| INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
Prev
Next
|
|
|
Exploring unbinding mechanism of drugs from SERT via molecular dynamics simulation and its implication in antidepressants |
| Xin-Guan Tan(谭新官)1, Xue-Feng Liu(刘雪峰)1,†, Ming-Hui Pang(庞铭慧)1, Yu-Qing Wang(王雨晴)1, and Yun-Jie Zhao(赵蕴杰)2,‡ |
1. College of Mathematics and Physics, Chengdu University of Technology, Chengdu 610059, China;
2. Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan 430079, China |
|
|
|
|
Abstract The human serotonin transporter (SERT) terminates neurotransmission by removing serotonin from the synaptic cleft, which is an essential process that plays an important role in depression. In addition to natural substrate serotonin, SERT is also the target of the abused drug cocaine and, clinically used antidepressants, escitalopram, and paroxetine. To date, few studies have attempted to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of SERT. In this article, the conserved property of the orthosteric and allosteric sites (S1 and S2) of SERT was revealed by combining the high resolutions of x-ray crystal structures and molecular dynamics (MD) simulations. The residues Tyr95 and Ser438 located within the S1 site, and Arg104 located within the S2 site in SERT illustrate conserved interactions (hydrogen bonds and hydrophobic interactions), as responses to selective serotonin reuptake inhibitors. Van der Waals interactions were keys to designing effective drugs inhibiting SERT and further, electrostatic interactions highlighted escitalopram as a potent antidepressant. We found that cocaine, escitalopram, and paroxetine, whether the S1 site or the S2 site, were more competitive. According to this potential of mean force (PMF) simulations, the new insights reveal the principles of competitive inhibitors that lengths of trails from central SERT to an opening were ～ 18 Å for serotonin and ～ 22 Å for the above-mentioned three drugs. Furthermore, the distance between the natural substrate serotonin and cocaine (or escitalopram) at the allosteric site was ～ 3 Å. Thus, it can be inferred that the potent antidepressants tended to bind at deeper positions of the S1 or the S2 site of SERT in comparison to the substrate. Continuing exploring the processes of unbinding four ligands against the two target pockets of SERT, this study observed a broad pathway in which serotonin, cocaine, escitalopram (at the S1 site), and paroxetine all were pulled out to an opening between MT1b and MT6a, which may be helpful to understand the dissociation mechanism of antidepressants.
|
Received: 27 February 2023
Revised: 17 April 2023
Accepted manuscript online: 18 May 2023
|
|
PACS:
|
87.14.ep
|
(Membrane proteins)
|
| |
87.15.A-
|
(Theory, modeling, and computer simulation)
|
| |
87.15.Cc
|
(Folding: thermodynamics, statistical mechanics, models, and pathways)
|
| |
87.15.K
|
|
|
| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos.11904036 and 12175081) and Fundamental Research Funds for the Central Universities (Grant No.CCNU22QNOO4). |
Corresponding Authors:
Xue-Feng Liu, Yun-Jie Zhao
E-mail: liuxuefeng17@cdut.edu.cn;yjzhaowh@mail.ccnu.edu.cn
|
Cite this article:
Xin-Guan Tan(谭新官), Xue-Feng Liu(刘雪峰), Ming-Hui Pang(庞铭慧), Yu-Qing Wang(王雨晴), and Yun-Jie Zhao(赵蕴杰) Exploring unbinding mechanism of drugs from SERT via molecular dynamics simulation and its implication in antidepressants 2023 Chin. Phys. B 32 088702
|
