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Journal of Chemical Theory and... Jul 2023Intrinsically disordered proteins participate in many biological processes by folding upon binding to other proteins. However, coupled folding and binding processes are...
Intrinsically disordered proteins participate in many biological processes by folding upon binding to other proteins. However, coupled folding and binding processes are not well understood from an atomistic point of view. One of the main questions is whether folding occurs prior to or after binding. Here we use a novel, unbiased, high-throughput adaptive sampling approach to reconstruct the binding and folding between the disordered transactivation domain of c-Myb and the KIX domain of the CREB-binding protein. The reconstructed long-term dynamical process highlights the binding of a short stretch of amino acids on c-Myb as a folded α-helix. Leucine residues, especially Leu298-Leu302, establish initial native contacts that prime the binding and folding of the rest of the peptide, with a mixture of conformational selection on the N-terminal region with an induced fit of the C-terminal.
Topics: Intrinsically Disordered Proteins; Molecular Dynamics Simulation; Protein Folding; Education, Distance; Protein Binding
PubMed: 37341654
DOI: 10.1021/acs.jctc.3c00008 -
Biomolecules Jan 2022Metal ions are critical for the biological and physiological functions of many proteins. Mass spectrometry (MS)-based structural proteomics is an ever-growing field that... (Review)
Review
Metal ions are critical for the biological and physiological functions of many proteins. Mass spectrometry (MS)-based structural proteomics is an ever-growing field that has been adopted to study protein and metal ion interactions. Native MS offers information on metal binding and its stoichiometry. Footprinting approaches coupled with MS, including hydrogen/deuterium exchange (HDX), "fast photochemical oxidation of proteins" (FPOP) and targeted amino-acid labeling, identify binding sites and regions undergoing conformational changes. MS-based titration methods, including "protein-ligand interactions by mass spectrometry, titration and HD exchange" (PLIMSTEX) and "ligand titration, fast photochemical oxidation of proteins and mass spectrometry" (LITPOMS), afford binding stoichiometry, binding affinity, and binding order. These MS-based structural proteomics approaches, their applications to answer questions regarding metal ion protein interactions, their limitations, and recent and potential improvements are discussed here. This review serves as a demonstration of the capabilities of these tools and as an introduction to wider applications to solve other questions.
Topics: Mass Spectrometry; Protein Binding; Protein Conformation; Proteins; Proteomics
PubMed: 35053283
DOI: 10.3390/biom12010135 -
Chemical Research in Toxicology Jun 2023New approach methodologies (NAMs) that make use of in vitro screening and in silico approaches to inform chemical evaluations rely on in vitro toxicokinetic (TK) data to...
New approach methodologies (NAMs) that make use of in vitro screening and in silico approaches to inform chemical evaluations rely on in vitro toxicokinetic (TK) data to translate in vitro bioactive concentrations to exposure metrics reflective of administered dose. With 1364 per- and polyfluoroalkyl substances (PFAS) identified as of interest under Section 8 of the U.S. Toxic Substances Control Act (TSCA) and concern over the lack of knowledge regarding environmental persistence, human health, and ecological effects, the utility of NAMs to understand potential toxicities and toxicokinetics across these data-poor compounds is being evaluated. To address the TK data deficiency, 71 PFAS selected to span a wide range of functional groups and physico-chemical properties were evaluated for in vitro human plasma protein binding (PPB) by ultracentrifugation with liquid chromatography-mass spectrometry analysis. For the 67 PFAS successfully evaluated by ultracentrifugation, fraction unbound in plasma () ranged from less than 0.0001 (pentadecafluorooctanoyl chloride) to 0.7302 (tetrafluorosuccinic acid), with over half of the PFAS showing PPB exceeding 99.5% ( < 0.005). Category-based evaluations revealed that perfluoroalkanoyl chlorides and perfluorinated carboxylates (PFCAs) with 6-10 carbons were the highest bound, with similar median values for alkyl, ether, and polyether PFCAs. Interestingly, binding was lower for the PFCAs with a carbon chain length of ≥11. Lower binding also was noted for fluorotelomer carboxylic acids when compared to their carbon-equivalent perfluoroalkyl acids. Comparisons of the value derived using two PPB methods, ultracentrifugation or rapid equilibrium dialysis (RED), revealed RED failure for a subset of PFAS of high mass and/or predicted octanol-water partition coefficients exceeding 4 due to failure to achieve equilibrium. Bayesian modeling was used to provide uncertainty bounds around point estimates for incorporation into TK modeling. This PFAS PPB evaluation and grouping exercise across 67 structures greatly expand our current knowledge and will aid in PFAS NAM development.
