Structure-based Inhibitor Design for the Intrinsically Disordered Protein c-Myc.
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ABSTRACT:
SUBMITTER: Yu C
PROVIDER: S-EPMC4773988 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A growing body of research has demonstrated that targeting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) is feasible and represents a new trending strategy in drug discovery. However, the number of inhibitors targeting IDPs/IDPRs is increasing slowly due to limitations of the methods that can be used to accelerate the discovery process. We have applied structure-based methods to successfully develop the first peptidic inhibitor (HIPe - Histone Inhibitory Peptide) that targets histone H4 that are released from NETs (Neutrophil Extracellular Traps). HIPe binds stably to the disordered N-terminal tail of histone H4, thereby preventing histone H4-induced cell death. Recently, by utilisation of the same state-of-the-art approaches, we have developed a novel peptidic inhibitor (CHIP - Cyclical Histone H2A Interference Peptide) that binds to NET-resident histone H2A, which results in a blockade of monocyte adhesion and consequently reduction in atheroprogression. Here, we present comprehensive details on the computational methods utilised to design and develop HIPe and CHIP. We have exploited protein-protein complexes as starting structures for rational peptide design and then applied binding free energy methods to predict and prioritise binding strength of the designed peptides with histone H4 and H2A. By doing this way, we have modelled only around 20 peptides and from these were able to select 4-5 peptides, from a total of more than a trillion candidate peptides, for functional characterisation in different experiments. The developed computational protocols are generic and can be widely used to design and develop novel inhibitors for other disordered proteins.
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Project description:Intrinsically disordered proteins (IDPs) perform a broad range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Computational design of IDPs with specific conformational properties has, however, been difficult because of their substantial dynamics and structural complexity. We describe a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs that differ in compaction, long-range contacts, and propensity to phase separate. We experimentally tested and validated our designs and analyzed the sequence features that determine conformations. We show how our results are captured by a machine learning model, enabling us to speed up the algorithm. Our work expands the toolbox for computational protein design and will facilitate the design of proteins whose functions exploit the many properties afforded by protein disorder.
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Project description:Intrinsically disordered proteins (IDPs) perform a wide range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Designing IDPs with specific structural or functional properties has, however, been diffcult, in part because determining accurate conformational ensembles of IDPs generally requires a combination of computational modelling and experiments. Motivated by recent advancements in effcient physics-based models for simulations of IDPs, we have developed a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs with different levels of compaction and that vary more than 100 fold in their propensity to undergo phase separation, even while keeping a fixed amino acid composition. We experimentally tested designs of variants of the low-complexity domain of hnRNPA1 and find high accuracy in our computational predictions, both in terms of single-chain compaction and propensity to undergo phase separation. We analyze the sequence features that determine changes in compaction and propensity to phase separate and find an overall good agreement with previous findings for naturally occurring sequences. Our general, physics-based method enables the design of disordered sequences with specified conformational properties. Our algorithm thus expands the toolbox for protein design to include also the most flexible proteins and will enable the design of proteins whose functions exploit the many properties afforded by protein disorder.
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Project description:There is increasing evidence that many intrinsically disordered regions (IDRs) in proteins play key functional roles through interactions with other proteins or nucleic acids. These interactions often exhibit a context-dependent structural behavior. We hypothesize that low complexity regions (LCRs), often found within IDRs, could have a role in inducing local structure in IDRs. To test this, we predicted IDRs in the human proteome and analyzed their structures or those of homologous sequences in the Protein Data Bank (PDB). We then identified two types of simple LCRs within IDRs: regions with only one (polyX or homorepeats) or with only two types of amino acids (polyXY). We were able to assign structural information from the PDB more often to these LCRs than to the surrounding IDRs (polyX 61.8% > polyXY 50.5% > IDRs 39.7%). The most frequently observed polyX and polyXY within IDRs contained E (Glu) or G (Gly). Structural analyses of these sequences and of homologs indicate that polyEK regions induce helical conformations, while the other most frequent LCRs induce coil structures. Our work proposes bioinformatics methods to help in the study of the structural behavior of IDRs and provides a solid basis suggesting a structuring role of LCRs within them.
| S-EPMC9405754 | biostudies-literature
Project description:Intrinsically disordaered proteins (IDPs) are a prevalent phenomenon with over 30% of human proteins estimated to have long disordered regions. Computational methods are widely used to study IDPs, however, nearly all treat disorder in a binary fashion, not accounting for the structural heterogeneity present in disordered regions. Here, we present a new de novo method, FRAGFOLD-IDP, which addresses this problem. Using 200 protein structural ensembles derived from NMR, we show that FRAGFOLD-IDP achieves superior results compared to methods which can predict related data (NMR order parameter, or crystallographic B-factor). FRAGFOLD-IDP produces very good predictions for 33.5% of cases and helps to get a better insight into the dynamics of the disordered ensembles. The results also show it is not necessary to predict the correct fold of the protein to reliably predict per-residue fluctuations. It implies that disorder is a local property and it does not depend on the fold. Our results are orthogonal to DynaMine, the only other method significantly better than the naïve prediction. We therefore combine these two using a neural network. FRAGFOLD-IDP enables better insight into backbone dynamics in IDPs and opens exciting possibilities for the design of disordered ensembles, disorder-to-order transitions, or design for protein dynamics.
