Molecular Generation with Reduced Labeling through Constraint Architecture.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.3c00579
Abstract: In the past few years, a number of machine learning (ML)-based molecular generative models have been proposed for generating molecules with desirable properties, but they all require a large amount of label data of pharmacological… read more here.
Keywords: reduced labeling; molecular generation; generation; labeling constraint ... See more keywords
CMGN: a conditional molecular generation net to design target-specific molecules with desired properties.
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad185
Abstract: The rational design of chemical entities with desired properties for a specific target is a long-standing challenge in drug design. Generative neural networks have emerged as a powerful approach to sample novel molecules with specific… read more here.
Keywords: desired properties; molecular generation; design; generation net ... See more keywords
Geometry-Based Molecular Generation With Deep Constrained Variational Autoencoder.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3147790
Abstract: Finding target molecules with specific chemical properties plays a decisive role in drug development. We proposed GEOM-CVAE, a constrained variational autoencoder based on geometric representation for molecular generation with specific properties, which is protein-context-dependent. In… read more here.
Keywords: molecular generation; constrained variational; variational autoencoder; geometry ... See more keywords
Cross-Adversarial Learning for Molecular Generation in Drug Design
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Pharmacology"
DOI: 10.3389/fphar.2021.827606
Abstract: Molecular generation is an important but challenging task in drug design, as it requires optimization of chemical compound structures as well as many complex properties. Most of the existing methods use deep learning models to… read more here.
Keywords: cross adversarial; drug design; molecular generation; generation ... See more keywords
3CLpro inhibitors: DEL-based molecular generation
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Pharmacology"
DOI: 10.3389/fphar.2022.1085665
Abstract: Molecular generation (MG) via machine learning (ML) has speeded drug structural optimization, especially for targets with a large amount of reported bioactivity data. However, molecular generation for structural optimization is often powerless for new targets.… read more here.
Keywords: inhibitors del; structural optimization; 3clpro inhibitors; molecular generation ... See more keywords
Deep learning for molecular generation.
Sign Up to like & getrecommendations! Published in 2019 at "Future medicinal chemistry"
DOI: 10.4155/fmc-2018-0358
Abstract: De novo drug design aims to generate novel chemical compounds with desirable chemical and pharmacological properties from scratch using computer-based methods. Recently, deep generative neural networks have become a very active research frontier in de… read more here.
Keywords: learning molecular; deep learning; novo drug; generation ... See more keywords