In silico repurposing of antipsychotic drugs for Alzheimer's disease

Novel 1,2,4-triazole derivatives containing the naphthalene moiety as selective butyrylcholinesterase inhibitors: Design, synthesis, and biological evaluation

Butyrylcholinesterase (BChE) is considered a promising therapeutic target for treating Alzheimer's disease due to the increase in the levels and activity of BChE in the late stage of the disease. In this study, a series of novel 1,2,4-triazole derivatives bearing the naphthalene moiety linked to the benzothiazole, thiazole, and phenyl scaffolds via amid chain were designed and synthesized as potential and selective BChE inhibitors. The results of the inhibitory activity studies revealed that most of these compounds exhibited significant inhibitor potency on BChE. Compounds 35a (0.025 ± 0.01 μM) and 37a (0.035 ± 0.01 μM) displayed the most potent inhibitory activity, with excellent selectivity against BChE over acetylcholinesterase (SIBChE, 23,686 and 16,936, respectively) among the target compounds. The kinetics studies revealed that these compounds behaved with noncompetitive BChE inhibitors. Molecular docking studies indicated that 35a and 37a fit well into the active side of BChE. In addition, 35a and 37a also had the lowest cytotoxicity for human neuroblastoma cells (SH-SY5Y), potential antioxidant capacity, moderate inhibition potency on amyloid-β1-42 aggregation, and significant neuroprotective effect against SH-SY5Y cell injury induced by H2O2 and amyloid-β1-42. All results suggest that these compounds might be considered as promising new lead compounds in the drug discovery process for the treatment of late-stage Alzheimer's disease.

Innovative Therapeutic Strategies in Alzheimer's Disease: A Synergistic Approach to Neurodegenerative Disorders

Alzheimer's disease (AD) remains a significant challenge in the field of neurodegenerative disorders, even nearly a century after its discovery, due to the elusive nature of its causes. The development of drugs that target multiple aspects of the disease has emerged as a promising strategy to address the complexities of AD and related conditions. The immune system's role, particularly in AD, has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in targeting antibodies against amyloid-β (Aβ) and using messenger RNA for genetic translation have revolutionized the production of antibodies and drug development, opening new possibilities for treatment. Despite these advancements, conventional therapies for AD, such as Cognex, Exelon, Razadyne, and Aricept, often have limited long-term effectiveness, underscoring the need for innovative solutions. This necessity has led to the incorporation advanced technologies like artificial intelligence and machine learning into the drug discovery process for neurodegenerative diseases. These technologies help identify therapeutic targets and optimize lead compounds, offering a more effective approach to addressing the challenges of AD and similar conditions.

Benzimidazole and Benzoxazole Derivatives Against Alzheimer's Disease

Benzimidazole and benzoxazole derivatives are included in the category of medical drugs in a wide range of areas such as anticancer, anticoagulant, antihypertensive, anti- inflammatory, antimicrobial, antiparasitic, antiviral, antioxidant, immunomodulators, proton pump inhibitors, hormone modulators, etc. Many researchers have focused on synthesizing more effective benzimidazole and benzoxazole derivatives for screening various biological activities. In addition, there are benzimidazole and benzoxazole rings as bioisosteres of aromatic rings found in drugs used in the treatment of Alzheimer's disease. Because of the diverse activity of the benzimidazole and benzoxazole rings and bioisosteres marketed as drugs for Alzheimer Diseases, designed compounds containing these rings are likely to be effective against Alzheimer's disease. In this study, the effectiveness of compounds containing benzimidazole and benzoxazole rings against Alzheimer's disease will be examined.

The Alzheimer's Knowledge Base: A Knowledge Graph for Alzheimer Disease Research

BACKGROUND

As global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease's etiology and response to drugs.

OBJECTIVE

We designed the Alzheimer's Knowledge Base (AlzKB) to alleviate this need by providing a comprehensive knowledge representation of AD etiology and candidate therapeutics.

METHODS

We designed the AlzKB as a large, heterogeneous graph knowledge base assembled using 22 diverse external data sources describing biological and pharmaceutical entities at different levels of organization (eg, chemicals, genes, anatomy, and diseases). AlzKB uses a Web Ontology Language 2 ontology to enforce semantic consistency and allow for ontological inference. We provide a public version of AlzKB and allow users to run and modify local versions of the knowledge base.

RESULTS

AlzKB is freely available on the web and currently contains 118,902 entities with 1,309,527 relationships between those entities. To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that may treat AD. For each use case, AlzKB recovers known therapeutic associations while proposing biologically plausible new ones.

CONCLUSIONS

AlzKB is a new, publicly available knowledge resource that enables researchers to discover complex translational associations for AD drug discovery. Through 2 use cases, we show that it is a valuable tool for proposing novel therapeutic hypotheses based on public biomedical knowledge.

A systematic review of cardiac in-silico clinical trials

Computational models of the heart are now being used to assess the effectiveness and feasibility of interventions through in-silico clinical trials (ISCTs). As the adoption and acceptance of ISCTs increases, best practices for reporting the methodology and analysing the results will emerge. Focusing in the area of cardiology, we aim to evaluate the types of ISCTs, their analysis methods and their reporting standards. To this end, we conducted a systematic review of cardiac ISCTs over the period of 1 January 2012-1 January 2022, following the preferred reporting items for systematic reviews and meta-analysis (PRISMA). We considered cardiac ISCTs of human patient cohorts, and excluded studies of single individuals and those in which models were used to guide a procedure without comparing against a control group. We identified 36 publications that described cardiac ISCTs, with most of the studies coming from the US and the UK. In 75% of the studies, a validation step was performed, although the specific type of validation varied between the studies. ANSYS FLUENT was the most commonly used software in 19% of ISCTs. The specific software used was not reported in 14% of the studies. Unlike clinical trials, we found a lack of consistent reporting of patient demographics, with 28% of the studies not reporting them. Uncertainty quantification was limited, with sensitivity analysis performed in only 19% of the studies. In 97% of the ISCTs, no link was provided to provide easy access to the data or models used in the study. There was no consistent naming of study types with a wide range of studies that could potentially be considered ISCTs. There is a clear need for community agreement on minimal reporting standards on patient demographics, accepted standards for ISCT cohort quality control, uncertainty quantification, and increased model and data sharing.

Hybrid neural network approaches to predict drug-target binding affinity for drug repurposing: screening for potential leads for Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease that primarily affects elderly individuals. Recent studies have found that sigma-1 receptor (S1R) agonists can maintain endoplasmic reticulum stress homeostasis, reduce neuronal apoptosis, and enhance mitochondrial function and autophagy, making S1R a target for AD therapy. Traditional experimental methods are costly and inefficient, and rapid and accurate prediction methods need to be developed, while drug repurposing provides new ways and options for AD treatment. In this paper, we propose HNNDTA, a hybrid neural network for drug-target affinity (DTA) prediction, to facilitate drug repurposing for AD treatment. The study combines protein-protein interaction (PPI) network analysis, the HNNDTA model, and molecular docking to identify potential leads for AD. The HNNDTA model was constructed using 13 drug encoding networks and 9 target encoding networks with 2506 FDA-approved drugs as the candidate drug library for S1R and related proteins. Seven potential drugs were identified using network pharmacology and DTA prediction results of the HNNDTA model. Molecular docking simulations were further performed using the AutoDock Vina tool to screen haloperidol and bromperidol as lead compounds for AD treatment. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) evaluation results indicated that both compounds had good pharmacokinetic properties and were virtually non-toxic. The study proposes a new approach to computer-aided drug design that is faster and more economical, and can improve hit rates for new drug compounds. The results of this study provide new lead compounds for AD treatment, which may be effective due to their multi-target action. HNNDTA is freely available at https://github.com/lizhj39/HNNDTA.

