RESUMO
Anticarsia gemmatalis Hübner, 1818 (Lepidoptera) is a major pest of soybean in the Brazil. It is known that the reduction of proteolytic activity by the ingestion of protease inhibitors reduces digestion and larval development of the insects. Control via inhibition of the digestive enzymes necessitates deeper knowledge of the enzyme kinetics and the characterization of the inhibition kinetics of these proteases, for better understanding of the active centers and action mechanisms of this enzyme. Trypsin-like proteases found in the gut of Anticarsia gemmatalis were purified in a p-aminobenzamidine agarose column. Kinetic characterization showed KM 0.503 mM for the L-BApNA substrate; Vmax= 46.650 nM s-1; Vmax/[E]= 9.256 nM s-1 mg L-1 and Vmax/[E]/KM= 18.402 nM s-1 mg L-1 mM. The Ki values for the inhibitors benzamidine, berenil, SKTI and SBBI were 11.2 µM, 32.4 µM, 0.25 nM and 1.4 nM, respectively, and all revealed linear competitive inhibition. The SKTI showed the greatest inhibition, which makes it a promising subject for future research to manufacture peptide mimetic inhibitors.
Assuntos
Trato Gastrointestinal/enzimologia , Lepidópteros/enzimologia , Inibidores de Proteases/farmacologia , Animais , Controle de Insetos/métodos , Cinética , Lepidópteros/crescimento & desenvolvimentoRESUMO
BACKGROUND: Interactions between proteins and non-proteic small molecule ligands play important roles in the biological processes of living systems. Thus, the development of computational methods to support our understanding of the ligand-receptor recognition process is of fundamental importance since these methods are a major step towards ligand prediction, target identification, lead discovery, and more. This article presents visGReMLIN, a web server that couples a graph mining-based strategy to detect motifs at the protein-ligand interface with an interactive platform to visually explore and interpret these motifs in the context of protein-ligand interfaces. RESULTS: To illustrate the potential of visGReMLIN, we conducted two cases in which our strategy was compared with previous experimentally and computationally determined results. visGReMLIN allowed us to detect patterns previously documented in the literature in a totally visual manner. In addition, we found some motifs that we believe are relevant to protein-ligand interactions in the analyzed datasets. CONCLUSIONS: We aimed to build a visual analytics-oriented web server to detect and visualize common motifs at the protein-ligand interface. visGReMLIN motifs can support users in gaining insights on the key atoms/residues responsible for protein-ligand interactions in a dataset of complexes.