Concurrent inhibition of oncogenic and wild-type RAS-GTP for cancer therapy.

RAS oncogenes (collectively NRAS, HRAS and especially KRAS) are among the most frequently mutated genes in cancer, with common driver mutations occurring at codons 12, 13 and 611. Small molecule inhibitors of the KRAS(G12C) oncoprotein have demonstrated clinical efficacy in patients with multiple cancer types and have led to regulatory approvals for the treatment of non-small cell lung cancer2,3. Nevertheless, KRASG12C mutations account for only around 15% of KRAS-mutated cancers4,5, and there are no approved KRAS inhibitors for the majority of patients with tumours containing other common KRAS mutations. Here we describe RMC-7977, a reversible, tri-complex RAS inhibitor with broad-spectrum activity for the active state of both mutant and wild-type KRAS, NRAS and HRAS variants (a RAS(ON) multi-selective inhibitor). Preclinically, RMC-7977 demonstrated potent activity against RAS-addicted tumours carrying various RAS genotypes, particularly against cancer models with KRAS codon 12 mutations (KRASG12X). Treatment with RMC-7977 led to tumour regression and was well tolerated in diverse RAS-addicted preclinical cancer models. Additionally, RMC-7977 inhibited the growth of KRASG12C cancer models that are resistant to KRAS(G12C) inhibitors owing to restoration of RAS pathway signalling. Thus, RAS(ON) multi-selective inhibitors can target multiple oncogenic and wild-type RAS isoforms and have the potential to treat a wide range of RAS-addicted cancers with high unmet clinical need. A related RAS(ON) multi-selective inhibitor, RMC-6236, is currently under clinical evaluation in patients with KRAS-mutant solid tumours (ClinicalTrials.gov identifier: NCT05379985).

Selective inhibitors of mTORC1 activate 4EBP1 and suppress tumor growth.

The clinical benefits of pan-mTOR active-site inhibitors are limited by toxicity and relief of feedback inhibition of receptor expression. To address these limitations, we designed a series of compounds that selectively inhibit mTORC1 and not mTORC2. These 'bi-steric inhibitors' comprise a rapamycin-like core moiety covalently linked to an mTOR active-site inhibitor. Structural modification of these components modulated their affinities for their binding sites on mTOR and the selectivity of the bi-steric compound. mTORC1-selective compounds potently inhibited 4EBP1 phosphorylation and caused regressions of breast cancer xenografts. Inhibition of 4EBP1 phosphorylation was sufficient to block cancer cell growth and was necessary for maximal antitumor activity. At mTORC1-selective doses, these compounds do not alter glucose tolerance, nor do they relieve AKT-dependent feedback inhibition of HER3. Thus, in preclinical models, selective inhibitors of mTORC1 potently inhibit tumor growth while causing less toxicity and receptor reactivation as compared to pan-mTOR inhibitors.

Interlayer spacing in pillared and grafted MCM-22 type silicas: density functional theory analysis versus experiment.

Pillaring of synthetic layered crystalline silicates and aluminosilicates provides a strategy to enhance their adsorption and separation performance, and can facilitate the understanding of such behavior in more complex natural clays. We perform the first-principles density functional theory calculations for the pillaring of the pure silica polymorph of an MCM-22 type molecular sieve. Starting with a precursor material MCM-22P with fully hydroxylated layers, a pillaring agent, (EtO)3SiR, can react with hydroxyl groups (-OH) on adjacent internal surfaces, 2(-OH) + (EtO)3SiR + H2O → (-O)2SiOHR + 3EtOH, to form a pillar bridging these surfaces, or with a single hydroxyl, -OH + (EtO)3SiR + 2H2O → (-O)Si(OH)2R + 3EtOH, grafting to one surface. For computational efficiency, we replace the experimental organic ligand, R, by a methyl group. We find that the interlayer spacing in MCM-22 is reduced by 2.66 Å relative to weakly bound layers in the precursor MCM-22P. Including (-O)2SiR bridges for 50% (100%) of the hydroxyl sites in MCM-22P increases the interlayer spacing relative to MCM-22 by 2.52 Å (2.46 Å). For comparison, we also analyze the system where all -OH groups in MCM-22P are replaced by non-bridging grafted (-O)Si(OH)2R which results in a smaller interlayer spacing expansion of 2.17 Å relative to MCM-22. Our results for the interlayer spacing in the pillared materials are compatible with experimental observations for a similar MCM-22 type material with low Al content (Si : Al = 51 : 1) of an expansion relative to MCM-22 of roughly 2.8 Å and 2.5 Å from our x-ray diffraction and scanning transmission electron microscopy analyses, respectively. The latter analysis reveals significant variation in individual layer spacings.