Preliminary study to identify CXCR4 inhibitors as potential therapeutic agents for Alzheimer's and Parkinson's diseases

Neurodegenerative disorders (NDDs) are known to exhibit genetic overlap and shared pathophysiology. This study aims to find the shared genetic architecture of Alzheimer's disease (AD) and Parkinson's disease (PD), two major age-related progressive neurodegenerative disorders. The gene expression profiles of GSE67333 (containing samples from AD patients) and GSE114517 (containing samples from PD patients) were retrieved from the Gene Expression Omnibus (GEO) functional genomics database managed by the National Center for Biotechnology Information. The web application GREIN (GEO RNA-seq Experiments Interactive Navigator) was used to identify differentially expressed genes (DEGs). A total of 617 DEGs (239 upregulated and 379 downregulated) were identified from the GSE67333 dataset. Likewise, 723 DEGs (378 upregulated and 344 downregulated) were identified from the GSE114517 dataset. The protein-protein interaction networks of the DEGs were constructed, and the top 50 hub genes were identified from the network of the respective dataset. Of the four common hub genes between two datasets, C-X-C chemokine receptor type 4 (CXCR4) was selected due to its gene expression signature profile and the same direction of differential expression between the two datasets. Mavorixafor was chosen as the reference drug due to its known inhibitory activity against CXCR4 and its ability to cross the blood-brain barrier. Molecular docking and molecular dynamics simulation of 51 molecules having structural similarity with Mavorixafor was performed to find two novel molecules, ZINC49067615 and ZINC103242147. This preliminary study might help predict molecular targets and diagnostic markers for treating Alzheimer's and Parkinson's diseases. Insight Box Our research substantiates the therapeutic relevance of CXCR4 inhibitors for the treatment of Alzheimer's and Parkinson's diseases. We would like to disclose the following insights about this study. We found common signatures between Alzheimer's and Parkinson's diseases at transcriptional levels by analyzing mRNA sequencing data. These signatures were used to identify putative therapeutic agents for these diseases through computational analysis. Thus, we proposed two novel compounds, ZINC49067615 and ZINC103242147, that were stable, showed a strong affinity with CXCR4, and exhibited good pharmacokinetic properties. The interaction of these compounds with major residues of CXCR4 has also been described.

Docking-Based Prediction of Peptide Binding to MHC Proteins

Major histocompatibility complex (MHC) proteins are the most polymorphic and polygenic proteins in humans. They bind peptides, derived from cleavage of different pathogenic antigens, and are responsible for presenting them to T cells. The peptides recognized by the T cell receptors are denoted as epitopes and they trigger an immune response.In this chapter, we describe a docking protocol for predicting the peptide binding to a given MHC protein using the software tool GOLD. The protocol starts with the construction of a combinatorial peptide library used in the docking and ends with the derivation of a quantitative matrix (QM) accounting for the contribution of each amino acid at each peptide position.

Foresee Novel Targets for Alzheimer's Disease by Investigating Repurposed Drugs

BACKGROUND

Alzheimer's Disease (AD) is the most rampant neurodegenerative disorder which has caused havoc worldwide. More than a century has passed since the first case of AD was reported, but still, no stable treatment is known to humanity. The available medications only provide temporary relief and are not a cure for the disease. The hunt for advanced techniques in drug development has paved the way for drug repurposing, i.e., repositioning or reutilizing drugs as an innovative approach.

METHODOLOGY

Several drugs which were repurposed for AD were collected by following PRISMA 2020 systemic review. Databases like PubMed, ScienceDirect, JSTOR, and SciELO were used for data extraction. Further, the Drugbank database was used to download all the identified drugs. Later, the Swiss Target Prediction tool was used to identify protein receptors for these drugs and the biological pathway followed by them.

RESULTS

Drugs like Zileuton, Salbutamol, Baricitinib, Carmustine, Paclitaxel, and Nilotinib were observed to be involved in regulation of neurotransmitters. Similarly, Metformin, Liraglutide, UDCA, and Bexarotene are involved in protein kinase cascades which also is one of the prime processes in metabolic disorders like AD. Furthermore, drugs like Rosiglitazone, Pioglitazone, and Lonafarnib are involved in interleukin-3 biosynthetic processes, which is again one of the most important processes studied in AD treatment.

CONCLUSION

The study concluded that the reviewed drugs that follow similar biological and molecular processes could be repurposed for AD if chosen judiciously with current medications and thus, drug repurposing is a promising approach that can be utilized to find a cure for AD within a brief time and fewer resources compared to de novo drug synthesis. Although certain loopholes still need to be worked upon, the technique has great prospects. Furthermore, in silico methods can be utilized to justify the findings and identify the best drug candidate.

Jatamansinol from Nardostachys jatamansi: a multi-targeted neuroprotective agent for Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial progressive and irreversible neurodegenerative disorder characterized by severe memory impairment and cognitive disability in the middle and old-aged human population. There are no proven drugs for AD treatment and prevention. In Ayurveda, medhya plants are used to prepare Rasayana, and its consumption improves memory and cognition. Nardostachys jatamansi (D.Don) DC is a medhya plant used in traditional medicine to treat neurological disorders, and its unique pyranocoumarins can be a potential drug candidate for AD. Given its traditional claims, this study aims to find the multi-target potential efficacy of the ligands (drug molecules) against the AD from N. jatamansi pyranocoumarins using computational drug discovery techniques. Drug likeliness analysis confirms that pyranocoumarins of N. jatamansi, such as seselin, jatamansinol, jatamansine, jatamansinone, and dihydrojatamansin are probable drug candidates for AD. Molecular docking, molecular dynamic simulations, and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis confirm that dihydrojatamansin inhibits acetylcholinesterase (AChE), and jatamansinol inhibits butyrylcholinesterase (BuChE), glycogen synthase kinase 3β (GSK3β), and kelch-like ECH-associating protein 1 (Keap1) AD therapeutic targets. Therefore, this study provides potential multi-target inhibitors that would further validate experimental studies, leading to new treatments for AD.Communicated by Ramaswamy H. Sarma.

pH Regulates Ligand Binding to an Enzyme Active Site by Modulating Intermediate Populations

