Molecular Dynamics Simulations Research Articles

Synthesis, impurity profiling, simultaneous NP-HPTLC method development, molecular modelling study and EGFR tyrosine kinase inhibitory profile: An integrated approach to characterize desethynyl erlotinib process impurity

The study presents an integrated approach to characterizing Desethynyl Erlotinib, a process impurity in the synthesis of Erlotinib, a potent EGFR tyrosine kinase (EGFR TK) inhibitor used in lung cancer treatment. A normal phase high-performance thin-layer chromatography (NP-HPTLC) method was developed and validated for the simultaneous profiling of Erlotinib and its Desethynyl Erlotinib impurity. The optimized method utilized ethyl acetate, methanol, and glacial acetic acid (9: 0.5: 0.5 v/v/v) as the mobile phase for effective separation and quantification. The method demonstrated excellent linearity for Erlotinib and its impurity over a concentration range of 200-1200 ng/spot, with R2 values of 0.9979 and 0.9998, respectively. Validation confirmed precision with intra-day and inter-day % RSD values of less than 2% and robustness. The “limits of detection (LOD) and quantification (LOQ)” were 5.18 ng/spot and 15.70 ng/spot for Erlotinib and 7.07 ng/spot and 21.43 ng/spot for the impurity. In-vitro assays against the A549 lung cancer cell line expressing wild-type EGFR tyrosine kinase (WT EGFR TK) showed that the Desethynyl Erlotinib impurity exhibits significant inhibition compared to Erlotinib, suggesting the potential toxicity of the Desethynyl Erlotinib impurity and causing side effects such as diarrhea, skin rashes and interstitial lung disease due to WT EGFR tyrosine kinase (WT EGFR TK) inhibition. Molecular docking and molecular dynamics simulations further corroborated greater stability in the Desethynyl Erlotinib impurity with WT EGFR tyrosine kinase (WT EGFR TK). Clinically, these findings highlight the importance of monitoring and minimizing impurities like Desethynyl Erlotinib to prevent adverse effects and maintain the therapeutic safety of Erlotinib in lung cancer treatment. This research underscores the necessity for rigorous quality control in Erlotinib production to ensure purity and therapeutic effectiveness.

Applicability of the thermodynamic and mechanical route to Young's equation for rigid and flexible solids: A molecular dynamics simulations study of a Lennard-Jones system model.

The wetting properties of a liquid in contact with a solid are commonly described by Young's equation, which defines the relationship between the angle made by a fluid droplet onto the solid surface and the interfacial properties of the different interfaces involved. When modeling such interfacial systems, several assumptions are usually made to determine this angle of contact, such as a completely rigid solid or the use of the tension at the interface instead of the surface free energy. In this work, we perform molecular dynamics simulations of a Lennard-Jones liquid in contact with a Lennard-Jones crystal and compare the contact angles measured from a droplet simulation with those calculated using Young's equation based on surface free energy or surface stress. We analyze cases where the solid atoms are kept frozen in their positions and where they are allowed to relax and simulate surfaces with different wettability and degrees of softness. Our results show that using either surface free energy or surface stress in Young's equation leads to similar contact angles but different interfacial properties. We find that the approximation of keeping the solid atoms frozen must be done carefully, especially if the liquid can efficiently pack at the interface. Finally, we show that to correctly reproduce the measured contact angles when the solid becomes soft, the quantity to be used in Young's equation is the surface free energy only and that the error committed in using the surface stress becomes larger as the softness of the solid increases.

The first step of cyanine dye self-assembly: Dimerization.

Self-assembling amphiphilic cyanine dyes, such as C8S3, are promising candidates for energy storage and optoelectronic applications due to their efficient energy transport properties. C8S3 is known to self-assemble in water into double-walled J-aggregates. Thus far, the molecular self-assembly steps remain shrouded in mystery. Here, we employ a multiscale approach to unravel the first self-assembly step: dimerization. Our multiscale approach combines molecular dynamics simulations with quantum chemistry calculations to obtain a Frenkel exciton Hamiltonian, which we then use in spectral calculations to determine the absorption and two-dimensional electronic spectra of C8S3 monomer and dimer systems. We model these systems solvated in both water and methanol, validating our model with experiments in methanol solution. Our theoretical results predict a measurable anisotropy decay upon dimerization, which is experimentally confirmed. Our approach provides a tool for the experimental probing of dimerization. Moreover, molecular dynamics simulations reveal that the dimer conformation is characterized by the interaction between the hydrophobic aliphatic tails rather than the π-π stacking previously reported for other cyanine dyes. Our results pave the way for future research into the mechanism of molecular self-assembly in similar light-harvesting complexes, offering valuable insights for understanding and optimizing self-assembly processes for various (nano)technological applications.

