Evaluation of protein–ligand affinity prediction using steered molecular dynamics simulations

In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein–ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski’s equality was employed compared with the second-order cumulant expansion equation of Jarzynski’s equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.     

The synthesis of peptide fragments of high affinity receptor Fc?RI and their binding to allergen-specific immunoglobulins E

Using computer analysis, a minimal sequence of Arg136-Asn137-Trp138-Asp139 that can bind to IgE C3 and C4 fragments was determined for the high-affinity receptor Fc?RI, a key protein of IgE-dependent allergic reactions of the immediate type. A number of peptides containing the Arg-Asn-Trp-Asp sequence were proposed as model analogues of the Fc?RI receptor. It was shown that these peptides manifested immunobiological effects and bound to IgE. The peptides were demonstrated to bind to IgE serum antibodies specific to the Dermatophagoides pteronyssinus allergen isolated from plasma of patients with allergic bronchial asthma.     

mRNA secondary structure optimization using a correlated stem–loop prediction

Secondary structure of messenger RNA plays an important role in the bio-synthesis of proteins. Its negative impact on translation can reduce the yield of protein by slowing or blocking the initiation and movement of ribosomes along the mRNA, becoming a major factor in the regulation of gene expression. Several algorithms can predict the formation of secondary structures by calculating the minimum free energy of RNA sequences, or perform the inverse process of obtaining an RNA sequence for a given structure. However, there is still no approach to redesign an mRNA to achieve minimal secondary structure without affecting the amino acid sequence. Here we present the first strategy to optimize mRNA secondary structures, to increase (or decrease) the minimum free energy of a nucleotide sequence, without changing its resulting polypeptide, in a time-efficient manner, through a simplistic approximation to hairpin formation. Our data show that this approach can efficiently increase the minimum free energy by >40%, strongly reducing the strength of secondary structures. Applications of this technique range from multi-objective optimization of genes by controlling minimum free energy together with CAI and other gene expression variables, to optimization of secondary structures at the genomic level.     

Crystal structure of Fcγ receptor I and its implication in high affinity γ-immunoglobulin binding

Fcγ receptors (FcγRs) play critical roles in humoral and cellular immune responses through interactions with the Fc region of immunoglobulin G (IgG). Among them, FcγRI is the only high affinity receptor for IgG and thus is a potential target for immunotherapy. Here we report the first crystal structure of an FcγRI with all three extracellular Ig-like domains (designated as D1, D2, and D3). The structure shows that, first, FcγRI has an acute D1-D2 hinge angle similar to that of FcεRI but much smaller than those observed in the low affinity Fcγ receptors. Second, the D3 domain of FcγRI is positioned away from the putative IgG binding site on the receptor and is thus unlikely to make direct contacts with Fc. Third, the replacement of FcγRIII FG-loop ((171)LVGSKNV(177)) with that of FcγRI ((171)MGKHRY(176)) resulted in a 15-fold increase in IgG(1) binding affinity, whereas a valine insertion in the FcγRI FG-loop ((171)MVGKHRY(177)) abolished the affinity enhancement. Thus, the FcγRI FG-loop with its conserved one-residue deletion is critical to the high affinity IgG binding. The structural results support FcγRI binding to IgG in a similar mode as its low affinity counterparts. Taken together, our study suggests a molecular mechanism for the high affinity IgG recognition by FcγRI and provides a structural basis for understanding its physiological function and its therapeutic implication in treating autoimmune diseases.     

