988
Acyclic alkane. Pal et al., 1992
than characterizing the core and the valence electronic environment (both local and mobile), parameters defining the branching and contribution of functional groups were also defined in the TAU scheme. Several modeling studies were performed using TAU indices and reliable results were obtained. Later the same group of authors also attempted to develop models employing other descriptors along with TAU parameters so as to judge the relative contribution of TAU scheme indices in predictive modeling studies. Table 2 summarizes the various endpoints modeled employing TAU scheme parameters. It was shown by Pal et al. (1988, 1989, 1990) that isosteric groups or isovertices have similar θ or
values.
The Motivation for Developing ETA Indices
Nearly a decade after the development of TAU indices, Roy and Ghosh (2003) observed that even the TAU scheme has some drawbacks and there are opportunities of their further development into more appropriate descriptors. The present authors’ group observed the following aspects of the TAU scheme to be inconsistent:
1. The core count ‘λ’ was observed to have a disproportionate incremental relationship with the atomic number of different vertices.
2. The VEM vertex count was not suitably distributed and a vertex forming sigma bond with another vertex of similar electronegativity and different electronegativity were given the same value.
3. Although it provides a weighting scheme for sigma and pi bonds, the TAU scheme does not dif­ferentiate the double bonds of different types i.e., ordinary alkenes, ordinary alkynes, conjugated system, aromatic system, etc.
4. Furthermore, the TAU scheme considers the contribution of functional groups at the molecular level, which should rather be considered at the atomic level or fragmental basis.
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The “ETA” Indices in QSAR/QSPR/QSTR Research
These were the chief motivations to the present authors’ group towards the development of a new group of predictor variables in order to achieve better diagnostic potential. In 2003, Roy and Ghosh presented a new formalism named ETA indices (Roy & Ghosh, 2003) comprising several molecular level as well as atomic level parameters. Then these indices were subjected to a thorough chemometric modeling employing different endpoints. Later in 2011, the present authors’ group realized the need for some more parameters to encode the issues related to hydrogen bonding propensity of molecules, mea­sure of polar surface area, unsaturation and electronegativity, and they came up with a second generation indices (Roy & Das, 2011). Figure 3 presents the basic features of the ETA indices from a perspective of their developmental stages.
The ETA Indices: Formalism
Presently the ETA indices comprise a set of two generation descriptors defining chemical features at the atomic as well as molecular level. Table 3 gives a generation-wise listing of the derived ETA indi­ces. In the present article, we would present all the ETA parameters from the viewpoint of atomic and molecular basis.
Figure 3. The principle features of ETA indices along with the path of their journey
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57
The “ETA” Indices in QSAR/QSPR/QSTR Research
ε
Table 3. Generation-wise presentation of the ETA indices
Generation Indices
First generation ∑α, ∑α/N
η′F, η
Second generation ΔαA, ΔαB, ε2, ε3, ε4, ε5, ΔεA, ΔεB, ΔεC, ΔεD, ψ1, ΔψA, ΔψB, Δβ, Δβ′, ∑β
, (∑α)p/∑α, (∑α)Y/∑α, (∑α)X/∑α, ∑ε, ∑ε/N, ∑β, ∑β′, ∑βs, ∑β′s, ∑βns, ∑β′ns, η, ηR, ηF,
v
local
local
local
, η
, η
R
local
, η′
F
, ηB, η′
B
F
Definition of the Atomic Level ETA Indices
The Core Count (α)
The ETA core count is formally defined as:
v
α =
−−Z Z
v
Z
.
PN
1
. (1)
1
ns(δ)
, ∑β′
ns(δ)
Here PN stands for period number, while Z and Z
v
represent atomic number and valence electron number respectively. Hydrogen atom being considered as the reference, α for hydrogen is taken to be zero. It was observed that α values of different atoms in common organic compounds show a high correla­tion (R=0.946) (Roy & Ghosh, 2003) with uncorrected van der Waals volume (Moriguchi et al., 1976).
