Alzheimer's Disease and β-secretase Inhibition: An Update with a Focus
on Computer-aided Inhibitor Design

Samuel   C.   Ugbaja; Isiaka   A.   Lawal; Hezekiel   M.   Kumalo; Monsurat   M.   Lawal
doi:10.2174/1389450122666210809100050
Abstract

Introduction: Alzheimer's disease (AD) is an intensifying neurodegenerative illness due to its irreversible nature. Identification of β‐site Amyloid Precursor Protein (APP) cleaving en-zyme1 (BACE1) has been a significant medicinal focus towards AD treatment, and this has opened ground for several investigations. Despite the numerous works in this direction, no BACE1 inhibitor has made it to the final approval stage as an anti-AD drug.
Methods: We provide an introductory background of the subject with a general overview of the pathogenesis of AD. The review features BACE1 inhibitor design and development with a focus on some clinical trials and discontinued drugs. Using the topical keywords BACE1, inhibitor design, and computational/theoretical study in the Web of Science and Scopus database, we retrieved over 49 relevant articles. The search years are from 2010 and 2020, with analysis conducted from May 2020 to March 2021.
Results and Discussion: Researchers have employed computational methodologies to unravel po-tential BACE1 inhibitors with a significant outcome. The most used computer-aided approach in BACE1 inhibitor design and binding/interaction studies are pharmacophore development, quantita-tive structure-activity relationship (QSAR), virtual screening, docking, and molecular dynamics (MD) simulations. These methods, plus more advanced ones including quantum mechan-ics/molecular mechanics (QM/MM) and QM, have proven substantial in the computational frame-work for BACE1 inhibitor design. Computational chemists have embraced the incorporation of in vitro assay to provide insight into the inhibition performance of identified molecules with potential inhibition towards BACE1. Significant IC50 values up to 50 nM, better than clinical trial com-pounds, are available in the literature.
Conclusion: The continuous failure of potent BACE1 inhibitors at clinical trials is attracting many queries prompting researchers to investigate newer concepts necessary for effective inhibitor de-sign. The considered properties for efficient BACE1 inhibitor design seem enormous and require thorough scrutiny. Lately, researchers noticed that besides appreciable binding affinity and Blood-Brain Barrier (BBB) permeation, BACE1 inhibitor must show low or no affinity for permeability-glycoprotein. Computational modeling methods have profound applications in drug discovery strat-egies. With the volume of recent in silico studies on BACE1 inhibition, the prospect of identifying potent molecules that would reach the approved level is feasible. Investigators should try pushing many of the identified BACE1 compounds with significant anti-AD properties to preclinical and clinical trial stages. We also advise computational research on allosteric inhibitor design, exosite modeling, and multisite inhibition of BACE1. These alternatives might be a solution to BACE1 drug discovery in AD therapy.
Keywords: β-Secretase, alzheimer's disease (AD), BACE1 inhibition, anti-AD drugs, computer-aided inhibitor design, docking.
« Previous Next »
Graphical Abstract

[1] 
Cantor SR, Cantor SG.  Proceedings of the 1995 IEEE International Frequency Control Symposium (49th Annual Symposium). 3-9.
[2] 
Ornstein RE, Thompson RF. The amazing brain. Houghton Mifflin Harcourt 1986.
[3] 
Fields RD. The other brain: From dementia to schizophrenia, how new discoveries about the brain are revolutionizing medicine and science. Simon and Schuster 2009.
[4] 
Carter R. The brain book: An illustrated guide to its structure, functions, and disorders. Dorling Kindersley Ltd. 2019.
[5] 
Dudai Y. Memory from A to Z: Keywords, concepts, and beyond. USA: Oxford University Press 2004.
[6] 
Brown TE. Attention deficit disorder: The unfocused mind in children and adults. Yale University Press 2005.
[7] 
Corliss J, Gilbert S. A guide to Alzheimer’s disease. Harvard Health Publications 2009.
[8] 
Kandel ER. The disordered mind: What unusual brains tell us about ourselves. UK: Hachette 2018.
[9] 
Reitz C, Brayne C, Mayeux R. Epidemiology of Alzheimer disease. Nat Rev Neurol  2011; 7(3): 137-52.
[http://dx.doi.org/10.1038/nrneurol.2011.2] [PMID:  21304480] 
[10] 
Cummings J, Lee G, Ritter A, Sabbagh M, Zhong K. Alzheimer’s disease drug development pipeline: 2019. Alzheimers Dement (N Y)  2019; 5: 272-93.
[http://dx.doi.org/10.1016/j.trci.2019.05.008] [PMID:  31334330] 
[11] 
Brookmeyer R, Corrada MM, Curriero FC, Kawas C. Survival following a diagnosis of Alzheimer disease. Arch Neurol  2002; 59(11): 1764-7.
[http://dx.doi.org/10.1001/archneur.59.11.1764] [PMID:  12433264] 
[12] 
Imbimbo BP, Watling M. Investigational BACE inhibitors for the treatment of Alzheimer’s disease. Expert Opin Investig Drugs  2019; 28(11): 967-75.
[http://dx.doi.org/10.1080/13543784.2019.1683160] [PMID:  31661331] 
[13] 
Sytnyk V. How synapses are destroyed in the early stages of Alzheimer’s disease Available from:. https://neurosciencenews.com/synapse-loss-alzheimers-genetics-3169/[Accessed on October 01,2020]
[14] 
First WHO ministerial conference on global action against dementia:
	meeting report. Geneva, Switzerland. WHO Headquarters
	2015.16-17 March. 
[15] 
Winblad B, Amouyel P, Andrieu S, et al. Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol  2016; 15(5): 455-532.
[http://dx.doi.org/10.1016/S1474-4422(16)00062-4] [PMID:  26987701] 
[16] 
Alzheimer A, Stelzmann RA, Schnitzlein HN, Murtagh FR. An english translation of Alzheimer’s 1907 paper, “Uber eine eigenartige Erkankung der Hirnrinde. Clin Anat  1995; 8(6): 429-31.
[http://dx.doi.org/10.1002/ca.980080612] [PMID:  8713166] 
[17] 
Duthey B. Background paper 6.11: Alzheimer disease and other
	dementias. A public health approach to innovation 2013; 6: 1-74.
[18] 
Lane CA, Parker TD, Cash DM, et al. Study protocol: Insight 46 - a neuroscience sub-study of the MRC National Survey of Health and Development. BMC Neurol  2017; 17(1): 75.
[http://dx.doi.org/10.1186/s12883-017-0846-x] [PMID:  28420323] 
[19] 
Alzheimer’s disease facts and figures. Alzheimers Dement  2017; 13(4): 325-73.
[http://dx.doi.org/10.1016/j.jalz.2017.02.001] 
[20] 
James S-N, Lane CA, Parker TD, et al. Using a birth cohort to study brain health and preclinical dementia: recruitment and participation rates in Insight 46. BMC Res Notes  2018; 11(1): 885.
[http://dx.doi.org/10.1186/s13104-018-3995-0] [PMID:  30545411] 
[21] 
Islam MA, Pillay TS. β-secretase inhibitors for Alzheimer’s disease: identification using pharmacoinformatics. J Biomol Struct Dyn  2019; 37(2): 503-22.
[http://dx.doi.org/10.1080/07391102.2018.1430619] [PMID:  29388503] 
[22] 
Dassel K, Butler J, Telonidis J, Edelman L. Development and evaluation of Alzheimer’s Disease and Related Dementias (ADRD) best care practices in long-term care online training program. Educ Gerontol  2020; 46(3): 150-7.
[http://dx.doi.org/10.1080/03601277.2020.1717079] 
[23] 
LaFerla FM, Green KN, Oddo S. Intracellular amyloid-β in Alzheimer’s disease. Nat Rev Neurosci  2007; 8(7): 499-509.
[http://dx.doi.org/10.1038/nrn2168] [PMID:  17551515] 
[24] 
Murphy MP, LeVine H III. Alzheimer’s disease and the amyloid-β peptide. J Alzheimers Dis  2010; 19(1): 311-23.
