Advanced Molecular Dynamics Simulations Research Articles

Mechanistic insights into P-glycoprotein ligand transport and inhibition revealed by enhanced molecular dynamics simulations

P-glycoprotein (P-gp) plays a crucial role in cellular detoxification and drug efflux processes, transitioning between inward-facing (IF) open, occluded, and outward-facing (OF) states to facilitate substrate transport. Its role is critical in cancer therapy, where P-gp contributes to the multidrug resistance phenotype. In our study, classical and enhanced molecular dynamics (MD) simulations were conducted to dissect the structural and functional features of the P-gp conformational states. Our advanced MD simulations, including kinetically excited targeted MD (ketMD) and adiabatic biasing MD (ABMD), provided deeper insights into state transition and translocation mechanisms. Our findings suggest that the unkinking of TM4 and TM10 helices is a prerequisite for correctly achieving the outward conformation. Simulations of the IF-occluded conformations, characterized by kinked TM4 and TM10 helices, consistently demonstrated altered communication between the transmembrane domains (TMDs) and nucleotide binding domain 2 (NBD2), suggesting the implication of this interface in inhibiting P-gp's efflux function. A particular emphasis was placed on the unstructured linker segment connecting the NBD1 to TMD2 and its role in the transporter's dynamics. With the linker present, we specifically noticed a potential entrance of cholesterol (CHOL) through the TM4-TM6 portal, shedding light on crucial residues involved in accommodating CHOL. We therefore suggest that this entry mechanism could be employed for some P-gp substrates or inhibitors. Our results provide critical data for understanding P-gp functioning and developing new P-gp inhibitors for establishing more effective strategies against multidrug resistance.

Superdiffusive Rotation of Interfacial Water on Noble Metal Surface.

Interfacial water on a metal surface acts as an active layer through the reorientation of water, thereby facilitating the energy transfer and chemical reaction across the metal surface in various physicochemical and industrial processes. However, how this active interfacial water collectively behaves on flat noble metal substrates remains largely unknown due to the experimental limitation in capturing librational vibrational motion of interfacial water and prohibitive computational costs at the first-principles level. Herein, by implementing a machine-learning approach to train neural network potentials, we enable performing advanced molecular dynamics simulations with ab initio accuracy at a nanosecond scale to map the distinct rotational motion of water molecules on a metal surface at room temperature. The vibrational density of states of the interfacial water with two-layer profiles reveals that the rotation and vibration of water within the strong adsorption layer on the metal surface behave as if the water molecules in the bulk ice, wherein the O-H stretching frequency is well consistent with the experimental results. Unexpectedly, the water molecules within the adjacent weak adsorption layer exhibit superdiffusive rotation, contrary to the conventional diffusive rotation of bulk water, while the vibrational motion maintains the characteristic of bulk water. The mechanism underlying this abnormal superdiffusive rotation is attributed to the translation-rotation decoupling of water, in which the translation is restrained by the strong hydrogen bonding within the bilayer interfacial water, whereas the rotation is accelerated freely by the asymmetric water environment. This superdiffusive rotation dynamics may elucidate the experimentally observed large fluctuation of the potential of zero charge on Pt and thereby the conventional Helmholtz layer model revised by including the contribution of interfacial water orientation. The surprising superdiffusive rotation of vicinal water next to noble metals will shed new light on the physicochemical processes and the activity of water molecules near metal electrodes or catalysts.

Interplay of precision therapeutics and MD study: Calocybe indica's potentials against cervical cancer and its interaction with VEGF via octadecanoic acid.

