Continuum solvent studies of the stability of RNA hairpin loops and helices

Growth-incompetent monomers of human calcitonin lead to a noncanonical direct relationship between peptide concentration and aggregation lag time

The role of the peptide hormone calcitonin in skeletal protection has led to its use as a therapeutic for osteoporosis. However, calcitonin aggregation into amyloid fibrils limits its therapeutic efficacy, necessitating a modification of calcitonin's aggregation kinetics. Here, we report a direct relationship between human calcitonin (hCT) concentration and aggregation lag time. This kinetic trend was contrary to the conventional understanding of amyloid aggregation and persisted over a range of aggregation conditions, as confirmed by thioflavin-T kinetics assays, CD spectroscopy, and transmission EM. Dynamic light scattering, 1H NMR experiments, and seeded thioflavin-T assay results indicated that differences in initial peptide species contribute to this trend more than variations in the primary nucleus formation rate. On the basis of kinetics modeling results, we propose a mechanism whereby a structural conversion of hCT monomers is needed before incorporation into the fibril. Our kinetic mechanism recapitulates the experimentally observed relationship between peptide concentration and lag time and represents a novel mechanism in amyloid aggregation. Interestingly, hCT at low pH and salmon calcitonin (sCT) exhibited the canonical inverse relationship between concentration and lag time. Comparative studies of hCT and sCT with molecular dynamics simulations and CD indicated an increased α-helical structure in sCT and low-pH hCT monomers compared with neutral-pH hCT, suggesting that α-helical monomers represent a growth-competent species, whereas unstructured random coil monomers represent a growth-incompetent species. Our finding that initial monomer concentration is positively correlated with lag time in hCT aggregation could help inform future efforts for improving therapeutic applications of CT.

The Antinociceptive Agent SBFI-26 Binds to Anandamide Transporters FABP5 and FABP7 at Two Different Sites

Human FABP5 and FABP7 are intracellular endocannabinoid transporters. SBFI-26 is an α-truxillic acid 1-naphthyl monoester that competitively inhibits the activities of FABP5 and FABP7 and produces antinociceptive and anti-inflammatory effects in mice. The synthesis of SBFI-26 yields several stereoisomers, and it is not known how the inhibitor binds the transporters. Here we report co-crystal structures of SBFI-26 in complex with human FABP5 and FABP7 at 2.2 and 1.9 Å resolution, respectively. We found that only (S)-SBFI-26 was present in the crystal structures. The inhibitor largely mimics the fatty acid binding pattern, but it also has several unique interactions. Notably, the FABP7 complex corroborates key aspects of the ligand binding pose at the canonical site previously predicted by virtual screening. In FABP5, SBFI-26 was unexpectedly found to bind at the substrate entry portal region in addition to binding at the canonical ligand-binding pocket. Our structural and binding energy analyses indicate that both R and S forms appear to bind the transporter equally well. We suggest that the S enantiomer observed in the crystal structures may be a result of the crystallization process selectively incorporating the (S)-SBFI-26-FABP complexes into the growing lattice, or that the S enantiomer may bind to the portal site more rapidly than to the canonical site, leading to an increased local concentration of the S enantiomer for binding to the canonical site. Our work reveals two binding poses of SBFI-26 in its target transporters. This knowledge will guide the development of more potent FABP inhibitors based upon the SBFI-26 scaffold.

Exploration of the binding affinities between ecdysone agonists and EcR/USP by docking and MM-PB/GBSA approaches

Ecdysone receptor (EcR) is a significant target in the identification of new environmentally friendly pesticides. There are two types of ecdysone agonists: steroidal ecdysone agonists and dibenzoylhydrazines (DBHs). In this study, various modeling methods (homology modeling, molecular docking, MD simulation, binding free energy calculation, and per-residue binding free energy decomposition) were utilized to study the different binding mechanisms of two types of ecdysone agonists. Our theoretical results indicated that the relative binding potencies of DBHs can be ranked sufficiently accurately using the MOE docking method. However, MM/PBSA calculations more accurately predicted the binding affinities between steroidal ecdysone agonists and EcR-LBD. To identify the key residues involved in ecdysone agonist binding, the binding free energy (ΔG _Bind) was decomposed into the energy contributions of individual residues. The results revealed that nine residues-Ile339, Thr343, Met380, Met381, Tyr403, Tyr408, Asp419, Gln503, and Asn504-determined the binding affinities of the DBHs. Glu309, Met342, Arg383, Arg387, and Leu396 were important influences on the binding affinities of the steroidal ecdysone agonists. Graphical abstract The ecdysone receptor (EcR) is related to insect growth and has been shown to be a useful target for insecticides.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

A newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit. ParFit is in an open source program available for free on GitHub ( https://github.com/fzahari/ParFit ).

Molecular dynamics and MM/GBSA-integrated protocol probing the correlation between biological activities and binding free energies of HIV-1 TAR RNA inhibitors

The interaction of HIV-1 transactivator protein Tat with its cognate transactivation response (TAR) RNA has emerged as a promising target for developing antiviral compounds and treating HIV infection, since it is a crucial step for efficient transcription and replication. In the present study, molecular dynamics (MD) simulations and MM/GBSA calculations have been performed on a series of neamine derivatives in order to estimate appropriate MD simulation time for acceptable correlation between ΔG_bind and experimental pIC₅₀ values. Initially, all inhibitors were docked into the active site of HIV-1 TAR RNA. Later to explore various conformations and examine the docking results, MD simulations were carried out. Finally, binding free energies were calculated using MM/GBSA method and were correlated with experimental pIC₅₀ values at different time scales (0-1 to 0-10 ns). From this study, it is clear that in case of neamine derivatives as simulation time increased the correlation between binding free energy and experimental pIC₅₀ values increased correspondingly. Therefore, the binding energies which can be interpreted at longer simulation times can be used to predict the bioactivity of new neamine derivatives. Moreover, in this work, we have identified some plausible critical nucleotide interactions with neamine derivatives that are responsible for potent inhibitory activity. Furthermore, we also provide some insights into a new class of oxadiazole-based back bone cyclic peptides designed by incorporating the structural features of neamine derivatives. On the whole, this approach can provide a valuable guidance for designing new potent inhibitors and modify the existing compounds targeting HIV-1 TAR RNA.

