Hybrid Molecular Dynamics Simulations Research Articles

Discovery and characterization of novel FGFR1 inhibitors in triple-negative breast cancer via hybrid virtual screening and molecular dynamics simulations

The overexpression of FGFR1 is thought to significantly contribute to the progression of triple-negative breast cancer (TNBC), impacting aspects such as tumorigenesis, growth, metastasis, and drug resistance. Consequently, the pursuit of effective inhibitors for FGFR1 is a key area of research interest. In response to this need, our study developed a hybrid virtual screening method. Utilizing KarmaDock, an innovative algorithm that blends deep learning with molecular docking, alongside Schrödinger’s Residue Scanning. This strategy led us to identify compound 6, which demonstrated promising FGFR1 inhibitory activity, evidenced by an IC50 value of approximately 0.24 nM in the HTRF bioassay. Further evaluation revealed that this compound also inhibits the FGFR1 V561M variant with an IC50 value around 1.24 nM. Our subsequent investigations demonstrate that Compound 6 robustly suppresses the migration and invasion capacities of TNBC cell lines, through the downregulation of p-FGFR1 and modulation of EMT markers, highlighting its promise as a potent anti-metastatic therapeutic agent. Additionally, our use of molecular dynamics simulations provided a deeper understanding of the compound’s specific binding interactions with FGFR1.

Optimization of Lithium Metal Anode Performance: Investigating the Interfacial Dynamics and Reductive Mechanism of Asymmetric Sulfonylimide Salts

Asymmetric lithium salts, such as lithium (difluoromethanesulfonyl)(trifluoromethanesulfonyl)imide (LiDFTFSI), have been demonstrated to surpass traditional symmetric lithium salts with improved Li+ conductivity and the capacity to generate a stable solid electrolyte interphase (SEI) while maintaining compatibility with an aluminum (Al0) current collector. However, the intrinsic reductive mechanism through which LiDFTFSI influences battery performance remains unclear and under debate. Herein, detailed SEI reactions of LiDFTFSI–based electrolytes were investigated by combining density functional theory and molecular dynamics, aiming to clarify the formation process and atomic structure of the SEI. Our results show that asymmetric DFTFSI− weakens the interaction between carbonate solvents and Li+, and substantially alters the solvation structure, exhibiting a well-balanced coordination capacity compared to bis(trifluoromethanesulfonyl)imide (TFSI−). Nanosecond hybrid molecular dynamics simulation further reveals that preferential decomposition of LiDFTFSI produces sufficient LiF and Li2O to facilitate a robust SEI. Moreover, abundant F− generated from LiDFTFSI decomposition accumulates on the Al surface and subsequently combines with Al3+ from the current collector to form AlF3, potentially inhibiting corrosion of the current collector. Overall, these findings elucidate how LiDFTFSI regulates the solvation sheath and SEI structure, advancing the development of high-performance electrolytes compatible with current collectors.

Shear-induced structural and viscosity changes of amphiphilic patchy nanocubes in suspension

Our study demonstrates the relationship between the design of patchy nanocubes, their self-assembled structures including shear-induced structural changes and the rheological properties of suspensions through coarse-grained molecular simulations.

Comprehensive scrutiny of surface mechanical parameters of graphyne-based materials for metal-ions and metal-air batteries applications: A perspective and a hybrid atomistic-continuum model

Graphyne family, as a low-dimensional carbon allotrope, is utilized for metal-ion and –air batteries as the anode and cathode materials due to their unique characteristics. These novel carbon nanomaterials can provide more theoretical storage capacity than graphene, while their specific surface mechanical parameters and vibrational frequencies can influence battery performance. However, there needs to be clear information that can explain the effects of these parameters on battery efficiency. In this respect, the influences of the surface elasticity, residual stress, density, vibrational modes, and frequencies of α, β, and γ-graphyne circular monolayers on anode and cathode materials have been investigated in current research using the hybrid molecular dynamics simulation and modified classical continuum mechanics methods. Concerning metal-ion batteries, the results disclose that the suitability sequence for anode materials can be expressed as γ-graphyne > graphene > β-graphyne > α-graphyne monolayers. In the case of metal-air batteries, the competence sequence for cathode materials is in the order of γ-graphyne > β-graphyne ∼ graphene > α-graphyne monolayers. Therefore, γ-graphyne with suitable storage capacity, low volume expansion, good surface elasticity, low surface residual stress, and appropriate specific surface area is the promising anode and cathode material for metal-ion and -air batteries, respectively.

