Intrinsically disordered proteins are potential drug targets

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Experimental methods to study the structure and dynamics of intrinsically disordered regions in proteins

Eukaryotic proteins often feature long stretches of amino acids that lack a well-defined three-dimensional structure and are referred to as intrinsically disordered proteins (IDPs) or regions (IDRs). Although these proteins challenge conventional structure-function paradigms, they play vital roles in cellular processes. Recent progress in experimental techniques, such as NMR spectroscopy, single molecule FRET, high speed AFM and SAXS, have provided valuable insights into the biophysical basis of IDP function. This review discusses the advancements made in these techniques particularly for the study of disordered regions in proteins. In NMR spectroscopy new strategies such as 13C detection, non-uniform sampling, segmental isotope labeling, and rapid data acquisition methods address the challenges posed by spectral overcrowding and low stability of IDPs. The importance of various NMR parameters, including chemical shifts, hydrogen exchange rates, and relaxation measurements, to reveal transient secondary structures within IDRs and IDPs are presented. Given the high flexibility of IDPs, the review outlines NMR methods for assessing their dynamics at both fast (ps-ns) and slow (μs-ms) timescales. IDPs exert their functions through interactions with other molecules such as proteins, DNA, or RNA. NMR-based titration experiments yield insights into the thermodynamics and kinetics of these interactions. Detailed study of IDPs requires multiple experimental techniques, and thus, several methods are described for studying disordered proteins, highlighting their respective advantages and limitations. The potential for integrating these complementary techniques, each offering unique perspectives, is explored to achieve a comprehensive understanding of IDPs.

High-throughput assay exploiting disorder-to-order conformational switches: application to the proteasomal Rpn10:E6AP complex

Conformational switching is pervasively driven by protein interactions, particularly for intrinsically disordered binding partners. We developed a dually orthogonal fluorescence-based assay to monitor such events, exploiting environmentally sensitive fluorophores. This assay is applied to E3 ligase E6AP, as its AZUL domain induces a disorder-to-order switch in an intrinsically disordered region of the proteasome, the so-named Rpn10 AZUL-binding domain (RAZUL). By testing various fluorophores, we developed an assay appropriate for high-throughput screening of Rpn10:E6AP-disrupting ligands. We found distinct positions in RAZUL for fluorophore labeling with either acrylodan or Atto610, which had disparate spectral responses to E6AP binding. E6AP caused a hypsochromic shift with increased fluorescence of acrylodan-RAZUL while decreasing fluorescence intensity of Atto610-RAZUL. Combining RAZUL labeled with either acrylodan or Atto610 into a common sample achieved robust and orthogonal measurement of the E6AP-induced conformational switch. This approach is generally applicable to disorder-to-order (or vice versa) transitions mediated by molecular interactions.

Unraveling the Behavior of Intrinsically Disordered Protein c-Myc: A Study Utilizing Gaussian-Accelerated Molecular Dynamics

The protein c-Myc is a transcription factor that remains largely intrinsically disordered and is known to be involved in various biological processes and is overexpressed in various cancers, making it an attractive drug target. However, intrinsically disordered proteins such as c-Myc do not show funnel-like basins in their free-energy landscapes; this makes their druggability a challenge. For the first time, we propose a heterodimer model of c-Myc/Max in full length in this work. We used Gaussian-accelerated molecular dynamics (GaMD) simulations to explore the behavior of c-Myc and its various regions, including the transactivation domain (TAD) and the basic helix-loop-helix-leucine-zipper (bHLH-Zipper) motif in three different conformational states: (a) monomeric c-Myc, (b) c-Myc when bound to its partner protein, Max, and (c) when Max was removed after binding. We analyzed the GaMD trajectories using root-mean-square deviation (RMSD), radius of gyration, root-mean-square fluctuation, and free-energy landscape (FEL) calculations to elaborate the behaviors of these regions. The results showed that the monomeric c-Myc structure showed a higher RMSD fluctuation as compared with the c-Myc/Max heterodimer in the bHLH-Zipper motif. This indicated that the bHLH-Zipper motif of c-Myc is more stable when it is bound to Max. The TAD region in both monomeric and Max-bound states showed similar plasticity in terms of RMSD. We also conducted residue decomposition calculations and showed that the c-Myc and Max interaction could be driven mainly by electrostatic interactions and the residues Arg299, Ile403, and Leu420 seemed to play important roles in the interaction. Our work provides insights into the behavior of c-Myc and its regions that could support the development of drugs that target c-Myc and other intrinsically disordered proteins.

The Coming of Age of AI/ML in Drug Discovery, Development, Clinical Testing, and Manufacturing: The FDA Perspectives

Artificial intelligence (AI) and machine learning (ML) represent significant advancements in computing, building on technologies that humanity has developed over millions of years-from the abacus to quantum computers. These tools have reached a pivotal moment in their development. In 2021 alone, the U.S. Food and Drug Administration (FDA) received over 100 product registration submissions that heavily relied on AI/ML for applications such as monitoring and improving human performance in compiling dossiers. To ensure the safe and effective use of AI/ML in drug discovery and manufacturing, the FDA and numerous other U.S. federal agencies have issued continuously updated, stringent guidelines. Intriguingly, these guidelines are often generated or updated with the aid of AI/ML tools themselves. The overarching goal is to expedite drug discovery, enhance the safety profiles of existing drugs, introduce novel treatment modalities, and improve manufacturing compliance and robustness. Recent FDA publications offer an encouraging outlook on the potential of these tools, emphasizing the need for their careful deployment. This has expanded market opportunities for retraining personnel handling these technologies and enabled innovative applications in emerging therapies such as gene editing, CRISPR-Cas9, CAR-T cells, mRNA-based treatments, and personalized medicine. In summary, the maturation of AI/ML technologies is a testament to human ingenuity. Far from being autonomous entities, these are tools created by and for humans designed to solve complex problems now and in the future. This paper aims to present the status of these technologies, along with examples of their present and future applications.

