Login Register Cart 0
Generic placeholder image

Current Computer-Aided Drug Design

Editor-in-Chief

ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Identification of Potential Inhibitors of PDE5 based on Structure-based Virtual Screening Approaches

Author(s): Lei Xu*, Lilei Sun, Peng Su, Teng Ma, Yingcong Yu, Haibin Liu* and Xianfeng Huang*

Volume 19, Issue 3, 2023

Published on: 06 January, 2023

Page: [234 - 242] Pages: 9

DOI: 10.2174/1573409919666221208143327

Price: $65

conference banner
Abstract

Background: Phosphodiesterase type 5 (PDE5), exclusively specific for cyclic guanidine monophosphate (cGMP), a potential target for the therapy of various diseases, and PDE5 inhibitors could be used as a treatment for erectile dysfunction (ED) or chronic pulmonary hypertension.

Objective: In the present study, we carried out an integrated computer-aided virtual screening technique against the natural products in the ZINC database to discover potential inhibitors of PDE5.

Methods: Pharmacophore, molecular docking and ADMET (Absorption, distribution, metabolism, excretion and toxicity) properties filtration were used to select the PDE5 inhibitors with the best binding affinities and drug-like properties. The binding modes of PDE5 inhibitors were investigated, and these complexes' stabilities were explored by molecular dynamic simulations and MM/GBSA free energy calculations.

Results: Two natural compounds (Z171 and Z283) were identified and may be used as a critical starting point for the development of novel PDE5 inhibitors. The MM/GBSA free energy decomposition analysis quantitatively analyzed the importance of hydrophobic interaction in PDE5- ligands binding.

Conclusion: In this study, we identified two novel natural compounds from the ZINC database to effectively inhibit PDE5 through virtual screening. The novel scaffolds of these compounds can be used as the starting templates in the drug design of PDE5 inhibitors with good pharmacokinetic profiles. These results may promote the de novo design of new compounds against PDE5.

Keywords: PDE5 inhibitors, natural compounds, pharmacophore model, virtual screening, molecular docking, molecular dynamics simulation.

