Dissociation of minor groove binders from DNA: insights from metadynamics simulations

All-atom simulations to studying metallodrugs/target interactions

Metallodrugs are extensively used to treat and diagnose distinct disease types. The unique physical-chemical properties of metal ions offer tantalizing opportunities to tailor effective scaffolds for selectively targeting specific biomolecules. Modern experimental techniques have collected a large body of structural data concerning the interactions of metallodrugs with their biomolecular targets, although being unable to exhaustively assess the molecular basis of their mechanism of action. In this scenario, the complementary use of accurate computational methods allows uncovering the minutiae of metallodrugs/targets interactions and their underlying mechanism of action at an atomic-level of detail. This knowledge is increasingly perceived as an invaluable requirement to rationally devise novel and selective metallodrugs. Building on literature studies, selected largely from the last 2 years, this compendium encompasses a cross-section of the current role, advances, and challenges met by computer simulations to decipher the mechanistic intricacies of prototypical metallodrugs.

Laplacian score and genetic algorithm based automatic feature selection for Markov State Models in adaptive sampling based molecular dynamics

Adaptive sampling molecular dynamics based on Markov State Models use short parallel MD simulations to accelerate simulations, and are proven to identify hidden conformers. The accuracy of the predictions provided by it depends on the features extracted from the simulated data that is used to construct it. The identification of the most important features in the trajectories of the simulated system has a considerable effect on the results.

Methods

In this study, we use a combination of Laplacian scoring and genetic algorithms to obtain an optimized feature subset for the construction of the MSM. The approach is validated on simulations of three protein folding complexes, and two protein ligand binding complexes.

Results

Our experiments show that this approach produces better results when the number of samples is significantly lesser than the number of features extracted. We also observed that this method mitigates over fitting that occurs due to high dimensionality of large biosystems with shorter simulation times.

Ligand-Binding Calculations with Metadynamics

All-atom molecular dynamics simulations can capture the dynamic degrees of freedom that characterize molecular recognition, the knowledge of which constitutes the cornerstone of rational approaches to drug design and optimization. In particular, enhanced sampling algorithms, such as metadynamics, are powerful tools to dramatically reduce the computational cost required for a mechanistic description of the binding process. Here, we describe the essential details characterizing these simulation strategies, focusing on the critical step of identifying suitable reaction coordinates, as well as on the different analysis algorithms to estimate binding affinity and residence times. We conclude with a survey of published applications that provides explicit examples of successful simulations for several targets.

DNA Damage and Chromatin Conformation Changes Confer Nonhost Resistance: A Hypothesis Based on Effects of Anti-cancer Agents on Plant Defense Responses

Over the last decades, medical research has utilized DNA altering procedures in cancer treatments with the objective of killing cells or suppressing cell proliferation. Simultaneous research related to enhancing disease resistance in plants reported that alterations in DNA can enhance defense responses. These two opposite perspectives have in common their effects on the center for gene transcription, the nuclear chromatin. A review of selected research from both anticancer- and plant defense-related research provides examples of some specific DNA altering actions: DNA helical distortion, DNA intercalation, DNA base substitution, DNA single cleavage by DNases, DNA alkylation/methylation, and DNA binding/exclusion. The actions of the pertinent agents are compared, and their proposed modes of action are described in this study. Many of the DNA specific agents affecting resistance responses in plants, e.g., the model system using pea endocarp tissue, are indeed anticancer agents. The tumor cell death or growth suppression in cancer cells following high level treatments may be accompanied with chromatin distortions. Likewise, in plants, DNA-specific agents activate enhanced expression of many genes including defense genes, probably due to the chromatin alterations resulting from the agents. Here, we propose a hypothesis that DNA damage and chromatin structural changes are central mechanisms in initiating defense gene transcription during the nonhost resistance response in plants.

Free energy landscape of siRNA-polycation complexation: Elucidating the effect of molecular geometry, polymer flexibility, and charge neutralization

The success of medical threatments with DNA and silencing interference RNA is strongly related to the design of efficient delivery technologies. Cationic polymers represent an attractive strategy to serve as nucleic-acid carriers with the envisioned advantages of efficient complexation, low cost, ease of production, well-defined size, and low polydispersity index. However, the balance between efficacy and toxicity (safety) of these polymers is a challenge and in need of improvement. With the aim of designing more effective polycationic-based gene carriers, many parameters such as carrier morphology, size, molecular weight, surface chemistry, and flexibility/rigidity ratio need to be taken into consideration. In the present work, the binding mechanism of three cationic polymers (polyarginine, polylysine and polyethyleneimine) to a model siRNA target is computationally investigated at the atomistic level. In order to better understand the polycationic carrier-siRNA interactions, replica exchange molecular dynamic simulations were carried out to provide an exhaustive exploration of all the possible binding sites, taking fully into account the siRNA flexibility together with the presence of explicit solvent and ions. Moreover, well-tempered metadynamics simulations were employed to elucidate how molecular geometry, polycation flexibility, and charge neutralization affect the siRNA-polycations free energy landscape in term of low-energy binding modes and unbinding free energy barriers. Significant differences among polymer binding modes have been detected, revealing the advantageous binding properties of polyarginine and polylysine compared to polyethyleneimine.