Confined Dynamics in Spherical Polymer Brushes.

We investigate the dynamics of polymers grafted to spherical nanoparticles in solution using hybrid molecular dynamics simulations with a coarse-grained solvent modeled via the multiparticle collision dynamics algorithm. The mean-square displacements of monomers near the surface of the nanoparticle exhibit a plateau on intermediate time scales, indicating confined dynamics reminiscent of those reported in neutron spin-echo experiments. The confined dynamics vanish beyond a specific radial distance from the nanoparticle surface that depends on the polymer grafting density. We show that this dynamical confinement transition follows theoretical predictions for the critical distance associated with the structural transition from confined to semidilute brush regimes. These findings suggest the existence of a hitherto unreported dynamic length scale connected with theoretically predicted static fluctuations in spherical polymer brushes and provide new insights into recent experimental observations.

Methane adsorption of nanocomposite shale in the presence of water: Insights from molecular simulations

Accurately predicting gas adsorption in shale gas is essential for estimating production capacity and optimizing extraction processes. However, the complex nature of shale reservoirs (heterogeneous structure, organic–inorganic nanopores, moisture content, etc.) presents significant challenges in understanding the mechanism of methane adsorption. To address these challenges, a nanocomposite shale model incorporating kerogen and illite with slit pore widths of 1 nm, 2 nm, and 4 nm is created. The hybrid grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations are used to investigate methane adsorption in rigid and flexible shale models (kerogen matrix and clay mineral) at three different temperatures, several pressures, and various moisture contents. The simulation results show that the methane density distributions revealed asymmetrical behavior due to the heterogeneous surfaces. Factors such as kerogen flexibility, pore width, moisture content, temperature, and pressure were found to significantly influence fluid behavior. A comparative analysis between the rigid and flexible shale models, considering varying pore widths under both dry and moist conditions, revealed noteworthy differences. Kerogen's flexibility led to increased surface roughness and decreased adsorbed density. Conversely, the presence of water reduced methane adsorption sites in illite, resulting in diverse and complex behaviors dependent on pore widths in the shale model. Finally, the results suggest that using adsorbed volume instead of classical adsorption models is recommended for converting excess adsorption into absolute adsorption. This alternative approach can provide more accurate predictions and enhance the understanding of adsorption in shale gas systems.

Insights into the Enhancement of the Poly(ethylene terephthalate) Degradation by FAST-PETase from Computational Modeling.

Polyethylene terephthalate (PET) is the most abundant polyester plastic, widely used in textiles and packaging, but, unfortunately, it is also one of the most discarded plastics after one use. In the last years, the enzymatic biodegradation of PET has sparked great interest owing to the discovery and subsequent mutation of PETase-like enzymes, able to depolymerize PET. FAST-PETase is one of the best enzymes hitherto proposed to efficiently degrade PET, although the origin of its efficiency is not completely clear. To understand the molecular origin of its enhanced catalytic activity, we have carried out a thorough computational study of PET degradation by the FAST-PETase action by employing classical and hybrid (QM/MM) molecular dynamics (MD) simulations. Our findings show that the rate-limiting reaction step for FAST-PETase corresponds to the acylation stage with an estimated free energy barrier of 12.1 kcal mol-1, which is significantly smaller than that calculated for PETase (16.5 kcal mol-1) and, therefore, supports the enhanced catalytic activity of FAST-PETase. The origin of this enhancement is mainly attributed to the N233K mutation, which, although sited relatively far from the active site, induces a chain folding where the Asp206 of the catalytic triad is located, impeding that this residue sets effective H-bonds with its neighboring residues. This effect makes Asp206 hold a more basic character compared to the wild-type PETase and boosts the interaction with the protonated His237 of the catalytic triad in the transition state of acylation, with the consequent decrease of the catalytic barrier and acceleration of the PET degradation reaction.

