Understanding microscopic binding of macrophage migration inhibitory factor with phenolic hydrazones by molecular docking, molecular dynamics simulations and free energy calculations

Macrophage migration inhibitory factor (MIF), an immunoregulatory protein, is a potential target for a number of inflammatory diseases. In the current work, the interactions between MIF and a series of phenolic hydrazones were studied by molecular docking, molecular dynamics (MD) simulations, binding free energy calculations, and binding energy decomposition analysis to determine the structural requirement for achieving favorable biological activity of phenolic hydrazones. First, molecular docking was used to predict the binding modes of inhibitors in the binding site of MIF. The good correlation between the predicted docking scores and the experimental activities shows that the binding conformations of the inhibitors in the active site of MIF are well predicted. Moreover, our results suggest that the flexibility of MIF is essential in ligand binding process. Then, MD simulations and MM/GBSA free energy calculations were employed to determine the dynamic binding process and compare the binding modes of the inhibitors with different activities. The predicted binding free energies given by MM/GBSA are not well correlated with the experimental activities for the two subsets of the inhibitors; however, for each subset, a good correlation between the predicted binding free energies and the experimental activities is achieved. The MM/GBSA free energy decomposition analysis highlights the importance of hydrophobic residues for the MIF binding of the studied inhibitors. Based on the essential factors for MIF-inhibitor interactions derived from the theoretical predictions, some derivatives were designed and the higher inhibitory activities of several candidates were confirmed by molecular docking studies. The structural insights obtained from our study are useful for designing potent inhibitors of MIF.     

Refined models of New Delhi metallo-beta-lactamase-1 with inhibitors: an QM/MM modeling study

New Delhi metallo-beta-lactamase 1 (NDM-1) has been identified as a potential target for the treatment of multi-drug resistance bacterial infections. We used molecular docking, normal MD, SIE, QM/MM MD simulations, QM/MM GBSA binding free energy, and QM/MM GBSA alanine-scanning mutagenesis techniques to investigate interactions of the NDM-1 with 11 inhibitors (Tigecycline, BAL30072, D-captopril, Penicillin G, Ampicillin, Carbenicillin, Cephalexin, Cefaclor, Nitrocefin, Meropenem, and Imipenem). From our normal MD and QM/MM simulations, the correlation coefficients between the predicted binding free energies and experimental values are .88 and .93, respectively. Then simulations, which combined QM/MM/GBSA and alanine-scanning mutagenesis techniques, were performed and our results show that two residues (Lys211 and His250) have the strongest impact on the binding affinities of the 11 NDM-1/inhibitors. Therefore, our approach theoretically suggests that the two residues (Lys211 and His250) are responsible for the selectivity of NDM-1 associated inhibitors.     

Intermolecular insights into allosteric inhibition of histone lysine-specific demethylase 1

BackgroundHistone lysine-specific demethylase 1 (LSD1) has become a potential anticancer target for the novel drug discovery. Recent reports have shown that SP2509 and its derivatives strongly inhibit LSD1 as allosteric inhibitors. However, the binding mechanism of these allosteric inhibitors in the allosteric site of LSD1 is not known yet.MethodsThe stability and binding mechanism of allosteric inhibitors in the binding site of LSD1 were evaluated by molecular docking, ligand-based pharmacophore, molecular dynamics (MD) simulations, molecular mechanics generalized born surface area (MM/GBSA) analysis, quantum mechanics/molecular mechanics (QM/MM) calculation and Hirshfeld surface analysis.ResultsThe conformational geometry and the intermolecular interactions of allosteric inhibitors showed high binding affinity towards allosteric site of LSD1 with the neighboring amino acids (Gly358, Cys360, Leu362, Asp375 and Glu379). Meanwhile, MD simulations and MM/GBSA analysis were performed on selected allosteric inhibitors in complex with LSD1 protein, which confirmed the high stability and binding affinity of these inhibitors in the allosteric site of LSD1.ConclusionThe simulation results revealed the crucial factors accounting for allosteric inhibitors of LSD1, including different protein–ligand interactions, the positions and conformations of key residues, and the ligands flexibilities. Meanwhile, a halogen bond interaction between chlorine atom of ligand and key residues Trp531 and His532 was recurrent in our analysis confirming its importance.General significanceOverall, our research analyzed in depth the binding modes of allosteric inhibitors with LSD1 and could provide useful information for the design of novel allosteric inhibitors.     

