Biology subjects

Robustelli, P.

Publications and source records attributed to Robustelli, P..

12 recordsLinked to original sources

bioRxiv2025

How small molecules stabilize oligomers of a phase-separating disordered protein

Small molecule inhibitors of the intrinsically disordered androgen receptor activation domain have been tested in clinical trials for the treatment of castration-resistant prostate cancer. These compounds have been shown to stabilize oligomeric forms of the androgen receptor activation domain in solution and alter the properties of androgen receptor condensates. The molecular mechanisms by which small molecules modulate these processes have been poorly understood in atomic detail. Here, we use long-timescale all-atom molecular dynamics (MD) simulations and nuclear magnetic resonance (NMR) spectroscopy to determine how small molecules stabilize highly dynamic, heterogeneous intermolecular interfaces that mediate oligomerization of the androgen receptor activation domain. The mechanisms determined here explain the relative potencies of androgen receptor activation domain inhibitors and suggest general strategies for designing small molecules that target oligomeric and, potentially, condensed forms of intrinsically disordered proteins.

biophysics↗

bioRxiv2025

Monomer binding modes of small molecules that modulate the kinetics of hIAPP amyloid formation

Human islet amyloid polypeptide (hIAPP) forms amyloid fibrils that accumulate in pancreatic {beta}-cells of Type II Diabetes (T2D) patients. Recently discovered small molecules that modulate the kinetics of hIAPP amyloid formation could serve as starting points for developing T2D therapeutics, but no structural or mechanistic rationale exists to explain their binding mechanisms or effects on hIAPP aggregation pathways. Here, we utilize all-atom molecular dynamics computer simulations to elucidate the binding mechanisms of an hIAPP aggregation inhibitor (YX-I-1) and an aggregation accelerator (YX-A-1) to disordered monomers of wild-type hIAPP and the naturally occurring pathogenic S20G hIAPP variant associated with early-onset T2D. We observe that the inhibitor exhibits substantially higher affinity for monomeric wild-type hIAPP than the accelerator, consistent with previously reported biophysical experiments. We dissect the interactions that stabilize binding of each molecule to wild-type and S20G hIAPP and characterize conformational changes that occur upon ligand binding. In all ligand-bound ensembles, distinct fragments of YX-I-1 and YX-A-1 are sequestered from solvent upon binding while other fragments remain solvent-exposed. Based on our simulations we hypothesize that buried ligand moieties confer hIAPP monomer binding affinity while solvent-exposed ligand moieties modulate the kinetics of intermolecular association of bound hIAPP into higher-order oligomeric intermediates on amyloid aggregation pathways.

biophysics↗

bioRxiv2025

Characterizing structural and kinetic ensembles of intrinsically disordered proteins using writhe

The biological functions of intrinsically disordered proteins (IDPs) are governed by the conformational states they adopt in solution and the kinetics of transitions between these states. We apply writhe, a knot-theoretic measure that quantifies the crossings of curves in three-dimensional space, to analyze the conformational ensembles and dynamics of IDPs. We develop multiscale descriptors of protein backbones from writhe to identify slow motions of IDPs and demonstrate that these descriptors provide a superior basis for constructing Markov state models of IDP conformational dynamics compared to traditional distance-based descriptors. Additionally, we leverage the symmetry properties of writhe to design an equivariant neural network architecture to sample conformational ensembles of IDPs with a denoising diffusion probabilistic model. The writhe-based frameworks presented here provide a powerful and versatile approach for understanding how the structural ensembles and conformational dynamics of IDPs influence their biological functions. Significance StatementIntrinsically disordered proteins (IDPs) are essential for many cellular processes and are implicated in numerous diseases. The biological functions of IDPs are dictated by the populations of the diverse conformational states they adopt in solution and the kinetics of the conformational transitions between these states. Computer simulations are a powerful tool for studying IDPs, but analyzing simulated structural ensembles of IDPs to identify functionally important conformational states and motions remains a significant challenge. In this study, we demonstrate that writhe, a geometric descriptor from the field of knot theory that describes the crossing of curves in space, provides a powerful basis for characterizing the structural ensembles and conformational dynamics of IDPs in atomic detail. Our results provide new tools for unraveling the relationships between IDP sequences, their conformational ensembles, and their biological functions.

biophysics↗

bioRxiv2025

Ensemble docking for intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are implicated in many human diseases and are increasingly being pursued as drug targets. Conventional structure-based drug design methods that rely on well-defined binding sites are however, largely unsuitable for IDPs. Here, we present computationally efficient ensemble docking approaches to predict the relative affinities of small molecules to IDPs and characterize their dynamic, heterogenous binding mechanisms at atomic resolution. We demonstrate that these ensemble docking protocols accurately predict the relative binding affinities of small molecule -synuclein ligands measured by NMR spectroscopy and generate conformational ensembles of ligand binding modes in remarkable agreement with experimentally validated long-timescale molecular dynamics simulations. Our results display the potential of ensemble docking approaches for predicting small molecule binding to IDPs and suggest that these methods may be valuable tools for IDP drug discovery campaigns.

