In silico modeling and experimental evidence of coagulant protein interaction with precursors for nanoparticle functionalization

The design of novel protein–nanoparticle hybrid systems has applications in many fields of science ranging from biomedicine, catalysis, water treatment, etc. The main barrier in devising such tool is lack of adequate information or poor understanding of protein–ligand chemistry. Here, we establish a new strategy based on computational modeling for protein and precursor linkers that can decorate the nanoparticles. Moringa oleifera (MO_2.1) seed protein that has coagulation and antimicrobial properties was used. Superparamagnetic nanoparticles (SPION) with precursor ligands were used for the protein–ligand interaction studies. The molecular docking studies reveal that there are two binding sites, one is located at the core binding site; tetraethoxysilane (TEOS) or 3-aminopropyl trimethoxysilane (APTES) binds to this site while the other one is located at the side chain residues where trisodium citrate (TSC) or Si₆₀ binds to this site. The protein–ligand distance profile analysis explains the differences in functional activity of the decorated SPION. Experimentally, TSC-coated nanoparticles showed higher coagulation activity as compared to TEOS- and APTES-coated SPION. To our knowledge, this is the first report on in vitro experimental data, which endorses the computational modeling studies as a powerful tool to design novel precursors for functionalization of nanomaterials; and develop interface hybrid systems for various applications.     

Free energy simulations for protein ligand binding and stability

Abstract

We summarize several computational techniques to determine relative free energies for condensed-phase systems. The focus is on practical considerations which are capable of making direct contact with experiments. Particular applications include the thermodynamic stability of apo- and holo-myoglobin, insulin dimerization free energy, ligand binding in lysozyme, and ligand diffusion in globular proteins. In addition to provide differential free energies between neighboring states, converged umbrella sampling simulations provide insight into migration barriers and ligand dissociation barriers and analysis of the trajectories yield additional insight into the structural dynamics of fundamental processes. Also, such simulations are useful tools to quantify relative stability changes for situations where experiments are difficult. This is illustrated for NO-bound myoglobin. For the dissociation of benzonitrile from lysozyme it is found that long umbrella sampling simulations are required to approximately converge the free energy profile. Then, however, the resulting differential free energy between the bound and unbound state is in good agreement with estimates from molecular mechanics with generalized Born surface area simulations. Furthermore, comparing the barrier height for ligand escape suggests that ligand dissociation contains a non-equilibrium component.     

Biosorption of trivalent and hexavalent chromium from aqueous systems using shelled Moringa oleifera seeds

Abstract

The present study explores the sorption properties of shelled Moringa oleifera seeds (SMOS) for removal of two environmentally important oxidation states of chromium (trivalent and hexavalent) from an aqueous system on the laboratory scale. Sorption studies reveal the optimum conditions for the removal of 81.02%; Cr (III) and 88.15% Cr (VI) as follows: biomass dosage (4.0 g), metal concentration [25mg/L for Cr (III); 50mg/L for Cr (VI)], contact time (40 minutes) at pH 6.5 and 2.5 respectively. The adsorption data were found to fit well both the Freundlich and Langmuir isotherms. Characterization of the seed powder by FTIR showed the clear presence of amino acid moieties having both positively charged amino and negatively charged carboxylic groups and confirmed that biosorption involves amino acid-chromium interactions. SEM studies of native and exhausted [Cr(III) and Cr(VI)] treated SMOS revealed large spherical clusters having a pore area of 8.66 µm² in the case of native SMOS while dense agglomerated etched dendrite type morphology have a pore area of 0.80 µm² in Cr (III) and 0.78 µm² in Cr (VI) treated SMOS The spent biosorbent was regenerated and found to be effectively reusable for four cycles.     

Dimerization of the p53 oligomerization domain: identification of a folding nucleus by molecular dynamics simulations

Dimerization of the p53 oligomerization domain involves coupled folding and binding of monomers. To examine the dimerization, we have performed molecular dynamics (MD) simulations of dimer folding from the rate-limiting transition state ensemble (TSE). Among 799 putative transition state structures that were selected from a large ensemble of high-temperature unfolding trajectories, 129 were identified as members of the TSE via calculation of a 50% transmission coefficient from at least 20 room-temperature simulations. This study is the first to examine the refolding of a protein dimer using MD simulations in explicit water, revealing a folding nucleus for dimerization. Our atomistic simulations are consistent with experiment and offer insight that was previously unobtainable.     

