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In Silico Approach to Cancer Therapy
Published in Anjana Pandey, Saumya Srivastava, Recent Advances in Cancer Diagnostics and Therapy, 2022
Anjana Pandey, Saumya Srivastava
Another common resource is the STITCH database. It is a tool of search and information integrations used to check interactions between chemicals and proteins. This tool utilized the chemicals of PubChem database, while the relations between chemicals and chemical–protein obtained from some different resources having high-throughput methods and protein sequence matching. The STITCH database has been employed in various systematic channels. Other tools involved are mainly information-rich databases such as DrugBank, Pharos, etc. DrugBank comprehends the data of chemical, pharmacological, and pharmaceutical studies for approximately 13,363 drugs (Wishart et al., 2018). Pharos is a web interface used to explore the Target Central Resource Database (TCRD) (Nguyen et al., 2017).
In Pursuit of Total Exposure Health
Published in Kirk A. Phillips, Dirk P. Yamamoto, LeeAnn Racz, Total Exposure Health, 2020
Researchers have cataloged over 42,000 metabolites associated with food, drugs, food additives, phytochemicals, and pollutants (Betts and Sawyer 2016). Metabolomic studies have identified environmentally linked biomarkers related to numerous diseases, to include chronic fatigue syndrome and congenital heart defects. Three online metabolomics databases allow free access to the metabolome: DrugBank, Human Metabolome Database, and Toxic Exposome Database (Betts and Sawyer 2016). As both a bioinformatics and cheminformatics resource, DrugBank (2020) contains information on drugs and drug targets and has approximately 2,280 drug and drug metabolites. The Human Metabolome Database (2020) includes information about small molecule metabolites found in the human body and contains over 114,000 metabolite entries, with 5,702 protein sequences linked to those entries. The Toxic Exposome Database (2020), formerly the Toxin and Toxin Target Database (T3DB), is a bioinformatics resource that combines detailed toxin data with comprehensive toxin target information and contains approximately 3,670 toxins and environmental pollutants.
Re-Analysis of Non-Small Cell Lung Cancer and Drug Resistance Microarray Datasets with Machine Learning
Published in Cybernetics and Systems, 2023
Çiğdem Erol, Tchare Adnaane Bawa, Yalçın Özkan
When the literature is examined, it is seen that machine learning models are used in the field of health, especially in drug interactions. In the review studies of Vo et al. (2022), it is seen that machine learning algorithms in the field of drug-drug interaction are generally made with text or structure data. Hung et al. (2022) applied machine learning techniques for drug-drug interaction in Osteoporosis and Pagets’ diseases to the data obtained from the Drugbank database. Lam et al. (2022) classified the molecular subtypes of gliomas using machine learning methods in image data. Unlike similar studies in the literature, machine learning methods were applied to microarray genetic data in this study. All of the microarray datasets produced in relation to drugs used in non-small cell lung cancer disease in the NCBI GEO database were analyzed within the scope of this research.
Environmental impact and biological removal processes of pharmaceutically active compounds: The particular case of sulfonamides, anticonvulsants and steroid estrogens
Published in Critical Reviews in Environmental Science and Technology, 2020
Cristiano S. Leal, Daniela P. Mesquita, António Luís Amaral, Almerinda M. Amaral, Eugénio C. Ferreira
Anticonvulsants are a class of PhACs that act by reducing abnormal activity in the brain, and are applied in the treatment of mental illnesses, depression, post-traumatic stress disorders, and drug and alcohol dependencies, among others (Mohapatra et al., 2014). One of the most frequently detected anticonvulsant in water bodies is carbamazepine (CBZ) (Zhang et al., 2008), usually employed in the treatment of epilepsy, seizures, trigeminal neuralgia, diabetic neuropathy, bipolar disorder, and drug and alcohol dependencies, among others (RxList, 2016a; Drugbank, 2016a). The mechanism of action of CBZ involves inhibiting sustained repetitive firing by blocking use-dependent sodium channels, norepinephrine release, synaptic transmission in the trigeminal nucleus, and reduction of post-tetanic potentiation on the spinal cord synaptic transmission. It is also believed to possess anticholinergic, antidiuretic, antiarrhythmic, and antidepressant activity, thus acting as a muscle relaxant and sedative (Drugbank, 2016a).
Crispr biosensing and Ai driven tools for detection and prediction of Covid-19
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2023
Abdullahi Umar Ibrahim, Pwadubashiyi Coston Pwavodi, Mehmet Ozsoz, Fadi Al-Turjman, Tirah Galaya, Joy Johnson Agbo
Li et al. (2020) utilised high-throughput screening approach to screen for potential COVID drug using dataset of sequences and structures of SARS-CoV obtained from PDB database using NCBI-blast version 2.9 installed on a local system, and 8000 approved and experimental molecules are obtained from Drugbank. The screening analysis identified four small molecular drugs, which include Nelfinavir, Bictegravir, Tegobuv and Prulifloxacin. These molecules were previously tested to be safe and therefore has the potentials as candidates for treatments of COVID-19.