Mutagenesis studies of the β I domain metal ion binding sites on integrin αVβ3 ligand binding affinity

Three divalent cation binding sites in the integrin β I domain have been shown to regulate ligand binding and adhesion. However, the degree of ligand binding and adhesion varies among integrins. The αLβ2 and α4β7 integrins show an increase in ligand binding affinity and adhesion when one of their ADMIDAS (adjacent to MIDAS, or the metal ion-dependent adhesion site) residues is mutated. By contrast, the α2β1, α5β1, and αIIbβ3 integrins show a decrease in binding affinity and adhesion when their ADMIDAS is mutated. Our study here indicated that integrin αVβ3 had lower affinity when the ADMIDAS was mutated. By comparing the primary sequences of these integrin subunits, we propose that one residue associated with the MIDAS (β3 Ala(252)) may account for these differences. In the β1 integrin subunit, the corresponding residue is also Ala, whereas in both β2 and β7 integrin subunits, it is Asp. We mutated the β3 residue Ala(252) to Asp and combined this mutant with mutations of one or two ADMIDAS residues. The mutant A252D showed reduced ligand binding affinity and adhesion. The ligand binding affinity and adhesion were increased when this A252D mutant was paired with mutations of one ADMIDAS residue. But when paired with mutations of two ADMIDAS residues the mutant nearly abolished ligand-binding ability, which was restored by the activating glycosylation mutation. Our study suggests that the variation of this residue contributes to the different ligand binding affinities and adhesion abilities among different integrin families.     

Protein structure and fold prediction using Tree-Augmented naïve Bayesian classifier

Due to the large volume of protein sequence data, computational methods to determine the structure class and the fold class of a protein sequence have become essential. Several techniques based on sequence similarity, Neural Networks, Support Vector Machines (SVMs), etc. have been applied. Since most of these classifiers use binary classifiers for multi-classification, there may be (N) c2 classifiers required. This paper presents a framework using the Tree-Augmented Bayesian Networks (TAN) which performs multi-classification based on the theory of learning Bayesian Networks and using improved feature vector representation of (Ding et al., 2001). In order to enhance TAN's performance, pre-processing of data is done by feature discretization and post-processing is done by using Mean Probability Voting (MPV) scheme. The advantage of using Bayesian approach over other learning methods is that the network structure is intuitive. In addition, one can read off the TAN structure probabilities to determine the significance of each feature (say, hydrophobicity) for each class, which helps to further understand the complexity in protein structure. The experiments on the datasets used in three prominent recent works show that our approach is more accurate than other discriminative methods. The framework is implemented on the BAYESPROT web server and it is available at http://www-appn.comp.nus.edu.sg/~bioinfo/bayesprot/Default.htm. More detailed results are also available on the above website.     

Stoichiometry and affinity of the human serum albumin-Alzheimer's Aβ peptide interactions

A promising strategy to control the aggregation of the Alzheimer's Aβ peptide in the brain is the clearance of Aβ from the central nervous system into the peripheral blood plasma. Among plasma proteins, human serum albumin plays a critical role in the Aβ clearance to the peripheral sink by binding to Aβ oligomers and preventing further growth into fibrils. However, the stoichiometry and the affinities of the albumin-Aβ oligomer interactions are still to be fully characterized. For this purpose, here we investigate the Aβ oligomer-albumin complexes through a novel and generally applicable experimental strategy combining saturation transfer and off-resonance relaxation NMR experiments with ultrafiltration, domain deletions, and dynamic light scattering. Our results show that the Aβ oligomers are recognized by albumin through sites that are evenly partitioned across the three albumin domains and that bind the Aβ oligomers with similar dissociation constants in the 1-100 nM range, as assessed based on a Scatchard-like model of the albumin inhibition isotherms. Our data not only explain why albumin is able to inhibit amyloid formation at physiological nM Aβ concentrations, but are also consistent with the presence of a single high affinity albumin-binding site per Aβ protofibril, which avoids the formation of extended insoluble aggregates.     