Hence, a summed value of the parameter, i.e., Σα for all non-hydrogen atoms in a molecule gives a
measure of molecular bulk. In order to incorporate relativeness to this parameter with respect to the number of vertices, another term
Σα Nvis commonly used where Nv is the number of non-hydrogen
atoms, i.e., vertices in the molecule.
The Electronegativity Count (ε)
The ETA electronegativity count can be defined as follows:
ε α= − + ×0 3. ZV (2)
The term ε is characterized by a significant correlation (R=0.937) with Pauling’s electronegativity
scale (EN) (Roy & Ghosh, 2003).
The Hydrogen-Bonding Propensity (ψ)
The ETA hydrogen bonding propensity measure can be defines as follows:
α
ψ
= (3)
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The “ETA” Indices in QSAR/QSPR/QSTR Research
Based on the values of α and ε, this parameter (ψ) was defined which performs a discrimination among the atoms involved and not involved in hydrogen bonding. Table 4 gives the α, ε, and ψ values of some atoms commonly found in organic molecules.
The VEM Count (β)
In the ETA scheme, a new formalism has been incorporated to describe the VEM vertex measure. The VEM count β for a non-hydrogen vertex can be defined as:
β σ π δ= + +Σ Σx y (4)
where the parameters σ and π correspond to the number of sigma and pi bonds, respectively, in the con- nected hydrogen suppressed molecular graph and δ represents a correction factor having a value of 0.5 per atom with loan pair of electrons capable of making resonance with an aromatic ring (e.g. nitrogen of aniline, oxygen of phenol etc.). Here x and y are the respective contributions of sigma (σ) and pi (π) bonds. We have assigned different contribution values for the sigma as well as pi bonds in the VEM count (β) of the ETA scheme. For the computation of β, contribution of a sigma bond (x) between two atoms of similar electronegativity ( two atoms of different electronegativity ( for π bonds (y) are assigned depending on the type of double bonds as depicted below.
ε 0 3. ) is considered to be 0.5, and for a sigma bond between
ε >0.3), it is considered to be 0.75. Again, the contributions
1. For a π bond between two atoms of similar electronegativity (
2. For a π bond between two atoms of different electronegativity (
ε 0 3. ), the value of y is 1.
ε >0.3) or for conjugated (non-
aromatic) π system, y is considered to be 1.5.
3. For an aromatic π system, the value of the contribution factor is 2.
Table 4. α, ε, and ψ values of the commonly occurring atoms
Sl. No. Atoms α ε ψ
1 H 0.000 0.300 0.000 2 C 0.500 0.700 0.714 3 N 0.400 1.100 0.364 4 O 0.333 1.467 0.227 5 F 0.286 1.814 0.158 6 P 1.000 0.500 2.000 7 S 0.833 0.967 0.861 8 Cl 0.714 1.386 0.515 9 Br 1.333 0.767 1.738 10 I 1.643 0.457 3.595
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59
The “ETA” Indices in QSAR/QSPR/QSTR Research
Hence, it is observable that the TAU scheme considered a value of 2.0 for all kinds of π bonds which is not in the case of ETA formalism. Furthermore, the VEM sigma contribution for a non-hydrogen vertex can be designated as β
and defined as:
s
β σsx= Σ (4a)
Similarly, the VEM non-sigma contribution of a non-hydrogen vertex can be designated as β defined as:
β π δ
ns
y= +Σ (4b)
It should be noted that,
β β β= +
s ns
. (4c)
The VEM Vertex Count (γ)
The VEM vertex count γi of the ith vertex in a connected molecular graph can be defined as:
α
γ
where α connected to the atom and lone pair of electrons (if any).
i
= (5)
i
β
i
stands for the alpha value for the ith vertex and βi being the VEM count considering all bonds
i
and
ns
The Atom Level Composite Index ([η]i)
The contribution of a particular vertex or position (within the common substructure in a congeneric series) to the composite index η can be determined in the following manner:
0 5
γ γ
i j
=
[ ].η
i
j i
Here, [η] to the topological distance between the i
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r
 
i
(6)
2
ij
denotes the contribution of the ith vertex to η. The term in the denominator rij corresponds
th
and jth atoms.
