Antidepressant Drug Design on TCAs and Phenoxyphenylpropylamines utilizing QSAR and Pharmacophore Modeling

Background: Depression is a mental illness caused by the imbalance of important neurotransmitters such as serotonin (5-HT) and norepinephrine (NE). It is a serious neurological disorder that could be treated by antidepressant drugs. Objective: There are two major classes such as TCAs and phenoxyphenylpropylamines which have been proven to be broad-spectrum antidepressant compounds. Several attempts were made to design, synthesize and discover potent antidepressant compounds having the least toxicity and most selectivity towards serotonin and norepinephrine transporters. But there is hardly any drug design based on quantitative structure-activity relationship (QSAR) and pharmacophore modeling attempted yet. Method: In the present study, many TCAs (dibenzoazepine) and phenoxyphenylpropylamine derivatives are taken into consideration for pharmacophore feature generation followed by pharmacophoric distant related descriptors based QSAR modeling. Further, several five new congeners have been designed which are subjected to the prediction of biological activities in terms of serotonin receptor affinity utilizing validated QSAR models developed by us. Results: An important pharmacophoric feature point C followed by the generation of a topography of the TCAs and phenoxyphenylpropylamine has been predicted. The developed pharmacophoric feature-based QSAR can explain 64.2% of the variances of 5-HT receptor antagonism. The best training model has been statistically validated by the prediction of test set compounds. This training model has been used for the prediction of some newly designed congeneric compounds which are comparable with the existed drugs. Conclusion: The newly designed compounds may be proposed for further synthesis and biological screening as antidepressant agents.

Improving Atom Type Diversity and Sampling in Co-Solvent Simulations Using λ-Dynamics

<div>Here we present a novel co-solvent MD simulation method based on the lambda-dynamics simulation concept that aims to address a serious issue of current co-solvent simulation approaches, the limited chemical diversity of probe molecules ignoring the chemical context of the pharmacophoric feature represented by a probe. The new concept significantly increases the chemical diversity of functional groups investigated during co-solvent simulations. Application to four different test cases highlights the utility of the new approach to identify binding preferences of different functional groups and to correctly rank ligand series that differ by their substitution patterns.</div>

Improving Atom Type Diversity and Sampling in Co-Solvent Simulations Using λ-Dynamics

<div>Here we present a novel co-solvent MD simulation method based on the lambda-dynamics simulation concept that aims to address a serious issue of current co-solvent simulation approaches, the limited chemical diversity of probe molecules ignoring the chemical context of the pharmacophoric feature represented by a probe. The new concept significantly increases the chemical diversity of functional groups investigated during co-solvent simulations. Application to four different test cases highlights the utility of the new approach to identify binding preferences of different functional groups and to correctly rank ligand series that differ by their substitution patterns.</div>

Stereochemistry of serotonin receptor ligands from crystallographic data. Crystal structures of NAN-190.HBr, 1-phenylbiguanide, MDL 72222 and mianserin.HCl and selectivity criteria towards 5-HT1, 5-HT2 and 5-HT3 receptor subtypes

The crystal and molecular structures of the following serotoninergic drugs have been determined: (1) 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]piperazine hydrobromide hemihydrate (NAN-190.HBr), C23H28N3O3 +.Br−.1/2H2O, Mr = 483.42, monoclinic, C2/c, a = 21.916 (4), b = 15.207 (2), c = 14.052 (2) Å, β = 101.56 (1)°, V = 4588 (1) Å3, Z = 8, Dx = 1.40 Mg m−3, λ(Mo Kα) = 0.71069 Å, μ = 1.823 mm−1, F(000) = 2008, T = 295 K, R = 0.035 for 2617 observed reflections; (2) N-phenylimidocarbonimidic diamide (1-phenylbiguanide), C8H11N5, Mr = 177.21, monoclinic, P21/c, a = 9.781 (2), b = 35.040 (5), c = 11.000 (2) Å, β = 97.72 (1)°, V = 3736 (1) Å3, Z = 16, Dx = 1.26 Mg m−3, λ(Mo Kα) = 0.71069 Å, μ= 0.084 mm−1, F(000) = 1504, T = 295 K, R = 0.070 for 3407 observed reflections; (3) 8-methyl-8-azabicyclo[3.2.1.]oct-3-yl 3,5-dichlorobenzoate (MDL 72222), C15H17C12NO2, Mr = 314.21, triclinic, P{\bar 1}, a = 8.480 (3), b = 9.840 (3), c = 10.15 (4) Å, α = 90.04 (3), β = 111.77 (3), γ = 105.07 (3)°, V = 755.6 (5) Å3, Z = 2, Dx = 1.38 Mg m−3, λ(Mo Kα) = 0.71069 Å, μ = 0.430 mm−1, F(000) = 328, T = 295 K, R = 0.070 for 1685 observed reflections; (4) 1,2,3,4,10,14b-hexahydro-2-methyldibenzo[cf]pyrizino[1,2-a]azepine hydrochloride (mianserin.HCl), C18H21N2 +.Cl−, Mr = 300.83, monoclinic, P21/a, a = 9.014 (2), b = 14.917 (2), c = 12.412 (2) Å, β = 108.84 (1)°, V = 1579.5 (5) Å3, Z = 4, Dx = 1.26 Mg m−3, λ(Mo Kα) = 0.71069 Å, μ = 0.237 mm−1, F(000) = 640, T = 295 K, R = 0.063 for 1493 observed reflections. A systematic structural analysis of the present compounds and others known to interact with the 5-HT1, 5-HT2 and 5-HT3 receptors allows to identify their similarities with the endogenous ligand serotonin (5-HT) and the stereochemical differences which determine selectivity for the various receptor subtypes. The pharmacophoric feature for 5-HT receptor binding is identified in a constant-length vector linking an aromatic ring with a protonated nitrogen, while specific affinities for receptorial subtypes and the nature of the effect appear to be modulated by the dimensions of the substituents at nitrogen.