Generative machine learning models have become widely adopted in drug discovery and other fields to produce new molecules and explore molecular space, with the goal of discovering novel compounds with

NIAID Data Ecosystem20

chandar-lab/ZINC_250k

药物发现

分子设计

该数据集是一个包含多种分子特征和药物相关数值特征的集合，适用于药物设计和分子性质预测等研究。它包含了分子的SMILES、Deep SMILES、SELFIES等表示，以及与多种药物分子相关的数值属性，如相似度评分和活性评分等。

Hugging Face2025-06-24 更新20

C3 symmetric peptide design number 1, Sporty, crystal form 1

分子设计

晶体结构分析

C3 symmetric peptide design number 1, Sporty, crystal form 1 Descriptor: C3-1, Sporty, crystal form 1, ... Authors: Mulligan, V.K, Kang, C.S, Antselovich, I, Sawaya, M.R, Yeates, T.O, Baker, D. Deposi

Protein Data Bank Japan2024-10-23 更新20

Molecular Design Learned from the Natural Product Porphyra-334: Molecular Generation via Chemical Variational Autoencoder versus Database Mining via Similarity Search, A Comparative Study

分子设计

功能基因发现

A comparative study is presented. The method via chemical variational autoencoder (VAE) and the method via similarity search are compared, focusing on their generation ability for new functional molec

NIAID Data Ecosystem20