Revealing inhibition difference between PFI-2 enantiomers against SETD7 by molecular dynamics simulations, binding free energy calculations and unbinding pathway analysis

SETD7 is associated with multiple diseases related signaling pathways. (R)-PFI-2 is the first SETD7 inhibitor with nanomolar inhibitory potency. The activity of (R)-PFI-2 is about 500 times over that of (S)-PFI-2. Understanding the mechanism behind this difference will be helpful to discovery and design of more potent SETD7 inhibitors. A computational study combining molecular dynamics simulation, binding free energy calculations, and residue interaction network (RIN) was performed on the (S)-PFI-2/SETD7 and (R)-PFI-2/SETD7 complexes to explore the molecular mechanism behind the different inhibition activity. The results from Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation show (R)-PFI-2 has lower binding free energy. Residues H252, D256, L267, Y335, G336 and H339 are responsible for the binding of SETD7 to the (R)-PFI-2. RIN analysis indicates van der Waals interaction is critical for the binding of (R)-PFI-2. The results from adaptive basing force (ABF) simulation confirm that the free energy barrier of (R)-PFI-2 dissociating from the SETD7 is larger than that of (S)-PFI-2. (S)-PFI-2 and (R)-PFI-2 dissociate from the SETD7 binding site along different reaction coordinate and have potential mean of force (PMF) depth. Our simulations results will be useful to understand molecular mechanism of activity difference between PFI-2 enantiomers against SETD7.

Peptide probes derived from pertuzumab by molecular dynamics modeling for HER2 positive tumor imaging

A high level of HER2 expression in breast cancer correlates with a higher tumor growth rate, high metastatic potential, and a poor long-term patient survival rate. Pertuzumab, a human monoclonal antibody, can reduce the effect of HER2 overexpression by preventing HER2 dimerization. In this study, a combination protocol of molecular dynamics modeling and MM/GBSA binding free energy calculations was applied to design peptides that interact with HER2 based on the HER2/pertuzumab crystal structure. Based on a β hairpin in pertuzumab from Glu46 to Lys65—which plays a key role in interacting with HER2—mutations were carried out in silico to improve the binding free energy of the hairpin that interacts with the Phe256-Lys314 of the HER2 protein. Combined the use of one-bead-one-compound library screening, among all the mutations, a peptide (58F63Y) with the lowest binding free energy was confirmed experimentally to have the highest affinity, and it may be used as a new probe in diagnosing and treating HER2-positive breast cancer.

Many therapeutic approaches, including the human monoclonal antibodies trastuzumab and pertuzumab, target the human epidermal growth factor receptor 2 (HER2) of any breast cancer that features HER2 overexpression. Compared to these antibodies, peptides have many advantages, including lower cost, easier synthesis, high affinity, and lower toxicity. Here, we first designed peptides that interact with HER2 protein based on the HER2/pertuzumab crystal structure (PDB entry: 1S78), using a combination protocol of molecular dynamics modeling, molecular mechanics/generalized Born solvent-accessible surface area (MM/GBSA) binding free energy calculations. Then, combined with the peptide library screening, six peptides were selected for further analysis and experimental validations. The results of ex vivo and in vivo experiments confirmed that one peptide (58F63Y) in particular has a strong affinity and high specificity to HER2-overexpressing tumors. This may due to more paired residues and lower binding free energy in peptide 58F63Y and HER2 complex based on free energy decomposition analysis and distances calculation. While both in silico and in vitro screenings point to the same high-affinity peptide, the findings suggest that in silico screening based on calculated binding free energies is rather reliable. Additionally, based on the calculation of binding free energies among mutants, we can reduce the library capacity of one-bead-one-compound screening. In summary, we present a rather simple and rapid means of deriving a peptide with a clear binding site to its target protein.

Applications of computer-aided approaches in the development of hepatitis C antiviral agents

INTRODUCTION

Hepatitis C virus (HCV) is a global health problem that causes several chronic life-threatening liver diseases. The numbers of people affected by HCV are rising annually. Since 2011, the FDA has approved several anti-HCV drugs; while many other promising HCV drugs are currently in late clinical trials. Areas covered: This review discusses the applications of different computational approaches in HCV drug design. Expert opinion: Molecular docking and virtual screening approaches have emerged as a low-cost tool to screen large databases and identify potential small-molecule hits against HCV targets. Ligand-based approaches are useful for filtering-out compounds with rich physicochemical properties to inhibit HCV targets. Molecular dynamics (MD) remains a useful tool in optimizing the ligand-protein complexes and understand the ligand binding modes and drug resistance mechanisms in HCV. Despite their varied roles, the application of in-silico approaches in HCV drug design is still in its infancy. A more mature application should aim at modelling the whole HCV replicon in its active form and help to identify new effective druggable sites within the replicon system. With more technological advancements, the roles of computer-aided methods are only going to increase several folds in the development of next-generation HCV drugs.

