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Multivariate PLS Modeling of Apicomplexan FabD-Ligand Interaction Space for Mapping Target-Specific Chemical Space and Pharmacophore Fingerprints.

Mamidi AS, Arora P, Surolia A - PLoS ONE (2015)

Bottom Line: Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products.It also highlights the selective variations in FabD of apicomplexan parasites with that of the host.Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.

View Article: PubMed Central - PubMed

Affiliation: Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.

ABSTRACT
Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.

No MeSH data available.


The key structural and functional descriptors obtained through PLS modeling of chemical space in (a) PfFabD and (b) TgFabD.These are crucial for rendering target-specificity of organic compounds are shown. The constitutional indices that form the major scaffolds are enclosed in a circle (dashed line----) and the functional groups are presented around it.
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pone.0141674.g008: The key structural and functional descriptors obtained through PLS modeling of chemical space in (a) PfFabD and (b) TgFabD.These are crucial for rendering target-specificity of organic compounds are shown. The constitutional indices that form the major scaffolds are enclosed in a circle (dashed line----) and the functional groups are presented around it.

Mentions: Understanding the structural and other physiochemical features of ligands is critical for designing drug molecules with proper functional groups. Hence, chemometric PLS models of the chemical space in PfFabD and TgFabD with respect to HsFabD were developed. In the chemometric PLS models, the cumulative R2Y and Q2 were above the threshold range, i.e. 0.7 and 0.4, while the Q2ext for ElecStat has alone qualified with ≥0.4. On the other hand, Q2ext values of dG and VDW were lesser than 0.4. The entire descriptor details corresponding to the three Y-dependent variables has been provided in S6 Table, in view of the above, these models are discussed in the context of ElecStat Y-response variable only. Based on these models, the ligand space that was conducive for the specificity for PfFabD and TgFabD are shown as column plots in S13 Fig. Further, analysis of the descriptors, which describe the organic compounds and their functional groups that enhance the binding interactions with respective apicomplexan FabD receptors are shown in Fig 8. Upon comparison with HsFabD, it is noticed that average molecular weight (AMW), mean atomic Sanderson electronegativity (Me), nCrs, nPyrrolidines, nArCONH2 as functional groups, MLOGP and Weiner index (WI) render specificity of the given ligands for PfFabD (S12a Fig). Similarly for TgFabD, ligand features influencing selectivity are AMW, Me, RBF, SCBO, nCIC, ARR, nBM, nCar, nRCONR2, nArCONH2, nImidazole, MLOGP (S12b Fig). Likewise, the contributing chemical descriptors that positively influence the electrostatic interactions of HsFabD are shown as column plot in S14 Fig. The chemical space specific to HsFabD relative to PfFabD was assessed and noted to consist of nCt, nCrt, nPyridines, hydrophilicity and number of hydrogen donor atoms (N and O). Similarly, functional groups like nRCOOH, nARCONHR, nCconj, nCrt, nDB, nO, nR = Cs, nR10, nPyrrolidines and hydrophilicity factor (Hy) specifically contribute for HsFabD in competition with TgFabD.


Multivariate PLS Modeling of Apicomplexan FabD-Ligand Interaction Space for Mapping Target-Specific Chemical Space and Pharmacophore Fingerprints.

Mamidi AS, Arora P, Surolia A - PLoS ONE (2015)

The key structural and functional descriptors obtained through PLS modeling of chemical space in (a) PfFabD and (b) TgFabD.These are crucial for rendering target-specificity of organic compounds are shown. The constitutional indices that form the major scaffolds are enclosed in a circle (dashed line----) and the functional groups are presented around it.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4633102&req=5

pone.0141674.g008: The key structural and functional descriptors obtained through PLS modeling of chemical space in (a) PfFabD and (b) TgFabD.These are crucial for rendering target-specificity of organic compounds are shown. The constitutional indices that form the major scaffolds are enclosed in a circle (dashed line----) and the functional groups are presented around it.
Mentions: Understanding the structural and other physiochemical features of ligands is critical for designing drug molecules with proper functional groups. Hence, chemometric PLS models of the chemical space in PfFabD and TgFabD with respect to HsFabD were developed. In the chemometric PLS models, the cumulative R2Y and Q2 were above the threshold range, i.e. 0.7 and 0.4, while the Q2ext for ElecStat has alone qualified with ≥0.4. On the other hand, Q2ext values of dG and VDW were lesser than 0.4. The entire descriptor details corresponding to the three Y-dependent variables has been provided in S6 Table, in view of the above, these models are discussed in the context of ElecStat Y-response variable only. Based on these models, the ligand space that was conducive for the specificity for PfFabD and TgFabD are shown as column plots in S13 Fig. Further, analysis of the descriptors, which describe the organic compounds and their functional groups that enhance the binding interactions with respective apicomplexan FabD receptors are shown in Fig 8. Upon comparison with HsFabD, it is noticed that average molecular weight (AMW), mean atomic Sanderson electronegativity (Me), nCrs, nPyrrolidines, nArCONH2 as functional groups, MLOGP and Weiner index (WI) render specificity of the given ligands for PfFabD (S12a Fig). Similarly for TgFabD, ligand features influencing selectivity are AMW, Me, RBF, SCBO, nCIC, ARR, nBM, nCar, nRCONR2, nArCONH2, nImidazole, MLOGP (S12b Fig). Likewise, the contributing chemical descriptors that positively influence the electrostatic interactions of HsFabD are shown as column plot in S14 Fig. The chemical space specific to HsFabD relative to PfFabD was assessed and noted to consist of nCt, nCrt, nPyridines, hydrophilicity and number of hydrogen donor atoms (N and O). Similarly, functional groups like nRCOOH, nARCONHR, nCconj, nCrt, nDB, nO, nR = Cs, nR10, nPyrrolidines and hydrophilicity factor (Hy) specifically contribute for HsFabD in competition with TgFabD.

Bottom Line: Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products.It also highlights the selective variations in FabD of apicomplexan parasites with that of the host.Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.

View Article: PubMed Central - PubMed

Affiliation: Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.

ABSTRACT
Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.

No MeSH data available.