Structural and regulatory insights into the glideosome-associated connector from Toxoplasma gondii

Identification of domains in Plasmodium falciparum proteins of unknown function using DALI search on AlphaFold predictions

Plasmodium falciparum, the causative agent of malaria, poses a significant global health challenge, yet much of its biology remains elusive. A third of the genes in the P. falciparum genome lack annotations regarding their function, impeding our understanding of the parasite's biology. In this study, we employ structure predictions and the DALI search algorithm to analyse proteins encoded by uncharacterized genes in the reference strain 3D7 of P. falciparum. By comparing AlphaFold predictions to experimentally determined protein structures in the Protein Data Bank, we found similarities to known domains in 353 proteins of unknown function, shedding light on their potential functions. The lowest-scoring 5% of similarities were additionally validated using the size-independent TM-align algorithm, confirming the detected similarities in 88% of the cases. Notably, in over 70 P. falciparum proteins the presence of domains resembling heptatricopeptide repeats, which are typically involvement in RNA binding and processing, was detected. This suggests this family, which is important in transcription in mitochondria and apicoplasts, is much larger in Plasmodium parasites than previously thought. The results of this domain search provide a resource to the malaria research community that is expected to inform and enable experimental studies.

Biomolecular NMR in the AI-assisted structural biology era: Old tricks and new opportunities

Over the last 40 years nuclear magnetic resonance (NMR) spectroscopy has established itself as one of the most versatile techniques for the characterization of biomolecules, especially proteins. Given the molecular size limitations of NMR together with recent advances in cryo-electron microscopy and artificial intelligence-assisted protein structure prediction, the bright future of NMR in structural biology has been put into question. In this mini review we argue the contrary. We discuss the unique opportunities solution NMR offers to the protein chemist that distinguish it from all other experimental or computational methods, and how it can benefit from machine learning.

Structural and regulatory insights into the glideosome-associated connector from Toxoplasma gondii

The phylum of Apicomplexa groups intracellular parasites that employ substrate-dependent gliding motility to invade host cells, egress from the infected cells, and cross biological barriers. The glideosome-associated connector (GAC) is a conserved protein essential to this process. GAC facilitates the association of actin filaments with surface transmembrane adhesins and the efficient transmission of the force generated by myosin translocation of actin to the cell surface substrate. Here, we present the crystal structure of Toxoplasma gondii GAC and reveal a unique, supercoiled armadillo repeat region that adopts a closed ring conformation. Characterisation of the solution properties together with membrane and F-actin binding interfaces suggests that GAC adopts several conformations from closed to open and extended. A multi-conformational model for assembly and regulation of GAC within the glideosome is proposed.