Abstract
This work applied the quantitative structure-activity relationships (QSAR) theory to predict the inhibitory activity exhibited by 40 unsymmetrical aromatic disulfide compounds against the SARS-CoV main protease. Different freely available molecular descriptor programs provided 67,116 independent non-conformational molecular descriptors. This great number of descriptors contained multidimensional representations of the chemical structure and was analyzed through multivariable linear regressions and the replacement method variable subset selection technique. The developed QSAR model achieved an acceptable statistical quality and provided a prospective guide that was considered useful for predicting the inhibitory activity of structurally-related aromatic disulfide compounds on the SARS-CoV main protease.
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