On the calculation of binding free energies using continuum methods: application to MHC class I protein-peptide interactions

Exploring the interactions of antihistamine with retinoic acid receptor beta (RARB) by molecular dynamics simulations and genome-wide meta-analysis

Kaposi sarcoma (KS) is one of the most common AIDS-related malignant neoplasms, which can leave lesions on the skin among HIV patients. These lesions can be treated with 9-cis-retinoic acid (9-cis-RA), an endogenous ligand of retinoic acid receptors that has been FDA-approved for treatment of KS. However, topical application of 9-cis-RA can induce several unpleasant side effects, like headache, hyperlipidemia, and nausea. Hence, alternative therapeutics with less side effects are desirable. There are case reports associating over-the-counter antihistamine usage with regression of KS. Antihistamines competitively bind to H1 receptor and block the action of histamine, best known for being released in response to allergens. Furthermore, there are already dozens of antihistamines that are FDA-approved with less side effects than 9-cis-RA. This led our team to conduct a series of in-silico assays to determine whether antihistamines can activate retinoic acid receptors. First, we utilized high-throughput virtual screening and molecular dynamics simulations to model high-affinity interactions between antihistamines and retinoic acid receptor beta (RARβ). We then performed systems genetics analysis to identify a genetic association between H1 receptor itself and molecular pathways involved in KS. Together, these findings advocate for exploration of antihistamines against KS, starting with our two promising hit compounds, bepotastine and hydroxyzine, for experimental validation study in the future.

Peptide mediated colorimetric detection of SARS-CoV-2 using gold nanoparticles: a molecular dynamics simulation study

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has necessitated the development of a rapid, simple yet selective naked-eye detection methodology that does not require any advanced instrumental techniques. In this study, we report our computational findings on the detection of SARS-CoV-2 using peptide- functionalized gold nanoparticles (GNPs). The peptide has been screened from angiotensin-converting enzyme 2 (ACE2) receptor situated on the surface of the host cell membrane which interacts with the spike protein of SARS-CoV-2, resulting entry of the virus into the host cell. As a result, the peptide-functionalized GNPs possess excellent affinity towards the spikes of SARS-CoV-2 and readily get aggregated once exposed to SARS-CoV-2 antigen or virus. The stability of the peptides on the surface of GNPs and their interaction with the spike protein of the virus have been investigated using coarse-grained molecular dynamic simulations. The potential of mean force calculation of spike protein confirmed strong binding between peptide and receptor-binding domain (RBD) of spike protein. Our in silico results demonstrate the potential of the peptide-functionalized GNPs in the development of simple and rapid colorimetric biosensors for clinical diagnosis.

Natural LILRB1 D1-D2 variants show frequency differences in populations and bind to HLA class I with various avidities

Leukocyte immunoglobulin-like receptor B1 (LILRB1) is widely expressed on various immune cells and the engagement of LILRB1 to HLA class I and pathogen-derived proteins can modulate the immune response. In the current study, 108 LILRB1 alleles were identified by screening the LILRB1 locus from the 1000 Genomes Phase 3 database. Forty-six alleles that occurred in three or more individuals encode 28 LILRB1 allotypes, and the inferred LILRB1 allotypes were then grouped into 9 LILRB1 D1-D2 variants for further analysis. We found that variants 1, 2, and 3 represent the three most frequent LILRB1 D1-D2 variants and the nine variants show frequency differences in populations. The binding assay demonstrated that variant 1 bound to HLA class I with the highest avidity, and all tested LILRB1 D1-D2 variants bound to HLA-C with lower avidity than to HLA-A and -B. Locus-specific polymorphisms at positions 183, 189, and 268 in HLA class I and dimorphisms in HLA-A (positions 207 and 253) and in HLA-B (position 194) affect their binding to LILRB1. Notably, the electrostatic interaction plays a critical role in the binding of LILRB1 to HLA class I as revealed by electrostatic analysis and by comparison of different binding avidities caused by polymorphisms at positions 72 and 103 of LILRB1. In this paper, we present a comprehensive study of the population genetics and binding abilities of LILRB1. The data will help us better understand the LILRB1-related diversity of the immune system and lay a foundation for functional studies.

Evaluation of kinetics and thermodynamics of interaction between immobilized SARS-CoV-2 nucleoprotein and specific antibodies by total internal reflection ellipsometry

During the pandemic, different methods for SARS-CoV-2 detection and COVID-19 diagnostics were developed, including antibody and antigen tests. For a better understanding of the interaction mechanism between SARS-CoV-2 virus proteins and specific antibodies, total internal reflection ellipsometry based evaluation of the interaction between SARS-CoV-2 nucleoprotein (SCoV2-rN) and anti-SCoV2-rN antibodies was performed. Results show that the appropriate mathematical model, which takes into account the formation of an intermediate complex, can be applied for the evaluation of SCoV2-rN/anti-SCoV2-rN complex formation kinetics. The calculated steric factor indicated that SCoV2-rN/anti-SCoV2-rN complex formation has very strict steric requirements. Estimated Gibbs free energy (ΔG_Assoc) for SCoV-rN and anti-SCoV-rN binding was determined as −34 kJ/mol. The reported findings are useful for the design of new analytical systems for the determination of anti-SCoV2-rN antibodies and for the development of new anti-SARS-CoV-2 medications.

