All-codon scanning identifies p53 cancer rescue mutations

Pyrimidine Triones as Potential Activators of p53 Mutants

p53 is a crucial tumor suppressor in vertebrates that is frequently mutated in human cancers. Most mutations are missense mutations that render p53 inactive in suppressing tumor initiation and progression. Developing small-molecule drugs to convert mutant p53 into an active, wild-type-like conformation is a significant focus for personalized cancer therapy. Prior research indicates that reactivating p53 suppresses cancer cell proliferation and tumor growth in animal models. Early clinical evidence with a compound selectively targeting p53 mutants with substitutions of tyrosine 220 suggests potential therapeutic benefits of reactivating p53 in patients. This study identifies and examines the UCI-1001 compound series as a potential corrector for several p53 mutations. The findings indicate that UCI-1001 treatment in p53 mutant cancer cell lines inhibits growth and reinstates wild-type p53 activities, including DNA binding, target gene activation, and induction of cell death. Cellular thermal shift assays, conformation-specific immunofluorescence staining, and differential scanning fluorometry suggest that UCI-1001 interacts with and alters the conformation of mutant p53 in cancer cells. These initial results identify pyrimidine trione derivatives of the UCI-1001 series as candidates for p53 corrector drug development.

Small-molecule correctors and stabilizers to target p53

The tumor suppressor p53 is the most frequently mutated protein in human cancer and tops the list of high-value precision oncology targets. p53 prevents initiation and progression of cancer by inducing cell-cycle arrest and various forms of cell death. Tumors have thus evolved ways to inactivate p53, mainly by TP53 mutations or by hyperactive p53 degradation. This review focuses on two types of p53 targeting compounds, MDM2 antagonists and mutant p53 correctors. MDM2 inhibitors prevent p53 protein degradation, while correctors restore tumor suppressor activity of p53 mutants by enhancing thermodynamic stability. Herein we explore both novel and repurposed p53 targeting compounds, discuss their mode of action, and examine the challenges in advancing them to the clinic.

High-throughput saturation mutagenesis generates a high-affinity antibody against SARS-CoV-2 variants using protein surface display assay on a human cell

As new mutations continue to emerge, the ability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus to evade the human immune system and neutralizing antibodies remains a huge challenge for vaccine development and antibody research. The majority of neutralizing antibodies have reduced or lost activity against SARS-CoV-2 variants. In this study, we reported a novel protein surface display system on a mammalian cell for obtaining a higher-affinity antibody in high-throughput manner. Using a saturation mutagenesis strategy through integrating microarray-based oligonucleotide synthesis and single-cell screening assay, we generated a group of new antibodies against diverse prevalent SARS-CoV-2 variants through high-throughput screening the human antibody REGN10987 within 2 weeks. The affinity of those optimized antibodies to seven prevalent mutants was greatly improved, and the EC50 values were no higher than 5 ng/mL. These results demonstrate the robustness of our screening system in the rapid generation of an antibody with higher affinity against a new SARS-CoV-2 variant, and provides a potential application to other protein molecular interactions.

ACE2 decoy receptor generated by high-throughput saturation mutagenesis efficiently neutralizes SARS-CoV-2 and its prevalent variants

The recent global pandemic was a spillover from the SARS-CoV-2 virus. Viral entry involves the receptor binding domain (RBD) of the viral spike protein interacting with the protease domain (PD) of the cellular receptor, ACE2. We hereby present a comprehensive mutational landscape of the effects of ACE2-PD point mutations on RBD-ACE2 binding using a saturation mutagenesis approach based on microarray-based oligo synthesis and a single-cell screening assay. We observed that changes in glycosylation sites and directly interacting sites of ACE2-PD significantly influenced ACE2-RBD binding. We further engineered an ACE2 decoy receptor with critical point mutations, D30I, L79W, T92N, N322V, and K475F, named C4-1. C4-1 shows a 200-fold increase in neutralization for the SARS-CoV-2 D614G pseudotyped virus compared to wild-type soluble ACE2 and a sevenfold increase in binding affinity to wild-type spike compared to the C-terminal Ig-Fc fused wild-type soluble ACE2. Moreover, C4-1 efficiently neutralized prevalent variants, especially the omicron variant (EC50=16 ng/mL), and rescued monoclonal antibodies, vaccine, and convalescent sera neutralization from viral immune-escaping. We hope to next investigate translating the therapeutic potential of C4-1 for the treatment of SARS-CoV-2.

