AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms—namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT’ inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.     

Mesenchymal Stromal Cell Therapy in Novel Porcine Model of Diffuse Liver Damage Induced by Repeated Biliary Obstruction

In liver surgery, biliary obstruction can lead to secondary biliary cirrhosis, a life-threatening disease with liver transplantation as the only curative treatment option. Mesenchymal stromal cells (MSC) have been shown to improve liver function in both acute and chronic liver disease models. This study evaluated the effect of allogenic MSC transplantation in a large animal model of repeated biliary obstruction followed by partial hepatectomy. MSC transplantation supported the growth of regenerated liver tissue after 14 days (MSC group, n = 10: from 1087 ± 108 (0 h) to 1243 ± 92 mL (14 days); control group, n = 11: from 1080 ± 95 (0 h) to 1100 ± 105 mL (14 days), p = 0.016), with a lower volume fraction of hepatocytes in regenerated liver tissue compared to resected liver tissue (59.5 ± 10.2% vs. 70.2 ± 5.6%, p < 0.05). Volume fraction of connective tissue, blood vessels and bile vessels in regenerated liver tissue, serum levels of liver enzymes (AST, ALT, ALP and GGT) and liver metabolites (albumin, bilirubin, urea and creatinine), as well as plasma levels of IL-6, IL-8, TNF-α and TGF-β, were not affected by MSC transplantation. In our novel, large animal (pig) model of repeated biliary obstruction followed by partial hepatectomy, MSC transplantation promoted growth of liver tissue without any effect on liver function. This study underscores the importance of translating results between small and large animal models as well as the careful translation of results from animal model into human medicine.     

Lipid Droplets and Their Autophagic Turnover via the Raft-Like Vacuolar Microdomains

Although once perceived as inert structures that merely serve for lipid storage, lipid droplets (LDs) have proven to be the dynamic organelles that hold many cellular functions. The LDs’ basic structure of a hydrophobic core consisting of neutral lipids and enclosed in a phospholipid monolayer allows for quick lipid accessibility for intracellular energy and membrane production. Whereas formed at the peripheral and perinuclear endoplasmic reticulum, LDs are degraded either in the cytosol by lipolysis or in the vacuoles/lysosomes by autophagy. Autophagy is a regulated breakdown of dysfunctional, damaged, or surplus cellular components. The selective autophagy of LDs is called lipophagy. Here, we review LDs and their degradation by lipophagy in yeast, which proceeds via the micrometer-scale raft-like lipid domains in the vacuolar membrane. These vacuolar microdomains form during nutrient deprivation and facilitate internalization of LDs via the vacuolar membrane invagination and scission. The resultant intra-vacuolar autophagic bodies with LDs inside are broken down by vacuolar lipases and proteases. This type of lipophagy is called microlipophagy as it resembles microautophagy, the type of autophagy when substrates are sequestered right at the surface of a lytic compartment. Yeast microlipophagy via the raft-like vacuolar microdomains is a great model system to study the role of lipid domains in microautophagic pathways.     

Computational Investigation Identified Potential Chemical Scaffolds for Heparanase as Anticancer Therapeutics

Heparanase (Hpse) is an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains. Its upregulated expression is implicated in tumor growth, metastasis and angiogenesis, thus making it an attractive target in cancer therapeutics. Currently, a few small molecule inhibitors have been reported to inhibit Hpse, with promising oral administration and pharmacokinetic (PK) properties. In the present study, a ligand-based pharmacophore model was generated from a dataset of well-known active small molecule Hpse inhibitors which were observed to display favorable PK properties. The compounds from the InterBioScreen database of natural (69,034) and synthetic (195,469) molecules were first filtered for their drug-likeness and the pharmacophore model was used to screen the drug-like database. The compounds acquired from screening were subjected to molecular docking with Heparanase, where two molecules used in pharmacophore generation were used as reference. From the docking analysis, 33 compounds displayed higher docking scores than the reference and favorable interactions with the catalytic residues. Complex interactions were further evaluated by molecular dynamics simulations to assess their stability over a period of 50 ns. Furthermore, the binding free energies of the 33 compounds revealed 2 natural and 2 synthetic compounds, with better binding affinities than reference molecules, and were, therefore, deemed as hits. The hit compounds presented from this in silico investigation could act as potent Heparanase inhibitors and further serve as lead scaffolds to develop compounds targeting Heparanase upregulation in cancer.     

