In the brain of patients with chronic Alzheimer’s disease (AD), the butyrylcholinesterase (BuChE) levels rise while the acetylcholinesterase (AChE) levels decrease. Therefore, development of new selective BuChE inhibitors is of vital importance. Here we present a series of bis(n)-lophine analogues, where two lophine derivatives are connected by a methylene chain. The bis(n)-lophine analogues were synthesized through one-pot four component reaction between pyridinecarboxaldehydes, 1,n-alkanediamines, benzil, and ammonium acetate. The reactions were performed in a microwave reactor in one step for symmetrical bis(n)-lophines, and in two steps for unsymmetrical bis(n)-lophines. The compounds are strongly selective to BuChE, since none of them inhibit AChE. All the compounds, except 7a, 7b and 7c, displayed potent inhibitory activity against BuChE at a micromolar and sub-micromolar range (half maximal inhibitory concentration (IC50) 32.25-0.03 µM). The enzyme kinetic and docking studies suggests that the inhibitor act as a dual binding site inhibitor, binding into the bottom of the gorge and in the peripheral anionic site (PAS) of BuChE cavity. Furthermore, in vitro studies showed that compounds 5b and 12b had no cytotoxic effects in kidney Vero, hepatic HepG2 and C6 astroglial cell lines.

The restoration of acetylcholine levels in the brain by inhibition of cholinesterases is currently the most successful therapeutic strategy to treat neurodegenerative disorders. In this context, tacrine has been largely investigated as a starting scaffold for the development of promising new anticholinesterases compounds for the treatment of neurodegenerative illnesses, including Alzheimer’s disease. Here we present a series of compounds containing the tacrine nucleus connected with squaric moiety by a diaminoalkylene chain. The compounds were obtained through a simple and short synthetic route and showed high inhibitory activity against acetylcholinesterase (AChE) within nanomolar IC50 (half maximal inhibitory concentration). The molecular modelling study showed that these compounds act as dual-binding inhibitors of AChE, interacting with both catalytic active site (CAS) and peripheral anionic site (PAS) of the enzyme’s binding cavity. The investigated compounds also demonstrated outstanding selectivity for AChE than in butyrylcholinesterase (BuChE). These results evince these compounds as promising agents for the treatment of neurodegenerative disorders and a fuller synthetic scope jointly with complementary biological evaluations are currently under investigation in our laboratory.

Cholinesterase enzymes are important targets for the therapy of Alzheimer’s disease. Tacrine-based dual binding site cholinesterases inhibitors are potential disease-modifying anti-Alzheimer drug candidates. In the present work, we described the synthesis of a series of chiral homo- and heterodimers of bis(7)-tacrine connected by a heptylene chain as a spacer with the methyl substituent at the C-3 position of the alicyclic region of tacrine nucleus and/or a chlorine atom attached to the C-6. Friedländer cyclocondensation between (R) or (S) 3-methylcyclohexanone prepared from monoterpene pulegone and o-aminobenzoic acids in the presence of POCl3 afford 9-chloroacridines as intermediates, which were used to the synthesis of homo- and heterodimers. All compounds demonstrated to be potent inhibitors of acetylcholinesterase (AChE) at low nanomolar concentration and showed selectivity for AChE over butyrylcholinesterase (BuChE). Furthermore, the affinity difference between enantiomeric bis(7)-tacrine analogues series indicated some degree of stereoselectivity in the active site of AChE for chiral bis-cognitin compounds.

An approach to the hydrophobic-polar (HP) protein folding model was developed using a genetic algorithm (GA) to find the optimal structures on a 3D cubic lattice. A modification was introduced to the scoring system of the original model to improve the model's capacity to generate more natural-like structures. The modification was based on the assumption that it may be preferable for a hydrophobic monomer to have a polar neighbor than to be in direct contact with the polar solvent. The compactness and the segregation criteria were used to compare structures created by the original HP model and by the modified one. An islands' algorithm, a new selection scheme and multiple-points crossover were used to improve the performance of the algorithm. Ten sequences, seven with length 27 and three with length 64 were analyzed. Our results suggest that the modified model has a greater tendency to form globular structures. This might be preferable, since the original HP model does not take into account the positioning of long polar segments. The algorithm was implemented in the form of a program with a graphical user interface that might have a didactical potential in the study of GA and on the understanding of hydrophobic core formation.

We analyzed the performance of a real coded "steady-state" genetic algorithm (SSGA) using a grid-based methodology in docking five HIV-1 protease-ligand complexes having known three-dimensional structures. All ligands tested are highly flexible, having more than 10 conformational degrees of freedom. The SSGA was tested for the rigid and flexible ligand docking cases. The implemented genetic algorithm was able to dock successfully rigid and flexible ligand molecules, but with a decreasing performance when the number of ligand conformational degrees of freedom increased. The docked lowest-energy structures have root mean square deviation (RMSD) with respect to the corresponding experimental crystallographic structure ranging from 0.037 Å to 0.090 Å in the rigid docking, and 0.420 Å to 1.943 Å in the flexible docking. We found that not only the number of ligand conformational degrees of freedom is an important aspect to the algorithm performance, but also that the more internal dihedral angles are critical. Furthermore, our results showed that the initial population distribution can be relevant for the algorithm performance.

The main goal of this study is to find the most effective set of parameters for the Simplified Generalized Simulated Annealing algorithm, SGSA, when applied to distinct cost function as well as to find a possible correlation between the values of these parameters sets and some topological characteristics of the hypersurface of the respective cost function. The SGSA algorithm is an extended and simplified derivative of the GSA algorithm, a Markovian stochastic process based on Tsallis statistics that has been used in many classes of problems, in particular, in biological molecular systems optimization. In all but one of the studied cost functions, the global minimum was found in 100% of the 50 runs. For these functions the best visiting parameter, qV, belongs to the interval [1.2, 1.7]. Also, the temperature decaying parameter, qT, should be increased when better precision is required. Moreover, the similarity in the locus of optimal parameter sets observed in some functions indicates that possibly one could extract topological information about the cost functions from these sets.