Topics: Humans; Bayes Theorem; Blood Proteins; Carboxylic Acids; Fluorocarbons; Protein Binding; Toxicokinetics; Water Pollutants, Chemical
PubMed: 37184865
DOI: 10.1021/acs.chemrestox.3c00003 -
Nanoscale Feb 2022Control over supramolecular recognition between proteins and nanoparticles (NPs) is of fundamental importance in therapeutic applications and sensor development. Most...
Control over supramolecular recognition between proteins and nanoparticles (NPs) is of fundamental importance in therapeutic applications and sensor development. Most NP-protein binding approaches use 'tags' such as biotin or His-tags to provide high affinity; protein surface recognition provides a versatile alternative strategy. Generating high affinity NP-protein interactions is challenging however, due to dielectric screening at physiological ionic strengths. We report here the co-engineering of nanoparticles and protein to provide high affinity binding. In this strategy, 'supercharged' proteins provide enhanced interfacial electrostatic interactions with complementarily charged nanoparticles, generating high affinity complexes. Significantly, the co-engineered protein-nanoparticle assemblies feature high binding affinity even at physiologically relevant ionic strength conditions. Computational studies identify both hydrophobic and electrostatic interactions as drivers for these high affinity NP-protein complexes.
Topics: Hydrophobic and Hydrophilic Interactions; Nanoparticles; Protein Binding; Proteins; Static Electricity
PubMed: 35089292
DOI: 10.1039/d1nr07497k -
Advanced Science (Weinheim,... Oct 2022Smart nanomaterials constitute a new approach toward safer and more effective combined anti-cancer immunotherapy. In this study, polydopamine-multiprotein conjugates...
Smart nanomaterials constitute a new approach toward safer and more effective combined anti-cancer immunotherapy. In this study, polydopamine-multiprotein conjugates (DmPCs) that can be used for targeted delivery of multiple proteins to cells, realize imaging and combine the advantages of multiple treatment methods (photothermal therapy, chemodynamic therapy, and immunotherapy) can be synthesized and characterized. Proteins, as biological agents, are frequently used in this context, given their low toxicity in vivo. To overcome protein instability and short half-life in vivo, the use of several proteins in combination with selected nanomaterials to treat patients with melanoma is proposed. In addition to the synthesis and characterization of protein-bound nanoparticles, it is further demonstrated that several proteins can be efficiently delivered to tumor sites. DmPCs have a wide range of potential adaptability, which provides new opportunities for proteins in the field of treatment and imaging.
Topics: Biological Factors; Humans; Hyperthermia, Induced; Nanoparticles; Neoplasms; Phototherapy; Protein Binding
PubMed: 35981878
DOI: 10.1002/advs.202202453 -
Experimental Biology and Medicine... Dec 2019The transforming growth factor beta (TGFβ) signaling pathway orchestrates a wide breadth of biological processes, ranging from bone development to reproduction. Given... (Review)
Review
UNLABELLED
The transforming growth factor beta (TGFβ) signaling pathway orchestrates a wide breadth of biological processes, ranging from bone development to reproduction. Given this, there has been a surge of interest from the drug development industry to modulate the pathway – at several points. This review discusses and provides additional context for several layers of the TGFβ signaling pathway from a structural biology viewpoint. The combination of structural techniques coupled with biophysical studies has provided a foundational knowledge of the molecular mechanisms governing this high impact, ubiquitous pathway, underlying many of the current therapeutic pursuits. This work seeks to consolidate TGFβ-related structural knowledge and educate other researchers of the apparent gaps that still prove elusive. We aim to highlight the importance of these structures and provide the contextual information to understand the contribution to the field, with the hope of advancing the discussion and exploration of the TGFβ signaling pathway.
IMPACT STATEMENT
The transforming growth factor beta (TGFβ) signaling pathway is a multifacetted and highly regulated pathway, forming the underpinnings of a large range of biological processes. Here, we review and consolidate the key steps in TGFβ signaling using literature rooted in structural and biophysical techniques, with a focus on molecular mechanisms and gaps in knowledge. From extracellular regulation to ligand–receptor interactions and intracellular activation cascades, we hope to provide an introductory base for understanding the TGFβ pathway as a whole.
Topics: Humans; Ligands; Molecular Biology; Protein Binding; Signal Transduction; Transforming Growth Factor beta
PubMed: 31594405
DOI: 10.1177/1535370219880894 -
Protein Science : a Publication of the... Nov 2022Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins often function by molecular recognition, in which they undergo induced...
Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins often function by molecular recognition, in which they undergo induced folding. Based on prior generalizations, the idea prevails in the IDP field that due to the entropic penalty of induced folding, the major functional advantage associated with this binding mode is "uncoupling" specificity from binding strength. Nevertheless, both weaker binding and high specificity of IDPs/IDRs rest on limited experimental observations, making these assumptions more speculations than evidence-supported facts. The issue is also complicated by the rather vague concept of specificity that lacks an exact measure, such as the K for binding strength. We addressed these issues by creating and analyzing a comprehensive dataset of well-characterized ID/globular protein complexes, for which both the atomic structure of the complex and free energy (ΔG, K ) of interaction is known. Through this analysis, we provide evidence that the affinity distributions of IDP/globular and globular/globular complexes show different trends, whereas specificity does not connote to weaker binding strength of IDPs/IDRs. Furthermore, protein disorder extends the spectrum in the direction of very weak interactions, which may have important regulatory consequences and suggest that, in a biological sense, strict correlation of specificity and binding strength are uncoupled by structural disorder.
Topics: Intrinsically Disordered Proteins; Protein Binding; Protein Conformation; Protein Folding
PubMed: 36305763
DOI: 10.1002/pro.4455 -
Communications Biology Jan 2023Protein-protein interactions (PPIs) govern cellular pathways and processes, by significantly influencing the functional expression of proteins. Therefore, accurate...
Protein-protein interactions (PPIs) govern cellular pathways and processes, by significantly influencing the functional expression of proteins. Therefore, accurate identification of protein-protein interaction binding sites has become a key step in the functional analysis of proteins. However, since most computational methods are designed based on biological features, there are no available protein language models to directly encode amino acid sequences into distributed vector representations to model their characteristics for protein-protein binding events. Moreover, the number of experimentally detected protein interaction sites is much smaller than that of protein-protein interactions or protein sites in protein complexes, resulting in unbalanced data sets that leave room for improvement in their performance. To address these problems, we develop an ensemble deep learning model (EDLM)-based protein-protein interaction (PPI) site identification method (EDLMPPI). Evaluation results show that EDLMPPI outperforms state-of-the-art techniques including several PPI site prediction models on three widely-used benchmark datasets including Dset_448, Dset_72, and Dset_164, which demonstrated that EDLMPPI is superior to those PPI site prediction models by nearly 10% in terms of average precision. In addition, the biological and interpretable analyses provide new insights into protein binding site identification and characterization mechanisms from different perspectives. The EDLMPPI webserver is available at http://www.edlmppi.top:5002/ .
Topics: Protein Binding; Proteome; Deep Learning; Algorithms; Binding Sites
PubMed: 36653447
DOI: 10.1038/s42003-023-04462-5 -
Biomolecules Nov 2021One-dimensional (1D) sliding of DNA-binding proteins has been observed by numerous kinetic studies. It appears that many of these sliding events play important roles in... (Review)
Review
One-dimensional (1D) sliding of DNA-binding proteins has been observed by numerous kinetic studies. It appears that many of these sliding events play important roles in a wide range of biological processes. However, one challenge is to determine the physiological relevance of these motions in the context of the protein's biological function. Here, we discuss methods of measuring protein 1D sliding by highlighting the single-molecule approaches that are capable of visualizing particle movement in real time. We also present recent findings that show how protein sliding contributes to function.
Topics: Binding Sites; DNA-Binding Proteins; Kinetics; Protein Binding
PubMed: 34827616
DOI: 10.3390/biom11111618 -
Biophysical Journal May 2022Biological functions of proteins rely on their specific interactions with binding partners. Many proteins contain multiple domains, which can bind to their targets that...
Biological functions of proteins rely on their specific interactions with binding partners. Many proteins contain multiple domains, which can bind to their targets that often have more than one binding site, resulting in multivalent interactions. While it has been shown that multivalent interactions play a crucial role in modulating binding affinity and specificity, other potential effects of multivalent interactions are less explored. Here, we developed a broadly applicable transfer-matrix formalism and used it to investigate the binding of two-domain ligands to targets with multiple binding sites. We show that 1) ligands with two specific binding domains can drastically boost both the binding affinity and specificity and downshift the working concentration range, compared with single-domain ligands, 2) the presence of a positive domain-domain cooperativity or containing a nonspecific binding domain can downshift the working concentration range of ligands by increasing the binding affinity without compromising the binding specificity, and 3) the configuration of the bound ligands has a strong concentration dependence, providing important insights into the physical origin of phase-separation processes taking place in living cells. In line with previous studies, our results suggest that multivalent interactions are utilized by cells for highly efficient regulation of target binding involved in a diverse range of cellular processes such as signal transduction, gene transcription, and antibody-antigen recognition.
Topics: Binding Sites; Ligands; Protein Binding; Proteins
PubMed: 35450827
DOI: 10.1016/j.bpj.2022.04.017