( )
( )
( )
The “ETA” Indices in QSAR/QSPR/QSTR Research
Definition of the Molecular Level ETA Indices
The molecular level indices indicate computation of those descriptors which involve the entire molecular structure. There are some ETA indices which can be computed at the atomic level as well as at the whole molecular level, while there are some indices for whole molecule only. Table 5 presents a comprehensive assembly of ETA indices for the whole molecule/ molecular fragment/ substructure with their notation, mathematical definition and significance. We would just like to clarify that throughout the Table 5, N indicates total number of atoms including hydrogens while N i.e., only non-hydrogen atoms. Again few terms are associated with a subscript ‘R’, e.g., N etc. corresponding to a reference alkane which refers to a molecular graph of the original structure where all the heteroatoms are replaced with carbon and multiple (double and triple) bonds with single bonds. Furthermore, four terms in Table 5 namely Δα
, ΔαB, ΔψA and ΔψB are spline terms (denoted by angle
A
bracket or chevrons, < >) meaning that any negative value will be considered zero. Regarding the com­putation of VEM β count, one more subtle point to be noted is that the index β is computed for edges taking the value of vertices. Since an edge is comprised of two vertices, the following relationships exist:
= Sum of βs values of all non-hydrogen vertices / 2
β
s
corresponds to the number of vertices,
v
, [Σα]R, ηR
R
β
= (Sum of βns values of all non-hydrogen vertices – Sum of all β
ns
Sum of all β
β
= Sum of all β
ns(δ)
values of all vertices
ns(δ)
values of all vertices
ns(δ)
values of all vertices) / 2 +
ns(δ)
Table 5. Definition of the ETA indices at the whole molecule/fragment/substructure level
Sl. No. Mathematical Definition Significance
1 α
2
3
4
5
6
Σα N
α
v
Σ Σα α
p
Σ Σα α
Y
Σ Σα α
X
=
A
α α
N
v
Summed α values of all non-hydrogen vertices of a molecule (or fragment/ substructure). Gives a measure of molecular bulk (or for the fragment/ substructure).
A relative measure of molecular bulk with respect to the number of vertices.
(∑α)p stands for summation of α values of the vertices that are joined to one other non-hydrogen vertex in the connected molecular graph. Gives a measure of molecular shape.
(∑α)Y stands for summation of α values of the vertices that are joined to three other non-hydrogen vertices in the connected molecular graph. Gives a measure of molecular shape.
(∑α)X stands for summation of α values of the vertices that are joined to four other non-hydrogen vertices in the connected molecular graph. Gives a measure of molecular shape.
 
R
A measure of count of heteroatoms.
α α
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α
=
B
R
N
v
A measure of count of hydrogen bond acceptor atoms and/or polar surface area.
continued on following page
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The “ETA” Indices in QSAR/QSPR/QSTR Research
Table 5. Continued
Sl. No. Mathematical Definition Significance
8
9
10
11
12
13
14
15
ε
1
ε
2
ε
3
ε
4
ε
5
ε ε ε
ε ε ε
ε ε ε
ε
=
N
ε
=
=
=
=
A
B
C
EH
N
v
ε
N
R
ε
N
SS
ε ε
EH XH
N N
v XH
=
1 3
=
1 4
=
3 4
R
SS
+
+
Summed epsilon (ε) value in a molecule relative to the total number of atoms including hydrogen. Gives a measure of electronegative atom count.
ΣεEH stands for summed epsilon count of a molecule excluding hydrogen atoms. Gives a measure of electronegative atom count.
Summation of epsilon (ε) value relative to the total number of atoms including hydrogen in the connected molecular graph of the reference alkane.
