Dynamics-Driven Allostery in Protein Kinases

Advances in the design, discovery, and optimization of aurora kinase inhibitors as anticancer agents

INTRODUCTION

Aurora kinases (AKs) play key roles during carcinogenesis and show a close relationship with many cellular effects including mitotic entry, spindle assembly and chromosomal alignment biorientation. Indeed, elevated levels of AKs have been reported in several different tumor types, leading research scientists to investigate ways that we can target AKs for the purpose of developing new anticancer therapeutics.

AREA COVERED

This review examines the design, discovery, and development of Aurora kinase inhibitors (AKIs) as anticancer agents and delineates their roles in cancer progression or development. Various databases like PubMed, Scopus, Google scholar, SciFinder were used to search the relevant information. This article provides a comprehensive overview of recent advances in the medicinal chemistry of AKIs including the candidates under clinical development and list of patents filed. In addition, their mechanistic findings, SARs, and in silico studies have also been discussed to offer prospects in this field.

EXPERT OPINION

The integration of artificial intelligence and computational approaches is poised to accelerate the development of AKIs as anticancer agents. However, the associated challenges currently hindering its impact in drug development must be overcome before drugs can successfully translate from early drug development into clinical practice.

Distinct Allosteric Networks in CDK4 and CDK6 in the Cell Cycle and in Drug Resistance

Cyclin-dependent kinases 4 and 6 (CDK4 and CDK6) are key regulators of the G1-S phase transition in the cell cycle. In cancer cells, CDK6 overexpression often outcompetes CDK4 in driving cell cycle progression, contributing to resistance against CDK4/6 inhibitors (CDK4/6i). This suggests distinct functional and conformational differences between these two kinases, despite their striking structural and sequence similarities. Understanding the mechanisms that differentiate CDK4 and CDK6 is crucial, as resistance to CDK4/6i-frequently linked to CDK6 overexpression-remains a significant therapeutic challenge. Notably, CDK6 is often upregulated in CDK4/6i-resistant cancers and rapidly proliferating hematopoietic stem cells, underscoring its unique regulatory roles. We hypothesize that their distinct conformational dynamics explain their differences in phosphorylation of retinoblastoma protein, Rb, inhibitor efficacy, and cell cycle control. This leads us to question how their dissimilar conformational dynamics encode their distinct actions. To elucidate their differential activities, molecular mechanisms, and inhibitor binding, we combine biochemical assays and molecular dynamics (MD) simulations. We discover that CDK4 and CDK6 have distinct allosteric networks connecting the β3-αC loop and the G-loop. CDK6 exhibits stronger coupling and shorter path lengths between these regions, resulting in higher kinase activity upon cyclin binding and impacting inhibitor specificity. We also discover an unrecognized role of the unstructured CDK6 C-terminus, which allosterically connects and stabilizes the R-spine, facilitating slightly higher activity. Our findings bridge the gap between the structural similarity and functional divergence of CDK4 and CDK6, advancing the understanding of kinase regulation in cancer biology.

Prognostic and immunological implications of protein kinases in gastric cancer: a focus on hub gene ABL2 and its impact on the polarization of M2 macrophages

BACKGROUND

Protein kinases are essential cellular signal modulators involved in tumorigenesis, metastasis, immune response, and drug resistance. However, the comprehensive features and clinical significance of protein kinases in gastric cancer (GC) remain inconclusive.

METHODS

We analyzed the transcriptional profiles of protein kinases in GC patients from the GEO and TCGA databases. Based on differentially expressed kinase genes (DE-KGs), a novel cluster was identified to assess its association with patient survival and the tumor microenvironment (TME) in GC. Subsequently, an optimal DE-KGs-based model (DE-KGsM) was determined using 101 machine-learning algorithm combinations. This model was evaluated using multi-omics data to investigate its associations with patient prognosis, clinical features, tumor microenvironment, tumor-infiltrating immune cells (TIICs), and immunotherapy response. Furthermore, scRNA-seq analysis and TIMER algorithm were applied to determine the correlation between the hub gene (ABL2) in the DE-KGsM and Macrophages. Finally, in vitro experiments were performed to explore the immune-related mechanisms of ABL2 in GC.

RESULTS

We identified two molecular subtypes of GC patients based on 64 DE-KGs expression. Significant differences were observed in overall survival and TIIC characteristics between Cluster 1 and Cluster 2. Among these 64 DE-KGs, we identified an optimal DE-KGsM that could be a prognostic indicator in GC. TIICs and TIDE analyses exhibited that GC patients in the high-DE-KGsM score group had a higher proportion of M2 macrophages and lower response rates to ICI treatment. scRNA-seq analysis indicated that ABL2 might play an indispensable role in tumor immunity. Furthermore, in vitro experiments demonstrated that ABL2 accelerated the proliferation, migration, and invasion of GC cells, as well as the polarization of M2 macrophages.

CONCLUSIONS

The DE-KGsM could be a powerful predictor of GC patients' survival and might facilitate the development of personalized therapy. Furthermore, as a hub gene in the DE-KGsM, ABL2 could be an immunological biomarker that modulates the polarization of M2 macrophages, thereby promoting GC progression.

CLINICAL TRIAL NUMBER

Not applicable.

A "Knob Switch" Model for the Phosphoregulatory Mechanism of KCC3 at the Carboxy-Terminal Domain

Phosphorylation is a reversible post-translational modification that can modulate protein function. For example, phosphorylation modifications of solute carrier family 12 (SLC12) proteins function as molecular switches that precisely regulate cation-chloride ion transport. Elucidating the phosphoregulatory mechanism of SLC12 at the carboxy-terminal domain (CTD) through structural determination approaches remains challenging due to the domain's disordered and flexible nature. In this study, molecular dynamics (MD) simulations and enhanced sampling techniques were employed to investigate the CTD phosphoregulatory mechanism of SLC12A6 (also known as KCC3). Atomistic MD and metadynamics simulations revealed that the dephosphorylation of residues T940 and T997 stabilizes CTD to a favorable state that "switches on" the solvent accessibility of the inward-facing pocket. Meanwhile, phosphorylation induces distinct orientations of the CTD, transitioning the dimer into another favorable state that "switches off" the solvent accessibility. The alteration of solvent accessibility in the inward-facing pocket influences the water and ion dynamics. Based on these findings, we propose a "knob switch" model to illustrate how CTD phosphorylation regulates ion transport in KCC3.

Distinct allosteric networks in CDK4 and CDK6 in the cell cycle and in drug resistance

Cyclin-dependent kinases 4 and 6 (CDK4 and CDK6) are key regulators of the G1-S phase transition in the cell cycle. In cancer cells, CDK6 overexpression often outcompetes CDK4 in driving cell cycle progression, contributing to resistance against CDK4/6 inhibitors (CDK4/6i). This suggests distinct functional and conformational differences between these two kinases, despite their striking structural and sequence similarities. Understanding the mechanisms that differentiate CDK4 and CDK6 is crucial, as resistance to CDK4/6i-frequently linked to CDK6 overexpression-remains a significant therapeutic challenge. Notably, CDK6 is often upregulated in CDK4/6i-resistant cancers and rapidly proliferating hematopoietic stem cells, underscoring its unique regulatory roles. We hypothesize that their distinct conformational dynamics explain their differences in phosphorylation of retinoblastoma protein, Rb, inhibitor efficacy, and cell cycle control. This leads us to question how their dissimilar conformational dynamics encode their distinct actions. To elucidate their differential activities, molecular mechanisms, and inhibitor binding, we combine biochemical assays and molecular dynamics (MD) simulations. We discover that CDK4 and CDK6 have distinct allosteric networks connecting the β3-αC loop and the G-loop. CDK6 exhibits stronger coupling and shorter path lengths between these regions, resulting in higher kinase activity upon cyclin binding and impacting inhibitor specificity. We also discover an unrecognized role of the unstructured CDK6 C-terminus, which allosterically connects and stabilizes the R-spine, facilitating slightly higher activity. Our findings bridge the gap between the structural similarity and functional divergence of CDK4 and CDK6, advancing the understanding of kinase regulation in cancer biology.

