Beyond structural bioinformatics for genomics with dynamics characterization of an expanded KRAS mutational landscape.

Current capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions. Because KRAS-altered tumors frequently harbor one of three classic hotspot mutations, nearly all studies have focused on these mutations, leaving significant functional ambiguity across the broader KRAS genomic landscape observed in cancer and non-cancer diseases. Herein, we extend structural bioinformatics with molecular simulations to study an expanded landscape of 86 KRAS mutations. We identify multiple coordinated changes strongly associated with experimentally established KRAS biophysical and biochemical properties. The patterns we observe span hotspot and non-hotspot alterations, which can all dysregulate Switch regions, producing mutation-restricted conformations with different effector binding propensities. We experimentally measured mutation thermostability and identified shared and distinct patterns with simulations. Our results indicate mutation-specific conformations, which show potential for future research into how these alterations reverberate into different molecular and cellular functions. The data we present is not predictable using current genomic tools, demonstrating the added functional information derived from molecular simulations for interpreting human genetic variation.

Beyond Structural Bioinformatics for Genomics with Dynamics Characterization of an Expanded KRAS Mutational Landscape.

Current capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions. Because KRAS-altered tumors frequently harbor one of three classic hotspot mutations, nearly all studies have focused on these mutations, leaving significant functional ambiguity across the broader KRAS genomic landscape observed in cancer and non-cancer diseases. Herein, we extend structural bioinformatics with molecular simulations to study an expanded landscape of 86 KRAS mutations. We identify multiple coordinated changes strongly associated with experimentally established KRAS biophysical and biochemical properties. The patterns we observe span hotspot and non-hotspot alterations, which can all dysregulate Switch regions, producing mutation-restricted conformations with different effector binding propensities. We experimentally measured mutation thermostability and identified shared and distinct patterns with simulations. Our results indicate mutation-specific conformations which show potential for future research into how these alterations reverberate into different molecular and cellular functions. The data we present is not predictable using current genomic tools, demonstrating the added functional information derived from molecular simulations for interpreting human genetic variation.

The synaptosome-associated protein 23 (SNAP23) is necessary for proper myogenesis.

Vesicle-mediated transport is necessary for maintaining cellular homeostasis and proper signaling. The synaptosome-associated protein 23 (SNAP23) is a member of the SNARE protein family and mediates the vesicle docking and membrane fusion steps of secretion during exocytosis. Skeletal muscle has been established as a secretory organ; however, the role of SNAP23 in the context of skeletal muscle development is still unknown. Here, we show that depletion of SNAP23 in C2C12 mouse myoblasts reduces their ability to differentiate into myotubes as a result of premature cell cycle exit and early activation of the myogenic transcriptional program. This effect is rescued when cells are seeded at a high density or when cultured in conditioned medium from wild type cells. Proteomic analysis of collected medium indicates that SNAP23 depletion leads to a misregulation of exocytosis, including decreased secretion of the insulin-like growth factor 1 (IGF1), a critical protein for muscle growth, development, and function. We further demonstrate that treatment of SNAP23-depleted cells with exogenous IGF1 rescues their myogenic capacity. We propose that SNAP23 mediates the secretion of specific proteins, such as IGF1, that are important for achieving proper differentiation of skeletal muscle cells during myogenesis. This work highlights the underappreciated role of skeletal muscle as a secretory organ and contributes to the understanding of factors necessary for myogenesis.

Structural bioinformatics enhances the interpretation of somatic mutations in KDM6A found in human cancers.

The histone demethylase KDM6A has recently elicited significant attention because its mutations are associated with a rare congenital disorder (Kabuki syndrome) and various types of human cancers. However, distinguishing KDM6A mutations that are deleterious to the enzyme and their underlying mechanisms of dysfunction remain to be fully understood. Here, we report the results from a multi-tiered approach evaluating the impact of 197 KDM6A somatic mutations using information derived from combining conventional genomics data with computational biophysics. This comprehensive approach incorporates multiple scores derived from alterations in protein sequence, structure, and molecular dynamics. Using this method, we classify the KDM6A mutations into 136 damaging variants (69.0%), 32 tolerated variants (16.2%), and 29 variants of uncertain significance (VUS, 14.7%), which is a significant improvement from the previous classification based on the conventional tools (over 40% VUS). We further classify the damaging variants into 15 structural variants (SV), 88 dynamic variants (DV), and 33 structural and dynamic variants (SDV). Comparison with variant scoring methods used in current clinical diagnosis guidelines demonstrates that our approach provides a more comprehensive evaluation of damaging potential and reveals mechanisms of dysfunction. Thus, these results should be taken into consideration for clinical assessment of the damaging potential of each mutation, as they provide hypotheses for experimental validation and critical information for the development of mutant-specific drugs to fight diseases caused by KDM6A dysfunctions.

Enhanced interpretation of 935 hotspot and non-hotspot RAS variants using evidence-based structural bioinformatics.

In the current study, we report computational scores for advancing genomic interpretation of disease-associated genomic variation in members of the RAS family of genes. For this purpose, we applied 31 sequence- and 3D structure-based computational scores, chosen by their breadth of biophysical properties. We parametrized our data by assembling a numerically homogenized experimentally-derived dataset, which when use in our calculations reveal that computational scores using 3D structure highly correlate with experimental measures (e.g., GAP-mediated hydrolysis RSpearman = 0.80 and RAF affinity Rspearman = 0.82), while sequence-based scores are discordant with this data. Performing all-against-all comparisons, we applied this parametrized modeling approach to the study of 935 RAS variants from 7 RAS genes, which led us to identify 4 groups of mutations according to distinct biochemical scores within each group. Each group was comprised of hotspot and non-hotspot KRAS variants, indicating that poorly characterized variants could functionally behave like pathogenic mutations. Combining computational scores using dimensionality reduction indicated that changes to local unfolding propensity associate with changes in enzyme activity by genomic variants. Hence, our systematic approach, combining methodologies from both clinical genomics and 3D structural bioinformatics, represents an expansion for interpreting genomic data, provides information of mechanistic value, and that is transferable to other proteins.