Summation of epsilon (ε) value relative to the total number of atoms including hydrogen for a saturated carbon skeleton moiety of the normal molecule i.e., carbon-carbon multiple bonds considered as single bond.
Here, ΣεXH stands for summed epsilon value for those hydrogen atoms which are connected to a heteroatom (e.g., −OH, −NH2, −SH etc.) and NXH gives a count of such hydrogens.
A measure of contribution of unsaturation and electronegative atom count.
A measure of contribution of unsaturation.
A measure of contribution of electronegativity.
16
17 β
18 β
19 β
20 β
21 β
22
23
ε ε ε
β β β=
=
D
2 5
/
s
/
ns
/
ns(δ)
/
β β
=
δ δns ns v
( )
ns s
( )
A measure of contribution of hydrogen bond donor atoms.
Σ Σ′=β β
s s v
contribution) relative to the number of vertices. Gives a measure of electronegative atom count of the molecule relative to the molecular size.
Σ Σ′=β β
ns ns v
lone electron pairs capable of resonance if any (VEM non-sigma contribution) relative to the number of vertices. Gives a measure of electron-richness of the molecule relative to the molecular size.
Σ Σ Σβ β β= +
vertices in a molecule.
Σ Σ′=β β N
measure of electronic features of the molecule relative to the molecular size.
A measure of lone electrons entering into resonance with an aromatic system.
A measure of lone electrons entering into resonance relative to the molecular
N
size.
A measure of relative unsaturation content.
N
. Summed β values for all the sigma bonds (VEM sigma
N
. Summed β values for all the non-sigma bonds including
s ns
. Summation of β values of all non-hydrogen
v
. Summed β values relative to the number of vertices. Gives a
continued on following page
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The “ETA” Indices in QSAR/QSPR/QSTR Research
Table 5. Continued
Sl. No. Mathematical Definition Significance
β
/
∆∆β
24
25
26
27
28
=
N
v
α
=
1
= 0 7141.
A
= −10 714.
B
=
<
i j
   
ε
γ γ
i j
r
ij
=  
EH
0 5.
  
2
 
ψ
ψ ψ
ψ ψ
η
α
ε
2
A measure of relative unsaturation content with respect to the molecular size.
N
v
A measure of hydrogen bonding propensity of the molecules and/or polar surface area.
A measure of hydrogen bonding propensity.
A measure of hydrogen bonding propensity.
The composite index (η). Here rij stands for the topological distance between ith atom and jth atom. Accounts for the global topology of the molecule/fragment/ substructure under investigation.
29 η
30
31
32 η
33
34
35
36
γ γ
  
ij
i j
2
r
ij
( )
1
1
ij
0 5.
   
i j
( )
i j
=
η
R
<
i j
η η η
=
F R
/
F
local
η γ γ
=
< =
i j r
local R
local F
local
F
=
 
< =
i j r
local local
=
R
localRlocal
η γ γ
η η η
η
η η η
B N
=η η N
  
R
.,0 5
The composite index for reference alkane (ηR).
The functionality index (ηF). Gives a measure of the heteroatoms and multiple bonds.
F F v
Functionality index relative to the molecular size.
The local composite index (η structure since only bonded interactions are considered (rij=1).
.,0 5
The local composite index for the corresponding reference alkane.
 
R
Local functionality contribution.
local
F
Local functionality contribution relative to molecular size.
ETA branching index (ηB), where NR stands for the number of rings in the connected molecular graph of the reference alkane structure and η
N= + ×0 086.
local
R
η
N
=η η
v
. The composite index relative to molecular size.
N
local
). Reflects the local topology of the analyzed
local
=η η
N
F
v
N= + ×1 414 3 0 5. ( ) .
v
when
local
can be defined as:
N
Nv> 3
, otherwise 0.
37 η
/
B
B B v
=η η
N
. It is a measure of branching relative to molecular size.