Prediction of induced fluxes in reverse nonequilibrium molecular dynamics.

Reverse nonequilibrium molecular dynamics (RNEMD) simulations impose a flux by swapping the velocities of two particles. This method allows for the calculation of transport coefficients, such as thermal conductivity and viscosity. The relation between the induced fluxes and the control parameters of RNEMD (such as the time interval between successive swap events) is not clear. Thus, trial-and-error is required to realize the desired fluxes in RNEMD simulations. In this study, we develop a theoretical framework using extreme value statistics to estimate the relation between the time interval and the resulting induced fluxes. Our RNEMD simulations, conducted with varying time intervals, confirm that the theoretical predictions are quantitatively consistent with the simulation results when the time interval exceeds the momentum relaxation time. Our RNEMD simulations also show that our theoretical predictions, which are valid for a large number of particles for swap candidates, work well even for a relatively small number of particles for swap candidates. These findings demonstrate that the induced fluxes can be reliably estimated, providing a valuable tool for selecting appropriate RNEMD parameters for simulations.

Computational Modeling of Pharmaceuticals with an Emphasis on Crossing the Blood–Brain Barrier

The discovery and development of new pharmaceutical drugs is a costly, time-consuming, and highly manual process, with significant challenges in ensuring drug bioavailability at target sites. Computational techniques are highly employed in drug design, particularly to predict the pharmacokinetic properties of molecules. One major kinetic challenge in central nervous system drug development is the permeation through the blood–brain barrier (BBB). Several different computational techniques are used to evaluate both BBB permeability and target delivery. Methods such as quantitative structure–activity relationships, machine learning models, molecular dynamics simulations, end-point free energy calculations, or transporter models have pros and cons for drug development, all contributing to a better understanding of a specific characteristic. Additionally, the design (assisted or not by computers) of prodrug and nanoparticle-based drug delivery systems can enhance BBB permeability by leveraging enzymatic activation and transporter-mediated uptake. Neuroactive peptide computational development is also a relevant field in drug design, since biopharmaceuticals are on the edge of drug discovery. By integrating these computational and formulation-based strategies, researchers can enhance the rational design of BBB-permeable drugs while minimizing off-target effects. This review is valuable for understanding BBB selectivity principles and the latest in silico and nanotechnological approaches for improving CNS drug delivery.

Influence of Waste Catalyst Surface Characteristics on High-Temperature Performance and Adhesion Properties of Asphalt Mortar

The incorporation of waste fluid catalytic cracking (FCC) catalysts (WFCs) into asphalt pavements represents an effective strategy for resource utilization. However, the influences of the composition of the waste catalyst and its surface characteristics on the performance of asphalt mortars are still unclear. Herein, five WFCs were selected as powder filler to replace partial mineral powder (MP) to prepare five asphalt mortars. The diffusion behaviors of asphalt binder on the components of WFCs were investigated based upon molecular dynamic simulation, as was the interfacial energy between them. The adhesion work values between asphalt and WFCs were evaluated based upon the surface free energy theory. A dynamic shear rheology test and multiple stress creep recovery test on the WFC asphalt mortar were also conducted. Furthermore, the gray correlation analysis (GCA) method was employed to analyze the correlation between the diffusion coefficient and interfacial energy with the performance of WFC asphalt mortar. The results showed that the asphalt exhibited a low diffusion coefficient and high interfacial energy with the alkaline components of WFCs. The adhesion work values between asphalt and WFCs are higher than those with MP. The addition of WFCs can enhance the anti-rutting property of asphalt mortar significantly. Among the five WFCs, 2# exhibited the best improvement effect on the anti-permanent deformation ability of asphalt mortar, which may be due to its large specific surface area and moderate pore width. The GCA results suggest that the diffusion coefficient and interfacial energy strongly correlated with the performance of asphalt mortar, with an order of adhesion > permanent deformation resistance > rutting resistance. This study provides both theoretical and experimental support for the application of WFCs in asphalt materials.

