QSPR analysis of the ability of individual avermectins to bioconcentration
Abstract
At the moment, the spread of coronavirus infection is a global problem for humanity. One of the promising compounds for the fight against SARS-CoV-2 coronavirus is ivermectin – a complex of semi-synthetic derivatives of natural avermectins, which have been effectively used in medicine, veterinary medicine, and agriculture as antiparasitic agents for many years. There are also several successful studies on the use of avermectins as antitumor drugs. However, despite the worldwide recognition, high physiological significance and prospects, there are still no reliable data for most individual avermectins on their main ecotoxicological characteristics, which in accordance with the current legislation of the European Union is a prerequisite for substances produced or imported over one ton per year. Using the OCHEM web-platform (https://ochem.eu) adequate models of Quantitative Structure – Property Relationship (QSPR) were constructed, which allowed us to evaluate the influence of the structure of organic compounds on the value of the bioconcentration factor (BCF). QSPR models were developed using various fragmentary, topological, physico-chemical molecular descriptors, as well as machine learning methods such as Random Forest (RF) and Associative Neural Networks (ASNN). To quantify the ability of individual avermectins to bioconcentrate, a consensus QSPR model has been developed, which is freely available on the Internet at: https://ochem.eu/model/20673575. In comparative QSPR modeling, molecular descriptors were used, including fractal ones, calculated using the HYBOT program. The developed models have a comparable predictive ability and can be useful in determining the strategy of synthesis, testing of new drugs based on individual avermectins, including the selection of leader compounds that are potent in inhibition of SARS-CoV-2 replication. When conducting structural interpretation by the method of molecular pairs, the most common molecular transformations that increase and decrease the bioconcentration factor have been determined, which can be taken into account in the rational molecular design of new physiologically active compounds.
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Copyright (c) 2020 Oleg V. Tinkov, Veniamin Yu. Grigoriev, and Lyudmila D. Grigorieva
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