Molecular Modeling Studies of Triazolyl Thiophenes As CDK5/P25 inhHibitors Using 3D-QSAR and Molecular Docking

Document Type : Original research article


1 Chemistry Department, Faculty of Science, Shahid Bahonar University of Kerman, Kerman, Iran

2 MAPNA Group Operation and Maintenance, North Mosaddeq St., Mirdamad Blvd., Tehran, Iran



Three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques are useful methods for ligand-based drug design by correlating physicochemical descriptors from a set of related compounds to their known molecular activity or molecular property values. A novel clubbed triazolyl thiophene series of cdk5/p25 inhibitors were selected to establish 3D-QSAR models using Comparative molecular field analysis (CoMFA) and Comparative molecular similarity indices analysis (CoMSIA) methods. The optimum CoMFA and CoMSIA models obtained, were statistically significant with cross-validated correlation coefficients r2cv (q2) of 0.539 and 0.558, and conventional correlation coefficients (r2) of 0.980 and 0.967, respectively. A training set containing 88 molecules and a test set containing 24 molecules served to establish the QSAR models. Independent test set validated the external predictive power of both models with predicted correlation coefficients (r2pred) 0.968 and 0.945 for CoMFA and CoMSIA, respectively. Molecular docking was applied to explore the binding mode between the ligand and the receptor. The information obtained from molecular modeling studies may be helpful to design novel CDK5/P25 inhibitors with desired activity.


[1]     M.W. Bondi, E.C. Edmonds and D.P. Salmon, Alzheimer’s Disease: Past, Present, and Future, J. Int. Neuropsychol. Soc.23 (2017) 818-831.
[2]     R.U. Haque and  A.I. Levey, Alzheimer’s disease: A clinical perspective and future nonhuman primate research opportunities, PNAS  116 (2019) 26224-26229.
[3]     D.J. Selkoe, Alzheimer ’s disease: genes, proteins and therapy, Physiol. Rev. 81 (2001) 741–766.
[4]     J. Park, J. Seo J. Won H. Yeo and Y. Ahn, Abnormal Mitochondria in a Non-human Primate Model of MPTP-induced Parkinson’s Disease: Drp1 and CDK5/p25 Signaling. Exp Neurobiol 28 (2019) 414–424.
[5]     K. Pozo and J.A. Bibb, The Emerging Role of Cdk5 in Cancer. Trends Cancer 10 (2016) 606–618.
[6]     J. Seo, O. Kritskiy, L.A. Watson, S.J. Barker, D. Dey, W.K. Raja, Y.T. Lin, T. Ko, S. Cho, J. Penney, M.C. Silva, S.D. Sheridan, D. Lucente and J.F. Gusella, Inhibition of p25/Cdk5 Attenuates Tauopathy in Mouse and iPSC Models of Frontotemporal Dementia. J. Neurosci. 37 (2017) 9917–9924.
[7]     Y.L. Zheng, N.D. Amin, Y.F. Hu, P. Rudrabhatla, V. Shukla, J. Kanungo, S. Kesavapany, P. Grant, W. Albers and H.C. Pant,  A 24-residue peptide (p5), derived from p35, the Cdk5 neuronal activator, specifically inhibits Cdk5-p25 hyperactivity and tau hyperphosphorylation. J. Biol. Chem. 285 (2010) 34202–34212.
[8]     M. KolarovaF. García-SierraA. BartosJ. Ricny and D. Ripova, Structure and pathology of tau protein in Alzheimer disease, Int. J. Alzheimers Dis.  2012  (2012) 731526.
[9]     J. Herzog, S.M. Ehrlich, L. Pfitzer, J. Liebl, T. Frohlich, G.J. Arnold, W. Mikulits, C. Haider, A.M. Vollmar and S. Zahler, Cyclin-dependent kinase 5 stabilizes hypoxia-inducible factor-1alpha: a novel approach for inhibiting angiogenesis in hepatocellular carcinoma. Oncotarget. 7 (2016) 27108-27121.
[10]            J.H. Christopher, A.S. Mark and B.C. Christopher, Discovery and SAR of 2-ami-nothiazole inhibitors of CDK5/p25 as a potential treatment for Alzheimer’s disease, Bioorg. Med. Chem. Lett. 14 (2004) 5521-5525.
[11] M. Tadayon and Z. Garkani-Nejad, In silico study combining QSAR,  docking and molecular dynamics simulation on 2,4- disubstituted pyridopyrimidine derivatives, J. Recept. Signal Trans. 39:2 (2019) 167-174.
[12] H. Safarizadeh and Z. Garkani-Nejad, Molecular docking, molecular dynamics simulations and QSAR studies on some of 2-arylethenylquinoline derivatives for inhibition of Alzheimer's amyloid-beta aggregation: Insight into mechanism of interactions and parameters for design of new inhibitors, J. Mol. Graph. Model. 87 (2019) 129-143.
[13] M. Shiradkar, J. Thomas, V. Kanase and R. Dighe, Studying Synergism of Methyl Linked Cyclohexyl Thiophenes with Triazole: Synthesis and Their Cdk5/P25 Inhibition Activity, Eur. J. Med. Chem. 46 (2011)2066-2074.
[14] SYBYL package, Tripos Inc.: St. Louis, MO, USA, (2006), Available online:
[15] D.M. Chhatbar, U.J. Chaube, V.K. Vyas and H.G. Bhatt, CoMFA, CoMSIA, Topomer CoMFA, HQSAR, molecular docking and molecular dynamics simulations study of triazine morpholino derivatives as mTOR inhibitors for the treatment of breast cancer, Comp. Bio. Chem. 80 (2019) 351–363.
[16] A. Khaldan, K.E. khatabi, R. El-Mernissi, A. Ghaleb, R. Hmamouchi, A. Sbai, M. Bouachrine and T. Lakhlifi, 3D-QSAR Modeling and Molecular Docking Studies of novel triazoles-quinine derivatives as antimalarial agents, J. Mater. Environ. Sci. 11 (2020) 429-443.
[17] J. Sun, S. Cai, N. Yan and H. Mei, Docking and 3D-QSAR studies of influenza neuraminidase inhibitors using three-dimensional holographic vector of atomic interaction field analysis, Eur. J. Med. Chem. 45 (2010) 1008–1014.
[18] J. Zhu, Q. Yu, Y. Cai, Y. Chen, H. Liu, W. Liang and J. Jin, Theoretical Exploring Selective-Binding Mechanisms of JAK3 by 3D-QSAR, Molecular Dynamics Simulation and Free Energy Calculation. Front. Mol. Biosci. 7 (2020) 1-12.
[19] Z.Q. Yang and P.H. Sun, 3D-QSAR Study of Potent Inhibitors of Phosphodiesterase-4 Using a CoMFA Approach, Int. J. Mol. Sci. 8 (2007)714–722.
[20] Q.L. Song, P.H. Sun and W.M. Chen, Exploring 3D-QSAR for Ketolide Derivatives as Antibacterial Agents Using CoMFA and CoMSIA, Lett. Drug Des. Discov. 7 (2010) 149–159.