In silico ADMET, molecular docking and molecular simulation-based study of glabridin’s natural and semisynthetic derivatives as potential tyrosinase inhibitors

Investigation and drug design for novel molecules from natural products as inhibitors for controlling multiple myeloma disease using in-silico tools

Multiple myeloma (MM) is a disease that causes plasma cell growth in the bone marrow and immune globulin buildup in blood and urine. Despite recent advances in MM therapy, many still die due to its high mortality rate. A study using computational simulations analyzed 100 natural ingredients from the SANC database to determine if they inhibited the IgH domain, a known cause of multiple myeloma. Natural component Diospyrin inhibited the IgH enzyme with the best binding energy of -10.3 kcal/mol and three carbon-hydrogen bonds, followed by Parviflorone F complex with a binding energy of -10.1 kcal/mol and two conventional-hydrogen bonds. As a result, the Molecular Dynamic simulation was used to test the stability of the two complexes. During the simulation, the Diospyrin molecule dissociated from the protein at roughly 67.5 ns, whereas the Parviflorone F molecule stayed attached to the protein throughout. The latter was the subject of the investigation. The analysis of the production run data revealed that the Parviflorone F molecule exhibits a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The analysis of the production run data revealed that the Parviflorone F molecule exhibited a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The root mean square deviation (RMSD) plots for both the protein and complex showed a stable and steady average value of 4.4 Å for the first 82 nanoseconds of manufacture. As a result, the average value increased to 8.3 Å. Furthermore, the components of the binding free energy, as computed by MM-GBSA, revealed that the mean binding energy of the Parviflorone F molecule was -23.88 kcal/mol. Finally, after analyzing all of the examination data, Parviflorone F was identified as a powerful inhibitor of the IgH domain and hence of the MM disease, which requires further in-vivo conformation.

Unveiling the tyrosinase inhibitory potential of phenolics from Centaurium spicatum: Bridging in silico and in vitro perspectives

Phenolics, abundant in plants, constitute a significant portion of phytoconstituents consumed in the human diet. The phytochemical screening of the aerial parts of Centaurium spicatum led to the isolation of five phenolics. The anti-tyrosinase activities of the isolated compounds were assessed through a combination of in vitro experiments and multiple in silico approaches. Docking and molecular dynamics (MD) simulation techniques were utilized to figure out the binding interactions of the isolated phytochemicals with tyrosinase. The findings from molecular docking analysis revealed that the isolated phenolics were able to bind effectively to tyrosinase and potentially inhibit substrate binding, consequently diminishing the catalytic activity of tyrosinase. Among isolated compounds, cichoric acid displayed the lowest binding energy and the highest extent of polar interactions with the target enzyme. Analysis of MD simulation trajectories indicated that equilibrium was reached within 30 ns for all complexes of tyrosinase with the isolated phenolics. Among the five ligands studied, cichoric acid exhibited the lowest interaction energies, rendering its complex with tyrosinase the most stable. Considering these collective findings, cichoric acid emerges as a promising candidate for the design and development of a potential tyrosinase inhibitor. Furthermore, the in vitro anti-tyrosinase activity assay unveiled significant variations among the isolated compounds. Notably, cichoric acid exhibited the most potent inhibitory effect, as evidenced by the lowest IC50 value (7.92 ± 1.32 µg/ml), followed by isorhamnetin and gentiopicrin. In contrast, sinapic acid demonstrated the least inhibitory activity against tyrosinase, with the highest IC50 value. Moreover, cichoric acid exhibited a mixed inhibition mode against the hydrolysis of l-DOPA catalyzed by tyrosinase, with Ki value of 1.64. Remarkably, these experimental findings align well with the outcomes of docking and MD simulations, underscoring the consistency and reliability of our computational predictions with the actual inhibitory potential observed in vitro.

Mycosporine-Like Amino Acids as a Potential Inhibitor of Tyrosinase-Related Protein 1: Computational Screening, Pharmacokinetics, and Molecular Dynamics Simulation