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Project description:Intrinsically disordered proteins (IDPs) carry out important biological functions and offer an instructive model system for folding and binding studies. However, their structural characterization in the absence of interactors is hindered by their highly dynamic conformation. The cyclin-dependent-kinase inhibitor (Cki) Sic1 from Saccharomyces cerevisiae is a key regulator of the yeast cell cycle, which controls entrance into S phase and coordination between cell growth and proliferation. Its last 70 out of 284 residues display functional and structural homology to the inhibitory domain of mammalian p21 and p27. Sic1 has escaped systematic structural characterization until now. Here, complementary biophysical methods are applied to the study of conformational properties of pure Sic1 in solution. Based on sequence analysis, gel filtration, circular dichroism (CD), electrospray-ionization mass spectrometry (ESI-MS), and limited proteolysis, it can be concluded that the whole molecule exists in a highly disordered state and can, therefore, be classified as an IDP. However, the results of these experiments indicate, at the same time, that the protein displays some content in secondary and tertiary structure, having properties similar to those of molten globules or premolten globules. Proteolysis-hypersensitive sites cluster at the N-terminus and in the middle of the molecule, whereas the most structured region resides at the C-terminus, including part of the inhibitory domain and the casein-kinase-2 (CK2) phosphorylation target S201. The mutations S201A and S201E, which are known to affect Sic1 function, do not have significant effects on the conformational properties of the pure protein.
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Project description:IDPs in their unbound state can transiently acquire secondary and tertiary structure. Describing such intrinsic structure is important to understand the transition between free and bound state, leading to supramolecular complexes with physiological interactors. IDP structure is highly dynamic and, therefore, difficult to study by conventional techniques. This work focuses on conformational analysis of the KID fragment of the Sic1 protein, an IDP with a key regulatory role in the cell-cycle of Saccharomyces cerevisiae. FT-IR spectroscopy, ESI-MS, and IM measurements are used to capture dynamic and short-lived conformational states, probing both secondary and tertiary protein structure. The results indicate that the isolated Sic1 KID retains dynamic helical structure and populates collapsed states of different compactness. A metastable, highly compact species is detected. Comparison between the fragment and the full-length protein suggests that chain length is crucial to the stabilization of compact states of this IDP. The two proteins are compared by a length-independent compaction index.
| S-EPMC3149264 | biostudies-literature
Project description:The hydrolysis of ATP by the ATP synthase in mitochondria is inhibited by a protein called IF1. Bovine IF1 has 84 amino acids, and its N-terminal inhibitory region is intrinsically disordered. In a known structure of bovine F1-ATPase inhibited with residues 1-60 of IF1, the inhibitory region from residues 1-50 is mainly α-helical and buried deeply at the α(DP)β(DP)-catalytic interface, where it forms extensive interactions with five of the nine subunits of F1-ATPase but mainly with the β(DP)-subunit. As described here, on the basis of two structures of inhibited complexes formed in the presence of large molar excesses of residues 1-60 of IF1 and of a version of IF1 with the mutation K39A, it appears that the intrinsically disordered inhibitory region interacts first with the αEβE-catalytic interface, the most open of the three catalytic interfaces, where the available interactions with the enzyme allow it to form an α-helix from residues 31-49. Then, in response to the hydrolysis of an ATP molecule and the associated partial closure of the interface to the αTPβTP state, the extent of the folded α-helical region of IF1 increases to residues 23-50 as more interactions with the enzyme become possible. Finally, in response to the hydrolysis of a second ATP molecule and a concomitant 120° rotation of the γ-subunit, the interface closes further to the α(DP)β(DP)-state, allowing more interactions to form between the enzyme and IF1. The structure of IF1 now extends to its maximally folded state found in the previously observed inhibited complex.
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Project description: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.
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Project description:In the nucleus, the spatiotemporal regulation of the catalytic subunit of cAMP-dependent protein kinase A (PKA-C) is orchestrated by an intrinsically disordered protein kinase inhibitor, PKI, which recruits the CRM1/RanGTP nuclear exporting complex. How the PKA-C/PKI complex assembles and recognizes CRM1/RanGTP is not well understood. Using NMR, SAXS, fluorescence, metadynamics, and Markov model analysis, we determined the multi-state recognition pathway for PKI. After a fast binding step in which PKA-C selects PKI's most competent conformations, PKI folds upon binding through a slow conformational rearrangement within the enzyme's binding pocket. The high-affinity and pseudo-substrate regions of PKI become more structured and the transient interactions with the kinase augment the helical content of the nuclear export sequence, which is then poised to recruit the CRM1/RanGTP complex for nuclear translocation. The multistate binding mechanism featured by PKA-C/PKI complex represents a paradigm on how disordered, ancillary proteins (or protein domains) are able to operate multiple functions such as inhibiting the kinase while recruiting other regulatory proteins for nuclear export.
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