biophysics↗

bioRxiv2024

Covalent adducts formed by the androgen receptor transactivation domain and small molecule drugs remain disordered

Intrinsically disordered proteins are implicated in many human diseases. Small molecules that target the disordered androgen receptor transactivation domain have entered human trials for the treatment of castration-resistant prostate cancer. These molecules have been shown to react with cysteine residues of the androgen receptor transactivation domain and form covalent adducts under physiological conditions. It is currently unclear how covalent attachment of these molecules alters the conformational ensemble of the androgen receptor. Here, we utilize all-atom molecular dynamics computer simulations to simulate covalent adducts of the small molecule ligands EPI-002 and EPI-7170 bound to the disordered androgen receptor transactivation domain. Our simulations reveal that the conformational ensembles of androgen receptor transactivation domain covalent adducts are heterogeneous and disordered. We find that covalent attachment of EPI-002 and EPI-7170 increases the population of collapsed helical transactivation domain conformations relative to the populations observed in non-covalent binding simulations and we identify networks of protein-ligand interactions that stabilize collapsed conformations in covalent adduct ensembles. We compare the populations of protein-ligand interactions observed in covalent adduct ensembles to those observed in non-covalent ligand-bound ensembles and find substantial differences. Our results provide atomically detailed descriptions of covalent adducts formed by small molecules and an intrinsically disordered protein and suggest strategies for developing more potent covalent inhibitors of intrinsically disordered proteins.

biophysics↗

bioRxiv2024

Towards accurate, force field independent conformational ensembles of intrinsically disordered proteins

Determining accurate atomic resolution conformational ensembles of intrinsically disordered proteins (IDPs) is extremely challenging. Molecular dynamics (MD) simulations provide atomistic conformational ensembles of IDPs, but their accuracy is highly dependent on the quality of physical models, or force fields, used. Here, we demonstrate how to determine accurate atomic resolution conformational ensembles of IDPs by integrating all-atom MD simulations with experimental data from nuclear magnetic resonance (NMR) spectroscopy and small-angle x-ray scattering (SAXS) with a simple, robust and fully automated maximum entropy reweighting procedure. We demonstrate that when this approach is applied with sufficient experimental data, IDP ensembles derived from different MD force fields converge to highly similar conformational distributions. The maximum entropy reweighting procedure presented here facilitates the integration of MD simulations with extensive experimental datasets and enables the calculation of accurate, force-field independent atomic resolution conformational ensembles of IDPs.

biophysics↗

bioRxiv2023

Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model

A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long-time scale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We do not, however, find evidence for the existence of canonical conformational selection or induced fit binding pathways. We observe four kinetically separated native-like bound states that interconvert on time scales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.

biophysics↗

bioRxiv2022

Clustering conformational ensembles of intrinsically disordered proteins with t-distributed stochastic neighbor embedding

Intrinsically disordered proteins (IDPs) populate a range of conformations that are best described by a heterogeneous ensemble. Grouping an IDP ensemble into "structurally similar" clusters for visualization, interpretation, and analysis purposes is a much-desired but formidable task as the conformational space of IDPs is inherently high-dimensional and reduction techniques often result in ambiguous classifications. Here, we employ the t-distributed stochastic neighbor embedding (t-SNE) technique to generate homogeneous clusters of IDP conformations from the full heterogeneous ensemble. We illustrate the utility of t-SNE by clustering conformations of two disordered proteins, A{beta}42, and a C-terminal fragment of -synuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered sub-states within disordered ensembles and provide structural and mechanistic insights into binding modes that confer specificity and affinity in IDP ligand binding. t-SNE projections preserve the local neighborhood information and provide interpretable visualizations of the conformational heterogeneity within each ensemble and enable the quantification of cluster populations and their relative shifts upon ligand binding. Our approach provides a new framework for detailed investigations of the thermodynamics and kinetics of IDP ligand binding and will aid rational drug design for IDPs. SignificanceGrouping heterogeneous conformations of IDPs into "structurally similar" clusters facilitates a clearer understanding of the properties of IDP conformational ensembles and provides insights into "structural ensemble: function" relationships. In this work, we provide a unique approach for clustering IDP ensembles efficiently using a non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), to create clusters with structurally similar IDP conformations. We show how this can be used for meaningful biophysical analyses such as understanding the binding mechanisms of IDPs such as -synuclein and Amyloid {beta}42 with small drug molecules. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/516231v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@8ef906org.highwire.dtl.DTLVardef@7f14e5org.highwire.dtl.DTLVardef@134f9eeorg.highwire.dtl.DTLVardef@104a2ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2022

Androgen receptor condensates as drug targets

Transcription factors are among the most attractive therapeutic targets but are considered largely undruggable due to the intrinsically disordered nature of their activation domains. Here we show that the aromatic character of the activation domain of the androgen receptor, a therapeutic target for castration resistant prostate cancer, is key for its activity as a transcription factor by allowing it to partition into transcriptional condensates. Based on this knowledge we optimized the structure of a small molecule inhibitor, previously identified by phenotypic screening, that targets a specific transactivation unit within the domain that is partially folded and rich in aromatic residues. The optimized compounds had more affinity for their target, inhibited androgen receptor-dependent transcriptional programs, and had antitumorigenic effect in models of castration-resistant prostate cancer in cells and in vivo. These results establish a generalizable framework to target small molecules to the activation domains of oncogenic transcription factors and other disease-associated proteins with therapeutic intent.

biochemistry↗

bioRxiv2021

Small Molecules Targeting the Disordered Transactivation Domain of the Androgen Receptor Induce the Formation of Collapsed Helical States

Castration-resistant prostate cancer (CRPC) is a lethal condition suffered by [~]35% of prostate cancer patients who become resistant to existing FDA-approved drugs. Small molecules that target the intrinsically disordered N-terminal domain of the androgen receptor (AR-NTD) have shown promise in circumventing CPRC drug-resistance. A prodrug of one such compound, EPI-002, entered human trials in 2015 but was discontinued after phase I due to poor potency. The compound EPI-7170 was subsequently found to have improved potency, and a related compound entered human trials in 2020. NMR measurements have localized the strongest effects of these compounds to a transiently helical region of the disordered AR-NTD but no detailed structural or mechanistic rationale exists to explain their affinity to this region or the comparative potency of EPI-7170. Here, we utilize all-atom molecular dynamics simulations to elucidate the binding mechanisms of the small molecules EPI-002 and EPI-7170 to the disordered AR-NTD. We observe that both compounds induce the formation of collapsed helical states in the Tau-5 transactivation domain and that these bound states consist of heterogenous ensembles of interconverting binding modes. We find that EPI-7170 has a higher affinity to Tau-5 than EPI-002 and that the EPI-7170 bound ensemble contains a substantially higher population of collapsed helical states than the bound ensemble of EPI-002. We identify a network of interactions in the EPI-7170 bound ensemble that stabilize collapsed helical conformations. Our results provide atomically detailed binding mechanisms for EPI compounds consistent with NMR experiments that will prove useful for drug discovery for CRPC. SummaryIntrinsically disordered proteins (IDPs), which do not fold into a well-defined three-dimensional structure under physiological conditions, are implicated in many human diseases. Such proteins are difficult to characterize at an atomic level and are extremely challenging drug targets. Small molecules that target a disordered domain of the androgen receptor have entered human trials for the treatment of castration-resistant prostate cancer, but no structural or mechanistic rationale exists to explain their inhibition mechanisms or relative potencies. Here, we utilize molecular dynamics computer simulations to elucidate atomically detailed binding mechanisms of these compounds and understand their inhibition mechanisms. Our results suggest strategies for developing more potent androgen receptor inhibitors and general strategies for IDP drug design.

biophysics↗

bioRxiv2021

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-timescale, atomic-level molecular dynamics (MD) simulations of monomeric -synuclein (an IDP whose aggregation is associated with Parkinsons 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 {pi}-stacking interactions near the C terminus of -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.

biophysics↗

bioRxiv2020

The mechanism of coupled folding-upon-binding of an intrinsically disordered protein

Intrinsically disordered proteins (IDPs), which in isolation do not adopt a well-defined tertiary structure but instead populate a structurally heterogeneous ensemble of interconverting states, play important roles in many biological pathways. IDPs often fold into ordered states upon binding to their physiological interaction partners (a so-called "folding-upon-binding" process), but it has proven difficult to obtain an atomic-level description of the structural mechanisms by which they do so. Here, we describe in atomic detail the folding-upon-binding mechanism of an IDP segment to its binding partner, as observed in unbiased molecular dynamics simulations. In our simulations, we observed over 70 binding and unbinding events between the -helical molecular recognition element (-MoRE) of the intrinsically disordered C-terminal domain of the measles virus nucleoprotein (NTAIL) and the X domain (XD) of the measles virus phosphoprotein complex. We found that folding-upon-binding primarily occurred through induced-folding pathways (in which intermolecular contacts form before or concurrently with the secondary structure of the disordered protein)--an observation supported by previous experiments--and that the transition state ensemble was characterized by the formation of just a few key intermolecular contacts, and was otherwise highly structurally heterogeneous. We found that when a large amount of helical content was present early in a transition path, NTAIL typically unfolded, then refolded after additional intermolecular contacts formed. We also found that, among conformations with similar numbers of intermolecular contacts, those with less helical content had a higher probability of ultimately forming the native complex than conformations with more helical content, which were more likely to unbind. These observations suggest that even after intermolecular contacts have formed, disordered regions can have a kinetic advantage over folded regions in the folding-upon-binding process.

biophysics↗