The evolving landscape of personalized medicine necessitates a shift from traditional therapeutic interventions towards precision-driven approaches. Embracing this paradigm, our research probes the therapeutic efficacy of the aqueous crude extract (ACE) of Calocybe indica in cervical cancer treatment, merging botanical insights with advanced molecular research. We observed that ACE exerts significant influences on nuclear morphology and cell cycle modulation, further inducing early apoptosis and showcasing prebiotic attributes. Characterization of ACE have identified several phytochemicals including significant presence of octadeconoic acid. Simultaneously, utilizing advanced Molecular Dynamics (MD) simulations, we deciphered the intricate molecular interactions between Vascular Endothelial Growth Factor (VEGF) and Octadecanoic acid to establish C.indica's role as an anticancer agent. Our study delineates Octadecanoic acid's potential as a robust binding partner for VEGF, with comprehensive analyses from RMSD and RMSF profiles highlighting the stability and adaptability of the protein-ligand interactions. Further in-depth thermodynamic explorations via MM-GBSA calculations reveal the binding landscape of the VEGF-Octadecanoic acid complex. Emerging therapeutic innovations, encompassing proteolysis-targeting chimeras (PROTACs) and avant-garde nanocarriers, are discussed in the context of their synergy with compounds like Calocybe indica P&C. This convergence underscores the profound therapeutic potential awaiting clinical exploration. This study offers a holistic perspective on the promising therapeutic avenues facilitated by C. indica against cervical cancer, intricately woven with advanced molecular interactions and the prospective integration of precision therapeutics in modern oncology.

Multidimensional decipherment of interactions in invert sugar–amino acid co-degradation colorants (IACDCs) capture by polyamine co-modified shaddock peel cellulose/graphene oxide aerogel

The development of an environmentally friendly scavenger with an outstanding ability to eliminate IACDCs from molasses-based distillery wastewater is essential for the safety of aquatic ecosystems and organisms. By combining polyamine co-modified shaddock peel cellulose (SPC) and graphene oxide (GO), a multistage porous aerogel (i.e., CP-GO/SPA) was constructed for the highly effective capture of IACDCs. CP-GO/SPA exhibited a surprisingly high IACDC adsorption capacity (1157 mg/g, which was 1.5–100 times that of previously reported ones). It also had an ultrafast adsorption mass transfer (AMT) rate. Advanced AMT-resistance models reveal that the capture on active site is the main AMT resistance, whereas liquid-film and pore diffusion are quite fast. CP-GO/SPA exhibited excellent reusability (>90% IACDC removal efficiency after six cycles) and considerable potential for industrial applications (i.e., treatment of actual wastewater by fixed-bed adsorption). The polyamine co-modified SPC and GO endowed CP-GO/SPA with substantial amine groups and high affinity for water, as validated by advanced molecular dynamics simulations. These features are extremely conducive for capturing electronegative and water-soluble IACDCs. A series of characterizations and multiple quantum chemical theory calculations (including ETP, ALIE, FMOs, IGM, and HIS analyses) further revealed the adsorption mechanisms from a molecular perspective. The IACDC capture by CP-GO/SPA resulted from charge, electron sharing, and van der Waals interactions. However, charge interactions played a dominant role. The optimal capture configurations were visualized at the molecular level, and the H-bond donor–acceptor relationship was determined. The IACDCs act as H-bond acceptors in a diverse range of capture configurations.

Monitoring water harvesting in metal-organic frameworks, one water molecule at a time.

Metal-organic frameworks (MOFs) have gained prominence as potential materials for atmospheric water harvesting, a vital solution for arid regions and areas experiencing severe water shortages. However, the molecular factors influencing the performance of MOFs in capturing water from the air remain elusive. Among all MOFs, Ni2X2BTDD (X = F, Cl, Br) stands out as a promising water harvester due to its ability to adsorb substantial amounts of water at low relative humidity (RH). Here, we use advanced molecular dynamics simulations carried out with the state-of-the-art MB-pol data-driven many-body potential to monitor water adsorption in the three Ni2X2BTDD variants as a function of RH. Our simulations reveal that the type of halide atom in the three Ni2X2BTDD frameworks significantly influences the corresponding molecular mechanisms of water adsorption: while water molecules form strong hydrogen bonds with the fluoride atoms in Ni2F2BTDD, they tend to form hydrogen bonds with the nitrogen atoms of the triazolate linkers in Ni2Cl2BTDD and Ni2Br2BTDD. Importantly, the large size of the bromide atoms reduces the void volume in the Ni2Br2BTDD pores, which enable water molecules to initiate an extended hydrogen-bond network at lower RH. These findings not only underscore the prospect for precisely tuning structural and chemical modifications of the frameworks to optimize their interaction with water, but also highlight the predictive power of simulations with the MB-pol data-driven many-body potential. By providing a realistic description of water under different thermodynamic conditions and environments, these simulations yield unique, molecular-level insights that can guide the design and optimization of energy-efficient water harvesting materials.

