Timezone: »
Predicting energetically favorable 3-dimensional conformations of organic molecules frommolecular graph plays a fundamental role in computer-aided drug discovery research.However, effectively exploring the high-dimensional conformation space to identify (meta) stable conformers is anything but trivial.In this work, we introduce RMCF, a novel framework to generate a diverse set of low-energy molecular conformations through samplingfrom a regularized molecular conformation field.We develop a data-driven molecular segmentation algorithm to automatically partition each molecule into several structural building blocks to reduce the modeling degrees of freedom.Then, we employ a Markov Random Field to learn the joint probability distribution of fragment configurations and inter-fragment dihedral angles, which enables us to sample from different low-energy regions of a conformation space.Our model constantly outperforms state-of-the-art models for the conformation generation task on the GEOM-Drugs dataset.We attribute the success of RMCF to modeling in a regularized feature space and learning a global fragment configuration distribution for effective sampling.The proposed method could be generalized to deal with larger biomolecular systems.
Author Information
Lihao Wang (ByteDance AI lab)
Yi Zhou (Bytedance)
Yiqun Wang (ByteDance Inc)
Xiaoqing Zheng (Fudan University)
Xuanjing Huang (Fudan University)
Xuanjing Huang is a Professor of the School of Computer Science, Fudan University, Shanghai, China. She received her PhD degree in Computer Science from Fudan University in 1998. From 2008 to 2009, she is a visiting scholar in CIIR, UMass Amherst. Her research interest includes text retrieval, natural language processing, and data intensive computing. She has published dozens of papers in several major conferences including SIGIR, ACL, ICML, IJCAI, AAAI, CIKM, ISWC, EMNLP, WSDM and COLING. She has also translated the second version of “Modern Information Retrieval” to Chinese. In the research community, she served as the organizer of WSDM 2015, competition chair of CIKM 2014, tutorial chair of COLING 2010, SPC or PC member of past WSDM, SIGIR, WWW, CIKM, ACL, IJCAI, EMNLP and many other conferences.
Hao Zhou (Bytedance AI Lab)
Related Events (a corresponding poster, oral, or spotlight)
-
2022 Poster: Regularized Molecular Conformation Fields »
Thu. Dec 1st through Fri the 2nd Room Hall J #341
More from the Same Authors
-
2022 Poster: CoNT: Contrastive Neural Text Generation »
Chenxin An · Jiangtao Feng · Kai Lv · Lingpeng Kong · Xipeng Qiu · Xuanjing Huang -
2022 Poster: Zero-Shot 3D Drug Design by Sketching and Generating »
Siyu Long · Yi Zhou · Xinyu Dai · Hao Zhou -
2022 Spotlight: CoNT: Contrastive Neural Text Generation »
Chenxin An · Jiangtao Feng · Kai Lv · Lingpeng Kong · Xipeng Qiu · Xuanjing Huang -
2022 Spotlight: Lightning Talks 2A-4 »
Sarthak Mittal · Richard Grumitt · Zuoyu Yan · Lihao Wang · Dongsheng Wang · Alexander Korotin · Jiangxin Sun · Ankit Gupta · Vage Egiazarian · Tengfei Ma · Yi Zhou · Yishi Xu · Albert Gu · Biwei Dai · Chunyu Wang · Yoshua Bengio · Uros Seljak · Miaoge Li · Guillaume Lajoie · Yiqun Wang · Liangcai Gao · Lingxiao Li · Jonathan Berant · Huang Hu · Xiaoqing Zheng · Zhibin Duan · Hanjiang Lai · Evgeny Burnaev · Zhi Tang · Zhi Jin · Xuanjing Huang · Chaojie Wang · Yusu Wang · Jian-Fang Hu · Bo Chen · Chao Chen · Hao Zhou · Mingyuan Zhou -
2022 Spotlight: Zero-Shot 3D Drug Design by Sketching and Generating »
Siyu Long · Yi Zhou · Xinyu Dai · Hao Zhou -
2018 Poster: BRITS: Bidirectional Recurrent Imputation for Time Series »
Wei Cao · Dong Wang · Jian Li · Hao Zhou · Lei Li · Yitan Li -
2017 Poster: A Learning Error Analysis for Structured Prediction with Approximate Inference »
Yuanbin Wu · Man Lan · Shiliang Sun · Qi Zhang · Xuanjing Huang