![]() Among the above compounds, Ellagic acid showed the high binding affinity against all three breast cancer biomarkers. Four phytochemicals with a higher binding affinity were chosen for each breast cancer biomarker to study their stability in interaction with the target proteins using MD simulation. Analyzing the pharmacokinetic properties and toxicity prediction results indicated that the fifteen selected plant compounds have good potency without toxicity and are safe for humans. ![]() ![]() The best docking interaction was chosen based on the higher binding affinity. Twenty plant compounds extracted from the rambutan (Nephelium lappaceum) were obtained from PubChem Database and screened against the breast cancer biomarkers including estrogen receptor (ER), progesterone receptor (PR), and androgen receptor (AR). A comprehensive substrate-based drug design was carried out to discover the potential plant compounds against the target breast cancer biomarkers including phytochemicals screening, active site identification, molecular docking, pharmacokinetic (PK) properties prediction, toxicity prediction, and molecular dynamics (MD) simulation approaches. This study has been designed to discover target-based small molecular-like natural drug candidates that have anti-cancer potential without causing any serious side effects. To date, no effective drug has been discovered to block the proliferation of breast cancer cells. Overexpression of various prognostic indicators, including nuclear receptors, is linked to breast cancer features. Worldwide, breast cancer is the leading type of cancer among women. Our novel approach combining NMA with multivariate linear regression is generalizable to any macromolecule for which relatively high-throughput mutational data is available. When training the linear regression model using all available data, the dynamical features identified as necessary for miR-125a maturation point to known patterns but also offer new insights into the biogenesis of microRNAs. This ability translates to better predictive power on a second benchmark in which sequence features are shared between the train and test sets. ![]() A stringent benchmark from the miR-125a maturation dataset, in which the training set contains no sequence information in common with the testing set, reveals that ENCoM is the only tested model able to capture signal beyond the sequence. ENCoM has a similar performance profile on RNA than on proteins when compared to the Anisotropic Network Model (ANM), the most widely used coarse-grained NMA model it has the advantage on predicting large-scale motions while ANM performs better on B-factors prediction. We also introduce a novel way of using dynamical information from NMA to train multivariate linear regression models, with the purpose of highlighting the most salient contributions of dynamics to function. We adapted ENCoM to simulate the dynamics of ribonucleic acid (RNA) molecules, benchmarked its performance against other popular NMA models and used it to study the 3D structural dynamics of human microRNA miR-125a, leveraging high-throughput experimental maturation efficiency data of over 26 000 sequence variants. The Elastic Network Contact Model (ENCoM) is a coarse-grained normal mode analysis (NMA) model unique in its all-atom sensitivity to the sequence of the studied macromolecule and thus to the effect of mutations. This study confirmed the potential applications of CDs as molecular stabilizers and aqueous solubilizers for the improved bioavailability and efficient delivery of food bioactive compounds. Perpendicular conformations of the pharmaceutically active forms of PRT (1) and PRZ (2) are first observed crystallographically. The induced-fit process yielded thermodynamically stable complexes 2 > 1 > 3, in agreement with the density functional theory (DFT)-optimized structures with the corresponding number of intermolecular OH∙∙∙O H-bonds (7 > 3 > 1). Single-crystal X-ray diffraction (XRD) revealed that one PRZ (2) and one FEA (3) insert the aromatic B-ring and C=C–C=O(O) group respectively into the β-CD (2) and α-CD (3) cavities, whereas a half-occupied PRT (1) inserts the B-ring across the β-CD cavity. This study aimed to provide atomistic insights of β-CD–PRT (1), β-CD–PRZ (2), and α-CD–FEA (3) complexes. Phloretin (PRT), phlorizin (PRZ), and ferulic acid (FEA) prevalent in apples are unstable and less soluble in water, which can be improved by cyclodextrin (CD) encapsulation.
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