Silicon phase transitions in nanoindentation: Advanced molecular dynamics simulations with machine learning phase recognition

Closing the gap between experiments and simulations in the investigation of high-pressure silicon phase transitions calls for advanced, new-generation modeling approaches. By exploiting massive parallelization, we here provide molecular dynamics (MD) simulations of Si nanoindentation based on the Gaussian Approximation Potential (GAP). Results are analyzed by exploiting a customized Neural Network Phase Recognition (NN-PR) approach, helping to shed light on the phase transitions occurring during the simulations. Our results show that GAP provides a realistic description of silicon phase transitions. With the support of NN-PR method, the formation mechanism and stability of high-pressure phases are comprehensively studied. Additionally, we also show how simulations based on the less demanding and widely-used Tersoff potential are still useful to investigate the role played by the indenter tip modeling. However, high-pressure phases obtained with GAP are more consistent with observations made in nanoindentation experiments, removing a spurious phase that is shown by Tersoff simulations. This behavior is explained on the base of relative phase stability with comparison with Density Functional Theory (DFT) calculations. This work provides insight into the application of state-of-the-art Machine Learning (ML) methods on nanoindentation simulations, enabling further understanding of the phase transition mechanisms in silicon.

A Study on the Microscopic Properties of the Oil–Stone Interfacial Phase of a Reclaimed Asphalt Mixture Based on Molecular Dynamics Simulation

In recent years, there has been a growing body of research focused on aged asphalt and recycled asphalt. Nevertheless, despite diligent endeavors, the precise micro-interaction mechanism occurring at the interface of weathered asphalt, reclaimed asphalt, and aggregates still eludes our understanding. This study leveraged molecular dynamics simulation technology to scrutinize the inherent behavior of aged asphalt and recycled asphalt at the micro-scale, elucidating the intricate interaction mechanism occurring at the interface of recycled asphalt, aged asphalt, and aggregates. The diffusion and adhesion properties of three distinct asphalt–aggregate interfaces were meticulously compared and comprehensively analyzed using advanced molecular dynamics simulation techniques. The findings revealed a substantial decline in the performance of aged asphalt, while the diffusion and adhesion properties of recycled asphalt were observed to be largely restored, reaching a remarkable level of approximately 85% in comparison to aged asphalt. The high-temperature performance, low-temperature performance, and water stability characteristics of both aged the asphalt mixture and recycled asphalt mixture were thoroughly investigated through rigorous laboratory testing of the asphalt mixtures. Based on the experimental findings, it was observed that the overall performance of the aged asphalt mixture exhibited a reduction of approximately 40%. However, through the process of regeneration, the overall performance of the asphalt mixture could be restored to approximately 90% of its non-aged counterpart.

Intelligent design and construction of novel APN-based theranostic probe driven by advanced computational methods

Multifunctional molecules with both optical signal and pharmacological activity play an important role in drug development, disease diagnosis, and basic theoretical research. Aminopeptidase N (APN), as a representative tumor biomarker with anti-tumor potential, still lacks a high-precision theranostic probe specifically targeting it. In this study, a novel quaternity design strategy for APN theranostic probe was developed. This proposed strategy utilizes advanced machine learning and molecular dynamics simulations, and cleverly employs the strategy of conformation-induced fluorescence recovery to achieve multi-objective optimization and integration of functional fragments. Through this strategy, a unique “Off–On” theranostic probe, ABTP-DPTB, was ingeniously constructed to light up APN through fluorescence restoration, relying on conformation-induced effects and solvent restriction. Differ from the common diagnostic probes, the intelligent design with non-substrated linkage makes ABTP-DPTB for long-term in-situ imaging. The fabricated probe was used for detecting and inhibiting APN in various environments, with a better in vitro inhibitory than golden-standard drug bestatin.

Molecular Crowders Can Induce Collapse in Hydrophilic Polymers via Soft Attractive Interactions.

