Three optimized assays for the evaluation of compounds that can rescue p53 mutants.
Ontology highlight
ABSTRACT:
SUBMITTER: Wu J
PROVIDER: S-EPMC8339244 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
Publications
Three optimized assays for the evaluation of compounds that can rescue p53 mutants.
Wu Jiale J Song Huaxin H Wang Zhengyuan Z Lu Min M
STAR protocols 20210727 3
Identifying drugs targeting p53 remains a major focus of precision oncology, with over twenty compounds that can rescue p53 mutants reported. Here, we suggest three easily accessible assays to determine the thermostability, protein folding, and transcriptional activity of p53 mutants-the go-to criteria for evaluating a rescue compound that acts by increasing p53 thermostability. Because of the diversity of p53 mutants, a compound that meets the criteria of one assay does not necessarily meet the ...[more]
Similar Datasets
Project description:Many biomedical problems relate to mutant functional properties across a sequence space of interest, e.g., flu, cancer, and HIV. Detailed knowledge of mutant properties and function improves medical treatment and prevention. A functional census of p53 cancer rescue mutants would aid the search for cancer treatments from p53 mutant rescue. We devised a general methodology for conducting a functional census of a mutation sequence space by choosing informative mutants early. The methodology was tested in a double-blind predictive test on the functional rescue property of 71 novel putative p53 cancer rescue mutants iteratively predicted in sets of three (24 iterations). The first double-blind 15-point moving accuracy was 47 percent and the last was 86 percent; r = 0.01 before an epiphanic 16th iteration and r = 0.92 afterward. Useful mutants were chosen early (overall r = 0.80). Code and data are freely available (http://www.igb.uci.edu/research/research.html, corresponding authors: R.H.L. for computation and R.K.B. for biology).
| S-EPMC2748235 | biostudies-literature
Project description:The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain ("cancer mutants"). Activity can be restored by second-site suppressor mutations ("rescue mutants"). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r(2)?=?0.77) with reported values of experimentally measured ??G protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants.
| S-EPMC3197647 | biostudies-literature
Project description:The tumor suppressor p53 is the most frequently mutated protein in human cancer. The majority of these mutations are missense mutations in the DNA binding domain of p53. Restoring p53 tumor suppressor function could have a major impact on the therapy for a wide range of cancers. Here we report a virtual screening approach that identified several small molecules with p53 reactivation activities. The UCI-LC0023 compound series was studied in detail and was shown to bind p53, induce a conformational change in mutant p53, restore the ability of p53 hotspot mutants to associate with chromatin, reestablish sequence-specific DNA binding of a p53 mutant in a reconstituted in vitro system, induce p53-dependent transcription programs, and prevent progression of tumors carrying mutant p53, but not p53null or p53WT alleles. Our study demonstrates feasibility of a computation-guided approach to identify small molecule corrector drugs for p53 hotspot mutations.
| S-EPMC9481737 | biostudies-literature
Project description:BackgroundSingle nucleotide polymorphisms (SNPs) are the most common form of genetic variability in the human genome and play a prominent role in the heritability of phenotypes. Especially rare alleles with frequencies less than 5% may exhibit a particularly strong influence on the development of complex diseases. The detection of rare alleles by standard DNA sequencing is time-consuming and cost-intensive. Here we discuss an alternative approach for a high throughput detection of rare mutations in large population samples using Ecotilling embedded in a collection of bioinformatic analysis tools. Ecotilling originally was introduced as TILLING for the screening for rare chemically induced mutations in plants and later adopted for human samples, showing an outstanding suitability for the detection of rare alleles in humans. An actual problem in the use of Ecotilling for large mutation screening projects in humans without bioinformatic support is represented by the lack of solutions to quickly yet comprehensively evaluate each newly found variation and place it into the correct genomic context.ResultsWe present an optimized strategy for the design, evaluation and interpretation of Ecotilling results by integrating several mostly freely available bioinformatic tools. A major focus of our investigations was the evaluation and meaningful economical combination of these software tools for the inference of different possible regulatory functions for each newly detected mutation.ConclusionOur streamlined procedure significantly facilitates the experimental design and evaluation of Ecotilling assays and strongly improves the decision process on prioritizing the newly found SNPs for further downstream analysis.
