Elena Cichero

Insights into the Structure and Pharmacology of the Human Trace Amine-Associated Receptor 1 (hTAAR1): Homology Modelling and Docking Studies

Trace amine‐associated receptor 1 (TAAR1) is a G protein–coupled receptor that belongs to the family of TAAR receptors and responds to a class of compounds called trace amines, such as β‐phenylethylamine (β‐PEA) and 3‐iodothyronamine (T1AM). The receptor is known to have a very rich pharmacology and could be also activated by other classes of compounds, including adrenergic and serotonergic ligands. It is expected that targeting TAAR1 could provide a novel pharmacological approach to correct monoaminergic dysfunctions found in several brain disorders, such as schizophrenia, depression, attention deficit hyperactivity disorder and Parkinson’s disease. Only recently, the first selective TAAR1 agonist RO5166017 has been identified. To explore the molecular mechanisms of protein–agonist interaction and speed up the identification of new chemical entities acting on this biomolecular target, we derived a homology model for the hTAAR1. The putative protein‐binding site has been explored by comparing the hTAAR1 model with the β2‐adrenoreceptor binding site, available by X‐ray crystallization studies, and with the homology modelled 5HT1A receptor. The obtained results, in tandem with docking studies performed with RO5166017, β‐PEA and T1AM, provided an opportunity to reasonably identify the hTAAR1 key residues involved in ligand recognition and thus define important starting points to design new agonists.

Further Insights Into the Pharmacology of the Human Trace Amine-Associated Receptors: Discovery of Novel Ligands for TAAR1 by a Virtual Screening Approach

Trace Amine‐Associated Receptor 1 (TAAR1) is a G protein‐coupled receptor that is expressed in brain and periphery and responds to a class of compounds called trace amines, such as β‐phenylethylamine (β‐PEA), tyramine, tryptamine, octopamine. The receptor is known to have a very rich pharmacology and could be also activated by different classes of compounds, including dopaminergic, adrenergic and serotonergic ligands. It is expected that targeting hTAAR1 could provide a novel pharmacological approach for several human disorders, such as schizophrenia, depression, attention deficit hyperactivity disorder, Parkinsons disease and metabolic diseases. Only recently, a small number of selective hTAAR1 agonists (among which RO5166017 and T1AM) and antagonist (EPPTB), have been reported in literature. With the aim to identify new molecular entities able to act as ligands for this target, we used an homology model for the hTAAR1 and performed a virtual screening procedure on an in‐house database of compounds. A number of interesting molecules were selected and by testing them in an in vitro assay we found several agonists and one antagonist, with activities in the low micromolar range. These compounds could represent the starting point for the development of more potent and selective TAAR1 ligands.

Synthesis, Biological Evaluation, and Docking Studies of Tetrahydrofuran- Cyclopentanone- and Cyclopentanol-Based Ligands Acting at Adrenergic α1- and Serotonine 5-HT1A Receptors

A series of aralkylphenoxyethylamine and aralkylmethoxyphenylpiperazine compounds was synthesized and their in vitro pharmacological profile at both 5-HT(1A) receptors and α(1)-adrenoceptor subtypes was measured by binding assay and functional studies. The results showed that the replacement of the 1,3-dioxolane ring by a tetrahydrofuran, cyclopentanone, or cyclopentanol moiety leads to an overall reduction of in vitro affinity at the α(1)-adrenoceptor while both potency and efficacy were increased at the 5-HT(1A) receptor. A significant improvement of 5-HT(1A)/α(1) selectivity was observed in some of the cyclopentanol derivatives synthesized (4acis, 4ccis and trans). Compounds 2a and 4ccis emerged as novel and interesting 5-HT(1A) receptor antagonist (pK(i) = 8.70) and a 5-HT(1A) receptor partial agonist (pK(i) = 9.25, pD(2) = 9.03, E(max) = 47%, 5-HT(1A)/α(1a) = 69), respectively. Docking studies were performed at support of the biological data and to elucidate the molecular basis for 5-HT(1A) agonism/antagonism activity.