Insights into the role of Nb segregation on grain boundary structural transition and mechanical response in a Ni–Nb system

The role of Nb segregation on the grain boundary (GB) structural transformation and mechanical response has been studied in a binary Ni–Nb system through atomistic simulation. To investigate the effect of dopant concentration on the GB structural transitions, a Σ5 (310) GB has been created with the help of molecular statics simulation. Thereafter, hybrid Monte Carlo and Molecular dynamics (MD) simulations have been performed to segregate Nb atoms at the Σ5 (310) GB. At lower dopant concentrations, the Nb atoms preferably segregated at the tip of the kite structure. With an increase in dopant concentration and temperature, the Nb atoms segregated at other sites in the GB as well as in the matrix and the GB structure becomes disordered. The effect of doping on the mechanical behavior has been investigated by applying constant strain rate along X-direction through MD. The stress-strain curve of the Ni–Nb system at 300 K revealed an increase in the strength and ductility with the dopant concentration up to a certain limit (0.4 at. % Nb) and decreased thereafter. The superior mechanical response of the Ni-0.4Nb system is attributed to the formation of stacking faults and sessile dislocations during deformation. Stacking faults delay the formation of cracks while sessile dislocations impede the dislocation motion, resulting in higher ductility and strength. Contrarily, nucleation of voids and cracks takes place at a lower extent of strain, resulting in an early fracture in the pure Ni. However, the strength of the doped specimen is found to be lower than the undoped one at 700 K due to the early initiation of cracks in the disordered GB region of the former specimen. The comprehensive understanding of the effect of interfacial segregation on the structural and mechanical behaviour would open up new avenues for alloy design and the development of advanced materials.

Chemical order transitions within extended interfacial segregation zones in NbMoTaW

Interfacial segregation and chemical short-range ordering influence the behavior of grain boundaries in complex concentrated alloys. In this study, we use atomistic modeling of a NbMoTaW refractory complex concentrated alloy to provide insight into the interplay between these two phenomena. Hybrid Monte Carlo and molecular dynamics simulations are performed on columnar grain models to identify equilibrium grain boundary structures. Our results reveal extended near-boundary segregation zones that are much larger than traditional segregation regions, which also exhibit chemical patterning that bridges the interfacial and grain interior regions. Furthermore, structural transitions pertaining to an A2-to-B2 transformation are observed within these extended segregation zones. Both grain size and temperature are found to significantly alter the widths of these regions. An analysis of chemical short-range order indicates that not all pairwise elemental interactions are affected by the presence of a grain boundary equally, as only a subset of elemental clustering types are more likely to reside near certain boundaries. The results emphasize the increased chemical complexity that is associated with near-boundary segregation zones and demonstrate the unique nature of interfacial segregation in complex concentrated alloys.

Retainable short-range order effects on the strength and toughness of NbMoTaW refractory high-entropy alloys

Short range order (SRO) can affect the dislocation glide and twin nucleation in high-entropy alloys (HEAs), leading to varying mechanical performance. However, the mechanical implications of SRO in refractory HEAs (RHEAs) remain largely unknown due to the lack of understanding of the nanoscale deformation. Here, the role of SRO on the tensile mechanical properties of single crystal equiatomic NbMoTaW RHEAs is investigated using the hybrid Monte Carlo method and molecular dynamics simulation. We find that the presence of SRO can simultaneously enhance the strength and toughness over a wide range of temperatures under very fast strain rate. The enhancement is larger at lower temperature due to higher degree of SRO. The effects of SRO strengthening and toughening are retainable after unloading from the plastic stage, due to the unexpected twinning-assisted pseudo-elastic deformation. The fundamental principles of SRO are provided to facilitate the rational design and applications of RHEAs.