Diffusion in liquid metals is directed by competing collective modes

The self-diffusion process in a dense liquid is influenced by collective particle movements. Extensive molecular dynamics simulations for liquid aluminium and rubidium evidence a crossover in the diffusion coefficient at about 1.4 times the melting temperature Tm, indicating a profound change in the diffusion mechanism. The corresponding velocity autocorrelation functions demonstrate a decrease of the cage effect with a gradual set in of a power-law decay, they celebrate long time tail. This behavior is caused by a competition of density fluctuations near the melting point with vortex-type particle patterns from transverse currents in the hot fluid. The investigation of the velocity autocorrelation function evidences a gradual transition in dynamics with rising temperature. The competition between these two collective particle movements, one hindering and one enhancing the diffusion process, leads to a non-Arrhenius-type behavior of the diffusion coefficient around 1.4Tm, which signals the transition from a dense to a fluidlike liquid dynamics in the potential energy landscape picture. Published by the American Physical Society 2025

Mechanisms of Enhanced Electrochemical Performance by Chemical Short-Range Disorder in Lithium Oxide Cathodes.

LiCoO2 has been one of the dominant cathode materials commercially used in rechargeable lithium-ion batteries, while the performance is severely limited by its low reversible capacity (∼140 mAh/g), primarily due to the destructive phase transitions at high voltages (>4.2 V vs Li/Li+), leading to structural degradation and rapid decay of capacity. A recent experimental study [Wang et al. Nature 2024, 629, 341] showed that chemical short-range disorder (CSRD) in LiCoO2 can effectively prevent phase transitions and structural deterioration. To better understand the underlying mechanisms, we carry out a theoretical study on CSRD-based LiCoO2 by performing ab initio molecular dynamics simulations accelerated by machine learning and find that CSRD effectively suppresses phase transitions from hexagonal to monoclinic at Li0.5CoO2 and from O3 to H1-3 at Li0.25CoO2. The enhanced phase stability is attributed to the reduced lattice variation in the c-axis, the increased oxygen vacancy formation energies, the higher oxygen dimer formation energies, and the stabilization of Co atoms in the Li layers during delithiation. The high Li+ diffusion coefficients are found to arise from the low-barrier 0-TM diffusion channels and an expanded diffusion network from 2D to quasi-3D induced by CSRD. Furthermore, CSRD narrows the band gap of LiCoO2 with enhanced electronic conductivity, driven by the changes in the Co valence state and the introduction of linear Li-O-Li configurations. Equally important, CSRD can also enhance the stability of Li-rich cathode Li1.2Co0.8O2 for high capacity and excellent cycling performance. This work provides theoretical insights into the effects of CSRD on LiCoO2 and Li-rich cathodes for rational design and synthesis.

Nitidine chloride inhibits the progression of hepatocellular carcinoma by suppressing IGF2BP3 and modulates metabolic pathways in an m6A-dependent manner

