一种基于蛋白质组学的稳健方法,用于鉴定合成糖胺聚糖模拟物的优选蛋白质靶点。

A Robust Proteomics-Based Method for Identifying Preferred Protein Targets of Synthetic Glycosaminoglycan Mimetics.

作者信息

Afosah Daniel K, Ongolu Ravikumar, Fayyad Rawan M, Hawkridge Adam, Desai Umesh R

机构信息

Department of Medicinal Chemistry, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298.

Institute for Structural Biology, Drug Discovery and Development, Virginia Commonwealth University, Richmond, VA 23219.

出版信息

bioRxiv. 2025 Jan 24:2025.01.23.634492. doi: 10.1101/2025.01.23.634492.

Abstract

A robust technology is critically needed for identifying preferred protein targets of glycosaminoglycans (GAGs), and synthetic mimetics thereof, in biological milieu. We present a robust 10-step strategy for identification and validation of preferred protein targets of highly sulfated, synthetic, small, GAG-like molecules using diazirine-based photoaffinity labeling-proteomics approach. Our work reveals that optimally designed, homogeneous probes based on minimalistic photoactivation and affinity pulldown groups coupled with rigorous proteomics, biochemical and orthogonal validation steps offer excellent potential to identify preferred targets of GAG mimetics from the potentially numerous possible targets that cloud GAG interaction studies. Application of this 10-step strategy for a promising highly sulfated, small GAG mimetic led to identification of only a handful of preferred targets in human plasma. This new robust strategy will greatly aid drug discovery and development efforts involving GAG sequences, or sulfated small mimetics thereof, as leads.

摘要

在生物环境中,迫切需要一种强大的技术来识别糖胺聚糖(GAGs)及其合成模拟物的优选蛋白质靶点。我们提出了一种强大的10步策略,用于使用基于重氮丙啶的光亲和标记-蛋白质组学方法来鉴定和验证高度硫酸化、合成的、小的、GAG样分子的优选蛋白质靶点。我们的工作表明,基于简约光活化和亲和下拉基团设计的优化、同质探针,再加上严格的蛋白质组学、生化和正交验证步骤,具有巨大潜力,能够从众多可能使GAG相互作用研究变得复杂的潜在靶点中识别出GAG模拟物的优选靶点。将这种10步策略应用于一种有前景的高度硫酸化小GAG模拟物,仅在人血浆中鉴定出了少数几个优选靶点。这种新的强大策略将极大地助力涉及GAG序列或其硫酸化小模拟物作为先导物的药物发现和开发工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9ba/11785238/105b007a5339/nihpp-2025.01.23.634492v1-f0001.jpg

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