Login Register Cart 0
Generic placeholder image

Current Pharmaceutical Biotechnology

Editor-in-Chief

ISSN (Print): 1389-2010
ISSN (Online): 1873-4316

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

In Silico Repurposing of J147 for Neonatal Encephalopathy Treatment: Exploring Molecular Mechanisms of Mutant Mitochondrial ATP Synthase

Author(s): Iwuchukwu A. Emmanuel, Fisayo A. Olotu, Clement Agoni and Mahmoud E.S. Soliman*

Volume 21, Issue 14, 2020

Page: [1551 - 1566] Pages: 16

DOI: 10.2174/1389201021666200628152246

Price: $65

Abstract

Background: Neonatal Encephalopathy (NE) is a mitochondrial ATP synthase (mATPase) disease, which results in the death of infants. The case presented here is reportedly caused by complex V deficiency as a result of mutation of Arginine to Cysteine at residue 329 in the mATPase. A recent breakthrough was the discovery of J147, which targets mATPase in the treatment of Alzheimer’s disease. Based on the concepts of computational target-based drug design, this study investigated the possibility of employing J147 as a viable candidate in the treatment of NE.

Objective/Methods: The structural dynamic implications of this drug on the mutated enzyme are yet to be elucidated. Hence, integrative molecular dynamics simulations and thermodynamic calculations were employed to investigate the activity of J147 on the mutated enzyme in comparison to its already established inhibitory activity on the wild-type enzyme.

Results: A correlated structural trend occurred between the wild-type and mutant systems whereby all the systems exhibited an overall conformational transition. Equal observations in favorable free binding energies further substantiated uniformity in the mobility, and residual fluctuation of the wild-type and mutant systems. The similarity in the binding landscape suggests that J147 could as well modulate mutant mATPase activity in addition to causing structural modifications in the wild-type enzyme.

Conclusion: Findings suggest that J147 can stabilize the mutant protein and restore it to a similar structural state as the wild-type which depicts functionality. These details could be employed in drug design for potential drug resistance cases due to mATPase mutations that may present in the future.

Keywords: Mitochondrial ATP synthase, mutation, neonatal encephalopathy, complex V deficiency, J147, wild-type enzyme.