A comprehensive understanding of protein folding and biomolecular self-assembly in the intracellular environment requires obtaining a microscopic view of the crowding effects. The classical view of crowding explains biomolecular collapse in such an environment in terms of the entropic solvent excluded volume effects subjected to hard-core repulsions exerted by the inert crowders, neglecting their soft chemical interactions. In this study, the effects of nonspecific, soft interactions of molecular crowders in regulating the conformational equilibrium of hydrophilic (charged) polymers are examined. Using advanced molecular dynamics simulations, collapse free energies of an uncharged, a negatively charged, and a charge-neutral 32-mer generic polymer are computed. The strength of the polymer-crowder dispersion energy is modulated to examine its effect on polymer collapse. The results show that the crowders preferentially adsorb and drive the collapse of all three polymers. The uncharged polymer collapse is opposed by the change in solute-solvent interaction energy but is overcompensated by the favorable change in the solute-solvent entropy as observed in hydrophobic collapse. However, the negatively charged polymer collapses with a favorable change in solute-solvent interaction energy due to reduction in the dehydration energy penalty as the crowders partition to the polymer interface and shield the charged beads. The collapse of a charge-neutral polymer is opposed by the solute-solvent interaction energy but is overcompensated by the solute-solvent entropy change. However, for the strongly interacting crowders, the overall energetic penalty decreases since the crowders interact with polymer beads via cohesive bridging attractions to induce polymer collapse. These bridging attractions are found to be sensitive to the binding sites of the polymer, since they are absent in the negatively charged or uncharged polymers. These interesting differences in thermodynamic driving forces highlight the crucial role of the chemical nature of the macromolecule as well as of the crowder in determining the conformational equilibria in a crowded milieu. The results emphasize that the chemical interactions of the crowders should be explicitly considered to account for the crowding effects. The findings have implications in understanding the crowding effects on the protein free energy landscapes.

Molecular dynamics simulations reveal the hidden EF-hand of EF-SAM as a possible key thermal sensor for STIM1 activation by temperature

Intracellular calcium signaling is essential for many cellular processes, including store-operated Ca2+ entry (SOCE), which is initiated by stromal interaction molecule 1 (STIM1) detecting endoplasmic reticulum (ER) Ca2+ depletion. STIM1 is also activated by temperature independent of ER Ca2+ depletion. Here we provide evidence, from advanced molecular dynamics simulations, that EF-SAM may act as a true temperature sensor for STIM1, with the prompt and extended unfolding of the hidden EF-hand subdomain (hEF) even at slightly elevated temperatures, exposing a highly conserved hydrophobic Phe108. Our study also suggests an interplay between Ca2+ and temperature sensing, as both, the canonical EF-hand subdomain (cEF) and the hidden EF-hand subdomain (hEF), exhibit much higher thermal stability in the Ca2+-loaded form compared to the Ca2+-free form. The SAM domain, surprisingly, displays high thermal stability compared to the EF-hands and may act as a stabilizer for the latter. We propose a modular architecture for the EF-hand-SAM domain of STIM1 composed of a thermal sensor (hEF), a Ca2+ sensor (cEF), and a stabilizing domain (SAM). Our findings provide important insights into the mechanism of temperature-dependent regulation of STIM1, which has broad implications for understanding the role of temperature in cellular physiology.

Diffusion coefficient and the volume swelling of CO2/light oil systems: Insights from dynamic volume analysis and molecular dynamics simulation

The oil volume expansion and CO2 diffusion are one of the main mechanism of CO2-enhanced oil recovery (CO2-EOR). This paper established a series of experiments, numerical simulations, and molecular dynamics (MD) simulations to describe mass transfer behaviors between oil–gas phases. Expressly, the CO2 diffusion coefficient and light oil swelling factor are signification parameters to quantify and analyze these behaviors. In detail, the CO2 diffusion coefficient and the oil swelling factor were obtained from the traditional pressure decay method and the advanced MD simulation. Synthetically, the pressure decay method and MD simulation results were mutually verified. The results showed that the equilibrium pressure was proportional to the mole fraction of CO2 and inversely proportional to the mole fraction of light oil. The equilibrium time was proportional to the mole fraction of CO2 and light oil. At the temperature of 333.15 K and the initial pressure of 7.5 MPa, the CO2 diffusion coefficient in light oil was positively correlated with the relative molar proportion of CO2, while the light oil swelling factor was vice versa. In addition, the closer to the CO2-light oil interface, the greater the light oil's potential energy and self-diffusion coefficient, and the stronger the transport ability.

