Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR.

Area of Science:

• Computational Chemistry
• Cheminformatics
• Drug Discovery

Background:

• The molecular similarity principle is a cornerstone in computational chemistry and drug discovery.
• Advancements in computational modeling require robust methods for capturing molecular properties.
• Effective analysis of large datasets, including high-throughput screening (HTS) data, is crucial.

Purpose of the Study:

• To discuss recent developments in computational chemistry, emphasizing the molecular similarity principle.
• To explore novel descriptors for molecular property prediction and the critical aspect of computational model validation.
• To present applications and data examination techniques, including HTS data analysis and virtual screening.

Main Methods:

• Utilizing novel descriptors to capture molecular properties.
• Applying the molecular similarity principle in computational modeling.
• Examining data from high-throughput screening (HTS) campaigns and employing virtual screening techniques.

Main Results:

• Successful applications of virtual screening for identifying potential drug candidates.
• Effective database clustering and comparisons, including drug-likeness and in-house-likeness assessments.
• Large-scale validations of docking and scoring programs demonstrating their utility.

Conclusions:

• The trend towards rigorous model validation in computational chemistry is highly valued.
• While current methods have limitations, ongoing research aims to overcome them.
• Continued development in descriptors and modeling techniques promises future advancements in drug discovery.