Fluorine spillover for ceria- vs silica-supported palladium nanoparticles: A MD study using machine learning potentials.

Supported metallic nanoparticles play a central role in catalysis. However, predictive modeling is particularly challenging due to the structural and dynamic complexity of the nanoparticle and its interface with the support, given that the sizes of interest are often well beyond those accessible via traditional ab initio methods. With recent advances in machine learning, it is now feasible to perform MD simulations with potentials retaining near-density-functional theory (DFT) accuracy, which can elucidate the growth and relaxation of supported metal nanoparticles, as well as reactions on those catalysts, at temperatures and time scales approaching those relevant to experiments. Furthermore, the surfaces of the support materials can also be modeled realistically through simulated annealing to include effects such as defects and amorphous structures. We study the adsorption of fluorine atoms on ceria and silica supported palladium nanoparticles using machine learning potential trained by DFT data using the DeePMD framework. We show defects on ceria and Pd/ceria interfaces are crucial for the initial adsorption of fluorine, while the interplay between Pd and ceria and the reverse oxygen migration from ceria to Pd control spillover of fluorine from Pd to ceria at later stages. In contrast, silica supports do not induce fluorine spillover from Pd particles.

Nucleation-mediated reshaping of facetted metallic nanocrystals: Breakdown of the classical free energy picture.

Shape stability is key to avoiding degradation of performance for metallic nanocrystals synthesized with facetted non-equilibrium shapes to optimize properties for catalysis, plasmonics, and so on. Reshaping of facetted nanocrystals is controlled by the surface diffusion-mediated nucleation and growth of new outer layers of atoms. Kinetic Monte Carlo (KMC) simulation of a realistic stochastic atomistic-level model is applied to precisely track the reshaping of Pd octahedra and nanocubes. Unexpectedly, separate constrained equilibrium Monte Carlo analysis of the free energy profile during reshaping reveals a fundamental failure of the classical nucleation theory (CNT) prediction for the reshaping barrier and rate. Why? Nucleation barriers can be relatively low for these processes, so the system is not locally equilibrated before crossing the barrier, as assumed in CNT. This claim is supported by an analysis of a first-passage problem for reshaping within a master equation framework for the model that reasonably captures the behavior in KMC simulations.

Molecular interactions in diffusion-controlled aldol condensation with mesoporous silica nanoparticles.

The aldol reaction of p-nitrobenzaldehyde in amino-catalyzed mesoporous silica nanoparticles (MSN) has revealed varying catalytic activity with the size of the pores of MSN. The pore size dependence related to the reactivity indicates that the diffusion process is important. A detailed molecular-level analysis for understanding diffusion requires assessment of the noncovalent interactions of the molecular species involved in the aldol reaction with each other, with the solvent, and with key functional groups on the pore surface. Such an analysis is presented here based upon the effective fragment potential (EFP). The EFP method can calculate the intermolecular interactions, decomposed into Coulomb, polarization, dispersion, exchange-repulsion, and charge-transfer interactions. In this study, the potential energy surfaces corresponding to each intermolecular interaction are analyzed for homo- and hetero-dimers with various configurations. The monomers that compose dimers are five molecules such as p-nitrobenzaldehyde, acetone, n-hexane, propylamine, and silanol. The results illustrate that the dispersion interaction is crucial in most dimers.

Reaction processes at step edges on S-decorated Cu(111) and Ag(111) surfaces: MD analysis utilizing machine learning derived potentials.

