AlphaFold and the future of structural biology

Structural and functional analysis of the key enzyme responsible for the degradation of ochratoxin A in the Alcaligenes genus

The potential to degrade ochratoxin A (OTA), a highly poisonous mycotoxin, was investigated in cultures from Alcaligenes-type strains. Genome sequence analyses from different Alcaligenes species have permitted us to demonstrate a direct, causal link between the gene coding a known N-acyl-L-amino acid amidohydrolase from A. faecalis (AfOTH) and the OTA-degrading activity of this bacterium. In agreement with this finding, we found the gene coding AfOTH in two additional species included in the Alcaligenes genus, namely, A. pakistanensis, and A. aquatilis, which also degraded OTA. Notably, A. faecalis subsp. faecalis DSM 30030T was able to transform OTα, the product of OTA hydrolysis. AfOTH from A. faecalis subsp. phenolicus DSM 16503T was recombinantly over-produced and enzymatically characterized. AfOTH is a Zn2+-containing metalloenzyme that possesses structural features and conserved residues identified in the M20D family of enzymes. AfOTH is a tetramer in solution that shows both aminoacylase and carboxypeptidase activities. Using diverse potential substrates, namely, N-acetyl-L-amino acids and carbobenzyloxy-L-amino acids, a marked preference towards C-terminal Phe and Tyr residues could be deduced. The structural basis for this specificity has been determined by in silico molecular docking analyses. The amidase activity of AfOTH on C-terminal Phe residues structurally supports its OTA and OTB degradation activity.

Functional and structural characterisation of RimL from Bacillus cereus, a new Nα-acetyltransferase of ribosomal proteins that was wrongly assigned as an aminoglycosyltransferase

Enzymes of the GNAT (GCN5-relate N-acetyltransferases) superfamily are important regulators of cell growth and development. They are functionally diverse and share low amino acid sequence identity, making functional annotation difficult. In this study, we report the function and structure of a new ribosomal enzyme, Nα-acetyl transferase from Bacillus cereus (RimLBC), a protein that was previously wrongly annotated as an aminoglycosyltransferase. Firstly, extensive comparative amino acid sequence analyses suggested RimLBC belongs to a cluster of proteins mediating acetylation of the ribosomal protein L7/L12. To assess if this was the case, several well established substrates of aminoglycosyltransferases were screened. The results of these studies did not support an aminoglycoside acetylating function for RimLBC. To gain further insight into RimLBC biological role, a series of studies that included MALDI-TOF, isothermal titration calorimetry, NMR, X-ray protein crystallography, and site-directed mutagenesis confirmed RimLBC affinity for Acetyl-CoA and that the ribosomal protein L7/L12 is a substrate of RimLBC. Last, we advance a mechanistic model of RimLBC mode of recognition of its protein substrates. Taken together, our studies confirmed RimLBC as a new ribosomal Nα-acetyltransferase and provide structural and functional insights into substrate recognition by Nα-acetyltransferases and protein acetylation in bacteria.

Deep learning applications in protein crystallography

Deep learning techniques can recognize complex patterns in noisy, multidimensional data. In recent years, researchers have started to explore the potential of deep learning in the field of structural biology, including protein crystallography. This field has some significant challenges, in particular producing high-quality and well ordered protein crystals. Additionally, collecting diffraction data with high completeness and quality, and determining and refining protein structures can be problematic. Protein crystallographic data are often high-dimensional, noisy and incomplete. Deep learning algorithms can extract relevant features from these data and learn to recognize patterns, which can improve the success rate of crystallization and the quality of crystal structures. This paper reviews progress in this field.