Ns Molecular Dynamics Simulations Research Articles

A structure based pattern recognition on antibodies

Motivations. Protein-protein interactions are deeply involved in the antibody::antigen recognition process. Crystallographic data offer evidence of conformational changes between apo and holo forms of antibodies complexed with antigens. Nevertheless, the dynamical aspects of intermolecular relationships still remain a challenging issue. Extensive molecular dynamics (MD) simulations offer the suitable tool for generating statistical ensembles of conformations from which various energetic, structural and dynamic properties can be collected. The interaction energy correlations between all residue pairs can be investigated in order to find relevant regions involved in the fold stability; furthermore, a global overview of these sites can highlight preferential signaling pathways along the protein structures. In the present work, we will describe those conformational change events which derive from the formation of antibody::antigen complex. In particular, we will define those pathways that start from the paratope region and propagate through the immunoglobulin domains. Methods. We have taken into account a dataset of 24 Fab::antigen complexes, whose structures have been deposited at the Protein Data Bank. For most of them, 50ns unrestrained MD simulations were computed, with a 2fs time-step. Three structures targeting the same epitope and sharing similar paratopes were submitted to 200ns MD simulations. Each case of the dataset was duplicated, considering two systems: the isolated Fab structure (apo form) and the complex (holo form). An amount of 3,300ns of MD simulations was performed. The time-curves of RMSD on backbone atoms were used to monitor system equilibration. For every simulation the first 10ns were discarded for the further analyses. The structures sampled from the trajectories were clustered with the purpose of defining the conformational space explored. From the most representative structures (medoids) of the most populated clusters energy interaction matrices were calculated, considering all the non-bonded interactions between each residue pairs. Principal component analyses were performed over such matrices (Energy Decomposition Analysis), and only the relevant eigenvectors were considered. Since every component renders the relative contribution of each residue to the overall stabilization energy, we selected those components whose values are higher than a threshold value which depends on the number of the residues in the protein. All the residues were mapped to a common reference, obtained from joining the Chothia numbering schema with structural multiple alignment based schema, for variable and constant domains respectively. Finally, we mapped the energetic relevant residues of each case to the numbering schema depicted above, in order to summarize a common residue pattern referred to a generic Fab structure. We then collected the occurrencies for each position, and we termed them as Interaction Energy Recurrent Positions (IERPs). Results. The results obtained herein are intended at identifying those interactions that define the formation of antibody::antigen complexes. The correlated motions are also investigated, reducing the complex protein dynamics to its essential degrees of freedom. The analyses of global distance fluctuation matrices show that the motions of residues belonging to the same domain appear more correlated with each other. The constant domains of the heavy chain (CH) show a higher mobility, with respect to the remaining protein. The CH domains are close to the boundary between Fab and Fc fragments; hence, CH domains may benefit from a greater degree of unrestrained motion. From the interaction energy analyses, we collected three subset of IERPs: the first ones are extracted only from apo forms simulations, the second ones are typical of holo forms, the third ones appear as relevant in both forms. The distribution of these subsets along the polypeptide chains of the Fab structures indicates that heavy chains contain most of the shared IERPs; in contrast, it seem that apo and holo forms show differerential IERPs profiles along the sequence of light chains. Then, we compared the distribution of IERPs, typical of apo and holo forms, along the four Ig domains VH, VL, CH and CL. In holo forms CL domains show lesser amount of IERPs, while CH domains appear enriched; variable domains (VH and VL) do not show significant differences between apo and holo. In holo form, CL domains still mantain few sparse IERPs that could be considered as local stabilizing hotspots. The visual inspection of the structures of the dataset illuminates the spatial distribution of IERPs. In the antigen bound Fabs (holo forms) the selected residues starts from the framework regions of variable domains and propagate downstream, preferentially along the CH domain. Finally, the signal arrive at the base of costant domains, focusing around the C-terminal regions. On the opposite side unbound Fabs (apo forms) do not show a preferential pattern.