| S-EPMC2586031 | biostudies-literature
Project description:The majority of TP53 missense mutations identified in cancer patients are in the DNA-binding domain and are characterized as either structural or contact mutations. These missense mutations exhibit inhibitory effects on wild-type p53 activity. More importantly, these mutations also demonstrate gain-of-function (GOF) activities characterized by increased metastasis, poor prognosis, and drug resistance. To better understand the activities by which TP53 mutations, identified in Li-Fraumeni syndrome, contribute to tumorigenesis, we generated mice harboring a novel germline Trp53R245W allele (contact mutation) and compared them with existing models with Trp53R172H (structural mutation) and Trp53R270H (contact mutation) alleles. Thymocytes from heterozygous mice showed that all three hotspot mutations exhibited similar inhibitory effects on wild-type p53 transcription in vivo, and tumors from these mice had similar levels of loss of heterozygosity. However, the overall survival of Trp53R245W/+ and Trp53R270H/+ mice, but not Trp53R172H/+ mice, was significantly shorter than that of Trp53+/- mice, providing strong evidence for p53-mutant-specific GOF contributions to tumor development. Furthermore, Trp53R245W/+ and Trp53R270H/+ mice had more osteosarcoma metastases than Trp53R172H/+ mice, suggesting that these two contact mutants have stronger GOF in driving osteosarcoma metastasis. Transcriptomic analyses using RNA sequencing data from Trp53R172H/+, Trp53R245W/+, and Trp53R270H/+ primary osteosarcomas in comparison with Trp53+/- indicated that GOF of the three mutants was mediated by distinct pathways. Thus, both the inhibitory effect of mutant over wild-type p53 and GOF activities of mutant p53 contributed to tumorigenesis in vivo. Targeting p53 mutant-specific pathways may be important for therapeutic outcomes in osteosarcoma.Significancep53 hotspot mutants inhibit wild-type p53 similarly but differ in their GOF activities, with stronger tumor-promoting activity in contact mutants and distinct protein partners of each mutant driving tumorigenesis and metastasis.
| S-EPMC9117479 | biostudies-literature
Project description:TODO: STUDY ABSTRACT AS IT COULD APPEAR IN A
PUBLICATION
| EGAS00001002463 | EGA
Project description:BackgroundStrongyloidiasis is caused by a neglected nematode, manifesting as chronic intestinal infection with potentially severe manifestations. The disease is an emerging problem in non-endemic countries affecting travelers and migrants. Diagnosis of strongyloidiasis is hampered by the lack of standardization and absence of a gold standard. Since adequate direct methods to detect the motile larvae in stool samples are not widely available, other techniques such as serology have been developed.MethodsWe evaluated three commercial ELISA kits (DRG Instruments, IVD Research, and Bordier Affinity Products) to detect IgG antibodies against Strongyloides stercoralis assays utilizing serum samples from travelers with microscopically confirmed strongyloidiasis (n = 50) and other imported helminthic infections (n = 159) as well as healthy controls (n = 50).ResultsThe DRG, IVD, and Bordier assays showed sensitivities of 58.0%, 64.0%, and 56.0%, respectively. Specificity values were 96.0%, 96.0%, and 92.0% in healthy controls, and 67.3%, 62.9%, and 76.7% in cases with other helminth infections, respectively. Cross-reactions were mostly observed in cases with other nematodes (37.5%, 42.5%, and 20.0%, respectively), but also in trematode (33.3%, 38.1%, and 19.0%, respectively) and in cestode infections (25.0%, 30.0%, and 32.5%, respectively).ConclusionThe study demonstrates the diagnostic limitations of serological assays to detect or exclude cases of strongyloidiasis in returning travelers, who frequently present with recent or acute infections.
| S-EPMC11253981 | biostudies-literature
Project description:Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clinical potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Experimentally measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of molecular and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clinical knowledge for the development of "lookup tables" of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis.
| S-EPMC5590843 | biostudies-literature
Project description:BackgroundOne of the most commonly used molecular test for malaria diagnosis is the polymerase chain reaction (PCR)-based amplification of the 18S ribosomal DNA (rDNA) gene. Published diagnostic assays based on the 18S gene include the "gold standard" nested assay, semi-nested multiplex assay, and one tube multiplex assay. To our knowledge, no one has reported whether the two multiplex methods are better at detecting mixed Plasmodium infections compared to the nested assay using known quantities of DNA in experimentally mixed cocktails.FindingsHere we evaluated three PCR assays (nested, semi-nested multiplex, and one-tube multiplex) for the simultaneous detection of human malaria parasites using experimentally mixed cocktails of known quantities of laboratory derived DNA. All three assays detected individual species with high sensitivity and specificity when DNA was from any one single species; however, experimentally mixed DNA cocktails with all four species present were correctly identified most consistently with the nested method. The other two methods failed to consistently identify all four species correctly, especially at lower concentrations of DNA -subclinical levels of malaria (DNA equivalent to or less than 10 parasites per microliter).ConclusionsThe nested PCR method remains the method of choice for the detection of mixed malaria infections and especially of sub-clinical infections. Further optimization and/or new molecular gene targets may improve the success rate of detecting multiple parasite species simultaneously using traditional PCR assays.
| S-EPMC2853551 | biostudies-literature
Project description:Compounds that exhibit assay interference or undesirable mechanisms of bioactivity ("nuisance compounds") are routinely encountered in cellular assays, including phenotypic and high-content screening assays. Much is known regarding compound-dependent assay interferences in cell-free assays. However, despite the essential role of cellular assays in chemical biology and drug discovery, there is considerably less known about nuisance compounds in more complex cell-based assays. In our view, a major obstacle to realizing the full potential of chemical biology will not just be difficult-to-drug targets or even the sheer number of targets, but rather nuisance compounds, due to their ability to waste significant resources and erode scientific trust. In this review, we summarize our collective academic, government, and industry experiences regarding cellular nuisance compounds. We describe assay design strategies to mitigate the impact of nuisance compounds and suggest best practices to efficiently address these compounds in complex biological settings.
| S-EPMC7979533 | biostudies-literature