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Theoretical and Computational Chemistry

Working Paper

A Deep Learning Based Scaffold Hopping Strategy for the Design of Kinase Inhibitors

Lizhao Hu, Yuyao Yang, Shuangjia Zheng, Jun Xu, Ting Ran, Hongming Chen

Version 1 posted 24 May 2021

707

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Theoretical and Computational Chemistry

Working Paper

3D conformational generative models for biological structures using graph information embedded relative coordinates

Mingyuan Xu, Weifeng Huang, Min Xu, Jinping Lei, Hongming Chen

Version 1 posted 27 January 2022

227

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Theoretical and Computational Chemistry

Working Paper

Deep Scaffold Hopping with Multi-modal Transformer Neural Networks

Shuangjia Zheng, Zengrong Lei, Haitao Ai, Hongming Chen, Daiguo Deng, Yuedong Yang

Version 1 posted 28 September 2020

1,315

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4

Citations

Theoretical and Computational Chemistry

Working Paper

Prediction of Compound Synthesis Accessibility Based on Reaction Knowledge Graph

Baiqing Li, Hongming Chen

Version 1 posted 21 May 2021

412

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Theoretical and Computational Chemistry

Working Paper

Memory-Assisted Reinforcement Learning for Diverse Molecular De Novo Design

Thomas Blaschke, Ola Engkvist, Jürgen Bajorath, Hongming Chen

Version 1 posted 23 July 2020

673

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1

Citations

Theoretical and Computational Chemistry

Working Paper

Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold-hopping capability

Oliver Laufkötter, Noé Sturm, Jürgen Bajorath, Ola Engkvist, Hongming Chen

Version 1 posted 15 February 2019

641

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1

Citations

Theoretical and Computational Chemistry

Working Paper

Direct Steering of de novo Molecular Generation using Descriptor Conditional Recurrent Neural Networks (cRNNs)

Panagiotis-Christos Kotsias, Josep Arús-Pous, Hongming Chen, Ola Engkvist, Christian Tyrchan, Esben Jannik Bjerrum

Version 2 posted 25 November 2019

2,439

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2

Citations

Theoretical and Computational Chemistry

Working Paper

Comparative Study of Deep Generative Models on Chemical Space Coverage (v18)

Jie Zhang, Rocío Mercado, Ola Engkvist, Hongming Chen

Version 3 posted 05 February 2021

1,846

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1

Citations

Theoretical and Computational Chemistry

Working Paper

A De Novo Molecular Generation Method Using Latent Vector Based Generative Adversarial Network

Oleksii Prykhodko, Simon Viet Johansson, Panagiotis-Christos Kotsias, Josep Arús-Pous, Esben Jannik Bjerrum, Ola Engkvist, Hongming Chen

Version 4 posted 23 September 2019

2,018

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Theoretical and Computational Chemistry

Working Paper

Exploring the GDB-13 Chemical Space Using Deep Generative Models

Josep Arús-Pous, Thomas Blaschke, Silas Ulander, Jean-Louis Reymond, Hongming Chen, Ola Engkvist

Version 2 posted 19 October 2018

1,749

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Refine Search

24 results in HongMing Chen in Authors: HongMing Chen

A Deep Learning Based Scaffold Hopping Strategy for the Design of Kinase Inhibitors

3D conformational generative models for biological structures using graph information embedded relative coordinates

Deep Scaffold Hopping with Multi-modal Transformer Neural Networks

Prediction of Compound Synthesis Accessibility Based on Reaction Knowledge Graph

Memory-Assisted Reinforcement Learning for Diverse Molecular De Novo Design

Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold-hopping capability

Direct Steering of de novo Molecular Generation using Descriptor Conditional Recurrent Neural Networks (cRNNs)

Comparative Study of Deep Generative Models on Chemical Space Coverage (v18)

A De Novo Molecular Generation Method Using Latent Vector Based Generative Adversarial Network

Exploring the GDB-13 Chemical Space Using Deep Generative Models

24 results in Authors: HongMing Chen