A united residue force-field for calcium-protein interactions

Coarse-grained modeling of the calcium, sodium, magnesium and potassium cations interacting with proteins

Metal ions play important biological roles, e.g., activation or deactivation of enzymatic reactions and signal transduction. Moreover, they can stabilize protein structure, or even be actively involved in the protein folding process. Therefore, accurate treatment of the ions is crucial to model and investigate biological phenomena properly. In this work the coarse-grained UNRES (UNited RESidue) force field was extended to include the interactions between proteins and four alkali or alkaline earth metal cations of biological significance, i.e., calcium, magnesium, sodium and potassium. Additionally, chloride anions were introduced as counter-ions. Parameters were derived from all-atom simulations and incorporate water in an implicit manner. The new force field was tested on the set of the proteins and was able to reproduce the ion-binding preferences.

Molecular chaperone RAP interacts with LRP1 in a dynamic bivalent mode and enhances folding of ligand-binding regions of other LDLR family receptors

The low-density lipoprotein receptor (LDLR) family of receptors are cell-surface receptors that internalize numerous ligands and play crucial role in various processes, such as lipoprotein metabolism, hemostasis, fetal development, etc. Previously, receptor-associated protein (RAP) was described as a molecular chaperone for LDLR-related protein 1 (LRP1), a prominent member of the LDLR family. We aimed to verify this role of RAP for LRP1 and two other LDLR family receptors, LDLR and vLDLR, and to investigate the mechanisms of respective interactions using a cell culture model system, purified system, and in silico modelling. Upon coexpression of RAP with clusters of the ligand-binding complement repeats (CRs) of the receptors in secreted form in insect cells culture, the isolated proteins had increased yield, enhanced folding, and improved binding properties compared with proteins expressed without RAP, as determined by circular dichroism and surface plasmon resonance. Within LRP1 CR-clusters II and IV, we identified multiple sites comprised of adjacent CR doublets, which provide alternative bivalent binding combinations with specific pairs of lysines on RAP. Mutational analysis of these lysines within each of isolated RAP D1/D2 and D3 domains having high affinity to LRP1 and of conserved tryptophans on selected CR-doublets of LRP1, as well as in silico docking of a model LRP1 CR-triplet with RAP, indicated a universal role for these residues in interaction of RAP and LRP1. Consequently, we propose a new model of RAP interaction with LDLR family receptors based on switching of the bivalent contacts between molecules over time in a dynamic mode.

Structural characterization of calcium-binding sunflower seed and peanut peptides and enhanced calcium transport by calcium complexes in Caco-2 cells

BACKGROUND

Peptide-Ca complexes can promote Ca absorption. The present study aimed to determine the transport mechanism and structural characteristics of sunflower seed and peanut peptides with high Ca binding capacity with respect to developing third-generation Ca supplements and functional food ingredients.

RESULTS

High Ca-binding fractions of 1-3 kDa sunflower seed peptide (SSP₄ ) and ≥ 10 kDa peanut peptide (PP₁ ) had higher amount of Ca transported than CaCl₂ and two hydrolyzed proteins in Caco-2 cells. SSP₄ and PP₁ were separated by Ca ion metal chelate affinity chromatography, and high Ca-binding fractions were observed for SSP₄ -P₂ and PP₁ -P₂ . The amino acid sequences of SSP₄ -P₂ and PP₁ -P₂ were characterized by high-performance liquid chromatography-electrospray ionization-time of flight mass spectrometry. Seven and eight peptides were identified from SSP₄ -P₂ and PP₁ -P₂ , respectively. These peptides had molecular weights ranging from 1500 Da to 2500 Da and a large number of characteristic amino acid sequences, such as EEEQQQ, EQ-QQQ-QQ, QQ-QQQQQ, E-EEE, EE-EEQ, RR, Q-QQ-QQQ, EE-EQ-EE-Q, QQ-QQQQ, and Q-QQQQ, where 'E' is glutamic acid and 'Q' is glutamine.

CONCLUSION

SSP₄ and PP₁ can promote Ca transport in Caco-2 cells without affecting cell permeability. The amino acid sequences of SSP₄ -P₂ and PP₁ -P₂ with high Ca-binding abilities contain characteristic sequences, such as continuous glutamic acid and glutamine, and have low molecular weights. © 2020 Society of Chemical Industry.

