nanoQSAR

The objective of this thematic area is to develop scientifically justified and technically viable methods of quantitative modelling relationships between chemical structure and toxicological targets which will extend understanding of toxicity and behaviour of emerging nanoparticles by establishing relations between experimental (based on available, validated data) and computational properties.

This includes:
• Investigating the impact of size on the physico/chemical properties of NPs at the appropriate level of the quantum-mechanical theory.
• Developing NanoQSAR models of toxicity and environmentally relevant physico/chemical endpoints, based on reliable experimental data and appropriate nano-descriptors.
• Comparing the efficiency of CoMFA/CoMSIA and Hansch Analysis modelling schemes in NanoQSAR.
• Investigating the minimum requirements sufficient for successful validation of NanoQSAR models (minimal number of data, evaluation of the applicability domain etc.) in the light of the OECD Principles for the Validation of (Q)SARs.
• Development of procedures for validating QSPR/QSAR models using probabilistic principles: balance of correlations, balance of correlations with ideal slopes, and filtration of the rare attributes, which can lead to overtraining.
• Estimating the environmental behaviour of NPs based on the physico/chemical data predicted with NanoQSAR.
• Evaluation and publication of the NanoQSAR models and the results in scientific journals and with use of QSAR reporting formats (QMRFs) and QSAR prediction reporting formats (QPRFs).
• Update of the database (including the predicted results).
• Development of the conceptual framework for further grouping NPs based on chemical structure, physicochemical properties, interactions and toxicity.

This part of the NanoPUZZLES brings together all findings and summarizes the results of the project. High quality experimental physicochemical and toxicological data (from Puzzle 1: NanoDATA) and novel descriptors of nanostructure (developed in Puzzle 2: NanoDESC) will be utilized to develop mathematical models describing relationships between the structure and properties/activity. Information on the significance of structural factors responsible for the observed activity will be delivered by Puzzle 3: NanoINTER. The information about the character of interaction mechanisms will be important for an appropriate selection of nanodescriptors representing structural features of the studied nanoparticles.