Genome-wide CRISPR screens identify novel regulators of wild-type and mutant p53 stability.

Tumor suppressor p53 (TP53) is frequently mutated in cancer, often resulting not only in loss of its tumor-suppressive function but also acquisition of dominant-negative and even oncogenic gain-of-function traits. While wild-type p53 levels are tightly regulated, mutants are typically stabilized in tumors, which is crucial for their oncogenic properties. Here, we systematically profiled the factors that regulate protein stability of wild-type and mutant p53 using marker-based genome-wide CRISPR screens. Most regulators of wild-type p53 also regulate p53 mutants, except for p53 R337H regulators, which are largely private to this mutant. Mechanistically, FBXO42 emerged as a positive regulator for a subset of p53 mutants, working with CCDC6 to control USP28-mediated mutant p53 stabilization. Additionally, C16orf72/HAPSTR1 negatively regulates both wild-type p53 and all tested mutants. C16orf72/HAPSTR1 is commonly amplified in breast cancer, and its overexpression reduces p53 levels in mouse mammary epithelium leading to accelerated breast cancer. This study offers a network perspective on p53 stability regulation, potentially guiding strategies to reinforce wild-type p53 or target mutant p53 in cancer.

Evolution of SLiM-mediated hijack functions in intrinsically disordered viral proteins.

Viruses and their hosts are involved in an 'arms race' where they continually evolve mechanisms to overcome each other. It has long been proposed that intrinsic disorder provides a substrate for the evolution of viral hijack functions and that short linear motifs (SLiMs) are important players in this process. Here, we review evidence in support of this tenet from two model systems: the papillomavirus E7 protein and the adenovirus E1A protein. Phylogenetic reconstructions reveal that SLiMs appear and disappear multiple times across evolution, providing evidence of convergent evolution within individual viral phylogenies. Multiple functionally related SLiMs show strong coevolution signals that persist across long distances in the primary sequence and occur in unrelated viral proteins. Moreover, changes in SLiMs are associated with changes in phenotypic traits such as host range and tropism. Tracking viral evolutionary events reveals that host switch events are associated with the loss of several SLiMs, suggesting that SLiMs are under functional selection and that changes in SLiMs support viral adaptation. Fine-tuning of viral SLiM sequences can improve affinity, allowing them to outcompete host counterparts. However, viral SLiMs are not always competitive by themselves, and tethering of two suboptimal SLiMs by a disordered linker may instead enable viral hijack. Coevolution between the SLiMs and the linker indicates that the evolution of disordered regions may be more constrained than previously thought. In summary, experimental and computational studies support a role for SLiMs and intrinsic disorder in viral hijack functions and in viral adaptive evolution.

Predicting the effect of disordered linkers on effective concentrations and avidity with the "Ceff calculator" app.

Linkers are crucial to the functions of multidomain proteins as they couple functional units to encode regulation such as auto-inhibition, enzyme targeting or tuning of interaction strength. A linker changes reactions from bimolecular to unimolecular, and the equilibrium and kinetics is thus determined by the properties of the linker rather than concentrations. We present a theoretical workflow for estimating the functional consequences of tethering by a linker. We discuss how to: (1) Identify flexible linkers from sequence. (2) Model the end-to-end distance distribution for a flexible linker using a worm-like chain. (3) Estimate the effective concentration of a ligand tethered by a flexible linker. (4) Calculate the decrease in binding affinity caused by auto-inhibition. (5) Calculate the expected avidity enhancement of a bivalent interaction from effective concentration. The worm-like chain modeling is available through a web application called the "Ceff calculator" (http://ceffapp.chemeslab.org), which will allow user-friendly prediction of experimentally inaccessible parameters.

Intrinsically Disordered Linkers Impart Processivity on Enzymes by Spatial Confinement of Binding Domains.

(1) Background: Processivity is common among enzymes and mechanochemical motors that synthesize, degrade, modify or move along polymeric substrates, such as DNA, RNA, polysaccharides or proteins. Processive enzymes can make multiple rounds of modification without releasing the substrate/partner, making their operation extremely effective and economical. The molecular mechanism of processivity is rather well understood in cases when the enzyme structurally confines the substrate, such as the DNA replication factor PCNA, and also when ATP energy is used to confine the succession of molecular events, such as with mechanochemical motors. Processivity may also result from the kinetic bias of binding imposed by spatial confinement of two binding elements connected by an intrinsically disordered (ID) linker. (2) Method: By statistical physical modeling, we show that this arrangement results in processive systems, in which the linker ensures an optimized effective concentration around novel binding site(s), favoring rebinding over full release of the polymeric partner. (3) Results: By analyzing 12 such proteins, such as cellulase, and RNAse-H, we illustrate that in these proteins linker length and flexibility, and the kinetic parameters of binding elements, are fine-tuned for optimizing processivity. We also report a conservation of structural disorder, special amino acid composition of linkers, and the correlation of their length with step size. (4) Conclusion: These observations suggest a unique type of entropic chain function of ID proteins, that may impart functional advantages on diverse enzymes in a variety of biological contexts.

Convergent evolution and mimicry of protein linear motifs in host-pathogen interactions.

Pathogen linear motif mimics are highly evolvable elements that facilitate rewiring of host protein interaction networks. Host linear motifs and pathogen mimics differ in sequence, leading to thermodynamic and structural differences in the resulting protein-protein interactions. Moreover, the functional output of a mimic depends on the motif and domain repertoire of the pathogen protein. Regulatory evolution mediated by linear motifs can be understood by measuring evolutionary rates, quantifying positive and negative selection and performing phylogenetic reconstructions of linear motif natural history. Convergent evolution of linear motif mimics is widespread among unrelated proteins from viral, prokaryotic and eukaryotic pathogens and can also take place within individual protein phylogenies. Statistics, biochemistry and laboratory models of infection link pathogen linear motifs to phenotypic traits such as tropism, virulence and oncogenicity. In vitro evolution experiments and analysis of natural sequences suggest that changes in linear motif composition underlie pathogen adaptation to a changing environment.