Protein Conformational Changes Research Articles

UV-Visible Spectroscopy: A Review on its Pharmaceutical and Bio-allied Sciences Applications

Abstract: Ultraviolet-Visible (UV-Vis) spectroscopy has emerged as a powerful analytical tool with diverse applications in pharmaceutical and bio-allied sciences. This article provides a comprehensive overview of the extensive utility of UV-Vis spectroscopy, emphasizing its pivotal role in characterizing and analyzing various compounds critical for drug development and bio-allied research. In the pharmaceutical sector, UV-Vis spectroscopy is a fundamental technique for quantifying the concentrations of active pharmaceutical ingredients (APIs) in formulations. Its non-destructive nature and high sensitivity make it an indispensable tool for quality control, ensuring the consistency and potency of pharmaceutical products. Furthermore, this technique has been employed in the study of drug-receptor interactions to elucidate the molecular mechanisms underlying therapeutic effects. In bio-allied applications, UV-Vis spectroscopy is used to analyze biomolecules like proteins, nucleic acids, and enzymes. This technique allows for the study of protein conformational changes, DNA structure, and enzymatic activity, offering crucial insights into fundamental biological processes. Additionally, UV-Vis spectroscopy aids in determining biomarker concentrations, assisting in the early diagnosis and monitoring of various diseases. This article also explores recent advancements in UV-Vis spectroscopy, including the integration of nanomaterials and computational approaches to enhance sensitivity and selectivity. Moreover, it discusses the potential of UV-Vis spectroscopy in emerging areas such as personalized medicine and point- of-care diagnostics. As technology continues to evolve, UV-Visible spectroscopy is poised to significantly contribute to the ever-expanding landscape of pharmaceutical and bio-related research.

Macrocyclic Conformational Switch Coupled with Pyridinium-Induced PET for Fluorescence Detection of Adenosine Triphosphate.

The binding of nucleotides is crucial for signal transduction as it induces conformational protein changes, leading to downstream cellular responses. Synthetic receptors that bind nucleotides and transduce the binding event into global conformational rearrangements are highly challenging to design, especially those that operate in an aqueous solution. Much work is focused on evaluating functionalized dyes to detect nucleotides, whereas coupling of a nucleotide-induced conformational switching to a sensing event has not been reported to date. We disclose synthetic receptors that undergo a global conformational rearrangement upon nucleotide binding. Integrating naphthalimide and the pyridinium ion into the structure enables stabilization of the folded conformation and efficient fluorescence quenching. The binding of a nucleotide rearranges the receptor conformation and alters the strong fluorescence enhancement. The methylpyridinium-containing receptor demonstrated high sensing selectivity for adenosine 5'-triphosphate (ATP) and a record 160-fold fluorescence enhancement. It can detect fluctuations of ATP in HeLa cells and possesses low cytotoxicity. The developed systems present an attractive approach for designing ATP-responsive artificial molecular switches that operate in water and integrate a strong fluorescence response.

Incorporating ε-polylysine hydrochloride, tea polyphenols, nisin, and ascorbic acid into edible coating solutions: Effect on oxidation and structure of marinated egg proteins

Egg processing products lose their attraction due to protein oxidation and degradation, while the edible coating incorporating antioxidant and antimicrobial agents can address this deficit. In this work, chitosan (CS) in combination with ε-polylysine hydrochloride, tea polyphenols, nisin, and vitamin C (CS–NH-TC) was applied as a novel edible coating material for preserving marinated eggs for 20 days and its effects on egg quality, and protein oxidation and structure were determined. The CS–NH–TC coating exhibited the highest antioxidant and antibacterial activities among all coatings. Compared to uncoated marinated eggs (Sulfhydryl: 12.02 μmol/g, dityrosine: 6251.8, protein hydrophobicity: 3691, turbidity: 0.13 mg/mL, particle size: 342.13 nm), CS- and CS–NH–TC-coated eggs exhibited improved protein stability, as evidenced by a higher sulfhydryl (22.20 and 30.92 μmol/g) and lower dityrosine content (4722 and 4216), protein hydrophobicity (2891.72 and 865.75), turbidity (0.06 and 0.03 mg/mL), and particle size (292.06 and 256.57 nm). Additionally, edible coatings, especially CS–NH–TC coatings, were positively correlated with smaller intermolecular force changes in marinated eggs, corresponding to suppressed protein oxidation and conformational changes. Furthermore, CS–NH–TC-coated samples showed more stable protein secondary structures and less disorderly and aggregated protein microstructure, and better color, texture, and sensory scores. Our study could provide a theoretical basis for stabilizing the protein structure of egg processing products.

