<i>In silico</i> Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of <i>Plasmodium falciparum</i> M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile

Hermann N'Guessan; Eugene Megnassan

doi:doi:10.11648/j.jddmc.20170306.13

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In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile

Hermann N'Guessan, Eugene Megnassan

Published in Journal of Drug Design and Medicinal Chemistry (Volume 3, Issue 6)

Received: 17 November 2017 Accepted: 8 December 2017 Published: 11 January 2018

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Abstract

We virtually design here new subnanomolar range antimalarials, inhibitors of plasmodium falciparum M17 Aminopeptidase (pfA-M17), by means of structure-based molecular design. Complexation QSAR models were elaborated for two training sets (6 methylphosphonic acids (APP) resp. 13 Hydroxamic Acid derivatives (AHO): QSAR_APP. resp. QSAR_AHO) and a linear correlation was established between the computed Gibbs free energies of binding (GFE: DDG_com) and observed enzyme inhibition constants (K_i^exp) for each training set: QSAR_APP: pK_i^exp=−0.1665´DDG_com+7.9581, R²=0.97 resp. QSAR_AHO: pK_i^exp=−0.4626´DDG_com+8.1842, R²=0.98. The predictive power of the QSAR models was validated with 3D-QSAR pharmacophore generation (PH4): PH4_APP: pK_i^exp=0.99677´pK_i^pred– 0.00457, R²=0.99 resp. PH4_AHO: pK_i^exp =1.02016´pK_i^pred–0.10478, R²=0.99. Breakdown of computed pfA-M17:APPs resp. pfA-M17:AHOs interaction energy into each active site residue’s contribution provided additional helpful structural information to design new APP and AHO analogues in a consistent way. In a first step we designed a virtual library (VL_APP resp. VL_AHO) from P₁ and P’ ₁ substitutions to explore both S₁ and S’ ₁ pockets. Further the VLs screened with the 3D-QSAR PH4s and the K_i^pred of the best fit hits virtually evaluated with QSAR_APP resp. QSAR_AHO models. This approach combining use of molecular modeling, PH4 and in silico VL screening helpfully provided valuable structural information for the synthesis of novel pfA-M17 inhibitors.

Published in	Journal of Drug Design and Medicinal Chemistry (Volume 3, Issue 6)
DOI	10.11648/j.jddmc.20170306.13
Page(s)	86-113
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Drug Design, QSAR Model, Pharmacophore Model, ADME Properties, Complexation Model, Molecular Modelling

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Hermann N'Guessan, Eugene Megnassan. (2018). In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile. Journal of Drug Design and Medicinal Chemistry, 3(6), 86-113. https://doi.org/10.11648/j.jddmc.20170306.13

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ACS Style

Hermann N'Guessan; Eugene Megnassan. In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile. J. Drug Des. Med. Chem. 2018, 3(6), 86-113. doi: 10.11648/j.jddmc.20170306.13

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AMA Style

Hermann N'Guessan, Eugene Megnassan. In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile. J Drug Des Med Chem. 2018;3(6):86-113. doi: 10.11648/j.jddmc.20170306.13

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@article{10.11648/j.jddmc.20170306.13,
  author = {Hermann N'Guessan and Eugene Megnassan},
  title = {In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile},
  journal = {Journal of Drug Design and Medicinal Chemistry},
  volume = {3},
  number = {6},
  pages = {86-113},
  doi = {10.11648/j.jddmc.20170306.13},
  url = {https://doi.org/10.11648/j.jddmc.20170306.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jddmc.20170306.13},
  abstract = {We virtually design here new subnanomolar range antimalarials, inhibitors of plasmodium falciparum M17 Aminopeptidase (pfA-M17), by means of structure-based molecular design. Complexation QSAR models were elaborated for two training sets (6 methylphosphonic acids (APP) resp. 13 Hydroxamic Acid derivatives (AHO): QSARAPP. resp. QSARAHO) and a linear correlation was established between the computed Gibbs free energies of binding (GFE: DDGcom) and observed enzyme inhibition constants (Kiexp) for each training set: QSARAPP: pKiexp=−0.1665´DDGcom+7.9581, R2=0.97 resp. QSARAHO: pKiexp=−0.4626´DDGcom+8.1842, R2=0.98. The predictive power of the QSAR models was validated with 3D-QSAR pharmacophore generation (PH4): PH4APP: pKiexp=0.99677´pKipred– 0.00457, R2=0.99 resp. PH4AHO: pKiexp =1.02016´pKipred–0.10478, R2=0.99. Breakdown of computed pfA-M17:APPs resp. pfA-M17:AHOs interaction energy into each active site residue’s contribution provided additional helpful structural information to design new APP and AHO analogues in a consistent way. In a first step we designed a virtual library (VLAPP resp. VLAHO) from P1 and P’ 1 substitutions to explore both S1 and S’ 1 pockets. Further the VLs screened with the 3D-QSAR PH4s and the Kipred of the best fit hits virtually evaluated with QSARAPP resp. QSARAHO models. This approach combining use of molecular modeling, PH4 and in silico VL screening helpfully provided valuable structural information for the synthesis of novel pfA-M17 inhibitors.},
 year = {2018}
}