A quantitative model of the bovine casein micelle: ion equilibria and calcium phosphate sequestration by individual caseins in bovine milk

The white appearance of skim milk is due to strong light scattering by colloidal particles called casein micelles. Bovine casein micelles comprise expressed proteins from four casein genes together with significant fractions of the total calcium, inorganic phosphate, magnesium and citrate ions in the milk. Thus, the milk salts are partitioned between the casein micelles, where they are mostly in the form of nanoclusters of an amorphous calcium phosphate sequestered by caseins through their phosphorylated residues, with the remainder in the continuous phase. Previously, a salt partition calculation was made assuming that the nanoclusters are sequestered only by short, highly phosphorylated casein sequences, sometimes called phosphate centres. Three of the four caseins have a proportion of their phosphorylated residues in either one or two phosphate centres and these were proposed to react with the nanoclusters equally and independently. An improved model of the partition of caseins and salts in milk is described in which all the phosphorylated residues in competent caseins act together to bind to and sequester the nanoclusters. The new model has been applied to results from a recent study of variation in salt and casein composition in the milk of individual cows. Compared to the previous model, it provides better agreement with experiment of the partition of caseins between free and bound states and equally good results for the partition of milk salts. In addition, new calculations are presented for the charge on individual caseins in their bound and free states.

Discovery of Inhibitors of Four Bromodomains by Fragment-Anchored Ligand Docking

The high-throughput docking protocol called ALTA-VS (anchor-based library tailoring approach for virtual screening) was developed in 2005 for the efficient in silico screening of large libraries of compounds by preselection of only those molecules that have optimal fragments (anchors) for the protein target. Here we present an updated version of ALTA-VS with a broader range of potential applications. The evaluation of binding energy makes use of a classical force field with implicit solvent in the continuum dielectric approximation. In about 2 days per protein target on a 96-core compute cluster (equipped with Xeon E3-1280 quad core processors at 2.5 GHz), the screening of a library of nearly 77 000 diverse molecules with the updated ALTA-VS protocol has resulted in the identification of 19, 3, 3, and 2 μM inhibitors of the human bromodomains ATAD2, BAZ2B, BRD4(1), and CREBBP, respectively. The success ratio (i.e., number of actives in a competition binding assay in vitro divided by the number of compounds tested) ranges from 8% to 13% in dose-response measurements. The poses predicted by fragment-based docking for the three ligands of the BAZ2B bromodomain were confirmed by protein X-ray crystallography.

Direction-dependent force-induced dissociation dynamics of an entropic-driven lock-and-key assembly

The unbinding dynamics of a nanosized sphere-and-cavity assembly under the pulling of constant force and constant loading rate is explored by dissipative particle dynamics simulations. The formation of this matched lock-and-key pair in a polymer solution is driven by the depletion attraction. The two-dimensional free energy landscape U(x,z) associated with this assembly is constructed. Our results indicate that the unbinding pathway along the orientation of the assembly is unfavorable due to the relatively high energy barrier compared to that along the tortuous minimum path whose energy barrier is not high. It is also found that the dissociation rate depends on the direction of the external force (θ) with respect to the assembly orientation. The presence of the force component perpendicular to the assembly orientation can reduce the bond lifetime significantly by driving the key particle to approach the minimum path. Moreover, the dissociation dynamics can be facilitated even by a pushing force compared to the spontaneous dissociation (without forces). To elucidate the effective pathway under pulling, the escaping position is analyzed and its mean direction with respect to the assembly orientation rises generally with increasing θ, revealing that the presence of the force component along the minimum pathway is helpful. The importance of the direction of the external pulling has been demonstrated in our simple system. Therefore, this effect should be considered in more complicated unbinding experiments.

Effect of secondary anchor amino acid substitutions on the immunogenic properties of an HLA-A*0201-restricted T cell epitope derived from the Trypanosoma cruzi KMP-11 protein

The TcTLE peptide (TLEEFSAKL) is a CD8(+) T cell HLA-A*0201-restricted epitope derived from the Trypanosoma cruzi KMP-11 protein that is efficiently processed, presented and recognized by CD8(+) T cells from chagasic patients. Since the immunogenic properties of wild-type epitopes may be enhanced by suitable substitutions in secondary anchor residues, we have studied the effect of introducing specific mutations at position 3, 6 and 7 of the TcTLE peptide. Mutations (E3L, S6V and A7F) were chosen on the basis of in silico predictions and in vitro assays were performed to determine the TcTLE-modified peptide binding capacity to the HLA-A*0201 molecule. In addition, the functional activity of peptide-specific CD8(+) T cells in HLA-A2(+) chagasic patients was also interrogated. In contrast to bioinformatics predictions, the TcTLE-modified peptide was found to have lower binding affinity and stability than the original peptide. Nevertheless, CD8(+) T cells from chronic chagasic patients recognized the TcTLE-modified peptide producing TNF-α and INF-γ and expressing CD107a/b, though in less extension than the response triggered by the original peptide. Overall, although the amino acids at positions 3, 6 and 7 of TcTLE are critical for the peptide affinity, they have a limited effect on the immunogenic properties of the TcTLE epitope.