Probing the interaction behavior of Nano-Resveratrol with α-lactalbumin in the presence of β-lactoglobulin and β-casein: spectroscopy and molecular simulation studies

The main purpose of this research was to evaluate the role of α-lactalbumin (α-LA), β-lactoglobulin (β-LG), and β-Caseins (β-CN) in the binding interaction between Nano Resveratrol (Nano Res), as binary and ternary systems. This investigation was fulfilled through the application of multi-spectroscopic, transmission electron microscopy (TEM), field emission scanning electron microscope (FE-SEM), conductometry, isothermal titration calorimetry (ITC), and molecular dynamics (MD) simulation techniques. Fluorescence spectroscopy observations illustrated the effectiveness of Nano Res throughout the quenching of α-LA, (α-LA-β-LG), and (α-LA-β-CN) complexes, confirming the occurrence of interaction through the combination of static and dynamic mechanisms. An enhancement in the temperature of all three complexes caused a decrease in their Ksv and Kb values, which indicates the static and dynamic behavior of their interactions. The obtained thermodynamic parameters proved the dominance of electrostatic interaction as the binding force of both binary and ternary systems. The observed properties of Tyr or Trp residues in proteins through the data of synchronous spectroscopy at Δλ = 15 and 60 nm, respectively, demonstrated the closer positioning of (α-LA-β-CN) complex to the proximity of Trp residues when compared to the two other cases. According to the resonance light scattering (RLS) measurements, the detection of a much greater RLS intensity in (α-LA-β-CN) Nano Res complex suggested the production of a larger complex. Furthermore, the conductometry outcomes displayed an increase in molar conductivity and therefore approved the occurrence of interaction between Nano Res and proteins in both binary and ternary systems. The spherical shape of Nano Res was confirmed through the results of FE-SEM and TEM analyses. The conformational changes of proteins throughout the binding of Nano Res was evaluated by circular dichroism (CD) technique, while molecular docking and MD simulations affirmed the binding of Nano Res to α-LA, (α-LA-β-LG), and (α-LA-β-CN) complexes as binary and ternary systems. These In Silico study data confirm the results of in vitro assessments. The occurrence of changes in the secondary structure of β-galactosidase was implied through the increased enzyme catalytic activity induced by the interaction of different lactose concentrations. Communicated by Ramaswamy H. Sarma

DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model

While significant advances have been made in predicting static protein structures, the inherent dynamics of proteins, modulated by ligands, are crucial for understanding protein function and facilitating drug discovery. Traditional docking methods, frequently used in studying protein-ligand interactions, typically treat proteins as rigid. While molecular dynamics simulations can propose appropriate protein conformations, they’re computationally demanding due to rare transitions between biologically relevant equilibrium states. In this study, we present DynamicBind, a deep learning method that employs equivariant geometric diffusion networks to construct a smooth energy landscape, promoting efficient transitions between different equilibrium states. DynamicBind accurately recovers ligand-specific conformations from unbound protein structures without the need for holo-structures or extensive sampling. Remarkably, it demonstrates state-of-the-art performance in docking and virtual screening benchmarks. Our experiments reveal that DynamicBind can accommodate a wide range of large protein conformational changes and identify cryptic pockets in unseen protein targets. As a result, DynamicBind shows potential in accelerating the development of small molecules for previously undruggable targets and expanding the horizons of computational drug discovery.

