In silico reconstruction of human dopamine transporter and design of novel neuroprotective drugs for Parkinson’s disease

Abnormally folded alpha-synuclein protein, dysfunctional mitochondria, increased oxidative stress and reduced dopamine neurotransmitter synthesis are a ll extremely well characterized phenomena in Parkinson’s disease (PD) and are thought to be interconnected. While direct targeting of these areas has demonstrated neuroprotection in vitro and in vivo, there has been a major lack of success in clinical trials. A critical component in the failure of these clinical trials is the inability to specifically target drugs to dopamine producing neurons in the brain. New drugs targeting the dopaminergic neurons by specific uptake through the human dopamine transporter (hDAT) could represent a viable strategy for establishing selective neuroprotection. Molecules able to increase the bioactive amount of extracellular dopamine, thereby enhancing and compensating a loss of dopaminergic neurotransmission, and to exert neuroprotective response because of their accumulation in the cytoplasm, are required. By means of homology modeling, molecular docking and molecular dynamics simulations, we have generated 3D structure models of hDAT in complex with substrate and inhibitors. Our results clearly reveal differences in binding kinetics of these compounds to the hDAT in the open and closed conformations, critical for future drug design. The established in silico approach allowed the identification of three promising substrate compounds that were subsequently analyzed for their efficiency in inhibiting hDAT-dependent fluorescent substrate uptake, through in vitro live cell imaging experiments. Taken together, our work presents the first implementation of a combined in silico/in vitro-approach enabling the selection of promising dopaminergic neuron specific substrates.Rad je osvojio prvu nagradu na 2. Simpozijumu iz biomedicine, 2019

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 designNew databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compoundsQSAR, 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 Alzheimer's 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

Docking of novel reversible monoamine oxidase-B inhibitors: efficient prediction of ligand binding sites and estimation of inhibitors thermodynamic properties

Monoamine oxidase (MAO, EC 1.4.3.4) is a flavoenzyme bound to the mitochondrial outer membranes of the cells, which is responsible for the oxidative deamination of neurotransmitter and dietary amines. It has two distinct isozymic forms, designated MAO-A and MAO-B, each displaying different substrate and inhibitor specificities. They are the well-known target for antidepressant, Parkinson?s disease and neuroprotective drugs. Elucidation of the x-ray crystallographic structure of MAO-B has opened the way for molecular modeling studies. In this research 12 reversible and MAO-B selective inhibitors have been docked computationally to the active site of the MAO-B enzyme. AutoDock 3.0.5 was employed to perform the automated molecular docking. The result of docking studies generated thermodynamic properties, such as free energy of bindings (?Gb) and inhibition constants (K i) for the inhibitors. Moreover, 3D pictures of inhibitor-enzyme complexes afforded valuable data regarding the binding orientation of each inhibitor in the active site of MAO-B

In silico identification of novel and selective monoamine oxidase B inhibitors

Monoamine oxidases (MAO) A and B are flavin adenine dinucleotides containing enzymes bound to the mitochondrial outer membranes of the cells of the brain, liver, intestine, and placenta, as well as platelets. Recently, selective MAO-B inhibitors have received increasing attention due to their neuroprotective properties and the multiple roles they can play in the therapy of neurodegenerative disorders. This study was based on 10 scaffolds that were selected from more than a million lead compounds in the ZINCv12 lead library for their structural and physicochemical properties which inhibit MAO-B. Utilizing ZINC and Accelrys 3.1 fragment-based libraries, which contain about 400 thousand fragments, we generated 200 potential candidates. GOLD, LibDock, and AutoDock 4.02 were used to identify the inhibition constants and their position in the active sites of both MAO isozymes. The dispositions of the candidate molecules within the organism were checked with ADMET PSA 2D (polar surface area) against ADMET AlogP98 (the logarithm of the partition coefficient between n-octanol and water). The MAO-B inhibition activities of the candidates were compared with the properties of rasagiline which is known to be a selective inhibitor of MAO-B