On Topological Indices of Remdesivir Compound Used in Treatment of Corona Virus (COVID 19)

Partition dimension of COVID antiviral drug structures

In November 2019, there was the first case of COVID-19 (Coronavirus) recorded, and up to 3$ ^{rd }$ of April 2020, 1,116,643 confirmed positive cases, and around 59,158 dying were recorded. Novel antiviral structures of the SARS-COV-2 virus is discussed in terms of the metric basis of their molecular graph. These structures are named arbidol, chloroquine, hydroxy-chloroquine, thalidomide, and theaflavin. Partition dimension or partition metric basis is a concept in which the whole vertex set of a structure is uniquely identified by developing proper subsets of the entire vertex set and named as partition resolving set. By this concept of vertex-metric resolvability of COVID-19 antiviral drug structures are uniquely identified and helps to study the structural properties of structure.

A new perspective on the modeling and topological characterization of H-Naphtalenic nanosheets with applications

In the past few years, two-dimensional (2D) layered nanomaterials have greatly attracted the scientific community. Among 2D nanomaterials, the porphyrin-based Naphtalenic nanosheets have been the subject of intense research due to their utilization in photo-dynamic therapy and nanodevices. New technologies based on nanomaterials or Naphtalenic nanosheet are advantageous in overcoming the problems in conventional drug delivery like poor solubility, toxicity and poor release pattern of drugs. In chemical network theory, various molecular descriptors are used to predict the chemical properties of molecules; these molecular descriptors are found to be very useful for Quantitative Structure–Activity/ Quantitative Structure–Property (QSAR/QSPR) relationship analysis in materials engineering, chemical and pharmaceutical industries. Researchers have computed the molecular descriptors for various nanostructures; however, despite intense research, the topology of nanostructures is not yet well understood. Specially, to our knowledge, the computation of topological indices for the line graph of subdivision graph of H-Naphtalenic nanosheet has not been discussed so far, which may open new perspectives for a more accurate and reliable topological characterization of this nanosheet.

In this article, we employed some important degree-based topological indices to study the chemical structure of Naphtalenic nanosheet as a chemical network for QSAR/QSPR analysis. We have computed these degree-based topological indices for the line graph of subdivision graph of H-Naphtalenic nanosheet and derived formulas for them. Based on the derived formulas, numerical results are obtained and the physical and chemical properties of the under study nanosheet are investigated.

Prediction of Exchange-Correlation Energy of Graphene Sheets from Reverse Degree-Based Molecular Descriptors with Applications

Over the past few years, the popularity of graphene as a potential 2D material has increased since graphene-based materials have applications in a variety of fields, including medicine, engineering, energy, and the environment. A large number of graphene sheets as well as an understanding of graphene’s structural hierarchy are critical to the development of graphene-based materials. For a variety of purposes, it is essential to understand the fundamental structural properties of graphene. Molecular descriptors were used in this study to investigate graphene sheets’ structural behaviour. Based on our findings, reverse degree-based molecular descriptors can significantly affect the exchange-correlation energy prediction. For the exchange-correlation energy of graphene sheets, a linear regression analysis was conducted using the reverse general inverse sum indeg descriptor, RGISI(p,q). From RGISI(p,q), a set of reverse topological descriptors can be obtained all at once as a special case, resulting in a model with a high correlation coefficient (R between 0.896 and 0.998). Used together, these reverse descriptors are graphed in relation to their response to graphene. Based on this study’s findings, it is possible to predict the exchange correlation energy as well as the geometric structures of graphene sheets with very little computational cost.

Topological Coindices and Quantitative Structure-Property Analysis of Antiviral Drugs Investigated in the Treatment of COVID-19

SARS-CoV-2 is a new strain of coronavirus family that has never been previously detected in humans. This has grown into a huge public health issue that has affected people all around the world. Presently, there is no specific antiviral treatment for COVID-19. To tackle the outbreak, a number of drugs are being explored or have been utilized based on past experience. A molecular descriptor (or topological index) is a numerical value that describes a compound’s molecular structure and has been successfully employed in many QSPR/QSAR investigations to represent several physicochemical attributes. In order to determine topological characteristics of graphs, coindices (topological) take nonadjacent pair of vertices into account. In this study, we introduced CoM-polynomial and numerous degree-based topological coindices for several antiviral medicines such as lopinavir, ritonavir remdesivir, hydroxychloroquine, chloroquine, theaflavin, thalidomide, and arbidol which were studied using the CoM-polynomial approach. In the QSPR model, the linear regression approach is used to analyze the relationships between physicochemical properties and topological coindices. The findings show that the topological coindices under investigation have a substantial relationship with the physicochemical properties of possible antiviral medicines in question. As a result, topological coindices may be effective tools for studying antiviral drugs in the future for QSPR analyses.

A Comparative Study of the Lipophilicity of Metformin and Phenformin

The results presented in this paper confirm the beneficial role of an easy-to-use and low-cost thin-layer chromatography (TLC) technique for describing the retention behavior and the experimental lipophilicity parameter of two biguanide derivatives, metformin and phenformin, in both normal-phase (NP) and reversed-phase (RP) TLC systems. The retention parameters (R_F, R_M) obtained under different chromatographic conditions, i.e., various stationary and mobile phases in the NP-TLC and RP-TLC systems, were used to determine the lipophilicity parameter (R_MW) of metformin and phenformin. This study confirms the poor lipophilicity of both metformin and phenformin. It can be stated that the optimization of chromatographic conditions, i.e., the kind of stationary phase and the composition of mobile phase, was needed to obtain the reliable value of the chromatographic lipophilicity parameter (R_MW) in this study. The fewer differences in the R_MW values of both biguanide derivatives were ensured by the RP-TLC system composed of RP2, RP18, and RP18W plates and the mixture composed of methanol, propan-1-ol, and acetonitrile as an organic modifier compared to the NP-TLC analysis. The new calculation procedures for logP of drugs based on topological indices ⁰χ^ν, ⁰χ, ¹χ^ν, M, and M^ν may be a certain alternative to other algorithms as well as the TLC procedure performed under optimized chromatographic conditions. The knowledge of different lipophilicity parameters of the studied biguanides can be useful in the future design of novel and more therapeutically effective metformin and phenformin formulations for antidiabetic and possible anticancer treatment. Moreover, the topological indices presented in this work may be further used in the QSAR study of the examined biguanides.