Structural Features that Distinguish Inactive and Active PI3K Lipid Kinases

Structural insights into the activation mechanism of phosphoinositide 3-kinase alpha

Phosphoinositide 3-kinases (PI3Ks) are lipid kinases known to regulate important cellular functions by phosphorylating the inositol ring of inositol-phospholipids (PtdIns) at 3' position. The PI3Kα is a heterodimer and the activation of the catalytic subunit (p110α) is regulated by its regulatory subunit (p85α). The current work deals with studying the activation mechanism of the PI3Kα using multi micro-second molecular dynamic simulations. Structural changes involved in activation mechanism is studied by gradually releasing the inhibitory effects of different domains of regulatory subunit namely, n-terminal SH2 (nSH2) and inter SH2 (iSH2). The observation shows that even in the presence of n-terminal and inter SH2 domain (niSH2) of regulatory subunit, the catalytic domain has some intrinsic activation activity and the presence of c-terminal SH2 (cSH2) domain may be required for complete inhibition. The release of nSH2 domain leads to loss of interactions between iSH2 domain (regulatory subunit) and C2 and kinase domain (catalytic subunit). The study shows that early events in the activation mechanism involve the movement of the ABD domain of the catalytic subunit along with the linker region between ABD and RBD region which may lead to movement of ABD closer to the CLobe of the kinase domain. This movement is essentially as it triggers the rearrangement of CLobe especially the catalytic loop and activation loop which bring catalytic important residues closer to ATP and PIP2(phosphatidylinositol-4,5-bisphosphate). Water mediated interaction analysis reveal that water may be playing an important role in the transfer of phosphate from ATP to PIP2. The study shows that initial signal for release of inhibitory effect of the regulatory subunit might be propagated through the linker region between ABD and RBD through allosteric effect to different regions of the protein. These understanding of early events during the activation mechanism may help in the design of better therapeutic targeting PI3K.

A comprehensive review of small molecules targeting PI3K pathway: Exploring the structural development for the treatment of breast cancer

Cancer stands as one of the deadliest diseases, ranking second in terms of its global impact. Despite the presence of numerous compelling theories concerning its origins, none have succeeded in fully elucidating the intricate nature of this ailment. Among the prevailing concerns in today's world, breast cancer proliferation remains a significant issue, particularly affecting females. The abnormal proliferation of the PI3K pathway emerges as a prominent driver of breast cancer, underscoring its role in cellular survival and proliferation. Consequently, targeting this pathway has emerged as a leading strategy in breast cancer therapeutics. Within this context, the present article explores the current landscape of anti-tumour drug development, focusing on structural activity relationships (SAR) in PI3K targeting breast cancer treatment. Notably, certain moieties like triazines, pyrimidine, quinazoline, quinoline, and pyridoxine have been explored as potential PI3K inhibitors for combating breast cancer. Various heterocyclic small molecules are undergoing clinical trials, such as Alpelisib, the first orally available FDA-approved drug targeting PI3K; others include buparlisib, pictilisib, and taselisib, which inhibit class I PI3K. These drugs are used for the treatment of breast cancer but still have various side effects with their high cost. Therefore, the primary goal of this review is to include all current advances in the development of anticancer medicines that target PI3K over-activation in the treatment of breast cancer.

The allosteric mechanism of mTOR activation can inform bitopic inhibitor optimization

mTOR serine/threonine kinase is a cornerstone in the PI3K/AKT/mTOR pathway. Yet, the detailed mechanism of activation of its catalytic core is still unresolved, likely due to mTOR complexes' complexity. Its dysregulation was implicated in cancer and neurodevelopmental disorders. Using extensive molecular dynamics (MD) simulations and compiled published experimental data, we determine exactly how mTOR's inherent motifs can control the conformational changes in the kinase domain, thus kinase activity. We also chronicle the critical regulation by the unstructured negative regulator domain (NRD). When positioned inside the catalytic cleft (NRD IN state), mTOR tends to adopt a deep and closed catalytic cleft. This is primarily due to the direct interaction with the FKBP-rapamycin binding (FRB) domain which restricts it, preventing substrate access. Conversely, when outside the catalytic cleft (NRD OUT state), mTOR favors an open conformation, exposing the substrate-binding site on the FRB domain. We further show how an oncogenic mutation (L2427R) promotes shifting the mTOR ensemble toward the catalysis-favored state. Collectively, we extend mTOR's "active-site restriction" mechanism and clarify mutation action. In particular, our mechanism suggests that RMC-5552 (RMC-6272) bitopic inhibitors may benefit from adjustment of the (PEG8) linker length when targeting certain mTOR variants. In the cryo-EM mTOR/RMC-5552 structure, the distance between the allosteric and orthosteric inhibitors is ∼22.7 Å. With a closed catalytic cleft, this linker bridges the sites. However, in our activation mechanism, in the open cleft it expands to ∼24.7 Å, offering what we believe to be the first direct example of how discovering an activation mechanism can potentially increase the affinity of inhibitors targeting mutants.

Structural and mechanistic insights provided by single particle cryo-EM analysis of phosphoinositide 3-kinase (PI3Kα)

Recent cryo-electron microscopic (cryo-EM) investigations have succeeded in the analysis of various structural conformations and functional states of PI3Kα, a dimer consisting of the catalytic subunit p110α and the regulatory subunit p85α of class IA of phosphoinositide 3-kinase. High resolution structures have been obtained of the unliganded and of BYL-719-bound PI3Kα. The latter provides information on excessively flexible domains of p85α that are then further analyzed with nanobodies and CXMS (chemical cross-linking, digestion and mass spectrometry). Analysis of p110α helical and kinase domain mutations reveals mutant-specific features that can be linked to the gain of function in enzymatic and signaling activities.

EnGens: a computational framework for generation and analysis of representative protein conformational ensembles

Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in the number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing representative protein conformational ensembles. In this work, we: (1) provide an overview of existing methods and tools for representative protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples from the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations.

EnGens: a computational framework for generation and analysis of representative protein conformational ensembles

Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing protein conformational ensembles. In this work we: (1) provide an overview of existing methods and tools for protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples found in the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations.

Strategy toward Kinase-Selective Drug Discovery

Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar kinase drug pockets, off-target inhibitor toxicity has been a major cause for clinical trial failures. The pockets are similar but not identical. Here, we describe a transformation invariant protocol to identify distinct geometric features in the drug pocket that can distinguish one kinase from all others. We integrate available experimental structures with the artificial intelligence-based structural kinome, performing a kinome-wide structural bioinformatic analysis to establish the structural principles of kinase drug selectivity. We generate the structural landscape from the experimental kinase-ligand complexes and propose a binary network that encapsulates the information. The results show that all kinases contain binary units that are shared by less than seven other kinases in the kinome. 331 kinases contain unique binary units that may distinguish them from all others. The structural features encoded by these binary units in the network represent the inhibitor-accessible geometric space that may capture the kinome-wide selectivity. Our proposed binary network with the unsupervised clustering can serve as a general structural bioinformatic protocol for extracting the distinguishing structural features for any protein from their families. We apply the binary network to epidermal growth factor receptor tyrosine kinase inhibitor selectivity by targeting the gate area and the AKT1 serine/threonine kinase selectivity by binding to the αC-helix region and the allosteric pocket. Finally, we develop the cross-platform software, KDS (Kinase Drug Selectivity), for customized visualization and analysis of the binary networks in the human kinome (https://github.com/CBIIT/KDS).

Pan-cancer clinical impact of latent drivers from double mutations

Here, we discover potential 'latent driver' mutations in cancer genomes. Latent drivers have low frequencies and minor observable translational potential. As such, to date they have escaped identification. Their discovery is important, since when paired in cis, latent driver mutations can drive cancer. Our comprehensive statistical analysis of the pan-cancer mutation profiles of ~60,000 tumor sequences from the TCGA and AACR-GENIE cohorts identifies significantly co-occurring potential latent drivers. We observe 155 same gene double mutations of which 140 individual components are cataloged as latent drivers. Evaluation of cell lines and patient-derived xenograft response data to drug treatment indicate that in certain genes double mutations may have a prominent role in increasing oncogenic activity, hence obtaining a better drug response, as in PIK3CA. Taken together, our comprehensive analyses indicate that same-gene double mutations are exceedingly rare phenomena but are a signature for some cancer types, e.g., breast, and lung cancers. The relative rarity of doublets can be explained by the likelihood of strong signals resulting in oncogene-induced senescence, and by doublets consisting of non-identical single residue components populating the background mutational load, thus not identified.

Oncogenic mutations of PIK3CA lead to increased membrane recruitment driven by reorientation of the ABD, p85 and C-terminus

PIK3CA encoding the phosphoinositide 3-kinase (PI3K) p110α catalytic subunit is frequently mutated in cancer, with mutations occurring widely throughout the primary sequence. The full set of mechanisms underlying how PI3Ks are activated by all oncogenic mutations on membranes are unclear. Using a synergy of biochemical assays and hydrogen deuterium exchange mass spectrometry (HDX-MS), we reveal unique regulatory mechanisms underlying PI3K activation. Engagement of p110α on membranes leads to disengagement of the ABD of p110α from the catalytic core, and the C2 domain from the iSH2 domain of the p85 regulatory subunit. PI3K activation also requires reorientation of the p110α C-terminus, with mutations that alter the inhibited conformation of the C-terminus increasing membrane binding. Mutations at the C-terminus (M1043I/L, H1047R, G1049R, and N1068KLKR) activate p110α through distinct mechanisms, with this having important implications for mutant selective inhibitor development. This work reveals unique mechanisms underlying how PI3K is activated by oncogenic mutations, and explains how double mutants can synergistically increase PI3K activity.

Cryo-EM structures of cancer-specific helical and kinase domain mutations of PI3Kα

Phosphoinositide 3-kinases (PI3Ks) are a family of lipid kinases that perform multiple and important cellular functions. The protein investigated here belongs to class IA of the PI3Ks; it is a dimer consisting of a catalytic subunit, p110α, and a regulatory subunit, p85α, and is referred to as PI3Kα. The catalytic subunit p110α is frequently mutated in cancer. The mutations induce a gain of function and constitute a driving force in cancer development. About 80% of these mutations lead to single-amino-acid substitutions in one of three sites of p110α: two in the helical domain of the protein (E542K and E545K) and one at the C-terminus of the kinase domain (H1047R). Here, we report the cryo-electron microscopy structures of these mutants in complex with the p110α-specific inhibitor BYL-719. The H1047R mutant rotates its sidechain to a new position and weakens the kα11 activation loop interaction, thereby reducing the inhibitory effect of p85α on p110α. E542K and E545K completely abolish the tight interaction between the helical domain of p110α and the N-terminal SH2 domain of p85α and lead to the disruption of all p85α binding and a dramatic increase in flexibility of the adaptor-binding domain (ABD) in p110α. Yet, the dimerization of PI3Kα is preserved through the ABD-p85α interaction. The local and global structural features induced by these mutations provide molecular insights into the activation of PI3Kα, deepen our understanding of the oncogenic mechanism of this important signaling molecule, and may facilitate the development of mutant-specific inhibitors.

Structural dynamics of the N‐terminal SH2 domain of PI3K in its free and CD28 ‐bound states

Protein conformational changes with fluctuations are fundamental aspects of protein-protein interactions (PPIs); understanding these motions is required for the rational design of PPI-regulating compounds. Src homology 2 (SH2) domains are commonly found in adapter proteins involved in signal transduction and specifically bind to consensus motifs of proteins containing phosphorylated tyrosine (pY). Here, we analysed the interaction between the N-terminal SH2 domain (nSH2) of the regulatory subunit in phosphoinositide 3-kinase (PI3K) and the cytoplasmic region of the T-cell co-receptor, CD28, using NMR and molecular dynamics (MD) simulations. First, we assigned the backbone signals of nSH2 on ¹ H-¹⁵ N heteronuclear single quantum coherence spectra in the absence or presence of the CD28 phosphopeptide, SDpYMNMTPRRPG. Chemical shift perturbation experiments revealed allosteric changes at the BC loop and the C-terminal region of nSH2 upon CD28 binding. NMR relaxation experiments showed a conformational exchange associated with CD28 binding in these regions. The conformational stabilisation of the C-terminal region correlated with the regulation of PI3K catalytic function. Further, using ¹⁹ F- and ³¹ P-labelled CD28 phosphopeptide, we analysed the structural dynamics of CD28 and demonstrated that the aromatic ring of the pY residue fluctuated between multiple conformations upon nSH2 binding. Our MD simulations largely explained the NMR results and the structural dynamics of nSH2 and CD28 in both bound and unbound states. Notably, in addition to its major conformation, we detected a minor conformation of nSH2 in the CD28 bound state that may explain the allosteric conformational change in the BC loop.

Nanobodies and chemical cross-links advance the structural and functional analysis of PI3Kα

Nanobodies and chemical cross-linking were used to gain information on the identity and positions of flexible domains of PI3Kα. The application of chemical cross-linking mass spectrometry (CXMS) facilitated the identification of the p85 domains BH, cSH2, and SH3 as well as their docking positions on the PI3Kα catalytic core. Binding of individual nanobodies to PI3Kα induced activation or inhibition of enzyme activity and caused conformational changes that could be correlated with enzyme function. Binding of nanobody Nb3-126 to the BH domain of p85α substantially improved resolution for parts of the PI3Kα complex, and binding of nanobody Nb3-159 induced a conformation of PI3Kα that is distinct from known PI3Kα structures. The analysis of CXMS data also provided mechanistic insights into the molecular underpinning of the flexibility of PI3Kα.

Open Structural Data in Precision Medicine

Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. Computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalized pharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Oncogenic mutations ofPIK3CAlead to increased membrane recruitment driven by reorientation of the ABD, p85 and C-terminus.. [DOI: 10.1101/2022.04.05.487205]

PIK3CAencoding the phosphoinositide 3-kinase (PI3K) p110α catalytic subunit is frequently mutated in cancer, with mutations occurring widely throughout the primary sequence. The full set of mechanisms underlying how PI3Ks are activated by all oncogenic mutations on membranes are unclear. Using a synergy of biochemical assays and hydrogen deuterium exchange mass spectrometry (HDX-MS), we reveal unique regulatory mechanisms underlying PI3K activation. Engagement of p110α on membranes leads to disengagement of the ABD of p110α from the catalytic core, and the C2 domain from the iSH2 domain of the p85 regulatory subunit. PI3K activation also requires reorientation of the p110α C-terminus, with mutations that alter the inhibited conformation of the C-terminus increasing membrane binding. Mutations at the C-terminus (M1043I/L, H1047R, G1049R, and N1068KLKR) activate p110α through distinct mechanisms, with this having important implications for mutant selective inhibitor development. This work reveals unique mechanisms underlying how PI3K is activated by oncogenic mutations, and explains how double mutants can synergistically increase PI3K activity.

Structural Insights from Molecular Modeling of Isoindolin-1-One Derivatives as PI3Kγ Inhibitors against Gastric Carcinoma

The upregulation of phosphoinositol-3-kinase γ (PI3Kγ) is deemed to be positively correlated with tumor-associated-macrophage (TAM)-mediated gastric carcinoma (GC). PI3Kγ suppresses tumor necrosis factor-alpha (TNF-α) and interleukin-12 (IL-12) through activation of the AKT/mTOR pathway, which promotes the immunosuppressant phenotype of TAM. Unlike α and β isoforms, δ and γ isoforms are primarily distributed in leucocytes and macrophages. Dual inhibitors against PI3Kδ and PI3Kγ have been proven to have merits in targeting solid tumors. Furthermore, it has been found that PI3Kδ is activated by cytokines, while PI3Kγ is activated by G-protein-coupled receptors (GPCRs). This facilitates determining the functional difference between these two isoforms. For this goal, selective inhibitors would be immensely helpful. In the current manuscript, we conducted various molecular modeling studies with a series of isoindolin-1-one derivatives as potent PI3Kγ inhibitors by combining molecular docking, molecular dynamics (MD), molecular mechanics, Poisson–Boltzmann/generalized Born surface area (MM-PB/GBSA) binding free energy calculation, and three-dimensional structure–activity relationship (3D-QSAR) study. To evaluate the selectivity of γ isoform over δ, the molecular modeling studies of idelalisib analogs reported as PI3Kδ inhibitors were also investigated. The contour polyhedrons were generated from the comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) around the ligand-bound active site for both isoforms, which could emphasize plausible explanations for the physicochemical factors that affect selective ligand recognition. The binding modalities of the two isoforms using CoMFA and MD models were compared, which suggested some key differences in the molecular interactions with the ligands and could be summarized as three subsites (one affinity subsite near the C-helix and DFG and two hydrophobic subsites). In the context of the structure–activity relationship (SAR), several new compounds were designed using a fragment-substitution strategy with the aim of selectively targeting PI3Kγ. The pIC50 values of the designed compounds were predicted by the 3D-QSAR models, followed by the MM-PB/GBSA binding energy estimation. The overall findings suggest that the designed compounds have the potential to be used as PI3Kγ inhibitors with a higher binding affinity and selectivity.

Therapeutic implications of activating noncanonical PIK3CA mutations in head and neck squamous cell carcinoma

Alpelisib selectively inhibits the p110α catalytic subunit of PI3Kα and is approved for treatment of breast cancers harboring canonical PIK3CA mutations. In head and neck squamous cell carcinoma (HNSCC), 63% of PIK3CA mutations occur at canonical hotspots. The oncogenic role of the remaining 37% of PIK3CA noncanonical mutations is incompletely understood. We report a patient with HNSCC with a noncanonical PIK3CA mutation (Q75E) who exhibited a durable (12 months) response to alpelisib in a phase II clinical trial. Characterization of all 32 noncanonical PIK3CA mutations found in HNSCC using several functional and phenotypic assays revealed that the majority (69%) were activating, including Q75E. The oncogenic impact of these mutations was validated in 4 cellular models, demonstrating that their activity was lineage independent. Further, alpelisib exhibited antitumor effects in a xenograft derived from a patient with HNSCC containing an activating noncanonical PIK3CA mutation. Structural analyses revealed plausible mechanisms for the functional phenotypes of the majority of the noncanonical PIK3CA mutations. Collectively, these findings highlight the importance of characterizing the function of noncanonical PIK3CA mutations and suggest that patients with HNSCC whose tumors harbor activating noncanonical PIK3CA mutations may benefit from treatment with PI3Kα inhibitors.

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.

Bioinformatics Study of Sea Cucumber Peptides as Antibreast Cancer Through Inhibiting the Activity of Overexpressed Protein (EGFR, PI3K, AKT1, and CDK4)

Breast cancer is the most common type of cancer in women globally. The overexpressed proteins, including EGFR, PI3K, AKT1, and CDK4, have a role in the growth of breast cancer cells. The 3D peptide structure of sea cucumber Cucumaria frondosa was modeled and then docked with EGFR, PI3K, AKT1, and CDK4 proteins using AutoDock Vina software. The docking result, which has the best binding affinity value, is continued with molecular dynamics simulation. The docking results showed that all peptides bind to the active sites of the four proteins. WPPNYQW and YDWRF peptides bind to proteins with lower binding affinity values than positive controls. The four proteins were in a stable state when complexed with the WPPNYQW peptide, which was seen from the RMSD and RMSF value. PI3K-YDWRF and AKT1-YDWRF complexes are stable, characterized by high RMSD values and increased volatility in several amino acids. WPPNYQW peptide has high potential as an antibreast cancer agent because it binds to the active sites of the four proteins with low binding affinity values and stable interactions. Meanwhile, the YDWRF peptide interacts with the four proteins with low binding affinity values, but the interaction is only stable on PI3K and AKT1 proteins.

Exploring the Allosteric Territory of Protein Function

While the pervasiveness of allostery in proteins is commonly accepted, we further show the generic nature of allosteric mechanisms by analyzing here transmembrane ion-channel viroporin 3a and RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2 along with metabolic enzymes isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) implicated in cancers. Using the previously developed structure-based statistical mechanical model of allostery (SBSMMA), we share our experience in analyzing the allosteric signaling, predicting latent allosteric sites, inducing and tuning targeted allosteric response, and exploring the allosteric effects of mutations. This, yet incomplete list of phenomenology, forms a complex and unique allosteric territory of protein function, which should be thoroughly explored. We propose a generic computational framework, which not only allows one to obtain a comprehensive allosteric control over proteins but also provides an opportunity to approach the fragment-based design of allosteric effectors and drug candidates. The advantages of allosteric drugs over traditional orthosteric compounds, complemented by the emerging role of the allosteric effects of mutations in the expansion of the cancer mutational landscape and in the increased mutability of viral proteins, leave no choice besides further extensive studies of allosteric mechanisms and their biomedical implications.

SUMOylation modulates the stability and function of PI3K-p110β

Class I PI3K are heterodimers composed of a p85 regulatory subunit and a p110 catalytic subunit involved in multiple cellular functions. Recently, the catalytic subunit p110β has emerged as a class I PI3K isoform playing a major role in tumorigenesis. Understanding its regulation is crucial for the control of the PI3K pathway in p110β-driven cancers. Here we sought to evaluate the putative regulation of p110β by SUMO. Our data show that p110β can be modified by SUMO1 and SUMO2 in vitro, in transfected cells and under completely endogenous conditions, supporting the physiological relevance of p110β SUMOylation. We identify lysine residue 952, located at the activation loop of p110β, as essential for SUMOylation. SUMOylation of p110β stabilizes the protein increasing its activation of AKT which promotes cell growth and oncogenic transformation. Finally, we show that the regulatory subunit p85β counteracts the conjugation of SUMO to p110β. In summary, our data reveal that SUMO is a novel p110β interacting partner with a positive effect on the activation of the PI3K pathway.

Properties of FDA-approved small molecule phosphatidylinositol 3-kinase inhibitors prescribed for the treatment of malignancies

The discovery of the phosphatidylinositol 3-kinase (PI 3-kinase) pathway was a major advance in understanding eukaryotic signal transduction. The high frequency of PI 3-kinase pathway mutations in many cancers stimulated the development of drugs targeting these oncogenic mutants. The PI 3-kinases are divided into three classes and Class I PI 3-kinases, which catalyze the phosphorylation of phosphatidylinositol-4,5-bisphosphate (PI-4,5-P2) to generate phosphatidylinositol-3,4,5-trisphosphate (PIP3), are the main subject of this review. The class I PI 3-kinases are made up of p110α, p110β, p110δ, and p110γ catalytic subunits. These catalytic subunits are constitutively bound to regulatory subunits (p85α, p85β, p55γ, p101, and p87 proteins). The p85/p55 regulatory subunits heterodimerize with p110α or p110δ thereby forming complexes that are regulated chiefly by receptor protein-tyrosine kinases. The p101 and p87 subunits heterodimerize with p110γ to form complexes that are regulated mainly by G protein-coupled receptors (GPCRs). Complexes containing the p110β subunit are activated by receptor protein-tyrosine kinases as well as GPCRs. Following the generation of PIP3, the AKT and mTOR protein-serine/threonine kinases are activated leading to cell growth, proliferation, and survival. Like protein kinases, the PI 3-kinase domains consist of a bilobed structure connected by a hinge-linker segment. ATP and most PI 3-kinase and protein kinase inhibitors form hydrogen bonds with hinge residues. The small and large lobes of PI 3-kinases and protein kinases have a very similar three-dimensional structure called the protein kinase fold. Both PI 3-kinases and eukaryotic protein kinases possess an activation segment that begins with a DFG triad (Asp-Phe-Gly); the activation segment of protein kinases usually ends with an APE (Ala-Pro-Glu) signature while that of PI 3-kinases ends with a PFxLT (Pro-Phe-Xxx-Leu-Thr) signature. Dormant PI 3-kinases have a collapsed activation loop and active PI 3-kinases have an extended activation loop. The distance between the α-carbon atom of the DFG-D residue at the beginning of the activation loop and that of the PFxLT-F residue at the end of the activation loop in dormant PI 3-kinases is about 13 Å; this distance in active PI 3-kinases is about 18 Å. The protein kinase catalytic loop has an HRD (His-Arg-Asp) signature while that of the PI 3-kinases reverses the order with a DRH triad. Alpelisib is an orally effective FDA-approved PI 3-kinase-α inhibitor used for the treatment of breast cancer. Copanlisib, duvelisib, idelalisib, and umbralisib are PI 3-kinase-δ inhibitors that are approved for the third-line treatment of follicular lymphomas and other hematological disorders. Copanlisib is also a potent inhibitor of PI 3-kinase-α. Of the five approved drugs, all are orally bioavailable except copanlisib. Idelalisib interacts with the active conformation of PI 3-kinase-δ and is classified as a type I inhibitor. Alpelisib and copanlisib interact with inactive PI 3-kinase-α and PI 3-kinase-γ, respectively, and are classified as a type I½ antagonists. Except for umbralisib with a molecular weight of 571.5, all five drugs conform to the Lipinski rule of five for oral effectiveness. Copanlisib, however, must be given intravenously. Alpelisib and copanlisib inhibit PI 3-kinase-α, which is involved in insulin signaling, and both drugs promote insulin-resistance and produce hyperglycemia. The five FDA-approved PI 3-kinase inhibitors produce significant on-target toxicities, more so than many approved protein kinase antagonists. The development of PI 3-kinase inhibitors with fewer toxicities is an important long-term therapeutic goal.

PI3K Driver Mutations: A Biophysical Membrane-Centric Perspective

Ras activates its effectors at the membrane. Active PI3Kα and its associated kinases/phosphatases assemble at membrane regions enriched in signaling lipids. In contrast, the Raf kinase domain extends into the cytoplasm and its assembly is away from the crowded membrane surface. Our structural membrane-centric outlook underscores the spatiotemporal principles of membrane and signaling lipids, which helps clarify PI3Kα activation. Here we focus on mechanisms of activation driven by PI3Kα driver mutations, spotlighting the PI3Kα double (multiple) activating mutations. Single mutations can be potent, but double mutations are stronger: their combination is specific, a single strong driver cannot fully activate PI3K, and two weak drivers may or may not do so. In contrast, two strong drivers may successfully activate PI3K, where one, for example, H1047R, modulates membrane interactions facilitating substrate binding at the active site (km) and the other, for example, E542K and E545K, reduces the transition state barrier (ka), releasing autoinhibition by nSH2. Although mostly unidentified, weak drivers are expected to be common, so we ask here how common double mutations are likely to be and why PI3Kα with double mutations responds effectively to inhibitors. We provide a structural view of hotspot and weak driver mutations in PI3Kα activation, explain their mechanisms, compare these with mechanisms of Raf activation, and point to targeting cell-specific, chromatin-accessible, and parallel (or redundant) pathways to thwart the expected emergence of drug resistance. Collectively, our biophysical outlook delineates activation and highlights the challenges of drug resistance.

Phosphorylation and Driver Mutations in PI3Kα and PTEN Autoinhibition

PI3K and PTEN are the second and third most highly mutated proteins in cancer following only p53. Their actions oppose each other. PI3K phosphorylates signaling lipid PIP₂ to PIP₃ PTEN dephosphorylates it back. Driver mutations in both proteins accrue PIP₃ PIP₃ recruits AKT and PDK1 to the membrane, promoting cell-cycle progression. Here we review phosphorylation events and mutations in autoinhibition in PI3K and PTEN from the structural standpoint. Our purpose is to clarify how they control the autoinhibited states. In autoinhibition, a segment or a subunit of the protein occludes its functional site. Protein-protein interfaces are often only marginally stable, making them sensitive to changes in conditions in living cells. Phosphorylation can stabilize or destabilize the interfaces. Driver mutations commonly destabilize them. In analogy to "passenger mutations," we coin "passenger phosphorylation" to emphasize that the presence of a phosphorylation recognition sequence logo does not necessarily imply function. Rather, it may simply reflect a statistical occurrence. In both PI3K and PTEN, autoinhibiting phosphorylation events are observed in the occluding "piece." In PI3Kα, the "piece" is the p85α subunit. In PTEN, it is the C-terminal segment. In both enzymes the stabilized interface covers the domain that attaches to the membrane. Driver mutations that trigger rotation of the occluding piece or its deletion prompt activation. To date, both enzymes lack specific, potent drugs. We discuss the implications of detailed structural and mechanistic insight into oncogenic activation and how it can advance allosteric precision oncology.