The expanding repertoire of G4 DNA structures

The definition of DNA and RNA G-quadruplexes (G4s) has recently been broadened to include structures with certain defects: bulges, G-vacancies or mismatches. Despite the striking progress in computational methods for assessing G4 folding propensity, predicting G4s with defects remains problematic, reflecting the enhanced sequential diversity of these motifs. "Imperfect" G4 motifs, i.e., those containing interrupted or truncated G-runs, are typically omitted from genomic analyses. We report here studies of G4s with defects and compare these structures with classical ("perfect") quadruplexes. Thermal stabilities and ligand interactions are also discussed. We exploited a simple in-house computational tool for mining putative G4s with defects in the human genome. The obtained profiles of the genomic distribution of imperfect G4 motifs were analyzed. Collectively, our findings suggest that, similar to classical G4s, imperfect G4s could be considered as potential regulatory elements, pathology biomarkers and therapeutic targets.

Multiplex 16S rRNA-derived geno-biochip for detection of 16 bacterial pathogens from contaminated foods

Foodborne diseases caused by various pathogenic bacteria occur worldwide. To prevent foodborne diseases and minimize their impacts, it is important to inspect contaminated foods and specifically detect many types of pathogenic bacteria. Several DNA oligonucleotide biochips based on 16S rRNA have been investigated to detect bacteria; however, a mode of detection that can be used to detect diverse pathogenic strains and to examine the safety of food matrixes is still needed. In the present work, a 16S rRNA gene-derived geno-biochip detection system was developed after screening DNA oligonucleotide specific capture probes, and it was validated for multiple detection of 16 pathogenic strains that frequently occur with a signature pattern. rRNAs were also used as detection targets directly obtained from cell lysates without any purification and amplification steps in the bacterial cells separated from 8 food matrixes by simple pretreatments. Thus, the developed 16S rRNA-derived geno-biochip can be successfully used for the rapid and multiple detection of the 16 pathogenic bacteria frequently isolated from contaminated foods that are important for food safety.

Conformational changes associated with L16P and T118M mutations in the membrane-embedded PMP22 protein, consequential in CMT-1A

Peripheral myelin protein 22 (PMP22) resides in the plasma membrane and is required for myelin formation in the peripheral nervous system. Excess PMP22 mutants accumulate in the endoplasmic reticulum (ER) resulting in the inherited neuropathies of Charcot-Marie-Tooth disease. However, there was no evidence of the structure of PMP22 or how mutations affect its folding. Therefore, in this study, we combined bioinformatics and homology modeling approaches to obtain three-dimensional native and mutated PMP22 models and its anchoring to a POPC membrane, submitted to .5-μs MD simulations, to determine how the L16P and T118M mutations affect the conformational behavior of PMP22. In addition, we investigated the ability of the native and mutated species to accumulate in the ER, via interaction with RER1, by combining protein-protein docking and MD simulations, taking the conformations that were most representative of the native and mutated PMP22 systems and RER1 conformations. Principal component analysis over MD simulations revealed that L16P and T118M mutations resulted in increased structural instability compared to the native form, which is consistent with previous experimental findings of increased structural fluctuations along a loop connecting transmembrane α-helix1 and α-helix2. Docking and MD simulations coupled with the MMGBSA approach allowed the identification that the binding interface for the PMP22-RER1 complex takes place through transmembrane α-helix1 and α-helix2, with higher effective binding free energy values between the mutated PMP22 systems and RER1 than for the native PMP22, mainly through van der Waals interactions.

Energetic and flexibility properties captured by long molecular dynamics simulations of a membrane-embedded pMHCII-TCR complex

Although crystallographic data have provided important molecular insight into the interactions in the pMHC-TCR complex, the inherent features of this structural approach cause it to only provide a static picture of the interactions. While unbiased molecular dynamics simulations (UMDSs) have provided important information about the dynamic structural behavior of the pMHC-TCR complex, most of them have modeled the pMHC-TCR complex as soluble, when in physiological conditions, this complex is membrane bound; therefore, following this latter UMDS protocol might hamper important dynamic results. In this contribution, we performed three independent 300 ns-long UMDSs of the pMHCII-TCR complex anchored in two opposing membranes to explore the structural and energetic properties of the recognition of pMHCII by the TCR. The conformational ensemble generated through UMDSs was subjected to clustering and Cartesian principal component analyses (cPCA) to explore the dynamical behavior of the pMHCII-TCR association. Furthermore, based on the conformational population sampled through UMDSs, the effective binding free energy, per-residue free energy decomposition, and alanine scanning mutations were explored for the native pMHCII-TCR complex, as well as for 12 mutations (p1-p12MHCII-TCR) introduced in the native peptide. Clustering analyses and cPCA provide insight into the rocking motion of the TCR onto pMHCII, together with the presence of new electrostatic interactions not observed through crystallographic methods. Energetic results provide evidence of the main contributors to the pMHC-TCR complex formation as well as the key residues involved in this molecular recognition process.

