Advanced Theory and Simulations最新文献

Here, we present a comprehensive computational evaluation of three FDA (Food and Drug Administration) approved drug leads, ZINC150338755, ZINC6716957, and ZINC203686879, as potential inhibitors targeting the Cripto/FRL-1/Cryptic (CFC) domain of the CRIPTO (Teratocarcinoma-derived growth factor1) protein. CRIPTO is a key oncogenic protein implicated in tumor progression, metastasis, and therapy resistance across multiple cancer types. Its overexpression promotes cancer stemness and survival in various tumors, such as liver cancer and glioblastoma, while its restricted expression in normal tissues makes it an attractive therapeutic target. Through an integrated approach merging molecular docking (with results −8.6 to −9.1 kcal/mol affinities), molecular dynamics (MD) simulations, molecular mechanics–generalized Born surface area (MM-GBSA) binding free energy calculations, and free energy landscape (FEL) analysis, we delineate distinct binding modes and thermodynamic fingerprints of the inhibitor complexes. Virtual screening determined the lead compounds, which were subjected to 250 ns MD simulations to check the stability and dynamics of interactions. Binding free energy calculation revealed striking disparities in binding energies (ΔG_bind from −26.83 to −57.37 kcal/mol), where Complex1 exhibited increased stability through hydrophobic superiority, Complex2 showed similar polar/nonpolar interactions, and Complex3 exhibited unique electrostatic-driven recognition. These findings shed atomic-level insight into CRIPTO-inhibitor interactions and offer a solid foundation for structure-based optimization of CRIPTO inhibitors.

Efficient thermal transmission is a necessary requirement of diversified engineering units to attain optimized output. For this purpose, the induction of tri-hybrid nanoparticles to achieve advanced heat transfer is considered as an innovative strategy because of an increase in the specific heat capacity of a system in different ways. The dispersion of silver (Ag), copper (Cu), and alumina (Al₂O₃) in water with different physical factors controlled the flow dynamics. A practical approach to enhance heat transfer effectiveness is to improve the thermal properties of the working fluid. Nanofluids, which are suspensions of nanoparticles in a base fluid, are recommended. In addition, the synergistic effects of homogeneous and heterogeneous reactions among nanoparticle interactions are also accounted for to improve overall thermal efficiency. The findings demonstrated that tri-hybrid nanofluids provide superior thermal conductivity and absorption rates compared with those of conventional fluids. A machine learning framework is employed to predict complex heat transfer behaviors and optimize system performance. Therefore, a machine learning paradigm based on an artificial neural network is used to analyze the particle concentration impacts for the estimation of the friction factor and heat transfer analysis of a water-based tri-hybrid nanofluid. The ANN model training for larger needle sizes exhibits higher accuracy and stability than that for smaller needle sizes, owing to the higher sensitivity and non-linearity, which are also indicated by the larger MSE. Validation failures remain zero in most cases, which represents fitness along with good generalization to the data.

Polydopamine (PDA) is a mussel-inspired material with remarkable adhesive properties and a wide range of applications. There has been significant interest in understanding the structure of the PDA coating itself, as well as the PDA/substrate interaction. In this study, the adsorption of model monomers and oligomers on defect-free graphene is examined computationally. The adsorption of 5,6-dihydroxyindole (DHI) and its oxidized form, dopaminechrome (DAC), on perfect graphene is studied using the DFT formalism under periodic conditions. Non-covalent and covalent dimers adsorption is considered, taking into account different possible arrangements to establish the role of stacking configurations and aryl-aryl, pyrrole-pyrrole and aryl-pyrrole valence bonds. A theoretical extension is developed to compute the adsorption energy for covalent trimers. The results show that adsorbates predominantly composed of DAC monomers are preferred candidates for the growth of an oligomeric structure. The reaction energy required to produce covalent dimers is thermodynamically more feasible when a free monomer reacts with a monomer that has already been adsorbed than when two monomers react as free species. A particular analysis of the interaction forces between monomers or dimers and perfect graphene is performed to predict the rupture of the adsorbate/substrate system.

This article focuses on the study of solid tumours, particularly malignant ones, through the use of sophisticated mathematical model aimed at explaining their growth, which is primarily driven by cellular proliferation. Among these, gliomas, one of the most severe forms of brain cancer, are notable for their distinct behaviour, marked by deep infiltration into surrounding tissues. We primarily focus on studying a specific type of glioma known as glioblastoma multiforme using the brain tumour growth model governed by the Burgess equation. To achieve this, we implement a hybrid numerical scheme which is combination of polynomial differential quadrature method and best four-stage, third-order strong stability-preserving time-stepping Runge–Kutta (SSP-RK43) algorithm. The stability of the proposed method is also studied using matrix method. Moreover, the order of convergence of the proposed scheme is presented. The proposed scheme is simulated and tested on some test examples. We compare the results with the existing methods in terms of error. The computational time for each example is presented. The low computational cost demonstrates the efficiency of the proposed scheme.

In this work, we present an analytical solution of Schrödinger equation of confined pseudoharmonic potential in the presence of a moving boundary condition for an arbitrary angular momentum state. It turns out that an important quantity to probe the problem is the internuclear distance ratio, which depends on the solution of Ermakov equation. The minimum value of the time-dependent (TD) Heisenberg uncertainty product always remains greater than that of the minimum uncertainty product $��\hslash �/�2�$. The TD average energy is derived analytically in a closed form, and the corresponding average force and average pressure are defined. Moreover, the time correlation function of two states for the case of six selected diatomic molecules (CO, NO, ScH, CH, $�H_2$, $�N_2$) is obtained. It is found to depend on the internuclear distance ratio at two different time domains. The TD survival probability and average life-time of a molecule in a confined quantum system are defined. Expressions are offered for quantum similarity measure, dissimilarity, and quantum similarity index. The latter is given for a pair of molecules. The obtained results are compared with available literature, wherever possible. To our knowledge this is the first detailed report of a non-harmonic central potential in a TD moving boundary condition.

This work is done to understand the mechanistic details of the excited state non-adiabatic process of diazirine and three other derivatives that are substituted with electron-donating (methoxy-diazirine) and withdrawing (fluoro-diazirine) groups, as well as combining both (fluoro-methoxy-diazirine), to study their effect on generating carbene and molecular nitrogen via diazomethane. All electronic structure calculations are performed at SA2-CASSCF followed by MS-CASPT2 levels of theory, and non-adiabatic molecular dynamics simulations at SA2-CASSCF level by choosing appropriate active spaces. Two conical intersections (CIs) are found for each of the molecules in the non-adiabatic process, which are associated with asymmetric vibrations of the C─N bonds in the three-membered ring of the diazirines, except for pure diazirine, where the second CI is associated with symmetric vibration. The dynamics starts from n-π* excited state (S₁). In the dynamics, trajectories are seen to go through both the CIs whichever is energetically and dynamically permissible. The first-order kinetics of N₂ formation revealed that the reaction is fastest for pure diazirine and slowest for fluoro-methoxy-diazirine. The mechanism, as revealed from the present calculation, looks so reliable that an MS-CASPT2 dynamics, if performed, would perhaps change the population in each pathway, leading to different rate constants of N₂ formation, but the number of pathways and the trend of rate constants may remain the same.