scholarly journals In Silico Design of Dual-Binding Site Anti-Cholinesterase Phytochemical Heterodimers as Treatment Options for Alzheimer's Disease

2021 ◽  
Vol 44 (1) ◽  
pp. 152-175
Author(s):  
Hafsa Amat-ur-Rasool ◽  
Mehboob Ahmed ◽  
Shahida Hasnain ◽  
Abrar Ahmed ◽  
Wayne Grant Carter
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Binding Site ◽  
In Silico ◽  
Treatment Options ◽  
Unmet Need ◽  
Drug Efficacy ◽  
Huperzine A ◽  
Binding Affinities ◽  
Number Of Patients

The number of patients with neurodegenerative diseases, particularly Alzheimer’s disease (AD), continues to grow yearly. Cholinesterase inhibitors (ChEIs) represent the first-line symptomatic drug treatment for mild-to-moderate AD; however, there is an unmet need to produce ChEIs with improved efficacy and reduced side effects. Herein, phytochemicals with reported anti-acetylcholinesterase (AChE) activity were ranked in silico for their anti-AChE potential. Ligands with a similar or higher binding affinity to AChE than galantamine were then selected for the design of novel dual-binding site heterodimeric drugs. In silico molecular docking of heterodimers with the target enzymes, AChE and butyrylcholinesterase (BuChE), were performed, and anti-cholinesterase binding affinities were compared with donepezil. Drug-likeliness properties and toxicity of the heterodimers were assessed using the SwissADME and ProTox-II webservers. Nine phytochemicals displayed similar or higher binding affinities to AChE than galantamine: sanguinarine > huperzine A > chelerythrine > yohimbine > berberine > berberastine > naringenin > akuammicine > carvone. Eleven heterodimeric ligands were designed with phytochemicals separated by four- or five-carbon alkyl-linkers. All heterodimers were theoretically potent AChE and BuChE dual-binding site inhibitors, with the highest affinity achieved with huperzine-4C-naringenin, which displayed 34% and 26% improved affinity to AChE and BuChE, respectively, then the potent ChEI drug, donepezil. Computational pharmacokinetic and pharmacodynamic screening suggested that phytochemical heterodimers would display useful gastrointestinal absorption and with relatively low predicted toxicity. Collectively, the present study suggests that phytochemicals could be garnered for the provision of novel ChEIs with enhanced drug efficacy and low toxicity.

Prescribing of drugs for Alzheimer's disease: a South African database analysis

2010 ◽  
Vol 22 (2) ◽  
pp. 264-269 ◽  
Author(s):  
Ilse Truter
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
South African ◽  
Active Ingredient ◽  
Average Cost ◽  
Treatment Options ◽  
Prescribing Patterns ◽  
Defined Daily Doses ◽  
Number Of Patients ◽  
The Cost

ABSTRACTBackground: Relatively few studies of mental illness in Africa have focused on dementia. The primary aim of this study was to determine the prescribing patterns and cost of drugs for Alzheimer's disease in a private health care sector patient population.Methods: A retrospective, exposure-cohort pharmacoepidemiological study was conducted. Data were obtained from a South African private pharmacy group for 2008. The database consisted of 1,578,346 medicine records.Results: A total of 588 patients (326 females and 262 males) received 2623 medicine items for Alzheimer's disease at a cost of R1,563,701.18 (average cost per item R596.15). The average age of the patients was 75.54 (SD = 10.48) years. Donepezil was the most frequently prescribed active ingredient (37.09%), followed by galantamine (36.94%). Donepezil accounted for 39.50% of the cost of Alzheimer medication. The average cost per prescription was R634.76 for donepezil and R551.35 for memantine. Only 5.27% of patients were prescribed more than one active ingredient for Alzheimer's disease during the year (mostly donepezil or galantamine, and memantine). Average prescribed daily doses (PDDs) of all active ingredients were generally lower than their respective defined daily doses (DDDs). The average PDD for donepezil was 7.45 mg (DDD = 7.5 mg), for galantamine 13.56 mg (DDD = 16 mg), for memantine 17.46 mg (DDD = 20 mg) and for rivastigmine 6.89 mg (DDD = 9 mg).Conclusions: A small number of patients were prescribed medicine for Alzheimer's disease. It is recommended that qualitative studies be undertaken to determine the cost-effectiveness of the different treatment options according to family members and carers.

