A virtual library of small molecules mimicking dipeptides.

Virtual combinatorial libraries are prevalent in drug discovery due to improvements in the prediction of synthetic reactions that can be performed. This has gone hand in hand with the development of virtual screening capabilities to effectively screen the large chemical spaces spanned by exhaustive enumeration of reaction products. In this study, we generated a small-molecule dipeptide mimic library to target proteins binding small peptides. The library was created based on the general idea of peptide synthesis, that is, amino acid mimics were reacted in silico to form the dipeptide mimics, yielding 2,036,819 unique compounds. After docking calculations, two compounds from the library were synthesized and tested against WD repeat-containing protein 5 (WDR5) and histamine receptors H1-H4 to evaluate whether these molecules are viable in assays. The compounds showed the highest potency at the histamine H3 receptor, with Ki values in the two-digit micromolar range.

Structure-Based Design and Pharmacophore-Based Virtual Screening of Combinatorial Library of Triclosan Analogues Active against Enoyl-Acyl Carrier Protein Reductase of Plasmodium falciparum with Favourable ADME Profiles.

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 (∆∆Gcom) between PfENR and TCL and the observed inhibitory potencies of the enzyme (IC50exp) 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 ∆∆Gcom and IC50exp values, which explained approximately 95% of the PfENR inhibition data: pIC50exp=-0.0544×∆∆Gcom+6.9336,R2=0.95. A similar agreement was established for the PH4 pharmacophore model of the PfENR inhibition (pIC50exp=0.9754×pIC50pre+0.1596, R2=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 IC50pre 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.

Structure Based Library Design (SBLD) for new 1,4-dihydropyrimidine scaffold as simultaneous COX-1/COX-2 and 5-LOX inhibitors.

The various scaffolds containing 1,4-dihydropyrimidine ring were designed by considering the environment of the active site of COX-1/COX-2 and 5-LOX enzymes. The structure-based library design approach, including the focused library design (Virtual Combinatorial Library Design) and virtual screening was used to select the 1,4-dihydropyrimidine scaffold for simultaneous inhibition of both enzyme pathways (COX-1/COX-2 and 5-LOX). The virtual library on each 1,4-dihydropyrimidine scaffold was enumerated in two alternative ways. In first way, the chemical reagents at R groups were filtered by docking of scaffold with single position substitution, that is, only at R1, or R2, or R3, … Rn on COX-2 enzyme using Glide XP docking mode. The structures that do not dock well were removed and the library was enumerated with filtered chemical reagents. In second alternative way, the single position docking stage was bypassed, and the entire library was enumerated using all chemical reagents by docking on the COX-2 enzyme. The entire library of approximately 15,629 compounds obtained from both ways after screening for drug like properties, were further screened for their binding affinity against COX-1 and 5-LOX enzymes using Virtual Screening Workflow. Finally, 142 hits were obtained and divided into two groups based on their binding affinity for COX-1/COX-2 and for both enzyme pathways (COX-1/COX-2 and 5-LOX). The ten molecules were selected, synthesized and evaluated for their COX-1, COX-2 and 5-LOX inhibiting activity.

Computer-Aided Design of Orally Bioavailable Pyrrolidine Carboxamide Inhibitors of Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis with Favorable Pharmacokinetic Profiles.

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 (ΔΔGcom) of InhA-PCAM complex formation and IC50(exp) (pIC50(exp) = -0.1552·ΔΔGcom + 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.

Hit Identification of a Novel Quinazoline Sulfonamide as a Promising EphB3 Inhibitor: Design, Virtual Combinatorial Library, Synthesis, Biological Evaluation, and Docking Simulation Studies.

EphB3 is a major key player in a variety of cellular activities, including cell migration, proliferation, and apoptosis. However, the exact role of EphB3 in cancer remains ambiguous. Accordingly, new EphB3 inhibitors can increase the understanding of the exact roles of the receptor and may act as promising therapeutic candidates. Herein, a hybrid approach of structure-based design and virtual combinatorial library generated 34 quinazoline sulfonamides as potential selective EphB3 inhibitors. A molecular docking study over EphB3 predicted the binding affinities of the generated library, and the top seven hit compounds (3a and 4a-f), with GlideScore ≥ -6.20 Kcal/mol, were chosen for further MM-GBSA calculations. Out of the seven top hits, compound 4c showed the highest MM-GBSA binding free energy (-74.13 Kcal/mol). To validate these predicted results, compounds 3a and 4a-f were synthesized and characterized using NMR, HRMS, and HPLC. The biological evaluation revealed compound 4c as a potent EphB3 inhibitory lead (IC50 = 1.04 µM). The screening of 4c over a mini-panel of kinases consisting of EGFR, Aurora A, Aurora B, CDK2/cyclin A, EphB1, EphB2, EphB4, ERBB2/HER2, and KDR/VEGFR2, showed a promising selective profile against EphB3 isoform. A dose-dependent assay of compound 4c and a molecular docking study over the different forms of EphB provided insights into the elicited biological activities and highlighted reasonable explanations of the selectivity.

Computer-Assisted Selective Optimization of Side-Activities-from Cinalukast to a PPARα Modulator.

Automated computational analogue design and scoring can speed up hit-to-lead optimization and appears particularly promising in selective optimization of side-activities (SOSA) where possible analogue diversity is confined. Probing this concept, we employed the cysteinyl leukotriene receptor 1 (CysLT1 R) antagonist cinalukast as lead for which we discovered peroxisome proliferator-activated receptor α (PPARα) modulatory activity. We automatically generated a virtual library of close analogues and classified these roughly 8000 compounds for PPARα agonism and CysLT1 R antagonism using automated affinity scoring and machine learning. A computationally preferred analogue for SOSA was synthesized, and in vitro characterization indeed revealed a marked activity shift toward enhanced PPARα activation and diminished CysLT1 R antagonism. Thereby, this prospective application study highlights the potential of automating SOSA.