Visualizing single-molecule conformational transition and binding dynamics of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) play crucial roles in cellular processes and hold promise as drug targets. However, the dynamic nature of IDPs remains poorly understood. Here, we construct a single-molecule electrical nanocircuit based on silicon nanowire field-effect transistors (SiNW-FETs) and functionalize it with an individual disordered c-Myc bHLH-LZ domain to enable label-free, in situ, and long-term measurements at the single-molecule level. We use the device to study c-Myc interaction with Max and/or small molecule inhibitors. We observe the self-folding/unfolding process of c-Myc and reveal its interaction mechanism with Max and inhibitors through ultrasensitive real-time monitoring. We capture a relatively stable encounter intermediate ensemble of c-Myc during its transition from the unbound state to the fully folded state. The c-Myc/Max and c-Myc/inhibitor dissociation constants derived are consistent with other ensemble experiments. These proof-of-concept results provide an understanding of the IDP-binding/folding mechanism and represent a promising nanotechnology for IDP conformation/interaction studies and drug discovery.

Overview Update: Computational Prediction of Intrinsic Disorder in Proteins

There are over 100 computational predictors of intrinsic disorder. These methods predict amino acid-level propensities for disorder directly from protein sequences. The propensities can be used to annotate putative disordered residues and regions. This unit provides a practical and holistic introduction to the sequence-based intrinsic disorder prediction. We define intrinsic disorder, explain the format of computational prediction of disorder, and identify and describe several accurate predictors. We also introduce recently released databases of intrinsic disorder predictions and use an illustrative example to provide insights into how predictions should be interpreted and combined. Lastly, we summarize key experimental methods that can be used to validate computational predictions. © 2023 Wiley Periodicals LLC.

Identification of Catechins' Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

The assembly of the amyloid-β peptide (Aβ) into toxic oligomers and fibrils is associated with Alzheimer's disease and dementia. Therefore, disrupting amyloid assembly by direct targeting of the Aβ monomeric form with small molecules or antibodies is a promising therapeutic strategy. However, given the dynamic nature of Aβ, standard computational tools cannot be easily applied for high-throughput structure-based virtual screening in drug discovery projects. In the current study, we propose a computational pipeline-in the framework of the ensemble docking strategy-to identify catechins' binding sites in monomeric Aβ₄₂. It is shown that both hydrophobic aromatic interactions and hydrogen bonding are crucial for the binding of catechins to Aβ₄₂. Additionally, it has been found that all the studied ligands, especially EGCG, can act as potent inhibitors against amyloid aggregation by blocking the central hydrophobic region of Aβ. Our findings are evaluated and confirmed with multi-microsecond MD simulations. Finally, it is suggested that our proposed pipeline, with low computational cost in comparison with MD simulations, is a suitable approach for the virtual screening of ligand libraries against Aβ.

Osmolytes: Wonder molecules to combat protein misfolding against stress conditions

The proper functioning of any protein depends on its three dimensional conformation which is achieved by the accurate folding mechanism. Keeping away from the exposed stress conditions leads to cooperative unfolding and sometimes partial folding, forming the structures like protofibrils, fibrils, aggregates, oligomers, etc. leading to several neurodegenerative diseases like Parkinson's disease, Alzheimer's, Cystic fibrosis, Huntington, Marfan syndrome, and also cancers in some cases, too. Hydration of proteins is necessary, which may be achieved by the presence of organic solutes called osmolytes within the cell. Osmolytes belong to different classes in different organisms and play their role by preferential exclusion of osmolytes and preferential hydration of water molecules and achieves the osmotic balance in the cell otherwise it may cause problems like cellular infection, cell shrinkage leading to apoptosis and cell swelling which is also the major injury to the cell. Osmolyte interacts with protein, nucleic acids, intrinsically disordered proteins by non-covalent forces. Stabilizing osmolytes increases the Gibbs free energy of the unfolded protein and decreases that of folded protein and vice versa with denaturants (urea and guanidinium hydrochloride). The efficacy of each osmolyte with the protein is determined by the calculation of m value which reflects its efficiency with protein. Hence osmolytes can be therapeutically considered and used in drugs.

Combined inhibition of polyamine metabolism and eIF5A hypusination suppresses colorectal cancer growth through a converging effect on MYC translation

A key mechanism driving colorectal cancer (CRC) development is the upregulation of MYC and its targets, including ornithine decarboxylase (ODC), a master regulator of polyamine metabolism. Elevated polyamines promote tumorigenesis in part by activating DHPS-mediated hypusination of the translation factor eIF5A, thereby inducing MYC biosynthesis. Thus, MYC, ODC and eIF5A orchestrate a positive feedback loop that represents an attractive therapeutic target for CRC therapy. Here we show that combined inhibition of ODC and eIF5A induces a synergistic antitumor response in CRC cells, leading to MYC suppression. We found that genes of the polyamine biosynthesis and hypusination pathways are significantly upregulated in colorectal cancer patients and that inhibition of ODC or DHPS alone limits CRC cell proliferation through a cytostatic mechanism, while combined ODC and DHPS/eIF5A blockade induces a synergistic inhibition, accompanied to apoptotic cell death in vitro and in mouse models of CRC and FAP. Mechanistically, we found that this dual treatment causes complete inhibition of MYC biosynthesis in a bimodal fashion, by preventing translational elongation and initiation. Together, these data illustrate a novel strategy for CRC treatment, based on the combined suppression of ODC and eIF5A, which holds promise for the treatment of CRC.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.