Multiple, Ligand-dependent Routes from the Active Site of Cytochrome P450 2C9

The active site of liver-specific, drug-metabolizing cytochrome P450 (CYP) monooxygenases is deeply buried in the protein and is connected to the protein surface through multiple tunnels, many of which were found open in different CYP crystal structures. It has been shown that different tunnels could serve as ligand passage routes in different CYPs. However, it is not understood whether one CYP uses multiple routes for substrate access and product release and whether these routes depend on ligand properties. From 300 ns of molecular dynamics simulations of CYP2C9, the second most abundant CYP in the human liver we found four main ligand exit routes, the occurrence of each depending on the ligand type and the conformation of the F-G loop, which is likely to be affected by the CYP-membrane interaction. A non-helical F-G loop favored exit towards the putative membrane-embedded region. Important protein features that direct ligand exit include aromatic residues that divide the active site and whose motions control access to two pathways. The ligands interacted with positively charged residues on the protein surface through hydrogen bonds that appear to select for acidic substrates. The observation of multiple, ligand-dependent routes in a CYP aids understanding of how CYP mutations affect drug metabolism and provides new possibilities for CYP inhibition.

The role of tyrosine 71 in modulating the flap conformations of BACE1

β-Site amyloid precursor protein cleaving enzyme 1 (BACE1) is a potential target for treating Alzheimer's disease. BACE1's binding site is partially covered by a flexible loop on its N-terminal domain, known as the "flap," which has been found in several conformations in crystal structures of BACE1 and other aspartyl proteases. The side chain of the invariant residue Tyr71 on the flap adopts several rotameric orientations, leading to our hypothesis that the orientation of this residue dictates the movement and conformations available to the flap. We investigated this hypothesis by performing 220 ns of molecular dynamics simulations of bound and unbound wild-type BACE1 as well as the unbound Y71A mutant. Our findings indicate that the flap exhibits various degrees of mobility and adopts different conformations depending on the Tyr71 orientation. Surprisingly, the "self-inhibited" form is stable in our simulations, making it a reasonable target for drug design. The alanine mutant, lacking a large side chain at position 71, displays significant differences in flap dynamics from wild type, freely sampling very open and closed conformations. Our simulations show that Tyr71, in addition to its previously determined functions in catalysis and substrate binding, has the important role of modulating flap conformations in BACE1.

Relation between the Conformational Heterogeneity and Reaction Cycle of Ras: Molecular Simulation of Ras

Ras functions as a molecular switch by cycling between the active GTP-bound state and the inactive GDP-bound state. It is known experimentally that there is another GTP-bound state called state 1. We investigate the conformational changes and fluctuations arising from the difference in the coordinations between the switch regions and ligands in the GTP- and GDP-bound states using a total of 830 ns of molecular-dynamics simulations. Our results suggest that the large fluctuations among multiple conformations of switch I in state 1 owing to the absence of coordination between Thr-35 and Mg2+ inhibit the binding of Ras to effectors. Furthermore, we elucidate the conformational heterogeneity in Ras by using principal component analysis, and propose a two-step reaction path from the GDP-bound state to the active GTP-bound state via state 1. This study suggests that state 1 plays an important role in signal transduction as an intermediate state of the nucleotide exchange process, although state 1 itself is an inactive state for signal transduction.

Modeling the Ternary Complex TCR-Vβ/CollagenII(261–273)/HLA-DR4 Associated with Rheumatoid Arthritis

BackgroundIt is known that genetic predisposition to rheumatoid arthritis (RA) is associated with the MHC class II allele HLA-DR4 and that residues 261–273 of type II collagen (huCollp261) represent an immunodominant T cell epitope restricted by the DR4 molecule. Despite recent advances in characterization of MHC and T cell receptor (TCR) contacts to this epitope, the atomic details of TCR/huCollp261/HLA-DR4 ternary complex are not known.Methodology/Principal FindingsHere we have used computational modeling to get insight into this interaction. A three-dimensional model of the TCR Vβ domain from a DR4+ patient affected by RA has been derived by homology modeling techniques. Subsequently, the structure of the TCR Vβ domain in complex with huCollp261/HLA-DR4 was obtained from a docking approach in conjunction with a filtering procedure based on biochemical information. The best complex from the docking experiments was then refined by 20 ns of molecular dynamics simulation in explicit water. The predicted model is consistent with available experimental data. Our results indicate that residues 97–101 of CDR3β are critical for recognition of huCollp261/HLA-DR4 by TCR. We also show that TCR contacts on p/MHC surface affect the conformation of the shared epitope expressed by DR alleles associated with RA susceptibility.Conclusions/SignificanceThis work presents a three-dimensional model for the ternary complex TCR-Vβ/collagenII(261–273)/HLA-DR4 associated with rheumatoid arthritis that can provide insights into the molecular mechanisms of self reactivity.

