[1] G. A. Heinzl, W. Huang, W. Yu, B. J. Giardina, Y. Zhou, Jr., A. D. MacKerell, A. Wilks, F. Xue, Iminoguanidines as Allosteric Inhibitors of the Iron-Regulated Heme Oxygenase (HemO) of Pseudomonas aeruginosa.
Journal of Medicinal Chemistry, 59 (2016) 6929-6942.
https://doi.org/10.1021/acs.jmedchem.6b00757[2] E. I. Edache, A. Uzairu, P. A. Mamza, G. A. Shallangwa, A 2D-QSAR, Homology Modeling, Docking, ADMET, and Molecular Dynamics Simulations Studies for Assessment of a Novel SARS-Cov-2 and Pseudomonas Aeruginosa Inhibitors.
Journal of Virology and Viral Diseases, 2 (2022) 1-28.
https://doi.org/10.54289/JVVD2200106.
[3] E. I. Edache, A. Uzairu, P. A. Mamza, G. A. Shallangwa, QSAR, homology modeling, and docking simulation on SARS‑CoV‑2 and pseudomonas aeruginosa inhibitors, ADMET, and molecular dynamic simulations to find a possible oral lead candidate.
Journal of Genetic Engineering and Biotechnology, 20 (2022) 88.DOI:
https://doi.org/10.1186/s43141-022-00362-z.
[4] R. Custelcean, Iminoguanidines: from anion recognition and separation to carbon capture.
Chemical Communications, 56 (2020) 10272-10280.
https://doi.org/10.1039/D0CC04332J.
[5] Q. Zhang, Y. Jiang, Y. Li, X. Song, X. Luo, Z. Ke, Y. Zou, Design, synthesis, and physicochemical study of a biomass-derived CO2 sorbent 2,5-furan-bis(iminoguanidine).
iScience, 24 (2021) 102263.
https://doi.org/10.1016/j.isci.2021.102263.
[6] E. I. Edache, A. Uzairu, P. A. Mamza, G. A. Shallangwa, A comparative QSAR analysis, 3D-QSAR, molecular docking and molecular design of iminoguanidine-based inhibitors of HemO: A rational approach to antibacterial drug design.
Journal of Drugs and Pharmaceutical Science, 4 (2020) 21-36.
https://doi.org/10.31248/JDPS2020.036.
[7] E. I. Edache, A. Uzairu, P. A. Mamza, G. A. Shallangwa, Theoretical Investigation of the Cooperation of Iminoguanidine with the Enzymes-Binding Domain of Covid-19 and Bacterial Lysozyme Inhibitors and their Pharmacokinetic Properties.
Journal of Mexican Chemical Society, 66 (2022), 513-542.
http://dx.doi.org/10.29356/jmcs.v66i4.1726.
[8] A. D. Becke, Density‐functional thermochemistry. III. The role of exact exchange.
The Journal of Chemical Physics, 98 (1993) 5648-5652.
https://doi.org/10.1063/1.464913.
[9] C. Lee, W. Yang, R. G. Parr, Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density.
Physical Review B, 37 (1988) 785-789.
https://doi.org/10.1103/physrevb.37.785.
[10] G. A. Petersson, A. Bennett, T. G. Tensfeldt, M. A. Al‐Laham, W. A. Shirley, A complete basis set model chemistry. I. The total energies of closed‐shell atoms and hydrides of the first‐row elements.
The Journal of Chemical Physics, 89 (1988) 2193-2218.
https://doi.org/10.1063/1.455064.
[11] M.J. Frisch, G.W. Trucks, H.B. Schlegel, G.E. Scuseria, M.A. Robb, J.R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G.A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H.P. Hratchian, A.F. Izmaylov, J. Bloino, G. Zheng, J.L. Sonnenberg, M. Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, T. Vreven, J.A. Montgomery, J.E. Peralta, F. Ogliaro, M. Bearpark, J.J. Heyd, E. Brothers, K.N. Kudin, V.N. Staroverov, R. Kobayashi, J. Normand, K. Raghavachari, A. Rendell, J.C. Burant, S.S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J.M. Millam, M. Klene, J.E. Knox, J.B. Cross, V. Bakken, C. Adamo, J. Aramillo, R. Gomperts, R.E. Stratmann, O. Yazyev, A.J. Austin, R. Cammi, C. Pomelli, J.W. Ochterski, R.L. Martin, K. Morokuma, V.G. Zakrzewski, G.A. Voth, P. Salvador, J.J. Dannenberg, S. Dapprich, A.D. Daniels, J.B. Farkas, J.V. Foresman, J. Ortiz, D.J. Cioslowski, Gaussian 09, Revision E. 01, Gaussian, Inc., 2013, Wallingford CT.