Binding of anticancer drug daunomycin to a TGGGGT G-quadruplex DNA probed by all-atom molecular dynamics simulations: additional pure groove binding mode and implications on designing more selective G-quadruplex ligands

DNA G-quadruplex structures are emerging cancer-specific targets for chemotherapeutics. Ligands that bind to and stabilize DNA G-quadruplexes have the potential to be anti-cancer drugs. Lack of binding selectivity to DNA G-quadruplex over DNA duplex remains a major challenge when attempting to develop G-quadruplex ligands into successful anti-cancer drugs. Thorough understanding of the binding nature of existing non-selective ligands that bind to both DNA quadruplex and DNA duplex will help to address this challenge. Daunomycin and doxorubicin, two commonly used anticancer drugs, are examples of non-selective DNA ligands. In this study, we extended our early all-atom binding simulation studies between doxorubicin and a DNA duplex (d(CGATCG)₂) to probe the binding between daunomycin and a parallel DNA quadruplex (d(TGGGGT)₄) and DNA duplex. In addition to the end stacking mode, which mimics the mode in the crystal structure, a pure groove binding mode was observed in our free binding simulations. The dynamic and energetic properties of these two binding modes are thoroughly examined, and a detailed comparison is made between DNA quadruplex binding modes and DNA duplex binding modes. Implications on the design of more selective DNA quadruplex ligands are also discussed. Graphical abstract Top stacking and groov binding modes from the MD simulations.

Ligand binding to telomeric G-quadruplex DNA investigated by funnel-metadynamics simulations

A thorough characterization of the binding interaction between a drug and its molecular target is fundamental to successfully lead drug design. We demonstrate that this characterization is also possible using the recently developed method of funnel-metadynamics (FM), here applied to investigate the binding of berberine to DNA G-quadruplex. We computed a quantitatively well-characterized free-energy landscape that allows identifying two low-energy ligand binding modes and the presence of higher energy prebinding states. We validated the accuracy of our calculations by steady-state fluorescence experiments. The good agreement between the theoretical and experimental binding free-energy value demonstrates that FM is a most reliable method to study ligand/DNA interaction.

G-quadruplexes (G4s) are higher-order DNA structures typically present at promoter regions of genes and telomeres. Here, the G4 formation decreases the replicative DNA at each cell cycle, finally leading to apoptosis. The ability to control this mitotic clock, particularly in cancer cells, is fascinating and passes through a rational understanding of the ligand/G4 interaction. We demonstrate that an accurate description of the ligand/G4 binding mechanism is possible using an innovative free-energy method called funnel-metadynamics (FM), which we have recently developed to investigate ligand/protein interaction. Using FM simulations, we have elucidated the binding mechanism of the anticancer alkaloid berberine to the human telomeric G4 (d[AG₃(T₂AG₃)₃]), computing also the binding free-energy landscape. Two ligand binding modes have been identified as the lowest energy states. Furthermore, we have found prebinding sites, which are preparatory to reach the final binding mode. In our simulations, the ions and the water molecules have been explicitly represented and the energetic contribution of the solvent during ligand binding evaluated. Our theoretical results provide an accurate estimate of the absolute ligand/DNA binding free energy (ΔGb0 = −10.3 ± 0.5 kcal/mol) that we validated through steady-state fluorescence binding assays. The good agreement between the theoretical and experimental value demonstrates that FM is a most powerful method to investigate ligand/DNA interaction and can be a useful tool for the rational design also of G4 ligands.

Metadynamics supports molecular dynamics simulation-based binding affinities of eucalyptol and beta-cyclodextrin inclusion complexes

The development of various molecular dynamics methods enables the detailed investigation of association processes, like host–guest complexes, including their dynamics and, additionally, the release of the guest compound.

Accurate Estimation of Protein Folding and Unfolding Times: Beyond Markov State Models

Because standard molecular dynamics (MD) simulations are unable to access time scales of interest in complex biomolecular systems, it is common to "stitch together" information from multiple shorter trajectories using approximate Markov state model (MSM) analysis. However, MSMs may require significant tuning and can yield biased results. Here, by analyzing some of the longest protein MD data sets available (>100 μs per protein), we show that estimators constructed based on exact non-Markovian (NM) principles can yield significantly improved mean first-passage times (MFPTs) for protein folding and unfolding. In some cases, MSM bias of more than an order of magnitude can be corrected when identical trajectory data are reanalyzed by non-Markovian approaches. The NM analysis includes "history" information, higher order time correlations compared to MSMs, that is available in every MD trajectory. The NM strategy is insensitive to fine details of the states used and works well when a fine time-discretization (i.e., small "lag time") is used.