Understanding the mechanism of ligands binding to their protein targets and the influence of various factors governing the binding thermodynamics is essential for rational drug design. The solution pH is one of the critical factors that can influence ligand binding to a protein cavity, especially in enzymes whose function is sensitive to the pH. Using computer simulations, we studied the pH effect on the binding of a guanidinium ion (Gdm⁺) to the active site of hen egg-white lysozyme (HEWL). HEWL serves as a model system for enzymes with two acidic residues in the active site and ligands with Gdm⁺ moieties, which can bind to the active sites of such enzymes and are present in several approved drugs treating various disorders. The computed free energy surface (FES) shows that Gdm⁺ binds to the HEWL active site using two dominant binding pathways populating multiple intermediates. We show that the residues close to the active site that can anchor the ligand could play a critical role in ligand binding. Using a Markov state model, we quantified the lifetimes and kinetic pathways connecting the different states in the FES. The protonation and deprotonation of the acidic residues in the active site in response to the pH change strongly influence the Gdm⁺ binding. There is a sharp jump in the ligand-binding rate constant when the pH approaches the largest pK_a of the acidic residue present in the active site. The simulations reveal that, at most, three Gdm⁺ can bind at the active site, with the Gdm⁺ bound in the cavity of the active site acting as a scaffold for the other two Gdm⁺ ions binding. These results can aid in providing greater insights into designing novel molecules containing Gdm⁺ moieties that can have high binding affinities to inhibit the function of enzymes with acidic residues in their active site.

Implications of Porphyromonas gingivalis peptidyl arginine deiminase and gingipain R in human health and diseases

Porphyromonas gingivalis is a major pathogenic bacterium involved in the pathogenesis of periodontitis. Citrullination has been reported as the underlying mechanism of the pathogenesis, which relies on the interplay between two virulence factors of the bacterium, namely gingipain R and the bacterial peptidyl arginine deiminase. Gingipain R cleaves host proteins to expose the C-terminal arginines for peptidyl arginine deiminase to citrullinate and generate citrullinated proteins. Apart from carrying out citrullination in the periodontium, the bacterium is found capable of citrullinating proteins present in the host synovial tissues, atherosclerotic plaques and neurons. Studies have suggested that both virulence factors are the key factors that trigger distal effects mediated by citrullination, leading to the development of some non-communicable diseases, such as rheumatoid arthritis, atherosclerosis, and Alzheimer’s disease. Thus, inhibition of these virulence factors not only can mitigate periodontitis, but also can provide new therapeutic solutions for systematic diseases involving bacterial citrullination. Herein, we described both these proteins in terms of their unique structural conformations and biological relevance to different human diseases. Moreover, investigations of inhibitory actions on the enzymes are also enumerated. New approaches for identifying inhibitors for peptidyl arginine deiminase through drug repurposing and virtual screening are also discussed.

New Drug Design Avenues Targeting Alzheimer's Disease by Pharmacoinformatics-Aided Tools

Neurodegenerative diseases (NDD) have been of great interest to scientists for a long time due to their multifactorial character. Among these pathologies, Alzheimer's disease (AD) is of special relevance, and despite the existence of approved drugs for its treatment, there is still no efficient pharmacological therapy to stop, slow, or repair neurodegeneration. Existing drugs have certain disadvantages, such as lack of efficacy and side effects. Therefore, there is a real need to discover new drugs that can deal with this problem. However, as AD is multifactorial in nature with so many physiological pathways involved, the most effective approach to modulate more than one of them in a relevant manner and without undesirable consequences is through polypharmacology. In this field, there has been significant progress in recent years in terms of pharmacoinformatics tools that allow the discovery of bioactive molecules with polypharmacological profiles without the need to spend a long time and excessive resources on complex experimental designs, making the drug design and development pipeline more efficient. In this review, we present from different perspectives how pharmacoinformatics tools can be useful when drug design programs are designed to tackle complex diseases such as AD, highlighting essential concepts, showing the relevance of artificial intelligence and new trends, as well as different databases and software with their main results, emphasizing the importance of coupling wet and dry approaches in drug design and development processes.

Allostery Inhibition of BACE1 by Psychotic and Meroterpenoid Drugs in Alzheimer's Disease Therapy

In over a century since its discovery, Alzheimer's disease (AD) has continued to be a global health concern due to its incurable nature and overwhelming increase among older people. In this paper, we give an overview of the efforts of researchers towards identifying potent BACE1 exosite-binding antibodies and allosteric inhibitors. Herein, we apply computer-aided drug design (CADD) methods to unravel the interactions of some proposed psychotic and meroterpenoid BACE1 allosteric site inhibitors. This study is aimed at validating the allosteric potentials of these selected compounds targeted at BACE1 inhibition. Molecular docking, molecular dynamic (MD) simulations, and post-MD analyses are carried out on these selected compounds, which have been experimentally proven to exhibit allosteric inhibition on BACE1. The SwissDock software enabled us to identify more than five druggable pockets on the BACE1 structural surface using docking. Besides the active site region, a melatonin derivative (compound 1) previously proposed as a BACE1 allostery inhibitor showed appreciable stability at eight different subsites on BACE1. Refinement with molecular dynamic (MD) simulations shows that the identified non-catalytic sites are potential allostery sites for compound 1. The allostery and binding mechanism of the selected potent inhibitors show that the smaller the molecule, the easier the attachment to several enzyme regions. This finding hereby establishes that most of these selected compounds failed to exhibit strong allosteric binding with BACE1 except for compound 1. We hereby suggest that further studies and additional identification/validation of other BACE1 allosteric compounds be done. Furthermore, this additional allosteric site investigation will help in reducing the associated challenges with designing BACE1 inhibitors while exploring the opportunities in the design of allosteric BACE1 inhibitors.

Isolation, Characterization, and In Silico Interaction Studies of Bioactive Compounds from Caesalpinia bonducella with Target Proteins Involved in Alzheimer's Disease

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by memory loss, cognitive deterioration, and neuropsychiatric symptoms. Various drug targets implicated in AD are amyloid beta peptides, cholinesterase enzymes, and anti-amylogenic protein. Medicinal plants derived phytochemical constituents provide a vast pool of diverse compounds as a source of novel drugs. In view of this, the Caesalpinia bonducella seed extract and its active phytoconstituents were used to study the disease-modifying effects in Alzheimer's disease. The present study successfully demonstrated the therapeutic potential of various phytochemicals as it binds to multiple drug targets, resulting in inhibition of acetylcholinesterase (AChE) enzyme, butyrylcholinesterase (BuChE), BACE-1 enzyme, and anti-amylogenic protein as indicated by docking analysis. In conclusion, phytochemicals identified can be used as a suitable lead to developing a molecule that might have multi-targeted directed ligand (MTDL) potential and disease amelioration effects in Alzheimer's disease.