Natural Anti-inflammatory compounds as Drug candidates in Alzheimer’s disease

2020 ◽  
Vol 27 ◽  
Author(s):  
Reyaz Hassan Mir ◽  
Abdul Jalil Shah ◽  
Roohi Mohi-ud-din ◽  
Faheem Hyder Potoo ◽  
Mohd. Akbar Dar ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Natural Products ◽  
Protective Action ◽  
New Drugs ◽  
Huperzine A ◽  
Brain Disorder ◽  
Anti Inflammatory

: Alzheimer's disease (AD) is a chronic neurodegenerative brain disorder characterized by memory impairment, dementia, oxidative stress in elderly people. Currently, only a few drugs are available in the market with various adverse effects. So to develop new drugs with protective action against the disease, research is turning to the identification of plant products as a remedy. Natural compounds with anti-inflammatory activity could be good candidates for developing effective therapeutic strategies. Phytochemicals including Curcumin, Resveratrol, Quercetin, Huperzine-A, Rosmarinic acid, genistein, obovatol, and Oxyresvertarol were reported molecules for the treatment of AD. Several alkaloids such as galantamine, oridonin, glaucocalyxin B, tetrandrine, berberine, anatabine have been shown anti-inflammatory effects in AD models in vitro as well as in-vivo. In conclusion, natural products from plants represent interesting candidates for the treatment of AD. This review highlights the potential of specific compounds from natural products along with their synthetic derivatives to counteract AD in the CNS.

Phytochemicals for drug discovery in Alzheimer’s disease: In silico Advances

2020 ◽  
Vol 26 ◽  
Author(s):  
Smriti Sharma ◽  
Vinayak Bhatia
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Design ◽  
In Silico ◽  
Drug Targets ◽  
Development Process ◽  
Phytochemical Analysis ◽  
Computational Drug Design ◽  
Novel Drugs ◽  
Game Changer

: The search for novel drugs that can prevent or control Alzheimer’s disease has attracted lot of attention from researchers across the globe. Phytochemicals are increasingly being used to provide scaffolds to design drugs for AD. In silico techniques, have proven to be a game-changer in this drug design and development process. In this review, the authors have focussed on current advances in the field of in silico medicine, applied to phytochemicals, to discover novel drugs to prevent or cure AD. After giving a brief context of the etiology and available drug targets for AD, authors have discussed the latest advances and techniques in computational drug design of AD from phytochemicals. Some of the prototypical studies in this area are discussed in detail. In silico phytochemical analysis is a tool of choice for researchers all across the globe and helps integrate chemical biology with drug design.

Identify Compounds' Target Against Alzheimer's Disease Based on In-Silico Approach

2019 ◽  
Vol 16 (3) ◽  
pp. 193-208 ◽  
Author(s):  
Yan Hu ◽  
Guangya Zhou ◽  
Chi Zhang ◽  
Mengying Zhang ◽  
Qin Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecule ◽  
Characteristic Curve ◽  
Machine Learning Algorithms ◽  
Learner Model ◽  
Mao B ◽  
Number Of Patients ◽  
Sar Model ◽  
Set Up

Background: Alzheimer's disease swept every corner of the globe and the number of patients worldwide has been rising. At present, there are as many as 30 million people with Alzheimer's disease in the world, and it is expected to exceed 80 million people by 2050. Consequently, the study of Alzheimer’s drugs has become one of the most popular medical topics. Methods: In this study, in order to build a predicting model for Alzheimer’s drugs and targets, the attribute discriminators CfsSubsetEval, ConsistencySubsetEval and FilteredSubsetEval are combined with search methods such as BestFirst, GeneticSearch and Greedystepwise to filter the molecular descriptors. Then the machine learning algorithms such as BayesNet, SVM, KNN and C4.5 are used to construct the 2D-Structure Activity Relationship(2D-SAR) model. Its modeling results are utilized for Receiver Operating Characteristic curve(ROC) analysis. Results: The prediction rates of correctness using Randomforest for AChE, BChE, MAO-B, BACE1, Tau protein and Non-inhibitor are 77.0%, 79.1%, 100.0%, 94.2%, 93.2% and 94.9%, respectively, which are overwhelming as compared to those of BayesNet, BP, SVM, KNN, AdaBoost and C4.5. Conclusion: In this paper, we conclude that Random Forest is the best learner model for the prediction of Alzheimer’s drugs and targets. Besides, we set up an online server to predict whether a small molecule is the inhibitor of Alzheimer's target at http://47.106.158.30:8080/AD/. Furthermore, it can distinguish the target protein of a small molecule.

