Targeting intrinsically disordered proteins at the edge of chaos

Proteasome activation: A novel strategy for targeting undruggable intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are characterized by their inability to adopt well-defined tertiary structures under physiological conditions. Nonetheless, they often play pivotal roles in the progression of various diseases, including cancer, neurodegenerative disorders, and cardiovascular ailments. Owing to their inherent dynamism, conventional drug design approaches based on structural considerations encounter substantial challenges when applied to IDPs. Consequently, the pursuit of therapeutic interventions directed towards IDPs presents a complex endeavor. While there are indeed existing methodologies for targeting IDPs, they are encumbered by noteworthy constrains. Hence, there exists an imminent imperative to investigate more efficacious and universally applicable strategies for modulating IDPs. Here, we present an overview of the latest advancements in the research pertaining to IDPs, along with the indirect regulation approach involving the modulation of IDP degradation through proteasome. By comprehending these advancements in research, novel insights can be generated to facilitate the development of new drugs targeted at addressing the accumulation of IDPs in diverse pathological conditions.

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.

Cucurbit[8]uril Binds Nonterminal Dipeptide Sites with High Affinity and Induces a Type II β-Turn

In an effort to target polypeptides at nonterminal sites, we screened the binding of the synthetic receptor cucurbit[8]uril (Q8) to a small library of tetrapeptides, each containing a nonterminal dipeptide binding site. The resulting leads were characterized in detail using a combination of isothermal titration calorimetry, 1H NMR spectroscopy, electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS), and X-ray crystallography. The equilibrium dissociation constant values determined for the binding of Q8 to nonterminal dipeptide sites Lys-Phe (KF) and Phe-Lys (FK) were 60 and 86 nm, respectively. These are to the best of our knowledge the highest affinities reported to date for any synthetic receptor targeting a nonterminal site on an unmodified peptide. A 0.79 Å resolution crystal structure was obtained for the complex of Q8 with the peptide Gly-Gly-Leu-Tyr-Gly-Gly-Gly (GGLYGGG) and reveals structural details of the pair-inclusion motif. The molecular basis for recognition is established to be the inclusion of the side chains of Leu and Tyr residues, as well as an extensive network of hydrogen bonds between the peptide backbone, the carbonyl oxygens of Q8, and proximal water molecules. In addition, the crystal structure reveals that Q8 induces a type II β-turn. The sequence-selectivity, high affinity, reversibility, and detailed structural characterization of this system should facilitate the development of applications involving ligand-induced polypeptide folding.

Intrinsic factors behind long COVID: IV. Hypothetical roles of the SARS-CoV-2 nucleocapsid protein and its liquid-liquid phase separation

When the SARS-CoV-2 virus infects humans, it leads to a condition called COVID-19 that has a wide spectrum of clinical manifestations, from no symptoms to acute respiratory distress syndrome. The virus initiates damage by attaching to the ACE-2 protein on the surface of endothelial cells that line the blood vessels and using these cells as hosts for replication. Reactive oxygen species levels are increased during viral replication, which leads to oxidative stress. About three-fifths (~60%) of the people who get infected with the virus eradicate it from their body after 28 days and recover their normal activity. However, a large fraction (~40%) of the people who are infected with the virus suffer from various symptoms (anosmia and/or ageusia, fatigue, cough, myalgia, cognitive impairment, insomnia, dyspnea, and tachycardia) beyond 12 weeks and are diagnosed with a syndrome called long COVID. Long-term clinical studies in a group of people who contracted SARS-CoV-2 have been contrasted with a noninfected matched group of people. A subset of infected people can be distinguished by a set of cytokine markers to have persistent, low-grade inflammation and often self-report two or more bothersome symptoms. No medication can alleviate their symptoms efficiently. Coronavirus nucleocapsid proteins have been investigated extensively as potential drug targets due to their key roles in virus replication, among which is their ability to bind their respective genomic RNAs for incorporation into emerging virions. This review highlights basic studies of the nucleocapsid protein and its ability to undergo liquid-liquid phase separation. We hypothesize that this ability of the nucleocapsid protein for phase separation may contribute to long COVID. This hypothesis unlocks new investigation angles and could potentially open novel avenues for a better understanding of long COVID and treating this condition.

A druggable conformational switch in the c-MYC transactivation domain

The c-MYC oncogene is activated in over 70% of all human cancers. The intrinsic disorder of the c-MYC transcription factor facilitates molecular interactions that regulate numerous biological pathways, but severely limits efforts to target its function for cancer therapy. Here, we use a reductionist strategy to characterize the dynamic and structural heterogeneity of the c-MYC protein. Using probe-based Molecular Dynamics (MD) simulations and machine learning, we identify a conformational switch in the c-MYC amino-terminal transactivation domain (termed coreMYC) that cycles between a closed, inactive, and an open, active conformation. Using the polyphenol epigallocatechin gallate (EGCG) to modulate the conformational landscape of coreMYC, we show through biophysical and cellular assays that the induction of a closed conformation impedes its interactions with the transformation/transcription domain-associated protein (TRRAP) and the TATA-box binding protein (TBP) which are essential for the transcriptional and oncogenic activities of c-MYC. Together, these findings provide insights into structure-activity relationships of c-MYC, which open avenues towards the development of shape-shifting compounds to target c-MYC as well as other disordered transcription factors for cancer treatment.