Portability of a Small-Molecule Binding Site between Disordered Proteins

Intrinsically disordered proteins (IDPs) are important in both normal and disease states. Small molecules can be targeted to disordered regions, but we currently have only a limited understanding of the nature of small-molecule binding sites in IDPs. Here, we show that a minimal small-molecule binding sequence of eight contiguous residues derived from the Myc protein can be ported into a different disordered protein and recapitulate small-molecule binding activity in the new context. We also find that the residue immediately flanking the binding site can have opposing effects on small-molecule binding in the different disordered protein contexts. The results demonstrate that small-molecule binding sites can act modularly and are portable between disordered protein contexts but that residues outside of the minimal binding site can modulate binding affinity.

Intrinsically Disordered Proteins: An Overview

Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.

Application of physiologically-based pharmacokinetic models for therapeutic proteins and other novel modalities

The past two decades have seen diversification of drug development pipelines and approvals from traditional small molecule therapies to alternative modalities including monoclonal antibodies, engineered proteins, antibody drug conjugates (ADCs), oligonucleotides and gene therapies. At the same time, physiologically-based pharmacokinetic (PBPK) models for small molecules have seen increased industry and regulatory acceptance.This review focusses on the current status of the application of PBPK models to these newer modalities and give a perspective on the successes, challenges and future directions of this field.There is greatest experience in the development of PBPK models for therapeutic proteins, and PBPK models for ADCs benefit from prior experience for both therapeutic proteins and small molecules. For other modalities, the application of PBPK models is in its infancy.Challenges are discussed and a common theme is lack of availability of physiological and experimental data to characterise systems and drug parameters to enable a priori prediction of pharmacokinetics. Furthermore, sufficient clinical data are required to build confidence in developed models.The PBPK modelling approach provides a quantitative framework for integrating knowledge and data from multiple sources and can be built on as more data becomes available.

Evolving Experimental Techniques for Structure-Based Drug Design

Structure-based drug design (SBDD) is a prominent method in rational drug development and has traditionally benefitted from the atomic models of protein targets obtained using X-ray crystallography at cryogenic temperatures. In this perspective, we highlight recent advances in the development of structural techniques that are capable of probing dynamic information about protein targets. First, we discuss advances in the field of X-ray crystallography including serial room-temperature crystallography as a method for obtaining high-resolution conformational dynamics of protein-inhibitor complexes. Next, we look at cryogenic electron microscopy (cryoEM), another high-resolution technique that has recently been used to study proteins and protein complexes that are too difficult to crystallize. Finally, we present small-angle X-ray scattering (SAXS) as a potential high-throughput screening tool to identify inhibitors that target protein complexes and protein oligomerization.

More is simpler: Decomposition of ligand-binding affinity for proteins being disordered

In statistical mechanics, it is well known that the huge number of degrees of freedom does not complicate the problem as it seems, but actually greatly simplifies the analysis (e.g., to give a Boltzmann distribution). Here, we reveal that the ensemble averaging from the vast conformations of intrinsically disordered proteins (IDPs) greatly simplifies the nature of binding affinity, which can be reliably decomposed into a sum of the ligandability of IDP and the capacity of ligand. Such an unexpected regularity is applied to facilitate the virtual screening upon IDPs. It also provides essential insight in understanding the specificity difference between IDPs and conventional ordered proteins since the specificity is caused by deviation from the baseline behavior of protein-ligand binding.

Topological dynamics of an intrinsically disordered N‐terminal domain of the human androgen receptor

Human androgen receptor contains a large N‐terminal domain (AR‐NTD) that is highly dynamic and this poses a major challenge for experimental and computational analysis to decipher its conformation. Misfolding of the AR‐NTD is implicated in prostate cancer and Kennedy's disease, yet our knowledge of its structure is limited to primary sequence information of the chain and a few functionally important secondary structure motifs. Here, we employed an innovative combination of molecular dynamics simulations and circuit topology (CT) analysis to identify the tertiary structure of AR‐NTD. We found that the AR‐NTD adopts highly dynamic loopy conformations with two identifiable regions with distinct topological make‐up and dynamics. This consists of a N‐terminal region (NR, residues 1–224) and a C‐terminal region (CR, residues 225–538), which carries a dense core. Topological mapping of the dynamics reveals a traceable time‐scale dependent topological evolution. NR adopts different positioning with respect to the CR and forms a cleft that can partly enclose the hormone‐bound ligand‐binding domain (LBD) of the androgen receptor. Furthermore, our data suggest a model in which dynamic NR and CR compete for binding to the DNA‐binding domain of the receptor, thereby regulating the accessibility of its DNA‐binding site. Our approach allowed for the identification of a previously unknown regulatory binding site within the CR core, revealing the structural mechanisms of action of AR inhibitor EPI‐001, and paving the way for other drug discovery applications.

Sequence to structure analysis of the ORF4 protein from Hepatitis E virus

Hepatitis E virus (HEV) is the main cause of acute hepatitis worldwide. HEV accounts for up to 30% mortality rate in pregnant women, with highest incidences reported for genotype 1 (G1) HEV. The contributing factors in adverse cases during pregnancy in women due to HEV infection is still debated. The mechanism underlying the pathogenesis of viral infection is attributed to different genomic component of HEV, i.e., open reading frames (ORFs): ORF1, ORF2, ORF3 and ORF4. Recently, ORF4 has been discovered in enhancing the replication of GI isolates of HEV through regulation of an IRES-like RNA element. However, its characterization through computational methodologies remains unexplored. In this novel study, we provide comprehensive overview of ORF4 protein's genetic and molecular characteristics through analyzing its sequence and different structural levels. A total of three different datasets (Human, Rat and Ferret) of ORF4 genomes were built and comparatively analyzed. Several non-synonymous mutations in conjunction with higher entropy values were observed in rat and ferret datasets, however, limited variation was observed in human ORF4 genomes. Higher transition to tranversion ratio was observed in the ORF4 genomes. Studies have reported the association of intrinsic disordered proteins (IDP) with drug discovery due to its role in several signaling and regulatory processes through protein-protein interactions (PPIs). As PPIs are potent drug target sources, thus the ORF4 protein was explored by analyzing its polypeptide structure in order to shed light on its intrinsic disorder. Pressures that lead towards preponderance of disordered-promoting amino acid residues shaped the evolution of ORF4. The intrinsic disorder propensity analysis revealed ORF4 protein (Human) as a highly disordered protein (IDP). Predominance of coils and lack of secondary structure further substantiated our findings suggesting its involvement in binding to ligand molecules. Thus, ORF4 contributes to cellular signaling processes through protein-protein interactions, as IDPs are targets for regulation to accelerate the process of drug designing strategies against HEV infections.