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of the influenza A virus

Viral proteins frequently mutate to evade host innate immune responses, yet the impact of these mutations on the molecular energy landscape remains unclear. Epistasis, the intramolecular communications between mutations, often renders the combined mutational effects unpredictable. Nonstructural protein 1 (NS1) is a major virulence factor of the influenza A virus (IAV) that activates host PI3K by binding to its p85β subunit. Here, we present a deep analysis of the impact of evolutionary mutations in NS1 that emerged between the 1918 pandemic IAV strain and its descendant PR8 strain. Our analysis reveals how the mutations rewired interresidue communications, which underlie long-range allosteric and epistatic networks in NS1. Our findings show that PR8 NS1 binds to p85β with approximately 10-fold greater affinity than 1918 NS1 due to allosteric mutational effects, which are further tuned by epistasis. NMR chemical shift perturbation and methyl-axis order parameter analyses revealed that the mutations induced long-range structural and dynamic changes in PR8 NS1, relative to 1918 NS1, enhancing its affinity to p85β. Complementary molecular dynamics simulations and graph theory-based network analysis for conformational dynamics on the submicrosecond timescales uncover how these mutations rewire the dynamic network, which underlies the allosteric epistasis. Significantly, we find that conformational dynamics of residues with high betweenness centrality play a crucial role in communications between network communities and are highly conserved across influenza A virus evolution. These findings advance our mechanistic understanding of the allosteric and epistatic communications between distant residues and provide insight into their role in the molecular evolution of NS1.

Allostery

Allostery describes the ability of biological macromolecules to transmit signals spatially through the molecule from an allosteric site – a site that is distinct from orthosteric binding sites of primary, endogenous ligands – to the functional or active site. This review starts with a historical overview and a description of the classical example of allostery – hemoglobin – and other well-known examples (aspartate transcarbamoylase, Lac repressor, kinases, G-protein-coupled receptors, adenosine triphosphate synthase, and chaperonin). We then discuss fringe examples of allostery, including intrinsically disordered proteins and inter-enzyme allostery, and the influence of dynamics, entropy, and conformational ensembles and landscapes on allosteric mechanisms, to capture the essence of the field. Thereafter, we give an overview over central methods for investigating molecular mechanisms, covering experimental techniques as well as simulations and artificial intelligence (AI)-based methods. We conclude with a review of allostery-based drug discovery, with its challenges and opportunities: with the recent advent of AI-based methods, allosteric compounds are set to revolutionize drug discovery and medical treatments.

A comprehensive review of targeting RAF kinase in cancer

RAF kinases, particularly the BRAF isoform, play a crucial role in the MAPK/ERK signaling pathway, regulating key cellular processes such as proliferation, differentiation, and survival. Dysregulation of this pathway often caused by mutations in the BRAF gene or alterations in upstream regulators like Ras and receptor tyrosine kinases contributes significantly to cancer development. Mutations, such as BRAF-V600E, are present in a variety of malignancies, with the highest prevalence in melanoma. Targeted therapies against RAF kinases have achieved substantial success, especially in BRAF-V600E-mutant melanomas, where inhibitors like vemurafenib and dabrafenib have demonstrated remarkable efficacy, leading to improved patient outcomes. These inhibitors have also shown clinical benefits in cancers such as thyroid and colorectal carcinoma, although to a lesser extent. Despite these successes, therapeutic resistance remains a major hurdle. Resistance mechanisms, including RAF dimerization, feedback reactivation of the MAPK pathway, and paradoxical activation of ERK signaling, often lead to diminished efficacy over time, resulting in disease progression or even secondary malignancies. In response, current research is focusing on novel therapeutic strategies, including combination therapies that target multiple components of the pathway simultaneously, such as MEK inhibitors used in tandem with RAF inhibitors. Additionally, next-generation RAF inhibitors are being developed to address resistance and enhance therapeutic specificity. This review discusses the clinical advancements in RAF-targeted therapies, with a focus on ongoing efforts to overcome therapeutic resistance and enhance outcomes for cancer patients. It also underscores the persistent challenges in effectively targeting RAF kinase in oncology.

Regulation and signaling of the LIM domain kinases

The LIM domain kinases (LIMKs) are important actin cytoskeleton regulators. These proteins, LIMK1 and LIMK2, are nodes downstream of Rho GTPases and are the key enzymes that phosphorylate cofilin/actin depolymerization factors to regulate filament severing. They therefore perform an essential role in cascades that control actin depolymerization. Signaling of the LIMKs is carefully regulated by numerous inter- and intra-molecular mechanisms. In this review, we discuss recent findings that improve the understanding of LIM domain kinase regulation mechanisms. We also provide an up-to-date review of the role of the LIM domain kinases, their architectural features, how activity is impacted by other proteins, and the implications of these findings for human health and disease.

Acquired resistance to tyrosine kinase targeted therapy: mechanism and tackling strategies

Over the past two decades, tyrosine kinase inhibitors (TKIs) have rapidly emerged as pivotal targeted agents, offering promising therapeutic prospects for patients. However, as the cornerstone of targeted therapies, an increasing number of TKIs have been found to develop acquired resistance during treatment, making the challenge of overcoming this resistance a primary focus of current research. This review comprehensively examines the evolution of TKIs from multiple perspectives, with particular emphasis on the mechanisms underlying acquired resistance, innovative drug design strategies, inherent challenges, and future directions.

Structures of KEOPS bound to tRNA reveal functional roles of the kinase Bud32

The enzyme complex KEOPS (Kinase, Endopeptidase and Other Proteins of Small size) installs the universally conserved and essential N6-threonylcarbamoyl adenosine modification (t6A) on ANN-decoding tRNAs in eukaryotes and in archaea. KEOPS consists of Cgi121, Kae1, Pcc1, Gon7 and the atypical kinase/ATPase Bud32. Except Gon7, all KEOPS subunits are needed for tRNA modification, and in humans, mutations in all five genes underlie the lethal genetic disease Galloway Mowat Syndrome (GAMOS). Kae1 catalyzes the modification of tRNA, but the specific contributions of Bud32 and the other subunits are less clear. Here we solved cryogenic electron microscopy structures of KEOPS with and without a tRNA substrate. We uncover distinct flexibility of KEOPS-bound tRNA revealing a conformational change that may enable its modification by Kae1. We further identified a contact between a flipped-out base of the tRNA and an arginine residue in C-terminal tail of Bud32 that correlates with the conformational change in the tRNA. We also uncover contact surfaces within the KEOPS-tRNA holo-enzyme substrate complex that are required for Bud32 ATPase regulation and t6A modification activity. Our findings uncover inner workings of KEOPS including a basis for substrate specificity and why Kae1 depends on all other subunits.

Role of the αC-β4 loop in protein kinase structure and dynamics

Although the αC-β4 loop is a stable feature of all protein kinases, the importance of this motif as a conserved element of secondary structure, as well as its links to the hydrophobic architecture of the kinase core, has been underappreciated. We first review the motif and then describe how it is linked to the hydrophobic spine architecture of the kinase core, which we first discovered using a computational tool, local spatial Pattern (LSP) alignment. Based on NMR predictions that a mutation in this motif abolishes the synergistic high-affinity binding of ATP and a pseudo substrate inhibitor, we used LSP to interrogate the F100A mutant. This comparison highlights the importance of the αC-β4 loop and key residues at the interface between the N- and C-lobes. In addition, we delved more deeply into the structure of the apo C-subunit, which lacks ATP. While apo C-subunit showed no significant changes in backbone dynamics of the αC-β4 loop, we found significant differences in the side chain dynamics of K105. The LSP analysis suggests disruption of communication between the N- and C-lobes in the F100A mutant, which would be consistent with the structural changes predicted by the NMR spectroscopy.