Effect of polarization on HIV-1protease and fluoro-substituted inhibitors binding energies by large scale molecular dynamics simulations

Molecular dynamics simulations in explicit water are carried out to study the binding of six inhibitors to HIV-1 protease (PR) for up to 700 ns using the standard AMBER force field and polarized protein-specific charge (PPC). PPC is derived from quantum mechanical calculation for protein in solution and therefore it includes electronic polarization effect. Our results show that in all six systems, the bridging water W301 drifts away from the binding pocket in AMBER simulation. However, it is very stable in all six complexes systems using PPC. Especially, intra-protease, protease-inhibitor hydrogen bonds are dynamic stabilized in MD simulation. The computed binding free energies of six complexes have a significantly linear correlation with those experiment values and the correlation coefficient is found to be 0.91 in PPC simulation. However, the result from AMBER simulation shows a weaker correlation with the correlation coefficient of −0.51 due to the lack of polarization effect. Detailed binding interactions of W301, inhibitors with PR are further analyzed and discussed. The present study provides important information to quantitative understanding the interaction mechanism of PR-inhibitor and PR-W301 and these data also emphasizes the importance of both the electronic polarization and the bridging water molecule in predicting precisely binding affinities.

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

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

Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations

The binding mode prediction is of great importance to structure-based drug design. The discrimination of various binding poses of ligand generated by docking is a great challenge not only to docking score functions but also to the relatively expensive free energy calculation methods. Here we systematically analyzed the stability of various ligand poses under molecular dynamics (MD) simulation. First, a data set of 120 complexes was built based on the typical physicochemical properties of drug-like ligands. Three potential binding poses (one correct pose and two decoys) were selected for each ligand from self-docking in addition to the experimental pose. Then, five independent MD simulations for each pose were performed with different initial velocities for the statistical analysis. Finally, the stabilities of ligand poses under MD were evaluated and compared with the native one from crystal structure. We found that about 94% of the native poses were maintained stable during the simulations, which suggests that MD simulations are accurate enough to judge most experimental binding poses as stable properly. Interestingly, incorrect decoy poses were maintained much less and 38-44% of decoys could be excluded just by performing equilibrium MD simulations, though 56-62% of decoys were stable. The computationally-heavy binding free energy calculation can be performed only for these survived poses.

A fragment-based docking simulation for investigating peptide–protein bindings

We developed a fragment-based docking strategy for long peptide docking simulations, which separates a long peptide into halves for docking, and then recombined to rebuild whole-peptide docking conformations. With further screening, optimizations and MM/GBSA scoring, our method was capable of efficiently predicting the near-native peptide binding conformations.

Molecular dynamics investigations of membrane-bound CYP2C19 polymorphisms reveal distinct mechanisms for peripheral variants by long-range effects on the enzymatic activity

The results reveal distinct mechanisms for enzymatic activity deficiencies upon two peripheral variants in CYP2C19.

Effect of electrostatic polarization and bridging water on CDK2–ligand binding affinities calculated using a highly efficient interaction entropy method

A new highly efficient interaction entropy (IE) method combined with the polarized protein-specific charge (PPC) force field is employed to investigate the interaction mechanism of CDK2–ligand binding and the effect of the bridging water.

Prediction of luciferase inhibitors by the high-performance MIEC-GBDT approach based on interaction energetic patterns

The MIEC-GBDT model can be used as a powerful tool to identify potential interference compounds in luciferase-based high-throughput screening.

