Identification of anti-cancer natural compounds against colchicine binding site of tubulin: a combined structure and QSAR-based approach

ABSTRACT Microtubules, investigated extensively in past few decades as a potential pharmaceutical target for cancer treatment, because of their important role in the mitotic process. However, agents that target microtubules frequently have limitations on the development of resistance. Microtubules, αβ-tubulin dimers have mainly four different interaction sites, including the colchicine binding site, a potential target for establishing new tubulin inhibitors. Numerous drugs in this domain are less likely to develop multidrug resistance, which limits the effectiveness of several inhibitors. In this study a virtual screening strategy was used with structure-based followed by QSAR model-based screening. First, a docking-based approach used to select high interacting compounds from the natural compound database, thereafter a QSAR model, built using literature data on anticancer activity of heterogeneous compounds used to screen the molecules from zinc natural databases. Following that, Lipinski's rule of five was used to filter the resulting hit compounds. The ADMET and DFT-based analyses were done to refine the retrieved hits and reduce the rate of false positives. Finally, molecular dynamics simulation and MMPBSA were performed to check the stability of selected leads with tubulin.

[1]  A. Olğaç,et al.  Novel Indole-Pyrazole Hybrids as Potential Tubulin-Targeting Agents; Synthesis, antiproliferative evaluation, and molecular modeling studies. , 2023, Journal of molecular structure.

[2]  M. Hawash Recent Advances of Tubulin Inhibitors Targeting the Colchicine Binding Site for Cancer Therapy , 2022, Biomolecules.

[3]  I. Banerjee,et al.  Molecular dynamics simulations, docking and MMGBSA studies of newly designed peptide-conjugated glucosyloxy stilbene derivatives with tumor cell receptors , 2022, Molecular Diversity.

[4]  A. Olğaç,et al.  Design and Synthesis of Novel Substituted Indole-acrylamide Derivatives and Evaluation of Their Anti-Cancer Activity as Potential Tubulin-Targeting Agents , 2022, Journal of Molecular Structure.

[5]  Guilherme Martins Silva,et al.  Potential colchicine binding site inhibitors unraveled by virtual screening, molecular dynamics and MM/PBSA , 2021, Comput. Biol. Medicine.

[6]  Aiping Lu,et al.  ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties , 2021, Nucleic Acids Res..

[7]  A. A. Al-karmalawy,et al.  Revisiting Activity of Some Nocodazole Analogues as a Potential Anticancer Drugs Using Molecular Docking and DFT Calculations , 2021, Frontiers in Chemistry.

[8]  A. Shiroudi,et al.  Theoretical investigations on the HOMO–LUMO gap and global reactivity descriptor studies, natural bond orbital, and nucleus-independent chemical shifts analyses of 3-phenylbenzo[d]thiazole-2(3H)-imine and its para-substituted derivatives: Solvent and substituent effects , 2021 .

[9]  Daiying Zuo,et al.  MAY, a novel tubulin inhibitor, induces cell apoptosis in A549 and A549/Taxol cells and inhibits epithelial-mesenchymal transition in A549/Taxol cells. , 2020, Chemico-biological interactions.

[10]  N. O’Boyle,et al.  Colchicine-Binding Site Inhibitors from Chemistry to Clinic: A Review , 2020, Pharmaceuticals.

[11]  Denis Fourches,et al.  Inductive transfer learning for molecular activity prediction: Next-Gen QSAR Models with MolPMoFiT , 2019, Journal of Cheminformatics.

[12]  Yang Jiao,et al.  Identification of novel and potent small-molecule inhibitors of tubulin with antitumor activities by virtual screening and biological evaluations , 2019, J. Comput. Aided Mol. Des..

[13]  D. Arthur,et al.  A Derived QSAR Model for Predicting Some Compounds as Potent Antagonist against Mycobacterium tuberculosis: A Theoretical Approach , 2019, Advances in preventive medicine.

[14]  S. Patel,et al.  The Role of Colchicine in Acute Coronary Syndromes. , 2019, Clinical therapeutics.

[15]  Madhuri Pola,et al.  In silico modelling and molecular dynamics simulation studies on L-Asparaginase isolated from bacterial endophyte of Ocimum tenuiflorum. , 2018, Enzyme and microbial technology.

[16]  E. Márquez,et al.  Molecular modeling studies of bromopyrrole alkaloids as potential antimalarial compounds: a DFT approach , 2018, Medicinal Chemistry Research.

[17]  D. Sackett,et al.  Colchicine: an ancient drug with novel applications , 2018, The British journal of dermatology.

[18]  Abdullah M. Asiri,et al.  Podophyllotoxin derivatives as an excellent anticancer aspirant for future chemotherapy: A key current imminent needs. , 2018, Bioorganic & medicinal chemistry.

[19]  Ke Li,et al.  Design, synthesis and biological evaluation of 2-phenylquinoline-4-carboxamide derivatives as a new class of tubulin polymerization inhibitors. , 2017, Bioorganic & medicinal chemistry.

