Advances in the Applications of Bioinformatics and Chemoinformatics.
Mohamed A RaslanSara A RaslanEslam M ShehataAmr S MahmoudNagwa Ali SabriPublished in: Pharmaceuticals (Basel, Switzerland) (2023)
Chemoinformatics involves integrating the principles of physical chemistry with computer-based and information science methodologies, commonly referred to as "in silico techniques", in order to address a wide range of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, the incorporation of machine learning has been considered of high importance in the field of drug design, enabling the extraction of chemical data from enormous compound databases to develop drugs endowed with significant biological features. The present review discusses the field of cheminformatics and proposes the use of virtual chemical libraries in virtual screening methods to increase the probability of discovering novel hit chemicals. The virtual libraries address the need to increase the quality of the compounds as well as discover promising ones. On the other hand, various applications of bioinformatics in disease classification, diagnosis, and identification of multidrug-resistant organisms were discussed. The use of ensemble models and brute-force feature selection methodology has resulted in high accuracy rates for heart disease and COVID-19 diagnosis, along with the role of special formulations for targeting meningitis and Alzheimer's disease. Additionally, the correlation between genomic variations and disease states such as obesity and chronic progressive external ophthalmoplegia, the investigation of the antibacterial activity of pyrazole and benzimidazole-based compounds against resistant microorganisms, and its applications in chemoinformatics for the prediction of drug properties and toxicity-all the previously mentioned-were presented in the current review.
Keyphrases
- drug discovery
- machine learning
- deep learning
- multidrug resistant
- molecular docking
- big data
- sars cov
- coronavirus disease
- metabolic syndrome
- multiple sclerosis
- artificial intelligence
- physical activity
- mental health
- insulin resistance
- public health
- single molecule
- type diabetes
- pulmonary hypertension
- adipose tissue
- emergency department
- convolutional neural network
- cystic fibrosis
- pseudomonas aeruginosa
- cerebrospinal fluid
- cross sectional
- dna methylation
- drug delivery
- cognitive decline
- escherichia coli
- body mass index
- weight gain
- high fat diet induced