A variety of complexation, reconstruction, and sulfide formation processes can occur at step edges on the {111} surfaces of coinage metals (M) in the presence of adsorbed S under ultra-high vacuum conditions. Given the cooperative many-atom nature of these reaction processes, Molecular Dynamics (MD) simulation of the associated dynamics is instructive. However, only quite restricted Density Functional Theory (DFT)-level ab initio MD is viable. Thus, for M = Ag and Cu, we instead utilize the DeePMD framework to develop machine-learning derived potentials, retaining near-DFT accuracy for the M-S systems, which should have broad applicability. These potentials are validated by comparison with DFT predictions for various key quantities related to the energetics of S on M(111) surfaces. The potentials are then utilized to perform extensive MD simulations elucidating the above diverse restructuring and reaction processes at step edges. Key observations from MD simulations include the formation of small metal-sulfur complexes, especially MS2; development of a local reconstruction at A-steps featuring an S-decorated {100} motif; and 3D sulfide formation. Additional analysis yields further information on the kinetics for metal-sulfur complex formation, where these complexes can strongly enhance surface mass transport, and on the propensity for sulfide formation.

Rotational and translational diffusion of liquid n-hexane: EFP-based molecular dynamics analysis.

Molecular Dynamics (MD) simulations based on the Effective Fragment Potential (EFP) method are utilized to provide a comprehensive assessment of diffusion in liquid n-hexane. We decompose translational diffusion into components along and orthogonal to the long axis of the molecule. Rotational diffusion is decomposed into tumbling and spinning motions about this axis. Our analysis yields four corresponding diffusion coefficients which are related to diagonal entries in the complete 6 × 6 diffusion tensor accounting for the three rotational and three translational degrees of freedom and for the potential coupling between them. However, coupling between different degrees of freedom is expected to be minimal for a natural choice of the molecular body-fixed axis, so then off-diagonal entries in the tensor are negligible. This expectation is supported by a hydrodynamic analysis of the diffusion tensor which treats the liquid surrounding the molecule being tracked as a viscous continuum. Thus, the EFP MD analysis provides a comprehensive characterization of diffusion and also reveals expected shortcomings of the hydrodynamic treatment, particularly for rotational diffusion, when applied to neat liquids.

Thrombus Migration and Fragmentation After Intravenous Alteplase Treatment: The INTERRSeCT Study.

BACKGROUND AND PURPOSE: There is interest in what happens over time to the thrombus after intravenous alteplase. We study the effect of alteplase on thrombus structure and its impact on clinical outcome in patients with acute stroke. METHODS: Intravenous alteplase treated stroke patients with intracranial internal carotid artery or middle cerebral artery occlusion identified on baseline computed tomography angiography and with follow-up vascular imaging (computed tomography angiography or first run of angiography before endovascular therapy) were enrolled from INTERRSeCT study (Identifying New Approaches to Optimize Thrombus Characterization for Predicting Early Recanalization and Reperfusion With IV Alteplase and Other Treatments Using Serial CT Angiography). Thrombus movement after intravenous alteplase was classified into complete recanalization, thrombus migration, thrombus fragmentation, and no change. Thrombus migration was diagnosed when occlusion site moved distally and graded according to degrees of thrombus movement (grade 0-3). Thrombus fragmentation was diagnosed when a new distal occlusion in addition to the primary occlusion was identified on follow-up imaging. The association between thrombus movement and clinical outcome was also evaluated. RESULTS: Among 427 patients in this study, thrombus movement was seen in 54% with a median time of 123 minutes from alteplase administration to follow-up imaging, and sub-classified as marked (thrombus migration grade 2-3 + complete recanalization; 27%) and mild to moderate thrombus movement (thrombus fragmentation + thrombus migration grade 0-1; 27%). In patients with proximal M1/internal carotid artery occlusion, marked thrombus movement was associated with a higher rate of good outcome (90-day modified Rankin Scale, 0-2) compared with mild to moderate movement (52% versus 27%; adjusted odds ratio, 5.64 [95% CI, 1.72-20.10]). No difference was seen in outcomes between mild to moderate thrombus movement and no change. In M1 distal/M2 occlusion, marked thrombus movement was associated with improved 90-day good outcome compared with no change (70% versus 56%; adjusted odds ratio, 2.54 [95% CI, 1.21-5.51]). CONCLUSIONS: Early thrombus movement is common after intravenous alteplase. Marked thrombus migration leads to good clinical outcomes. Thrombus dynamics over time should be further evaluated in clinical trials of acute reperfusion therapy.