[http://dx.doi.org/10.3233/JAD-2010-1221] [PMID:  20061647] 
[25] 
Stansley B, Post J, Hensley K. A comparative review of cell culture systems for the study of microglial biology in Alzheimer’s disease. J Neuroinflammation  2012; 9(1): 115.
[http://dx.doi.org/10.1186/1742-2094-9-115] [PMID:  22651808] 
[26] 
Zhang F, Jiang L. Neuroinflammation in Alzheimer’s disease. Neuropsychiatr Dis Treat  2015; 11: 243-56.
[http://dx.doi.org/10.2147/NDT.S75546] [PMID:  25673992] 
[27] 
Fortini ME. γ-secretase-mediated proteolysis in cell-surface-receptor signalling. Nat Rev Mol Cell Biol  2002; 3(9): 673-84.
[http://dx.doi.org/10.1038/nrm910] [PMID:  12209127] 
[28] 
Teich AF, Arancio O. Is the amyloid hypothesis of Alzheimer’s disease therapeutically relevant? Biochem J  2012; 446(2): 165-77.
[http://dx.doi.org/10.1042/BJ20120653] [PMID:  22891628] 
[29] 
Crump CJ, Johnson DS, Li Y-M. Development and mechanism of γ-secretase modulators for Alzheimer’s disease. Biochemistry  2013; 52(19): 3197-216.
[http://dx.doi.org/10.1021/bi400377p] [PMID:  23614767] 
[30] 
Dillen K, Annaert W. A two decade contribution of molecular cell biology to the centennial of Alzheimer’s disease: Are we progressing toward therapy? Int Rev Cytol  2006; 254: 215-300.
[http://dx.doi.org/10.1016/S0074-7696(06)54005-7] [PMID:  17148000] 
[31] 
Ohno M. Genetic and pharmacological basis for therapeutic inhibition of beta- and γ-secretases in mouse models of Alzheimer’s memory deficits. Rev Neurosci  2006; 17(4): 429-54.
[http://dx.doi.org/10.1515/revneuro.2006.17.4.429] [PMID:  17139843] 
[32] 
Wakabayashi T, De Strooper B. Presenilins: members of the γ-secretase quartets, but part-time soloists too. Physiology (Bethesda)  2008; 23(4): 194-204.
[http://dx.doi.org/10.1152/physiol.00009.2008] [PMID:  18697993] 
[33] 
Schenk D, Basi GS, Pangalos MN. Treatment strategies targeting amyloid β-protein. Cold Spring Harb Perspect Med  2012; 2(9)a006387
[http://dx.doi.org/10.1101/cshperspect.a006387] [PMID:  22951439] 
[34] 
Fukumori A, Steiner H. Substrate recruitment of γ-secretase and mechanism of clinical presenilin mutations revealed by photoaffinity mapping. EMBO J  2016; 35(15): 1628-43.
[http://dx.doi.org/10.15252/embj.201694151] [PMID:  27220847] 
[35] 
Powrie YSL. Investigating Tau pathology in an in vitro model for Alzheimer’s disease.  Stellenbosch: Stellenbosch University 2016; pp. 1-139.
[36] 
Cutler NR. Understanding Alzheimer’s disease. University Press of Mississippi 2010.
[37] 
Oliver DMA, Reddy PH. Molecular basis of Alzheimer’s disease: focus on mitochondria. J Alzheimers Dis  2019; 72(s1): S95-S116.
[http://dx.doi.org/10.3233/JAD-190048] [PMID:  30932888] 
[38] 
Hardy JA, Higgins GA. Alzheimer’s disease: the amyloid cascade hypothesis. Science  1992; 256(5054): 184-5.
[http://dx.doi.org/10.1126/science.1566067] [PMID:  1566067] 
[39] 
Nisbet RM, Polanco J-C, Ittner LM, Götz J. Tau aggregation and its interplay with amyloid-β. Acta Neuropathol  2015; 129(2): 207-20.
[http://dx.doi.org/10.1007/s00401-014-1371-2] [PMID:  25492702] 
[40] 
Baleriola J, Walker CA, Jean YY, et al. Axonally synthesized ATF4 transmits a neurodegenerative signal across brain regions. Cell  2014; 158(5): 1159-72.
[http://dx.doi.org/10.1016/j.cell.2014.07.001] [PMID:  25171414] 
[41] 
Suzuki K, Iwata A, Iwatsubo T. The past, present, and future of disease-modifying therapies for Alzheimer’s disease. Proc Jpn Acad, Ser B, Phys Biol Sci  2017; 93(10): 757-71.
[http://dx.doi.org/10.2183/pjab.93.048] [PMID:  29225305] 
[42] 
Um JW, Nygaard HB, Heiss JK, et al. Alzheimer amyloid-β oligomer bound to postsynaptic prion protein activates Fyn to impair neurons. Nat Neurosci  2012; 15(9): 1227-35.
[http://dx.doi.org/10.1038/nn.3178] [PMID:  22820466] 
[43] 
Keskin AO, Durmaz N, Uncu G, et al. Geriatric medicine and gerontology. IntechOpen 2019.
[44] 
Herrup K. The case for rejecting the amyloid cascade hypothesis. Nat Neurosci  2015; 18(6): 794-9.
[http://dx.doi.org/10.1038/nn.4017] [PMID:  26007212] 
[45] 
Alonso AC, Zaidi T, Grundke-Iqbal I, Iqbal K. Role of abnormally phosphorylated tau in the breakdown of microtubules in Alzheimer disease. Proc Natl Acad Sci USA  1994; 91(12): 5562-6.
[http://dx.doi.org/10.1073/pnas.91.12.5562] [PMID:  8202528] 
[46] 
Iqbal K, Liu F, Gong C-X, Alonso Adel C, Grundke-Iqbal I. Mechanisms of tau-induced neurodegeneration. Acta Neuropathol  2009; 118(1): 53-69.
[http://dx.doi.org/10.1007/s00401-009-0486-3] [PMID:  19184068] 
[47] 
Moussa-Pacha NM, Abdin SM, Omar HA, Alniss H, Al-Tel TH. BACE1 inhibitors: Current status and future directions in treating Alzheimer’s disease. Med Res Rev  2020; 40(1): 339-84.
[http://dx.doi.org/10.1002/med.21622] [PMID:  31347728] 
[48] 
Giménez-Llort L, Blázquez G, Cañete T, et al. Modeling behavioral and neuronal symptoms of Alzheimer’s disease in mice: a role for intraneuronal amyloid. Neurosci Biobehav Rev  2007; 31(1): 125-47.
[http://dx.doi.org/10.1016/j.neubiorev.2006.07.007] [PMID:  17055579] 
[49] 
Zhang X, Song W. The role of APP and BACE1 trafficking in APP processing and amyloid-β generation. Alzheimers Res Ther  2013; 5(5): 46.
[http://dx.doi.org/10.1186/alzrt211] [PMID:  24103387] 
[50] 
Do TD, LaPointe NE, Nelson R, et al. Amyloid β-protein C-terminal fragments: Formation of cylindrins and β-barrels. J Am Chem Soc  2016; 138(2): 549-57.
[http://dx.doi.org/10.1021/jacs.5b09536] [PMID:  26700445] 
[51] 
Bode DC, Baker MD, Viles JH. Ion channel formation by amyloid-β42 oligomers but not amyloid-β40 in cellular membranes. J Biol Chem  2017; 292(4): 1404-13.
[http://dx.doi.org/10.1074/jbc.M116.762526] [PMID:  27927987] 
[52] 
Das B, Yan R. A close look at BACE1 inhibitors for Alzheimer’s disease treatment. CNS Drugs  2019; 33(3): 251-63.
[http://dx.doi.org/10.1007/s40263-019-00613-7] [PMID:  30830576] 
[53] 
Pinheiro L, Faustino C. Therapeutic strategies targeting amyloid-β in Alzheimer’s disease. Curr Alzheimer Res  2019; 16(5): 418-52.
[http://dx.doi.org/10.2174/1567205016666190321163438] [PMID:  30907320] 
[54] 
Coley N, Andrieu S, Delrieu J, Voisin T, Vellas B. Biomarkers in Alzheimer’s disease: not yet surrogate endpoints. Ann N Y Acad Sci  2009; 1180(1): 119-24.