Tertiary and Secondary Structure Elasticity of a Six-Ig Titin Chain

The protein titin functions as a mechanical spring conferring passive elasticity to muscle. Force spectroscopy studies have shown that titin exhibits several regimes of elasticity. Disordered segments bring about a soft, entropic spring-type elasticity; secondary structures of titin's immunoglobulin-like (Ig-) and fibronectin type III-like (FN-III) domains provide a stiff elasticity. In this study, we demonstrate a third type of elasticity due to tertiary structure and involving domain-domain interaction and reorganization along the titin chain. Through 870 ns of molecular dynamics simulations involving 29,000–635,000 atom systems, the mechanical properties of a six-Ig domain segment of titin (I65-I70), for which a crystallographic structure is available, are probed. The results reveal a soft tertiary structure elasticity. A remarkably accurate statistical mechanical description for this elasticity is derived and applied. Simulations also studied the stiff, secondary structure elasticity of the I65-I70 chain due to the unraveling of its domains and revealed how force propagates along the chain during the secondary structure elasticity response.

Bovine Chymosin: A Computational Study of Recognition and Binding of Bovine κ-Casein

Bovine chymosin is an aspartic protease that selectively cleaves the milk protein kappa-casein. The enzyme is widely used to promote milk clotting in cheese manufacturing. We have developed models of residues 97-112 of bovine kappa-casein complexed with bovine chymosin, using ligand docking, conformational search algorithms, and molecular dynamics simulations. In agreement with limited experimental evidence, the model suggests that the substrate binds in an extended conformation with charged residues on either side of the scissile bond playing an important role in stabilizing the binding pose. Lys111 and Lys112 are observed to bind to the N-terminal domain of chymosin displacing a conserved water molecule. A cluster of histidine and proline residues (His98-Pro99-His100-Pro101-His102) in kappa-casein binds to the C-terminal domain of the protein, where a neighboring conserved arginine residue (Arg97) is found to be important for stabilizing the binding pose. The catalytic site (including the catalytic water molecule) is stable in the starting conformation of the previously proposed general acid/base catalytic mechanism for 18 ns of molecular dynamics simulations.

Preferential Interactions between Small Solutes and the Protein Backbone: A Computational Analysis

To improve our understanding of the effects of small solutes on protein stability, we conducted atomistic simulations to quantitatively characterize the interactions between two broadly used small solutes, urea and glycine betaine (GB), and a triglycine peptide, which is a good model for a protein backbone. Multiple solute concentrations were analyzed, and each solute-peptide-water ternary system was studied with approximately 200-300 ns of molecular dynamics simulations with the CHARMM force field. The comparison between calculated preferential interaction coefficients (Gamma(23)) and experimentally measured values suggests that semiquantitative agreement with experiments can be obtained if care is exercised to balance interactions among the solute, protein, and water. On the other hand, qualitatively incorrect (i.e., wrong sign in Gamma(23)) results can be obtained if a solute model is constructed by directly taking parameters for chemically similar groups from an existing force field. Such sensitivity suggests that small solute thermodynamic data can be valuable in the development of accurate force field models of biomolecules. Further decomposition of Gamma(23) into group contributions leads to additional insights regarding the effects of small solutes on protein stability. For example, use of the CHARMM force field predicts that urea preferentially interacts with not only amide groups in the peptide backbone but also aliphatic groups, suggesting a role for these interactions in urea-induced protein denaturation; quantitatively, however, it is likely that the CHARMM force field overestimates the interaction between urea and aliphatic groups. The results with GB support a simple thermodynamic model that assumes additivity of preferential interaction between GB and various biomolecular surfaces.

Quantifying Correlations Between Allosteric Sites in Thermodynamic Ensembles

Allostery describes altered protein function at one site due to a perturbation at another site. One mechanism of allostery involves correlated motions, which can occur even in the absence of substantial conformational change. We present a novel method, “MutInf”, to identify statistically significant correlated motions from equilibrium molecular dynamics simulations. Our approach analyzes both backbone and side chain motions using internal coordinates to account for the gear-like twists that can take place even in the absence of the large conformational changes typical of traditional allosteric proteins. We quantify correlated motions using a mutual information metric, which we extend to incorporate data from multiple short simulations and to filter out correlations that are not statistically significant. Applying our approach to uncover mechanisms of cooperative small molecule binding in human interleukin-2, we identify clusters of correlated residues from 50 ns of molecular dynamics simulations. Interest...

