Modeling post-translational modifications and cancer-associated mutations that impact the heterochromatin protein 1α-importin α heterodimers

Writers and readers of H3K9me2 form distinct protein networks during the cell cycle that include candidates for H3K9 mimicry

Histone H3 lysine 9 methylation (H3K9me), which is written by the Euchromatic Histone Lysine Methyltransferases EHMT1 and EHMT2 and read by the heterochromatin protein 1 (HP1) chromobox (CBX) protein family, is dysregulated in many types of cancers. Approaches to inhibit regulators of this pathway are currently being evaluated for therapeutic purposes. Thus, knowledge of the complexes supporting the function of these writers and readers during the process of cell proliferation is critical for our understanding of their role in carcinogenesis. Here, we immunopurified each of these proteins and used mass spectrometry to define their associated non-histone proteins, individually and at two different phases of the cell cycle, namely G1/S and G2/M. Our findings identify novel binding proteins for these writers and readers, as well as corroborate known interactors, to show the formation of distinct protein complex networks in a cell cycle phase-specific manner. Furthermore, there is an organizational switch between cell cycle phases for interactions among specific writer-reader pairs. Through a multi-tiered bioinformatics-based approach, we reveal that many interacting proteins exhibit histone mimicry, based on an H3K9-like linear motif. Gene ontology analyses, pathway enrichment, and network reconstruction inferred that these comprehensive EHMT and CBX-associated interacting protein networks participate in various functions, including transcription, DNA repair, splicing, and membrane disassembly. Combined, our data reveals novel complexes that provide insight into key functions of cell cycle-associated epigenomic processes that are highly relevant for better understanding these chromatin-modifying proteins during cell cycle and carcinogenesis.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

Interpreting Sequence Variation in PDAC-Predisposing Genes Using a Multi-Tier Annotation Approach Performed at the Gene, Patient, and Cohort Level

We investigated germline variation in pancreatic ductal adenocarcinoma (PDAC) predisposition genes in 535 patients, using a custom-built panel and a new complementary bioinformatic approach. Our panel assessed genes belonging to DNA repair, cell cycle checkpoints, migration, and preneoplastic pancreatic conditions. Our bioinformatics approach integrated annotations of variants by using data derived from both germline and somatic references. This integrated approach with expanded evidence enabled us to consider patterns even among private mutations, supporting a functional role for certain alleles, which we believe enhances individualized medicine beyond classic gene-centric approaches. Concurrent evaluation of three levels of evidence, at the gene, sample, and cohort level, has not been previously done. Overall, we identified in PDAC patient germline samples, 12% with mutations previously observed in pancreatic cancers, 23% with mutations previously discovered by sequencing other human tumors, and 46% with mutations with germline associations to cancer. Non-polymorphic protein-coding pathogenic variants were found in 18.4% of patient samples. Moreover, among patients with metastatic PDAC, 16% carried at least one pathogenic variant, and this subgroup was found to have an improved overall survival (22.0 months versus 9.8; p=0.008) despite a higher pre-treatment CA19-9 level (p=0.02). Genetic alterations in DNA damage repair genes were associated with longer overall survival among patients who underwent resection surgery (92 months vs. 46; p=0.06). ATM alterations were associated with more frequent metastatic stage (p = 0.04) while patients with BRCA1 or BRCA2 alterations had improved overall survival (79 months vs. 39; p=0.05). We found that mutations in genes associated with chronic pancreatitis were more common in non-white patients (p<0.001) and associated with longer overall survival (52 months vs. 26; p=0.004), indicating the need for greater study of the relationship among these factors. More than 90% of patients were found to have variants of uncertain significance, which is higher than previously reported. Furthermore, we generated 3D models for selected mutant proteins, which suggested distinct mechanisms underlying their dysfunction, likely caused by genetic alterations. Notably, this type of information is not predictable from sequence alone, underscoring the value of structural bioinformatics to improve genomic interpretation. In conclusion, the variation in PDAC predisposition genes appears to be more extensive than anticipated. This information adds to the growing body of literature on the genomic landscape of PDAC and brings us closer to a more widespread use of precision medicine for this challenging disease.

A Phosphorylation-Induced Switch in the Nuclear Localization Sequence of the Intrinsically Disordered NUPR1 Hampers Binding to Importin

Several carrier proteins are involved in protein transport from the cytoplasm to the nucleus in eukaryotic cells. One of those is importin α, of which there are several human isoforms; among them, importin α3 (Impα3) has a high flexibility. The protein NUPR1, a nuclear protein involved in the cell-stress response and cell cycle regulation, is an intrinsically disordered protein (IDP) that has a nuclear localization sequence (NLS) to allow for nuclear translocation. NUPR1 does localize through the whole cell. In this work, we studied the affinity of the isolated wild-type NLS region (residues 54–74) of NUPR1 towards Impα3 and several mutants of the NLS region by using several biophysical techniques and molecular docking approaches. The NLS region of NUPR1 interacted with Impα3, opening the way to model the nuclear translocation of disordered proteins. All the isolated NLS peptides were disordered. They bound to Impα3 with low micromolar affinity (1.7–27 μM). Binding was hampered by removal of either Lys65 or Lys69 residues, indicating that positive charges were important; furthermore, binding decreased when Thr68 was phosphorylated. The peptide phosphorylated at Thr68, as well as four phospho-mimetic peptides (all containing the Thr68Glu mutation), showed the presence of a sequential NN(i,i + 1) nuclear Overhauser effect (NOE) in the 2D-¹H-NMR (two-dimensional–proton NMR) spectra, indicating the presence of turn-like conformations. Thus, the phosphorylation of Thr68 modulates the binding of NUPR1 to Impα3 by a conformational, entropy-driven switch from a random-coil conformation to a turn-like structure.

Modeling post-translational modifications and cancer-associated mutations that impact the heterochromatin protein 1α-importin α heterodimers

Heterochromatin protein 1α (HP1α) is a protein that mediates cancer-associated processes in the cell nucleus. Proteomic experiments, reported here, demonstrate that HP1α complexes with importin α (IMPα), a protein necessary for its nuclear transport. This data is congruent with Simple Linear Motif (SLiM) analyses that identify an IMPα-binding motif within the linker that joins the two globular domains of this protein. Using molecular modeling and dynamics simulations, we develop a model of the IMPα-HP1α complex and investigate the impact of phosphorylation and genomic variants on their interaction. We demonstrate that phosphorylation of the HP1α linker likely regulates its association with IMPα, which has implications for HP1α access to the nucleus, where it functions. Cancer-associated genomic variants do not abolish the interaction of HP1α but instead lead to rearrangements where the variant proteins maintain interaction with IMPα, but with less specificity. Combined, this new mechanistic insight bears biochemical, cell biological, and biomedical relevance.