« Previous
Graphical Abstract

[1]
Salter, E.A.; Wierzbicki, A. The mechanism of cyclic nucleotide hydrolysis in the phosphodiesterase catalytic site. J. Phys. Chem. B, 2007, 111(17), 4547-4552.
[http://dx.doi.org/10.1021/jp066582+] [PMID: 17425352]
[2]
Maurice, D.H.; Ke, H.; Ahmad, F.; Wang, Y.; Chung, J.; Manganiello, V.C. Advances in targeting cyclic nucleotide phosphodiesterases. Nat. Rev. Drug Discov., 2014, 13(4), 290-314.
[http://dx.doi.org/10.1038/nrd4228] [PMID: 24687066]
[3]
Conti, M.; Beavo, J. Biochemistry and physiology of cyclic nucleotide phosphodiesterases: essential components in cyclic nucleotide signaling. Annu. Rev. Biochem., 2007, 76(1), 481-511.
[http://dx.doi.org/10.1146/annurev.biochem.76.060305.150444] [PMID: 17376027]
[4]
Omori, K.; Kotera, J. Overview of PDEs and their regulation. Circ. Res., 2007, 100(3), 309-327.
[http://dx.doi.org/10.1161/01.RES.0000256354.95791.f1] [PMID: 17307970]
[5]
Rotella, D.P. Phosphodiesterase 5 inhibitors: Current status and potential applications. Nat. Rev. Drug Discov., 2002, 1(9), 674-682.
[http://dx.doi.org/10.1038/nrd893] [PMID: 12209148]
[6]
Corbin, J.D.; Francis, S.H. Cyclic GMP phosphodiesterase-5: Target of sildenafil. J. Biol. Chem., 1999, 274(20), 13729-13732.
[http://dx.doi.org/10.1074/jbc.274.20.13729] [PMID: 10318772]
[7]
Yoo, H.; Kim, N.; Im, G.; Kim, D. Pharmacokinetics and tissue distribution of a novel PDE5 inhibitor, SK-3530, in rats. Acta Pharmacol. Sin., 2007, 28(8), 1247-1253.
[http://dx.doi.org/10.1111/j.1745-7254.2007.00611.x] [PMID: 17640490]
[8]
Weeks, J.L., II; Zoraghi, R.; Beasley, A.; Sekhar, K.R.; Francis, S.H.; Corbin, J.D. High biochemical selectivity of tadalafil, sildenafil and vardenafil for human phosphodiesterase 5A1 (PDE5) over PDE11A4 suggests the absence of PDE11A4 cross-reaction in patients. Int. J. Impot. Res., 2005, 17(1), 5-9.
[http://dx.doi.org/10.1038/sj.ijir.3901283] [PMID: 15538396]
[9]
Bruzziches, R.; Francomano, D.; Gareri, P.; Lenzi, A.; Aversa, A. An update on pharmacological treatment of erectile dysfunction with phosphodiesterase type 5 inhibitors. Expert Opin. Pharmacother., 2013, 14(10), 1333-1344.
[http://dx.doi.org/10.1517/14656566.2013.799665] [PMID: 23675780]
[10]
García-Osta, A.; Cuadrado-Tejedor, M.; García-Barroso, C.; Oyarzábal, J.; Franco, R. Phosphodiesterases as therapeutic targets for Alzheimer’s disease. ACS Chem. Neurosci., 2012, 3(11), 832-844.
[http://dx.doi.org/10.1021/cn3000907] [PMID: 23173065]
[11]
Ugarte, A.; Gil-Bea, F.; García-Barroso, C.; Cedazo-Minguez, Á.; Ramírez, M.J.; Franco, R.; García-Osta, A.; Oyarzabal, J.; Cuadrado-Tejedor, M. Decreased levels of guanosine 3′, 5′-monophosphate (cGMP) in cerebrospinal fluid (CSF) are associated with cognitive de-cline and amyloid pathology in Alzheimer’s disease. Neuropathol. Appl. Neurobiol., 2015, 41(4), 471-482.
[http://dx.doi.org/10.1111/nan.12203] [PMID: 25488891]
[12]
Cuadrado-Tejedor, M.; Hervias, I.; Ricobaraza, A.; Puerta, E.; Pérez-Roldán, J.M.; García-Barroso, C.; Franco, R.; Aguirre, N.; García-Osta, A. Sildenafil restores cognitive function without affecting β-amyloid burden in a mouse model of Alzheimer’s disease. Br. J. Pharmacol., 2011, 164(8), 2029-2041.
[http://dx.doi.org/10.1111/j.1476-5381.2011.01517.x] [PMID: 21627640]
[13]