Comparison of end-point continuum-solvation methods for the calculation of protein-ligand binding free energies

We have compared the predictions of ligand‐binding affinities from several methods based on end‐point molecular dynamics simulations and continuum solvation, that is, methods related to MM/PBSA (molecular mechanics combined with Poisson–Boltzmann and surface area solvation). Two continuum‐solvation models were considered, viz., the Poisson–Boltzmann (PB) and generalised Born (GB) approaches. The nonelectrostatic energies were also obtained in two different ways, viz., either from the sum of the bonded, van der Waals, nonpolar solvation energies, and entropy terms (as in MM/PBSA), or from the scaled protein–ligand van der Waals interaction energy (as in the linear interaction energy approach, LIE). Three different approaches to calculate electrostatic energies were tested, viz., the sum of electrostatic interaction energies and polar solvation energies, obtained either from a single simulation of the complex or from three independent simulations of the complex, the free protein, and the free ligand, or the linear‐response approximation (LRA). Moreover, we investigated the effect of scaling the electrostatic interactions by an effective internal dielectric constant of the protein (?_int). All these methods were tested on the binding of seven biotin analogues to avidin and nine 3‐amidinobenzyl‐1H‐indole‐2‐carboxamide inhibitors to factor Xa. For avidin, the best results were obtained with a combination of the LIE nonelectrostatic energies with the MM+GB electrostatic energies from a single simulation, using ?_int = 4. For fXa, standard MM/GBSA, based on one simulation and using ?_int = 4–10 gave the best result. The optimum internal dielectric constant seems to be slightly higher with PB than with GB solvation. © Proteins 2012; © 2012 Wiley Periodicals, Inc.     

Thermodynamics calculation of protein–ligand interactions by QM/MM polarizable charge parameters

The calculation of protein–ligand binding free energy (ΔG) is of great importance for virtual screening and drug design. Molecular dynamics (MD) simulation has been an attractive tool to investigate this scientific problem. However, the reliability of such approach is affected by many factors including electrostatic interaction calculation. Here, we present a practical protocol using quantum mechanics/molecular mechanics (QM/MM) calculations to generate polarizable QM protein charge (QMPC). The calculated QMPC of some atoms in binding pockets was obviously different from that calculated by AMBER ff03, which might significantly affect the calculated ΔG. To evaluate the effect, the MD simulations and MM/GBSA calculation with QMPC for 10 protein–ligand complexes, and the simulation results were then compared to those with the AMBER ff03 force field and experimental results. The correlation coefficient between the calculated ΔΔG using MM/GBSA under QMPC and the experimental data is .92, while that with AMBER ff03 force field is .47 for the complexes formed by streptavidin or its mutants and biotin. Moreover, the calculated ΔΔG with QMPC for the complexes formed by ERβ and five ligands is positively related to experimental result with correlation coefficient of .61, while that with AMBER ff03 charge is negatively related to experimental data with correlation coefficient of .42. The detailed analysis shows that the electrostatic polarization introduced by QMPC affects the electrostatic contribution to the binding affinity and thus, leads to better correlation with experimental data. Therefore, this approach should be useful to virtual screening and drug design.     

Structure‐guided screening of chemical database to identify NS3‐NS2B inhibitors for effective therapeutic application in dengue infection

Dengue infection is the most common arthropod‐borne disease caused by dengue viruses, predominantly affecting millions of human beings annually. To find out promising chemical entities for therapeutic application in Dengue, in the current research, a multi‐step virtual screening effort was conceived to screen out the entire “screening library” of the Asinex database. Initially, through “Lipinski rule of five” filtration criterion almost 0.6 million compounds were collected and docked with NS3‐NS2B protein. Thereby, the chemical space was reduced to about 3500 compounds through the analysis of binding affinity obtained from molecular docking study in AutoDock Vina. Further, the “Virtual Screening Workflow” (VSW) utility of Schrödinger suite was used, which follows a stepwise multiple docking programs such as ‐ high‐throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) docking, and in postprocessing analysis the MM‐GBSA based free binding energy calculation. Finally, five potent molecules were proposed as potential inhibitors for the dengue NS3‐NS2B protein based on the investigation of molecular interactions map and protein‐ligand fingerprint analyses. Different pharmacokinetics and drug‐likeness parameters were also checked, which favour the potentiality of selected molecules for being drug‐like candidates. The molecular dynamics (MD) simulation analyses of protein‐ligand complexes were explained that NS3‐NS2B bound with proposed molecules quite stable in dynamic states as observed from the root means square deviation (RMSD) and root means square fluctuation (RMSF) parameters. The binding free energy was calculated using MM‐GBSA method from the MD simulation trajectories revealed that all proposed molecules possess such a strong binding affinity towards the dengue NS3‐NS2B protein. Therefore, proposed molecules may be potential chemical components for effective inhibition of dengue NS3‐NS2B protein subjected to experimental validation.     

