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Identification of sitagliptin binding proteins by affinity purification mass spectrometry.

ABSTRACT: Type 2 diabetes mellitus (T2DM) is recognized as a serious public health concern with increasing incidence. The dipeptidyl peptidase-4 (DPP-4) inhibitor sitagliptin has been used for the treatment of T2DM worldwide. Although sitagliptin has excellent therapeutic outcome, adverse effects are observed. In addition, previous studies have suggested that sitagliptin may have pleiotropic effects other than treating T2DM. These pieces of evidence point to the importance of further investigation of the molecular mechanisms of sitagliptin, starting from the identification of sitagliptin-binding proteins. In this study, by combining affinity purification mass spectrometry (AP-MS) and stable isotope labeling by amino acids in cell culture (SILAC), we discover seven high-confidence targets that can interact with sitagliptin. Surface plasmon resonance (SPR) assay confirms the binding of sitagliptin to three proteins, i. e., LYPLAL1, TCP1, and CCAR2, with binding affinities (K _D) ranging from 50.1 μM to 1490 μM. Molecular docking followed by molecular dynamic (MD) simulation reveals hydrogen binding between sitagliptin and the catalytic triad of LYPLAL1, and also between sitagliptin and the P-loop of ATP-binding pocket of TCP1. Molecular mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis indicates that sitagliptin can stably bind to LYPLAL1 and TCP1 in active sites, which may have an impact on the functions of these proteins. SPR analysis validates the binding affinity of sitagliptin to TCP1 mutant D88A is ~10 times lower than that to the wild-type TCP1. Our findings provide insights into the sitagliptin-targets interplay and demonstrate the potential of sitagliptin in regulating gluconeogenesis and in anti-tumor drug development.

SUBMITTER: Wang XN

PROVIDER: S-EPMC9827809 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Identification of sitagliptin binding proteins by affinity purification mass spectrometry.

Wang Xue-Ning XN Sim Byu-Ri BR Chen Hong H Zheng Yun-Xiao YX Xue Jun-Biao JB Wang Lei L Kong Wei-Sha WS Zhou Kuan K Guo Shu-Juan SJ Hou Jing-Li JL Zhang Jiong J Jiang He-Wei HW Tao Sheng-Ce SC

Acta biochimica et biophysica Sinica 20221001 10

Type 2 diabetes mellitus (T2DM) is recognized as a serious public health concern with increasing incidence. The dipeptidyl peptidase-4 (DPP-4) inhibitor sitagliptin has been used for the treatment of T2DM worldwide. Although sitagliptin has excellent therapeutic outcome, adverse effects are observed. In addition, previous studies have suggested that sitagliptin may have pleiotropic effects other than treating T2DM. These pieces of evidence point to the importance of further investigation of the ...[more]

PMID: 36239351

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Project description:Many species possess an endogenous circadian clock to synchronize internal physiology with an oscillating external environment. In plants, the circadian clock coordinates growth, metabolism and development over daily and seasonal time scales. Many proteins in the circadian network form oscillating complexes that temporally regulate myriad processes, including signal transduction, transcription, protein degradation and post-translational modification. In Arabidopsis thaliana, a tripartite complex composed of EARLY FLOWERING 4 (ELF4), EARLY FLOWERING 3 (ELF3), and LUX ARRHYTHMO (LUX), named the evening complex, modulates daily rhythms in gene expression and growth through transcriptional regulation. However, little is known about the physical interactions that connect the circadian system to other pathways. We used affinity purification and mass spectrometry (AP-MS) methods to identify proteins that associate with the evening complex in A. thaliana. New connections within the circadian network as well as to light signaling pathways were identified, including linkages between the evening complex, TIMING OF CAB EXPRESSION1 (TOC1), TIME FOR COFFEE (TIC), all phytochromes and TANDEM ZINC KNUCKLE/PLUS3 (TZP). Coupling genetic mutation with affinity purifications tested the roles of phytochrome B (phyB), EARLY FLOWERING 4, and EARLY FLOWERING 3 as nodes connecting the evening complex to clock and light signaling pathways. These experiments establish a hierarchical association between pathways and indicate direct and indirect interactions. Specifically, the results suggested that EARLY FLOWERING 3 and phytochrome B act as hubs connecting the clock and red light signaling pathways. Finally, we characterized a clade of associated nuclear kinases that regulate circadian rhythms, growth, and flowering in A. thaliana. Coupling mass spectrometry and genetics is a powerful method to rapidly and directly identify novel components and connections within and between complex signaling pathways.

Project description:BackgroundRecent advances in molecular biology have led to the accumulation of large amounts of data on protein-protein interaction networks in different species. An important challenge for the analysis of these data is to extract functional modules such as protein complexes and biological processes from networks which are characterised by the present of a significant number of false positives. Various computational techniques have been applied in recent years. However, most of them treat protein interaction as binary. Co-complex relations derived from affinity purification/mass spectrometry (AP-MS) experiments have been largely ignored.MethodsThis paper presents a new algorithm for detecting protein complexes from AP-MS data. The algorithm intends to detect groups of prey proteins that are significantly co-associated with the same set of bait proteins. We first construct AP-MS data as a bipartite network, where one set of nodes consists of bait proteins and the other set is composed of prey proteins. We then calculate pair-wise similarities of bait proteins based on the number of their commonly shared neighbours. A hierarchical clustering algorithm is employed to cluster bait proteins based on the similarities and thus a set of 'seed' clusters is obtained. Starting from these 'seed' clusters, an expansion process is developed to identify prey proteins which are significantly associated with the same set of bait proteins. Then, a set of complete protein complexes is derived. In application to two real AP-MS datasets, we validate biological significance of predicted protein complexes by using curated protein complexes and well-characterized cellular component annotation from Gene Ontology (GO). Several statistical metrics have been applied for evaluation.ResultsExperimental results show that, the proposed algorithm achieves significant improvement in detecting protein complexes from AP-MS data. In comparison to the well-known MCL algorithm, our algorithm improves the accuracy rate by about 20% in detecting protein complexes in both networks and increases the F-Measure value by about 50% in Krogan_2006 network. Greater precision and better accuracy have been achieved and the identified complexes are demonstrated to match well with existing curated protein complexes.ConclusionsOur study highlights the significance of taking co-complex relations into account when extracting protein complexes from AP-MS data. The algorithm proposed in this paper can be easily extended to the analysis of other biological networks which can be conveniently represented by bipartite graphs such as drug-target networks.

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Identification of sitagliptin binding proteins by affinity purification mass spectrometry.

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Identification of sitagliptin binding proteins by affinity purification mass spectrometry.

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