Structural and mechanistic insight into substrate binding from the conformational dynamics in apo and substrate-bound DapE enzyme

Conformational dynamics induced by substrate binding in DapE enzyme.

Structural Basis for the Structure–Activity Behaviour of Oxaliplatin and its Enantiomeric Analogues: A Molecular Dynamics Study of Platinum-DNA Intrastrand Crosslink Adducts

The discrimination of Pt-GG adducts by mismatch repair proteins, DNA damage-recognition proteins, and translation DNA polymerases was thought to be vital in determining the toxicity, efficacy, and mutagenicity of platinum anti-tumour drugs. Studies on cis-diammine-Pt-GG (from cisplatin and carboplatin) and trans-R,R-diaminocyclohexane (DACH)-Pt-GG indicated that these proteins recognized the differences in conformation and conformational dynamics of Pt-DNA complexes. However, the structural basis of enantiomeric DACH-Pt-GG forms is unclear. Molecular dynamics simulations results presented here reveal that the conformational dynamics between trans-R,R-DACH-Pt-GG, trans-S,S-DACH-Pt-GG, cis-DACH-Pt-GG and undamaged DNA are distinct and depend on the chirality of DACH though their major conformations are similar. Trans-DACH-Pt was found to be energetically favoured over cis-DACH-Pt to form DNA adducts. Moreover, oxaliplatin and its cis-DACH analogues were found to preferentially form hydrogen bonds on the 3′ side of the Pt-GG adduct, whereas the S,S-DACH-Pt preferred the 5′ side. A three-centre hydrogen bond formed between cis1-DACH-Pt and DNA was observed, and the differences in hydrogen bond formation are highly correlated with differences in DNA conformational dynamics. Based on these results, it is suggested that the different bioactivities of oxaliplatin and its enantiomeric analogues were controlled by the difference in hydrogen bonds formation dynamics between DNA and the Pt moiety. Our molecular dynamics approach was demonstrated to be applicable to the study of stereoisomer conformations of platinum-DNA model, thereby suggesting its potential application as a tool for the study and design of new effective platinum-based drugs.

Molecular dynamics simulation studies of GSK-3β ATP competitive inhibitors: understanding the factors contributing to selectivity

Glycogen synthase kinase-3 is a constitutively acting, multifunctional serine threonine kinase, the role of which has been implicated in several physiological pathways and has emerged as a promising target for the treatment of type-II diabetes and Alzheimer's disease. In order to provide a detailed understanding of the origin of selectivity determinants of ATP competitive inhibitors, molecular dynamics simulations in combination with MM-PBSA binding energy calculations were performed using crystal structures of GSK-3β and CDK-2 in complex with 12 ATP competitive inhibitors. Analysis of energy contributions indicate that electrostatic interaction energy dictates the selectivity of ATP competitive inhibitors against CDK-2. Key interactions as well as residues that potentially make a major contribution to the binding free energy were identified at the ATP binding site. This analysis stresses the need for the inhibitors to interact with Lys85, Thr138, and Arg141 in the binding site of GSK-3β to show selectivity. The residue-wise energy decomposition analysis further suggested the additional role of Gln185 in determining the selectivity of maleimides. The results obtained in this study can be utilized to design new selective GSK-3 ATP competitive inhibitors.

Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions

Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies.

Molecular Dynamics Simulation Studies of dTTP Binding and Catalysis Mediated by YhdE Dimerization

YhdE is a Maf-like (multicopy associated filamentation) protein that primarily acts as dTTPase to hydrolyze dTTP into dTMP and two phosphate molecules in cell metabolism pathway. Two crystal structures of YhdE have been previously determined, representing the open and closed active site conformations, respectively. Based on the structures, we have carried out molecular dynamics simulations and free energy calculations to investigate dTTP binding to and hydrolysis by YhdE. Our results suggest that YhdE closed state is structurally more compact than its open state at room temperature. YhdE open state is a favorable conformation for dTTP binding and closed state is a structurally favorable conformation for catalytic reaction. This observation is supported by the structure of YhdE homolog in complex with a nucleotide analog. Free energy calculations reveal that YhdE dimerization occurs preferentially in dTTP binding and is favorable for successive cooperative reaction. The key residues R11, R12 and K80, are found to contribute to the substrate stabilization. Further, YhdE dimerization and binding of dTTP induce the cooperative effect through a direct allosteric communication network in YhdE from the dTTP binding sites in the catalytic center to the intermolecular β-strand in YhdE dimer.

Benzopyrimido-pyrrolo-oxazine-dione (R)-BPO-27 Inhibits CFTR Chloride Channel Gating by Competition with ATP

We previously reported that benzopyrimido-pyrrolo-oxazinedione BPO-27 [6-(5-bromofuran-2-yl)-7,9-dimethyl-8,10-dioxo-11-phenyl-7,8,9,10-tetrahydro-6H-benzo[b]pyrimido [4',5':3,4]pyrrolo [1,2-d][1,4]oxazine-2-carboxylic acid] inhibits the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel with low nanomolar potency and reduces cystogenesis in a model of polycystic kidney disease. We used computational chemistry and patch-clamp to show that enantiomerically pure (R)-BPO-27 inhibits CFTR by competition with ATP, whereas (S)-BPO-27 is inactive. Docking computations using a homology model of CFTR structure suggested that (R)-BPO-27 binds near the canonical ATP binding site, and these findings were supported by molecular dynamics simulations showing a lower binding energy for the (R) versus (S) stereoisomers. Three additional lower-potency BPO-27 analogs were modeled in a similar fashion, with the binding energies predicted in the correct order. Whole-cell patch-clamp studies showed linear CFTR currents with a voltage-independent (R)-BPO-27 block mechanism. Single-channel recordings in inside-out patches showed reduced CFTR channel open probability and increased channel closed time by (R)-BPO-27 without altered unitary channel conductance. At a concentration of (R)-BPO-27 that inhibited CFTR chloride current by ∼50%, the EC50 for ATP activation of CFTR increased from 0.27 to 1.77 mM but was not changed by CFTRinh-172 [4-[[4-oxo-2-thioxo-3-[3-trifluoromethyl)phenyl]-5-thiazolidinylidene]methyl]benzoic acid], a thiazolidinone CFTR inhibitor that acts at a site distinct from the ATP binding site. Our results suggest that (R)-BPO-27 inhibition of CFTR involves competition with ATP.