DisProt in 2024: improving function annotation of intrinsically disordered proteins

DisProt (URL: https://disprot.org) is the gold standard database for intrinsically disordered proteins and regions, providing valuable information about their functions. The latest version of DisProt brings significant advancements, including a broader representation of functions and an enhanced curation process. These improvements aim to increase both the quality of annotations and their coverage at the sequence level. Higher coverage has been achieved by adopting additional evidence codes. Quality of annotations has been improved by systematically applying Minimum Information About Disorder Experiments (MIADE) principles and reporting all the details of the experimental setup that could potentially influence the structural state of a protein. The DisProt database now includes new thematic datasets and has expanded the adoption of Gene Ontology terms, resulting in an extensive functional repertoire which is automatically propagated to UniProtKB. Finally, we show that DisProt's curated annotations strongly correlate with disorder predictions inferred from AlphaFold2 pLDDT (predicted Local Distance Difference Test) confidence scores. This comparison highlights the utility of DisProt in explaining apparent uncertainty of certain well-defined predicted structures, which often correspond to folding-upon-binding fragments. Overall, DisProt serves as a comprehensive resource, combining experimental evidence of disorder information to enhance our understanding of intrinsically disordered proteins and their functional implications.

Current and emerging approaches to noncompetitive AR inhibition

The androgen receptor (AR) has been shown to be a key determinant in the pathogenesis of castration-resistant prostate cancer (CRPC). The current standard of care therapies targets the ligand-binding domain of the receptor and can afford improvements to life expectancy often only in the order of months before resistance occurs. Emerging preclinical and clinical compounds that inhibit receptor activity via differentiated mechanisms of action which are orthogonal to current antiandrogens show promise for overcoming treatment resistance. In this review, we present an authoritative summary of molecules that noncompetitively target the AR. Emerging small molecule strategies for targeting alternative domains of the AR represent a promising area of research that shows significant potential for future therapies. The overall quality of lead candidates in the area of noncompetitive AR inhibition is discussed, and it identifies the key chemotypes and associated properties which are likely to be, or are currently, positioned to be first in human 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.

A New Tool to Study the Binding Behavior of Intrinsically Disordered Proteins

Understanding the binding behavior and conformational dynamics of intrinsically disordered proteins (IDPs) is crucial for unraveling their regulatory roles in biological processes. However, their lack of stable 3D structures poses challenges for analysis. To address this, we propose an algorithm that explores IDP binding behavior with protein complexes by extracting topological and geometric features from the protein surface model. Our algorithm identifies a geometrically favorable binding pose for the IDP and plans a feasible trajectory to evaluate its transition to the docking position. We focus on IDPs from Homo sapiens and Mus-musculus, investigating their interaction with the Plasmodium falciparum (PF) pathogen associated with malaria-related deaths. We compare our algorithm with HawkDock and HDOCK docking tools for quantitative (computation time) and qualitative (binding affinity) measures. Our results indicated that our method outperformed the compared methods in computation performance and binding affinity in experimental conformations.

Thermodynamic and kinetic approaches for drug discovery to target protein misfolding and aggregation

INTRODUCTION

Protein misfolding diseases, including Alzheimer's and Parkinson's diseases, are characterized by the aberrant aggregation of proteins. These conditions are still largely untreatable, despite having a major impact on our healthcare systems and societies.

AREAS COVERED

We describe drug discovery strategies to target protein misfolding and aggregation. We compare thermodynamic approaches, which are based on the stabilization of the native states of proteins, with kinetic approaches, which are based on the slowing down of the aggregation process. This comparison is carried out in terms of the current knowledge of the process of protein misfolding and aggregation, the mechanisms of disease and the therapeutic targets.

EXPERT OPINION

There is an unmet need for disease-modifying treatments that target protein misfolding and aggregation for the over 50 human disorders known to be associated with this phenomenon. With the approval of the first drugs that can prevent misfolding or inhibit aggregation, future efforts will be focused on the discovery of effective compounds with these mechanisms of action for a wide range of conditions.

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.

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.

The influence of random-coil chemical shifts on the assessment of structural propensities in folded proteins and IDPs

In studying secondary structural propensities of proteins by nuclear magnetic resonance (NMR) spectroscopy, secondary chemical shifts (SCSs) serve as the primary atomic scale observables. For SCS calculation, the selection of an appropriate random coil chemical shift (RCCS) dataset is a crucial step, especially when investigating intrinsically disordered proteins (IDPs). The scientific literature is abundant in such datasets, however, the effect of choosing one over all the others in a concrete application has not yet been studied thoroughly and systematically. Hereby, we review the available RCCS prediction methods and to compare them, we conduct statistical inference by means of the nonparametric sum of ranking differences and comparison of ranks to random numbers (SRD-CRRN) method. We try to find the RCCS predictors best representing the general consensus regarding secondary structural propensities. The existence and the magnitude of resulting differences on secondary structure determination under varying sample conditions (temperature, pH) are demonstrated and discussed for globular proteins and especially IDPs.