Structure and dynamics of proflavine association around DNA

Proflavine is a small molecule that intercalates into DNA and, thereby, acts as an anticancer agent. Intercalation of proflavine is shown to be a two-step process in which the first step is believed to be the formation of a pre-intercalative outside bound state. Experimental studies so far have been unable to capture the nature of the outside bound state. However, the sub-millisecond timescale observed in fluorescence kinetic experiments is often attributed to the binding of proflavine outside of DNA. Here, we have performed molecular dynamics simulations with multiple proflavine molecules to study the structure and dynamics of the formation of the outside bound state of DNA at different ion concentrations. We observed that the timescale of the outside bound state formation is, at least, five orders of magnitude faster (in nanoseconds) than the experimentally reported timescale (sub-milliseconds) attributed to binding outside DNA. Moreover, we also observed the stacked arrangement of proflavine all around DNA, which is different from the experimentally predicted stacking arrangement perpendicular to the helical axis of DNA in the close vicinity of the phosphate groups. This study, therefore, provides insight into the molecular structure and dynamics of the pre-intercalative outside bound state and will help in understanding the overall intercalation mechanism.

Computational metallomics of the anticancer drug cisplatin

Cisplatin, cis-diamminedichlorido-platinum(II), is an important therapeutic tool in the struggle against different tumors, yet it is plagued with the emergence of resistance mechanisms after repeated administrations. This hampers greatly its efficacy. Overcoming resistance problems requires first and foremost an integrated and systematic understanding of the structural determinants and molecular recognition processes involving the drug and its cellular targets. Here we review a strategy that we have followed for the last few years, based on the combination of modern tools from computational chemistry with experimental biophysical methods. Using hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) simulations, validated by spectroscopic experiments (including NMR, and CD), we have worked out for the first time at atomic level the structural determinants in solution of platinated cellular substrates. These include the copper homeostasis proteins Ctr1, Atox1, and ATP7A. All of these proteins have been suggested to influence the pre-target resistance mechanisms. Furthermore, coupling hybrid QM/MM simulations with classical Molecular Dynamics (MD) and free energy calculations, based on force field parameters refined by the so-called "Force Matching" procedure, we have characterized the structural modifications and the free energy landscape associated with the recognition between platinated DNA and the protein HMGB1, belonging to the chromosomal high-mobility group proteins HMGB that inhibit the repair of platinated DNA. This may alleviate issues relative to on-target resistance process. The elucidation of the mechanisms by which tumors are sensitive or refractory to cisplatin may lead to the discovery of prognostic biomarkers. The approach reviewed here could be straightforwardly extended to other metal-based drugs.

Molecular view of ligands specificity for CAG repeats in anti-Huntington therapy

Huntington's disease is a fatal and devastating neurodegenerative genetic disorder for which there is currently no cure. It is characterized by Huntingtin protein's mRNA transcripts with 36 or more CAG repeats. Inhibiting the formation of pathological complexes between these expanded transcripts and target proteins may be a valuable strategy against the disease. Yet, the rational design of molecules specifically targeting the expanded CAG repeats is limited by the lack of structural information. Here, we use well-tempered metadynamics-based free energy calculations to investigate pose and affinity of two ligands targeting CAG repeats for which affinities have been previously measured. The first consists of two 4-guanidinophenyl rings linked by an ester group. It is the most potent ligand identified so far, with Kd = 60(30) nM. The second consists of a 4-phenyl dihydroimidazole and 4-1H-indole dihydroimidazole connected by a C-C bond (Kd = 700(80) nM). Our calculations reproduce the experimental affinities and uncover the recognition pattern between ligands' and their RNA target. They also provide a molecular basis for the markedly different affinity of the two ligands for CAG repeats as observed experimentally. These findings may pave the way for a structure-based hit-to-lead optimization to further improve ligand selectivity toward CAG repeat-containing mRNAs.

Investigating drug-target association and dissociation mechanisms using metadynamics-based algorithms

CONSPECTUS: This Account highlights recent advances and discusses major challenges in the field of drug-target recognition, binding, and unbinding studied using metadynamics-based approaches, with particular emphasis on their role in structure-based design. Computational chemistry has significantly contributed to drug design and optimization in an extremely broad range of areas, including prediction of target druggability and drug likeness, de novo design, fragment screening, ligand docking, estimation of binding affinity, and modulation of ADMET (absorption, distribution, metabolism, excretion, toxicity) properties. Computationally driven drug discovery must continuously adapt to keep pace with the evolving knowledge of the factors that modulate the pharmacological action of drugs. There is thus an urgent need for novel computational approaches that integrate the vast amount of complex information currently available for small (bio)organic compounds, biologically relevant targets and their complexes, while also accounting accurately for the thermodynamics and kinetics of drug-target association, the intrinsic dynamical behavior of biomolecular systems, and the complexity of protein-protein networks. Understanding the mechanism of drug binding to and unbinding from biological targets is fundamental for optimizing lead compounds and designing novel biologically active ones. One major challenge is the accurate description of the conformational complexity prior to and upon formation of drug-target complexes. Recently, enhanced sampling methods, including metadynamics and related approaches, have been successfully applied to investigate complex mechanisms of drugs binding to flexible targets. Metadynamics is a family of enhanced sampling techniques aimed at enhancing the rare events and reconstructing the underlying free energy landscape as a function of a set of order parameters, usually referred to as collective variables. Studies of drug binding mechanisms have predicted the most probable association and dissociation pathways and the related binding free energy profile. In addition, the availability of an efficient open-source implementation, running on cost-effective GPU (i.e., graphical processor unit) architectures, has considerably decreased the learning curve and the computational costs of the methods, and increased their adoption by the community. Here, we review the recent contributions of metadynamics and other enhanced sampling methods to the field of drug-target recognition and binding. We discuss how metadynamics has been used to search for transition states, to predict binding and unbinding paths, to treat conformational flexibility, and to compute free energy profiles. We highlight the importance of such predictions in drug discovery. Major challenges in the field and possible solutions will finally be discussed.

