Targeting the Intrinsically Disordered Proteome Using Small-Molecule Ligands

Machine Learning Generation of Dynamic Protein Conformational Ensembles

Machine learning has achieved remarkable success across a broad range of scientific and engineering disciplines, particularly its use for predicting native protein structures from sequence information alone. However, biomolecules are inherently dynamic, and there is a pressing need for accurate predictions of dynamic structural ensembles across multiple functional levels. These problems range from the relatively well-defined task of predicting conformational dynamics around the native state of a protein, which traditional molecular dynamics (MD) simulations are particularly adept at handling, to generating large-scale conformational transitions connecting distinct functional states of structured proteins or numerous marginally stable states within the dynamic ensembles of intrinsically disordered proteins. Machine learning has been increasingly applied to learn low-dimensional representations of protein conformational spaces, which can then be used to drive additional MD sampling or directly generate novel conformations. These methods promise to greatly reduce the computational cost of generating dynamic protein ensembles, compared to traditional MD simulations. In this review, we examine recent progress in machine learning approaches towards generative modeling of dynamic protein ensembles and emphasize the crucial importance of integrating advances in machine learning, structural data, and physical principles to achieve these ambitious goals.

Small molecules targeting the disordered transactivation domain of the androgen receptor induce the formation of collapsed helical states

Intrinsically disordered proteins, which do not adopt well-defined structures under physiological conditions, are implicated in many human diseases. Small molecules that target the disordered transactivation domain of the androgen receptor have entered human trials for the treatment of castration-resistant prostate cancer (CRPC), but no structural or mechanistic rationale exists to explain their inhibition mechanisms or relative potencies. Here, we utilize all-atom molecular dynamics computer simulations to elucidate atomically detailed binding mechanisms of the compounds EPI-002 and EPI-7170 to the androgen receptor. Our simulations reveal that both compounds bind at the interface of two transiently helical regions and induce the formation of partially folded collapsed helical states. We find that EPI-7170 binds androgen receptor more tightly than EPI-002 and we identify a network of intermolecular interactions that drives higher affinity binding. Our results suggest strategies for developing more potent androgen receptor inhibitors and general strategies for disordered protein drug design.

Targeting disorders in unstructured and structured proteins in various diseases

Intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) are proteins and protein segments that usually do not acquire well-defined folded structures even under physiological conditions. They are abundantly present and challenge the "one sequence-one structure-one function" theory due to a lack of stable secondary and/or tertiary structure. Due to conformational flexibility, IDPs/IDPRs can bind with multiple interacting partners with high-specificity and low-affinity and perform essential biological functions associated with signalling, recognition and regulation. Mis-functioning and mis-regulation of IDPs and IDPRs causes disorder in disordered proteins and disordered protein segments which results in numerous human diseases, such as cancer, Parkinson's disease (PD), Alzheimer's disease (AD), diabetes, metabolic disorders, systemic disorders and so on. Due to the strong connection of IDPs/IDPRs with human diseases they are considered potentential targets for drug therapy. Since they disobey the "one sequence-one structure-one function" concept, IDPs/IDPRs are complex systems for drug targeting. This review summarises various protein disorder diseases and different methods for therapeutic targeting of disordered proteins/segments. Targeting IDPs/IDPRs for diseases will open up a new era of rational drug design and drug discovery.

Defining the Neuropathological Aggresome across in Silico, in Vitro, and ex Vivo Experiments

The loss of proteostasis over the life course is associated with a wide range of debilitating degenerative diseases and is a central hallmark of human aging. When left unchecked, proteins that are intrinsically disordered can pathologically aggregate into highly ordered fibrils, plaques, and tangles (termed amyloids), which are associated with countless disorders such as Alzheimer's disease, Parkinson's disease, type II diabetes, cancer, and even certain viral infections. However, despite significant advances in protein folding and solution biophysics techniques, determining the molecular cause of these conditions in humans has remained elusive. This has been due, in part, to recent discoveries showing that soluble protein oligomers, not insoluble fibrils or plaques, drive the majority of pathological processes. This has subsequently led researchers to focus instead on heterogeneous and often promiscuous protein oligomers. Unfortunately, significant gaps remain in how to prepare, model, experimentally corroborate, and extract amyloid oligomers relevant to human disease in a systematic manner. This Review will report on each of these techniques and their successes and shortcomings in an attempt to standardize comparisons between protein oligomers across disciplines, especially in the context of neurodegeneration. By standardizing multiple techniques and identifying their common overlap, a clearer picture of the soluble neuropathological aggresome can be constructed and used as a baseline for studying human disease and aging.