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63
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The “ETA” Indices in QSAR/QSPR/QSTR Research
The “ETA” Indices in QSAR/QSPR/QSTR Research
SAMPLE CALCULATION
The ETA indices are easily computed from the information of molecular composition and two dimen­sional representations. The topological aspects of the ETA formalism is enlightened using the hydrogen suppressed molecular graph based distance matrix, while parameters like shape, size, electronegativity, electron-richness, heteroatom content, unsaturation, hydrogen bonding propensity etc. involve chemical attributes of atoms and bonds. Since, such calculation does not require any spatial information or energy minimization operation, these indices for a large number of compounds can readily be computed. Table 6 shows sample calculations of two compounds namely 2-cholobenzaldehyde and 3-hydroxypyridine.
Computation of the ETA Indices
At the beginning, the ETA indices (first generations only) were computed using our in-house GW–BA­SIC programs namely KRETA1 and KRETA2 (GW-BASIC programs, 2003) that use distance matrix and VEM vertex count as inputs. Presently, two software platforms allow the computation of ETA indices namely Dragon (version 6) (Dragon version 6, 2010) and PaDEL-Descriptor (an open source software of the NUS, http://padel.nus.edu.sg/software/padeldescriptor/) (Yap, 2011). In Dragon (version 6), only first generation ETA indices can be computed while PaDEL-Descriptor allows the computation of all indices in this scheme. Table 7 presents the list of ETA indices corresponding to the notations used in Dragon (version 6) and PaDEL-Descriptor software.
AN OVERVIEW OF THE MODELED STUDIES
The ETA indices have been subjected to extensive chemometric modeling studies in order to judge their diagnostic potential since the inception. The initial studies reflected the predictive power of the first generation indices only, while after the development of the second generation indices, the appli­cation of both generation descriptors have been exemplified. The QSAR studies employing the ETA indices cover a wide variety of chemicals ranging from simple aliphatic hydrocarbons to complex drug molecules. Recently, the ETA indices have also been successfully employed to model relatively novel chemicals like ‘ionic liquids’. Table 8 gives an overview of the in silico models reported so far using the ETA indices. It may be noted that in all the studies, various other topological non-ETA indices have been additionally used and the ETA indices have been found to produce models of better or comparable statistical qualities in comparison to the models from non-ETA indices. In many of the cases, the qual­ity of the developed equations improved when ETA indices have been used in combination with other non-ETA parameters. Another observation was also very interesting during the modeling of non-specific toxicity endpoints when addition of computed lipophilicity parameter AlogP to the ETA descriptor pool gave better results. It may be noted that the non-specific toxicity of chemicals is largely encoded by the ETA bulk parameter that gives a measure of lipophilicity of the molecules. The toxicity shows either a proportionate or a parabolic relationship with molecular bulk. The toxicity is also influenced by mo­lecular branchedness as encoded by the ETA branching and shape parameters. The ETA functionality parameters additionally show the positive effect of lipophilic heteroatoms like chlorine, bromine etc. and carbonyl oxygen group towards the toxicity. The latter factor is implicated to the Schiff base formation phenomenon with biological amines. The toxicity of chemicals is found to be negatively related to the
