papers related to Generative AI and Deep Learning for Molecular Optimization.
A visual presentation of the process of molecular optimization
Refs
Beck, Hartmut, Tobias Thaler, Daniel Meibom, Mark Meininghaus, Hannah Jörißen, Lisa Dietz, Carsten Terjung et al. "Potent and selective human prostaglandin F (FP) receptor antagonist (BAY-6672) for the treatment of idiopathic pulmonary fibrosis (IPF)." Journal of medicinal chemistry 63, no. 20 (2020): 11639-11662.
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Deep Lead Optimization: Leveraging Generative AI for Structural Modification [2024]
Zhang, Odin, Haitao Lin, Hui Zhang, Huifeng Zhao, Yufei Huang, Yuansheng Huang, Dejun Jiang, Chang-yu Hsieh, Peichen Pan, and Tingjun Hou.
arXiv:2404.19230 (2024) -
Computer-aided multi-objective optimization in small molecule discovery [2023]
Fromer, J. C., & Coley, C. W.
Patterns 4.2 (2023)
DrugBank
ChEMBL
PubChem
https://pubchem.ncbi.nlm.nih.gov/
- Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization [2022]
Gao, Wenhao, Tianfan Fu, Jimeng Sun, and Connor W. Coley.
Paper | code
- Utilizing deep learning to explore chemical space for drug lead optimization [2023]
Chakraborty, Rajkumar, and Yasha Hasija.
Expert Systems with Applications (2023) | code
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FFLOM: A Flow-Based Autoregressive Model for Fragment-to-Lead Optimization [2023]
Jieyu Jin, Dong Wang, Guqin Shi, Jingxiao Bao, Jike Wang, Haotian Zhang, Peichen Pan, Dan Li, Xiaojun Yao, Huanxiang Liu, Tingjun Hou, and Yu Kang
J. Med. Chem. (2023) | code -
Domain-Agnostic Molecular Generation with Self-feedback [2023]
Yin Fang, Ningyu Zhang, Zhuo Chen, Xiaohui Fan, Huajun Chen
Paper | code
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Molecular generation strategy and optimization based on A2C reinforcement learning in de novo drug design [2023]
Wang, Qian, Zhiqiang Wei, Xiaotong Hu, Zhuoya Wang, Yujie Dong, and Hao Liu.
Bioinformatics: btad693. (2023) | code -
CFOM: Lead Optimization For Drug Discovery With Limited Data [2023]
Kaminsky, Natan, Uriel Singer, and Kira Radinsky.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. (2023) | code -
Transformer-based deep learning method for optimizing ADMET properties of lead compounds [2023]
Yang, Lijuan, Chao Jin, Guanghui Yang, Zhitong Bing, Liang Huang, Yuzhen Niu, and Lei Yang.
Physical Chemistry Chemical Physics 25.3 (2023) -
Molecular optimization by capturing chemist’s intuition using deep neural networks [2021]
He, Jiazhen, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, and Ola Engkvist.
J Cheminform 13, 26 (2021) | code -
Transformer-based molecular optimization beyond matched molecular pairs [2022]
He, Jiazhen, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, and Ola Engkvist.
J Cheminform 14, 18 (2022) | code -
Transformer Neural Network-Based Molecular Optimization Using General Transformations [2021]
He, Jiazhen, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, and Ola Engkvist.
Paper | code
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Multi-objective Molecular Optimization for Opioid Use Disorder Treatment Using Generative Network Complex [2023]
Feng, Hongsong, Rui Wang, Chang-Guo Zhan, and Guo-Wei Wei.
J. Med. Chem. (2023) | code -
Utilizing deep learning to explore chemical space for drug lead optimization [2023]
Chakraborty, Rajkumar, and Yasha Hasija.
Expert Systems with Applications (2023) | code -
Constrained Bayesian optimization for automatic chemical design using variational autoencoders [2019]
Griffiths, Ryan-Rhys, and José Miguel Hernández-Lobato.
Chemical science 11.2 (2020) | code
- FFLOM: A Flow-Based Autoregressive Model for Fragment-to-Lead Optimization [2023]
Jieyu Jin, Dong Wang, Guqin Shi, Jingxiao Bao, Jike Wang, Haotian Zhang, Peichen Pan, Dan Li, Xiaojun Yao, Huanxiang Liu, Tingjun Hou, and Yu Kang
J. Med. Chem. (2023) | code
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Text-Guided Multi-Property Molecular Optimization with a Diffusion Language Model [2024]
Yida Xiong, Kun Li, Weiwei Liu, Jia Wu, Bo Du, Shirui Pan, Wenbin Hu.
arXiv:2410.13597 (2024) -
Fragment-Masked Molecular Optimization [2024]
Kun Li and Xiantao Cai and Jia Wu and Bo Du and Wenbin Hu.
arXiv:2408.09106 (2024) -
Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules with Desirable Properties [2023]
Guo, Siyuan, Jihong Guan, and Shuigeng Zhou.
arXiv:2310.04463 (2023) -
A dual diffusion model enables 3D binding bioactive molecule generation and lead optimization given target pockets [2023]
Huang, Lei.
bioRxiv 2023.01.28.526011
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Molecular generation strategy and optimization based on A2C reinforcement learning in de novo drug design [2023]
Wang, Qian, Zhiqiang Wei, Xiaotong Hu, Zhuoya Wang, Yujie Dong, and Hao Liu.
