What Combined Measurements From Structures and Imaging Tell Us About DNA Damage Responses

Decoding Cancer Variants of Unknown Significance for Helicase-Nuclease-RPA Complexes Orchestrating DNA Repair During Transcription and Replication

All tumors have DNA mutations, and a predictive understanding of those mutations could inform clinical treatments. However, 40% of the mutations are variants of unknown significance (VUS), with the challenge being to objectively predict whether a VUS is pathogenic and supports the tumor or whether it is benign. To objectively decode VUS, we mapped cancer sequence data and evolutionary trace (ET) scores onto crystallography and cryo-electron microscopy structures with variant impacts quantitated by evolutionary action (EA) measures. As tumors depend on helicases and nucleases to deal with transcription/replication stress, we targeted helicase–nuclease–RPA complexes: (1) XPB-XPD (within TFIIH), XPF-ERCC1, XPG, and RPA for transcription and nucleotide excision repair pathways and (2) BLM, EXO5, and RPA plus DNA2 for stalled replication fork restart. As validation, EA scoring predicts severe effects for most disease mutations, but disease mutants with low ET scores not only are likely destabilizing but also disrupt sophisticated allosteric mechanisms. For sites of disease mutations and VUS predicted to be severe, we found strong co-localization to ordered regions. Rare discrepancies highlighted the different survival requirements between disease and tumor mutations, as well as the value of examining proteins within complexes. In a genome-wide analysis of 33 cancer types, we found correlation between the number of mutations in each tumor and which pathways or functional processes in which the mutations occur, revealing different mutagenic routes to tumorigenesis. We also found upregulation of ancient genes including BLM, which supports a non-random and concerted cancer process: reversion to a unicellular, proliferation-uncontrolled, status by breaking multicellular constraints on cell division. Together, these genes and global analyses challenge the binary “driver” and “passenger” mutation paradigm, support a gradient impact as revealed by EA scoring from moderate to severe at a single gene level, and indicate reduced regulation as well as activity. The objective quantitative assessment of VUS scoring and gene overexpression in the context of functional interactions and pathways provides insights for biology, oncology, and precision medicine.

Target highlights in CASP14: Analysis of models by structure providers

The biological and functional significance of selected Critical Assessment of Techniques for Protein Structure Prediction 14 (CASP14) targets are described by the authors of the structures. The authors highlight the most relevant features of the target proteins and discuss how well these features were reproduced in the respective submitted predictions. The overall ability to predict three-dimensional structures of proteins has improved remarkably in CASP14, and many difficult targets were modeled with impressive accuracy. For the first time in the history of CASP, the experimentalists not only highlighted that computational models can accurately reproduce the most critical structural features observed in their targets, but also envisaged that models could serve as a guidance for further studies of biologically-relevant properties of proteins.

Evolving SAXS versatility: solution X-ray scattering for macromolecular architecture, functional landscapes, and integrative structural biology

Small-angle X-ray scattering (SAXS) has emerged as an enabling integrative technique for comprehensive analyses of macromolecular structures and interactions in solution. Over the past two decades, SAXS has become a mainstay of the structural biologist's toolbox, supplying multiplexed measurements of molecular shape and dynamics that unveil biological function. Here, we discuss evolving SAXS theory, methods, and applications that extend the field of small-angle scattering beyond simple shape characterization. SAXS, coupled with size-exclusion chromatography (SEC-SAXS) and time-resolved (TR-SAXS) methods, is now providing high-resolution insight into macromolecular flexibility and ensembles, delineating biophysical landscapes, and facilitating high-throughput library screening to assess macromolecular properties and to create opportunities for drug discovery. Looking forward, we consider SAXS in the integrative era of hybrid structural biology methods, its potential for illuminating cellular supramolecular and mesoscale structures, and its capacity to complement high-throughput bioinformatics sequencing data. As advances in the field continue, we look forward to proliferating uses of SAXS based upon its abilities to robustly produce mechanistic insights for biology and medicine.

