A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19

Abstract

In order to treat Coronavirus Disease 2019 (COVID-19), we predicted and implemented a drug delivery system (DDS) that can provide stable drug delivery through a computational approach including a clustering algorithm and the Schrödinger software. Six carrier candidates were derived by the proposed method that could find molecules meeting the predefined conditions using the molecular structure and its functional group positional information. Then, just one compound named glycyrrhizin was selected as a candidate for drug delivery through the Schrödinger software. Using glycyrrhizin, nafamostat mesilate (NM), which is known for its efficacy, was converted into micelle nanoparticles (NPs) to improve drug stability and to effectively treat COVID-19. The spherical particle morphology was confirmed by transmission electron microscopy (TEM), and the particle size and stability of 300–400 nm were evaluated by measuring DLSand the zeta potential. The loading of NM was confirmed to be more than 90% efficient using the UV spectrum.

Glycyrrhizin as a promising kryptonite against SARS-CoV-2: Clinical, experimental, and theoretical evidences

“…Again, it has further been proposed that licorice root membrane may be utilized to produce a bio-based antiviral face mask to limit COVID-19 spreading [144] . Again, based on the carrier stability scoring (CSS) method, glycyrrhizin was selected as the potential compound against SARS-CoV-2 [145] and was subjected to the formulation of micelle nanoparticles. In combination with nafamostat mesylate micelle, it was observed that these two compounds yielded synergistic activity against viral infection.…”

Exploring the Pharmacological Potential of Glycyrrhizic Acid: From Therapeutic Applications to Trends in Nanomedicine

“…As stated before, GA plays key roles in different pathophysiological processes. In this context, the delivery of GA in a controlled and targeted manner may result in new and effective treatments for hepatocarcinoma, viral, and inflammatory diseases [65][66][67][68][69][70][71][72][73][74][75][76][77][78]. This section discusses recent reports that describe the development of new nanomedicine strategies for GA delivery, as summarized in Table 2.…”

“…In vivo investigations using the MHV-A59-induced surrogate mouse model of COVID-19 showed that GA nanoparticles specifically target areas with severe inflammation, such as the lungs, which appeared to improve the accumulation of GANPs and enhance the effectiveness of the treatment [30]. In this sense, a recent interesting approach described a novel computational method named carrier suitability scoring (CSS) for identifying drug carrier candidates using molecular functional groups [78]. After computational analyses, GA and nafamostat mesilate (NM) were selected and converted into micelle nanoparticles to improve drug stability and to effectively treat COVID-19.…”

Recent advances in targeted drug delivery systems for resistant colorectal cancer

“…Hence, to produce CD based tablets, molecular details, analyzing chemical group and molecular dynamics of CA-CD interaction need to be investigated by spectroscopy and molecular modeling [ 145 ]. Additionally, CAD approaches including a clustering algorithm and the Schrödinger software [ 146 ] machine learning (ML) techniques, ensemble learning, support vector machine, artificial neural networks and deep learning models [ 147 ] have been extended to recent pandemic concern, Covid 19 infection [ 148 ]. CAD and artificial intelligence provide new insight in colorectal cancer detection, screening and treatment especially in early stage of disease [ 149 ].…”