We have carried out a computational structure-based design of new potent pyrrolidine carboxamide (PCAMs) inhibitors of enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (MTb). Three-dimensional (3D) models of InhA-PCAMx complexes were prepared by in situ modification of the crystal structure of InhA-PCAM1 (Protein Data Bank (PDB) entry code: 4U0J), the reference compound of a training set of 20 PCAMs with known experimental inhibitory potencies (IC₅₀^exp). First, we built a gas phase quantitative structure-activity relationships (QSAR) model, linearly correlating the computed enthalpy of the InhA-PCAM complex formation and the IC₅₀^exp. Further, taking into account the solvent effect and loss of inhibitor entropy upon enzyme binding led to a QSAR model with a superior linear correlation between computed Gibbs free energies (ΔΔG_com) of InhA-PCAM complex formation and IC₅₀^exp (pIC₅₀^exp = −0.1552·ΔΔG_com + 5.0448, R² = 0.94), which was further validated with a 3D-QSAR pharmacophore model generation (PH4). Structural information from the models guided us in designing of a virtual combinatorial library (VL) of more than 17 million PCAMs. The VL was adsorption, distribution, metabolism and excretion (ADME) focused and reduced down to 1.6 million drug like orally bioavailable analogues and PH4 in silico screened to identify new potent PCAMs with predicted IC₅₀^pre reaching up to 5 nM. Combining molecular modeling and PH4 in silico screening of the VL resulted in the proposed novel potent antituberculotic agent candidates with favorable pharmacokinetic profiles.

We have designed new potent inhibitors of thymidine monophosphate kinase of Mycobacterium tuberculosis (TMPK _mt ) using structure-based molecular design.

Cost-effective therapy of neglected and tropical diseases such as malaria requires everlasting drug discovery efforts due to the rapidly emerging drug resistance of the plasmodium parasite. We have carried out computational design of new inhibitors of the enoyl-acyl carrier protein reductase (ENR) of Plasmodium falciparum (PfENR) using computer-aided combinatorial and pharmacophore-based molecular design. The Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) complexation QSAR model was developed for triclosan-based inhibitors (TCL) and a significant correlation was established between the calculated relative Gibbs free energies of complex formation $(∆∆{\mathrm{G}}_{\mathrm{c}\mathrm{o}\mathrm{m}})$ between PfENR and TCL and the observed inhibitory potencies of the enzyme $\left({\mathrm{I}\mathrm{C}}_{50}^{\mathrm{e}\mathrm{x}\mathrm{p}}\right)$ for a training set of 20 known TCL analogues. Validation of the predictive power of the MM-PBSA QSAR model was carried out with the generation of 3D QSAR pharmacophore (PH4). We obtained a reasonable correlation between the relative Gibbs free energy of complex formation ${∆∆\mathrm{G}}_{\mathrm{c}\mathrm{o}\mathrm{m}}$ and ${\mathrm{I}\mathrm{C}}_{50}^{\mathrm{e}\mathrm{x}\mathrm{p}}$ values, which explained approximately 95% of the PfENR inhibition data: ${{p\mathrm{I}\mathrm{C}}_{50}^{\mathrm{e}\mathrm{x}\mathrm{p}}=-0.0544\times {∆∆\mathrm{G}}_{\mathrm{c}\mathrm{o}\mathrm{m}}+6.9336,\mathrm{R}}^2=0.95$. A similar agreement was established for the PH4 pharmacophore model of the PfENR inhibition (${\mathrm{p}\mathrm{I}\mathrm{C}}_{50}^{\mathrm{e}\mathrm{x}\mathrm{p}}=0.9754\times {\mathrm{p}\mathrm{I}\mathrm{C}}_{50}^{\mathrm{p}\mathrm{r}\mathrm{e}}+0.1596$, ${\mathrm{R}}^2=0.98$). Analysis of enzyme–inhibitor binding site interactions suggested suitable building blocks to be used in a virtual combinatorial library of 33,480 TCL analogues. Structural information derived from the complexation model and the PH4 pharmacophore guided us through in silico screening of the virtual combinatorial library of TCL analogues to finally identify potential new TCL inhibitors effective at low nanomolar concentrations. Virtual screening of the library by PfENR-PH4 led to a predicted ${\mathrm{I}\mathrm{C}}_{50}^{\mathrm{p}\mathrm{r}\mathrm{e}}$ value for the best inhibitor candidate as low as 1.9 nM. Finally, the stability of PfENR-TCLx complexes and the flexibility of the active conformation of the inhibitor for selected top-ranking TCL analogues were checked with the help of molecular dynamics. This computational study resulted in a set of proposed new potent inhibitors with predicted antimalarial effects and favourable pharmacokinetic profiles that act on a novel pharmacological target, PfENR.