Dynamics-Based Regulatory Switches of Type II Antitoxins: Insights into New Antimicrobial Discovery

Type II toxin-antitoxin (TA) modules are prevalent in prokaryotes and are involved in cell maintenance and survival under harsh environmental conditions, including nutrient deficiency, antibiotic treatment, and human immune responses. Typically, the type II TA system consists of two protein components: a toxin that inhibits an essential cellular process and an antitoxin that neutralizes its toxicity. Antitoxins of type II TA modules typically contain the structured DNA-binding domain responsible for TA transcription repression and an intrinsically disordered region (IDR) at the C-terminus that directly binds to and neutralizes the toxin. Recently accumulated data have suggested that the antitoxin's IDRs exhibit variable degrees of preexisting helical conformations that stabilize upon binding to the corresponding toxin or operator DNA and function as a central hub in regulatory protein interaction networks of the type II TA system. However, the biological and pathogenic functions of the antitoxin's IDRs have not been well discussed compared with those of IDRs from the eukaryotic proteome. Here, we focus on the current state of knowledge about the versatile roles of IDRs of type II antitoxins in TA regulation and provide insights into the discovery of new antibiotic candidates that induce toxin activation/reactivation and cell death by modulating the regulatory dynamics or allostery of the antitoxin.

Intrinsic disorder in the open reading frame 2 of hepatitis E virus: a protein with multiple functions beyond viral capsid

BACKGROUND

Hepatitis E virus (HEV) is the cause of a liver disease hepatitis E. The translation product of HEV ORF2 has recently been demonstrated as a protein involved in multiple functions besides performing its major role of a viral capsid. As intrinsically disordered regions (IDRs) are linked to various essential roles in the virus's life cycle, we analyzed the disorder pattern distribution of the retrieved ORF2 protein sequences by employing different online predictors. Our findings might provide some clues on the disorder-based functions of ORF2 protein that possibly help us in understanding its behavior other than as a HEV capsid protein.

RESULTS

The modeled three dimensional (3D) structures of ORF2 showed the predominance of random coils or unstructured regions in addition to major secondary structure components (alpha helix and beta strand). After initial scrutinization, the predictors VLXT and VSL2 predicted ORF2 as a highly disordered protein while the predictors VL3 and DISOPRED3 predicted ORF2 as a moderately disordered protein, thus categorizing HEV-ORF2 into IDP (intrinsically disordered protein) or IDPR (intrinsically disordered protein region) respectively. Thus, our initial predicted disorderness in ORF2 protein 3D structures was in excellent agreement with their predicted disorder distribution patterns (evaluated through different predictors). The abundance of MoRFs (disorder-based protein binding sites) in ORF2 was observed that signified their interaction with binding partners which might further assist in viral infection. As IDPs/IDPRs are targets of regulation, we carried out the phosphorylation analysis to reveal the presence of post-translationally modified sites. Prevalence of several disordered-based phosphorylation sites further signified the involvement of ORF2 in diverse and significant biological processes. Furthermore, ORF2 structure-associated functions revealed its involvement in several crucial functions and biological processes like binding and catalytic activities.

CONCLUSIONS

The results predicted ORF2 as a protein with multiple functions besides its role as a capsid protein. Moreover, the occurrence of IDPR/IDP in ORF2 protein suggests that its disordered region might serve as novel drug targets via functioning as potential interacting domains. Our data collectively might provide significant implication in HEV vaccine search as disorderness in viral proteins is related to mechanisms involved in immune evasion.

A central chaperone-like role for 14-3-3 proteins in human cells

14-3-3 proteins are highly conserved regulatory proteins that interact with hundreds of structurally diverse clients and act as central hubs of signaling networks. However, how 14-3-3 paralogs differ in specificity and how they regulate client protein function are not known for most clients. Here, we map the interactomes of all human 14-3-3 paralogs and systematically characterize the effect of disrupting these interactions on client localization. The loss of 14-3-3 binding leads to the coalescence of a large fraction of clients into discrete foci in a client-specific manner, suggesting a central chaperone-like function for 14-3-3 proteins. Congruently, the engraftment of 14-3-3 binding motifs to nonclients can suppress their aggregation or phase separation. Finally, we show that 14-3-3s negatively regulate the localization of the RNA-binding protein SAMD4A to cytoplasmic granules and inhibit its activity as a translational repressor. Our work suggests that 14-3-3s have a more prominent role as chaperone-like molecules than previously thought.

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.

Models versus pathogens: how conserved is the FtsZ in bacteria?