[http://dx.doi.org/10.1111/j.1749-6632.2009.04947.x] [PMID:  19906266] 
[55] 
Jadoopat R. Review of Alzheimer’s disease treatment and potential future therapies. Annual Review of Changes in Healthcare  2018; 2(1)
[56] 
Cummings J, Lee G, Ritter A, Zhong K. Alzheimer’s disease drug development pipeline: 2018. Alzheimers Dement (N Y)  2018; 4: 195-214.
[http://dx.doi.org/10.1016/j.trci.2018.03.009] [PMID:  29955663] 
[57] 
Wiessner C, Wiederhold K-H, Tissot AC, et al. The second-generation active Aβ immunotherapy CAD106 reduces amyloid accumulation in APP transgenic mice while minimizing potential side effects. J Neurosci  2011; 31(25): 9323-31.
[http://dx.doi.org/10.1523/JNEUROSCI.0293-11.2011] [PMID:  21697382] 
[58] 
National Institute on Aging. 2019. Available from:. https://www.nia.nih.gov/news/statement-discontinuation-bace-1-inhibitor-cnp520-alzheimers-prevention-initiative-generation
[59] 
Salloway S, Sperling R, Fox NC, et al. Two phase 3 trials of bapineuzumab in mild-to-moderate Alzheimer’s disease. N Engl J Med  2014; 370(4): 322-33.
[http://dx.doi.org/10.1056/NEJMoa1304839] [PMID:  24450891] 
[60] 
Goure WF, Krafft GA, Jerecic J, Hefti F. Targeting the proper amyloid-beta neuronal toxins: a path forward for Alzheimer’s disease immunotherapeutics. Alzheimers Res Ther  2014; 6(4): 42.
[http://dx.doi.org/10.1186/alzrt272] [PMID:  25045405] 
[61] 
Wolfe MS. Developing therapeutics for Alzheimer’s disease: Progress and challenges. Academic Press 2016.
[62] 
Prati F, Bottegoni G, Bolognesi ML, Cavalli A. Bace-1 inhibitors: from recent single-target molecules to multitarget compounds for alzheimer’s disease: Miniperspective. J Med Chem  2018; 61(3): 619-37.
[http://dx.doi.org/10.1021/acs.jmedchem.7b00393] [PMID:  28749667] 
[63] 
Polgár L. The mechanism of action of aspartic proteases involves ‘push-pull’ catalysis. FEBS Lett  1987; 219(1): 1-4.
[http://dx.doi.org/10.1016/0014-5793(87)81179-1] [PMID:  3036594] 
[64] 
Berman HM, Westbrook J, Feng Z, et al. The protein data bank. Nucleic Acids Res  2000; 28(1): 235-42.
[http://dx.doi.org/10.1093/nar/28.1.235] [PMID:  10592235] 
[65] 
Ghosh AK, Kumaragurubaran N, Hong L, et al. Design, synthesis and X-ray structure of protein-ligand complexes: important insight into selectivity of memapsin 2 (β-secretase) inhibitors. J Am Chem Soc  2006; 128(16): 5310-1.
[http://dx.doi.org/10.1021/ja058636j] [PMID:  16620080] 
[66] 
Lawal MM, Sanusi ZK, Govender T, Maguire GEM, Honarparvar B, Kruger HG. From recognition to reaction mechanism: an overview on the interactions between HIV-1 protease and its natural targets. Curr Med Chem  2020; 27(15): 2514-49.
[http://dx.doi.org/10.2174/0929867325666181113122900] [PMID:  30421668] 
[67] 
Shimizu H, Tosaki A, Kaneko K, Hisano T, Sakurai T, Nukina N. Crystal structure of an active form of BACE1, an enzyme responsible for amyloid β protein production. Mol Cell Biol  2008; 28(11): 3663-71.
[http://dx.doi.org/10.1128/MCB.02185-07] [PMID:  18378702] 
[68] 
Andreeva NS, Rumsh LD. Analysis of crystal structures of aspartic proteinases: On the role of amino acid residues adjacent to the catalytic site of pepsin-like enzymes. Protein Sci  2001; 10(12): 2439-50.
[http://dx.doi.org/10.1110/ps.ps.25801] [PMID:  11714911] 
[69] 
Hong L, Koelsch G, Lin X, et al. Structure of the protease domain of memapsin 2 (β-secretase) complexed with inhibitor. Science  2000; 290(5489): 150-3.
[http://dx.doi.org/10.1126/science.290.5489.150] [PMID:  11021803] 
[70] 
Hong L, Turner RT III, Koelsch G, Shin D, Ghosh AK, Tang J. Crystal structure of memapsin 2 (β-secretase) in complex with an inhibitor OM00-3. Biochemistry  2002; 41(36): 10963-7.
[http://dx.doi.org/10.1021/bi026232n] [PMID:  12206667] 
[71] 
Barman A, Prabhakar R. Computational insights into substrate and site specificities, catalytic mechanism, and protonation states of the catalytic Asp dyad of β-secretaseScientifica (Cairo)2014 2014.
[http://dx.doi.org/10.1155/2014/598728] 
[72] 
James MN, Sielecki A, Salituro F, Rich DH, Hofmann T. Conformational flexibility in the active sites of aspartyl proteinases revealed by a pepstatin fragment binding to penicillopepsin. Proc Natl Acad Sci USA  1982; 79(20): 6137-41.
[http://dx.doi.org/10.1073/pnas.79.20.6137] [PMID:  6755464] 
[73] 
Simon TJ, Halford GS, Eds. Developing cognitive competence: New approaches to process modeling. Psychology Press, Taylor & Francis 2015.
[http://dx.doi.org/10.4324/9781315785271] 
[74] 
Rossner S, Ueberham U, Schliebs R, Perez-Polo JR, Bigl V. The regulation of amyloid precursor protein metabolism by cholinergic mechanisms and neurotrophin receptor signaling. Prog Neurobiol  1998; 56(5): 541-69.
[http://dx.doi.org/10.1016/S0301-0082(98)00044-6] [PMID:  9775403] 
[75] 
Crisby M, Carlson LA, Winblad B. Statins in the prevention and treatment of Alzheimer disease. Alzheimer Dis Assoc Disord  2002; 16(3): 131-6.
[http://dx.doi.org/10.1097/00002093-200207000-00001] [PMID:  12218642] 
[76] 
Haass C. Take five-BACE and the γ-secretase quartet conduct Alzheimer’s amyloid β-peptide generation. EMBO J  2004; 23(3): 483-8.
[http://dx.doi.org/10.1038/sj.emboj.7600061] [PMID:  14749724] 
[77] 
Ghosh AK, Osswald HL. BACE1 (β-secretase) inhibitors for the treatment of Alzheimer’s disease. Chem Soc Rev  2014; 43(19): 6765-813.
[http://dx.doi.org/10.1039/C3CS60460H] [PMID:  24691405] 
[78] 
Calsolaro V, Edison P. Neuroinflammation in Alzheimer’s disease: Current evidence and future directions. Alzheimers Dement  2016; 12(6): 719-32.
[http://dx.doi.org/10.1016/j.jalz.2016.02.010] [PMID:  27179961] 
[79] 
Jannis S, Dempsey W, Fredenburg R. Inside the brain: Unraveling the mystery of Alzheimer’s disease. Science  2010; 327(5968): 945.
[http://dx.doi.org/10.1126/science.327.5968.945] 
[80] 
Al-Tel TH, Semreen MH, Al-Qawasmeh RA, et al. Design, synthesis, and qualitative structure-activity evaluations of novel β-secretase inhibitors as potential Alzheimer’s drug leads. J Med Chem  2011; 54(24): 8373-85.
[http://dx.doi.org/10.1021/jm201181f] [PMID:  22044119] 
[81] 
Vassar R, Kuhn PH, Haass C, et al. Function, therapeutic potential and cell biology of BACE proteases: current status and future prospects. J Neurochem  2014; 130(1): 4-28.