Stacking in RNA: NMR of Four Tetramers Benchmark Molecular Dynamics

Molecular dynamics (MD) simulations for RNA tetramers r(AAAA), r(CAAU), r(GACC), and r(UUUU) are benchmarked against 1H-1H NOESY distances and 3J scalar couplings to test effects of RNA torsion parametrizations. Four different starting structures were used for r(AAAA), r(CAAU), and r(GACC), while five starting structures were used for r(UUUU). On the basis of X-ray structures, criteria are reported for quantifying stacking. The force fields, AMBER ff99, parmbsc0, parm99χ_Yil, ff10, and parmTor, all predict experimentally unobserved stacks and intercalations, e.g., base 1 stacked between bases 3 and 4, and incorrect χ, ϵ, and sugar pucker populations. The intercalated structures are particularly stable, often lasting several microseconds. Parmbsc0, parm99χ_Yil, and ff10 give similar agreement with NMR, but the best agreement is only 46%. Experimentally unobserved intercalations typically are associated with reduced solvent accessible surface area along with amino and hydroxyl hydrogen bonds to phosphate nonbridging oxygens. Results from an extensive set of MD simulations suggest that recent force field parametrizations improve predictions, but further improvements are necessary to provide reasonable agreement with NMR. In particular, intramolecular stacking and hydrogen bonding interactions may not be well balanced with the TIP3P water model. NMR data and the scoring method presented here provide rigorous benchmarks for future changes in force fields and MD methods.

The Interaction of Heparin Tetrasaccharides with Chemokine CCL5 Is Modulated by Sulfation Pattern and pH

Interactions between chemokines such as CCL5 and glycosaminoglycans (GAGs) are essential for creating haptotactic gradients to guide the migration of leukocytes into inflammatory sites, and the GAGs that interact with CCL5 with the highest affinity are heparan sulfates/heparin. The interaction between CCL5 and its receptor on monocytes, CCR1, is mediated through residues Arg-17 and -47 in CCL5, which overlap with the GAG-binding (44)RKNR(47) "BBXB" motifs. Here we report that heparin and tetrasaccharide fragments of heparin are able to inhibit CCL5-CCR1 binding, with IC50 values showing strong dependence on the pattern and extent of sulfation. Modeling of the CCL5-tetrasaccharide complexes suggested that interactions between specific sulfate and carboxylate groups of heparin and residues Arg-17 and -47 of the protein are essential for strong inhibition; tetrasaccharides lacking the specific sulfation pattern were found to preferentially bind CCL5 in positions less favorable for inhibition of the interaction with CCR1. Simulations of a 12-mer heparin fragment bound to CCL5 indicated that the oligosaccharide preferred to interact simultaneously with both (44)RKNR(47) motifs in the CCL5 homodimer and engaged residues Arg-47 and -17 from both chains. Direct engagement of these residues by the longer heparin oligosaccharide provides a rationalization for its effectiveness as an inhibitor of CCL5-CCR1 interaction. In this mode, histidine (His-23) may contribute to CCL5-GAG interactions when the pH drops just below neutral, as occurs during inflammation. Additionally, an examination of the contribution of pH to modulating CCL5-heparin interactions suggested a need for careful interpretation of experimental results when experiments are performed under non-physiological conditions.

Specificity of furanoside-protein recognition through antibody engineering and molecular modeling

Recognition of furanosides (five-membered ring sugars) by proteins plays important roles in host-pathogen interactions. In comparison to their six-membered ring counterparts (pyranosides), detailed studies of the molecular motifs involved in the recognition of furanosides by proteins are scarce. Here the first in-depth molecular characterization of a furanoside-protein interaction system, between an antibody (CS-35) and cell wall polysaccharides of mycobacteria, including the organism responsible for tuberculosis is reported. The approach was centered on the generation of the single chain variable fragment of CS-35 and a rational library of its mutants. Investigating the interaction from various aspects revealed the structural motifs that govern the interaction, as well as the relative contribution of molecular forces involved in the recognition. The specificity of the recognition was shown to originate mainly from multiple CH-π interactions and, to a lesser degree, hydrogen bonds formed in critical distances and geometries.

Implicit solvent methods for free energy estimation

Solvation is a fundamental contribution in many biological processes and especially in molecular binding. Its estimation can be performed by means of several computational approaches. The aim of this review is to give an overview of existing theories and methods to estimate solvent effects giving a specific focus on the category of implicit solvent models and their use in Molecular Dynamics. In many of these models, the solvent is considered as a continuum homogenous medium, while the solute can be represented at the atomic detail and at different levels of theory. Despite their degree of approximation, implicit methods are still widely employed due to their trade-off between accuracy and efficiency. Their derivation is rooted in the statistical mechanics and integral equations disciplines, some of the related details being provided here. Finally, methods that combine implicit solvent models and molecular dynamics simulation, are briefly described.

