Summary Genetic studies have established anaplastic lymphoma kinase (ALK), a cell surface receptor tyrosine kinase, as a tractable molecular target in neuroblastoma. We describe comprehensive genomic, biochemical, and computational analyses of ALK mutations across 1596 diagnostic neuroblastoma samples. ALK tyrosine kinase domain mutations occurred in 8% of samples; at three hotspots plus 13 minor sites – and correlated significantly with poorer survival in high- and intermediate-risk neuroblastoma. Biochemical and computational studies distinguished oncogenic (constitutively activating) from non-oncogenic mutations and allowed robust computational prediction of their effects. We also established differential in vitro crizotinib sensitivity of mutated variants. Our studies identify ALK genomic status as a clinically important therapeutic stratification tool in neuroblastoma, and will allow tailoring of ALK-targeted therapy to specific mutations.

Molecular dynamics calculations have been used to determine the structure of phosphatidylinositol 4,5 bisphosphate (PIP2) at the quantum level and to quantify the propensity for PIP2 to bind two physiologically relevant divalent cations, Mg2+ and Ca2+. We performed a geometry optimization at the Hartree-Fock 6-31+G(d) level of theory in vacuum and with a polarized continuum dielectric to determine the conformation of the phospholipid headgroup in the presence of water and its partial charge distribution. The angle between the headgroup and the acyl chains is nearly perpendicular, suggesting that in the absence of other interactions, the inositol ring would lie flat along the cytoplasmic surface of the plasma membrane. Next, we employed hybrid quantum mechanics / molecular mechanics (QM/MM) simulations to investigate the protonation state of PIP2 and its interactions with magnesium or calcium. We test the hypothesis suggested by prior experiments that binding of magnesium to PIP2 is mediated by a water molecule that is absent when calcium binds. These results may explain the selective ability of calcium to induce the formation of PIP2 clusters and phase separation from other lipids.

Antibody maturation is a critical immune process governed by the enzyme activation-induced deaminase (AID), a member of the AID/APOBEC DNA deaminase family. AID/APOBEC deaminases preferentially target cytosine within distinct preferred sequence motifs in DNA, with specificity largely conferred by a small 9–11 residue protein loop that differs among family members. Here, we aimed to determine the key functional characteristics of this protein loop in AID and to thereby inform our understanding of the mode of DNA engagement. To this end, we developed a methodology (Sat-Sel-Seq) that couples saturation mutagenesis at each position across the targeting loop, with iterative functional selection and next-generation sequencing. This high-throughput mutational analysis revealed dominant characteristics for residues within the loop and additionally yielded enzymatic variants that enhance deaminase activity. To rationalize these functional requirements, we performed molecular dynamics simulations that suggest that AID and its hyperactive variants can engage DNA in multiple specific modes. These findings align with AID's competing requirements for specificity and flexibility to efficiently drive antibody maturation. Beyond insights into the AID-DNA interface, our Sat-Sel-Seq approach also serves to further expand the repertoire of techniques for deep positional scanning and may find general utility for high-throughput analysis of protein function.

The cancer-predisposing Lynch Syndrome (LS) arises from germline mutations in DNA mismatch repair (MMR) genes, predominantly MLH1, MSH2, MSH6, and PMS2. A major challenge for clinical diagnosis of LS is the frequent identification of variants of uncertain significance (VUS) in these genes, as it is often difficult to determine variant pathogenicity, particularly for missense variants. Generic programs such as SIFT and PolyPhen-2, and MMR gene-specific programs such as PON-MMR and MAPP-MMR, are often used to predict deleterious or neutral effects of VUS in MMR genes. We evaluated the performance of multiple predictive programs in the context of functional biologic data for 15 VUS in MLH1, MSH2, and PMS2. Using cell line models, we characterized VUS predicted to range from neutral to pathogenic on mRNA and protein expression, basal cellular viability, viability following treatment with a panel of DNA-damaging agents, and functionality in DNA damage response (DDR) signaling, benchmarking to wild-type MMR proteins. Our results suggest that the MMR gene-specific classifiers do not always align with the experimental phenotypes related to DDR. Our study highlights the importance of complementary experimental and computational assessment to develop future predictors for the assessment of VUS.

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