Discovery of novel choline acetyltransferase inhibitors using structure-based virtual screening

Virtual screening and biological activity evaluation of novel efflux pump inhibitors targeting AdeB

The AdeABC efflux pump is an important mechanism causing multidrug resistance in Acinetobacter baumannii, and its main component AdeB can recognize carbapenems, aminoglycosides, and other multi-class antibiotics and efflux them intracellularly, which is an ideal target for the development of anti-multidrug resistant bacteria drugs. Here, we combined multiple computer-aided drug design methods to target AdeB to identify promising novel structural inhibitors. Virtual screening was performed by molecular docking and molecular dynamics simulation (MD) and 12 potential compounds were identified from the databases. Meanwhile, their biological activities were validated by in vitro activity assays, and ChemDiv L676-2179 (γ-IFN), ChemDiv L676-1461, and Chembridge 53717615 were confirmed to suppress efflux effects and restore antibiotic susceptibility of resistant bacteria, which are expected to be developed as adjuvant drugs for the treatment of multi-drug resistant Acinetobacter baumannii clinical infections.

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates to test in in vitro assays. We then illustrate how CADD can be used to optimize the potency of experimentally validated hit compounds from virtual screening for use in positron emission tomography (PET). Finally, we conclude with a survey of the newest techniques in CADD employing machine learning (ML).

Mechanistic Insight into the Inhibition of Choline Acetyltransferase by Proton Pump Inhibitors

Various pharmacoepidemiological investigational studies have indicated that Proton Pump Inhibitors (PPIs) may increase the likelihood of developing Alzheimer's disease (AD) and non-AD related dementias. Previously, we have reported the inhibition of the acetylcholine biosynthesizing enzyme choline acetyltransferase (ChAT) by PPIs, for which omeprazole, lansoprazole, and pantoprazole exhibited IC₅₀ values of 0.1, 1.5, and 5.3 μM, respectively. In this study we utilize a battery of computational tools to perceive a mechanistic insight into the molecular interaction of PPIs with the ChAT binding pocket that may further help in designing novel ChAT ligands. Various in-silico tools make it possible for us to elucidate the binding interaction, conformational stability, and dynamics of the protein-ligand complexes within a 200 ns time frame. Further, the binding free energies for the PPI-ChAT complexes were explored. The results suggest that the PPIs exhibit equal or higher binding affinity toward the ChAT catalytic tunnel and are stable throughout the simulated time and that the pyridine ring of the PPIs interacts primarily with the catalytic residue His₃₂₄. A free energy landscape analysis showed that the folding process was linear, and the residue interaction network analysis can provide insight into the roles of various amino acid residues in stabilization of the PPIs in the ChAT binding pocket. As a major factor for the onset of Alzheimer's disease is linked to cholinergic dysfunction, our previous and the present findings give clear insight into the PPI interaction with ChAT. The scaffold can be further simplified to develop novel ChAT ligands, which can also be used as ChAT tracer probes for the diagnosis of cholinergic dysfunction and to initiate timely therapeutic interventions to prevent or delay the progression of AD.

Structure-based virtual screening and molecular dynamics simulation for the identification of sphingosine kinase-2 inhibitors as potential analgesics

Neuropathic pain is due to an injury or disease of the somatosensory nervous system, which accounts for a significant economical and health burden to society. Due to poor understanding of their underlying mechanisms, the available treatments merely provide symptomatic relief and precipitates a variety of adverse effects. This suggests that there is an unmet medical need that must be addressed with effective strategies for the development of novel therapeutics. Sphingosine kinase 2 (SphK2) is an oncogenic lipid kinase that has emerged as a promising target for chronic pain and other diseases. In the present study, we have explored the structure-based virtual high-throughput screening of the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE) to identify potent natural products as inhibitors of SphK2. A molecular docking study was performed to calculate binding affinities and specificity to identify potential leads against SphK2. Initially, hits were selected by the implementation of absorption, distribution, metabolism, excretion and toxicity properties, Lipinski rule, and PAINS filters. The top-scoring hits also exhibiting an optimal ADMET profile were subjected to MM/GBSA free binding free energy calculation and molecular dynamics simulation. The results from molecular dynamics simulation revealed a stable ligand -SphK2 complex with protein and ligand RMSD within reasonable limits. Overall, we identified compounds, NuBBE_972 and NuBBE_1107 as potential inhibitors of SphK2 with optimal pharmacokinetic properties which have the potential to be developed as novel therapeutics for the management of chronic pain.Communicated by Ramaswamy H. Sarma.

