Citation: Shi-Ming Peng, Yu Zhou, Niu Huang. Improving the accuracy of pose prediction in molecular docking via structural filtering and conformational clustering[J]. Chinese Chemical Letters, ;2013, 24(11): 1001-1004. shu

Improving the accuracy of pose prediction in molecular docking via structural filtering and conformational clustering

Shi-Ming Peng ^a,c ,
Yu Zhou ^b,c ,
Niu Huang ^c,,

1.
a College of Biological Sciences, China Agricultural University, Beijing 100193, China;
2.
b College of Life Sciences, Beijing Normal University, Beijing 100875, China;
3.
c National Institute of Biological Sciences, Beijing 102206, China

Corresponding author: Niu Huang,
Received Date: 7 March 2013
Available Online: 27 May 2013

Structure-based virtual screening (molecular docking) is now one of the most pragmatic techniques to leverage target structure for ligand discovery. Accurate binding pose prediction is critical to molecular docking. Here, we describe a general strategy to improve the accuracy of docking pose prediction by implementing the structural descriptor-based filtering and KGS-penalty function-based conformational clustering in an unbiased manner. We assessed our method against 150 high-quality protein-ligand complex structures. Surprisingly, such simple components are sufficient to improve the accuracy of docking pose prediction. The success rate of predicting near-native docking pose increased from 53% of the targets to 78%. We expect that our strategymay have general usage in improving currently available molecular docking programs.
- Molecular docking,
- Pose prediction,
- Structural descriptor,
- Conformational clustering
1. [1]
  [1] X. Barril, R.E. Hubbard, S.D. Morley, Virtual screening in structure-based drug discovery, Mini Rev. Med. Chem. 4 (2004) 779-791.
2. [2]
  [2] H. Xu, Z. Jin, S. Liu, et al., Design, synthesis characterization and in vitro biological activity of a series of 3-aryl-6-(bromoarylmethyl)-7H-thiazolo[3,2-b]-1, 2, 4-triazin-7-one derivatives as the novel acetylcholinesterase inhibitors, Chin. Chem. Lett. 23 (2012) 765-768.
3. [3]
  [3] F. Zeng, S. Peng, L. Li, et al., HAT off: structure-based identification of druglike inhibitors of p300 histone acetyltransferase, Acta Pharm. Sin. 48 (2013) 700-708.
4. [4]
  [4] X.H. Ma, F. Zhu, X. Liu, et al., Virtual screening methods as tools for drug lead discovery from large chemical libraries, Curr. Med. Chem. 19 (2012) 5562-5571.
5. [5]
  [5] B.K. Shoichet, Virtual screening of chemical libraries, Nature 432 (2004) 862-865.
6. [6]
  [6] N. Huang, C. Kalyanaraman, K. Bernacki, M.P. Jacobson, Molecular mechanics methods for predicting protein-ligand binding, Phys. Chem. Chem. Phys. 8 (2006) 5166-5177.
7. [7]
  [7] R. Cao, M. Liu, M. Yin, et al., Discovery of novel tubulin inhibitors via structurebased hierarchical virtual screening, J. Chem. Inf. Model. 52 (2012) 2730-2740.
8. [8]
  [8] N. Huang, C. Kalyanaraman, J.J. Irwin, M.P. Jacobson, Physics-based scoring of protein-ligand complexes: enrichment of known inhibitors in large-scale virtual screening, J. Chem. Inf. Model. 46 (2006) 243-253.
9. [9]
  [9] M.G. Lerner, K.L. Meagher, H.A. Carlson, Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design, J. Comput. Aided Mol. Des. 22 (2008) 727-736.
10. [10]
  [10] D.M. Lorber, B.K. Shoichet, Hierarchical docking of databases of multiple ligand conformations, Curr. Top. Med. Chem. 5 (2005) 739-749.
11. [11]
  [11] L.A. Kelley, S.P. Gardner, M.J. Sutcliffe, An automated approach for clustering an ensemble of NMR-derived protein structures into conformationally related subfamilies, Protein Eng. 9 (1996) 1063-1065.
12. [12]