Combating anti-microbial resistance by developing alternative strategies is the need of the hour. Cell division, particularly FtsZ, is being extensively studied for its potential as an alternative target for anti-bacterial therapy. Bacillus subtilis and Escherichia coli are the two well-studied models for research on FtsZ, the leader protein of the cell division machinery. As representatives of gram-positive and gram-negative bacteria, respectively, these organisms have provided an extensive outlook into the process of cell division in rod-shaped bacteria. However, research on other shapes of bacteria, like cocci and ovococci, lags behind that of model rods. Even though most regions of FtsZ show sequence and structural conservation throughout bacteria, the differences in FtsZ functioning and interacting partners establish several different modes of division in different bacteria. In this review, we compare the features of FtsZ and cell division in the model rods B. subtilis and E. coli and the four pathogens: Staphylococcus aureus, Streptococcus pneumoniae, Mycobacterium tuberculosis, and Pseudomonas aeruginosa. Reviewing several recent articles on these pathogenic bacteria, we have highlighted the functioning of FtsZ, the unique roles of FtsZ-associated proteins, and the cell division processes in them. Further, we provide a detailed look at the anti-FtsZ compounds discovered and their target bacteria, emphasizing the need for elucidation of the anti-FtsZ mechanism of action in different bacteria. Current challenges and opportunities in the ongoing journey of identifying potent anti-FtsZ drugs have also been described.

High-affinity binding of celastrol to monomeric α-synuclein mitigates in vitro aggregation

α-Synuclein (αSyn) aggregation is associated with Parkinson's disease (PD). The region αSyn36-42 acts as the nucleation 'master controller' and αSyn1-12 as a 'secondary nucleation site'. They drive monomeric αSyn to aggregation. Small molecules targeting these motifs are promising for disease-modifying therapy. Using computational techniques, we screened thirty phytochemicals for αSyn binding. The top three compounds were experimentally validated for their binding affinity. Amongst them, celastrol showed high binding affinity. NMR analysis confirmed stable αSyn-celastrol interactions involving several residues in the N-terminus and NAC regions but not in the C-terminal tail. Importantly, celastrol interacted extensively with the key motifs that drive αSyn aggregation. Thioflavin-T assay indicated that celastrol reduced αSyn aggregation. Thus, celastrol holds promise as a potent drug candidate for PD.Communicated by Ramaswamy H. Sarma.

Liquid-liquid phase separation of nucleocapsid proteins during SARS-CoV-2 and HIV-1 replication

The leap of retroviruses and coronaviruses from animal hosts to humans has led to two ongoing pandemics and tens of millions of deaths worldwide. Retrovirus and coronavirus nucleocapsid proteins have been studied extensively as potential drug targets due to their central roles in virus replication, among which is their capacity to bind their respective genomic RNAs for packaging into nascent virions. This review focuses on fundamental studies of these nucleocapsid proteins and how their intrinsic abilities to condense through liquid-liquid phase separation (LLPS) contribute to viral replication. Therapeutic targeting of these condensates and methodological advances are also described to address future questions on how phase separation contributes to viral replication.

Therapeutic targeting of TEAD transcription factors in cancer

The Hippo signaling pathway inhibits the activity of the oncogenic YAP (Yes-associated protein)/TAZ (transcriptional co-activator with PDZ-binding motif)-TEAD (TEA/ATTS domain) transcriptional complex. In cancers, inactivating mutations in upstream Hippo components and/or enhanced activity of YAP/TAZ and TEAD have been observed. The activity of this transcriptional complex can be effectively inhibited by targeting the TEAD family of transcription factors. The development of TEAD inhibitors has been driven by the discovery that TEAD has druggable hydrophobic pockets, and is currently at the clinical development stage. Three small molecule TEAD inhibitors are currently being tested in Phase I clinical trials. In this review, we highlight the role of TEADs in cancer, discuss various avenues through which TEAD activity can be inhibited, and outline the opportunities for the administration of TEAD inhibitors.

Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling

The cardiac sarcomere is a cellular structure in the heart that enables muscle cells to contract. Dozens of proteins belong to the cardiac sarcomere, which work in tandem to generate force and adapt to demands on cardiac output. Intriguingly, the majority of these proteins have significant intrinsic disorder that contributes to their functions, yet the biophysics of these intrinsically disordered regions (IDRs) have been characterized in limited detail. In this review, we first enumerate these myofilament-associated proteins with intrinsic disorder (MAPIDs) and recent biophysical studies to characterize their IDRs. We secondly summarize the biophysics governing IDR properties and the state-of-the-art in computational tools toward MAPID identification and characterization of their conformation ensembles. We conclude with an overview of future computational approaches toward broadening the understanding of intrinsic disorder in the cardiac sarcomere.

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.

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.

Anchor Residues Govern Binding and Folding of an Intrinsically Disordered Domain

Minimal protein mimics have yielded novel classes of protein-protein interaction inhibitors; however, this success has not been extended to targeting intrinsically disordered proteins, which represent a significant proportion of important therapeutic targets. We sought to determine the requirements for binding an intrinsically disordered region (IDR) by its native binding partner as a prelude to developing minimal protein mimics that regulate IDR interactions. Our analysis reinforces the hypothesis that IDRs reside on a fulcrum between unfolded and folded states and that a handful of key binding residues on partner protein surfaces dictate their folding. Our studies also suggest that minimal mimics of protein surfaces may not offer specific ligands for IDRs and that it would be more judicious to target the globular protein partners of IDRs.

