Katarina Nikolic

Design, synthesis, pharmacological evaluation, QSAR analysis, molecular modeling and ADMET of novel donepezil–indolyl hybrids as multipotent cholinesterase/monoamine oxidase inhibitors for the potential treatment of Alzheimer's disease

The design, synthesis, and pharmacological evaluation of donepezil-indolyl based amines 7-10, amides 12-16, and carboxylic acid derivatives 5 and 11, as multipotent ASS234 analogs, able to inhibit simultaneously cholinesterase (ChE) and monoamine oxidase (MAO) enzymes for the potential treatment of Alzheimers disease (AD), is reported. Theoretical studies using 3D-Quantitative Structure-Activity Relationship (3D-QSAR) was used to define 3D-pharmacophores for inhibition of MAO A/B, AChE, and BuChE enzymes. We found that, in general, and for the same substituent, amines are more potent ChE inhibitors (see compounds 12, 13 versus 7 and 8) or equipotent (see compounds 14, 15 versus 9 and 10) than the corresponding amides, showing a clear EeAChE inhibition selectivity. For the MAO inhibition, amides were not active, and among the amines, compound 14 was totally MAO A selective, while amines 15 and 16 were quite MAO A selective. Carboxylic acid derivatives 5 and 11 showed a multipotent moderate selective profile as EeACE and MAO A inhibitors. Propargylamine 15 [N-((5-(3-(1-benzylpiperidin-4-yl)propoxy)-1-methyl-1H-indol-2-yl)methyl)prop-2-yn-1-amine] resulted in the most potent hMAO A (IC50 = 5.5 ± 1.4 nM) and moderately potent hMAO B (IC50 = 150 ± 31 nM), EeAChE (IC50 = 190 ± 10 nM), and eqBuChE (IC50 = 830 ± 160 nM) inhibitor. However, the analogous N-allyl and the N-morpholine derivatives 16 and 14 deserve also attention as they show an attractive multipotent profile. To sum up, donepezil-indolyl hybrid 15 is a promising drug for further development for the potential prevention and treatment of AD.

Multitarget compounds bearing tacrine- and donepezil-like structural and functional motifs for the potential treatment of Alzheimer's disease.

Alzheimers disease is a multifactorial and fatal neurodegenerative disorder characterized by decline of cholinergic function, deregulation of other neurotransmitter systems, β-amyloid fibril deposition, and β-amyloid oligomers formation. Based on the involvement of a relevant number of biological systems in Alzheimers disease progression, multitarget compounds may enable therapeutic efficacy. Accordingly, compounds possessing, besides anticholinergic activity and β-amyloid aggregation inhibition properties, metal chelating and/or nitric oxide releasing properties with additional antioxidant capacity were developed. Other targets relevant to Alzheimers disease have also been considered in the last years for producing multitarget compounds such as β-secretase, monoamino oxidases, serotonin receptors and sigma 1 receptors. The purpose of this review will be to highlight recent reports on the development of multitarget compounds for Alzheimers disease published within the last years focusing on multifunctional ligands characterized by tacrine-like and donepezil-like structures.

N-methyl-N-((1-methyl-5-(3-(1-(2-methylbenzyl)piperidin-4-yl)propoxy)-1H-indol-2-yl)methyl)prop-2-yn-1-amine, a new cholinesterase and monoamine oxidase dual inhibitor

On the basis of N-((5-(3-(1-benzylpiperidin-4-yl)propoxy)-1-methyl-1H-indol-2-yl)methyl)-N-methylprop-2-yn-1-amine (II, ASS234) and QSAR predictions, in this work we have designed, synthesized, and evaluated a number of new indole derivatives from which we have identified N-methyl-N-((1-methyl-5-(3-(1-(2-methylbenzyl)piperidin-4-yl)propoxy)-1H-indol-2-yl)methyl)prop-2-yn-1-amine (2, MBA236) as a new cholinesterase and monoamine oxidase dual inhibitor.

QSAR study of imidazoline antihypertensive drugs.

