Molecular Complexity: You Know It When You See It.
Molecular Complexity: You Know It When You See It.
复制标题
分子复杂性：当你看到它时你就知道它。
DOI：
10.1021/acs.jmedchem.3c01507
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发表时间：
2023
影响因子：
7.3
通讯作者：
Bologa,Cristian
中科院分区：
文献类型：
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作者：
Oprea,TudorI;Bologa,Cristian
分子复杂性 (MC) 缺乏通用的定义，但各种研究在从配体-受体相互作用到 DNA 测序的范围内解决了它，首要重点是它在合成有机化学和药物研究中的重要性。在药物发现中量化 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、信息论和用于测量 MC 的子结构特征计数的策略通常与分子量 (MW) 相关。 Herbert Waldmann 和他的团队引入了一种新的 MC 指标，称为空间分数 (SPS)，该指标基于原子杂交和立体异构考虑等因素。虽然 SPS 及其标准化版本 nSPS 与天然产品相似度评分相关，但它们与传统化学特性不一致。我们检查了已批准药物的 nSPS 趋势，发现 8 年来 MC 没有显着变化，nSPS 也没有捕获该期间的药物创新。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，但该指标与目标生物活性和口服生物利用度等关键药物特性无关。 nSPS 反映了化学家对化学复杂性的直观感受，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。
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.