Wing 1 of protein HOP2 is as important as helix 3 in DNA binding by MD simulation

The repair of programmed DNA double-strand breaks through recombination is required for proper association and disjunction of the meiotic homologous chromosomes. Meiosis-specific protein HOP2 plays essential roles in recombination by promoting recombinase activities. The N-terminal domain of HOP2 interacts with DNA through helix 3 (H3) and wing 1 (W1). Mutations in wing 1 (Y65A/K67A/Q68A) slightly weakened the binding but mutations in helices 2 and 3 (Q30A/K44A/K49A) nearly abolished the binding. To better understand such differential effects at atomic level, molecular dynamics simulations were employed. Despite losing some hydrogen bonds, the W1-mutant DNA complex was rescued by stronger hydrophobic interactions. For the wild type and W1-mutant, the protein was found to slide along the DNA grooves as the DNA rolls along its double-helix axis. This motion could be functionally important to facilitate the precise positioning of the single-stranded DNA with the homologous double-stranded DNA. The sliding motion was reduced in the W1-mutant. The H-mutant nearly lost all intermolecular interactions. Moreover, an additional mutation in wing 1 (Y65A/K67A/Q68A/K69A) also caused complete complex dissociation. Therefore, both wing 1 and helix 3 make important contribution to the DNA binding, which could be important to the strand invasion function of HOP2 homodimer and HOP2-MND1 heterodimer. Similar to cocking a medieval crossbow with the archer’s foot placed in the stirrup, wing 1 may push the minor groove to cause distortion while helix 3 grabs the major groove.     

An integrated in silico approach to understand protein–protein interactions: human meprin-β with fetuin-A

Abstract

Human meprin-β, a zinc metalloprotease belonging to the astacin family, have been found to be associated with many pathological conditions like inflammatory bowel disease, fibrosis and neurodegenerative disease. The inhibition of meprin-β by various inhibitors, both macromolecular and small molecules, is crucial in the control of several diseases. Human fetuin-A, a negative acute phase protein involved in inflammatory disease, has recently been identified as an endogenous inhibitor for meprin-β. In this computational study, an integrated in silico approach was performed using existing structural information of meprin-β coupled with ab initio modelling of human fetuin-A to predict a rational model of the complex through protein–protein docking. Further, the models were optimized and validated to generate an ensemble of conformations through extensive molecular dynamics simulation. Virtual alanine scanning mutagenesis was explored to identify hotspot residues on both proteins significant for protein–protein interaction (PPI). The results of the study provide structural insight into PPI between meprin-β and fetuin-A which can be useful in designing molecules to modulate meprin-β activity.

Communicated by Ramaswamy H. Sarma     

Zika virus NS5 protein potential inhibitors: an enhanced in silico approach in drug discovery

The re-emerging Zika virus (ZIKV) is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus has already been linked to irreversible chronic central nervous system conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of ZIKV Methyltransferase and RNA dependent RNA polymerase. This in silico ‘per-residue energy decomposition pharmacophore’ virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.     

Finding biologically relevant protein domain interactions: conserved binding mode analysis

Proteins evolved through the shuffling of functional domains, and therefore, the same domain can be found in different proteins and species. Interactions between such conserved domains often involve specific, well-determined binding surfaces reflecting their important biological role in a cell. To find biologically relevant interactions we developed a method of systematically comparing and classifying protein domain interactions from the structural data. As a result, a set of conserved binding modes (CBMs) was created using the atomic detail of structure alignment data and the protein domain classification of the Conserved Domain Database. A conserved binding mode is inferred when different members of interacting domain families dock in the same way, such that their structural complexes superimpose well. Such domain interactions with recurring structural themes have greater significance to be biologically relevant, unlike spurious crystal packing interactions. Consequently, this study gives lower and upper bounds on the number of different types of interacting domain pairs in the structure database on the order of 1000-2000. We use CBMs to create domain interaction networks, which highlight functionally significant connections by avoiding many infrequent links between highly connected nodes. The CBMs also constitute a library of docking templates that may be used in molecular modeling to infer the characteristics of an unknown binding surface, just as conserved domains may be used to infer the structure of an unknown protein. The method's ability to sort through and classify large numbers of putative interacting domain pairs is demonstrated on the oligomeric interactions of globins.     