Betaine Attenuates Chronic Constriction Injury-Induced Neuropathic Pain in Rats by Inhibiting KIF17-Mediated Nociception

Kinesin superfamily proteins transport a diverse range of cargo, including excitatory receptors to the dendrite and axon of a neuron via retrograde and anterograde fashions along microtubules, causing central sensitization and neuropathic pain. In this study, we have performed in silico molecular dynamics simulation to delineate the dynamic interaction of betaine with KIF17, a kinesin protein, known to be involved in neuropathic pain. The results from the molecular dynamics study suggest that the betaine-KIF17 complex is stabilized through hydrogen bonding, polar interactions, and water bridges. Findings from in vivo studies suggest a significant increase in pain hypersensitivity, oxido-nitrosative stress, and KIF17 overexpression in the sciatic nerve, dorsal root ganglion (DRG), and spinal cord of nerve-injured rats, which was significantly attenuated on treatment with betaine. Betaine treatment also restored the increased NR2B expressions and levels of proinflammatory cytokines and neuropeptides in the DRG and spinal cord of nerve-injured rats. Findings from the current study suggest that betaine attenuates neuropathic pain in rats by inhibiting KIF17-NR2B-mediated neuroinflammatory signaling.

Structure-based virtual screening for identification of potential non-steroidal LXR modulators against neurodegenerative conditions

Liver X Receptors (LXRs) are members of the nuclear receptor superfamily that regulate cholesterol metabolism. LXRs have been suggested as promising targets against many neurodegenerative diseases (NDDs). The present study was aimed to identify novel non-steroidal molecules that may potentially modulate LXR activity. The structure-based virtual screening (SBVS) was used to search for suitable compounds from the Asinex library. The top hits were selected and filtered based on their binding affinity for LXR α and β isoforms. Based on molecular docking and scoring results, 24 compounds were selected that had binding energy in the range of - 13.9 to - 12 for LXRα and - 12.5 to - 11 for LXRβ, which were higher than the reference ligands (GW3965 and TO901317). Further, the five hits referred to as model 29, 64, 202, 250, 313 were selected by virtue of their binding interactions with amino acid residues at the active site of LXRs. The selected hits were then subjected to absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis and blood-brain permeability prediction. It was observed that the selected hits had better pharmacokinetic properties with no toxicity and could cross blood-brain barrier. Further, the selected hits were analysed for dynamic evolution of the system with LXRs by molecular dynamics (MD) simulation at 100 ns using GROMACS. The MD simulation results validated that selected hits possess a remarkable amount of flexibility, stability, compactness, binding energy and exhibited limited conformational modification. The root mean square deviation (RMSD) values of the top-scoring hits complexed with LXRα and LXRβ were 0.05-0.6 nm and 0.05-0.45 nm respectively, which is greater than the protein itself. Altogether the study identified potential non-steroidal LXR modulators that appear to be effective against various neurodegenerative conditions involving perturbed cholesterol and lipid homeostasis.

Metabolic and Cellular Compartments of Acetyl-CoA in the Healthy and Diseased Brain

The human brain is characterised by the most diverse morphological, metabolic and functional structure among all body tissues. This is due to the existence of diverse neurons secreting various neurotransmitters and mutually modulating their own activity through thousands of pre- and postsynaptic interconnections in each neuron. Astroglial, microglial and oligodendroglial cells and neurons reciprocally regulate the metabolism of key energy substrates, thereby exerting several neuroprotective, neurotoxic and regulatory effects on neuronal viability and neurotransmitter functions. Maintenance of the pool of mitochondrial acetyl-CoA derived from glycolytic glucose metabolism is a key factor for neuronal survival. Thus, acetyl-CoA is regarded as a direct energy precursor through the TCA cycle and respiratory chain, thereby affecting brain cell viability. It is also used for hundreds of acetylation reactions, including N-acetyl aspartate synthesis in neuronal mitochondria, acetylcholine synthesis in cholinergic neurons, as well as divergent acetylations of several proteins, peptides, histones and low-molecular-weight species in all cellular compartments. Therefore, acetyl-CoA should be considered as the central point of metabolism maintaining equilibrium between anabolic and catabolic pathways in the brain. This review presents data supporting this thesis.