Selective Capture and Identification of Methicillin-Resistant Staphylococcus aureus by Combining Aptamer-Modified Magnetic Nanoparticles and Mass Spectrometry

A nucleic acid aptamer that specifically recognizes methicillin-resistant Staphylococcus aureus (MRSA) has been immobilized on magnetic nanoparticles to capture the target bacteria prior to mass spectrometry analysis. After the MRSA species were captured, they were further eluted from the nanoparticles and identified using matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). The combination of aptamer-based capture/enrichment and MS analysis of microorganisms took advantage of the selectivity of both techniques and should enhance the accuracy of MRSA identification. The capture and elution efficiencies for MRSA were optimized by examining factors such as incubation time, temperature, and elution solvents. The aptamer-modified magnetic nanoparticles showed a capture rate of more than 90% under the optimized condition, whereas the capture rates were less than 11% for non-target bacteria. The as-prepared nanoparticles exhibited only a 5% decrease in the capture rate and a 9% decrease in the elution rate after 10 successive cycles of utilization. Most importantly, the aptamer-modified nanoparticles revealed an excellent selectivity towards MRSA in bacterial mixtures. The capture of MRSA at a concentration of 10² CFU/mL remained at a good percentage of 82% even when the other two species were at 10⁴ times higher concentration (10⁶ CFU/mL). Further, the eluted MRSA bacteria were successfully identified using MALDI mass spectrometry.     

Effect of cutting process on the stress corrosion susceptibility of AISI 304L stainless steel

During manufacturing of a component, cutting, turning, grinding, and milling operations are inevitable and these operations induce surface residual stresses. In this study, it is shown that, depending on the process employed for cutting, residual stresses generated at the cut surfaces can vary widely and they can, in turn, make the cut surfaces of austenitic stainless steel (SS) prone to stress corrosion cracking (SCC). An austenitic SS 304L plate was cut using three different procesess: bandsaw cutting, cutting using the cut-off wheel, and shearing. Surface residual stress measurement using the X-ray diffraction (XRD) technique is carried out close to the cutting edges and on the cross-section. SCC susceptibility studies were carried out as per ASTM G36 in 45% boiling magnesium chloride solution. Optical microscopic examination showed the presence of cracks, and confocal microscopy was used to measure the depth of cracks. The study confirmed that high tensile residual stresses present in the cut surfaces produced by cut-off wheel and shear cutting make the surfaces susceptible to SCC while the surfaces produced by bandsaw cutting are resistant to SCC. Hence, it is shown that there is a definite risk of SCC for product forms of austenitic SS with cut surfaces produced using cutting processes that generate high tensile residual stresses stored for a long period of time in a susceptible environment.     

Adsorption of anionic dye on eco-friendly synthesised reduced graphene oxide anchored with lanthanum aluminate: Isotherms,kinetics and statistical error analysis

In the present study we made an effort to deploy eco-friendly synthesized reduced graphene oxide/Lanthanum Alluminate nanocomposites (RGO-LaAlO₃) and Lanthanum Alluminate (LaAlO₃) as adsorbents to remove dye from the synthetic media. XRD, SEM, BET surface area and EDX have been used to characterize the above-mentioned adsorbents. The impacts of different factors like adsorbent dosage, the concentration of adsorbate and PH on adsorption were studied. The best fit linear and nonlinear equations for the adsorption isotherms and kinetic models had been examined. The sum of the normalized errors and the coefficient of determination were used to determine the best fit model. The experimental data were more aptly fitted for nonlinear forms of isotherms and kinetic equations. Pseudo-second-order and Freundlich isotherm model fits the equilibrium data satisfactorily. Methyl orange (MO) has been used as model dye pollutant and maximum adsorption capacity was found to be 469.7 and 702.2 mg g^?1 for LaAlO₃ and RGO-LaAlO₃, respectively.     

Experimental investigation of Co and Fe-Doped CuO nanostructured electrode material for remarkable electrochemical performance

The current research work presents a facile and cost–effective co-precipitation method to prepare doped (Co & Fe) CuO and undoped CuO nanostructures without usage of any type of surfactant or capping agents. The structural analysis reveals monoclinic crystal structure of synthesized pure CuO and doped-CuO nanostructures. The effect of different morphologies on the performance of supercapacitors has been found in CV (cyclic voltammetry) and GCD (galvanic charge discharge) investigations. The specific capacitances have been obtained 156 (±5) Fg^?1, 168(±5) Fg^?1 and 186 (±5) Fg^?1 for CuO, Co-doped CuO and Fe-doped CuO electrodes, respectively at scan rate of 5 mVs^?1, while it is found to be 114 (±5) Fg^?1, 136 (±5) Fg^?1 and 170 (±5) Fg^?1 for CuO, Co–CuO and Fe–CuO, respectively at 0.5 Ag^-1 as calculated from the GCD. The super capacitive performance of the Fe–CuO nanorods is mainly attributed to the synergism that evolves between CuO and Fe metal ion. The Fe-doped CuO with its nanorods like morphology provides superior specific capacitance value and excellent cyclic stability among all studied nanostructured electrodes. Consequently, it motivates to the use of Fe-doped CuO nanostructures as electrode material in the next generation energy storage devices.