García-Barroso, C.; Ricobaraza, A.; Pascual-Lucas, M.; Unceta, N.; Rico, A.J.; Goicolea, M.A.; Sallés, J.; Lanciego, J.L.; Oyarzabal, J.; Franco, R.; Cuadrado-Tejedor, M.; García-Osta, A. Tadalafil crosses the blood–brain barrier and reverses cognitive dysfunction in a mouse model of AD. Neuropharmacology, 2013, 64, 114-123.
[http://dx.doi.org/10.1016/j.neuropharm.2012.06.052] [PMID: 22776546]
[14]
Pissarnitski, D. Phosphodiesterase 5 (PDE 5) inhibitors for the treatment of male erectile disorder: Attaining selectivity versus PDE6. Med. Res. Rev., 2006, 26(3), 369-395.
[http://dx.doi.org/10.1002/med.20053] [PMID: 16388517]
[15]
Wespes, E.; Amar, E.; Hatzichristou, D.; Hatzimouratidis, K.; Montorsi, F.; Pryor, J.; Vardi, Y. EAU Guidelines on erectile dysfunction: an update. Eur. Urol., 2006, 49(5), 806-815.
[http://dx.doi.org/10.1016/j.eururo.2006.01.028] [PMID: 16530932]
[16]
Chung, E.; Brock, G.B. Emerging and novel therapeutic approaches in the treatment of male erectile dysfunction. Curr. Urol. Rep., 2011, 12(6), 432-443.
[http://dx.doi.org/10.1007/s11934-011-0216-y] [PMID: 21922167]
[17]
Drewes, S.E.; George, J.; Khan, F. Recent findings on natural products with erectile-dysfunction activity. Phytochemistry, 2003, 62(7), 1019-1025.
[http://dx.doi.org/10.1016/S0031-9422(02)00621-0] [PMID: 12591255]
[18]
Li, J.W.H.; Vederas, J.C. Drug discovery and natural products: end of an era or an endless frontier? Science, 2009, 325(5937), 161-165.
[http://dx.doi.org/10.1126/science.1168243] [PMID: 19589993]
[19]
Rodríguez-Ramos, F.; Navarrete, A.; González-Andrade, M.; Alarcón, C.; Aguilera-Cruz, A.; Reyes-Ramírez, A. Synthesis, docking study and relaxant effect of 2-alkyl and 2-naphthylchromones on rat aorta and guinea-pig trachea through phosphodiesterase inhibition. Bioorg. Chem., 2013, 50, 17-25.
[http://dx.doi.org/10.1016/j.bioorg.2013.07.001] [PMID: 23933402]
[20]
Ojewole, J.A.O.; Drewes, S.E.; Khan, F. Vasodilatory and hypoglycaemic effects of two pyrano-isoflavone extractives from Eriosema kraussianum N. E. Br. [Fabaceae] rootstock in experimental rat models. Phytochemistry, 2006, 67(6), 610-617.
[http://dx.doi.org/10.1016/j.phytochem.2005.11.019] [PMID: 16434072]
[21]
Ribaudo, G.; Pagano, M.A.; Pavan, V.; Redaelli, M.; Zorzan, M.; Pezzani, R.; Mucignat-Caretta, C.; Vendrame, T.; Bova, S.; Zagotto, G. Semi-synthetic derivatives of natural isoflavones from Maclura pomifera as a novel class of PDE-5A inhibitors. Fitoterapia, 2015, 105, 132-138.
[http://dx.doi.org/10.1016/j.fitote.2015.06.020] [PMID: 26136059]
[22]
Irwin, J.J.; Sterling, T.; Mysinger, M.M.; Bolstad, E.S.; Coleman, R.G. ZINC: A free tool to discover chemistry for biology. J. Chem. Inf. Model., 2012, 52(7), 1757-1768.
[http://dx.doi.org/10.1021/ci3001277] [PMID: 22587354]
[23]
Card, G.L.; England, B.P.; Suzuki, Y.; Fong, D.; Powell, B.; Lee, B.; Luu, C.; Tabrizizad, M.; Gillette, S.; Ibrahim, P.N.; Artis, D.R.; Bollag, G.; Milburn, M.V.; Kim, S.H.; Schlessinger, J.; Zhang, K.Y.J. Structural basis for the activity of drugs that inhibit phosphodiesterases. Structure, 2004, 12(12), 2233-2247.
[http://dx.doi.org/10.1016/j.str.2004.10.004] [PMID: 15576036]
[24]
