Bilodeau, Camille published the artcileGenerating molecules with optimized aqueous solubility using iterative graph translation, Recommanded Product: N-Methylformamide, the main research area is candidate mol optimization aqueous solubility.
While mol. discovery is critical for solving many scientific problems, the time and resource costs of experiments make it intractable to fully explore chem. space. Here, we present a generative modeling framework that proposes novel mols. that are 1) based on starting candidate structures and 2) optimized with respect to one or more objectives or constraints. We explore how this framework performs in an applied setting by focusing on the problem of optimizing mols. for aqueous solubility, using an exptl. database containing data curated from the literature. The resulting model was capable of improving mols. with a range of starting solubilities. When synthetic feasibility was applied as a secondary optimization constraint (estimated using a combination of synthetic accessibility and retrosynthetic accessibility scores), the model generated synthetically feasible mols. 83.0% of the time (compared with 59.9% of the time without the constraint). To validate model performance exptl., a set of candidate mols. was translated using the model and the solubilities of the candidate and generated mols. were verified exptl. We addnl. validated model performance via exptl. measurements by holding out the top 100 most soluble mols. during training and showing that the model could rediscover 33 of those mols. To determine the sensitivity of model performance to dataset size, we trained the model on different subsets of the initial training dataset. We found that model performance did not decrease significantly when the model was trained on a random 50% subset of the training data but did decrease when the model was trained on subsets containing only less soluble mols. (i.e., the bottom 50%). Overall, this framework serves as a tool for generating optimized, synthetically feasible mols. that can be applied to a range of problems in chem. and chem. engineering.
Reaction Chemistry & Engineering published new progress about Solubility. 123-39-7 belongs to class amides-buliding-blocks, name is N-Methylformamide, and the molecular formula is C2H5NO, Recommanded Product: N-Methylformamide.
Referemce:
Amide – Wikipedia,
Amide – an overview | ScienceDirect Topics