背景:由于对化合物药理活性的潜在影响,N-氧化物降解物的形成是新药开发中的主要问题。这些效果包括但不限于溶解度,稳定性,毒性,和功效。此外,这些化学转化会影响理化性质,从而影响药物的可制造性。因此,对N-氧化物转化的识别和控制在开发新疗法中至关重要。
目的:本研究描述了一种在硅方法的发展,以确定在原料药中自氧化的N-氧化物的形成。
方法:使用分子建模技术和密度泛函理论(DFT)在B3LYP/6-31G(d,P)理论水平。总共使用257个氮原子和15种不同的可氧化氮类型来开发该方法。
结果:结果表明,ALIE可以可靠地用于预测最容易形成N-氧化物的氮。开发了一个风险量表,快速将氮的氧化脆弱性分类为小,中等,或高。
结论:开发的过程提供了一种强大的工具来识别N-氧化的结构磁化率,并能够快速阐明结构以解决潜在的实验歧义。
BACKGROUND: The formation of N-oxide degradants is a major concern in development of new drugs due to potential effects on a compound\'s pharmacological activity. Such effects include but are not limited to solubility, stability, toxicity, and efficacy. In addition, these chemical transformations can impact physicochemical properties that affect drug manufacturability. Hence identification and control of N-oxide transformations is of critical importance in the development of new therapeutics.
OBJECTIVE: This study describes the development of an in-silico approach to identify N-oxide formation in APIs with respect to autoxidation.
METHODS: Average Local Ionization Energy (ALIE) calculations were carried out using molecular modeling techniques and application of Density Functional Theory (DFT) at the B3LYP/6-31G(d,p) level of theory. A total of 257 nitrogen atoms and 15 different oxidizable nitrogen types were used in developing this method.
RESULTS: The results show that ALIE could be reliably used to predict the most susceptible nitrogen for N-oxide formation. A risk scale was developed that rapidly categorizes nitrogen\'s oxidative vulnerabilities as small, medium, or high.
CONCLUSIONS: The developed process presents a powerful tool to identify structural susceptibilities for N-oxidation as well as enabling rapid structure elucidation in resolving potential experimental ambiguities.