Towards the discovery of potential RdRp inhibitors for the treatment of COVID-19: structure guided virtual screening, computational ADME and molecular dynamics study

Coronavirus disease 2019 (COVID-19) has become a major challenge affecting almost every corner of the world, with more than five million deaths worldwide. Despite several efforts, no drug or vaccine has shown the potential to check the ever-mutating SARS-COV-2. The emergence of novel variants is a major concern increasing the need for the discovery of novel therapeutics for the management of this pandemic. Out of several potential drug targets such as S protein, human ACE2, TMPRSS2 (transmembrane protease serine 2), 3CLpro, RdRp, and PLpro (papain-like protease), RNA-dependent RNA polymerase (RdRP) is a vital enzyme for viral RNA replication in the mammalian host cell and is one of the legitimate targets for the development of therapeutics against this disease. In this study, we have performed structure-based virtual screening to identify potential hit compounds against RdRp using molecular docking of a commercially available small molecule library of structurally diverse and drug-like molecules. Since non-optimal ADME properties create hurdles in the clinical development of drugs, we performed detailed in silico ADMET prediction to facilitate the selection of compounds for further studies. The results from the ADMET study indicated that most of the hit compounds had optimal properties. Moreover, to explore the conformational dynamics of protein-ligand interaction, we have performed an atomistic molecular dynamics simulation which indicated a stable interaction throughout the simulation period. We believe that the current findings may assist in the discovery of drug candidates against SARS-CoV-2.

Systemic administration of choline acetyltransferase decreases blood pressure in murine hypertension

Acetylcholine (ACh) decreases blood pressure by stimulating endothelium nitric oxide-dependent vasodilation in resistance arterioles. Normal plasma contains choline acetyltransferase (ChAT) and its biosynthetic product ACh at appreciable concentrations to potentially act upon the endothelium to affect blood pressure. Recently we discovered a T-cell subset expressing ChAT (TChAT), whereby genetic ablation of ChAT in these cells produces hypertension, indicating that production of ACh by TChAT regulates blood pressure. Accordingly, we reasoned that increasing systemic ChAT concentrations might induce vasodilation and reduce blood pressure. To evaluate this possibility, recombinant ChAT was administered intraperitoneally to mice having angiotensin II-induced hypertension. This intervention significantly and dose-dependently decreased mean arterial pressure. ChAT-mediated attenuation of blood pressure was reversed by administration of the nitric oxide synthesis blocker L-nitro arginine methyl ester, indicating ChAT administration decreases blood pressure by stimulating nitic oxide dependent vasodilation, consistent with an effect of ACh on the endothelium. To prolong the half life of circulating ChAT, the molecule was modified by covalently attaching repeating units of polyethylene glycol (PEG), resulting in enzymatically active PEG-ChAT. Administration of PEG-ChAT to hypertensive mice decreased mean arterial pressure with a longer response duration when compared to ChAT. Together these findings suggest further studies are warranted on the role of ChAT in hypertension.

In Situ Assembly of Choline Acetyltransferase Ligands by a Hydrothiolation Reaction Reveals Key Determinants for Inhibitor Design

The potential drug target choline acetyltransferase (ChAT) catalyses the production of the neurotransmitter acetylcholine in cholinergic neurons, T-cells, and B-cells. Herein, we show that arylvinylpyridiniums (AVPs), the most widely studied class of ChAT inhibitors, act as substrate in an unusual coenzyme A-dependent hydrothiolation reaction. This in situ synthesis yields an adduct that is the actual enzyme inhibitor. The adduct is deeply buried in the active site tunnel of ChAT and interactions with a hydrophobic pocket near the choline binding site have major implications for the molecular recognition of inhibitors. Our findings clarify the inhibition mechanism of AVPs, establish a drug modality that exploits a target-catalysed reaction between exogenous and endogenous precursors, and provide new directions for the development of ChAT inhibitors with improved potency and bioactivity.

