Discrimination of isomeric structures using information theoretic topological indices

Raychaudhury, Chandan; Ray, Sudipta; Ghosh, Joydip; Roy, Aidan; Basak, Subhash C.

doi:10.1002/jcc.540050612

Cited by 124 publications

(74 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…H , ICO, and SICo = topological parameters: Raychaudhury et al [42]; information and struc-'n(6) atomic charge on atom N(6) [35]. tions between topological indices used here and physicochemical properties of molecules (see Table IX for more details).…”

Section: (B) Discussionmentioning

confidence: 99%

The application of the graph‐theoretical method in the QSAR scheme: Possibilities and limits

Romanowska

1992

Int J of Quantum Chemistry

View full text Add to dashboard Cite

The correlation between topological features of molecular structure and physicochemical as well as biological properties of molecules were examined for some sets of compounds, using graph-theoretical descriptions. It was found that the topological similarity plays a role in the determination of molecular properties for almost all compound sets studied, As a conclusion, one can presume that the less elaborated and complicated similarity measure based on the graphtheoretical description is sufficient in the case of distinct structure-property dependence.

show abstract

Section: (B) Discussionmentioning

confidence: 99%

The application of the graph‐theoretical method in the QSAR scheme: Possibilities and limits

Romanowska

1992

Int J of Quantum Chemistry

View full text Add to dashboard Cite

show abstract

“…This value may give the valency of the atom it is representing if hydrogen-filled graphs are considered. Again, the sum of all the entries of any row / column of D(G), known as distance sum, 9,10,16,17 is obtained from the distance distribution of all the vertices of G from the given vertex. From structural point of view, this distance distribution helps get some interesting features.…”

Section: Methodsmentioning

confidence: 99%

“…Let there be n i vertices at a distance d i from a vertex v in a molecular graph for which the vertex index D x has to be computed and d i , i = 1, 2, …, m, are different topological distances 10,13,16,17 of those n vertices from v (vertex v lies at a distance zero from itself) in that molecular graph. Then the index D x for vertex v may be computed from Equation (1).…”

Section: Methodsmentioning

confidence: 99%

“…In order to do that, one requires structural descriptors of chemical compounds for having structural interpretation of their biological activities. Over the years, structural descriptors have been derived from molecular structures in the form of 2D (two-dimensional) descriptors [7][8][9][10][11][12] using methods based on graph theory 13 and are derived from molecular graph models of the structural formula of chemical compounds and as 3D (three-dimensional) descriptors 14 derived from 3D structural information of chemical compounds obtained from X-ray crystallographic studies or, developed using 3D structure generating computational tools. While 3D descriptors reflect some physical characteristics of a molecule or, parts of it such as those obtained from 3D co-ordinates / conformations of a molecule, 14 2D descriptors translate into numbers the topological characteristics of a molecule such as, branching, cyclicity, neighborhood etc.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Raychaudhury¹,

Kandel²,

Pal³

2014

Croat. Chem. Acta

View full text Add to dashboard Cite

Abstract. Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named 'distance exponent index (D x )' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design. (doi: 10.5562/cca2306)

show abstract

“…HVcpx represents the graph vertex complexity index [15], BIC2 symbolizes the Bond Information Content (neighborhood symmetry of second order) [16], GATS7e denotes Geary autocorrelation -lag 7, weighted by atomic Sanderson electronegativities, and GATS8p stands for Geary autocorrelation -lag 8, weighted by atomic polarizabilities [17]. This df has been already applied in VS, discovering the anticonvulsant activities of abietic acid, and methyl and propyl paraben [18 -20].…”

Section: Full Papersmentioning

confidence: 99%

A Combined Virtual Screening 2D and 3D QSAR Methodology for the Selection of New Anticonvulsant Candidates from a Natural Product Library

Gavernet¹,

Talevi²,

Castro³

et al. 2008

QSAR Comb. Sci.

View full text Add to dashboard Cite

A virtual screening methodology combining a discriminant function (df) based on Dragon 2D-descriptors, general ADME filters, and a pharmacophore identified through superposition of rigid analogs was applied in order to identify new anticonvulsant agents among 10 903 natural products. Fifty-six compounds were selected from the application of this df, Lipinskis rule-of-five and other criteria for prediction of oral bioavailability, and the optimal value of log P for a compound to diffuse passively through the blood -brain barrier. Seven of these compounds were removed because they did not belong to descriptor space defined by the training set. The remaining 49 compounds were fitted to the pharmacophore structural constrains, selecting 7 structures with RMS distance value below 0.2. Systematic conformational analysis was performed to find the global minimum conformation, using the PM3 base included in Hyperchem 6.03. The global minimum conformations were further refined at a 6-31G** level with Gaussian 03. Restricted optimization was then performed to determine the energy difference between the energy minimum conformation and the active conformation defined by the pharmacophore, retaining those structures whose energy differences were below 7 kcal/mol. Four new potential anticonvulsants which fulfill the df and the pharmacophore requisites were selected. One of these structures, 2-(4,6-dimethyl-1-benzofuran-3-yl)acetic acid, was acquired and assayed in the MES and Rotorod tests, confirming anticonvulsant activity in mice at 30 and 100 mg/kg (0.5 and 4 h, i.p.) and absence of neurotoxicity at the tested doses.

show abstract

Discrimination of isomeric structures using information theoretic topological indices

Cited by 124 publications

References 13 publications

The application of the graph‐theoretical method in the QSAR scheme: Possibilities and limits

The application of the graph‐theoretical method in the QSAR scheme: Possibilities and limits

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

A Combined Virtual Screening 2D and 3D QSAR Methodology for the Selection of New Anticonvulsant Candidates from a Natural Product Library

Contact Info

Product

Resources

About