Computational methods employed in drug discovery

  • What are the computational techniques used for drug discovery?

    Over the past decades, various CADD techniques such as homology modeling, docking, pharmacophore modeling based virtual screening, conformation generation, ab initio design, toxicity profile, quantitative structure–activity relationship (QSAR), and quantitative free-energy calculation have been greatly improved..

  • Computer-aided drug design (CADD) is a discipline that collects multiple chemical-molecular and quantum strategies with the aim of discovering, designing, and developing therapeutic chemical agents.
  • Machine learning and deep learning algorithms, which are at the core of AI, are being used to analyse vast amounts of data to identify potential drug targets and optimise drug design, resulting in the development of more targeted and effective treatments, which are tailored to the specific needs of individual patients.
CADD methods are broadly classified into structure-based and ligand-based methods. Structure-based methods require the 3D information of the target to be known. Ligand-based methods are used when the 3D structure of the target is not known. They use information about the molecules that bind to the target of interest.
CADD methods are broadly classified into structure-based and ligand-based methods. Structure-based methods require the 3D information of the target to be known. Ligand-based methods are used when the 3D structure of the target is not known.
Computational methods in drug discovery allow rapid screening of a large compound library and determination of potential binders through modeling/simulation and visualization techniques.

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