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Regulators of Signal Transduction: Families of GTP-Binding Proteins
Published in Robert I. Glazer, Developments in Cancer Chemotherapy, 2019
The prototype of this regulatory protein family is Gs, as both receptors and effector have been identified and purified. The ability to functionally reconstitute these three components in a defined environment has allowed and will continue to add to our understanding of the detailed mechanism of activation of adenylate cyclase. Regulation of adenylate cyclase activity by Gs will serve here as a model for other regulatory GTP-binding proteins. For detailed analysis of the mechanism of action, structure, or function of the G-proteins, the reader is referred to one or more of the recent excellent reviews on these subjects.1-7
Three-Dimensional Structure of p21 and Its Implications
Published in Juan Carlos Lacal, Frank McCormick, The ras Superfamily of GTPases, 2017
GNB proteins have been shown (for some) or are supposed (for the others) to be involved in many cellular processes such as signal transduction, protein transport and secretion, and polypeptide chain elongation (for recent reviews, see References 1-4). They possess several characteristics which classify them as members of this protein family.
Why Cancer?
Published in John Melford, Pocket Guide to Cancer, 2017
The widespread similarity of conserved domains among members of a protein family poses a problem for the pharmaceutical industry. Many faulty proteins contribute to the development of cancer. Suitable targets for cancer drugs are those involved in the transmission of signals between cells and within cells that regulate cell division and supportive metabolic pathways. Unfortunately, a significant number of these signaling proteins belong to a family of enzymes that share conserved regions, called tyrosine kinases. There are over 1000 kinases in humans, which makes it difficult to find a drug that targets a specific one. A drug that acts on a single protein is likely to cause fewer unpredictable side effects than one that acts on a large number of proteins.
The evolving role of JAK inhibitors in the treatment of inflammatory bowel disease
Published in Expert Review of Clinical Immunology, 2023
Nancy Gupta, Sam Papasotiriou, Stephen Hanauer
The JAK protein family has four members: JAK1, JAK2, JAK3, and Tyrosine kinase 2 (Tyk2), which are intracellular tyrosine kinases. JAK inhibitors bind to the kinase domain of JAK proteins and inhibit its activation, thereby preventing downstream STAT phosphorylation and translocation to the nucleus, thus interrupting activation of transcription of multiple cytokine pathways (Figure 1) [4]. JAK proteins act in pairs as homodimers or heterodimers and can create multiple JAK combinations. For example, activation of JAK1 and JAK3 heterodimer via cytokines, IL-2, IL-4, IL-7, IL-9, IL-15, and IL-21 stimulates the adaptive immune response. Activation of JAK1 and JAK2 heterodimer via interferon-gamma (IFN-γ) and IL-6 mediates downstream inflammation and affects lipid metabolism. Activation of JAK2 homodimers stimulates hematopoiesis [4]. Because JAK proteins act in pairs, it is difficult to predict the pathophysiologic effect when one specific JAK protein is inhibited. Each JAK inhibitor has a varying degree of selectivity to the inhibition of different JAK proteins. Table 1 shows the JAK protein specificity of various JAK inhibitors and those under investigation [6]. The exact outcome and the final functional impact ultimately depend upon the downstream cytokines that are predominantly blocked [4]. Tyk2 inhibitors, such as deucravacitinib, are also undergoing clinical trials in ulcerative colitis [4,7].
Computational approaches for the design of modulators targeting protein-protein interactions
Published in Expert Opinion on Drug Discovery, 2023
Ashfaq Ur Rehman, Beenish Khurshid, Yasir Ali, Salman Rasheed, Abdul Wadood, Ho-Leung Ng, Hai-Feng Chen, Zhiqiang Wei, Ray Luo, Jian Zhang
However, this information might not generate exact three-dimensional structures [190]. The majority of computational methods, such as free energy techniques, require the availability of structural data. Due to proteins’ inherent flexibility, approximations are often included in the algorithms when using these methods, but this creates biased systems; therefore, one must be extremely careful when choosing a computational technique for a specific problem [191]. Knowledge-based methods use the current structural data for proteins and ligands, meaning the results can be only as reliable as the data used to create them. Some PPI descriptors are more predictive than others [190]. A model built on one protein family or class of ligands might not accurately describe the properties of other protein families or ligand classes. Similarly, for screening methods, structural information is required, which makes this strategy unsuitable for unknown targets.
Multi-targeted drug design strategies for the treatment of schizophrenia
Published in Expert Opinion on Drug Discovery, 2021
Piotr Stępnicki, Magda Kondej, Oliwia Koszła, Justyna Żuk, Agnieszka A. Kaczor
The design of multi-target drugs in a rational way remains a big challenge when it comes to both selection of targets and discovery of small molecules [47]. Concerning the target selection, there are online tools available [48–50], but it is difficult to select the appropriate set of targets for the illness of interest taking into account multi-functional compounds and therapeutic combinations [47]. A good target selection is based on the detailed knowledge of target-disease associations, pathway-target-drug-disease relationships and adverse events profiling [47,51]. In case of schizophrenia, effort was made to use a novel multilevel statistical method to separate the desired molecular targets and off-targets [52]. Moreover, synergistic or additive effects of modulation of multiple targets should be taken into account as in this case the therapeutic effect can be achieved at the lower dose of a drug [53]. Designing multi-target ligands is easier when targets belong to the same protein family [54] like in case of antipsychotics; however, it also implies that it is much more difficult to avoid the affinity to off-target from the same family.