Abstract
In this paper, a novel eccentric neighborhood degree-based topological indices, termed eccentric neighborhood Zagreb indices, have been conceptualized and its discriminating power investigated with regard to the predictability of the boiling point of the chemical substances. The discriminating power of the eccentric neighborhood Zagreb indices was compared with that of Wiener and eccentric connectivity indices. Some explicit results for those new indices for some graphs and graph operations such as join, disjunction, composition, and symmetric difference.
MSC: 05C12, 05C90, 05C76
Keywords: Eccentric neighborhood Zagreb indices, Eccentricity neighborhood degree, Graph operations, Boiling point, Molecular descriptors
1. Introduction
A molecular graph [8], [9] is a connected simple graph such that the vertices and edges are supposed to be atoms and chemical bonds respectively. Chemical graph theory is an important branch of both chemistry and graph theory as it has taken a lot of attention because of the important results obtained in chemical graph theory and has been applied in many applications such as chemical engineering as well as pharmaceutical [13]. The main idea of chemical graph theory is that the physical and chemical properties of molecules can be studied and explained using information [10]. It can also be noted that in contemporary mathematical chemical literature, there are many descriptors of molecular structure based on vertex degree. In this research by a graph, we main undirected finite, simple and connected graph. For a graph, , and denote the vertex set and edge set, respectively. The set of all neighbors of u is said the open neighborhood of u, i.e., . The degree of a vertex u in G is defined as . The length of the shortest path joining between the two vertices u and v is called the distance between those two vertices and is denoted by or . The origin of topological indices goes back to 1947 when a chemist by name, Wiener established the first topological index, recognize as the Wiener index [16], to search for boiling points and defined as . Among the topological indices defined in the initial phase, Zagreb indices are related to the most common molecular descriptors. First introduced by Gutman and Trinajestic [7], the first and second Zagreb indices are given as follows:
For more details of those indices see [3], [6], [11]. The eccentricity .
Also, and are the radius and diameter of G respectively. The eccentric connectivity index [15] is defined as . For some applications of eccentric connectivity index see [5], [10], [14], and for the mathematical properties of this topological index [12], [17], [19]. The goal of this research is to define new topological indices based on new parameter known as the neighborhood eccentricity of the vertex, these new indices have a good significant to applied in chemical graph theory also have mathematical significance.
Lemma 1.1
[4] Let and be any two graphs. Then
- (a)
- (b)
- (c)
- (d)
.
2. Materials and methods
In this research, the primary amines group was adopted as a standard group in which the chemical and physical applicability of the new indices are tested. Primary amines are widely used to test the applicability of topological indices, as they were used in the Wiener index test in estimating the boiling points of these compounds [15]. Also, it is used for the structural determination of the paraffin boiling point [16]. For more studies application of topological indices on primary amines, the reader can refer to the following references [2], [18]. The values of the boiling point are described in Table 2 according to their experimental data [15], and also https://pubchem.ncbi.nlm.nih.gov After that, a non-linear regression analysis is performed using the R-program analysis, and with this analysis, the expected boiling point values of the primary amines are estimated. Linear combinations of the obtained models are plotted using Excel. This is the first part of organizing the main results of this research. In the second part, the novel-designed indices are studied and analyzed mathematically to study their properties, apply them to different families of graphs, and perform basic operations on them. We have used the analytical method, in the process.
Table 2.
Relationship of predicted boiling points calculated by eccentric neighborhood Zagreb indices, ξc(G) and W(G) with BP of primary amines.