BackgroundHepatocellular carcinoma (HCC) stands as a major health concern due to its significant morbidity and mortality. Among potential botanical therapeutics, nitidine chloride (NC) has garnered attention for its potential anti-HCC properties. However, the underlying mechanisms, especially the possible involvement of the m6A pathway, remain to be elucidated.MethodsHCC cell and zebrafish xenograft models were utilized to validate the anti-HCC effects of NC. RNA-seq and MeRIP-seq analyses were performed to explore the potential targets and mechanisms of NC against HCC. The target effect of NC on IGF2BP3 was verified through RT-qPCR, WB, molecular docking, molecular dynamics (MD) simulation, surface plasmon resonance (SPR), and CCK8 off-target assays. Downstream target genes were confirmed using RNA stability assays.ResultsIn this study, utilizing HCC cell and zebrafish xenograft models, we validated NC’s ability to inhibit the growth, metastasis, and angiogenesis of HCC. Subsequently, employing RNA sequencing, RT-qPCR, WB, molecular docking, MD simulation, SPR, and CCK8 off-target assays, we pinpointed IGF2BP3 as a direct target of NC. IGF2BP3 is highly expressed in HCC, and IGF2BP3 knockdown significantly inhibited the proliferation, migration and invasion of HCC cells. Further MeRIP-seq and RIP-seq revealed 197 genes interacting with IGF2BP3, downregulated at mRNA and m6A levels after NC treatment, primarily associated with multiple metabolism-related pathways. Through intersection analysis, we pinpointed 30 potential metabolic target genes regulated by NC through IGF2BP3. Based on the expression of these genes, the metabolic scores for each HCC patient were calculated. Our findings suggest that patients with high metabolic scores have poorer prognoses, and the metabolic score serves as an independent prognostic factor. Finally, RNA stability experiments confirmed CKB, RRM2, NME1, PKM, and UXS1 as specific metabolic target genes affected by NC/IGF2BP3, displaying reduced RNA half-life post IGF2BP3 downregulation.ConclusionOur study suggest that NC may exert its anti-HCC effects by downregulating IGF2BP3, inhibiting the m6A modification levels of metabolic-related genes, thereby reducing their stability and expression. Such insights provide a new direction in the study of NC’s anti-HCC mechanisms and offer novel perspectives for the treatment of HCC patients, focusing on both metabolic levels and m6A modification levels.

Shock-induced chemistry and high strain-rate viscoelastic behavior of a phenolic polymer

We use impact experiments and a finite element model (up to 1.2 GPa), and molecular dynamics simulations (up to 60 GPa), to examine the behavior of a phenolic polymer under shock compression, spanning both nonreactive and reactive regimes. In the nonreactive regime, relaxation following compression at strain rates of ∼105 s−1 can be explained by viscoelasticity observed at ordinary laboratory rates (≲1 s−1) by accounting for the temperature dependence of the phenolic β-transition. Reasonable agreement is found between the measured shock Hugoniot up to 1.2 GPa and molecular dynamics simulation for cross-linked structures of comparable density. We also observed a first-order mechanical transition near 0.36 GPa shock stress and estimated a spall strength of 0.102 GPa and Hugoniot elastic limit of 1–2 GPa. The shock stress is found to vary up to 24% among phenolics made with different resin and/or cure processes. Finally, molecular dynamics simulations are used to identify a reactive regime at shock pressures ≳20 GPa that is characterized by chemically driven, rate-dependent relaxation processes, including dehydrogenation and dehydration reactions that promote the formation of a dense, highly cross-linked carbonaceous solid and the release of light volatiles.

Martini compatible coarse-grained model of polyethylenimine for pulmonary gene delivery

Pulmonary gene delivery has demonstrated high specificity for respiratory diseases, offering great control on dosage of therapeutics and side effects. On the other hand, intrinsic barriers in pulmonary systems impose new challenges such as crossing the pulmonary surfactant and evading mucus entrapment. Differences in hydrophobicity of plasma membrane and pulmonary surfactant require different chemistries of gene carriers to improve efficacy. Large-scale coarse-grained (CG) molecular dynamics simulations would facilitate the screening of gene carriers and understanding of the molecular mechanisms involved in pulmonary delivery. Among non-viral carriers, polyethyleneimine (PEI) has been a promising candidate that can be synthesized with various molecular weight, degree of branching, and functionalization. In this work, CG models are developed for PEI and its lipid-functionalized form, within the Martini framework, to provide a platform for exploring structure-function relationships of PEI-based pulmonary delivery systems. Special attention is focused on parameterizing the non-bonded interactions associated with CG PEI, to ensure compatibility with Martini proteins, short interfering RNA, and phospholipids that are essential components in pulmonary gene delivery. The non-bonded parameters are validated by comparing all-atom (AA) and CG potential of mean force (PMF) curves, where the root-mean-square deviations between the AA and CG PMF curves are shown to be comparable to or smaller than those reported in Martini literature.