Melanin is the major pigment responsible for the coloring of mammalian skin, hair, and eyes to defend against ultraviolet radiation. However, excessive melanin production has resulted in numerous types of hyperpigmentation disorders. Tyrosinase-related protein 1 (TYRP1) is a transmembrane glycoprotein enzyme found in many organisms, including humans, that plays an important role in melanogenesis. Thus, controlling the enzyme activity of TYRP1 with tyrosinase inhibitors is a vital step in the treatment of hyperpigmentation problems in humans. In the present investigation, virtual screening, pharmacokinetics, drug docking, and molecular dynamics (MD) simulation were used to find the most potent drug as an inhibitor of TYRP1 to effectively treat hyperpigmentation disorder. The 3D structure of TYRP1 was retrieved from the Protein Data Bank (PDB) database (PDB ID: 5M8M) and validated by the Ramachandran plot. Pharmacokinetics and drug-likeness showed that mycosporine 2 glycine (M2G) and shinorine (SHI) were the best compounds over other ligands in the same (P-1) structural pose. However, MD simulations of the M2G showed the highest CDOCKER interaction energy (-45.182 kcal/mol) and binding affinity (-65.0529 kcal/mol) as compared to SHI and reference drugs. The molecular binding modes RMSD and RMSF plots have exhibited more relevance to the M2G ligand in comparison to other drug ligands. The bioactivity and ligand efficiency profiles revealed that M2G is the most effective compound as a TYRP1 inhibitor. Thus, M2G could be used as a most effective drug for developing valuable sunscreen products to cure hyperpigmentation-related diseases.

A novel professional-use synergistic peel technology to reduce visible hyperpigmentation on face: Clinical evidence and mechanistic understanding by computational biology and optical biopsy

Topicals and chemical peels are the standard of care for management of facial hyperpigmentation. However, traditional therapies have come under recent scrutiny, such as topical hydroquinone (HQ) has some regulatory restrictions, and high concentration trichloroacetic acid (TCA) peel pose a risk in patients with skin of colour. The objective of our research was to identify, investigate and elucidate the mechanism of action of a novel TCA- and HQ-free professional-use chemical peel to manage common types of facial hyperpigmentation. Using computational modelling and in vitro assays on tyrosinase, we identified proprietary multi-acid synergistic technology (MAST). After a single application on human skin explants, MAST peel was found to be more effective than a commercial HQ peel in inhibiting melanin (histochemical imaging and gene expression). All participants completed the case study (N = 9) without any adverse events. After administration of the MAST peel by a dermatologist, the scoring and VISIA photography reported improvements in hyperpigmentation, texture and erythema, which could be linked to underlying pathophysiological changes in skin after peeling, visualized by non-invasive optical biopsy of face. Using reflectance confocal microscopy (VivaScope®) and multiphoton tomography (MPTflex™), we observed reduction in melanin, increase in metabolic activity of keratinocytes, and no signs of inflammatory cells after peeling. Subsequent swabbing of the cheek skin found no microbiota dysbiosis resulting from the chemical peel. The strong efficacy with minimum downtime and no adverse events could be linked to the synergistic action of the ingredients in the novel HQ- and TCA-free professional peel technology.

Cytotoxic, antioxidant, and antiglycation activities, and tyrosinase inhibition using silver nanoparticles synthesized by leaf extract of Solanum aculeatissimum Jacq

The present study aimed to determine the biological properties of an extract of Solanum aculeatissimum aqueous extract (SaCE) alone as well as silver nanoparticles (AgNPs) generated by green synthesis utilizing S. aculeatissimum aqueous extract (SaCE). These synthesized SaCE AgNPs were characterized using UV-VIS spectrophotometry, scanning transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), zeta potential (ZP), dynamic light scattering (DLS). Determination of total polyphenols, flavonoids, saponins content was conducted. In addition, high performance liquid chromatography-mass spectrometry (HPLC-MS) was employed to identify constituents in this extract. Antioxidant activity was determined by DPPH radical scavenging and ferric ion reducing power (FRAP) methods. Antiglycation activity was demonstrated through relative mobility in electrophoresis (RME) and determination of free amino groups. The inhibitory activity on tyrosinase was also examined. Molecular docking analyses were performed to assess the molecular interactions with DNA and tyrosinase. The antitumor activity SaCE was also measured. Phytochemical analysis of SaCE and AgNPs showed presence polyphenols (1000.41 and 293.37 mg gallic acid equivalent/g), flavonoids (954.87 and 479.87 mg rutin equivalent/g), saponins (37.89 and 23.01% total saponins), in particular steroidal saponins (aculeatiside A and B). Both SaCE and AgNPs exhibited significant antioxidant (respectively, 73.97%, 56.27% in DPPH test, 874.67 and 837.67 μM Trolox Equivalent/g in FRAP test) and antiglycation activities (72.81 and 67.98% free amino groups, results observed in RME). SaCE and AgNPs presented 33.2, 36.1% inhibitory activity on tyrosinase, respectively. In silico assay demonstrated interaction between steroidal saponins, DNA or tyrosinase. SaCE exhibited antitumor action against various human tumor cells. Data demonstrated that extracts SaCE alone and AgNPs synthesized from SaCE presented biological properties of interest for application in new therapeutic formulations in medicine.

Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process

The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure-activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.