The evolution and polymorphism of mono-amino acid repeats in androgen receptor and their regulatory role in health and disease

Androgen receptor (AR) is a key member of nuclear hormone receptors with the longest intrinsically disordered N-terminal domain (NTD) in its protein family. There are four mono-amino acid repeats (polyQ1, polyQ2, polyG, and polyP) located within its NTD, of which two are polymorphic (polyQ1 and polyG). The length of both polymorphic repeats shows clinically important correlations with disease, especially with cancer and neurodegenerative diseases, as shorter and longer alleles exhibit significant differences in expression, activity and solubility. Importantly, AR has also been shown to undergo condensation in the nucleus by liquid-liquid phase separation, a process highly sensitive to protein solubility and concentration. Nonetheless, in prostate cancer cells, AR variants also partition into transcriptional condensates, which have been shown to alter the expression of target gene products. In this review, we summarize current knowledge on the link between AR repeat polymorphisms and cancer types, including mechanistic explanations and models comprising the relationship between condensate formation, polyQ1 length and transcriptional activity. Moreover, we outline the evolutionary paths of these recently evolved amino acid repeats across mammalian species, and discuss new research directions with potential breakthroughs and controversies in the literature.

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.

AlphaFold, Artificial Intelligence (AI), and Allostery

AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises an untold number of applications with vast potential impacts that are still difficult to surmise. AI approaches can revolutionize personalized treatments and usher in better-informed clinical trials. They promise to make giant leaps toward reshaping and revamping drug discovery strategies, selecting and prioritizing combinations of drug targets. Here, we briefly overview AI in structural biology, including in molecular dynamics simulations and prediction of microbiota–human protein–protein interactions. We highlight the advancements accomplished by the deep-learning-powered AlphaFold in protein structure prediction and their powerful impact on the life sciences. At the same time, AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways. The models that AlphaFold provides do not capture conformational mechanisms like frustration and allostery, which are rooted in ensembles, and controlled by their dynamic distributions. Allostery and signaling are properties of populations. AlphaFold also does not generate ensembles of intrinsically disordered proteins and regions, instead describing them by their low structural probabilities. Since AlphaFold generates single ranked structures, rather than conformational ensembles, it cannot elucidate the mechanisms of allosteric activating driver hotspot mutations nor of allosteric drug resistance. However, by capturing key features, deep learning techniques can use the single predicted conformation as the basis for generating a diverse ensemble.

AlphaFold illuminates half of the dark human proteins

We investigate the use of confidence scores to evaluate the accuracy of a given AlphaFold (AF2) protein model for drug discovery. Prediction of accuracy is improved by not considering confidence scores below 80 due to the effects of disorder. On a set of recent crystal structures, 95% are likely to have accurate folds. Conformational discordance in the training set has a much more significant effect on accuracy than sequence divergence. We propose criteria for models and residues that are possibly useful for virtual screening. Based on these criteria, AF2 provides models for half of understudied (dark) human proteins and two-thirds of residues in those models.

Energetics of a protein disorder-order transition in small molecule recognition

Many proteins recognise other proteins via mechanisms that involve the folding of intrinsically disordered regions upon complex formation. Here we investigate how the selectivity of a drug-like small molecule arises from its modulation of a protein disorder-to-order transition. Binding of the compound AM-7209 has been reported to confer order upon an intrinsically disordered ‘lid’ region of the oncoprotein MDM2. Calorimetric measurements revealed that truncation of the lid region of MDM2 increases the apparent dissociation constant of AM-7209 250-fold. By contrast, lid truncation has little effect on the binding of the ligand Nutlin-3a. Insights into these differential binding energetics were obtained via a complete thermodynamic analysis that featured adaptive absolute alchemical free energy of binding calculations with enhanced-sampling molecular dynamics simulations. The simulations reveal that in apo MDM2 the ordered lid state is energetically disfavoured. AM-7209, but not Nutlin-3a, shows a significant energetic preference for ordered lid conformations, thus shifting the balance towards ordering of the lid in the AM-7209/MDM2 complex. The methodology reported herein should facilitate broader targeting of intrinsically disordered regions in medicinal chemistry.

Molecular simulations and biophysical measurements elucidate why the ligand AM-7209 orders a disordered region of the protein MDM2 on binding. This work expands strategies available to medicinal chemists for targeting disordered proteins.

Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy

Intrinsically disordered proteins lack a stable tertiary structure and form dynamic conformational ensembles due to their characteristic physicochemical properties and amino acid composition. They are abundant in nature and responsible for a large variety of cellular functions. While numerous bioinformatics tools have been developed for in silico disorder prediction in the last decades, there is a need for experimental methods to verify the disordered state. CD spectroscopy is widely used for protein secondary structure analysis. It is usable in a wide concentration range under various buffer conditions. Even without providing high-resolution information, it is especially useful when NMR, X-ray, or other techniques are problematic or one simply needs a fast technique to verify the structure of proteins. Here, we propose an automatized binary disorder–order classification method by analyzing far-UV CD spectroscopy data. The method needs CD data at only three wavelength points, making high-throughput data collection possible. The mathematical analysis applies the k-nearest neighbor algorithm with cosine distance function, which is independent of the spectral amplitude and thus free of concentration determination errors. Moreover, the method can be used even for strong absorbing samples, such as the case of crowded environmental conditions, if the spectrum can be recorded down to the wavelength of 212 nm. We believe the classification method will be useful in identifying disorder and will also facilitate the growth of experimental data in IDP databases. The method is implemented on a webserver and freely available for academic users.