Generalized iterative annealing model for the action of RNA chaperones

As a consequence of the rugged landscape of RNA molecules their folding is described by the kinetic partitioning mechanism according to which only a small fraction (φF) reaches the folded state while the remaining fraction of molecules is kinetically trapped in misfolded intermediates. The transition from the misfolded states to the native state can far exceed biologically relevant time. Thus, RNA folding in vivo is often aided by protein cofactors, called RNA chaperones, that can rescue RNAs from a multitude of misfolded structures. We consider two models, based on chemical kinetics and chemical master equation, for describing assisted folding. In the passive model, applicable for class I substrates, transient interactions of misfolded structures with RNA chaperones alone are sufficient to destabilize the misfolded structures, thus entropically lowering the barrier to folding. For this mechanism to be efficient the intermediate ribonucleoprotein complex between collapsed RNA and protein cofactor should have optimal stability. We also introduce an active model (suitable for stringent substrates with small φF), which accounts for the recent experimental findings on the action of CYT-19 on the group I intron ribozyme, showing that RNA chaperones do not discriminate between the misfolded and the native states. In the active model, the RNA chaperone system utilizes chemical energy of adenosine triphosphate hydrolysis to repeatedly bind and release misfolded and folded RNAs, resulting in substantial increase of yield of the native state. The theory outlined here shows, in accord with experiments, that in the steady state the native state does not form with unit probability.

Computational analysis of the binding specificity of Gleevec to Abl, c-Kit, Lck, and c-Src tyrosine kinases

Gleevec, a well-known cancer therapeutic agent, is an effective inhibitor of several tyrosine kinases, including Abl and c-Kit, but displays less potency to inhibit closely homologous tyrosine kinases, such as Lck and c-Src. Because many structural features of the binding site are highly conserved in these homologous kinases, the molecular determinants responsible for the binding specificity of Gleevec remain poorly understood. To address this issue, free energy perturbation molecular dynamics (FEP/MD) simulations with explicit solvent was used to compute the binding affinity of Gleevec to Abl, c-Kit, Lck, and c-Src. The results of the FEP/MD calculations are in good agreement with experiments, enabling a detailed and quantitative dissection of the absolute binding free energy in terms of various thermodynamic contributions affecting the binding specificity of Gleevec to the kinases. Dominant binding free energy contributions arises from the van der Waals dispersive interaction, compensating about two-thirds of the unfavorable free energy penalty associated with the loss of translational, rotational, and conformational freedom of the ligand upon binding. In contrast, the contributions from electrostatic and repulsive interactions nearly cancel out due to solvent effects. Furthermore, the calculations show the importance of the conformation of the kinase activation loop. Among the kinases examined, Abl provides the most favorable binding environment for Gleevec via optimal protein-ligand interactions and a small free energy cost for loss of the translational, rotational, and conformational freedom upon ligand binding. The FEP/MD calculations additionally reveal that Lck and c-Src provide similar nonbinding interactions with the bound-Gleevec, but the former pays less entropic penalty for the ligand losing its translational, rotational, and conformational motions to bind, examining the empirically observed differential binding affinities of Gleevec between the two Src-family kinases.

Protein surface dynamics: interaction with water and small solutes

Previous time resolved measurements had indicated that protons could propagate on the surface of a protein, or a membrane, by a special mechanism that enhances the shuttle of the proton towards a specific site [1]. It was proposed that a proper location of residues on the surface contributes to the proton shuttling function. In the present study, this notion was further investigated using molecular dynamics, with only the mobile charge replaced by Na(+) and Cl(-) ions. A molecular dynamics simulation of a small globular protein (the S6 of the bacterial ribosome) was carried out in the presence of explicit water molecules and four pairs of Na(+) and Cl(-) ions. A 10 ns simulation indicated that the ions and the protein's surface were in equilibrium, with rapid passage of the ions between the protein's surface and the bulk. Yet it was noted that, close to some domains, the ions extended their duration near the surface, suggesting that the local electrostatic potential prevented them from diffusing to the bulk. During the time frame in which the ions were detained next to the surface, they could rapidly shuttle between various attractor sites located under the electrostatic umbrella. Statistical analysis of molecular dynamics and electrostatic potential/entropy consideration indicated that the detainment state is an energetic compromise between attractive forces and entropy of dilution. The similarity between the motion of free ions next to a protein and the proton transfer on the protein's surface are discussed.