Are different stoichiometries feasible for complexes between lymphotoxin-alpha and tumor necrosis factor receptor 1?

Background

Tumor necrosis factors, TNF and lymphotoxin-?? (LT), are cytokines that bind to two receptors, TNFR1 and TNFR2 (TNF-receptor 1 and 2) to trigger their signaling cascades. The exact mechanism of ligand-induced receptor activation is still unclear. It is generally assumed that three receptors bind to the homotrimeric ligand to trigger a signaling event. Recent evidence, though, has raised doubts if the ligand:receptor stoichiometry should indeed be 3:3 for ligand-induced cellular response. We used molecular dynamics simulations, elastic network models, as well as MM/PBSA to analyze this question.

Results

Applying MM/PBSA methodology to different stoichiometric complexes of human LT-(TNFR1)_n=1,2,3 the free energy of binding in these complexes has been estimated by single-trajectory and separate-trajectory methods. Simulation studies rationalized the favorable binding energy in the LT-(TNFR1)₁ complex, as evaluated from single-trajectory analysis to be an outcome of the interaction of cysteine-rich domain 4 (CRD4) and the ligand. Elastic network models (ENMs) help to associate the difference in the global fluctuation of the receptors in these complexes. Functionally relevant transformation associated with these complexes reveal the difference in the dynamics of the receptor when free and in complex with LT.

Conclusions

MM/PBSA predicts complexes with a ligand-receptor molar ratio of 3:1 and 3:2 to be energetically favorable. The high affinity associated with LT-(TNFR1)₁ is due to the interaction between the CRD4 domain with LT. The global dynamics ascertained from ENMs have highlighted the differential dynamics of the receptor in different states.     

Highlighting a π–π interaction: a protein modeling and molecular dynamics simulation study on Anopheles gambiae glutathione S-transferase 1-2

Cytosolic insect theta class glutathione S-transferases (GSTs) have not been studied completely and their physiological roles are unknown. A detailed understanding of Anopheles gambiae GST (Aggst1-2) requires an accurate structure, which has not yet been determined. A high quality model structure of Aggst1-2 was constructed using homology modeling and the ligand–protein complex was obtained by the docking method. Molecular dynamics (MD) simulations were carried out to study conformational changes and to calculate binding free energy. The results of MD simulation indicate that Aggst1-2 undergoes small conformational changes after ligands dock to the protein, which facilitate the catalytic reaction. An essential hydrogen bond was found between the sulfur atom of glutathione (GSH) and the hydrogen atom of hydroxyl group in Ser9, which was in good agreement with experimental data. A π–π interaction between Phe204 and CDNB ligand was also found. This interaction seems to be important in stabilization of the ligand. Further study of binding free energy decomposition revealed a van der Waals interaction between two ligands that may play a key role in nucleophilic addition reaction. This work will be a good starting point for further determination of the biological role of cytosolic insect theta class GSTs and will aid the design of structure-based inhibitors.     

Evaluation of potential flavonoid inhibitors of glyoxalase-I based on virtual screening and in vitro studies

Glyoxalase-I (GLO-I) is a component of the ubiquitous detoxification system involved in the conversion of methylglyoxal (MG) to d-lactate in the glycolytic pathway. MG toxicity arises from its ability to form advanced glycation end products. GLO-I has been reported to be frequently overexpressed in various types of cancer cells. In this study, we performed structure-based virtual screening of focused flavonoids commercial library to identify potential and specific inhibitors of GLO-I. The compounds were ranked based on Glide extra precision docking score and five hits (curcumin, quercetin, morin, naringin and silibinin) were selected on the basis of their interaction with active site amino acid residues of GLO-I. Mixed mode QM/MM calculation was performed on the top-scoring hit to ascertain the role of zinc ion in ligand binding. In addition, the identified hits were subjected to MM/GBSA binding energy prediction, ADME prediction and similarity studies. The hits were tested in vitro for cell viability, and GLO-I inhibition. Naringin (ST072162) was found to be most potent inhibitor of GLO-I among the identified hits with highest glide XP dock score of ?14.906. These findings suggest that naringin could be a new scaffold for designing inhibitors against GLO-I with potential application as anticancer agents.     