Ligand Migration between Internal Docking Sites in Photodissociated Carbonmonoxy Neuroglobin

Neuroglobin (Ngb) belongs to the large family of globular heme proteins capable of binding small gaseous ligands such as O(2), CO, or NO within their active site. In this work, we have analyzed CO migration pathways in photolyzed NgbCO using molecular dynamics (MD) simulations in combination with Fourier transform infrared temperature derivative spectroscopy (FTIR-TDS). A total of 55 ns of MD simulation was analyzed to explore the approximately 300 A(3) internal Ngb cavity. Overall, the simulations differentiated between eight possible docking sites, three of which were also identified experimentally. Low-temperature FTIR-TDS experiments on wild-type (wt) and F28W mutant NgbCO revealed that a small fraction of ligands migrates from site B to site C from which they rebound after slow cool illumination. For the F28L mutant, however, population of site C was not observed. In agreement with these findings, the simulations at 20 K showed ligand transfer between sites B and C for wt Ngb, but not for the F28L mutant. The ligand migration network could be mapped out and two key gate residues, Phe28 and Pro52, were identified. Ligand population analysis from the MD simulations revealed a direct relation between the size of the B10 side chain (Phe28 in wild-type Ngb) and the barrier against migration. Barriers for the transition of photodissociated CO from the distal pocket to the Xe4 site in Ngb are lower by up to 4 kcal/mol compared to myoglobin, suggesting that ligand migration between different docking sites is more facile in Ngb than in myoglobin.

Relative free energy of binding between antimicrobial peptides and SDS or DPC micelles

We present relative binding free energy calculations for six antimicrobial peptide–micelle systems, three peptides interacting with two types of micelles. The peptides are the scorpion derived antimicrobial peptide (AMP), IsCT and two of its analogues. The micelles are dodecylphosphatidylcholine (DPC) and sodium dodecylsulphate (SDS) micelles. The interfacial electrostatic properties of DPC and SDS micelles are assumed to be similar to those of zwitterionic mammalian and anionic bacterial membrane interfaces, respectively. We test the hypothesis that the binding strength between peptides and the anionic micelle SDS can provide information on peptide antimicrobial activity, since it is widely accepted that AMPs function by binding to and disrupting the predominantly anionic lipid bilayer of the bacterial cytoplasmic membrane. We also test the hypothesis that the binding strength between peptides and the zwitterionic micelle DPC can provide information on peptide haemolytic activities, since it is accepted that they also bind to and disrupt the zwitterionic membrane of mammalian cells. Equilibrium structures of the peptides, micelles and peptide–micelle complexes are obtained from more than 300 ns of molecular dynamics simulations. A thermodynamic cycle is introduced to compute the binding free energy from electrostatic, non-electrostatic and entropic contributions. We find relative binding free energy strengths between peptides and SDS to correlate with the experimentally measured rankings for peptide antimicrobial activities, and relative free energy binding strengths between peptides and DPC to correlate with the observed rankings for peptide haemolytic toxicities. These findings point to the importance of peptide–membrane binding strength for antimicrobial activity and haemolytic activity.

Quantifying Correlations Between Allosteric Sites in Thermodynamic Ensembles.

Allostery describes altered protein function at one site due to a perturbation at another site. One mechanism of allostery involves correlated motions, which can occur even in the absence of substantial conformational change. We present a novel method, "MutInf", to identify statistically significant correlated motions from equilibrium molecular dynamics simulations. Our approach analyzes both backbone and sidechain motions using internal coordinates to account for the gear-like twists that can take place even in the absence of the large conformational changes typical of traditional allosteric proteins. We quantify correlated motions using a mutual information metric, which we extend to incorporate data from multiple short simulations and to filter out correlations that are not statistically significant. Applying our approach to uncover mechanisms of cooperative small molecule binding in human interleukin-2, we identify clusters of correlated residues from 50 ns of molecular dynamics simulations. Interestingly, two of the clusters with the strongest correlations highlight known cooperative small-molecule binding sites and show substantial correlations between these sites. These cooperative binding sites on interleukin-2 are correlated not only through the hydrophobic core of the protein but also through a dynamic polar network of hydrogen bonding and electrostatic interactions. Since this approach identifies correlated conformations in an unbiased, statistically robust manner, it should be a useful tool for finding novel or "orphan" allosteric sites in proteins of biological and therapeutic importance.

