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Heat shock protein 90 (Hsp90) is an ATP-dependent molecular chaperone which is essential in eukaryotes. It is required for the activation and stabilization of a wide variety of client proteins and many of them are involved in important cellular pathways. Since Hsp90 affects numerous physiological processes such as signal transduction, intracellular transport, and protein degradation, it became an interesting target for cancer therapy. Structurally, Hsp90 is a flexible dimeric protein composed of three different domains which adopt structurally distinct conformations. ATP binding triggers directionality in these conformational changes and leads to a more compact state. To achieve its function, Hsp90 works together with a large group of cofactors, termed co-chaperones. Co-chaperones form defined binary or ternary complexes with Hsp90, which facilitate the maturation of client proteins. In addition, posttranslational modifications of Hsp90, such as phosphorylation and acetylation, provide another level of regulation. They influence the conformational cycle, co-chaperone interaction, and inter-domain communications. In this review, we discuss the recent progress made in understanding the Hsp90 machinery.

Optogenetic and chemogenetic control of proteins has revealed otherwise inaccessible facets of signaling dynamics. Here, we use light- or ligand-sensitive domains to modulate the structural disorder of diverse proteins, thereby generating robust allosteric switches. Sensory domains were inserted into nonconserved, surface-exposed loops that were tight and identified computationally as allosterically coupled to active sites. Allosteric switches introduced into motility signaling proteins (kinases, guanosine triphosphatases, and guanine exchange factors) controlled conversion between conformations closely resembling natural active and inactive states, as well as modulated the morphodynamics of living cells. Our results illustrate a broadly applicable approach to design physiological protein switches.

SARS-CoV-2 is the causative agent behind the COVID-19 pandemic, responsible for over 170 million infections, and over 3.7 million deaths worldwide. Efforts to test, treat and vaccinate against this pathogen all benefit from an improved understanding of the basic biology of SARS-CoV-2. Both viral and cellular proteases play a crucial role in SARS-CoV-2 replication. Here, we study proteolytic cleavage of viral and cellular proteins in two cell line models of SARS-CoV-2 replication using mass spectrometry to identify protein neo-N-termini generated through protease activity. We identify previously unknown cleavage sites in multiple viral proteins, including major antigens S and N: the main targets for vaccine and antibody testing efforts. We discover significant increases in cellular cleavage events consistent with cleavage by SARS-CoV-2 main protease, and identify 14 potential high-confidence substrates of the main and papain-like proteases. We show that siRNA depletion of these cellular proteins inhibits SARS-CoV-2 replication, and that drugs targeting two of these proteins: the tyrosine kinase SRC and Ser/Thr kinase MYLK, show a dose-dependent reduction in SARS-CoV-2 titres. Overall, our study provides a powerful resource to understand proteolysis in the context of viral infection, and to inform the development of targeted strategies to inhibit SARS-CoV-2 and treat COVID-19. During SARS-CoV-2 replication, viral and cellular proteases play crucial roles and have been shown to be promising anti-viral targets. Here, Meyer et al. apply mass spectrometry to characterize the proteolytic cleavage profile of viral and cellular proteins in vitro.

Tyrosine-protein kinase Src plays a key role in cell proliferation and growth under favorable conditions, but its overexpression and genetic mutations can lead to the progression of various inflammatory diseases. Due to the specificity and selectivity problems of previously discovered inhibitors like dasatinib and bosutinib, we employed an integrated machine learning and structure-based drug repurposing strategy to find novel, targeted, and non-toxic Src kinase inhibitors. Different machine learning models including random forest (RF), k-nearest neighbors (K-NN), decision tree, and support vector machine (SVM), were trained using already available bioactivity data of Src kinase targeting compounds. The performance evaluation of these models demonstrated SVM as the best model, which was further utilized to shortlist 51 highly potent compounds by screening an FDA-approved library of 1040 drugs. Molecular docking and molecular dynamic simulation were subsequently employed to evaluate the binding affinity and stability of the proposed compounds. Orlistat, acarbose and afatinib were identified as the potent leads, demonstrating stable conformations and stronger interactions, validated by root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (RoG), and hydrogen bond analyses. Molecular Mechanics/Generalized Born Surface Area (MMGBSA) analysis validated their binding affinities by providing comparably lower binding free energies for orlistat (− 33.4743 ± 3.8908), acarbose (− 19.5455 ± 5.4702), and afatinib (− 36.4944 ± 5.4929) than the control, dasatinib (− 13.7785 ± 5.8058). Finally, toxicity analysis revealed orlistat and acarbose as the possible safer therapeutics by eliminating afatinib as it showed significant toxicity concerns. Our investigation supports the advance computational methods utilization in the field of drug discovery and suggest further experimental validation of proposed inhibitors of Src kinase for their safer use against inflammatory diseases. The ultimate aim of this study is to advance the development of effective treatments for inflammatory diseases, linked with Src overexpression.

