RNA Polymerase Tags To Monitor Multidimensional Protein-Protein Interactions Reveal Pharmacological Engagement of Bcl-2 Proteins

Screening for molecular glues - Challenges and opportunities

Molecular glues are small molecules, typically smaller than PROTACs, and usually with improved physicochemical properties that aim to stabilise the interaction between two proteins. Most often this approach is used to improve or induce an interaction between the target and an E3 ligase, but other interactions which stabilise interactions to increase activity or to inhibit binding to a natural effector have also been demonstrated. This review will describe the effects of induced proximity, discuss current methods used to identify molecular glues and introduce approaches that could be adapted for molecular glue screening.

Target-dependent RNA polymerase as universal platform for gene expression control in response to intracellular molecules

Controlling gene expression in response to specific molecules is an essential technique for regulating cellular functions. However, current platforms with transcription and translation regulators have a limited number of detectable molecules to induce gene expression. Here to address these issues, we present a Target-dependent RNA polymerase (TdRNAP) that can induce RNA transcription in response to the intracellular target specifically recognized by single antibody. By substituting the fused antibody, we demonstrate that TdRNAPs respond to a wide variety of molecules, including peptides, proteins, RNA, and small molecules, and produce desired transcripts in human cells. Furthermore, we show that multiple TdRNAPs can construct orthogonal and multilayer genetic circuits. Finally, we apply TdRNAP to achieve cell-specific genome editing that is autonomously triggered by detecting the target gene product. TdRNAP can expand the molecular variety for controlling gene expression and provide the genetic toolbox for bioengineering and future therapeutic applications.

Innate Conformational Dynamics Drive Binding Specificity in Anti-Apoptotic Proteins Mcl-1 and Bcl-2

The structurally conserved B-cell lymphoma 2 (Bcl-2) family of protein function to promote or inhibit apoptosis through an exceedingly complex web of specific, intrafamilial protein-protein interactions. The critical role of these proteins in lymphomas and other cancers has motivated a widespread interest in understanding the molecular mechanisms that drive specificity in Bcl-2 family interactions. However, the high degree of structural similarity among Bcl-2 homologues has made it difficult to rationalize the highly specific (and often divergent) binding behavior exhibited by these proteins using conventional structural arguments. In this work, we use time-resolved hydrogen deuterium exchange mass spectrometry to explore shifts in conformational dynamics associated with binding partner engagement in the Bcl-2 family proteins Bcl-2 and Mcl-1. Using this approach combined with homology modeling, we reveal that Mcl-1 binding is driven by a large-scale shift in conformational dynamics, while Bcl-2 complexation occurs primarily through a classical charge compensation mechanism. This work has implications for understanding the evolution of internally regulated biological systems composed of structurally similar proteins and for the development of drugs targeting Bcl-2 family proteins for promotion of apoptosis in cancer.

A System for the Evolution of Protein-Protein Interaction Inducers

Molecules that induce interactions between proteins, often referred to as "molecular glues", are increasingly recognized as important therapeutic modalities and as entry points for rewiring cellular signaling networks. Here, we report a new PACE-based method to rapidly select and evolve molecules that mediate interactions between otherwise noninteracting proteins: rapid evolution of protein-protein interaction glues (rePPI-G). By leveraging proximity-dependent split RNA polymerase-based biosensors, we developed E. coli-based detection and selection systems that drive gene expression outputs only when interactions between target proteins are induced. We then validated the system using engineered bivalent molecular glues, showing that rePPI-G robustly selects for molecules that induce the target interaction. Proof-of-concept evolutions demonstrated that rePPI-G reduces the "hook effect" of the engineered molecular glues, due at least in part to tuning the interaction affinities of each individual component of the bifunctional molecule. Altogether, this work validates rePPI-G as a continuous, phage-based evolutionary technology for optimizing molecular glues, providing a strategy for developing molecules that reprogram protein-protein interactions.

Contingency and chance erase necessity in the experimental evolution of ancestral proteins

The roles of chance, contingency, and necessity in evolution are unresolved because they have never been assessed in a single system or on timescales relevant to historical evolution. We combined ancestral protein reconstruction and a new continuous evolution technology to mutate and select proteins in the B-cell lymphoma-2 (BCL-2) family to acquire protein–protein interaction specificities that occurred during animal evolution. By replicating evolutionary trajectories from multiple ancestral proteins, we found that contingency generated over long historical timescales steadily erased necessity and overwhelmed chance as the primary cause of acquired sequence variation; trajectories launched from phylogenetically distant proteins yielded virtually no common mutations, even under strong and identical selection pressures. Chance arose because many sets of mutations could alter specificity at any timepoint; contingency arose because historical substitutions changed these sets. Our results suggest that patterns of variation in BCL-2 sequences – and likely other proteins, too – are idiosyncratic products of a particular and unpredictable course of historical events.