[1] Sepanlou S G, Safiri S, Bisignano C, Ikuta K S, Merat S, Saberifiroozi M, Poustchi H, Tsoi D, Colombara D V and Abdoli A 2020 Lancet Gastroenterol. Hepatol. 5 17
[2] Coccaro E F 2019 N. Engl. J. Med. 381 980
[3] Recourt K, de Boer P, Zuiker R, Luthringer R, Kent J, van der Ark P, Van Hove I, van Gerven J, Jacobs G and van Nueten L 2019 Transl. Psychiatry 9 110
[4] Saltiel P F and Silvershein D I 2015 Neuropsychiatr. Dis. Treat. 11 875
[5] Krishnan V and Nestler E J 2008 Nature 455 894
[6] Kupfer D J, Frank E and Phillips M L 2012 Lancet 379 1045
[7] Caspi A, Sugden K, Moffitt T E, Taylor A, Craig I W, Harrington H, McClay J, Mill J, Martin J and Braithwaite A 2003 Science 301 386
[8] Fuller R W and Wong D T 1990 Ann. N. Y. Acad. Sci. 600 68
[9] Murphy D L, Lerner A, Rudnick G and Lesch K P 2004 Mol. Interv. 4 109
[10] Chen N H, Reith M E A and Quick M W 2004 Pflügers Archiv 447 519
[11] Sitte H H and Freissmuth M 2015 Trends Pharmacol. Sci. 36 41
[12] Niello M, Gradisch R, Loland C J, Stockner T and Sitte H H 2020 Trends Pharmacol. Sci. 41 446
[13] Rothman R B, Partilla J S, Baumann M H, Lightfoot-Siordia C and Blough B E 2012 J. Pharmacol. Exp. Ther. 341 251
[14] Hasenhuetl P S, Bhat S, Freissmuth M and Sandtner W 2019 Mol. Pharmacol. 95 303
[15] Xue W, Fu T, Deng S, Yang F, Yang J and Zhu F 2022 ACS Chem. Neurosci. 13 340
[16] Yang D and Gouaux E 2021 Science Advances 7
[17] Chan M C, Selvam B, Young H J, Procko E and Shukla D 2022 Biophys. J. 121 715
[18] Gether U, Andersen P H, Larsson O M and Schousboe A 2006 Trends Pharmacol. Sci. 27 375
[19] Kristensen A S, Andersen J, Jorgensen T N, Sorensen L, Eriksen J, Loland C J, Stromgaard K and Gether U 2011 Pharmacol. Rev. 63 585
[20] Hahn M and Blakely R 2002 Pharmacogenomics J. 2 217
[21] Severinsen K, Koldso H, Thorup K A V, Schjoth-Eskesen C, Moller P T, Wiborg O, Jensen H H, Sinning S and Schiott B 2014 Mol. Pharmacol. 85 208
[22] Henry L K, Field J R, Adkins E M, Parnas M L, Vaughan R A, Zou M F, Newman A H and Blakely R D 2006 J. Biol. Chem. 281 2012
[23] Andersen J, Taboureau O, Hansen K B, Olsen L, Egebjerg J, Stromgaard K and Kristensen A S 2009 J. Biol. Chem. 284 10276
[24] Coleman J A and Gouaux E 2018 Nat. Struct. Mol. Biol. 25 170
[25] Gradisch R, Szöllösi D, Niello M, Lazzarin E, Sitte H H and Stockner T 2022 J. Biol. Chem. 298
[26] Yamashita A, Singh S K, Kawate T, Jin Y and Gouaux E 2005 Nature 437 215
[27] Coleman J A, Green E M and Gouaux E 2016 Nature 532 334
[28] Zhu R, Sinwel D, Hasenhuetl P S, Saha K, Kumar V, Zhang P, Rankl C, Holy M, Sucic S and Kudlacek O 2016 Angew. Chem. 128 1751
[29] Jorgensen A M and Topiol S 2008 Chem. Biol. Drug Des. 72 265
[30] Topiol S, Bang-Andersen B, Sanchez C and Bogeso K P 2016 Bioorg. Med. Chem. Lett. 26 5058
[31] Zhang Y, Zheng G, Fu T, Hong J, Li F, Yao X, Xue W and Zhu F 2020 Phys. Chem. Chem. Phys. 22 5132
[32] Millan M J 2009 Neurotherapeutics 6 53
[33] Stuivenga M, Giltay E J, Cools O, Roosens L, Neels H and Sabbe B 2019 Expert Opin. Pharmacother. 20 251
[34] Crits-Christoph P, Siqueland L, Blaine J, Frank A, Luborsky L, Onken L S, Muenz L R, Thase M E, Weiss R D and Gastfriend D R 1999 Arch. Gen. Psychiatry 56 493
[35] Lambert N M, McLeod M and Schenk S 2006 Addiction 101 713
[36] Larsen M A B, Plenge P, Andersen J, Eildal J N, Kristensen A S, Bogeso K P, Gether U, Stromgaard K, Bang-Andersen B and Loland C J 2016 Br. J. Pharmacol. 173 925
