Chemical, Pharmacological, and in vitro Metabolic Stability Studies on Enantiomerically Pure RC‐33 Compounds: Promising Neuroprotective Agents Acting as σ₁ Receptor Agonists

Abstract

Our recent research efforts identified racemic RC-33 as a potent and metabolically stable σ₁ receptor agonist. Herein we describe the isolation of pure RC-33 enantiomers by chiral chromatography, assignment of their absolute configuration, and in vitro biological studies in order to address the role of chirality in the biological activity of these compounds and their metabolic processing. The binding of enantiopure RC-33 to the σ₁ receptor was also investigated in silico by molecular dynamics simulations. Both RC-33 enantiomers showed similar affinities for the σ₁ receptor and appeared to be almost equally effective as σ₁ receptor agonists. However, the R-configured enantiomer showed higher in vitro hepatic metabolic stability in the presence of NADPH than the S enantiomer. Overall, the results presented herein led us to select (R)-RC-33 as the optimal candidate for further in vivo studies in an animal model of amyotrophic lateral sclerosis.

Mallard Blue binding to heparin, its SDS micelle-driven de-complexation, and interaction with human serum albumin: A combined experimental/modeling investigation

“…The enthalpic nature of MalB/HSA is confirmed computationally (-13.82 kcal/mol), as is the unfavorable contribution from entropy variation upon binding (-8.19 kcal/mol). It is important to observe here that both (b and T Sb are normally overestimated in MM/PBSA calculations[37], as in the present case; yet, a parallel shift is generally observed between experimental and computed ( and -T S so that ultimately their difference is indeed close to the relevant experimental value. The analysis of the MD trajectory for the MalB/HSA complex shows that the dye is engaged in two permanent salt bridges, involving the negatively charged side chains of residues Glu379 and Glu593 on the protein side and one guanidinic and one tertiary amines of the dye, respectively(Fig.…”

“…The resulting docked conformations were clustered and visualized; then, only the molecular conformation satisfying the combined criteria of having the lowest (i.e., more favorable) Autodock energy and belonging to a highly populated cluster was selected to carry forward for further modeling. The MalB/HSA complex obtained from the docking procedure was further refined in Amber 16 using the quenched molecular dynamics (QMD) method as previously described [36][37][38].…”

Thiazole‐Based σ1 Receptor Ligands: Diversity by Late‐Stage C−H Arylation of Thiazoles, Structure–Affinity and Selectivity Relationships, and Molecular Interactions

“…All MD simulations were carried out using the Pmemd modules of Amber 14 [66] running on aC PU/GPU calculation cluster.T he binding free energy, DG calcd ,b etween the selected compounds and the s 1 receptor was estimated by resorting to the MM/PBSA [67] approach implemented in Amber 14, according to aw ell-validated methodology. [45,[68][69][70][71][72][73][74] Molecular graphics images were produced using the UCSF Chimera package (v.1.10). [75] The interaction spectra were obtained using GraphPad Prism version 6.00 for Mac OS XY osemite (GraphPad Software, La Jolla, CA, USA).…”

Computer-assisted design, synthesis, binding and cytotoxicity assessments of new 1-(4-(aryl(methyl)amino)butyl)-heterocyclic sigma 1 ligands

“…In particular, compounds 1a (H) and 1d showed the most interesting σ1R affinity within this molecular series, with K i σ 1 values of 2.6 nM and 7.1 nM and selectivity ratio (K i σ 2 /K i σ 1 ) of 46.2 and 5.1, respectively. Encouraged by these results, we then selected some of these molecules as training/test set compounds for the construction of a three-dimensional (3D) pharmacophore model for σ1R binding [17], and the subsequent original development of a σ1R 3D homology model [18], extensively validated in successive works [19][20][21][22][23][24][25][26][27][28]. The information retrieved from the combined application of 3D pharmacophore modeling and molecular dynamics (MD)-based docking and scoring calculations using the 3D σ1R homology model allowed us to fully characterize the network of intermolecular interactions responsible for the potency of compounds 1 as σ1R binders.…”