[13] M. F. Sanner, Python: a programming language for software integration and development. Journal of molecular graphics & modelling, 17 (1999) 57–61.
[14] J. C. Phillips, D. J. H. Julio D. C. Maia, J. E. Stone, J. V. Ribeiro, R. C. Bernardi, R. Buch, G. Fiorin, J. Henin, W. Jiang, R. McGreevy, M. C. R. Melo, B. K. Radak, R. D. Skeel, A. Singharoy, Y. Wang, B. Roux, A. Aksimentiev, Z. Luthey-Schulten, L. V. Kale, K. Schulten, C. Chipot, E. Tajkhorshid, Scalable molecular dynamics on CPU and GPU architectures with NAMD.
Journal of Chemical Physics, 153 (2020) 044130;
https://doi.org/044110.041063/044135.0014475.
[15] J. Lee, X. Cheng, J. M. Swails, M. S. Yeom, P. K. Eastman, J. A. Lemkul, S. Wei, J. Buckner, J. C. Jeong, Y. Qi, S. Jo, V. S. Pande, D. A. Case, C. L. Brooks, A. D. MacKerell, Jr, J. B. Klauda, W. Im, CHARMMGUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field.
Journal of Chemical Theory and Computation, 12 (2016) 405–413.
https://doi.org/10.1021/acs.jctc.5b00935.
[17] E. Wang, H. Sun, J. Wang, Z. Wang, H. Liu, J. Z. H. Zhang, T. Hou, End-point binding free energy calculation with MM/PBSA and MM/GBSA: strategies and applications in drug design.
Chemical Reviews, 119 (2019) 9478–9508.
https://doi.org/10.1021/acs.chemrev.9b00055.
[18] Q. Bai, S. Tan, T. Xu, H. Liu, J. Huang, X. Yao, MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm.
Briefings in Bioinformatics, 22 (2021) bbaa161.
https://doi.org/10.1093/bib/bbaa161.
[19] R. D. Jawarkar, R. L. Bakal, N. Mukherjee, A. Ghosh, M. E. A. Zaki, S. A. AL-Hussain, A. A. Al-Mutairi, A. Samad, A. Gandhi, V. H. Masand, QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA.
Molecules, 27 (2022) 4758.
https://doi.org/10.3390/molecules27154758.
[20] F. A. Ugbe, G. A. Shallangwa, A. Uzairu, I. Abdulkadir, Activity modeling, molecular docking and pharmacokinetic studies of some boron-pleuromutilins as anti-wolbachia agents with potential for treatment of filarial diseases.
Chemical Data Collections, 36 (2021) 100783.
https://doi.org/10.1016/j.cdc.2021.100783.
[21] C. A. Lipinski, F. Lombardo, B. W. Dominy, P. J. Feeney, Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings.
Advanced Drug Delivery Reviews, 46 (2001) 3–26.
https://doi.org/10.1016/s0169-409x(00)00129-0.
[22] J. D. Hughes, J. Blagg, D. A. Price, S. Bailey, G. A. Decrescenzo, R. V. Devraj, E. Ellsworth, Y. M. Fobian, M. E. Gibbs, R. W. Gilles, N. Greene, E. Huang, T. Krieger-Burke, J. Loesel, T. Wager, L. Whiteley, Y. Zhang, Physiochemical drug properties associated with in vivo toxicological outcomes.
Bioorganic & medicinal chemistry letters, 18 (2008) 4872–4875.
https://doi.org/10.1016/j.bmcl.2008.07.071.
[23] Gleeson, M.P. Generation of a set of simple, interpretable ADMET rules of thumb.
Journal of Medicinal Chemistry, 51(2008) 817–834.
https://doi.org/10.1021/jm701122q.
[24] T. W. Johnson, K. R. Dress, M. Edwards, Using the Golden Triangle to optimize clearance and oral absorption.
Bioorganic & medicinal chemistry letters, 19 (2009) 5560–5564.
https://doi.org/10.1016/j.bmcl.2009.08.045.
[25] J. Dong, N. N. Wang, Z. J. Yao, L. Zhang, Y. Cheng, D. Ouyang, A. P. Lu, D. S. Cao, ADMETlab: A platform for systematic ADMET evaluation based on a comprehensively collected ADMET database. J. Cheminform, 10 (2018) 29.
https://doi.org/10.1186/s13321-018-0283-x.