Examining pharmacodynamic and pharmacokinetic properties of eleven analogues of saquinavir for HIV protease inhibition
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HIV is one of the most lethal viral diseases in the human population. Patients often suffer from drug resistance, which hampers HIV therapy. Eleven different structural analogues of saquinavir (SQV), designed using ChemSketch™ and named S1 through S11, were compared with SQV with respect to their pharmacodynamic and pharmacokinetic properties. Pharmacokinetic predictions were carried out using AutoDock, and molecular docking between macromolecule HIV protease (PDB ID: 3IXO) and analogues S1 – S11 as ligands was performed. Analogues S1, S3, S4, S9 and S11 had lower binding scores when compared with saquinavir, whereas that of analogue S5 was similar. Pharmacokinetic predictions made using ACDilab2, including the Lipinski profile, general physical features, absorption, distribution, metabolism and excretion parameters, and toxicity values, for the eleven analogues and SQV suggested that S1 and S5 are pharmacodynamically and pharmacokinetically robust molecules that could be developed and established as lead molecules after in vitro and in vivo studies.
AJ acknowledges University Grants Commission, New Delhi, for financial support.
This study was funded by University Grants Commission, New Delhi, India, in the form of fellowship to AJ.
Compliance with ethical standards
Conflict of interest
KS, AJ, HM and AM declare that all authors have contributed equally to this research work and that there is no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- 1.Patrick GL (2012) An introduction to medicinal chemistry, 4th edn. Oxford University Press Inc., New YorkGoogle Scholar
- 5.Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, Sajed T, Johnson D, Li C, Sayeeda Z, Assempour N, Iynkkaran I, Liu Y, Maciejewski A, Gale N, Wilson A, Chin L, Cummings R, Le D, Pon A, Knox C, Wilson M (2017) DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 46:D1074–D1082CrossRefGoogle Scholar
- 8.Robbins AH, Coman RM, Bracho-Sanchez E, Fernandez MA, Gilliland CT, Li M, Agbandje-McKenna M, Wlodawer A, Dunn BM, McKenna R (2010) Structure of the unbound form of HIV-1 subtype A protease: comparison with unbound forms of proteases from other HIV subtypes. Acta Crystallogr D Biol Crystallogr D66:233–242CrossRefGoogle Scholar
- 10.ACDiLab2 (2010) February 26. ACD/Chemsketch version 12.00. www.acdlabs.com
- 13.Shah K, Gupta S, Mishra H, Sharma PK, Jayaswal A (2014) Examining structural analogs of elvitegravir as potential inhibitors of HIV-1 integrase. Adv Virol 159:2069–2080Google Scholar
- 14.Charnley G (2002) Ames test. Encyclopedia of public health. eNotes.com. http://www.enotes.com/public-health-encyclopedia/ames-test. Retrieved 14 May 2018
- 15.Lu J, Lu D, Fu Z, Zheng M, Luo X (2018) Machine learning-based modeling of drug toxicity. In: Huang T (ed) Computational systems biology. Methods in molecular biology, vol 1754. Humana Press, New York, pp 247–264Google Scholar
- 19.Wendt MD (2012) The discovery of Navitoclax, a Bcl-2 family inhibitor, protein-protein interactions. Trop Med Chem 8:231–258Google Scholar
- 20.U.S. Food and Drug Administration (2018) Silver Spring, Maryland. https://www.fda.gov/ForPatients/Illness/HIVAIDS/Treatment/ucm118915.htm Accessed 14 May 2018