Investigating the disordered regions (MoRFs, SLiMs and LCRs) and functions of mimicry proteins/peptides in silico

Microbial mimicry of the host proteins/peptides can elicit host auto-reactive T- or B-cells resulting in autoimmune disease(s). Since intrinsically disordered protein regions (IDPRs) are involved in several host cell signaling and PPI networks, molecular mimicry of the IDPRs can help the pathogens in substituting their own proteins in the host cell-signaling and PPI networks and, ultimately hijacking the host cellular machinery. Thus, the present study was conducted to discern the structural disorder and intrinsically disordered protein regions (IDPRs) like, molecular recognition features (MoRFs), short linear motifs (SLiMs), and low complexity regions (LCRs) in the experimentally verified mimicry proteins and peptides (mimitopes) of bacteria, viruses and host. Also, functional characteristics of the mimicry proteins were studied in silico. Our results indicated that 78% of the bacterial host mimicry proteins and 45% of the bacterial host mimitopes were moderately/highly disordered while, 73% of the viral host mimicry proteins and 31% of the viral host mimitopes were moderately/highly disordered. Among the pathogens, 27% of the bacterial mimicry proteins and 13% of the bacterial mimitopes were moderately/highly disordered while, 53% of the viral mimicry proteins and 21% of the viral mimitopes were moderately/highly disordered. Though IDPR were frequent in host, bacterial and viral mimicry proteins, only a few mimitopes overlapped with the IDPRs like, MoRFs, SLiMs and LCRs. This suggests that most of the microbes cannot use molecular mimicry to modulate the host PPIs and hijack the host cell machinery. Functional analyses indicated that most of the pathogens exhibited mimicry with the host proteins involved in ion binding and signaling pathways. This is the first report on the disordered regions and functional aspects of experimentally proven host and microbial mimicry proteins.

E3 ligase ligand chemistries: from building blocks to protein degraders

In recent years, proteolysis-targeting chimeras (PROTACs), capable of achieving targeted protein degradation, have proven their great therapeutic potential and usefulness as molecular biology tools. These heterobifunctional compounds are comprised of a protein-targeting ligand, an appropriate linker, and a ligand binding to the E3 ligase of choice. A successful PROTAC induces the formation of a ternary complex, leading to the E3 ligase-mediated ubiquitination of the targeted protein and its proteasomal degradation. In over 20 years since the concept was first demonstrated, the field has grown substantially, mainly due to the advancements in the discovery of non-peptidic E3 ligase ligands. Development of small-molecule E3 binders with favourable physicochemical profiles aided the design of PROTACs, which are known for breaking the rules of established guidelines for discovering small molecules. Synthetic accessibility of the ligands and numerous successful applications led to the prevalent use of cereblon and von Hippel-Lindau as the hijacked E3 ligase. However, the pool of over 600 human E3 ligases is full of untapped potential, which is why expanding the artillery of E3 ligands could contribute to broadening the scope of targeted protein degradation. In this comprehensive review, we focus on the chemistry aspect of the PROTAC design process by providing an overview of liganded E3 ligases, their chemistries, appropriate derivatisation, and synthetic approaches towards their incorporation into heterobifunctional degraders. By covering syntheses of both established and underexploited E3 ligases, this review can serve as a chemistry blueprint for PROTAC researchers during their future ventures into the complex field of targeted protein degradation.

Targeting key proteins involved in transcriptional regulation for cancer therapy: Current strategies and future prospective

The key proteins involved in transcriptional regulation play convergent roles in cellular homeostasis, and their dysfunction mediates aberrant gene expressions that underline the hallmarks of tumorigenesis. As tumor progression is dependent on such abnormal regulation of transcription, it is important to discover novel chemical entities as antitumor drugs that target key tumor-associated proteins involved in transcriptional regulation. Despite most key proteins (especially transcription factors) involved in transcriptional regulation are historically recognized as undruggable targets, multiple targeting approaches at diverse levels of transcriptional regulation, such as epigenetic intervention, inhibition of DNA-binding of transcriptional factors, and inhibition of the protein-protein interactions (PPIs), have been established in preclinically or clinically studies. In addition, several new approaches have recently been described, such as targeting proteasomal degradation and eliciting synthetic lethality. This review will emphasize on accentuating these developing therapeutic approaches and provide a thorough conspectus of the drug development to target key proteins involved in transcriptional regulation and their impact on future oncotherapy.

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.

A FRET-Based Biosensor for the Src N-Terminal Regulatory Element

In signaling proteins, intrinsically disordered regions often represent regulatory elements, which are sensitive to environmental effects, ligand binding, and post-translational modifications. The conformational space sampled by disordered regions can be affected by environmental stimuli and these changes trigger, vis a vis effector domain, downstream processes. The disordered nature of these regulatory elements enables signal integration and graded responses but prevents the application of classical approaches for drug screening based on the existence of a fixed three-dimensional structure. We have designed a genetically encodable biosensor for the N-terminal regulatory element of the c-Src kinase, the first discovered protooncogene and lead representative of the Src family of kinases. The biosensor is formed by two fluorescent proteins forming a FRET pair fused at the two extremes of a construct including the SH4, unique and SH3 domains of Src. An internal control is provided by an engineered proteolytic site allowing the generation of an identical mixture of the disconnected fluorophores. We show FRET variations induced by ligand binding. The biosensor has been used for a high-throughput screening of a library of 1669 compounds with seven hits confirmed by NMR.

DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation

The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure.

[Development of peptide binder design method for disease-related phase separation proteins]

Neurodegenerative diseases such as dementia and Alzheimer's disease are caused by liquid-liquid phase separation (LLPS) proteins. LLPS is a phenomenon in which a dense liquid phase of proteins is formed in a liquid phase in which proteins are dispersed at a low concentration. The concentrated proteins enable highly efficient chemical reactions, but at the same time, there is a risk of forming insoluble aggregates that cause diseases. In fact, neurodegenerative disease-related proteins form insoluble aggregates, which cause great damage to nerves, resulting in memory and motor disorders. Drug discovery requires the design of drug candidates that can strongly bind to the intrinsically disordered region of a phase-separated protein and control the phase-separated state. This paper mainly introduces our research on peptide design that binds to phase-separated proteins. For peptide drug discovery, it is necessary to efficiently search for drug candidates among a huge number of peptides. As an efficient search method for peptides that control phase-separated proteins, we searched for amino acids that can control liquid-liquid phase separation, and devised a method for designing peptides containing effective amino acids. It was demonstrated that this method can be used to control the LLPS and solid aggregate formation of the neurodegenerative disease-related protein FUS. Furthermore, we devised a method for rationally designing a peptide that binds complementarily to the intrinsically disordered region of the target, and demonstrated the functional control of the cancer disease-related protein p53. Finally, we discuss the possibility of peptide drug discovery for disease-related LLPS proteins.

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.

Design of Inhibitors of the Intrinsically Disordered Protein NUPR1: Balance between Drug Affinity and Target Function

Intrinsically disordered proteins (IDPs) are emerging as attractive drug targets by virtue of their physiological ubiquity and their prevalence in various diseases, including cancer. NUPR1 is an IDP that localizes throughout the whole cell, and is involved in the development and progression of several tumors. We have previously repurposed trifluoperazine (TFP) as a drug targeting NUPR1 and, by using a ligand-based approach, designed the drug ZZW-115 starting from the TFP scaffold. Such derivative compound hinders the development of pancreatic ductal adenocarcinoma (PDAC) in mice, by hampering nuclear translocation of NUPR1. Aiming to further improve the activity of ZZW-115, here we have used an indirect drug design approach to modify its chemical features, by changing the substituent attached to the piperazine ring. As a result, we have synthesized a series of compounds based on the same chemical scaffold. Isothermal titration calorimetry (ITC) showed that, with the exception of the compound preserving the same chemical moiety at the end of the alkyl chain as ZZW-115, an increase of the length by a single methylene group (i.e., ethyl to propyl) significantly decreased the affinity towards NUPR1 measured in vitro, whereas maintaining the same length of the alkyl chain and adding heterocycles favored the binding affinity. However, small improvements of the compound affinity towards NUPR1, as measured by ITC, did not result in a corresponding improvement in their inhibitory properties and in cellulo functions, as proved by measuring three different biological effects: hindrance of the nuclear translocation of the protein, sensitization of cells against DNA damage mediated by NUPR1, and prevention of cancer cell growth. Our findings suggest that a delicate compromise between favoring ligand affinity and controlling protein function may be required to successfully design drugs against NUPR1, and likely other IDPs.

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.

Folding and self-assembly of short intrinsically disordered peptides and protein regions

Proteins and peptide fragments are highly relevant building blocks in self-assembly for nanostructures with plenty of applications. Intrinsically disordered proteins (IDPs) and protein regions (IDRs) are defined by the absence of a well-defined secondary structure, yet IDPs/IDRs show a significant biological activity. Experimental techniques and computational modelling procedures for the characterization of IDPs/IDRs are discussed. Directed self-assembly of IDPs/IDRs allows reaching a large variety of nanostructures. Hybrid materials based on the derivatives of IDPs/IDRs show a promising performance as alternative biocides and nanodrugs. Cell mimicking, in vivo compartmentalization, and bone regeneration are demonstrated for IDPs/IDRs in biotechnological applications. The exciting possibilities of IDPs/IDRs in nanotechnology with relevant biological applications are shown.

Intrinsically disordered proteins and biomolecular condensates as drug targets

Intrinsically disordered domains represent attractive therapeutic targets because they play key roles in cancer, as well as in neurodegenerative and infectious diseases. They are, however, considered undruggable because they do not form stable binding pockets for small molecules and, therefore, have not been prioritized in drug discovery. Under physiological solution conditions many biomedically relevant intrinsically disordered proteins undergo phase separation processes leading to the formation of mesoscopic highly dynamic assemblies, generally known as biomolecular condensates that define environments that can be quite different from the solutions surrounding them. In what follows, we review key recent findings in this area and show how biomolecular condensation can offer opportunities for modulating the activities of intrinsically disordered targets.

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.

Structural and dynamic characterization of the C-terminal tail of ErbB2: Disordered but not random

ErbB2 (or HER2) is a receptor tyrosine kinase overexpressed in some breast cancers and associated with poor prognosis. Treatments targeting the receptor extracellular and kinase domains have greatly improved disease outcome in the last 20 years. In parallel, the structures of these domains have been described, enabling better mechanistic understanding of the receptor function and targeted inhibition. However, the ErbB2 disordered C-terminal cytoplasmic tail (CtErbB2) remains very poorly characterized in terms of structure, dynamics, and detailed functional mechanism. Yet, it is where signal transduction is triggered via phosphorylation of tyrosine residues and carried out via interaction with adaptor proteins. Here, we report the first description, to our knowledge, of the ErbB2 disordered tail at atomic resolution using NMR, complemented by small-angle x-ray scattering. We show that although no part of CtErbB2 has any fully populated secondary or tertiary structure, it contains several transient α-helices and numerous transient polyproline II helices, populated up to 20 and 40%, respectively, and low but significant compaction. The presence of some structural elements suggests, along the lines of the results obtained for EGFR (ErbB1), that they may have a functional role in ErbB2's autoregulation processes. In addition, the transient formation of polyproline II helices is compliant with previously suggested interactions with SH3 domains. All in all, our in-depth structural study opens perspectives in the mechanistic understanding of ErbB2.

IDRMutPred: predicting disease-associated germline nonsynonymous single nucleotide variants (nsSNVs) in intrinsically disordered regions

Motivation

Despite of the lack of folded structure, intrinsically disordered regions (IDRs) of proteins play versatile roles in various biological processes, and many nonsynonymous single nucleotide variants (nsSNVs) in IDRs are associated with human diseases. The continuous accumulation of nsSNVs resulted from the wide application of NGS has driven the development of disease-association prediction methods for decades. However, their performance on nsSNVs in IDRs remains inferior, possibly due to the domination of nsSNVs from structured regions in training data. Therefore, it is highly demanding to build a disease-association predictor specifically for nsSNVs in IDRs with better performance.

Results

We present IDRMutPred, a machine learning-based tool specifically for predicting disease-associated germline nsSNVs in IDRs. Based on 17 selected optimal features that are extracted from sequence alignments, protein annotations, hydrophobicity indices and disorder scores, IDRMutPred was trained using three ensemble learning algorithms on the training dataset containing only IDR nsSNVs. The evaluation on the two testing datasets shows that all the three prediction models outperform 17 other popular general predictors significantly, achieving the ACC between 0.856 and 0.868 and MCC between 0.713 and 0.737. IDRMutPred will prioritize disease-associated IDR germline nsSNVs more reliably than general predictors.

Availability and implementation

The software is freely available at http://www.wdspdb.com/IDRMutPred.

Supplementary information

Supplementary data are available at Bioinformatics online.

The structure and phase of tau: from monomer to amyloid filament

Tau is a microtubule-associated protein involved in regulation of assembly and spatial organization of microtubule in neurons. However, in pathological conditions, tau monomers assemble into amyloid filaments characterized by the cross-β structures in a number of neurodegenerative diseases known as tauopathies. In this review, we summarize recent progression on the characterization of structures of tau monomer and filament, as well as the dynamic liquid droplet assembly. Our aim is to reveal how post-translational modifications, amino acid mutations, and interacting molecules modulate the conformational ensemble of tau monomer, and how they accelerate or inhibit tau assembly into aggregates. Structure-based aggregation inhibitor design is also discussed in the context of dynamics and heterogeneity of tau structures.

Current and Future Challenges in Modern Drug Discovery

Drug discovery is an expensive, time-consuming, and risky business. To avoid late-stage failure, learnings from past projects and the development of new approaches are crucial. New modalities and emerging new target spaces allow the exploration of unprecedented indications or to address so far undrugable targets. Late-stage attrition is usually attributed to the lack of efficacy or to compound-related safety issues. Efficacy has been shown to be related to a strong genetic link to human disease, a better understanding of the target biology, and the availability of biomarkers to bridge from animals to humans. Compound safety can be improved by ligand optimization, which is becoming increasingly demanding for difficult targets. Therefore, new strategies include the design of allosteric ligands, covalent binders, and other modalities. Design methods currently heavily rely on artificial intelligence and advanced computational methods such as free energy calculations and quantum chemistry. Especially for quantum chemical methods, a more detailed overview is given in this chapter.