Classification of beta‐site amyloid precursor protein cleaving enzyme 1 inhibitors by using machine learning methods

Singh, Ravi; Ganeshpurkar, Ankit; Ghosh, Powsali; Pokle, Ankit Vyankatrao; Kumar, Devendra; Singh, Ravi Bhushan; Singh, Sushil Kumar; Kumar, Ashok

doi:10.1111/cbdd.13965

Cited by 12 publications

(5 citation statements)

References 23 publications

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“…The present approach to BACE-1 blocker studies is based on the identification of hundreds, or even thousands, of such possible drugs analyzed by multiple distinct procedures. In [ 65 ], five drugs are classified as high score. The employed approach appears promising for the identification, in the future, of appropriate new BACE-1 inhibitors.…”

Section: Present Therapies For Alzheimer’s Diseasementioning

confidence: 99%

News about Therapies of Alzheimer’s Disease: Extracellular Vesicles from Stem Cells Exhibit Advantages Compared to Other Treatments

Meldolesi

2022

Biomedicines

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Upon its discovery, Alzheimer’s, the neurodegenerative disease that affects many millions of patients in the world, remained without an effective therapy. The first drugs, made available near the end of last century, induced some effects, which remained only marginal. More promising effects are now present, induced by two approaches. Blockers of the enzyme BACE-1 induce, in neurons and glial cells, decreased levels of Aβ, the key peptide of the Alzheimer’s disease. If administered at early AD steps, the BACE-1 blockers preclude further development of the disease. However, they have no effect on established, irreversible lesions. The extracellular vesicles secreted by mesenchymal stem cells induce therapy effects analogous, but more convenient, than the effects of their original cells. After their specific fusion to target cells, the action of these vesicles depends on their ensuing release of cargo molecules, such as proteins and many miRNAs, active primarily on the cell cytoplasm. Operationally, these vesicles exhibit numerous advantages: they exclude, by their accurate selection, the heterogeneity of the original cells; exhibit molecular specificity due to their engineering and drug accumulation; and induce effective actions, mediated by variable concentrations of factors and molecules and by activation of signaling cascades. Their strength is reinforced by their combination with various factors and processes. The recent molecular and operations changes, induced especially by the stem cell target cells, result in encouraging and important improvement of the disease. Their further development is expected in the near future.

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Section: Present Therapies For Alzheimer’s Diseasementioning

confidence: 99%

News about Therapies of Alzheimer’s Disease: Extracellular Vesicles from Stem Cells Exhibit Advantages Compared to Other Treatments

Meldolesi

2022

Biomedicines

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“…Each fingerprint shows certain characteristics contained in these compounds. Each operational and decoy data is extracted to its character with the help of Python's RDkit package [28]. The active data group produces a data matrix of 148 x 79 and in the feed data, the extraction process forms a data matrix with a matrix size of 296 x 79.…”

Section: Data Constructionmentioning

confidence: 99%

Classification of IGF1R ligand compounds for Identification of herbal extracts using extreme gradient boosting

Faroby

Amiroch

Aji³

et al. 2022

Jurnal Informatika

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Diabetes Mellitus is a serious disease that requires serious treatment. The cause of this disease is due to malfunctions in insulin and insulin-producing organs. One of the proteins that become insulin signaling receptors is IGF1R, which has an important role in activating and maximizing insulin performance. In this study, we aimed to obtain herbal compounds that can activate the function of the IGF1R protein by utilizing compound data in an open database and modeling it using the ensemble method, namely extreme gradient boosting. We found that this method produces the best classification model than with other algorithms. We predicted 844 data for herbal compounds, but only 15 data met the threshold of 0.6. We got one plant from the fifteen herbal compounds, namely Zostera Marine, which was confirmed to have compounds that bind to IGF1R. These compounds have the highest probability value in the classification model that we formed compared to others.

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“…Beta-secretase 1 also known as β-site amyloid precursor protein cleaving enzyme 1, is crucial in producing Aβ peptides [4], [5]. Inhibition of beta-secretase 1 has emerged as a promising therapeutic strategy for Alzheimer's disease, potentially reducing Aβ production and slowing down the disease's progression [6].…”

Section: Introductionmentioning

confidence: 99%

Classifying Beta-Secretase 1 Inhibitor Activity for Alzheimer’s Drug Discovery with LightGBM

Noviandy,

Nisa,

Idroes

et al. 2024

J. Comput. Theor. Appl.

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This study explores the utilization of LightGBM, a gradient-boosting framework, to classify the inhibitory activity of beta-secretase 1 inhibitors, addressing the challenges of Alzheimer's disease drug discovery. The study aims to enhance classification performance by focusing on overcoming the limitations of traditional statistical models and conventional machine-learning techniques in handling complex molecular datasets. By sourcing a dataset of 7298 compounds from the ChEMBL database and calculating molecular descriptors for each compound as features, we employed LightGBM in conjunction with a set of carefully selected molecular descriptors to achieve a nuanced analysis of compound activities. The model's efficiency was benchmarked against traditional machine-learning algorithms, revealing LightGBM's superior accuracy (84.93%), precision (87.14%), sensitivity (89.93%), specificity (77.63%), and F1-score (88.17%) in classifying beta-secretase 1 inhibitor activity. The study underscores the critical role of molecular descriptors in understanding drug efficacy, highlighting LightGBM's potential in streamlining the virtual screening process. Conclusively, the findings advocate for LightGBM's adoption in computational drug discovery, offering a promising avenue for advancing Alzheimer's disease therapeutic development by facilitating the identification of potential drug candidates with enhanced precision and reliability.

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Classification of beta‐site amyloid precursor protein cleaving enzyme 1 inhibitors by using machine learning methods

Cited by 12 publications

References 23 publications

News about Therapies of Alzheimer’s Disease: Extracellular Vesicles from Stem Cells Exhibit Advantages Compared to Other Treatments

News about Therapies of Alzheimer’s Disease: Extracellular Vesicles from Stem Cells Exhibit Advantages Compared to Other Treatments

Classification of IGF1R ligand compounds for Identification of herbal extracts using extreme gradient boosting

Classifying Beta-Secretase 1 Inhibitor Activity for Alzheimer’s Drug Discovery with LightGBM

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