Editorial [Hot Topic: Computational Approaches in Drug Research (Guest Editor: Carlton A. Taft)]

This issue is aimed for anyone who is interested or works with current theoretical methods in medicinal chemistry, with particular interest in chemoinformatics and bioinformatics for many therapeutic purposes. This issue attempts to convey something of the fascination of working in the multidisciplinar field of Medicinal Chemistry, which overlap knowledge of chemistry, physics, biochemistry, biology and pharmacology. Alpha- and beta-glucosidases are postulated to be very attractive therapeutic targets since they catalyze the cleavage of glycosidic bonds releasing glucose from the non-reducing end of an oligo- or polysaccharide chain involved in glycoprotein biosynthesis. Glucosidase inhibitors are currently of interest owing to their promising therapeutic potential in the treatment of disorders such as diabetes, AIDS, metastatic cancer and lysosomal storage diseases. In Chapter 1 comparative modeling and bioinformatic procedures have been reported to suggest the highest affinity of the human enzyme with the rat intestinal sucrase, when compared to other homolog proteins commonly used in activity assays. Consequently, the authors have built and validated a 3D model for this rat alpha-glucosidase, and additionally performed docking simulations of well-known glucosidase inhibitors as well as pharmacophore modeling and molecular interaction field studies in order to establish the most relevant structural features of inhibitors and enzyme as well as for inhibitory activity. Using this mixed methodology they have explained activities of reported inhibitors as well as discussed about key alpha-glucosidase residues in the active site, in order to design novel pharmaceuticals candidates. The high frequency of contamination by herbicides suggests the need for more active and selective herbicides. Glyphosate is the active component of one of the top-selling herbicides, which is also a potent EPSP synthase inhibitor. In this line, molecular modeling studies using molecular dynamics simulations and molecular docking techniques have been described in Chapter 2 leaving to the understanding of the interaction of glyphosate and its analogs with the wild type enzyme and Gly96Ala mutant EPSP synthase. Findings indicate some key points for the designing of new selective glyphosate derivates. Alzheimer's disease has become one of the most serious healthcare problems nowadays, where age is clearly the major risk factor. The pathology of the disease is characterized by the formation of senile plaques outside of the neurons, which are composed, predominantly, by the beta-amyloid peptide. Considering that beta-secretase is an aspartyl protease involved in the cleavage of the amyloid precursor, the first step required for the formation of the beta-amyloid, it becomes an attractive therapeutic target for drug design. In Chapter 3, a virtual screening approach based on flexible docking was applied in order to identify potential inhibitor candidates of beta-secretase, since the docking method used here showed to be able to reproduce the binding modes of crystallographic complexes. Overall, results here obtained suggest that novel potential beta-secretase inhibitors proposed could be a promising pharmaceutical for the Alzheimer's disease treatment. The enzyme reverse transcriptase (RT) is essential in the replication of human immunodeficiency virus (HIV). Nonnucleoside reverse transcriptase inhibitors (NNRTI's) are a promising class of anti-HIV drugs, which block the chemical step of DNA polymerization reaction by binding at the allosteric site of RT, leading to a viral suppression. A major limitation to the success of therapy with NNRTIs is the rapid development of drug-resistant mutants. In Chapter 4 the usage of molecular modeling, virtual screening, flexible docking, molecular interaction field, pharmacophoric alignment, toxicity predictions, and molecular dynamics simulations has been reported in order to design new molecules with potential higher selectivity and enzymatic inhibitory activity over K103N RT enzyme, which is the most common mutation to emerge.