Promising anti-cancer compounds using drug design strategies
Pourya Zarshenas, Fereshteh Azimian · Zenodo (CERN European Organization for Nuclear Research) · 2022
During drug development, standard or average dosages are determined. However, people react differently to drugs. Many factors, including weight, genetic makeup, and the presence of other disorders, affect response to medication. These factors need to be taken into account when a doctor determines the dosage for a particular person. Rational design strategies used to develop multitarget tyrosine kinase inhibitors (MTKIs), which were an emerging model when first published in early 2000, became one of the hottest topics in drug discovery in 2019, providing opportunities for innovative drug discovery and development. The current review provides a comprehensive presentation of the application of high throughput, in silico screening, and knowledge-based techniques in MTKI design, including machine learning, structure-based, sieving virtual-based, de novo-based, fragment-based, ligand-based, and other related design approaches. After presenting the basic principles, this review outlines the possibilities and limitations of the methods and addresses studies conducted by the drug discovery community both within academia and pharmaceutical companies. products, especially on multi-targeted drugs already on the market. The rationale used behind the design and results achieved through these adoption strategies were clearly discussed in the hope of presenting a "big picture" of the adoption of strategic approaches. Recent and successful examples attract the attention of researchers working in this field.