Structural dynamics and mechanistic action guided engineering of lipolytic enzymes.

Lipases have been established as important biocatalysts in several industrial applications, owing to their diverse substrate specificity. The availability of data on three-dimensional crystal structures for various lipases offers an opportunity for modulating their structural and functional aspects to design and engineer better versions of lipases. With the aim of investigating the structural components governing the extremophilic behavior of lipases, structural analysis of microbial lipases was performed using advanced bioinformatics and molecular dynamics simulation approaches. In sequences and functionally distinct alkaliphilic and thermophilic lipases were investigated for their functional properties to understand the distinguishing features of their structures. The alkaliphilic lipase from Bacillus subtilis (LipA) showed conformational changes in the loop region Ala132-Met137, subsequently, the active site residue His156 shows two conformations, toward the active site nucleophilic residues Ser77 and away from the Ser77. Interestingly, the active site of LipA is more solvent-exposed and can be correlated with the adoption of an open conformation which might extend and expose the active site region to solvents during the catalysis process. Furthermore, the MD simulation of thermophilic lipase from marine Streptomyces (MAS1) revealed the role of N- and C-terminal regions with disulfide bridges and identified a metal ion binding site that facilitates the enzyme stability. The novel thermo-alkaliphilic lipase can be designed to integrate the stability features of MAS1 into the alkaliphilic LipA. These structural-level intrinsic characteristics can be used for lipase engineering to amend the lipase activity and stability as per the requirements of the industrial processes.

Recent Advances in Molecular Dynamics Simulations of Tau Fibrils and Oligomers

The study of tau protein aggregation and interactions with other molecules or solvents using molecular dynamics simulations (MDs) is of interest to many researchers to propose new mechanism-based therapeutics for neurodegenerative diseases such as Alzheimer's disease, Pick's disease, chronic traumatic encephalopathy, and other tauopathies. In this review, we present recent MD simulation studies of tau oligomers and fibrils such as tau-NPK, tau-PHF, tau-K18, and tau-R3-R4 monomers and dimers. All-atom simulations by replica exchange MDs and coarse-grained MDs in lipid bilayers and in solution were used. The simulations revealed different mechanisms in the binding of tau in bilayers and in solutions, depending on the peptide size. Phosphorylation is also an important factor in MD simulations. The use of steered MDs was also included to simulate the dissociation of tau fibrils. The exponential improvement in the computing power of computers has led to an increasing number of scientists and engineers using a cost-effective, high-performance computing platform to study how the tau protein interacts and the effects of changing its structure, such as the phosphorylation of tau fibrils.

Probing Temperature Responsivity of Microgels and Its Interplay with a Solid Surface by Super-Resolution Microscopy and Numerical Simulations.

Super-resolution microscopy has become a powerful tool to investigate the internal structure of complex colloidal and polymeric systems, such as microgels, at the nanometer scale. An interesting feature of this method is the possibility of monitoring microgel response to temperature changes in situ. However, when performing advanced microscopy experiments, interactions between the particle and the environment can be important. Often microgels are deposited on a substrate, since they have to remain still for several minutes during the experiment. This study uses direct stochastic optical reconstruction microscopy (dSTORM) and advanced coarse-grained molecular dynamics simulations to investigate how individual microgels anchored on hydrophilic and hydrophobic surfaces undergo their volume phase transition with temperature. We find that, in the presence of a hydrophilic substrate, the structure of the microgel is unperturbed and the resulting density profiles quantitatively agree with simulations performed under bulk conditions. Instead, when a hydrophobic surface is used, the microgel spreads at the interface and an interesting competition between the two hydrophobic strengths,monomer-monomer vs monomer-surface,comes into play at high temperatures. The robust agreement between experiments and simulations makes the present study a fundamental step to establish this high-resolution monitoring technique as a platform for investigating more complex systems, these being either macromolecules with peculiar internal structure or nanocomplexes where molecules of interest can be encapsulated in the microgel network and controllably released with temperature.