Transcription Factor Inhibition as a Potential Additional Mechanism of Action of Pyrrolobenzodiazepine (PBD) Dimers

Background: The pyrrolobenzodiazepine (PBD) dimer SJG-136 reached Phase II clinical trials in ovarian cancer and leukaemia in the UK and USA in the 2000s. Several structural analogues of SJG-136 are currently in clinical development as payloads for Antibody-Drug Conjugates (ADCs). There is growing evidence that PBDs exert their pharmacological effects through inhibition of transcription factors (TFs) in addition to arrest at the replication fork, DNA strand breakage, and inhibition of enzymes including endonucleases and RNA polymerases. Hence, PBDs can be used to target specific DNA sequences to inhibit TFs as a novel anticancer therapy. Objective: To explore the ability of SJG-136 to bind to the cognate sequences of transcription factors using a previously described HPLC/MS method, to obtain preliminary mechanistic evidence of its ability to inhibit transcription factors (TF), and to determine its effect on TF-dependent gene expression. Methods: An HPLC/MS method was used to assess the kinetics and thermodynamics of adduct formation between the PBD dimer SJG-136 and the cognate recognition sequence of the TFs NF-κB, EGR-1, AP-1, and STAT3. CD spectroscopy, molecular dynamics simulations, and gene expression analyses were used to rationalize the findings of the HPLC/MS study. Results: Notable differences in the rate and extent of adduct formation were observed with different DNA sequences, which might explain the variations in cytotoxicity of SJG-136 observed across different tumour cell lines. The differences in adduct formation result in variable downregulation of several STAT3-dependent genes in the human colon carcinoma cell line HT-29 and the human breast cancer cell line MDA-MB-231. Conclusions: SJG-136 can disrupt transcription factor-mediated gene expression, which contributes to its exceptional cytotoxicity in addition to the DNA-strand cleavage initiated by its ability to crosslink DNA.

Structural prediction of chimeric immunogen candidates to elicit targeted antibodies against betacoronaviruses.

Betacoronaviruses pose an ongoing pandemic threat. Antigenic evolution of the SARS-CoV-2 virus has shown that much of the spontaneous antibody response is narrowly focused rather than broadly neutralizing against even SARS-CoV-2 variants, let alone future threats. One way to overcome this is by focusing the antibody response against better-conserved regions of the viral spike protein. This has been demonstrated empirically in prior work, but we posit that systematic design tools will further potentiate antigenic focusing approaches. Here, we present a design approach to predict stable chimeras between SARS-CoV-2 and other coronaviruses, creating synthetic spike proteins that display a desired conserved region, in this case S2, and vary other regions. We leverage AlphaFold to predict chimeric structures and create a new metric for scoring chimera stability based on AlphaFold outputs. We evaluated 114 candidate spike chimeras using this approach. Top chimeras were further evaluated using molecular dynamics simulation as an intermediate validation technique, showing good stability compared to low-scoring controls. Experimental testing of five predicted-stable and two predicted-unstable chimeras confirmed 5/7 predictions, with one intermediate result. This demonstrates the feasibility of the underlying approach, which can be used to design custom immunogens to focus the immune response against a desired viral glycoprotein epitope.

Electrolyte Design Using "Porous Water” for High‐purity Carbon Monoxide Electrosynthesis from Dilute Carbon Dioxide

Electrosynthesis of high‐purity carbon monoxide (CO) from captured carbon dioxide (CO₂) remains energy‐intensive due to the unavoidable CO₂ regeneration and post‐purification stages. Here, we propose a direct high‐purity CO electrosynthesis strategy employing an innovative electrolyte, termed porous electrolyte (PE), based on "porous water". Zeolite nanocrystals within PE provide permanent pores in the liquid phase, enabling physical CO₂ adsorption through an intraparticle diffusion model, as demonstrated by molecular dynamics simulations and in‐situ spectral analysis. Captured CO₂ spontaneously desorbs under applied reductive potential, driven by the interfacial CO₂ concentration gradient, and is subsequently reduced electrochemically. The high CO₂ concentration in PE enhances mass transfer, and surface ion exchange between Si–OH groups and K⁺ ions on the zeolite surface generates a stronger interfacial electric field, promoting electron transfer steps. This optimized kinetics for mass and electron transfer confers heightened intrinsic activity toward CO₂ electroreduction. The PE‐based electrolysis system demonstrated superior CO Faradaic efficiency and partial current density compared to the conventional CO₂‐fed system. A circular system using PE and a Ni‐N/C cathode realized continuous production of high‐purity CO (97.0 wt%) from dilute CO2 (15%) and maintained > 90.0 wt% under 150 mA cm‐2, with significantly reduced energy consumption and costs.

