Prediction of ligand binding mode among multiple cross-docking poses by molecular dynamics simulations (original) (raw)

References

1. Renaud J-P, Chari A, Ciferri C, Liu W-t, Rémigy H-W, Stark H, Wiesmann C (2018) Cryo-EM in drug discovery: achievements, limitations and prospects. Nat Rev Drug Discov 17:471–492
   PubMed CAS Google Scholar
2. Merk A, Bartesaghi A, Banerjee S, Falconieri V, Rao P, Davis MI, Pragani R, Boxer MB, Earl LA, Milne JLS, Subramaniam S (2016) Breaking Cryo-EM resolution barriers to facilitate drug discovery. Cell 165:1698–1707
   PubMed PubMed Central CAS Google Scholar
3. Grosdidier S, Fernández-Recio J (2009) Docking and scoring: applications to drug discovery in the interactomics era. Expert Opin Drug Discov 4:673–686
   PubMed CAS Google Scholar
4. Kitchen DB, Decornez H, Furr JR, Bajorath J (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3:935–949
   PubMed CAS Google Scholar
5. Kontoyianni M (2017) Docking and virtual screening in drug discovery. In: Lazar IM, Kontoyianni M, Lazar AC (eds) Proteomics for drug discovery, vol 1647. Springer, New York, pp 255–266
   Google Scholar
6. Liu Z, Su M, Han L, Liu J, Yang Q, Li Y, Wang R (2017) Forging the basis for developing protein-ligand interaction scoring functions. Acc Chem Res 50:302–309
   PubMed CAS Google Scholar
7. Wang R, Fang X, Lu Y, Wang S (2004) The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures. J Med Chem 47:2977–2980
   PubMed CAS Google Scholar
8. Kellenberger E, Muller P, Schalon C, Bret G, Foata N, Rognan D (2006) sc-PDB: an annotated database of druggable binding sites from the Protein Data Bank. J Chem Inf Model 46:717–727
   PubMed CAS Google Scholar
9. Paul N, Kellenberger E, Bret G, Muller P, Rognan D (2004) Recovering the true targets of specific ligands by virtual screening of the protein data bank. Proteins 54:671–680
   PubMed CAS Google Scholar
10. Desaphy J, Bret G, Rognan D, Kellenberger E (2015) sc-PDB: a 3D-database of ligandable binding sites–10 years on. Nucleic Acids Res 43:D399–D404
    PubMed CAS Google Scholar
11. Li Y, Su M, Liu Z, Li J, Liu J, Han L, Wang R (2018) Assessing protein-ligand interaction scoring functions with the CASF-2013 benchmark. Nat Protoc 13:666–680
    PubMed CAS Google Scholar
12. Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med Chem 49:6789–6801
    PubMed PubMed Central CAS Google Scholar
13. Rosenfeld R, Vajda S, DeLisi C (1995) Flexible docking and design. Annu Rev Biophys Biomol Struct 24:677–700
    PubMed CAS Google Scholar
14. Krippahl L, Barahona P (2015) Protein docking with predicted constraints. Algorithms Mol Biol 10:9
    PubMed PubMed Central Google Scholar
15. Sherman W, Beard HS, Farid R (2006) Use of an induced fit receptor structure in virtual screening. Chem Biol Drug Des 67:83–84
    PubMed CAS Google Scholar
16. Wang Z, Sun H, Yao X, Li D, Xu L, Li Y, Tian S, Hou T (2016) Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power. Phys Chem Chem Phys 18:12964–12975
    PubMed CAS Google Scholar
17. Cheng T, Li X, Li Y, Liu Z, Wang R (2009) Comparative assessment of scoring functions on a diterse test set. J Chem Inf Model 49:1079–1093
    PubMed CAS Google Scholar
18. Pierce B, Weng Z (2007) ZRANK: reranking protein docking predictions with an optimized energy function. Proteins 67:1078–1086
    PubMed CAS Google Scholar
19. Wang E, Sun H, Wang J, Wang Z, Liu H, Zhang JZH, Hou T (2019) End-point binding free energy calculation with MM/PBSA and MM/GBSA: strategies and applications in drug design. Chem Rev 119:9478–9508
    PubMed CAS Google Scholar
20. Greenidge PA, Lewis RA, Ertl P (2016) Boosting pose ranking performance via rescoring with MM-GBSA. Chem Biol Drug Des 88:317–328