Atomic level simulations of the phase stability and stacking fault energy of FeCoCrMnSi high entropy alloy

High entropy alloys (HEAs) have many promising properties beneficial to advanced technologies. However, their underlying deformation mechanisms are largely unclear. So, as a first step, we have developed a modified embedded atom method potential for FeCoCrMnSi alloys to study such mechanisms. We predict the phase stability, chemical short-range ordering (CSRO), and stacking fault energy (SFE) of a specific alloy system using molecular dynamics (MD) and hybrid Monte-Carlo and molecular dynamics (MC/MD) simulation techniques. Room temperature MD simulations showed that both the potential energy and free energy of the single phase ε-hcp alloy is marginally more stable than the γ-fcc phase alloy, which resulted in a large, negative SFE. However, the room temperature MC/MD simulation showed an opposite trend where the γ-fcc phase was found to be more stable than the ε-hcp phase, and this resulted in a small, positive SFE. The prediction of the lower energy γ-fcc phase and resultant SFE agreed well with the experimentally reported SFE and phase stability for the Fe40Co20Cr15Mn20Si5 HEA, illustrating the importance of CSRO. Also, the calculated basal SFE of the hcp phase was close to that of the fcc phase. Therefore, the MC/MD implementation is crucial for the proper prediction of the phase stability and structural evolution in this HEA system. Many previous studies showed the ability of hybrid MC/MD technique to obtain consistent structural and configurational information of different alloy systems. The current work illustrates the potential of accelerating HEA materials development by utilizing computational methods based on the MC/MD technique which can reduce time and cost associated with experimental methods.

Surface segregation and relaxation in free-standing Ni1–x Cux alloy nanofilms

The interaction between mechanics and chemistry plays an essential and critical role in the surface segregation and relaxation in nanoscale alloys. Following the thermodynamics analysis based on surface eigenstress, the present study takes the free-standing nanometer thick films of Ni1–xCux solid solutions with face-centered cubic (fcc) crystalline structures as an example to investigate surface segregation of Cu and relaxation of the films. Hybrid Monte Carlo and Molecular Dynamics (MCMD) simulations are conducted on free-standing Ni1–xCux alloys of (100) and (111) nanofilms. The MCMD simulations verify the theoretical analytic results and determine the values of parameters involved in the theoretical analysis. Especially, the parameter of the differentiation in reference chemical potential behaves like the molar free energy of segregation in the McLean adsorption isotherm, and the differentiation in chemical composition induced eigenstrain plays also an important role in surface segregation and relaxation. The integrated theoretical and numerical study exhibits that both surface excess Cu concentration and apparent biaxial Young's modulus of Ni1–xCux nanofilms depend on the nominal Cu concentration and the film thickness.

Impact of Charge Regulation on Self-Assembly of Zwitterionic Nanoparticles.

Zwitterionic modification of colloids with weak acids and bases represents a promising strategy in creating functional materials with tunable properties and modeling the self-organization of charged proteins. However, accurate incorporation of the dynamic dissociation or association of ionization groups known as charge regulation (CR) is often intractable in theoretical and computational investigations since charge redistribution and configuration need to be evolved self-consistently. Using hybrid MonteCarlo and molecular dynamics simulations, we demonstrate that a dilute suspension of overall charge-neutral zwitterionic Janus nanoparticles shows a conformational transition from an open assembly of string or bundle to compact cluster along with the variation in pH. The behavior under CR is qualitatively different from the commonly employed constant charge condition where the transition is absent. The CR-induced clustering is due to the inhomogeneous and fluctuating charges localized near the equatorial boundary of the Janus particle. These features are enhanced particularly at low salt concentration and high electrostatic coupling strength. Our results indicate the critical role of charge regulation in the spatial self-organization of zwitterionic nanoparticles.