One of the most fundamental and unresolved questions in evolutionary biology is whether the outcomes of evolution are predictable. Is the diversity of life we see today the expected result of organisms adapting to their environment throughout history (also known as natural selection) or the product of random chance? Or did chance events early in history shape the paths that evolution could take next, determining the biological forms that emerged under natural selection much later?

These questions are hard to study because evolution happened only once, long ago. To overcome this barrier, Xie, Pu, Metzger et al. developed an experimental approach that can evolve reconstructed ancestral proteins that existed deep in the past. Using this method, it is possible to replay evolution multiple times, from various historical starting points, under conditions similar to those that existed long ago. The end products of the evolutionary trajectories can then be compared to determine how predictable evolution actually is.

Xie, Pu, Metzger et al. studied proteins belonging to the BCL-2 family, which originated some 800 million years ago. These proteins have diversified greatly over time in both their genetic sequences and their ability to bind to specific partner proteins called co-regulators. Xie, Pu, Metzger et al. synthesized BCL-2 proteins that existed at various times in the past. Each ancestral protein was then allowed to evolve repeatedly under natural selection to acquire the same co-regulator binding functions that evolved during history.

At the end of each evolutionary trajectory, the genetic sequence of the resulting BCL-2 proteins was recorded. This revealed that the outcomes of evolution were almost completely unpredictable: trajectories initiated from the same ancestral protein produced proteins with very different sequences, and proteins launched from different ancestral starting points were even more dissimilar.

Further experiments identified the mutations in each trajectory that caused changes in coregulator binding. When these mutations were introduced into other ancestral proteins, they did not yield the same change in function. This suggests that early chance events influenced each protein’s evolution in an unpredictable way by opening and closing the paths available to it in the future.

This research expands our understanding of evolution on a molecular level whilst providing a new experimental approach for studying evolutionary drivers in more detail. The results suggest that BCL-2 proteins, in all their various forms, are unique products of a particular, unpredictable course of history set in motion by ancient chance events.

Split T7 RNA polymerase biosensors to study multiprotein interaction dynamics

Protein-protein interactions (PPIs) are involved in nearly all cellular processes. PPIs are particularly crucial for mediating selectivity along signaling pathways. Thus, measuring the competitive interplay between PPIs in a cell is important for both understanding fundamental cellular regulation and developing therapeutics targeting those whose dysregulation is associated with disease. A variety of split protein reporter-based tools are available to measure if two proteins interact within a cell and thereby characterize the general determinants of their interactions. PPIs, however, occur within complex networks facilitated by dynamic biophysical nuances that determine activity and selectivity. Evolved, proximity-dependent split T7 RNA polymerase (RNAP) biosensors have recently been used to perform deep mutational scanning of PPI interfaces, and to create synthetic gene circuits. In this chapter, we present the application of proximity-dependent split RNAP biosensors as a method to measure multidimensional PPIs in live cells. Orthogonal split RNAP "tags" encode each interaction in a unique RNA signal, thereby enabling the study of multiple competitive PPIs in live cells. Each unique RNA signal can be quantified via established RNA analysis methods. Herein, we provide advice and protocols to aid other researchers in using the split RNAP biosensor, focusing primarily on how to detect multiple PPIs in mammalian cells, including their dynamic interplay in the presence of small molecule inhibitors.

Detecting Protein-Protein Interaction Based on Protein Fragment Complementation Assay

Proteins are the most critical executive molecules by responding to the instructions stored in the genetic materials in any form of life. More frequently, proteins do their jobs by acting as a roleplayer that interacts with other protein(s), which is more evident when the function of a protein is examined in the real context of a cell. Identifying the interactions between (or amongst) proteins is very crucial for the biochemistry investigation of an individual protein and for the attempts aiming to draw a holo-picture for the interacting members at the scale of proteomics (or protein-protein interactions mapping). Here, we introduced the currently available reporting systems that can be used to probe the interaction between candidate protein pairs based on the fragment complementation of some particular proteins. Emphasis was put on the principles and details of experimental design. These systems are dihydrofolate reductase (DHFR), β-lactamase, tobacco etch virus (TEV) protease, luciferase, β- galactosidase, GAL4, horseradish peroxidase (HRP), focal adhesion kinase (FAK), green fluorescent protein (GFP), and ubiquitin.