Measuring conformational equilibria in allosteric proteins with time-resolved tmFRET

Proteins are the workhorses of biology, orchestrating a myriad of cellular functions through intricate conformational changes. Protein allostery, the phenomenon where binding of ligands or environmental changes induce conformational rearrangements in the protein, is fundamental to these processes. We have previously shown that transition metal Förster resonance energy transfer (tmFRET) can be used to interrogate the conformational rearrangements associated with protein allostery and have recently introduced novel FRET acceptors utilizing metal-bipyridyl derivatives to measure long (>20 Å) intramolecular distances in proteins. Here, we combine our tmFRET system with fluorescence lifetime measurements to measure the distances, conformational heterogeneity, and energetics of maltose-binding protein, a model allosteric protein. Time-resolved tmFRET captures near-instantaneous snapshots of distance distributions, offering insights into protein dynamics. We show that time-resolved tmFRET can accurately determine distance distributions and conformational heterogeneity of proteins. Our results demonstrate the sensitivity of time-resolved tmFRET in detecting subtle conformational or energetic changes in protein conformations, which are crucial for understanding allostery. In addition, we extend the use of metal-bipyridyl compounds, showing that Cu(phen)2+ can serve as a spin label for pulse dipolar electron paramagnetic resonance (EPR) spectroscopy, a method that also reveals distance distributions and conformational heterogeneity. The EPR studies both establish Cu(phen)2+ as a useful spin label for pulse dipolar EPR and validate our time-resolved tmFRET measurements. Our approach offers a versatile tool for deciphering conformational landscapes and understanding the regulatory mechanisms governing biological processes.

Optimal enhanced sampling of protein conformational changes by exact reaction coordinates from energy relaxation

Optimal enhanced sampling of protein conformational changes by exact reaction coordinates from energy relaxation

Molecular Study on Conformational Changes in Trypsin Inhibitors in Multidirectional Electrostatic Fields

Proteins undergo a series of conformational changes when affected by the applied electric field, which changes their functions and properties. The conformational changes in proteins in various electric fields are different due to their internal structures. This study simulates the molecular dynamics of proteins in different amounts and directions of electric fields with gromacs software. According to the root mean square deviation, hydrogen bond, dipole moment, and solvent accessible surface area, it is proved that the conformation change in proteins is more drastic under the simultaneous action of multiple electric fields under various directions, and different fragments unfold with divergent electric fields combined, which is of great importance to control protein function, improve biochemical research and production efficiency in the food and drug safety field.

Next-Generation Tags for Fluorine Nuclear Magnetic Resonance: Designing Amplification of Chemical Shift Sensitivity.

Fluorine NMR is a highly sensitive technique for delineating the conformational states of biomolecules and has shown great utility in drug screening and in understanding protein function. Current fluorinated protein tags leverage the intrinsic chemical shift sensitivity of the 19F nucleus to detect subtle changes in protein conformation and topology. This chemical shift sensitivity can be amplified by embedding the fluorine or trifluoromethyl reporter within a pyridone. Due to their polarizability and rapid tautomerization, pyridones exhibit a greater range of electron delocalization and correspondingly greater 19F NMR chemical shift dispersion. To assess the chemical shift sensitivity of these tautomeric probes to the local environment, 19F NMR spectra of all possible monofluorinated and trifluoromethyl-tagged versions of 2-pyridone were recorded in methanol/water mixtures ranging from 100% methanol to 100% water. 4-Fluoro-2-pyridone and 6-(trifluoromethyl)-2-pyridone (6-TFP) displayed the greatest sensitivity of the monofluorinated and trifluoromethylated pyridones, exceeding that of known conventional CF3 reporters. To evaluate the utility of tautomeric pyridone tags for 19F NMR of biomolecules, the alpha subunit of the stimulatory G protein (Gsα) and human serum albumin (HSA) were each labeled with a thiol-reactive derivative of 6-TFP and the spectra were recorded as a function of various adjuvants and drugs. The tautomeric tag outperformed the conventional tag, 2-bromo-N-(4-(trifluoromethyl)phenyl)acetamide through the improved resolution of several functional states.