Substrate binding and specificity of rhomboid intramembrane protease revealed by substrate–peptide complex structures

The mechanisms of intramembrane proteases are incompletely understood due to the lack of structural data on substrate complexes. To gain insight into substrate binding by rhomboid proteases, we have synthesised a series of novel peptidyl-chloromethylketone (CMK) inhibitors and analysed their interactions with Escherichia coli rhomboid GlpG enzymologically and structurally. We show that peptidyl-CMKs derived from the natural rhomboid substrate TatA from bacterium Providencia stuartii bind GlpG in a substrate-like manner, and their co-crystal structures with GlpG reveal the S1 to S4 subsites of the protease. The S1 subsite is prominent and merges into the ‘water retention site’, suggesting intimate interplay between substrate binding, specificity and catalysis. Unexpectedly, the S4 subsite is plastically formed by residues of the L1 loop, an important but hitherto enigmatic feature of the rhomboid fold. We propose that the homologous region of members of the wider rhomboid-like protein superfamily may have similar substrate or client-protein binding function. Finally, using molecular dynamics, we generate a model of the Michaelis complex of the substrate bound in the active site of GlpG.     

Probing the determinants of diacylglycerol binding affinity in the C1B domain of protein kinase Cα

C1 domains are independently folded modules that are responsible for targeting their parent proteins to lipid membranes containing diacylglycerol (DAG), a ubiquitous second messenger. The DAG binding affinities of C1 domains determine the threshold concentration of DAG required for the propagation of signaling response and the selectivity of this response among DAG receptors in the cell. The structural information currently available for C1 domains offers little insight into the molecular basis of their differential DAG binding affinities. In this work, we characterized the C1B domain of protein kinase Cα (C1Bα) and its diagnostic mutant, Y123W, using solution NMR methods and molecular dynamics simulations. The mutation did not perturb the C1Bα structure or the sub-nanosecond dynamics of the protein backbone, but resulted in a > 100-fold increase in DAG binding affinity and a substantial change in microsecond timescale conformational dynamics, as quantified by NMR rotating-frame relaxation-dispersion methods. The differences in the conformational exchange behavior between wild type and Y123W C1Bα were localized to the hinge regions of ligand-binding loops. Molecular dynamics simulations provided insight into the identity of the exchanging conformers and revealed the significance of a particular residue (Gln128) in modulating the geometry of the ligand-binding site. Taken together with the results of binding studies, our findings suggest that the conformational dynamics and preferential partitioning of the tryptophan side chain into the water-lipid interface are important factors that modulate the DAG binding properties of the C1 domains.     

Aggregation of amphipathic peptides at an aqueous–organic interface using coarse-grained simulations

The effect of an aqueous/organic interface on the folding and aggregation of amphipathic peptides is examined by applying discontinuous molecular dynamics (DMD) simulations combined with an intermediate resolution protein model, PRIME20, to a peptide/interface system. The systems contain 48 (KLLK)₄ peptides in random coil or α-helical conformations interacting with both strong and weak interfaces. In the absence of an interface, most of the oligomers form helical bundles, a small fraction of which convert to β-sheets when the temperature is above the folding transition. Adding a weak interface decreases oligomer formation above the folding temperature and increases it below. Little monolayer formation is observed at the weak interface; instead reversible adsorption increases the local peptide concentration near the interface, promoting helical bundle formation in the aqueous phase below the folding temperature and β-sheet formation above the folding temperature. Introducing a strong interface leads to irreversible adsorption, promoting formation of helical monolayers below the folding temperature and mixed β-sheet/amorphous monolayers above the folding temperature. The (KLLK)₄ peptide is more likely to adsorb to the interface when it is in an α-helical conformation, as opposed to a random coil, because of its larger hydrophobic moment.     

Solution structure of a synthetic peptide corresponding to a receptor binding region of FSH (hFSH-β 33–53)