Charges for Large Scale Binding Free Energy Calculations with the Linear Interaction Energy Method.

The linear interaction energy method (LIE), which combines force field based molecular dynamics (MD) simulations and linear response theory, has previously been shown to give fast and reliable estimates of ligand binding free energies, suggesting that this type of technique could be used also in a high-throughput fashion. However, a limiting step in such applications is the assignment of atomic charges for compounds that have not been parametrized within the given force field, in this case OPLS-AA. In order to reach an automatable solution to this problem, we have examined the performance of nine different ab initio and semiempirical charge methods, together with estimates of solvent induced polarization. A test set of ten HIV-1 reverse transcriptase inhibitors was selected, and LIE estimates of their relative binding free energies were calculated using the resulting 23 different charge variants. Over 800 ns of MD simulation show that the LIE method provides excellent estimates with several different charge methods and that the semiempirically derived CM1A charges, in particular, emerge as a fast and reliable alternative for fully automated LIE based virtual screens with the OPLS-AA force field. Our conclusions regarding different charge models are also expected to be valid for other types of force field based binding free energy calculations, such as free energy perturbation and thermodynamic integration simulations.

Molecular Dynamics Simulations and Free Energy Calculations of a Novel Series of Protein Tyrosine Phosphatase 1B Difluoromethylenephosphonic Acid Inhibitors

Binding models for a series of difluoromethylenephosphonic (DFMP) and difluoromethylenesulfonic (DFMS) acids to protein tyrosine phosphatase 1B (PTP1B) were studied by molecular docking,molecular dynamics (MD) simulations,and free energy calculations. Binding free energies were computed using the molecular mechanics/ generalized Born surface area (MM/GBSA) methodology based on 1 ns MD simulations. The order of affinities for the studied inhibitors can be accurately predicted using previously predicted binding free energies. Inhibitor/residue interaction profiles for all inhibitors were systematically generated using MM/GBSA free energy decomposition analysis. Inhibitor/residue interaction profiles demonstrated that electrostatic interactions between the negative charge center of DFMP/DFMS groups and Arg221 of PTP1B are a crucial part of the studied molecule affinities. Furthermore,the fluorine atom or other hydrogen bonding donor atoms with appropriate radii will improve inhibitor binding to the primary binding site of PTP1B.

Structure and dynamics of the anti-AMCV scFv(F8): Effects of selected mutations on the antigen combining site

The recombinant antibody fragment scFv(F8), which recognizes the coat protein of the plant virus AMCV, is characterized by peculiar high in vitro stability and functional folding even in reducing environments, making it fit for designing stable antibodies with desired properties. Mutagenesis and functional analysis evidenced two residues, at positions 47 and 58 of the V(H) chain, playing a crucial role in the antigen binding recognition. Here, we used a computational procedure to assess the effects of these mutations on the stability, structure and dynamics of the antigen-binding site. Structural models of the wild type scFv(F8) and of its H47 and H58 mutants were built by homology modelling and assessed by multiple 15.5ns of molecular dynamics simulations. Computational results indicate that the 47H substitution strongly affects the CDR-H(2) conformation, destabilizes the V(H)/V(L) interface and confers high conformational flexibility to the antigen-binding site, leading the mutant to functional loss. The mutation at position H58 strenghtens the binding site, bestowing a high antigen specificity on the mutant. The essential dynamics and the analysis of the protein-solvent interface further corroborate the correspondence between the extent of the structurally-determined flexibility of the binding site with the different functional behaviours proved by the wild-type and its mutants. These results may have useful implications for structure-based design of antibody combining site.