Abstract B016: Developing diagnostic tools via mutational spectra analysis and multiomic plasma profiling from liquid biopsies to identify potential signatures in cancer in Trinidad and Tobago

Abstract Cancer, especially lung cancer is a leading cause of nosocomial deaths worldwide. Non-small cell lung cancer (NSCLC) has a five-year survival rate of only 24%. Early diagnoses markedly improves survival with personalized cancer therapies using non-invasive techniques for asymptomatic detection of mutational spectrum-related by genotyping NSCLC patients, even prior to symptoms. Analysis of conformational change in proteins due to mutations in oncogenes allow for mutation-specific treatment with specialized cancer drugs. In addition, tumor mutational burden (TMB) is a promising predictive biomarker for cancer immunotherapy as high TMB patients respond better to immune checkpoint inhibitors cancer drugs. Treatment planning for non-small cell lung cancer generally requires testing for EGFR, ALK, ROS1, BRAF, MET, RET and KRAS gene alterations or whole genome analysis to assess TMB. The Caribbean region remains disadvantaged by the lack of available genetic testing mainly due to accessibility. We propose the genotyping of 30 stage III-IV NSCLC patients via next-generation sequencing (NGS) to improve personalized therapies. Through the analysis of tumor-specific alterations amongst a complete mutation spectrum analysis, including single nucleotide variants (SNVs), insertions, deletions, copy number variations (CNVs), and methylation alterations, we would generate data to be used as an accurate form of cancer genotyping for diagnostic purposes. We intend to include these genes as biomarkers in a mutational spectrum analysis, to be collated into a predictive DNA assay to be used for the first time as a diagnostic/prognostic tool in a medically underserved community. We intend to also identify TMB-high patients without cost-prohibitive whole genome sequencing by focusing on DNA damage repair (DDR) genes. There is an increasing utilization of agnostic testing which involves the analysis of all potentially actionable genes across all tumor and cancer types. The invention of genomic-tailored specialized cancer treatments has resulted in a spectacular improvement in disease outcomes for a significant portion of cancer patients, which we hope to offer to improve clinical outcomes and prognosis in the racially diverse population of Trinidad and Tobago. Citation Format: Nicole Ramlachan, Samuel M. West. Developing diagnostic tools via mutational spectra analysis and multiomic plasma profiling from liquid biopsies to identify potential signatures in cancer in Trinidad and Tobago [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr B016.

PH-dependent interactions of biologically important metal ions with hen egg white lysozyme based on its hydration properties: Thermodynamic and mechanistic insights

Importance of metal ion selectivity in biomolecules and their key role in proteins are widely explored. However, understanding the thermodynamics of how hydrated metal ions alter the protein hydration and their conformation is also important. In this study, the interaction of some biologically important Ca2+, Mn2+, Co2+, Cu2+, and Zn2+ ions with hen egg white lysozyme at pH 2.1, 3.0, 4.5 and 7.4 has been investigated. Intrinsic fluorescence studies have been employed for metal ion-induced protein conformational changes analysis. Thermostability based on protein hydration has been investigated using differential scanning calorimetry (DSC). Thermodynamic parameters emphasizing on metal ion-protein binding mechanistic insights have been well discussed using isothermal titration calorimetry (ITC). Overall, these experiments have reported that their interactions are pH-dependent and entropically driven. This research also reports the strongly hydrated metal ions as water structure breaker unlike osmolytes based on DSC studies. These experimental results have highlighted higher concentrations of different metal ions effect on the protein hydration and thermostability which might be helpful in understanding their interactions in aqueous solutions.

