{"title":"Cancer Therapeutics: Structure-Based Drug Design of Inhibitors for a Novel Angiogenic Growth Factor","authors":"Navaneetha Nambigari","doi":"10.17537/2023.18.72","DOIUrl":null,"url":null,"abstract":"\nAngiogenesis, the formation of new blood vessels, is a critical and rate-limiting tumor growth step controlled by pro-angiogenic factors and specific inhibitors. Tumor angiogenesis is essential for cancer progression and metastasis. Platelet growth factors (PDGF) and their receptors (PDGFR) are associated with tumor angiogenesis through overexpression of PDGF. Inhibition of PDGF and its signaling pathway is a new approach to the discovery of anticancer therapeutic agents. The present study focuses on the PDGF-C protein in the identification of novel anti-angiogenic compounds. MODELLER 9.10 software allows users to create and refine a 3D homology model of the PDGF-C protein (345 a.a. length). Secondary structure analysis of the 3D energy model reveals 16 β sheets held together by four cation–π and one π–σ interactions, and three salt bridges. The quality of the model is assessed using the Ramachandran plot (90 percent amino acids in the favorable region) and the ProSA server (Z-score = –2.28). Active site residues are identified using Castp, QSite search engine, site map, and protein docking of the protein to its receptor. In addition, virtual screening is performed at the active site using the Glide module of the Schrodinger Suite. Glide score, glide energy and ADME are being measured to discover new benefits of pyrazolone and pyrrolidine-2,3-dione scaffolds as potent PDGF-C antagonists for anti-angiogenic cancer chemotherapy drugs.\n","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"55 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biology and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17537/2023.18.72","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
Angiogenesis, the formation of new blood vessels, is a critical and rate-limiting tumor growth step controlled by pro-angiogenic factors and specific inhibitors. Tumor angiogenesis is essential for cancer progression and metastasis. Platelet growth factors (PDGF) and their receptors (PDGFR) are associated with tumor angiogenesis through overexpression of PDGF. Inhibition of PDGF and its signaling pathway is a new approach to the discovery of anticancer therapeutic agents. The present study focuses on the PDGF-C protein in the identification of novel anti-angiogenic compounds. MODELLER 9.10 software allows users to create and refine a 3D homology model of the PDGF-C protein (345 a.a. length). Secondary structure analysis of the 3D energy model reveals 16 β sheets held together by four cation–π and one π–σ interactions, and three salt bridges. The quality of the model is assessed using the Ramachandran plot (90 percent amino acids in the favorable region) and the ProSA server (Z-score = –2.28). Active site residues are identified using Castp, QSite search engine, site map, and protein docking of the protein to its receptor. In addition, virtual screening is performed at the active site using the Glide module of the Schrodinger Suite. Glide score, glide energy and ADME are being measured to discover new benefits of pyrazolone and pyrrolidine-2,3-dione scaffolds as potent PDGF-C antagonists for anti-angiogenic cancer chemotherapy drugs.