| Compound | BP | BP ENM1(G) | BP ENM2(G) | BP ENM3(G) | BP ξc(G) | BP W(G) |
|---|---|---|---|---|---|---|
| n-propylamine | 49 | 50.94 | 52.67 | 45.63 | 53.27 | 46.7 |
| 2-aminopropane | 33 | 42.76 | 36.41 | 41.65 | 39.97 | 44.1 |
| 2-amino-2-methylpropane | 46 | 50.12 | 45.91 | 60.19 | 48.19 | 60.52 |
| 2-aminobutane | 63 | 65.06 | 67.08 | 64.68 | 64.97 | 64.57 |
| 2-methylpropylamine | 69 | 65.06 | 67.08 | 64.68 | 64.97 | 64.57 |
| n-butylamine | 77 | 71.72 | 74.96 | 66.87 | 75.6 | 68.42 |
| 2-amino-2-methylbutane | 78 | 80.13 | 81.02 | 87.25 | 75.62 | 82.33 |
| 2-aminopentane | 92 | 87.74 | 90.84 | 88.21 | 89.31 | 88.6 |
| 3-methylbutylamine | 96 | 87.74 | 90.84 | 88.21 | 89.31 | 87.07 |
| 2-methylbutylamine | 96 | 82.9 | 88.26 | 84.35 | 85.52 | 88.6 |
| n-pentylamine | 104 | 98.38 | 100.75 | 92.94 | 101.94 | 93.08 |
| 4-methylpentylamine | 125 | 116.57 | 117.86 | 116.78 | 117.05 | 113.25 |
| n-hexylamine | 130 | 124.74 | 125.49 | 119.29 | 128.1 | 120.54 |
| 3-methylpentylamine | 114 | 110.97 | 115.83 | 112.55 | 113.79 | 113.25 |
| 4-aminoheptane | 139 | 135.26 | 137.65 | 137.76 | 138.67 | 141.55 |
| 2-aminoheptane | 142 | 145.13 | 144.02 | 145.44 | 144.5 | 145.65 |
| n-heptylamine | 155 | 154.88 | 154.88 | 149.21 | 157.22 | 150.65 |
| n-octylamine | 180 | 184.83 | 181.7 | 179.32 | 186.2 | 183.3 |
| n-nonylamine | 201 | 217.67 | 211.99 | 212.35 | 217.59 | 218.39 |
| 2-aminoundecane | 237 | 276.5 | 267.77 | 278.43 | 268.93 | 289.23 |
| 3-aminopentane | 91 | 82.9 | 88.26 | 84.35 | 85.52 | 87.07 |
3. Results and discussion
To understand the different properties of chemicals, laboratory tests must be performed, and this is extremely costly. To vanquish this problem, many topological indices in theoretical chemistry have been introduced and defined. To define a new topological index one must verify two things. The index must correspond well with at least one physical or chemical property of a standard data set, on the other hand, it should be simple in the formulation it and give some theoretical insight. In this section, we have two subsections. First, we define the significance of the first, second, and third eccentric neighborhood Zagreb indices in determining the predicted boiling point using nonlinear regression analysis. Second, we study the eccentric neighborhood Zagreb indices mathematically.
3.1. The significance of the eccentric neighborhood Zagreb indices in predicting the boiling point of molecular descriptors
To verify the importance and the efficiency of a topological index for modeling physicalchemical properties we use nonlinear regression analysis. Commonly, for such an investigation, primary amines are useful because of their diverse structurally. In this section, we find the Wiener index and eccentric connectivity index with the eccentric neighborhood Zagreb indices and the data listed in Table 1. We get the relationship of eccentric neighborhood Zagreb indices with boiling points of primary amines as in Table 2. Table 3, is shown that the predicted boiling points calculated by the first, second, and third eccentric neighborhood Zagreb indices are strongly correlated with boiling points of primary amines (), () and () respectively, (see Fig. 1, a, b and c). Also, we present the correlation coefficient of boiling points predicted by the eccentric connectivity index and Wiener index with these indices (see Fig. 2, a and b). In Table 4, we determined the correlation coefficient of , and with and . For more delicate statistical tests, which rank the indices by their predictive power, see Table 5.
Table 1.
Eccentric neighborhood Zagreb indices with eccentric connectivity index and Wiener index of primary amines.