[20]  Daiying Zuo,et al.  BZML, a novel colchicine binding site inhibitor, overcomes multidrug resistance in A549/Taxol cells by inhibiting P-gp function and inducing mitotic catastrophe. , 2017, Cancer letters.

[21]  Ritu Jain,et al.  GQSAR modeling and combinatorial library generation of 4-phenylquinazoline-2-carboxamide derivatives as antiproliferative agents in human Glioblastoma tumors , 2017, Comput. Biol. Chem..

[22]  A. Eastman,et al.  Microtubule destabilising agents: far more than just antimitotic anticancer drugs , 2017, British journal of clinical pharmacology.

[23]  M. M. Rizvi,et al.  Pharmacophore modeling, 3D-QSAR, docking study and ADME prediction of acyl 1,3,4-thiadiazole amides and sulfonamides as antitubulin agents , 2016 .

[24]  Y. Zhen,et al.  A Novel Nitrobenzoate Microtubule Inhibitor that Overcomes Multidrug Resistance Exhibits Antitumor Activity , 2016, Scientific Reports.

[25]  B. Gigant,et al.  Structures of a diverse set of colchicine binding site inhibitors in complex with tubulin provide a rationale for drug discovery , 2016, The FEBS journal.

[26]  Ya-Juan Qin,et al.  Combined Molecular Docking, 3D‐QSAR, and Pharmacophore Model: Design of Novel Tubulin Polymerization Inhibitors by Binding to Colchicine‐binding Site , 2015, Chemical biology & drug design.

[27]  Berk Hess,et al.  GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers , 2015 .

[28]  Duane D. Miller,et al.  Structural Optimization of Indole Derivatives Acting at Colchicine Binding Site as Potential Anticancer Agents. , 2015, ACS medicinal chemistry letters.

[29]  Supratik Kar,et al.  On a simple approach for determining applicability domain of QSAR models , 2015 .

[30]  David A. Winkler,et al.  Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models , 2015, J. Chem. Inf. Model..

[31]  Jigar A. Makawana,et al.  Discovery and molecular modeling of novel 1-indolyl acetate--5-nitroimidazole targeting tubulin polymerization as antiproliferative agents. , 2014, European journal of medicinal chemistry.

[32]  Rajendra Kumar,et al.  g_mmpbsa - A GROMACS Tool for High-Throughput MM-PBSA Calculations , 2014, J. Chem. Inf. Model..

[33]  K. Rohini,et al.  Molecular Dynamics Simulations and Principal Component Analysis on Human Laforin Mutation W32G and W32G/K87A , 2014, The Protein Journal.

[34]  J. Dhanjal,et al.  Mechanistic insights into mode of action of novel natural cathepsin L inhibitors , 2013, BMC Genomics.

[35]  Xiao‐Feng Wang,et al.  N-aryl-6-methoxy-1,2,3,4-tetrahydroquinolines: a novel class of antitumor agents targeting the colchicine site on tubulin. , 2013, European journal of medicinal chemistry.

[36]  J. Díaz,et al.  The binding sites of microtubule-stabilizing agents. , 2013, Chemistry & biology.

[37]  P. R. Sharma,et al.  Novel indole-bearing combretastatin analogues as tubulin polymerization inhibitors , 2013, Organic and medicinal chemistry letters.

[38]  Duane D. Miller,et al.  An Overview of Tubulin Inhibitors That Interact with the Colchicine Binding Site , 2012, Pharmaceutical Research.

[39]  Maria Kavallaris,et al.  Microtubules and resistance to tubulin-binding agents , 2010, Nature Reviews Cancer.

[40]  R. Boggia,et al.  Genetic algorithms as a strategy for feature selection , 1992 .

[41]  K. Ojha Development of predictive in silico cytotoxic activity model to predict the cytotoxicity of a diverse set of colchicine binding site inhibitors , 2022, Eurasian Journal of Medicine and Oncology.

[42]  Chaoyang Zhang,et al.  A Review of Feature Reduction Methods for QSAR-Based Toxicity Prediction , 2019, Challenges and Advances in Computational Chemistry and Physics.

[43]  S. Emami,et al.  New thiazole-2(3H)-thiones containing 4-(3,4,5-trimethoxyphenyl) moiety as anticancer agents. , 2019, European journal of medicinal chemistry.

[44]  Duane D. Miller,et al.  A Potent, Metabolically Stable Tubulin Inhibitor Targets the Colchicine Binding Site and Overcomes Taxane Resistance. , 2018, Cancer research.

[45]  S. Ahmadi,et al.  QSAR Modeling of the Arylthioindole Class of Colchicine Polymerization Inhibitors as Anticancer Agents. , 2017, Current computer-aided drug design.

[46]  E. Nogales Structural insights into microtubule function. , 2000, Annual review of biochemistry.