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Evaluation on performance of MM/PBSA in nucleic acid-protein systems |
| Yuan-Qiang Chen(陈远强)1, Yan-Jing Sheng(盛艳静)1, Hong-Ming Ding(丁泓铭)1,†, and Yu-Qiang Ma(马余强)2,‡ |
1 Center for Soft Condensed Matter Physics and Interdisciplinary Research, School of Physical Science and Technology, Soochow University, Suzhou 215006, China;
2 National Laboratory of Solid State Microstructures and Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China |
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Abstract The molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method has been widely used in predicting the binding affinity among ligands, proteins, and nucleic acids. However, the accuracy of the predicted binding energy by the standard MM/PBSA is not always good, especially in highly charged systems. In this work, we take the protein-nucleic acid complexes as an example, and showed that the use of screening electrostatic energy (instead of Coulomb electrostatic energy) in molecular mechanics can greatly improve the performance of MM/PBSA. In particular, the Pearson correlation coefficient of dataset II in the modified MM/PBSA (i.e., screening MM/PBSA) is about 0.52, much better than that (< 0.33) in the standard MM/PBSA. Further, we also evaluate the effect of solute dielectric constant and salt concentration on the performance of the screening MM/PBSA. The present study highlights the potential power of the screening MM/PBSA for predicting the binding energy in highly charged bio-systems.
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Received: 11 October 2021
Revised: 11 November 2021
Accepted manuscript online: 17 November 2021
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PACS:
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87.14.E-
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(Proteins)
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87.14.G-
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(Nucleic acids)
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87.15.A-
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(Theory, modeling, and computer simulation)
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87.15.kj
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(Protein-polynucleotide interactions)
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| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 11874045 and 11774147). |
Corresponding Authors:
Hong-Ming Ding, Yu-Qiang Ma
E-mail: dinghm@suda.edu.cn;myqiang@nju.edu.cn
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Cite this article:
Yuan-Qiang Chen(陈远强), Yan-Jing Sheng(盛艳静), Hong-Ming Ding(丁泓铭), and Yu-Qiang Ma(马余强) Evaluation on performance of MM/PBSA in nucleic acid-protein systems 2022 Chin. Phys. B 31 048701
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[1] Wang E, Sun H, Wang J, Wang Z, Liu H, Zhang J Z H and Hou T 2019 Chem. Rev. 119 9478
[2] Genheden S and Ryde U 2015 Expert. Opin. Drug. Dis. 10 449
[3] Wang C, Greene D, Xiao L, Qi R and Luo R 2018 Front. Mol. Biosci. 4 87
[4] Homeyer N and Gohlke H 2012 Mol. Inform. 31 114
[5] Williamsnoonan B J, Yuriev E and Chalmers D K 2017 J. Med. Chem. 61 638
[6] Chodera J D, Mobley D L, Shirts M R, Dixon R W, Branson K and Pande V S 2011 Curr. Opin. Struc. Biol. 21 150
[7] Pohorille A, Jarzynski C and Chipot C 2010 J. Phys. Chem. B 114 10235
[8] Pu C, Yan G, Shi J and Li R 2017 Med. Chem. Comm. 8 1452
[9] Sun H, Li Y, Shen M, Tian S, Xu L, Pan P, Guan Y and Hou T 2014 Phys. Chem. Chem. Phys. 16 22035
[10] Hou T, Wang J, Li Y and Wang W 2011 J. Comput. Chem. 32 866
[11] Ahinko M, Niinivehmas S, Jokinen E M and Pentikainen O T 2019 Chem. Biol. Drug. Des. 93 522
[12] Hou T, Wang J, Li Y and Wang W 2011 J. Chem. Inf. Model. 51 69
[13] Liu J, He X and Zhang J Z H 2013 J. Chem. Inf. Model. 53 1306
[14] Wang E, Liu H, Wang J, Weng G, Sun H, Wang Z, Kang Y and Hou T 2020 J. Chem. Inf. Model. 60 5353
[15] Mikulskis P, Genheden S and Ryde U 2014 J. Chem. Inf. Model. 54 2794
[16] Greenidge P, Kramer C, Mozziconacci J and Wolf R M 2013 J. Chem. Inf. Model. 53 201
[17] Wang E, Weng G, Sun H, Du H, Zhu F, Chen F, Wang Z and Hou T 2019 Phys. Chem. Chem. Phys. 21 18958
[18] Maffucci I and Contini A 2016 J. Chem. Inf. Model. 56 1692
[19] Liu X, Peng L and Zhang J Z H 2019 J. Chem. Inf. Model. 59 272
[20] Sun Z, Yan Y N, Yang M and Zhang J Z H 2017 J. Chem. Phys. 146 124124
[21] Chen F, Sun H, Wang J, Zhu F, Liu H, Wang Z, Lei T, Li Y and Hou T 2018 RNA 24 1183
[22] Sun H, Li Y, Tian S, Xu L and Hou T 2014 Phys. Chem. Chem. Phys. 16 16719
[23] Ravindranathan K P, Tiradorives J, Jorgensen W L and Guimaraes C R W 2011 J. Chem. Theory Comput. 7 3859
[24] Li Y, Cong Y, Feng G, Zhong S, Zhang J Z H, Sun H and Duan L 2018 Struct. Dynam. 5 064101
[25] Sheng Y J, Yin Y W, Ma Y Q and Ding H M 2021 J. Chem. Inf. Model. 61 2454
[26] Ding H M, Yin Y W, Ni S D, Sheng Y J and Ma Y Q 2021 Chin. Phys. Lett. 38 018701
[27] Manning G S 1969 J. Chem. Phys. 51 924
[28] Liljas A, Liljas L, Piskur J, Linblom G, Nissen P and Kjeldgaard M 2009 Textbook of Structural Biology (Singapore:World Scientific Publishing)
[29] Ding H, Li J, Chen N, Hu X, Yang X, Guo L, Li Q, Zuo X, Wang L and Ma Y 2018 ACS Central. Sci. 4 1344
[30] Douglas S M, Dietz H, Liedl T, Hogberg B, Graf F and Shih W M 2009 Nature 459 414
[31] Hu Q, Li H, Wang L, Gu H and Fan C 2018 Chem. Rev. 119 6459
[32] Orphanides G and Reinberg D 2002 Cell 108 439
[33] Liu Z, Su M, Han L, Liu J, Yang Q, Li Y and Wang R 2017 Acc. Chem. Res. 50 302
[34] Wang R, Fang X, Lu Y and Wang S 2004 J. Med. Chem. 47 2977
[35] Jorgensen W L and Madura J D 1983 J. Am. Chem. Soc. 105 1407
[36] Der Spoel D V, Lindahl E, Hess B, Groenhof G, Mark A E and Berendsen H J C 2005 J. Comput. Chem. 26 1701
[37] Abraham M J, Murtola T, Schulz R, Pall S, Smith J C, Hess B and Lindahl E 2015 SoftwareX 1-2 19
[38] Maier J, Martinez C, Kasavajhala K, Wickstrom L, Hauser K and Simmerling C 2015 J. Chem. Theory Comput. 11 3696
[39] Hess B, Bekker H, Berendsen H J C and Fraaije J G E M 1997 J. Comput. Chem. 18 1463
[40] Essmann U, Perera L, Berkowitz M L, Darden T, Lee H and Pedersen L G 1995 J. Chem. Phys. 103 8577
[41] Bussi G, Donadio D and Parrinello M 2007 J. Chem. Phys. 126 014101
[42] Parrinello M and Rahman A 1981 J. Appl. Phys. 52 7182
[43] https://jerkwin.github.io/gmxtool |
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