« Previous
Graphical Abstract

[1]
Rühle, T.; Leister, D. Assembly of F1F0-ATP synthases. Biochim. Biophys. Acta, 2015, 1847(9), 849-860.
[http://dx.doi.org/10.1016/j.bbabio.2015.02.005] [PMID: 25667968]
[2]
Walker, J.E.J.TP Synthase: The understood, the uncertain and the unknown. Biochem. Soc. Trans., 2013, 41(1), 1-16.
[3]
Martínez-Reyes, I.; Cuezva, J. M. The H(+)-ATP synthase: A gate to ROS-mediated cell death or cell survival. Biochim. Biophys. Acta, 2014, 1837(7), 1099-1112.
[http://dx.doi.org/10.1016/j.bbabio.2014.03.010] [PMID: 24685430]
[4]
Formentini, L.; Sánchez-Aragó, M.; Sánchez-Cenizo, L.; Cuezva, J.M. The mitochondrial ATPase inhibitory factor 1 triggers a ROS-mediated retrograde prosurvival and proliferative response. Mol. Cell, 2012, 45(6), 731-742.
[http://dx.doi.org/10.1016/j.molcel.2012.01.008] [PMID: 22342343]
[5]
Boyer, P.D. The ATP synthase-a splendid molecular machine. Annu. Rev. Biochem., 1997, 66, 717-749.
[http://dx.doi.org/10.1146/annurev.biochem.66.1.717] [PMID: 9242922]
[6]
Bernardi, P.; Rasola, A.; Forte, M.; Lippe, G. The mitochondrial permeability transition pore: Channel formation by F-ATP synthase, integration in signal transduction, and role in pathophysiology Physiologic. Rev.,, 2015, 95(4)
[7]
Pedersen, P.L. Transport ATPases into the year 2008: A brief overview related to types, structures, functions and roles in health and disease. J. Bioenerg. Biomembr., 2007, 39(5-6), 349-355.
[http://dx.doi.org/10.1007/s10863-007-9123-9] [PMID: 18175209]
[8]
Hong, S.; Pedersen, P.L. ATP synthase and the actions of inhibitors utilized to study its roles in human health, disease, and other scientific areas. Microbiol. Mol. Biol. Rev., 2008, 72(4), 590-641.
[http://dx.doi.org/10.1128/MMBR.00016-08] [PMID: 19052322]
[9]
García-Aguilar, A.; Cuezva, J.M. A review of the inhibition of the mitochondrial ATP Synthase by IF1 in vivo: Reprogramming energy metabolism and inducing mitohormesis. Front. Physiol., 2018, 9, 1322.
[http://dx.doi.org/10.3389/fphys.2018.01322] [PMID: 30283362]
[10]
Pedersen, P.L.; Amzel, L.M. ATP synthases. Structure, reaction center, mechanism, and regulation of one of nature’s most unique machines. J. Biol. Chem., 1993, 268(14), 9937-9940.
[PMID: 8486720]
[11]
Pedersen, P.L.; Ko, Y.H.; Hong, S. ATP synthases in the year 2000: Evolving views about the structures of these remarkable enzyme complexes. J. Bioenerg. Biomembr., 2000, 32(4), 325-332.
[http://dx.doi.org/10.1023/A:1005594800983] [PMID: 11768293]
[12]
Preiss, L.; Klyszejko, A.L.; Hicks, D.B.; Liu, J.; Fackelmayer, O.J.; Yildiz, Ö.; Krulwich, T.A.; Meier, T.; Kaback, H.R. The C-ring stoichiometry of ATP synthase is adapted to cell physiological requirements of alkaliphilic Bacillus pseudofirmus OF4. Proc. Natl. Acad. Sci. USA, 2013, 110(19), 7874-7879.
[http://dx.doi.org/10.1073/pnas.1303333110]
[13]
Hakulinen, J.K.; Klyszejko, A.L.; Hoffmann, J.; Eckhardt-Strelau, L.; Brutschy, B.; Vonck, J.; Meier, T. Structural study on the architecture of the bacterial ATP Synthase Fo Motor. Proc. Natl. Acad. Sci. USA, 2012, 109(30), E2050-E2056.
[14]
Ko, Y.H.; Hong, S.; Pedersen, P.L. Mitochondrial Atp synthase: crystal structure of the catalytic F 1 unit in a vanadate-induced transition-like state and implications for mechanism. J. Biol. Chem., 1997, 272, 28853-28856.
[15]
Abrahams, J.P.; Leslie, A.G.W.; Lutter, R.; Walker, J.E. Structure at 2.8 A resolution of F1-ATPase from bovine heart mitochondria. Nature, 1994, 370(6491), 621-628.
[http://dx.doi.org/10.1038/370621a0] [PMID: 8065448]
[16]
Johnson, J.A.; Ogbi, M. Targeting the F1Fo ATP Synthase: Modulation of the body’s powerhouse and its implications for human disease. Curr. Med. Chem., 2011, 18(30), 4684-4714.
[http://dx.doi.org/10.2174/092986711797379177] [PMID: 21864274]