MXene Membranes Inserted with Tannic Acid Etched MOF Nanocrystals for Ultrafast Water Permeation: Elucidating the Water Transport Mechanism in Nanoconfined Interlaminar Channels.

Utilizing pore and interlayer engineering within nanoconfined interlaminar channels represents an ingenious approach to design highly permselective MXene (Ti3C2TX) membranes. Herein, the tannic acid (TA) etched ZIF-8 (TZIF-8) nanocrystals with hollow structures were effectually inserted into the interlayer spacing of MXene membranes. First, the density functional theory (DFT) results demonstrated the reaction mechanism between TA and ZIF-8. Then, the underlying mechanism of enhanced water-adsorptive properties for MXene/TZIF-8 membrane was due to the higher binding energy of water/TZIF-8 system than that of water/ZIF-8 system, elucidated by molecular dynamic simulation. Furthermore, the low mass transfer resistance and abundant mass transfer pathways of the MXene/TZIF-8 membrane were comprehensively proved by various experimental conclusions, characterizations and simulation calculations. As a result, the optimal MXene/TZIF-8 membrane exhibited high water permeance and concurrently satisfactory separation efficacy toward various oil/water emulsions. This work is anticipated to deepen the comprehension of high-efficiency water transport along interbedded nanochannels in MXene membranes.

Electrolyte Design Using "Porous Water" for High-purity Carbon Monoxide Electrosynthesis from Dilute Carbon Dioxide.

Electrosynthesis of high-purity carbon monoxide (CO) from captured carbon dioxide (CO₂) remains energy-intensive due to the unavoidable CO₂ regeneration and post-purification stages. Here, we propose a direct high-purity CO electrosynthesis strategy employing an innovative electrolyte, termed porous electrolyte (PE), based on "porous water". Zeolite nanocrystals within PE provide permanent pores in the liquid phase, enabling physical CO₂ adsorption through an intraparticle diffusion model, as demonstrated by molecular dynamics simulations and in-situ spectral analysis. Captured CO₂ spontaneously desorbs under applied reductive potential, driven by the interfacial CO₂ concentration gradient, and is subsequently reduced electrochemically. The high CO₂ concentration in PE enhances mass transfer, and surface ion exchange between Si-OH groups and K⁺ ions on the zeolite surface generates a stronger interfacial electric field, promoting electron transfer steps. This optimized kinetics for mass and electron transfer confers heightened intrinsic activity toward CO₂ electroreduction. The PE-based electrolysis system demonstrated superior CO Faradaic efficiency and partial current density compared to the conventional CO₂-fed system. A circular system using PE and a Ni-N/C cathode realized continuous production of high-purity CO (97.0 wt%) from dilute CO2 (15%) and maintained > 90.0 wt% under 150 mA cm-2, with significantly reduced energy consumption and costs.

Complex formation between n-alkyltrimethylammonium bromides and water-soluble calix[n]arenes

Abstract Complex formation between n-alkyltrimethylammonium bromides and water-soluble calix[n]arenes (n = 4, 6, 8) (CALXSn) was studied by potentiometric titration and molecular dynamic simulation. The binding isotherms were found to be composed of two phases; the first phase is strong specific binding to a few sites and the second phase is cooperative binding to the residual sites. Binding constant for the first specific binding was found to increase with an increase in the number of ring members of CALXSn. Binding constants for CALXS4 and CALXS6 systems did not change significantly with the length of the surfactant's alkyl chain and with the pH change from 7.0 to 12.5, while that for CALXS8 systems tended to increase with an increase in the alkyl-chain length. The specific binding disappeared with the pH increase. The thermodynamic parameters showed an enthalpy-entropy compensation relation with a compensation temperature of 289 K. The second phase was observed mainly for n-dodecyltrimethylammonium-CALXSn systems. The cooperativity parameter was found to increase with an increase in the number of ring member of CALXSn and is attributed to the contribution of increasing conformational flexibility of CALXSn as the number of ring members increases. MD simulation on CALXSn with and without n-alkyltrimethylammonium ion provided structural interpretation for the features of binding data.