Calcium Delivery System Assembled by a Nanostructured Peptide Derived from the Sea Cucumber Ovum

In this study, the binding mechanism, morphological, and conformational analysis of the complex of a sea cucumber ovum derived octapeptide (EDLAALEK) with Ca²⁺ as well as its calcium delivery behavior via the gastrointestinal (GI) tract were investigated. The Ca²⁺ specifically bound to two carboxyl oxygen atoms of C-terminal Glu and Asp on the EDLAALEK peptide at a stoichiometric ratio of 1:1. Calcium coordination induced the self-assembly of the EDLAALEK peptide, resulting in the formation of a nanocomposite with a crystal structure. Furthermore, the formed nanocomposite went through dissociation and self-assembly during in vitro GI digestion, accompanied by the release and rechelation of Ca²⁺, which was related to changes in their secondary structure. Nevertheless, the GI digests of the EDLAALEK-calcium complex could significantly enhance Ca²⁺ absorption across Caco-2 cell monolayers. The findings suggest that the sea cucumber ovum derived peptide has the potential as an efficient nanocarrier to transport calcium through the GI system.

Introduction of Phosphorylated Residues into the UNRES Coarse-Grained Model: Toward Modeling of Signaling Processes

Phosphorylated proteins take part in many signaling pathways and play a key role in homeostasis regulation. The all-atom force fields enable us to study the systems containing phosphorylated proteins, but they are limited to short time scales. In this paper, we report the extension of the physics-based coarse-grained UNRES force field to treat systems with phosphorylated amino-acid residues. To derive the respective potentials, appropriate physics-based analytical expressions were fitted to the potentials of mean force of systems modeling phosphorylated amino-acid residues computed in our previous work and implemented in UNRES. The extended UNRES performed well in ab initio simulations of two miniproteins containing phosphorylated residues, strongly suggesting that realistic large-scale simulations of processes involving phosphorylated proteins, especially signaling processes, are now possible.

The formation mechanism of a sea cucumber ovum derived heptapeptide–calcium nanocomposite and its digestion/absorption behavior

Calcium coordination induced the self-assembly of the sea cucumber ovum derived heptapeptide (NDEELNK), resulting in the formation of the nanocomposite with potential function to transport calcium through the gastrointestinal system.

A novel calcium-binding peptide from Antarctic krill protein hydrolysates and identification of binding sites of calcium-peptide complex

Trypsin was used for preparing peptides with high calcium-binding capacity from Antarctic krill. Hydroxyapatite chromatography (HAC), size-exclusion chromatography (SEC), and reversed phase high performance liquid chromatography (RP-HPLC) were used to capture and purify calcium-binding peptides. The peptide sequence was determined to be VLGYIQIR (N- to C-terminal, MW = 960.58 Da), using LTQ Orbitrap XL. According to the results of FTIR and mass spectrometry, chelating site of calcium ions may possibly involve the carbonal or amino groups of Gln, Ile and Arg residues. Molecular dynamic simulation showed the conformation of peptide was markedly varied, and the distance between calcium ion and Gln and Ile residues was changing all the time. However, the distance between calcium ion and carboxyl oxygen of arginine residues was not changed significantly from 2 ns to 100 ns. Identified peptide can be used as a novel calcium supplement.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

Molecular mechanics

Molecular Mechanics (MM) force fields are the methods of choice for protein simulations, which are essential in the study of conformational flexibility. Given the importance of protein flexibility in drug binding, MM is involved in most if not all Computational Structure-Based Drug Discovery (CSBDD) projects. This paper introduces the reader to the fundamentals of MM, with a special emphasis on how the target data used in the parametrization of force fields determine their strengths and weaknesses. Variations and recent developments such as polarizable force fields are discussed. The paper ends with a brief overview of common force fields in CSBDD.

