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Signal transduction and exercise
Published in Adam P. Sharples, James P. Morton, Henning Wackerhage, Molecular Exercise Physiology, 2022
Brendan Egan, Adam P. Sharples
Proteins need to be in contact with each other so that they can modify one another and convey information. Furthermore, many cellular functions rely on multimeric protein complexes, such as AMPK being a heterotrimeric complex as mentioned above. Another example of a multimeric protein complex is mTORC, which consists of several proteins and is a key regulator of ribosomal translation implicated in nutrient-, growth factor- and exercise-induced MPS. In fact, mTORC can assimilate as either mTORC1 or mTORC2 depending on conformation and composition of the various proteins that make up each complex, with each complex then serving somewhat different roles in cellular metabolism.
An Analysis of Protein Interaction and Its Methods, Metabolite Pathway and Drug Discovery
Published in Ayodeji Olalekan Salau, Shruti Jain, Meenakshi Sood, Computational Intelligence and Data Sciences, 2022
Figure 13.1 shows that the structure of the interacted protein complex is classified into two types. Protein function lifetime is permanent is known as stable and another one is transient, that is interacting partners with a short lifetime and the flow of the function belongs to the stable one [9]. PPIN contains some duplicate pre-processes such as gene duplication, mutation and duplication model to describe the DNA sequence evolution [10]. Inside the biological network pathways, protein interactions are experimentally determined and evaluated. To analyse the metabolic pathways and signalling pathways helps to know the special attention to reconstruct the cellular processes. This direction leads to understanding the transcription factor and moving information between them [11–13].
ChIP-seq analysis
Published in Altuna Akalin, Computational Genomics with R, 2020
Clustering is an ordering procedure which groups samples by similarity; the more similar samples are grouped closer to one another. The details of clustering methodologies are described in Chapter 4. Clustering of ChIP signal profiles is used for two purposes: The first one is to ascertain whether there is concordance between biological replicates; biological replicates should show greater similarity than ChIP of different proteins. The second function is to see whether our experiments conform to known prior knowledge. For example, we would expect to see greater similarity between proteins which belong to the same protein complex.
Proximity labeling and other novel mass spectrometric approaches for spatiotemporal protein dynamics
Published in Expert Review of Proteomics, 2021
Lindsay Pino, Birgit Schilling
Innovative methodologies at the intersection of molecular biology, analytical chemistry, and bioinformatics are enabling four-dimensional protein network analysis encompassing not only protein identity and quantity but also spatial arrangement and temporal dynamics. A particularly exciting example of this is proximity labeling, which although requires effort to generate constructs in living animals, provides unique opportunities to detect and quantify protein interactions in proximity. The in-depth study of protein complexes as they vary across phenotypes and exhibit different biological function offer the opportunity to capture network analyses, even in mammalian tissues in vivo. The resulting protein–protein interaction networks not only generate new hypotheses but also uncover mechanisms of action and phenotypes. Temporal monitoring of biological conditions provides relevant information that can be investigated using protein turnover and/or PTM signaling. These spatiotemporal tools empower systems biology, with the goal of understanding biomolecules not only as their expression levels change but also within context-dependent protein networks that are dynamic across space and time. These properties are not static, and their study can provide insights into temporal protein changes within disease, in response to environmental stressors, or therapeutic interventions.
Mining cancer biology through bioinformatic analysis of proteomic data
Published in Expert Review of Proteomics, 2019
Marcello Manfredi, Jessica Brandi, Claudia Di Carlo, Virginia Vita Vanella, Elettra Barberis, Emilio Marengo, Mauro Patrone, Daniela Cecconi
After performing protein annotation and functional enrichment, the bioinformatic analysis of proteomic data is usually followed by the examination of PPIs. Indeed, the majority of proteins do not act as independent entities because many cellular processes, such as DNA replication, RNA transcription, protein translation, post-translational modification, targeted degradation, signal transduction, cell cycle control, and cell mobility involve the formation of protein complexes. In particular, in cancer proteomics studies, the analysis of PPIsaims to detect the components of protein complexes by creating up a map of interactions that may play a key role in, for example, carcinogenesis and/or the mechanism of action of anticancer drugs. Protein interactions are often displayed as large interaction networks where nodes indicate the molecular entities (protein, transcripts, or genes), and edges represent either the different types of relationships (such as co-expression, co-localization, and physical interactions) or the different types of processes or hierarchical connections between the nodes. Different curated databases contain information on protein interactions that are associated with biological processes. The protein interactions that are annotated in public databases are based either on experimental observations or on predictions that are obtained by using a variety of algorithms.
A patent review of the ubiquitin ligase system: 2015–2018
Published in Expert Opinion on Therapeutic Patents, 2018
Xin Li, Ekinci Elmira, Sagar Rohondia, Jicang Wang, Jinbao Liu, Q. Ping Dou
One of the most effective strategies for development of specific small molecule inhibitors is structure-based drug design. The main obstacle for this approach is availability of structural data as crystallization and assays of large multi-subunit protein complexes may be rather difficult. Additionally, large size of the full complexes and their multi-subunit composition pose a challenge for NMR spectroscopic studies. Some of these interfaces are already being targeted for potential therapeutic intervention. Crystal structures of subunits, components, and full-size complexes, alone or with bound small molecules and substrate peptides, should provide increasing opportunities to the rational structure-based design of chemical probes and potential small molecule therapeutics [145]. The successful examples include newly characterized PROTACs [146], CMAs [135], and bifunctional molecule dBET1 [147].