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TY - JOUR
T1 - In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile
AU - Hermann N'Guessan
AU - Eugene Megnassan
Y1 - 2018/01/11
PY - 2018
N1 - https://doi.org/10.11648/j.jddmc.20170306.13
DO - 10.11648/j.jddmc.20170306.13
T2 - Journal of Drug Design and Medicinal Chemistry
JF - Journal of Drug Design and Medicinal Chemistry
JO - Journal of Drug Design and Medicinal Chemistry
SP - 86
EP - 113
PB - Science Publishing Group
SN - 2472-3576
UR - https://doi.org/10.11648/j.jddmc.20170306.13
AB - We virtually design here new subnanomolar range antimalarials, inhibitors of plasmodium falciparum M17 Aminopeptidase (pfA-M17), by means of structure-based molecular design. Complexation QSAR models were elaborated for two training sets (6 methylphosphonic acids (APP) resp. 13 Hydroxamic Acid derivatives (AHO): QSARAPP. resp. QSARAHO) and a linear correlation was established between the computed Gibbs free energies of binding (GFE: DDGcom) and observed enzyme inhibition constants (Kiexp) for each training set: QSARAPP: pKiexp=−0.1665´DDGcom+7.9581, R2=0.97 resp. QSARAHO: pKiexp=−0.4626´DDGcom+8.1842, R2=0.98. The predictive power of the QSAR models was validated with 3D-QSAR pharmacophore generation (PH4): PH4APP: pKiexp=0.99677´pKipred– 0.00457, R2=0.99 resp. PH4AHO: pKiexp =1.02016´pKipred–0.10478, R2=0.99. Breakdown of computed pfA-M17:APPs resp. pfA-M17:AHOs interaction energy into each active site residue’s contribution provided additional helpful structural information to design new APP and AHO analogues in a consistent way. In a first step we designed a virtual library (VLAPP resp. VLAHO) from P1 and P’ 1 substitutions to explore both S1 and S’ 1 pockets. Further the VLs screened with the 3D-QSAR PH4s and the Kipred of the best fit hits virtually evaluated with QSARAPP resp. QSARAHO models. This approach combining use of molecular modeling, PH4 and in silico VL screening helpfully provided valuable structural information for the synthesis of novel pfA-M17 inhibitors.
VL - 3
IS - 6
ER -

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Hermann N'Guessan

Faculty of Fundamental and Applied Sciences (UFR SFA), Laboratoire de Physique Fondamentale et Appliquée, University Abobo Adjamé (Now Nangui Abrogoua), Abidjan, Cote D’Ivoire
Eugene Megnassan

Faculty of Fundamental and Applied Sciences (UFR SFA), Laboratoire de Physique Fondamentale et Appliquée, University Abobo Adjamé (Now Nangui Abrogoua), Abidjan, Cote D’Ivoire

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APA Style

Hermann N'Guessan, Eugene Megnassan. (2018). In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile. Journal of Drug Design and Medicinal Chemistry, 3(6), 86-113. https://doi.org/10.11648/j.jddmc.20170306.13

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Hermann N'Guessan; Eugene Megnassan. In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile. J. Drug Des. Med. Chem. 2018, 3(6), 86-113. doi: 10.11648/j.jddmc.20170306.13

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Hermann N'Guessan, Eugene Megnassan. In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile. J Drug Des Med Chem. 2018;3(6):86-113. doi: 10.11648/j.jddmc.20170306.13

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@article{10.11648/j.jddmc.20170306.13,
  author = {Hermann N'Guessan and Eugene Megnassan},
  title = {In silico Design of Phosphonic Arginine and Hydroxamic Acid Inhibitors of Plasmodium falciparum M17 Leucyl Aminopeptidase with Favorable Pharmacokinetic Profile},
  journal = {Journal of Drug Design and Medicinal Chemistry},
  volume = {3},
  number = {6},
  pages = {86-113},
  doi = {10.11648/j.jddmc.20170306.13},
  url = {https://doi.org/10.11648/j.jddmc.20170306.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jddmc.20170306.13},
  abstract = {We virtually design here new subnanomolar range antimalarials, inhibitors of plasmodium falciparum M17 Aminopeptidase (pfA-M17), by means of structure-based molecular design. Complexation QSAR models were elaborated for two training sets (6 methylphosphonic acids (APP) resp. 13 Hydroxamic Acid derivatives (AHO): QSARAPP. resp. QSARAHO) and a linear correlation was established between the computed Gibbs free energies of binding (GFE: DDGcom) and observed enzyme inhibition constants (Kiexp) for each training set: QSARAPP: pKiexp=−0.1665´DDGcom+7.9581, R2=0.97 resp. QSARAHO: pKiexp=−0.4626´DDGcom+8.1842, R2=0.98. The predictive power of the QSAR models was validated with 3D-QSAR pharmacophore generation (PH4): PH4APP: pKiexp=0.99677´pKipred– 0.00457, R2=0.99 resp. PH4AHO: pKiexp =1.02016´pKipred–0.10478, R2=0.99. Breakdown of computed pfA-M17:APPs resp. pfA-M17:AHOs interaction energy into each active site residue’s contribution provided additional helpful structural information to design new APP and AHO analogues in a consistent way. In a first step we designed a virtual library (VLAPP resp. VLAHO) from P1 and P’ 1 substitutions to explore both S1 and S’ 1 pockets. Further the VLs screened with the 3D-QSAR PH4s and the Kipred of the best fit hits virtually evaluated with QSARAPP resp. QSARAHO models. This approach combining use of molecular modeling, PH4 and in silico VL screening helpfully provided valuable structural information for the synthesis of novel pfA-M17 inhibitors.},
 year = {2018}
}

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