Functional inhibition of c-Myc using novel inhibitors identified through “hot spot” targeting

Protein–protein interactions drive various biological processes in healthy as well as disease states. The transcription factor c-Myc plays a crucial role in maintaining cellular homeostasis, and its deregulated expression is linked to various human cancers; therefore, it can be considered a viable target for cancer therapeutics. However, the structural heterogeneity of c-Myc due to its disordered nature poses a major challenge to drug discovery. In the present study, we used an in silico alanine scanning mutagenesis approach to identify “hot spot” residues within the c-Myc/Myc-associated factor X interface, which is highly disordered and has not yet been systematically analyzed for potential small molecule binding sites. We then used the information gained from this analysis to screen potential inhibitors using a conformation ensemble approach. The fluorescence-based biophysical experiments showed that the identified hit molecules displayed noncovalent interactions with these hot spot residues, and further cell-based experiments showed substantial in vitro potency against diverse c-Myc-expressing cancer/stem cells by deregulating c-Myc activity. These biophysical and computational studies demonstrated stable binding of the hit compounds with the disordered c-Myc protein. Collectively, our data indicated effective drug targeting of the disordered c-Myc protein via the determination of hot spot residues in the c-Myc/Myc-associated factor X heterodimer.

Intrinsically Disordered Proteins: Critical Components of the Wetware

Despite the wealth of knowledge gained about intrinsically disordered proteins (IDPs) since their discovery, there are several aspects that remain unexplored and, hence, poorly understood. A living cell is a complex adaptive system that can be described as a wetware─a metaphor used to describe the cell as a computer comprising both hardware and software and attuned to logic gates─capable of "making" decisions. In this focused Review, we discuss how IDPs, as critical components of the wetware, influence cell-fate decisions by wiring protein interaction networks to keep them minimally frustrated. Because IDPs lie between order and chaos, we explore the possibility that they can be modeled as attractors. Further, we discuss how the conformational dynamics of IDPs manifests itself as conformational noise, which can potentially amplify transcriptional noise to stochastically switch cellular phenotypes. Finally, we explore the potential role of IDPs in prebiotic evolution, in forming proteinaceous membrane-less organelles, in the origin of multicellularity, and in protein conformation-based transgenerational inheritance of acquired characteristics. Together, these ideas provide a new conceptual framework to discern how IDPs may perform critical biological functions despite their lack of structure.

Structure-Activity Relationships of Novel Tau Ligands: Passive Fibril Binders and Active Aggregation Inhibitors

Intrinsically disordered proteins (IDPs) are core components of many biological processes and are central players in several pathologies. Despite being important drug targets, attempts to design small-molecule ligands that would help understand and attenuate their behavior are frustrated by the structural diversity exhibited by these flexible proteins. To accommodate the dynamic nature of IDPs, we developed a procedure that efficiently identifies active small-molecule ligands for disordered proteins. By exploring the chemical space around these ligands, we refined their effect on aggregation and identified molecular features critical for activity and affinity. Notably, the discovery of this new family of disordered protein ligands was achieved more quickly and with less expense than conventional high-throughput screening (HTS) or docking alone would have allowed. The resulting ligands include tau aggregation inhibitors as well as at least one compound that binds fibrils potently but does not appear to perturb the extent of kinetics of aggregation.

Role of structural disorder in the multi-functionality of flavivirus proteins

INTRODUCTION

The life cycle of a virus involves interacting with the host cell, entry, hijacking host machinery for viral replication, evading the host's immune system, and releasing mature virions. However, viruses, being small in size, can only harbor a genome large enough to code for the minimal number of proteins required for the replication and maturation of the virions. As a result, many viral proteins are multifunctional machines that do not directly obey the classic structure-function paradigm. Often, such multifunctionality is rooted in intrinsic disorder that allows viral proteins to interact with various cellular factors and remain functional in the hostile environment of different cellular compartments.

AREAS COVERED

This report covers the classification of flaviviruses, their proteome organization, and the prevalence of intrinsic disorder in the proteomes of different flaviviruses. Further, we have summarized the speculations made about the apparent roles of intrinsic disorder in the observed multifunctionality of flaviviral proteins.

EXPERT OPINION

Small sizes of viral genomes impose multifunctionality on their proteins, which is dependent on the excessive usage of intrinsic disorder. In fact, intrinsic disorder serves as a universal functional tool, weapon, and armor of viruses and clearly plays an important role in their functionality and evolution.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Molecular Basis of Small-Molecule Binding to α-Synuclein

Intrinsically disordered proteins (IDPs) are implicated in many human diseases. They have generally not been amenable to conventional structure-based drug design, however, because their intrinsic conformational variability has precluded an atomic-level understanding of their binding to small molecules. Here we present long-time-scale, atomic-level molecular dynamics (MD) simulations of monomeric α-synuclein (an IDP whose aggregation is associated with Parkinson’s disease) binding the small-molecule drug fasudil in which the observed protein–ligand interactions were found to be in good agreement with previously reported NMR chemical shift data. In our simulations, fasudil, when bound, favored certain charge–charge and π-stacking interactions near the C terminus of α-synuclein but tended not to form these interactions simultaneously, rather breaking one of these interactions and forming another nearby (a mechanism we term dynamic shuttling). Further simulations with small molecules chosen to modify these interactions yielded binding affinities and key structural features of binding consistent with subsequent NMR experiments, suggesting the potential for MD-based strategies to facilitate the rational design of small molecules that bind with disordered proteins.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

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.