Enhancement of functional properties, digestive properties, and in vitro digestion product physiological activity of extruded corn gluten meal by enzymatic modification.

Enzymatic modification is an effective means of improving the functional properties, digestive properties, and in vitro digestion product physiological activity of proteins, thus significantly expanding protein uses in various food applications. In this study, the addition of chymotrypsin (CT) at pH 9.0 and 11.0 was found to significantly improve the functional properties (solubility, foaming properties, water holding capacity, oil holding capacity, etc.) and digestive properties of extruded corn gluten meal (ECGM). Similar changes were observed when treating ECGM with glutaminase, protein glutaminase, and papain. These changes were likely due to the increase in number of carboxyl groups and the multiple effects of change in protein net charge and conformation caused by enzymatic deamidation. Of note, ECGM deamidated by CT showed the highest degree of deamidation, solubility, and gastrointestinal digestibility at pH 11.0, up to 44.92%, 43.75%, and 82.22%, respectively. In addition, CT-ECGM digestion product exhibited strong antioxidant activity and potential to promote alcohol metabolism in both a static digestion model and dynamic digestion model, even comparable to commercial corn peptides (CCP), while being inexpensive and of low bitterness compared to CCP. Meanwhile, the physiological activity enhanced as the molecular weight of digestion product decreased with the digested component having strongest activity. This study may promote the application of ECGM as a food component in the food industry or even as a substitute for CCP. © 2023 Society of Chemical Industry.

Development of “clean label” gluten-free breads fortified with flaxseed slurry and sesame cake: Implications on batter rheology, bread quality and shelf life

Following the recently emerged trends for products without additives and valorization of food processing by-products, “clean label” gluten-free (GF) breads were developed using a flaxseed slurry (FS) at 3% or 4.5% level (flaxseed basis), instead of the commonly used structurant in GF doughs, methylcellulose, and 3 or 6% (flour mixture basis) sesame cake (SC) for further product nutritional improvement. These alternative ingredients increased batter hardness and cohesiveness (back extrusion test) as well as elastic modulus, complex and steady shear viscosity (rheometry), compared to formulation containing only methylcellulose (control). The fortified breads had lower loaf specific volumes, than the control, but significantly higher than a GF bread made without any added hydrocolloid. FS and SC enhanced the formation of β-sheet structures (FTIR spectroscopy) in the batter and bread protein matrix. FS breads exhibited similar crumb hardness, cohesiveness, and springiness (TPA test) with the control, whereas inclusion of SC compromised these textural attributes. Nevertheless, the latter samples showed less pronounced textural changes upon storage (25°C-48 h), with similar extent of staling to control. For the fortified stored breads, there were no significant changes in protein conformation, compared to fresh products, whereas crumb starch retrogradation (calorimetry-DSC) was lower than the control. Additionally, the FS and SC increased the protein and dietary fiber contents and introduced nutty and sesame-like flavor notes to the breads, leading to improved overall acceptability scores. Overall, FS and SC seemed to be promising functional ingredients for the development of “clean label” GF breads with enhanced quality and shelf life.

Probing the role of protein conformational changes in the mechanism of prenylated-FMN-dependent phenazine-1-carboxylic acid decarboxylase

Phenazine-1-carboxylic acid decarboxylase (PhdA) is a prenylated-FMN-dependent (prFMN) enzyme belonging to the UbiD family of decarboxylases. Many UbiD-like enzymes catalyze (de)carboxylation reactions on aromatic rings and conjugated double bonds and are potentially valuable industrial catalysts. We have investigated the mechanism of PhdA using a slow turnover substrate, 2,3-dimethylquinoxaline-5-carboxylic acid (DQCA). Detailed analysis of the pH dependence and solvent deuterium isotope effects associated with the reaction uncovered unusual kinetic behavior. At low substrate concentrations, a substantial inverse solvent isotope effect (SIE) is observed on Vmax/KM of ∼ 0.5 when reaction rates of DQCA in H2O and D2O are compared. Under the same conditions, a normal SIE of 4.15 is measured by internal competition for proton transfer to the product. These apparently contradictory results indicate that the SIE values report on different steps in the mechanism. A proton inventory analysis of the reaction under Vmax/KM and Vmax conditions points to a "medium effect" as the source of the inverse SIE. Molecular dynamics simulations of the effect of D2O on PhdA structure support that D2O reduces the conformational lability of the enzyme and results in a more compact structure, akin to the active, "closed" conformer observed in crystal structures of some UbiD-like enzymes. Consistent with the simulations, PhdA was found to be more stable in D2O and to bind DQCA more tightly, leading to the observed rate enhancement under Vmax/KM conditions.

