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Molecular Motif Learning as a pretraining objective for molecular property prediction [PDF]

Nature Communications
Molecular property prediction is crucial for drug discovery in biopharmaceuticals since it helps identify promising compounds, optimizing the efficacy of developing new therapies. Despite its importance, existing deep learning-based methods for this task
Ziyang Liu, Chaokun Wang, Shuwen Zheng, Cheng Wu, Hao Feng, Li Xu, Yue Zheng, Liang Rong, Peng Li   +8 more
doaj   +4 more sources

Advanced deep learning methods for molecular property prediction

Quantitative Biology, 2023
The prediction of molecular properties is a crucial task in the field of drug discovery. Computational methods that can accurately predict molecular properties can significantly accelerate the drug discovery process and reduce the cost of drug discovery.
Chao Pang, Henry H. Y. Tong, Leyi Wei
doaj   +3 more sources

PotentialNet for Molecular Property Prediction [PDF]

ACS Central Science, 2018
13 pages, 5 figures, 8 ...
Evan N. Feinberg, Debnil Sur, Zhenqin Wu, Brooke E. Husic, Huanghao Mai, Yang Li, Saisai Sun, Jianyi Yang, Bharath Ramsundar, Vijay S. Pande   +9 more
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Multimodal fusion with relational learning for molecular property prediction [PDF]

Communications Chemistry
Graph-based molecular representation learning is essential for predicting molecular properties in drug discovery and materials science. Despite its importance, current approaches struggle with capturing the intricate molecular relationships and often ...
Zhengyang Zhou, Yunrui Li, Pengyu Hong, Hao Xu   +3 more
doaj   +5 more sources

Molecular Property Prediction by Combining LSTM and GAT

Biomolecules, 2023
Molecular property prediction is an important direction in computer-aided drug design. In this paper, to fully explore the information from SMILE stings and graph data of molecules, we combined the SALSTM and GAT methods in order to mine the feature ...
Lei Xu, Shourun Pan, Leiming Xia, Zhen Li   +3 more
doaj   +3 more sources

GEOM, energy-annotated molecular conformations for property prediction and molecular generation

Scientific Data, 2022
Measurement(s) Conformer geometries and properties Technology Type(s) Computational ...
Simon Axelrod, Rafael Gómez-Bombarelli
doaj   +5 more sources

Context-informed few-shot molecular property prediction via heterogeneous meta-learning [PDF]

Computational and Structural Biotechnology Journal
Molecular property prediction is essential in diversified applications, as it helps identify molecules with the desired characteristics. However, the task often suffers from limited data, making the few-shot learning challenging.
Junhao Xue, Jun Liu, Kai Chen
doaj   +2 more sources

Efficient 3D kernels for molecular property prediction [PDF]

Bioinformatics
Abstract Motivation This paper addresses the challenge of incorporating 3-dimensional (3D) structural information in graph kernels for machine learning-based virtual screening, a crucial task in drug discovery.
Ankit, Sahely Bhadra, Juho Rousu
europepmc   +3 more sources

MSGRL: A Motif-Driven Self-Supervised Graph Representation Learning Framework for Interpretable Molecular Property Prediction [PDF]

Molecules
Molecular property prediction is a fundamental task in drug discovery and chemical biology, where effective molecular representations are essential for accurate prediction.
You Wu, Yuxin Jiang, Xiaoyun Qi, Haitao Fu, Qiyu Tang, Wen Wang, Cheng Zeng, Guosheng Zhu   +7 more
doaj   +2 more sources

Meta-learning linear models for molecular property prediction [PDF]

Digital Discovery
Chemists in search of structure–property relationships face great challenges due to limited high quality, concordant datasets. Machine learning (ML) has significantly advanced predictive capabilities in chemical sciences, but these modern data-driven ...
Yulia Pimonova, Michael G. Taylor, Alice Allen, Ping Yang, Nicholas Lubbers   +4 more
doaj   +4 more sources