Bioinformatics: btad693. (2023) | code -
ReBADD-SE: Multi-objective molecular optimisation using SELFIES fragment and off-policy self-critical sequence training [2023]
Choi, Jonghwan, Sangmin Seo, Seungyeon Choi, Shengmin Piao, Chihyun Park, Sung Jin Ryu, Byung Ju Kim, and Sanghyun Park.
Paper | code -
Gargoyles: An Open Source Graph-based molecular optimization method based on Deep Reinforcement Learning [2023]
Erikawa, D., Yasuo, N., & Sekijima, M.
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Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design [2019]
Ståhl, Niclas, Goran Falkman, Alexander Karlsson, Gunnar Mathiason, and Jonas Bostrom.
Paper | code
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Optimizing Drug Design by Merging Generative AI With Active Learning Frameworks [2023]
Isaac Filella-Merce, Alexis Molina, Marek Orzechowski, Lucía Díaz, Yang Ming Zhu, Julia Vilalta Mor, Laura Malo, Ajay S Yekkirala, Soumya Ray, Victor Guallar
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Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling [2023]
Gusev, Filipp, Evgeny Gutkin, Maria G. Kurnikova, and Olexandr Isayev.
Paper
- GPMO: Gradient Perturbation-Based Contrastive Learning for Molecule Optimization [2023]
Yang, Xixi, Li Fu, Yafeng Deng, Yuansheng Liu, Dongsheng Cao, and Xiangxiang Zeng
IJCAI(2023)
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MolDrug (from Molecule to Drug) is a python package for drug-oriented optimization on the chemical space [2023]
- Domain-Agnostic Molecular Generation with Self-feedback [2023]
Yin Fang, Ningyu Zhang, Zhuo Chen, Xiaohui Fan, Huajun Chen
Paper | code
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Small Molecule Optimization with Large Language Models [2024]
Guevorguian, Philipp, Menua Bedrosian, Tigran Fahradyan, Gayane Chilingaryan, Hrant Khachatrian, and Armen Aghajanyan.
arXiv:2407.18897 (2024) | code -
DrugAssist: A Large Language Model for Molecule Optimization [2023]
Ye, Geyan, Xibao Cai, Houtim Lai, Xing Wang, Junhong Huang, Longyue Wang, Wei Liu, and Xiangxiang Zeng.
arXiv:2401.10334 (2023) | code
- Differentiable Scaffolding Tree for Molecule Optimization [2022]
Fu, Tianfan, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, and Jimeng Sun.
Paper | code
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Fragment-Masked Molecular Optimization [2024]
Kun Li and Xiantao Cai and Jia Wu and Bo Du and Wenbin Hu.
arXiv:2408.09106 (2024) -
FOMO: A Fragment-based Objective Molecule Optimization Framework [2023]
Ma, Cong, Zeqi Zhang, Min Xu, and Haimin Zhang.
Research Square. PREPRINT. (2023) | code -
FFLOM: A Flow-Based Autoregressive Model for Fragment-to-Lead Optimization [2023]
Jieyu Jin, Dong Wang, Guqin Shi, Jingxiao Bao, Jike Wang, Haotian Zhang, Peichen Pan, Dan Li, Xiaojun Yao, Huanxiang Liu, Tingjun Hou, and Yu Kang
J. Med. Chem. (2023) | code -
ReBADD-SE: Multi-objective molecular optimisation using SELFIES fragment and off-policy self-critical sequence training [2023]
Choi, Jonghwan, Sangmin Seo, Seungyeon Choi, Shengmin Piao, Chihyun Park, Sung Jin Ryu, Byung Ju Kim, and Sanghyun Park.
Paper | code -
A deep generative model for molecule optimization via one fragment modification [2021]
Chen, Ziqi, Martin Renqiang Min, Srinivasan Parthasarathy, and Xia Ning.
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Fragment-Based Sequential Translation for Molecular Optimization [2021]
Chen, Benson, Xiang Fu, Regina Barzilay, and Tommi Jaakkola.
Paper
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Elion: A Deep Learning Based Platform for Multi-Objective Drug Hit Optimization [2023]
Seabra, Gustavo, and Chenglong Li.
chemrxiv-2023-n526m (2023) | code -
Multi-Objective and Many-Objective Optimisation: Present and Future in de novo Drug Design [2023]
Angelo, Jaqueline S., Isabella Alvim Guedes, Helio JC Barbosa, and Laurent E. Dardenne.
chemrxiv-2023-q0zdf-v2 (2023) -
Human-in-the-loop assisted de novo molecular design [2022]
Sundin, Iiris, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos, Esben Jannik Bjerrum, Markus Heinonen, Atanas Patronov, Samuel Kaski, and Ola Engkvist.
Paper | code -
Molecule optimization via multi-objective evolutionary in implicit chemical space [2022]
Xia, Xin, Yansen Su, Chunhou Zheng, and Xiangxiang Zeng.
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Efficient multi-objective molecular optimization in a continuous latent spac [2019]
Winter, Robin, Floriane Montanari, Andreas Steffen, Hans Briem, Frank Noé, and Djork-Arné Clevert.
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