Fluorescence Depolarization Kinetics Captures Short-Range Backbone Dihedral Rotations and Long-Range Correlated Dynamics of an Intrinsically Disordered Protein

Intrinsically disordered proteins (IDPs) do not autonomously fold into well-defined three-dimensional structures and are best described as a heterogeneous ensemble of rapidly interconverting conformers. It is challenging to elucidate their complex dynamic signatures using a single technique. In this study, we employed sensitive fluorescence depolarization kinetics by following picosecond time-resolved fluorescence anisotropy decays to directly capture the essential dynamical features of intrinsically disordered α-synuclein (α-syn) site-specifically labeled with thiol-active fluorophores. By utilizing a long-lifetime (≥10 ns) anisotropic label, we were able to discern three distinct rotational components of α-syn. The subnanosecond component represents the local wobbling-in-cone motion of the fluorophore, whereas the slower (∼1.4 ns) component corresponds to the short-range backbone dynamics governed by collective torsional fluctuations in the Ramachandran Φ-Ψ dihedral space. This backbone dihedral rotational time scale is sensitive to the local chain stiffness and slows down in the presence of an adjacent proline residue. We also observed a small-amplitude (≤10%) slower rotational correlation time (6-10 ns) that represents the long-range correlated dynamics involving a much longer segment of the polypeptide chain. These intrinsic dynamic signatures of IDPs will provide critical mechanistic underpinnings in a mosaic of biophysical phenomena involving internal friction, allosteric interactions, and phase separation.

EWS-FLI1-targeting peptide identifies Ewing sarcoma tumor boundaries and lymph node metastasis via near-infrared imaging

Ewing sarcoma (ES) is one of the most aggressive types of pediatric tumors. The lack of tools for the identification of ES has largely hindered clinical diagnosis and the improvement of treatment. To address this challenge, we synthesized a near‐infrared (NIR) fluorescent probe (CS2‐N‐E9R) that targets the ES‐specific fusion protein EWS–FLI1 (E/F). This probe exhibited specific and high binding affinity to E/F. Further studies in animal models showed that CS2‐N‐E9R can be used to identify the boundaries of ES and lymph node metastases under a complex biological environment. These results demonstrate that CS2‐N‐E9R is a promising probe for early diagnosis and surgical guidance of ES through molecularly targeted NIR imaging.

Revealing Intrinsic Disorder and Aggregation Properties of the DPF3a Zinc Finger Protein

Double PHD fingers 3 (DPF3) is a human epigenetic factor found in the multiprotein BRG1-associated factor (BAF) chromatin remodeling complex. It has two isoforms: DPF3b and DPF3a, but very little is known about the latter. Despite the lack of structural data, it has been established that DPF3a is involved in various protein-protein interactions and that it is subject to phosphorylation. These features are typical of intrinsically disordered proteins (IDPs) for which the disorder is essential to their functionality. IDPs are also prone to aggregation and can assemble into cytotoxic amyloid fibrils in specific pathological contexts. In the present work, the DPF3a disordered nature and propensity to aggregation have been investigated using a combination of disorder predictors and biophysical methods. The DPF3a-predicted disordered character has been correlated to a characteristic random coil signal in far-UV circular dichroism (CD) and to a fluorescence emission band typical of Trp residues fully exposed to the solvent. After DPF3a purification and 24 h of incubation at room temperature, dynamic light scattering confirmed the presence of DPF3a aggregates whose amyloid nature have been highlighted by a specific deep-blue autofluorescence signature, as well as by an increase in thioflavin T fluorescence upon binding. These results are supported by an enrichment in twisted β-sheets as observed in far-UV CD and a blue shift in intrinsic Trp fluorescence. Both indicate that DPF3a spontaneously tends to orderly aggregate into amyloid fibrils. The diversity of optical signatures originates from dynamical transitions between the disordered and aggregated states of the protein during the incubation. Transmission electron microscopy micrographs reveal that the DPF3a fibrillation process leads to the formation of short needle-shape filaments.

Ubiquitin Interacting Motifs: Duality Between Structured and Disordered Motifs

Ubiquitin is a small protein at the heart of many cellular processes, and several different protein domains are known to recognize and bind ubiquitin. A common motif for interaction with ubiquitin is the Ubiquitin Interacting Motif (UIM), characterized by a conserved sequence signature and often found in multi-domain proteins. Multi-domain proteins with intrinsically disordered regions mediate interactions with multiple partners, orchestrating diverse pathways. Short linear motifs for binding are often embedded in these disordered regions and play crucial roles in modulating protein function. In this work, we investigated the structural propensities of UIMs using molecular dynamics simulations and NMR chemical shifts. Despite the structural portrait depicted by X-crystallography of stable helical structures, we show that UIMs feature both helical and intrinsically disordered conformations. Our results shed light on a new class of disordered UIMs. This group is here exemplified by the C-terminal domain of one isoform of ataxin-3 and a group of ubiquitin-specific proteases. Intriguingly, UIMs not only bind ubiquitin. They can be a recruitment point for other interactors, such as parkin and the heat shock protein Hsc70-4. Disordered UIMs can provide versatility and new functions to the client proteins, opening new directions for research on their interactome.

Low complexity domains, condensates, and stem cell pluripotency

Biological reactions require self-assembly of factors in the complex cellular milieu. Recent evidence indicates that intrinsically disordered, low-complexity sequence domains (LCDs) found in regulatory factors mediate diverse cellular processes from gene expression to DNA repair to signal transduction, by enriching specific biomolecules in membraneless compartments or hubs that may undergo liquid-liquid phase separation (LLPS). In this review, we discuss how embryonic stem cells take advantage of LCD-driven interactions to promote cell-specific transcription, DNA damage response, and DNA repair. We propose that LCD-mediated interactions play key roles in stem cell maintenance and safeguarding genome integrity.