| Compound | ξc(G) | W(G) | ENM1(G) | ENM2(G) | ENM3(G) | |
|---|---|---|---|---|---|---|
| 1 | n-propylamine | 14 | 10 | 58 | 45 | 24 |
| 2 | 2-aminopropane | 9 | 9 | 39 | 18 | 21 |
| 3 | 2-amino-2-methylpropane | 12 | 16 | 56 | 32 | 36 |
| 4 | 2-aminobutane | 19 | 18 | 101 | 82 | 40 |
| 5 | 2-methylpropylamine | 19 | 18 | 101 | 82 | 40 |
| 6 | n-butylamine | 24 | 20 | 126 | 108 | 42 |
| 7 | 2-amino-2-methylbutane | 24 | 28 | 162 | 131 | 62 |
| 8 | 2-aminopentane | 31 | 32 | 199 | 174 | 63 |
| 9 | 3-methylbutylamine | 31 | 31 | 199 | 174 | 63 |
| 10 | 2-methylbutylamine | 29 | 32 | 175 | 162 | 59 |
| 11 | n-pentylamine | 38 | 35 | 258 | 225 | 68 |
| 12 | 4-methylpentylamine | 47 | 50 | 379 | 332 | 95 |
| 13 | n-hexylamine | 54 | 56 | 442 | 388 | 98 |
| 14 | 3-methylpentylamine | 45 | 50 | 339 | 318 | 90 |
| 15 | 4-aminoheptane | 61 | 75 | 531 | 488 | 121 |
| 16 | 2-aminoheptane | 65 | 79 | 623 | 546 | 131 |
| 17 | n-heptylamine | 74 | 84 | 722 | 654 | 136 |
| 18 | n-octylamine | 96 | 120 | 1078 | 972 | 178 |
| 19 | n-nonylamine | 122 | 165 | 1562 | 1425 | 228 |
| 20 | 2-aminoundecane | 169 | 275 | 2687 | 2474 | 339 |
| 21 | 3-aminopentane | 29 | 31 | 175 | 162 | 59 |
Table 3.
Correlation coefficient of boiling points predicted by eccentric neighborhood Zagreb indices, ξc(G) and W(G) with BP of primary amines.
| BP ENM1(G) | BP ENM2(G) | BP ENM3(G) | BP ξc(G) | BP W(G) | |
|---|---|---|---|---|---|
| BP | 0.987 | 0.993 | 0.9814 | 0.99199 | 0.97875 |
Figure 1.
Linear fitting of BP predicted by (a) ENM1(G), (b) ENM2(G), (c) ENM3(G) with BP.
Figure 2.
Linear fitting of BP predicted by (a) W(G) with BP, (b) ξc(G) with BP.
Table 4.
Correlation coefficients of ENM1(G), ENM2(G) and ENM3(G) with ξc(G) and W(G).
| ENM1(G) | ENM2(G) | ENM3(G) | ξc(G) | W(G) | |
|---|---|---|---|---|---|
| ENM1(G) | 1 | ||||
| ENM2(G) | 0.9999 | 1 | |||
| ENM3(G) | 0.9869 | 0.9865 | 1 | ||
| ξc(G) | 0.9807 | 0.9802 | 0.9962 | 1 | |
| W(G) | 0.9978 | 0.9979 | 0.994 | 0.9872 | 1 |
Table 5.
Some delicate statistical tests, which rank the indices by their predictive power.
| Residual Standard Error on 19 degree of freedom | Multiple R-Squared | Adjusted R-Squared | F-Statistic on 1 and 19 DF | P-Value | |
|---|---|---|---|---|---|
| ENM1(G) | 0.09442 | 0.966 | 0.9642 | 539.2 | 2.077 × 10−15 |
| ENM2(G) | 0.05331 | 0.9891 | 0.9886 | 1732 | <2.2 × 10−16 |
| 0.1161 | 0.9485 | 0.9458 | 350.1 | 1.064 × 10−13 | |
| ξc(G) | 0.07367 | 0.9793 | 0.9782 | 897.9 | <2.2 × 10−16 |
| W(G) | 0.1209 | 0.9442 | 0.9413 | 321.4 | 2.301 × 10−13 |
The non linear regression analysis equations which are used are:
3.2. Eccentric neighborhood Zagreb indices of graphs and graph operations
Definition 3.1
Let be a connected simple graph and be the eccentricity neighborhood degree. Then the first, second and third eccentric neighborhood Zagreb indices are defined as follows:
Proposition 3.2
- 1.
For star graphwithvertices, we have,and.
- 2.
Ifwithvertices, then,and.
- 3.
Suppose,. Then
- 4.
Ifis the wheel graph withvertices, then,, and.
Lemma 3.3
Letwith vertex set. Then
- 1.
If n is even and, then
- 2.
If n is odd and, then
Proposition 3.4
- 1.
Letbe a path withwhere n is even, then
- 2.
Ifis even, then
- 3.
Letbe a path withwhere n is odd, then
- 4.
If n is odd and, then
An banana tree denoted by , defined by Chan et al. [1], is a graph obtained by connecting one leaf of each of r copies of an s-star graph with a single root vertex that is different from all the stars.