The receptor binding surface of human follicle-stimulating hormone (hFSH) is mimicked by synthetic peptides corresponding to the hFSH-β chain amino acid sequences 33–53 [Santa-Coloma, T. A., Dattatreyamurty, D., and Reichert, L. E., Jr. (1990),Biochemistry 29, 1194–1200], 81–95 [Santa-Coloma, T. A., and Reichert, L. E., Jr. (1990),J. Biol. Chem. 265, 5037–5042], and the combined sequence (33–53)–(81–95) [Santa-Coloma, T. A., Crabb, J. W., and Reichert, L. E., Jr. (1991),Mol. Cell. Endocrinol. 78, 197–204]. These peptides have been shown to inhibit binding of hFSH to its receptor. Circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy were used to determine the structure of the first peptide in this series, the 21 amino acid peptide hFSH-β-(33–53), H₂N-YTRDLVYKDPARPKIQKTCTF-COOH. Analysis of CD data indicated the presence of approximately equal amounts of antiparallel β-pleated sheet, turns including a β-turn, “other” structures, and a small amount ofa-helix. The major characteristics of the structure were found to be relatively stable at acidicpH and the predominant effect of increased solvent polarity was a small increase ina-helical content. One- and two-dimensional NMR techniques were used to obtain full proton and carbon signal assignments in aqueous solution atpH 3.1. Analysis of NMR results confirmed the presence of the structural features revealed by CD analysis and provided a detailed picture of the secondary structural elements and global folding pattern in hFSH-β-(33–53). These features included an antiparallel β-sheet (residues 38–51 and 46–48), turns within residues 41–46, and 50–52 (a β-turn) and a small N-terminal helical region comprised of amino acids 34–36. One of the turns is facilitated by prolines 42 and 45. Proline-45 was constrained to thetrans conformation, whereas proline-42 favored thetrans conformer (～70%) over thecis (～30%). Two resonances were observed for the single alanine residue (A-43) sequentially proximal to P-42, but the rest of the structure was minimally affected by the isomerization at proline-42. The major population of molecules, containingtrans-42 andtrans-45 prolines, presented 120 NOEs. Distance geometry calculations with 140 distance constraints and energy minimization refinements were used to derive a moderately well-defined model of the peptide's structure. The hFSH-β-(33–53) structure has a highly polar surface composed of six cationic amino acid (arginie-35, lysine-40, arginine-44, lysine-46, glutamine-48, and lysine-49) and two anionic residues (aspartate-36 and aspartic acid-41). A hydrophobic region in the structure is composed of residues in the antiparallel β-sheet and β-turn which fold to produce a distorted “hairpin.” The structure of this domain, together with the protruding and positively charged region in the vicinity of residues 42–45, may mimic the surface of hFSH that binds to the receptor.     

Nucleotide binding domain 1 pharmacophore modeling for visualization and analysis of P-glycoprotein–flavonoid molecular interactions

Background

P-glycoprotein (P-gp) is a 170-kDa membrane protein. It provides a barrier function and help to excrete toxins from the body as a transporter. Some bioflavonoids have been shown to block P-gp activity.

Objective

To evaluate the important amino acid residues within nucleotide binding domain 1 (NBD1) of P-gp that play a key role in molecular interactions with flavonoids using structure-based pharmacophore model.

Methods

In the molecular docking with NBD1 models, a putative binding site of flavonoids was proposed and compared with the site for ATP. The binding modes for ligands were achieved using LigandScout to generate the P-gp–flavonoid pharmacophore models.

Results

The binding pocket for flavonoids was investigated and found these inhibitors compete with the ATP for binding site in NBD1 including the NBD1 amino acid residues identified by the in silico techniques to be involved in the hydrogen bonding and van der Waals (hydrophobic) interactions with flavonoids.

Conclusion

These flavonoids occupy with the same binding site of ATP in NBD1 proffering that they may act as an ATP competitive inhibitor.

     

Comparative modeling of retinol-binding protein-3 and retinal S-antigen in Eales’ disease and prediction of their binding sites using computational methods

Retinal S-antigen and interphotoreceptor retinoid-binding protein-3 play a significant role in the etiopathogenesis of Eales' disease. Protein 3D structures are functionally very important and play a significant role in progression of the disease, hence these 3D structures are better target for further drug designing and relative studies. We developed 3D model structure of retinol-binding protein-3 and retinal S-antigen protein of human involved in Eales' disease. Functional site prediction is a very important and related step; hence, in the current course of analysis, we predicted putative functional site residues in the target proteins. Molecular models of these proteins of Eales' disease as documented in this study may provide a valuable aid for designing an inhibitor or better ligand against Eales' disease and could play a significant role in drug design.