Прионы и прионные болезни: мифы и реальность

The article contains modern data about prions and the main prion-associated diseases. The authors describe the main conditions that provide prion-associated infectious diseases, primarily the conformation changes of protein PrPС expressed in healthy tissues of humans and animals and forming the pathogenic PrPSc protein. All prion-caused diseases are considered to be neurodegenerative with fatal outcomes due to a specific spongy brain damage. Information on some aspects of pathogenesis and therapeutic options for prion diseases is presented. The data on the prion safety of biological preparations widely used in healthcare are also presented.

Effect of UHT Thermal Treatment on the Secondary Structures of Milk Proteins: Insights From FTIR Analysis and Potential Allergenic Activity.

Although thermal treatments are beneficial for the preservation and safety of milk, they can also alter its immunogenic activity by affecting its protein components. To achieve precise results, it is essential to identify the specific proteins that cause food allergies. Therefore, investigating the possible alterations of cow's milk proteins (CMPs) resulting from thermal treatments is necessary. In this study, the Fourier transform infrared spectroscopy (FTIR) technique was used to analyze the effect of UHT thermal treatment on the secondary structures of milk casein. Using the second derivative, six characteristic peaks were identified in the Amide I region, ranging from 1700 to 1600 cm-1. It was found that thermal treatments produce shifts in absorption peaks, indicating changes in protein conformation and possibly in allergenic activity. These shifts were clearly identified in the first characteristic peak of samples M8 and M9, from 1621 to 1600 cm-1. The results suggest that thermal treatments may promote protein aggregation by increasing β turns and reducing β sheets and α helices, which could enhance the allergenic potential of the proteins and facilitate the formation of complexes between different milk proteins, such as β-lactoglobulin and κ-casein. Further studies are needed to experimentally validate the allergenic activity of proteins modified by thermal treatments, as only an analytical method (FTIR) was used to evaluate the secondary structures of the proteins.

Phosphorylation of Tau Protein by CDK2/cyclin A and GSK3β Recombinant Kinases: Analysis of Phosphorylation Patterns by Nuclear Magnetic Resonance Spectroscopy.

Posttranslational modifications (PTMs) of proteins can be investigated by Nuclear Magnetic Resonance (NMR) spectroscopy as a powerful analytical tool to define modification sites, their relative stoichiometry, and crosstalk between modifications. As a Structural Biology method, NMR provides important additional information on changes in protein conformation and dynamics upon modification as well as a mapping of binding sites upon biomolecular interactions. Indeed, PTMs not only mediate functional modulation in protein-protein interactions, but can also induce diverse structural responses with different biological outcomes. Here we present protocols that have been developed for the production and phosphorylation of the neuronal tau protein. Under its aggregated form, tau is a hallmark ofAlzheimer's disease and other neurodegenerative diseases named tauopathies involving tau dysfunction and/or mutations. As a common feature shared by various tauopathies, tau aggregates are found into a form displaying an increased, abnormal phosphorylation, also referred to hyperphosphorylation. We have used NMR to investigate the phosphorylation patterns of tau induced by several kinases or cell extracts, how phosphorylation affects the local and overall conformation of tau, its interactions with partners (proteins, DNA, small-molecules, etc.) including tubulin and microtubules, and its capacity to form insoluble fibrillar aggregates. We present here detailed protocols for in vitro phosphorylation of tau by the recombinant kinases CDK2/cyclin A and GSK3β, the production of the recombinant kinases thereof, as well as the analytical characterization of phosphorylated tau by NMR spectroscopy.