Molecular dynamics simulations reveal membrane lipid interactions of the full-length lymphocyte specific kinase (Lck)

The membrane-bound lymphocyte-specific protein-tyrosine kinase (Lck) triggers T cell antigen receptor signalling to initiate adaptive immune responses. Despite many structure–function studies, the mode of action of Lck and the potential role of plasma membrane lipids in regulating Lck’s activity remains elusive. Advances in molecular dynamics simulations of membrane proteins in complex lipid bilayers have opened a new perspective in gathering such information. Here, we have modelled the full-length Lck open and closed conformations using data available from different crystalographic studies and simulated its interaction with the inner leaflet of the T cell plasma membrane. In both conformations, we found that the unstructured unique domain and the structured domains including the kinase interacted with the membrane with a preference for PIP lipids. Interestingly, our simulations suggest that the Lck-SH2 domain interacts with lipids differently in the open and closed Lck conformations, demonstrating that lipid interaction can potentially regulate Lck’s conformation and in turn modulate T cell signalling. Additionally, the Lck-SH2 and kinase domain residues that significantly contacted PIP lipids are found to be conserved among the Src family of kinases, thereby potentially representing similar PIP interactions within the family.

Intrinsically disordered ectodomain modulates ion permeation through a metal transporter

The function of many channels and transporters is enriched by the conformational plasticity of intrinsically disordered regions (IDRs). Copper transporter 1 (Ctr1) is the main entry point for Cu(I) ions in eukaryotes and contains IDRs both at its N-terminal (Nterm) and C-terminal ends. The former delivers copper ions from the extracellular matrix to the selectivity filter in the Ctr1 lumen. However, the molecular mechanism of this process remains elusive due to Nterm's disordered nature. Here, we combine advanced molecular dynamics simulations and circular dichroism experiments to show that Cu(I) ions and a lipidic environment drive the insertion of the Nterm into the Ctr1 selectivity filter, causing its opening. Through a lipid-aided conformational switch of one of the transmembrane helices, the conformational change of the selectivity filter propagates down to the cytosolic gate of Ctr1. Taken together, our results elucidate how conformational variability of IDRs modulates ion transport.

Neurotrophic Activity and Its Modulation by Zinc Ion of a Dimeric Peptide Mimicking the Brain-Derived Neurotrophic Factor N-Terminal Region.

Brain-derived neurotrophic factor (BDNF) is a neurotrophin (NT) essential for neuronal development and synaptic plasticity. Dysregulation of BDNF signaling is implicated in different neurological disorders. The direct NT administration as therapeutics has revealed to be challenging. This has prompted the design of peptides mimicking different regions of the BDNF structure. Although loops 2 and 4 have been thoroughly investigated, less is known regarding the BDNF N-terminal region, which is involved in the selective recognition of the TrkB receptor. Herein, a dimeric form of the linear peptide encompassing the 1-12 residues of the BDNF N-terminal (d-bdnf) was synthesized. It demonstrated to act as an agonist promoting specific phosphorylation of TrkB and downstream ERK and AKT effectors. The ability to promote TrkB dimerization was investigated by advanced fluorescence microscopy and molecular dynamics (MD) simulations, finding activation modes shared with BDNF. Furthermore, d-bdnf was able to sustain neurite outgrowth and increase the expression of differentiation (NEFM, LAMC1) and polarization markers (MAP2, MAPT) demonstrating its neurotrophic activity. As TrkB activity is affected by zinc ions in the synaptic cleft, we first verified the ability of d-bdnf to coordinate zinc and then the effect of such complexation on its activity. The d-bdnf neurotrophic activity was reduced by zinc complexation, demonstrating the role of the latter in tuning the activity of the new peptido-mimetic. Taken together our data uncover the neurotrophic properties of a novel BDNF mimetic peptide and pave the way for future studies to understand the pharmacological basis of d-bdnf action and develop novel BDNF-based therapeutic strategies.