Computational modeling reveals key molecular properties and dynamic behavior of disruptor of telomeric silencing 1-like (DOT1L) and partnering complexes involved in leukemogenesis.

Disruptor of telomeric silencing 1-like (DOT1L) is the only non-SET domain histone lysine methyltransferase (KMT) and writer of H3K79 methylation on nucleosomes marked by H2B ubiquitination. DOT1L has elicited significant attention because of its interaction or fusion with members of the AF protein family in blood cell biology and leukemogenic transformation. Here, our goal was to extend previous structural information by performing a robust molecular dynamic study of DOT1L and its leukemogenic partners combined with mutational analysis. We show that statically and dynamically, D161, G163, E186, and F223 make frequent time-dependent interactions with SAM, while additional residues T139, K187, and N241 interact with SAM only under dynamics. Dynamics models reveal DOT1L, SAM, and H4 moving as one and show that more than twice the number of DOT1L residues interacts with these partners, relative to the static structure. Mutational analyses indicate that six of these residues are intolerant to substitution. We describe the dynamic behavior of DOT1L interacting with AF10 and AF9. Studies on the dynamics of a heterotrimeric complex of DOT1L1-AF10 illuminated describe coordinated motions that impact the relative position of the DOT1L HMT domain to the nucleosome. The molecular motions of the DOT1L-AF9 complex are less extensive and highly dynamic, resembling a swivel-like mechanics. Through molecular dynamics and mutational analysis, we extend the knowledge previous provided by static measurements. These results are important to consider when describing the biochemical properties of DOT1L, under normal and in disease conditions, as well as for the development of novel therapeutic agents.

KrasG12D induces changes in chromatin territories that differentially impact early nuclear reprogramming in pancreatic cells.

BACKGROUND: Pancreatic ductal adenocarcinoma initiation is most frequently caused by Kras mutations. RESULTS: Here, we apply biological, biochemical, and network biology methods to validate GEMM-derived cell models using inducible KrasG12D expression. We describe the time-dependent, chromatin remodeling program that impacts function during early oncogenic signaling. We find that the KrasG12D-induced transcriptional response is dominated by downregulated expression concordant with layers of epigenetic events. More open chromatin characterizes the ATAC-seq profile associated with a smaller group of upregulated genes and epigenetic marks. RRBS demonstrates that promoter hypermethylation does not account for the silencing of the extensive gene promoter network. Moreover, ChIP-Seq reveals that heterochromatin reorganization plays little role in this early transcriptional program. Notably, both gene activation and silencing primarily depend on the marking of genes with a combination of H3K27ac, H3K4me3, and H3K36me3. Indeed, integrated modeling of all these datasets shows that KrasG12D regulates its transcriptional program primarily through unique super-enhancers and enhancers, and marking specific gene promoters and bodies. We also report chromatin remodeling across genomic areas that, although not contributing directly to cis-gene transcription, are likely important for KrasG12D functions. CONCLUSIONS: In summary, we report a comprehensive, time-dependent, and coordinated early epigenomic program for KrasG12D in pancreatic cells, which is mechanistically relevant to understanding chromatin remodeling events underlying transcriptional outcomes needed for the function of this oncogene.

Molecular mechanics and dynamic simulations of well-known Kabuki syndrome-associated KDM6A variants reveal putative mechanisms of dysfunction.

BACKGROUND: Kabuki syndrome is a genetic disorder that affects several body systems and presents with variations in symptoms and severity. The syndrome is named for a common phenotype of faces resembling stage makeup used in a Japanese traditional theatrical art named kabuki. The most frequent cause of this syndrome is mutations in the H3K4 family of histone methyltransferases while a smaller percentage results from genetic alterations affecting the histone demethylase, KDM6A. Because of the rare presentation of the latter form of the disease, little is known about how missense changes in the KDM6A protein sequence impact protein function. RESULTS: In this study, we use molecular mechanic and molecular dynamic simulations to enhance the annotation and mechanistic interpretation of the potential impact of eleven KDM6A missense variants found in Kabuki syndrome patients. These variants (N910S, D980V, S1025G, C1153R, C1153Y, P1195L, L1200F, Q1212R, Q1248R, R1255W, and R1351Q) are predicted to be pathogenic, likely pathogenic or of uncertain significance by sequence-based analysis. Here, we demonstrate, for the first time, that although Kabuki syndrome missense variants are found outside the functionally critical regions, they could affect overall function by significantly disrupting global and local conformation (C1153R, C1153Y, P1195L, L1200F, Q1212R, Q1248R, R1255W and R1351Q), chemical environment (C1153R, C1153Y, P1195L, L1200F, Q1212R, Q1248R, R1255W and R1351Q), and/or molecular dynamics of the catalytic domain (all variants). In addition, our approaches predict that many mutations, in particular C1153R, could allosterically disrupt the key enzymatic interactions of KDM6A. CONCLUSIONS: Our study demonstrates that the KDM6A Kabuki syndrome variants may impair histone demethylase function through various mechanisms that include altered protein integrity, local environment, molecular interactions and protein dynamics. Molecular dynamics simulations of the wild type and the variants are critical to gain a better understanding of molecular dysfunction. This type of comprehensive structure- and MD-based analyses should help develop improved impact scoring systems to interpret the damaging effects of variants in this protein and other related proteins as well as provide detailed mechanistic insight that is not currently predictable from sequence alone.