Choudhary Sumita, Kesavan Anup Kumar, Juneja Vijay, Thakur Sheetal
Department of Molecular Biology and Biochemistry, Guru Nanak Dev University, Amritsar, Punjab, India.
Department of Biotechnology and Microbiology, Kannur University, Dr. E. K. Janaki Ammal Campus, PalayadKannur, Kerala, India.
Front Bioinform. 2023 Apr 12;3:1125479. doi: 10.3389/fbinf.2023.1125479. eCollection 2023.
Computational prediction and protein structure modeling have come to the aid of various biological problems in determining the structure of proteins. These technologies have revolutionized the biological world of research, allowing scientists and researchers to gain insights into their biological questions and design experimental research much more efficiently. Pathogenic spp. is known to stay alive within the macrophages of its host. is an acid-fast bacterium that is the most common cause of tuberculosis and is considered to be the main cause of resistance of tuberculosis as a leading health issue. The genome of contains more than 4,000 genes, of which the majority are of unknown function. An attempt has been made to computationally model and dock one of its proteins, Rv1250 (MTV006.22), which is considered as an apparent drug-transporter, integral membrane protein, and member of major facilitator superfamily (MFS). The most widely used techniques, i.e., homology modeling, molecular docking, and molecular dynamics (MD) simulation in the field of structural bioinformatics, have been used in the present work to study the behavior of Rv1250 protein from . The structure of unknown TB protein, i.e., Rv1250 was retrived using homology modeling with the help of I-TASSER server. Further, one of the sites responsible for infection was identified and docking was done by using the specific Isoniazid ligand which is an inhibitor of this protein. Finally, the stability of protein model and analysis of stable and static interaction between protein and ligand molecular dynamic simulation was performed at 100 ns The designing of novel Rv1250 enzyme inhibitors is likely achievable with the use of proposed predicted model, which could be helpful in preventing the pathogenesis caused by . Finally, the MD simulation was done to evaluate the stability of the ligand for the specific protein.
计算预测和蛋白质结构建模在确定蛋白质结构方面为各种生物学问题提供了帮助。这些技术彻底改变了生物学研究领域,使科学家和研究人员能够更深入地了解他们的生物学问题,并更高效地设计实验研究。已知致病物种在其宿主的巨噬细胞内存活。是一种抗酸细菌,是结核病最常见的病因,被认为是结核病耐药这一主要健康问题的主要原因。的基因组包含4000多个基因,其中大多数功能未知。已尝试对其一种蛋白质Rv1250(MTV006.22)进行计算建模和对接,该蛋白质被认为是一种明显的药物转运蛋白、整合膜蛋白和主要转运体超家族(MFS)成员。结构生物信息学领域最广泛使用的技术,即同源建模、分子对接和分子动力学(MD)模拟,已用于本研究以研究来自的Rv1250蛋白的行为。利用I-TASSER服务器通过同源建模检索未知结核蛋白即Rv1250的结构。此外,确定了一个负责感染的位点,并使用该蛋白质的特异性抑制剂异烟肼进行对接。最后,在100纳秒的时间内对蛋白质模型的稳定性以及蛋白质与配体分子动力学模拟之间的稳定和静态相互作用进行了分析。利用所提出的预测模型可能设计出新型Rv1250酶抑制剂,这可能有助于预防由引起的发病机制。最后,进行MD模拟以评估配体对特定蛋白质的稳定性。