Subventricular zone adult mouse neural stem cells require insulin receptor for self-renewal.

The insulin receptor (INSR) is an evolutionarily conserved signaling protein that regulates development and cellular metabolism. INSR signaling promotes neurogenesis in Drosophila; however, a specific role for the INSR in maintaining adult neural stem cells (NSCs) in mammals has not been investigated. We show that conditionally deleting the Insr gene in adult mouse NSCs reduces subventricular zone NSCs by ∼70% accompanied by a corresponding increase in progenitors. Insr deletion also produced hyposmia caused by aberrant olfactory bulb neurogenesis. Interestingly, hippocampal neurogenesis and hippocampal-dependent behaviors were unperturbed. Highly aggressive proneural and mesenchymal glioblastomas had high INSR/insulin-like growth factor (IGF) pathway gene expression, and isolated glioma stem cells had an aberrantly high ratio of INSR:IGF type 1 receptor. Moreover, INSR knockdown inhibited GBM tumorsphere growth. Altogether, these data demonstrate that the INSR is essential for a subset of normal NSCs, as well as for brain tumor stem cell self-renewal.

Discovery of receptor-ligand interfaces in the immunoglobulin superfamily.

Cell-surface-anchored immunoglobulin superfamily (IgSF) proteins are widespread throughout the human proteome, forming crucial components of diverse biological processes including immunity, cell-cell adhesion, and carcinogenesis. IgSF proteins generally function through protein-protein interactions carried out between extracellular, membrane-bound proteins on adjacent cells, known as trans-binding interfaces. These protein-protein interactions constitute a class of pharmaceutical targets important in the treatment of autoimmune diseases, chronic infections, and cancer. A molecular-level understanding of IgSF protein-protein interactions would greatly benefit further drug development. A critical step toward this goal is the reliable identification of IgSF trans-binding interfaces. We propose a novel combination of structure and sequence information to identify trans-binding interfaces in IgSF proteins. We developed a structure-based binding interface prediction approach that can identify broad regions of the protein surface that encompass the binding interfaces and suggests that IgSF proteins possess binding supersites. These interfaces could theoretically be pinpointed using sequence-based conservation analysis, with performance approaching the theoretical upper limit of binding interface prediction accuracy, but achieving this in practice is limited by the current ability to identify an appropriate multiple sequence alignment for conservation analysis. However, an important contribution of combining the two orthogonal methods is that agreement between these approaches can estimate the reliability of the predictions. This approach was benchmarked on the set of 22 IgSF proteins with experimentally solved structures in complex with their ligands. Additionally, we provide structure-based predictions and reliability scores for the 62 IgSF proteins with known structure but yet uncharacterized binding interfaces.

Assessing the accuracy of contact predictions in CASP13.

The accuracy of sequence-based tertiary contact predictions was assessed in a blind prediction experiment at the CASP13 meeting. After 4 years of significant improvements in prediction accuracy, another dramatic advance has taken place since CASP12 was held 2 years ago. The precision of predicting the top L/5 contacts in the free modeling category, where L is the corresponding length of the protein in residues, has exceeded 70%. As a comparison, the best-performing group at CASP12 with a 47% precision would have finished below the top 1/3 of the CASP13 groups. Extensively trained deep neural network approaches dominate the top performing algorithms, which appear to efficiently integrate information on coevolving residues and interacting fragments or possibly utilize memories of sequence similarities and sometimes can deliver accurate results even in the absence of virtually any target specific evolutionary information. If the current performance is evaluated by F-score on L contacts, it stands around 24% right now, which, despite the tremendous impact and advance in improving its utility for structure modeling, also suggests that there is much room left for further improvement.

Protein-protein binding supersites.

The lack of a deep understanding of how proteins interact remains an important roadblock in advancing efforts to identify binding partners and uncover the corresponding regulatory mechanisms of the functions they mediate. Understanding protein-protein interactions is also essential for designing specific chemical modifications to develop new reagents and therapeutics. We explored the hypothesis of whether protein interaction sites serve as generic biding sites for non-cognate protein ligands, just as it has been observed for small-molecule-binding sites in the past. Using extensive computational docking experiments on a test set of 241 protein complexes, we found that indeed there is a strong preference for non-cognate ligands to bind to the cognate binding site of a receptor. This observation appears to be robust to variations in docking programs, types of non-cognate protein probes, sizes of binding patches, relative sizes of binding patches and full-length proteins, and the exploration of obligate and non-obligate complexes. The accuracy of the docking scoring function appears to play a role in defining the correct site. The frequency of interaction of unrelated probes recognizing the binding interface was utilized in a simple prediction algorithm that showed accuracy competitive with other state of the art methods.

Nuc-ErbB3 regulates H3K27me3 levels and HMT activity to establish epigenetic repression during peripheral myelination.

Nuc-ErbB3 an alternative transcript from the ErbB3 locus binds to a specific DNA motif and associates with Schwann cell chromatin. Here we generated a nuc-ErbB3 knockin mouse that lacks nuc-ErbB3 expression in the nucleus without affecting the neuregulin-ErbB3 receptor signaling. Nuc-ErbB3 knockin mice exhibit hypermyelination and aberrant myelination at the paranodal region. This phenotype is attributed to de-repression of myelination associated gene transcription following loss of nuc-ErbB3 and histone H3K27me3 promoter occupancy. Nuc-ErbB3 knockin mice exhibit reduced association of H3K27me3 with myelination-associated gene promoters and increased RNA Pol-II rate of transcription of these genes. In addition, nuc-ErbB3 directly regulates levels of H3K27me3 in Schwann cells. Nuc-ErbB3 knockin mice exhibit significant decrease of histone H3K27me3 methyltransferase (HMT) activity and reduced levels of H3K27me3. Collectively, nuc-ErbB3 is a master transcriptional repressor, which regulates HMT activity to establish a repressive chromatin landscape on promoters of genes during peripheral myelination.