    PubMed CAS Google Scholar
21. Wichapong K, Rohe A, Platzer C, Slynko I, Erdmann F, Schmidt M, Sippl W (2014) Application of docking and QM/MM-GBSA rescoring to screen for novel Myt1 kinase inhibitors. J Chem Inf Model 54:881–893
    PubMed CAS Google Scholar
22. Greenidge PA, Kramer C, Mozziconacci JC, Sherman W (2014) Improving docking results via reranking of ensembles of ligand poses in multiple X-ray protein conformations with MM-GBSA. J Chem Inf Model 54:2697–2717
    PubMed CAS Google Scholar
23. Hou T, Wang J, Li Y, Wang W (2011) Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking. J Comput Chem 32:866–877
    PubMed CAS Google Scholar
24. Thompson DC, Humblet C, Joseph-McCarthy D (2008) Investigation of MM-PBSA rescoring of docking poses. J Chem Inf Model 48:1081–1091
    PubMed CAS Google Scholar
25. Zhang X, Wong SE, Lightstone FC (2014) Toward fully automated high performance computing drug discovery: a massively parallel virtual screening pipeline for docking and molecular mechanics/generalized Born surface area rescoring to improve enrichment. J Chem Inf Model 54:324–337
    PubMed CAS Google Scholar
26. Lu Y, Wang R, Yang CY, Wang S (2007) Analysis of ligand-bound water molecules in high-resolution crystal structures of protein-ligand complexes. J Chem Inf Model 47:668–675
    PubMed CAS Google Scholar
27. Genheden S, Nilsson I, Ryde U (2011) Binding affinities of factor Xa inhibitors estimated by thermodynamic integration and MM/GBSA. J Chem Inf Model 51:947–958
    PubMed CAS Google Scholar
28. Wang L, Wu Y, Deng Y, Kim B, Pierce L, Krilov G, Lupyan D, Robinson S, Dahlgren MK, Greenwood J, Romero DL, Masse C, Knight JL, Steinbrecher T, Beuming T, Damm W, Harder E, Sherman W, Brewer M, Wester R, Murcko M, Frye L, Farid R, Lin T, Mobley DL, Jorgensen WL, Berne BJ, Friesner RA, Abel R (2015) Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field. J Am Chem Soc 137:2695–2703
    PubMed CAS Google Scholar
29. Chipot C, Pohorille A (2007) Free energy calculations: theory and applications in chemistry and biology. Springer, Berlin
    Google Scholar
30. Williams-Noonan BJ, Yuriev E, Chalmers DK (2018) Free energy methods in drug design: prospects of “alchemical perturbation” in medicinal chemistry. J Med Chem 61:638–649
    PubMed CAS Google Scholar
31. Liu K, Watanabe E, Kokubo H (2017) Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations. J Comput Aided Mol Des 31:201–211
    PubMed CAS Google Scholar
32. Liu K, Kokubo H (2017) Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations: a cross-docking study. J Chem Inf Model 57:2514–2522
    PubMed CAS Google Scholar
33. Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749
    PubMed CAS Google Scholar
34. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF, Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery JA Jr, Peralta JE, Ogliaro F, Bearpark M, Heyd JJ, Brothers E, Kudin KN, Staroverov VN, Kobayashi R, Normand J, Raghavachari K, Rendell A, Burant JC, Iyengar SS, Tomasi J, Cossi M, Rega N, Millam JM, Klene M, Knox JE, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Martin RL, Morokuma K, Zakrzewski VG, Voth GA, Salvador P, Dannenberg JJ, Dapprich S, Daniels AD, Farkas Ö, Foresman JB, Ortiz JV, Cioslowski J, Fox DJ (2009) Gaussian 09 Revision C.01: Gaussian Inc., Wallingford
35. Genheden S, Ryde U (2015) The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin Drug Discov 10:449–461
    PubMed PubMed Central CAS Google Scholar
36. Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins 55:383–394
    PubMed CAS Google Scholar