Improvement on the modified Lowry method against interference of divalent cations in soluble protein measurement

This paper systematically investigated the interference of calcium and magnesium in protein measurement with a modified Lowry method first proposed by Frølund et al. (Appl Microbiol Biotechnol 43:755-761, 1995). This interference has in the past been largely ignored resulting in variable and unreliable results when applied to natural water matrices. We discovered significant formation of calcium and magnesium precipitates that lead to a decline in light absorbance at 750 nm during protein determination. Underestimation of protein concentration (sometimes even yielding negative concentrations) and low experiment reproducibility were demonstrated at high concentrations of divalent cations (e.g., [Ca(2+)] over 1 mmol L(-1)). To eliminate interference from calcium and magnesium, two pretreatment strategies were established based on cation exchange and dialysis. These pretreatments were convenient and were found to be highly effective in removing calcium and magnesium in protein samples. By using the modified Lowry method with these pretreatments, proteins in standard solutions and in wastewater samples were successfully quantified with good reliability and reproducibility. In addition, we demonstrated that simultaneous quantification of humic substances with the modified Lowry method was not affected by the two pretreatments. These approaches are expected to be applicable to protein and humic substance determination in different research fields, in cases where the modified Lowry method is sensitive to divalent cation concentrations.

Docking of calcium ions in proteins with flexible side chains and deformable backbones

A method of docking Ca(2+) ions in proteins with flexible side chains and deformable backbones is proposed. The energy was calculated with the AMBER force field, implicit solvent, and solvent exposure-dependent and distance-dependent dielectric function. Starting structures were generated with Ca(2+) coordinates and side-chain torsions sampled in 1000 A(3) cubes centered at the experimental Ca(2+) positions. The energy was Monte Carlo-minimized. The method was tested on fourteen Ca(2+)-binding sites. For twelve Ca(2+)-binding sites the root mean square (RMS) deviation of the apparent global minimum from the experimental structure was below 1.3 and 1.7 A for Ca(2+) ions and side-chain heavy atoms, respectively. Energies of multiple local minima correlate with the RMS deviations from the X-ray structures. Two Ca(2+)-binding sites at the surface of proteinase K were not predicted, because of underestimation of Ca(2+) hydration energy by the implicit-solvent method.

Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach

Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins irrespective of sequence similarity. This work explores support vector machines (SVM) as such a method. SVM prediction systems were developed by using 53,333 metal-binding and 147,347 non-metal-binding proteins, and evaluated by an independent set of 31,448 metal-binding and 79,051 non-metal-binding proteins. The computed prediction accuracy is 86.3%, 81.6%, 83.5%, 94.0%, 81.2%, 85.4%, 77.6%, 90.4%, 90.9%, 74.9% and 78.1% for calcium-binding, cobalt-binding, copper-binding, iron-binding, magnesium-binding, manganese-binding, nickel-binding, potassium-binding, sodium-binding, zinc-binding, and all metal-binding proteins respectively. The accuracy for the non-member proteins of each class is 88.2%, 99.9%, 98.1%, 91.4%, 87.9%, 94.5%, 99.2%, 99.9%, 99.9%, 98.0%, and 88.0% respectively. Comparable accuracies were obtained by using a different SVM kernel function. Our method predicts 67% of the 87 metal-binding proteins non-homologous to any protein in the Swissprot database and 85.3% of the 333 proteins of known metal-binding domains as metal-binding. These suggest the usefulness of SVM for facilitating the prediction of metal-binding proteins. Our software can be accessed at the SVMProt server http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.

Predicting calcium-binding sites in proteins - a graph theory and geometry approach

Identifying calcium-binding sites in proteins is one of the first steps towards predicting and understanding the role of calcium in biological systems for protein structure and function studies. Due to the complexity and irregularity of calcium-binding sites, a fast and accurate method for predicting and identifying calcium-binding protein is needed. Here we report our development of a new fast algorithm (GG) to detect calcium-binding sites. The GG algorithm uses a graph theory algorithm to find oxygen clusters of the protein and a geometric algorithm to identify the center of these clusters. A cluster of four or more oxygen atoms has a high potential for calcium binding. High performance with about 90% site sensitivity and 80% site selectivity has been obtained for three datasets containing a total of 123 proteins. The results suggest that a sphere of a certain size with four or more oxygen atoms on the surface and without other atoms inside is necessary and sufficient for quickly identifying the majority of the calcium-binding sites with high accuracy. Our finding opens a new avenue to visualize and analyze calcium-binding sites in proteins facilitating the prediction of functions from structural genomic information.