From Phenotypic Hit to Chemical Probe: Chemical Biology Approaches to Elucidate Small Molecule Action in Complex Biological Systems

Bridging the gap between target-based and phenotypic-based drug discovery

INTRODUCTION

The unparalleled progress in science of the last decades has brought a better understanding of the molecular mechanisms of diseases. This promoted drug discovery processes based on a target approach. However, despite the high promises associated, a critical decrease in the number of first-in-class drugs has been observed.

AREAS COVERED

This review analyses the challenges, advances, and opportunities associated with the main strategies of the drug discovery process, i.e. based on a rational target approach and on an empirical phenotypic approach. This review also evaluates how the gap between these two crossroads can be bridged toward a more efficient drug discovery process.

EXPERT OPINION

The critical lack of knowledge of the complex biological networks is leading to targets not relevant for the clinical context or to drugs that present undesired adverse effects. The phenotypic systems designed by considering available molecular mechanisms can mitigate these knowledge gaps. Associated with the expansion of the chemical space and other technologies, these designs can lead to more efficient drug discoveries. Technological and scientific knowledge should also be applied to identify, as early as possible, both drug targets and mechanisms of action, leading to a more efficient drug discovery pipeline.

Novel Compounds Derived from DFPM Induce Root Growth Arrest through the Specific VICTR Alleles of Arabidopsis Accessions

The small compound [5-(3,4-dichlorophenyl) furan-2-yl]-piperidine-1-ylmethanethione (DFPM) inhibits ABA responses by activating effector-triggered immune signal transduction in Arabidopsis. In addition to the known function of DFPM as an antagonist of ABA signaling, DFPM causes accession-specific root growth arrest in Arabidopsis Columbia-0 via the TIR-NLR protein VICTR (VARIATION IN COMPOUND TRIGGERED ROOT growth response) in an EDS1/PAD4/RAR1/SGT1B-dependent manner. Although DFPM could control the specific steps of various cellular responses, the functional residues for the activity of DFPM or the existence of a stronger version of DFPM modification have not been characterized thoroughly. This study analyzed twenty-two DFPM derivatives during root growth arrest, inhibition of ABA signaling, and induction of biotic signal transduction to determine critical residues that confer the specific activity of DFPM. Furthermore, this study identified two more Arabidopsis accessions that generate significant root growth arrest in response to DFPM derivatives dependent on multiple amino acid polymorphisms in the coding region of VICTR. The isolation of novel compounds, such as DFPM-5, and specific amino acid polymorphisms critical for the compound-induced responses will help determine the detailed regulatory mechanism for how DFPM regulates abiotic and biotic stress signaling interactions.

Targeted protein degradation reveals BET bromodomains as the cellular target of Hedgehog pathway inhibitor-1

Target deconvolution of small molecule hits from phenotypic screens presents a major challenge. Many screens have been conducted to find inhibitors for the Hedgehog signaling pathway - a developmental pathway with many implications in health and disease - yielding many hits but only few identified cellular targets. We here present a strategy for target identification based on Proteolysis-Targeting Chimeras (PROTACs), combined with label-free quantitative proteomics. We develop a PROTAC based on Hedgehog Pathway Inhibitor-1 (HPI-1), a phenotypic screen hit with unknown cellular target. Using this Hedgehog Pathway PROTAC (HPP) we identify and validate BET bromodomains as the cellular targets of HPI-1. Furthermore, we find that HPP-9 is a long-acting Hedgehog pathway inhibitor through prolonged BET bromodomain degradation. Collectively, we provide a powerful PROTAC-based approach for target deconvolution, that answers the longstanding question of the cellular target of HPI-1 and yields a PROTAC that acts on the Hedgehog pathway.

Fragment-Based Lead Discovery Strategies in Antimicrobial Drug Discovery

Fragment-based lead discovery (FBLD) is a powerful application for developing ligands as modulators of disease targets. This approach strategy involves identification of interactions between low-molecular weight compounds (100-300 Da) and their putative targets, often with low affinity (K_D ~0.1-1 mM) interactions. The focus of this screening methodology is to optimize and streamline identification of fragments with higher ligand efficiency (LE) than typical high-throughput screening. The focus of this review is on the last half decade of fragment-based drug discovery strategies that have been used for antimicrobial drug discovery.

High-dimensional gene expression and morphology profiles of cells across 28,000 genetic and chemical perturbations

Cells can be perturbed by various chemical and genetic treatments and the impact on gene expression and morphology can be measured via transcriptomic profiling and image-based assays, respectively. The patterns observed in these high-dimensional profile data can power a dozen applications in drug discovery and basic biology research, but both types of profiles are rarely available for large-scale experiments. Here, we provide a collection of four datasets with both gene expression and morphological profile data useful for developing and testing multimodal methodologies. Roughly a thousand features are measured for each of the two data types, across more than 28,000 chemical and genetic perturbations. We define biological problems that use the shared and complementary information in these two data modalities, provide baseline analysis and evaluation metrics for multi-omic applications, and make the data resource publicly available ( https://broad.io/rosetta/ ).

