Structure and thermodynamics of RNA-protein binding: using molecular dynamics and free energy analyses to calculate the free energies of binding and conformational change

Exploring the material basis and molecular targets of Changma Xifeng tablet in treating Tourette syndrome: an integrative approach of network pharmacology and miRNA analysis

This study was to investigate the mechanism of Changma Xifeng tablet, a traditional Chinese medicine in the treatment of Tourette syndrome. Network pharmacology was utilized to pinpoint blood-entering constituents of Changma Xifeng and explore their potential targets. Additionally, differential microRNA expression analysis was conducted to predict Tourette syndrome-associated targets, complemented by molecular docking and dynamics simulations to support the interactions of the active compounds with these targets. The study identified 98 common targets between Changma Xifeng and Tourette syndrome, which may be involved in the treatment process. A protein-protein interaction network and a drug-active ingredient-disease target network highlighted the formulation's multi-component, multi-target therapeutic approach. Eight pivotal targets-AR, GRM5, MET, RORA, HTR2A, CNR1, PDE4B, and TOP1-were identified at the intersection of microRNA and drug targets. Molecular docking revealed 12 complexes with favorable binding energies below - 7 kcal/mol, specifically: AR with Alfacalcidol, TOP1 with Albiflorin, GRM5 with Arachidic Acid, GRM5 with Palmitic Acid, AR with Arachidic Acid, AR with 2-Hydroxyoctadecanoic Acid, RORA with Pinellic Acid, RORA with Palmitic Acid, AR with Acoronene, AR with Epiacoronene, AR with 4,4'-Methylenediphenol, and HTR2A with Calycosin. Our molecular docking and molecular dynamics simulations suggest potential stable interactions between the formulation's active components and target proteins. These computational methods provide a preliminary theoretical framework that will guide our future experimental work. The study provides a scientific rationale for the use of traditional Chinese medicine in Tourette syndrome management and offers new insights for drug development.

Apoptotic Potential of Iloneoside from Gongronema latifolium Benth against Prostate Cancer Cells Using In Vitro and In Silico Approach

Prostate cancer is a major cause of cancer-related mortality in men worldwide. The anti-proliferative activity of Gongronema latifolium leaf extracts on some cancer cells has been reported. Herein, we investigated the growth inhibitory effect of the Gongronema latilolium leaf methanol extract and isolated pregnane (iloneoside) against prostate cancer cell lines using the MTT cell proliferation assay, apoptosis quantification, cell cycle analysis using flow cytometry and computational analysis molecular docking, molecular dynamics simulation (MDs), binding free energy computation and cluster analysis. In addition, UPLC-ESI-TOFMS chemical fingerprinting of previously isolated compounds was performed. The extract inhibited the growth of the cell lines with an IC50 of 49.3 µg/ml and 28.4 µg/ml for 24 h and 48 h, respectively, for PC3; and 43.7 µg/ml and 22.3 µg/ml for 24 h and 48 h, respectively, for DU145. Iloneoside demonstrated low inhibitory activities against PC3 and DU145 (IC50 > 80 μM). Apoptotic quantification and cell cycle analysis further showed that iloneoside induced apoptosis in a few cells at a dose of 200 uM. The ensemble-based molecular docking of the iloneoside to BCL-XL and BCL-2 proteins, and docking to MCL-1, BCL-A1 and BFL-1 proteins, respectively, presented binding energies of -7.22 ± 0.5, -8.12 ± 0.55, -7.1, -7.2 and -6.3 kcal/mol, while the MM/PBSA binding free energy was -25.72 ± 7.22 and -27.76 ± 11.32 kcal/mol for BCL-XL and BCL-2 proteins. Furthermore, iloneoside was stable during the 100 ns MDs analysis, while the clustering of the MDs trajectories showed that the interactions were strongly preserved. Iloneoside, in part, or in synergy with other constituents, may be responsible for the antiproliferative activities of the leaf, subject to further investigation.

Dynamics of Protein-RNA Interfaces Using All-Atom Molecular Dynamics Simulations

Facing the current challenges posed by human health diseases requires the understanding of cell machinery at a molecular level. The interplay between proteins and RNA is key for any physiological phenomenon, as well protein-RNA interactions. To understand these interactions, many experimental techniques have been developed, spanning a very wide range of spatial and temporal resolutions. In particular, the knowledge of tridimensional structures of protein-RNA complexes provides structural, mechanical, and dynamical pieces of information essential to understand their functions. To get insights into the dynamics of protein-RNA complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on nine different protein-RNA complexes with different functions and interface size by taking into account the bound and unbound forms. First, we characterized structural changes upon binding and, for the RNA part, the change in the puckering. Second, we extensively analyzed the interfaces, their dynamics and structural properties, and the structural waters involved in the binding, as well as the contacts mediated by them. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

General Theory of Specific Binding: Insights from a Genetic-Mechano-Chemical Protein Model

Proteins need to selectively interact with specific targets among a multitude of similar molecules in the cell. However, despite a firm physical understanding of binding interactions, we lack a general theory of how proteins evolve high specificity. Here, we present such a model that combines chemistry, mechanics, and genetics and explains how their interplay governs the evolution of specific protein-ligand interactions. The model shows that there are many routes to achieving molecular discrimination-by varying degrees of flexibility and shape/chemistry complementarity-but the key ingredient is precision. Harder discrimination tasks require more collective and precise coaction of structure, forces, and movements. Proteins can achieve this through correlated mutations extending far from a binding site, which fine-tune the localized interaction with the ligand. Thus, the solution of more complicated tasks is enabled by increasing the protein size, and proteins become more evolvable and robust when they are larger than the bare minimum required for discrimination. The model makes testable, specific predictions about the role of flexibility and shape mismatch in discrimination, and how evolution can independently tune affinity and specificity. Thus, the proposed theory of specific binding addresses the natural question of "why are proteins so big?". A possible answer is that molecular discrimination is often a hard task best performed by adding more layers to the protein.

