Sőregi Petra, Zwillinger Márton, Vágó Lajos, Csékei Márton, Kotschy Andras
Servier Research Institute of Medicinal Chemistry Záhony utca 7 1031 Budapest Hungary
Hevesy György PhD School of Chemistry, Eötvös Loránd University Pázmány Péter sétány 1/A 1117 Budapest Hungary.
Chem Sci. 2024 Aug 22;15(36):14938-45. doi: 10.1039/d4sc03519d.
The need for reliable information storage is on a steep rise. Sequence-defined polymers, particularly oligonucleotides, are already in use in several areas, while compound mixtures also offer a simple way for storing information. We investigated the use of a set of isotopologues in information storage by mixing, where the information is stored in the form of a mass spectrometric (MS) fingerprint of the mixture. A small molecule with 24 non-labile and replaceable hydrogen atoms was selected as a model, and a set of components covering the D-D deuteration range were synthesized. Theoretical analysis predicted that by mixing up to 10 out of the prepared components, one can encode over 130 million different combinations and distinguish their MS fingerprints. As a proof of principle, several mixtures predicted to have similar fingerprints were prepared and their MS fingerprints were recorded. From each measured MS fingerprint, we were able to unambiguously identify the actual composition of the mixture. It was also demonstrated that one can make the MS fingerprints of a given mixture unique, thereby making counterfeiting of the stored information very difficult. Finally, the utility of isotope ratio encoding in covalent tagging was also demonstrated.
对可靠信息存储的需求正在急剧上升。序列定义的聚合物，特别是寡核苷酸，已经在多个领域得到应用，而化合物混合物也为信息存储提供了一种简单的方式。我们通过混合研究了一组同位素异构体在信息存储中的应用，其中信息以混合物的质谱（MS）指纹图谱的形式存储。选择了一个具有24个非不稳定且可替换氢原子的小分子作为模型，并合成了一组涵盖D-D氘代范围的组分。理论分析预测，通过混合制备的多达10种组分，可以编码超过1.3亿种不同的组合，并区分它们的MS指纹图谱。作为原理验证，制备了几种预计具有相似指纹图谱的混合物，并记录了它们的MS指纹图谱。从每个测量的MS指纹图谱中，我们能够明确识别混合物的实际组成。还证明了可以使给定混合物的MS指纹图谱独一无二，从而使存储信息的伪造变得非常困难。最后，还展示了同位素比率编码在共价标记中的实用性。