Rational design, synthesis and biological evaluation of new 1,5-diarylpyrazole derivatives as CB1 receptor antagonists, structurally related to rimonabant.

Among cannabinoid type-1 (CB(1)) receptor antagonists, those developed around the 1,5-diarylpyrazole scaffold of rimonabant (Acomplia are the most extensively investigated. In recent years, many SAR and QSAR reports on this topic have been published, focusing on the substitution and orientation of the N1 and C5 aryl functionalities and on the substituents at the 3-carboxamide position. In this context, the purpose of our study was to design and synthesize a set of 1-(2,4-dichlorophenyl)-5-arylpyrazoles strictly related to rimonabant, but with the hydrazide/amide group shifted from position 3 to position 4 of the pyrazole scaffold. The synthesized compounds were evaluated in vitro for their affinity on human CB(1) and CB(2) (cannabinoid type-2) receptors. Computational studies, performed both in the design step and after biological assays, contributed to rationalize the obtained results in terms of specific molecular interactions between antagonists and the human CB(1) receptor.

Homology modeling in tandem with 3D-QSAR analyses: A computational approach to depict the agonist binding site of the human CB2 receptor

CB2 receptor belongs to the large family of G-protein coupled receptors (GPCRs) controlling a wide variety of signal transduction. The recent crystallographic determination of human β2 adrenoreceptor and its high sequence similarity with human CB2 receptor (hCB2) prompted us to compute a theoretical model of hCB2 based also on β2 adrenoreceptor coordinates. This model has been employed to perform docking and molecular dynamic simulations on WIN-55,212-2 (CB2 agonist commonly used in binding experiments), in order to identify the putative CB2 receptor agonist binding site, followed by molecular docking studies on a series of indol-3-yl-tetramethylcyclopropyl ketone derivatives, a novel class of potent CB2 agonists. Successively, docking-based Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies were also performed. The CoMSIA model resulted to be the more predictive, showing r(ncv)(2) = 0.96, r(cv)(2) = 0.713, SEE = 0.193, F = 125.223, and r(2)(pred) = 0.78. The obtained 3D-QSAR models allowed us to derive more complete guidelines for the design of new analogues with improved potency so as to synthesize new indoles showing high CB2 affinity.

Docking-based 3D-QSAR analyses of pyrazole derivatives as HIV-1 non-nucleoside reverse transcriptase inhibitors

Abstract1,3,4,5-tetrasubstituted-pyrazoles (TPs) have been recently identified as a new class of potent non-nucleoside HIV-1 reverse transcriptase (RT) inhibitors. A computational strategy based on molecular docking studies, followed by docking-based comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), has been used to elucidate the atomic details of the RT/TP interactions and to identify the most important features impacting the TP antiretroviral activity. The final CoMSIA model resulted to be the more predictive, showing rncv2 = 0.97, rcv2 = 0.723, SEE = 0.248, F = 240.291, and r2pred = 0.77. The results allowed us to obtain useful information for the design of new compounds with improved potency toward WT HIV-1 and also against clinically relevant resistant mutants.

CoMFA and CoMSIA analyses on 1,2,3,4-tetrahydropyrrolo[3,4- b ]indole and benzimidazole derivatives as selective CB2 receptor agonists

AbstractNovel classes of cannabinoid 2 receptor (CB2) agonists based on 1,2,3,4-tetrahydropyrrolo[3,4-b]indole and benzimidazole scaffolds have shown high binding affinity toward CB2 receptor and good selectivity over cannabinoid 1 receptor (CB1). A computational study of comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) was performed, initially on each series of agonists, and subsequently on all compounds together, in order to identify the key structural features impacting their binding affinity. The final CoMSIA model resulted to be the more predictive, showing cross-validated r2 (rcv2) = 0.680, non cross-validated r2 (rncv2) = 0.97 and test set

Homology Modeling, Docking Studies and Molecular Dynamic Simulations Using Graphical Processing Unit Architecture to Probe the Type‐11 Phosphodiesterase Catalytic Site: A Computational Approach for the Rational Design of Selective Inhibitors

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