[http://dx.doi.org/10.1111/jnc.12715] [PMID:  24646365] 
[82] 
Coimbra JRM, Marques DFF, Baptista SJ, et al. Highlights in BACE1 inhibitors for Alzheimer’s disease treatment. Front Chem  2018; 6: 178.
[http://dx.doi.org/10.3389/fchem.2018.00178] [PMID:  29881722] 
[83] 
Ghosh AK, Brindisi M, Tang J. Developing β-secretase inhibitors for treatment of Alzheimer’s disease. J Neurochem  2012; 120(Suppl. 1): 71-83.
[http://dx.doi.org/10.1111/j.1471-4159.2011.07476.x] [PMID:  22122681] 
[84] 
Manoharan P, Chennoju K, Ghoshal N. Computational analysis of BACE1-ligand complex crystal structures and linear discriminant analysis for identification of BACE1 inhibitors with anti P-glycoprotein binding property. J Biomol Struct Dyn  2018; 36(1): 262-76.
[http://dx.doi.org/10.1080/07391102.2016.1276477] [PMID:  28081663] 
[85] 
Yuan J, Venkatraman S, Zheng Y, McKeever BM, Dillard LW, Singh SB. Structure-based design of β-site APP cleaving enzyme 1 (BACE1) inhibitors for the treatment of Alzheimer’s disease. J Med Chem  2013; 56(11): 4156-80.
[http://dx.doi.org/10.1021/jm301659n] [PMID:  23509904] 
[86] 
Vassar R, Bennett BD, Babu-Khan S, et al. β-secretase cleavage of Alzheimer’s amyloid precursor protein by the transmembrane aspartic protease BACE. Science  1999; 286(5440): 735-41.
[http://dx.doi.org/10.1126/science.286.5440.735] [PMID:  10531052] 
[87] 
Knopman DS. Bad news and good news in AD, and how to reconcile them. Nat Rev Neurol  2019; 15(2): 61-2.
[http://dx.doi.org/10.1038/s41582-018-0131-7] [PMID:  30622292] 
[88] 
Egan MF, Kost J, Voss T, et al. Randomized trial of verubecestat for prodromal Alzheimer’s disease. N Engl J Med  2019; 380(15): 1408-20.
[http://dx.doi.org/10.1056/NEJMoa1812840] [PMID:  30970186] 
[89] 
Henley D, Raghavan N, Sperling R, Aisen P, Raman R, Romano G. Preliminary results of a trial of atabecestat in preclinical Alzheimer’s disease. N Engl J Med  2019; 380(15): 1483-5.
[http://dx.doi.org/10.1056/NEJMc1813435] [PMID:  30970197] 
[90] 
Liu L, Lauro BM, Ding L, Rovere M, Wolfe MS, Selkoe DJ. Multiple BACE1 inhibitors abnormally increase the BACE1 protein level in neurons by prolonging its half-life. Alzheimers Dement  2019; 15(9): 1183-94.
[http://dx.doi.org/10.1016/j.jalz.2019.06.3918] [PMID:  31416794] 
[91] 
Wang J, Urban L. The impact of early ADME profiling on drug discovery and development strategy. Drug Discovery World  2004; 5(4): 73-86.
[92] 
Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev  2001; 46(1-3): 3-26.
[http://dx.doi.org/10.1016/S0169-409X(00)00129-0] [PMID:  11259830] 
[93] 
Wire B. Merck announces discontinuation of APECS study evaluating verubecestat (MK-8931) for the treatment of people with prodromal Alzheimer’s disease. Business Wire 2018.
[94] 
Egan MF, Kost J, Tariot PN, et al. Randomized trial of verubecestat for mild-to-moderate Alzheimer’s disease. N Engl J Med  2018; 378(18): 1691-703.
[http://dx.doi.org/10.1056/NEJMoa1706441] [PMID:  29719179] 
[95] 
Yan R. Stepping closer to treating Alzheimer’s disease patients with BACE1 inhibitor drugs. Transl Neurodegener  2016; 5(1): 13.
[http://dx.doi.org/10.1186/s40035-016-0061-5] [PMID:  27418961] 
[96] 
Sakamoto K, Matsuki S, Matsuguma K, et al. BACE1 inhibitor lanabecestat (AZD3293) in a phase 1 study of healthy Japanese subjects: Pharmacokinetics and effects on plasma and cerebrospinal fluid Aβ peptides. J Clin Pharmacol  2017; 57(11): 1460-71.
[http://dx.doi.org/10.1002/jcph.950] [PMID:  28618005] 
[97] 
Wessels AM, Tariot PN, Zimmer JA, et al. Efficacy and safety of lanabecestat for treatment of early and mild Alzheimer disease: the AMARANTH and DAYBREAK-ALZ randomized clinical trials. JAMA Neurol  2020; 77(2): 199-209.
[http://dx.doi.org/10.1001/jamaneurol.2019.3988] [PMID:  31764959] 
[98] 
Mullard A. BACE failures lower AD expectations, again. Nat Rev Drug Discov  2018; 17(6): 385-5.
[PMID: 29844595] 
[99] 
Panza F, Lozupone M, Watling M, Imbimbo BP. Taylor & Francis.  2019.
[100] 
Agatonovic-Kustrin S, Kettle C, Morton DW. A molecular approach in drug development for Alzheimer’s disease. Biomed Pharmacother  2018; 106: 553-65.
[http://dx.doi.org/10.1016/j.biopha.2018.06.147] [PMID:  29990843] 
[101] 
Piazzi L, Cavalli A, Colizzi F, et al. Multi-target-directed coumarin derivatives: hAChE and BACE1 inhibitors as potential anti-Alzheimer compounds. Bioorg Med Chem Lett  2008; 18(1): 423-6.
[http://dx.doi.org/10.1016/j.bmcl.2007.09.100] [PMID:  17998161] 
[102] 
Cao D, Liu Z, Verwilst P, et al. Coumarin-based small-molecule fluorescent chemosensors. Chem Rev  2019; 119(18): 10403-519.
[http://dx.doi.org/10.1021/acs.chemrev.9b00145] [PMID:  31314507] 
[103] 
Wang L, Wu Y, Deng Y, et al. 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  2015; 137(7): 2695-703.
[http://dx.doi.org/10.1021/ja512751q] [PMID:  25625324] 
[104] 
Ambure P, Bhat J, Puzyn T, Roy K. Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: an in silico approach. J Biomol Struct Dyn  2019; 37(5): 1282-306.
[http://dx.doi.org/10.1080/07391102.2018.1456975] [PMID:  29578387] 
[105] 
Ion GND, Mihai DP, Lupascu G, Nitulescu GM. Application of molecular framework-based data-mining method in the search for beta-secretase 1 inhibitors through drug repurposing. J Biomol Struct Dyn  2019; 37(14): 3674-85.
[http://dx.doi.org/10.1080/07391102.2018.1526115] [PMID:  30234434] 
[106] 
Hu Y, Zhou G, Zhang C, et al. Identify compounds’ target against Alzheimer’s disease based on in-silico approach. Curr Alzheimer Res  2019; 16(3): 193-208.
[http://dx.doi.org/10.2174/1567205016666190103154855] [PMID:  30605059] 
[107] 
Gupta M, Madan AK. Detour cum distance matrix based topological descriptors for QSAR/QSPR part-II: Application in drug discovery process. Lett Drug Des Discov  2014; 11(7): 864-76.
[http://dx.doi.org/10.2174/1570180811666140401182931] 
[108] 
Adeowo FY, Lawal MM, Kumalo HM. Design and development of cholinesterase dual inhibitors towards Alzheimer’s disease treatment: A focus on recent contributions from computational and theoretical perspective. ChemistrySelect  2020; 5(44): 14136-52.
[http://dx.doi.org/10.1002/slct.202003573] 
[109] 
Zhao J, Liu X, Xia W, Zhang Y, Wang C. Targeting amyloidogenic processing of APP in Alzheimer’s disease. Front Mol Neurosci  2020; 13: 137.
[http://dx.doi.org/10.3389/fnmol.2020.00137] [PMID:  32848600] 
[110] 
Rubesova P. Protease inhibitors as chemotherapeutics. Chem Listy  2020; 114(8): 515-22.
