Ibrahim Ali Noorbatcha

Regio‐ and Stereoselective Biomimetic Synthesis of Oligostilbenoid Dimers from Resveratrol Analogues: Influence of the Solvent, Oxidant, and Substitution

Oligostilbenoids are polyphenols that are widely distributed in nature with multifaceted biological activities. To achieve biomimetic synthesis of unnatural derivatives, we subjected three resveratrol analogues to oligomerization by means of one-electron oxidants. Upon varying the metal oxidant (AgOAc, CuBr(2), FeCl(3)6 H(2)O, FeCl(3)6 H(2)O/NaI, PbO(2), VOF(3)), the solvent (over the whole range of polarities), and the oxygenated substitution pattern of the starting material, stilbenoid oligomers with totally different carbon skeletons were obtained. Here we propose to explain the determinism of the type of skeleton produced with the aid of hard and soft acid/base concepts in conjunction with the solvating properties of the solvents and the preferred alignment by the effect of pi stacking.

Developing CAS models in immunology teaching

How can mathematical modelling be integrated with complex network of biological system in comprehensive education? There are mutual agreements between academia from various fields that mathematical modelling is an important part of the curriculum. Immunology is a complex subject and for student to fully understand its complex interaction at molecular level requires computer supported models. This research tries to resolve the ever emerging problem of teaching immunology in higher education. The main objective is to develop multimedia educational software to enhance immunology teaching, with the use of a Computer Algebra System (CAS) that fully utilizes mathematical equation, modelling and simulation of complex network of gene regulation and metabolism. A survey was conducted among students in higher learning institutions, and the result clearly shows that the current teaching method is not feasible to the current learning style. To overcome this, new teaching techniques to support the required understanding need to be introduced. With the development of this educational package that uses new modelling and simulation techniques hopefully can aid in teaching some of immunology courses.

Fabrication of Fucoxanthin-Loaded Microsphere(F-LM) By Two Steps Double-Emulsion Solvent Evaporation Method and Characterization of Fucoxanthin before and after Microencapsulation

Microencapsulation is a promising approach in drug delivery to protect the drug from degradation and allow controlled release of the drug in the body. Fucoxanthin-loaded microsphere (F-LM) was fabricated by two step w/o/w double emulsion solvent evaporation method with poly (L-lactic-coglycolic acid) (PLGA) as carrier. The effect of four types of surfactants (PVA, Tween-20, Span-20 and SDS), homogenization speed, and concentration of PLGA polymer and surfactant (PVA), respectively, on particle size and morphology of F-LM were investigated. Among the surfactants tested, PVA showed the best results with smallest particle size (9.18 µm) and a smooth spherical surface. Increasing the homogenization speed resulted in a smaller mean F-LM particle size [d(0.50)] from 17.12 to 9.18 µm. Best particle size results and good morphology were attained at homogenization speed of 20 500 rpm. Meanwhile, increased PLGA concentration from 1.5 to 11.0 (% w/v) resulted in increased F-LM particle size. The mean particle size [d(0.5)] of F-LM increased from 3.93 to 11.88 µm. At 6.0 (% w/v) PLGA, F-LM showed the best structure and external morphology. Finally, increasing PVA concentration from 0.5 to 3.5 (% w/v) resulted in decreased particle size from 9.18 to 4.86 µm. Fucoxanthin characterization before and after microencapsulation was carried out to assess the success of the microencapsulation procedure. Thermo gravimetry analysis (TGA), glass transition (Tg) temperature of F-LM and fucoxanthin measured using DSC, ATR-FTIR and XRD indicated that fucoxanthin was successfully encapsulated into the PLGA matrix, while maintaining the structural and chemical integrity of fucoxanthin.

