2. Academic Validation
  3. Sequence-based drug design as a concept in computational drug design

Sequence-based drug design as a concept in computational drug design

  • Nat Commun. 2023 Jul 14;14(1):4217. doi: 10.1038/s41467-023-39856-w.
Lifan Chen # 1 2,  Zisheng Fan # 1 3 4,  Jie Chang # 1 3,  Ruirui Yang # 1 2 4,  Hui Hou # 1,  Hao Guo 1,  Yinghui Zhang 1 2,  Tianbiao Yang 1 2,  Chenmao Zhou 1 3,  Qibang Sui 1 2,  Zhengyang Chen 1 2,  Chen Zheng 1,  Xinyue Hao 1 3,  Keke Zhang 1 3,  Rongrong Cui 1,  Zehong Zhang 1 2,  Hudson Ma 1,  Yiluan Ding 5,  Naixia Zhang 5,  Xiaojie Lu 1 2,  Xiaomin Luo 1 2,  Hualiang Jiang 1 2 3 4 6,  Sulin Zhang 7 8,  Mingyue Zheng 9 10 11 12 13
Affiliations

Affiliations

  • 1 Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China.
  • 2 University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing, 100049, China.
  • 3 School of Chinese Materia Medica, Nanjing University of Chinese Medicine, 138 Xianlin Road, Jiangsu, Nanjing, 210023, China.
  • 4 Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, No. 393 Huaxia Middle Road, Shanghai, 200031, China.
  • 5 Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China.
  • 6 School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, 1 Sub-lane Xiangshan, Hangzhou, 310024, China.
  • 7 Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China. [email protected].
  • 8 University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing, 100049, China. [email protected].
  • 9 Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China. [email protected].
  • 10 University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing, 100049, China. [email protected].
  • 11 School of Chinese Materia Medica, Nanjing University of Chinese Medicine, 138 Xianlin Road, Jiangsu, Nanjing, 210023, China. [email protected].
  • 12 Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, No. 393 Huaxia Middle Road, Shanghai, 200031, China. [email protected].
  • 13 School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, 1 Sub-lane Xiangshan, Hangzhou, 310024, China. [email protected].
  • # Contributed equally.
PMID: 37452028 DOI: 10.1038/s41467-023-39856-w
Abstract

Drug development based on target proteins has been a successful approach in recent decades. However, the conventional structure-based drug design (SBDD) pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, we propose a sequence-to-drug concept for computational drug design based on protein sequence information by end-to-end differentiable learning. We validate this concept in three stages. First, we design TransformerCPI2.0 as a core tool for the concept, which demonstrates generalization ability across proteins and compounds. Second, we interpret the binding knowledge that TransformerCPI2.0 learned. Finally, we use TransformerCPI2.0 to discover new hits for challenging drug targets, and identify new target for an existing drug based on an inverse application of the concept. Overall, this proof-of-concept study shows that the sequence-to-drug concept adds a perspective on drug design. It can serve as an alternative method to SBDD, particularly for proteins that do not yet have high-quality 3D structures available.

Figures
Products