Process optimization for gold nanoparticles biosynthesis by Streptomyces albogriseolus using artificial neural network, characterization and antitumor activities.

Gold nanoparticles (GNPs) are highly promising in cancer therapy, wound healing, drug delivery, biosensing, and biomedical imaging. Furthermore, GNPs have anti-inflammatory, anti-angiogenic, antioxidants, anti-proliferative and anti-diabetic effects. The present study presents an eco-friendly approach for GNPs biosynthesis using the cell-free supernatant of Streptomyces albogriseolus as a reducing and stabilizing agent. The biosynthesized GNPs have a maximum absorption peak at 540 nm. The TEM images showed that GNPs ranged in size from 5.42 to 13.34 nm and had a spherical shape. GNPs have a negatively charged surface with a Zeta potential of - 24.8 mV. FTIR analysis identified several functional groups including C-H, -OH, C-N, amines and amide groups. The crystalline structure of GNPs was verified by X-ray diffraction and the well-defined and distinct diffraction rings observed by the selected area electron diffraction analysis. To optimize the biosynthesis of GNPs using the cell-free supernatant of S. albogriseolus, 30 experimental runs were conducted using central composite design (CCD). The artificial neural network (ANN) was employed to analyze, validate, and predict GNPs biosynthesis compared to CCD. The maximum experimental yield of GNPs (778.74 µg/mL) was obtained with a cell-free supernatant concentration of 70%, a HAuCl4 concentration of 800 µg/mL, an initial pH of 7, and a 96-h incubation time. The theoretically predicted yields of GNPs by CCD and ANN were 809.89 and 777.32 µg/mL, respectively, which indicates that ANN has stronger prediction potential compared to the CCD. The anticancer activity of GNPs was compared to that of doxorubicin (Dox) in vitro against the HeP-G2 human cancer cell line. The IC50 values of Dox and GNPs-based treatments were 7.26 ± 0.4 and 22.13 ± 1.3 µg/mL, respectively. Interestingly, treatments combining Dox and GNPs together showed an IC50 value of 3.52 ± 0.1 µg/mL, indicating that they targeted cancer cells more efficiently.

Artificial neural network approach for prediction of AuNPs biosynthesis by Streptomyces flavolimosus, characterization, antitumor potency in-vitro and in-vivo against Ehrlich ascites carcinoma.

Gold nanoparticles (AuNPs) have emerged as promising and versatile nanoparticles for cancer therapy and are widely used in drug and gene delivery, biomedical imaging, diagnosis, and biosensors. The current study describes a biological-based strategy for AuNPs biosynthesis using the cell-free supernatant of Streptomyces flavolimosus. The biosynthesized AuNPs have an absorption peak at 530-535 nm. The TEM images indicate that AuNPs were spherical and ranged in size from 4 to 20 nm. The surface capping molecules of AuNPs are negatively charged, having a Zeta potential of - 10.9 mV. FTIR analysis revealed that the AuNPs surface composition contains a variety of functional groups as -OH, C-H, N-, C=O, NH3+, amine hydrochloride, amide group of proteins, C-C and C-N. The bioprocess variables affecting AuNPs biosynthesis were optimized by using the central composite design (CCD) in order to maximize the AuNPs biosynthesis. The maximum yield of AuNPs (866.29 µg AuNPs/mL) was obtained using temperature (35 °C), incubation period (4 days), HAuCl4 concentration (1000 µg/mL) and initial pH level 6. Comparison was made between the fitness of CCD versus Artificial neural network (ANN) approach based on their prediction and the corresponding experimental results. AuNPs biosynthesis values predicted by ANN exhibit a more reasonable agreement with the experimental result. The anticancer activities of AuNPs were assessed under both in vitro and in vivo conditions. The results revealed a significant inhibitory effect on the proliferation of the MCF-7 and Hela carcinoma cell lines treated with AuNPs with IC50 value of 13.4 ± 0.44 µg/mL and 13.8 ± 0.45 µg/mL for MCF-7 and Hela cells; respectively. Further, AuNPs showed potential inhibitory effect against tumor growth in tumor-bearing mice models. AuNPs significantly reduced the tumor volume, tumor weight, and decreased number of viable tumor cells in EAC bearing mice.

Small molecules targeting different cellular pathologies for the treatment of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease in which the motor neuron circuitry displays progressive degeneration, affecting mostly the motor neurons in the brain and in the spinal cord. There are no effective cures, albeit three drugs, riluzole, edaravone, and AMX0035 (a combination of sodium phenylbutyrate and taurursodiol), have been approved by the Food and Drug Administration, with limited improvement in patients. There is an urgent need to build better and more effective treatment strategies for ALS. Since the disease is very heterogenous, numerous approaches have been explored, such as targeting genetic mutations, decreasing oxidative stress and excitotoxicity, enhancing mitochondrial function and protein degradation mechanisms, and inhibiting neuroinflammation. In addition, various chemical libraries or previously identified drugs have been screened for potential repurposing in the treatment of ALS. Here, we review previous drug discovery efforts targeting a variety of cellular pathologies that occur from genetic mutations that cause ALS, such as mutations in SOD1, C9orf72, FUS, and TARDP-43 genes. These mutations result in protein aggregation, which causes neuronal degeneration. Compounds used to target cellular pathologies that stem from these mutations are discussed and comparisons among different preclinical models are presented. Because the drug discovery landscape for ALS and other motor neuron diseases is changing rapidly, we also offer recommendations for a novel, more effective, direction in ALS drug discovery that could accelerate translation of effective compounds from animals to patients.