Sierpinski Structure and Electronic Topology in Bi Thin Films on InSb(111)B Surfaces.

Deposition of Bi on InSb(111)B reveals a striking Sierpinski-triangle (ST)-like structure in Bi thin films. Such a fractal geometric topology is further shown to turn off the intrinsic electronic topology in a thin film. Relaxation of a huge misfit strain of about 30% to 40% between Bi adlayer and substrate is revealed to drive the ST-like island formation. A Frenkel-Kontrova model is developed to illustrate the enhanced strain relief in the ST islands offsetting the additional step energy cost. Besides a sufficiently large tensile strain, forming ST-like structures also requires larger adlayer-substrate and intra-adlayer elastic stiffnesses, and weaker intra-adlayer interatomic interactions.

Enhanced Nanostructure Dynamics on Au(111) with Adsorbed Sulfur due to Au-S Complex Formation.

Chemisorbed species can enhance the fluxional dynamics of nanostructured metal surfaces which has implications for applications such as catalysis. Scanning tunneling microscopy studies at room temperature reveal that the presence of adsorbed sulfur (S) greatly enhances the decay rate of 2D Au islands in the vicinity of extended step edges on Au(111). This enhancement is already significant at S coverages, θS , of a few hundredths of a monolayer (ML), and is most pronounced for 0.1-0.3 ML where the decay rate is increased by a factor of around 30. For θS close to saturation at about 0.6 ML, sulfur induces pitting and reconstruction of the entire surface, and Au islands are stabilized. Enhanced coarsening at lower θS is attributed to the formation and diffusion across terraces of Au-S complexes, particularly AuS2 and Au4 S4 , with some lesser contribution from Au3 S4 . This picture is supported by density functional theory analysis of complex formation energies and diffusion barriers.

Reshaping, Intermixing, and Coarsening for Metallic Nanocrystals: Nonequilibrium Statistical Mechanical and Coarse-Grained Modeling.

Self-assembly of supported 2D or 3D nanocrystals (NCs) by vacuum deposition and of 3D NCs by solution-phase synthesis (with possible subsequent transfer to a support) produces intrinsically nonequilibrium systems. Individual NCs can have far-from-equilibrium shapes and composition profiles. The free energy of NC ensembles is lowered by coarsening which can involve Ostwald ripening or Smoluchowski ripening (NC diffusion and coalescence). Preservation of individual NC structure and inhibition of coarsening are key, e.g., for avoiding catalyst degradation. This review focuses on postsynthesis evolution of metallic NCs. Atomistic-level modeling typically utilizes stochastic lattice-gas models to access appropriate time and length scales. However, predictive modeling requires incorporation of realistic rates for relaxation mechanisms, e.g., periphery diffusion and intermixing, in numerous local environments (rather than the use of generic prescriptions). Alternative coarse-grained modeling must also incorporate appropriate mechanisms and kinetics. At the level of individual NCs, we present analyses of reshaping, including sintering and pinch-off, and of compositional evolution in a vacuum environment. We also discuss modeling of coarsening including diffusion and decay of individual NCs and unconventional coarsening processes. We describe high-level modeling integrated with scanning tunneling microscopy (STM) studies for supported 2D epitaxial nanoclusters and developments in modeling for 3D NCs motivated by in situ transmission electron microscopy (TEM) studies.

Effective Fragment Potential-Based Molecular Dynamics Studies of Diffusion in Acetone and Hexane.

To facilitate more reliable descriptions of transport properties in liquids, molecular dynamics (MD) simulations are performed based on the effective fragment potential (EFP) method derived from first-principles quantum mechanics (in contrast to MD based upon empirically fitted potentials). The EFP method describes molecular interactions in terms of Coulomb, polarization/induction, dispersion, exchange-repulsion, and charge-transfer interactions. The EFP MD simulations described in this paper, performed on hexane and acetone, are able to track the mean-square displacement of molecules for sufficient time to reliably extract translational diffusion coefficients. The results reported here are in reasonable agreement with experiment.