[17]
Ahmad, Z.; Laughlin, T.F. Medicinal chemistry of ATP synthase: A potential drug target of dietary polyphenols and amphibian antimicrobial peptides. Curr. Med. Chem., 2010, 17(25), 2822-2836.
[http://dx.doi.org/10.2174/092986710791859270] [PMID: 20586714]
[18]
Gledhill, J.R.; Montgomery, M.G.; Leslie, A.G.; Walker, J.E. Mechanism of inhibition of bovine F1-ATPase by resveratrol and related polyphenols. Proc. Natl. Acad. Sci. USA, 2007, 104(34), 13632-13637.
[http://dx.doi.org/10.1073/pnas.0706290104] [PMID: 17698806]
[19]
Kenan, D.J.; Wahl, M.L. Ectopic localization of mitochondrial ATP synthase: A target for anti-angiogenesis intervention? J. Bioenerg. Biomembr., 2005, 37(6), 461-465.
[http://dx.doi.org/10.1007/s10863-005-9492-x] [PMID: 16691484]
[20]
Champagne, E.; Martinez, L.O.; Collet, X.; Barbaras, R. Ecto-F1Fo ATP synthase/F1 ATPase: Metabolic and immunological functions. Curr. Opin. Lipidol., 2006, 17(3), 279-284.
[http://dx.doi.org/10.1097/01.mol.0000226120.27931.76] [PMID: 16680033]
[21]
Berger, K.; Sivars, U.; Winzell, M.S.; Johansson, P.; Hellman, U.; Rippe, C.; Erlanson-Albertsson, C. Mitochondrial ATP synthase--a possible target protein in the regulation of energy metabolism in vitro and in vivo. Nutr. Neurosci., 2002, 5(3), 201-210.
[http://dx.doi.org/10.1080/10284150290008604] [PMID: 12041876]
[22]
Arakaki, N.; Kita, T.; Shibata, H.; Higuti, T. Cell-surface H+-ATP synthase as a potential molecular target for anti-obesity drugs. FEBS Lett., 2007, 581(18), 3405-3409.
[http://dx.doi.org/10.1016/j.febslet.2007.06.041] [PMID: 17612527]
[23]
Goldberg, J.; Currais, A.; Prior, M.; Fischer, W.; Chiruta, C.; Ratliff, E.; Daugherty, D.; Dargusch, R.; Finley, K.; Esparza-Moltó, P.B.; Cuezva, J.M.; Maher, P.; Petrascheck, M.; Schubert, D. The mitochondrial ATP synthase is a shared drug target for aging and dementia. Aging Cell, 2018, 17(2)e12715
[http://dx.doi.org/10.1111/acel.12715] [PMID: 29316249]
[24]
Prior, M.; Dargusch, R.; Ehren, J.L.; Chiruta, C.; Schubert, D. The neurotrophic compound J147 reverses cognitive impairment in aged Alzheimer’s disease mice. Alzheimers Res. Ther., 2013, 5(3), 25.
[http://dx.doi.org/10.1186/alzrt179] [PMID: 23673233]
[25]
Emmanuel, I.A.; Olotu, F.A.; Agoni, C.; Soliman, M. Deciphering the “Elixir of Life”: dynamic perspectives into the allosteric modulation of mitochondrial ATP synthase by J147, a novel drug in the treatment of Alzheimer’s disease. Chem. Biodivers., 2019, 16(6)e1900085
[26]
Jonckheere, A.I.; Renkema, G.H.; Bras, M.; van den Heuvel, L.P.; Hoischen, A.; Gilissen, C.; Nabuurs, S.B.; Huynen, M.A.; de Vries, M.C.; Smeitink, J.A.M.; Rodenburg, R.J.T. A complex V ATP5A1 defect causes fatal neonatal mitochondrial encephalopathy. Brain, 2013, 136(Pt 5), 1544-1554.
[http://dx.doi.org/10.1093/brain/awt086] [PMID: 23599390]
[27]
Xu, T.; Pagadala, V.; Mueller, D.M. Understanding structure, function, and mutations in the mitochondrial ATP synthase. Microb. Cell, 2015, 2(4), 105-125.
[http://dx.doi.org/10.15698/mic2015.04.197] [PMID: 25938092]
[28]
Martinello, K.; Hart, A.R.; Yap, S.; Mitra, S.; Robertson, N.J. Management and investigation of neonatal encephalopathy: 2017 update. Arch. Dis. Child. Fetal Neonatal Ed., 2017, 102(4), F346-F358.
[http://dx.doi.org/10.1136/archdischild-2015-309639] [PMID: 28389438]
[29]
Sell, E.; Munoz, F.M.; Soe, A.; Wiznitzer, M.; Heath, P.T.; Clarke, E.D.; Spiegel, H.; Sawlwin, D.; Šubelj, M.; Tikhonov, I.; Mohammad, K.; Kochhar, S. Brighton Collaboration Acute Neonatal Encephalopathy Working Group. Neonatal encephalopathy: Case definition & guidelines for data collection, analysis, and presentation of maternal immunisation safety data. Vaccine, 2017, 35(48 Pt A), 6501-6505.
