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分子复杂性:一看便知。

Molecular Complexity: You Know It When You See It.

机构信息

Expert Systems Inc, 12760 High Bluff Dr #370, San Diego, California 92130, United States.

Department of Internal Medicine, University of New Mexico, MSC09-5025, Albuquerque, New Mexico 87131, United States.

出版信息

J Med Chem. 2023 Sep 28;66(18):12710-12714. doi: 10.1021/acs.jmedchem.3c01507. Epub 2023 Sep 7.

DOI:10.1021/acs.jmedchem.3c01507
PMID:37675804
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10544322/
Abstract

Molecular complexity (MC) lacks a universal definition, but various studies address it in contexts ranging from ligand-receptor interactions to DNA sequencing, with the overarching emphasis being its significance in synthetic organic chemistry and pharmaceutical research. Efforts to quantify MC in drug discovery have been numerous, but a unified approach remains challenging. Strategies based on graph theory, information theory, and substructural feature counts employed to gauge MC are often correlated to molecular weight (MW). Herbert Waldmann and his team introduced a new MC metric called the spacial score (SPS), which is based on factors like atom hybridization and stereoisomeric considerations. While SPS and its normalized version, nSPS, correlate with the natural product likeness score, they do not align with traditional chemical properties. We examined nSPS trends for approved drugs and found no significant changes in MC over eight decades, nor did nSPS capture drug innovation during that period. Furthermore, our analysis indicates that while the majority of approved drugs have an nSPS value between 10 and 20, this metric does not correlate with key drug properties like target bioactivity and oral bioavailability. Mirroring a chemist's intuitive sense of chemical complexity, nSPS addresses the need for a precise empirical tool while a universal definition of MC remains elusive.

摘要

分子复杂性 (MC) 缺乏通用定义,但各种研究在从配体-受体相互作用到 DNA 测序的范围内都涉及到它,其在合成有机化学和药物研究中的重要性是核心关注点。在药物发现中定量 MC 的努力已经很多,但统一的方法仍然具有挑战性。基于图论、信息论和亚结构特征计数的策略被用于衡量 MC,这些策略通常与分子量 (MW) 相关。Herbert Waldmann 和他的团队引入了一种新的 MC 度量,称为空间分数 (SPS),它基于原子杂化和立体异构考虑等因素。虽然 SPS 及其归一化版本 nSPS 与天然产物相似性评分相关,但它们与传统化学性质不匹配。我们检查了批准药物的 nSPS 趋势,发现在 80 多年的时间里 MC 没有明显变化,nSPS 也没有捕捉到该期间的药物创新。此外,我们的分析表明,虽然大多数批准药物的 nSPS 值在 10 到 20 之间,但该度量与关键药物特性(如靶标生物活性和口服生物利用度)不相关。nSPS 反映了化学家对化学复杂性的直观感觉,它满足了对精确经验工具的需求,而 MC 的通用定义仍然难以捉摸。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f687/10544322/e655f6a317d5/jm3c01507_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f687/10544322/739b15e95006/jm3c01507_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f687/10544322/e655f6a317d5/jm3c01507_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f687/10544322/739b15e95006/jm3c01507_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f687/10544322/e655f6a317d5/jm3c01507_0002.jpg

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Chem Sci. 2025 Jan 24;16(7):2961-2979. doi: 10.1039/d4sc08017c. eCollection 2025 Feb 12.
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ACS Omega. 2024 Jun 24;9(26):28476-28484. doi: 10.1021/acsomega.4c02427. eCollection 2024 Jul 2.
Nat Commun. 2021 Mar 25;12(1):1883. doi: 10.1038/s41467-021-22174-4.
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ChEMBL: towards direct deposition of bioassay data.ChEMBL:致力于直接生成生物测定数据。
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