Claudin-15 strand flexibility and its alteration in mutant strands

Tight junction claudins polymerize across two neighboring cell membranes to form a barrier for the transport of ions and small molecules in paracellular space. Functional properties of tight junction strands are dependent on the morphology, density, and composition of these strand networks. Although how claudins self-polymerize into flexible strands is still cloaked in mystery, computational studies have shed some light on the molecular characteristics of this flexibility. We carried out all-atom and hybrid molecular dynamics simulations of claudin-15 strands between 30 and 130 nm in two parallel lipid membranes and revealed that a mutation influencing the claudin subtype-specific structure restricts the architectural flexibility of claudin strands.

Computing grain boundary diagrams of thermodynamic and mechanical properties

Computing the grain boundary (GB) counterparts to bulk phase diagrams represents an emerging research direction. Using a classical embrittlement model system Ga-doped Al alloy, this study demonstrates the feasibility of computing temperature- and composition-dependent GB diagrams to represent not only equilibrium thermodynamic and structural characters, but also mechanical properties. Specifically, hybrid Monte Carlo and molecular dynamics (MC/MD) simulations are used to obtain the equilibrium GB structure as a function of temperature and composition. Simulated GB structures are validated by aberration-corrected scanning transmission electron microscopy. Subsequently, MD tensile tests are performed on the simulated equilibrium GB structures. GB diagrams are computed for not only GB adsorption and structural disorder, but also interfacial structural and chemical widths, MD ultimate tensile strength, and MD tensile toughness. This study suggests a research direction to investigate GB composition–structure–property relationships via computing GB diagrams of thermodynamic, structural, and mechanical (or potentially other) properties.

Moisture uptake in nanocellulose: the effects of relative humidity, temperature and degree of crystallinity

Foams made from cellulose nanomaterials are highly porous and possess excellent mechanical and thermal insulation properties. However, the moisture uptake and hygroscopic properties of these materials need to be better understood for their use in biomedical and bioelectronics applications, in humidity sensing and thermal insulation. In this work, we present a combination of hybrid Grand Canonical Monte Carlo and Molecular Dynamics simulations and experimental measurements to investigate the moisture uptake within nanocellulose foams. To explore the effect of surface modification on moisture uptake we used two types of celluloses, namely TEMPO-oxidized cellulose nanofibrils and carboxymethylated cellulose nanofibrils. We find that the moisture uptake in both the cellulose nanomaterials increases with increasing relative humidity (RH) and decreases with increasing temperature, which is explained using the basic thermodynamic principles. The measured and calculated moisture uptake in amorphous cellulose (for a given RH or temperature) is higher as compared to crystalline cellulose with TEMPO- and CM-modified surfaces. The high water uptake of amorphous cellulose films is related to the formation of water-filled pores with increasing RH. The microscopic insight of water uptake in nanocellulose provided in this study can assist the design and fabrication of high-performance cellulose materials with improved properties for thermal insulation in humid climates or packaging of water sensitive goods.Graphic abstract

Highly efficient parallel grand canonical simulations of interstitial-driven diffusion-deformation processes

Absorption of interstitial alloying elements like H, O, C, and N in metals and their continuous relocation and interactions with various microstructural features such as vacancies, dislocations, and grain boundaries have crucial influences on metals’ properties. However, besides limitations in experimental tools in capturing these mechanisms, the inefficiency of numerical tools also inhibits modeling efforts. Here, we present an efficient framework to perform hybrid grand canonical Monte Carlo and molecular dynamics simulations that allow for parallel insertion/deletion of Monte Carlo moves. A new methodology for calculation of the energy difference at trial moves that can be applied to many-body potentials as well as pair ones is a primary feature of our implementation. We study H diffusion in Fe (ferrite phase) and Ni polycrystalline samples to demonstrate the efficiency and scalability of the algorithm and its application. The computational cost of using our framework for half a million atoms is a factor of 250 less than the cost of using existing libraries.

