Derivatives in discrete mathematics: a novel graph-theoretical invariant for generating new 2/3D molecular descriptors. I. Theory and QSPR application

In this report, we present a new mathematical approach for describing chemical structures of organic molecules at atomic-molecular level, proposing for the first time the use of the concept of the derivative ($$ \partial $$) of a molecular graph (MG) with respect to a given event (E), to obtain a new family of molecular descriptors (MDs). With this purpose, a new matrix representation of the MG, which generalizes graph’s theory’s traditional incidence matrix, is introduced. This matrix, denominated the generalized incidence matrix, Q, arises from the Boolean representation of molecular sub-graphs that participate in the formation of the graph molecular skeleton MG and could be complete (representing all possible connected sub-graphs) or constitute sub-graphs of determined orders or types as well as a combination of these. The Q matrix is a non-quadratic and unsymmetrical in nature, its columns (n) and rows (m) are conditions (letters) and collection of conditions (words) with which the event occurs. This non-quadratic and unsymmetrical matrix is transformed, by algebraic manipulation, to a quadratic and symmetric matrix known as relations frequency matrix, F, which characterizes the participation intensity of the conditions (letters) in the events (words). With F, we calculate the derivative over a pair of atomic nuclei. The local index for the atomic nuclei i, Δi, can therefore be obtained as a linear combination of all the pair derivatives of the atomic nuclei i with all the rest of the j′s atomic nuclei. Here, we also define new strategies that generalize the present form of obtaining global or local (group or atom-type) invariants from atomic contributions (local vertex invariants, LOVIs). In respect to this, metric (norms), means and statistical invariants are introduced. These invariants are applied to a vector whose components are the values Δi for the atomic nuclei of the molecule or its fragments. Moreover, with the purpose of differentiating among different atoms, an atomic weighting scheme (atom-type labels) is used in the formation of the matrix Q or in LOVIs state. The obtained indices were utilized to describe the partition coefficient (Log P) and the reactivity index (Log K) of the 34 derivatives of 2-furylethylenes. In all the cases, our MDs showed better statistical results than those previously obtained using some of the most used families of MDs in chemometric practice. Therefore, it has been demonstrated to that the proposed MDs are useful in molecular design and permit obtaining easier and robust mathematical models than the majority of those reported in the literature. All this range of mentioned possibilities open “the doors” to the creation of a new family of MDs, using the graph derivative, and avail a new tool for QSAR/QSPR and molecular diversity/similarity studies.

[1]  Milan Randic,et al.  Search for useful graph theoretical invariants of molecular structure , 1988, Journal of chemical information and computer sciences.

[2]  Alexander Golbraikh,et al.  Novel Chirality Descriptors Derived from Molecular Topology , 2001, J. Chem. Inf. Comput. Sci..

[3]  A. Balaban,et al.  Topological Indices and Related Descriptors in QSAR and QSPR , 2003 .

[4]  Stuart A. Rice,et al.  Quantum Chemistry: Methods and Applications , 1960 .

[5]  Ernesto Estrada,et al.  Physicochemical Interpretation of Molecular Connectivity Indices , 2002 .

[6]  Ernesto Estrada,et al.  Generalization of topological indices , 2001 .

[7]  Milan Randić,et al.  Generalized molecular descriptors , 1991 .

[8]  A. Balaban Chemical applications of graph theory , 1976 .

[9]  L B Kier,et al.  Issues in representation of molecular structure the development of molecular connectivity. , 2001, Journal of molecular graphics & modelling.

[10]  Nenad Trinajstić,et al.  In search for graph invariants of chemical interes , 1993 .

[11]  I. W Nowell,et al.  Molecular Connectivity in Structure-Activity Analysis , 1986 .

[12]  J. Gálvez ON A TOPOLOGICAL INTERPRETATION OF ELECTRONIC AND VIBRATIONAL MOLECULAR ENERGIES , 1998 .

[13]  Alan R. Katritzky,et al.  CODESSA-Based Theoretical QSPR Model for Hydantoin HPLC-RT Lipophilicities , 2001, J. Chem. Inf. Comput. Sci..

[14]  Lemont B. Kier,et al.  Intermolecular Accessibility: The Meaning of Molecular Connectivity , 2000, J. Chem. Inf. Comput. Sci..

[15]  Lemont B. Kier,et al.  Molecular structure description , 1999 .

[16]  L B Kier,et al.  Molecular connectivity: intermolecular accessibility and encounter simulation. , 2001, Journal of molecular graphics & modelling.

[17]  Anton J. Hopfinger,et al.  Application of Genetic Function Approximation to Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships , 1994, J. Chem. Inf. Comput. Sci..

[18]  M. Karelson Molecular descriptors in QSAR/QSPR , 2000 .

[19]  L. W. Beineke Chemical Applications of Graph Theory (A. T. Balaban, ed.) , 1978 .

[20]  E. Castro,et al.  3D-chiral (2.5) atom-based TOMOCOMD-CARDD descriptors: theory and QSAR applications to central chirality codification , 2008 .

[21]  L. Hall,et al.  Molecular Structure Description: The Electrotopological State , 1999 .

[22]  Johann Gasteiger,et al.  Prediction of enantiomeric selectivity in chromatography. Application of conformation-dependent and conformation-independent descriptors of molecular chirality. , 2002, Journal of molecular graphics & modelling.

[23]  M Karplus,et al.  Evolutionary optimization in quantitative structure-activity relationship: an application of genetic neural networks. , 1996, Journal of medicinal chemistry.

[24]  Roberto Todeschini,et al.  Handbook of Molecular Descriptors , 2002 .

[25]  E Estrada,et al.  Novel local (fragment-based) topological molecular descriptors for QSpr/QSAR and molecular design. , 2001, Journal of molecular graphics & modelling.

[26]  On a quantum chemical interpretation of molecular connectivity indices for conjugated hydrocarbons , 1995 .

[27]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[28]  Enrique Molina,et al.  3D connectivity indices in QSPR/QSAR studies. , 2001 .

[29]  H HallLowell,et al.  The electrotopological state , 1991 .

[30]  E Uriarte,et al.  Recent advances on the role of topological indices in drug discovery research. , 2001, Current medicinal chemistry.

[31]  V. A. Gorbatov Fundamentos de la matemática discreta , 1988 .