T-cell epitope vaccine design by immunoinformatics

Vaccination is generally considered to be the most effective method of preventing infectious diseases. All vaccinations work by presenting a foreign antigen to the immune system in order to evoke an immune response. The active agent of a vaccine may be intact but inactivated ('attenuated') forms of the causative pathogens (bacteria or viruses), or purified components of the pathogen that have been found to be highly immunogenic. The increased understanding of antigen recognition at molecular level has resulted in the development of rationally designed peptide vaccines. The concept of peptide vaccines is based on identification and chemical synthesis of B-cell and T-cell epitopes which are immunodominant and can induce specific immune responses. The accelerating growth of bioinformatics techniques and applications along with the substantial amount of experimental data has given rise to a new field, called immunoinformatics. Immunoinformatics is a branch of bioinformatics dealing with in silico analysis and modelling of immunological data and problems. Different sequence- and structure-based immunoinformatics methods are reviewed in the paper.

Molecular mechanism of the effects of salt and pH on the affinity between protein A and human immunoglobulin G1 revealed by molecular simulations

Protein A from the bacterium Staphylococcus aureus (SpA) has been widely used as an affinity ligand for purification of immunoglobulin G (IgG). The affinity between SpA and IgG is affected differently by salt and pH, but their molecular mechanisms still remain unclear. In this work, molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area analysis were performed to investigate the salt (NaCl) and pH effects on the affinity between SpA and human IgG1 (hIgG1). It is found that salt and pH affect the interactions of the hot spots of SpA by different mechanisms. In the salt solution, the compensations between helices I and II of SpA as well as between the nonpolar and electrostatic energies make the binding free energy independent of salt concentration. At pH 3.0, the unfavorable electrostatic interactions increase greatly and become the driving force for dissociation of the SpA-hIgG1 complex. They mainly come from the strong electrostatic repulsions between positively charged residues (H137, R146, and K154) of SpA and the positively charged residues of hIgG1. It is considered to be the molecular basis for hIgG1 elution from SpA-based affinity adsorbents at pH 3.0. The dissociation mechanism is then used to refine the binding model of SpA to hIgG1. The model is expected to help design high-affinity peptide ligands of IgG.

Simulating electrostatic energies in proteins: perspectives and some recent studies of pKas, redox, and other crucial functional properties

Electrostatic energies provide what is arguably the most effective tool for structure-function correlation of biological molecules. Here, we provide an overview of the current state-of-the-art simulations of electrostatic energies in macromolecules, emphasizing the microscopic perspective but also relating it to macroscopic approaches. We comment on the convergence issue and other problems of the microscopic models and the ways of keeping the microscopic physics while moving to semi-macroscopic directions. We discuss the nature of the protein dielectric "constants" reiterating our long-standing point that the dielectric "constants" in semi-macroscopic models depend on the definition and the specific treatment. The advances and the challenges in the field are illustrated considering different functional properties including pK(a)'s, redox potentials, ion and proton channels, enzyme catalysis, ligand binding, and protein stability. We emphasize the microscopic overcharging approach for studying pK(a) 's of internal groups in proteins and give a demonstration of power of this approach. We also emphasize recent advances in coarse grained models with a physically based electrostatic treatment and provide some examples including further directions in treating voltage activated ion channels.

The measured and calculated affinity of methyl- and methoxy-substituted benzoquinones for the Q(A) site of bacterial reaction centers

Quinones play important roles in mitochondrial and photosynthetic energy conversion acting as intramembrane, mobile electron, and proton carriers between catalytic sites in various electron transfer proteins. They display different affinity, selectivity, functionality, and exchange dynamics in different binding sites. The computational analysis of quinone binding sheds light on the requirements for quinone affinity and specificity. The affinities of 10 oxidized, neutral benzoquinones were measured for the high affinity Q(A) site in the detergent-solubilized Rhodobacter sphaeroides bacterial photosynthetic reaction center. Multiconformation Continuum Electrostatics was then used to calculate their relative binding free energies by grand canonical Monte Carlo sampling with a rigid protein backbone, flexible ligand, and side chain positions and protonation states. Van der Waals and torsion energies, Poisson-Boltzmann continuum electrostatics, and accessible surface area-dependent ligand-solvent interactions are considered. An initial, single cycle of GROMACS backbone optimization improves the match with experiment as do coupled-ligand and side-chain motions. The calculations match experiment with an root mean square deviation (RMSD) of 2.29 and a slope of 1.28. The affinities are dominated by favorable protein-ligand van der Waals rather than electrostatic interactions. Each quinone appears in a closely clustered set of positions. Methyl and methoxy groups move into the same positions as found for the native quinone. Difficulties putting methyls into methoxy sites are observed. Calculations using a solvent-accessible surface area-dependent implicit van der Waals interaction smoothed out small clashes, providing a better match to experiment with a RMSD of 0.77 and a slope of 0.97.

T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.