Cancer mutational burden is shaped by G4 DNA, replication stress and mitochondrial dysfunction

A hallmark of cancer is genomic instability, which can enable cancer cells to evade therapeutic strategies. Here we employed a computational approach to uncover mechanisms underlying cancer mutational burden by focusing upon relationships between 1) translocation breakpoints and the thousands of G4 DNA-forming sequences within retrotransposons impacting transcription and exemplifying probable non-B DNA structures and 2) transcriptome profiling and cancer mutations. We determined the location and number of G4 DNA-forming sequences in the Genome Reference Consortium Human Build 38 and found a total of 358,605 covering ∼13.4 million bases. By analyzing >97,000 unique translocation breakpoints from the Catalogue Of Somatic Mutations In Cancer (COSMIC), we found that breakpoints are overrepresented at G4 DNA-forming sequences within hominid-specific SVA retrotransposons, and generally occur in tumors with mutations in tumor suppressor genes, such as TP53. Furthermore, correlation analyses between mRNA levels and exome mutational loads from The Cancer Genome Atlas (TCGA) encompassing >450,000 gene-mutation regressions revealed strong positive and negative associations, which depended upon tissue of origin. The strongest positive correlations originated from genes not listed as cancer genes in COSMIC; yet, these show strong predictive power for survival in most tumor types by Kaplan-Meier estimation. Thus, correlation analyses of DNA structure and gene expression with mutation loads complement and extend more traditional approaches to elucidate processes shaping genomic instability in cancer. The combined results point to G4 DNA, activation of cell cycle/DNA repair pathways, and mitochondrial dysfunction as three major factors driving the accumulation of somatic mutations in cancer cells.

RNA Modifications: Reversal Mechanisms and Cancer

An emerging molecular understanding of RNA alkylation and its removal is transforming our knowledge of RNA biology and its interplay with cancer chemotherapy responses. DNA modifications are known to perform critical functions depending on the genome template, including gene expression, DNA replication timing, and DNA damage protection, yet current results suggest that the chemical diversity of DNA modifications pales in comparison to those on RNA. More than 150 RNA modifications have been identified to date, and their complete functional implications are still being unveiled. These include intrinsic roles such as proper processing and RNA maturation; emerging evidence has furthermore uncovered RNA modification "readers", seemingly analogous to those identified for histone modifications. These modification recognition factors may regulate mRNA stability, localization, and interaction with translation machinery, affecting gene expression. Not surprisingly, tumors differentially modulate factors involved in expressing these marks, contributing to both tumorigenesis and responses to alkylating chemotherapy. Here we describe the current understanding of RNA modifications and their removal, with a focus primarily on methylation and alkylation as functionally relevant changes to the transcriptome. Intriguingly, some of the same RNA modifications elicited by physiological processes are also produced by alkylating agents, thus blurring the lines between what is a physiological mark and a damage-induced modification. Furthermore, we find that a high level of gene expression of enzymes with RNA dealkylation activity is a sensitive readout for poor survival in four different cancer types, underscoring the likely importance of examining RNA dealkylation mechanisms to cancer biology and for cancer treatment and prognosis.

XLF and APLF bind Ku80 at two remote sites to ensure DNA repair by non-homologous end joining

The Ku70-Ku80 (Ku) heterodimer binds rapidly and tightly to the ends of DNA double-strand breaks and recruits factors of the non-homologous end-joining (NHEJ) repair pathway through molecular interactions that remain unclear. We have determined crystal structures of the Ku-binding motifs (KBM) of the NHEJ proteins APLF (A-KBM) and XLF (X-KBM) bound to a Ku-DNA complex. The two KBM motifs bind remote sites of the Ku80 α/β domain. The X-KBM occupies an internal pocket formed by an unprecedented large outward rotation of the Ku80 α/β domain. We observe independent recruitment of the APLF-interacting protein XRCC4 and of XLF to laser-irradiated sites via binding of A- and X-KBMs, respectively, to Ku80. Finally, we show that mutation of the X-KBM and A-KBM binding sites in Ku80 compromises both the efficiency and accuracy of end joining and cellular radiosensitivity. A- and X-KBMs may represent two initial anchor points to build the intricate interaction network required for NHEJ.

The MRE11-RAD50-NBS1 Complex Conducts the Orchestration of Damage Signaling and Outcomes to Stress in DNA Replication and Repair

Genomic instability in disease and its fidelity in health depend on the DNA damage response (DDR), regulated in part from the complex of meiotic recombination 11 homolog 1 (MRE11), ATP-binding cassette-ATPase (RAD50), and phosphopeptide-binding Nijmegen breakage syndrome protein 1 (NBS1). The MRE11-RAD50-NBS1 (MRN) complex forms a multifunctional DDR machine. Within its network assemblies, MRN is the core conductor for the initial and sustained responses to DNA double-strand breaks, stalled replication forks, dysfunctional telomeres, and viral DNA infection. MRN can interfere with cancer therapy and is an attractive target for precision medicine. Its conformations change the paradigm whereby kinases initiate damage sensing. Delineated results reveal kinase activation, posttranslational targeting, functional scaffolding, conformations storing binding energy and enabling access, interactions with hub proteins such as replication protein A (RPA), and distinct networks at DNA breaks and forks. MRN biochemistry provides prototypic insights into how it initiates, implements, and regulates multifunctional responses to genomic stress.

