A mitophagy sensor PPTC7 controls BNIP3 and NIX degradation to regulate mitochondrial mass

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.

Autophagy is a process by which cytoplasmic organelles can be catabolized either to remove defective structures or as a means of providing macromolecules for energy generation under conditions of nutrient starvation. In this study we demonstrate that mitochondrial autophagy is induced by hypoxia, that this process requires the hypoxia-dependent factor-1-dependent expression of BNIP3 and the constitutive expression of Beclin-1 and Atg5, and that in cells subjected to prolonged hypoxia, mitochondrial autophagy is an adaptive metabolic response which is necessary to prevent increased levels of reactive oxygen species and cell death.

Autophagy not only recycles intracellular components to compensate for nutrient deprivation but also selectively eliminates organelles to regulate their number and maintain quality control. Mitophagy, the specific autophagic elimination of mitochondria, has been identified in yeast, mediated by autophagy-related 32 (Atg32), and in mammals during red blood cell differentiation, mediated by NIP3-like protein X (NIX; also known as BNIP3L). Moreover, mitophagy is regulated in many metazoan cell types by parkin and PTEN-induced putative kinase protein 1 (PINK1), and mutations in the genes encoding these proteins have been linked to forms of Parkinson's disease.