Multi-QSAR approaches for investigating the relationship between chemical structure descriptors of Thiadiazole derivatives and their corrosion inhibition performance

In this study, different QSAR approaches based on the multiple linear regression (MLR), the kernel-based Partial Least-Square (kPLS) and Pharma-RQSAR models have been applied to investigate the relationship between chemical structure descriptors of thiadiazole derivatives and their anticorrosion activity. The screened classical descriptors were firstly used to establish the linear regression model. In addition, six binary fingerprints were successfully applied using the kernel-based Partial Least-Square (kPLS), with priority given to the atom-pair fingerprint model. The Pharma-RQSAR model was also used to analyze the role of the various substitutions in the common substructure. The atom-pair descriptors and Pharma-RQSAR models have the advantage of visualizing the contribution maps, suggesting the general substitution requirements of the thiadiazole derivatives as potential corrosion inhibitors. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

In this study, various QSAR approaches were used to investigate the relationship between chemical structure descriptors of thiadiazole derivatives and their anticorrosion activity, providing insights into the general substitution requirements of potential corrosion inhibitors.