Computer-aided Drug Design and Drug Pharmacokinetic Prediction: A Mini-review

Abstract

Prediction of pharmacokinetics and drug targeting is a challenge in drug design. There are different types of software that can help predicting the pharmacokinetic profile of a drug. Quantitative structure-activity relationship (QSAR) modeling is used for drug design with less cost. Drug-excipient interactions are predicted by docking tools. Computerized drug target prediction and docking programs offer additional options to predict potential effects and adverse reactions of a given candidate as well as the best orientation of the compound on the receptor active site. Information on the absorption, distribution, metabolism and excretion of the drug in the body can enhance prediction of drug release and distribution in the blood and central nervous system (CNS). Computer-aided drug design and delivery can help saving the time and cost in the process of rational drug development.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

“…(1) two-dimensional molecular topology information; (2) three-dimensional molecular structure; and (3) physicochemical and electronic descriptors, which are commonly used to predict ADMET-related properties (Danishuddin and Khan, 2016;Tabeshpour et al, 2018;Zhang et al, 2018). Jiang et al (2020) developed a series of QSAR models by using 379 molecular descriptors to discriminate BCRP inhibitors.…”

“…QSAR modeling uses a large number of descriptors that allow lookups, enable structure/response associations, and help with similarity and substructure searches (Khan, 2010 ). Most of the available descriptors can be divided into three categories: (1) two-dimensional molecular topology information; (2) three-dimensional molecular structure; and (3) physicochemical and electronic descriptors, which are commonly used to predict ADMET-related properties (Danishuddin and Khan, 2016 ; Tabeshpour et al, 2018 ; Zhang et al, 2018 ). Jiang et al ( 2020 ) developed a series of QSAR models by using 379 molecular descriptors to discriminate BCRP inhibitors.…”

Inhibition of neutrophil elastase and cathepsin G as a new approach to the treatment of psoriasis: from fundamental biology to development of new target-specific drugs

“…действие таргетной молекулы к началу развития иммунного ответа и подавляя его на ранней стадии. Использование методов компьютерного молекулярного дизайна -актуальный подход к поиску лигандов протеаз CatG и HNE1 [8]. С точки зрения аминокислотного состава, вторичной структуры, гидрофобности активные сайты CatG и HNE1 гомологичны на 45%, что позволяет предположить реализуемость концепта мультитаргетного ингибитора [9,10].…”

Development of novel antipsychotic agents by inhibiting dopamine transporter –in silicoapproach

“…Chemoinformatic studies are in silico methods with vast applications, including the search for novel lead compounds or the optimization of pharmacological activity (or pharmacokinetic properties) of a series of chemical compounds with already determined biological activity. 30,31 Quantitative structure–activity relationship (QSAR) and molecular docking have been established as the most important and the most commonly used chemoinformatic methods. In current QSAR studies models are developed based on various molecular descriptors, calculated from defined molecular structures, with their strengths and weakness, and represented as a mathematical equation that links the biological activities of studied molecules with their chemical characteristics (molecular descriptors).…”