[37] Polovinkin L, Hassaine G, Perot J, Neumann E, Jensen A A, Lefebvre S N, Corringer P J, Neyton J, Chipot C and Dehez F 2018 Nature 563 275
[38] Pozharski E, Moulin A, Hewagama A, Shanafelt A B, Petsko G A and Ringe D 2005 J. Mol. Biol. 349 570
[39] Vilar S, Cozza G and Moro S 2008 Curr. Top. Med. Chem. 8 1555
[40] Pearlman D A, Case D A, Caldwell J W, Ross W S, Cheatham III T E, DeBolt S, Ferguson D, Seibel G and Kollman P 1995 Comput. Phys. Commun. 91 1
[41] Case D A, Cheatham III T E, Darden T, Gohlke H, Luo R, Merz Jr K M, Onufriev A, Simmerling C, Wang B and Woods R J 2005 J. Comput. Chem. 26 1668
[42] Frank M, Gutbrod P, Hassayoun C and von Der Lieth C-W 2003 J. Mol. Model. 9 308
[43] Karplus M 2003 Biopolymers 68 350
[44] Adcock S A and McCammon J A 2006 Chem. Rev. 106 1589
[45] Maier J A, Martinez C, Kasavajhala K, Wickstrom L, Hauser K E and Simmerling C 2015 J. Chem. Theory Comput. 11 3696
[46] Dickson C J, Madej B D, Skjevik Å A, Betz R M, Teigen K, Gould I R and Walker R C 2014 J. Chem. Theory Comput. 10 865
[47] He X, Man V H, Yang W, Lee T S and Wang J 2020 J. Chem. Phys. 153 114502
[48] Lu T and Chen F 2012 J. Comput. Chem. 33 580
[49] Frisch M, Trucks G, Schlegel H, Scuseria G, Robb M, Cheeseman J, Scalmani G, Barone V, Mennucci B and Petersson G 2009 Gaussian Inc, Wallingford
[50] Zhang J and Lu T 2021 Phys. Chem. Chem. Phys. 23 20323
[51] Morishita T 2000 J. Chem. Phys. 113 2976
[52] Toukmaji A, Sagui C, Board J and Darden T 2000 J. Chem. Phys. 113 10913
[53] Ryckaert J-P, Ciccotti G and Berendsen H J 1977 J. Comput. Phys. 23 327
[54] Berendsen H J, Postma J v, Van Gunsteren W F, DiNola A and Haak J R 1984 J. Chem. Phys. 81 3684
[55] Kollman P A, Massova I, Reyes C, Kuhn B, Huo S, Chong L, Lee M, Lee T, Duan Y and Wang W 2000 Acc. Chem. Res. 33 889
[56] Fu T, Zheng G, Tu G, Yang F, Chen Y, Yao X, Li X, Xue W and Zhu F 2018 ACS Chem. Neurosci. 9 1492
[57] Xue W, Wang P, Li B, Li Y, Xu X, Yang F, Yao X, Chen Y Z, Xu F and Zhu F 2016 Phys. Chem. Chem. Phys. 18 3260
[58] Xue W, Wang P, Tu G, Yang F, Zheng G, Li X, Li X, Chen Y, Yao X and Zhu F 2018 Phys. Chem. Chem. Phys. 20 6606
[59] Zheng G, Xue W, Wang P, Yang F, Li B, Li X, Li Y, Yao X and Zhu F 2016 Sci. Rep. 6 26883
[60] Wang P, Fu T, Zhang X, Yang F, Zheng G, Xue W, Chen Y, Yao X and Zhu F 2017 Biochim. Biophys. Acta 1861
[61] Torrie G M and Valleau J P 1977 J. Comput. Phys. 23 187
[62] Kirkwood J G 1935 J. Chem. Phys. 3 300
[63] Berneche S and Roux B 2001 Nature 414 73
[64] Roux B 1995 Comput. Phys. Commun. 91 275
[65] García A E and Sanbonmatsu K Y 2002 Proc. Natl. Acad. Sci. 99 2782
[66] Pace C N, Fu H, Fryar K L, Landua J, Trevino S R, Shirley B A, Hendricks M M, Iimura S, Gajiwala K and Scholtz J M 2011 J. Mol. Biol. 408 514
[67] Ning S, Zeng C, Zeng C and Zhao Y 2021 Biophys. J. 120 5158
[68] Wang H, Song L, Zhou T, Zeng C, Jia Y and Zhao Y 2020 Phys. Chem. Chem. Phys. 22 25474
[69] Wallace A C, Laskowski R A and Thornton J M 1995 Protein Eng. Des. Sel. 8 127
[70] Sarkadi B and Szakács G 2010 Nat. Rev. Drug Discovery 9 897
[71] Huang X, Zhao X, Zheng F and Zhan C G 2012 J. Phys. Chem. B 116 3361
[72] Wang K H, Penmatsa A and Gouaux E 2015 Nature 521 322
[73] Coleman J A, Yang D, Zhao Z, Wen P C, Yoshioka C, Tajkhorshid E and Gouaux E 2019 Nature 569 141
[74] Singh S K, Piscitelli C L, Yamashita A and Gouaux E 2008 Science 322 1655
[75] Krishnamurthy H and Gouaux E 2012 Nature 481 469 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|