The in silico identification of small molecules for protein-protein interaction inhibition in AKAP-Lbc-RhoA signaling complex

The rational design of small molecules that mimic key residues at the interface of interacting proteins can be a successful approach to target certain biological signaling cascades causing pathophysiological outcome. The A-Kinase Anchoring Protein, i.e. AKAP-Lbc, catalyses nucleotide exchange on RhoA and is involved in cardiac repolarization. The oncogenic AKAP-Lbc induces the RhoA GTPase hyperactivity and aberrantly amplifies the signaling pathway leading to hypertrophic cardiomyocytes. We took advantage of the AKAP-Lbc-RhoA complex crystal structure to design in silico small molecules predicted to inhibit the associated pathological signaling cascade. We adopted the strategies of pharmacophore building, virtual screening and molecular docking to identify the small molecules capable to target AKAP-Lbc and RhoA interactions. The pharmacophore model based virtual screening unveils two lead compounds from the TIMBAL database of small molecules modulating the targeted protein-protein interactions. The molecular docking analysis revealed the lead compounds' potentialities to establish the essential chemical interactions with the key interactive residues of the complex. These features provided a road map for designing additional potent chemical derivatives and fragments of the original lead compounds to perturb the AKAP-Lbc and RhoA interactions. Experimental validations may elucidate the therapeutic potential of these lead chemical scaffolds to deal with aberrant AKAP-Lbc signaling based cardiac hypertrophy.

Theoretical studies on the selective mechanisms of GSK3β and CDK2 by molecular dynamics simulations and free energy calculations

Glycogen synthase kinase 3 (GSK3) is a serine/threonine protein kinase which is widely involved in cell signaling and controls a broad number of cellular functions. GSK3 contains α and β isoforms, and GSK3β has received more attention and becomes an attractive drug target for the treatment of several diseases. The binding pocket of cyclin-dependent kinase 2 (CDK2) shares high sequence identity to that of GSK3β, and therefore, the design of highly selective inhibitors toward GSK3β remains a big challenge. In this study, a computational strategy, which combines molecular docking, molecular dynamics simulations, free energy calculations, and umbrella sampling simulations, was employed to explore the binding mechanisms of two selective inhibitors to GSK3β and CDK2. The simulation results highlighted the key residues critical for GSK3β selectivity. It was observed that although GSK3β and CDK2 share the conserved ATP-binding pockets, some different residues have significant contributions to protein selectivity. This study provides valuable information for understanding the GSK3β-selective binding mechanisms and the rational design of selective GSK3β inhibitors.

Molecular mechanism of R-bicalutamide switching from androgen receptor antagonist to agonist induced by amino acid mutations using molecular dynamics simulations and free energy calculation

R-bicalutamide, a first generation antiandrogen, was used to treat prostate cancer for decades. Although it is very effective at the beginning, resistance appears after 2-3 years of treatment. Mutation of androgen receptor (AR) is considered a main reason for drug resistance. It is reported that AR W741C, W741L, W741C_T877A, T877A, F876L, F876L_T877A and L701H mutations can convert R-bicalutamide from AR antagonist to agonist, but the switching mechanisms are not clear. In this study, molecular dynamics simulations and molecular mechanics generalized Born surface area (MM-GBSA) calculations were performed to analyze the interaction mechanisms between R-bicalutamide and wild type/mutant ARs. The results indicate that helix H12, which lies on the top of AR LBD like a cover, plays a vital role in R-bicalutamide binding. When interacting with AR, the B-ring of R-bicalutamide pushes H12 aside, distorting the coactivator binding site (AF2) resulting in the inactivation of transcription. Several residue mutations appear to enlarge the distance between the B-ring of R-bicalutamide and H12, reducing steric clash, which is conducive to a closed H12 conformation, leading to the formation of the coactivator binding site AF2 and increased transcription. Hydrogen bond and per-residue free energy decomposition analyses are also investigated to explore the interacting mechanisms, and M895 is found to be a key residue in the antagonist mechanism. The obtained molecular mechanisms will aid rational screening and design of novel AR antagonists, even to mutant AR.