Lemma 3.5
Ifwith, andand w is the root vertex, then
Proposition 3.6
Supposewithand. Then
Proposition 3.7
For any graph G
Proposition 3.8
Suppose G is a graph with diameter and radiusandrespectively, then
,
,
.
Equality holds if and only if.
3.3. Join
A join [11] of two graphs G and H with and as disjoint vertex sets is the graph on the vertex set and the edge set .
Lemma 3.9
For any two graphs G and H
- (a)
If, then.
- (b)
Ifandsuch that,, then
We can partition the edge set of as follows:
Let be the set of edges connecting vertices of G with vertices of H. Then
Theorem 3.10
Let G and H be any two graphs with,and. Then
Proof
Applying Lemma 3.9(b), we get
To prove (b) and (c) we use the partition of the edge set as mentioned earlier. Hence applying Lemma 3.9(b), we get
□
Corollary 3.11
Suppose G and H are any two graphs such that,. Then
Example 3.12
, and .
Example 3.13
For , we have
3.4. Disjunction
The disjunction [11] is the graph with vertex set in which is adjacent with whenever or .
Lemma 3.14
Suppose G and H are two graphs. Then
- (a)
If G and H are complete graphs, then.
- (b)
Ifor, then.
- (c)
Ifandare not empty sets, such that,,, then
One can partition the edges of as: be the set of edges connecting the vertices which satisfy , be the set of edges connecting the vertices which satisfy and be the set of edges connecting the vertices which satisfy with the vertices which satisfy .
Theorem 3.15
Suppose G and H are two graphs such that,,with. Then
Proof
(a) Applying Lemma 3.14 (c), we have
To prove (b) and (c) we use the edge partition of as mentioned earlier. Hence by Lemma 3.14(c), we have
□
Corollary 3.16
- (a)
If, then
- (b)
If G and H are two complete graphs, then
Example 3.17
For , we have
3.5. Composition
The composition [11] of G and H having and as vertex sets and and as edge sets is a graph containing vertex set and is connected to if and only if or and .
Lemma 3.18
For any two graphs G and H
- (a)
If G and H are complete graphs, then.
- (b)
If G has at least one vertex withand H does not have any vertex with, then.
- (c)
Ifandare not empty sets, such that,,, then
Theorem 3.19
For any two graphs G and H with,and. Then
Proof
(a) Applying Lemma 3.18(c), we get
To prove (b) and (c) we use the edge partition of which is similar to the edge partition of . Hence by Lemma 3.18(c), we have
□
Corollary 3.20
If G and H are complete graphs, then, and.
Corollary 3.21
If G has at least one vertex withand H does not have any vertex with, then
Example 3.22
For , we have
3.6. Symmetric difference
The symmetric deference [11] is defined by and .
Lemma 3.23
For any two graphs G and H
Theorem 3.24
For any two graphs G and H
Example 3.25
4. Conclusion
In this article, we've introduced new indices referred to as eccentric neighborhood Zagreb indices. These indices have been conceptualized and their discriminating power investigated with regard to the predictability of the boiling point of the chemical substances, as the correlation coefficients between 0.9814 and 0.993 were acquired greater than the ones received in the case of eccentric connectivity and Winner indices. We have calculated those indices for some graphs and additionally studied a number of their characteristics. We've got calculated the formulation for some graph operations such as join, disjunction, composition, and symmetric deference. Because these indices are appearing for the first time, we have some issues to address in the feature, such as
-
1.
Define some new versions of these topological indices that are parallel to the usual Zagreb topological indices.
-
2.
Which graphs have the highest value for those indices as well as the lowest value?
-
3.
The investigation of bounds is still an open area to study.
-
4.
The mathematical relationships between the new and prior indices.
-
5.
Used such indices to analyze certain significant chemical substances.
-
6.
Investigating the polynomials that are connected to these indices.
CRediT authorship contribution statement
Hanan Ahmed: Performed the experiments; Analyzed and interpreted the data; Wrote the paper.
Anwer Saleh: Conceived and designed the experiments.
Rashad Ismail, Ruby Salestina M, Abdu Alameri: Contributed reagents, materials, analysis tools or data.
Declaration of Competing Interest
The authors declare that they have no competing interests.
Acknowledgements
The third author expresses his appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under Grant Number (R.G.P.2/163/44).
Contributor Information
Hanan Ahmed, Email: hananahmed1a@gmail.com.