Competitive formation of intercalated versus supported metal nanoclusters during deposition on layered materials with surface point defects.

Intercalated metal nanoclusters (NCs) can be formed under the surface of graphite after sputtering to generate surface "portal" defects that allow deposited atoms to reach the subsurface gallery. However, there is a competition between formation of supported NCs on top of the surface and intercalated NCs under the surface, the latter only dominating at sufficiently high temperature. A stochastic model incorporating appropriate system thermodynamics and kinetics is developed to capture this complex and competitive nucleation and growth process. Kinetic Monte Carlo simulation shows that the model captures experimental trends observed for Cu and other metals and reveals that higher temperatures are needed to facilitate detachment of atoms from supported NCs enabling them to reach the gallery.

Comparison of different methods of thrombus permeability measurement and impact on recanalization in the INTERRSeCT multinational multicenter prospective cohort study.

PURPOSE: To compare the association of different measures of intracranial thrombus permeability on non-contrast computerized tomography (NCCT) and computed tomography angiography (CTA) with recanalization with or without intravenous alteplase. METHODS: Patients with anterior circulation occlusion from the INTERRSeCT study were included. Thrombus permeability was measured on non-contrast CT and CTA using the following methods: [1] automated method, mean attenuation increase on co-registered thin (< 2.5 mm) CTA/NCCT; [2] semi-automated method, maximum attenuation increase on non-registered CTA/NCCT (ΔHUmax); [3] manual method, maximum attenuation on CTA (HUmax); and [4] visual method, residual flow grade. Primary outcome was recanalization with intravenous alteplase on the revised AOL scale (2b/3). Regression models were compared using C-statistic, Akaike (AIC), and Bayesian information criterion (BIC). RESULTS: Four hundred eighty patients were included in this analysis. Statistical models using methods 2, 3, and 4 were similar in their ability to discriminate recanalizers from non-recanalizers (C-statistic 0.667, 0.683, and 0.634, respectively); method 3 had the least information loss (AIC = 483.8; BIC = 492.2). A HUmax ≥ 89 measured with method 3 provided optimal sensitivity and specificity in discriminating recanalizers from non-recanalizers [recanalization 55.4% (95%CI 46.2-64.6) when HUmax > 89 vs. 16.8% (95%CI 13.0-20.6) when HUmax ≤ 89]. In sensitivity analyses restricted to patients with co-registered CTA/NCCT (n = 88), methods 1-4 predicted recanalization similarly (C-statistic 0.641, 0.688, 0.640, 0.648, respectively) with Method 2 having the least information loss (AIC 104.8, BIC 109.8). CONCLUSION: Simple methods that measure thrombus permeability are as reliable as complex image processing methods in discriminating recanalizers from non-recanalizers.

Surface structure of linear nanopores in amorphous silica: Comparison of properties for different pore generation algorithms.

We compare the surface structure of linear nanopores in amorphous silica (a-SiO2) for different versions of "pore drilling" algorithms (where the pores are generated by the removal of atoms from the preformed bulk a-SiO2) and for "cylindrical resist" algorithms (where a-SiO2 is formed around a cylindrical exclusion region). After adding H to non-bridging O, the former often results in a moderate to high density of surface silanol groups, whereas the latter produces a low density. The silanol surface density for pore drilling can be lowered by a final dehydroxylation step, and that for the cylindrical resist approach can be increased by a final hydroxylation step. In this respect, the two classes of algorithms are complementary. We focus on the characterization of the chemical structure of the pore surface, decomposing the total silanol density into components corresponding to isolated and vicinal mono silanols and geminal silanols. The final dehyroxylation and hydroxylation steps can also be tuned to better align some of these populations with the target experimental values.

Structure of chalcogen overlayers on Au(111): Density functional theory and lattice-gas modeling.

