Screening the molecular surface of human anticoagulant protein C: A search for interaction sites

Protein C (PC), a 62 kDa multi-modular zymogen, is activated to an anticoagulant serine protease (activated PC or APC) by thrombin bound to thrombomodulin on the surface of endothelial cells. PC/APC interacts with many proteins and the characterisation of these interactions is not trivial. However, molecular modelling methods help to study these complex biological processes and provide basis for rational experimental design and interpretation of the results. PC/APC consists of a Gla domain followed by two EGF modules and a serine protease domain. In this report, we present two structural models for full-length APC and two equivalent models for full-length PC, based on the X-ray structures of Gla-domainless APC and of known serine protease zymogens. The overall elongated shape of the models is further cross-validated using size exclusion chromatography which allows evaluation of the Stokes radius (r_s for PC = 33.15 Å r_s for APC = 34.19 Å), frictional ratio and axial ratio. We then propose potential binding sites at the surface of PC/APC using surface hydrophobicity as a determinant of the preferred sites of intermolecular recognition. Most of the predicted binding sites are consistent with previously reported experimental data, while some clusters highlight new regions that should be involved in protein-protein interactions.     

N-glycosylation of High Mobility Group Box 1 protein (HMGB1) modulates the interaction with glycyrrhizin: A molecular modeling study

High Mobility Group Box 1 protein (HMGB1) is an abundant protein with multiple functions in cells, acting as a DNA chaperone and damage-associated molecular pattern molecule. It represents an attractive target for the treatment of inflammatory diseases and cancers. The plant natural product glycyrrhizin (GLR) is a well-characterized ligand of HMGB1 and a drug used to treat diverse liver and skin diseases. The drug is known to bind to each of the two adjacent HMG boxes of the non-glycosylated protein. In cells, HMGB1 is N-glycosylated at three asparagine residues located in boxes A and B, and these N-glycans are essential for the nucleocytoplasmic transport of the protein. But the impact of the N-glycans on drug binding is unknown. Here we have investigated the effect of the N-glycosylation of HMGB1 on its interaction with GLR using molecular modelling, after incorporation of three N-glycans on a Human HMGB1 structure (PDB code 2YRQ). Sialylated bi-antennary N-glycans were introduced on the protein and exposed in a folded or an extended conformation for the drug binding study. The docking of the drug was performed using both 18α- and 18β-epimers of GLR and the conformations and potential energy of interaction (ΔE) of the different drug-protein complexes were compared. The N-glycans do not shield the drug binding sites on boxes A and B but can modulate the drug-protein interaction, via both direct and indirect effects. The calculations indicate that binding of 18α/β-GLR to the HMG box is generally reduced when the protein is N-glycosylated vs. the non-glycosylated protein. In particular, the N-glycans in an extended configuration significantly weaken the binding of GLR to box-B. The effects of the N-glycans are mostly indirect, but in one case a direct contact with the drug, via a carbohydrate-carbohydrate interaction, was observed with 18β-GLR bound to Box-B of glycosylated HMGB1. For the first time, it is shown (at least in silico) that N-glycosylation, one of the many post-translational modifications of HMGB1, can affect drug binding.     

Boltzmann's principle,knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures

Summary The data base of known protein structures contains a tremendous amount of information on protein-solvent systems. Boltzmann's principle enables the extraction of this information in the form of potentials of mean force. The resulting force field constitutes an energetic model for protein-solvent systems. We outline the basic physical principles of this approach to protein folding and summarize several techniques which are useful in the development of knowledge-based force fields. Among the applications presented are the validation of experimentally determined protein structures, data base searches which aim at the identification of native-like sequence structure pairs, sequence structure alignments and the calculation of protein conformations from amino acid sequences.     