AlphaFold-SFA: Accelerated sampling of cryptic pocket opening, protein-ligand binding and allostery by AlphaFold, slow feature analysis and metadynamics

Sampling rare events in proteins is crucial for comprehending complex phenomena like cryptic pocket opening, where transient structural changes expose new binding sites. Understanding these rare events also sheds light on protein-ligand binding and allosteric communications, where distant site interactions influence protein function. Traditional unbiased molecular dynamics simulations often fail to sample such rare events, as the free energy barrier between metastable states is large relative to the thermal energy. This renders these events inaccessible on the timescales typically simulated by unbiased molecular dynamics, limiting our understanding of these critical processes. In this paper, we proposed a novel unsupervised learning approach termed as slow feature analysis (SFA) which aims to extract slowly varying features from high-dimensional temporal data. SFA trained on small unbiased molecular dynamics simulations launched from AlphaFold generated conformational ensembles manages to capture rare events governing cryptic pocket opening, protein-ligand binding, and allosteric communications in a kinase. Metadynamics simulations using SFA as collective variables manage to sample 'deep' cryptic pocket opening within a few hundreds of nanoseconds which was beyond the reach of microsecond long unbiased molecular dynamics simulations. SFA augmented metadynamics also managed to capture conformational plasticity of protein upon ligand binding/unbinding and provided novel insights into allosteric communication in receptor-interacting protein kinase 2 (RIPK2) which dictates protein-protein interaction. Taken together, our results show how SFA acts as a dimensionality reduction tool which bridges the gap between AlphaFold, molecular dynamics simulation and metadynamics in context of capturing rare events in biomolecules, extending the scope of structure-based drug discovery in the era of AlphaFold.

Explaining Conformational Diversity in Protein Families through Molecular Motions

Proteins play a central role in biological processes, and understanding their conformational variability is crucial for unraveling their functional mechanisms. Recent advancements in high-throughput technologies have enhanced our knowledge of protein structures, yet predicting their multiple conformational states and motions remains challenging. This study introduces Dimensionality Analysis for protein Conformational Exploration (DANCE) for a systematic and comprehensive description of protein families conformational variability. DANCE accommodates both experimental and predicted structures. It is suitable for analysing anything from single proteins to superfamilies. Employing it, we clustered all experimentally resolved protein structures available in the Protein Data Bank into conformational collections and characterized them as sets of linear motions. The resource facilitates access and exploitation of the multiple states adopted by a protein and its homologs. Beyond descriptive analysis, we assessed classical dimensionality reduction techniques for sampling unseen states on a representative benchmark. This work improves our understanding of how proteins deform to perform their functions and opens ways to a standardised evaluation of methods designed to sample and generate protein conformations.

Adaptive Workflows of Machine Learning Illuminate the Sequential Operation Mechanism of the TAK1's Allosteric Network

Allostery is a fundamental mechanism driving biomolecular processes that holds significant therapeutic concern. Our study rigorously investigates how two distinct machine-learning algorithms uniquely classify two already close-to-active DFG-in states of TAK1, differing just by the presence or absence of its allosteric activator TAB1, from an ensemble mixture of conformations (obtained from 2.4 μs molecular dynamics (MD) simulations). The novelty, however, lies in understanding the deeper algorithmic potentials to systematically derive a diverse set of differential residue connectivity features that reconstruct the essential mechanistic architecture for TAK1-TAB1 allostery in such a close-to-active biochemical scenario. While the recursive, random forest-based workflow displays the potential of conducting discretized, hierarchical derivation of allosteric features, a multilayer perceptron-based approach gains considerable efficacy in revealing fluid connected patterns of features when hybridized with mutual information scoring. Interestingly, both pipelines benchmark similar directions of functional conformational changes for TAK1's activation. The findings significantly advance the depth of mechanistic understanding by highlighting crucial activation signatures along a directed C-lobe → activation loop → ATP pocket channel of information flow, including (1) the αF-αE biterminal alignments and (2) the "catalytic" drift of the activation loop toward kinase active site. Besides, some novel allosteric hotspots (K253, Y206, N189, etc.) are further recognized as TAB1 sensors, transducers, and responders, including a benchmark E70 mutation site, precisely mapping the important structural segments for sequential allosteric execution. Hence, our work demonstrates how to navigate through greater structural depths and dimensions of dynamic allosteric machineries just by leveraging standard ML methods in suitable streamlined workflows adaptive to the specific system and objectives.

CDK2 and CDK4: Cell Cycle Functions Evolve Distinct, Catalysis-Competent Conformations, Offering Drug Targets

Cyclin-dependent kinases (CDKs), particularly CDK4 and CDK2, are crucial for cell cycle progression from the Gap 1 (G1) to the Synthesis (S) phase by phosphorylating targets such as the Retinoblastoma Protein (Rb). CDK4, paired with cyclin-D, operates in the long G1 phase, while CDK2 with cyclin-E, manages the brief G1-to-S transition, enabling DNA replication. Aberrant CDK signaling leads to uncontrolled cell proliferation, which is a hallmark of cancer. Exactly how they accomplish their catalytic phosphorylation actions with distinct efficiencies poses the fundamental, albeit overlooked question. Here we combined available experimental data and modeling of the active complexes to establish their conformational functional landscapes to explain how the two cyclin/CDK complexes differentially populate their catalytically competent states for cell cycle progression. Our premise is that CDK catalytic efficiencies could be more important for cell cycle progression than the cyclin-CDK biochemical binding specificity and that efficiency is likely the prime determinant of cell cycle progression. We observe that CDK4 is more dynamic than CDK2 in the ATP binding site, the regulatory spine, and the interaction with its cyclin partner. The N-terminus of cyclin-D acts as an allosteric regulator of the activation loop and the ATP-binding site in CDK4. Integrated with a suite of experimental data, we suggest that the CDK4 complex is less capable of remaining in the active catalytically competent conformation, and may have a lower catalytic efficiency than CDK2, befitting their cell cycle time scales, and point to critical residues and motifs that drive their differences. Our mechanistic landscape may apply broadly to kinases, and we propose two drug design strategies: (i) allosteric Inhibition by conformational stabilization for targeting allosteric CDK4 regulation by cyclin-D, and (ii) dynamic entropy-optimized targeting which leverages the dynamic, entropic aspects of CDK4 to optimize drug binding efficacy.

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of influenza A virus

Viral proteins frequently mutate to evade or antagonize host innate immune responses, yet the impact of these mutations on the molecular energy landscape remains unclear. Epistasis, the intramolecular communications between mutations, often renders the combined mutational effects unpredictable. Nonstructural protein 1 (NS1) is a major virulence factor of the influenza A virus (IAV) that activates host PI3K by binding to its p85β subunit. Here, we present the deep analysis for the impact of evolutionary mutations in NS1 that emerged between the 1918 pandemic IAV strain and its descendant PR8 strain. Our analysis reveal how the mutations rewired inter-residue communications which underlies long-range allosteric and epistatic networks in NS1. Our findings show that PR8 NS1 binds to p85β with approximately 10-fold greater affinity than 1918 NS1 due to allosteric mutational effects. Notably, these mutations also exhibited long-range epistatic effects. NMR chemical shift perturbation and methyl-axis order parameter analyses revealed that the mutations induced long-range structural and dynamic changes in PR8 NS1, enhancing its affinity to p85β. Complementary MD simulations and graph-based network analysis uncover how these mutations rewire dynamic residue interaction networks, which underlies the long-range epistasis and allosteric effects on p85β-binding affinity. Significantly, we find that conformational dynamics of residues with high betweenness centrality play a crucial role in communications between network communities and are highly conserved across influenza A virus evolution. These findings advance our mechanistic understanding of the allosteric and epistatic communications between distant residues and provides insight into their role in the molecular evolution of NS1.