Predicting the Origins of Anti-Blood Group Antibody Specificity: A Case Study of the ABO A- and B-Antigens

The ABO blood group system is the most important blood type system in human transfusion medicine. Here, we explore the specificity of antibody recognition toward ABO blood group antigens using computational modeling and biolayer interferometry. Automated docking and molecular dynamics simulations were used to explore the origin of the specificity of an anti-blood group A antibody variable fragment (Fv AC1001). The analysis predicts a number of Fv-antigen interactions that contribute to affinity, including a hydrogen bond between a His^L49 and the carbonyl moiety of the GalNAc in antigen A. This interaction was consistent with the dependence of affinity on pH, as measured experimentally; at lower pH there is an increase in binding affinity. Binding energy calculations provide unique insight into the origin of interaction energies at a per-residue level in both the scFv and the trisaccharide antigen. The calculations indicate that while the antibody can accommodate both blood group A and B antigens in its combining site, the A antigen is preferred by 4 kcal/mol, consistent with the lack of binding observed for the B antigen.

Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design

The docking methods used in structure-based virtual database screening offer the ability to quickly and cheaply estimate the affinity and binding mode of a ligand for the protein receptor of interest, such as a drug target. These methods can be used to enrich a database of compounds, so that more compounds that are subsequently experimentally tested are found to be pharmaceutically interesting. In addition, like all virtual screening methods used for drug design, structure-based virtual screening can focus on curated libraries of synthesizable compounds, helping to reduce the expense of subsequent experimental verification. In this review, we introduce the protein-ligand docking methods used for structure-based drug design and other biological applications. We discuss the fundamental challenges facing these methods and some of the current methodological topics of interest. We also discuss the main approaches for applying protein-ligand docking methods. We end with a discussion of the challenging aspects of evaluating or benchmarking the accuracy of docking methods for their improvement, and discuss future directions.

Insights into the binding of GABA to the insect RDL receptor from atomistic simulations: a comparison of models

The resistance to dieldrin (RDL) receptor is an insect pentameric ligand-gated ion channel (pLGIC). It is activated by the neurotransmitter γ-aminobutyric acid (GABA) binding to its extracellular domain; hence elucidating the atomistic details of this interaction is important for understanding how the RDL receptor functions. As no high resolution structures are currently available, we built homology models of the extracellular domain of the RDL receptor using different templates, including the widely used acetylcholine binding protein and two pLGICs, the Erwinia Chrysanthemi ligand-gated ion channel (ELIC) and the more recently resolved GluCl. We then docked GABA into the selected three dimensional structures, which we used as starting points for classical molecular dynamics simulations. This allowed us to analyze in detail the behavior of GABA in the binding sites, including the hydrogen bond and cation-π interaction networks it formed, the conformers it visited and the possible role of water molecules in mediating the interactions; we also estimated the binding free energies. The models were all stable and showed common features, including interactions consistent with experimental data and similar to other pLGICs; differences could be attributed to the quality of the models, which increases with increasing sequence identity, and the use of a pLGIC template. We supplemented the molecular dynamics information with metadynamics, a rare event method, by exploring the free energy landscape of GABA binding to the RDL receptor. Overall, we show that the GluCl template provided the best models. GABA forming direct salt-bridges with Arg211 and Glu204, and cation-π interactions with an aromatic cage including Tyr109, Phe206 and Tyr254, represents a favorable binding arrangement, and the interaction with Glu204 can also be mediated by a water molecule.

Defining the structural origin of the substrate sequence independence of O-GlcNAcase using a combination of molecular docking and dynamics simulation

Protein glycosylation with O-linked N-acetylglucosamine (O-GlcNAc) is a post-translational modification of serine/threonine residues in nucleocytoplasmic proteins. O-GlcNAc has been shown to play a role in many different cellular processes and O-GlcNAcylation is often found at sites that are also known to be phosphorylated. Unlike phosphorylation, O-GlcNAc levels are regulated by only two enzymes, O-GlcNAc transferase (OGT) and O-GlcNAc hydrolase (O-GlcNAcase or OGA). So far, no obvious consensus sequence has been found for sites of O-GlcNAcylation. Additionally, O-GlcNAcase recognizes and cleaves all O-GlcNAcylated proteins, independent of their sequence. In this work, we generate and analyze five models of O-GlcNAcylated peptides in complex with a bacterial OGA. Each of the five glycopeptides bind to OGA in a similar fashion, with OGA-peptide interactions primarily, but not exclusively, involving the peptide backbone atoms, thus explaining the lack of sensitivity to peptide sequence. Nonetheless, differences in peptide sequences, particularly at the -1 to -4 positions, lead to variations in predicted affinity, consistent with observed experimental variations in enzyme kinetics. The potential exists, therefore, to employ the present analysis to guide the development glycopeptide-specific inhibitors, or conversely, the conversion of OGA into a reagent that could target specific O-GlcNAcylated peptide sequences.

Ligand recognition by the TPR domain of the import factor Toc64 from Arabidopsis thaliana

The specific targeting of protein to organelles is achieved by targeting signals being recognised by their cognate receptors. Cytosolic chaperones, bound to precursor proteins, are recognized by specific receptors of the import machinery enabling transport into the specific organelle. The aim of this study was to gain greater insight into the mode of recognition of the C-termini of Hsp70 and Hsp90 chaperones by the Tetratricopeptide Repeat (TPR) domain of the chloroplast import receptor Toc64 from Arabidopsis thaliana (At). The monomeric TPR domain binds with 1∶1 stoichiometry in similar micromolar affinity to both Hsp70 and Hsp90 as determined by isothermal titration calorimetry (ITC). Mutations of the terminal EEVD motif caused a profound decrease in affinity. Additionally, this study considered the contributions of residues upstream as alanine scanning experiments of these residues showed reduced binding affinity. Molecular dynamics simulations of the TPR domain helices upon peptide binding predicted that two helices within the TPR domain move backwards, exposing the cradle surface for interaction with the peptide. Our findings from ITC and molecular dynamics studies suggest that AtToc64_TPR does not discriminate between C-termini peptides of Hsp70 and Hsp90.