'RNA modulation of transport properties and stability in phase-separated condensates

One of the key mechanisms employed by cells to control their spatiotemporal organization is the formation and dissolution of phase-separated condensates. The balance between condensate assembly and disassembly can be critically regulated by the presence of RNA. In this work, we use a chemically-accurate sequence-dependent coarse-grained model for proteins and RNA to unravel the impact of RNA in modulating the transport properties and stability of biomolecular condensates. We explore the phase behavior of several RNA-binding proteins such as FUS, hnRNPA1, and TDP-43 proteins along with that of their corresponding prion-like domains and RNA recognition motifs from absence to moderately high RNA concentration. By characterizing the phase diagram, key molecular interactions, surface tension, and transport properties of the condensates, we report a dual RNA-induced behavior: on the one hand, RNA enhances phase separation at low concentration as long as the RNA radius of gyration is comparable to that of the proteins, whereas at high concentration, it inhibits the ability of proteins to self-assemble independently of its length. On the other hand, along with the stability modulation, the viscosity of the condensates can be considerably reduced at high RNA concentration as long as the length of the RNA chains is shorter than that of the proteins. Conversely, long RNA strands increase viscosity even at high concentration, but barely modify protein self-diffusion which mainly depends on RNA concentration and on the effect RNA has on droplet density. On the whole, our work rationalizes the different routes by which RNA can regulate phase separation and condensate dynamics, as well as the subsequent aberrant rigidification implicated in the emergence of various neuropathologies and age-related diseases.

'RNA modulation of transport properties and stability in phase-separated condensates

One of the key mechanisms employed by cells to control their spatiotemporal organization is the formation and dissolution of phase-separated condensates. The balance between condensate assembly and disassembly can be critically regulated by the presence of RNA. In this work, we use a chemically-accurate sequence-dependent coarse-grained model for proteins and RNA to unravel the impact of RNA in modulating the transport properties and stability of biomolecular condensates. We explore the phase behavior of several RNA-binding proteins such as FUS, hnRNPA1, and TDP-43 proteins along with that of their corresponding prion-like domains and RNA recognition motifs from absence to moderately high RNA concentration. By characterizing the phase diagram, key molecular interactions, surface tension, and transport properties of the condensates, we report a dual RNA-induced behavior: on the one hand, RNA enhances phase separation at low concentration as long as the RNA radius of gyration is comparable to that of the proteins, whereas at high concentration, it inhibits the ability of proteins to self-assemble independently of its length. On the other hand, along with the stability modulation, the viscosity of the condensates can be considerably reduced at high RNA concentration as long as the length of the RNA chains is shorter than that of the proteins. Conversely, long RNA strands increase viscosity even at high concentration, but barely modify protein self-diffusion which mainly depends on RNA concentration and on the effect RNA has on droplet density. On the whole, our work rationalizes the different routes by which RNA can regulate phase separation and condensate dynamics, as well as the subsequent aberrant rigidification implicated in the emergence of various neuropathologies and age-related diseases.

Role of salt-bridging interactions in recognition of viral RNA by arginine-rich peptides

Interactions between RNA molecules and proteins are critical to many cellular processes and are implicated in various diseases. The RNA-peptide complexes are good model systems to probe the recognition mechanism of RNA by proteins. In this work, we report studies on the binding-unbinding process of a helical peptide from a viral RNA element using nonequilibrium molecular dynamics simulations. We explored the existence of various dissociation pathways with distinct free-energy profiles that reveal metastable states and distinct barriers to peptide dissociation. We also report the free-energy differences for each of the four pathways to be 96.47 ± 12.63, 96.1 ± 10.95, 91.83 ± 9.81, and 92 ± 11.32 kcal/mol. Based on the free-energy analysis, we further propose the preferred pathway and the mechanism of peptide dissociation. The preferred pathway is characterized by the formation of sequential hydrogen-bonding and salt-bridging interactions between several key arginine amino acids and the viral RNA nucleotides. Specifically, we identified one arginine amino acid (R8) of the peptide to play a significant role in the recognition mechanism of the peptide by the viral RNA molecule.

Salt dependent phase behavior of intrinsically disordered proteins from a coarse-grained model with explicit water and ions

Multivalent proteins and nucleic acids can self-assemble into biomolecular condensates that contribute to compartmentalize the cell interior. Computer simulations offer a unique view to elucidate the mechanisms and key intermolecular interactions behind the dynamic formation and dissolution of these condensates. In this work, we present a novel approach to include explicit water and salt in sequence-dependent coarse-grained (CG) models for proteins and RNA, enabling the study of biomolecular condensate formation in a salt-dependent manner. Our framework combines a reparameterized version of the HPS protein force field with the monoatomic mW water model and the mW-ion potential for NaCl. We show how our CG model qualitatively captures the experimental radius of the gyration trend of a subset of intrinsically disordered proteins and reproduces the experimental protein concentration and water percentage of the human fused in sarcoma (FUS) low-complexity-domain droplets at physiological salt concentration. Moreover, we perform seeding simulations as a function of salt concentration for two antagonist systems: the engineered peptide PR₂₅ and poly-uridine/poly-arginine mixtures, finding good agreement with their reported in vitro phase behavior with salt concentration in both cases. Taken together, our work represents a step forward towards extending sequence-dependent CG models to include water and salt, and to consider their key role in biomolecular condensate self-assembly.