Anwar Saleh, Email: math.msfs@gmail.com.
Rashad Ismail, Email: rismail@kku.edu.sa.
Ruby Salestina M, Email: ruby.salestina@gmail.com.
Abdu Alameri, Email: a.alameri.2222@gmail.com.
Data availability
Data included in article/supp.material/referenced in article
References
- 1.Chen W.C., Lu H., Yeh Y. Operations of interlaced trees and graceful trees. Southeast Asian Bull. Math. 1997;21:337–348. [Google Scholar]
- 2.Feng C.J., Du X.H. Topological research of Kováts indices for amines. Se Pu. 2001 Mar;19(2):124–127. (in Chinese), PMID: 12541653. [PubMed] [Google Scholar]
- 3.da Fonseca C.M., Stevanovic D. Further properties of the second Zagreb index. MATCH Commun. Math. Comput. Chem. 2014;72:655–668. [Google Scholar]
- 4.Doslic T., Saheli Mahboubeh. Eccentric connectivity index of composite graphs. Util. Math. 2014;95:3–22. [Google Scholar]
- 5.Dureja H., Madan A.K. Superaugmented eccentric connectivity indices: new-generation highly discriminating topological descriptors for QSAR/QSPR modeling. Med. Chem. Res. 2007;16:331–341. doi: 10.1007/s00044-007-9032-9. [DOI] [Google Scholar]
- 6.Gutman I., Das K.C. The first Zagreb index 30 years after. MATCH Commun. Math. Comput. Chem. 2004;50:83–92. [Google Scholar]
- 7.Gutman I., Trinajstić N. Graph theory and molecular orbitals. Total π-electron energy of alternant hydrocarbons. Chem. Phys. Lett. 1972;17:535–538. [Google Scholar]
- 8.Gutman I., Polansky O.E. Springer; Berlin: 1986. Mathematical Concepts in Organic Chemistry. [Google Scholar]
- 9.Gutman I., Rucic B., Trinajstic N., Wilcox C.F. Graph theory and molecular orbitals. XII. Acyclic polyenes. J. Chem. Phys. 1975;62:3399–3405. [Google Scholar]
- 10.Ilic A., Gutman I. Eccentric connectivity index of chemical trees. MATCH Commun. Math. Comput. Chem. 2011;65:731–744. [Google Scholar]
- 11.Khalifeh M.H., Yousefi-Azari H., Ashrafi A.R. The first and second Zagreb indices of some graph operations. Discrete Appl. Math. 2009;157:804–811. doi: 10.1016/j.dam.2008.06.015. [DOI] [Google Scholar]
- 12.Morgan M.J., Mukwembi S., Swart H.C. On the eccentric connectivity index of a graph. Discrete Math. 2011;311:1229–1234. doi: 10.1016/j.disc.2009.12.013. [DOI] [Google Scholar]
- 13.Prathik A., Uma K., Anuradha J. An overview of application of graph theory. Int. J. Chem. Tech. Res. 2016;9(2):242–248. [Google Scholar]
- 14.Sardana S., Madan A.K. Application of graph theory: relationship of molecular connectivity index, Wiener index and eccentric connectivity index with diuretic activity. MATCH Commun. Math. Comput. Chem. 2001;43:85–98. [Google Scholar]
- 15.Sharma V., Goswami R., Madan A.K. Eccentric connectivity index: a novel highly discriminating topological descriptor for structure-property and structure-activity studies. J. Chem. Inf. Comput. Sci. 1997;37:273–282. [Google Scholar]
- 16.Wiener H. Structural determination of the paraffin boiling points. J. Am. Chem. Soc. 1947;69:17–20. doi: 10.1021/ja01193a005. [DOI] [PubMed] [Google Scholar]
- 17.Xu K., Das K.C., Klavzar S., Li H. Comparison of Wiener index and Zagreb eccentricity indices. MATCH Commun. Math. Comput. Chem. 2020;84:595–610. [Google Scholar]
- 18.Xu L., Yao Y., Wang H. New topological index and prediction of phase transfer energy for protonated amines and tetraalkylammonium ions. J. Chem. Inf. Comput. Sci. 1995:45–49. doi: 10.1021/ci00023a006. [DOI] [Google Scholar]
- 19.Zhou B. On eccentric connectivity index. MATCH Commun. Math. Comput. Chem. 2010;63:181–198. [Google Scholar]
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