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Leveraging nitrogen occurrence in approved drugs to identify structural patterns

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DataCite Commons2024-01-08 更新2024-08-18 收录
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https://tandf.figshare.com/articles/dataset/Leveraging_nitrogen_occurrence_in_approved_drugs_to_identify_structural_patterns/24271365/1
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The process of drug development and discovery is costly and slow. Although an understanding of molecular design principles and biochemical processes has progressed, it is essential to minimize synthesis-testing cycles. An effective approach is to analyze key heteroatoms, including oxygen and nitrogen. Herein, we present an analysis focusing on the utilization of nitrogen atoms in approved drugs. The present work examines the frequency, distribution, prevalence, and diversity of nitrogen atoms in a dataset comprising 2,049 small molecules approved by different regulatory agencies (FDA and others). Various types of nitrogen atoms, such as sp<sup>3</sup>-, sp<sup>2</sup>-, sp-hybridized, planar, ring, and non-ring are included in this investigation. The results unveil both previously reported and newly discovered patterns of nitrogen atom distribution around the center of mass in the majority of drug molecules. This study has highlighted intriguing trends in the role of nitrogen atoms in drug design and development. The majority of drugs contain 1–3 nitrogen atoms within 5Å from the center of mass (COM) of a molecule, with a higher preference for the ring and planar nitrogen atoms. The results offer invaluable guidance for the multiparameter optimization process, thus significantly contributing toward the conversion of lead compounds into potential drug candidates.

药物研发与发现的过程往往耗时良久且成本高昂。尽管当前对于分子设计原则与生化过程的认知已有长足进展,但尽可能缩短合成-测试循环仍是至关重要的环节。其中一种行之有效的优化路径,便是对包括氧、氮在内的关键杂原子开展分析。本研究聚焦已获批药物中的氮原子应用情况,展开相关分析工作。本研究针对由不同监管机构(美国食品药品监督管理局FDA及其他机构)批准的2049个小分子组成的数据集,对氮原子的出现频率、分布特征、占比情况与多样性展开分析。本次研究涵盖多种类型的氮原子,包括sp³杂化、sp²杂化、sp杂化、平面型、环内型与环外型氮原子。研究结果揭示了多数药物分子中,围绕质心(center of mass, COM)的氮原子分布模式,其中既有此前已被报道的规律,也包含新发现的分布特征。本研究阐明了氮原子在药物研发与设计过程中所扮演角色的若干有趣趋势。多数药物分子的质心5埃(Å)范围内,含有1至3个氮原子,且更倾向于选择环内型与平面型氮原子。该研究结果可为多参数优化流程提供极具价值的指导,从而有力推动先导化合物向潜在候选药物的转化工作。
提供机构:
Taylor & Francis
创建时间:
2023-10-09
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