Virtual Therapy with the NMDA Antagonist Memantine in Hippocampal Models of Moderate to Severe Alzheimer's Disease, in Silico Trials

The variability in clinical trial results on memantine treatment of Alzheimer's disease remains incompletely explained. The aim of this in silico study is a virtual memantine therapy for Alzheimer's disease that provides a different perspective on clinical trials; An in silico randomised trial using virtual hippocampi to treat moderate to severe Alzheimer's disease with doses of memantine 3-30 µM compared to placebo. The primary endpoint was the number of impulses (spikes). Secondary endpoints included interspike interval and frequency; The number of virtual moderate-AD hippocampal spikes was significantly lower, at 1648.7 (95% CI, 1344.5-1952.9), versus those treated with the 3 µM dose, 2324.7 (95% CI, 2045.9-2603.5), and the 10 µM dose, 3607.0 (95% CI, 3137.6-4076.4). In contrast, the number of virtual spikes (spikes) of severe AD of the hippocampus was significantly lower, at 1461.8 (95% CI, 1196.2-1727.4), versus those treated with the 10 µM dose, at 2734.5 (95% CI, 2369.8-3099.2), and the 30 µM dose, at 3748.9 (95% CI, 3219.8-4278.0). The results of the analysis of secondary endpoints, interspike intervals and frequencies changed statistically significantly relative to the placebo; The results of the in silico study confirm that memantine monotherapy is effective in the treatment of moderate to severe Alzheimer's disease, as assessed by various neuronal parameters.

The Influence of Selected Antipsychotic Drugs on Biochemical Aspects of Alzheimer's Disease

The aim of this study was to assess the potency of selected antipsychotic drugs (haloperidol (HAL), bromperidol (BRMP), benperidol (BNP), penfluridol (PNF), pimozide (PIM), quetiapine (QUET) and promazine (PROM)) on the main pathological hallmarks of Alzheimer's disease (AD). Binary mixtures of donepezil and antipsychotics produce an anti-BuChE effect, which was greater than either compound alone. The combination of rivastigmine and antipsychotic drugs (apart from PNF) enhanced AChE inhibition. The tested antipsychotics (excluding HAL and PNF) significantly reduce the early stage of Aβ aggregation. BRMP, PIM, QUET and PROM were found to substantially inhibit Aβ aggregation after a longer incubation time. A test of human erythrocytes hemolysis showed that short-term incubation of red blood cells (RBCs) with QUET resulted in decreased hemolysis. The antioxidative properties of antipsychotics were also proved in human umbilical vein endothelial cells (HUVEC); all tested drugs were found to significantly increase cell viability. In the case of astrocytes, BNP, PNF, PIM and PROM showed antioxidant potential.

An in-silico approach to identify potential drug molecules for Alzheimer’s disease: a case with four therapeutic targets

Background:

Computational Methods in the ‘omics’ era has been a boon in the drug discovery field. Bioinformatics and cheminformatics databases and tools complement the successful discovery of promising lead compounds in the treatment of several disease conditions including neurodegenerative diseases such as Alzheimer’s Disease (AD). However, commercially available drugs in the market to alleviate the disease progression in AD patients is sparse. The current research aims to apply an in-silico approach on multi-therapeutic agents against multi-therapeutic targets through docking studies to explore potential lead compounds for AD clinical trials.

Method:

In the proposed research, virtual screening was performed with four US FDA-approved control drugs (Donepezil (DON), Galantamine (GAL), Rivastigmine (RIV), and Tacrine (TAC)) for mild-moderate-severe stages of AD treatment. The panel of compounds identified through virtual screening was subjected to chemical absorption, distribution, metabolism, excretion, and toxicity (ADMET) and Pharmacokinetics (PK). The compound with good ADMET and PK score was investigated further with molecular docking against the four therapeutic targets involved in AD. Ligands showing the highest binding affinity against cholinesterase inhibitors (AChE, BuChE), receptor antagonist (NMDA), and β-amyloid peptide (Aβ) were computed.

Result:

It was observed that the compounds Quinazolidinone analogue, 2b, Isoquinoline-pyridine, 1, Benzylmorphine and Coelenteramide are the best lead candidates with the least side effects and better efficacy.

Conclusion:

The predicted lead candidates are suitable for further investigation in the drug discovery pipeline.

UPLC-PDA-ESI-QTOF-MS/MS fingerprint of purified flavonoid enriched fraction of Bryophyllum pinnatum; antioxidant properties, anticholinesterase activity and in silico studies

CONTEXT

Bryophyllum pinnatum (Lam.) Oken (Crassulaceae) is used traditionally to treat many ailments.

OBJECTIVES

This study characterizes the constituents of B. pinnatum flavonoid-rich fraction (BPFRF) and investigates their antioxidant and anticholinesterase activity using in vitro and in silico approaches.

MATERIALS AND METHODS

Methanol extract of B. pinnatum leaves was partitioned to yield the ethyl acetate fraction. BPFRF was isolated from the ethyl acetate fraction and purified. The constituent flavonoids were structurally characterized using UPLC-PDA-MS². Antioxidant activity (DPPH), Fe²⁺-induced lipid peroxidation (LP) and anticholinesterase activity (Ellman's method) of the BPFRF and standards (ascorbic acid and rivastigmine) across a concentration range of 3.125-100 μg/mL were evaluated in vitro for 4 months. Molecular docking was performed to give insight into the binding potentials of BPFRF constituents against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE).

RESULTS

UPLC-PDA-MS² analysis of BPFRF identified carlinoside, quercetin (most dominant), luteolin, isorhamnetin, luteolin-7-glucoside. Carlinoside was first reported in this plant. BPFRF significantly inhibited DPPH radical (IC₅₀ = 7.382 ± 0.79 µg/mL) and LP (IC₅₀ = 7.182 ± 0.60 µg/mL) better than quercetin and ascorbic acid. Also, BPFRF exhibited potent inhibition against AChE and BuChE with IC₅₀ values of 22.283 ± 0.27 µg/mL and 33.437 ± 1.46 µg/mL, respectively compared to quercetin and rivastigmine. Docking studies revealed that luteolin-7-glucoside, carlinoside and quercetin interact effectively with crucial amino acid residues of AChE and BuChE through hydrogen bonds.

DISCUSSION AND CONCLUSIONS

BPFRF possesses an excellent natural source of cholinesterase inhibitor and antioxidant. The material could be further explored for the potential treatment of oxidative damage and cholinergic dysfunction in Alzheimer's disease.

Artificial Intelligence for Alzheimer's Disease: Promise or Challenge?

Decades of experimental and clinical research have contributed to unraveling many mechanisms in the pathogenesis of Alzheimer's disease (AD), but the puzzle is still incomplete. Although we can suppose that there is no complete set of puzzle pieces, the recent growth of open data-sharing initiatives collecting lifestyle, clinical, and biological data from AD patients has provided a potentially unlimited amount of information about the disease, far exceeding the human ability to make sense of it. Moreover, integrating Big Data from multi-omics studies provides the potential to explore the pathophysiological mechanisms of the entire biological continuum of AD. In this context, Artificial Intelligence (AI) offers a wide variety of methods to analyze large and complex data in order to improve knowledge in the AD field. In this review, we focus on recent findings and future challenges for AI in AD research. In particular, we discuss the use of Computer-Aided Diagnosis tools for AD diagnosis and the use of AI to potentially support clinical practices for the prediction of individual risk of AD conversion as well as patient stratification in order to finally develop effective and personalized therapies.