A molecular docking model of SARS-CoV S1 protein in complex with its receptor, human ACE2

The exact residues within severe acute respiratory syndrome coronavirus (SARS-CoV) S1 protein and its receptor, human ACE2, involved in their interaction still remain largely undetermined. Identification of exact amino acid residues that are crucial for the interaction of S1 with ACE2 could provide working hypotheses for experimental studies and might be helpful for the development of antiviral inhibitor. In this paper, a molecular docking model of SARS-CoV S1 protein in complex with human ACE2 was constructed. The interacting residue pairs within this complex model and their contact types were also identified. Our model, supported by significant biochemical evidence, suggested receptor-binding residues were concentrated in two segments of S1 protein. In contrast, the interfacial residues in ACE2, though close to each other in tertiary structure, were found to be widely scattered in the primary sequence. In particular, the S1 residue ARG453 and ACE2 residue LYS341 might be the key residues in the complex formation.     

Anticoagulatory Substances of Bloodsucking Animals: From Hirudin to Hirudin Mimetics

Bloodsucking animals contain substances in their saliva that specifically interfere with the blood clotting system. These substances are mainly low molecular weight proteins with a molecular mass of between 4 and 50 kDa. Some have become accessible in large quantities with the help of genetic engineering, and as a result their structures and structure—activity relationships have been studied and clinically tested. In the light of what is known about the mode of action of these natural products at the molecular level, new compounds with possible therapeutic effect can be derived. In the last ten years this approach has been tested with the proteinase inhibitor hirudin, obtained from medicinal leeches, and with the thrombin/hirudin complex. The serine protease thrombin plays a central role in the complex pathway of the blood clotting process and its pathophysiological effect finally results in thrombosis. The selectivity of the formation of complexes from hirudin and thrombin lies in the bivalent interaction of the inhibitor with the active site of the enzyme as well as with a substrate recognition site outside of the active site, the so-called fibrin-(ogen) binding site (FBS). The knowledge of this mode of action enabled the synthesis of bifunctional thrombin inhibitors based on hirudin peptides. Hirudin and hirudin mimetics in vivo have been shown to be highly potent anticoagulants for the treatment of arterial and venous thrombosis.     

维生素C的历史——从征服"海上凶神"到诺贝尔奖

This paper reviews the course of understanding vitamin C. From the "sea god" that sailors first encountered to the scurvy that caused the British Navy to suffer, understanding vitamin C is improved little by little. Until modern times, with the guidance of advanced theory and the rapid development of chemical research, human beings finally got to known vitamin C and conquered scurvy. This marks the arrival of a new era.     

Helical region of the potential energy surface of α-aminoisobutyric acid: A theoretical study

The helical region of the potential energy surface of blocked α-aminoisobutyric acid (Aib) dipeptide has been studied by using ab initio and semiempirical quantum mechanical methods, as well as force-field-derived methods. Depending on the method, an α-helix or a 3₁₀-helix is found to be the energy minimum. The conformations obtained from computations performed at the ab initio quantum mechanical level, as well as by using the AMBER force field, are in excellent agreement with X-ray data. Semiempirical results display some important differences with regard to experimental data. On the other hand, the CVFF force field predicts no energy minimum in the helical region of the Aib potential energy surface. © 1993 John Wiley & Sons, Inc.     

A theoretical model for the critical micelle concentration of bile salts

Critical micelle concentration (CMC) is a fundamental parameter in the evaluation of the biological activity of natural and synthetic bile salts. The CMC is logarithmically related to the free energy of solute micellization in aqueous solution. Hydrophobic and hydrogen bonding interaction energies were identified as the primary contributors to this free energy and the logarithm of the CMC was modeled as a linear function of relevant chemical group contributions to the solvent accessible molecular surface area of the solute. The structures (three-dimensional atomic coordinates) of 23 mono-, di-, and tri-hydroxyl bile acids were generated and optimized by energy minimization. The accessible surface area for each structure was computed and partitioned according to calculated charge distribution and polar group orientation. Experimental CMC values were fitted to these computed quantities by least squares multiple linear regression. Two regression equations, based on slightly different surface area partition schemes, were derived and compared. Their significance in explaining the aggregation process and in predicting the CMC of new bile salts is discussed.     