Esomeprazole reduces sperm motility index by targeting the spermic cholinergic machinery: A mechanistic study for the association between use of proton pump inhibitors and reduced sperm motility index

Recent studies have linked prolonged use of the most commonly prescribed proton pump inhibitors (PPIs) with declined human sperm function and infertility. Here, we report for the first time the most plausible underlying mechanism for this unwarranted secondary mode of action. We followed up on a recent serendipitous discovery in our laboratory regarding PPIs' off-target action and performed detailed pharmacodynamic analyses by combining in silico and in vitro studies to determine the off-target effect of one of the most commonly used PPI, esomeprazole, on the key human acetylcholine biosynthesizing enzyme, choline acetyltransferase (ChAT; EC 2.3.1.6). A pivotal enzyme in the spermic cholinergic system that governs the sperm motility, concentration and quality. Our results were conclusive and showed that both the racemic form, omeprazole and its pure S-enantiomer, esomeprazole, acted as potent mixed-competitive inhibitor of human ChAT with a global inhibition constant (K_i) of 88 nM (95%CI: 10-167 nM) for esomeprazole and 178 nM (95%CI: 140-230 nM) for the racemic drug omeprazole. Most importantly, esomeprazole substantially reduces both total number of motile sperm (by 36%, p < 0.001; and 21% p < 0.0001, at 10 and 100 nM, respectively) as well as the total number of sperm with progressive motility (by 42% p < 0.0016 and by 26% p < 0.0001, respectively) after 60 min relative to 20 min incubation in our ex vivo functional assay performed on ejaculated human sperm. In conclusion, this study presents a completely new perspective regarding PPIs secondary mode of action/unwarranted side effects and calls for further mechanistic and larger clinical studies to elucidate the role of PPIs in infertility.

The TLC-Bioautography as a Tool for Rapid Enzyme Inhibitors detection - A Review

Microorganisms and plants can be important sources of many compounds with potential pharmaceutical applications. Extraction of these matrices is one of the ways of identifying the presence of inhibitory active substances against enzymes whose high activity leads to serious human diseases including cancer, Parkinson's or Crohn's diseases. The isolation and purification of inhibitors are time-consuming and expensive steps in the analysis of the crude extract and therefore, it is necessary to find a fast, efficient, and inexpensive method for screening extracts of interest. TLC-Bioautography combines the separation of the extract on a thin layer with its subsequent biological analysis. TLC-Bioautography methods have been developed for several classes of enzymes including oxidoreductases, hydrolases and isomerases, and there is a potential for developing functional methods for other classes of enzymes. This review summarizes known TLC-Bioautography methods and their applications for determining the presence of enzyme inhibitors in extracts and compares the effectiveness of different methodological approaches. It also indicates the current state and perspective of the development of TLC-Bioautography and its possible future applications.

Proton pump inhibitors act with unprecedented potencies as inhibitors of the acetylcholine biosynthesizing enzyme-A plausible missing link for their association with incidence of dementia

INTRODUCTION

Several pharmacoepidemiological studies indicate that proton pump inhibitors (PPIs) significantly increase the risk of dementia. Yet, the underlying mechanism is not known. Here, we report the discovery of an unprecedented mode of action of PPIs that explains how PPIs may increase the risk of dementia.

METHODS

Advanced in silico docking analyses and detailed enzymological assessments were performed on PPIs against the core-cholinergic enzyme, choline-acetyltransferase (ChAT), responsible for biosynthesis of acetylcholine (ACh).

RESULTS

This report shows compelling evidence that PPIs act as inhibitors of ChAT, with high selectivity and unprecedented potencies that lie far below their in vivo plasma and brain concentrations.

DISCUSSION

Given that accumulating evidence points at cholinergic dysfunction as a driving force of major dementia disorders, our findings mechanistically explain how prolonged use of PPIs may increase incidence of dementia. This call for restrictions for prolonged use of PPIs in elderly, and in patients with dementia or amyotrophic lateral sclerosis.

Advances in Docking

BACKGROUND

Design of small molecules which are able to bind to the protein responsible for a disease is the key step of the entire process of the new medicine discovery. Atomistic computer modeling can significantly improve effectiveness of such design. The accurate calculation of the free energy of binding a small molecule (a ligand) to the target protein is the most important problem of such modeling. Docking is one of the most popular molecular modeling methods for finding ligand binding poses in the target protein and calculating the protein-ligand binding energy. This energy is used for finding the most active compounds for the given target protein. This short review aims to give a concise description of distinctive features of docking programs focusing on computation methods and approximations influencing their accuracy.