Computational design of protein-ligand binding: modifying the specificity of asparaginyl-tRNA synthetase

A method for computational design of protein-ligand interactions is implemented and tested on the asparaginyl- and aspartyl-tRNA synthetase enzymes (AsnRS, AspRS). The substrate specificity of these enzymes is crucial for the accurate translation of the genetic code. The method relies on a molecular mechanics energy function and a simple, continuum electrostatic, implicit solvent model. As test calculations, we first compute AspRS-substrate binding free energy changes due to nine point mutations, for which experimental data are available; we also perform large-scale redesign of the entire active site of each enzyme (40 amino acids) and compare to experimental sequences. We then apply the method to engineer an increased binding of aspartyl-adenylate (AspAMP) into AsnRS. Mutants are obtained using several directed evolution protocols, where four or five amino acid positions in the active site are randomized. Promising mutants are subjected to molecular dynamics simulations; Poisson-Boltzmann calculations provide an estimate of the corresponding, AspAMP, binding free energy changes, relative to the native AsnRS. Several of the mutants are predicted to have an inverted binding specificity, preferring to bind AspAMP rather than the natural substrate, AsnAMP. The computed binding affinities are significantly weaker than the native, AsnRS:AsnAMP affinity, and in most cases, the active site structure is significantly changed, compared to the native complex. This almost certainly precludes catalytic activity. One of the designed sequences has a higher affinity and more native-like structure and may represent a valid candidate for Asp activity.

Correlation analyses on binding affinity of substituted benzenesulfonamides with carbonic anhydrase using ab initio MO calculations on their complex structures

Quantitative structure-activity relationship analyses on the free energy change during complex formation between substituted benzenesulfonamides (BSAs) and bovine carbonic anhydrase II (bCA II) were performed using generilized Born/surface area (GB/SA) and ab initio fragment molecular orbital (FMO) calculations for the whole complex structures. The result shows that the overall free energy change is governed by the contribution from solvation and dissociation free energy changes accompanying by complex formation. The FMO-IFIE (interfragment interaction energy) analysis quantitatively revealed that the intrinsic interaction energy of bCA II with BSAs is mostly from interactions with amino acid residues in the active site of bCA II. The "Zn block" (Zn(2+) and three histidine residues coordinated to Zn(2+)) in the active site shows the lowest interaction energy and the greatest variance of interaction energy with BSAs through their coordination interaction. The proposed procedure was demonstrated to provide a quantitative basis for understanding a ligand-protein interaction at electronic and atomic levels.

Molecular dynamics simulations show that conformational selection governs the binding preferences of imatinib for several tyrosine kinases

Tyrosine kinases transmit cellular signals through a complex mechanism, involving their phosphorylation and switching between inactive and active conformations. The cancer drug imatinib binds tightly to several homologous kinases, including Abl, but weakly to others, including Src. Imatinib specifically targets the inactive, so-called "DFG-out" conformation of Abl, which differs from the preferred, "DFG-in" conformation of Src in the orientation of a conserved Asp-Phe-Gly (DFG) activation loop. However, recent x-ray structures showed that Src can also adopt the DFG-out conformation and uses it to bind imatinib. The Src/Abl-binding free energy difference can thus be decomposed into two contributions. Contribution i measures the different protein-imatinib interactions when either kinase is in its DFG-out conformation. Contribution ii depends on the ability of imatinib to select or induce this conformation, i.e. on the relative stabilities of the DFG-out and DFG-in conformations of each kinase. Neither contribution has been measured experimentally. We use molecular dynamics simulations to show that contribution i is very small, 0.2 +/- 0.6 kcal/mol; imatinib interactions are very similar in the two kinases, including long range electrostatic interactions with the imatinib positive charge. Contribution ii, deduced using the experimental binding free energy difference, is much larger, 4.4 +/- 0.9 kcal/mol. Thus, conformational selection, easy in Abl, difficult in Src, underpins imatinib specificity. Contribution ii has a simple interpretation; it closely approximates the stability difference between the DFG-out and DFG-in conformations of apo-Src. Additional calculations show that conformational selection also governs the relative binding of imatinib to the kinases c-Kit and Lck. These results should help clarify the current framework for engineering kinase signaling.

Exit strategies for charged tRNA from GluRS

For several class I aminoacyl-tRNA synthetases (aaRSs), the rate-determining step in aminoacylation is the dissociation of charged tRNA from the enzyme. In this study, the following factors affecting the release of the charged tRNA from aaRSs are computationally explored: the protonation states of amino acids and substrates present in the active site, and the presence and the absence of AMP and elongation factor Tu. Through molecular modeling, internal pK(a) calculations, and molecular dynamics simulations, distinct, mechanistically relevant post-transfer states with charged tRNA bound to glutamyl-tRNA synthetase from Thermus thermophilus (Glu-tRNA(Glu)) are considered. The behavior of these nonequilibrium states is characterized as a function of time using dynamical network analysis, local energetics, and changes in free energies to estimate transitions that occur during the release of the tRNA. The hundreds of nanoseconds of simulation time reveal system characteristics that are consistent with recent experimental studies. Energetic and network results support the previously proposed mechanism in which the transfer of amino acid to tRNA is accompanied by the protonation of AMP to H-AMP. Subsequent migration of proton to water reduces the stability of the complex and loosens the interface both in the presence and in the absence of AMP. The subsequent undocking of AMP or tRNA then proceeds along thermodynamically competitive pathways. Release of the tRNA acceptor stem is further accelerated by the deprotonation of the alpha-ammonium group on the charging amino acid. The proposed general base is Glu41, a residue binding the alpha-ammonium group that is conserved in both structure and sequence across nearly all class I aaRSs. This universal handle is predicted through pK(a) calculations to be part of a proton relay system for destabilizing the bound charging amino acid following aminoacylation. Addition of elongation factor Tu to the aaRS.tRNA complex stimulates the dissociation of the tRNA core and the tRNA acceptor stem.