Breast cancer (BC) has been ranked the most common malignant tumor throughout the world and is also a leading cause of cancer-related deaths among women. SRC family kinases (SFKs) belong to the non-receptor tyrosine kinase (nRTK) family, which has eleven members sharing similar structure and function. Among them, SRC is the first identified proto-oncogene in mammalian cells. Oncogenic overexpression or activation of SRC has been revealed to play essential roles in multiple events of BC progression, including tumor initiation, growth, metastasis, drug resistance and stemness regulations. In this review, we will first give an overview of SRC kinase and SRC-relevant functions in various subtypes of BC and then systematically summarize SRC-mediated signaling transductions, with particular emphasis on SRC-mediated substrate phosphorylation in BC. Furthermore, we will discuss the progress of SRC-based targeted therapies in BC and the potential future direction.

Lyn is a multifunctional Src-family kinase (SFK) that regulates immune signaling and has been implicated in diverse types of cancer. Unlike other SFKs, its full-length structure and regulatory dynamics remain poorly characterized. In this study, we present the first long-timescale molecular dynamics analysis of full-length Lyn, including the SH3, SH2, and SH1 domains, across wildtype, ligand-bound, and cancer-associated mutant states. Using principal component analysis, dynamic cross-correlation matrices, and network-based methods, we show that ATP binding stabilizes the kinase core and promotes interdomain coordination, while the ATP-competitive inhibitor dasatinib and specific mutations (e.g., E290K, I364N) induce conformational decoupling and weaken long-range communication. We identify integration modules and develop an interface-weighted scoring scheme to rank dynamically central residues. This analysis reveals 44 allosteric hubs spanning SH3, SH2, SH1, and interdomain regions. Finally, a random forest classifier trained on 16 MD-derived features highlights key interdomain descriptors, distinguishing functional states with an AUC of 0.98. Our results offer a dynamic and network-level framework for understanding Lyn regulation and identify potential regulatory hotspots for structure-based drug design. More broadly, our approach demonstrates the value of integrating full-length MD simulations with network and machine learning techniques to probe allosteric control in multidomain kinases.

The catalytic domain of protein tyrosine kinases can interconvert between active and inactive conformations in response to regulatory inputs. We recently demonstrated that Src kinase features an allosteric network that couples substrate-binding sites. However, the extent of conformational and dynamic changes that are propagated throughout the kinase domain remains poorly understood. Here, we monitor by NMR the effect of conformationally selective inhibitors on kinase backbone dynamics. We find that inhibitor binding and activation loop autophosphorylation induces dynamic changes across the entire kinase. We identify a highly conserved amino acid, Gly449, that is necessary for Src activation. Finally, we show for the first time how the SH3–SH2 domains perturb the dynamics of the kinase domain in the context of the full length protein. We provide experimental support for long-range communication in Src kinase that leads to the relative stabilization of active or inactive conformations and modulation of substrate affinity. Src is a prototypical signaling non-receptor protein tyrosine kinase that interconverts between distinct conformations. Here the authors use variants of the kinase-inhibitor dasatinib to define three specific conformational states of the Src kinase and shed insight on the effect of conformation-specific inhibitors on Src dynamics.

Src is the representative member of the Src-family kinases (SFKs), a group of tyrosine kinases involved in several cellular processes. Its main function has been for long confined to the plasma membrane/cytoplasm compartment, being a myristoylated protein anchored to the cell membrane and functioning downstream to receptors, most of them lacking intrinsic kinase activity. In the last decades, new roles for some SFKs have been described in the nuclear compartment, suggesting that these proteins can also be involved in directly regulating gene transcription or nucleoskeleton architecture. In this review, we focused on those nuclear functions specifically attributable to Src, by considering its function as both tyrosine kinase and adapting molecule. In particular, we addressed the Src involvement in physiological as well as in pathological conditions, especially in tumors.

Over a century of scientific inquiry since the discovery of v-SRC but still no final judgement on SRC function. However, a significant body of work has defined Src family kinases as key players in tumor progression, invasion and metastasis in human cancer. With the ever-growing evidence supporting the role of epithelial-mesenchymal transition (EMT) in invasion and metastasis, so does our understanding of the role SFKs play in mediating these processes. Here we describe some key mechanisms through which Src family kinases play critical role in epithelial homeostasis and how their function is essential for the propagation of invasive signals. 2ZV4EXC_b8wwifo_vGg7uf Video abstract

Src family kinases are prototypical modular signaling proteins. Their conserved domain organization includes a myristoylated N-terminal segment followed by SH3, SH2, and tyrosine kinase domains, and a short C-terminal tail. Structural dissection of Src kinases has elucidated the canonical mechanisms of phosphotyrosine recognition by the SH2 domain and proline-motif recognition by the SH3 domain. Crystallographic analysis of nearly intact Src kinases in the autoinhibited state has shown that these protein interaction motifs turn inward and lock the kinase in an inactive conformation via intramolecular interactions. The autoinhibited Src kinase structures reveal a mode of domain assembly used by other tyrosine kinases outside the Src family, including Abl and likely Tec family kinases. Furthermore, they illustrate the underlying regulatory principles that have proven to be general among diverse modular signaling proteins. Although there is considerable structural information available for the autoinhibited conformation of Src kinases, how they may assemble into active signaling complexes with substrates and regulators remains largely unexplored.