Intrinsically Disordered Proteins as Regulators of Transient Biological Processes and as Untapped Drug Targets

Intrinsically disordered proteins (IDPs) are critical players in the dynamic control of diverse cellular processes, and provide potential new drug targets because their dysregulation is closely related to many diseases. This review focuses on several medicinal studies that have identified low-molecular-weight inhibitors of IDPs. In addition, clinically relevant liquid-liquid phase separations-which critically involve both intermolecular interactions between IDPs and their posttranslational modification-are analyzed to understand the potential of IDPs as new drug targets.

Drugging the "Undruggable" MYCN Oncogenic Transcription Factor: Overcoming Previous Obstacles to Impact Childhood Cancers

Effective treatment of pediatric solid tumors has been hampered by the predominance of currently "undruggable" driver transcription factors. Improving outcomes while decreasing the toxicity of treatment necessitates the development of novel agents that can directly inhibit or degrade these elusive targets. MYCN in pediatric neural-derived tumors, including neuroblastoma and medulloblastoma, is a paradigmatic example of this problem. Attempts to directly and specifically target MYCN have failed due to its similarity to MYC, the unstructured nature of MYC family proteins in their monomeric form, the lack of an understanding of MYCN-interacting proteins and ability to test their relevance in vivo, the inability to obtain structural information on MYCN protein complexes, and the challenges of using traditional small molecules to inhibit protein-protein or protein-DNA interactions. However, there is now promise for directly targeting MYCN based on scientific and technological advances on all of these fronts. Here, we discuss prior challenges and the reasons for renewed optimism in directly targeting this "undruggable" transcription factor, which we hope will lead to improved outcomes for patients with pediatric cancer and create a framework for targeting driver oncoproteins regulating gene transcription.

Determination of the molecular reach of the protein tyrosine phosphatase SHP-1

Immune receptors signal by recruiting (or tethering) enzymes to their cytoplasmic tails to catalyze reactions on substrates within reach. This is the case for the phosphatase SHP-1, which, upon tethering to inhibitory receptors, dephosphorylates diverse substrates to control T cell activation. Precisely how tethering regulates SHP-1 activity is incompletely understood. Here, we measure binding, catalysis, and molecular reach for tethered SHP-1 reactions. We determine the molecular reach of SHP-1 to be 13.0 nm, which is longer than the estimate from the allosterically active structure (5.3 nm), suggesting that SHP-1 can achieve a longer reach by exploring multiple active conformations. Using modeling, we show that when uniformly distributed, receptor-SHP-1 complexes can only reach 15% of substrates, but this increases to 90% when they are coclustered. When within reach, we show that membrane recruitment increases the activity of SHP-1 by a 1000-fold increase in local concentration. The work highlights how molecular reach regulates the activity of membrane-recruited SHP-1 with insights applicable to other membrane-tethered reactions.

Reinforcement learning to boost molecular docking upon protein conformational ensemble

Intrinsically disordered proteins (IDPs) are widely involved in human diseases and thus are attractive therapeutic targets. In practice, however, it is computationally prohibitive to dock large ligand libraries to thousands and tens of thousands of conformations. Here, we propose a reversible upper confidence bound (UCB) algorithm for the virtual screening of IDPs to address the influence of the conformation ensemble. The docking process is dynamically arranged so that attempts are focused near the boundary to separate top ligands from the bulk accurately. It is demonstrated in the example of transcription factor c-Myc that the average docking number per ligand can be greatly reduced while the performance is merely slightly affected. This study suggests that reinforcement learning is highly efficient in solving the bottleneck of virtual screening due to the conformation ensemble in the rational drug design of IDPs.

Mutations of Intrinsically Disordered Protein Regions Can Drive Cancer but Lack Therapeutic Strategies

Many proteins contain intrinsically disordered regions (IDRs) which carry out important functions without relying on a single well-defined conformation. IDRs are increasingly recognized as critical elements of regulatory networks and have been also associated with cancer. However, it is unknown whether mutations targeting IDRs represent a distinct class of driver events associated with specific molecular and system-level properties, cancer types and treatment options. Here, we used an integrative computational approach to explore the direct role of intrinsically disordered protein regions driving cancer. We showed that around 20% of cancer drivers are primarily targeted through a disordered region. These IDRs can function in multiple ways which are distinct from the functional mechanisms of ordered drivers. Disordered drivers play a central role in context-dependent interaction networks and are enriched in specific biological processes such as transcription, gene expression regulation and protein degradation. Furthermore, their modulation represents an alternative mechanism for the emergence of all known cancer hallmarks. Importantly, in certain cancer patients, mutations of disordered drivers represent key driving events. However, treatment options for such patients are currently severely limited. The presented study highlights a largely overlooked class of cancer drivers associated with specific cancer types that need novel therapeutic options.

Intrinsically disordered features of carbonic anhydrase IX proteoglycan-like domain

hCA IX is a multi-domain protein belonging to the family of hCAs which are ubiquitous zinc enzymes that catalyze the reversible hydration of CO2 to HCO3- and H+. hCA IX is a tumor-associated enzyme with a limited distribution in normal tissues, but over-expressed in many tumors, and is a promising drug target. Although many studies concerning the CA IX catalytic domain were performed, little is known about the proteoglycan-like (PG-like) domain of hCA IX which has been poorly investigated so far. Here we attempt to fill this gap by providing an overview on the functional, structural and therapeutic studies of the PG-like domain of hCA IX which represents a unique feature within the CA family. The main studies and recent advances concerning PG role in modulating hCA IX catalytic activity as well as in tumor spreading and migration are here reported. Special attention has been paid to the newly discovered disordered features of the PG domain which open new perspectives about its molecular mechanisms of action under physiological and pathological conditions, since disorder is likely involved in mediating interactions with partner proteins. The emerged disordered features of PG domain will be explored for putative diagnostic and therapeutic applications involving CA IX targeting in tumors.