Discovery of compounds that reactivate p53 mutants in vitro and in vivo

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.

Targeting mutant p53 for efficient cancer therapy

The tumour suppressor gene TP53 is the most frequently mutated gene in cancer. Wild-type p53 can suppress tumour development by multiple pathways. However, mutation of TP53 and the resultant inactivation of p53 allow evasion of tumour cell death and rapid tumour progression. The high frequency of TP53 mutation in tumours has prompted efforts to restore normal function of mutant p53 and thereby trigger tumour cell death and tumour elimination. Small molecules that can reactivate missense-mutant p53 protein have been identified by different strategies, and two compounds are being tested in clinical trials. Novel approaches for targeting TP53 nonsense mutations are also underway. This Review discusses recent progress in pharmacological reactivation of mutant p53 and highlights problems and promises with these strategies.

In silico identification of rescue sites by double force scanning

Motivation

A deleterious amino acid change in a protein can be compensated by a second-site rescue mutation. These compensatory mechanisms can be mimicked by drugs. In particular, the location of rescue mutations can be used to identify protein regions that can be targeted by small molecules to reactivate a damaged mutant.

Results

We present the first general computational method to detect rescue sites. By mimicking the effect of mutations through the application of forces, the double force scanning (DFS) method identifies the second-site residues that make the protein structure most resilient to the effect of pathogenic mutations. We tested DFS predictions against two datasets containing experimentally validated and putative evolutionary-related rescue sites. A remarkably good agreement was found between predictions and experimental data. Indeed, almost half of the rescue sites in p53 was correctly predicted by DFS, with 65% of remaining sites in contact with DFS predictions. Similar results were found for other proteins in the evolutionary dataset.

Availability and implementation

The DFS code is available under GPL at https://fornililab.github.io/dfs/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Directed Evolution of Proteins Based on Mutational Scanning

Directed evolution has emerged as one of the most effective protein engineering methods in basic research as well as in applications in synthetic organic chemistry and biotechnology. The successful engineering of protein activity, allostery, binding affinity, expression, folding, fluorescence, solubility, substrate scope, selectivity (enantio-, stereo-, and regioselectivity), and/or stability (temperature, organic solvents, pH) is just limited by the throughput of the genetic selection, display, or screening system that is available for a given protein. Sometimes it is possible to analyze millions of protein variants from combinatorial libraries per day. In other cases, however, only a few hundred variants can be screened in a single day, and thus the creation of smaller yet smarter libraries is needed. Different strategies have been developed to create these libraries. One approach is to perform mutational scanning or to construct "mutability landscapes" in order to understand sequence-function relationships that can guide the actual directed evolution process. Herein we provide a protocol for economically constructing scanning mutagenesis libraries using a cytochrome P450 enzyme in a high-throughput manner. The goal is to engineer activity, regioselectivity, and stereoselectivity in the oxidative hydroxylation of a steroid, a challenging reaction in synthetic organic chemistry. Libraries based on mutability landscapes can be used to engineer any fitness trait of interest. The protocol is also useful for constructing gene libraries for deep mutational scanning experiments.

Compensated pathogenic deviations

Deleterious or 'disease-associated' mutations are mutations that lead to disease with high phenotype penetrance: they are inherited in a simple Mendelian manner, or, in the case of cancer, accumulate in somatic cells leading directly to disease. However, in some cases, the amino acid that is substituted resulting in disease is the wild-type native residue in the functionally equivalent protein in another species. Such examples are known as 'compensated pathogenic deviations' (CPDs) because, somewhere in the second species, there must be compensatory mutations that allow the protein to function normally despite having a residue which would cause disease in the first species. Depending on the nature of the mutations, compensation can occur in the same protein, or in a different protein with which it interacts. In principle, compensation can be achieved by a single mutation (most probably structurally close to the CPD), or by the cumulative effect of several mutations. Although it is clear that these effects occur in proteins, compensatory mutations are also important in RNA potentially having an impact on disease. As a much simpler molecule, RNA provides an interesting model for understanding mechanisms of compensatory effects, both by looking at naturally occurring RNA molecules and as a means of computational simulation. This review surveys the rather limited literature that has explored these effects. Understanding the nature of CPDs is important in understanding traversal along fitness landscape valleys in evolution. It could also have applications in treating diseases that result from such mutations.