Structure prediction and molecular dynamics simulations of a G-protein coupled receptor: human CCR2 receptor

CC chemokine receptor type-2 (CCR2) is a member of G-protein coupled receptors superfamily, expressed on the cell surface of monocytes and macrophages. It binds to the monocyte chemoattractant protein-1, a CC chemokine, produced at the sites of inflammation and infection. A homology model of human CCR2 receptor based on the recently available C-X-C chemokine recepor-4 crystal structure has been reported. Ligand information was used as an essential element in the homology modeling process. Six known CCR2 antagonists were docked into the model using simple and induced fit docking procedure. Docked complexes were then subjected to visual inspection to check their suitability to explain the experimental data obtained from site directed mutagenesis and structure-activity relationship studies. The homology model was refined, validated, and assessed for its performance in docking-based virtual screening on a set of CCR2 antagonists and decoys. The docked complexes of CCR2 with the known antagonists, TAK779, a dual CCR2/CCR5 antagonist, and Teijin-comp1, a CCR2 specific antagonist were subjected to molecular dynamics (MD) simulations, which further validated the binding modes of these antagonists. B-factor analysis of 20?ns MD simulations demonstrated that Cys190 is helpful in providing structural rigidity to the extracellular loop (EL2). Residues important for CCR2 antagonism were recognized using free energy decomposition studies. The acidic residue Glu291 from TM7, a conserved residue in chemokine receptors, is favorable for the binding of Teijin-comp1 with CCR2 by ΔG of ?11.4?kcal/mol. Its contribution arises more from the side chains than the backbone atoms. In addition, Tyr193 from EL2 contributes ?0.9?kcal/mol towards the binding of the CCR2 specific antagonist with the receptor. Here, the homology modeling and subsequent molecular modeling studies proved successful in probing the structure of human CCR2 chemokine receptor for the structure-based virtual screening and predicting the binding modes of CCR2 antagonists.     

ChikvInt: a Chikungunya virus–host protein–protein interaction database

Chikungunya is a fast-mutating virus causing Chikungunya virus disease (ChikvD) with a significant load of disability-adjusted life years (DALY) around the world. The outbreak of this virus is significantly higher in the tropical countries. Several experiments have identified crucial viral–host protein–protein interactions (PPIs) between Chikungunya Virus (Chikv) and the human host. However, no standard database that catalogs this PPI information exists. Here we develop a Chikv-Human PPI database, ChikvInt, to facilitate understanding ChikvD disease pathogenesis and the progress of vaccine studies. ChikvInt consists of 109 interactions and is available at www.chikvint.com .     

Combining features in a graphical model to predict protein binding sites

Large efforts have been made in classifying residues as binding sites in proteins using machine learning methods. The prediction task can be translated into the computational challenge of assigning each residue the label binding site or non‐binding site. Observational data comes from various possibly highly correlated sources. It includes the structure of the protein but not the structure of the complex. The model class of conditional random fields (CRFs) has previously successfully been used for protein binding site prediction. Here, a new CRF‐approach is presented that models the dependencies of residues using a general graphical structure defined as a neighborhood graph and thus our model makes fewer independence assumptions on the labels than sequential labeling approaches. A novel node feature “change in free energy” is introduced into the model, which is then denoted by ΔF‐CRF. Parameters are trained with an online large‐margin algorithm. Using the standard feature class relative accessible surface area alone, the general graph‐structure CRF already achieves higher prediction accuracy than the linear chain CRF of Li et al. ΔF‐CRF performs significantly better on a large range of false positive rates than the support‐vector‐machine‐based program PresCont of Zellner et al. on a homodimer set containing 128 chains. ΔF‐CRF has a broader scope than PresCont since it is not constrained to protein subgroups and requires no multiple sequence alignment. The improvement is attributed to the advantageous combination of the novel node feature with the standard feature and to the adopted parameter training method. Proteins 2015; 83:844–852. © 2015 Wiley Periodicals, Inc.     