Molecular Dynamics Simulation and Thermodynamic Modeling of the Self-Assembly of the Triterpenoids Asiatic Acid and Madecassic Acid in Aqueous Solution

The self-assembly behavior of the triterpenoids asiatic acid (AA) and madecassic acid (MA), both widely studied bioactive phytochemicals that are similar in structure to bile salts, were investigated in aqueous solution through atomistic-level molecular dynamics (MD) simulation. AA and MA molecules initially distributed randomly in solution were observed to aggregate into micelles during 75 ns of MD simulation. A "hydrophobic contact criterion" was developed to identify micellar aggregates from the computer simulation results. From the computer simulation data, the aggregation number of AA and MA micelles, the monomer concentration, the principal moments of the micelle radius of gyration tensor, the one-dimensional growth exhibited by AA and MA micelles as the aggregation number increases, the level of internal ordering within AA and MA micelles (quantified using two different orientational order parameters), the local environment of atoms within AA and MA in the micellar environment, and the total, hydrophilic, and hydrophobic solvent accessible surface areas of the AA and MA micelles were each evaluated. The MD simulations conducted provide insights into the self-assembly behavior of structurally complex, nontraditional surfactants in aqueous solution. Motivated by the high computational cost required to obtain an accurate estimate of the critical micelle concentrations (CMCs) of AA and MA from evaluation of the average monomer concentration present in the AA and MA simulation cells, a modified computer simulation/molecular-thermodynamic model (referred to as the MCS-MT model) was formulated to quantify the free-energy change associated with optimal AA and MA micelle formation in order to predict the CMCs of AA and MA. The predicted CMC of AA was found to be 59 microM, compared with the experimentally measured CMC of 17 microM, and the predicted CMC of MA was found to be 96 microM, compared with the experimentally measured CMC of 62 microM. The AA and MA CMCs predicted using the MCS-MT model are much more accurate than the CMCs inferred from the monomer concentrations of AA and MA present in the simulation cells after micelle self-assembly (2390 microM and 11,300 microM, respectively). The theoretical modeling results obtained for AA and MA indicate that, by combining computer simulation inputs with molecular-thermodynamic models of surfactant self-assembly, reasonably accurate estimates of surfactant CMCs can be obtained with a fraction of the computational expense that would be required by using computer simulations alone.

Can molecular dynamics simulations help in discriminating correct from erroneous protein 3D models?

BackgroundRecent approaches for predicting the three-dimensional (3D) structure of proteins such as de novo or fold recognition methods mostly rely on simplified energy potential functions and a reduced representation of the polypeptide chain. These simplifications facilitate the exploration of the protein conformational space but do not permit to capture entirely the subtle relationship that exists between the amino acid sequence and its native structure. It has been proposed that physics-based energy functions together with techniques for sampling the conformational space, e.g., Monte Carlo or molecular dynamics (MD) simulations, are better suited to the task of modelling proteins at higher resolutions than those of models obtained with the former type of methods. In this study we monitor different protein structural properties along MD trajectories to discriminate correct from erroneous models. These models are based on the sequence-structure alignments provided by our fold recognition method, FROST. We define correct models as being built from alignments of sequences with structures similar to their native structures and erroneous models from alignments of sequences with structures unrelated to their native structures.ResultsFor three test sequences whose native structures belong to the all-α, all-β and αβ classes we built a set of models intended to cover the whole spectrum: from a perfect model, i.e., the native structure, to a very poor model, i.e., a random alignment of the test sequence with a structure belonging to another structural class, including several intermediate models based on fold recognition alignments. We submitted these models to 11 ns of MD simulations at three different temperatures. We monitored along the corresponding trajectories the mean of the Root-Mean-Square deviations (RMSd) with respect to the initial conformation, the RMSd fluctuations, the number of conformation clusters, the evolution of secondary structures and the surface area of residues. None of these criteria alone is 100% efficient in discriminating correct from erroneous models. The mean RMSd, RMSd fluctuations, secondary structure and clustering of conformations show some false positives whereas the residue surface area criterion shows false negatives. However if we consider these criteria in combination it is straightforward to discriminate the two types of models.ConclusionThe ability of discriminating correct from erroneous models allows us to improve the specificity and sensitivity of our fold recognition method for a number of ambiguous cases.