Metadynamics simulations reveal a Na+ independent exiting path of galactose for the inward-facing conformation of vSGLT

Sodium-Galactose Transporter (SGLT) is a secondary active symporter which accumulates sugars into cells by using the electrochemical gradient of Na⁺ across the membrane. Previous computational studies provided insights into the release process of the two ligands (galactose and sodium ion) into the cytoplasm from the inward-facing conformation of Vibrio parahaemolyticus sodium/galactose transporter (vSGLT). Several aspects of the transport mechanism of this symporter remain to be clarified: (i) a detailed kinetic and thermodynamic characterization of the exit path of the two ligands is still lacking; (ii) contradictory conclusions have been drawn concerning the gating role of Y263; (iii) the role of Na⁺ in modulating the release path of galactose is not clear. In this work, we use bias-exchange metadynamics simulations to characterize the free energy profile of the galactose and Na⁺ release processes toward the intracellular side. Surprisingly, we find that the exit of Na⁺ and galactose is non-concerted as the cooperativity between the two ligands is associated to a transition that is not rate limiting. The dissociation barriers are of the order of 11–12 kcal/mol for both the ion and the substrate, in line with kinetic information concerning this type of transporters. On the basis of these results we propose a branched six-state alternating access mechanism, which may be shared also by other members of the LeuT-fold transporters.

Membrane proteins are crucial for the communication of the cell with the environment. Among these, symporters are in charge of the transport of molecules (like sugars, amino acids, osmolytes) inside the cells, exploiting the concentration gradient of an ion to perform the task. Here we investigate by atomistic simulations the transport mechanism of the Sodium-Galactose symporter. Our results allow constructing a detailed and quantitative model of the release process of the two ligands. Surprisingly, we find that the galactose is released to the cytosol independently from the ion, unambiguously indicating that the coupling in their transport mechanism is associated to the steps preceding the release process. A large family of symporters shares the same fold and potentially the same transport mechanism. As such our results are important also because they can provide insights on common mechanistic features of these transporters.

DNA recognition process of the lactose repressor protein studied via metadynamics and umbrella sampling simulations

The lactose repressor, LacI, finds its DNA target sites via a process that is faster than what it is expected from a diffusion-driven mechanism. This is possible thanks to nonspecific binding of LacI to DNA, followed by diffusion along the DNA molecule. The diffusion of the protein along DNA might lead to a fast-searching mechanism only if LacI binds with comparable strength to different nonspecific sequences and if, in addition, the value of the binding energy remarkably decreases in the presence of a binding site. The first condition would be favored by loose interactions with the base edges, while the second would take advantage from the opposite situation. In order to understand how the protein satisfies these two opposing requirements, the DNA recognition process was studied by a combination of umbrella sampling and metadynamics simulations. The simulations revealed that when aligned with a specific sequence, LacI establishes polar interactions with the base edges that require ∼4 kcal/mol to be disrupted. In contrast, these interactions are not stable when the protein is aligned with nonspecific sequences. These results confirm that LacI is able to efficiently recognize a specific sequence while sliding along DNA before any structural change of the protein-DNA complex occurs.

Mechanical Model of DNA Allostery

The importance of allosteric effects in DNA is becoming increasingly appreciated, but the underlying mechanisms remain poorly understood. In this work, we propose a general modeling framework to study DNA allostery. We describe DNA in a coarse-grained manner by intra-base pair and base pair step coordinates, complemented by groove widths. Quadratic deformation energy is assumed, yielding linear relations between the constraints and their effect. Model parameters are inferred from standard unrestrained, explicit-solvent molecular dynamics simulations of naked DNA. We applied the approach to study minor groove binding of diamidines and pyrrole-imidazole polyamides. The predicted DNA bending is in quantitative agreement with experiment and suggests that diamidine binding to the alternating TA sequence brings the DNA closer to the A-tract conformation, with potentially important functional consequences. The approach can be readily applied to other allosteric effects in DNA and generalized to model allostery in various molecular systems.