N-glycosylation and ubiquitinylation of PD-L1 do not restrict interaction with BMS-202: A molecular modeling study

The Programmed cell Death protein-1/Ligand 1 (PD-1/L1) checkpoint is a major target in oncology. Monoclonal antibodies targeting PD-1 or PD-L1 are used to treat different types of solid tumors and lymphoma. PD-L1-binding small molecules are also actively searched. The lead compound is the biphenyl drug BMS-202 which stabilizes PD-L1 protein dimers and displays a potent antitumor activity in experimental models. Here we have investigated the effect of N-glycosylation (at N35, N192, N200 and N219) and mono-ubiquitination (at K178) of PD-L1 on the interaction with BMS-202 by molecular modeling. Two complementary tridimensional models of PD-L1, based on available crystallographic structures, were constructed with BMS-202 bound. The structures were glycosylated, with a fucosylated bi-antennary N-glycan and ubiquitinated. Model 1 refers to glycoPD-L1 bearing 16 N-glycans, with or without 4 ubiquitin residues. Model 2 presents 8 N-glycans and 2 ubiquitin residues. In both cases, BMS-202 was bound to the protein interface, stabilizing a PD-L1 dimer. The incorporation of the N-glycans or the ubiquitins did not significantly alter the drug-protein recognition. The interface of the drug-stabilized protein dimer is unaffected by the glycosylation or ubiquitination. Calculations of the binding energies indicated that the glycosylation slightly reduces the stability of the drug-protein complexes but does not prevent the drug binding process. Our modeling study suggests that the drug can target efficiently the different forms of PD-L1 in cells, glycosylated, ubiquitinated or not. These models of N-glycosylated and ubiquitinated PD-L1 will be useful to study other PD-L1 protein complexes.     

A benchmark of optimally folded protein structures using integer programming and the 3D-HP-SC model

The Protein Structure Prediction (PSP) problem comprises, among other issues, forecasting the three-dimensional native structure of proteins using only their primary structure information. Most computational studies in this area use synthetic data instead of real biological data. However, the closer to the real-world, the more the impact of results and their applicability. This work presents 17 real protein sequences extracted from the Protein Data Bank for a benchmark to the PSP problem using the tri-dimensional Hydrophobic-Polar with Side-Chains model (3D-HP-SC). The native structure of these proteins was found by maximizing the number of hydrophobic contacts between the side-chains of amino acids. The problem was treated as an optimization problem and solved by means of an Integer Programming approach. Although the method optimally solves the problem, the processing time has an exponential trend. Therefore, due to computational limitations, the method is a proof-of-concept and it is not applicable to large sequences. For unknown sequences, an upper bound of the number of hydrophobic contacts (using this model) can be found, due to a linear relationship with the number of hydrophobic residues. The comparison between the predicted and the biological structures showed that the highest similarity between them was found with distance thresholds around 5.2–8.2 Å. Both the dataset and the programs developed will be freely available to foster further research in the area.     

A new thermodynamic model describes the effects of ligand density and type,salt concentration and protein species in hydrophobic interaction chromatography

A new thermodynamic model is derived that describes both loading and pulse-response behavior of proteins in hydrophobic interaction chromatography (HIC). The model describes adsorption in terms of protein and solvent activities, and water displacement from hydrophobic interfaces, and distinguishes contributions from ligand density, ligand type and protein species. Experimental isocratic response and loading data for a set of globular proteins on Sepharose™ resins of various ligand types and densities are described by the model with a limited number of parameters. The model is explicit in ligand density and may provide insight into the sensitivity of protein retention to ligand density in HIC as well as the limited reproducibility of HIC data.     

A simple mechanistic model to interpret the effects of narcotics

In this research we will show the advantages of using a time-independent dose metric in a mechanistic model to evaluate toxic effects for different narcotic compounds on different species. We will show how different already existing QSARs can be combined within a mechanistic framework to 1) make predictions of lethal thresholds; 2) show some limitations in the use of existing QSARs; 3) show how a mechanistic framework solves some conceptual problems in current approaches and 4) show how such a framework can be used to be of aid in an experimental setup in predicting the outcome of a survival experiment. The approach we chose is based on the simplest mechanistic model available, a scaled one-compartment model to describe uptake and elimination and hazard model to link the exposure to effects on survival. Within this theoretical framework a prediction for an internal threshold for effects on survival of 3 mmol/kg bw can be made, which should be similar for different species and independent of the partitioning characteristics of the toxicant. To demonstrate this, a threshold for 51 different species was derived, which indeed appeared to lie in a relatively small range, typically between 1 and 10 mmol/kg bw.     