Corrosion protection mechanisms of graphene oxide-reinforced polypropylene coating for mild carbon steel by advanced molecular dynamics simulations with emphasis on resistance to water and chloride ion penetration

Polypropylene can be used as a raw material for manufacturing corrosion-resistant coatings to protect the surface of the mild carbon steel substrate. To improve the properties of polypropylene (PP), graphene oxide (GO) can be added to the coating. In this research, molecular dynamics (MD) simulations were employed to evaluate the effect of GO additives on the PP coating using COMPASS Force-Filed of the Forcite module. The results of molecular modeling, such as mean square displacement (MSD), diffusion coefficient, concentration profile, and gyration radius (Rg), revealed that the permeability of corrosive agents, including water molecules and chloride ions in the composite coating (PP/GO), is much lower than pure one (PP). In addition, by reducing the surface energy from 77 to 68 mJ/m2, the water contact angle (WCA) is improved from 150◦ for the pure PP coating to 170◦ for the composite one. It can also be due to an 18% increase in system compaction in the presence of GO. In the other hand, the free fraction volume (FFV) in the presence of GO is reduced by about 4%. The adhesion of the coating to the mild carbon steel substrate has also been ameliorated by 38% for the PP/GO coating compared to the pure PP. Therefore, most of the simulated parameters reported the positive effects of compositing PP with GO.

Characterizing (un)binding mechanism of USP7 inhibitors to unravel the cause of enhanced binding potencies at allosteric checkpoint.

The ability to predict the intricate mechanistic behavior of ligands and associated structural determinants during protein-ligand (un)binding is of great practical importance in drug discovery. Ubiquitin specific protease-7 (USP7) is a newly emerging attractive cancer therapeutic target with bound allosteric inhibitors. However, none of the inhibitors have reached clinical trials, allowing opportunities to examine every aspect of allosteric modulation. The crystallographic insights reveal that these inhibitors have common properties such as chemical scaffolds, binding site and interaction fingerprinting. However, they still possess a broader range of binding potencies, ranging from 22 nM to 1,300 nM. Hence, it becomes more critical to decipher the structural determinants guiding the enhanced binding potency of the inhibitors. In this regard, we elucidated the atomic-level insights from both interacting partners, that is, protein-ligand perspective, and established the structure-activity link between USP7 inhibitors by using classical and advanced molecular dynamics simulations combined with linear interaction energy and molecular mechanics-Poisson Boltzmann surface area. We revealed the inhibitor potency differences by examining the contributions of chemical moieties and USP7 residues, the involvement of water-mediated interactions, and the thermodynamic landscape alterations. Additionally, the dissociation profiles aided in the establishment of a correlation between experimental potencies and structural determinants. Our study demonstrates the critical role of blocking loop 1 in allosteric inhibition and enhanced binding affinity. Comprehensively, our findings provide a constructive expansion of experimental outcomes and show the basis for varying binding potency using in-silico approaches. We expect this atomistic approach to be useful for effective drug design.

Gmxapi: A GROMACS-native Python interface for molecular dynamics with ensemble and plugin support.

Gmxapi provides an integrated, native Python API for both standard and advanced molecular dynamics simulations in GROMACS. The Python interface permits multiple levels of integration with the core GROMACS libraries, and legacy support is provided via an interface that mimics the command-line syntax, so that all GROMACS commands are fully available. Gmxapi has been officially supported since the GROMACS 2019 release and is enabled by default in current versions of the software. Here we describe gmxapi 0.3 and later. Beyond simply wrapping GROMACS library operations, the API permits several advanced operations that are not feasible using the prior command-line interface. First, the API allows custom user plugin code within the molecular dynamics force calculations, so users can execute custom algorithms without modifying the GROMACS source. Second, the Python interface allows tasks to be dynamically defined, so high-level algorithms for molecular dynamics simulation and analysis can be coordinated with loop and conditional operations. Gmxapi makes GROMACS more accessible to custom Python scripting while also providing support for high-level data-flow simulation algorithms that were previously feasible only in external packages.