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Found 5 papers, 3 papers with code
Latent Chemical Space Searching for Plug-in Multi-objective Molecule Generation
Molecular generation, an essential method for identifying new drug structures, has been supported by advancements in machine learning and computational technology.
Bridging the Gap between Chemical Reaction Pretraining and Conditional Molecule Generation with a Unified Model
Chemical reactions are the fundamental building blocks of drug design and organic chemistry research.
TF3P: Three-dimensional Force Fields Fingerprint Learned by Deep Capsular Network
Molecular fingerprints are the workhorse in ligand-based drug discovery.
DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning
Furthermore, the generated compounds were evaluated by molecular docking in DRD2 targets and the results demonstrated that this approach can be effectively applied to solve several drug design problems, including the generation of compounds containing a given scaffold and de novo drug design of potential drug candidates with specific docking scores.
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model
Recently, deep generative models have revealed itself as a promising way of performing de novo molecule design.
Ranked #4 on
Molecular Graph Generation
on InterBioScreen
