Conformational analysis of piperazine and piperidine analogs of GBR 12909: stochastic approach to evaluating the effects of force fields and solvent

Integrating multiscale and machine learning approaches towards the SAMPL9 log P challenge

The partition coefficient (log P) is an important physicochemical property that provides information regarding a molecule's pharmacokinetics, toxicity, and bioavailability. Methods to accurately predict the partition coefficient have the potential to accelerate drug design. In an effort to test current methods and explore new computational techniques, the statistical assessment of the modeling of proteins and ligands (SAMPL) has established a blind prediction challenge. The ninth iteration challenge was to predict the toluene-water partition coefficient (log Ptol/w) of sixteen drug molecules. Herein, three approaches are reported broadly under the categories of quantum mechanics (QM), molecular mechanics (MM), and data-driven machine learning (ML). The three blind submissions yield mean unsigned errors (MUE) ranging from 1.53-2.93 log Ptol/w units. The MUEs were reduced to 1.00 log Ptol/w for the QM methods. While MM and ML methods outperformed DFT approaches for challenge molecules with fewer rotational degrees of freedom, they suffered for the larger molecules in this dataset. Overall, DFT functionals paired with a triple-ζ basis set were the simplest and most effective tool to obtain quantitatively accurate partition coefficients.

Ether modifications to 1-[2-(3,4-dimethoxyphenyl)ethyl]-4-(3-phenylpropyl)piperazine (SA4503): effects on binding affinity and selectivity for sigma receptors and monoamine transporters

Two series of novel ether analogs of the sigma (σ) receptor ligand 1-[2-(3,4-dimethoxyphenyl)ethyl]-4-(3-phenylpropyl)piperazine (SA4503) have been prepared. In one series, the alkyl portion of the 4-methoxy group was replaced with allyl, propyl, bromoethyl, benzyl, phenethyl, and phenylpropyl moieties. In the second series, the 3,4-dimethoxy was replaced with cyclic methylenedioxy, ethylenedioxy and propylenedioxy groups. These ligands, along with 4-O-des-methyl SA4503, were evaluated for σ1 and σ2 receptor affinity, and compared to SA4503 and several known ether analogs. SA4503 and a subset of ether analogs were also evaluated for dopamine transporter (DAT) and serotonin transporter (SERT) affinity. The highest σ1 receptor affinities, Ki values of 1.75-4.63 nM, were observed for 4-O-des-methyl SA4503, SA4503 and the methylenedioxy analog. As steric bulk increased, σ1 receptor affinity decreased, but only to a point. Allyl, propyl and bromoethyl substitutions gave σ1 receptor Ki values in the 20-30 nM range, while bulkier analogs having phenylalkyl, and Z- and E-iodoallyl, ether substitutions showed higher σ1 affinities, with Ki values in the 13-21 nM range. Most ligands studied exhibited comparable σ1 and σ2 affinities, resulting in little to no subtype selectivity. SA4503, the fluoroethyl analog and the methylenedioxy congener showed modest six- to fourteen-fold selectivity for σ1 sites. DAT and SERT interactions proved much more sensitive than σ receptor interactions to these structural modifications. For example, the benzyl congener (σ1Ki=20.8 nM; σ2Ki=16.4 nM) showed over 100-fold higher DAT affinity (Ki=121 nM) and 6-fold higher SERT affinity (Ki=128nM) than the parent SA4503 (DAT Ki=12650 nM; SERT Ki=760 nM). Thus, ether modifications to the SA4503 scaffold can provide polyfunctional ligands having a broader spectrum of possible pharmacological actions.

Flexible and biomimetic analogs of triple uptake inhibitor 4-((((3S,6S)-6-benzhydryltetrahydro-2H-pyran-3-yl)amino)methyl)phenol: Synthesis, biological characterization, and development of a pharmacophore model

In this study we have generated a pharmacophore model of triple uptake inhibitor compounds based on novel asymmetric pyran derivatives and the newly developed asymmetric furan derivatives. The model revealed features important for inhibitors to exhibit a balanced activity against dopamine transporter (DAT), serotonin transporter (SERT), and norepinephrine transporter (NET). In particular, a 'folded' conformation was found common to the active pyran compounds in the training set and was crucial to triple uptake inhibitory activity. Furthermore, the distances between the benzhydryl moiety and the N-benzyl group as well as the orientation of the secondary nitrogen were also important for TUI activity. We have validated our findings by synthesizing and testing novel asymmetric pyran analogs. The present work has also resulted in the discovery of a new series of asymmetric tetrahydrofuran derivatives as novel TUIs. Lead compounds 41 and 42 exhibited moderate TUI activity. Interestingly, the highest TUI activity by lead tetrahydrofuran compounds for example, 41 and 42, was exhibited in a stereochemical preference similar to pyran TUI for example, D-161.

Singular value decomposition analysis of the torsional angles of dopamine reuptake inhibitor GBR 12909 analogs: effect of force field and charges

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis of large, flexible molecules, such as the dopamine reuptake inhibitor GBR 12909 (1), is complicated by the fact that they can take on a wide range of closely-related conformations. The first step in the analysis is to classify the conformers into groups. Over 600 conformers each of a piperazine (2) and piperidine (3) analog of 1 were generated by random search conformational analysis using the Merck Molecular Force Field (MMFF94). Singular value decomposition (SVD) was used to group the conformers of 2 and 3 by the similarity of their non-ring torsional angles. SVD uncovered subtle differences in their conformer populations due to that fact that the conformers separate along different principal components, and ultimately to the fact that different torsional angles are the chief contributors to these components. The results were compared to our previous SVD analysis (Fiorentino, et al., Journal of Computational Chemistry, 2006, 27, 609-620) of conformer populations of 2 and 3 generated by the Tripos force field and Gasteiger-Hückel charges. Except for the dominant contribution of angle B3 to principal component 8 seen with both force fields, the angles which are chiefly responsible for the grouping of the conformers of 2 and 3 are different with both force fields. This illustrates that SVD is useful in identifying unique groupings of conformers in large data sets of flexible molecules-a first step in selecting representative conformers for 3D-QSAR modeling studies.