Intermediate states in the binding process of folic acid to folate receptor α: insights by molecular dynamics and metadynamics

Folate receptor α (FRα) is a cell surface, glycophosphatidylinositol-anchored protein which has focussed attention as a therapeutic target and as a marker for the diagnosis of cancer. It has a high affinity for the dietary supplemented folic acid (FOL), carrying out endocytic transport across the cell membrane and delivering the folate at the acidic pH of the endosome. Starting from the recently reported X-ray structure at pH 7, 100 ns classical molecular dynamics simulations have been carried out on the FRα-FOL complex; moreover, the ligand dissociation process has been studied by metadynamics, a recently reported method for the analysis of free-energy surfaces (FES), providing clues on the intermediate states and their energy terms. Multiple dissociation runs were considered to enhance the configurational sampling; a final clustering of conformations within the averaged FES provides the representative structures of several intermediate states, within an overall barrier for ligand escape of about 75 kJ/mol. Escaping of FOL to solvent occurs while only minor changes affect the FRα conformation of the binding pocket. During dissociation, the FOL molecule translates and rotates around a turning point located in proximity of the receptor surface. FOL at this transition state assumes an "L" shaped conformation, with the pteridin ring oriented to optimize stacking within W102 and W140 residues, and the negatively charged glutamate tail, outside the receptor, interacting with the positively charged R103 and R106 residues, that contrary to the bound state, are solvent exposed. We show that metadynamics method can provide useful insights at the atomistic level on the effects of point-mutations affecting functionality, thus being a very promising tool for any study related to folate-targeted drug delivery or cancer therapies involving folate uptake.

Molecular Recognition of Platinated DNA from Chromosomal HMGB1

Cisplatin cures testicular and ovarian cancers with unprecedented potency. It induces its beneficial activity by covalently binding to DNA. Repair enzymes, which remove the platinated lesions from DNA, cause drug resistance. Chromosomal High Mobility Group Box proteins (HMGB) may interfere with this process by binding to platinated DNA. Using 8 μs multiple-walker well-tempered metadynamics simulations, here, we investigated the structural and the energetic determinants of one of the HMGB proteins (HMGB1A) in complex with the platinated oligonucleotide [Pt(NH3)2](2+)-d(CCUCTCTG*G*ACCTTCC)-d(GGAGAGACCTGGAAGG) (*G are platinated guanines), for which experimental structural information is available. The calculated affinity is in good agreement with experiment. The process is predicted to be enthalpy-driven, as found for other protein/DNA complexes. The Lys7 residue, whose side-chain was not resolved in the X-ray structure, is found to interact with the C4 5'-phosphate and this interaction emerges as a key facet for the molecular recognition process. In addition, our calculations provide a molecular basis for the experimentally measured decreased affinity of HMGB1A for platinated DNA, as a consequence of Cys22-Cys44 S-S bridge formation (such an oxidation cannot take place in some members of this protein family present in the testis, where the drug is particularly effective). This decrease is likely to be caused by a small yet significant rearrangement of helices H1 and H2 with consequent alteration of the Phe37 juxtaposition.

Molecular recognition of DNA by ligands: roughness and complexity of the free energy profile

Understanding the molecular mechanism by which probes and chemotherapeutic agents bind to nucleic acids is a fundamental issue in modern drug design. From a computational perspective, valuable insights are gained by the estimation of free energy landscapes as a function of some collective variables (CVs), which are associated with the molecular recognition event. Unfortunately the choice of CVs is highly non-trivial because of DNA's high flexibility and the presence of multiple association-dissociation events at different locations and/or sliding within the grooves. Here we have applied a modified version of Locally-Scaled Diffusion Map (LSDMap), a nonlinear dimensionality reduction technique for decoupling multiple-timescale dynamics in macromolecular systems, to a metadynamics-based free energy landscape calculated using a set of intuitive CVs. We investigated the binding of the organic drug anthramycin to a DNA 14-mer duplex. By performing an extensive set of metadynamics simulations, we observed sliding of anthramycin along the full-length DNA minor groove, as well as several detachments from multiple sites, including the one identified by X-ray crystallography. As in the case of equilibrium processes, the LSDMap analysis is able to extract the most relevant collective motions, which are associated with the slow processes within the system, i.e., ligand diffusion along the minor groove and dissociation from it. Thus, LSDMap in combination with metadynamics (and possibly every equivalent method) emerges as a powerful method to describe the energetics of ligand binding to DNA without resorting to intuitive ad hoc reaction coordinates.