The AGBNP2 Implicit Solvation Model

The AGBNP2 implicit solvent model, an evolution of the Analytical Generalized Born plus Non-Polar (AGBNP) model we have previously reported, is presented with the aim of modeling hydration effects beyond those described by conventional continuum dielectric representations. A new empirical hydration free energy component based on a procedure to locate and score hydration sites on the solute surface is introduced to model first solvation shell effects, such as hydrogen bonding, which are poorly described by continuum dielectric models. This new component is added to the Generalized Born and non-polar AGBNP terms. Also newly introduced is an analytical Solvent Excluded Volume (SEV) model which improves the solute volume description by reducing the effect of spurious high-dielectric interstitial spaces present in conventional van der Waals representations. The AGBNP2 model is parametrized and tested with respect to experimental hydration free energies of small molecules and the results of explicit solvent simulations. Modeling the granularity of water is one of the main design principles employed for the the first shell solvation function and the SEV model, by requiring that water locations have a minimum available volume based on the size of a water molecule. It is shown that the new volumetric model produces Born radii and surface areas in good agreement with accurate numerical evaluations of these quantities. The results of molecular dynamics simulations of a series of mini-proteins show that the new model produces conformational ensembles in substantially better agreement with reference explicit solvent ensembles than the original AGBNP model with respect to both structural and energetics measures.

Coulomb energies of protein-protein complexes with monopole-free charge distributions

From an analysis of Coulomb energy distributions of a large set of protein-protein complexes we show that the positive tail in the energy distribution disappears when the monopole-monopole term, the only energy term independent of inter-subunit orientations, is removed. This indicates that unfavorable Coulomb energies associated with subunit orientations are excluded in protein-protein complexes. The overall result remained unchanged when solvent effects were included. Our results have important bearing on the restriction of subunit orientations in protein-protein complexes and complement a recent work [K. Brock, K. Talley, K. Coley, P. Kundrotas, E. Alexov, Optimization of electrostatic interactions in protein-protein complexes, Biophys. J. 93 (2007) 3340-3352.] which showed that Coulomb energy of interaction in protein-protein complexes is sequence-optimized.

Poisson-Boltzmann model analysis of binding mRNA cap analogues to the translation initiation factor eIF4E

The electrostatic free energy of binding of two analogues of the 5'-mRNA cap, differing in size and electric charge, to the wild type and mutated eukaryotic initiation factor eIF4E was computed using the finite difference solutions to the Poisson-Boltzmann equation. Two definitions of the solute-solvent dielectric boundary were used: van der Waals model, solvent exclusion (SE) model. The computed electrostatic energies were supplemented by estimations of the non polar and entropic contributions. A comparison with experimental data for the investigated systems was done. It appears that the SE model with additional contribution fits experimental findings better than the van der Waals model does.

Identification and rational redesign of peptide ligands to CRIP1, a novel biomarker for cancers

Cysteine-rich intestinal protein 1 (CRIP1) has been identified as a novel marker for early detection of cancers. Here we report on the use of phage display in combination with molecular modeling to identify a high-affinity ligand for CRIP1. Panning experiments using a circularized C7C phage library yielded several consensus sequences with modest binding affinities to purified CRIP1. Two sequence motifs, A1 and B5, having the highest affinities for CRIP1, were chosen for further study. With peptide structure information and the NMR structure of CRIP1, the higher-affinity A1 peptide was computationally redesigned, yielding a novel peptide, A1M, whose affinity was predicted to be much improved. Synthesis of the peptide and saturation and competitive binding studies demonstrated approximately a 10–28-fold improvement in the affinity of A1M compared to that of either A1 or B5 peptide. These techniques have broad application to the design of novel ligand peptides.

Breast cancer is one of the most frequently diagnosed malignancies in American females and is the second leading cause of cancer deaths in women. Several improvements in diagnostic protocols have enhanced our ability for earlier detection of breast cancer, resulting in improvement of therapeutic outcome and an increased survival rate for breast cancer patients. However, current early screening techniques are neither comprehensive nor infallible. Imaging techniques that improve breast cancer detection, localization, and evaluation of therapy are essential in combating the disease. Cysteine-rich intestinal protein 1 (CRIP1) has been identified as a novel marker for early detection of breast cancers. Here, we report the use of phage display and computational molecular modeling to identify a high-affinity ligand for CRIP1. Phage display panning experiments initially identified consensus peptide sequences with modest binding affinity to purified CRIP1. Using ab initio modeling of binding peptide structures, computational docking, and recently developed free energy estimation protocols, we redesigned the peptides to increase their affinity for CRIP1. Synthesis of the redesigned peptide and binding studies demonstrated approximately a 10–28-fold improvement in the binding affinity. The combination of computational and experimental techniques in this study demonstrates a potentially powerful tool in modulating protein–protein interactions.