A Phage-Assisted Continuous Selection Approach for Deep Mutational Scanning of Protein-Protein Interactions

Protein-protein interactions (PPIs) are critical for organizing molecules in a cell and mediating signaling pathways. Dysregulation of PPIs is often a key driver of disease. To better understand the biophysical basis of such disease processes-and to potentially target them-it is critical to understand the molecular determinants of PPIs. Deep mutational scanning (DMS) facilitates the acquisition of large amounts of biochemical data by coupling selection with high throughput sequencing (HTS). The challenging and labor-intensive design and optimization of a relevant selection platform for DMS, however, limits the use of powerful directed evolution and selection approaches. To address this limitation, we designed a versatile new phage-assisted continuous selection (PACS) system using our previously reported proximity-dependent split RNA polymerase (RNAP) biosensors, with the aim of greatly simplifying and streamlining the design of a new selection platform for PPIs. After characterization and validation using the model KRAS/RAF PPI, we generated a library of RAF variants and subjected them to PACS and DMS. Our HTS data revealed positions along the binding interface that are both tolerant and intolerant to mutations, as well as which substitutions are tolerated at each position. Critically, the "functional scores" obtained from enrichment data through continuous selection for individual variants correlated with K_D values measured in vitro, indicating that biochemical data can be extrapolated from sequencing using our new system. Due to the plug and play nature of RNAP biosensors, this method can likely be extended to a variety of other PPIs. More broadly, this, and other methods under development support the continued development of evolutionary and high-throughput approaches to address biochemical problems, moving toward a more comprehensive understanding of sequence-function relationships in proteins.

Development of a Split Esterase for Protein-Protein Interaction-Dependent Small-Molecule Activation

Split reporters based on fluorescent proteins and luciferases have emerged as valuable tools for measuring interactions in biological systems. Relatedly, biosensors that transduce measured input signals into outputs that influence the host system are key components of engineered gene circuits for synthetic biology applications. While small-molecule-based imaging agents are widely used in biological studies, and small-molecule-based drugs and chemical probes can target a range of biological processes, a general method for generating a target small molecule in a biological system based on a measured input signal is lacking. Here, we develop a proximity-dependent split esterase that selectively unmasks ester-protected small molecules in an interaction-dependent manner. Exploiting the versatility of an ester-protected small-molecule output, we demonstrate fluorescent, chemiluminescent, and pharmacological probe generation, each created by masking key alcohol functional groups on a target small molecule. We show that the split esterase system can be used in combination with ester-masked fluorescent or luminescent probes to measure protein-protein interactions and protein-protein interaction inhibitor engagement. We demonstrate that the esterase-based reporter system is compatible with other commonly used split reporter imaging systems for the simultaneous detection of multiple protein-protein interactions. Finally, we develop a system for selective small-molecule-dependent cell killing by unmasking a cytotoxic molecule using an inducible split esterase. Presaging utility in future synthetic biology-based therapeutic applications, we also show that the system can be used for intercellular cell killing via a bystander effect, where one activated cell unmasks a cytotoxic molecule and kills cells physically adjacent to the activated cells. Collectively, this work illustrates that the split esterase system is a valuable new addition to the split protein toolbox, with particularly exciting potential in synthetic biology applications.

Evolution of C-Terminal Modification Tolerance in Full-Length and Split T7 RNA Polymerase Biosensors

T7 RNA polymerase (RNAP) is a powerful protein scaffold for the construction of synthetic biology tools and biosensors. However, both T7 RNAP and its split variants are intolerant to C-terminal modifications or fusions, thus placing a key limitation on their engineering and deployment. Here, we use rapid continuous-evolution approaches to evolve both full-length and split T7 RNAP variants that tolerate modified C termini and fusions to entire other proteins. Moreover, we show that the evolved split C-terminal RNAP variants can function as small-molecule biosensors, even in the context of large C-terminal fusions. This work provides a panel of modified RNAP variants with robust activity and tolerance to C-terminal fusions, and provides insights into the biophysical requirements of the C-terminal carboxylic acid functional group of T7 RNAP.

Multidimensional Control of Cas9 by Evolved RNA Polymerase-Based Biosensors

Systems to control Cas9 with spatial and temporal precision offer opportunities to decrease side effects, protect sensitive tissues, and create gene therapies that are only activated at defined times and places. Here, we present the design of new Cas9 controllers based on RNA polymerase (RNAP)-based biosensors that produce gRNAs, thereby regulating target knockout. After development and validation of a new abscisic acid-inducible biosensor to control Cas9, we lowered the background of the system using continuous evolution. To showcase the versatility of the approach, we designed biosensors that measure medically relevant protein-protein interactions to drive knockout. Finally, to test whether orthogonal RNAP biosensors could integrate multiple input signals to drive multiple gRNA-based outputs with a single Cas9 protein, we designed an "on-switch/off switch" controller. The addition of one input activates the "on switch" and induces knockout, while the addition of a second input activates the "off switch" and produces a gRNA that directs the Cas9 protein to degrade the "on switch" gRNA vector, thereby deactivating it. This combined activation and deactivation system displayed very low background and inducible target knockout using different combinations of small-molecule treatment. Our results establish engineered RNAP biosensors as deployable Cas9 control elements and open up new opportunities for driving genetic editing technologies by diverse input signals.

DIRECTING DRUG EVOLUTION

Directed evolution is poised to change small molecule discovery and provide greater access to "drug space." Sarah Webb looks into the evolving drug discovery landscape.