Computational Analysis of Activation of Dimerized Epidermal Growth Factor Receptor Kinase Using the String Method and Markov State Model

Epidermal growth factor receptor (EGFR) activation is accompanied by dimerization. During the activation of the intracellular kinase domain, two EGFR kinases form an asymmetric dimer, and one side of the dimer (receiver) is activated. Using the string method and Markov state model (MSM), we performed a computational analysis of the structural changes in the activation of the EGFR dimer in this study. The string method reveals the minimum free-energy pathway (MFEP) from the inactive to active structure. The MSM was constructed from numerous trajectories of molecular dynamics simulations around the MFEP, which revealed the free-energy map of structural changes. In the activation of the receiver kinase, the unfolding of the activation loop (A-loop) is followed by the rearrangement of the C-helix, as observed in other kinases. However, unlike other kinases, the free-energy map of EGFR at the asymmetric dimer showed that the active state yielded the highest stability and revealed how interactions at the dimer interface induced receiver activation. As the H-helix of the activator approaches the C-helix of the receiver during activation, the A-loop unfolds. Subsequently, L782 of the receiver enters the pocket between the G- and H-helices of the activator, leading to a rearrangement of the hydrophobic residues around L782 of the receiver, which constitutes a structural rearrangement of the C-helix of the receiver from an outward to an inner position. The MSM analysis revealed long-time scale trajectories via kinetic Monte Carlo.

Dynamics-driven allosteric stimulation of diguanylate cyclase activity in a red light-regulated phytochrome

Sensor-effector proteins integrate information from different stimuli and transform this into cellular responses. Some sensory domains, like red-light responsive bacteriophytochromes, show remarkable modularity regulating a variety of effectors. One effector domain is the GGDEF diguanylate cyclase catalyzing the formation of the bacterial second messenger cyclic-dimeric-guanosine monophosphate. While critical signal integration elements have been described for different phytochromes, a generalized understanding of signal processing and communication over large distances, roughly 100 Å in phytochrome diguanylate cyclases, is missing. Here we show that dynamics-driven allostery is key to understanding signal integration on a molecular level. We generated protein variants stabilized in their far-red-absorbing Pfr state and demonstrated by analysis of conformational dynamics using hydrogen-deuterium exchange coupled to mass spectrometry that single amino acid replacements are accompanied by altered dynamics of functional elements throughout the protein. We show that the conformational dynamics correlate with the enzymatic activity of these variants, explaining also the increased activity of a non-photochromic variant. In addition, we demonstrate the functional importance of mixed Pfr/intermediate state dimers using a fast-reverting variant that still enables wild-type-like fold-changes of enzymatic stimulation by red light. This supports the functional role of single protomer activation in phytochromes, a property that might correlate with the non-canonical mixed Pfr/intermediate-state spectra observed for many phytochrome systems. We anticipate our results to stimulate research in the direction of dynamics-driven allosteric regulation of different bacteriophytochrome-based sensor-effectors. This will eventually impact design strategies for the creation of novel sensor-effector systems for enriching the optogenetic toolbox.

Combination immune checkpoint and targeted protein kinase inhibitors for the treatment of renal cell carcinomas

Kidney cancers comprise about 3% of all new malignancies in the United States. Renal cell carcinomas (RCCs) are the most common type of renal malignancy making up about 85% of kidney cancer cases. Signs and symptoms of renal cell carcinomas can result from local tumor growth, paraneoplastic syndromes, or distant metastases. The classic triad of presentation with flank pain, hematuria, and a palpable abdominal mass occurs in fewer than 10% of patients. Most diagnoses result from incidental imaging findings (ultrasonography or abdominal CT imaging) performed for another reason. Localized disease is treated by partial nephrectomy, total nephrectomy, or ablation (tumor destruction with heat or cold). When the tumors have metastasized, systemic therapy with protein-tyrosine kinase antagonists including sorafenib, sunitinib, pazopanib, and tivozanib that target vascular endothelial, platelet-derived, fibroblast, hepatocyte, and stem cell factor growth factor receptors (VEGFR, PDGFR, FGFR, MET, and Kit) were prescribed after 2005. The monoclonal antibody immune checkpoint inhibitor nivolumab (targeting programed cell death protein 1, PD1) was approved for the treatment of RCCs in 2015. It is usually used now in combination with ipilimumab (targeting CTLA-4) or cabozantinib (a multikinase blocker). Other combination therapies include pembrolizumab (targeting PD1) and axitinib (a VEGFR and PDGFR blocker) or lenvatinib (a multikinase inhibitor). Since the KEYNOTE-426 clinical trial, the use of immune checkpoint inhibitors in combination with protein-tyrosine kinase inhibitors is now the standard of care for most patients with metastatic renal cell carcinomas and monotherapies are used only in those individuals who cannot receive or tolerate immune checkpoint inhibitors.

Architecture, Function, Regulation, and Evolution of α-Glucans Metabolic Enzymes in Prokaryotes

Bacteria have acquired sophisticated mechanisms for assembling and disassembling polysaccharides of different chemistry. α-d-Glucose homopolysaccharides, so-called α-glucans, are the most widespread polymers in nature being key components of microorganisms. Glycogen functions as an intracellular energy storage while some bacteria also produce extracellular assorted α-glucans. The classical bacterial glycogen metabolic pathway comprises the action of ADP-glucose pyrophosphorylase and glycogen synthase, whereas extracellular α-glucans are mostly related to peripheral enzymes dependent on sucrose. An alternative pathway of glycogen biosynthesis, operating via a maltose 1-phosphate polymerizing enzyme, displays an essential wiring with the trehalose metabolism to interconvert disaccharides into polysaccharides. Furthermore, some bacteria show a connection of intracellular glycogen metabolism with the genesis of extracellular capsular α-glucans, revealing a relationship between the storage and structural function of these compounds. Altogether, the current picture shows that bacteria have evolved an intricate α-glucan metabolism that ultimately relies on the evolution of a specific enzymatic machinery. The structural landscape of these enzymes exposes a limited number of core catalytic folds handling many different chemical reactions. In this Review, we present a rationale to explain how the chemical diversity of α-glucans emerged from these systems, highlighting the underlying structural evolution of the enzymes driving α-glucan bacterial metabolism.

Community analysis of large-scale molecular dynamics simulations elucidated dynamics-driven allostery in tyrosine kinase 2

TYK2 is a nonreceptor tyrosine kinase, member of the Janus kinases (JAK), with a central role in several diseases, including cancer. The JAKs' catalytic domains (KD) are highly conserved, yet the isolated TYK2-KD exhibits unique specificities. In a previous work, using molecular dynamics (MD) simulations of a catalytically impaired TYK2-KD variant (P1104A) we found that this amino acid change of its JAK-characteristic insert (αFG), acts at the dynamics level. Given that structural dynamics is key to the allosteric activation of protein kinases, in this study we applied a long-scale MD simulation and investigated an active TYK2-KD form in the presence of adenosine 5'-triphosphate and one magnesium ion that represents a dynamic and crucial step of the catalytic cycle, in other protein kinases. Community analysis of the MD trajectory shed light, for the first time, on the dynamic profile and dynamics-driven allosteric communications within the TYK2-KD during activation and revealed that αFG and amino acids P1104, P1105, and I1112 in particular, hold a pivotal role and act synergistically with a dynamically coupled communication network of amino acids serving intra-KD signaling for allosteric regulation of TYK2 activity. Corroborating our findings, most of the identified amino acids are associated with cancer-related missense/splice-site mutations of the Tyk2 gene. We propose that the conformational dynamics at this step of the catalytic cycle, coordinated by αFG, underlie TYK2-unique substrate recognition and account for its distinct specificity. In total, this work adds to knowledge towards an in-depth understanding of TYK2 activation and may be valuable towards a rational design of allosteric TYK2-specific inhibitors.