Molecular determinants of Ebola nucleocapsid stability from molecular dynamics simulations

Ebola virus (EBOV) is a human pathogen with the ability to cause hemorrhagic fever and bleeding diathesis in hosts. The life cycle of EBOV depends on its nucleocapsid. The Ebola nucleocapsid consists of a helical assembly of nucleoproteins (NPs) encapsidating single-stranded viral RNA (ssRNA). Knowledge of the molecular determinants of Ebola nucleocapsid stability is essential for the development of therapeutics against EBOV. However, large degrees of freedom associated with the Ebola nucleocapsid helical assembly pose a computational challenge, thereby limiting the previous simulation studies to the level of monomers. In the present work, we have performed all atom molecular dynamics (MD) simulations of the helical assembly of EBOV nucleoproteins in the absence and presence of ssRNA. We found that ssRNA is essential for maintaining structural integrity of the nucleocapsid. Other molecular determinants observed to stabilize the nucleocapsid include NP-RNA and NP-NP interactions and ion distributions. Additionally, the structural and dynamical behavior of the nucleocapsid monomer depends on its position in the helical assembly. NP monomers present on the longitudinal edges of the helical tube are more exposed, flexible, and have weaker NP-NP interactions than those residing in the center. This work provides key structural features stabilizing the nucleocapsid that may serve as therapeutic targets.

Battle for supremacy: nucleic acid interactions between viruses and cells

Since the COVID-19 pandemic swept across the globe, researchers have been trying to understand its origin, life cycle, and pathogenesis. There is a striking variability in the phenotypic response to infection with SARS-CoV-2 that may reflect differences in host genetics and/or immune response. It is known that the human epigenome is influenced by ethnicity, age, lifestyle, and environmental factors, including previous viral infections. This Review examines the influence of viruses on the host epigenome. We describe general lessons and methodologies that can be used to understand how the virus evades the host immune response. We consider how variation in the epigenome may contribute to heterogeneity in the response to SARS-CoV-2 and may identify a precision medicine approach to treatment.

Computational elucidation and validation of the three-dimensional structure of humanized aldolase catalytic antibody 38C2

Catalytic antibodies are immunoglobulin proteins that are capable of catalyzing multiple reactions with diverse substrates. Aldolase catalytic antibody 38C2 catalyzes aldol and retro-aldol reactions via an enamine mechanism. Therefore, 38C2 has a high potential to be used in prodrug activation, and it is currently developed for selective chemotherapy. For medical applications, its humanization is essential, and therefore, the understanding of the three-dimensional (3D) spatial atomistic structure of 38C2 is mandatory. In this study, it was attempted to construct the 3D atomic structure of humanized abzyme 38C2 using computational methods. A homology modeled structure was simulated for 100 ns with classical molecular dynamics simulations for its dynamics stability. The accuracy of the constructed model was further evaluated with various theoretical methods. The binding of four selected natural substrates to the constructed structure was studied in detail to further validate the model. Finally, to evaluate the reaction readiness of the constructed protein, the first step of the catalytic reaction has been successfully carried out with QST3/IRC calculations using the DFT/B3LYP-6-31G level of theory in the presence of extracted catalytic residues with the preserved coordinates in implicit water. Hence, the reaction readiness of the proposed protein structure, along with all the other validation tests, strongly proves that the modeled structure has high accuracy. This study, therefore, sheds new light on the structure, mechanism of action and applications of the 38C2 abzyme by constructing and validating its full 3D atomistic model. Further, this highly reliable modeled structure will expedite and facilitate future 38C2-based drug discovery.Communicated by Ramaswamy H. Sarma.

Ligand Binding Mechanism and Its Relationship with Conformational Changes in Adenine Riboswitch

Riboswitches are naturally occurring RNA aptamers that control the expression of essential bacterial genes by binding to specific small molecules. The binding with both high affinity and specificity induces conformational changes. Thus, riboswitches were proposed as a possible molecular target for developing antibiotics and chemical tools. The adenine riboswitch can bind not only to purine analogues but also to pyrimidine analogues. Here, long molecular dynamics (MD) simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) computational methodologies were carried out to show the differences in the binding model and the conformational changes upon five ligands binding. The binding free energies of the guanine riboswitch aptamer with C74U mutation complexes were compared to the binding free energies of the adenine riboswitch (AR) aptamer complexes. The calculated results are in agreement with the experimental data. The differences for the same ligand binding to two different aptamers are related to the electrostatic contribution. Binding dynamical analysis suggests a flexible binding pocket for the pyrimidine ligand in comparison with the purine ligand. The 18 μs of MD simulations in total indicate that both ligand-unbound and ligand-bound aptamers transfer their conformation between open and closed states. The ligand binding obviously affects the conformational change. The conformational states of the aptamer are associated with the distance between the mass center of two key nucleotides (U51 and A52) and the mass center of the other two key nucleotides (C74 and C75). The results suggest that the dynamical character of the binding pocket would affect its biofunction. To design new ligands of the adenine riboswitch, it is recommended to consider the binding affinities of the ligand and the conformational change of the ligand binding pocket.

Scoring Functions for Protein-RNA Complex Structure Prediction: Advances, Applications, and Future Directions

Protein-RNA interaction is among the most essential of biological events in living cells, being involved in protein synthesizing, RNA processing and transport, DNA transcription, and regulation of gene expression, and many other critical bio-molecular activities. A thorough understanding of this interaction is of paramount importance in fundamental study of a variety of vital cellular processes and therapeutic application for remedy of a broad range of diseases. Experimental high-resolution 3D structure determination is the primary source of knowledge for protein-RNA complexes. However, due to technical limitations, the existing techniques for experimental structure determination couldn't match the demand from fast growing interest in academia and industry. This problem necessitates the alternative high-throughput computational method for protein-RNA complex structure prediction. Similar to the in silico methods used for protein-protein and protein-DNA interactions, a reliable prediction of protein-RNA complex structure requires a scoring function with commensurate discriminatory power. Derived from determined structures and purposed to predict the to-be-determined structures, the scoring function is not only a predictive tool but also a gauge of our knowledge of protein-RNA interaction. In this review, we present an overview of the status of existing scoring functions and the scientific principle behind their constructions as well as their strengths and limitations. Finally, we will discuss about future directions of the scoring function development for protein-RNA structure prediction.