Sam–Sam Association Between EphA2 and SASH1: In Silico Studies of Cancer-Linked Mutations

Recently, SASH1 has emerged as a novel protein interactor of a few Eph tyrosine kinase receptors like EphA2. These interactions involve the first N-terminal Sam (sterile alpha motif) domain of SASH1 (SASH1-Sam1) and the Sam domain of Eph receptors. Currently, the functional meaning of the SASH1-Sam1/EphA2-Sam complex is unknown, but EphA2 is a well-established and crucial player in cancer onset and progression. Thus, herein, to investigate a possible correlation between the formation of the SASH1-Sam1/EphA2-Sam complex and EphA2 activity in cancer, cancer-linked mutations in SASH1-Sam1 were deeply analyzed. Our research plan relied first on searching the COSMIC database for cancer-related SASH1 variants carrying missense mutations in the Sam1 domain and then, through a variety of bioinformatic tools and molecular dynamic simulations, studying how these mutations could affect the stability of SASH1-Sam1 alone, leading eventually to a defective fold. Next, through docking studies, with the support of AlphaFold2 structure predictions, we investigated if/how mutations in SASH1-Sam1 could affect binding to EphA2-Sam. Our study, apart from presenting a solid multistep research protocol to analyze structural consequences related to cancer-associated protein variants with the support of cutting-edge artificial intelligence tools, suggests a few mutations that could more likely modulate the interaction between SASH1-Sam1 and EphA2-Sam.

Effect of interface structure on solid-state amorphization of dual-phase Mg alloys

The interface and its structure have a significant impact on the mechanical properties of the magnesium (Mg) alloys. However, the role of the interface in the solid-state amorphization process of the Mg alloys is still unclear. Here, the effect of four interface structures, namely, basal/prismatic (BP), stacking fault (SF), twin boundary (TB), and high-angle grain boundary (HAGB) on the solid-state amorphization (SSA) of the amorphous/crystalline dual-phase Mg alloys is investigated using molecular dynamics simulation. The results indicate that the introduction of all four interfaces increases the SSA degree of the alloys. For the four models, the SSA degree of the alloys varies from high to low in order as the BP model, the TB model, the SF model, and the HAGB model, which means that atomic diffusion has a significant dependence on the interface structure and interface energy. The results show that the interface plays two roles in the SSA process: first, it changes the structure of the amorphous–crystalline interface in contact with the interface and second, the interface with a more open structure itself is a fast channel for atomic diffusion, both of which are beneficial for the SSA of the alloys.

Proline cis/trans Conformational Selection Controls 14-3-3 Binding.

Intrinsically disordered protein regions (IDRs) are structurally dynamic yet functional, often interacting with other proteins through short linear motifs (SLiMs). Proline residues in IDRs introduce conformational heterogeneity on a uniquely slow time scale arising from cis/trans isomerization of the Xaa-Pro peptide bond. Here, we explore the role of proline isomerization in the interaction between the prolactin receptor (PRLR) and 14-3-3. Using NMR spectroscopy, thermodynamic profiling, and molecular dynamics (MD) simulations, we uncover a unique proline isomer-dependent binding, with a cis conformation affinity 3 orders of magnitude higher than the trans. MD simulations identify structural constraints in the narrow 14-3-3 binding groove that provide an explanation for the observed isomer selectivity. The cis preference of WT PRLR introduces a slow kinetic component relevant to signal propagation and a steric component that impacts chain direction. Proline isomerization constitutes a previously unrecognized selective component relevant to the ubiquitous 14-3-3 interactome. Given the prevalence of prolines in IDRs and SLiMs, our study highlights the importance of considering the distinct properties of proline isomers in experimental design and data interpretation to fully comprehend IDR functionality.