Ab initio fragment molecular orbital (FMO) method applied to analysis of the ligand-protein interaction in a pheromone-binding protein

Full quantum computation of the electronic state of proteins has recently become possible by the advent of the ab initio fragment molecular orbital (FMO) method. We applied this method to the analysis of the interaction between the Bombyx mori pheromone-binding protein and its ligand, bombykol. The protein–ligand interaction of this molecular complex was minutely analyzed by the FMO method, and the analysis revealed several important interactions between the ligand and amino acid residues.     

Sexual attraction in the silkworm moth: structure of the pheromone-binding-protein-bombykol complex

BACKGROUND: Insects use volatile organic molecules to communicate messages with remarkable sensitivity and specificity. In one of the most studied systems, female silkworm moths (Bombyx mori) attract male mates with the pheromone bombykol, a volatile 16-carbon alcohol. In the male moth's antennae, a pheromone-binding protein conveys bombykol to a membrane-bound receptor on a nerve cell. The structure of the pheromone-binding protein, its binding and recognition of bombykol, and its full role in signal transduction are not known. RESULTS: The three-dimensional structure of the B. mori pheromone-binding protein with bound bombykol has been determined by X-ray diffraction at 1.8 A resolution. CONCLUSIONS: The pheromone binding protein of B. mori has six helices, and bombykol binds in a completely enclosed hydrophobic cavity formed by four antiparallel helices. Bombykol is bound in this cavity through numerous hydrophobic interactions, and sequence alignments suggest critical residues for specific pheromone binding.     

Thermodynamic Studies of Amino Acid–Denaturant Interactions in Aqueous Solutions at 298.15 K

As proteins and other biomolecules consisting of amino acid residues require external additives for their dissolution and recrystallization, it is important to have information about how such additives interact with amino acids. Therefore we have studied the interactions of simple model amino acids with the additives urea and guanidine hydrochloride in aqueous solutions at 298.15 K, using vapor pressure osmometry. During the measurements, the concentration of urea was fixed as ∼2 mol⋅kg⁻¹ and that of guanidine hydrochloride was fixed as ∼1 mol⋅kg⁻¹ whereas the concentrations of amino acids were varied. The experimental water activity data were processed to get the individual activity coefficients of all the three components in the ternary mixture. Further, the activity coefficients were used to get the excess Gibbs energies of solutions and Gibbs energies for transfer of either amino acids from water to aqueous denaturant solutions or denaturant from water to aqueous amino acid solutions. An application of the McMillan-Mayer theory of solutions through virial expansion of transfer Gibbs energies was made to get pair and triplet interaction parameter whose sign and magnitude yielded information about amino acid–denaturant interactions, relative to their interactions with water. The pair interaction parameters have been further used to obtain salting constants and in turn the thermodynamic equilibrium constant values for the amino acid–denaturant mixing process in aqueous solutions at 298.15 K. The results have been explained in terms of hydrophobic hydration, hydrophobic interactions and amino acid–denaturant binding.     

Computational analysis of binding affinity and neural response at the l-alanine receptor

Summary A model of analogue-receptor binding is developed for the l-alanine receptor in the channel catfish using the AM1-SM2 and ab initio SCRF computational methods. Besides interactions involving the zwitterionic moiety of the amino acid analogue and complementary subsites on the receptor, the model suggests the presence of a hydrophobic pocket with dispersion interactions between the receptor and the residue on the amino acid analogue. Conformational analysis suggests not only a small compact active site on the receptor, but also that the analogues with the highest affinity occupy nearly identical regions of space. Although the binding interaction is dominated by the ionic terms, AM1-SM2 calculations indicate that free energy terms associated with cavity formation, solvent reorganization, and dispersion interactions can be correlated to activation and neural response. From a consideration of this model, molecular features of the analogues that are important for binding and neural response were deduced and other analogues or ligands were developed and tested.     

