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

Plasmepsin II (PlmII), an aspartic protease expressed in the food vacuole of Plasmodium falciparum (pf), cleaves the hemoglobin of the host during the erythrocytic stage of the parasite life cycle. Various peptidomimetic inhibitors of PlmII reported so far discriminate poorly between the drug target and aspartic proteases of the host organism, e.g., human cathepsin D (hCatD). hCatD is a protein digestion enzyme and signaling molecule involved in a variety of physiological processes; therefore, inhibition of hCatD by PlmII inhibitors may lead to pathophysiological conditions. In this study, binding of PlmII inhibitors has been modeled using the crystal structures of pfPlmII and hCatD complexes to gain insight into structural requirements underlying the target selectivity. A series of 26 inhibitors were modeled in the binding clefts of the pfPlmII and hCatD to establish QSAR models of the protease inhibition. In addition, 3D-QSAR pharmacophore models were generated for each enzyme. It was concluded that the contributions of the P 2 and P 3¢ residues to the inhibitor's binding affinity are responsible for the target selectivity. Based on these findings, new inhibitor candidates were designed with predicted inhibition constants K

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 () 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 () and the experimentally measured . 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.

We virtually design here new subnanomolar range antimalarial, inhibitors of plasmodium falciparum M1 Aminopeptidase (PfA-M1), by means of structure-based molecular design. We developed the complexation QSAR models from Hydroxamic Acid derivatives (AHO). A linear correlation was established between the computed Gibbs free energies of binding (GFE: ∆∆Gcom) and observed enzyme inhibition constants (Kiexp) for each training set pKiexp = −0.063×∆∆Gcom+ 8.003, R2 = 0.92. The predictive power of the QSAR model was validated with 3D-QSAR pharmacophore generation (PH4): pKiexp = 1.0289×pKipred − 0.155, R2 = 0.90. We then conducted a study on catalytic residues to exploit the different interactions (enzyme: inhibitor). Structural information from the models guided us in designing of a virtual combinatorial library (VCL) of more than 44 thousands AHOs. The PH4 screening retained 51 new and potent AHOs with predicted inhibitory potencies pKipre up to 13 times lower than that of AHO1 (pKiexp = 700 nM). Combining molecular modeling and PH4 in silico screening of the VCL resulted in the proposed novel potent antimalarial agent candidates with favorable pharmacokinetic profiles.