[http://dx.doi.org/10.1016/j.vaccine.2017.01.045] [PMID: 29150055]
[30]
Ramharack, P.; Soliman, M.E.S. Zika virus drug targets: A missing link in drug design and discovery - a route map to fill the gap. RSC Advances, 2016, 6, 68719-68731.
[http://dx.doi.org/10.1039/C6RA12142J]
[31]
Munsamy, G.; Ramharack, P.; Soliman, M.E.S. Egress and invasion machinery of malaria: An in-depth look into the structural and functional features of the flap dynamics of plasmepsin IX and X. RSC Adv.,, 2018, 8, 21829-21840.
[http://dx.doi.org/10.1039/C8RA04360D]
[32]
Munsamy, G.; Soliman, M.E.S. Homology modeling in drug discovery-an update on the last decade. Lett. Drug Des. Discov., 2017, 14(9), 1099-1111.
[http://dx.doi.org/10.2174/1570180814666170110122027]
[33]
Laskowski, R.A.; MacArthur, M.W.; Moss, D.S.; Thornton, J.M. IUCr. PROCHECK: A program to check the stereochemical quality of protein structures. J. Appl. Cryst., 1993, 26, 283-291.
[http://dx.doi.org/10.1107/S0021889892009944]
[34]
Wiederstein, M.; Sippl, M.J. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins Nucleic Acids Res, 2007, 35 (Web Server issue), W407-10.
[http://dx.doi.org/10.1093/nar/gkm290] [PMID: 17517781]
[35]
Lovell, S.C.; Davis, I.W.; Arendall, W.B., III; de Bakker, P.I.W.; Word, J.M.; Prisant, M.G.; Richardson, J.S.; Richardson, D.C. Structure validation by Calpha geometry: ϕ,ψ and Cbeta deviation. Proteins, 2003, 50(3), 437-450.
[http://dx.doi.org/10.1002/prot.10286] [PMID: 12557186]
[36]
Eisenberg, D.; Lüthy, R.; Bowie, J.U. VERIFY3D: Assessment of protein models with three-dimensional profiles. Methods Enzymol., 1997, 277, 396-404.
[http://dx.doi.org/10.1016/S0076-6879(97)77022-8] [PMID: 9379925]
[37]
Trott, O.; Olson, A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2010, 31(2), 455-461.
[PMID: 19499576]
[38]
Yang, Z.; Lasker, K.; Schneidman-Duhovny, D.; Webb, B.; Huang, C.C.; Pettersen, E.F.; Goddard, T.D.; Meng, E.C.; Sali, A.; Ferrin, T.E. UCSF Chimera, MODELLER, and IMP: An integrated modeling system. J. Struct. Biol., 2012, 179(3), 269-278.
[http://dx.doi.org/10.1016/j.jsb.2011.09.006] [PMID: 21963794]
[39]
Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera-a visualization system for exploratory research and analysis. J. Comput. Chem., 2004, 25(13), 1605-1612.
[http://dx.doi.org/10.1002/jcc.20084] [PMID: 15264254]
[40]
Case, D.A.; Cheatham, T.E., III; Darden, T.; Gohlke, H.; Luo, R.; Merz, K.M., Jr; Onufriev, A.; Simmerling, C.; Wang, B.; Woods, R.J. The Amber biomolecular simulation programs. J. Comput. Chem., 2005, 26(16), 1668-1688.
[http://dx.doi.org/10.1002/jcc.20290] [PMID: 16200636]
[41]
Wang, J.; Wang, W.; Kollman, P.A.; Case, D.A. Antechamber, an accessory software package for molecular mechanical calculations. J. Chemic. Info. Comp. Sci.,, 2000.
[42]
Perez, A.; MacCallum, J.L.; Brini, E.; Simmerling, C.; Dill, K.A. Grid-based backbone correction to the ff12SB protein force field for implicit-solvent simulations. J. Chem. Theory Comput., 2015, 11(10), 4770-4779.
[http://dx.doi.org/10.1021/acs.jctc.5b00662] [PMID: 26574266]
[43]
Jorgensen, W.L.; Chandrasekhar, J.; Madura, J.D.; Impey, R.W.; Klein, M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys., 1983, 79, 926-935.
[http://dx.doi.org/10.1063/1.445869]
[44]
Smith, W. Yasuoka K. Darden T. Ebisuzaki T. A smooth-particle Mesh Ewald method for DL_POLY molecular dynamics simulation package on the Fujitsu VPP700. J. Comput. Chem., 2000, 21(13), 1187-1191.
[45]
Machaba, K.E.; Mhlongo, N.N.; Soliman, M.E.S. induced mutation proves a potential target for TB therapy: A molecular dynamics study on LprG. Cell Biochem. Biophys., 2018, 76(3), 345-356.
[http://dx.doi.org/10.1007/s12013-018-0852-7] [PMID: 30073572]
[46]