Insight into the binding modes and inhibition mechanisms of adamantyl-based 1,3-disubstituted urea inhibitors in the active site of the human soluble epoxide hydrolase

Soluble epoxide hydrolase (sEH) is a promising new target for treating hypertension and inflammation. Considerable efforts have been devoted to develop novel inhibitors. In this study, the binding modes and interaction mechanisms of a series of adamantyl-based 1,3-disubstituted urea inhibitors were investigated by molecular docking, molecular dynamics simulations, binding free energy calculations, and binding energy decomposition analysis. Based on binding affinity, the most favorable binding mode was determined for each inhibitor. The calculation results indicate that the total binding free energy (ΔG_TOT, the sum of enthalpy ΔG_MM-GB/SA, and entropy ?TΔS) presents a good correlation with the experimental inhibitory activity (IC₅₀, r²?=?.99). The van der Waals energy contributes most to the total binding free energy (ΔG_TOT). A detailed discussion on the interactions between inhibitors and those residues located in the active pocket is made based on hydrogen bond and binding modes analysis. According to binding energy decomposition, the residues Asp333 and Trp334 contribute the most to binding free energy in all systems. Furthermore, Hip523 plays a major role in determining this class of inhibitor-binding orientations. Combined with the results of hydrogen bond analysis and binding free energy, we believe that the conserved hydrogen bonds play a role only in anchoring the inhibitors to the exact site for binding and the number of hydrogen bonds may not directly relate to the binding free energy. The results we obtained will provide valuable information for the design of high potency sEH inhibitors.     

Influence of Chirality of Crizotinib on Its MTH1 Protein Inhibitory Activity: Insight from Molecular Dynamics Simulations and Binding Free Energy Calculations

As a promising target for the treatment of lung cancer, the MutT Homolog 1 (MTH1) protein can be inhibited by crizotinib. A recent work shows that the inhibitory potency of (S)-crizotinib against MTH1 is about 20 times over that of (R)-crizotinib. But the detailed molecular mechanism remains unclear. In this study, molecular dynamics (MD) simulations and free energy calculations were used to elucidate the mechanism about the effect of chirality of crizotinib on the inhibitory activity against MTH1. The binding free energy of (S)-crizotinib predicted by the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Adaptive biasing force (ABF) methodologies is much lower than that of (R)-crizotinib, which is consistent with the experimental data. The analysis of the individual energy terms suggests that the van der Waals interactions are important for distinguishing the binding of (S)-crizotinib and (R)-crizotinib. The binding free energy decomposition analysis illustrated that residues Tyr7, Phe27, Phe72 and Trp117 were important for the selective binding of (S)-crizotinib to MTH1. The adaptive biasing force (ABF) method was further employed to elucidate the unbinding process of (S)-crizotinib and (R)-crizotinib from the binding pocket of MTH1. ABF simulation results suggest that the reaction coordinates of the (S)-crizotinib from the binding pocket is different from (R)-crizotinib. The results from our study can reveal the details about the effect of chirality on the inhibition activity of crizotinib to MTH1 and provide valuable information for the design of more potent inhibitors.     

Discovery of VEGFR inhibitors through virtual screening and energy assessment

Vascular endothelial growth factor receptor-2 (VEGFR-2) is crucial in promoting tumor angiogenesis and cancer metastasis. Thus, inhibition of VEGFR-2 has appeared as a good tactic for cancer treatment. To find out novel VEGFR-2 inhibitors, first, the PDB structure of VEGFR-2, 6GQO, was selected based on atomic nonlocal environment assessment (ANOLEA) and PROCHECK assessment. 6GQO was then further used for structure-based virtual screening (SBVS) of different molecular databases, including US-FDA approved drugs, US-FDA withdrawn drugs, may bridge, MDPI, and Specs databases using Glide. Based on SBVS, receptor fit, drug-like filters, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of 427877 compounds, the best 22 hits were selected. From the 22 hits, hit 5 complex with 6GQO was put through molecular mechanics/generalized born surface area (MM/GBSA) study and hERG binding. The MM/GBSA study revealed that hit 5 possesses lesser binding free energy with more inferior stability in the receptor pocket than the reference compound. The VEGFR-2 inhibition assay of hit 5 disclosed an IC₅₀ of 165.23 nM against VEGFR-2, which can be possibly enhanced through structural modifications.     

