This repository contains the implementation of MMO-VAE, a Variational AutoEncoder (VAE) with mask-guided multi-objective optimization for de novo drug design. Implements KLD Sigmoid Annealing and ...

This repository is the official implementation of DrugHIVE, a deep hierarchical variational autoencoder developed for structure-based drug design. JCIM paper. To sample from DrugHIVE, first adjust the ...

The de novo design of drug molecules is recognized as a time-consuming and costly process, and computational approaches have been applied in each stage of the drug discovery pipeline. Variational ...

Schematic of variational autoencoder (VAE) antimicrobial peptide (AMP) generation and design process. The VAE AMP generation and design process occurs in two stages: (1) training the VAE for the ...

Variational Autoencoder for Generation of Antimicrobial Peptides. Scott N. Dean. Scott N. Dean. National Research Council Associate, Washington, D.C. 20001, ... De novo drug design aims to generate ...

1 Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Department of Chemistry, Southern Methodist University, Dallas, ... The variational autoencoder with 4 hidden ...

In this work, we propose a machine learning approach to generate novel molecules starting from a seed compound, its three-dimensional (3D) shape, and its pharmacophoric features. The pipeline draws ...

Generating Synthetic Data Using a Variational Autoencoder with PyTorch. Generating synthetic data is useful when you have imbalanced training data for a particular ... Because the input values are ...