Enzymatic basis for N-glycan sialylation: structure of rat α2,6-sialyltransferase (ST6GAL1) reveals conserved and unique features for glycan sialylation

Glycan structures on glycoproteins and glycolipids play critical roles in biological recognition, targeting, and modulation of functions in animal systems. Many classes of glycan structures are capped with terminal sialic acid residues, which contribute to biological functions by either forming or masking glycan recognition sites on the cell surface or secreted glycoconjugates. Sialylated glycans are synthesized in mammals by a single conserved family of sialyltransferases that have diverse linkage and acceptor specificities. We examined the enzymatic basis for glycan sialylation in animal systems by determining the crystal structures of rat ST6GAL1, an enzyme that creates terminal α2,6-sialic acid linkages on complex-type N-glycans, at 2.4 Å resolution. Crystals were obtained from enzyme preparations generated in mammalian cells. The resulting structure revealed an overall protein fold broadly resembling the previously determined structure of pig ST3GAL1, including a CMP-sialic acid-binding site assembled from conserved sialylmotif sequence elements. Significant differences in structure and disulfide bonding patterns were found outside the sialylmotif sequences, including differences in residues predicted to interact with the glycan acceptor. Computational substrate docking and molecular dynamics simulations were performed to predict and evaluate the CMP-sialic acid donor and glycan acceptor interactions, and the results were compared with kinetic analysis of active site mutants. Comparisons of the structure with pig ST3GAL1 and a bacterial sialyltransferase revealed a similar positioning of donor, acceptor, and catalytic residues that provide a common structural framework for catalysis by the mammalian and bacterial sialyltransferases.

Determination of the α-conotoxin Vc1.1 binding site on the α9α10 nicotinic acetylcholine receptor

α-Conotoxin Vc1.1 specifically and potently inhibits the nicotinic acetylcholine receptor subtype α9α10 (α9α10 nAChR) and is a potential novel treatment for neuropathic pain. Here, we used a combination of computational modeling and electrophysiology experiments to determine the Vc1.1 binding site on the α9α10 nAChR. Interactions of Vc1.1 with two probable binding sites, α9α10 and α10α9, were modeled. Mutational energies calculated by assuming specific interactions in the α10α9 binding site correlated better with electrophysiological recordings than those assuming interactions with the α9α10 binding site. Two novel Vc1.1 analogues, [N9F]Vc1.1 and [N9W]Vc1.1, were predicted to have large differences in affinity between the two binding sites. Data from functional studies were consistent with computational predictions that assumed preferred binding of Vc1.1 to the α10α9 pocket. Moreover, our modeling study suggested that a single hydrogen bond formed between Vc1.1 and position 59 of the α10α9 pocket confers specificity to rat versus human α9α10 nAChRs.

Tertiary structure-based analysis of microRNA-target interactions

Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex-Argonaute protein complexes into a pipeline to model and predict miRNA-target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson-Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA-target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA-target duplexes agree with titration calorimetry data. Analysis of duplex-Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods.

Free Energy Profile and Kinetics Studies of Paclitaxel Internalization from the Outer to the Inner Wall of Microtubules

Several pieces of experimental evidence led us to hypothesize that the mechanism of action of paclitaxel (Taxol) could involve a two-steps binding process, with paclitaxel first binding within the outer wall of microtubules and then moving into the inner binding site. In this work, we first used multiply targeted molecular dynamics (MTMD) for steering paclitaxel from the outer toward the inner binding site. This rough trajectory was then submitted to a refinement procedure in the path collective variables space. Paclitaxel binding energy was monitored along the refined pathway, highlighting the relevance of residues belonging to the H6-H7 and the M- loops. Computational results were supported by kinetics studies performed on fluorescent paclitaxel derivatives.

Molecular dynamics investigation on a series of HIV protease inhibitors: assessing the performance of MM-PBSA and MM-GBSA approaches

The binding free energies (ΔG(Bind)) obtained from molecular mechanics with Poisson-Boltzmann surface area (MM-PBSA) or molecular mechanics with Generalized Born surface area (MM-GBSA) calculations using molecular dynamics (MD) trajectories are the most popular procedures to measure the strength of interactions between a ligand and its receptor. Several attempts have been made to correlate the ΔG(Bind) and experimental IC(50) values in order to observe the relationship between binding strength of a ligand (with its receptor) and its inhibitory activity. The duration of MD simulations seems very important for getting acceptable correlation. Here, we are presenting a systematic study to estimate the reasonable MD simulation time for acceptable correlation between ΔG(Bind) and experimental IC(50) values. A comparison between MM-PBSA and MM-GBSA approaches is also presented at various time scales. MD simulations (10 ns) for 14 HIV protease inhibitors have been carried out by using the Amber program. MM-PBSA/GBSA based ΔG(Bind) have been calculated and correlated with experimental IC(50) values at different time scales (0-1 to 0-10 ns). This study clearly demonstrates that the MM-PBSA based ΔG(Bind) (ΔG(Bind)-PB) values provide very good correlation with experimental IC(50) values (quantitative and qualitative) when MD simulation is carried out for a longer time; however, MM-GBSA based ΔG(Bind) (ΔG(Bind)-GB) values show acceptable correlation for shorter time of simulation also. The accuracy of ΔG(Bind)-PB increases and ΔG(Bind)-GB remains almost constant with the increasing time of simulation.