Hyaluronidase Inhibitory Activity of Pentacylic Triterpenoids from Prismatomeris tetrandra (Roxb.) K. Schum: Isolation, Synthesis and QSAR Study

The mammalian hyaluronidase degrades hyaluronic acid by the cleavage of the β-1,4-glycosidic bond furnishing a tetrasaccharide molecule as the main product which is a highly angiogenic and potent inducer of inflammatory cytokines. Ursolic acid 1, isolated from Prismatomeris tetrandra, was identified as having the potential to develop inhibitors of hyaluronidase. A series of ursolic acid analogues were either synthesized via structure modification of ursolic acid 1 or commercially obtained. The evaluation of the inhibitory activity of these compounds on the hyaluronidase enzyme was conducted. Several structural, topological and quantum chemical descriptors for these compounds were calculated using semi empirical quantum chemical methods. A quantitative structure activity relationship study (QSAR) was performed to correlate these descriptors with the hyaluronidase inhibitory activity. The statistical characteristics provided by the best multi linear model (BML) (R2 = 0.9717, R2cv = 0.9506) indicated satisfactory stability and predictive ability of the developed model. The in silico molecular docking study which was used to determine the binding interactions revealed that the ursolic acid analog 22 had a strong affinity towards human hyaluronidase.

Cyclization vs. Cyclization/Dimerization in o-Amidostilbene Radical Cation Cascade Reactions: The Amide Question

The n-butyramido, isobutyramido, benzamido, and furancarboxamido functions profoundly modulate the electronics of the stilbene olefinic and NH groups and the corresponding radical cations in ways that influence the efficiency of the cyclization due presumably to conformational and stereoelectronic factors. For example, isobutyramido- stilbene undergoes FeCl3 promoted cyclization to produce only indoline, while n-butyramidostilbene, under the same conditions, produces both indoline and bisindoline.

Prediction of anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) methods

Design and development of new anticancer drugs with low toxicity is a very challenging task and computer aided methods are being increasingly used to solve this problem. In this study, we investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) approach. In this method, the physic-chemical properties, known as descriptors, necessary for predicting quantitative structure activity relations was obtained from semi empirical quantum chemical methods. We used Recife Model 1 to optimize the structure of the molecules and to calculate the quantum chemical descriptors, while heuristic and best multilinear regression methods were applied to obtain the best correlation. Two data sets containing aliphatic nitrosoureas and chloroethyl substituted nitrosoureas were used in the present calculations. The QSAR equations obtained here can be used to design new anticancer drugs prior to resorting to experimental activity studies.

Quantum chemical structure activity studies of anticancer activity of seconucleoside nitrosourea analogs

Nucleosides can be considered as specific carriers for the nitrosourea moiety with altered pharmacological properties such as improved water solubility, lower myelotoxicity with enhanced cell membrane transport. Several seconucleoside nitrosourea compounds have been reported to have anticancer activity against solid tumors such as, murine adenocarcinomas of the colon 13 (MAC 13), MAC 15A, colon 38 and mammary carcinoma. In an effort to have a good understanding of the role of the structural features on the anticancer activity of these seconucleosides, we have constructed the quantitative structure activity relationship (QSAR) involving 26 seconucleoside nitrosourea compounds having anticancer activity against murine adenocarcinomas of the colon 15A (MAC 15). Traditional QSAR studies require knowledge of several physicochemical properties to obtain a good QSAR. To circumvent this problem, we have made use of quantum chemical methods to calculate several electronic and molecular properties of these compounds and used these properties to obtain the best QSAR using statistical procedures. Semi-empirical quantum chemical RM1 methods were used to optimize the molecular structures. From the optimized structure, hundreds of molecular and electronic properties were calculated and correlated with the anticancer activities of the compounds. The best correlation was obtained using heuristic and multi-linear regression methods. We were able to obtain a best QSAR with correlation coefficient, R2=0.8993. We find that the average structural information contents of the second order, average bond order of oxygen atom and maximum columbic interaction for H-N bond play significant roles in influencing the anticancer activity of the selected compounds. The QSAR obtained in our study can be used to predict the anticancer activity of new seconucleoside nitrosourea analogs, prior to resorting to any experimental studies.