The numerical encoding of chemical structure with Topological Indices(TIs) is currently growing in importance in Medicinal Chemistry with the use of Bioinformatics. This approach allows the rapid collection, retrieval, annotation, mining comparison and of chemical structures within in the case of large databases. Topological Indices can subsequently be used to seek quantitative structure-activity relationships (QSAR), which are models connecting chemical structure with biological activity. In the Starting days more than 1500 of these indices are there but at the end of the last century, researchers produced many Topological Indices with essentially the same advantages and disadvantages. One of the problems associated with Topological Indices is that researchers aimed their efforts only at the codification of chemical connectivity for small-sized drugs, but the emphasis is placed on new chiral Topical Indices.
3D QSAR approaches in QSAR studies based on the biological activity of Lead Molecules:
• 3D nano-QSAR (three-dimensional Quantitative Structure-Activity Relationships, such us Comparative Molecular Field Analysis
• CoMFA/Comparative Molecular Similarity Indices Analysis, CoMSIA analysis employed for nanomaterials)
• QSAR model users to be able to identify a proper and efficient method to investigate biological activity of nanoparticles to describe the un3D QSAR approaches in nano-QSAR studies based on the biological activity of the Lead molecules.
Advantages of QSAR Studies in Medicinal Chemistry:
· flexible Topological Indices for unifying QSAR models with multiple targets
· TIs for DNA and protein sequences
· TIs for 2D RNA structures
· TPGIs and drug-protein or drug-RNA quantitative
· TIs to encode protein surface information and TIs for protein interaction networks (PINs)
· Use of automatic relevance determination in QSAR studies using Bayesian neural networks
To know More about medicinal Chemistry Follow the link:
https://bioorganic-medicinal.chemistryconferences.org/
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