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A critical factor in achieving accurate molecular property prediction lies in the appropriate representation of molecular structures. Presently, prevalent deep learning\u2013based molecular representations rely on 2D structure information as the primary molecular representation, often overlooking essential three-dimensional (3D) conformational information due to the inherent limitations of 2D structures in conveying atomic spatial relationships. In this study, we propose employing the Gram matrix as a condensed representation of 3D molecular structures and for efficient pretraining objectives. Subsequently, we leverage this matrix to construct a novel molecular representation model, Pre-GTM, which inherently encapsulates 3D information. The model accurately predicts the 3D structure of a molecule by estimating the Gram matrix. Our findings demonstrate that Pre-GTM model outperforms the baseline Graphormer model and other pretrained models in the QM9 and MoleculeNet quantitative property prediction task. The integration of the Gram matrix as a condensed representation of 3D molecular structure, incorporated into the Pre-GTM model, opens up promising avenues for its potential application across various domains of molecular research, including drug design, materials science, and chemical engineering.<\/jats:p>","DOI":"10.1093\/bib\/bbae340","type":"journal-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T11:39:34Z","timestamp":1720697974000},"source":"Crossref","is-referenced-by-count":3,"title":["Gram matrix: an efficient representation of molecular conformation and learning objective for molecular pretraining"],"prefix":"10.1093","volume":"25","author":[{"given":"Wenkai","family":"Xiang","sequence":"first","affiliation":[{"name":"Lingang Laboratory , Shanghai 200031 , China"}]},{"given":"Feisheng","family":"Zhong","sequence":"additional","affiliation":[{"name":"Drug Discovery and Design Center , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"Shanghai Institute of Materia Medica, Chinese Academy of Sciences , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"University of Chinese Academy of Sciences , No. 19A Yuquan Road, Beijing 100049 , China"},{"name":"Fujian Key Laboratory of Drug Target Discovery and Structural and Functional Research , School of Pharmacy, , Fuzhou 350122 , China"},{"name":"Fujian Medical University , School of Pharmacy, , Fuzhou 350122 , China"}]},{"given":"Lin","family":"Ni","sequence":"additional","affiliation":[{"name":"Drug Discovery and Design Center , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"Shanghai Institute of Materia Medica, Chinese Academy of Sciences , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"Nanjing University of Chinese Medicine , 138 Xianlin Road, Nanjing 210023 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3323-3092","authenticated-orcid":false,"given":"Mingyue","family":"Zheng","sequence":"additional","affiliation":[{"name":"Drug Discovery and Design Center , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"Shanghai Institute of Materia Medica, Chinese Academy of Sciences , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"University of Chinese Academy of Sciences , No. 19A Yuquan Road, Beijing 100049 , China"},{"name":"Nanjing University of Chinese Medicine , 138 Xianlin Road, Nanjing 210023 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9547-0643","authenticated-orcid":false,"given":"Xutong","family":"Li","sequence":"additional","affiliation":[{"name":"Drug Discovery and Design Center , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"Shanghai Institute of Materia Medica, Chinese Academy of Sciences , State Key Laboratory of Drug Research, , 555 Zuchongzhi Road, Shanghai 201203 , China"},{"name":"University of Chinese Academy of Sciences , No. 19A Yuquan Road, Beijing 100049 , China"}]},{"given":"Qian","family":"Shi","sequence":"additional","affiliation":[{"name":"Lingang Laboratory , Shanghai 200031 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2964-7425","authenticated-orcid":false,"given":"Dingyan","family":"Wang","sequence":"additional","affiliation":[{"name":"Lingang Laboratory , Shanghai 200031 , China"}]}],"member":"286","published-online":{"date-parts":[[2024,7,11]]},"reference":[{"key":"2024071111382289000_ref1","doi-asserted-by":"crossref","DOI":"10.3390\/ijms17020144","article-title":"Insights into protein\u2013ligand interactions: mechanisms, models, and methods","volume":"17","author":"Du","year":"2016","journal-title":"Int J Mol 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