Economical analysis of saturation mutagenesis experiments

Saturation mutagenesis is a powerful technique for engineering proteins, metabolic pathways and genomes. In spite of its numerous applications, creating high-quality saturation mutagenesis libraries remains a challenge, as various experimental parameters influence in a complex manner the resulting diversity. We explore from the economical perspective various aspects of saturation mutagenesis library preparation: We introduce a cheaper and faster control for assessing library quality based on liquid media; analyze the role of primer purity and supplier in libraries with and without redundancy; compare library quality, yield, randomization efficiency, and annealing bias using traditional and emergent randomization schemes based on mixtures of mutagenic primers; and establish a methodology for choosing the most cost-effective randomization scheme given the screening costs and other experimental parameters. We show that by carefully considering these parameters, laboratory expenses can be significantly reduced.

CHOPER filters enable rare mutation detection in complex mutagenesis populations by next-generation sequencing

Next-generation sequencing (NGS) has revolutionized genetics and enabled the accurate identification of many genetic variants across many genomes. However, detection of biologically important low-frequency variants within genetically heterogeneous populations remains challenging, because they are difficult to distinguish from intrinsic NGS sequencing error rates. Approaches to overcome these limitations are essential to detect rare mutations in large cohorts, virus or microbial populations, mitochondria heteroplasmy, and other heterogeneous mixtures such as tumors. Modifications in library preparation can overcome some of these limitations, but are experimentally challenging and restricted to skilled biologists. This paper describes a novel quality filtering and base pruning pipeline, called Complex Heterogeneous Overlapped Paired-End Reads (CHOPER), designed to detect sequence variants in a complex population with high sequence similarity derived from All-Codon-Scanning (ACS) mutagenesis. A novel fast alignment algorithm, designed for the specified application, has O(n) time complexity. CHOPER was applied to a p53 cancer mutant reactivation study derived from ACS mutagenesis. Relative to error filtering based on Phred quality scores, CHOPER improved accuracy by about 13% while discarding only half as many bases. These results are a step toward extending the power of NGS to the analysis of genetically heterogeneous populations.

Contemporary, yeast-based approaches to understanding human genetic variation

Determining how genetic variation contributes to human health and disease is a critical challenge. As one of the most genetically tractable model organisms, yeast has played a central role in meeting this challenge. The advent of new technologies, including high-throughput DNA sequencing and synthesis, proteomics, and computational methods, has vastly increased the power of yeast-based approaches to determine the consequences of human genetic variation. Recent successes include systematic exploration of the effects of gene dosage, large-scale analysis of the effect of coding variation on gene function, and the use of humanized yeast to model disease. By virtue of its manipulability, small genome size, and genetic tractability, yeast is poised to help us understand human genetic variation.

Computational identification of a transiently open L1/S3 pocket for reactivation of mutant p53

The tumour suppressor p53 is the most frequently mutated gene in human cancer. Reactivation of mutant p53 by small molecules is an exciting potential cancer therapy. Although several compounds restore wild-type function to mutant p53, their binding sites and mechanisms of action are elusive. Here computational methods identify a transiently open binding pocket between loop L1 and sheet S3 of the p53 core domain. Mutation of residue Cys124, located at the centre of the pocket, abolishes p53 reactivation of mutant R175H by PRIMA-1, a known reactivation compound. Ensemble-based virtual screening against this newly revealed pocket selects stictic acid as a potential p53 reactivation compound. In human osteosarcoma cells, stictic acid exhibits dose-dependent reactivation of p21 expression for mutant R175H more strongly than does PRIMA-1. These results indicate the L1/S3 pocket as a target for pharmaceutical reactivation of p53 mutants.

