Prof. Krishnan Balasubramanian

The physicochemical characteristics of polycyclic aromatic compounds critical to environmental modelling such as octanol partition coefficients, solubility, lipophilicity, polarity and several equilibrium constants are functions of their underlying molecular structures, prompting the development of mathematical models to predict such characteristics for which experimental results are difficult to obtain. We propose twelve novel descriptors derived from geometric, harmonic and Zagreb degree-based descriptors and then test the effectiveness of these descriptors on a data set consisting of 55 benzenoid hydrocarbons of environmental importance. Our computations show that the proposed descriptors have a good linear correlation and predictive power when compared to the degree and distance type descriptors. We have also derived the QSPR expressions for four properties of a large series of polycyclic aromatics arising from circumscribing coronenes and show that a scaling factor can be deduced to derive physicochemical properties of such series up to 2D graphene sheets.

1 September 2021 in The Journal of Physical Chemistry A

Journal Article

Topological Characterization and Graph Entropies of Tessellations of Kekulene Structures: Existence of Isentropic Structures and Applications to Thermochemistry, Nuclear Magnetic Resonance, and Electron Spin Resonance

S. Ruth Julie Kavitha

Jessie Abraham

Micheal Arockiaraj

Joseph Jency

Krishnan Balasubramanian

26 May 2022 in Molecular Physics

Journal Article

Two-dimensional coronene fractal structures: topological entropy measures, energetics, NMR and ESR spectroscopic patterns and existence of isentropic structures

Micheal Arockiaraj

Joseph Jency

Jessie Abraham

S. Ruth Julie Kavitha

Krishnan Balasubramanian

Molecular fractals are geometric patterns that appear self-similar across all length scales and are constructed by repeating a single unit on a regular basis. The benzenoid compounds are found to have a natural pattern that helps to analyse and explore the potential attributes of these molecular fractals. Here, we focus on coronene-based fractals where coronene is a benzenoid molecule with a symmetric graphite-like structure and challenging synthesis methods. Topological molecular descriptors are obtained in order to provide structure-activity relations for the physico-chemical properties. We obtain these descriptors for the molecular fractals that are constructed by repeating a fixed unit of coronene on different stages systematically. The structural characterisation of the two-dimensional coronene fractals in various tessellations is presented through a wide range of degree-based topological indices. The entropy measures of these significant frameworks are also computed for estimating their potential attributes, and the comparison of their values among various degree-based indices is performed, which shows the existence of isentropic structures. We have developed machine learning techniques for robust computations of the enthalpies, NMR and ESR spectroscopic patterns of coronene fractals. GRAPHICAL ABSTRACT

20 February 2023 in Symmetry

Journal Article

Topological Indices, Graph Spectra, Entropies, Laplacians, and Matching Polynomials of n-Dimensional Hypercubes

Krishnan Balasubramanian

We obtain a large number of degree and distance-based topological indices, graph and Laplacian spectra and the corresponding polynomials, entropies and matching polynomials of n-dimensional hypercubes through the use of Hadamard symmetry and recursive dynamic computational techniques. Moreover, computations are used to provide independent numerical values for the topological indices of the 11- and 12-cubes. We invoke symmetry-based recursive Hadamard transforms to obtain the graph and Laplacian spectra of nD-hypercubes and the computed numerical results are constructed for up to 23-dimensional hypercubes. The symmetries of these hypercubes constitute the hyperoctahedral wreath product groups which also pave the way for the symmetry-based elegant computations. These results are used to independently validate the exact analytical expressions that we have obtained for the topological indices as well as graph, Laplacian spectra and their polynomials. We invoke a robust dynamic programming technique to handle the computationally intensive generation of matching polynomials of hypercubes and compute all matching polynomials up to the 6-cube. The distance degree sequence vectors have been obtained numerically for up to 108-dimensional cubes and their frequencies are found to be in binomial distributions akin to the spectra of n-cubes.

28 February 2022 in Journal of Mathematical Chemistry

Journal Article

Graph entropies, enumeration of circuits, walks and topological properties of three classes of isoreticular metal organic frameworks

Jessie Abraham

Micheal Arockiaraj

Joseph Jency

S. Ruth Julie Kavitha

Krishnan Balasubramanian

21 October 2021 in Molecular Physics

Journal Article

Structure–activity relations for antiepileptic drugs through omega polynomials and topological indices

Medha Itagi Huilgol

V. Sriram

Krishnan Balasubramanian

Epilepsy has impacted more than 50 million people worldwide, and it continues to pose challenges for drug discovery. There is a dearth of reliable experimental data on antiepileptic drugs (AED) and the mechanisms of drug activity are not well understood. In the current study we develop novel mathematical tools for antiepileptic molecules as an integral part of machine learning and artificial intelligence through omega polynomials and topological indices to derive robust structure–activity relations for the correlation and prediction of anticonvulsant activities as measured by their ED₅₀ values. We have applied the developed mathematical and computational tools to 31 potential AEDs for the development of reliable structure–activity relations. We show using both statistical and topological tools that the developed structure–activity relations on the basis of graph theoretical tools provide a robust 3D-QSAR equation for the ED₅₀ prediction of AEDs with an R value of 0.975, and one of the key factors that determines the potency of an AED is its ability to penetrate the blood–brain–barrier (BBB). GRAPHICAL ABSTRACT

About Me

website: https://sites.google.com/asu.edu/prof-krishnan-balasubramanian/ Professor Balasubramanian’s areas of research are theoretical, computational, and mathematical chemistry, computational medicinal chemistry, artificial intelligence in medicinal chemistry, drug discovery and administration, mathematical and computational biology, actinide and superheavy element chemistry, relativistic chemistry, predictive toxicology, drug discovery, protein–protein interactions, computational nanochemistry, functionalized mesoporous materials, environmental actinide chemistry, the chemical and biological applications of discrete mathematics, machine learning, and artificial intelligence. He is a two-time Fulbright Scholar, Camille and Henry Dreyfus Teacher-Scholar, Alfred P. Sloan Fellow, and a recipient of the Distinction Award in Graduate Teaching, the Joint Prize of Minister of Education, Poland, the Lawrence Livermore Distinguished Service Award, the Rev Fr. Yeddanapalli Memorial Award, and the Birla Institute of Technology & Science Distinguished Alumnus Award. He is an elected member of the International Academy of Mathematical Chemistry. He was a Robert S. Mulliken Lecturer, an Indian Institute of Technology Madras Extramural Lecturer, a Rev Yeddanapalli Memorial Lecturer, and a Padmashri Gemini Ganesan Centennial Lecturer. Research Interests He has over 740 publications & 2 books- full list https://sites.google.com/asu.edu/prof-krishnan-balasubramanian/research-publications

Prof. Krishnan Balasubramanian

Prof. Krishnan Balasubramanian

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