COVID-19 is a disease caused by the new coronavirus, which has been spreading rapidly all over the world. There is no exact drug yet for the treatment of COVID-19 disease, and its treatment is tried to be provided with existing drugs. However, new drug research is being carried out to treat this disease. Topological indices are numerical descriptors based on the molecular graph of the molecular structure. Topological indices are used in modeling to predict the physicochemical properties and biological activities of molecules in the quantitative structure-property relationship (QSPR), quantitative structure-activity relationship (QSAR) studies. In this study, remdesivir, chloroquine, hydroxychloroquine, theaflavin, thalidomide, arbidol, lopinavir, ritonavir drugs used in the treatment of COVID-19 patients are studied. The QSPR model is designed using some degree-based indices, Mostar-type indices, and distance-based topological indices to predict the various physicochemical properties of these drugs. The relationship analyses between the physicochemical properties and the topological indices in the QSPR model are done by using the curvilinear regression method.

COVID‐19, which has spread all over the world and was declared as a pandemic, is a new disease caused by the coronavirus family. There is no medicine yet to prevent or end this pandemic. Even if existing drugs are used to alleviate the pandemic, this is not enough. Therefore, combinations of existing drugs and their analogs are being studied. Vaccines produced for COVID‐19 may not be effective for new variants of this virus. Therefore, it is necessary to find the drugs for this disease as soon as possible. Topological indices are the numerical descriptors of a molecular structure obtained by the molecular graph. Topological indices can provide information about the physicochemical properties and biological properties of molecules in the quantitative structure‐property relationship (QSPR) and quantitative structure‐activity relationship (QSAR) studies. In this paper, some analogs of lopinavir, favipiravir, and ritonavir drugs that have the property of being potential drugs against COVID‐19 are studied. QSPR models are studied using linear and quadratic regression analysis with topological indices for enthalpy of vaporization, flash point, molar refractivity, polarizability, surface tension, and molar volume properties of these analogs.

Topological indices are the numerical descriptor of a molecular structure obtained via molecular graph G. Topological indices are used for studying the properties of molecules such as structure-property relationship (QSPR), structure-activity relationship (QSAR) and structural design in chemistry, nanotechnology, and pharmacology. Its main role is to work as a numerical molecular descriptor in QSAR/QSPR models. Moreover, physicochemical properties such as boiling point, enthalpy of vaporization, and stability could be envisaged by QSAR/QSPR models. In this study, the QSPR (Quantitative Structure Property Relationship) model is designed using the Forgotten topological index, the Forgotten coindex, the max-min Rodeg index, and the inverse sum indeg index to predict the thermodynamic properties of monocarboxylic acids. The relationship analysis between the thermodynamic properties and the topological indices was done by using the multiple linear regression method.

Molecular topological indices are numerical descriptor of molecular structure obtained via molecular graph G. The forgotten topological index F(G) is a vertex degree based topological index and it can be expressed with $F\left(G\right)=\sum {d\left(v\right)}^3=\sum \left({d\left(u\right)}^2+{d\left(v\right)}^2\right),$ where d(u) denotes the degree of u. The forgotten co-index Co-F(G) is defined as the sum of squares of a graph’s vertex degrees which is not adjacent. In this study, the F(G) and Co-F(G) index of HAC₅C₇, HAC₅C₆C₇, linear [n]-phenylenes and cyclic phenylenes nanostructures are computed for possible works in the properties of molecules such as structure–property relationship. In addition, polynomials of the forgotten index and co-index are found for these nanostructures.

Monkeypox has recently re‐emerged. Since monkeypox has started to be seen in many countries without an epidemic, studies have started on new drugs used to treat this disease. Drug discovery is a challenging process. To alleviate this process, molecular descriptors used to predict the physical, chemical, and biological properties of chemical structures are studied. Molecular descriptors are numerical values of a chemical structure represented by a graph. In this study, M‐polynomial and neighborhood M‐polynomial molecular descriptors of drugs used and candidates for use in monkeypox are calculated and these descriptors are compared.