Small-molecule inhibitors targeting Polycomb repressive complex 1 RING domain.

Polycomb repressive complex 1 (PRC1) is an essential chromatin-modifying complex that monoubiquitinates histone H2A and is involved in maintaining the repressed chromatin state. Emerging evidence suggests PRC1 activity in various cancers, rationalizing the need for small-molecule inhibitors with well-defined mechanisms of action. Here, we describe the development of compounds that directly bind to RING1B-BMI1, the heterodimeric complex constituting the E3 ligase activity of PRC1. These compounds block the association of RING1B-BMI1 with chromatin and inhibit H2A ubiquitination. Structural studies demonstrate that these inhibitors bind to RING1B by inducing the formation of a hydrophobic pocket in the RING domain. Our PRC1 inhibitor, RB-3, decreases the global level of H2A ubiquitination and induces differentiation in leukemia cell lines and primary acute myeloid leukemia (AML) samples. In summary, we demonstrate that targeting the PRC1 RING domain with small molecules is feasible, and RB-3 represents a valuable chemical tool to study PRC1 biology.

An evolution-based approach to De Novo protein design and case study on Mycobacterium tuberculosis.

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality.

Changing the Apoptosis Pathway through Evolutionary Protein Design.

One obstacle in de novo protein design is the vast sequence space that needs to be searched through to obtain functional proteins. We developed a new method using structural profiles created from evolutionarily related proteins to constrain the simulation search process, with functions specified by atomic-level ligand-protein binding interactions. The approach was applied to redesigning the BIR3 domain of the X-linked inhibitor of apoptosis protein (XIAP), whose primary function is to suppress the cell death by inhibiting caspase-9 activity; however, the function of the wild-type XIAP can be eliminated by the binding of Smac peptides. Isothermal calorimetry and luminescence assay reveal that the designed XIAP domains can bind strongly with the Smac peptides but do not significantly inhibit the caspase-9 proteolytic activity in vitro compared with the wild-type XIAP protein. Detailed mutation assay experiments suggest that the binding specificity in the designs is essentially determined by the interplay of structural profile and physical interactions, which demonstrates the potential to modify apoptosis pathways through computational design.

BMI1 regulates PRC1 architecture and activity through homo- and hetero-oligomerization.

BMI1 is a core component of the polycomb repressive complex 1 (PRC1) and emerging data support a role of BMI1 in cancer. The central domain of BMI1 is involved in protein-protein interactions and is essential for its oncogenic activity. Here, we present the structure of BMI1 bound to the polyhomeotic protein PHC2 illustrating that the central domain of BMI1 adopts an ubiquitin-like (UBL) fold and binds PHC2 in a ß-hairpin conformation. Unexpectedly, we find that the UBL domain is involved in homo-oligomerization of BMI1. We demonstrate that both the interaction of BMI1 with polyhomeotic proteins and homo-oligomerization via UBL domain are necessary for H2A ubiquitination activity of PRC1 and for clonogenic potential of U2OS cells. Here, we also emphasize need for joint application of NMR spectroscopy and X-ray crystallography to determine the overall structure of the BMI1-PHC2 complex.

Detection of disordered regions in globular proteins using ¹³C-detected NMR.

Characterization of disordered regions in globular proteins constitutes a significant challenge. Here, we report an approach based on ¹³C-detected nuclear magnetic resonance experiments for the identification and assignment of disordered regions in large proteins. Using this method, we demonstrate that disordered fragments can be accurately identified in two homologs of menin, a globular protein with a molecular weight over 50 kDa. Our work provides an efficient way to characterize disordered fragments in globular proteins for structural biology applications.