Potential alternatives to current cholinesterase inhibitors: an in silico drug repurposing approach

Acetylcholinesterase/Butyrylcholinesterase inhibitors are considered an effective method for treating Alzheimer's disease (AD). In this current work, we have computationally analyzed 11 new small molecule drugs used in various neurological diseases and Donepezil, a known inhibitor of acetylcholinesterase, as a positive control. We investigated these drugs for possible fundamental interactions with acetylcholinesterase and butyrylcholinesterase as both are critical in the pathophysiology of Alzheimer's disease. We have selected FDA approved compounds for repurposing as possible inhibitors of these enzymes and novel therapeutic option for Alzheimer's disease. We selected the top two molecules for each protein for their binding energies, interactions, and Donepezil, the most commonly used drug for AD treatment. Molecular simulation and dynamics studies of the top 2 drugs in each case and free energy analysis helped us reach further conclusions about the best possible drugs for repurposing. Brexipirazole and Deutetrabenazine produce encouraging results as butyrylcholinesterase and acetylcholinesterase inhibitors, respectively.

Computational Drug Repurposing for Alzheimer's Disease Using Risk Genes From GWAS and Single-Cell RNA Sequencing Studies

Background: Traditional therapeutics targeting Alzheimer's disease (AD)-related subpathologies have so far proved ineffective. Drug repurposing, a more effective strategy that aims to find new indications for existing drugs against other diseases, offers benefits in AD drug development. In this study, we aim to identify potential anti-AD agents through enrichment analysis of drug-induced transcriptional profiles of pathways based on AD-associated risk genes identified from genome-wide association analyses (GWAS) and single-cell transcriptomic studies. Methods: We systematically constructed four gene lists (972 risk genes) from GWAS and single-cell transcriptomic studies and performed functional and genes overlap analyses in Enrichr tool. We then used a comprehensive drug repurposing tool Gene2Drug by combining drug-induced transcriptional responses with the associated pathways to compute candidate drugs from each gene list. Prioritized potential candidates (eight drugs) were further assessed with literature review. Results: The genomic-based gene lists contain late-onset AD associated genes (BIN1, ABCA7, APOE, CLU, and PICALM) and clinical AD drug targets (TREM2, CD33, CHRNA2, PRSS8, ACE, TKT, APP, and GABRA1). Our analysis identified eight AD candidate drugs (ellipticine, alsterpaullone, tomelukast, ginkgolide A, chrysin, ouabain, sulindac sulfide and lorglumide), four of which (alsterpaullone, ginkgolide A, chrysin and ouabain) have shown repurposing potential for AD validated by their preclinical evidence and moderate toxicity profiles from literature. These support the value of pathway-based prioritization based on the disease risk genes from GWAS and scRNA-seq data analysis. Conclusion: Our analysis strategy identified some potential drug candidates for AD. Although the drugs still need further experimental validation, the approach may be applied to repurpose drugs for other neurological disorders using their genomic information identified from large-scale genomic studies.

In Silico Repositioning of Dopamine Modulators with Possible Application to Schizophrenia: Pharmacophore Mapping, Molecular Docking and Molecular Dynamics Analysis

We have performed theoretical calculations with 70 drugs that have been considered in 231 clinical trials as possible candidates to repurpose drugs for schizophrenia based on their interactions with the dopaminergic system. A hypothesis of shared pharmacophore features was formulated to support our calculations. To do so, we have used the crystal structure of the D2-like dopamine receptor in complex with risperidone, eticlopride, and nemonapride. Linagliptin, citalopram, flunarizine, sildenafil, minocycline, and duloxetine were the drugs that best fit with our model. Molecular docking calculations, molecular dynamics outcomes, blood-brain barrier penetration, and human intestinal absorption were studied and compared with the results. From the six drugs selected in the shared pharmacophore features input, flunarizine showed the best docking score with D2, D3, and D4 dopamine receptors and had high stability during molecular dynamics simulations. Flunarizine is a frequently used medication to treat migraines and vertigo. However, its antipsychotic properties have been previously hypothesized, particularly because of its possible ability to block the D2 dopamine receptors.

An Overview of β-Amyloid Cleaving Enzyme 1 (Bace1) in Alzheimer's Disease Therapy Elucidating its Exosite-Binding Antibody and Allosteric Inhibitor

Over decades of its identification, numerous past and ongoing researches have focused on the therapeutic roles of β-amyloid cleaving enzyme 1 (BACE1) as a target in treating Alzheimer's disease (AD). Although the initial BACE1 inhibitors at phase-3 clinical trials tremendously reduced β-amyloid-associated plaques in patients with AD, the researchers eventually discontinued the tests due to the lack of potency. This discontinuation has resulted in limited drug development and discovery targeted at BACE1, despite the high demand for dementia and AD therapies. It is, therefore, imperative to describe the detailed underlying biological basis of the BACE1 therapeutic option in neurological diseases. Herein, we highlight BACE1 bioactivity, genetic properties, and role in neurodegenerative therapy. We review research contributions to BACE1 exosite-binding antibody and allosteric inhibitor development as AD therapies. The review also covers BACE1 biological function, the disease-associated mechanisms, and the enzyme conditions for amyloid precursor protein sites splitting. Based on the present review, we suggest further studies on anti-BACE1 exosite antibodies and BACE1 allosteric inhibitors. Non-active site inhibition might be the way forward to BACE1 therapy in Alzheimer's neurological disorder.

A Study to Decipher the Potential Effects of Butylphthalide against Central Nervous System Diseases Based on Network Pharmacology and Molecular Docking Integration Strategy

Background

Butylphthalide (NBP), approved by the China National Medical Products Administration (NMPA) for the treatment of ischemic stroke (IS), showed pleiotropic potentials against central nervous system (CNS) diseases, including neuroprotection and cognitive deficits improvement. However, the effects and corresponding modes of action were not fully explored. This study was designed to investigate the potential of NBP against IS-associated CNS diseases based on network pharmacology (NP) and molecular docking (MD).

Methods

IS was inputted as the index disease to retrieve the “associated diseases” in DisGeNET. Three-database-based IS genes were obtained and integrated (DisGeNET, Malacards, and OMIM). Then, IS-associated genes were identified by combining these genes. Meanwhile, PubMed references and online databases were applied to identify NBP target genes. The IS-related disease-disease association (DDA) network and NBP-disease regulation network were constructed and analyzed in Cytoscape. In silico MD and references were used to validate the binding affinity of NBP with critical targets and the potential of NBP against certain IS-related CNS disease regulation.

Results

175 NBP target genes were obtained, while 312 IS-related disease genes were identified. 36 NBP target genes were predicted to be associated with IS-related CNS diseases, including Alzheimer's disease (AD), epilepsy, major depressive disorder (MDD), amyotrophic lateral sclerosis (ALS), and dementia. Six target genes (i.e., GRIN1, PTGIS, PTGES, ADRA1A, CDK5, and SULT1E1) indicating disease specificity index (DSI) >0.5 showed certain to good degree binding affinity with NBP, ranging from −9.2 to −6.7 kcal/mol. And the binding modes may be mainly related to hydrogen bonds and hydrophobic “bonds.” Further literature validations inferred that these critical NBP targets had a tight association with AD, epilepsy, ALS, and depression.

