Sivakumar Subramaniam, Niranjali Devaraj Sivasitambaram
Department of Biochemistry, Sri Sankara Arts and Science College, Enathur 631561, Tamilnadu, India.
J Diabetes Metab Disord. 2014 Jan 8;13(1):13. doi: 10.1186/2251-6581-13-13.
Osteopontin (Eta, secreted sialoprotein 1, opn) is secreted from different cell types including cancer cells. Three splice variant forms namely osteopontin-a, osteopontin-b and osteopontin-c have been identified. The main astonishing feature is that osteopontin-c is found to be elevated in almost all types of cancer cells. This was the vital point to consider it for sequence analysis and structure predictions which provide ample chances for prognostic, therapeutic and preventive cancer research.
Osteopontin-c gene sequence was determined from Breast Cancer sample and was translated to protein sequence. It was then analyzed using various software and web tools for binding pockets, docking and druggability analysis. Due to the lack of homological templates, tertiary structure was predicted using ab-initio method server - I-TASSER and was evaluated after refinement using web tools. Refined structure was compared with known bone sialoprotein electron microscopic structure and docked with CD44 for binding analysis and binding pockets were identified for drug designing.
Signal sequence of about sixteen amino acid residues was identified using signal sequence prediction servers. Due to the absence of known structures of similar proteins, three dimensional structure of osteopontin-c was predicted using I-TASSER server. The predicted structure was refined with the help of SUMMA server and was validated using SAVES server. Molecular dynamic analysis was carried out using GROMACS software. The final model was built and was used for docking with CD44. Druggable pockets were identified using pocket energies.
The tertiary structure of osteopontin-c was predicted successfully using the ab-initio method and the predictions showed that osteopontin-c is of fibrous nature comparable to firbronectin. Docking studies showed the significant similarities of QSAET motif in the interaction of CD44 and osteopontins between the normal and splice variant forms of osteopontins and binding pockets analyses revealed several pockets which paved the way to the identification of a druggable pocket.
骨桥蛋白(Eta,分泌性唾液酸蛋白1,opn)由包括癌细胞在内的不同细胞类型分泌。已鉴定出三种剪接变体形式,即骨桥蛋白-a、骨桥蛋白-b和骨桥蛋白-c。主要令人惊讶的特征是,在几乎所有类型的癌细胞中都发现骨桥蛋白-c水平升高。这是对其进行序列分析和结构预测的关键点,为癌症的预后、治疗和预防研究提供了充足的机会。
从乳腺癌样本中确定骨桥蛋白-c基因序列,并将其翻译成蛋白质序列。然后使用各种软件和网络工具对其进行结合口袋、对接和药物可及性分析。由于缺乏同源模板,使用从头算方法服务器-I-TASSER预测三级结构,并在使用网络工具进行优化后进行评估。将优化后的结构与已知的骨唾液蛋白电子显微镜结构进行比较,并与CD44对接以进行结合分析,并确定结合口袋以用于药物设计。
使用信号序列预测服务器鉴定出约16个氨基酸残基的信号序列。由于缺乏相似蛋白质的已知结构,使用I-TASSER服务器预测骨桥蛋白-c的三维结构。预测的结构在SUMMA服务器的帮助下进行了优化,并使用SAVES服务器进行了验证。使用GROMACS软件进行分子动力学分析。构建了最终模型并用于与CD44对接。使用口袋能量确定可成药口袋。
使用从头算方法成功预测了骨桥蛋白-c的三级结构,预测结果表明骨桥蛋白-c具有与纤连蛋白相当的纤维性质。对接研究表明,在正常和剪接变体形式的骨桥蛋白之间,CD44与骨桥蛋白相互作用中的QSAET基序具有显著相似性,结合口袋分析揭示了几个口袋,为鉴定可成药口袋铺平了道路。