Mutations in passive residues modulate 3D-structure of NDM (New Delhi metallo-β-lactamase) protein that endue in drug resistance: a MD simulation approach

The ability of antimicrobial resistance developed by bacteria enhanced the complexity of bacterial treatment leading a serious threat to human health. Production of β-lactamase by bacteria that inactivates β-lactam is a generic cause of resistance. One such β-lactamase enzyme is New Delhi Metallo-β-lactamase (NDM) which is recently reported to have clinically more importance and recognized as an antibiotic resistance marker. Mutations in active and passive residues of NDM protein play a fateful role in the substrate and inhibitor specificity. In this study, in silico point mutations of residues near the active site and flexible regions of protein were investigated. Hybrid modelling and molecular dynamics (MD) simulations were carried to build up the mutant models and monitored structural stability. Molecular docking results articulated that mutant proteins had lesser binding affinities with methicillin, oxacillin and doripenem drugs. Further, to scrutinize the structural alterations and rescore the binding energies per-residue basis, MD simulations of wildtype (WT) and mutant (MT) NDM proteins with methicillin, oxacillin and doripenem were performed. Our results demonstrated that mutations in N193A, S217A, G219A and T262A residues led to protein destabilization and amend their binding affinities with methicillin, oxacillin and doripenem. The present study exploited computational approaches which displayed differential binding of drugs with WT and MT NDM proteins that confer resistance to oxacillin and doripenem. The study features the significance of passive residues, thus provides a clue to accelerate the process of designing an ergastic antibiotic against NDM protein. Communicated by Ramaswamy H. Sarma

Study on hydrogen-affected interaction between dislocation and grain boundary by MD simulation

Hydrogen-affected dislocation motion and hydrogen-induced intergranular fracture play key roles in hydrogen embrittlement. The quantitative characterization of H-affected interaction between dislocation and grain boundary (GB) is of great significance to understand the underlying physics of hydrogen embrittlement, which is systematically studied here by hybrid Grand Canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. The structural features of GBs are depicted through the structural unit model (SUM) and grain boundary dislocation model (GBDM). The mechanisms of interactions between dislocation and H-free/H-segregated GB arethoroughly investigated and classified. For the cases without H segregation at GB, dislocation nucleation from GB and dislocation gliding on GB are the fundamental mechanisms governing the dislocation-GB interaction. In contrast, for the cases with H segregation, the dislocation-GB interaction mechanism is changed owing to H-inhibited GB dislocation emission, dislocation transmission across GB and dislocation gliding on GB. Due to dislocation pile-up promoted by H segregation, crack initiation is facilitated at the H-segregated GB. These results can provide essential information not only for understanding H-induced intergranular fracture but also for developing an up-scaled discrete dislocation dynamics (DDD) simulation framework.

Hybrid In Silico and TR-FRET-Guided Discovery of Novel BCL-2 Inhibitors.

B-Cell lymphoma 2 (BCL-2) regulates cell death in humans. In this study, combined multiscale in silico approaches and in vitro studies were employed. A small-molecule library that includes more than 210 000 compounds was used. The predicted therapeutic activity value (TAV) of the compounds in this library was computed with the binary cancer quantitative structure-activity relationships (QSAR) model. The molecules with a high calculated TAV were used in 26 individual toxicity QSAR models. As a result of this screening protocol, 288 nontoxic molecules with high predicted TAV were identified. These selected hits were then screened against the BCL-2 target protein using hybrid docking and molecular dynamics (MD) simulations. The interaction energies of identified compounds were compared with two known BCL-2 inhibitors. Then, the short MD simulations were carried out by initiating the best docking poses of 288 molecules. Average MM/GBSA energies were computed, and long MD simulations were employed to selected hits. The same calculations were also applied for two known BCL-2 inhibitors. Moreover, a five-site (AHRRR) structure-based pharmacophore model was constructed, and this model was used in the screening of the same database. On the basis of hybrid data-driven ligand identification study, final hits were selected and used in in vitro studies. Based on results of the time-resolved fluorescence resonance energy transfer (TR-FRET) analysis, further filtration was carried out for the U87-MG cell line tests. MTT cell proliferation assay analysis results showed that selected three potent compounds were significantly effective on glioma cells.