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( )
( )
( )
( )
( )
( )
The “ETA” Indices in QSAR/QSPR/QSTR Research
0.500 0.333
1.000 1.767
1.250 0.750
2.000 0.500
3.250 1.250
0.154 0.266
0.548 0.574
0.500 0.500
1.300 1.600
1.000 0.500
0.500 1.000
1.813 1.933
0.181 0.194
Value
-0.115
0.071
0.607
0.929
1.536
0.321
0.071
0.533
0.181
0.000
Atom Level Indices
(Arbitrary
Numbering)
0.400 0.500 0.500 0.500 0.500
i
α
Normal
Structure:
1.100 1.000 0.700 1.000 1.000
i
1.500 1.250 1.750 1.000 1.000
i
]
s
2.000 2.000 2.000 2.000 2.000
i
]
ns
3.500 3.250 3.75 3.000 3.000
i
Reference
0.114 0.154 0.133 0.167 0.167
i
Alkane:
0.500 0.587 0.665 0.627 0.594
i
0.500 0.500 0.500 0.500 0.500
i
]
R
1.300 1.300 1.000 1.300 1.300
i
]
R
1.000 1.000 1.500 1.000 1.000
i
]
R
Saturated
0.500 0.500 0.333 0.500 0.500
1.856 1.928 1.938 1.928 1.856
i
]
]
R
Carbon
Skeleton:
s
ns
/
3.414 β
local
N
0.103 η
0.556
/
0.015 β
0.631 β
B
1
0.155 η
0.000 ε
p
Y
Σ Σα α
Σ Σα α
0.889
C
D
3.394 Δε
2.321 Δε
local
local
R
F
0.462 η
0.194 0.192 0.182 0.186 0.180
i
i
]
F
R
v
Σα N
0.000
-0.119 α 3.233 η
ns(δ)
A
B
1
0.867 Δβ
0.433 β
0.548 ψ
0.796 Δψ
0.197 Δψ
0.083
A
2
3
4
0.000 ε
0.038 ε
X
A
B
Σ Σα α
0.056 Δα
0.586 η 2.048 ε
B
5
6.267 ε
0.654 Δε
1.073 Δε
F
R
local
0.128 η
0.000 η
2-Cholorobenzaldehyde 3- Hydroxypyridine
ns
s
/
C
4.343 Δε
Atom Level Indices Structure
1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7
0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.333 0.714
0.700 0.700 1.000 1.000 1.000 1.000 1.000 1.467 1.386 ε
1.500 1.750 1.000 1.000 1.000 1.000 1.25 0.750 0.750 [β
2.000 2.000 2.000 2.000 2.000 2.000 1.500 1.500 0.500 [β
3.500 3.750 3.000 3.000 3.000 3.000 2.750 2.250 1.250 β
0.143 0.133 0.167 0.167 0.167 0.167 0.182 0.148 0.571 γ
0.875 0.886 0.783 0.720 0.718 0.777 0.757 0.519 1.036 [η]
0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 [α
1.000 1.000 1.300 1.300 1.300 1.300 1.300 1.600 1.600 [ε
1.500 1.500 1.000 1.000 1.000 1.000 1.000 0.500 0.500
0.333 0.333 0.500 0.500 0.500 0.500 0.500 1.000 1.000
Index Vertex (Arbitrary Numbering) Index Vertex (Arbitrary Numbering)
i
i
]
]
s
i
α
ns
i
ε
i
[β
[β
β
i
i
i
i
]
]
]
]
i
R
R
R
i
γ
R
[η]
[α
[ε
Molecular Level Indices Molecular Level Indices
local
R
2.272 2.260 2.226 2.092 2.110 2.250 2.264 2.169 2.353 [η
0.155 0.153 0.160 0.152 0.155 0.164 0.167 0.183 0.146 [η
Index Value Index Value Index Value Index Value Index Value Index
i
i
]
]
F
R
[η
[η
α 4.547 η
/
D
2.800 Δε
local
F
0.505 η
0.018 β
4.414 β
local
N
0.230 η
0.661 β 1.444
B
1
0.220 η
0.000 ε
v
p
Y
Σ Σα α
Σ Σα α
Σα N
ns(δ)
A
B
1
0.861 Δβ 0.333 Δα
0.433 β
0.553 ψ
0.861 Δψ
0.228 Δψ
0.108 η
A
2
3
4
0.005 ε
0.000 ε
X
A
B
Σ Σα α
Δα
Δα
η 3.536 ε
B
5
9.998 ε
0.718 Δε
1.543 Δε
F
R
local
η
η
η
Structure
(Arbitrary
Numbering)
Normal
Table 6. Computation of ETA indices using two sample molecules 2-cholorobenzaldehyde and 3-hydroxypyridine
Structure:
Reference
Alkane:
Saturated
Carbon
Skeleton:
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