Discovery of novel tubulin inhibitors via structure-based hierarchical virtual screening

To discover novel tubulin inhibitors, we performed structure-based virtual screening against the colchicine binding pocket. In combination with a hierarchical docking and scoring procedure, the structural information of an additional subpocket in colchicine site was applied to filter out the undesired docking hits. This strategy automatically resulted in 63 candidates meeting the structural and energetic criteria from a screening library containing approximately 100,000 diverse druglike compounds. Among them, nine molecules were chosen for experimental validation, which all share the similar binding pose and contain an enriched scaffold bearing thiophene core. Encouragingly, five compounds are active in tubulin polymerization assay. The most potent inhibitor, 2-(2-fluorobenzamido)-3-carboxamide-4,5-dimethylthiophene, is structurally distinct to any known colchicine site binders and has higher ligand efficiency than colchicine. On the basis of its predicted binding pose, we systematically probed its binding characteristics by testing series of structural modifications. The obtained structure-activity relationship results are consistent with our binding model, and the inhibition activities of two analogues are improved by 2-fold. We expect that the novel structure discovered in the present study may serve as a starting point for developing tubulin inhibitors with improved efficacy and fewer side effects. We also expect that our hierarchical strategy may be generally applicable in structure-based virtual screening campaigns.

Subunit F modulates ATP binding and migration in the nucleotide-binding subunit B of the A(1)A(O) ATP synthase of Methanosarcina mazei Gö1

The interaction of the nucleotide-binding subunit B with subunit F is essential in coupling of ion pumping and ATP synthesis in A(1)A(O) ATP synthases. Here we provide structural and thermodynamic insights on the nucleotide binding to the surface of subunits B and F of Methanosarcina mazei Gö1 A(1)A(O) ATP synthase, which initiated migration to its final binding pocket via two transitional intermediates on the surface of subunit B. NMR- and fluorescence spectroscopy as well as ITC data combined with molecular dynamics simulations of the nucleotide bound subunit B and nucleotide bound B-F complex in explicit solvent, suggests that subunit F is critical for the migration to and eventual occupancy of the final binding site by the nucleotide of subunit B. Rotation of the C-terminus and conformational changes in subunit B are initiated upon binding with subunit F causing a perturbation that leads to the migration of ATP from the transition site 1 through an intermediate transition site 2 to the final binding site 3. This mechanism is elucidated on the basis of change in binding affinity for the nucleotide at the specific sites on subunit B upon complexation with subunit F. The change in enthalpy is further explained based on the fluctuating local environment around the binding sites.

Accurate prediction of the binding free energy and analysis of the mechanism of the interaction of replication protein A (RPA) with ssDNA

The eukaryotic replication protein A (RPA) has several pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Moreover, RPA seems to have a crucial role in organizing the sequential assembly of DNA processing proteins along single stranded DNA (ssDNA). The strong RPA affinity for ssDNA, K(A) between 10(-9)-10(-10) M, is characterized by a low cooperativity with minor variation for changes on the nucleotide sequence. Recently, new data on RPA interactions was reported, including the binding free energy of the complex RPA70AB with dC(8) and dC(5), which has been estimated to be -10 ± 0.4 kcal mol(-1) and -7 ± 1 kcal mol(-1), respectively. In view of these results we performed a study based on molecular dynamics aimed to reproduce the absolute binding free energy of RPA70AB with the dC(5) and dC(8) oligonucleotides. We used several tools to analyze the binding free energy, rigidity, and time evolution of the complex. The results obtained by MM-PBSA method, with the use of ligand free geometry as a reference for the receptor in the separate trajectory approach, are in excellent agreement with the experimental data, with ±4 kcal mol(-1) error. This result shows that the MM-PB(GB)SA methods can provide accurate quantitative estimates of the binding free energy for interacting complexes when appropriate geometries are used for the receptor, ligand and complex. The decomposition of the MM-GBSA energy for each residue in the receptor allowed us to correlate the change of the affinity of the mutated protein with the ΔG(gas+sol) contribution of the residue considered in the mutation. The agreement with experiment is optimal and a strong change in the binding free energy can be considered as the dominant factor in the loss for the binding affinity resulting from mutation.

MOLECULAR DYNAMICS AND FREE ENERGY ANALYSES OF ERK2–PYRAZOLYLPYRROLE INHIBITORS INTERACTIONS: INSIGHT INTO STRUCTURE-BASED LIGAND DESIGN

The extracellular signal-regulated protein kinase 2 (ERK2) is a pivotal member involving in Ras/Raf/MEK/ERK signal transduction pathway, acting as a central point where multiple signaling pathways coalesce to drive transcription. The pyrazolylpyrrole compounds as ATP competitive inhibitors of ERK2 can bind target with a special binding mode and have higher inhibitory potency than other ERK2-inhibitors. We investigated the interaction mode of ERK2-inhibitor using molecular dynamics simulation. The molecular mechanics Poisson–Boltzmann surface area approach is used to calculate the binding free energy of ERK2 with pyrazolylpyrrole inhibitors to analyze the factors of improving the affinity. The results indicated that the electrostatic interactions play the most important role in keeping the stabilization of ERK2-inhibitor. The structural analyses showed that the protein motions can be controlled by changing the structures of inhibitors; furthermore, the full use of available space in the binding site by improving the flexibilities of inhibitors and introducing hydrophobic groups can increase the inhibitory effect.