El Rashedy, A.A.; Appiah-Kubi, P.; Soliman, M.E.S. A synergistic combination against chronic myeloid leukemia: An intra-molecular mechanism of communication in BCR-ABL1 resistance. Protein J., 2019, 38(2), 142-150.
[http://dx.doi.org/10.1007/s10930-019-09820-z] [PMID: 30877503]
[47]
Karubiu, W.; Bhakat, S.; Soliman, M.E.S. Compensatory role of double mutation N348I/M184V on nevirapine binding landscape: insight from molecular dynamics simulation. Protein J., 2014, 33(5), 432-446.
[http://dx.doi.org/10.1007/s10930-014-9576-8] [PMID: 25107349]
[48]
Roe, D.R.; Cheatham, T.E. III PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. J. Chem. Theory Comput., 2013, 9(7), 3084-3095.
[http://dx.doi.org/10.1021/ct400341p] [PMID: 26583988]
[49]
Seifert, E. OriginPro 9.1: Scientific data analysis and graphing software-software review. J. Chem. Inf. Model., 2014, 54(5), 1552-1552.
[http://dx.doi.org/10.1021/ci500161d] [PMID: 24702057]
[50]
Zhou, Z.; Madura, J.D. Relative free energy of binding and binding mode calculations of HIV-1 RT inhibitors based on dock-MM-PB/GS. Proteins, 2004, 57(3), 493-503.
[http://dx.doi.org/10.1002/prot.20223] [PMID: 15382241]
[51]
Zhou, Z.; Wang, Y.; Bryant, S.H. Computational analysis of the cathepsin B inhibitors activities through LR-MMPBSA binding affinity calculation based on docked complex. J. Comput. Chem., 2009, 30(14), 2165-2175.
[http://dx.doi.org/10.1002/jcc.21214] [PMID: 19242965]
[52]
Genheden, S.; Ryde, U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin. Drug Discov., 2015, 10(5), 449-461.
[http://dx.doi.org/10.1517/17460441.2015.1032936] [PMID: 25835573]
[53]
Adeniji, E.A.; Olotu, F.A.; Shunmugam, L.; Soliman, M.E.S. From a computational point of view: Deciphering the molecular synergism between oxidative stress-induced lipid peroxidation products and metabolic dysfunctionality of human liver mitochondrial aldehyde dehydrogenase-2. Mol. Simul., 2019, 45, 652-665.
[http://dx.doi.org/10.1080/08927022.2019.1578355]
[54]
Contreras-Riquelme, S.; Garate, J-A.; Perez-Acle, T.; Martin, A.J.M. RIP-MD: A tool to study residue interaction networks in protein molecular dynamics. PeerJ, 2018, 6e5998
[http://dx.doi.org/10.7717/peerj.5998] [PMID: 30568854]
[55]
Piovesan, D.; Minervini, G.; Tosatto, S.C.E. The RING 2.0 web server for high quality residue interaction networks. Nucleic Acids Res., 2016, 44(W1)W367-74
[http://dx.doi.org/10.1093/nar/gkw315] [PMID: 27198219]
[56]
Doncheva, N.T.; Klein, K.; Domingues, F.S.; Albrecht, M. Analyzing and visualizing residue networks of protein structures. Trends Biochem. Sci., 2011, 36(4), 179-182.
[http://dx.doi.org/10.1016/j.tibs.2011.01.002] [PMID: 21345680]
[57]
Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res., 2003, 13(11), 2498-2504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]
[58]
Assenov, Y.; Ramírez, F.; Schelhorn, S-E.; Lengauer, T.; Albrecht, M. Computing topological parameters of biological networks. Bioinformatics, 2008, 24(2), 282-284.
[http://dx.doi.org/10.1093/bioinformatics/btm554] [PMID: 18006545]
[59]
Pitera, J.W. Expected distributions of root-mean-square positional deviations in proteins. J. Phys. Chem. B, 2014, 118(24), 6526-6530.
[http://dx.doi.org/10.1021/jp412776d] [PMID: 24655018]
[60]
Lawal, M.; Olotu, F.A.; Soliman, M.E.S. Across the blood-brain barrier: Neurotherapeutic screening and characterization of naringenin as a novel CRMP-2 inhibitor in the treatment of Alzheimer’s disease using bioinformatics and computational tools. Comput. Biol. Med., 2018, 98, 168-177.
[http://dx.doi.org/10.1016/j.compbiomed.2018.05.012] [PMID: 29860210]
[61]
Olotu, F.A.; Soliman, M.E.S. From mutational inactivation to aberrant gain-of-function: Unraveling the structural basis of mutant p53 oncogenic transition. J. Cell. Biochem., 2018, 119(3), 2646-2652.