Conclusions

Our study proposed a drug-target-disease integrated method to predict the drug repurposing potentials to associated diseases by application of NP and MD, which could be an attractive alternative to facilitate the development of CNS disease therapies. NBP may be promising and showed potentials to be repurposed for treatments for AD, epilepsy, ALS, and depression, and further investigations are warranted to be carefully designed and conducted.

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.

Recent Developments in New Therapeutic Agents against Alzheimer and Parkinson Diseases: In-Silico Approaches

Neurodegenerative diseases (ND), including Alzheimer's (AD) and Parkinson's Disease (PD), are becoming increasingly more common and are recognized as a social problem in modern societies. These disorders are characterized by a progressive neurodegeneration and are considered one of the main causes of disability and mortality worldwide. Currently, there is no existing cure for AD nor PD and the clinically used drugs aim only at symptomatic relief, and are not capable of stopping neurodegeneration. Over the last years, several drug candidates reached clinical trials phases, but they were suspended, mainly because of the unsatisfactory pharmacological benefits. Recently, the number of compounds developed using in silico approaches has been increasing at a promising rate, mainly evaluating the affinity for several macromolecular targets and applying filters to exclude compounds with potentially unfavorable pharmacokinetics. Thus, in this review, an overview of the current therapeutics in use for these two ND, the main targets in drug development, and the primary studies published in the last five years that used in silico approaches to design novel drug candidates for AD and PD treatment will be presented. In addition, future perspectives for the treatment of these ND will also be briefly discussed.

Role of extracellular vesicles in neurodegenerative diseases

Extracellular vesicles (EVs) are heterogeneous cell-derived membranous structures that arise from the endosome system or directly detach from the plasma membrane. In recent years, many advances have been made in the understanding of the clinical definition and pathogenesis of neurodegenerative diseases, but translation into effective treatments is hampered by several factors. Current research indicates that EVs are involved in the pathology of diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD). Besides, EVs are also involved in the process of myelin formation, and can also cross the blood-brain barrier to reach the sites of CNS injury. It is suggested that EVs have great potential as a novel therapy for the treatment of neurodegenerative diseases. Here, we reviewed the advances in understanding the role of EVs in neurodegenerative diseases and addressed the critical function of EVs in the CNS. We have also outlined the physiological mechanisms of EVs in myelin regeneration and highlighted the therapeutic potential of EVs in neurodegenerative diseases.

Structure-Based Scaffold Repurposing toward the Discovery of Novel Cholinesterase Inhibitors

Cholinesterases (ChE) are well-known drug targets for the treatment of Alzheimer's disease (AD). In continuation of work to develop novel cholinesterase inhibitors, we utilized a structure-based scaffold repurposing approach and discovered six novel ChE inhibitors from our recently developed DNA gyrase inhibitor library. Among the identified hits, two compounds (denoted 3 and 18) were found to be the most potent inhibitor of acetylcholinesterase (AChE, IC₅₀ = 6.10 ± 1.01 μM) and butyrylcholinesterase (BuChE, IC₅₀ = 5.50 ± 0.007 μM), respectively. Compound 3 was responsible for the formation of H-bond and π-π stacking interactions within the active site of AChE. In contrast, compound 18 was well fitted in the choline-binding pocket and catalytic site of BuChE. Results obtained from in vitro cytotoxicity assays and in silico derived physicochemical and absorption, distribution, metabolism, and excretion (ADME) properties indicate that repurposed scaffold 3 and 18 could be potential drug candidates for further development as novel ChE inhibitors.

Synthesis of novel 4-methylthiocoumarin and comparison with conventional coumarin derivative as a multi-target-directed ligand in Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial disorder characterized by cognitive deficit and memory loss. The pathological feature of the disease involves β-amyloid senile plaques, reduced levels of acetylcholine neurotransmitter, oxidative stress and neurofibrillary tangles formation within the brain of AD patients. The present study aims to screen the inhibitory activity of newly synthesized and existing novel 4-methylthiocoumarin derivative against acetylcholinesterase, butyrylcholinesterase, BACE1, β-amyloid aggregation and oxidative stress involved in the AD pathogenesis. The in vitro assays used in this study were Ellman's assay, FRET assays, Thioflavin T, transmission electron microscopy, circular dichroism, FRAP, and TEAC. Molecular docking and dynamics studies were performed to correlate the results. C3 and C7 (thiocoumarin derivatives) were found to be the most potent inhibitors of acetylcholinesterase (IC50-5.63 µM) and butyrylcholinesterase (IC50-3.40 µM) using Ellman's assays. Enzyme kinetic studies showed that C3 and C7 compounds followed by the mixed mode of inhibition using LB plot. C3 also moderately inhibited the BACE1 using FRET assay. C3 inhibited the fibrillization of β-amyloid peptides in a concentration-dependent manner as observed by Thioflavin T, TEM studies and Circular dichroism data. Molecular modeling studies were performed to understand the probable mode of binding of C3 and C7 in the binding pocket of acetylcholinesterase, butyrylcholinesterase, BACE1 and amyloid β peptides. This indicates the important role of hydrophobic interactions between C3 and acetylcholinesterase. C3 also exhibited significant antioxidant potential by FRAP and TEAC assays. Hence, C3 might serve as a promising lead for developing novel multi target-directed ligand for the treatment of AD.

Inhibition of BACE1, MAO-B, cholinesterase enzymes, and anti-amyloidogenic potential of selected natural phytoconstituents: Multi-target-directed ligand approach

Alzheimer's disease (AD) is a neurodegenerative disorder, and multiple factors are involved in disease progression. This is why there is an urgent need to develop novel molecules with multi-target-directed ligands (MTDLs) potential. The current study explores the active phytoconstituents from traditionally used medicinal spices, namely piperine, cinnamaldehyde, eugenol, cuminaldehyde, and alpha-terpinyl acetate for the inhibition of β-secretase, monoamine oxidase, cholinesterase enzymes, anti-aggregation of amyloid β (Aβ) fibrils, and their protective effect against hydrogen peroxide (H₂ O₂ ) and Aβ-induced toxicity. Eugenol showed inhibitory activity against MAO-B enzyme, free radical scavenging activity, and anti-aggregation activity against Aβ peptides than other phytoconstituents. It also demonstrated a significant cytoprotective effect against H₂ O₂ -induced oxidative stress and Aβ-induced cytotoxicity in pheochromocytoma (PC) 12 cells. A molecular docking study of eugenol showed interactions with active site residue of the target enzymes. The study successfully demonstrated that eugenol could have an MTDLs potential better than synthesized drugs used in the treatment of AD. PRACTICAL APPLICATIONS: The present study demonstrated multi-target-directed ligand potential of eugenol and can be developed to treat complex diseases like Alzheimer's. Eugenol can bind to different Alzheimer's targets such as β-secretase (BACE1), Monoamine oxidase B (MAO-B), Cholinesterase's, and amyloid β_1-42 fibrils and might have a disease-modifying potential. The other natural phytoconstituents such as piperine, cinnamaldehyde, cuminaldehyde, and alpha-terpinyl acetate also demonstrated MTDL potential could also be used for developing novel molecules for disease-modifying effect. It also protects against oxidative stress.

