Background: Egyptians recognized the healing power of herbs and used them in their medicinal formulations. Nowadays, “Attarin” drug shops and the public use mainly the Unani medicinal system for treatment of their health problems including improvement of memory and old age related diseases. Numerous medicinal plants have been described in old literature of Arabic traditional medicine for treatment of Alzheimer’s disease (AD) (or to strengthen memory).Methods: In this study, some of these plants were evaluated against three different preliminary bioassays related to AD to explore the possible way of their bio-interaction. Twenty three selected plants were extracted with methanol and screenedin vitroagainst acetylcholinesterase (AChE) and cycloxygenase-1 (COX-1) enzymes. In addition, anti-oxidant activity using DPPH was determined.Results: Of the tested plant extracts;Adhatoda vasicaandPeganum harmalashowed inhibitory effect on AChE at IC₅₀294 μg/ml and 68 μg/ml respectively. Moreover,A. vasicainteracted reversibly with the enzyme whileP. harmalashowed irreversible inhibition.Ferula assafoetida(IC₅₀3.2 μg/ml),Syzygium aromaticum(34.9 μg/ml) andZingiber officinalis(33.6 μg/ml) showed activity against COX-1 enzyme. Potent radical scavenging activity was demonstrated by three plant extractsTerminalia chebula(EC₅₀2.2 μg/ml),T. arjuna(3.1 μg/ml) andEmblica officinalis(6.3 μg/ml).Conclusion: Interestingly, differential results have been obtained which indicate the variability of the mode of actions for the selected plants. Additionally, the reversible interaction ofA. vasicaagainst AChE and the potent activity ofF. assafoetidaagainst COX-1 make them effective, new and promising agents for treatment of AD in the future, either as total extracts or their single bioactive constituents.

The glutathione transferases (GSTs) represent a superfamily of dimeric proteins. Each subunit has an active site, but there is no evidence for the existence of catalytically active monomers. The lock and key motif is responsible for a highly conserved hydrophobic interaction in the subunit interface of pi, mu, and alpha class glutathione transferases. The key residue, which is either Phe or Tyr (Tyr(50) in human GSTP1-1) in one subunit, is wedged into a hydrophobic pocket of the other subunit. To study how an essentially inactive subunit influences the activity of the neighboring subunit, we have generated the heterodimer composed of subunits from the fully active human wild-type GSTP1-1 and the nearly inactive mutant Y50A obtained by mutation of the key residue Tyr(50) to Ala. Although the key residue is located far from the catalytic center, the k(cat) value of mutant Y50A decreased about 1300-fold in comparison with the wild-type enzyme. The decrease of the k(cat) value of the heterodimer by about 27-fold rather than the expected 2-fold in comparison with the wild-type enzyme indicates that the two active sites of the dimeric enzyme work synergistically. Further evidence for cooperativity was found in the nonhyperbolic GSH saturation curves. A network of hydrogen-bonded water molecules, found in crystal structures of GSTP1-1, connects the two active sites and the main chain carbonyl group of Tyr(50), thereby offering a mechanism for communication between the two active sites. It is concluded that a subunit becomes catalytically competent by positioning the key residue of one subunit into the lock pocket of the other subunit, thereby stabilizing the loop following the helix alpha2, which interacts directly with GSH.

We have used design of experiments (DOE) and systematic variance to efficiently explore glutathione transferase substrate specificities caused by amino acid substitutions. Amino acid substitutions selected using phylogenetic analysis were synthetically combined using a DOE design to create an information-rich set of gene variants, termed infologs. We used machine learning to identify and quantify protein sequence–function relationships against 14 different substrates. The resulting models were quantitative and predictive, serving as a guide for engineering of glutathione transferase activity toward a diverse set of herbicides. Predictive quantitative models like those presented here have broad applicability for bioengineering.