Role of R292K mutation in influenza H7N9 neuraminidase toward oseltamivir susceptibility: MD and MM/PB(GB)SA study

The H7N9 avian influenza virus is a novel re-assortment from at least four different strains of virus. Neuraminidase, which is a glycoprotein on the surface membrane, has been the target for drug treatment. However, some H7N9 strains that have been isolated from patient after drug treatment have a R292K mutation in neuraminidase. This substitution was found to facilitate drug resistance using protein- and virus- assays, in particular it gave a high resistance to the most commonly used drug, oseltamivir. The aim of this research is to understand the source of oseltamivir resistance using MD simulations and the MM/PB(GB)SA binding free energy approaches. Both methods can predict the reduced susceptibility of oseltamivir in good agreement to the IC ₅₀ binding energy, although MM/GBSA underestimates this prediction compared to the MM/PBSA calculation. Electrostatic interaction is the main contribution for oseltamivir binding in terms of both interaction and solvation. We found that the source of the drug resistance is a decrease in the binding interaction combined with the reduction of the dehydration penalty. The smaller K292 mutated residue has a larger binding pocket cavity compared to the wild-type resulting in the loss of drug carboxylate-K292 hydrogen bonding and an increased accessibility for water molecules around the K292 mutated residue. In addition, oseltamivir does not bind well to the R292K mutant complex as shown by the high degree of fluctuation in ligand RMSD during the simulation and the change in angular distribution of bulky side chain groups.

Energetic and conformational features linked to the monomeric and dimeric states of bovine BLG

Bovine β-lactoglobulin (BLG) belong to the lipocalin family. This is a group of proteins involved in the binding and transporting of hydrophobic molecules. Experimental and theoretical reports have stated its complex structural behavior in solution, with coupled effects between homodimerization and ligand recognition. Nonetheless, structural evidence at the atomic level about the cause of this coupled effect has not been reported to date. To address this issue microsecond molecular dynamics (MD) simulations were combined with the molecular mechanics generalized Born surface area (MM/GBSA) approach, clustering analysis and principal component analysis (PCA), to explore the conformational complexity of BLG protein-protein self-association and palmitic acid (PLM) or dodecyl sulfate (SDS) ligand recognition in the monomeric and dimeric state. MD simulations, coupled to the MM/GBSA method, revealed that dimerization exerts contrasting effects on the ligand-binding capacity of BLG. Protein dimerization decreases PLM affinity, promoting dimer association. For SDS the dimeric state increases affinity, enhancing dimer dissociation. MD simulations based on PCA revealed that while few differences in the conformational subspace are observed between the free and bound monomer and dimer coupling for PLM, substantial changes are observed between the free and bound monomer and dimer coupling for SDS.

Effect of Inactivating Mutations on Peptide Conformational Ensembles: The Plant Polypeptide Hormone Systemin

As part of their basal immune mechanism against insect/herbivore attacks, plants have evolved systemic response mechanisms. Such a systemic wound response in tomato was found to involve an 18 amino acid polypeptide called systemin, the first polypeptide hormone to be discovered in plants. Systematic alanine scanning and deletion studies showed differential modulation in its activity, particularly a major loss of function due to alanine substitution at positions 13 and 17 and less extentive loss of function due to substitution at position 12. We have studied the conformational ensembles of wild-type systemin along with its 17 variants by carrying out a total of 5.76 μs of replica-exchange molecular dynamics simulation in an implicit solvent environment. In our simulations, wild-type systemin showed a lack of α-helical and β-sheet structures, in conformity with earlier circular dichroism and NMR data. On the other hand, two regions containing diproline segments showed a tendency to adopt polyproline II structures. Examination of conformational ensembles of the 17 variants revealed a change in the population distributions, suggesting a less flexible structure for alanine substitutions at positions 12 and 13 but not for position 17. Combined with the experimental observations that positions 1-14 of systemin are important for the formation of the peptide-receptor complex, this leads to the hypothesis that loss of conformational flexibility may play a role in the loss of activity of systemin due to the P12A and P13A substitutions, while T17A deactivation probably occurs for a different reason, most likely the loss of the threonine phosphorylation site. We also indicate possible structural reasons why the substitution of the prolines at positions 12 and 13 leads to a loss of conformational freedom in the peptide.

Identification of phenoxyacetamide derivatives as novel DOT1L inhibitors via docking screening and molecular dynamics simulation

Dot1-like protein (DOT1L) is a histone methyltransferase that has become a novel and promising target for acute leukemias bearing mixed lineage leukemia (MLL) gene rearrangements. In this study, a hierarchical docking-based virtual screening combined with molecular dynamic (MD) simulation was performed to identify DOT1L inhibitors with novel scaffolds. Consequently, 8 top-ranked hits were eventually identified and were further subjected to MD simulation. It was indicated that all hits could reach equilibrium with DOT1L in the MD simulation and further binding free energy calculations suggested that phenoxyacetamide-derived hits such as L01, L03, L04 and L05 exhibited remarkably higher binding affinity compared to other hits. Among them, L03 showed both the lowest glide score (-12.281) and the most favorable binding free energy (-303.9+/-16.5kJ/mol), thereby making it a promising lead for further optimization.