Correlation between symmetry breaker position and the preferences of conformationally constrained homopeptides: A molecular dynamics investigation

The conformational tendencies of C(alpha,alpha)-diethylglycine (Deg)-based peptides have been studied in solution using all atom molecular dynamics simulations. Specifically, the conformational effects of breaking the symmetry of the host Tfa-(Deg)(5)-OtBu (Tfa, trifluoroacetyl; OtBu, tert-butoxy) pentapeptide with punctual replacements at different sequence positions of one Deg residue by its corresponding guest chiral analogue, L-alpha-aminobutyric acid (L-Abu), have been examined by simulating the following peptides: Tfa-(Deg)(5)-OtBu, Tfa-(Deg)(2)-L-Abu-(Deg)(2)-OtBu, Tfa-(Deg)(3)-L-Abu-Deg-OtBu, and Tfa-(Deg)(4)-L-Abu-OtBu. Simulations show that only the Deg homopeptide is able to stabilize a 2.0(5) helix, even though a kinked arrangement with all the Deg residues adopting a fully-extended conformation was found to be stable when the L-Abu residue is introduced in the middle of the sequence. On the other hand, when the L-Abu residue is closer to the C-end of the sequence, the peptide chain prefers a partially folded 3(10)-helix. Additional simulations on Tfa-(Deg)(3)-L-Abu-(Deg)(3)-OtBu highlighted that, when the size of the Deg segments increases, their tendency to adopt a 2.0(5) helix predominates over the preferred folded conformation of L-Abu. The overall picture extracted after more than 300 ns of molecular dynamics simulation is that breaking the alpha-carbon symmetry of achiral C(alpha)-tetrasubstituted amino acids is a promising strategy to build up polypeptides with modulated conformational tendencies.

Computational and experimental approaches assess the interactions between bovine β-lactoglobulin and synthetic compounds of pharmacological interest

Extending a previous investigation, the ability of binding to the model calycin β-lactoglobulin (BLG) was evaluated both in silico and in vitro for several fluorine-containing (semi-)synthetic molecules of pharmacological and pharmaceutical interest (antibiotics, vastatins, steroid drugs). Simulation procedures included molecular docking according to a Montecarlo-simulated annealing protocol and molecular dynamics; heteronuclear NMR and denaturant gradient gel electrophoresis were the selected experimental techniques. For the tested drugs, ranking of the binding affinity was consistently assessed by computation and by experiment. The affinity for BLG increased in the sequence: 5-fluorosalycilic acid < dexamethasone ≪ sulindac = norfloxacin < fluvastatin. The computed K i for fluorosalycilate was in the order of 10 −4 M; accordingly, in a molecular dynamics simulation the chemical diffused out of the BLG calyx in less than 2 ns, and no evidence of binding was found by NMR or electrophoresis. Conversely, the K i for fluvastatin and norfloxacin were in the order of 10 −7 and 10 −6 M, similar to the affinity for BLG by natural ligands, such as retinoids and long-chain fatty acids. Moreover fluvastatin was found still bound to the protein after 5 ns of molecular dynamics simulation. Interaction of fluvastatin and norfloxacin with BLG was made evident by changes in chemical shift and dynamic parameters in the 19F NMR spectra and in effective urea concentration and cooperativity features in denaturant gradient gel electrophoresis. Such findings prove BLG may act as a drug carrier accepting in its cavity molecules of different bulk, rigidity and hydrophobicity.

Adsorption of Acridine Orange at a C8,18/Water/Acetonitrile Interface

Fully atomistic simulations are used to characterize the molecular dynamics (MD) of acridine orange (3,6-dimethylaminoacridine) at a chromatographic interface. Multiple 1 ns MD simulations were performed for acridine orange at the interface between three different acetonitrile/water mixtures (0/100, 20/80, and 50/50) with C8 and C18 alkyl chains. The diffusion coefficient, D, of acridine orange in pure solvent was found to be 4 times smaller at the water/C18 interface (D = 0.022 x 10(-4) cm2/s) than in bulk water (D = 0.087 x 10(-4) cm2/s), in qualitative agreement with experiment. Rotational reorientation times were 20 and 700 ps, which also agree favorably with the measured time scales of 130 and 740 ps. Contrary to experiment, the simulations found that for increasing surface coverage, the diffusion coefficient for acridine decreased. Detailed analysis of the solvent structure showed that the transport properties of acridine were primarily governed by the solvent distribution above the functionalized surface. The solvent structure, in turn, was largely determined by the surface consisting of the silica layer, the alkyl chains, and their functionalization.