The hypotensive effect of imidazoline ligands was attributed to both alpha(2)-adrenergic receptors and nonadrenergic imidazoline-1 receptors (I(1)-R). Selective I(1)-R ligands, devoid of the typical side effects of other centrally acting antihypertensive drugs, could be widely used in antihypertensive therapy. Thus, there is significant interest in developing new imidazoline analogs with higher selectivity and affinity for I(1) receptors. The quantitative structure-activity relationship (QSAR) study of 12 ligands was carried out using multilinear regression method on I(1)-R and alpha(2)-adrenergic receptors binding affinities on human platelets. The compounds have been studied using Becke3LYP/3-21G (d,p) and Becke3LYP/6-31G(d,p) DFT methods. Among 42 descriptors that were considered in generating the QSAR model, three descriptors such as partial atomic charges of nitrogen in the heterocyclic moiety, distribution coefficient, and molar refractivity of the ligands resulted in a statistically significant model with R(2)=0.935 and cross-validation parameter q(2)(pre) =0.803. The validation of the QSAR models was done by cross-validation and external test set prediction. The developed multiple linear regression models for the I(1)-R ligands were aimed to link the structures to their reported I(1)-R binding affinity log(1/K(i)). The theoretical approach indicates that an increase in distribution coefficient and molar refractivity value, together with a decrease in average N-charge in the heterocyclic moiety of the ligands, causes better binding affinity for active site of the I(1) receptors. The developed QSAR model is intended to predict I(1)-R binding affinity of related compounds and to define possible physicochemical, electrical, and structural requirements for selective I(1)-receptor ligands.

Multipotent cholinesterase/monoamine oxidase inhibitors for the treatment of Alzheimer’s disease: design, synthesis, biochemical evaluation, ADMET, molecular modeling, and QSAR analysis of novel donepezil-pyridyl hybrids

The design, synthesis, and biochemical evaluation of donepezil-pyridyl hybrids (DPHs) as multipotent cholinesterase (ChE) and monoamine oxidase (MAO) inhibitors for the potential treatment of Alzheimer’s disease (AD) is reported. The 3D-quantitative structure-activity relationship study was used to define 3D-pharmacophores for inhibition of MAO A/B, acetylcholinesterase (AChE), and butyrylcholinesterase (BuChE) enzymes and to design DPHs as novel multi-target drug candidates with potential impact in the therapy of AD. DPH14 (Electrophorus electricus AChE [EeAChE]: half maximal inhibitory concentration [IC50] =1.1±0.3 nM; equine butyrylcholinesterase [eqBuChE]: IC50 =600±80 nM) was 318-fold more potent for the inhibition of AChE, and 1.3-fold less potent for the inhibition of BuChE than the reference compound ASS234. DPH14 is a potent human recombinant BuChE (hBuChE) inhibitor, in the same range as DPH12 or DPH16, but 13.1-fold less potent than DPH15 for the inhibition of human recombinant AChE (hAChE). Compared with donepezil, DPH14 is almost equipotent for the inhibition of hAChE, and 8.8-fold more potent for hBuChE. Concerning human monoamine oxidase (hMAO) A inhibition, only DPH9 and 5 proved active, compound DPH9 being the most potent (IC50 [MAO A] =5,700±2,100 nM). For hMAO B, only DPHs 13 and 14 were moderate inhibitors, and compound DPH14 was the most potent (IC50 [MAO B] =3,950±940 nM). Molecular modeling of inhibitor DPH14 within EeAChE showed a binding mode with an extended conformation, interacting simultaneously with both catalytic and peripheral sites of EeAChE thanks to a linker of appropriate length. Absortion, distribution, metabolism, excretion and toxicity analysis showed that structures lacking phenyl-substituent show better druglikeness profiles; in particular, DPHs13–15 showed the most suitable absortion, distribution, metabolism, excretion and toxicity properties. Novel donepezil-pyridyl hybrid DPH14 is a potent, moderately selective hAChE and selective irreversible hMAO B inhibitor which might be considered as a promising compound for further development for the treatment of AD.

Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies.

HIGHLIGHTS Many CNS targets are being explored for multi-target drug design New databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compounds QSAR, virtual screening and docking methods increase the potential of rational drug design The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer‘s disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a “predictor” model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D1-R/D2-R/5-HT2A-R/H3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimers and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs.

One for All? Hitting Multiple Alzheimer's Disease Targets with One Drug

HIGHLIGHTS Many AD target combinations are being explored for multi-target drug design. New databases and models increase the potential of computational drug design Liraglutide and other antidiabetics are strong candidates for repurposing to AD. Donecopride a dual 5-HT/AChE inhibitor shows promise in pre-clinical studies Alzheimers Disease is a complex and multifactorial disease for which the mechanism is still not fully understood. As new insights into disease progression are discovered, new drugs must be designed to target those aspects of the disease that cause neuronal damage rather than just the symptoms currently addressed by single target drugs. It is becoming possible to target several aspects of the disease pathology at once using multi-target drugs (MTDs). Intended as an introduction for non-experts, this review describes the key MTD design approaches, namely structure-based, in silico, and data-mining, to evaluate what is preventing compounds progressing through the clinic to the market. Repurposing current drugs using their off-target effects reduces the cost of development, time to launch, and the uncertainty associated with safety and pharmacokinetics. The most promising drugs currently being investigated for repurposing to Alzheimers Disease are rasagiline, originally developed for the treatment of Parkinsons Disease, and liraglutide, an antidiabetic. Rational drug design can combine pharmacophores of multiple drugs, systematically change functional groups, and rank them by virtual screening. Hits confirmed experimentally are rationally modified to generate an effective multi-potent lead compound. Examples from this approach are ASS234 with properties similar to rasagiline, and donecopride, a hybrid of an acetylcholinesterase inhibitor and a 5-HT4 receptor agonist with pro-cognitive effects. Exploiting these interdisciplinary approaches, public-private collaborative lead factories promise faster delivery of new drugs to the clinic.