Identification and Analysis of Key Residues in Protein-RNA Complexes

Protein-RNA complexes play important roles in various biological processes. The functions of protein-RNA complexes are dictated by their interactions, binding, stability, and affinity. In this work, we have identified the key residues (KRs), which are involved in both stability and binding. We found that 42 percent of considered proteins share common binding and stabilizing residues, whereas these residues are distinct in 58 percent of the proteins. Overall, 5 percent of stabilizing and 3 percent of binding residues serve as key residues. These residues are enriched with the combination of polar, charged, aliphatic, and aromatic residues. Analysis on subclasses of protein-RNA complexes based on protein structural class, function and RNA type showed that regulatory proteins, and complexes with single stranded RNA and rRNA have appreciable number of key residues. Specifically, Arg, Tyr, and Thr are preferred in most of the subclasses of protein-RNA complexes. In addition, residues with similar chemical behavior have different preferences to be KRs, such that Arg, Tyr, Val, and Thr are preferred over Lys, Trp, Ile, and Ser, respectively. Atomic level contacts revealed that charged and polar-nonpolar contacts are dominant in enzymes, polar in structural, and nonpolar in regulatory proteins. On the other hand, polar-nonpolar contacts are enriched in all these classes of protein-RNA complexes. Further, the influence of sequence and structural features such as conservation score, surrounding hydrophobicity, solvent accessibility, secondary structure, and long-range order in key residues are also discussed. We envisage that the present study provides insights to understand the structural and functional aspects of protein-RNA complexes.

Assessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approaches

Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often neglected by end-point binding free energy calculation methods, such as MM/GBSA and MM/PBSA, due to the expensive computational cost of normal mode analysis (NMA). Here, we systematically investigated entropy effects on the prediction power of MM/GBSA and MM/PBSA using >1500 protein-ligand systems and six representative AMBER force fields. Two computationally efficient methods, including NMA based on truncated structures and the interaction entropy approach, were used to estimate the entropic contributions to ligand-target binding free energies. In terms of the overall accuracy, we found that, for the minimized structures, in most cases the inclusion of the conformational entropies predicted by truncated NMA (enthalpynmode_min_9Å) compromises the overall accuracy of MM/GBSA and MM/PBSA compared with the enthalpies calculated based on the minimized structures (enthalpymin). However, for the MD trajectories, the binding free energies can be improved by the inclusion of the conformation entropies predicted by either truncated-NMA for a relatively high dielectric constant (εin = 4) or the interaction entropy method for εin = 1-4. In terms of reproducing the absolute binding free energies, the binding free energies estimated by including the truncated-NMA entropies based on the MD trajectories (ΔGnmode_md_9Å) give the lowest average absolute deviations against the experimental data among all the tested strategies for both MM/GBSA and MM/PBSA. Although the inclusion of the truncated NMA based on the MD trajectories (ΔGnmode_md_9Å) for a relatively high dielectric constant gave the overall best result and the lowest average absolute deviations against the experimental data (for the ff03 force field), it needs too much computational time. Alternatively, considering that the interaction entropy method does not incur any additional computational cost and can give comparable (at high dielectric constant, εin = 4) or even better (at low dielectric constant, εin = 1-2) results than the truncated-NMA entropy (ΔGnmode_md_9Å), the interaction entropy approach is recommended to estimate the entropic component for MM/GBSA and MM/PBSA based on MD trajectories, especially for a diverse dataset. Furthermore, we compared the predictions of MM/GBSA with six different AMBER force fields. The results show that the ff03 force field (ff03 for proteins and gaff with AM1-BCC charges for ligands) performs the best, but the predictions given by the tested force fields are comparable, implying that the MM/GBSA predictions are not very sensitive to force fields.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Computational identification of the binding mechanism of a triple reuptake inhibitor amitifadine for the treatment of major depressive disorder

A shared binding mode involving eleven key residues at the S1 site of MATs for the binding of amitifadine is identified.

The fused SnoaL_2 domain in the Mycobacterium tuberculosis sigma factor σJ modulates promoter recognition

Extra-cytoplasmic function (ECF) σ-factors are widespread in bacteria, linking environmental stimuli with changes in gene expression. These transcription factors span several phylogenetically distinct groups and are remarkably diverse in their activation and regulatory mechanisms. Here, we describe the structural and biochemical features of a Mycobacterium tuberculosis ECF factor σJ that suggests that the SnoaL_2 domain at the C-terminus can modulate the activity of this initiation factor in the absence of a cognate regulatory anti-σ factor. M. tuberculosis σJ can bind promoter DNA in vitro; this interaction is substantially impaired by the removal of the SnoaL_2 domain. This finding is consistent with assays to evaluate σJ-mediated gene expression. Structural similarity of the SnoaL_2 domain with epoxide hydrolases also suggests a novel functional role for this domain. The conserved sequence features between M. tuberculosis σJ and other members of the ECF41 family of σ-factors suggest that the regulatory mechanism involving the C-terminal SnoaL_2 domain is likely to be retained in this family of proteins. These studies suggest that the ECF41 family of σ-factors incorporate features of both-the σ70 family and bacterial one-component systems thereby providing a direct mechanism to implement environment-mediated transcription changes.