[111] 
Mouchlis VD, Melagraki G, Zacharia LC, Afantitis A. Computer-aided drug design of β-secretase, γ-secretase and anti-tau inhibitors for the discovery of novel alzheimer’s therapeutics. Int J Mol Sci  2020; 21(3)E703
[http://dx.doi.org/10.3390/ijms21030703] [PMID:  31973122] 
[112] 
Iraji A, Khoshneviszadeh M, Firuzi O, Khoshneviszadeh M, Edraki N. Novel small molecule therapeutic agents for Alzheimer disease: Focusing on BACE1 and multi-target directed ligands. Bioorg Chem  2020; 97103649
[http://dx.doi.org/10.1016/j.bioorg.2020.103649] [PMID:  32101780] 
[113] 
Gupta SP, Patil VM. Recent studies on design and development of drugs against Alzheimer’s disease (AD) based on inhibition of BACE-1 and other AD-causative agents. Curr Top Med Chem  2020; 20(13): 1195-213.
[http://dx.doi.org/10.2174/1568026620666200416091623] [PMID:  32297584] 
[114] 
Ettcheto M, Busquets O, Espinosa-Jiménez T, Verdaguer E, Auladell C, Camins A. A chronological review of potential disease-modifying therapeutic strategies for Alzheimer’s disease. Curr Pharm Des  2020; 26(12): 1286-99.
[http://dx.doi.org/10.2174/1381612826666200211121416] [PMID:  32066356] 
[115] 
De Simone A, Naldi M, Tedesco D, Bartolini M, Davani L, Andrisano V. Advanced analytical methodologies in Alzheimer’s disease drug discovery. J Pharm Biomed Anal  2020; 178112899
[http://dx.doi.org/10.1016/j.jpba.2019.112899] [PMID:  31606562] 
[116] 
Das S, Sengupta S, Chakraborty S. Scope of β-secretase (BACE1)-targeted therapy in Alzheimer’s disease: Emphasizing the flavonoid based natural scaffold for BACE1 inhibition. ACS Chem Neurosci  2020; 11(21): 3510-22.
[http://dx.doi.org/10.1021/acschemneuro.0c00579] [PMID:  33073981] 
[117] 
Dabur M, Loureiro JA, Pereira MC. Fluorinated molecules and nanotechnology: Future ‘avengers’ against the Alzheimer’s disease? Int J Mol Sci  2020; 21(8)E2989
[http://dx.doi.org/10.3390/ijms21082989] [PMID:  32340267] 
[118] 
Wang T, Wu M-B, Lin J-P, Yang L-R. Quantitative structure-activity relationship: Promising advances in drug discovery platforms. Expert Opin Drug Discov  2015; 10(12): 1283-300.
[http://dx.doi.org/10.1517/17460441.2015.1083006] [PMID:  26358617] 
[119] 
Danishuddin, Khan AU. Descriptors and their selection methods in QSAR analysis: Paradigm for drug design. Drug Discov Today  2016; 21(8): 1291-302.
[http://dx.doi.org/10.1016/j.drudis.2016.06.013] [PMID:  27326911] 
[120] 
Tandon H, Chakraborty T, Suhag V. A concise review on the significance of QSAR in drug design. Biomol Eng  2019; 4(4): 45-51.
[121] 
Wu F, Zhou Y, Li L, et al. Computational approaches in preclinical studies on drug discovery and development. Front Chem  2020; 8: 726.
[http://dx.doi.org/10.3389/fchem.2020.00726] [PMID:  33062633] 
[122] 
Manoharan P, Vijayan RSK, Ghoshal N. Rationalizing fragment based drug discovery for BACE1: Insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies. J Comput Aided Mol Des  2010; 24(10): 843-64.
[http://dx.doi.org/10.1007/s10822-010-9378-9] [PMID:  20740315] 
[123] 
Kuhn B, Guba W, Hert J, et al. A real-world perspective on molecular design. J Med Chem  2016; 59(9): 4087-102.
[http://dx.doi.org/10.1021/acs.jmedchem.5b01875] [PMID:  26878596] 
[124] 
Monceaux CJ, Hirata-Fukae C, Lam PCH, Totrov MM, Matsuoka Y, Carlier PR. Triazole-linked reduced amide isosteres: An approach for the fragment-based drug discovery of anti-Alzheimer’s BACE1 inhibitors. Bioorg Med Chem Lett  2011; 21(13): 3992-6.
[http://dx.doi.org/10.1016/j.bmcl.2011.05.007] [PMID:  21621412] 
[125] 
Mok NY, Chadwick J, Kellett KA, et al. Discovery of biphenylacetamide-derived inhibitors of BACE1 using de novo structure-based molecular design. J Med Chem  2013; 56(5): 1843-52.
[http://dx.doi.org/10.1021/jm301127x] [PMID:  23374014] 
[126] 
Panek D, Więckowska A, Wichur T, et al. Design, synthesis and biological evaluation of new phthalimide and saccharin derivatives with alicyclic amines targeting cholinesterases, beta-secretase and amyloid beta aggregation. Eur J Med Chem  2017; 125: 676-95.
[http://dx.doi.org/10.1016/j.ejmech.2016.09.078] [PMID:  27721153] 
[127] 
Hamada Y, Tagad HD, Nishimura Y, Ishiura S, Kiso Y. Tripeptidic BACE1 inhibitors devised by in-silico conformational structure-based design. Bioorg Med Chem Lett  2012; 22(2): 1130-5.
[http://dx.doi.org/10.1016/j.bmcl.2011.11.102] [PMID:  22178553] 
[128] 
Hamada Y, Ishiura S, Kiso Y. BACE1 inhibitor peptides: Can an infinitely small k cat value turn the substrate of an enzyme into Its Inhibitor? ACS Med Chem Lett  2011; 3(3): 193-7.
[http://dx.doi.org/10.1021/ml2002373] [PMID:  24900449] 
[129] 
Wu Q, Li X, Gao Q, Wang J, Li Y, Yang L. Interaction mechanism exploration of HEA derivatives as BACE1 inhibitors by in silico analysis. Mol Biosyst  2016; 12(4): 1151-65.
[http://dx.doi.org/10.1039/C5MB00859J] [PMID:  26915506] 
[130] 
Dixon SL, Smondyrev AM, Knoll EH, Rao SN, Shaw DE, Friesner RA. PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results. J Comput Aided Mol Des  2006; 20(10-11): 647-71.
[http://dx.doi.org/10.1007/s10822-006-9087-6] [PMID:  17124629] 
[131] 
Khedkar SA, Malde AK, Coutinho EC, Srivastava S. Pharmacophore modeling in drug discovery and development: An overview. Med Chem  2007; 3(2): 187-97.
[http://dx.doi.org/10.2174/157340607780059521] [PMID:  17348856] 
[132] 
Lin X, Li X, Lin X. A review on applications of computational methods in drug screening and design. Molecules  2020; 25(6): 1375.
[http://dx.doi.org/10.3390/molecules25061375] [PMID:  32197324] 
[133] 
Kumalo HM, Soliman ME. Per-residue energy footprints-based pharmacophore modeling as an enhanced in silico approach in drug discovery: A case study on the identification of novel beta-secretase1 (BACE1) inhibitors as anti-alzheimer agents. Cell Mol Bioeng  2016; 9(1): 175-89.
[http://dx.doi.org/10.1007/s12195-015-0421-8] 
[134] 
Chakraborty S, Ramachandran B, Basu S. Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: Discovery of novel phytochemicals for BACE1 inhibition. Mol Biosyst  2014; 10(10): 2684-92.
[http://dx.doi.org/10.1039/C4MB00307A] [PMID:  25088750] 
[135] 
Suwanttananuruk P, Jiaranaikulwanitch J, Waiwut P, Vajragupta O. Lead discovery of a guanidinyl tryptophan derivative on amyloid cascade inhibition. Open Chem  2020; 18(1): 546-58.
[http://dx.doi.org/10.1515/chem-2020-0067] 
[136] 
Gupta S, Parihar D, Shah M, et al. Computational screening of promising beta-secretase 1 inhibitors through multi-step molecular docking and molecular dynamics simulations - Pharmacoinformatics approach. J Mol Struct  2020; 1205.