METHODS

This review is based on the peer-reviewed research literature including author's own publications. The main features of several representative docking programs are briefly described focusing on their characteristics influencing docking accuracy: force fields, energy calculations, solvent models, algorithms of the best ligand pose search, global and local optimizations, ligand and target protein flexibility, and the simplifications made for the docking accelerating. Apart from other recent reviews focused mainly on the performance of different docking programs, in this work, an attempt is made to extract the most important functional characteristics defining the docking accuracy. Also a roadmap for increasing the docking accuracy is proposed. This is based on the new generation of docking programs which have been realized recently. These programs and respective new global optimization algorithms are described shortly.

RESULTS

Several popular conventional docking programs are considered. Their search of the best ligand pose is based explicitly or implicitly on the global optimization problem. Several algorithms are used to solve this problem, and among them, the heuristic genetic algorithm is distinguished by its popularity and an elaborate design. All conventional docking programs for their acceleration use the preliminary calculated grids of protein-ligand interaction potentials or preferable points of protein and ligand conjugation. These approaches and commonly used fitting parameters restrict strongly the docking accuracy. Solvent is considered in exceedingly simplified approaches in the course of the global optimization and the search for the best ligand poses. More accurate approaches on the base of implicit solvent models are used frequently for more careful binding energy calculations after docking. The new generation of docking programs are developed recently. They find the spectrum of low energy minima of a protein-ligand complex including the global minimum. These programs should be more accurate because they do not use a preliminary calculated grid of protein-ligand interaction potentials and other simplifications, the energy of any conformation of the molecular system is calculated in the frame of a given force field and there are no fitting parameters. A new docking algorithm is developed and fulfilled specially for the new docking programs. This algorithm allows docking a flexible ligand into a flexible protein with several dozen mobile atoms on the base of the global energy minimum search. Such docking results in improving the accuracy of ligand positioning in the docking process. The adequate choice of the method of molecular energy calculations also results in the better docking positioning accuracy. An advancement in the application of quantum chemistry methods to docking and scoring is revealed.

CONCLUSION

The findings of this review confirm the great demand in docking programs for discovery of new medicine substances with the help of molecular modeling. New trends in docking programs design are revealed. These trends are focused on the increase of the docking accuracy at the expense of more accurate molecular energy calculations without any fitting parameters, including quantum-chemical methods and implicit solvent models, and by using new global optimization algorithms which make it possible to treat flexibility of ligands and mobility of protein atoms simultaneously. Finally, it is shown that all the necessary prerequisites for increasing the docking accuracy can be accomplished in practice.

A new fluorescent probe for sensing of biothiols and screening of acetylcholinesterase inhibitors

An axial N₂O-type BODIPY probe has been proposed for sensitive and selective sensing of biothiols and screening of AChE inhibitors using a fluorescence turn-on assay.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Photocatalytic Hydrogen Evolution via Water Splitting: A Short Review

Photocatalytic H2 generation via water splitting is increasingly gaining attention as a viable alternative for improving the performance of H2 production for solar energy conversion. Many methods were developed to enhance photocatalyst efficiency, primarily by modifying its morphology, crystallization, and electrical properties. Here, we summarize recent achievements in the synthesis and application of various photocatalysts. The rational design of novel photocatalysts was achieved using various strategies, and the applications of novel materials for H2 production are displayed herein. Meanwhile, the challenges and prospects for the future development of H2-producing photocatalysts are also summarized.

Acetylcholine signaling system in progression of lung cancers

The neurotransmitter acetylcholine (ACh) acts as an autocrine growth factor for human lung cancer. Several lines of evidence show that lung cancer cells express all of the proteins required for the uptake of choline (choline transporter 1, choline transporter-like proteins) synthesis of ACh (choline acetyltransferase, carnitine acetyltransferase), transport of ACh (vesicular acetylcholine transport, OCTs, OCTNs) and degradation of ACh (acetylcholinesterase, butyrylcholinesterase). The released ACh binds back to nicotinic (nAChRs) and muscarinic receptors on lung cancer cells to accelerate their proliferation, migration and invasion. Out of all components of the cholinergic pathway, the nAChR-signaling has been studied the most intensely. The reason for this trend is due to genome-wide data studies showing that nicotinic receptor subtypes are involved in lung cancer risk, the relationship between cigarette smoke and lung cancer risk as well as the rising popularity of electronic cigarettes considered by many as a "safe" alternative to smoking. There are a small number of articles which review the contribution of the other cholinergic proteins in the pathophysiology of lung cancer. The primary objective of this review article is to discuss the function of the acetylcholine-signaling proteins in the progression of lung cancer. The investigation of the role of cholinergic network in lung cancer will pave the way to novel molecular targets and drugs in this lethal malignancy.

