生物信息学
溶解度
共晶
生物利用度
溶解
生化工程
结晶
化学
计算机科学
组合化学
生物信息学
有机化学
分子
生物
生物化学
工程类
氢键
基因
作者
Parth Sarathi,Swarupanjali Padhi
标识
DOI:10.1080/03639045.2022.2042554
摘要
Most of the widely used drugs have problems associated with their oral bioavailability either due to their poor aqueous solubility or due to their poor permeability. Co-crystallization is an efficient and economically feasible approach that offers a great opportunity for improvement in physicochemical properties such as solubility, stability, and bioavailability of such type of therapeutic agent. Selection of the best co-former plays a major role in co-crystallization. Various approaches have been developed for the selection of suitable co-formers with API. In recent years in silico screening, a computational tool paying more attention for screening of co-formers has been developed. Numerous approaches can be used for in silico screening such as the Autodocking tool, COSMORS, COSMOTHERM, etc. Autodocking can predict several numbers of co-former effectively screened in silico method to identify a suitable co-former with an API. Prediction of solubility and dissolution is also important for the development of co-crystal. In this review, we discuss in silico screening of coformer and thermodynamic approaches to determine the dissolution and solubility of co-crystal specially with reference to the drugs belonging to BCS class II group.
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