Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the 3-dimensional electron density of a protein, as it would be determined by cryo-EM or X-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous densitydriven molecular dynamics methodologies that determine only the best map-model fits, our work uses the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along reaction coordinates derived from electron densities can serve to induce conformational transitions between known intermediates. The simulated pathways appear reversible, with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein DataBank. We find that the best quantitative agreement with experimental freeenergy differences is obtained using medium resolution (∼5 Å) density information coupled to comparatively large structural transitions. Practical considerations for generating transitions with multiple intermediate atomic density distributions are also discussed.2

No abstract

No abstract

No abstract

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that lacks three major drug-targetable receptors, ER, PR, and HER2. TNBC patients have much worse 5-year survival rates (60%) in contrast to 90% for other breast cancer subtypes and display highly heterogeneous molecular profiles, cellular phenotypes, and drug responses, which poses major challenges in patient treatments. The tumor suppressor gene TP53 is mutated in 30% of breast tumors overall and but highly prevalent (~80%) in TNBC. Unlike mutations in other tumor suppressor genes that are predominantly loss-of-function deletions or truncations, TP53 mutations occur mostly as >100 different missense mutations within the DNA binding domain, implying that the mutant proteins may exert both loss-of-function activities and gain of distinct neomorphic functions, thus contributing to phenotypic heterogeneity of TNBC. When we characterized systematically a panel of MCF10A cell lines expressing 10 most prevalent missense mutant p53 proteins, the cell lines indeed displayed highly diverse neomorphic cellular phenotypes distinct from those of p53-knockdown cells. To investigate molecular mechanisms underlying the heterogeneity, we then performed RNA-Seq and pathway analysis and identified the key pathways, such as the Hippo/YAP pathway, that were dysregulated correlatively with phenotypic aggressiveness of the mutant p53 cell lines. In addition, ChIP-Seq analysis revealed that promoter binding capacity and preference of mutant p53 proteins associated with more aggressive phenotypes were more severely affected, especially for the genes in the dysregulated pathways identified from RNA-Seq analysis. These demonstrated collectively that different missense p53 mutations lead to heterogeneous phenotypes by exerting distinct neomorphic molecular functions. Further, given that TP53 mutations by themselves cannot drive full cancer progression, these imply that cells with different p53 missense mutations need distinct sets of additional “co-driver” mutations and alteration of cellular programs specific to each mutation for full cancer progression, representing potential molecular targets for personalized therapies. Supporting this hypothesis, when we performed genome-wide in vitro CRISPR screens in search of co-driver mutations specific to different p53 mutations, a unique set of hits was identified for each mutant p53-expressing cell lines. However, in in vivo mouse xenograft models, even the cells expressing aggressive p53 mutants such R273C failed to develop tumors upon transducing gene-deleting CRISPR gRNA libraries at high MOI. Based on reasoning that development of tumor requires mutations in both tumor suppressors and oncogenes, we then performed CRISPR screens on the p53-R273C cells overexpressing MYC, a known oncogene for TNBC, and observed tumor formation within 9 weeks, only after the CRISPR library transduction. By next-generation sequencing of the gRNA cassettes amplified from the tumors, >20 novel co-driver candidates in addition to known tumor suppressors such as NF2 and PTEN were identified. Interestingly, ARAF, a proto-oncogene, was one of the top candidates found in multiple tumors, and the targeted sequencing confirmed out-of-frame deletions resulting in truncated proteins with only the N-term Ras-binding domain. We are currently validating the functional relevance of these findings in conjunction with the dysregulated pathways identified from RNA-Seq and ChIP-Seq analysis. Taken together, our integrated approach of utilizing phenotyping, multi-omics bioinformatics analysis, and screening has revealed the molecular mechanisms underlying phenotypic and molecular heterogeneity and potential molecular targets of TNBC. Citation Format: Dustin Grief, Anasuya Pal, Laura Gonzalez-Malerva, Seron Eaton, Chenxi Xu, Grant Christensen, Joy Blain, Nicholas Mellor, Jason Steel, Chitrak Gupta, Ellen Streitwieser, Abhishek Singharoy, Jin Park, Joshua LaBaer. A genome-wide functional genomics screen reveals unique co-driver mutations of mutant TP53 promoting cellular heterogeneity during breast cancer progression [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-02-05.