Disaggregation mechanism of prion amyloid for tweezer inhibitor

The aggregation of amyloid has been an important event in the pathology of amyloidogenicity. A number of small molecules have been designed for Amyloidosis treatment. Molecular tweezer CLR01, a potential drug for misfolded β-amyloids inhibition, was reportedly bind directly to Lysine residues and interrupt oligomerization. However, the disaggregation mechanism of amyloid for this inhibitor is unclear. Here we used long timescale of molecular dynamic simulation to reveal the mechanism of disaggregation for pentamer prion amyloid. Molecular docking and molecular dynamics simulation demonstrate that CLR01 is attached with Lysine₂₂₂ nitrogen by π-cation interaction of its nine aromatic rings and formation of salt bridge/hydrogen bond of one of the two rotatable peripheral anionic phosphate groups. Upon CLR01 binding, we found a major shifting occurs in initial conformation of the oligomer and stretch out the N-terminal chain A from the rest of the amyloid which seems to be the first stage of disaggregated the fibrils slowly yet efficiently. Moreover, the CLR01 remodelled the pentamer Prion_220-272 into a compact structure which might be the resistant conformation for further oligomerization. Our work will contribute to better understand the interaction and deterioration mechanism of molecular tweezer for prions and similar amyloids, and offer significant insights into therapeutic development for Amyloidosis treatment.

EGCG binds intrinsically disordered N-terminal domain of p53 and disrupts p53-MDM2 interaction

Epigallocatechin gallate (EGCG) from green tea can induce apoptosis in cancerous cells, but the underlying molecular mechanisms remain poorly understood. Using SPR and NMR, here we report a direct, μM interaction between EGCG and the tumor suppressor p53 (KD = 1.6 ± 1.4 μM), with the disordered N-terminal domain (NTD) identified as the major binding site (KD = 4 ± 2 μM). Large scale atomistic simulations (>100 μs), SAXS and AUC demonstrate that EGCG-NTD interaction is dynamic and EGCG causes the emergence of a subpopulation of compact bound conformations. The EGCG-p53 interaction disrupts p53 interaction with its regulatory E3 ligase MDM2 and inhibits ubiquitination of p53 by MDM2 in an in vitro ubiquitination assay, likely stabilizing p53 for anti-tumor activity. Our work provides insights into the mechanisms for EGCG's anticancer activity and identifies p53 NTD as a target for cancer drug discovery through dynamic interactions with small molecules.

Biomolecular Condensates and Cancer

Malignant transformation is characterized by dysregulation of diverse cellular processes that have been the subject of detailed genetic, biochemical, and structural studies, but only recently has evidence emerged that many of these processes occur in the context of biomolecular condensates. Condensates are membrane-less bodies, often formed by liquid-liquid phase separation, that compartmentalize protein and RNA molecules with related functions. New insights from condensate studies portend a profound transformation in our understanding of cellular dysregulation in cancer. Here we summarize key features of biomolecular condensates, note where they have been implicated-or will likely be implicated-in oncogenesis, describe evidence that the pharmacodynamics of cancer therapeutics can be greatly influenced by condensates, and discuss some of the questions that must be addressed to further advance our understanding and treatment of cancer.

Recent Developments in the Field of Intrinsically Disordered Proteins: Intrinsic Disorder-Based Emergence in Cellular Biology in Light of the Physiological and Pathological Liquid-Liquid Phase Transitions

This review deals with two important concepts-protein intrinsic disorder and proteinaceous membrane-less organelles (PMLOs). The past 20 years have seen an upsurge of scientific interest in these phenomena. However, neither are new discoveries made in this century, but instead are timely reincarnations of old ideas that were mostly ignored by the scientific community for a long time. Merging these concepts in the form of the intrinsic disorder-based biological liquid-liquid phase separation provides a basis for understanding the molecular mechanisms of PMLO biogenesis.

Computational strategy for intrinsically disordered protein ligand design leads to the discovery of p53 transactivation domain I binding compounds that activate the p53 pathway

Intrinsically disordered proteins or intrinsically disordered regions (IDPs) have gained much attention in recent years due to their vital roles in biology and prevalence in various human diseases. Although IDPs are perceived as attractive therapeutic targets, rational drug design targeting IDPs remains challenging because of their conformational heterogeneity. Here, we propose a hierarchical computational strategy for IDP drug virtual screening (IDPDVS) and applied it in the discovery of p53 transactivation domain I (TAD1) binding compounds. IDPDVS starts from conformation sampling of the IDP target, then it combines stepwise conformational clustering with druggability evaluation to identify potential ligand binding pockets, followed by multiple docking screening runs and selection of compounds that can bind multi-conformations. p53 is an important tumor suppressor and restoration of its function provides an opportunity to inhibit cancer cell growth. TAD1 locates at the N-terminus of p53 and plays key roles in regulating p53 function. No compounds that directly bind to TAD1 have been reported due to its highly disordered structure. We successfully used IDPDVS to identify two compounds that bind p53 TAD1 and restore wild-type p53 function in cancer cells. Our study demonstrates that IDPDVS is an efficient strategy for IDP drug discovery and p53 TAD1 can be directly targeted by small molecules.

A hierarchical computational strategy for IDP drug virtual screening (IDPDVS) was proposed and successfully applied to identify compounds that bind p53 TAD1 and restore wild-type p53 function in cancer cells.