Computational Studies of a Mechanism for Binding and Drug Resistance in the Wild Type and Four Mutations of HIV-1 Protease with a GRL-0519 Inhibitor

Drug resistance of mutations in HIV-1 protease (PR) is the most severe challenge to the long-term efficacy of HIV-1 PR inhibitor in highly active antiretroviral therapy. To elucidate the molecular mechanism of drug resistance associated with mutations (D30N, I50V, I54M, and V82A) and inhibitor (GRL-0519) complexes, we have performed five molecular dynamics (MD) simulations and calculated the binding free energies using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The ranking of calculated binding free energies is in accordance with the experimental data. The free energy spectra of each residue and inhibitor interaction for all complexes show a similar binding model. Analysis based on the MD trajectories and contribution of each residues show that groups R2 and R3 mainly contribute van der Waals energies, while groups R1 and R4 contribute electrostatic interaction by hydrogen bonds. The drug resistance of D30N can be attributed to the decline in binding affinity of residues 28 and 29. The size of Val50 is smaller than Ile50 causes the residue to move, especially in chain A. The stable hydrophobic core, including the side chain of Ile54 in the wild type (WT) complex, became unstable in I54M because the side chain of Met54 is flexible with two alternative conformations. The binding affinity of Ala82 in V82A decreases relative to Val82 in WT. The present study could provide important guidance for the design of a potent new drug resisting the mutation inhibitors.

Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery

The MIEC-SVM approach, which combines molecular interaction energy components (MIEC) derived from free energy decomposition and support vector machine (SVM), has been found effective in capturing the energetic patterns of protein-peptide recognition. However, the performance of this approach in identifying small molecule inhibitors of drug targets has not been well assessed and validated by experiments. Thereafter, by combining different model construction protocols, the issues related to developing best MIEC-SVM models were firstly discussed upon three kinase targets (ABL, ALK, and BRAF). As for the investigated targets, the optimized MIEC-SVM models performed much better than the models based on the default SVM parameters and Autodock for the tested datasets. Then, the proposed strategy was utilized to screen the Specs database for discovering potential inhibitors of the ALK kinase. The experimental results showed that the optimized MIEC-SVM model, which identified 7 actives with IC50 < 10 μM from 50 purchased compounds (namely hit rate of 14%, and 4 in nM level) and performed much better than Autodock (3 actives with IC50 < 10 μM from 50 purchased compounds, namely hit rate of 6%, and 2 in nM level), suggesting that the proposed strategy is a powerful tool in structure-based virtual screening.

Deciphering the mechanism behind the varied binding activities of COXIBs through Molecular Dynamic Simulations, MM-PBSA binding energy calculations and per-residue energy decomposition studies

COX-2 is a well-known drug target in inflammatory disorders. COX-1/COX-2 selectivity of NSAIDs is crucial in assessing the gastrointestinal side effects associated with COX-1 inhibition. Celecoxib, rofecoxib, and valdecoxib are well-known specific COX-2 inhibiting drugs. Recently, polmacoxib, a COX-2/CA-II dual inhibitor has been approved by the Korean FDA. These COXIBs have similar structure with diverse activity range. Present study focuses on unraveling the mechanism behind the 10-fold difference in the activities of these sulfonamide-containing COXIBs. In order to obtain insights into their binding with COX-2 at molecular level, molecular dynamics simulations studies, and MM-PBSA approaches were employed. Further, per-residue decomposition of these energies led to the identification of crucial amino acids and interactions contributing to the differential binding of COXIBs. The results clearly indicated that Leu338, Ser339, Arg499, Ile503, Phe504, Val509, and Ser516 (Leu352, Ser353, Arg513, Ile517, Phe518, Val523, and Ser530 in PGHS-1 numbering) were imperative in determining the activity of these COXIBs. The binding energies and energy contribution of various residues were similar in all the three simulations. The results suggest that hydrogen bond interaction between the hydroxyl group of Ser516 and five-membered ring of diarylheterocycles augments the affinity in COXIBs. The SAR of the inhibitors studied and the per-residue energy decomposition values suggested the importance of Ser516. Additionally, the positive binding energy obtained with Arg106 explains the binding of COXIBs in hydrophobic channel deep in the COX-2 active site. The findings of the present work would aid in the development of potent COX-2 inhibitors.