Targeting VEGFR2 protein by marine Streptomyces globosus VITLGK011-derived compound BECA: An in vitro and in silico analysis

This study investigates the anticancer cytotoxic mechanism of action of benzoyloxy-ethyl-carbamic acid (BECA) produced by Streptomyces globosus VITLGK011. Flow cytometry analysis confirmed that BECA (at IC₅₀ : 3.12 µg/ml) treatment for 24 h induced apoptosis in 60% of cells. Schrodinger Maestro tools such as QikProp and DFT were used to confirm that BECA is an eligible drug-like molecule, with suitable physiochemical properties. Glide XP tool was used to perform induced-fit docking between BECA and 30 cancer drug target proteins. The highest significance was observed for VEGFR2 protein (-6.7 kcal/mol). GROMACS tool was used to perform molecular dynamic simulation between BECA and VEGFR2 protein for 40 ns. Root mean square deviation, root mean square fluctuation, H-bond, and trajectory analysis, confirmed that BECA is a suitable inhibitor of VEGFR2 protein. Results conclude that BECA is a valid VEGFR2 inhibitor, and it thus exerts the observed anticancer cytotoxicity against MCF-7 cells.

Quetiapine and novel PDE10A inhibitors potentiate the anti-BuChE activity of donepezil

The symptoms of Alzheimer’s disease (AD) do not include only memory loss and cognitive decline but also neuropsychiatric manifestation. These AD-related symptoms are usually treated with the aid of antipsychotics; however, their effects on cognition and safety remain unexplored. The present study determines the effects of quetiapine, an atypical antipsychotic, and two imidazo[1,2-a]pyrimidine-based inhibitors of PDE10A on the activity of human cholinesterases. Quetiapine moderately inhibited BuChE (IC₅₀ = 6.08 ± 1.64 µmol/L) but improved the anti-BuChE properties of donepezil by decreasing its IC₅₀ value. Both PDE10A inhibitors were found to possess moderate anti-AChE properties. The combined mixtures of donepezil and imidazo[1,2-a]pyrimidine analogues produce a synergistic anti-BuChE effect which was greater than either compound alone, improving the IC₅₀ value by approximately six times. These favourable interactions between quetiapine, PDE10A inhibitors and clinically approved donepezil, resulting in improved anti-BuChE activity, can lead to a wider variety of potent AD treatment options.

Protective role of anticancer drugs in neurodegenerative disorders: A drug repurposing approach

The disease heterogeneity and little therapeutic progress in neurodegenerative diseases justify the need for novel and effective drug discovery approaches. Drug repurposing is an emerging approach that reinvigorates the classical drug discovery method by divulging new therapeutic uses of existing drugs. The common biological background and inverse tuning between cancer and neurodegeneration give weight to the conceptualization of repurposing of anticancer drugs as novel therapeutics. Many studies are available in the literature, which highlights the success story of anticancer drugs as repurposed therapeutics. Among them, kinase inhibitors, developed for various oncology indications evinced notable neuroprotective effects in neurodegenerative diseases. In this review, we shed light on the salient role of multiple protein kinases in neurodegenerative disorders. We also proposed a feasible explanation of the action of kinase inhibitors in neurodegenerative disorders with more attention towards neurodegenerative disorders. The problem of neurotoxicity associated with some anticancer drugs is also highlighted. Our review encourages further research to better encode the hidden potential of anticancer drugs with the aim of developing prospective repurposed drugs with no toxicity for neurodegenerative disorders.

Repurposed agents in the Alzheimer's disease drug development pipeline

BACKGROUND

Treatments are needed to address the growing prevalence of Alzheimer's disease (AD). Clinical trials have failed to produce any AD drugs for Food and Drug Administration (FDA) approval since 2003, and the pharmaceutical development process is both time-consuming and costly. Drug repurposing provides an opportunity to accelerate this process by investigating the AD-related effects of agents approved for other indications. These drugs have known safety profiles, pharmacokinetic characterization, formulations, doses, and manufacturing processes.

METHODS

We assessed repurposed AD therapies represented in Phase I, Phase II, and Phase III of the current AD pipeline as registered on ClinicalTrials.gov as of February 27, 2020.

RESULTS

We identified 53 clinical trials involving 58 FDA-approved agents. Seventy-eight percent of the agents in trials had putative disease-modifying mechanisms of action. Of the repurposed drugs in the pipeline 20% are hematologic-oncologic agents, 18% are drugs derived from cardiovascular indications, 14% are agents with psychiatric uses, 12% are drug used to treat diabetes, 10% are neurologic agents, and the remaining 26% of drugs fall under other conditions. Intellectual property strategies utilized in these programs included using the same drug but altering doses, routes of administration, or formulations. Most repurposing trials were supported by Academic Medical Centers and were not funded through the biopharmaceutical industry. We compared our results to a European trial registry and found results similar to those derived from ClinicalTrials.gov.

CONCLUSIONS

Drug repurposing is a common approach to AD drug development and represents 39% of trials in the current AD pipeline. Therapies from many disease areas provide agents potentially useful in AD. Most of the repurposed agents are generic and a variety of intellectual property strategies have been adopted to enhance their economic value.

Dopamine receptors in emesis: Molecular mechanisms and potential therapeutic function

Dopamine is a member of the catecholamine family and is associated with multiple physiological functions. Together with its five receptor subtypes, dopamine is closely linked to neurological disorders such as schizophrenia, Parkinson's disease, depression, attention deficit-hyperactivity, and restless leg syndrome. Unfortunately, several dopamine receptor-based agonists used to treat some of these diseases cause nausea and vomiting as impending side-effects. The high degree of cross interactions of dopamine receptor ligands with many other targets including G-protein coupled receptors, transporters, enzymes, and ion-channels, add to the complexity of discovering new targets for the treatment of nausea and vomiting. Using activation status of signaling cascades as mechanism-based biomarkers to foresee drug sensitivity combined with the development of dopamine receptor-based biased agonists may hold great promise and seems as the next step in drug development for the treatment of such multifactorial diseases. In this review, we update the present knowledge on dopamine and dopamine receptors and their potential roles in nausea and vomiting. The pre- and clinical evidence provided in this review supports the implication of both dopamine and dopamine receptor agonists in the incidence of emesis. Besides the conventional dopaminergic antiemetic drugs, potential novel antiemetic targeting emetic protein signaling cascades may offer superior selectivity profile and potency.

Repurposing of existing FDA approved drugs for Neprilysin inhibition: An in-silico study

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Drug repurposing of FDA approved drugs from ZINC 12 database was done using the crystal structure of extracellular domain of human NEP (PDB ID: 5JMY)

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The interactions with catalytic triad of HIS583, HIS587 and GLU646 are important for NEP inhibition.

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Based on XP molecular docking, binding energy, IFD-SP and MD simulation top 4 NEP inhibitors were identified.

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ZINC000000601283 and ZINC000003831594 were found to be stable during MD simulation and may act as NEP inhibitors.

