Hybrid Docking-Nano-QSPR: An Alternative Approach for Prediction of Chemicals Adsorption on Nanoparticles

In this study, a new hybrid docking-quantitative structure–property relationship (QSPR) methodology was used to model and predict the adsorption coefficients of some small organic compounds on pristine multiwall carbon nanotube (MWCNT). In this method, descriptors are calculated from the reproduced experimental conformations by molecular docking to develop predictive QSPR models. Three MLR models with squared correlation coefficient ([Formula: see text] values of 0.93, 0.94 and 0.95 were selected. The prediction power of models was evaluated on 12-member test set, which was not used during the modeling and led to [Formula: see text] values of 0.88, 0.85 and 0.93. This methodology gives new insight into factors influenced on the adsorption of nanoparticles.

SEABED: Small molEcule activity scanner weB servicE baseD

Motivation: The SEABED web server integrates a variety of docking and QSAR techniques in a user-friendly environment. SEABED goes beyond the basic docking and QSAR web tools and implements extended functionalities like receptor preparation, library editing, flexible ensemble docking, hybrid docking/QSAR experiments or virtual screening on protein mutants. SEABED is not a monolithic workflow tool but Software as a Service platform. Availability and implementation: SEABED is a free web server available athttp://www.bsc.es/SEABED. No registration is required. Contact: [email protected] Supplementary information: Supplementary data are available atBioinformatics online.