Differentiating physicochemical properties between NDRIs and sNRIs clinically important for the treatment of ADHD

BACKGROUND

Drugs available for treating attention-deficit hyperactivity disorder (ADHD) are mainly selective norepinephrine (sNRIs) and dual norepinephrine-dopamine (NDRIs) reuptake inhibitors. The major problem of sNRIs lines in their delayed onset of action and partial- or non-responses, which makes NDRIs distinguished in drug efficacy. Understanding of the differential binding modes of these 2 types of drugs to their corresponding targets can give great insights into the discovery of privileged drug-like scaffolds with improved efficacy. So far, no such study has been carried out.

METHODS

A combinatorial computational strategy, integrating homology modeling, molecular docking, molecular dynamics (MD) and binding free energy calculation, was employed to analyze the binding modes of 8 clinically important ADHD drugs in their targets.

RESULTS

Binding modes of 2 types of ADHD drugs (sNRIs and NDRIs) in their targets was identified for the first time by MD simulation, and 15 hot spot residues were discovered as crucial for NDRIs' binding in hNET and hDAT. Comparing to sNRIs, a clear reduction in the hydrophobic property of NDRIs' one functional group was observed, and the depth of drugs' aromatic ring stretched into the pocket of both targets was further identified as key contributors to drugs' selectivity.

CONCLUSIONS

The hydrophobic property of NDRI ADHD drugs' one functional group contributes to their selectivity when bind hNET and hDAT.

GENERAL SIGNIFICANCE

These results provide insights into NDRI ADHD drugs' binding mechanisms, which could be utilized as structural blueprints for assessing and discovering more efficacious drugs for ADHD therapy.

Differentiating Physicochemical Properties between Addictive and Nonaddictive ADHD Drugs Revealed by Molecular Dynamics Simulation Studies

Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed mental disorder of children and adolescents. Although psychostimulants are currently the first-line drugs for ADHD, their highly addictive profile raises great abuse concerns. It is known that psychostimulants' addictiveness is largely attributed to their interaction with dopamine transporter (DAT) and their binding modes in DAT can thus facilitate the understanding of the mechanism underlining drugs' addictiveness. However, no DAT residue able to discriminate ADHD drugs' addictiveness is identified, and the way how different drug structures affect their abuse liability is still elusive. In this study, multiple computational methods were integrated to differentiate binding modes between approved psychostimulants and ADHD drugs of little addictiveness. As a result, variation in energy contribution of 8 residues between addictive and nonaddictive drugs was observed, and a reduction in hydrophobicity of drugs' 2 functional groups was identified as the indicator of drugs' addictiveness. This finding agreed well with the physicochemical properties of 8 officially reported controlled substances. The identified variations in binding mode can shed light on the mechanism underlining drugs' addictiveness, which may thus facilitate the discovery of improved ADHD therapeutics with reduced addictive profile.

Accurate, robust, and reliable calculations of Poisson-Boltzmann binding energies

Poisson-Boltzmann (PB) model is one of the most popular implicit solvent models in biophysical modeling and computation. The ability of providing accurate and reliable PB estimation of electrostatic solvation free energy, ΔGel, and binding free energy, ΔΔGel, is important to computational biophysics and biochemistry. In this work, we investigate the grid dependence of our PB solver (MIBPB) with solvent excluded surfaces for estimating both electrostatic solvation free energies and electrostatic binding free energies. It is found that the relative absolute error of ΔGel obtained at the grid spacing of 1.0 Å compared to ΔGel at 0.2 Å averaged over 153 molecules is less than 0.2%. Our results indicate that the use of grid spacing 0.6 Å ensures accuracy and reliability in ΔΔGel calculation. In fact, the grid spacing of 1.1 Å appears to deliver adequate accuracy for high throughput screening. © 2017 Wiley Periodicals, Inc.

Ligand Selectivity Mechanism and Conformational Changes in Guanine Riboswitch by Molecular Dynamics Simulations and Free Energy Calculations

Riboswitches regulate gene expression through direct and specific interactions with small metabolite molecules. Binding of a ligand to its RNA target is high selectivity and affinity and induces conformational changes of the RNA's secondary and tertiary structure. The structural difference of two purine riboswitches aptamers is caused by only one single mutation, where cytosine 74 in the guanine riboswitch is corresponding to a uracil 74 in adenine riboswitch. Here we employed molecular dynamics (MD) simulation, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and thermodynamic integration computational methodologies to evaluate the energetic and conformational changes of ligands binding to purine riboswitches. The snapshots used in MM-PBSA calculation were extracted from ten 50 ns MD simulation trajectories for each complex. These free energy results are in consistent with the experimental data and rationalize the selectivity of the riboswitches for different ligands. In particular, it is found that the loss in binding free energy upon mutation is mainly electrostatic in guanine (GUA) and riboswitch complex. Furthermore, new hydrogen bonds are found in mutated complexes. To reveal the conformational properties of guanine riboswitch, we performed a total of 6 μs MD simulations in both the presence and the absence of the ligand GUA. The MD simulations suggest that the conformation of guanine riboswitch depends on the distance of two groups in the binding pocket of ligand. The conformation is in a close conformation when U51-A52 is close to C74-U75.