[http://dx.doi.org/10.1002/jcb.26430] [PMID: 29058783]
[62]
Ndagi, U.; Mhlongo, N.N.; Soliman, M.E. The impact of Thr91 mutation on c-Src resistance to UM-164: Molecular dynamics study revealed a new opportunity for drug design. Mol. Biosyst., 2017, 13(6), 1157-1171.
[http://dx.doi.org/10.1039/C6MB00848H] [PMID: 28463369]
[63]
Bornot, A.; Etchebest, C.; de Brevern, A.G. Predicting protein flexibility through the prediction of local structures. Proteins, 2011, 79(3), 839-852.
[http://dx.doi.org/10.1002/prot.22922] [PMID: 21287616]
[64]
Hahn-Herrera, O.; Salcedo, G.; Barril, X.; García-Hernández, E. Inherent conformational flexibility of F1-ATPase α-subunit. Biochim. Biophys. Acta, 2016, 1857(9), 1392-1402.
[http://dx.doi.org/10.1016/j.bbabio.2016.04.283] [PMID: 27137408]
[65]
Zheng, W. Normal-mode-based modeling of allosteric couplings that underlie cyclic conformational transition in F(1) ATPase. Proteins, 2009, 76(3), 747-762.
[http://dx.doi.org/10.1002/prot.22386] [PMID: 19280602]
[66]
Ekimoto, T.; Ikeguchi, M. Multiscale molecular dynamics simulations of rotary motor proteins. Biophys. Rev., 2018, 10(2), 605-615.
[http://dx.doi.org/10.1007/s12551-017-0373-4] [PMID: 29204882]
[67]
Ito, Y.; Oroguchi, T.; Ikeguchi, M. Mechanism of the conformational change of the F1-ATPase β subunit revealed by free energy simulations. J. Am. Chem. Soc., 2011, 133(10), 3372-3380.
[http://dx.doi.org/10.1021/ja1070152] [PMID: 21341660]
[68]
Ito, Y.; Ikeguchi, M. Mechanism of the αβ conformational change in F1-ATPase after ATP hydrolysis: free-energy simulations. Biophys. J., 2015, 108(1), 85-97.
[http://dx.doi.org/10.1016/j.bpj.2014.11.1853] [PMID: 25564855]
[69]
Xie, Y.; An, J.; Yang, G.; Wu, G.; Zhang, Y.; Cui, L.; Feng, Y. Enhanced enzyme kinetic stability by increasing rigidity within the active site. J. Biol. Chem., 2014, 289(11), 7994-8006.
[http://dx.doi.org/10.1074/jbc.M113.536045] [PMID: 24448805]
[70]
Karshikoff, A.; Nilsson, L.; Ladenstein, R. Rigidity versus flexibility: the dilemma of understanding protein thermal stability. FEBS J., 2015, 282(20), 3899-3917.
[http://dx.doi.org/10.1111/febs.13343] [PMID: 26074325]
[71]
Ramharack, P.; Oguntade, S.; Soliman, M.E.S. Delving into zika virus structural dynamics - a closer look at NS3 helicase loop flexibility and its role in drug discovery. RSC Advances, 2017, 7, 22133-22144.
[http://dx.doi.org/10.1039/C7RA01376K]
[72]
Lobanov, M.Y.; Bogatyreva, N.S.; Galzitskaya, O.V. Radius of gyration as an indicator of protein structure compactness. Mol. Biol., 2008, 42, 623-628.
[http://dx.doi.org/10.1134/S0026893308040195] [PMID: 18856071]
[73]
Chen, D.; Oezguen, N.; Urvil, P.; Ferguson, C.; Dann, S.M.; Savidge, T.C. Regulation of protein-ligand binding affinity by hydrogen bond pairing. Sci. Adv., 2016, 2(3)e1501240
[http://dx.doi.org/10.1126/sciadv.1501240] [PMID: 27051863]
[74]
Hu, G.; Yan, W.; Zhou, J.; Shen, B. Residue interaction network analysis of dronpa and a DNA clamp. J. Theor. Biol., 2014, 348, 55-64.
[http://dx.doi.org/10.1016/j.jtbi.2014.01.023]
[75]
Yan, W.; Zhou, J.; Sun, M.; Chen, J.; Hu, G.; Shen, B. The construction of an amino acid network for understanding protein structure and function. Amino Acids, 2014, 46(6), 1419-1439.
[http://dx.doi.org/10.1007/s00726-014-1710-6] [PMID: 24623120]
[76]
Xue, W.; Jin, X.; Ning, L.; Wang, M.; Liu, H.; Yao, X. Exploring the molecular mechanism of cross-resistance to HIV-1 integrase strand transfer inhibitors by molecular dynamics simulation and residue interaction network analysis. J. Chem. Inf. Model., 2013, 53(1), 210-222.
[http://dx.doi.org/10.1021/ci300541c] [PMID: 23231029]

Rights & Permissions Print Cite
Article Metrics
29
© 2024 Bentham Science Publishers | Privacy Policy