Evaluation of electrostatic interactions

Described here are several computational procedures for the analysis of electrostatic interactions in molecular complexes, all based on a continuum model of solvation. The first section describes how to compute the residual potential, a measure of how electrostatically complementary a ligand is for its receptor. The second procedure describes electrostatic component analysis, a method by which the electrostatic contribution to the binding free energy can be broken up into terms directly attributable to individual chemical groups. Finally, electrostatic affinity optimization is described. This procedure is particularly useful in determining what portions of a ligand are the most suboptimal, and thus provide the greatest opportunity for the design of improvements.

Using DelPhi to compute electrostatic potentials and assess their contribution to interactions

There is a general agreement that electrostatic interactions play a significant role in the structure and function of biological molecules. However, obtaining quantitative estimation of the electrostatic energy requires computational models that capture the microscopic nature of the heterogeneous environment of macromolecules. This protocol offers elaboration on one of the common methods to calculate the electrostatic energetic contributions using continuum electrostatics. The method involves solving the Poisson-Boltzmann (PB) equation numerically and regarding the solute as having a homogenous dielectric constant. In order to apply this method, a three dimensional structure of the molecule derived from experimental data (crystallography, NMR) or modeling techniques is required. The protocol will focus on the DelPhi program (Accelrys Inc. San Diego), which is one of the most common programs used for the estimation of electrostatic free energy contribution. A simple procedure of assigning criteria and parameters (charge distribution, solvent and solute dielectric constants, iterations, grid resolution, etc) enables one to illustrate an electrostatic potential map and estimate the electrostatic free energy, although with limited accuracy.

Metal-mediated self-assembly of protein superstructures: influence of secondary interactions on protein oligomerization and aggregation

We have previously demonstrated that non-self-associating protein building blocks can oligomerize to form discrete supramolecular assemblies under the control of metal coordination. We show here that secondary interactions (salt bridges and hydrogen bonds) can be critical in guiding the metal-induced self-assembly of proteins. Crystallographic and hydrodynamic measurements on appropriately engineered cytochrome cb562 variants pinpoint the importance of a single salt-bridging arginine side chain in determining whether the protein monomers form a discrete Zn-induced tetrameric complex or heterogeneous aggregates. The combined ability to direct PPIs through metal coordination and secondary interactions should provide the specificity required for the construction of complex protein superstructures and the selective control of cellular processes that involve protein-protein association reactions.

Prediction of T-cell epitope

The prevailing methods to predict T-cell epitopes are reviewed. Motif matching, matrix, support vector machine (SVM), and empirical scoring function methods are mainly reviewed; and the thermodynamic integration (TI) method using all-atom molecular dynamics (MD) simulation is mentioned briefly. The motif matching method appeared first and developed with the increased understanding of the characteristic structure of MHC-peptide complexes, that is, pockets aligned in the groove and corresponding residues fitting on them. This method is now becoming outdated due to the insufficiency and inaccuracy of information. The matrix method, the generalization of interaction between pockets of MHC and residues of bound peptide to all the positions in the groove, is the most prevalent one. Efficiency of calculation makes this method appropriate to scan for candidates of T-cell epitopes within whole expressed proteins in an organ or even in a body. A large amount of experimental binding data is necessary to determine a matrix. SVM is a relative of the artificial neural network, especially direct generalization of a linear Perceptron. By incorporating non-binder data and adopting encoding that reflects the physical properties of amino acids, its performance becomes quite high. Empirical scoring functions apparently seem to be founded on a physical basis. However, the estimates directly derived from the method using only structural data are far from practical use. Through regression with binding data of a series of ligands and receptors, this method predicts binding affinity with appropriate accuracy. The TI method using MD requires only structural data and a general atomic parameter, that is, force field, and hence theoretically most consistent; however, the extent of perturbation, inaccuracy of the force field, the necessity of an immense amount of calculations, and continued difficulty of sampling an adequate structure hamper the application of this method in practical use.

Interaction of antagonists with calmodulin: insights from molecular dynamics simulations

We report results of 12 ns, all-atom molecular dynamics simulation (MDS) and Poisson-Boltzmann free energy calculations (PBFE) on calmodulin (CaM) bound to two molecules of trifluoperazine (TFP) and of N-(3,3, diphenylpropyl)- N'-[1- R-(3,4-bis-butoxyphenyl)-ethyl]-propylenediamine (DPD). X-ray data show very similar structures for the two complexes, yet the antagonists significantly differ with respect to their CaM binding affinities, the neutral DPD is much more potent. The goal of the study was to unravel the reason why TFP is less potent although its positive charge should facilitate binding. The electrostatic energy terms in CHARMM and binding free energy terms of the PBFE approach showed TFP a better antagonist, while inspection of hydrophobic contacts supports DPD binding. Detailed inspection of the amino acid contributions of PBFE calculations unravel that steric reasons oppose the favorable binding of TFP. Structural conditions are given for a successful drug design strategy, which may benefit also from charge-charge interactions.