37. Gallicchio E, Kubo MM, Levy RM (2000) Enthalpy–entropy and cavity decomposition of alkane hydration free energies: numerical results and implications for theories of hydrophobic solvation. J Phys Chem B 104:6271–6285
    CAS Google Scholar
38. Weis A, Katebzadeh K, Soderhjelm P, Nilsson I, Ryde U (2006) Ligand affinities predicted with the MM/PBSA method: dependence on the simulation method and the force field. J Med Chem 49:6596–6606
    PubMed CAS Google Scholar
39. Xu L, Sun H, Li Y, Wang J, Hou T (2013) Assessing the performance of MM/PBSA and MM/GBSA methods. 3. The impact of force fields and ligand charge models. J Phys Chem B 117:8408–8421
    PubMed CAS Google Scholar
40. Sun H, Li Y, Tian S, Xu L, Hou T (2014) Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set. Phys Chem Chem Phys 16:16719–16729
    PubMed CAS Google Scholar
41. Okamoto Y, Kokubo H, Tanaka T (2014) Prediction of ligand binding affinity by the combination of replica-exchange method and double-decoupling method. J Chem Theory Comput 10:3563–3569
    PubMed CAS Google Scholar
42. Deng N, Cui D, Zhang BW, Xia J, Cruz J, Levy R (2018) Comparing alchemical and physical pathway methods for computing the absolute binding free energy of charged ligands. Phys Chem Chem Phys 20:17081–17092
    PubMed PubMed Central CAS Google Scholar
43. Boresch S, Tettinger F, Leitgeb M, Karplus M (2003) Absolute binding free energies: a quantitative approach for their calculation. J Phys Chem B 107:9535–9551
    CAS Google Scholar
44. Liu K, Kokubo H (2019) Uncovering abnormal changes in logP after fluorination using molecular dynamics simulations. J Comput Aided Mol Des 33:345–356
    PubMed CAS Google Scholar
45. Yang W, Bitetti-Putzer R, Karplus M (2004) Free energy simulations: use of reverse cumulative averaging to determine the equilibrated region and the time required for convergence. J Chem Phys 120:2618–2628
    PubMed CAS Google Scholar
46. Homeyer N, Gohlke H (2013) FEW: A workflow tool for free energy calculations of ligand binding. J Comput Chem 34:965–973
    PubMed CAS Google Scholar
47. Hamelberg D, McCammon JA (2004) Standard Free Energy of Releasing a Localized Water Molecule from the Binding Pockets of Proteins: Double-Decoupling Method. J Am Chem Soc 126:7683–7689
    PubMed CAS Google Scholar
48. Kovalenko A, Hirata F (1999) Self-consistent description of a metal–water interface by the Kohn–Sham density functional theory and the three-dimensional reference interaction site model. J Chem Phys 110:10095
    CAS Google Scholar
49. Essex JW, Jorgensen WL (1995) An empirical boundary potential for water droplet simulations. J Comput Chem 16:951–972
    CAS Google Scholar
50. Woo H-J, Dinner AR, Roux B (2004) Grand canonical Monte Carlo simulations of water in protein environments. J Chem Phys 121:6392
    PubMed CAS Google Scholar
51. Young T, Abel R, Kim B, Berne BJ, Friesner RA (2007) Motifs for molecular recognition exploiting hydrophobic enclosure in protein–ligand binding. Proc Natl Acad Sci 104:808–813
    PubMed CAS Google Scholar
52. Wu P, Nielsen TE, Clausen MH (2016) Small-molecule kinase inhibitors: an analysis of FDA-approved drugs. Drug Discov Today 21:5–10
    PubMed CAS Google Scholar
53. Ghose AK, Herbertz T, Pippin DA, Salvino JM, Mallamo JP (2008) Knowledge based prediction of ligand binding modes and rational inhibitor design for kinase drug discovery. J Med Chem 51:5149–5171
    PubMed CAS Google Scholar
54. Song LF, Lee TS, Zhu C, York DM, Merz KM Jr (2019) Using AMBER18 for Relative Free Energy Calculations. J Chem Inf Model 59:3128–3135
    PubMed PubMed Central CAS Google Scholar

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