DeepBioisostere: Discovering Bioisosteres with Deep Learning for a Fine Control of Multiple Molecular Properties

enthalten in: arXiv.org | 2024

von Kim, H. | Moon, S. | Zhung, W. | +2

DeepBioisostere: Discovering Bioisosteres with Deep Learning for a Fine Control of Multiple Molecular Properties

enthalten in: arXiv.org | 2024

von Kim, H. | Moon, S. | Zhung, W. | +2

Toward generalizable structure‐based deep learning models for protein–ligand interaction prediction : Challenges and strategies

enthalten in: Wiley Interdisciplinary Reviews: Computational Molecular Science | 2024

von Moon, S. | Zhung, W. | Kim, W.

PIGNet2: A Versatile Deep Learning-based Protein-Ligand Interaction Prediction Model for Binding Affinity Scoring and Virtual Screening

enthalten in: arXiv.org | 2023

von Moon, S. | Hwang, S. | Lim, J. | +1

GeoTMI:Predicting quantum chemical property with easy-to-obtain geometry via positional denoising

enthalten in: arXiv.org | 2023

von Kim, H. | Woo, J. | Kim, S. | +3

PIGNet : a physics-informed deep learning model toward generalized drug-target interaction predictions

enthalten in: Chemical science | 2022

von Moon, S. | Zhung, W. | Yang, S. | +2

PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions

enthalten in: arXiv.org | 2020

von Moon, S. | Zhung, W. | Yang, S. | +2

Scaffold-based molecular design with a graph generative model

enthalten in: Chemical science | 2019

von Lim, J. | Hwang, S. | Moon, S. | +2

Scaffold-based molecular design using graph generative model

enthalten in: arXiv.org | 2019

von Lim, J. | Hwang, S. | Kim, S. | +2