Scoring a diverse set of high-quality docked conformations: a metascore based on electrostatic and desolvation interactions

Predicting protein-protein interactions involves sampling and scoring docked conformations. Barring some large structural rearrangement, rapidly sampling the space of docked conformations is now a real possibility, and the limiting step for the successful prediction of protein interactions is the scoring function used to reduce the space of conformations from billions to a few, and eventually one high affinity complex. An atomic level free-energy scoring function that estimates in units of kcal/mol both electrostatic and desolvation interactions (plus van der Waals if appropriate) of protein-protein docked conformations is used to rerank the blind predictions (860 in total) submitted for six targets to the community-wide Critical Assessment of PRediction of Interactions (CAPRI; http://capri.ebi.ac.uk). We found that native-like models often have varying intermolecular contacts and atom clashes, making unlikely that one can construct a universal function that would rank all these models as native-like. Nevertheless, our scoring function is able to consistently identify the native-like complexes as those with the lowest free energy for the individual models of 16 (out of 17) human predictors for five of the targets, while at the same time the modelers failed to do so in more than half of the cases. The scoring of high-quality models developed by a wide variety of methods and force fields confirms that electrostatic and desolvation forces are the dominant interactions determining the bound structure. The CAPRI experiment has shown that modelers can predict valuable models of protein-protein complexes, and improvements in scoring functions should soon solve the docking problem for complexes whose backbones do not change much upon binding. A scoring server and programs are available at http://structure.pitt.edu.     

Stability scale and atomic solvation parameters extracted from 1023 mutation experiments

The stability scale of 20 amino acid residues is derived from a database of 1023 mutation experiments on 35 proteins. The resulting scale of hydrophobic residues has an excellent correlation with the octanol-to-water transfer free energy corrected with an additional Flory-Huggins molar-volume term (correlation coefficient r = 0.95, slope = 1.05, and a near zero intercept). Thus, hydrophobic contribution to folding stability is characterized remarkably well by transfer experiments. However, no corresponding correlation is found for hydrophilic residues. Both the hydrophilic portion and the entire scale, however, correlate strongly with average burial accessible surface (r = 0.76 and 0.97, respectively). Such a strong correlation leads to a near uniform value of the atomic solvation parameters for atoms C, S, O/N, O(-0.5), and N(+0.5,1). All are in the range of 12-28 cal x mol(-1) A(-2), close to the original estimate of hydrophobic contribution of 25-30 cal x mol(-1) A(-2) to folding stability. Without any adjustable parameters, the new stability scale and new atomic solvation parameters yielded an accurate prediction of protein-protein binding free energy for a separate database of 21 protein-protein complexes (r = 0.80 and slope = 1.06, and r = 0.83 and slope = 0.93, respectively).     

Ligand binding energy and enzyme efficiency from reductions in protein dynamics

Tetrameric rabbit muscle glyceraldehyde 3-phosphate dehydrogenase (GAPDH; EC 1.2.1.12) binds successively four molecules of its cofactor (NAD+) with affinities of ca 10(11) M(-1), 10(9) M(-1), 10(7) M(-1), and 10(5) M(-1). The reduction in the dynamics of the protein is greatest upon binding the first NAD+ molecule. Smaller reductions then occur upon binding the second and third NAD+ molecules, and the fourth NAD+ molecule binds without dynamic change. Reduction of the GAPDH dynamics, with consequent improvements in its internal bonding, can account for the increase in NAD+ binding affinity from 10(5) M(-1) to 10(11) M(-1). Evidence is provided that comparable fractions of the binding energy of other ligands, and of the catalytic efficiency of enzymes, may be derived in the same way.     

Investigating the linkage between disease‐causing amino acid variants and their effect on protein stability and binding

Single amino acid variations (SAV) occurring in human population result in natural differences between individuals or cause diseases. It is well understood that the molecular effect of SAV can be manifested as changes of the wild type characteristics of the corresponding protein, among which are the protein stability and protein interactions. Typically the effect of SAV on protein stability and interactions was assessed via the changes of the wild type folding and binding free energies. However, in terms of SAV affecting protein functionally and disease susceptibility, one wants to know to what extend the wild type function is perturbed by the SAV. Here it is demonstrated that relative, rather than the absolute, change of the folding and binding free energy serves as a good indicator for SAV association with disease. Using HumVar as a source for disease‐causing SAV and experimentally determined free energy changes from ProTherm and SKEMPI databases, correlation coefficients (CC) between the disease index and relative folding and binding probability indexes, respectively, was achieved. The obtained CCs demonstrated the applicability of the proposed approach and it served as good indicator for SAV association with disease. Proteins 2016; 84:232–239. © 2015 Wiley Periodicals, Inc.     

