Pawar Shivani V, Banini Wilson Sena Kwaku, Shamsuddeen Musa Muhammad, Jumah Toheeb A, Dolling Nigel N O, Tiamiyu Abdulwasiu, Awe Olaitan I
Department of Biotechnology and Bioinformatics, Deogiri College, Auranagabad, Maharashtra, India.
Department of Theoretical and Applied Biology, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Front Chem. 2024 Nov 29;12:1509407. doi: 10.3389/fchem.2024.1509407. eCollection 2024.
Homology modeling is a widely used computational technique for predicting the three-dimensional (3D) structures of proteins based on known templates,evolutionary relationships to provide structural insights critical for understanding protein function, interactions, and potential therapeutic targets. However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.
Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. Integrating Biopython for sequence alignment, BLAST for template identification, and ProMod3 for structure generation, Prostruc streamlines complex workflows into a user-friendly interface. The tool enables researchers to input protein sequences, identify homologous templates from databases such as the Protein Data Bank (PDB), and generate high-quality 3D structures with minimal computational expertise. Prostruc implements a two-stage vSquarealidation process: first, it uses TM-align for structural comparison, assessing Root Mean Deviations (RMSD) and TM scores against reference models. Second, it evaluates model quality via QMEANDisCo to ensure high accuracy.
The top five models are selected based on these metrics and provided to the user. Prostruc stands out by offering scalability, flexibility, and ease of use. It is accessible via a cloud-based web interface or as a Python package for local use, ensuring adaptability across research environments. Benchmarking against existing tools like SWISS-MODEL,I-TASSER and Phyre2 demonstrates Prostruc's competitive performance in terms of structural accuracy and job runtime, while its open-source nature encourages community-driven innovation.
Prostruc is positioned as a significant advancement in homology modeling, making high-quality protein structure prediction more accessible to the scientific community.
同源建模是一种广泛使用的计算技术，用于基于已知模板预测蛋白质的三维（3D）结构，其进化关系可为理解蛋白质功能、相互作用及潜在治疗靶点提供关键的结构见解。然而，现有工具通常需要大量专业知识和计算资源，这对许多研究人员来说是一个障碍。
Prostruc是一个基于Python的同源建模工具，旨在通过直观、自动化的流程简化蛋白质结构预测。Prostruc集成了用于序列比对的Biopython、用于模板识别的BLAST和用于结构生成的ProMod3，将复杂的工作流程简化为用户友好的界面。该工具使研究人员能够输入蛋白质序列，从诸如蛋白质数据库（PDB）等数据库中识别同源模板，并以最少的计算专业知识生成高质量的3D结构。Prostruc实施两阶段验证过程：首先，它使用TM-align进行结构比较，根据参考模型评估均方根偏差（RMSD）和TM分数。其次，它通过QMEANDisCo评估模型质量以确保高精度。
根据这些指标选择前五个模型并提供给用户。Prostruc具有可扩展性、灵活性和易用性，脱颖而出。它可通过基于云的网络界面访问，也可作为Python包供本地使用，确保在各种研究环境中都具有适应性。与现有工具如SWISS-MODEL、I-TASSER和Phyre2进行基准测试表明，Prostruc在结构准确性和作业运行时间方面具有竞争力，而其开源性质鼓励社区驱动的创新。
Prostrustruc被定位为同源建模的一项重大进展，使科学界能够更轻松地进行高质量蛋白质结构预测。