In silico screening of pyridoxine carbamates for Anti-Alzheimer’s activities

2020 ◽  
Vol 20 ◽  
Author(s):  
Dnyaneshwar Baswar ◽  
Abha Sharma ◽  
Awanish Mishra
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
In Silico ◽  
Neurodegenerative Disorder ◽  
Biological Activities ◽  
Cholinergic Neurons ◽  
In Silico Screening ◽  
In Silico Studies ◽  
Bbb Permeability ◽  
Ld50 Value

Background: Alzheimer’s disease (AD), an irreversible complex neurodegenerative disorder, is most common type of dementia, with progressive loss of cholinergic neurons. Based on the multi- factorial etiology of Alzheimer’s disease, novel ligands strategy appears as up-coming approach for the development of newer molecules against AD. This study is envisaged to investigate anti-Alzheimer’s potential of 10 synthesized compounds. The screening of compounds (1-10) was carried out using in silico techniques. Methods: For in silico screening of physicochemical properties of compounds molinspiration property engine v.2018.03, Swiss ADME online web-server and pkCSM ADME were used. For pharmacodynamic prediction PASS software while toxicity profile of compounds were analyzed through ProTox-II online software. Simultaneously, molecular docking analysis was performed on mouse AChE enzyme (PDB ID:2JGE, obtained from RSCB PDB) using Auto Dock Tools 1.5.6. Results: Based on in silico studies, compound 9 and 10 have been found to have better drug likeness, LD50 value, and better anti-Alzheimer’s, nootropic activities. However, these compounds had poor blood brain barrier (BBB) permeability. Compound 4 and 9 were predicted with better docking score for AChE enzyme. Conclusion: The outcome of in silico studies have suggested, out of various substitutions at different positions of pyridoxine-carbamate, compound 9 have shown promising drug likeness, with better safety and efficacy profile for anti-Alzheimer’s activity. However, BBB permeability appears as one the major limitation of all these compounds. Further studies are required to confirm its biological activities.

scholarly journals Endophytic Fungal Community of Huperzia serrata: Diversity and Relevance to the Production of Huperzine A by the Plant Host

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 892
Author(s):  
Lingli Cui ◽  
Hamza Armghan Noushahi ◽  
Yipeng Zhang ◽  
Jinxin Liu ◽  
Andreea Cosoveanu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Fungal Community ◽  
Slow Growth ◽  
Specific Treatment ◽  
Huperzine A ◽  
Ionization Mass ◽  
Correlation Index ◽  
Plant Host ◽  
Huperzia Serrata

As the population ages globally, there seem to be more people with Alzheimer’s disease. Unfortunately, there is currently no specific treatment for the disease. At present, Huperzine A (HupA) is one of the best drugs used for the treatment of Alzheimer’s disease and has been used in clinical trials for several years in China. HupA was first separated from Huperzia serrata, a traditional medicinal herb that is used to cure fever, contusions, strains, hematuria, schizophrenia, and snakebite for several hundreds of years in China, and has been confirmed to have acetylcholinesterase inhibitory activity. With the very slow growth of H. serrata, resources are becoming too scarce to meet the need for clinical treatment. Some endophytic fungal strains that produce HupA were isolated from H. serrate in previous studies. In this article, the diversity of the endophytic fungal community within H. serrata was observed and the relevance to the production of HupA by the host plant was further analyzed. A total of 1167 strains were obtained from the leaves of H. serrata followed by the stems (1045) and roots (824). The richness as well as diversity of endophytic fungi within the leaf and stem were higher than in the root. The endophytic fungal community was similar within stems as well as in leaves at all taxonomic levels. The 11 genera (Derxomyces, Lophiostoma, Cyphellophora, Devriesia, Serendipita, Kurtzmanomyces, Mycosphaerella, Conoideocrella, Brevicellicium, Piskurozyma, and Trichomerium) were positively correlated with HupA content. The correlation index of Derxomyces with HupA contents displayed the highest value (CI = 0.92), whereas Trichomerium showed the lowest value (CI = 0.02). Through electrospray ionization mass spectrometry (ESI-MS), it was confirmed that the HS7-1 strain could produce HupA and the total alkaloid concentration was 3.7 ug/g. This study will enable us to screen and isolate the strain that can produce HupA and to figure out the correlation between endophytic fungal diversity with HupA content in different plant organs. This can provide new insights into the screening of strains that can produce HupA more effectively.

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