Phosphorylation-Dependent Conformations of the Disordered Carboxyl-Terminus Domain in the Epidermal Growth Factor Receptor

The epidermal growth factor receptor (EGFR), a receptor tyrosine kinase, regulates basic cellular functions and is a major target for anticancer therapeutics. The carboxyl-terminus domain is a disordered region of EGFR that contains the tyrosine residues, which undergo autophosphorylation followed by docking of signaling proteins. Local phosphorylation-dependent secondary structure has been identified and is thought to be associated with the signaling cascade. Deciphering and distinguishing the overall conformations, however, have been challenging because of the disordered nature of the carboxyl-terminus domain and resultant lack of well-defined three-dimensional structure for most of the domain. We investigated the overall conformational states of the isolated EGFR carboxyl-terminus domain using single-molecule Förster resonance energy transfer and coarse-grained simulations. Our results suggest that electrostatic interactions between charged residues emerge within the disordered domain upon phosphorylation, producing a looplike conformation. This conformation may enable binding of downstream signaling proteins and potentially reflect a general mechanism in which electrostatics transiently generate functional architectures in disordered regions of a well-folded protein.

Mechanisms of Macromolecular Interactions Mediated by Protein Intrinsic Disorder

Intrinsically disordered proteins or regions (IDPs or IDRs) are widespread in the eukaryotic proteome. Although lacking stable three-dimensional structures in the free forms, IDRs perform critical functions in various cellular processes. Accordingly, mutations and altered expression of IDRs are associated with many pathological conditions. Hence, it is of great importance to understand at the molecular level how IDRs interact with their binding partners. In particular, discovering the unique interaction features of IDRs originating from their dynamic nature may reveal uncharted regulatory mechanisms of specific biological processes. Here we discuss the mechanisms of the macromolecular interactions mediated by IDRs and present the relevant cellular processes including transcription, cell cycle progression, signaling, and nucleocytoplasmic transport. Of special interest is the multivalent binding nature of IDRs driving assembly of multicomponent macromolecular complexes. Integrating the previous theoretical and experimental investigations, we suggest that such IDR-driven multiprotein complexes can function as versatile allosteric switches to process diverse cellular signals. Finally, we discuss the future challenges and potential medical applications of the IDR research.

Liquid-Liquid Phase Separation by Intrinsically Disordered Protein Regions of Viruses: Roles in Viral Life Cycle and Control of Virus-Host Interactions

Intrinsically disordered proteins (IDPs) are unable to adopt a unique 3D structure under physiological conditions and thus exist as highly dynamic conformational ensembles. IDPs are ubiquitous and widely spread in the protein realm. In the last decade, compelling experimental evidence has been gathered, pointing to the ability of IDPs and intrinsically disordered regions (IDRs) to undergo liquid-liquid phase separation (LLPS), a phenomenon driving the formation of membrane-less organelles (MLOs). These biological condensates play a critical role in the spatio-temporal organization of the cell, where they exert a multitude of key biological functions, ranging from transcriptional regulation and silencing to control of signal transduction networks. After introducing IDPs and LLPS, we herein survey available data on LLPS by IDPs/IDRs of viral origin and discuss their functional implications. We distinguish LLPS associated with viral replication and trafficking of viral components, from the LLPS-mediated interference of viruses with host cell functions. We discuss emerging evidence on the ability of plant virus proteins to interfere with the regulation of MLOs of the host and propose that bacteriophages can interfere with bacterial LLPS, as well. We conclude by discussing how LLPS could be targeted to treat phase separation-associated diseases, including viral infections.

Identifying molecular recognition features in intrinsically disordered regions of proteins by transfer learning

MOTIVATION

Protein intrinsic disorder describes the tendency of sequence residues to not fold into a rigid three-dimensional shape by themselves. However, some of these disordered regions can transition from disorder to order when interacting with another molecule in segments known as molecular recognition features (MoRFs). Previous analysis has shown that these MoRF regions are indirectly encoded within the prediction of residue disorder as low-confidence predictions [i.e. in a semi-disordered state P(D)≈0.5]. Thus, what has been learned for disorder prediction may be transferable to MoRF prediction. Transferring the internal characterization of protein disorder for the prediction of MoRF residues would allow us to take advantage of the large training set available for disorder prediction, enabling the training of larger analytical models than is currently feasible on the small number of currently available annotated MoRF proteins. In this paper, we propose a new method for MoRF prediction by transfer learning from the SPOT-Disorder2 ensemble models built for disorder prediction.

RESULTS

We confirm that directly training on the MoRF set with a randomly initialized model yields substantially poorer performance on independent test sets than by using the transfer-learning-based method SPOT-MoRF, for both deep and simple networks. Its comparison to current state-of-the-art techniques reveals its superior performance in identifying MoRF binding regions in proteins across two independent testing sets, including our new dataset of >800 protein chains. These test chains share <30% sequence similarity to all training and validation proteins used in SPOT-Disorder2 and SPOT-MoRF, and provide a much-needed large-scale update on the performance of current MoRF predictors. The method is expected to be useful in locating functional disordered regions in proteins.

AVAILABILITY AND IMPLEMENTATION

SPOT-MoRF and its data are available as a web server and as a standalone program at: http://sparks-lab.org/jack/server/SPOT-MoRF/index.php.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exploring IDP-Ligand Interactions: tau K18 as A Test Case

Over the past decade intrinsically disordered proteins (IDPs) have emerged as a biologically important class of proteins, many of which are of therapeutic relevance. Here, we investigated the interactions between a model IDP system, tau K18, and nine literature compounds that have been reported as having an effect on tau in order to identify a robust IDP–ligand system for the optimization of a range of biophysical methods. We used NMR, surface plasmon resonance (SPR) and microscale thermophoresis (MST) methods to investigate the binding of these compounds to tau K18; only one showed unambiguous interaction with tau K18. Several near neighbors of this compound were synthesized and their interactions with tau K18 characterized using additional NMR methods, including 1D ligand-observed NMR, diffusion-ordered spectroscopy (DOSY) and ¹⁹F NMR. This study demonstrates that it is possible to detect and characterize IDP–ligand interactions using biophysical methods. However, care must be taken to account for possible artefacts, particularly the impact of compound solubility and where the protein has to be immobilized.

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.