Neprilysin (NEP) is a neutral endopeptidase with diverse physiological roles in the body. NEP's role in degradation of diverse classes of peptides such as amyloid beta, natriuretic peptide, substance P, angiotensin, endothelins, etc., is associated with pathologies of alzheimer's, kidney and heart diseases, obesity, diabetes and certain malignancies. Hence, the functional inhibition of NEP in the above systems can be a good therapeutic target. In the present study, in-silico drug repurposing approach was used to identify NEP inhibitors. Molecular docking was carried out using GLIDE tool. 2934 drugs from the ZINC12 database were screened using high throughput virtual screening (HTVS) followed by standard precision (SP) and extra precision (XP) docking. Based on the XP docking score and ligand interaction, the top 8 hits were subjected to free ligand binding energy calculation, to filter out 4 hits (ZINC000000001427, ZINC000001533877, ZINC000000601283, and ZINC000003831594). Further, induced fit docking-standard precision (IFD-SP) and molecular dynamics (MD) studies were performed. The results obtained from MD studies suggest that ZINC000000601283-NEP and ZINC000003831594-NEP complexes were most stable for 20ns simulation period as compared to ZINC000001533877-NEP and ZINC000000001427-NEP complexes. Interestingly, ZINC000000601283 and ZINC000003831594 showed similarity in binding with the reported NEP inhibitor sacubitrilat. Findings from this study suggest that ZINC000000601283 and ZINC000003831594 may act as NEP inhibitors. In future studies, the role of ZINC000000601283 and ZINC000003831594 in NEP inhibition should be tested in biological systems to evaluate therapeutic effect in NEP associated pathological conditions.

In silico clinical trials: concepts and early adoptions

Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term 'in silico clinical trials' refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach.

Scopoletin ameliorates anxiety-like behaviors in complete Freund's adjuvant-induced mouse model

Anxiety disorder is highly prevalent worldwide and represents a chronic and functionally disabling condition, with high levels of psychological stress characterized by cognitive and physiological symptoms. Scopoletin (SP), a main active compound in Angelica dahurica, is traditionally used for the treatment of headache, rhinitis, pain, and other conditions. Here, we evaluated the effects of SP in a mouse model of complete Freund’s adjuvant (CFA)-induced chronic inflammation anxiety. SP (2.0, 10.0, 50.0 mg/kg) administration for 2 weeks dose-dependently ameliorated CFA-induced anxiety-like behaviors in the open field test and elevated plus maze test. Moreover, we found that SP treatment inhibited microglia activation and decreased both peripheral and central IL-1β, IL-6, and TNF-α levels in a dose-dependent manner. Additionally, the imbalance in excitatory/inhibitory receptors and neurotransmitters in the basolateral nucleus after CFA injection was also modulated by SP administration. Our findings indicate that the inhibition of the nuclear factor-kappa B and mitogen-activated protein kinase signaling pathways involving anti-inflammatory activities and regulation of the excitatory/inhibitory balance can be attributed to the anxiolytic effects of SP. Moreover, our molecular docking analyses show that SP also has good affinity for gamma-aminobutyric acid (GABA) transaminase and GABA_A receptors. Therefore, these results suggest that SP could be a candidate compound for anxiolytic therapy and for use as a structural base for developing new drugs.

The Structure and Function of α, β and γ-Secretase as Therapeutic Target Enzymes in the Development of Alzheimer’s Disease: A Review

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Alzheimer's disease is a progressive neurodegenerative disorder that affects the central nervous system. There are several factors that cause AD, like, intracellular hyperphosphorylated Tau tangles, collection of extracellular Amyloid-β42 and generation of reactive oxygen species due to mitochondrial dysfunction. This review analyses the most active target of AD and both types of AD-like early-onset AD and late-onset AD. BACE1 is a β-secretase involved in the cleavage of amyloid precursor protein and the pathogenesis of Alzheimer's disease. The presenilin proteins play a critical role in the pathogenesis of Alzheimer malady by intervening the intramembranous cleavage of amyloid precursor protein and the generation of amyloid β. The two homologous proteins PS1 and PS2 speak to the reactant subunits of particular γ-secretase edifices that intercede an assortment of cellular processes. Natural products are common molecular platforms in drug development in AD. Many natural products are being tested in various animal model systems for their role as a potential therapeutic target in AD. Presently, there are a few theories clarifying the early mechanisms of AD pathogenesis. Recently, research advancements in the field of nanotechnology, which utilize macromolecular strategies to make drugs in nanoscale measurements, offer nanotechnology-based diagnostic tools and drug carriers which are highly sensitive for effective drug targeting in the treatment of Alzheimer’s disease.

Repurposed Analog of GLP-1 Ameliorates Hyperglycemia in Type 1 Diabetic Mice Through Pancreatic Cell Reprogramming

Type 1 diabetes is an autoimmune disease caused by the destruction of the insulin-producing β-cells. An ideal immunotherapy should combine the blockade of the autoimmune response with the recovery of functional target cell mass. With the aim to develop new therapies for type 1 diabetes that could contribute to β-cell mass restoration, a drug repositioning analysis based on systems biology was performed to identify the β-cell regenerative potential of commercially available compounds. Drug repositioning is a strategy used for identifying new uses for approved drugs that are outside the scope of the medical indication. A list of 28 non-synonymous repurposed drug candidates was obtained, and 16 were selected as diabetes mellitus type 1 treatment candidates regarding pancreatic β-cell regeneration. Drugs with poor safety profile were further filtered out. Lastly, we selected liraglutide for its predictive efficacy values for neogenesis, transdifferentiation of α-cells, and/or replication of pre-existing β-cells. Liraglutide is an analog of glucagon-like peptide-1, a drug used in patients with type 2 diabetes. Liraglutide was tested in immunodeficient NOD-Scid IL2rg^-/- (NSG) mice with type 1 diabetes. Liraglutide significantly improved the blood glucose levels in diabetic NSG mice. During the treatment, a significant increase in β-cell mass was observed due to a boost in β-cell number. Both parameters were reduced after withdrawal. Interestingly, islet bihormonal glucagon⁺insulin⁺ cells and insulin⁺ ductal cells arose during treatment. In vitro experiments showed an increase of insulin and glucagon gene expression in islets cultured with liraglutide in normoglycemia conditions. These results point to β-cell replacement, including transdifferentiation and neogenesis, as aiding factors and support the role of liraglutide in β-cell mass restoration in type 1 diabetes. Understanding the mechanism of action of this drug could have potential clinical relevance in this autoimmune disease.

Rebalancing metal dyshomeostasis for Alzheimer's disease therapy

Alzheimer's disease (AD) is a type of neurodegenerative malady that is associated with the accumulation of amyloid plaques. Metal ions are critical for the development and upkeep of brain activity, but metal dyshomeostasis can contribute to the development of neurodegenerative diseases, including AD. This review highlights the association between metal dyshomeostasis and AD pathology, the feasibility of rebalancing metal homeostasis as a therapeutic strategy for AD, and a survey of current drugs that action via rebalancing metal homeostasis. Finally, we discuss the challenges that should be overcome by researchers in the future to enable the practical use of metal homeostasis rebalancing agents for clinical application.