Quantum study of HIV-1 protease-bridge water interaction

We present a fully quantum mechanical calculation for binding interaction between HIV-1 protease (PR) and the water molecule W301 which bridges the flaps of the protease with the inhibitors of PR. The quantum calculation is made possible by applying a recently developed molecular fractionation with conjugate caps (MFCC) method which divides a protein molecule into capped amino acid-based fragments and their conjugate caps. These individual fragments are properly treated to preserve the chemical property of bonds that are cut. Ab initio methods at HF, B3LYP, and MP2 levels with a fixed basis set 6-31+G* have been employed in the present calculation. The MFCC calculation produces a quantum mechanical interaction "map" representing interactions between individual residues of PR and W301. This enables a detailed quantitative analysis on binding of W301 to specific residues of PR at quantum mechanical level.     

A quantitative, real-time assessment of binding of peptides and proteins to gold surfaces

Interactions of peptides and proteins with inorganic surfaces are important to both natural and artificial systems; however, a detailed understanding of such interactions is lacking. In this study, we applied new approaches to quantitatively measure the binding of amino acids and proteins to gold surfaces. Real‐time surface plasmon resonance (SPR) measurements showed that TEM1‐β‐lactamase inhibitor protein (BLIP) interacts only weakly with Au nanoparticles (NPs). However, fusion of three histidine residues to BLIP (3H‐BLIP) resulted in a significant increase in the binding to the Au NPs, which further increased when the histidine tail was extended to six histidines (6H‐BLIP). Further increasing the number of His residues had no effect on the binding. A parallel study using continuous (111)‐textured Au surfaces and single‐crystalline, (111)‐oriented, Au islands by ellipsometry, FTIR, and localized surface plasmon resonance (LSPR) spectroscopy further confirmed the results, validating the broad applicability of Au NPs as model surfaces. Evaluating the binding of all other natural amino acid homotripeptides fused to BLIP (except Cys and Pro) showed that aromatic and positively‐charged residues bind preferentially to Au with respect to small aliphatic and negatively charged residues, and that the rate of association is related to the potency of binding. The binding of all fusions was irreversible. These findings were substantiated by SPR measurements of synthesized, free, soluble tripeptides using Au‐NP‐modified SPR chips. Here, however, the binding was reversible allowing for determination of binding affinities that correlate with the binding potencies of the related BLIP fusions. Competition assays performed between 3H‐BLIP and the histidine tripeptide (3 His) suggest that Au binding residues promote the adsorption of proteins on the surface, and by this facilitate the irreversible interaction of the polypeptide chain with Au. The binding of amino acids to Au was simulated by using a continuum solvent model, showing agreement with the experimental values. These results, together with the observed binding potencies and kinetics of the BLIP fusions and free peptides, suggest a binding mechanism that is markedly different from biological protein–protein interactions.     

Tracing kinetic intermediates during ligand binding

Specific protein-ligand interactions are central to biological control. Although structure determination provides important insight into these interactions, it does not address dynamic events that occur during binding. While many biophysical techniques can provide a global view of these dynamics, NMR can be used to derive site-specific dynamics at atomic resolution. Here we show how NMR line shapes can be analyzed to identify long-lived kinetic intermediates for individual amino acids on the reaction pathway for a protein-ligand interaction. Different ligands cause different intermediate states. The lifetimes of these states determine the specificity of binding. This novel approach provides a direct, site-specific visualization of the kinetic mechanism of protein-ligand interactions.     

Understanding the recognition mechanism of protein-RNA complexes using energy based approach

Protein-RNA interactions perform diverse functions within the cell. Understanding the recognition mechanism of protein-RNA complexes is a challenging task in molecular and computational biology. In this work, we have developed an energy based approach for identifying the binding sites and important residues for binding in protein-RNA complexes. The new approach considers the repulsive interactions as well as the effect of distance between the atoms in protein and RNA in terms of interaction energy, which are not considered in traditional distance based methods to identify the binding sites. We found that the positively charged, polar and aromatic residues are important for binding. These residues influence to form electrostatic, hydrogen bonding and stacking interactions. Our observation has been verified with the experimental binding specificity of protein-RNA complexes and found good agreement with experiments. Further, the propensities of residues/nucleotides in the binding sites of proteins/RNA and their atomic contributions have been derived. Based on these results we have proposed a novel mechanism for the recognition of protein-RNA complexes: the charged and polar residues in proteins initiate recognition with RNA by making electrostatic and hydrogen bonding interactions between them; the aromatic side chains tend to form aromatic-aromatic interactions and the hydrophobic residues aid to stabilize the complex.     

Residue preference mapping of ligand fragments in the Protein Data Bank

The interaction between small molecules and proteins is one of the major concerns for structure-based drug design because the principles of protein-ligand interactions and molecular recognition are not thoroughly understood. Fortunately, the analysis of protein-ligand complexes in the Protein Data Bank (PDB) enables unprecedented possibilities for new insights. Herein, we applied molecule-fragmentation algorithms to split the ligands extracted from PDB crystal structures into small fragments. Subsequently, we have developed a ligand fragment and residue preference mapping (LigFrag-RPM) algorithm to map the profiles of the interactions between these fragments and the 20 proteinogenic amino acid residues. A total of 4032 fragments were generated from 71?798 PDB ligands by a ring cleavage (RC) algorithm. Among these ligand fragments, 315 unique fragments were characterized with the corresponding fragment-residue interaction profiles by counting residues close to these fragments. The interaction profiles revealed that these fragments have specific preferences for certain types of residues. The applications of these interaction profiles were also explored and evaluated in case studies, showing great potential for the study of protein-ligand interactions and drug design. Our studies demonstrated that the fragment-residue interaction profiles generated from the PDB ligand fragments can be used to detect whether these fragments are in their favorable or unfavorable environments. The algorithm for a ligand fragment and residue preference mapping (LigFrag-RPM) developed here also has the potential to guide lead chemistry modifications as well as binding residues predictions.     

A quantum chemistry study of binding carotenoids in the bacterial light-harvesting complexes

Carotenoids play the dual function of light harvesting and photoprotection in photosynthetic organisms. Despite their functional importance, the molecular basis for binding of carotenoids in the photosynthetic proteins is poorly understood. We have discovered that all carotenoids are surrounded either by aromatic residues or by chlorophylls in all known crystal structures of the photosynthetic pigment-protein complexes. The intermolecular pi-pi stacking interactions between carotenoids and the surrounding aromatic residues in the light-harvesting complex II (LH-II) of Rhodospirillum molischianum were analyzed by high level ab initio electronic structure calculations. Intermolecular interaction energies were calculated with the second-order M?ller-Plesset perturbation method (MP2) using the modified 6-31G*(0.25) basis set with diffuse d-polarization by Hobza and co-workers. The MP2/6-31G*(0.25) calculations yield a total stabilization energy of -15.66 kcal/mol between the carotenoid molecule and the four surrounding aromatic residues (alpha-Trp-23, beta-Phe-20, beta-Phe-24, beta-Phe-27). It is thus concluded that pi-pi stacking interactions between carotenoids and the aromatic residues play an essential role in binding carotenoids in the LH-II complex of Rhodospirillum molischianum. The physical nature of the pi-pi stacking interactions was further analyzed, and the dispersion interactions were found to be the dominant intermolecular attraction force. There is also a substantial electrostatic contribution to the overall intermolecular stabilization energy.     

The importance of aromatic-type interactions in serotonin synthesis: protein-ligand interactions in tryptophan hydroxylase and aromatic amino acid decarboxylase

The biosynthesis of serotonin requires aromatic substrates to be bound in the active sites of the enzymes tryptophan hydroxylase and aromatic amino acid decarboxylase. These aromatic substrates are held in place partially by dispersion and induction interactions with the enzymes' aromatic amino acid residues. Mutations that decrease substrate binding can result in a decrease in serotonin production and thus can lead to depression and related disorders. We use optimized crystal structures of these two enzymes to examine pair-wise electronic interaction energies between aromatic residues in the active sites and the aromatic ligands. We also perform in silico mutations on the aromatic residues to determine the change in interaction energies as mutations occur. Our second-order Moller-Plessett perturbation theory calculations show that drastic changes in interaction energy can occur and, in light of our previous work, we are able to use these data to offer predictions on the loss of protein function and on the possibility of disease upon mutation. We also examine local and gradient corrected density functional theory methods to evaluate their ability to predict these induction/dispersion-dominated interaction energies. We find that the hybrid B3LYP cannot model these interactions well, whereas the GGA HCTH407 offers largely qualitatively correct results, and the local functional SVWN quantitatively mimics the MP2 results rather well.     

A computational analysis of the binding model of MDM2 with inhibitors

Abstract  

It is a new and promising strategy for anticancer drug design to block the MDM2-p53 interaction using a non-peptide small-molecule inhibitor. We carry out molecular dynamics simulations to study the binding of a set of six non-peptide small-molecule inhibitors with the MDM2. The relative binding free energies calculated using molecular mechanics Poisson–Boltzmann surface area method produce a good correlation with experimentally determined results. The study shows that the van der Waals energies are the largest component of the binding free energy for each complex, which indicates that the affinities of these inhibitors for MDM2 are dominated by shape complementarity. The A-ligands and the B-ligands are the same except for the conformation of 2,2-dimethylbutane group. The quantum mechanics and the binding free energies calculation also show the B-ligands are the more possible conformation of ligands. Detailed binding free energies between inhibitors and individual protein residues are calculated to provide insights into the inhibitor-protein binding model through interpretation of the structural and energetic results from the simulations. The study shows that G1, G2 and G3 group mimic the Phe19, Trp23 and Leu26 residues in p53 and their interactions with MDM2, but the binding model of G4 group differs from the original design strategy to mimic Leu22 residue in p53.     

The use of ECD/ETD to identify the site of electrostatic interaction in noncovalent complexes

Electrostatic interactions play an important role in the formation of noncovalent complexes. Our previous work has highlighted the role of certain amino acid residues, such as arginine, glutamate, aspartate, and phosphorylated/sulfated residues, in the formation of salt bridges resulting in noncovalent complexes between peptides. Tandem mass spectrometry (MS) studies of these complexes using collision-induced dissociation (CID) have provided information on their relative stability. However, product-ion spectra produced by CID have been unable to assign specifically the site of interaction for the complex. In this work, tandem MS experiments were conducted on noncovalent complexes using both electron capture dissociation (ECD) and electron-transfer dissociation (ETD). The resulting spectra were dominated by intramolecular fragments of the complex with the electrostatic interaction site intact. Based upon these data, we were able to assign the binding site for the peptides forming the noncovalent complex.     

Cation-pi interactions: an energy decomposition analysis and its implication in delta-opioid receptor-ligand binding

The nature and strength of the cation-pi interaction in protein-ligand binding are modeled by considering a series of nonbonded complexes involving N-substituted piperidines and substituted monocylic aromatics that mimic the delta-opioid receptor-ligand binding. High-level ab initio quantum mechanical calculations confirm the importance of such cation-pi interactions, whose intermolecular interaction energy ranges from -6 to -12 kcal/mol. A better understanding of the electrostatics, polarization, and other intermolecular interactions is obtained by appropriately decomposing the total interaction energy into their individual components. The energy decomposition analysis is also useful for parametrizing existing molecular mechanics force fields that could then account for energetic contributions arising out of cation-pi interactions in biomolecules. The present results further provide a framework for interpreting experimental results from point mutation reported for the delta-opioid receptor.     

Electrostatics in protein binding and function

Protein electrostatic properties stem from the proportion and distribution of polar and charged residues. Polar and charged residues regulate the electrostatic properties by forming short-range interactions, like salt-bridges and hydrogen-bonds, and by defining the over-all electrostatic environment in the protein. Electrostatics play a major role in defining the mechanisms of protein-protein complex formation, molecular recognitions, thermal stabilities, conformational adaptabilities and protein movements. For example:- Functional hinges, or flexible regions of the protein, lack short-range electrostatic interactions; Thermophilic proteins have higher electrostatic interactions than their mesophilic counter parts; Increase in binding specificity and affinity involve optimization of electrostatics; High affinity antibodies have higher, and stronger, electrostatic interactions with their antigens; Rigid parts of proteins have higher and stronger electrostatic interactions. In this review we address the significance of electrostatics in protein folding, binding and function. We discuss that the electrostatic properties are evolutionally selected by a protein to perform an specific function. We also provide bona fide examples to illustrate this. Additionally, using continuum electrostatic and molecular dynamics approaches we show that the "hot-spot" inter-molecular interactions in a very specific antibody-antigen binding are mainly established through charged residues. These "hot-spot" molecular interactions stay intact even during high temperature molecular dynamics simulations, while the other inter-molecular interactions, of lesser functional significance, disappear. This further corroborates the significance of charge-charge interactions in defining binding mechanisms. High affinity binding frequently involves "electrostatic steering". The forces emerge from over-all electrostatic complementarities and by the formation of charged and polar interactions. We demonstrate that although the high affinity binding of barnase-barstar and anti-hen egg white lysozyme (HEL) antibody-HEL complexes involve different molecular mechanisms, it is electrostatically regulated in both the cases. These observations, and several other studies, suggest that a fine tuning of local and global electrostatic properties are essential for protein binding and function.     

Individually double minimum-distance definition of protein–RNA binding residues and application to structure-based prediction

Identifying protein–RNA binding residues is essential for understanding the mechanism of protein–RNA interactions. So far, rigid distance thresholds are commonly used to define protein–RNA binding residues. However, after investigating 182 non-redundant protein–RNA complexes, we find that it would be unsuitable for a certain amount of complexes since the distances between proteins and RNAs vary widely. In this work, a novel definition method was proposed based on a flexible distance cutoff. This method can fully consider the individual differences among complexes by setting a variable tolerance limit of protein–RNA interactions, i.e. the double minimum-distance by which different distance thresholds are achieved for different complexes. In order to validate our method, a comprehensive comparison between our flexible method and traditional rigid methods was implemented in terms of interface structure, amino acid composition, interface area and interaction force, etc. The results indicate that this method is more reasonable because it incorporates the specificity of different complexes by extracting the important residues lost by rigid distance methods and discarding some redundant residues. Finally, to further test our double minimum-distance definition strategy, we developed a classifier to predict those binding sites derived from our new method by using structural features and a random forest machine learning algorithm. The model achieved a satisfactory prediction performance and the accuracy on independent data sets reaches to 85.0%. To the best of our knowledge, it is the first prediction model to define positive and negative samples using a flexible cutoff. So the comparison analysis and modeling results have demonstrated that our method would be a very promising strategy for more precisely defining protein–RNA binding sites.     

Copper(II) binding to Cap43 protein fragments

The C-terminal 20 and 30 amino acid sequences of Cap43 protein were chosen as models to study their interactions with Cu(II) ions. The behaviour of the 20 amino acid Ac-TRSRSH6TSEG-TRSRSH16TSEG and 30 amino acid Ac-TRSRSH6TSEG-TRSRSH16TSEG-TRSRSH26TSEG peptides towards Cu(II) ions at different pH values and different ligand-to-metal molar ratios, was examined. Spectroscopic (EPR, UV-Vis) and potentiometric techniques were performed to understand the details of metal binding to the peptides. The study showed that, starting from pH 4.0, each 10 amino acid fragment T1R2S3R4S5H6T7S8E9G10 was able to independently coordinate a single Cu(II) ion. The coordination mode involved the imidazole nitrogen of histidine H6 residue, and three amidic nitrogens from histidine H6, serine S5, and arginine R4 residues, respectively.     

Determination of binding constant and binding region of programmed cell death 5-heparin by capillary zone electrophoresis

A sensitive and selective high-performance analytical method based on capillary zone electrophoresis (CZE) was developed for investigating interactions between heparin and programmed cell death 5 (PDCD5) qualitatively and quantitatively. The binding constant of the interaction between PDCD5 and heparin calculated by Scatchard analysis was 4.17x10(4) M(-1) and the binding sites located in the C-terminal region of PDCD5 (residues 109-115). The precisions of migration times, peak heights and binding constants, expressed as the relative standard deviation, were less than 2.4%, 1.1% and 5.7%, respectively.