Mechanistic insight into ligand binding to G-quadruplex DNA

Specific guanine-rich regions in human genome can form higher-order DNA structures called G-quadruplexes, which regulate many relevant biological processes. For instance, the formation of G-quadruplex at telomeres can alter cellular functions, inducing apoptosis. Thus, developing small molecules that are able to bind and stabilize the telomeric G-quadruplexes represents an attractive strategy for antitumor therapy. An example is 3-(benzo[d]thiazol-2-yl)-7-hydroxy-8-((4-(2-hydroxyethyl)piperazin-1-yl)methyl)-2H-chromen-2-one (compound 1: ), recently identified as potent ligand of the G-quadruplex [d(TGGGGT)]4 with promising in vitro antitumor activity. The experimental observations are suggestive of a complex binding mechanism that, despite efforts, has defied full characterization. Here, we provide through metadynamics simulations a comprehensive understanding of the binding mechanism of 1: to the G-quadruplex [d(TGGGGT)]4. In our calculations, the ligand explores all the available binding sites on the DNA structure and the free-energy landscape of the whole binding process is computed. We have thus disclosed a peculiar hopping binding mechanism whereas 1: is able to bind both to the groove and to the 3' end of the G-quadruplex. Our results fully explain the available experimental data, rendering our approach of great value for further ligand/DNA studies.

Simultaneous Computation of Dynamical and Equilibrium Information Using a Weighted Ensemble of Trajectories

Equilibrium formally can be represented as an ensemble of uncoupled systems undergoing unbiased dynamics in which detailed balance is maintained. Many nonequilibrium processes can be described by suitable subsets of the equilibrium ensemble. Here, we employ the “weighted ensemble” (WE) simulation protocol [Huber and Kim, Biophys. J.1996, 70, 97–110] to generate equilibrium trajectory ensembles and extract nonequilibrium subsets for computing kinetic quantities. States do not need to be chosen in advance. The procedure formally allows estimation of kinetic rates between arbitrary states chosen after the simulation, along with their equilibrium populations. We also describe a related history-dependent matrix procedure for estimating equilibrium and nonequilibrium observables when phase space has been divided into arbitrary non-Markovian regions, whether in WE or ordinary simulation. In this proof-of-principle study, these methods are successfully applied and validated on two molecular systems: explicitly solvated methane association and the implicitly solvated Ala4 peptide. We comment on challenges remaining in WE calculations.

Some ligands enhance the efflux of other ligands by the Escherichia coli multidrug pump AcrB

By measuring quantitatively the active efflux of cephalosporins by the RND (resistance-nodulation-division) family efflux pump AcrB in intact cells of Escherichia coli, we found that the simultaneous presence of another substrate, such as chloramphenicol, benzene, cyclohexane, or Arg β-naphthilamide, significantly enhanced the extrusion of cephalosporins. The stimulation occurred also in a strain expressing the covalently linked trimer of AcrB, and thus cannot be ascribed to the enhanced assembly of the trimer from AcrB monomers. When Val139 of AcrB was changed into Phe, the stimulation by benzene was found to occur at much lower concentration of the solvent. A plausible explanation of these observations is that the AcrB pump is constructed to pump out very rapidly the solvent or chloramphenicol molecules, and thus the efflux of cephalosporins, which presumably bind to a different subsite within the large binding pocket of AcrB, can become facilitated. Computer simulations of ligand binding to AcrB, both by docking and by molecular dynamics simulations, produced results supporting and extending this hypothesis. Benzene and the cephalosporin nitrocefin can bind simultaneously to the distal binding pocket of AcrB, both in the wild type and in the V139F variant. Interestingly, while the binding position and strength of benzene are almost unaffected by the presence of nitrocefin, this latter substrate is significantly displaced toward the exit gate in both wild type and mutant transporter in the presence of benzene. Additionally, the cephalosporin efflux may be enhanced by the binding of solvents (sometimes to the cephalosporin-free protomer), which could accelerate AcrB conformational changes necessary for substrate extrusion.

Role of the protein in the DNA sequence specificity of the cleavage site stabilized by the camptothecin topoisomerase IB inhibitor: a metadynamics study

Camptothecin (CPT) is a topoisomerase IB (TopIB) selective inhibitor whose derivatives are currently used in cancer therapy. TopIB cleaves DNA at any sequence, but in the presence of CPT the only stabilized protein–DNA covalent complex is the one having a thymine in position −1 with respect to the cleavage site. A metadynamics simulation of two TopIB–DNA–CPT ternary complexes differing for the presence of a thymine or a cytosine in position −1 indicates the occurrence of two different drug’s unbinding pathways. The free-energy difference between the bound state and the transition state is large when a thymine is present in position −1 and is strongly reduced in presence of a cytosine, in line with the different drug stabilization properties of the two systems. Such a difference is strictly related to the changes in the hydrogen bond network between the protein, the DNA and the drug in the two systems, indicating a direct role of the protein in determining the specificity of the cleavage site sequence stabilized by the CPT. Calculations carried out in presence of one compound of the indenoisoquinoline family (NSC314622) indicate a comparable energy difference between the bound and the transition state independently of the presence of a thymine or a cytosine in position −1, in line with the experimental results.

Molecular docking methodologies

Molecular docking represents an important technology for structure-based drug design. Docking is a computational technique aimed at the prediction of the most favorable ligand-target spatial configuration and an estimate of the corresponding complex free energy, although as stated at the beginning accurate scoring methods remain still elusive. In this chapter, the state of art of molecular docking methodologies and their applications in drug discovery is summarized.

Exploring binding properties of agonists interacting with a δ-opioid receptor

Ligand-receptor interactions are at the basis of the mediation of our physiological responses to a large variety of ligands, such as hormones, neurotransmitters and environmental stimulants, and their tuning represents the goal of a large variety of therapies. Several molecular details of these interactions are still largely unknown. In an effort to shed some light on this important issue, we performed a computational study on the interaction of two related compounds differing by a single methyl group (clozapine and desmethylclozapine) with a -opioid receptor. According to experiments, desmethylclozapine is more active than clozapine, providing a system well suited for a comparative study. We investigated stable configurations of the two drugs inside the receptor by simulating their escape routes by molecular dynamics simulations. Our results point out that the action of the compounds might be related to the spatial and temporal distribution of the affinity sites they visit during their permanency. Moreover, no particularly pronounced structural perturbations of the receptor were detected during the simulations, reinforcing the idea of a strong dynamical character of the interaction process, with an important role played by the solvent in addition.

Molecular mechanism of direct proflavine-DNA intercalation: evidence for drug-induced minimum base-stacking penalty pathway

DNA intercalation, a biophysical process of enormous clinical significance, has surprisingly eluded molecular understanding for several decades. With appropriate configurational restraint (to prevent dissociation) in all-atom metadynamics simulations, we capture the free energy surface of direct intercalation from minor groove-bound state for the first time using an anticancer agent proflavine. Mechanism along the minimum free energy path reveals that intercalation happens through a minimum base stacking penalty pathway where nonstacking parameters (Twist→Slide/Shift) change first, followed by base stacking parameters (Buckle/Roll→Rise). This mechanism defies the natural fluctuation hypothesis and provides molecular evidence for the drug-induced cavity formation hypothesis. The thermodynamic origin of the barrier is found to be a combination of entropy and desolvation energy.

A novel dendrimeric peptide with antimicrobial properties: structure-function analysis of SB056

The novel antimicrobial peptide with a dimeric dendrimer scaffold, SB056, was empirically optimized by high-throughput screening. This procedure produced an intriguing primary sequence whose structure-function analysis is described here. The alternating pattern of hydrophilic and hydrophobic amino acids suggests the possibility that SB056 is a membrane-active peptide that forms amphiphilic β-strands in a lipid environment. Circular dichroism confirmed that the cationic SB056 folds as β-sheets in the presence of anionic vesicles. Lipid monolayer surface pressure experiments revealed unusual kinetics of monolayer penetration, which suggest lipid-induced aggregation as a membranolytic mechanism. NMR analyses of the linear monomer and the dendrimeric SB056 in water and in 30% trifluoroethanol, on the other hand, yielded essentially unstructured conformations, supporting the excellent solubility and storage properties of this compound. However, simulated annealing showed that many residues lie in the β-region of the Ramachandran plot, and molecular-dynamics simulations confirmed the propensity of this peptide to fold as a β-type conformation. The excellent solubility in water and the lipid-induced oligomerization characteristics of this peptide thus shed light on its mechanism of antimicrobial action, which may also be relevant for systems that can form toxic β-amyloid fibrils when in contact with cellular membranes. Functionally, SB056 showed high activity against Gram-negative bacteria and some limited activity against Gram-positive bacteria. Its potency against Gram-negative strains was comparable (on a molar basis) to that of colistin and polymyxin B, with an even broader spectrum of activity than numerous other reference compounds.

Frontiers in molecular dynamics simulations of DNA

It has been known for decades that DNA is extremely flexible and polymorphic, but our knowledge of its accessible conformational space remains limited. Structural data, primarily from X-ray diffraction studies, is sparse in comparison to the manifold configurations possible, and direct experimental examinations of DNA's flexibility still suffer from many limitations. In the face of these shortcomings, molecular dynamics (MD) is now an essential tool in the study of DNA. It affords detailed structural and dynamical insights, which explains its recent transition from a small number of highly specialized laboratories to a large variety of groups dealing with challenging biological problems. MD is now making an irreversible journey to the mainstream of research in biology, with the attendant opportunities and challenges. But given the speed with which MD studies of DNA have spread, the roots remain somewhat shallow: in many cases, there is a lack of deep knowledge about the foundations, strengths, and limits of the technique. In this Account, we discuss how MD has become the most important source of structural and flexibility data on DNA, focusing on advances since 2007 of atomistic MD in the description of DNA under near-physiological conditions and highlighting the possibilities and shortcomings of the technique. The evolution in the field over the past four years is a prelude to the ongoing revolution. The technique has gained in robustness and predictive power, which when coupled with the spectacular improvements in software and hardware has enabled the tackling of systems of increasing complexity. Simulation times of microseconds have now been achieved, with even longer times when specialized hardware is used. As a result, we have seen the first real-time simulation of large conformational transitions, including folding and unfolding of short DNA duplexes. Noteworthy advances have also been made in the study of DNA-ligand interactions, and we predict that a global thermodynamic and kinetic picture of the binding landscape of DNA will become available in a few years. MD will become a crucial tool in areas such as biomolecular engineering and synthetic biology. MD has also been shown to be an excellent source of parameters for mesoscopic models of DNA flexibility. Such models can be refined through atomistic MD simulations on small duplexes and then applied to the study of entire chromosomes. Recent evidence suggests that MD-derived elastic models can successfully predict the position of regulatory regions in DNA and can help advance our understanding of nucleosome positioning and chromatin plasticity. If these results are confirmed, MD simulations can become the ultimate tool to decipher a physical code that can contribute to gene regulation. We are entering the golden age of MD simulations of DNA. Undoubtedly, the expectations are high, but the challenges are also enormous. These include the need for more accurate potential energy functionals and for longer and more complex simulations in more realistic systems. The joint research effort of several groups will be crucial for adapting the technique to the requirements of the coming decade.

Molecular motions in drug design: the coming age of the metadynamics method

Metadynamics is emerging as a useful free energy method in physics, chemistry and biology. Recently, it has been applied also to investigate ligand binding to biomolecules of pharmacological interest. Here, after introducing the basic idea of the method, we review applications to challenging targets for pharmaceutical intervention. We show that this methodology, especially when combined with a variety of other computational approaches such as molecular docking and/or molecular dynamics simulation, may be useful to predict structure and energetics of ligand/target complexes even when the targets lack a deep binding cavity, such as DNA and proteins undergoing fibrillation in neurodegenerative diseases. Furthermore, the method allows investigating the routes of molecular recognition and the associated binding energy profiles, providing a molecular interpretation to experimental data.

Breathing motions of a respiratory protein revealed by molecular dynamics simulations

Internal cavities, which are central to the biological functions of myoglobin, are exploited by gaseous ligands (e.g., O(2), NO, CO, etc.) to migrate inside the protein matrix. At present, it is not clear whether the ligand makes its own way inside the protein or instead the internal cavities are an intrinsic feature of myoglobin. To address this issue, standard molecular dynamics simulations were performed on horse-heart met-myoglobin with no ligand migrating inside the protein matrix. To reveal intrinsic internal pathways, the use of a statistical approach was applied to the cavity calculation, with special emphasis on the major pathway from the distal pocket to Xe1. Our study points out the remarkable dynamical behavior of Xe4, whose "breathing motions" may facilitate migration of ligands through the distal region. Additionally, our results highlight a two-way path for a ligand to diffuse through the proximal region, possibly allowing an alternative route in case Xe1 is occupied. Finally, our approach has led us to the identification of key residues, such as leucines, that may work as switches between cavities.

Substrate binding mechanism of HIV-1 protease from explicit-solvent atomistic simulations

The binding mechanism of a peptide substrate (Thr-Ile-Met-Met-Gln-Arg, cleavage site p2-NC of the viral polyprotein) to wild-type HIV-1 protease has been investigated by 1.6 micros biased all-atom molecular dynamics simulations in explicit water. The configuration space has been explored biasing seven reaction coordinates by the bias-exchange metadynamics technique. The structure of the Michaelis complex is obtained starting from the substrate outside the enzyme within a backbone rmsd of 0.9 A. The calculated free energy of binding is -6 kcal/mol, and the kinetic constants for association and dissociation are 1.3 x 10(6) M(-1) s(-1) and 57 s(-1), respectively, consistent with experiments. In the main binding pathway, the flaps of the protease do not open sizably. The substrate slides inside the enzyme cavity from the tight lateral channel. This may contrast with the natural polyprotein substrate which is expected to bind by opening the flaps. Thus, mutations might influence differently the binding kinetics of peptidomimetic ligands and of the natural substrate.

Docking Ligands on Protein Surfaces: The Case Study of Prion Protein

Molecular docking of ligands targeting proteins undergoing fibrillization in neurodegenerative diseases is difficult because of the lack of deep binding sites. Here we extend standard docking methods with free energy simulations in explicit solvent to address this issue in the context of the prion protein surface. We focus on a specific ligand (2-pyrrolidin-1-yl-N-[4-[4-(2-pyrrolidin-1-yl-acetylamino)-benzyl]-phenyl]-acetamide), which binds to the structured part of the protein as shown by NMR (Kuwata, K. et al. Proc Natl Acad Sci U.S.A. 2007, 104, 11921-11926). The calculated free energy of dissociation (7.8 ± 0.9 kcal/mol) is in good agreement with the value derived by the experimental dissociation constant (Kd = 3.9 μM, corresponding to ΔG(0) = -7.5 kcal/mol). Several binding poses are predicted, including the one reported previously. Our prediction is fully consistent with the presence of multiple binding sites, emerging from NMR measurements. Our molecular simulation-based approach emerges, therefore, as a useful tool to predict poses and affinities of ligand binding to protein surfaces.