In this work, antiparasitic peptidomimetics inhibitors (PEP) of falcipain-3 (FP3) of Plasmodium falciparum (Pf) are proposed using structure-based and computer-aided molecular design. Beginning with the crystal structure of PfFP3-K11017 complex (PDB ID: 3BWK), three-dimensional (3D) models of FP3-PEPx complexes with known activities (${ \mathrm{IC}}_{50}^{\exp }$) were prepared by in situ modification, based on molecular mechanics and implicit solvation to compute Gibbs free energies (GFE) of inhibitor-FP3 complex formation. This resulted in a quantitative structure–activity relationships (QSAR) model based on a linear correlation between computed GFE (ΔΔG_com) and the experimentally measured ${ \mathrm{IC}}_{50}^{\exp }$. Apart from the structure-based relationship, a ligand-based quantitative pharmacophore model (PH4) of novel PEP analogues where substitutions were directed by comparative analysis of the active site interactions was derived using the proposed bound conformations of the PEPx. This provided structural information useful for the design of virtual combinatorial libraries (VL), which was virtually screened based on the 3D-QSAR PH4. The end results were predictive inhibitory activities falling within the low nanomolar concentration range.

Background: During the previous decade a new class of benzamide-based inhibitors of 2-trans enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (Mt) with unusual binding mode have emerged. Here we report in silico design and evaluation of novel benzamide InhA-Mt inhibitors with favorable predicted pharmacokinetic profiles. Methods: By using in situ modifications of the crystal structure of N-benzyl-4-((heteroaryl)methyl) benzamide (BHMB)-InhA complex (PDB entry 4QXM), 3D models of InhA-BHMBx complexes were prepared for a training set of 19 BHMBs with experimentally determined inhibitory potencies (half-maximal inhibitory concentrations IC50exp). In the search for active conformation of the BHMB1-19, linear QSAR model was prepared, which correlated computed gas phase enthalpies of formation (∆∆HMM) of InhA-BHMBx complexes with the IC50exp. Further, taking into account the solvent effect and entropy changes upon ligand, binding resulted in a superior QSAR model correlating computed complexation Gibbs free energies (∆∆Gcom). The successive pharmacophore model (PH4) generated from the active conformations of BHMBs served as a virtual screening tool of novel analogs included in a virtual combinatorial library (VCL) of compounds containing benzamide scaffolds. The VCL filtered by Lipinski’s rule-of-five was screened by the PH4 model to identify new BHMB analogs. Results: Gas phase QSAR model: −log₁₀(IC₅₀^exp) = pIC₅₀^exp = −0.2465 × ∆∆H_MM + 7.95503, R² = 0.94; superior aqueous phase QSAR model: pIC₅₀^exp = −0.2370 × ∆∆G_com + 7.8783, R² = 0.97 and PH4 pharmacophore model: $p{{\mathrm{IC}}_{50}}^{\exp }$ = 1.0013 × p ${{\mathrm{IC}}_{50}}^{\exp }$ − 0.0085, R² = 0.95. The VCL of more than 114 thousand BHMBs was filtered down to 73,565 analogs Lipinski’s rule. The five-point PH4 screening retained 90 new and potent BHMBs with predicted inhibitory potencies IC₅₀^pre up to 65 times lower than that of BHMB1 (IC₅₀^exp = 20 nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability and high human oral absorption compared to current anti-tuberculotics. Conclusions: Combined use of QSAR models that considered binding of the BHMBs to InhA, pharmacophore model, and ADME properties helped to recognize bound active conformation of the benzamide inhibitors, permitted in silico screening of VCL of compounds sharing benzamide scaffold and identification of new analogs with predicted high inhibitory potencies and favorable pharmacokinetic profiles.