Role of two modules controlling the interaction between SKAP1 and SRC kinases comparison with SKAP2 architecture and consequences for evolution

SRC kinase associated phosphoprotein 1 (SKAP1), an adaptor for protein assembly, plays an important role in the immune system such as stabilizing immune synapses. Understanding how these functions are controlled at the level of the protein-protein interactions is necessary to describe these processes and to develop therapeutics. Here, we dissected the SKAP1 modular organization to recognize SRC kinases and compared it to that of its paralog SRC kinase associated phosphoprotein 2 (SKAP2). Different conserved motifs common to either both proteins or specific to SKAP2 were found using this comparison. Two modules harboring different binding properties between SKAP1 and SKAP2 were identified: one composed of two conserved motifs located in the second interdomain interacting at least with the SH2 domain of SRC kinases and a second one composed of the DIM domain modulated by the SH3 domain and the activation of SRC kinases. This work suggests a convergent evolution of the binding properties of some SRC kinases interacting specifically with either SKAP1 or SKAP2.

Large-scale analysis of the N-terminal regulatory elements of the kinase domain in plant Receptor-like kinase family

BACKGROUND

The N-terminal regulatory element (NRE) of Receptor-like kinases (RLKs), consisting of the juxtamembrane segment in receptor kinases (RKs) and the N-terminal extension segment in RLCKs, is a crucial component that regulates the activities of these proteins. However, the features and functions of the NRE have remained largely unexplored. Herein, we comprehensively analyze 510,233 NRE sequences in RLKs from 528 plant species, using information theory and data mining techniques to unravel their common characteristics and diversity. We also use recombinant RKs to investigate the function of the NRE in vitro.

RESULTS

Our findings indicate that the majority of NRE segments are around 40-80 amino acids in length and feature a serine-rich region and a 14-amino-acid consensus sequence, 'FSYEELEKAT[D/N]NF[S/D]', which contains a characteristic α-helix and ST motif that connects to the core kinase domain. This conserved signature sequence is capable of suppressing FERONIA's kinase activity. A motif discovery algorithm identifies 29 motifs with highly conserved phosphorylation sites in RK and RLCK classes, especially the motif 'VGPWKpTGLpSGQLQKAFVTGVP' in LRR-VI-2 class. Phosphorylation of an NRE motif in an LRR-VI-2 member, MDIS1, modulates the auto-phosphorylation of its co-receptor, MIK1, indicating the potential role of NRE as a 'kinase switch' in RLK activation. Furthermore, the characterization of phosphorylatable NRE motifs improves the accuracy of predicting phosphorylatable sites.

CONCLUSIONS

Our study provides a comprehensive dataset to investigate NRE segments from individual RLKs and enhances our understanding of the underlying mechanisms of RLK signal transduction and kinase activation processes in plant adaptation.

New pan-ALK inhibitor-resistant EML4::ALK mutations detected by liquid biopsy in lung cancer patients

ALK and ROS1 fusions are effectively targeted by tyrosine kinase inhibitors (TKIs), however patients inevitably relapse after an initial response, often due to kinase domain mutations. We investigated circulating DNA from TKI-relapsed NSCLC patients by deep-sequencing. New EML4::ALK substitutions, L1198R, C1237Y and L1196P, were identified in the plasma of NSCLC ALK patients and characterized in a Ba/F3 cell model. Variants C1237Y and L1196P demonstrated pan-inhibitor resistance across 5 clinical and 2 investigational TKIs.

Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study, we employ this paradigm to answer a basic question: in enzyme superfamilies, where the catalytic mechanism, active sites, and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as representatives of the conserved protein tyrosine phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of the catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Protein dynamics underlying allosteric regulation

Allostery is the mechanism by which information and control are propagated in biomolecules. It regulates ligand binding, chemical reactions, and conformational changes. An increasing level of experimental resolution and control over allosteric mechanisms promises a deeper understanding of the molecular basis for life and powerful new therapeutics. In this review, we survey the literature for an up-to-date biological and theoretical understanding of protein allostery. By delineating five ways in which the energy landscape or the kinetics of a system may change to give rise to allostery, we aim to help the reader grasp its physical origins. To illustrate this framework, we examine three systems that display these forms of allostery: allosteric inhibitors of beta-lactamases, thermosensation of TRP channels, and the role of kinetic allostery in the function of kinases. Finally, we summarize the growing power of computational tools available to investigate the different forms of allostery presented in this review.

Properties of FDA-approved small molecule protein kinase inhibitors: A 2024 update

Owing to the dysregulation of protein kinase activity in many diseases including cancer, this enzyme family has become one of the most important drug targets in the 21st century. There are 80 FDA-approved therapeutic agents that target about two dozen different protein kinases and seven of these drugs were approved in 2023. Of the approved drugs, thirteen target protein-serine/threonine protein kinases, four are directed against dual specificity protein kinases (MEK1/2), twenty block nonreceptor protein-tyrosine kinases, and 43 inhibit receptor protein-tyrosine kinases. The data indicate that 69 of these drugs are prescribed for the treatment of neoplasms. Six drugs (abrocitinib, baricitinib, deucravacitinib, ritlecitinib, tofacitinib, upadacitinib) are used for the treatment of inflammatory diseases (atopic dermatitis, rheumatoid arthritis, psoriasis, alopecia areata, and ulcerative colitis). Of the 80 approved drugs, nearly two dozen are used in the treatment of multiple diseases. The following seven drugs received FDA approval in 2023: capivasertib (HER2-positive breast cancer), fruquintinib (metastatic colorectal cancer), momelotinib (myelofibrosis), pirtobrutinib (mantle cell lymphoma, chronic lymphocytic leukemia, small lymphocytic lymphoma), quizartinib (Flt3-mutant acute myelogenous leukemia), repotrectinib (ROS1-positive lung cancer), and ritlecitinib (alopecia areata). All of the FDA-approved drugs are orally effective with the exception of netarsudil, temsirolimus, and trilaciclib. This review summarizes the physicochemical properties of all 80 FDA-approved small molecule protein kinase inhibitors including the molecular weight, number of hydrogen bond donors/acceptors, polar surface area, potency, solubility, lipophilic efficiency, and ligand efficiency.

Allosteric communication and signal transduction in proteins

Allostery is one of the cornerstones of biological function, as it plays a fundamental role in regulating protein activity. The modelling of allostery has gradually moved from a conformation-based framework, linked to structural changes, to dynamics-based allostery, whereby the effects of ligand binding propagate via signal transduction from the allosteric site to other regions of the protein via inter-residue interactions. Characterising such allosteric signalling pathways, which do not necessarily lead to conformational changes, has been pursued experimentally and complemented by computational analysis of protein networks to detect subtle dynamic propagation paths. Considering allostery from the perspective of signal transduction broadens the understanding of allosteric mechanisms, underscores the importance of protein topology, and can provide insights into allosteric drug design.

Unraveling the Potential of ALK-Targeted Therapies in Non-Small Cell Lung Cancer: Comprehensive Insights and Future Directions

Background and Objective: This review comprehensively explores the intricate landscape of anaplastic lymphoma kinase (ALK), focusing specifically on its pivotal role in non-small cell lung cancer (NSCLC). Tracing ALK's discovery, from its fusion with nucleolar phosphoprotein (NPM)-1 in anaplastic large cell non-Hodgkin's lymphoma (ALCL) in 1994, the review elucidates the subsequent impact of ALK gene alterations in various malignancies, including inflammatory myofibroblastoma and NSCLC. Approximately 3-5% of NSCLC patients exhibit complex ALK rearrangements, leading to the approval of six ALK-tyrosine kinase inhibitors (TKIs) by 2022, revolutionizing the treatment landscape for advanced metastatic ALK + NSCLC. Notably, second-generation TKIs such as alectinib, ceritinib, and brigatinib have emerged to address resistance issues initially associated with the pioneer ALK-TKI, crizotinib. Methods: To ensure comprehensiveness, we extensively reviewed clinical trials on ALK inhibitors for NSCLC by 2023. Additionally, we systematically searched PubMed, prioritizing studies where the terms "ALK" AND "non-small cell lung cancer" AND/OR "NSCLC" featured prominently in the titles. This approach aimed to encompass a spectrum of relevant research studies, ensuring our review incorporates the latest and most pertinent information on innovative and alternative therapeutics for ALK + NSCLC. Key Content and Findings: Beyond exploring the intricate details of ALK structure and signaling, the review explores the convergence of ALK-targeted therapy and immunotherapy, investigating the potential of immune checkpoint inhibitors in ALK-altered NSCLC tumors. Despite encouraging preclinical data, challenges observed in trials assessing combinations such as nivolumab-crizotinib, mainly due to severe hepatic toxicity, emphasize the necessity for cautious exploration of these novel approaches. Additionally, the review explores innovative directions such as ALK molecular diagnostics, ALK vaccines, and biosensors, shedding light on their promising potential within ALK-driven cancers. Conclusions: This comprehensive analysis covers molecular mechanisms, therapeutic strategies, and immune interactions associated with ALK-rearranged NSCLC. As a pivotal resource, the review guides future research and therapeutic interventions in ALK-targeted therapy for NSCLC.