Ordering of different chalcogens, S, Se, and Te, on Au(111) exhibit broad similarities but also some distinct features, which must reflect subtle differences in relative values of the long-range pair and many-body lateral interactions between adatoms. We develop lattice-gas (LG) models within a cluster expansion framework, which includes about 50 interaction parameters. These LG models are developed based on density functional theory (DFT) analysis of the energetics of key adlayer configurations in combination with the Monte Carlo (MC) simulation of the LG models to identify statistically relevant adlayer motifs, i.e., model development is based entirely on theoretical considerations. The MC simulation guides additional DFT analysis and iterative model refinement. Given their complexity, development of optimal models is also aided by strategies from supervised machine learning. The model for S successfully captures ordering motifs over a broader range of coverage than achieved by previous models, and models for Se and Te capture the features of ordering, which are distinct from those for S. More specifically, the modeling for all three chalcogens successfully explains the linear adatom rows (also subtle differences between them) observed at low coverages of ∼0.1 monolayer. The model for S also leads to a new possible explanation for the experimentally observed phase with a (5 × 5)-type low energy electron diffraction (LEED) pattern at 0.28 ML and to predictions for LEED patterns that would be observed with Se and Te at this coverage.

Strain-Enhanced Metallic Intermixing in Shape-Controlled Multilayered Core-Shell Nanostructures: Toward Shaped Intermetallics.

Controlling the surface composition of shaped bimetallic nanoparticles could offer precise tunability of geometric and electronic surface structure for new nanocatalysts. To achieve this goal, a platform for studying the intermixing process in a shaped nanoparticle was designed, using multilayered Pd-Ni-Pt core-shell nanocubes as precursors. Under mild conditions, the intermixing between Ni and Pt could be tuned by changing layer thickness and number, triggering intermixing while preserving nanoparticle shape. Intermixing of the two metals is monitored using transmission electron microscopy. The surface structure evolution is characterized using electrochemical methanol oxidation. DFT calculations suggest that the low-temperature mixing is enhanced by shorter diffusion lengths and strain introduced by the layered structure. The platform and insights presented are an advance toward the realization of shape-controlled multimetallic nanoparticles tailored to each potential application.

Sulfur adsorption on coinage metal(100) surfaces: propensity for metal-sulfur complex formation relative to (111) surfaces.

Experimental data from low-temperature Scanning Tunneling Microscopy (LTSTM) studies on coinage metal surfaces with very low coverages of S is providing new insights into metal-S interactions. A previous LTSTM study for Cu(100), and a new analysis reported here for Ag(100), both indicate no metal-sulfur complex formation, but an Au4S5 complex was observed previously on Au(100). In marked contrast, various complexes have been proposed and/or observed on Ag(111) and Cu(111), but not on Au(111). Also, exposure to trace amounts of S appears to enhance mass transport far more dramatically on (111) than on (100) surfaces for Cu and Ag, a feature tied to the propensity for complex formation. Motivated by these observations, we present a comprehensive assessment at the level of DFT to assess the existence and stability of complexes on (100) surfaces, and compare results with previous analyses for (111) surfaces. Consistent with experiment, our DFT analysis finds no stable complexes on Ag(100) and Cu(100), but several exist for Au(100). In addition, we systematically relate stability for adsorbed and gas-phase species within the framework of Hess's law. We thereby provide key insight into the various energetic contributions to stability which in turn elucidates the difference in behavior between (100) and (111) surfaces.

Discontinuous Phase Transitions in Nonlocal Schloegl Models for Autocatalysis: Loss and Reemergence of a Nonequilibrium Gibbs Phase Rule.

We consider Schloegl models (or contact processes) where particles on a square grid annihilate at a rate p and are created at a rate of k_{n}=n(n-1)/[N(N-1)] at empty sites with n particles in a neighborhood Ω_{N} of size N. Simulation reveals a discontinuous transition between populated and vacuum states, but equistable p=p_{eq} determined by the stationarity of planar interfaces between these states depends on the interface orientation and on Ω_{N}. The behavior for large Ω_{N} follows from continuum equations. These also depend on the interface orientation and on Ω_{N} shape, but a unique p_{eq}=0.211 376 320 4 emerges imposing a Gibbs phase rule.