Insights into the Structural Dynamics of Nucleocytoplasmic Transport of tRNA by Exportin-t

Exportin-t (Xpot) transports mature 5'- and 3'-end processed tRNA from the nucleus to the cytoplasm by associating with a small G-protein Ran (RAs-related nuclear protein), in the nucleus. The release of tRNA in cytoplasm involves RanGTP hydrolysis. Despite the availability of crystal structures of nuclear and cytosolic forms of Xpot, the molecular details regarding the sequential events leading to tRNA release and subsequent conformational changes occurring in Xpot remain unknown. We have performed a combination of classical all-atom and accelerated molecular dynamics simulations on a set of complexes involving Xpot to study a range of features including conformational flexibility of free and cargo-bound Xpot and functionally critical contacts between Xpot and its cargo. The systems investigated include free Xpot and its different complexes, bound either to Ran (GTP/GDP) or tRNA or both. This approach provided a statistically reliable estimate of structural dynamics of Xpot after cargo release. The mechanistic basis for Xpot opening after cargo release has been explained in terms of dynamic structural hinges, about which neighboring region could be displaced to facilitate the nuclear to cytosolic state transition. Post-RanGTP hydrolysis, a cascade of events including local conformational change in RanGTP and loss of critical contacts at Xpot/tRNA interface suggest factors responsible for eventual release of tRNA. The level of flexibility in different Xpot complexes varied depending on the arrangement of individual HEAT repeats. Current study provides one of the most comprehensive and robust analysis carried out on this protein using molecular dynamics schemes.

Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs

RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM-RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein-RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein-RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for 'MD-adapted structure ensemble' as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein-RNA complexes.

Exploring the Inhibitory Mechanism of Approved Selective Norepinephrine Reuptake Inhibitors and Reboxetine Enantiomers by Molecular Dynamics Study

Selective norepinephrine reuptake inhibitors (sNRIs) provide an effective class of approved antipsychotics, whose inhibitory mechanism could facilitate the discovery of privileged scaffolds with enhanced drug efficacy. However, the crystal structure of human norepinephrine transporter (hNET) has not been determined yet and the inhibitory mechanism of sNRIs remains elusive. In this work, multiple computational methods were integrated to explore the inhibitory mechanism of approved sNRIs (atomoxetine, maprotiline, reboxetine and viloxazine), and 3 lines of evidences were provided to verify the calculation results. Consequently, a binding mode defined by interactions between three chemical moieties in sNRIs and eleven residues in hNET was identified as shared by approved sNRIs. In the meantime, binding modes of reboxetine's enantiomers with hNET were compared. 6 key residues favoring the binding of (S, S)-reboxetine over that of (R, R)-reboxetine were discovered. This is the first study reporting that those 11 residues are the common determinants for the binding of approved sNRIs. The identified binding mode shed light on the inhibitory mechanism of approved sNRIs, which could help identify novel scaffolds with improved drug efficacy.

Identification of the inhibitory mechanism of FDA approved selective serotonin reuptake inhibitors: an insight from molecular dynamics simulation study

The binding mode shared by 4 FDA approved SSRIs treating major depression was identified by integrating multiple computational methods.

Searching the Sequence Space for Potent Aptamers Using SELEX in Silico

To isolate functional nucleic acids that bind to defined targets with high affinity and specificity, which are known as aptamers, the systematic evolution of ligands by exponential enrichment (SELEX) methodology has emerged as the preferred approach. Here, we propose a computational approach, SELEX in silico, that allows the sequence space to be more thoroughly explored regarding binding of a certain target. Our approach consists of two steps: (i) secondary structure-based sequence screening, which aims to collect the sequences that can form a desired RNA motif as an enhanced initial library, followed by (ii) sequence enrichment regarding target binding by molecular dynamics simulation-based virtual screening. Our SELEX in silico method provided a practical computational solution to three key problems in aptamer sequence searching: design of nucleic acid libraries, knowledge of sequence enrichment, and identification of potent aptamers. Six potent theophylline-binding aptamers, which were isolated by SELEX in silico from a sequence space containing 4(13) sequences, were experimentally verified to bind theophylline with high affinity: Kd ranging from 0.16 to 0.52 μM, compared with the dissociation constant of the original aptamer-theophylline, 0.32 μM. These results demonstrate the significant potential of SELEX in silico as a new method for aptamer discovery and optimization.

Quinoline based furanones and their nitrogen analogues: Docking, synthesis and biological evaluation

A small library of twenty-four quinoline based butenolides also known as furanones and their nitrogen analogues was prepared by using two different aroylpropionic acids, viz. 3-(2-naphthoyl)propionic acid (3) and 3-(biphenyl-4-yl)propionic acid (4), as starting materials. The 3-aroylpropionic acids were reacted with different 6-substituted-2-chloroquinolin-3-carbaldehydes (2a–d) to obtain the corresponding furan-2(3H)-ones (5a–h). The purified and characterized furanones were then converted into their corresponding 2(3H)-pyrrolones (6a–h) and N-benzyl-pyrrol-2(3H)-ones (7a–h). The antimicrobial activities of the title compounds were evaluated against two strains of each Gram +ve (Staphylococcus aureus and Bacillus subtilis), Gram −ve bacteria (Escherichia coli and Pseudomonas aeruginosa) and against fungal strains of Aspergillus niger and Aspergillus flavus. In vivo anti-inflammatory potential of the title compounds was investigated by standard method. Majority of the compounds showed significant antibacterial activity against both the Gram +ve strains. Eight most potent anti-inflammatory compounds (5b, 5d, 5h, 6b, 7b, 7d, 7f, 7h) which exhibited >53% inhibition in edema, were also screened for their in vivo analgesic activity. All the tested compounds were found to have significant reduction in ulcerogenic action but only three compounds (5d, 5h and 7h) showed comparable analgesic activity to standard drug, diclofenac. The results were also validated using in silico approach and maximum mol doc score was obtained for compounds 7a–h. On comparing the in vivo and in silico anti-inflammatory results of synthesized compounds, N-benzyl pyrrolones (7a–h) emerged as the potent anti-inflammatory agents. It was also observed that compounds that possess electron withdrawing group such as —Cl or NO₂ are more biologically active.

Can We Execute Stable Microsecond-Scale Atomistic Simulations of Protein-RNA Complexes?

We report over 30 μs of unrestrained molecular dynamics simulations of six protein-RNA complexes in explicit solvent. We utilize the AMBER ff99bsc0χ(OL3) RNA force field combined with the ff99SB protein force field and its more recent ff12SB version with reparametrized side-chain dihedrals. The simulations show variable behavior, ranging from systems that are essentially stable to systems with progressive deviations from the experimental structure, which we could not stabilize anywhere close to the starting experimental structure. For some systems, microsecond-scale simulations are necessary to achieve stabilization after initial sizable structural perturbations. The results show that simulations of protein-RNA complexes are challenging and every system should be treated individually. The simulations are affected by numerous factors, including properties of the starting structures (the initially high force field potential energy, resolution limits, conformational averaging, crystal packing, etc.), force field imbalances, and real flexibility of the studied systems. These factors, and thus the simulation behavior, differ from system to system. The structural stability of simulated systems does not correlate with the size of buried interaction surface or experimentally determined binding affinities but reflects the type of protein-RNA recognition. Protein-RNA interfaces involving shape-specific recognition of RNA are more stable than those relying on sequence-specific RNA recognition. The differences between the protein force fields are considerably smaller than the uncertainties caused by sampling and starting structures. The ff12SB improves description of the tyrosine side-chain group, which eliminates some problems associated with tyrosine dynamics.

Influence of Grid Spacing in Poisson-Boltzmann Equation Binding Energy Estimation

Grid-based solvers of the Poisson-Boltzmann, PB, equation are routinely used to estimate electrostatic binding, ΔΔG_el, and solvation, ΔG_el, free energies. The accuracies of such estimates are subject to grid discretization errors from the finite difference approximation to the PB equation. Here, we show that the grid discretization errors in ΔΔG_el are more significant than those in ΔG_el, and can be divided into two parts: (i) errors associated with the relative positioning of the grid and (ii) systematic errors associated with grid spacing. The systematic error in particular is significant for methods, such as the molecular mechanics PB surface area, MM-PBSA, approach that predict electrostatic binding free energies by averaging over an ensemble of molecular conformations. Although averaging over multiple conformations can control for the error associated with grid placement, it will not eliminate the systematic error, which can only be controlled by reducing grid spacing. The present study indicates that the widely-used grid spacing of 0.5 Å produces unacceptable errors in ΔΔG_el, even though its predictions of ΔG_el are adequate for the cases considered here. Although both grid discretization errors generally increase with grid spacing, the relative sizes of these errors differ according to the solute-solvent dielectric boundary definition. The grid discretization errors are generally smaller on the Gaussian surface used in the present study than on either the solvent-excluded or van der Waals surfaces, which both contain more surface discontinuities (e.g., sharp edges and cusps). Additionally, all three molecular surfaces converge to very different estimates of ΔΔG_el.

Importance of polar solvation and configurational entropy for design of antiretroviral drugs targeting HIV-1 protease

Both KNI-10033 and KNI-10075 are high affinity preclinical HIV-1 protease (PR) inhibitors with affinities in the picomolar range. In this work, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method has been used to investigate the potency of these two HIV-1 PR inhibitors against the wild-type and mutated proteases assuming that potency correlates with the affinity of the drugs for the target protein. The decomposition of the binding free energy reveals the origin of binding affinities or mutation-induced affinity changes. Our calculations indicate that the mutation I50V causes drug resistance against both inhibitors. On the other hand, we predict that the mutant I84V causes drug resistance against KNI-10075 while KNI-10033 is more potent against the I84V mutant compared to wild-type protease. Drug resistance arises mainly from unfavorable shifts in van der Waals interactions and configurational entropy. The latter indicates that neglecting changes in configurational entropy in the computation of relative binding affinities as often done is not appropriate in general. For the bound complex PR(I50V)-KNI-10075, an increased polar solvation free energy also contributes to the drug resistance. The importance of polar solvation free energies is revealed when interactions governing the binding of KNI-10033 or KNI-10075 to the wild-type protease are compared to the inhibitors darunavir or GRL-06579A. Although the contributions from intermolecular electrostatic and van der Waals interactions as well as the nonpolar component of the solvation free energy are more favorable for PR-KNI-10033 or PR-KNI-10075 compared to PR-DRV or PR-GRL-06579A, both KNI-10033 and KNI-10075 show a similar affinity as darunavir and a lower binding affinity relative to GRL-06579A. This is because of the polar solvation free energy which is less unfavorable for darunavir or GRL-06579A relative to KNI-10033 or KNI-10075. The importance of the polar solvation as revealed here highlights that structural inspection alone is not sufficient for identifying the key contributions to binding affinities and affinity changes for the design of drugs but that solvation effects must be taken into account. A detailed understanding of the molecular forces governing binding and drug resistance might assist in the design of new inhibitors against HIV-1 PR variants that are resistant against current drugs.

Structures, dynamics, and stabilities of fully modified locked nucleic acid (β-D-LNA and α-L-LNA) duplexes in comparison to pure DNA and RNA duplexes

Locked nucleic acid (LNA) is a chemical modification which introduces a -O-CH2- linkage in the furanose sugar of nucleic acids and blocks its conformation in a particular state. Two types of modifications, namely, 2'-O,4'-C-methylene-β-D-ribofuranose (β-D-LNA) and 2'-O,4'-C-methylene-α-L-ribofuranose (α-L-LNA), have been shown to yield RNA and DNA duplex-like structures, respectively. LNA modifications lead to increased melting temperatures of DNA and RNA duplexes, and have been suggested as potential therapeutic agents in antisense therapy. In this study, molecular dynamics (MD) simulations were performed on fully modified LNA duplexes and pure DNA and RNA duplexes sharing a similar sequence to investigate their structure, stabilities, and solvation properties. Both LNA duplexes undergo unwinding of the helical structure compared to the pure DNA and RNA duplexes. Though the α-LNA substituent has been proposed to mimic deoxyribose sugar in its conformational properties, the fully modified duplex was found to exhibit unique structural and dynamic properties with respect to the other three nucleic acid structures. Free energy calculations accurately capture the enhanced stabilization of the LNA duplex structures compared to DNA and RNA molecules as observed in experiments. π-stacking interaction between bases from complementary strands is shown to be one of the contributors to enhanced stabilization upon LNA substitution. A combination of two factors, namely, nature of the -O-CH2- linkage in the LNAs vs their absence in the pure duplexes and similar conformations of the sugar rings in DNA and α-LNA vs the other two, is suggested to contribute to the stark differences among the four duplexes studied here in terms of their structural, dynamic, and energetic properties.

The interactions and recognition of cyclic peptide mimetics of Tat with HIV-1 TAR RNA: a molecular dynamics simulation study

The interaction of HIV-1 trans-activator protein Tat with its cognate trans-activation response element (TAR) RNA is critical for viral transcription and replication. Therefore, it has long been considered as an attractive target for the development of antiviral compounds. Recently, the conformationally constrained cyclic peptide mimetics of Tat have been tested to be a promising family of lead peptides. Here, we focused on two representative cyclic peptides termed as L-22 and KP-Z-41, both of which exhibit excellent inhibitory potency against Tat and TAR interaction. By means of molecular dynamics simulations, we obtained a detailed picture of the interactions between them and HIV-1 TAR RNA. In results, it is found that the binding modes of the two cyclic peptides to TAR RNA are almost identical at or near the bulge regions, whereas the binding interfaces at the apical loop exhibit large conformational heterogeneity. In addition, it is revealed that electrostatic interaction energy contributes much more to KP-Z-41 complex formation than to L-22 complex, which is the main source of energy that results in a higher binding affinity of KP-Z-41 over-22 for TAR RNA. Furthermore, we identified a conserved motif RRK (Arg-Arg-Lys) that is shown to be essential for specific binding of this class of cyclic peptides to TAR RNA. This work can provide a useful insight into the design and modification of cyclic peptide inhibitors targeting the association of HIV-1 Tat and TAR RNA.

Insights into the thermal stabilization and conformational transitions of DNA by hyperthermophile protein Sso7d: molecular dynamics simulations and MM-PBSA analysis

In the assembly of DNA-protein complex, the DNA kinking plays an important role in nucleoprotein structures and gene regulation. Molecular dynamics (MD) simulations were performed on specific protein-DNA complexes in this study to investigate the stability and structural transitions of DNA depending on temperature. Furthermore, we introduced the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) approach to analyze the interactions between DNA and protein in hyperthermophile. Focused on two specific Sso7d-DNA complexes (PDB codes: 1BNZ and 1BF4), we performed MD simulations at four temperatures (300, 360, 420, and 480 K) and MM-PBSA at 300 and 360 K to illustrate detailed information on the changes of DNA. Our results show that Sso7d stabilizes DNA duplex over a certain temperature range and DNA molecules undergo B-like to A-like form transitions in the binary complex with the temperature increasing, which are consistent with the experimental data. Our work will contribute to a better understanding of protein-DNA interaction.

High-resolution single-molecule recognition imaging of the molecular details of ricin-aptamer interaction

We studied the molecular details of DNA aptamer-ricin interactions. The toxic protein ricin molecules were immobilized on a Au(111) surface using a N-hydroxysuccinimide (NHS) ester to specifically react with lysine residues located on the ricin B chains. A single ricin molecule was visualized in situ using the AFM tip modified with an antiricin aptamer. Computer simulation was used to illustrate the protein and aptamer structures, the single-molecule ricin images on a Au(111) surface, and the binding conformations of ricin-aptamer and ricin-antibody complexes. The various ricin conformations on a Au(111) surface were caused by the different lysine residues reacting with the NHS ester. It was also observed that most of the binding sites for aptamer and antibody on the A chains of ricin molecules were not interfered by the immobilization reaction. The different locations of the ricin binding sites to aptamer and antibody were also distinguished by AFM recognition images and interpreted by simulations.

Theoretical prediction of the binding free energy for mutants of replication protein A

The replication protein A (RPA) is a heterotrimeric (70, 32, and 14 kDa subunits), single stranded DNA (ssDNA) binding protein required for pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Studies based on deletions and mutations have identified the high affinity ssDNA binding domains in the 70 kDa subunit of RPA, regions A and B. Individually, the domain A and B have a low affinity for ssDNA, while tandems composed of AA, AB, BB, and BA sequences bind the ssDNA with moderate to high affinity. Single and double point mutations on polar residues in the binding domains leads to a reduction in affinity of RPA for ssDNA, in particular when two hydrophilic residues are involved. In view of these results, we performed a study based on molecular dynamics simulation aimed to reproduce the experimental change in binding free energy, ΔΔG, of RPA70 mutants to further elucidate the nature of the protein-ssDNA interaction. The MM-PB(GB)SA methods implemented in Amber10 and the code FoldX were used to estimate the binding free energy. The theoretical and experimental ΔΔG values correlate better when the results are obtained by MM-PBSA calculated on individual trajectories for each mutant. In these conditions, the correlation coefficient between experimental and theoretical ΔΔG reaches a value of 0.95 despite the overestimation of the energy change by one order of magnitude. The decomposition of the MM-GBSA energy per residue allows us to correlate the change of the affinity with the residue polarity and energy contribution to the binding. The method revealed reliable predictions of the change in the affinity in function of mutations, and can be used to identify new mutants with distinct binding properties.

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.