DNA-dependent protein kinase: Epigenetic alterations and the role in genomic stability of cancer

DNA-dependent protein kinase (DNA-PK), a member of phosphatidylinositol-kinase family, is a key protein in mammalian DNA double-strand break (DSB) repair that helps to maintain genomic integrity. DNA-PK also plays a central role in immune cell development and protects telomerase during cellular aging. Epigenetic deregulation due to endogenous and exogenous factors may affect the normal function of DNA-PK, which in turn could impair DNA repair and contribute to genomic instability. Recent studies implicate a role for epigenetics in the regulation of DNA-PK expression in normal and cancer cells, which may impact cancer progression and metastasis as well as provide opportunities for treatment and use of DNA-PK as a novel cancer biomarker. In addition, several small molecules and biological agents have been recently identified that can inhibit DNA-PK function or expression, and thus hold promise for cancer treatments. This review discusses the impact of epigenetic alterations and the expression of DNA-PK in relation to the DNA repair mechanisms with a focus on its differential levels in normal and cancer cells.

Targeting Allostery with Avatars to Design Inhibitors Assessed by Cell Activity: Dissecting MRE11 Endo- and Exonuclease Activities

For inhibitor design, as in most research, the best system is question dependent. We suggest structurally defined allostery to design specific inhibitors that target regions beyond active sites. We choose systems allowing efficient quality structures with conformational changes as optimal for structure-based design to optimize inhibitors. We maintain that evolutionarily related targets logically provide molecular avatars, where this Sanskrit term for descent includes ideas of functional relationships and of being a physical embodiment of the target's essential features without requiring high sequence identity. Appropriate biochemical and cell assays provide quantitative measurements, and for biomedical impacts, any inhibitor's activity should be validated in human cells. Specificity is effectively shown empirically by testing if mutations blocking target activity remove cellular inhibitor impact. We propose this approach to be superior to experiments testing for lack of cross-reactivity among possible related enzymes, which is a challenging negative experiment. As an exemplary avatar system for protein and DNA allosteric conformational controls, we focus here on developing separation-of-function inhibitors for meiotic recombination 11 nuclease activities. This was achieved not by targeting the active site but rather by geometrically impacting loop motifs analogously to ribosome antibiotics. These loops are neighboring the dimer interface and active site act in sculpting dsDNA and ssDNA into catalytically competent complexes. One of our design constraints is to preserve DNA substrate binding to geometrically block competing enzymes and pathways from the damaged site. We validate our allosteric approach to controlling outcomes in human cells by reversing the radiation sensitivity and genomic instability in BRCA mutant cells.

Small angle X-ray scattering and cross-linking for data assisted protein structure prediction in CASP 12 with prospects for improved accuracy

Experimental data offers empowering constraints for structure prediction. These constraints can be used to filter equivalently scored models or more powerfully within optimization functions toward prediction. In CASP12, Small Angle X-ray Scattering (SAXS) and Cross-Linking Mass Spectrometry (CLMS) data, measured on an exemplary set of novel fold targets, were provided to the CASP community of protein structure predictors. As solution-based techniques, SAXS and CLMS can efficiently measure states of the full-length sequence in its native solution conformation and assembly. However, this experimental data did not substantially improve prediction accuracy judged by fits to crystallographic models. One issue, beyond intrinsic limitations of the algorithms, was a disconnect between crystal structures and solution-based measurements. Our analyses show that many targets had substantial percentages of disordered regions (up to 40%) or were multimeric or both. Thus, solution measurements of flexibility and assembly support variations that may confound prediction algorithms trained on crystallographic data and expecting globular fully-folded monomeric proteins. Here, we consider the CLMS and SAXS data collected, the information in these solution measurements, and the challenges in incorporating them into computational prediction. As improvement opportunities were only partly realized in CASP12, we provide guidance on how data from the full-length biological unit and the solution state can better aid prediction of the folded monomer or subunit. We furthermore describe strategic integrations of solution measurements with computational prediction programs with the aim of substantially improving foundational knowledge and the accuracy of computational algorithms for biologically-relevant structure predictions for proteins in solution.