Brooks, B.R.; Brooks, C.L., III; Mackerell, A.D., Jr; Nilsson, L.; Petrella, R.J.; Roux, B.; Won, Y.; Archontis, G.; Bartels, C.; Boresch, S.; Caflisch, A.; Caves, L.; Cui, Q.; Dinner, A.R.; Feig, M.; Fischer, S.; Gao, J.; Hodoscek, M.; Im, W.; Kuczera, K.; Lazaridis, T.; Ma, J.; Ovchinnikov, V.; Paci, E.; Pastor, R.W.; Post, C.B.; Pu, J.Z.; Schaefer, M.; Tidor, B.; Venable, R.M.; Woodcock, H.L.; Wu, X.; Yang, W.; York, D.M.; Karplus, M. CHARMM: The biomolecular simulation program. J. Comput. Chem., 2009, 30(10), 1545-1614.
[http://dx.doi.org/10.1002/jcc.21287] [PMID: 19444816]
[25]
Feng, Z.; Hou, T.; Li, Y. Concerted movement in pH-dependent gating of FocA from molecular dynamics simulations. J. Chem. Inf. Model., 2012, 52(8), 2119-2131.
[http://dx.doi.org/10.1021/ci300250q] [PMID: 22747061]
[26]
Feng, Z.; Hou, T.; Li, Y. Studies on the interactions between β2 adrenergic receptor and Gs protein by molecular dynamics simulations. J. Chem. Inf. Model., 2012, 52(4), 1005-1014.
[http://dx.doi.org/10.1021/ci200594d] [PMID: 22404225]
[27]
Feng, Z.; Alqarni, M.H.; Yang, P.; Tong, Q.; Chowdhury, A.; Wang, L.; Xie, X.Q. Modeling, molecular dynamics simulation, and mutation validation for structure of cannabinoid receptor 2 based on known crystal structures of GPCRs. J. Chem. Inf. Model., 2014, 54(9), 2483-2499.
[http://dx.doi.org/10.1021/ci5002718] [PMID: 25141027]
[28]
Wang, J.; Wolf, R.M.; Caldwell, J.W.; Kollman, P.A.; Case, D.A. Development and testing of a general amber force field. J. Comput. Chem., 2004, 25(9), 1157-1174.
[http://dx.doi.org/10.1002/jcc.20035] [PMID: 15116359]
[29]
Maier, J.A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K.E.; Simmerling, C. ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. J. Chem. Theory Comput., 2015, 11(8), 3696-3713.
[http://dx.doi.org/10.1021/acs.jctc.5b00255] [PMID: 26574453]
[30]
Peters, M.B.; Yang, Y.; Wang, B.; Füsti-Molnár, L.; Weaver, M.N.; Merz, K.M. Jr Structural survey of zinc containing proteins and the development of the zinc AMBER force field (ZAFF). J. Chem. Theory Comput., 2010, 6(9), 2935-2947.
[http://dx.doi.org/10.1021/ct1002626] [PMID: 20856692]
[31]
Sun, H.; Li, Y.; Li, D.; Hou, T. Insight into crizotinib resistance mechanisms caused by three mutations in ALK tyrosine kinase using free energy calculation approaches. J. Chem. Inf. Model., 2013, 53(9), 2376-2389.
[http://dx.doi.org/10.1021/ci400188q] [PMID: 23952683]
[32]
Li, L.; Li, Y.; Zhang, L.; Hou, T. Theoretical studies on the susceptibility of oseltamivir against variants of 2009 A/H1N1 influenza neuraminidase. J. Chem. Inf. Model., 2012, 52(10), 2715-2729.
[http://dx.doi.org/10.1021/ci300375k] [PMID: 22998323]
[33]
Xu, L.; Zhang, Y.; Zheng, L.; Qiao, C.; Li, Y.; Li, D.; Zhen, X.; Hou, T. Discovery of novel inhibitors targeting the macrophage migration inhibitory factor via structure-based virtual screening and bioassays. J. Med. Chem., 2014, 57(9), 3737-3745.
[http://dx.doi.org/10.1021/jm401908w] [PMID: 24712915]
[34]
Pan, P.; Li, L.; Li, Y.; Li, D.; Hou, T. Insights into susceptibility of antiviral drugs against the E119G mutant of 2009 influenza A (H1N1) neuraminidase by molecular dynamics simulations and free energy calculations. Antiviral Res., 2013, 100(2), 356-364.
[http://dx.doi.org/10.1016/j.antiviral.2013.09.006] [PMID: 24055835]
[35]
Sun, H.; Li, Y.; Tian, S.; Xu, L.; Hou, T. 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., 2014, 16(31), 16719-16729.
[http://dx.doi.org/10.1039/C4CP01388C] [PMID: 24999761]
[36]