Gauging Dynamics-driven Allostery Using a New Computational Tool: A CAP Case Study

In this study, we utilize Protein Residue Networks (PRNs), constructed using Local Spatial Pattern (LSP) alignment, to explore the dynamic behavior of Catabolite Activator Protein (CAP) upon the sequential binding of cAMP. We employed the Degree Centrality of these PRNs to investigate protein dynamics on a sub-nanosecond time scale, hypothesizing that it would reflect changes in CAP's entropy related to its thermal motions. We show that the binding of the first cAMP led to an increase in stability in the Cyclic-Nucleotide Binding Domain A (CNBD-A) and destabilization in CNBD-B, agreeing with previous reports explaining the negative cooperativity of cAMP binding in terms of an entropy-driven allostery. LSP-based PRNs also allow for the study of Betweenness Centrality, another graph-theoretical characteristic of PRNs, providing insights into global residue connectivity within CAP. Using this approach, we were able to correctly identify amino acids that were shown to be critical in mediating allosteric interactions in CAP. The agreement between our studies and previous experimental reports validates our method, particularly with respect to the reliability of Degree Centrality as a proxy for entropy related to protein thermal dynamics. Because LSP-based PRNs can be easily extended to include dynamics of small organic molecules, polynucleotides, or other allosteric proteins, the methods presented here mark a significant advancement in the field, positioning them as vital tools for a fast, cost-effective, and accurate analysis of entropy-driven allostery and identification of allosteric hotspots.

Dark kinase annotation, mining, and visualization using the Protein Kinase Ontology

The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships among protein kinase sequence, structure, function, and disease in a human and machine-readable format. In this study, we have significantly expanded ProKinO by incorporating additional data on expression patterns and drug interactions. Furthermore, we have developed a completely new browser from the ground up to render the knowledge graph visible and interactive on the web. We have enriched ProKinO with new classes and relationships that capture information on kinase ligand binding sites, expression patterns, and functional features. These additions extend ProKinO's capabilities as a discovery tool, enabling it to uncover novel insights about understudied members of the protein kinase family. We next demonstrate the application of ProKinO. Specifically, through graph mining and aggregate SPARQL queries, we identify the p21-activated protein kinase 5 (PAK5) as one of the most frequently mutated dark kinases in human cancers with abnormal expression in multiple cancers, including a previously unappreciated role in acute myeloid leukemia. We have identified recurrent oncogenic mutations in the PAK5 activation loop predicted to alter substrate binding and phosphorylation. Additionally, we have identified common ligand/drug binding residues in PAK family kinases, underscoring ProKinO's potential application in drug discovery. The updated ontology browser and the addition of a web component, ProtVista, which enables interactive mining of kinase sequence annotations in 3D structures and Alphafold models, provide a valuable resource for the signaling community. The updated ProKinO database is accessible at https://prokino.uga.edu.

Genetic switching by the Lac repressor is based on two-state Monod-Wyman-Changeux allostery

High-resolution NMR spectroscopy enabled us to characterize allosteric transitions between various functional states of the dimeric Escherichia coli Lac repressor. In the absence of ligands, the dimer exists in a dynamic equilibrium between DNA-bound and inducer-bound conformations. Binding of either effector shifts this equilibrium toward either bound state. Analysis of the ternary complex between repressor, operator DNA, and inducer shows how adding the inducer results in allosteric changes that disrupt the interdomain contacts between the inducer binding and DNA binding domains and how this in turn leads to destabilization of the hinge helices and release of the Lac repressor from the operator. Based on our data, the allosteric mechanism of the induction process is in full agreement with the well-known Monod-Wyman-Changeux model.

Protein Kinase Structure and Dynamics: Role of the αC-β4 Loop

Although the αC-β4 loop is a stable feature of all protein kinases, the importance of this motif as a conserved element of secondary structure, as well as its links to the hydrophobic architecture of the kinase core, has been underappreciated. We first review the motif and then describe how it is linked to the hydrophobic spine architecture of the kinase core, which we first discovered using a computational tool, Local Spatial Pattern (LSP) alignment. Based on NMR predictions that a mutation in this motif abolishes the synergistic high-affinity binding of ATP and a pseudo substrate inhibitor, we used LSP to interrogate the F100A mutant. This comparison highlights the importance of the αC-β4 loop and key residues at the interface between the N- and C-lobes. In addition, we delved more deeply into the structure of the apo C-subunit, which lacks ATP. While apo C-subunit showed no significant changes in backbone dynamics of the αC-β4 loop, we found significant differences in the side chain dynamics of K105. The LSP analysis suggests disruption of communication between the N- and C-lobes in the F100A mutant, which would be consistent with the structural changes predicted by the NMR spectroscopy.

The choreography of protein kinase PDK1 and its diverse substrate dance partners

The protein kinase PDK1 phosphorylates at least 24 distinct substrates, all of which belong to the AGC protein kinase group. Some substrates, such as conventional PKCs, undergo phosphorylation by PDK1 during their synthesis and subsequently get activated by DAG and Calcium. On the other hand, other substrates, including members of the Akt/PKB, S6K, SGK, and RSK families, undergo phosphorylation and activation downstream of PI3-kinase signaling. This review presents two accepted molecular mechanisms that determine the precise and timely phosphorylation of different substrates by PDK1. The first mechanism involves the colocalization of PDK1 with Akt/PKB in the presence of PIP3. The second mechanism involves the regulated docking interaction between the hydrophobic motif (HM) of substrates and the PIF-pocket of PDK1. This interaction, in trans, is equivalent to the molecular mechanism that governs the activity of AGC kinases through their HMs intramolecularly. PDK1 has been instrumental in illustrating the bi-directional allosteric communication between the PIF-pocket and the ATP-binding site and the potential of the system for drug discovery. PDK1's interaction with substrates is not solely regulated by the substrates themselves. Recent research indicates that full-length PDK1 can adopt various conformations based on the positioning of the PH domain relative to the catalytic domain. These distinct conformations of full-length PDK1 can influence the interaction and phosphorylation of substrates. Finally, we critically discuss recent findings proposing that PIP3 can directly regulate the activity of PDK1, which contradicts extensive in vitro and in vivo studies conducted over the years.