Understanding the molecular basis of agonist/antagonist mechanism of GPER1/GPR30 through structural and energetic analyses

The G-protein coupled receptors (GPCRs) represent the largest superfamily of membrane proteins in charge to pass the cell signaling after binding with their cognate ligands to the cell interior. In breast cancer, a GPCR named GPER1 plays a key role in the process of growth and the proliferation of cancer cells. In a previous study, theoretical methods were applied to construct a model of GPER1, which later was submitted to molecular dynamics (MD) simulations to perform a docking calculation. Based on this preceding work, it is known that GPER1 is sensitive to structural differences in its binding site. However, due to the nature of that past study, conformational changes linked to the ligand binding were not observed. Therefore, in this study, in order to explore the conformational changes coupled to the agonist/antagonist binding, MD simulations of about 0.25μs were performed for the free and bound states, summarizing 0.75μs of MD simulation in total. For the bound states, one agonist (G-1) and antagonist (G-15) were chosen since is widely known that these two molecules cause an impact on GPER1 mobility. Based on the conformational ensemble generated through MD simulations, we found that despite G-1 and G-15 being stabilized by similar map of residues, the structural differences between both ligands impact the hydrogen bond pattern not only at the GPER1 binding site but also along the seven-helix bundle, causing significant differences in the conformational mobility along the extracellular and cytoplasmic domain, and to a lesser degree in the curvatures of helix 2, helix 3 and helix 7 between the free and bound states, which is in agreement with reported literature, and might be linked to microscopic characteristics of the activated-inactivated transition. Furthermore, binding free energy calculations using the MM/GBSA method for the bound states, followed by an alanine scanning analysis allowed us to identify some important residues for the complex stabilization.

Assessing the ligand selectivity of sphingosine kinases using molecular dynamics and MM-PBSA binding free energy calculations

The dynamic balance of sphingolipids plays a crucial role in diverse biological processes such as mitogenesis, cell migration and angiogenesis. Sphingosine kinases (SKs) including SK1 and SK2 phosphorylate sphingosine to sphingosine 1-phosphate (S1P), and control the critical balance. SK1 overexpression was reported to increase cell survival and proliferation. Although several SK1 selective inhibitors have been reported, detailed analysis toward their selectivity to understand the molecular mechanism has not been performed to our knowledge. Herein, the crystal structure of SK1 and a homology model of SK2 were used to dock five inhibitors (1, 2, 3, 4 and 5). Protein-ligand complexes were then subjected to a molecular dynamics study and MM-PBSA binding free energy calculations. By analyzing the binding model of these inhibitors, we found that residues ILE170, PHE188 and THR192 in SK1 significantly contribute a favorable binding energy to the selectivity.

Binding mechanisms of 1,4-dihydropyridine derivatives to L-type calcium channel Cav1.2: a molecular modeling study

L-type Ca²⁺channels (LTCCs), the heteromultimeric proteins, are associated with electrical signaling and provide the key link between electrical signals and non-electrical processes.

Molecular principle of the cyclin-dependent kinase selectivity of 4-(thiazol-5-yl)-2-(phenylamino) pyrimidine-5-carbonitrile derivatives revealed by molecular modeling studies

Due to the high sequence identity of the binding pockets of cyclin-dependent kinases (CDKs), designing highly selective inhibitors towards a specific CDK member remains a big challenge.

Structural identification of an HER2 receptor model binding pocket to optimize lead compounds: a combined experimental and computational approach

In silico methods and experimental data obtained from fluorescence studies allowed the identification of a new binding pocket for the HER2-DIVMP receptor model.

Study of novel pyrazolo[3,4-d]pyrimidine derivatives as selective TgCDPK1 inhibitors: molecular docking, structure-based 3D-QSAR and molecular dynamics simulation

We explored the structural features that have an impact on TgCDPK1 activity and TgCDPK1/Src selectivity by multi-computational methods with different statistical models.