About 40% of human cancers carry missense mutations in the tumour suppressor protein p53. Here the authors identify a transiently open pocket in the protein, and by targeting a small molecule to it, partially restore mutant p53 tumour suppressor activity.

Directed DNA shuffling of retrovirus and retrotransposon integrase protein domains

Chimeric proteins are used to study protein domain functions and to recombine protein domains for novel or optimal functions. We used a library of chimeric integrase proteins to study DNA integration specificity. The library was constructed using a directed shuffling method that we adapted from fusion PCR. This method easily and accurately shuffles multiple DNA gene sequences simultaneously at specific base-pair positions, such as protein domain boundaries. It produced all 27 properly-ordered combinations of the amino-terminal, catalytic core, and carboxyl-terminal domains of the integrase gene from human immunodeficiency virus, prototype foamy virus, and Saccharomyces cerevisiae retrotransposon Ty3. Retrotransposons can display dramatic position-specific integration specificity compared to retroviruses. The yeast retrotransposon Ty3 integrase interacts with RNA polymerase III transcription factors to target integration at the transcription initiation site. In vitro assays of the native and chimeric proteins showed that human immunodeficiency virus integrase was active with heterologous substrates, whereas prototype foamy virus and Ty3 integrases were not. This observation was consistent with a lower substrate specificity for human immunodeficiency virus integrase than for other retrovirus integrases. All eight chimeras containing the Ty3 integrase carboxyl-terminal domain, a candidate targeting domain, failed to target strand transfer in the presence of the targeting protein, suggesting that multiple domains of the Ty3 integrase cooperate in this function.

Molecular modelling and simulations in cancer research

The complexity of cancer and the vast amount of experimental data available have made computer-aided approaches necessary. Biomolecular modelling techniques are becoming increasingly easier to use, whereas hardware and software are becoming better and cheaper. Cross-talk between theoretical and experimental scientists dealing with cancer-research from a molecular approach, however, is still uncommon. This is in contrast to other fields, such as amyloid-related diseases, where molecular modelling studies are widely acknowledged. The aim of this review paper is therefore to expose some of the more common approaches in molecular modelling to cancer scientists in simple terms, illustrating success stories while also revealing the limitations of computational studies at the molecular level.

Microbial synthetic biology for human therapeutics

The emerging field of synthetic biology holds tremendous potential for developing novel drugs to treat various human conditions. The current study discusses the scope of synthetic biology for human therapeutics via microbial approach. In this context, synthetic biology aims at designing, engineering and building new microbial synthetic cells that do not pre-exist in nature as well as re-engineer existing microbes for synthesis of therapeutic products. It is expected that the construction of novel microbial genetic circuitry for human therapeutics will greatly benefit from the data generated by 'omics' approaches and multidisciplinary nature of synthetic biology. Development of novel antimicrobial drugs and vaccines by engineering microbial systems are a promising area of research in the field of synthetic biology for human theragnostics. Expression of plant based medicinal compounds in the microbial system using synthetic biology tools is another avenue dealt in the present study. Additionally, the study suggest that the traditional medicinal knowledge can do value addition for developing novel drugs in the microbial systems using synthetic biology tools. The presented work envisions the success of synthetic biology for human therapeutics via microbial approach in a holistic manner. Keeping this in view, various legal and socio-ethical concerns emerging from the use of synthetic biology via microbial approach such as patenting, biosafety and biosecurity issues have been touched upon in the later sections.

Ensemble-based computational approach discriminates functional activity of p53 cancer and rescue mutants

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 (r² = 0.77) with reported values of experimentally measured ΔΔG 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.

p53 is a tumor suppressor protein that controls a central apoptotic pathway (programmed cell death). Thus, it is the most-mutated gene in human cancers. Due to the marginal stability of p53, a single mutation can abolish p53 function (“cancer mutants”), while a second mutation (or several) can restore it (“rescue mutants”). Restoring p53 function is a promising therapeutic goal that has been strongly supported by recent experimental results on mice. Understanding of the effects of p53 cancer and rescue mutations would be helpful for designing drugs that are able to achieve the same goal. The challenge is that cancer and rescue mutations are distributed widely in the protein, and experimental testing of all possible combinations of mutations is not feasible. This paper describes a simple computational metric that reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants.