Protein-protein recognition analyzed by docking simulation.

Antibody-lysozyme and protease-inhibitor complexes are reconstituted by docking lysozyme as a rigid body onto the combining site of the antibodies and the inhibitors onto the active site of the proteases. Simplified protein models with one sphere per residue are subjected to simulated annealing using a crude energy function where the attractive component is proportional to the interface area. The procedure finds clusters of orientations in which a steric fit between the two protein components is achieved over a large contact surface. With five out of six complexes, the native structure of the complexes determined by X-ray crystallography is among those retained. Docked complexes are then subjected to conformational energy refinement with full atomic detail. With Fab HyHEL 5 and lysozyme, a native-like complex has the lowest refined energy. It can also be retrieved when starting with the X-ray structure of free lysozyme. However, some non-native complexes cannot be rejected: they form large interfaces, have a large number of H-bonds, and few unpaired polar groups. While these are necessary features of protein-protein recognition, they are not sufficient in determining specificity.     

The effect of structural parameters and positive charge distance on the interaction free energy of antimicrobial peptides with membrane surface

Many attempts have been made to find hints explaining the relationship between physicochemical and structural properties of antimicrobial peptides (AMPs) which are relevant to their antimicrobial activities. We here found that there is a difference in the percentages of hydrophobic, hydrophilic, and charged residues between AMPs killing both bacteria and fungi (Group A) and AMPs that only kill bacteria (Group B). The percentage of charged residues in Group A AMPs is highly elevated, while in Group B the percentage of hydrophobic residues is increased. This result suggests a sequence-based mechanism of selectivity for AMPs. Moreover, we examined how the distance between basic residues affects the interaction free energy of AMPs with the membrane surface, since most of the known AMPs act by membrane perturbation. We measured the average distance between basic residues throughout the 3D structure of AMPs by defining D_pr parameter and calculated the interaction free energy for 10 AMPs that interacted with the DPPC membrane using molecular dynamics simulation. We found that the changes of the interaction free energy correlates with the change of D_pr by a linear regression coefficient of r^2?=?.47 and a cubic regression coefficient of r^2?=?.70.     

Inclusion of solvation free energy with molecular mechanics energy: alanyl dipeptide as a test case.

A combined force field of molecular mechanics and solvation free energy is tested by carrying out energy minimization and molecular dynamics on several conformations of the alanyl dipeptide. Our results are qualitatively consistent with previous experimental and computational studies, in that the addition of solvation energy stabilizes the C5 conformation of the alanyl dipeptide relative to the C7.     

Nucleotide modifications and tRNA anticodon-mRNA codon interactions on the ribosome

We have carried out molecular dynamics simulations of the tRNA anticodon and mRNA codon, inside the ribosome, to study the effect of the common tRNA modifications cmo(5)U34 and m(6)A37. In tRNA(Val), these modifications allow all four nucleotides to be successfully read at the wobble position in a codon. Previous data suggest that entropic effects are mainly responsible for the extended reading capabilities, but detailed mechanisms have remained unknown. We have performed a wide range of simulations to elucidate the details of these mechanisms at the atomic level and quantify their effects: extensive free energy perturbation coupled with umbrella sampling, entropy calculations of tRNA (free and bound to the ribosome), and thorough structural analysis of the ribosomal decoding center. No prestructuring effect on the tRNA anticodon stem-loop from the two modifications could be observed, but we identified two mechanisms that may contribute to the expanded decoding capability by the modifications: The further reach of the cmo(5)U34 allows an alternative outer conformation to be formed for the noncognate base pairs, and the modification results in increased contacts between tRNA, mRNA, and the ribosome.     

Site specific point mutation changes specificity: A molecular modeling study by free energy simulations and enzyme kinetics of the thermodynamics in ribonuclease T1 substrate interactions

We have theoretically and experimentally studied the binding of two different ligands to wild-type ribonuclease T₁ (RNT1) and to a mutant of RNT1 with Glu-46 replaced by Gln. The binding of the natural substrate 3′-GMP has been compared with the binding of a fluorescent probe, 2-aminopurine 3′-monophosphate (2AP), and relative free energies of binding of these ligands to the mutant and the wild-type (wt) enzyme have been calculated by free energy perturbation methods. The free energy perturbations predict that the mutant RNT1-Gln-46 binds 2AP better than 3′GMP, in agreement with experiments on dinucleotides. Four free energy perturbations, forming a closed loop, have been performed to allow the detection of systematic errors in the simulation procedure. Because of the larger number of atoms involved, it was necessary to use a much longer simulation time for the change in the protein, i.e., the perturbation from Glu to Gln, than in the perturbation from 3′-GMP to 2AP. Finally the structure of the binding site is analyzed for understanding differences in catalytic speed and binding strength. © 1993 Wiley-Liss, Inc.     

3D-QSAR and molecular recognition of Klebsiella pneumoniae NDM-1 inhibitors

New Delhi metallo-β-lactamase-1 (NDM-1) as a target for the development of anti-superbug agents, plays an important role in the resistance of β-lactam antibiotics and has received worldwide attention. Sulfhydryl propionic acid derivatives can effectively inhibit the catalytic activity of NDM-1, but the quantitative structure–activity relationship (QSAR) and inhibitor-target recognition mechanism both remain unclear. In this work, CoMFA and CoMSIA models of sulfhydryl propionic acid inhibitors with high predictive ability were obtained, from which the effect of different substituents on the inhibitory activity against NDM-1 were revealed at the molecular level. Then, two 120-nanosecond comparative molecular dynamics (MD) simulations for NDM-1 enzyme and NDM-1-inhibitor complex systems were performed to study the recognition and inhibition mechanism of sulfhydryl propionic acid derivatives. The binding of inhibitors alters the entire H-bond network of the NDM-1 system accompanied by the formation of strong interactions with I35, W93, H120, H122, D124, H189 and H250, further weakens the recognition of NDM-1 by its endogenic substrates. Finally, the results of free energy landscape and conformation cluster analyses show that NDM-1 underwent a significant conformational change after the association with sulfhydryl propionic acid inhibitors. Our findings can provide theoretical support and help for anti-superbug agents design based on the structures of NDM-1 and sulfhydryl propionic acid derivatives.     

Identification of novel natural inhibitor for NorM – a multidrug and toxic compound extrusion transporter – an insilico molecular modeling and simulation studies

The emergence of bacterial multidrug resistance is an increasing problem in treatment of infectious diseases. An important cause for the multidrug resistance of bacteria is the expression of multidrug efflux transporters. The multidrug and toxic compound extrusion (MATE) transporters are most recently recognized as unique efflux system for extrusion of antimicrobials and therapeutic drugs due to energy stored in either Na⁺ or H⁺ electrochemical gradient. In the present study, high throughput virtual screening of natural compound collections against NorM – a MATE transporter from Neisseria gonorrhea (NorM-NG) has been carried out followed by flexible docking. The molecular simulation in membrane environment has been performed for understanding the stability and binding energetic of top lead compounds. Results identified a compound from the Indian medicinal plant “Terminalia chebula” which has good binding free energy compared to substrates (rhodamine 6 g, ethidium) and more favorable interactions with the central cavity forming active site residues. The compound has restricted movement in TM7, TM8, and TM1, thus blocking the disruption of Na+ – coordination along with equilibrium state bias towards occlude state of NorM transporter. Thus, this compound blocks the effluxing pathway of antimicrobial drugs and provides as a natural bioactive lead inhibitor against NorM transporter in drug-resistant gonorrhea.     

Computational carbohydrate chemistry: what theoretical methods can tell us

Computational methods have had a long history of application to carbohydrate systems and their development in this regard is discussed. The conformational analysis of carbohydrates differs in several ways from that of other biomolecules. Many glycans appear to exhibit numerous conformations coexisting in solution at room temperature and a conformational analysis of a carbohydrate must address both spatial and temporal properties. When solution nuclear magnetic resonance data are used for comparison, the simulation must give rise to ensemble-averaged properties. In contrast, when comparing to experimental data obtained from crystal structures a simulation of a crystal lattice, rather than of an isolated molecule, is appropriate. Molecular dynamics simulations are well suited for such condensed phase modeling. Interactions between carbohydrates and other biological macromolecules are also amenable to computational approaches. Having obtained a three-dimensional structure of the receptor protein, it is possible to model with accuracy the conformation of the carbohydrate in the complex. An example of the application of free energy perturbation simulations to the prediction of carbohydrate-protein binding energies is presented.     

Modeling protein recognition of carbohydrates

We have a limited understanding of the details of molecular recognition of carbohydrates by proteins, which is critical to a multitude of biological processes. Furthermore, carbohydrate-modifying proteins such as glycosyl hydrolases and phosphorylases are of growing importance as potential drug targets. Interactions between proteins and carbohydrates have complex thermodynamics, and in general the specific positioning of only a few hydroxyl groups determines their binding affinities. A thorough understanding of both carbohydrate and protein structures is thus essential to predict these interactions. An atomic-level view of carbohydrate recognition through structures of carbohydrate-active enzymes complexed with transition-state inhibitors reveals some of the distinctive molecular features unique to protein-carbohydrate complexes. However, the inherent flexibility of carbohydrates and their often water-mediated hydrogen bonding to proteins makes simulation of their complexes difficult. Nonetheless, recent developments such as the parameterization of specific force fields and docking scoring functions have greatly improved our ability to predict protein-carbohydrate interactions. We review protein-carbohydrate complexes having defined molecular requirements for specific carbohydrate recognition by proteins, providing an overview of the different computational techniques available to model them.     

Automated docking of substrates to proteins by simulated annealing

The Metropolis technique of conformation searching is combined with rapid energy evaluation using molecular affinity potentials to give an efficient procedure for docking substrates to macromolecules of known structure. The procedure works well on a number of crystallographic test systems, functionally reproducing the observed binding modes of several substrates.     

Molecular modeling of the interactions of trichosanthin with four substrate analogs

Trichosanthin (TCS) is a ribosome-inactivating protein (RIP) that possesses N-glycosidase activity. It inactivates ribosomes and arrests protein synthesis by removing a specific adenine from 28S rRNA. A molecular dynamics simulated annealing method was applied to study the binding modes of TCS with substrate analogs, three oligonucleotides GAG, GAGA, and CGAGAG, based on the crystal structures of the stable complexes of TCS with NADPH and with the reaction product adenine. A water molecule proposed to be responsible for hydrolyzing the N-glycosidic bond was included in the model. All the oligoribonucleotides can dock into the active cleft of TCS without unfavorable contacts. The interaction energies between TCS and the three oligonucleotides were calculated. The interactions of TCS with NADH were also studied by a molecular dynamics simulated annealing method. The interaction energy between NADH and TCS was compared with that between NADPH and TCS, showing that the lack of 2-phosphate group leads to an energy rise of 20 kcal/mol.     

A reduced representation of proteins for use in restraint satisfaction calculations

A reduced representation of paroteins has been developed for use in restraint satisfaction calculations with dynamic simulated annealing. Each amino acid residue is represented by up to four spherical virtual atoms. The virtual bonds and excluded volume of these atoms has ben parameterized by analysis of 83 protein structures determined at high resolution by X-ray crystallography. The use of the new representation in NOE distance restraint satisfaction has been compared with the standard all-atom represntation for the determination of the structures of crambin, eshistatin, and protein G. Using the reduced representation, there is a 30-fold decrease in the computer time needed for generatin a single structure, and up to a 20-fold decrease in the time taken to produce an acceptable structure compared to using the all-atom representation. The root mean square deviation between the mean structure obtain with all-atom and reduced representation si between 1.5 and 1.7 Å for C_α atoms. The new representation is adequate for describing the “low-resolution” features of protein structure such as the general fold and the positions of the secondary structure for more detailed refinement with the full all-atom representation. © 1993 Wiley-Liss, Inc.     

Substrate directs enzyme dynamics by bridging distal sites: UDP-galactopyranose mutase

UDP-Galactopyranose mutase (UGM) is a flavoenzyme that catalyzes interconversion of UDP-galactopyranose (UDP-Galp) and UDP-galactofuranose (UDP-Galf); its activity depends on FAD redox state. The enzyme is vital to many pathogens, not native to mammals, and is an important drug target. We have probed binding of substrate, UDP-Galp, and UDP to wild type and W160A UGM from K. pneumoniae, and propose that substrate directs recognition loop dynamics by bridging distal FAD and W160 sites; W160 interacts with uracil of the substrate and is functionally essential. Enhanced Trp fluorescence upon substrate binding to UGM indicates conformational changes remote from the binding site because the fluorescence is unchanged upon binding to W70F/W290F UGM where W160 is the sole Trp. MD simulations map these changes to recognition loop closure to coordinate substrate. This requires galactose-FAD interactions as Trp fluorescence is unchanged upon substrate binding to oxidized UGM, or binding of UDP to either form of the enzyme, and MD show heightened recognition loop mobility in complexes with UDP. Consistent with substrate-directed loop closure, UDP binds 10-fold more tightly to oxidized UGM, yet substrate binds tighter to reduced UGM. This requires the W160-U interaction because redox-switched binding affinity of substrate reverses in the W160A mutant where it only binds when oxidized. Without the anchoring W160-U interaction, an alternative binding mode for UDP is detected, and STD-NMR experiments show simultaneous binding of UDP-Galp and UDP to different subsites in oxidized W160A UGM: Substrate no longer directs recognition loop dynamics to coordinate tight binding to the reduced enzyme.     

Micelle-bound conformation of a hairpin-forming peptide: combined NMR and molecular dynamics study

A peptide fragment from a protein hairpin turn region was modified by addition of isoleucine residues to both ends to enhance binding to lipid micelles; the resulting peptide (I(1)-I(2)-C(3)-N(4)-N(5)-P(6)-H(7)-I(8)-I(9)) contains the core sequence I-C-N-N-P-H from an antibody-binding region of hemagglutinin A. Nuclear magnetic resonance (NMR) diffusion measurements indicated partial binding (43-65%) of the peptide to micelles of n-octylglucoside and significantly stronger binding (85%) to dodecylphosphocholine (DPC) micelles. Simulated annealing and conformational analysis using nuclear Overhauser enhancement restraints revealed a type I or III hairpin turn between residues N(5) and I(8) of the DPC-bound peptide. Amide exchange experiments support the possibility that a hydrogen bond forms between N(5) and I(8), stabilizing the turn. In contrast, no discernable structure was observed for the peptide in aqueous solution by either NMR or circular dichroism. Molecular dynamics simulations of DPC micelles and peptide-micelle complexes suggested that the peptide lies flat on the micelle surface and showed rapid rearrangement of the lipids to accommodate the bound peptide. According to a search performed using the basic local alignment search tool (BLAST), the sequences N-P-H-I and N-P-H-V are present as hairpin turns in eight of the nine proteins whose crystal structures were available. The addition of isoleucine residues and the use of lipid micelles to stabilize hairpin conformations equivalent to those found in proteins generates new possibilities for reproducing biologically important hairpin turns from short, linear peptides.     

Simulated folding in polypeptides of diversified molecular tacticity: implications for protein folding and de novo design

Stereochemistry could be a powerful variable for conformational tune up of polypeptides for de novo design. It may be also useful probe of possible role of interamide energetics in selection and stabilization of conformation. The homopolypeptides Ac-Xxx30-NHMe, with Xxx = Ala, Val, and Leu, of diversified stereochemical structure are generated by simulated racemization with a modified GROMOS-96 force field. The polypeptides, and other systematic stereochemical variants, are folded by simulated annealing with another modified GROMOS-96 force field under the dielectric constant values 1, 4, and 10. The resultant 15,000 molecular folds of isotactic (poly-L-chiral), syndiotactic (alternating L,D-chiral), and heterotactic (random-L,D-chiral) stereochemical structure, belonging to three polypeptide series, achieved under three different folding conditions, are assessed statistically for structure-to-energy-to-conformation relationship. The results suggest that interamide electrostatics could be a major factor in secondary-structure selection in polypeptides while main-chain stereochemistry could dictate molecular packing and therefore the relative magnitude of hydrogen-bond and Lennard-Jones (LJ) contributions in conformational energy. A method for computational design of heterotactic molecular folds in polypeptide structure has been developed, and the first road map for a chiral tune up of polypeptide structure based on stereochemical engineering has been laid down. Broad implications for protein structure, folding, and de novo design are briefly discussed.     

