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By harnessing the vast amounts of data generated throughout the development pipeline, pharmaceutical companies can accelerate the discovery of novel therapies, optimize clinical trial design, enhance drug safety monitoring, and deliver personalized medicine, ultimately improving patient outcomes and transforming the future of healthcare.
The current version of Chemistry42 uses over 40 generative models, including generative autoencoders and generative adversarial networks as well as both structure-based and ligand-based drug design to generate and optimise de novo smallmolecules. The novel molecules were further ranked based on their ADME and selectivity profiles.
Now >20% of all commercialised medicines in the pharmaceutical industry contain a fluorine atom [2]. Even newer from the pharma benches are 12 smallmolecule drugs highlighted by Chris de Savi [4], whose structures were first disclosed at the ACS and AACR meetings in Q1 2023. Benjamin M. Airaksinen.
In a brief section entitled “Predicting Protein-SmallMolecule Complexes”, the authors mention their efforts to generate structures of bound non-covalent and covalent smallmolecule ligands. from the deposited model. Similar issues can impact datasets used for QSAR or ADME modeling.
Traditionally, drug discovery has focused on small-molecule therapeutics, typically with a molecular weight of less than 500 Daltons. 2 Typically, small-molecule drugs target active sites buried inside proteins. What are macrocycles and why are they interesting for drug discovery?
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