[http://dx.doi.org/10.1016/j.molstruc.2019.127660] 
[137] 
Kumar A, Roy S, Tripathi S, Sharma A. Molecular docking based virtual screening of natural compounds as potential BACE1 inhibitors: 3D QSAR pharmacophore mapping and molecular dynamics analysis. J Biomol Struct Dyn  2016; 34(2): 239-49.
[http://dx.doi.org/10.1080/07391102.2015.1022603] [PMID:  25707809] 
[138] 
Chakraborty S, Basu S. Multi-functional activities of citrus flavonoid narirutin in Alzheimer’s disease therapeutics: An integrated screening approach and in vitro validation. Int J Biol Macromol  2017; 103: 733-43.
[http://dx.doi.org/10.1016/j.ijbiomac.2017.05.110] [PMID:  28528948] 
[139] 
Iwaloye O, Elekofehinti OO, Momoh AI, Babatomiwa K, Ariyo EO. In silico molecular studies of natural compounds as possible anti-Alzheimer’s agents: Ligand-based design. Netw Model Anal Health Inform Bioinform  2020; 9(1): 54.
[http://dx.doi.org/10.1007/s13721-020-00262-7] 
[140] 
Joseph OA, Babatomiwa K, Niyi A, Olaposi O, Olumide I. Molecular docking and 3D Qsar studies of C000000956 as a potent inhibitor of Bace-1. Drug Res (Stuttg)  2019; 69(8): 451-7.
[http://dx.doi.org/10.1055/a-0849-9377] [PMID:  30780168] 
[141] 
Hernández-Rodríguez M, Correa-Basurto J, Martínez-Ramos F, et al. Design of multi-target compounds as AChE, BACE1, and amyloid-β(1-42) oligomerization inhibitors: in silico and in vitro studies. J Alzheimers Dis  2014; 41(4): 1073-85.
[http://dx.doi.org/10.3233/JAD-140471] [PMID:  24762947] 
[142] 
Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep  2017; 7: 42717.
[http://dx.doi.org/10.1038/srep42717] [PMID:  28256516] 
[143] 
VLS3D-CONSULTING ADMET and physchem predictions and
	related tools. Available from:. https://www.vls3d.com/index.php/links/chemoinformatics/admet
[144] 
 Computational tools for ADMET. Available from:. http://crdd. osdd.net/admet.php
[145] 
QSAR and toxicity prediction software. Available from:. http://www.saae-i.org/docs/insilico-toxicology.pdf
[146] 
Salvadores N, Sanhueza M, Manque P, Court FA. Axonal degeneration during aging and its functional role in neurodegenerative disorders. Front Neurosci  2017; 11: 451.
[http://dx.doi.org/10.3389/fnins.2017.00451] [PMID:  28928628] 
[147] 
Yu YJ, Zhang Y, Kenrick M, et al. Boosting brain uptake of a therapeutic antibody by reducing its affinity for a transcytosis target. Sci Transl Med  2011; 3(84): 84ra44-4.
[http://dx.doi.org/10.1126/scitranslmed.3002230] 
[148] 
Atwal JK, Chen Y, Chiu C, et al. A therapeutic antibody targeting BACE1 inhibits amyloid-β production in vivo. Sci Transl Med  2011; 3(84): 84ra43-3.
[http://dx.doi.org/10.1126/scitranslmed.3002254] 
[149] 
Devraj K, Poznanovic S, Spahn C, et al. BACE-1 is expressed in the blood-brain barrier endothelium and is upregulated in a murine model of Alzheimer’s disease. J Cereb Blood Flow Metab  2016; 36(7): 1281-94.
[http://dx.doi.org/10.1177/0271678X15606463] [PMID:  26661166] 
[150] 
Ruderisch N, Schlatter D, Kuglstatter A, et al. Potent and selective BACE-1 peptide inhibitors lower brain Aβ levels mediated by brain shuttle transport. EBioMedicine  2017; 24: 76-92.
[http://dx.doi.org/10.1016/j.ebiom.2017.09.004] [PMID:  28923680] 
[151] 
Al-Nadaf AH, Taha MO. Identification of small molecule memapsin inhibitors via computation-based virtual screening. Adv Pharmacol Pharma  2015; 3(3): 53-63.
[http://dx.doi.org/10.13189/app.2015.030301] 
[152] 
Khalid S, Zahid MA, Ali H, Kim YS, Khan S. Biaryl scaffold-focused virtual screening for anti-aggregatory and neuroprotective effects in Alzheimer’s disease. BMC Neurosci  2018; 19(1): 74.
[http://dx.doi.org/10.1186/s12868-018-0472-6] [PMID:  30424732] 
[153] 
Gurjar AS, Andrisano V, Simone AD, Velingkar VS. Design, synthesis, in silico and in vitro screening of 1,2,4-thiadiazole analogues as non-peptide inhibitors of beta-secretase. Bioorg Chem  2014; 57: 90-8.
[http://dx.doi.org/10.1016/j.bioorg.2014.09.002] [PMID:  25303313] 
[154] 
Lavecchia A. Machine-learning approaches in drug discovery: Methods and applications. Drug Discov Today  2015; 20(3): 318-31.
[http://dx.doi.org/10.1016/j.drudis.2014.10.012] [PMID:  25448759] 
[155] 
Coimbra JRM, Baptista SJ, Dinis TCP, et al. Combining virtual screening protocol and in vitro evaluation towards the discovery of BACE1 inhibitors. Biomolecules  2020; 10(4): 535.
[http://dx.doi.org/10.3390/biom10040535] [PMID:  32244832] 
[156] 
Rifaioglu AS, Atas H, Martin MJ, Cetin-Atalay R, Atalay V, Doğan T. Recent applications of deep learning and machine intelligence on in silico drug discovery: Methods, tools and databases. Brief Bioinform  2019; 20(5): 1878-912.
[http://dx.doi.org/10.1093/bib/bby061] [PMID:  30084866] 
[157] 
Fischer A, Sellner M, Neranjan S, Smieško M, Lill MA. Potential inhibitors for novel coronavirus protease identified by virtual screening of 606 million compounds. Int J Mol Sci  2020; 21(10): 3626.
[http://dx.doi.org/10.3390/ijms21103626] [PMID:  32455534] 
[158] 
Hospital A, Goñi JR, Orozco M, Gelpí JL. Molecular dynamics simulations: Advances and applications. Adv Appl Bioinform Chem  2015; 8: 37-47.
[PMID: 26604800] 
[159] 
Ugbaja SC, Appiah-Kubi P, Lawal MM, Gumede NS, Kumalo HM. Unravelling the molecular basis of AM-6494 high potency at BACE1 in Alzheimer’s disease: An integrated dynamic interaction investigation. J Biomol Struct Dyn  2021; 1-13.
[http://dx.doi.org/10.1080/07391102.2020.1869099] [PMID:  33410374] 
[160] 
Saravanan K, Sivanandam M, Hunday G, Mathiyalagan L, Kumaradhas P. Investigation of intermolecular interactions and stability of verubecestat in the active site of BACE1: Development of first model from QM/MM-based charge density and MD analysis. J Biomol Struct Dyn  2019; 37(9): 2339-54.
[http://dx.doi.org/10.1080/07391102.2018.1479661] [PMID:  30044206] 
[161] 
Warshel A, Levitt M. Theoretical studies of enzymic reactions: Dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozyme. J Mol Biol  1976; 103(2): 227-49.
[http://dx.doi.org/10.1016/0022-2836(76)90311-9] [PMID:  985660] 
[162] 
(a)Polymeropoulos E, Warshel A. Computer modeling of chemical reactions in enzymes and solutions.  New York: J. Wiley & Sons, Inc. 1991; p. 236.; (b)Ber Bunsenges Phys Chem  1992; 96(9): 1323-4.
[163] 
Xu D, Zheng M, Wu S. Quantum simulations of materials and biological systems.  Springer 2012; pp. 155-68.