Discovery of Novel ROCK1 Inhibitors via Integrated Virtual Screening Strategy and Bioassays

Rho-associated kinases (ROCKs) have been regarded as promising drug targets for the treatment of cardiovascular diseases, nervous system diseases and cancers. In this study, a novel integrated virtual screening protocol by combining molecular docking and pharmacophore mapping based on multiple ROCK1 crystal structures was utilized to screen the ChemBridge database for discovering potential inhibitors of ROCK1. Among the 38 tested compounds, seven of them exhibited significant inhibitory activities of ROCK1 (IC₅₀ < 10 μM) and the most potent one (compound TS-f22) with the novel scaffold of 4-Phenyl-1H-pyrrolo [2,3-b] pyridine had an IC₅₀ of 480 nM. Then, the structure-activity relationships of 41 analogues of TS-f22 were examined. Two potent inhibitors were proven effective in inhibiting the phosphorylation of the downstream target in the ROCK signaling pathway in vitro and protecting atorvastatin-induced cerebral hemorrhage in vivo. The high hit rate (28.95%) suggested that the integrated virtual screening strategy was quite reliable and could be used as a powerful tool for identifying promising active compounds for targets of interest.

In-silico modeling studies of G-quadruplex with soy isoflavones having anticancerous activity

Telomere forms t-loop and G-quadruplex as the protective structure and the formation of these structures hinder the telomerase enzyme action. The binding affinities of ligand which stabilize the G-quadruplex represent good correlation with telomerase inhibition depicted in the anti-cancerous action. Most of the potent G-quadruplex stabilizing compounds suffer from the poor drug like properties. Herein, natural dietary compounds isoflavones were taken for the theoretical study to examine their stabilizing effect on G-quadruplex structure. The experimental G-quadruplex complexes were reproduced to obtain and validate the theoretical parameters. The obtained theoretical binding energies are in significant correlation with the experimental data. Analysis of binding shows isoflavones to be groove binders, and differential nature of quadruplex grooves might be beneficial in the selectivity aspects. Among all, derrubone was found to have better selectivity as well as affinity for the G-quadruplex comparable to well known ligand TMPyP4. The GBSA rescoring result enlightens the various interaction terms involved in the binding process. Cumulative stabilizing effects coming from VDW, ES, and GB energy terms attest to optimal binding of derrubone molecule which can be considered as a lead for the higher phases of drug designing. These findings are of great value in terms of unexplored groove binding modes and the studied natural compounds might be helpful to direct the focus of synthetic chemists in designing of new generation of antitumor agents.

Structure-based Design of Peptides with High Affinity and Specificity to HER2 Positive Tumors

To identify peptides with high affinity and specificity against human epidermal growth factor receptor 2 (HER2), a series of peptides were designed based on the structure of HER2 and its Z(HER2:342) affibody. By using a combination protocol of molecular dynamics modeling, MM/GBSA binding free energy calculations, and binding free energy decomposition analysis, two novel peptides with 27 residues, pep27 and pep27-24M, were successfully obtained. Immunocytochemistry and flow cytometry analysis verified that both peptides can specifically bind to the extracellular domain of HER2 protein at cellular level. The Surface Plasmon Resonance imaging (SPRi) analysis showed that dissociation constants (K D) of these two peptides were around 300 nmol/L. Furthermore, fluorescence imaging of peptides against nude mice xenografted with SKBR3 cells indicated that both peptides have strong affinity and high specificity to HER2 positive tumors.

Study of the Binding Energies between Unnatural Amino Acids and Engineered Orthogonal Tyrosyl-tRNA Synthetases

We utilized several computational approaches to evaluate the binding energies of tyrosine (Tyr) and several unnatural Tyr analogs, to several orthogonal aaRSes derived from Methanocaldococcus jannaschii and Escherichia coli tyrosyl-tRNA synthetases. The present study reveals the following: (1) AutoDock Vina and ROSETTA were able to distinguish binding energy differences for individual pairs of favorable and unfavorable aaRS-amino acid complexes, but were unable to cluster together all experimentally verified favorable complexes from unfavorable aaRS-Tyr complexes; (2) MD-MM/PBSA provided the best prediction accuracy in terms of clustering favorable and unfavorable enzyme-substrate complexes, but also required the highest computational cost; and (3) MM/PBSA based on single energy-minimized structures has a significantly lower computational cost compared to MD-MM/PBSA, but still produced sufficiently accurate predictions to cluster aaRS-amino acid interactions. Although amino acid-aaRS binding is just the first step in a complex series of processes to acylate a tRNA with its corresponding amino acid, the difference in binding energy, as shown by MD-MM/PBSA, is important for a mutant orthogonal aaRS to distinguish between a favorable unnatural amino acid (unAA) substrate from unfavorable natural amino acid substrates. Our computational study should assist further designing and engineering of orthogonal aaRSes for the genetic encoding of novel unAAs.