Morphology and gene expression profiling provide complementary information for mapping cell state

Morphological and gene expression profiling can cost-effectively capture thousands of features in thousands of samples across perturbations by disease, mutation, or drug treatments, but it is unclear to what extent the two modalities capture overlapping versus complementary information. Here, using both the L1000 and Cell Painting assays to profile gene expression and cell morphology, respectively, we perturb human A549 lung cancer cells with 1,327 small molecules from the Drug Repurposing Hub across six doses, providing a data resource including dose-response data from both assays. The two assays capture both shared and complementary information for mapping cell state. Cell Painting profiles from compound perturbations are more reproducible and show more diversity but measure fewer distinct groups of features. Applying unsupervised and supervised methods to predict compound mechanisms of action (MOAs) and gene targets, we find that the two assays not only provide a partially shared but also a complementary view of drug mechanisms. Given the numerous applications of profiling in biology, our analyses provide guidance for planning experiments that profile cells for detecting distinct cell types, disease phenotypes, and response to chemical or genetic perturbations.

Accelerating reaction generality and mechanistic insight through additive mapping

Reaction generality is crucial in determining the overall impact and usefulness of synthetic methods. Typical generalization protocols require a priori mechanistic understanding and suffer when applied to complex, less understood systems. We developed an additive mapping approach that rapidly expands the utility of synthetic methods while generating concurrent mechanistic insight. Validation of this approach on the metallaphotoredox decarboxylative arylation resulted in the discovery of a phthalimide ligand additive that overcomes many lingering limitations of this reaction and has important mechanistic implications for nickel-catalyzed cross-couplings.

Induction of Genes Implicated in Stress Response and Autophagy by a Novel Quinolin-8-yl-nicotinamide QN523 in Pancreatic Cancer

Using a cytotoxicity-based phenotypic screen of a highly diverse library of 20,000 small-molecule compounds, we identified a quinolin-8-yl-nicotinamide, QN519, as a promising lead. QN519 represents a novel scaffold with drug-like properties, showing potent in vitro cytotoxicity in a panel of 12 cancer cell lines. Subsequently, lead optimization campaign generated compounds with IC50 values < 1 μM. An optimized compound, QN523, shows significant in vivo efficacy in a pancreatic cancer xenograft model. QN523 treatment significantly increased the expression of HSPA5, DDIT3, TRIB3, and ATF3 genes, suggesting activation of the stress response pathway. We also observed a significant increase in the expression of WIPI1, HERPUD1, GABARAPL1, and MAP1LC3B, implicating autophagy as a major mechanism of action. Due to the lack of effective treatments for pancreatic cancer, discovery of novel agents such as the QN series of compounds with unique mechanism of action has the potential to fulfill a clear unmet medical need.

Validating Small Molecule Chemical Probes for Biological Discovery

Small molecule chemical probes are valuable tools for interrogating protein biological functions and relevance as a therapeutic target. Rigorous validation of chemical probe parameters such as cellular potency and selectivity is critical to unequivocally linking biological and phenotypic data resulting from treatment with a chemical probe to the function of a specific target protein. A variety of modern technologies are available to evaluate cellular potency and selectivity, target engagement, and functional response biomarkers of chemical probe compounds. Here, we review these technologies and the rationales behind using them for the characterization and validation of chemical probes. In addition, large-scale phenotypic characterization of chemical probes through chemical genetic screening is increasingly leading to a wealth of information on the cellular pharmacology and disease involvement of potential therapeutic targets. Extensive compound validation approaches and integration of phenotypic information will lay foundations for further use of chemical probes in biological discovery. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Selectivity aspects of activity-based (chemical) probes

Selective chemical modulators are ideal tools to study the function of a protein. Yet, the poor ligandability of many proteins has hampered the development of specific chemical probes for numerous protein classes. Tools, such as covalent inhibitors and activity-based protein profiling, have enhanced our understanding of thus-far difficult-to-target proteins and have enabled correct assessment of the selectivity of small-molecule modulators. This also requires deeper knowledge of compound and target site reactivity, evaluation of binding to noncovalent targets and protein turnover. The availability of highly selective chemical probes, the evolution of activity-based probes, and the development of profiling methods will open a new era of drugging the undruggable proteome.

The right tools for the job: the central role for next generation chemical probes and chemistry-based target deconvolution methods in phenotypic drug discovery

The reconnection of the scientific community with phenotypic drug discovery has created exciting new possibilities to develop therapies for diseases with highly complex biology. It promises to revolutionise fields such as neurodegenerative disease and regenerative medicine, where the development of new drugs has consistently proved elusive. Arguably, the greatest challenge in readopting the phenotypic drug discovery approach exists in establishing a crucial chain of translatability between phenotype and benefit to patients in the clinic. This remains a key stumbling block for the field which needs to be overcome in order to fully realise the potential of phenotypic drug discovery. Excellent quality chemical probes and chemistry-based target deconvolution techniques will be a crucial part of this process. In this review, we discuss the current capabilities of chemical probes and chemistry-based target deconvolution methods and evaluate the next advances necessary in order to fully support phenotypic screening approaches in drug discovery.