  [12] J.H. Hsieh, S. Yin, S. Liu, et al., Combined application of cheminformatics-and physical force field-based scoring functions improves binding affinity prediction for CSAR data sets, J. Chem. Inf. Model. 51 (2011) 2027-2035.
13. [13]
  [13] J.H. Hsieh, S. Yin, X.S. Wang, et al., Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force fieldbased hit scoring functions improves the accuracy of structure-based virtual screening, J. Chem. Inf. Model. 52 (2012) 16-28.
14. [14]
  [14] M.D. Eldridge, C.W. Murray, T.R. Auton, G.V. Paolini, R.P. Mee, Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes, J. Comput. Aided Mol. Des. 11 (1997) 425-445.
15. [15]
  [15] C.A. Sotriffer, P. Sanschagrin, H. Matter, G. Klebe, SFCscore: scoring functions for affinity prediction of protein-ligand complexes, Proteins 73 (2008) 395-419.
16. [16]
  [16] J.B. Dunbar Jr., R.D. Smith, C.Y. Yang, et al., CSAR benchmark exercise of 2010: selection of the protein-ligand complexes, J. Chem. Inf. Model. 51 (2011) 2036-2046.
17. [17]
  [17] N. Huang, B.K. Shoichet, J.J. Irwin, Benchmarking sets for molecular docking, J. Med. Chem. 49 (2006) 6789-6801.
18. [18]
  [18] J.J. Irwin, B.K. Shoichet, ZINC-a free database of commercially available compounds for virtual screening, J. Chem. Inf. Model. 45 (2005) 177-182.
19. [19]
  [19] C.S. Rapp, C. Schonbrun, M.P. Jacobson, C. Kalyanaraman, N. Huang, Automated site preparation in physics-based rescoring of receptor ligand complexes, Proteins 77 (2009) 52-61.
20. [20]
  [20] E.F. Pettersen, T.D.Goddard, C.C.Huang, et al.,UCSF Chimera-a visualizationsystem for exploratory research and analysis, J. Comput. Chem. 25 (2004) 1605-1612.
1. [1]
  Yi-Ru Bai , Qing-Chuan Duan , Dong-Jie Seng , Ying Xu , Hong-Bo Ren , Jie Zhang , Dan-Dan Shen , Li Yang , Hong-Min Liu , Shuo Yuan . A comprehensive review of small molecule drugs approved by the FDA in 2024: Advance and prospect. Chinese Chemical Letters, 2025, 36(10): 111025-. doi: 10.1016/j.cclet.2025.111025
2. [2]
  Zhi Zhou , Yu-E Lian , Yuqing Li , Hui Gao , Wei Yi . New Insights into the Molecular Mechanism Behind Clinical Tragedies of “Cephalosporin with Alcohol”. University Chemistry, 2025, 40(3): 42-51. doi: 10.12461/PKU.DXHX202403104
3. [3]
  Yutong Xiong , Ting Meng , Wendi Luo , Bin Tu , Shuai Wang , Qingdao Zeng . Molecular conformational effects on co-assembly systems of low-symmetric carboxylic acids investigated by scanning tunneling microscopy. Chinese Journal of Structural Chemistry, 2025, 44(2): 100511-100511. doi: 10.1016/j.cjsc.2025.100511
4. [4]
  Yuhao Jin , Zheng Zhou , Haixiang Han . Revisit the classical [Fe4S4(SR)4]2– molecular clusters: The steric effects of ligands and their structural transformations. Chinese Journal of Structural Chemistry, 2025, 44(9): 100660-100660. doi: 10.1016/j.cjsc.2025.100660
5. [5]
  Weiyu Chen , Zenghui Li , Chenguang Zhao , Lisha Zha , Junfeng Shi , Dan Yuan . Enzyme-modulate conformational changes in amphiphile peptide for selectively cell delivery. Chinese Chemical Letters, 2024, 35(12): 109628-. doi: 10.1016/j.cclet.2024.109628
6. [6]
  Yunzhe Zheng , Si Sun , Jiali Liu , Qingyu Zhao , Heng Zhang , Jing Zhang , Peng Zhou , Zhaokun Xiong , Chuan-Shu He , Bo Lai . Application of machine learning for material prediction and design in the environmental remediation. Chinese Chemical Letters, 2025, 36(9): 110722-. doi: 10.1016/j.cclet.2024.110722
7. [7]
  Qihou Li , Jiamin Liu , Fulu Chu , Jinwei Zhou , Jieshuangyang Chen , Zengqiang Guan , Xiyun Yang , Jie Lei , Feixiang Wu . Coordinating lithium polysulfides to inhibit intrinsic clustering behavior and facilitate sulfur redox conversion in lithium-sulfur batteries. Chinese Chemical Letters, 2025, 36(5): 110306-. doi: 10.1016/j.cclet.2024.110306
8. [8]