Targeting Intrinsically Disordered Proteins through Dynamic Interactions

Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and have attracted significant interest in understanding if and how they may be targeted using small molecules for therapeutic purposes. While most existing studies have focused on extending the traditional structure-centric drug design strategies and emphasized exploring pre-existing structure features of IDPs for specific binding, several examples have also emerged to suggest that small molecules could achieve specificity in binding IDPs and affect their function through dynamic and transient interactions. These dynamic interactions can modulate the disordered conformational ensemble and often lead to modest compaction to shield functionally important interaction sites. Much work remains to be done on further elucidation of the molecular basis of the dynamic small molecule-IDP interaction and determining how it can be exploited for targeting IDPs in practice. These efforts will rely critically on an integrated experimental and computational framework for disordered protein ensemble characterization. In particular, exciting advances have been made in recent years in enhanced sampling techniques, Graphic Processing Unit (GPU)-computing, and protein force field optimization, which have now allowed rigorous physics-based atomistic simulations to generate reliable structure ensembles for nontrivial IDPs of modest sizes. Such de novo atomistic simulations will play crucial roles in exploring the exciting opportunity of targeting IDPs through dynamic interactions.

Discovery of drugs that directly target the intrinsically disordered region of the androgen receptor

Introduction: Intrinsically disordered proteins (IDPs) and regions (IDRs) lack stable three-dimensional structure making drug discovery challenging. A validated therapeutic target for diseases such as prostate cancer is the androgen receptor (AR) which has a disordered amino-terminal domain (NTD) that contains all of its transcriptional activity. Drug discovery against the AR-NTD is of intense interest as a potential treatment for disease such as advanced prostate cancer that is driven by truncated constitutively active splice variants of AR that lack the C-terminal ligand-binding domain (LBD).Areas covered: This article presents an overview of the relevance of AR and its intrinsically disordered NTD as a drug target. AR structure and approaches to blocking AR transcriptional activity are discussed. The discovery of small molecules, including the libraries used, proven binders to the AR-NTD, and site of interaction of these small molecules in the AR-NTD are presented along with discussion of the Phase I clinical trial.Expert opinion: The lack of drugs in the clinic that directly bind IDPs/IDRs reflects the difficulty of targeting these proteins and obtaining specificity. However, it may also point to an inappropriateness of too closely borrowing concepts and resources from drug discovery to folded proteins.

Presence and structure-activity relationship of intrinsically disordered regions across mucins

Many members of the mucin family are evolutionarily conserved and are often aberrantly expressed and glycosylated in various benign and malignant pathologies leading to tumor invasion, metastasis, and immune evasion. The large size and extensive glycosylation present challenges to study the mucin structure using traditional methods, including crystallography. We offer the hypothesis that the functional versatility of mucins may be attributed to the presence of intrinsically disordered regions (IDRs) that provide dynamism and flexibility and that the IDRs offer potential therapeutic targets. Herein, we examined the links between the mucin structure and function based on IDRs, posttranslational modifications (PTMs), and potential impact on their interactome. Using sequence-based bioinformatics tools, we observed that mucins are predicted to be moderately (20%-40%) to highly (>40%) disordered and many conserved mucin domains could be disordered. Phosphorylation sites overlap with IDRs throughout the mucin sequences. Additionally, the majority of predicted O- and N- glycosylation sites in the tandem repeat regions occur within IDRs and these IDRs contain a large number of functional motifs, that is, molecular recognition features (MoRFs), which directly influence protein-protein interactions (PPIs). This investigation provides a novel perspective and offers an insight into the complexity and dynamic nature of mucins.

Sequence-Derived Markers of Drug Targets and Potentially Druggable Human Proteins

Recent research shows that majority of the druggable human proteome is yet to be annotated and explored. Accurate identification of these unexplored druggable proteins would facilitate development, screening, repurposing, and repositioning of drugs, as well as prediction of new drug–protein interactions. We contrast the current drug targets against the datasets of non-druggable and possibly druggable proteins to formulate markers that could be used to identify druggable proteins. We focus on the markers that can be extracted from protein sequences or names/identifiers to ensure that they can be applied across the entire human proteome. These markers quantify key features covered in the past works (topological features of PPIs, cellular functions, and subcellular locations) and several novel factors (intrinsic disorder, residue-level conservation, alternative splicing isoforms, domains, and sequence-derived solvent accessibility). We find that the possibly druggable proteins have significantly higher abundance of alternative splicing isoforms, relatively large number of domains, higher degree of centrality in the protein-protein interaction networks, and lower numbers of conserved and surface residues, when compared with the non-druggable proteins. We show that the current drug targets and possibly druggable proteins share involvement in the catalytic and signaling functions. However, unlike the drug targets, the possibly druggable proteins participate in the metabolic and biosynthesis processes, are enriched in the intrinsic disorder, interact with proteins and nucleic acids, and are localized across the cell. To sum up, we formulate several markers that can help with finding novel druggable human proteins and provide interesting insights into the cellular functions and subcellular locations of the current drug targets and potentially druggable proteins.