Thermitase, a thermostable subtilisin: comparison of predicted and experimental structures and the molecular cause of thermostability

The Subtilisin family of proteases has four members of known sequence and structure: subtilisin Carlsberg, Subtilisin novo, proteinase K, and thermitase. Using thermitase as a test case, we ask two questions. How good are methods for model building a three-dimensional structure of a protein based on sequence homology to a known structure? And what are the molecular causes of thermostability? First, we compare predicted models of thermitase, refined by energy minimization and varied by molecular dynamics, with the preliminary crystal structure. The predictions work best in the conserve structural core and less well in seven loop regions involving insertions and deletions relative to Subtilisin. Here, variation of loop regions by molecular dynamics simulation in vacuo followed by energy minimization does not improve the prediction since we find no correlation between in vacuo energy and correctness of structure when comparing local energy minima. Second, in order to identify the molecular case of thermostability we confront hypotheses erived by calculation of the details of interatomic interactions with inactivation experiments. As a result, we can exclude salt bridges and hydrophobic interactions as main cause of thermostability. Based on a combination of theoretical and experimental evidence, the unusually tight binding of calcium by thermitase emerges as the most likely single influence responsible for its increased thermostability.     

In silico analyses of substrate interactions with human serum paraoxonase 1

Human paraoxonase (HuPON1) is a serum enzyme that exhibits a broad spectrum of hydrolytic activities, including the hydrolysis of various organophosphates, esters, and recently identified lactone substrates. Despite intensive site-directed mutagenesis and other biological studies, the structural basis for the specificity of substrate interactions of HuPON1 remains elusive. In this study, we apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the binding interactions of HuPON1 with representative substrates. The results suggest that the active site of HuPON1 is characterized by two distinct binding regions: the hydrophobic binding site for arylesters/lactones, and the paraoxon binding site for phosphotriesters. The unique binding modes proposed for each type of substrate reveal a number of key residues governing substrate specificity. The polymorphic residue R/Q192 interacts with the leaving group of paraoxon, suggesting it plays an important role in the proper positioning of this substrate in the active site. MD simulations of the optimal binding complexes show that residue Y71 undergoes an "open-closed" conformational change upon ligand binding, and forms strong interactions with substrates. Further binding free energy calculations and residual decomposition give a more refined molecular view of the energetics and origin of HuPON1/substrate interactions. These studies provide a theoretical model of substrate binding and specificity associated with wild type and mutant forms of HuPON1, which can be applied in the rational design of HuPON1 variants as bioscavengers with enhanced catalytic activity.     

Helix-capping interaction in λ cro protein: A free energy simulation analysis

The stability mutant Tyr-26 → Asp was studied in the Cro protein from bacteriophage λ using free energy molecular dynamics simulations. The mutant was calculated to be more stable than the wild type by 3.0 ± 1.7 kcal/mol/monomer, in reasonable agreement with experiment (1.4 kcal/mol/monomer). Moreover, the aspartic acid in the mutant was found to form a capping interation with the amino terminus of the third α-helix of Cro. The simulations were analyzed to understand better the source of the stability of this helix-capping interaction and to examine the results in light of previous explanations of stabilizing helix caps-namely, a model of local unsatisfied hydrogen bonds at the helix termini and the helix macro dipole model. Analysis of the simulations shows that the stabilizing effect of this charged helical cap is due both to favorable hydrogen bonds with backbone NH groups at the helix terminus and to favorable electrostatic interactions (but not hydrogen bonds) with their carbonyls (effectively the next row of local dipoles in the helix). However, electrostatic interactions are weak or negligible with backbone dipolar groups in the helix further away from the terminus. Moreover, the importance of other local electrostatic interactions with polar side chains near the helix terminus, which are neglected in most treatments of this effect, are shown to be important. Thus, the results support a model that is intermediate between the two previous explanations: both unsatisfied hydrogen bonds at the helix terminus and other, local preoriented dipolar groups stabilize the helix cap. These findings suggest that similar interactions with preoriented dipolar groups may be important for cooperativity in other charge–dipole interactions and may be employed to advantage for molecular design. © 1994 Wiley-Liss, Inc.