Modulating biomolecular condensates: a novel approach to drug discovery

Abstract

In the past decade, membraneless assemblies known as biomolecular condensates have been reported to play key roles in many cellular functions by compartmentalizing specific proteins and nucleic acids in subcellular environments with distinct properties. Furthermore, growing evidence supports the view that biomolecular condensates often form by phase separation, in which a single-phase system demixes into a two-phase system consisting of a condensed phase and a dilute phase of particular biomolecules. Emerging understanding of condensate function in normal and aberrant cellular states, and of the mechanisms of condensate formation, is providing new insights into human disease and revealing novel therapeutic opportunities. In this Perspective, we propose that such insights could enable a previously unexplored drug discovery approach based on identifying condensate-modifying therapeutics (c-mods), and we discuss the strategies, techniques and challenges involved.

Fig. 1. Examples of complex composition of biomolecular condensates.

The molecular community defines the identity of a biomolecular condensate. Examples of three biomolecular condensates and selected components. The centrosome is the central organizer of microtubules and is involved in regulation of mitosis; the image shows a mitotic SiHa cell, with the centrosome structural protein CDK5RAP2 stained green, the nucleus blue and microtubules red. The nucleolus is the site of ribosome biogenesis; the image shows U2OS cells with the nucleolar scaffold protein NPM1 stained green and microtubules red. Stress granules; the image shows stress granules in HeLa cells, visualized via G3BP1 immunofluorescence. lncRNA, long non-coding RNA; rRNA, ribosomal RNA; snoRNA, small nucleolar RNA. The centrosome image is reproduced from https://www.proteinatlas.org/ENSG00000136861-CDK5RAP2/cell#img, and the nucleolus image is reproduced from https://www.proteinatlas.org/ENSG00000181163-NPM1/cell#img.

Fig. 2. Principles of condensate assembly and their regulation.

a | Phase separation enables a sharp, switch-like response as the concentration of phase-separating biomolecule(s) exceeds the saturation concentration (C_sat). In this case, a small change in bulk concentration can lead to sudden change in a molecule’s local concentration, and may lead to large changes in activity/signalling (top). By contrast, without phase separation, a molecule’s local concentration scales linearly with the bulk concentration, resulting in subtle effects (bottom). b | At atomic and molecular levels (angstrom to nanometre), various types of interactions (top left) and their valency (top right) define condensates. These interactions, in turn, define condensate composition. Examples of biomolecular topology that promote condensation include intrinsically disordered proteins with multivalency encoded in short linear motifs, modular proteins with multivalency encoded in repeat folded binding domains, modular proteins with a condensation-prone intrinsically disordered region (IDR) and one or more folded domains that drive specific localization (for example, transcription factors), and nucleic acids (DNA and RNA). Scaffolds (orange) are characterized by higher partition coefficients and lower C_sat values compared with clients (blue). Together, all smaller-scale interactions modulate the biomolecular network of the molecular community (bottom left) and the emergent material properties (bottom right) at the mesoscale (nanometre to micrometre), optimized for condensate function (fit for purpose). Solid-like condensates such as the Balbiani body are reversible under physiological conditions, in contrast to solid-like pathological amyloids. Part b is adapted with permission from ref., Elsevier.

Fig. 3. Goals and strategies for developing c-mods.

a | Condensate-modifying therapeutics (c-mods) are developed to achieve one or more of the following objectives: to repair or eliminate a condensatopathy (left); to prevent a specific target from functioning by either delocalizing it from its native condensate (centre) or rendering it inactive within the condensate; or to disrupt the function of a normal condensate (right). b | Strategies to modulate the emerging properties of condensates with c-mods, described in detail in the text. These strategies can be used individually or in combination, and any one strategy can influence multiple characteristics of a condensate; for example, modulating the scaffold will probably result in changes in composition and material properties.

Fig. 4. Building a c-mod discovery pipeline: NUP98–HOXA9 as a case study.

a | The first step is validation of the condensate hypothesis by testing the correlation between the genetic alteration (NUP98 and HOX9 fusion), aberrant condensate phenotype and aberrant transcription of HOX genes. b | A proof-of-concept drug discovery pipeline for the NUP98–HOXA9 condensatopathy. A primary phenotypic high-throughput screen (HTS) in a cell line expressing NUP98–HOXA9 could identify compounds that change the morphology of aberrant condensates. Hit compounds with various chemotypes could be filtered and prioritized (for example, with the aid of machine learning/artificial intelligence or through traditional methods) based on various characteristics (two are shown in the graph). Selected hits would then move into secondary validation assays, where one or more functional outcomes are monitored, in disease-relevant cell lines (for example, genome occupancy by ChIP-seq, and in vitro pharmacology by proliferation kinetics) and in vivo activity (for example, tumour growth and survival rates in animal models). Lead compound characteristics would then be optimized in a panel of assays, ranging from in vitro binding studies to the target, biophysical characterization of the lead compound effects on composition and material properties of in vitro reconstituted and endogenous condensates, partitioning measurements, toxicity and off-target measurements, in addition to secondary functional assays. Parts a and b are adapted with permission from refs.^,, CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), Elsevier.