Characterization of molecular branching

Randić, Milan

doi:10.1021/ja00856a001

Cited by 3,132 publications

(1,694 citation statements)

References 5 publications

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“…For obvious chemical reasons, molecular graphs of hydrocarbons cannot possess vertices whose degrees are greater than 4. (see below), and these were included among topological indices much later. The first genuine degree-based topological index was put forward in 1975 by Milan Randić in his seminal paper 16 "On characterization of molecular branching". His index was defined as…”

Section: Randić or Connectivity Indexmentioning

confidence: 99%

“…Randić himself wrote two reviews on his index, 22,23 and there are three more. [24][25][26] The suitability of the Randić index for drug design was immediately recognized, 15,16 and eventually the index was used for this purpose on countless occasion. The physical reason for the success of such a simple graph invariant is still an enigma, although several more-or-less plausible explanations were offered.…”

Section: Randić or Connectivity Indexmentioning

confidence: 99%

“…154 They noticed that in the definition of Randić's branching index, 16 Equation (1), there is no a priori reason for using the product d u ×d v of vertex degrees, and this term may be replaced by the sum d u + d v . If so, then instead of Equation (1), one gets…”

Section: Sum-connectivity Indexmentioning

confidence: 99%

“…[184][185][186] Unfortunately, it happens that different physico-chemical properties require significantly different "optimal" λ-values. Vukičević considered the interesting problem, 187,188 closely related to Randić's original work, 16 namely which value of λ provides the best measure of molecular branching. The mathematical studies of the general Randić index and its higher-order variants is legion.…”

Section: Generalizations and Parametrizationsmentioning

confidence: 99%

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Degree-Based Topological Indices

Gutman¹

2013

Croat. Chem. Acta

659

384

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Section: Randić or Connectivity Indexmentioning

confidence: 99%

Section: Randić or Connectivity Indexmentioning

confidence: 99%

Section: Sum-connectivity Indexmentioning

confidence: 99%

Section: Generalizations and Parametrizationsmentioning

confidence: 99%

See 2 more Smart Citations

Degree-Based Topological Indices

Gutman¹

2013

Croat. Chem. Acta

659

384

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“…Recently this combination of descriptors was successfully used in QSAR studies of several data sets containing chiral compounds. 28 MolconnZ descriptors included valence, path, cluster, path/cluster, and chain molecular connectivity indices, [42][43][44] Bonchev-Trinajstić 60 information indices, counts of different vertices, 23 and counts of paths and edges between different types of vertices. 23 In this case, after applying complete correlation analysis (see below), the total number of the MolconnZ/CMTD descriptors was equal to 64 33 were used in this study including three principal moments of inertia I x , I y , and I z , dipole and quadrupole moments p and Q, three dipolar components, p x , p y , and p z , and three components of displacement between the center of mass and center of dipole d x , d y , and d z as well as two quadrupole moments Q xx and Q yy .…”

Section: Descriptorsmentioning

confidence: 99%

Combinatorial QSAR of Ambergris Fragrance Compounds

Kovatcheva

Gelbukh

Oloff

et al. 2004

J. Chem. Inf. Comput. Sci.

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A combinatorial quantitative structure-activity relationships (Combi-QSAR) approach has been developed and applied to a data set of 98 ambergris fragrance compounds with complex stereochemistry. The Combi-QSAR approach explores all possible combinations of different independent descriptor collections and various individual correlation methods to obtain statistically significant models with high internal (for the training set) and external (for the test set) accuracy. Seven different descriptor collections were generated with commercially available MOE, CoMFA, CoMMA, Dragon, VolSurf, and MolconnZ programs; we also included chirality topological descriptors recently developed in our laboratory Tropsha, A. J. Chem. Inf. Comput. Sci. 2001, 41, 147-158). CoMMA descriptors were used in combination with MOE descriptors. MolconnZ descriptors were used in combination with chirality descriptors. Each descriptor collection was combined individually with four correlation methods, including k-nearest neighbors (kNN) classification, Support Vector Machines (SVM), decision trees, and binary QSAR, giving rise to 28 different types of QSAR models. Multiple diverse and representative training and test sets were generated by the divisions of the original data set in two. Each model with high values of leave-one-out cross-validated correct classification rate for the training set was subjected to extensive internal and external validation to avoid overfitting and achieve reliable predictive power. Two validation techniques were employed, i.e., the randomization of the target property (in this case, odor intensity) also known as the Y-randomization test and the assessment of external prediction accuracy using test sets. We demonstrate that not every combination of the data modeling technique and the descriptor collection yields a validated and predictive QSAR model. kNN classification in combination with CoMFA descriptors was found to be the best QSAR approach overall since predictive models with correct classification rates for both training and test sets of 0.7 and higher were obtained for all divisions of the ambergris data set into the training and test sets. Many predictive QSAR models were also found using a combination of kNN classification method with other collections of descriptors. The combinatorial QSAR affords automation, computational efficiency, and higher probability of identifying significant QSAR models for experimental data sets than the traditional approaches that rely on a single QSAR method.

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Exhaustive enumeration of molecular substructures

Bone

Villar

1997

J. Comput. Chem.

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Characterization of molecular branching

Cited by 3,132 publications

References 5 publications

Degree-Based Topological Indices

Degree-Based Topological Indices

Combinatorial QSAR of Ambergris Fragrance Compounds

Exhaustive enumeration of molecular substructures

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