  Yanyan Yuan , Niu Zhang , Pangkuan Chen . An unprecedented supramolecular docking strategy enables rapid structure-determination of long alkyl-chain compounds. Chinese Journal of Structural Chemistry, 2025, 44(12): 100721-100721. doi: 10.1016/j.cjsc.2025.100721
9. [9]
  Run-Han Li , Tian-Yi Dang , Wei Guan , Jiang Liu , Ya-Qian Lan , Zhong-Min Su . Evolution exploration and structure prediction of Keggin-type group IVB metal-oxo clusters. Chinese Chemical Letters, 2024, 35(5): 108805-. doi: 10.1016/j.cclet.2023.108805
10. [10]
  Yao Zou , Difei Gong , Haiguang Yang , Hongmei Yu , Guorong He , Ningbo Gong , Lianhua Fang , Guanhua Du , Yang Lu . Prediction, screening, characterization, antioxidant and antihypoxic effects of multi-component zwitterionic cocrystals of dietary flavonoids with picolinic acid. Chinese Chemical Letters, 2025, 36(9): 110768-. doi: 10.1016/j.cclet.2024.110768
11. [11]
  Lu Li , Jianing Shen , Qinkun Xiao , Chaozheng He , Jinzhou Zheng , Chaoqin Chu , Chen Chen . Stable crystal structure prediction using machine learning-based formation energy and empirical potential function. Chinese Chemical Letters, 2025, 36(11): 110421-. doi: 10.1016/j.cclet.2024.110421
12. [12]
  Xing-Cheng Hu , Qiu-Shui Mu , Shu-Jin Bao , Yan Zou , Xin-Yu Wang , Guo-Xin Jin . Ligand conformational adaptability modulated self-assembly of Solomon links (412) and trefoil knots (31). Chinese Journal of Structural Chemistry, 2025, 44(10): 100712-100712. doi: 10.1016/j.cjsc.2025.100712
13. [13]
  Fang-Yuan Chen , Wen-Chao Geng , Kang Cai , Dong-Sheng Guo . Molecular recognition of cyclophanes in water. Chinese Chemical Letters, 2024, 35(5): 109161-. doi: 10.1016/j.cclet.2023.109161
14. [14]
  Yueyan Zhang , Zhihai Yang , Xia Suo , Ruicheng Wang , Xuewei Nie , Zafar Mahmood , Yanping Huo , Shi-Jian Su , Shaomin Ji . Tailoring luminescence properties of NIR-BODIPY emitters through donor engineering and intramolecular conformational locking for high-performance solution-processed OLEDs. Chinese Chemical Letters, 2025, 36(12): 111071-. doi: 10.1016/j.cclet.2025.111071
15. [15]
  Caihong Mao , Yanfeng He , Xiaohan Wang , Yan Cai , Xiaobo Hu . Synthesis and molecular recognition characteristics of a tetrapodal benzene cage. Chinese Chemical Letters, 2024, 35(8): 109362-. doi: 10.1016/j.cclet.2023.109362
16. [16]
  Cheng-Da Zhao , Huan Yao , Shi-Yao Li , Fangfang Du , Li-Li Wang , Liu-Pan Yang . Amide naphthotubes: Biomimetic macrocycles for selective molecular recognition. Chinese Chemical Letters, 2024, 35(4): 108879-. doi: 10.1016/j.cclet.2023.108879
17. [17]
  Yanwei Duan , Qing Yang . Molecular targets and their application examples for interrupting chitin biosynthesis. Chinese Chemical Letters, 2025, 36(4): 109905-. doi: 10.1016/j.cclet.2024.109905
18. [18]
  Yin-Hang Chai , Li-Long Dang . New structural breakthrough and topological transformation of homogeneous metalla[4]catenane compounds. Chinese Journal of Structural Chemistry, 2024, 43(10): 100322-100322. doi: 10.1016/j.cjsc.2024.100322
19. [19]
  Yinghui Xia , Yixi Lin , Zhenming Xu . Cation potential guiding structural regulation of lithium halide superionic conductors. Chinese Journal of Structural Chemistry, 2025, 44(3): 100448-100448. doi: 10.1016/j.cjsc.2024.100448
20. [20]
  Xiao-Qian Wan , Ya-Ning Xu , Jian-Xin Yang , Dan Tian , Li-Long Dang , Feng Bai , Lu-Fang Ma . Structural optimization of organometallic cages for enhanced photothermal solar water evaporation. Chinese Journal of Structural Chemistry, 2025, 44(10): 100705-100705. doi: 10.1016/j.cjsc.2025.100705

Get Citation

PDF

XML

Metrics

PDF Downloads(0)
Abstract views(1427)
HTML views(23)

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142