Continuum molecular electrostatics, salt effects, and counterion binding--a review of the Poisson-Boltzmann theory and its modifications

This work is a review of the Poisson-Boltzmann (PB) continuum electrostatics theory and its modifications, with a focus on salt effects and counterion binding. The PB model is one of the mesoscopic theories that describes the electrostatic potential and equilibrium distribution of mobile ions around molecules in solution. It serves as a tool to characterize electrostatic properties of molecules, counterion association, electrostatic contributions to solvation, and molecular binding free energies. We focus on general formulations which can be applied to large molecules of arbitrary shape in all-atomic representation, including highly charged biomolecules such as nucleic acids. These molecules present a challenge for theoretical description, because the conventional PB model may become insufficient in those cases. We discuss the conventional PB equation, the corresponding functionals of the electrostatic free energy, including a connection to DFT, simple empirical extensions to this model accounting for finite size of ions, the modified PB theory including ionic correlations and fluctuations, the cell model, and supplementary methods allowing to incorporate site-bound ions in the PB calculations.

Dynamics of Recognition between tRNA and elongation factor Tu

Elongation factor Tu (EF-Tu) binds to all standard aminoacyl transfer RNAs (aa-tRNAs) and transports them to the ribosome while protecting the ester linkage between the tRNA and its cognate amino acid. We use molecular dynamics simulations to investigate the dynamics of the EF-Tu.guanosine 5'-triphosphate.aa-tRNA(Cys) complex and the roles played by Mg2+ ions and modified nucleosides on the free energy of protein.RNA binding. Individual modified nucleosides have pronounced effects on the structural dynamics of tRNA and the EF-Tu.Cys-tRNA(Cys) interface. Combined energetic and evolutionary analyses identify the coevolution of residues in EF-Tu and aa-tRNAs at the binding interface. Highly conserved EF-Tu residues are responsible for both attracting aa-tRNAs as well as providing nearby nonbonded repulsive energies that help fine-tune molecular attraction at the binding interface. In addition to the 3' CCA end, highly conserved tRNA nucleotides G1, G52, G53, and U54 contribute significantly to EF-Tu binding energies. Modification of U54 to thymine affects the structure of the tRNA common loop resulting in a change in binding interface contacts. In addition, other nucleotides, conserved within certain tRNA specificities, may be responsible for tuning aa-tRNA binding to EF-Tu. The trend in EF-Tu.Cys-tRNA(Cys) binding energies observed as the result of mutating the tRNA agrees with experimental observation. We also predict variations in binding free energies upon misacylation of tRNA(Cys) with d-cysteine or O-phosphoserine and upon changing the protonation state of l-cysteine. Principal components analysis in each case reveals changes in the communication network across the protein.tRNA interface and is the basis for the entropy calculations.

Identification of DNA-binding protein target sequences by physical effective energy functions: free energy analysis of lambda repressor-DNA complexes

Background

Specific binding of proteins to DNA is one of the most common ways gene expression is controlled. Although general rules for the DNA-protein recognition can be derived, the ambiguous and complex nature of this mechanism precludes a simple recognition code, therefore the prediction of DNA target sequences is not straightforward. DNA-protein interactions can be studied using computational methods which can complement the current experimental methods and offer some advantages. In the present work we use physical effective potentials to evaluate the DNA-protein binding affinities for the λ repressor-DNA complex for which structural and thermodynamic experimental data are available.

Results

The binding free energy of two molecules can be expressed as the sum of an intermolecular energy (evaluated using a molecular mechanics forcefield), a solvation free energy term and an entropic term. Different solvation models are used including distance dependent dielectric constants, solvent accessible surface tension models and the Generalized Born model. The effect of conformational sampling by Molecular Dynamics simulations on the computed binding energy is assessed; results show that this effect is in general negative and the reproducibility of the experimental values decreases with the increase of simulation time considered. The free energy of binding for non-specific complexes, estimated using the best energetic model, agrees with earlier theoretical suggestions. As a results of these analyses, we propose a protocol for the prediction of DNA-binding target sequences. The possibility of searching regulatory elements within the bacteriophage λ genome using this protocol is explored. Our analysis shows good prediction capabilities, even in absence of any thermodynamic data and information on the naturally recognized sequence.

Conclusion

This study supports the conclusion that physics-based methods can offer a completely complementary methodology to sequence-based methods for the identification of DNA-binding protein target sequences.

Mean-field analysis of protein-protein interactions

Calculations were performed on the D1.3-E5.2 antibody-antibody complex estimating the binding affinities of the wild-type and 16 alanine substitutions. Analyzed were structural models of the interfacial region containing a zinc ion and crystallographic waters. A continuum approach was used to evaluate the electrostatic free energies and the hydrophobic effect was calculated by employing a buried molecular surface area relationship. Estimates of the absolute binding affinity reproduced the experimental value within the uncertainty of assessing entropic and strain energy contributions. The best correlation for mutants with experimental data was achieved when the hydrophilicity of created cavities were considered, and yielded a correlation coefficient of 0.7 and an average error of +/-1.4 kcal/mol. Empirically fitting the free energy function produced a smaller error of +/-1.0 kcal/mol. Depending on the electrical potential and electrostatic reorganization, scaling the 'protein dielectric constant' to approximately 10 may improve the accuracy of continuum models for evaluating amino acid substitutions.