On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction
- Jannis Born
- Yoel Shoshan
- et al.
- 2022
- J. Chem. Inf. Model.
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9 results for Wendy D. Cornell
CACHE (Critical Assessment of Computational Hit-finding Experiments): A public–private partnership benchmarking initiative to enable the development of computational methods for hit-finding
- Suzanne Ackloo
- Rima Al-awar
- et al.
- 2022
- Nature Reviews Chemistry
Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model
- Jannis Born
- Tien Huynh
- et al.
- 2021
- J. Chem. Inf. Model.
Simplified, interpretable graph convolutional neural networks for small molecule activity prediction
- 2021
- J. Comput. Aided Mol. Des.
Combining docking pose rank and structure with deep learning improves protein−ligand binding mode prediction over a baseline docking approach
- 2020
- J. Chem. Inf. Model.
Deep generative molecular design reshapes drug discovery
- Xiangxiang Zeng
- Fei Wang
- et al.
- 2022
- Cell Reports Medicine
Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation
- Seung-Gu Kang
- Joseph A. Morrone
- et al.
- 2022
- J. Chem. Inf. Model.
In silico Exploration of Inhibitors for SARS-CoV-2's Papain-Like Protease
- Tien Huynh
- Wendy D. Cornell
- et al.
- 2021
- Frontiers in Chemistry
Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development
- Robin Mcentire
- Debbie Szalkowski
- et al.
- 2016
- Drug Discovery Today