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Author(s): Irena Cosic, Drasko Cosic, Ivan Loncarevic
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DOI: 10.18483/ijSci.2390
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Volume 9 - Sep 2020
Abstract
With the huge demand for new effective drugs there is large need for computational methods capable of quick preselection of potential drugs before they are chemically and biologically tested. Particularly, with the latest outbreak of coronavirus SARS-CoV-2 causing COVID-19 pandemic, there is urgent need to preselect number of potential small molecule drugs that are already approved for other purposes and are clinically tested on infected people with variety of success. The already established Resonant Recognition Model (RRM) proposes that selectivity of biological interactions and functions between proteins, DNA/RNA, is based on resonant electromagnetic energy between interacting macromolecules at the specific frequency for the specific interaction/function. However, this approach cannot be applied for selective specific interactions between proteins and small molecules (potential drugs), as small molecules are not linear sequential molecules. Here, we extended the RRM model to small molecules interaction with proteins proposing that energy frequencies of free electrons in small molecules are the most relevant for their resonant recognition and interaction with proteins. This extended RRM model is firstly tested here with couple of natural examples to explain and support the model, following with application to already approved drugs, which are also potential COVID-19 drugs including remdesivir, chloroquine and hydroxychloroquine. This newly extended RRM model opens new avenues for biochemistry and pharmaceutical industry in analyzes of small molecule – protein interaction, and consequently in preselection of new drugs and drug design in general.
Keywords
Drug Design, Small Molecules, Resonant Energy, Bioelectromagnetism, Resonant Recognition Model, SARS-Cov-2, COVID-19, Hydroxychloroquine, Chloroquine, Remdesivir
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