[http://dx.doi.org/10.1007/978-94-007-4948-1_9] 
[164] 
Chung LW, Sameera WM, Ramozzi R, et al. The ONIOM method and its applications. Chem Rev  2015; 115(12): 5678-796.
[http://dx.doi.org/10.1021/cr5004419] [PMID:  25853797] 
[165] 
Svensson M, Humbel S, Froese RD, Matsubara T, Sieber S, Morokuma K. ONIOM: A multilayered integrated MO+ MM method for geometry optimizations and single point energy predictions. A test for Diels− Alder reactions and Pt (P (t-Bu) 3) 2+ H2 oxidative addition. J Phys Chem  1996; 100(50): 19357-63.
[http://dx.doi.org/10.1021/jp962071j] 
[166] 
Torrie GM, Valleau JP. Monte Carlo free energy estimates using non-Boltzmann sampling: Application to the sub-critical Lennard-Jones fluid. Chem Phys Lett  1974; 28(4): 578-81.
[http://dx.doi.org/10.1016/0009-2614(74)80109-0] 
[167] 
Kästner J. Umbrella sampling. Wiley Interdiscip Rev Comput Mol Sci  2011; 1(6): 932-42.
[http://dx.doi.org/10.1002/wcms.66] 
[168] 
Sanusi ZK, Govender T, Maguire GEM, et al. Investigation of the binding free energies of FDA approved drugs against subtype B and C-SA HIV PR: ONIOM approach. J Mol Graph Model  2017; 76: 77-85.
[http://dx.doi.org/10.1016/j.jmgm.2017.06.026] [PMID:  28711760] 
[169] 
Sanusi ZK, Govender T, Maguire GEM, et al. An insight to the molecular interactions of the FDA approved HIV PR drugs against L38L↑N↑L PR mutant. J Comput Aided Mol Des  2018; 32(3): 459-71.
[http://dx.doi.org/10.1007/s10822-018-0099-9] [PMID:  29397520] 
[170] 
Ugbaja SC, Sanusi ZK, Appiah-Kubi P, Lawal MM, Kumalo HM. Computational modelling of potent β-secretase (BACE1) inhibitors towards Alzheimer’s disease treatment. Biophys Chem  2021; 270106536
[http://dx.doi.org/10.1016/j.bpc.2020.106536] [PMID:  33387910] 
[171] 
Sanusi ZK, Lawal MM, Govender T, Maguire GEM, Honarparvar B, Kruger HG. Theoretical model for HIV-1 PR that accounts for substrate recognition and preferential cleavage of natural substrates. J Phys Chem B  2019; 123(30): 6389-400.
[http://dx.doi.org/10.1021/acs.jpcb.9b02207] [PMID:  31283878] 
[172] 
Lawal MM, Sanusi ZK, Govender T, et al. Unraveling the concerted catalytic mechanism of the human immunodeficiency virus type 1 (HIV-1) protease: A hybrid QM/MM study. Struct Chem  2019; 30(1): 409-17.
[http://dx.doi.org/10.1007/s11224-018-1251-9] 
[173] 
Sanusi ZK, Lawal MM, Gupta PL, et al. Exploring the concerted mechanistic pathway for HIV-1 PR-substrate revealed by umbrella sampling simulation. J Biomol Struct Dyn  2020; 1-12.
[http://dx.doi.org/10.1080/07391102.2020.1832578] [PMID:  33073714] 
[174] 
Sanusi ZK, Lawal MM, Govender T, et al. Concerted hydrolysis mechanism of HIV-1 natural substrate against subtypes B and C-SA PR: Insight through molecular dynamics and hybrid QM/MM studies. Phys Chem Chem Phys  2020; 22(4): 2530-9.
[http://dx.doi.org/10.1039/C9CP05639D] [PMID:  31942584] 
[175] 
Frush EH, Sekharan S, Keinan S. In silico prediction of ligand binding energies in multiple therapeutic targets and diverse ligand sets-A case study on BACE1, TYK2, HSP90, and PERK proteins. J Phys Chem B  2017; 121(34): 8142-8.
[http://dx.doi.org/10.1021/acs.jpcb.7b07224] [PMID:  28759991] 
[176] 
Pettus LH, Bourbeau MP, Bradley J, et al. Discovery of AM-6494: A potent and orally efficacious β-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitor with in vivo selectivity over BACE2. J Med Chem  2020; 63(5): 2263-81.
[http://dx.doi.org/10.1021/acs.jmedchem.9b01034] [PMID:  31589043] 
[177] 
Gutiérrez LJ, Parravicini O, Sánchez E, Rodríguez R, Cobo J, Enriz RD. New substituted aminopyrimidine derivatives as BACE1 inhibitors: In silico design, synthesis and biological assays. J Biomol Struct Dyn  2019; 37(1): 229-46.
[http://dx.doi.org/10.1080/07391102.2018.1424036] [PMID:  29301478] 
[178] 
Pai RV, Monpara JD, Vavia PR. Exploring molecular dynamics simulation to predict binding with ocular mucin: An in silico approach for screening mucoadhesive materials for ocular retentive delivery systems. J Control Release  2019; 309: 190-202.
[http://dx.doi.org/10.1016/j.jconrel.2019.07.037] [PMID:  31356839] 
[179] 
Stuyver T, Danovich D, Joy J, Shaik S. External electric field effects on chemical structure and reactivity. WIREs Computational Molecular Science  2020; 10(2)e1438
[http://dx.doi.org/10.1002/wcms.1438] 
[180] 
Gutiérrez M, Vallejos GA, Cortés MP, Bustos C. Bennett acceptance ratio method to calculate the binding free energy of BACE1 inhibitors: Theoretical model and design of new ligands of the enzyme. Chem Biol Drug Des  2019; 93(6): 1117-28.
[http://dx.doi.org/10.1111/cbdd.13456] [PMID:  30693676] 
[181] 
Keränen H, Pérez-Benito L, Ciordia M, et al. Acylguanidine beta secretase 1 inhibitors: A combined experimental and free energy perturbation study. J Chem Theory Comput  2017; 13(3): 1439-53.
[http://dx.doi.org/10.1021/acs.jctc.6b01141] [PMID:  28103438] 
[182] 
Malamas MS, Erdei J, Gunawan I, et al. Design and synthesis of 5,5′-disubstituted aminohydantoins as potent and selective human β-secretase (BACE1) inhibitors. J Med Chem  2010; 53(3): 1146-58.
[http://dx.doi.org/10.1021/jm901414e] [PMID:  19968289] 
[183] 
Mandal M, Zhu Z, Cumming JN, et al. Design and validation of bicyclic iminopyrimidinones as beta amyloid cleaving enzyme-1 (BACE1) inhibitors: Conformational constraint to favor a bioactive conformation. J Med Chem  2012; 55(21): 9331-45.
[http://dx.doi.org/10.1021/jm301039c] [PMID:  22989333] 
[184] 
Stamford AW, Scott JD, Li SW, et al. Discovery of an orally available, brain penetrant BACE1 inhibitor that affords robust CNS Aβ reduction. ACS Med Chem Lett  2012; 3(11): 897-902.
[http://dx.doi.org/10.1021/ml3001165] [PMID:  23412139] 
[185] 
Jiaranaikulwanitch J, Govitrapong P, Fokin VV, Vajragupta O. From BACE1 inhibitor to multifunctionality of tryptoline and tryptamine triazole derivatives for Alzheimer’s disease. Molecules  2012; 17(7): 8312-33.
[http://dx.doi.org/10.3390/molecules17078312] [PMID:  22781443] 
[186] 
Huang HJ, Lee CC, Chen CYC. In silico design of BACE1 inhibitor for Alzheimer ' s disease by traditional chinese medicine. BioMed Res Int  2014; 2014741703
[187] 
Wu Y-J, Guernon J, Yang F, et al. Targeting the BACE1 active site flap leads to a potent inhibitor that elicits robust brain Aβ reduction in rodents. ACS Med Chem Lett  2016; 7(3): 271-6.
[http://dx.doi.org/10.1021/acsmedchemlett.5b00432] [PMID:  26985314] 
[188] 
Azimi S, Zonouzi A, Firuzi O, et al. Discovery of imidazopyridines containing isoindoline-1,3-dione framework as a new class of BACE1 inhibitors: Design, synthesis and SAR analysis. Eur J Med Chem  2017; 138: 729-37.
