Abstract:The development of virtual screening techniques represents a major advance in the current drug design era. Through several strategies, virtual screening is able to facilitate the selection of molecules with the desired chemical features to modulate the biological activity of the most attractive molecular targets currently available. From the simplest techniques, as the similarity search or molecular docking, to more complex strategies, including statistical methods and machine learning, the main goal of virtual screening is to improve the searching for molecules with the desired features required for becoming drug candidates, thus accelerating the continuous process of drug design. The aim of this review is to discuss the main virtual screening strategies and how they relate to the drug design process.Keywords: Virtual screening; drug design; molecular modeling. ResumoO desenvolvimento de técnicas de triagem virtual representa um dos maiores avanços na atual era de planejamento de fármacos. A triagem virtual, através de inúmeras estratégias distintas, é capaz de direcionar a seleção de moléculas com as características químicas desejadas para modular a atividade biológica dos mais diversos e atrativos alvos moleculares conhecidos na atualidade. Desde as técnicas mais simples, como a bus a po si ila idade ou do age molecular, até as estratégias mais complexas, que envolvem métodos estatísticos e de aprendizagem de máquinas, o objetivo principal da triagem virtual é aprimorar o processo de busca de novos candidatos a fármacos e acelerar o processo contínuo do seu planejamento. O objetivo desta revisão é discutir as principais técnicas de triagem virtual e como elas se relacionam com o desenvolvimento de novos fármacos.Palavras-chave: Triagem virtual; planejamento de fármacos; modelagem molecular.

The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics, ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.

No abstract

Alzheimer's disease is the major cause of senile dementia, flewing out 10% of 65 years old and 50% of 85 years old global population. The major fisiopathologic characteristics of Alzheimer's disease are the deposition of extracellular neuritic plaques and the presence of intracellular neurofibrillary tangles in memory-related areas of the brain. The plaques are composed by the β-amyloid peptide with 40 or 42 residues, result from hydrolysis of the amyloid precursor protein by the β-secretase 1 (BACE-1) on the amyloidogenic pathway, that begins with the BACE-1 and which inhibition is considered one of the most promising treatments available of Alzheimer's disease. In this work, molecular modeling techniques such as virtual screening of compound libraries, pharmacophore-based virtual screening, molecular interaction fields, ADME/Tox predictions, and similarity search were used to design novel inhibitors of BACE-1, starting from structures available in the Protein Data Bank. The results obtained from all virtual screening techniques leaded to 10 promising compounds, which were then evaluated by enzymatic assays, and, three of them showed inhibitory activity of BACE-1 at a 1 μm range.