A conserved arginine within the αC-helix of Erk1/2 is a latch of autoactivation and of oncogenic capabilities

Eukaryotic protein kinases (EPKs) adopt an active conformation following phosphorylation of a particular activation loop residue. Most EPKs spontaneously autophosphorylate this residue. While structure-function relationships of the active conformation are essentially understood, those of the "prone-to-autophosphorylate" conformation are unclear. Here, we propose that a site within the αC-helix of EPKs, occupied by Arg in the mitogen-activated protein kinase (MAPK) Erk1/2 (Arg84/65), impacts spontaneous autophosphorylation. MAPKs lack spontaneous autoactivation, but we found that converting Arg84/65 of Erk1/2 to various residues enables spontaneous autophosphorylation. Furthermore, Erk1 molecules mutated in Arg84 are oncogenic. Arg84/65 thus obstructs the adoption of the "prone-to-autophosphorylate" conformation. All MAPKs harbor an Arg that is equivalent to Arg84/65 of Erks, whereas Arg is rarely found at the equivalent position in other EPKs. We observed that Arg84/65 of Erk1/2 interacts with the DFG motif, suggesting that autophosphorylation may be inhibited by the Arg84/65-DFG interactions. Erk1/2s mutated in Arg84/65 autophosphorylate not only the TEY motif, known as critical for catalysis, but also on Thr207/188. Our MS/MS analysis revealed that a large proportion of the Erk2R65H population is phosphorylated on Thr188 or on Tyr185 + Thr188, and a small fraction is phosphorylated on the TEY motif. No molecules phosphorylated on Thr183 + Thr188 were detected. Thus, phosphorylation of Thr183 and Thr188 is mutually exclusive suggesting that not only TEY-phosphorylated molecules are active but perhaps also those phosphorylated on Tyr185 + Thr188. The effect of mutating Arg84/65 may mimic a physiological scenario in which allosteric effectors cause Erk1/2 activation by autophosphorylation.

Evaluating the ability of end-point methods to predict the binding affinity tendency of protein kinase inhibitors

Because of the high economic cost of exploring the experimental impact of mutations occurring in kinase proteins, computational approaches have been employed as alternative methods for evaluating the structural and energetic aspects of kinase mutations. Among the main computational methods used to explore the affinity linked to kinase mutations are docking procedures and molecular dynamics (MD) simulations combined with end-point methods or alchemical methods. Although it is known that end-point methods are not able to reproduce experimental binding free energy (ΔG) values, it is also true that they are able to discriminate between a better or a worse ligand through the estimation of ΔG. In this contribution, we selected ten wild-type and mutant cocrystallized EGFR-inhibitor complexes containing experimental binding affinities to evaluate whether MMGBSA or MMPBSA approaches can predict the differences in affinity between the wild type and mutants forming a complex with a similar inhibitor. Our results show that a long MD simulation (the last 50 ns of a 100 ns-long MD simulation) using the MMGBSA method without considering the entropic components reproduced the experimental affinity tendency with a Pearson correlation coefficient of 0.779 and an R2 value of 0.606. On the other hand, the correlation between theoretical and experimental ΔΔG values indicates that the MMGBSA and MMPBSA methods are helpful for obtaining a good correlation using a short rather than a long simulation period.

Small molecule protein kinase inhibitors approved by regulatory agencies outside of the United States

Owing to genetic alterations and overexpression, the dysregulation of protein kinases plays a significant role in the pathogenesis of many autoimmune and neoplastic disorders and protein kinase antagonists have become an important drug target. Although the efficacy of imatinib in the treatment of chronic myelogenous leukemia in the United States in 2001 was the main driver of protein kinase inhibitor drug discovery, this was preceded by the approval of fasudil (a ROCK antagonist) in Japan in 1995 for the treatment of cerebral vasospasm. There are 21 small molecule protein kinase inhibitors that are approved in China, Japan, Europe, and South Korea that are not approved in the United Sates and 75 FDA-approved inhibitors in the United States. Of the 21 agents, eleven target receptor protein-tyrosine kinases, eight inhibit nonreceptor protein-tyrosine kinases, and two block protein-serine/threonine kinases. All 21 drugs are orally bioavailable or topically effective. Of the non-FDA approved drugs, sixteen are prescribed for the treatment of neoplastic diseases, three are directed toward inflammatory disorders, one is used for glaucoma, and fasudil is used in the management of vasospasm. The leading targets of kinase inhibitors approved by both international regulatory agencies and by the FDA are members of the EGFR family, the VEGFR family, and the JAK family. One-third of the 21 internationally approved drugs are not compliant with Lipinski's rule of five for orally bioavailable drugs. The rule of five relies on four parameters including molecular weight, number of hydrogen bond donors and acceptors, and the Log of the partition coefficient.

Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study we employ this paradigm to answer a basic question: in enzyme superfamilies where the catalytic mechanism, active sites and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as the representatives of the conserved Protein Tyrosine Phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.

PK1 from Drosophila obscurin is an inactive pseudokinase with scaffolding properties

Obscurins are large filamentous proteins with crucial roles in the assembly, stability and regulation of muscle. Characteristic of these proteins is a tandem of two C-terminal kinase domains, PK1 and PK2, that are separated by a long intrinsically disordered sequence. The significance of this conserved domain arrangement is unknown. Our study of PK1 from Drosophila obscurin shows that this is a pseudokinase with features typical of the CAM-kinase family, but which carries a minimalistic regulatory tail that no longer binds calmodulin or has mechanosensory properties typical of other sarcomeric kinases. PK1 binds ATP with high affinity, but in the absence of magnesium and lacks detectable phosphotransfer activity. It also has a highly diverged active site, strictly conserved across arthropods, that might have evolved to accommodate an unconventional binder. We find that PK1 interacts with PK2, suggesting a functional relation to the latter. These findings lead us to speculate that PK1/PK2 form a pseudokinase/kinase dual system, where PK1 might act as an allosteric regulator of PK2 and where mechanosensing properties, akin to those described for regulatory tails in titin-like kinases, might now reside on the unstructured interkinase segment. We propose that the PK1-interkinase-PK2 region constitutes an integrated functional unit in obscurin proteins.

The quaternary question: Determining allostery in spastin through dynamics classification learning and bioinformatics

The nanomachine from the ATPases associated with various cellular activities superfamily, called spastin, severs microtubules during cellular processes. To characterize the functionally important allostery in spastin, we employed methods from evolutionary information, to graph-based networks, to machine learning applied to atomistic molecular dynamics simulations of spastin in its monomeric and the functional hexameric forms, in the presence or absence of ligands. Feature selection, using machine learning approaches, for transitions between spastin states recognizes all the regions that have been proposed as allosteric or functional in the literature. The analysis of the composition of the Markov State Model macrostates in the spastin monomer, and the analysis of the direction of change in the top machine learning features for the transitions, indicate that the monomer favors the binding of ATP, which primes the regions involved in the formation of the inter-protomer interfaces for binding to other protomer(s). Allosteric path analysis of graph networks, built based on the cross-correlations between residues in simulations, shows that perturbations to a hub specific for the pre-hydrolysis hexamer propagate throughout the structure by passing through two obligatory regions: the ATP binding pocket, and pore loop 3, which connects the substrate binding site to the ATP binding site. Our findings support a model where the changes in the terminal protomers due to the binding of ligands play an active role in the force generation in spastin. The secondary structures in spastin, which are found to be highly degenerative within the network paths, are also critical for feature transitions of the classification models, which can guide the design of allosteric effectors to enhance or block allosteric signaling.

The "violin model": Looking at community networks for dynamic allostery

Allosteric regulation of proteins continues to be an engaging research topic for the scientific community. Models describing allosteric communication have evolved from focusing on conformation-based descriptors of protein structural changes to appreciating the role of internal protein dynamics as a mediator of allostery. Here, we explain a "violin model" for allostery as a contemporary method for approaching the Cooper-Dryden model based on redistribution of protein thermal fluctuations. Based on graph theory, the violin model makes use of community network analysis to functionally cluster correlated protein motions obtained from molecular dynamics simulations. This Review provides the theory and workflow of the methodology and explains the application of violin model to unravel the workings of protein kinase A.

