Intrinsically Disordered Proteins (IDPs) are proteins without a single fixed three-dimensional conformation or structure. Their mere existence is a subversion of the idea that proteins must possess a stable structure to carry out their functions: indeed, IDPs are involved in crucial aspects of DNA regulation and cell signaling. They are ideal for this function: disorder can facilitate highly specific interactions, which are also low-affinity and highly reversible. They have also been implicated in disease pathophysiology – making them attractive targets for drug discovery efforts. This article will provide a brief overview of IDPs and efforts to target them in therapeutic interventions.
IDPs are rarely fully disordered proteins in their native state. The majority of IDPs are otherwise well-structured proteins with Intrinsically Disordered Regions (IDRs). Typically, IDRs will exhibit nearly no secondary protein structure. Multiple clues in their amino acid sequence can hint at disorder. These include low hydrophobicity and low complexity, arising from the overrepresentation of a few amino acid residues. Attempts have even been made to rank amino acids by their propensity for promoting disorder.
The low degree of hydrophobicity leads to strong polar interactions with water and high overall charge – which can promote repulsion and lack of structure. While these are predictors of intrinsic disorder, validating the lack of structure is a more complicated affair. Methods such as Nuclear Magnetic Resonance (NMR), small angle X-ray scattering (SAXS) are particularly useful. Newer methods include Fast parallel proteolysis (FASTpp), which exploits the higher susceptibility of disordered proteins to protease enzymes to identify structural stability.
Perhaps the most well-known pathology involving IDPs are synucleinopathies – diseases which exhibit aggregates of misfolded alpha-Synuclein proteins. This is a family of disorders which comprises multiple diseases, such as Parkinson’s Disease, Dementia with Lewy Bodies, multiple systems atrophy, pure autonomic failure and others. Homologues of alpha-Synuclein such as beta-Synuclein also exhibit intrinsic disorder – studies show that beta-Synuclein may have an inhibitory role in alpha-Synuclein aggregation. This hints at the broad goal of therapeutics targeting IDPs to begin with: inhibiting the disordered regions of proteins, which are often responsible for many of their disease-causing interactions.
This pattern holds true for disease areas beyond protein aggregation. For example, the p53 tumor suppressor is a transcription factor with antitumor activity. Studies have shown that the C-terminal Domain (CTD) in p53 is an IDR, and it plays an essential role in all transcription regulating aspects of p53. The lack of structural constraints, conformational dynamics and amino acid composition enabled by its intrinsically disordered nature are crucial for these functions. In this scenario, disorder enables a greater variety of functions. Mutations in TP53, the gene responsible for producing p53, can modulate the degree of conformational expansion and structural rigidity available to the protein – even when they do not occur within the highly conserved disordered regions.
BRCA1, one of the best studied proteins implicated in breast and ovarian cancers, also contains an intrinsically disordered linker region. The highly disordered central region in the BRCA1 protein is hypothesized to act as a long, flexible scaffold that can facilitate multiple different signals by the protein – enabling it to interact with diverse molecules, such as DNA and p53. This highlights the widespread presence and significance of IDPs in cellular and genetic modulation processes
Androgen Receptor (AR) protein, one of the most widely studied proteins implicated in prostate cancer, also possesses a disordered amino-terminal domain (NTD) implicated in all of its transcriptional activity. Various formulations of ralaniten have been studied which block the transcriptional activity of AR, to various effects. Studies have also shown that ralaniten can sensitize prostate cancers to radiotherapy. However, progress in the area is being slow and laborious – particularly because of a collective instinct to adopt the same methods used to drug structured proteins when investigating therapeutics for IDPs. With IDPs and IDRs representing structures that are uniquely difficult to predict, much of the work had to be done empirically – in the face of limitations such as protein aggregation, susceptibility to proteolytic activity and other attributes which rule out a plethora of established assays that would otherwise be used for structured proteins.
Other early successes in the field show that targeting IDPs remains a feasible endeavor, albeit one that is still in its infancy. Improving the methods with which IDPs are characterized and identified will be crucial in promoting further growth in this space. Tools such as AlphaFOLD have made waves in revolutionizing structural biology and protein structure prediction – but caution is advised when using such tools to infer IDR “structure” and function. Developing sequence-ensemble relationships will be crucial for the inference of IDR functions – and AI neural networks are expected to make a massive difference in how well, and timely, we can understand how IDRs work.
With implications in wide-ranging disease classes – neurological disorders, cancer, and even viral infections with Hepatitis E virus, IDPs and IDRs are crucial biological regulators. Improvements in technology hold the key to facilitating an understanding of how we can exploit them as a vast swath of untapped drug targets. But in our pursuit to do so, we must remember to approach them as what they are – and leave our traditional, structure-guided biases behind.
Join Proventa International’s Drug Discovery Biology Strategy Meeting in Boston to hear more on IDPs & IDRs and the potential they hold for future drug discovery efforts. Network with leading industry experts and participate in conversations running the full gamut of current trends
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