Machine Learning Methods in Protein-Protein Docking.

An exponential increase in the number of publications that address artificial intelligence (AI) usage in life sciences has been noticed in recent years, while new modeling techniques are constantly being reported. The potential of these methods is vast-from understanding fundamental cellular processes to discovering new drugs and breakthrough therapies. Computational studies of protein-protein interactions, crucial for understanding the operation of biological systems, are no exception in this field. However, despite the rapid development of technology and the progress in developing new approaches, many aspects remain challenging to solve, such as predicting conformational changes in proteins, or more "trivial" issues as high-quality data in huge quantities.Therefore, this chapter focuses on a short introduction to various AI approaches to study protein-protein interactions, followed by a description of the most up-to-date algorithms and programs used for this purpose. Yet, given the considerable pace of development in this hot area of computational science, at the time you read this chapter, the development of the algorithms described, or the emergence of new (and better) ones should come as no surprise.

Prediction of Inter-residue Multiple Distances and Exploration of Protein Multiple Conformations by Deep Learning.

AlphaFold2 has achieved a major breakthrough in end-to-end prediction for static protein structures. However, protein conformational change is considered to be a key factor in protein biological function. Inter-residue multiple distances prediction is of great significance for research on protein multiple conformations exploration. In this study, we proposed an inter-residue multiple distances prediction method, DeepMDisPre, based on an improved network which integrates triangle update, axial attention and ResNet to predict multiple distances of residue pairs. We built a dataset which contains proteins with a single structure and proteins with multiple conformations to train the network. We tested DeepMDisPre on 114 proteins with multiple conformations. The results show that the inter-residue distance distribution predicted by DeepMDisPre tends to have multiple peaks for flexible residue pairs than for rigid residue pairs. On two cases of proteins with multiple conformations, we modeled the multiple conformations relatively accurately by using the predicted inter-residue multiple distances. In addition, we also tested the performance of DeepMDisPre on 279 proteins with a single structure. Experimental results demonstrate that the average contact accuracy of DeepMDisPre is higher than that of the comparative method. In terms of static protein modeling, the average TM-score of the 3D models built by DeepMDisPre is also improved compared with the comparative method. The executable program is freely available at https://github.com/iobio-zjut/DeepMDisPre.

The role of solvation on the conformational landscape of α-synuclein.

Native ion mobility mass spectrometry has been used extensively to characterize ensembles of intrinsically disordered protein (IDP) conformers, but the extent to which the gaseous measurements provide realistic pictures of the solution conformations for such flexible proteins remains unclear. Therefore, we systematically studied the relationship between the solution and gaseous structural ensembles by measuring electrospray charge state and collision cross section (CCS) distributions for cationic and anionic forms of α-synuclein (αSN), an anionic protein in solution, as well as directly probed gas phase residue to residue distances via ion/ion reactions between gaseous α-synuclein cations and disulfonic acid linkers that form strong electrostatic bonds. We also combined results from in-solution protein crosslinking identified from native tandem mass spectrometry (MS/MS) with an initial αSN ensemble generated computationally by IDPConformerGenerator to generate an experimentally restrained solution ensemble of αSN. CCS distributions were directly calculated for the solution ensembles determined by NMR and compared to predicted gaseous conformers. While charge state and collision cross section distributions are useful for qualitatively describing the relative structural dynamics of proteins and major conformational changes induced by changes to solution states, the predicted and measured gas phase conformers include subpopulations that are significantly different than those expected from completely "freezing" solution conformations and preserving them in the gas phase. However, insights were gained on the various roles of solvent in stabilizing various conformers for extremely dynamic proteins like α-synuclein.