konnect2prot 2.0: Integrating advanced analytical tools for deeper understanding of protein properties in a functional protein-protein interaction network.

IF 4.4 2区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY

Computational and structural biotechnology journal Pub Date : 2025-07-05 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.07.006

Shivam Kumar, Abhinav Agarwal, Dipanka Tanu Sarmah, Samrat Chatterjee

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引用次数: 0

Abstract

Proteins work in coordination to catalyze and regulate all biological activities and drive cellular functions. The collective behavior of proteins is studied through protein-protein interaction (PPI) networks, which provide a system-level understanding of their regulatory behavior. konnect2prot (k2p) is a web application that generates a context-specific directional PPI network from a list of proteins as input. It identifies influential spreaders in the generated network and detects their biological and topological importance. Here, we report the features added to k2p since its first release. Building on the foundation of its predecessor, k2p 2.0 now integrates differential gene expression analysis, thereby bridging the gap between gene-level regulation and protein-level activity, providing a holistic view of how transcriptional changes fuel cellular behavior. konnect2prot 2.0 is freely accessible at: https://konnect2prot_v2.thsti.in.

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konnect2prot 2.0：集成先进的分析工具，以更深入地了解功能性蛋白质相互作用网络中的蛋白质特性。

蛋白质协同工作，催化和调节所有生物活动，驱动细胞功能。蛋白质的集体行为是通过蛋白质-蛋白质相互作用（PPI）网络来研究的，它提供了对其调节行为的系统级理解。konnect2prot （k2p）是一个web应用程序，它从一个蛋白质列表作为输入生成一个上下文特定的定向PPI网络。它在生成的网络中识别有影响力的传播者，并检测它们的生物学和拓扑重要性。在这里，我们报告了k2p自第一次发布以来增加的特性。在其前身的基础上，k2p 2.0现在集成了差异基因表达分析，从而弥合了基因水平调控和蛋白质水平活性之间的差距，提供了转录变化如何促进细胞行为的整体观点。Konnect2prot 2.0可免费访问：https://konnect2prot_v2.thsti.in。

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来源期刊

Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics

CiteScore

9.30

自引率

3.30%

发文量

540

审稿时长

6 weeks

期刊介绍： Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology