Biology subjects

Nussinov, R.

Publications and source records attributed to Nussinov, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-Cell Mapping of Malignant Signaling Networks Guides Drug Combinations

Single-cell breast cancer atlases reveal malignant, immune, and stromal diversity; however, how the recurrent signaling pathways drive untreated malignant-cell states and could inform combination therapy remains unclear. Here, we analyzed 15,753 malignant cells from untreated primary breast tumors using a cell-resolved network framework. Individual transcriptomes were projected onto a protein-protein interaction network, partitioned into Leiden communities, and annotated by pathway enrichment. Pathway recurrence was evaluated against matched null models preserving community size, protein-network degree, and gene detection rate. Before null correction, recurrent pathways included PI3K/AKT, MAPK, JAK/STAT, and HIF-1 (hypoxia-inducible factor 1) signaling. After correction, HIF-1 emerged as the dominant recurrent signal across patients, indicating convergence of diverse upstream pathways on a shared hypoxia- and stress-adaptive malignant-cell program. The recurrent JAK/STAT, cAMP, glucagon, oxytocin, and thyroid hormone signaling suggest inflammatory, metabolic, and endocrine crosstalk. These findings support rational drug combinations targeting HIF-1 together with upstream PI3K/AKT/mTOR, MAPK, or JAK/STAT signaling.

bioinformatics↗

bioRxiv2026

The structural basis of RanGAP1 regulation and catalysis in nuclear transport

RanGAP1 promotes GTP hydrolysis of nuclear pore complex (NPC) transport complexes at the cytoplasmic face. A disordered linker connects its catalytic GAP domain to the C-terminal sumoylation domain, anchoring into NPCs cytoplasmic filaments. This arrangement raises the question of how these distinct functions are coordinated within a crowded cellular environment. Using atomistic molecular dynamics simulations, we show that RanGAP1 adopts an autoinhibited conformation, where the C-terminal domain masks the catalytic GAP domain. Sumoylation allosterically relieves this autoinhibition, enabling GTP-bound Ran access to the GAP domain. In the cytosol, Ran-GTP/RanBP1 can bind a less populated open conformation of RanGAP1, providing a backup mechanism for GTP hydrolysis in Ran. Importantly, we observe that Arg191 of human RanGAP1 inserts into the GTP-binding pocket of Ran and directly interacts with the {gamma}-phosphate, consistent with a canonical arginine finger. This observation contrasts with earlier models derived from yeast RanGAP and suggests that human RanGAP1 may follow a catalytic mechanism similar to classical small GTPase regulators like NF1. Together, these findings provide a framework of RanGAP1, linking autoinhibition, sumoylation, spatial organization at the NPC, and the catalytic mechanism. They also highlight how conformational regulation and post-translational modification coordinate efficient GTP hydrolysis in Ran during nuclear transport.

biophysics↗

bioRxiv2026

How Functional Variants Reconfigure the Rac2 Conformational Landscape

Rac2, a member of the Rho family of small GTPases, is a fundamental regulator of essential cellular processes. Pathogenic substitutions near and within the Switch II region, specifically D57N and E62K, have been implicated in oncogenesis and immunodeficiency. Despite their proximity, D57N is characterized as a loss-of-function mutation, while E62K is a constitutively active, gain-of-function mutation. In this study, we addressed several critical questions: (i) the structural basis of their altered cellular functions, (ii) how these variants rearrange the conformational ensemble, and (iii) the subsequent impact on cellular signaling networks. Using molecular dynamics (MD) simulations, we characterized the conformational dynamics of these Rac2 variants in GDP- and GTP-bound states. Our results demonstrate that Rac2D57N predominantly adopts an inactive-like conformation, regardless of the bound nucleotide. GTP binding is insufficient to induce the canonical active state in this mutant. Conversely, Rac2E62K maintains a nucleotide-dependent toggle, appearing inactive when bound to GDP and active when bound to GTP. Additionally, we examined the assembly of these variants with the regulator p50-RhoGAP. In the wild-type complex, GAP binding facilitates a shift toward a near-transition-state ensemble. In stark contrast, both the D57N and E62K complexes remain sequestered in a ground-ON state configuration, effectively trapping the GTPase and hindering GAP-mediated hydrolysis. While both Rac2 mutations result in immune system dysfunction, the underlying mechanisms are opposite: inactive vs. overactive. This work provides a high-resolution, mechanistic framework for understanding how localized perturbations in the switch loops landscape dictate systemic cellular outcomes.

biophysics↗

bioRxiv2025

Cellular Mechanisms Underlying Melanoma Brain Metastasis

Brain metastasis is a major contributor to melanoma-related mortality, arising from both genomic alterations and dynamic adaptations to the brain microenvironment. Tumor cells must cross the blood-brain barrier and exploit brain-specific signaling and metabolic landscapes to establish metastases. Brain metastases display molecular and phenotypic programs distinct from other organs, reflecting pre-existing and acquired mutations during progression. We analyzed primary melanoma, metastatic melanoma, and metastatic brain tumors genomic datasets to identify mutated proteins and signaling pathways that are common to or distinct among these tumor types. Our comprehensive computational analyses uncovered key pathways and proteins associated with brain metastasis. Brain metastases exhibit unique mutational landscapes and convergent alterations in neurotrophin, MAPK, and PI3K/AKT signaling compared with primary and metastatic melanoma. Proteins especially frequent in brain metastases pathways support survival, proliferation, and adaptation in the brain microenvironment. Pharmacology-wise, rational strategies such as combining c-KIT and VEGFR inhibitors can suppress converging oncogenic pathways and mitigate resistance in advanced melanoma. Co-targeting neurotrophin receptors with MAPK pathway members, particularly in combination with BRAF inhibitors, appears a promising approach for treating melanoma brain metastases. Our findings underscore the molecular heterogeneity of melanoma brain metastases, shaped by interconnected signaling networks, and reveal therapeutic targets that may diverge from those in other metastatic sites.

bioinformatics↗

bioRxiv2025

The mechanism of oncogenic PI3K lipid kinase variants at the membrane and their cryptic pockets

Cancer-prone alleles exhibit single hotspot mutations. However, the combination of a cancer hotspot and a weak or moderate mutation (the one-two punch hypothesis) produces same-allele double variants with a significantly different and potentially graded clinical phenotypic spectrum. Oncogenic PI3K variants, which are also associated with benign tumors and neurodevelopmental disorders, offer statistical support for this model. Using atomistic molecular dynamics (MD) simulations, we revealed that PI3K variants with single and double mutations exhibit expanded conformational profiles. Double mutations significantly shift the conformational ensembles toward the active form--a more pronounced effect than a single mutation. These double mutants facilitate nSH2 release, iSH2 shift, and A-loop protrusion in solution, promoting PIP2 substrate recruitment at the membrane. We discovered that observable, potentially drug-targetable cryptic pockets are PI3K mutation-specific. Ab initio discovery of these pockets through simulations is essential for AI-aided virtual drug screening. A key challenge is that a single drug is often ineffective against PI3K variants due to their diverse conformational spectra. To address this, we propose a conformational selection strategy involving a combination of allosteric drugs for variants with graded conformational spectra, particularly those with strong double mutations; we identified such potentially targetable cryptic pockets in double mutants conformers.

biophysics↗

bioRxiv2025

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 {beta}3-C 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. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/640857v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@cbdc16org.highwire.dtl.DTLVardef@1de54deorg.highwire.dtl.DTLVardef@195ed04org.highwire.dtl.DTLVardef@1fbc860_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2025

ERK Allosteric Activation: The Importance of Two Ordered Phosphorylation Events

ERK, a coveted proliferation drug target, is a pivotal kinase in the Ras/ERK signaling cascade. Despite this, crucial questions about its activation have not been fully explored on the foundational, conformational level. Such questions include (i) Why ERKs activation demands dual phosphorylation; (ii) What is the role of each phosphorylation site in the activation loop; and (iii) Exactly how the (ordered) phosphorylation steps affect the conformational ensembles of the activation loop, their propensities and restriction to a narrower range favoring ERKs catalytic action. Here we used explicit molecular dynamics simulations to study ERKs stability and the conformational changes in different stages along the activation process. The initial monophosphorylation event elongates the activation loop to enable the successive phosphorylations, which reintroduce stability/compactness through newly formed salt bridges. The interactions formed by the monophosphorylation are site-dependent, with threonines phosphorylation presenting stronger electrostatic interactions compared to tyrosines. Dual phosphorylated ERKs revealed a compact kinase structure which allows the HRD catalytic motif to stabilize the ATP. We further observe that the hinge and the homodimerization binding site responded to a tri-state signaling code based solely on the phosphorylation degree (unphosphorylated, monophosphorylated, dual phosphorylated) of the activation loop, confirming that the activation loop can allosterically influence distant regions. Last, our findings indicate that threonine phosphorylation as the second step is necessary for ERK to become effectively activated and that activation depends on the phosphorylation order. Collectively, we offer ERKs dual allosteric phosphorylation code in activation and explain why the phosphorylation site order is crucial.

molecular biology↗

bioRxiv2024

Anticancer Target Combinations: Network-Informed Signaling-Based Approach to Discovery

While anticancer drug discovery has seen dramatic innovations and successes, sequential single therapies are time-limited by resistance, and combinatorial strategies have been lagging. The number of possible drug combinations is vast. To select drug combinations the oncologist requires knowledge of the optimal combination of proteins to co-target. Currently, combinations that the oncologist considers are primarily from empirical observations and clinical praxis. Our aim is to develop a signaling-based method to discover optimal proteins for the oncologist to co-target with drug combinations, and test it on available, patient-derived data. To temper the expected resistance to single drug regimen, we offer a concept-based stratified pipeline aimed at selecting co-targets for drug combinations. Our strategy is unique in its co-target selection being based on signaling pathways. This is significant since in cancer, drug resistance commonly bypasses blocked proteins by wielding alternative, or complementary, routes to execute cell proliferation. Our network-informed signaling-based approach harnesses advanced network concepts and metrics, and our compiled, tissue-specific co-existing mutations. Co-existing driver mutations are common in resistance. Thus, to mimic cancer and counter drug resistance scenarios, our pipeline seeks co-targets that when targeted by drug combinations, can shut off cancers modus operandi. That is, its parallel or complementary signaling pathways would be blocked. Rotating through combinations could further lessen emerging resistance. We applied it to patient-derived breast and colorectal ESR1|PIK3CA and BRAF|PIK3CA subnetworks. Consistently, in breast cancer, our results suggest co-targeting proteins from the ESR1|PIK3CA subnetwork with an alpelisib-LJM716 combination. In colorectal cancer, they co-target BRAF|PIK3CA with alpelisib, cetuximab, and encorafenib combination. Collectively, our pipelines results are promising, and validated by patient-based xenografts. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/617918v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@81dc11org.highwire.dtl.DTLVardef@197012dorg.highwire.dtl.DTLVardef@ce3853org.highwire.dtl.DTLVardef@d3ec3a_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

mTOR variants activation discovers PI3K-like cryptic pocket, expanding allosteric, mutant-selective inhibitor designs

mTOR plays a crucial role in PI3K/AKT/mTOR signaling. We hypothesized that mTOR activation mechanisms driving oncogenesis can advise effective therapeutic designs. To test this, we combined cancer genomic analysis with extensive molecular dynamics simulations of mTOR oncogenic variants. We observed that conformational changes within mTOR kinase domain are associated with multiple mutational activation events. The mutations disturb the -packing formed by the kAL, k3, k9, k9b, and k10 helices in the kinase domain creating cryptic pocket. Its opening correlates with opening of the catalytic cleft, including active site residues realignment, favoring catalysis. The cryptic pocket created by disrupted -packing coincides with the allosteric pocket in PI3K can be harmoniously fitted by the PI3K allosteric inhibitor RLY-2608, suggesting that analogous drugs designed based on RLY-2608 can restore the packed -structure, resulting in mTOR inactive conformation. Our results exemplify that knowledge of detailed kinase activation mechanisms can inform innovative allosteric inhibitor development.

cancer biology↗

bioRxiv2024

Co-occurring Mutations in Different Genes Can Fuel Oncogenic Signaling and Serve as Metastatic Tumor Markers

Interrogation of big genomic data and integration with large-scale protein-protein interaction networks and pathways, can provide deep patterns that are rare- yet can prompt dramatic phenotypic alterations and serve as clinical signatures. Mapping cancer-specific co-occurring mutation-pair signatures, in primary and metastatic tumors, is indispensable in precision oncology. The additivity of co-occurring driver mutations in different genes (in trans) can lead to powerful proliferation signals. Co-occurring rare in trans combinations can serve as metastasis markers; excluded combinations may indicate candidates for oncogene-induced senescence (OIS), a tumor-suppressive mechanism. Our statistical framework of the pan-cancer mutation profiles of [~]60,000 tumor sequences from the TCGA and AACR GENIE databases, identified 3424 statistically significant different double mutations in non-redundant pathways, that is, have different downstream targets that may promote specific cancers through single or multiple pathways. Our analysis indicates that they are mostly in primary tumors. We list actionable in trans mutations for 2385 metastatic tumors and provide co-occurrence trees of metastatic breast- cancer markers. This innovative work clarifies the mechanistic conceptual basis and establishes the first of its kind tool for identifying and predicting metastasis. Crucially, when coupled with their proliferative functions and pathways, and linked with drugs, it could provide an invaluable metastasis-targeting resource.

systems biology↗

bioRxiv2023

Cell cycle progression mechanisms: slower cyclin-D/CDK4 activation and faster cyclin-E/CDK2

Dysregulation of cyclin-dependent kinases (CDKs) impacts cell proliferation, driving cancer. Here, we ask why the cyclin-D/CDK4 complex governs cell cycle progression through the longer G1 phase, whereas cyclin-E/CDK2 regulates the short G1/S phase transition. We consider the experimentally established high-level bursting of cyclin-E, and sustained duration of elevated cyclin-D expression in the cell, available experimental cellular and structural data, and comprehensive explicit solvent molecular dynamics simulations to provide the mechanistic foundation of the distinct activation scenarios of cyclin-D/CDK4 and cyclin-E/CDK2 in the G1 phase and G1/S transition of the cell cycle, respectively. These lead us to propose slower activation of cyclin-D/CDK4 and rapid activation of cyclin-E/CDK2. Importantly, we determine the mechanisms through which this occurs, offering innovative CDK4 drug design considerations. Our insightful mechanistic work addresses the compelling cell cycle regulation question and illuminates the distinct activation speeds in the G1 versus G1/S phases, which are crucial for cell function. StatementOur work provides an unprecedented mechanistic understanding of the distinct activation scenarios of cyclin-D/CDK4 and cyclin-E/CDK2 in cell cycle regulation, underpinning the slower activation of cyclin-D/CDK4 in the more extended G1 phase and the rapid activation of cyclin-E/CDK2 in the brief G1/S transition. Our findings address a long-standing question in cell cycle biology and suggest the design of targeted CDK4 inhibitors.

molecular biology↗

bioRxiv2023

Molecular Mechanism of Regulation of RhoA GTPase by Phosphorylation of RhoGDI

Rho-specific guanine dissociation inhibitors (RhoGDIs) play a crucial role in the regulation of Rho family GTPases. They act as negative regulators that prevent the activation of Rho GTPases by forming complexes with the inactive GDP-bound state of GTPase. Release of Rho GTPase from the RhoGDI-bound complex is necessary for Rho GTPase activation. Biochemical studies provide evidence of a "phosphorylation code", where phosphorylation of some specific residues of RhoGDI selectively releases its GTPase partner (RhoA, Rac1, Cdc42 etc.). This work attempts to understand the molecular mechanism behind this phosphorylation code. Using several microseconds long atomistic molecular dynamics (MD) simulations of the wild-type and phosphorylated states of the RhoA-RhoGDI complex, we propose a molecular-interaction-based mechanistic model for the dissociation of the complex. Phosphorylation induces major structural changes, particularly in the positively charged polybasic region (PBR) of RhoA and the negatively charged N-terminal region of RhoGDI that contribute most to the binding affinity. MM-PBSA binding free energy calculations show a significant weakening of interaction on phosphorylation at the RhoA-specific site of RhoGDI. In contrast, phosphorylation at a Rac1-specific site leads to the strengthening of the interaction confirming the presence of a phosphorylation code. RhoA-specific phosphorylation leads to a reduction in the number of contacts between the PBR of RhoA and the N-terminal region of RhoGDI, which manifests reduction of the binding affinity. Using hydrogen bond occupancy analysis and energetic perturbation network, we propose a mechanistic model for the allosteric response, i.e., long range signal propagation from the site of phosphorylation to the PBR and buried geranylgeranyl group in the form of rearrangement and rewiring of hydrogen bonds and salt bridges. Our results highlight the crucial role of specific electrostatic interactions in manifestation of the phosphorylation code.

biophysics↗

bioRxiv2023

Neurodevelopmental disorders and cancer networks share pathways; but differ in mechanisms, signaling strength, and outcome

Neurodevelopmental disorders (NDDs) and cancer are connected, with immunity as their common factor. Their clinical presentations differ; however, individuals with NDDs are more likely to acquire cancer. Schizophrenia patients have [~]50% increased risk; autistic individuals also face an increased cancer likelihood. NDDs are associated with specific brain cell types at specific locations, emerging at certain developmental time windows during brain evolution. Their related mutations are germline; cancer mutations are sporadic, emerging during life. At the same time, NDDs and cancer share proteins, pathways, and mutations. Here we ask exactly which features they share, and how despite their commonality, they differ in outcomes. Our pioneering bioinformatics exploration of the mutations, reconstructed disease-specific networks, pathways, and transcriptome profiles of autism spectrum disorder (ASD) and cancers, points to elevated signal strength in pathways related to proliferation in cancer, and differentiation in ASD. Signaling strength, not the activating mutation, is the key factor in deciding cancer versus NDDs.

systems biology↗

bioRxiv2023

How PTEN mutations degrade function at the membrane and life expectancy of carriers of mutations in the human brain

PTEN dysfunction, caused by loss of lipid phosphatase activity or deletion, promotes pathologies, cancer, benign tumors, and neurodevelopmental disorders (NDDs). Despite efforts, exactly how the mutations trigger distinct phenotypic outcomes, cancer or NDD, has been puzzling. It has also been unclear how to distinguish between mutations harbored by isoforms, are they cancer or NDDs-related. Here we address both. We demonstrate that PTEN mutations differentially allosterically bias P-loop dynamics and its connection to the catalytic site, affecting catalytic activity. NDD-related mutations are likely to sample conformations present in the wild-type, while sampled conformations sheltering cancer-related hotspots favor catalysis-prone conformations, suggesting that NDD mutations are weaker. Analysis of isoform expression data indicates that if the transcript has NDD-related mutations, alone or in combination with cancer hotspots, there is high prenatal expression. If no mutations within the measured days, low expression levels. Cancer mutations promote stronger signaling and cell proliferation; NDDs are weaker, influencing brain cell differentiation. Further, exon 5 is impacted by NDD or non-NDD mutations, while exon 7 is exclusively impacted by NDD mutations. Our comprehensive conformational and genomic analysis helps discover how same allele mutations can foster different clinical manifestations and uncovers correlations of splicing isoform expression to life expectancy.

biophysics↗

bioRxiv2022

Comprehensive characterization of multi-omic landscapes between gut-microbiota metabolites and the G-protein-coupled receptors in Alzheimer's disease

Accumulating evidence suggests that gut-microbiota metabolites contribute to human disease pathophysiology, yet the host receptors that sense these metabolites are largely unknown. Here, we developed a systems pharmacogenomics framework that integrates machine learning (ML), AlphaFold2-derived structural pharmacology, and multi-omics to identify disease-relevant metabolites derived from gut-microbiota with non-olfactory G-protein-coupled receptors (GPCRome). Specifically, we evaluated 1.68 million metabolite-protein pairs connecting 408 human GPCRs and 516 gut metabolites using an Extra Trees algorithm-improved structural pharmacology strategy. Using genetics-derived Mendelian randomization and multi-omics (including transcriptomic and proteomic) analyses, we identified likely causal GPCR targets (C3AR, FPR1, GALR1 and TAS2R60) in Alzheimers disease (AD). Using three-dimensional structural fingerprint analysis of the metabolite-GPCR complexome, we identified over 60% of the allosteric pockets of orphan GPCR models for gut metabolites in the GPCRome, including AD-related orphan GPCRs (GPR27, GPR34, and GPR84). We additionally identified the potential targets (e.g., C3AR) of two AD-related metabolites (3-hydroxybutyric acid and Indole-3-pyruvic acid) and four metabolites from AD-related bacterium Eubacterium rectale, and also showed that tridecylic acid is a candidate ligand for orphan GPR84 in AD. In summary, this study presents a systems pharmacogenomics approach that serves to uncover the GPCR molecular targets of gut microbiota in AD and likely many other human diseases if broadly applied.

systems biology↗

bioRxiv2021

The mechanism of activation of monomeric B-Raf V600E

Oncogenic mutations in the serine/threonine kinase B-Raf, particularly the V600E mutation, are frequent in cancer, making it a major drug target. Although much is known about B-Rafs active and inactive states, questions remain about the mechanism by which the protein changes between these two states. Here, we utilize molecular dynamics to investigate both wild-type and V600E B-Raf to gain mechanistic insights into the impact of the Val to Glu mutation. The results show that the wild-type and mutant follow similar activation pathways involving an extension of the activation loop and an inward motion of the C-helix. The V600E mutation, however, destabilizes the inactive state by disrupting hydrophobic interactions present in the wild-type structure while the active state is stabilized through the formation of a salt bridge between Glu600 and Lys507. Additionally, when the activation loop is extended, the C-helix is able to move between an inward and outward orientation as long as the DFG motif adopts a specific orientation. In that orientation Phe595 rotates away from the C-helix, allowing the formation of a salt bridge between Lys483 and Glu501. These mechanistic insights have implications for the development of new Raf inhibitors.

cancer biology↗

bioRxiv2021

Discovery of Latent Drivers from Double Mutations in Pan-Cancer Data Reveal their Clinical Impact

Background Transforming patient-specific molecular data into clinical decisions is fundamental to personalized medicine. Despite massive advancements in cancer genomics, to date driver mutations whose frequencies are low, and their observable transformation potential is minor have escaped identification. Yet, when paired with other mutations in cis, such latent driver mutations can drive cancer. Here, we discover potential latent driver double mutations. Method We applied a statistical approach to identify significantly co-occurring mutations in the pan-cancer data of mutation profiles of [~]80,000 tumor sequences from the TCGA and AACR GENIE databases. The components of same gene doublets were assessed as potential latent drivers. We merged the analysis of the significant double mutations with drug response data of cell lines and patient derived xenografts (PDXs). This allowed us to link the potential impact of double mutations to clinical information and discover signatures for some cancer types. Results Our comprehensive statistical analysis identified 228 same gene double mutations of which 113 mutations are cataloged as latent drivers. Oncogenic activation of a protein can be through either single or multiple independent mechanisms of action. Combinations of a driver mutation with either a driver, a weak driver, or a strong latent driver have the potential of a single gene leading to a fully activated state and high drug response rate. Tumor suppressors require higher mutational load to coincide with double mutations compared to oncogenes which implies their relative robustness to losing their functions. Evaluation of the response of cell lines and patient-derived xenograft data to drug treatment indicate that in certain genes double mutations can increase oncogenic activity, hence a better drug response (e.g. in PIK3CA), or they can promote resistance to the drugs (e.g. in EGFR). Conclusion Our comprehensive analysis of same allele double mutations in cancer genome landscapes emphasizes that interrogation of big genomic data and integration with the results of large-scale small-molecule sensitivity data can provide deep patterns that are rare; but can still result in dramatic phenotypic alterations, and provide clinical signatures for some cancer types.

systems biology↗

bioRxiv2021

The mechanism of full activation of tumor suppressor PTEN at the phosphatidylinositol-enriched membrane

Tumor suppressor PTEN, the second most highly mutated protein in cancer, dephosphorylates signaling lipid PIP3 produced by PI3Ks. Excess PIP3 promotes cell proliferation. The mechanism at the membrane of this pivotal phosphatase is unknown hindering drug discovery. Exploiting explicit solvent simulations, we tracked full-length PTEN trafficking from the cytosol to the membrane. We observed its interaction with membranes composed of zwitterionic phosphatidylcholine, anionic phosphatidylserine, and phosphoinositides, including signaling lipids PIP2 and PIP3. We tracked its moving away from the zwitterionic and getting absorbed onto anionic membrane that harbors PIP3. We followed it localizing on microdomains enriched in signaling lipids, as PI3K does, and observed PIP3 allosterically unfolding the N-terminal PIP2 binding domain, positioning it favorably for the polybasic motif interaction with PIP2. Finally, we determined PTEN catalytic action at the membrane, all in line with experimental observations, deciphering the mechanisms of how PTEN anchors to the membrane and restrains cancer.

molecular biology↗