The Influence of Starting Coordinates in Free Energy Simulations of Ligand Binding to Dihydrofolate Reductase

Abstract

Molecular dynamics (MD) simulation combined with free energy perturbation (FEP) methods have been used to study the key structural differences and relative free energies for the binding of 6-methyl-N5-deazapterin (N8 protonated) and the 8-substituted compound, 6,8-dimethyl-N5-deazapterin (N3 protonated), to dihydrofolate reductase (DHFR). The free energy changes have been calculated using a variety of initial X-ray coordinates derived from bacterial and vertebrate (including human) DHFRs, and both with and without the reduced cofactor nicotinamide adenine dinucleotide (NADPH) bound. Given a sufficiently long simulation time for the FEP calculations (ca. 200 ps), all structures obtained after mutating 6,8-methyl-N5-deazapterin to 6-methyl-N5-deazapterin exhibited hydrogen bond formation between a backbone carbonyl group of DHFR and H(N8) of 6-methyl-N5-deazapterin, analogous to that found in the X-ray crystal structure of N5-deazafolate(N8 protonated) bound to human DHFR. However, both simulation and experiment suggest this additional H-bonding does not greatly enhance thermodynamic stability, with experiment indicating at most a factor of 2 difference in the relative affinities of the two ligand cations for vertebrate DHFR. Moreover, a binding differential of 10 in favour of the protonated 8-substituted compound is found experimentally for bacterial DHFR. The MD/FEP calculations suggest that the relative cost of ligand desolvation may largely cancel the lowering of free energy obtained in the active site, resulting in predicted binding differences within the range indicated by the vertebrate and bacterial DHFR experiments. However, the theoretical free energy changes could not be obtained with the accuracy required for the rationalization of the observed species dependence. While sampling difficulties are known to be inherent in MD simulation methodologies, these studies with several initial coordinate sets have demonstrated the contribution of coordinate choice to this problem. The results indicate that for demanding protein-ligand binding problems such as this one, the accuracy of the method may be no better than ± 2 kcal/mol.     

A general Bayesian method for an automated signal class recognition in 2D NMR spectra combined with a multivariate discriminant analysis

Summary A generally applicable method for the automated classification of 2D NMR peaks has been developed, based on a Bayesian approach coupled to a multivariate linear discriminant analysis of the data. The method can separate true NMR signals from noise signals, solvent stripes and artefact signals. The analysis relies on the assumption that the different signal classes have different distributions of specific properties such as line shapes, line widths and intensities. As to be expected, the correlation network of the distributions of the selected properties affects the choice of the discriminant function and the final selection of signal properties. The classification rule for the signal classes was deduced from Bayes's theorem. The method was successfully tested on a NOESY spectrum of HPr protein from Staphylococcus aureus. The calculated probabilities for the different signal class memberships are realistic and reliable, with a high efficiency of discrimination between peaks that are true NOE signals and those that are not.     

Modeling the interaction between the N‐terminal domain of the tumor suppressor p53 and azurin

It is known that the half life of the tumor suppressor p53 can be increased by the interaction with the bacterial protein azurin, resulting in an enhanced anti‐tumoral activity. The understanding of the molecular mechanisms on the basis of this phenomenon can open the way to new anti‐cancer strategies. Some experimental works have given evidence of an interaction between p53 and azurin (AZ); however the binding regions of the proteins are still unknown. Recently, fluorescence studies have shown that p53 partakes in the binding with the bacterial protein by its N‐terminal (NT) domain. Here we have used a computational method to get insight into this interacting mode. The model that we propose for the best complex between AZ and p53 has been obtained from a rigid‐body docking, coupled with a molecular dynamics (MD) simulation, a free energy calculation, and validated by mutagenesis analysis. We have found a high degree of geometric fit between the two proteins that are kept together by several hydrophobic interactions and numerous hydrogen bonds. Interestingly, it has emerged that AZ binds essentially to the helices H_I and H_III of the p53 NT domain, which are also interacting regions for the foremost inhibitor of p53, MDM2. Copyright © 2009 John Wiley & Sons, Ltd.