BACKGROUND Protein-protein interactions (PPIs) are challenging but attractive targets for small chemical drugs. Whole PPIs, called the 'interactome', have been emerged in several organisms, including human, based on the recent development of high-throughput screening (HTS) technologies. Individual PPIs have been targeted by small drug-like chemicals (SDCs), however, interactome data have not be...

Protein-protein interactions (PPIs) play important roles in most fundamental cellular processes including cell cycle, metabolism, and cell proliferation. Therefore, the development of effective statistical approaches to predicting protein interactions based on recently available large-scale experimental data is very important. Because protein domains are the functional units of proteins and PPI...

Predicting protein-protein interactions (PPIs) is a challenging task and essential to construct the protein interaction networks, which is important for facilitating our understanding of the mechanisms of biological systems. Although a number of high-throughput technologies have been proposed to predict PPIs, there are unavoidable shortcomings, including high cost, time intensity, and inherentl...

Core elements of cell regulation are made up of protein-protein interaction (PPI) networks. However, many parts of the cell regulatory systems include unknown PPIs. To approach this problem, we have developed a computational method of high-throughput PPI network prediction based on all-to-all rigid-body docking of protein tertiary structures. The prediction system accepts a set of data comprisi...

Protein-protein interactions (PPIs) can be classified as permanent or transient based on their stability lifetime. Understanding the precise details of such protein will pave way for discovery inhibitors and understanding nature function PPIs. In present work, 43 relevant physicochemical, geometrical structural features were calculated a curated dataset from literature, comprising 402 protein-p...

The study of protein-protein interactions (PPIs) can be very important for the understanding of biological cellular functions. However, detecting PPIs in the laboratories are both time-consuming and expensive. For this reason, there has been much recent effort to develop techniques for computational prediction of PPIs as this can complement laboratory procedures and provide an inexpensive way o...

Decades of research into cell biology, molecular biology, biochemistry, structural biology, and biophysics have produced a remarkable compendium of knowledge on the function and molecular properties of individual proteins. This knowledge is well recorded and manually curated into major protein databases like UniProt [1,2]. However, proteins rarely act alone. Many times they team up into ‘‘molec...

The Wnt signaling pathway plays a critical role in cell proliferation and differentiation, thus it is often associated with diseases such as cancers. Unfortunately, although attractive, developing anti-cancer strategy targeting Wnt signaling has been challenging given that the most attractive targets are involved in protein-protein interactions (PPIs). Here, we develop a stapled peptide inhibit...

Pattern discovery in protein interaction networks can reveal crucial biological knowledge on the inner workings of cellular machinery. Although far from complete, extracting meaningful patterns from proteomic networks is a nontrivial task due to their size-complexity. This paper proposes a computational framework to efficiently discover topologically-similar patterns from large proteomic networ...

Most of the information about protein-protein interactions (PPIs) can only be found in unstructured natural language texts (Ono et al., 2001). PubMed, a publicly accessible database for biomedical literature, nowadays consists of over 20 million citations and is still growing fast. Thus, methods that extract PPIs automatically are of great importance. The extraction of PPIs requires the recogni...