[http://dx.doi.org/10.1016/j.ejmech.2017.06.040] [PMID:  28728105] 
[189] 
Guix FX, Sartório CL, Ill-Raga G. BACE1 translation: At the crossroads between Alzheimer’s disease neurodegeneration and memory consolidation. J Alzheimers Dis Rep  2019; 3(1): 113-48.
[http://dx.doi.org/10.3233/ADR-180089] [PMID:  31259308] 
[190] 
Zhu Z, Schuster DI, Tuckerman ME. Molecular dynamics study of the connection between flap closing and binding of fullerene-based inhibitors of the HIV-1 protease. Biochemistry  2003; 42(5): 1326-33.
[http://dx.doi.org/10.1021/bi020496s] [PMID:  12564936] 
[191] 
Hornak V, Okur A, Rizzo RC, Simmerling C. HIV-1 protease flaps spontaneously open and reclose in molecular dynamics simulations. Proc Natl Acad Sci USA  2006; 103(4): 915-20.
[http://dx.doi.org/10.1073/pnas.0508452103] [PMID:  16418268] 
[192] 
Tozzini V, Trylska J, Chang CE, McCammon JA. Flap opening dynamics in HIV-1 protease explored with a coarse-grained model. J Struct Biol  2007; 157(3): 606-15.
[http://dx.doi.org/10.1016/j.jsb.2006.08.005] [PMID:  17029846] 
[193] 
Heaslet H, Rosenfeld R, Giffin M, et al. Conformational flexibility in the flap domains of ligand-free HIV protease. Acta Crystallogr D Biol Crystallogr  2007; 63(Pt 8): 866-75.
[http://dx.doi.org/10.1107/S0907444907029125] [PMID:  17642513] 
[194] 
Kumalo HM, Soliman ME. A comparative molecular dynamics study on BACE1 and BACE2 flap flexibility. J Recept Signal Transduct Res  2016; 36(5): 505-14.
[http://dx.doi.org/10.3109/10799893.2015.1130058] [PMID:  26804314] 
[195] 
Brauer DJ, Schenk S, Roßenbach S, et al. Water soluble phosphines: Part XIII. Chiral phosphine ligands with amino acid moieties. J Organomet Chem  2000; 598(1): 116-26.
[http://dx.doi.org/10.1016/S0022-328X(99)00689-0] 
[196] 
Butini S, Brogi S, Novellino E, et al. The structural evolution of β-secretase inhibitors: a focus on the development of small-molecule inhibitors. Curr Top Med Chem  2013; 13(15): 1787-807.
[http://dx.doi.org/10.2174/15680266113139990137] [PMID:  23931442] 
[197] 
Ghosh AK, Shin D, Downs D, et al. Design of potent inhibitors for human brain memapsin 2 (β-secretase). J Am Chem Soc  2000; 122(14): 3522-3.
[http://dx.doi.org/10.1021/ja000300g] [PMID:  30443047] 
[198] 
Li D, Liu MS, Ji B, Hwang KC, Huang Y. Identifying the molecular mechanics and binding dynamics characteristics of potent inhibitors to HIV-1 protease. Chem Biol Drug Des  2012; 80(3): 440-54.
[http://dx.doi.org/10.1111/j.1747-0285.2012.01417.x] [PMID:  22621379] 
[199] 
Blass B. Cyclopropyl-fused 1, 3-thiazepines as BACE1 and BACE2 inhibitors.  ACS Publications 2013; pp. 379-80.
[200] 
Thomas AA, Hunt KW, Newhouse B, et al. 8-Tetrahydropyran-2-yl chromans: Highly selective beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitors. J Med Chem  2014; 57(23): 10112-29.
[http://dx.doi.org/10.1021/jm5015132] [PMID:  25411915] 
[201] 
Hernández-Rodríguez M, Correa-Basurto J, Gutiérrez A, Vitorica J, Rosales-Hernández MC. Asp32 and Asp228 determine the selective inhibition of BACE1 as shown by docking and molecular dynamics simulations. Eur J Med Chem  2016; 124: 1142-54.
[http://dx.doi.org/10.1016/j.ejmech.2016.08.028] [PMID:  27639619] 
[202] 
Johansson P, Kaspersson K, Gurrell IK, et al. Toward β-secretase-1 inhibitors with improved isoform selectivity. J Med Chem  2018; 61(8): 3491-502.
[http://dx.doi.org/10.1021/acs.jmedchem.7b01716] [PMID:  29617572] 
[203] 
Sabbah DA, Zhong HA. Modeling the protonation states of β-secretase binding pocket by molecular dynamics simulations and docking studies. J Mol Graph Model  2016; 68: 206-15.
[http://dx.doi.org/10.1016/j.jmgm.2016.07.005] [PMID:  27474865] 
[204] 
Nepovimova E, Kuca K. Neurodegenerative diseases-molecular mechanisms and current therapeutic approaches. IntechOpen 2020.
[205] 
Youn K, Lee J, Yun EY, et al. Biological evaluation and in silico docking study of γ-linolenic acid as a potential BACE1 inhibitor. J Funct Foods  2014; 10: 187-91.
[http://dx.doi.org/10.1016/j.jff.2014.06.005] 
[206] 
Wang W, Liu Y, Lazarus RA. Allosteric inhibition of BACE1 by an exosite-binding antibody. Curr Opin Struct Biol  2013; 23(6): 797-805.
[http://dx.doi.org/10.1016/j.sbi.2013.08.001] [PMID:  23998983] 
[207] 
Kornacker MG, Copeland RA, Hendrick J, et al. Beta secretase exosite binding peptides and methods for identifying beta secretase modulators Patent No US20040121412A1 2008.
[208] 
Gutierrez LJ, Enriz RD, Baldoni HA. Structural and thermodynamic characteristics of the exosite binding pocket on the human BACE1: a molecular modeling approach. J Phys Chem A  2010; 114(37): 10261-9.
[http://dx.doi.org/10.1021/jp104983a] [PMID:  20806954] 
[209] 
Gutiérrez LJ, Andujar SA, Enriz RD, Baldoni HA. Structural and functional insights into the anti-BACE1 Fab fragment that recognizes the BACE1 exosite. J Biomol Struct Dyn  2014; 32(9): 1421-33.
[http://dx.doi.org/10.1080/07391102.2013.821024] [PMID:  23879547] 
[210] 
Campagna J, Vadivel K, Jagodzinska B, et al. Evaluation of an allosteric BACE inhibitor peptide to identify mimetics that can interact with the loop F region of the enzyme and prevent APP cleavage. J Mol Biol  2018; 430(11): 1566-76.
[http://dx.doi.org/10.1016/j.jmb.2018.04.002] [PMID:  29649434] 
[211] 
Gutierrez LJ, Angelina E, Gyebrovszki A, et al. New small-size peptides modulators of the exosite of BACE1 obtained from a structure-based design. J Biomol Struct Dyn  2017; 35(2): 413-26.
[http://dx.doi.org/10.1080/07391102.2016.1145143] [PMID:  26813690] 
[212] 
Ugbaja SC, Lawal MM, Kumalo HM. An overview of β-amyloid cleaving enzyme 1 (BACE1) in alzheimer’s disease therapy elucidating its exosite-binding antibody and allosteric inhibitor. Curr Med Chem  2022; 29(1): 114-35.
[http://dx.doi.org/10.2174/0929867328666210608145357] 
Rights & Permissions Print Cite
Article Metrics
29
1
Journal Information
For Authors
For Editors
For Reviewers
Explore Articles
Open Access
Open Access Articles
For Visitors
DOI https://dx.doi.org/10.2174/1389450122666210809100050	Print ISSN 1389-4501
Publisher Name Bentham Science Publisher	Online ISSN 1873-5592
Current Drug Targets

Alzheimer's Disease and β-secretase Inhibition: An Update with a Focus on Computer-aided Inhibitor Design

Abstract Play Pause

Graphical Abstract

Related Journals

Related Books

Abstract
