In silico investigation of medicinal spectrum of imidazo-azines from the perspective of multitarget screening against malaria, tuberculosis and Chagas disease

Advances in the treatment of Chagas disease: Promising new drugs, plants and targets

Chagas disease, caused by Trypanosoma cruzi, is treated with only two drugs; benznidazole and nifurtimox. These drugs have some disadvantages, including their efficacy only in the acute or early infection phases, adverse effects during their use, and the resistance that the parasite has developed to their activity. Therefore, it is necessary to identify new, safe and effective therapeutic alternatives to treat Chagas disease, though governments and the pharmaceutical industry have shown a lack of interest in contributing to this solution. Institutions and research groups on the other hand have worked on some strategies that can help to address the problem. Some of these include the modification of conventional drug dosages, drug repurposing, and combined therapy. Plants and derived compounds with antiparasitic effects have also been studied, taking advantage of traditional medicinal knowledge. Others have studied the parasite to identify essential genes that can be used as therapeutic targets to design new, targeted drugs. Some of these studies have generated promising results, but few reach clinical phase studies. Institutions and research groups should be encouraged to unify efforts and cover all aspects of drug development according to resources and knowledge availability. In the end, this exchange of knowledge would lead to the development of new therapeutic alternatives to treat Chagas disease and benefit the populations it affects.

Multicomponent Reactions Upon the Known Drug Trimethoprim as a Source of Novel Antimicrobial Agents

Novel antibiotic compounds have been prepared through a selective multicomponent reaction upon the known drug Trimethoprim. The Groebke-Blackburn-Bienaymé reaction involving this α-aminoazine, with a range of aldehydes and isocyanides afforded the desired adducts in one-step. The analogs display meaningful structural features of the initial drug together with relevant modifications at several points, keeping antibiotic potency and showing satisfactory antimicrobial profile (good activity levels and reduced growth rates), especially against methicillin-resistant Staphylococcus aureus. The new products may open new possibilities to fight bacterial infections.

Molecular docking, pharmacophore based virtual screening and molecular dynamics studies towards the identification of potential leads for the management of H. pylori

The enzyme pantothenate synthetase panC is one of the potential new antimicrobial drug targets, but it is poorly characterized in H. pylori. H. pylori infection can cause gastric cancer and the management of H. pylori infection is crucial in various gastric ulcers and gastric cancer. The current study describes the use of innovative drug discovery and design approaches like comparative metabolic pathway analysis (Metacyc), exploration of database of essential genes (DEG), homology modelling, pharmacophore based virtual screening, ADMET studies and molecular dynamics simulations in identifying potential lead compounds for the H. pylori specific panC. The top ranked virtual hits STOCK1N-60270, STOCK1N-63040, STOCK1N-44424 and STOCK1N-63231 can act as templates for synthesis of new H. pylori inhibitors and they hold a promise in the management of gastric cancers caused by H. pylori.

Computational approaches such as pharmacophore modeling, virtual screening and MD simulations were explored to find the potential hits as H. pylori specific panC inhibitors for the management of gastric ulcers and gastric cancers.

Computational Approaches in Multitarget Drug Discovery

Current therapeutic strategies entail identifying and characterizing a single protein receptor whose inhibition is likely to result in the successful treatment of a disease of interest, and testing experimentally large libraries of small molecule compounds "in vitro" and "in vivo" to identify promising inhibitors in model systems and determine if the findings are extensible to humans. This highly complex process is largely based on tests, errors, risk, time, and intensive costs. The virtual computational study of compounds simulates situations predicting possible drug linkages with multiple protein target atomic structures, taking into account the dynamic protein inhibitor, and can help identify inhibitors efficiently, particularly for complex drug-resistant diseases. Some discussions will relate to the potential benefits of this approach, using HIV-1 and Plasmodium falciparum infections as examples. Some authors have proposed a virtual drug discovery that not only identifies efficient inhibitors but also helps to minimize side effects and toxicity, thus increasing the likelihood of successful therapies. This chapter discusses concepts and research of bioactive multitargets related to toxicology.