Biological Activity of Cyclic Peptide Extracted from Sphaeranthus amaranthoides Using De Novo Sequencing Strategy by Mass Spectrometry for Cancer.
Swarnalatha YanamadalaSivakumar ShanthirappanSidhika KannanNarendran ChiterasuKumaran SubramanianLamya Ahmed Al-KeridisTarun Kumar UpadhyayNawaf AlshammariMohd SaeedGuru Prasad SrinivasanRohini KarunakaranPublished in: Biology (2023)
Though there are several advancements and developments in cancer therapy, the treatment remains challenging. In recent years, the antimicrobial peptides (AMPs) from traditional herbs are focused for identifying and developing potential anticancer molecules. In this study, AMPs are identified from Sphaeranthus amaranthoides , a natural medicinal herb widely used as a crucial immune stimulant in Indian medicine. A total of 86 peptide traces were identified using liquid-chromatography-electrospray-ionisation mass spectrometry (LC-ESI-MS). Among them, three peptides were sequenced using the manual de novo sequencing technique. The in-silico prediction revealed that SA923 is a cyclic peptide with C-N terminal interaction of the carbon atom of ASP7 with the nitrogen atom of GLU1 (1ELVFYRD7). Thus, SA923 is presented under the orbitides class of peptides, which lack the disulfide bonds for cyclization. In addition, SA923, steered with the physicochemical properties and support vector machine (SVM) algorithm mentioned for the segment, has the highest in silico anticancer potential. Further, the in vitro cytotoxicity assay revealed the peptide has anti-proliferative activity, and toxicity studies were demonstrated in Danio rerio (zebrafish) embryos.
Keyphrases
- mass spectrometry
- liquid chromatography
- single cell
- high resolution mass spectrometry
- tandem mass spectrometry
- molecular dynamics
- gas chromatography
- high resolution
- capillary electrophoresis
- high performance liquid chromatography
- cancer therapy
- ms ms
- simultaneous determination
- molecular docking
- squamous cell carcinoma
- solid phase extraction
- drug delivery
- amino acid
- papillary thyroid
- deep learning
- machine learning
- molecular dynamics simulations
- young adults
- attention deficit hyperactivity disorder
- autism spectrum disorder
- squamous cell
- combination therapy
- high throughput