RESUMO
ß-glucosidases are enzymes that catalyze the hydrolysis of oligosaccharides and disaccharides, such as cellobiose. These enzymes play a key role in cellulose degrading, such as alleviating product inhibition of cellulases. Consequently, they have been considered essential for the biofuel industry. However, the majority of the characterized ß-glucosidases is inhibited by glucose. Hence, glucose-tolerant ß-glucosidases have been targeted to improve the production of second-generation biofuels. In this paper, we proceeded a systematic literature review (SLR), collected protein structures and constructed a database of glucose-tolerant ß-glucosidases, called betagdb. SLR was performed at PubMed, ScienceDirect and Scopus Library databases and conducted according to PRISMA framework. It was conducted in five steps: i) analysis of duplications, ii) title reading, iii) abstract reading, iv) diagonal reading, and v) full-text reading. The second, third, fourth, and fifth steps were performed independently by two researchers. Besides, we performed bioinformatics analysis on the collected data, such as structural and multiple alignments to detect the most conserved residues in the catalytic pocket, and molecular docking to characterize essential residues for substrate recognizing, glucose tolerance, and the ß-glucosidase activity. We selected 27 papers, 23 sequences, and 5 PDB files of glucose-tolerant ß-glucosidases. We characterized 11 highly conserved residues: H121, W122, N166, E167, N297, Y299, E355, W402, E409, W410, and F418. The presence of these residues may be essential for ß-glucosidases. We also discussed the importance of residues W169, C170, L174, H181, and T226. Furthermore, we proposed that the number of contacts for each residue in the catalytic pocket might be a metric that could be used to suggest mutations. We believe that the herein propositions, together with the sequence and structural data collection, might be helpful for effective engineering of ß-glucosidases for biofuel production and may help to shed some light on the degradation of cellulosic biomass.
RESUMO
MOTIVATION: Protein-protein interfaces contain important information about molecular recognition. The discovery of conserved patterns is essential for understanding how substrates and inhibitors are bound and for predicting molecular binding. When an inhibitor binds to different enzymes (e.g. dissimilar sequences, structures or mechanisms what we call cross-inhibition), identification of invariants is a difficult task for which traditional methods may fail. RESULTS: To clarify how cross-inhibition happens, we model the problem, propose and evaluate a methodology called HydroPaCe to detect conserved patterns. Interfaces are modeled as graphs of atomic apolar interactions and hydrophobic patches are computed and summarized by centroids (HP-centroids), and their conservation is detected. Despite sequence and structure dissimilarity, our method achieves an appropriate level of abstraction to obtain invariant properties in cross-inhibition. We show examples in which HP-centroids successfully predicted enzymes that could be inhibited by the studied inhibitors according to BRENDA database. AVAILABILITY: www.dcc.ufmg.br/~raquelcm/hydropace CONTACT: valdetemg@ufmg.br; raquelcm@dcc.ufmg.br; santoro@icb.ufmg.br SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
