Molecular Dynamics of "Fuzzy" Transcriptional Activator-Coactivator Interactions.

Transcriptional activation domains (ADs) are generally thought to be intrinsically unstructured, but capable of adopting limited secondary structure upon interaction with a coactivator surface. The indeterminate nature of this interface made it hitherto difficult to study structure/function relationships of such contacts. Here we used atomistic accelerated molecular dynamics (aMD) simulations to study the conformational changes of the GCN4 AD and variants thereof, either free in solution, or bound to the GAL11 coactivator surface. We show that the AD-coactivator interactions are highly dynamic while obeying distinct rules. The data provide insights into the constant and variable aspects of orientation of ADs relative to the coactivator, changes in secondary structure and energetic contributions stabilizing the various conformers at different time points. We also demonstrate that a prediction of α-helical propensity correlates directly with the experimentally measured transactivation potential of a large set of mutagenized ADs. The link between α-helical propensity and the stimulatory activity of ADs has fundamental practical and theoretical implications concerning the recruitment of ADs to coactivators.

Alkylamine-tethered molecules recruit FBXO22 for targeted protein degradation.

Targeted protein degradation (TPD) relies on small molecules to recruit proteins to E3 ligases to induce their ubiquitylation and degradation by the proteasome. Only a few of the approximately 600 human E3 ligases are currently amenable to this strategy. This limits the actionable target space and clinical opportunities and thus establishes the necessity to expand to additional ligases. Here we identify and characterize SP3N, a specific degrader of the prolyl isomerase FKBP12. SP3N features a minimal design, where a known FKBP12 ligand is appended with a flexible alkylamine tail that conveys degradation properties. We found that SP3N is a precursor and that the alkylamine is metabolized to an active aldehyde species that recruits the SCFFBXO22 ligase for FKBP12 degradation. Target engagement occurs via covalent adduction of Cys326 in the FBXO22 C-terminal domain, which is critical for ternary complex formation, ubiquitylation and degradation. This mechanism is conserved for two recently reported alkylamine-based degraders of NSD2 and XIAP, thus establishing alkylamine tethering and covalent hijacking of FBXO22 as a generalizable TPD strategy.

Monovalent Pseudo-Natural Product Degraders Supercharge the Native Degradation of IDO1 by KLHDC3.

Targeted protein degradation (TPD) modulates protein function beyond inhibition of enzyme activity or protein-protein interactions. Most degraders function by proximity induction, and directly bridge an E3 ligase with the target to be degraded. However, many proteins might not be addressable via proximity-based degraders, and other challenges, such as resistance acquisition, exist. Here, we identified pseudo-natural products derived from (-)-myrtanol, termed iDegs, that inhibit and induce degradation of the immunomodulatory enzyme indoleamine-2,3-dioxygenase 1 (IDO1) by a distinct mechanism. iDegs induce a unique conformational change and, thereby, boost IDO1 ubiquitination and degradation by the cullin-RING E3 ligase CRL2KLHDC3, which we identified to also mediate native IDO1 degradation. Therefore, iDegs supercharge the native proteolytic pathway of IDO1, rendering this mechanism of action distinct from traditional degrader approaches involving proteolysis-targeting chimeras (PROTACs) or molecular-glue degraders (MGDs). In contrast to clinically explored IDO1 inhibitors, iDegs reduce formation of kynurenine by both inhibition and induced degradation of the enzyme and should also modulate non-enzymatic functions of IDO1. This unique mechanism of action may open up new therapeutic opportunities for the treatment of cancer beyond classical inhibition of IDO1.

Discovery of Molecular Glue Degraders via Isogenic Morphological Profiling.

Molecular glue degraders (MGDs) are small molecules that degrade proteins of interest via the ubiquitin-proteasome system. While MGDs were historically discovered serendipitously, approaches for MGD discovery now include cell-viability-based drug screens or data mining of public transcriptomics and drug response datasets. These approaches, however, have target spaces restricted to the essential proteins. Here we develop a high-throughput workflow for MGD discovery that also reaches the nonessential proteome. This workflow begins with the rapid synthesis of a compound library by sulfur(VI) fluoride exchange chemistry coupled to a morphological profiling assay in isogenic cell lines that vary in levels of the E3 ligase CRBN. By comparing the morphological changes induced by compound treatment across the isogenic cell lines, we were able to identify FL2-14 as a CRBN-dependent MGD targeting the nonessential protein GSPT2. We envision that this workflow would contribute to the discovery and characterization of MGDs that target a wider range of proteins.

Identification and selectivity profiling of small-molecule degraders via multi-omics approaches.

The therapeutic modality of targeted protein degradation promises to overcome limitations of traditional pharmacology. Small-molecule degraders recruit disease-causing proteins to E3 ubiquitin ligases, prompting their ubiquitination and degradation by the proteasome. The discovery, mechanistic elucidation, and selectivity profiling of novel degraders are often conducted in cellular systems. This highlights the need for unbiased multi-omics strategies that inform on the functionally involved components. Here, we review how proteomics and functional genomics can be integrated to identify and mechanistically understand degraders, their target selectivity as well as putative resistance mechanisms.

A Comprehensive Network Atlas Reveals That Turing Patterns Are Common but Not Robust.

Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to distill design rules. We exhaustively analyze 2- and 3-node biological candidate Turing systems, amounting to 7,625 networks and more than 3 × 1011 analyzed scenarios. We find that network structure alone neither implies nor guarantees emergent TPs. A large fraction (>61%) of network design space can produce TPs, but these are sensitive to even subtle changes in parameters, network structure, and regulatory mechanisms. This implies that TP networks are more common than previously thought, and evolution might regularly encounter prototypic solutions. We deduce compositional rules for TP systems that are almost necessary and sufficient (96% of TP networks contain them, and 92% of networks implementing them produce TPs). This comprehensive network atlas provides the blueprints for identifying natural TPs and for engineering synthetic systems.

A three-step framework for programming pattern formation.

The spatial organisation of gene expression is essential to create structure and function in multicellular organisms during developmental processes. Such organisation occurs by the execution of algorithmic functions, leading to patterns within a given domain, such as a tissue. Engineering these processes has become increasingly important because bioengineers are seeking to develop tissues ex vivo. Moreover, although there are several theories on how pattern formation can occur in vivo, the biological relevance and biotechnological potential of each of these remains unclear. In this review, we will briefly explain four of the major theories of pattern formation in the light of recent work. We will explore why programming of such patterns is necessary, while discussing a three-step framework for artificial engineering approaches.