Characterization of the Interaction between Gallic Acid and Lysozyme by Molecular Dynamics Simulation and Optical Spectroscopy

The binding interaction between gallic acid (GA) and lysozyme (LYS) was investigated and compared by molecular dynamics (MD) simulation and spectral techniques. The results from spectroscopy indicate that GA binds to LYS to generate a static complex. The binding constants and thermodynamic parameters were calculated. MD simulation revealed that the main driving forces for GA binding to LYS are hydrogen bonding and hydrophobic interactions. The root-mean-square deviation verified that GA and LYS bind to form a stable complex, while the root-mean-square fluctuation results showed that the stability of the GA-LYS complex at 298 K was higher than that at 310 K. The calculated free binding energies from the molecular mechanics/Poisson-Boltzmann surface area method showed that van der Waals forces and electrostatic interactions are the predominant intermolecular forces. The MD simulation was consistent with the spectral experiments. This study provides a reference for future study of the pharmacological mechanism of GA.

Curcumin specifically binds to the human calcium-calmodulin-dependent protein kinase IV: fluorescence and molecular dynamics simulation studies

Calcium-calmodulin-dependent protein kinase IV (CAMK4) plays significant role in the regulation of calcium-dependent gene expression, and thus, it is involved in varieties of cellular functions such as cell signaling and neuronal survival. On the other hand, curcumin, a naturally occurring yellow bioactive component of turmeric possesses wide spectrum of biological actions, and it is widely used to treat atherosclerosis, diabetes, cancer, and inflammation. It also acts as an antioxidant. Here, we studied the interaction of curcumin with human CAMK4 at pH 7.4 using molecular docking, molecular dynamics (MD) simulations, fluorescence binding, and surface plasmon resonance (SPR) methods. We performed MD simulations for both neutral and anionic forms of CAMK4-curcumin complexes for a reasonably long time (150 ns) to see the overall stability of the protein-ligand complex. Molecular docking studies revealed that the curcumin binds in the large hydrophobic cavity of kinase domain of CAMK4 through several hydrophobic and hydrogen-bonded interactions. Additionally, MD simulations studies contributed in understanding the stability of protein-ligand complex system in aqueous solution and conformational changes in the CAMK4 upon binding of curcumin. A significant increase in the fluorescence intensity at 495 nm was observed (λexc = 425 nm), suggesting a strong interaction of curcumin to the CAMK4. A high binding affinity (KD = 3.7 × 10(-8) ± .03 M) of curcumin for the CAMK4 was measured by SPR further indicating curcumin as a potential ligand for the CAMK4. This study will provide insights into designing a new inspired curcumin derivatives as therapeutic agents against many life-threatening diseases.

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

INTRODUCTION

The molecular mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor-ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success.

AREAS COVERED

The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications.

EXPERT OPINION

MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used successfully to reproduce and rationalize experimental findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approximations, for example, the lack of conformational entropy and information about the number and free energy of water molecules in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mechanical calculations, polarizable force fields or improved solvation have deteriorated the results.

Revealing the favorable dissociation pathway of type II kinase inhibitors via enhanced sampling simulations and two-end-state calculations

How does a type II inhibitor bind to/unbind from a kinase target is still a confusing question because the small molecule occupies both the ATP pocket and the allosteric pocket of the kinase binding site. Here, by using enhanced sampling simulations (umbrella sampling, US) and two-end-state free energy calculations (MM/GSBA), we systemically studied the dissociation processes of two distinct small molecules escaping from the binding pocket of p38 MAP kinase through the allosteric channel and the ATP channel. The results show that the unbinding pathways along the allosteric channel have much lower PMF depths than those along the ATP channel, suggesting that the allosteric channel is more favorable for the dissociations of the two inhibitors and thereby supporting the general understanding that the largest channel of a target is usually the entry/exit pathway for the binding/dissociation of small molecules. Interestingly, the MM/GBSA approach yielded similar PMF profiles compared with those based on US, a much time consuming approach, indicating that for a general study, such as detecting the important transition state of a ligand binding/unbinding process, MM/GBSA may be a feasible choice.