Activation loop phosphorylation tunes conformational dynamics underlying Pyk2 tyrosine kinase activation

Pyk2 is a multidomain non-receptor tyrosine kinase that undergoes a multistage activation mechanism. Activation is instigated by conformational rearrangements relieving autoinhibitory FERM domain interactions. The kinase autophosphorylates a central linker residue to recruit Src kinase. Pyk2 and Src mutually phosphorylate activation loops to confer full activation. While the mechanisms of autoinhibition are established, the conformational dynamics associated with autophosphorylation and Src recruitment remain unclear. We employ hydrogen/deuterium exchange mass spectrometry and kinase activity profiling to map the conformational dynamics associated with substrate binding and Src-mediated activation loop phosphorylation. Nucleotide engagement stabilizes the autoinhibitory interface, while phosphorylation deprotects both FERM and kinase regulatory surfaces. Phosphorylation organizes active site motifs linking catalytic loop with activation segment. Dynamics of the activation segment anchor propagate to EF/G helices to prevent reversion of the autoinhibitory FERM interaction. We employ targeted mutagenesis to dissect how phosphorylation-induced conformational rearrangements elevate kinase activity above the basal autophosphorylation rate.

Allosteric Boost by TAB1 on the TAK1 Kinase Favorably Sculpts the Thermodynamic Landscape of Activation

The intricate mechanisms of allosteric regulation in kinases are of general interest to the scientific community for potential therapeutic implications. However, the diversity among kinases and their regulatory routes requires a case-by-case study to widen the repertoire of known mechanisms. The present study achieves this by understanding TAK1 kinase activation by TAB1 as a model phenomenon for the first time. Despite the known capacity of TAK1 to switch between its inactive ("DFG-out") and active-like ("DFG-in") conformations, the questionable role of TAB1 in offering an energetic favor to this has been addressed here using sequential combination of enhanced sampling methods like targeted molecular dynamics (TMD) and Gaussian accelerated molecular dynamics (GaMD). It reveals how a minimal domain of TAB1 sufficiently acts like a "catalytic gear" by favorably sculpting TAK1's thermodynamic landscape (potential of mean force in 2D) that accelerates "in"-"out" conformational switching of the conserved DFG motif. Standard molecular dynamics simulations (∼5 μs) reveal that TAB1 fascinatingly exploits the "lever-like" αF helix of TAK1 kinase domain to remotely propel the DFG motif via subtle helical "unfolding-folding" modifications within the kinase activation loop. The presence of two charged residues on terminal poles of αF helix imparts it, with this unique "lever-like" utility, and this turns out to be one important signature of co-evolution between TAK1 and TAB1. The entire mechanism of TAB1's impact transduction, which is found to be analogous to the moves in the popular "Chinese checker" game, gives a clear proof of the "dynamics-driven allostery" concept in kinases. The findings further benchmark TAK1's known autophosphorylation capacity. A novel insight into kinase allostery is thus provided, which potentiates investigation of similar capacities in other kinases.

An intelligent, autocatalytic, DNAzyme biocircuit for amplified imaging of intracellular microRNAs

DNAzymes hold great promise as transducing agents for the analysis of intracellular biomarkers. However, their low intracellular delivery efficiency and limited signal amplification capability (including an additional supply of cofactors) hinder their application in low-abundance biomarker analysis. Herein, a general strategy to design an intelligent, autocatalytic, DNAzyme biocircuit is developed for amplified microRNA imaging in living cells. The DNAzyme biocircuit is constructed based on a nanodevice composed of catalytic hairpin assembly (CHA) and DNAzyme biocatalytic functional units, sustained by Au nanoparticles (AuNPs) and MnO₂ nanosheets (CD/AM nanodevices). Once the CD/AM nanodevices are endocytosed by cells, the MnO₂ nanosheets are reduced by intracellular glutathione (GSH), which not only releases the different units of the DNAzyme circuit, but also generates the cofactor Mn²⁺ for DNAzyme autocatalysis. The intracellular analytes could trigger the coordinated cross-activation of CHA and autocatalytic DNAzymes on AuNPs, enabling reliable and accurate detection of miRNAs in living cells. This intelligent autocatalytic multilayer DNAzyme biocircuit can effectively avoid signal leakage and obtain high amplification gain, expanding the application of programmable complex DNA nanocircuits in biosensing, nanomaterial assembly, and biomedicine.

Biochemical and hydrogen-deuterium exchange studies of the single nucleotide polymorphism Y649C in human platelet 12-lipoxygenase linked to a bleeding disorder

Human platelet 12-lipoxygenase (h12-LOX) is responsible for the formation of oxylipin products that play an important role in platelet aggregation. Single nucleotide polymorphisms (SNPs) of h12-LOX have been implicated in several diseases. In this study, we investigate the structural, dynamical, and functional impact of a h12-LOX SNP that generates a tyrosine-to-cysteine mutation at a buried site (Y649C h12-LOX) and was previously ascribed with reduced levels of 12(S)-hydroxyeicosatetraenoic acid (12S-HETE) production in isolated platelets. Herein, in vitro Michaelis-Menten kinetics show reduced catalytic rates for Y649C compared to WT h12-LOX at physiological or lower temperatures. Both proteins exhibited similar melting temperatures, metal content, and oligomerization state. Liposome binding for both proteins was also dependent upon the presence of calcium, temperature, and liposome composition; however, the Y649C variant was found to have lowered binding capacity to liposomes compared to WT at physiological temperatures. Further, hydrogen-deuterium exchange mass spectrometry (HDX-MS) experiments revealed a regional defined enhancement in the peptide mobility caused by the mutation. This increased instability for the mutation stemmed from a change in an interaction with an arched helix that lines the substrate binding site, located ≥15 Å from the mutation site. Finally, differential scanning calorimetry demonstrated a reduced protein (un)folding enthalpy, consistent with the HDX results. Taken together, these results demonstrate remarkable similarity between the mutant and WT h12-LOX, and yet, subtle changes in activity, membrane affinity and protein stability may be responsible for the significant physiological changes that the Y649C SNP manifests in platelet biology.

Properties of FDA-approved small molecule protein kinase inhibitors: A 2023 update

Owing to the dysregulation of protein kinase activity in many diseases including cancer, this enzyme family has become one of the most important drug targets in the 21st century. There are 72 FDA-approved therapeutic agents that target about two dozen different protein kinases and three of these drugs were approved in 2022. Of the approved drugs, twelve target protein-serine/threonine protein kinases, four are directed against dual specificity protein kinases (MEK1/2), sixteen block nonreceptor protein-tyrosine kinases, and 40 target receptor protein-tyrosine kinases. The data indicate that 62 of these drugs are prescribed for the treatment of neoplasms (57 against solid tumors including breast, lung, and colon, ten against nonsolid tumors such as leukemia, and four against both solid and nonsolid tumors: acalabrutinib, ibrutinib, imatinib, and midostaurin). Four drugs (abrocitinib, baricitinib, tofacitinib, upadacitinib) are used for the treatment of inflammatory diseases (atopic dermatitis, psoriatic arthritis, rheumatoid arthritis, Crohn disease, and ulcerative colitis). Of the 72 approved drugs, eighteen are used in the treatment of multiple diseases. The following three drugs received FDA approval in 2022 for the treatment of these specified diseases: abrocitinib (atopic dermatitis), futibatinib (cholangiocarcinomas), pacritinib (myelofibrosis). All of the FDA-approved drugs are orally effective with the exception of netarsudil, temsirolimus, and trilaciclib. This review summarizes the physicochemical properties of all 72 FDA-approved small molecule protein kinase inhibitors including lipophilic efficiency and ligand efficiency.

Modeling the ribosome as a bipartite graph

Developing mathematical representations of biological systems that can allow predictions is a challenging and important research goal. It is demonstrated here how the ribosome, the nano-machine responsible for synthesizing all proteins necessary for cellular life, can be represented as a bipartite network. Ten ribosomal structures from Bacteria and six from Eukarya are explored. Ribosomal networks are found to exhibit unique properties despite variations in the nodes and edges of the different graphs. The ribosome is shown to exhibit very large topological redundancies, demonstrating mathematical resiliency. These results can potentially explain how it can function consistently despite changes in composition and connectivity. Furthermore, this representation can be used to analyze ribosome function within the large machinery of network theory, where the degrees of freedom are the possible interactions, and can be used to provide new insights for translation regulation and therapeutics.