Procognitive Properties of Drugs with Single and Multitargeting H3 Receptor Antagonist Activities

The histamine H3 receptor (H3R) is an important modulator of numerous central control mechanisms. Novel lead optimizations for H3R antagonists/inverse agonists involved studies of structure–activity relationships, cross‐affinities, and pharmacokinetic properties of promising ligands. Blockade of inhibitory histamine H3 autoreceptors reinforces histaminergic transmission, while antagonism of H3 heteroreceptors accelerates the corticolimbic liberation of acetylcholine, norepinephrine, glutamate, dopamine, serotonin and gamma‐aminobutyric acid (GABA). The H3R positioned at numerous neurotransmission crossroads indicates therapeutic applications of small‐molecule H3R modulators in a number of psychiatric and neurodegenerative diseases with various clinical candidates available. Dual target drugs displaying H3R antagonism/inverse agonism with inhibition of acetylcholine esterase (AChE), histamine N‐methyltransferase (HMT), or serotonin transporter (SERT) are novel class of procognitive agents. Main chemical diversities, pharmacophores, and pharmacological profiles of procognitive agents acting as H3R antagonists/inverse agonists and dual H3R antagonists/inverse agonists with inhibiting activity on AChE, HMT, or SERT are highlighted here.

Pharmacophore development and SAR studies of imidazoline receptor ligands.

Relationship between biological responses and binding affinities at I(1)/I(2)/I(3) imidazoline receptors of compounds with imidazoline, pyrroline or oxazoline moieties was studied by 2D-QSAR, 3D-QSAR and quantitative pharmacophore development approaches. Since the I(1) imidazoline receptor is involved in central inhibition of sympathicus that produce hypotensive effect, the I(2) receptor is allosteric modulator of monoamine oxidase B (MAO-B) and the I(3) receptor regulates insulin secretion from pancreatic β-cells, design and synthesis of selective I(1)/I(2)/I(3) imidazoline ligands are very important for the development of new effective therapeutic agents. New agonists and antagonists with high selectivity for I(1)/I(2)/I(3) imidazoline receptor classes have been recently synthesized and examined. The present review will highlight the main chemical diversity and pharmacophore features of selective I(1)/I(2)/I(3) imidazoline receptor ligands.

Prediction of blood–brain barrier permeation of α-adrenergic and imidazoline receptor ligands using PAMPA technique and quantitative-structure permeability relationship analysis

Imidazoline receptor ligands are a numerous family of biologically active compounds known to produce central hypotensive effect by interaction with both α2-adrenoreceptors (α2-AR) and imidazoline receptors (IRs). Recent hypotheses connect those ligands with several neurological disorders. Therefore some IRs ligands are examined as novel centrally acting antihypertensives and drug candidates for treatment of various neurological diseases. Effective Blood-Brain Barrier (BBB) permeability (P(e)) of 18 IRs/α-ARs ligands and 22 Central Nervous System (CNS) drugs was experimentally determined using Parallel Artificial Membrane Permeability Assay (PAMPA) and studied by the Quantitative-Structure-Permeability Relationship (QSPR) methodology. The dominant molecules/cations species of compounds have been calculated at pH = 7.4. The analyzed ligands were optimized using Density Functional Theory (B3LYP/6-31G(d,p)) included in ChemBio3D Ultra 13.0 program and molecule descriptors for optimized compounds were calculated using ChemBio3D Ultra 13.0, Dragon 6.0 and ADMET predictor 6.5 software. Effective permeability of compounds was used as dependent variable (Y), while calculated molecular parametres were used as independent variables (X) in the QSPR study. SIMCA P+ 12.0 was used for Partial Least Square (PLS) analysis, while the stepwise Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) modeling were performed using STASTICA Neural Networks 4.0. Predictive potential of the formed models was confirmed by Leave-One-Out Cross- and external-validation and the most reliable models were selected. The descriptors that are important for model building are identified as well as their influence on BBB permeability. Results of the QSPR studies could be used as time and cost efficient screening tools for evaluation of BBB permeation of novel α-adrenergic/imidazoline receptor ligands, as promising drug candidates for treatment of hypertension or neurological diseases.