Probing the structural and energetic basis of kinesin-microtubule binding using computational alanine-scanning mutagenesis

Kinesin-microtubule (MT) binding plays a critical role in facilitating and regulating the motor function of kinesins. To obtain a detailed structural and energetic picture of kinesin-MT binding, we performed large-scale computational alanine-scanning mutagenesis based on long-time molecular dynamics (MD) simulations of the kinesin-MT complex in both ADP and ATP states. First, we built three all-atom kinesin-MT models: human conventional kinesin bound to ADP and mouse KIF1A bound to ADP and ATP. Then, we performed 30 ns MD simulations followed by kinesin-MT binding free energy calculations for both the wild type and mutants obtained after substitution of each charged residue of kinesin with alanine. We found that the kinesin-MT binding free energy is dominated by van der Waals interactions and further enhanced by electrostatic interactions. The calculated mutational changes in kinesin-MT binding free energy are in excellent agreement with results of an experimental alanine-scanning study with a root-mean-square error of ~0.32 kcal/mol [Woehlke, G., et al. (1997) Cell 90, 207-216]. We identified a set of important charged residues involved in the tuning of kinesin-MT binding, which are clustered on several secondary structural elements of kinesin (including well-studied loops L7, L8, L11, and L12, helices α4, α5, and α6, and less-explored loop L2). In particular, we found several key residues that make different contributions to kinesin-MT binding in ADP and ATP states. The mutations of these residues are predicted to fine-tune the motility of kinesin by modulating the conformational transition between the ADP state and the ATP state of kinesin.

Solvent interaction energy calculations on molecular dynamics trajectories: increasing the efficiency using systematic frame selection

End-point methods such as linear interaction energy (LIE) analysis, molecular mechanics generalized Born solvent-accessible surface (MM/GBSA), and solvent interaction energy (SIE) analysis have become popular techniques to calculate the free energy associated with protein-ligand binding. Such methods typically use molecular dynamics (MD) simulations to generate an ensemble of protein structures that encompasses the bound and unbound states. The energy evaluation method (LIE, MM/GBSA, or SIE) is subsequently used to calculate the energy of each member of the ensemble, thus providing an estimate of the average free energy difference between the bound and unbound states. The workflow requiring both MD simulation and energy calculation for each frame and each trajectory proves to be computationally expensive. In an attempt to reduce the high computational cost associated with end-point methods, we study several methods by which frames may be intelligently selected from the MD simulation including clustering and address the question of how the number of selected frames influences the accuracy of the SIE calculations.

Overview of computational methods employed in early-stage drug discovery

BACKGROUND

The understanding of biomolecular interactions ultimately depends on knowledge about the structural and dynamic details of the interacting system. Rational structure-based drug design implements computational methodology in this rationale.

DISCUSSION

Together with increasing throughput of structural biology, molecular modeling has progressively contributed to rational drug design and elucidation of nontoxic and patient-tailored interventions, helping to make drug development more cost-efficient. But in this challenging time for the pharmaceutical industry, the successful discovery of novel therapeutics should rely on integration of computational modeling with experimentation when it comes to ligand-binding energetics, system flexibility and genetic diversity/heterogeneity of the target. Moreover, it appears that many drugs--even those for which specific receptors have been identified--intercalate in biological membranes, which could also become the actual target.

CONCLUSIONS

Understanding the drug-target and drug-unwanted-target interactions at the atomic level is fundamental in the initial phases of the drug development process. Molecular dynamics simulations and complementary computational methods are already contributing in this endeavor for the soluble pharmacological targets and show an increasing importance in the understanding of membrane-ligand interactions.

Efficient incorporation of protein flexibility and dynamics into molecular docking simulations

Flexibility and dynamics are protein characteristics that are essential for the process of molecular recognition. Conformational changes in the protein that are coupled to ligand binding are described by the biophysical models of induced fit and conformational selection. Different concepts that incorporate protein flexibility into protein-ligand docking within the context of these two models are reviewed. Several computational studies that discuss the validity and possible limitations of such approaches will be presented. Finally, different approaches that incorporate protein dynamics, e.g., configurational entropy, and solvation effects into docking will be highlighted.

Allosteric transition and binding of small molecule effectors causes curvature change in central β-sheets of selected enzymes

A quantitative description of allosteric transition remains a significant science challenge. Many allosteric enzymes contain a central β-sheet in their catalytic domain. When an allosteric protein undergoes the transition between T (tense) and R (relaxed) allosteric states, this central β-sheet undergoes a conformational change. A traditional method of measuring this change, the root mean square deviation (RMSD), appears to be inadequate to describe such changes in meaningful quantitative manner. We designed a novel quantitative method to demonstrate this conformational transition by measuring the change in curvature of the central β-sheet when enzymes transition between allosteric states. The curvature was established by calculating the semiaxes of a 3-D hyperboloid fitted by least squares to the Cα atomic positions of the β-sheet. The two enzymes selected for this study, fructose 1,6-bisphosphatase (FBPase) from pig kidney and aspartate carbamoyltransferase (ATCase) from E. coli, showed while transitioning between the allosteric states (T ⇔ R) a notable change in β-sheet curvature (∼5%) that results in a large lateral shift at the sheet's edge, which is necessary to convey the signal. The results suggest that the β-sheet participates in storing elastic energy associated with the transition. Establishing a tentative link between the energetics of the β-sheet in different allosteric states provides a more objective basis for the naming convention of allosteric states (tense or relaxed), and provides insight into the hysteretic nature of the transition. The approach presented here allows for a better understanding of the internal dynamics of allosteric enzymes by defining the domains that directly participate in the transition.