Sun, H.; Li, Y.; Shen, M.; Tian, S.; Xu, L.; Pan, P.; Guan, Y.; Hou, T. Assessing the performance of MM/PBSA and MM/GBSA methods. 5. improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring. Phys. Chem. Chem. Phys., 2014, 16(40), 22035-22045.
[http://dx.doi.org/10.1039/C4CP03179B] [PMID: 25205360]
[37]
Chen, F.; Liu, H.; Sun, H.; Pan, P.; Li, Y.; Li, D.; Hou, T. Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. capability to predict protein–protein binding free energies and re-rank binding poses generated by protein–protein docking. Phys. Chem. Chem. Phys., 2016, 18(32), 22129-22139.
[http://dx.doi.org/10.1039/C6CP03670H] [PMID: 27444142]
[38]
Xu, L.; Sun, H.; Li, Y.; Wang, J.; Hou, T. Assessing the performance of MM/PBSA and MM/GBSA methods. 3. the impact of force fields and ligand charge models. J. Phys. Chem. B, 2013, 117(28), 8408-8421.
[http://dx.doi.org/10.1021/jp404160y] [PMID: 23789789]
[39]
Hou, T.; Wang, J.; Li, Y.; Wang, W. Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. the accuracy of binding free energy calculations based on molecular dynamics simulations. J. Chem. Inf. Model., 2011, 51(1), 69-82.
[http://dx.doi.org/10.1021/ci100275a] [PMID: 21117705]
[40]
Hou, T.; Wang, J.; Li, Y.; Wang, W. 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., 2011, 32(5), 866-877.
[http://dx.doi.org/10.1002/jcc.21666] [PMID: 20949517]
[41]
Wang, E.; Sun, H.; Wang, J.; Wang, Z.; Liu, H.; Zhang, J.Z.H.; Hou, T. End-point binding free energy calculation with mm/pbsa and mm/gbsa: Strategies and applications in drug design. Chem. Rev., 2019, 119(16), 9478-9508.
[http://dx.doi.org/10.1021/acs.chemrev.9b00055] [PMID: 31244000]
[42]
Weng, G.; Wang, E.; Wang, Z.; Liu, H.; Zhu, F.; Li, D.; Hou, T. HawkDock: A web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA. Nucleic Acids Res., 2019, 47(W1), W322-W330.
[http://dx.doi.org/10.1093/nar/gkz397] [PMID: 31106357]
[43]
Onufriev, A.; Bashford, D.; Case, D.A. Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins, 2004, 55(2), 383-394.
[http://dx.doi.org/10.1002/prot.20033] [PMID: 15048829]
[44]
Lei, T.; Sun, H.; Kang, Y.; Zhu, F.; Liu, H.; Zhou, W.; Wang, Z.; Li, D.; Li, Y.; Hou, T. ADMET evaluation in drug discovery. 18. reliable prediction of chemical-induced urinary tract toxicity by boosting machine learning approaches. Mol. Pharm., 2017, 14(11), 3935-3953.
[http://dx.doi.org/10.1021/acs.molpharmaceut.7b00631] [PMID: 29037046]
[45]
Wu, Z.; Lei, T.; Shen, C.; Wang, Z.; Cao, D.; Hou, T. ADMET evaluation in drug discovery. 19. reliable prediction of human cytochrome P450 inhibition using artificial intelligence approaches. J. Chem. Inf. Model., 2019, 59(11), 4587-4601.
[http://dx.doi.org/10.1021/acs.jcim.9b00801] [PMID: 31644282]
[46]
Li, D.; Chen, L.; Li, Y.; Tian, S.; Sun, H.; Hou, T. ADMET evaluation in drug discovery. 13. development of in silico prediction models for P-glycoprotein substrates. Mol. Pharm., 2014, 11(3), 716-726.
[http://dx.doi.org/10.1021/mp400450m] [PMID: 24499501]
[47]
Tian, S.; Li, Y.; Wang, J.; Zhang, J.; Hou, T. ADME evaluation in drug discovery. 9. prediction of oral bioavailability in humans based on molecular properties and structural fingerprints. Mol. Pharm., 2011, 8(3), 841-851.
[http://dx.doi.org/10.1021/mp100444g] [PMID: 21548635]

Rights & Permissions Print Cite
Article Metrics
34
3
Wayfinder Image
© 2024 Bentham Science Publishers | Privacy Policy