Soluble Aβ42 Acts as Allosteric Activator of the Core Cholinergic Enzyme Choline Acetyltransferase

Two major questions in the field of Alzheimer-type dementia remain elusive. One is the native function of amyloid-β (Aβ) peptides and the other is an early deficit in the central cholinergic network. Nevertheless, recent evidence suggests that Aβ peptides are involved in the regulation of acetylcholine (ACh) homeostasis either by allosteric activation of ACh-degrading cholinesterases or by inhibiting the high-affinity choline uptake transporter. In the current study, we report that Aβ peptides, in particular Aβ42, allosterically enhances the catalytic rate of the core-cholinergic enzyme choline acetyltransferase (ChAT), responsible for biosynthesis of ACh. Detailed in vitro enzyme kinetic analysis indicated that both soluble Aβ40 and Aβ42 enhanced the catalytic efficiency of ChAT by ∼21% and 26% at physiological concentration ranges found in human cerebrospinal fluid (CSF). Further analyses indicated that activation of ChAT by Aβ was highly specific. Intriguingly, Aβ42 exhibited an EC₅₀ of activation potency at 10-fold lower concentrations compared to Aβ40. The activation was persistent even in the presence of a physiological Aβ 40/42 mixture ratio, expected in human CSF. In conclusion, we report for the first time that Aβ42 peptide acts as allosteric enhancers of ACh-biosynthesizing enzyme ChAT. Together with two previous observations, this points to a complex molecular cross-talk between Aβ and the enzymatic machinery involved in maintaining cellular, synaptic and extra-synaptic ACh homeostasis, warranting further investigation.

The Regulatory Effects of Acetyl-CoA Distribution in the Healthy and Diseased Brain

Brain neurons, to support their neurotransmitter functions, require a several times higher supply of glucose than non-excitable cells. Pyruvate, the end product of glycolysis, through pyruvate dehydrogenase complex reaction, is a principal source of acetyl-CoA, which is a direct energy substrate in all brain cells. Several neurodegenerative conditions result in the inhibition of pyruvate dehydrogenase and decrease of acetyl-CoA synthesis in mitochondria. This attenuates metabolic flux through TCA in the mitochondria, yielding energy deficits and inhibition of diverse synthetic acetylation reactions in all neuronal sub-compartments. The acetyl-CoA concentrations in neuronal mitochondrial and cytoplasmic compartments are in the range of 10 and 7 μmol/L, respectively. They appear to be from 2 to 20 times lower than acetyl-CoA Km values for carnitine acetyltransferase, acetyl-CoA carboxylase, aspartate acetyltransferase, choline acetyltransferase, sphingosine kinase 1 acetyltransferase, acetyl-CoA hydrolase, and acetyl-CoA acetyltransferase, respectively. Therefore, alterations in acetyl-CoA levels alone may significantly change the rates of metabolic fluxes through multiple acetylation reactions in brain cells in different physiologic and pathologic conditions. Such substrate-dependent alterations in cytoplasmic, endoplasmic reticulum or nuclear acetylations may directly affect ACh synthesis, protein acetylations, and gene expression. Thereby, acetyl-CoA may regulate the functional and adaptative properties of neuronal and non-neuronal brain cells. The excitotoxicity-evoked intracellular zinc excess hits several intracellular targets, yielding the collapse of energy balance and impairment of the functional and structural integrity of postsynaptic cholinergic neurons. Acute disruption of brain energy homeostasis activates slow accumulation of amyloid-β_1-42 (Aβ). Extra and intracellular oligomeric deposits of Aβ affect diverse transporting and signaling pathways in neuronal cells. It may combine with multiple neurotoxic signals, aggravating their detrimental effects on neuronal cells. This review presents evidences that changes of intraneuronal levels and compartmentation of acetyl-CoA may contribute significantly to neurotoxic pathomechanisms of different neurodegenerative brain disorders.