Solvation effect on the vertical ionization energy of adenine-thymine base pair: From microhydration to bulk

In the present work, we investigate the effect of aqueous environment on the vertical ionization potential (VIP) of adenine-thymine (AT) base pair using a multilayer equation of the motion-coupled cluster method. The microsolvation can cause both blue-shift and red-shit of the IP values. However, the bulk water environment always results in the red-shift of the vertical ionization potential. Our study shows that the correct treatment of the short-range interaction plays an essential role in determining the magnitude of the red-shift. We have developed a biased sampling scheme based on Koopmans' energy, which can significantly speed up the convergence with respect to the number of solvent-solute configurations.     

A theoretical investigation on the geometry and vibrational spectra of 10,10,2,6,5-pentamethyl-1-hydroxychroman: a model of alpha-tocopherol

In the present study, density functional theory calculations with the combined Becke's three-parameter exchange functional in combination with the Lee, Yang, and Parr correlation functional (B3LYP) exchange-correlation energy functions were performed by using the 6-311G** basis set to study the structure and vibrational spectra of 10,10,2,6,5-pentamethyl-1-hydroxychroman (a model of alpha-tocopherol). The fully optimized geometry of the molecule was found to be very consistent with the X-ray crystal structure. The predicted vibrational frequencies made it possible to give a reliable assignment of the IR spectrum of the molecule according to the potential energy distributions (PEDs).     

The role of graphene interactions and geometry on thermal and electrical properties of epoxy nanocomposites: A theoretical to experimental approach

The influence of dispersion procedure and nanofiller geometry on thermal and electrical properties of graphene nanoplatelet (GNP) based composites has been investigated. A theoretical model, based on the contacts between adjacent nanoparticles, has been proposed aiming to connect thermal and electrical properties. It has been observed that GNP overlapping (type I) induces a decrease on thermal conductivity. Its effect on electrical conductivity is more complex and depends on the areas of overlap and in-plane contacts (type II). A higher type I area in comparison to type II implies an increase of electrical conductivity with overlapping whereas the opposite effect is found when type II area is higher than type I. The predicted results of the theoretical model fitted experimental measurements at different GNP contents and three roll milling processing conditions, giving a better overview of the influence of GNP geometry and interactions on electrical and thermal properties of nanocomposites.     

Tri-peptide reference structures for the calculation of relative solvent accessible surface area in protein amino acid residues

Relative amino acid residue solvent accessibility values allow the quantitative comparison of atomic solvent-accessible surface areas in different residue types and physical environments in proteins and in protein structural alignments. Geometry-optimised tri-peptide structures in extended solvent-exposed reference conformations have been obtained for 43 amino acid residue types at a high level of quantum chemical theory. Significant increases in side-chain solvent accessibility, offset by reductions in main-chain atom solvent exposure, were observed for standard residue types in partially geometry-optimised structures when compared to non-minimised models built from identical sets of proper dihedral angles abstracted from the literature. Optimisation of proper dihedral angles led most notably to marked increases of up to 54% in proline main-chain atom solvent accessibility compared to literature values. Similar effects were observed for fully-optimised tri-peptides in implicit solvent. The relief of internal strain energy was associated with systematic variation in N, C^α and C^β atom solvent accessibility across all standard residue types. The results underline the importance of optimisation of ‘hard’ degrees of freedom (bond lengths and valence bond angles) and improper dihedral angle values from force field or other context-independent reference values, and impact on the use of standardised fixed internal co-ordinate geometry in sampling approaches to the determination of absolute values of protein amino acid residue solvent accessibility. Quantum chemical methods provide a useful and accurate alternative to molecular mechanics methods to perform energy minimisation of peptides containing non-standard (chemically modified) amino acid residues frequently present in experimental protein structure data sets, for which force field parameters may not be available. Reference tri-peptide atomic co-ordinate sets including hydrogen atoms are made freely available.