Binding selectivity studies of PKBα using molecular dynamics simulation and free energy calculations

Designing selective protein kinase B (PKB/Akt) inhibitor is an area of intense research to develop potential anticancer drugs. In the present study, the molecular basis governing PKB-selective inhibition has been investigated using molecular dynamics simulation. The binding free energies calculated by MM/PBSA gave a good correlation with the experimental biological activity and a good explanation of the activity difference of the studied inhibitors. The decomposition of free energies by MM/GBSA indicates that the ethyl group on pyrrolo[2,3-d]pyrimidine ring of inhibitor Lig1 (N-{[(3S)-3-amino-1-(5-ethyl-7H-pyrrolo[2,3-d]pyrimidin-4-yl)pyrrolidin-3-yl]-methyl}-2,4-difluoro-benzamide) is an important contributor to its PKBα selectivity due to its hydrophobic interaction with the side chain of Thr291 in PKBα. The substituted groups on the pyrrolidine ring of Lig1 also show a strong tendency to mediate protein-ligand interactions through the hydrogen bonds formed between the amino or amide groups of Lig1 and the carboxyl O atoms of Glu234, Glu278, and Asp292 of PKBα. It was reported that there are only three key amino acid differences between PKBα (Thr211, Ala230, Met281) and PKA (Val104, Val123, Leu173) within the clefts of ATP-binding sites. These differences propel a drastic conformational change in PKA, weakening its binding interactions with inhibitor. The impact was also confirmed by MD simulated interaction modes of inhibitor binding to PKBα mutants with the in silico mutations of the three key amino acids, respectively. We expect that the results obtained here could be useful for future rational design of specific ATP-competitive inhibitors of PKBα.     

Molecular modeling study of the opioid receptor interactions with series of cyclic deltorphin analogues

In this study, ten tetra‐ and heptapeptide analogues of deltorphin containing the urea bridges between residues 2 and 4 have been docked into the δ‐ and µ‐opioid receptors to explain their different biological activities. The important factors explaining particular ligand activity such as free energy of binding, conformation of the ligand, its location inside the binding pocket as well as the number and strength of the receptor–ligand interactions have been discussed. Several different binding modes for investigated ligands have been proposed. It appears that the binding site is not identical even for very similar ligands. Results of this study help to explain the differences in biological activity of the deltorphin analogues, their interaction with the opioid receptors at the molecular level and support designing a new generation of potent opioid drugs with improved selectivity. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.     

Computational investigation of the HIV-1 Rev multimerization using molecular dynamics simulations and binding free energy calculations

The HIV Rev protein mediates the nuclear export of viral mRNA, and is thereby essential for the production of late viral proteins in the replication cycle. Rev forms a large organized multimeric protein-protein complex for proper functioning. Recently, the three-dimensional structures of a Rev dimer and tetramer have been resolved and provide the basis for a thorough structural analysis of the binding interaction. Here, molecular dynamics (MD) and binding free energy calculations were performed to elucidate the forces thriving dimerization and higher order multimerization of the Rev protein. It is found that despite the structural differences between each crystal structure, both display a similar behavior according to our calculations. Our analysis based on a molecular mechanics-generalized Born surface area (MM/GBSA) and a configurational entropy approach demonstrates that the higher order multimerization site is much weaker than the dimerization site. In addition, a quantitative hot spot analysis combined with a mutational analysis reveals the most contributing amino acid residues for protein interactions in agreement with experimental results. Additional residues were found in each interface, which are important for the protein interaction. The investigation of the thermodynamics of the Rev multimerization interactions performed here could be a further step in the development of novel antiretrovirals using structure based drug design. Moreover, the variability of the angle between each Rev monomer as measured during the MD simulations suggests a role of the Rev protein in allowing flexibility of the arginine rich domain (ARM) to accommodate RNA binding.     

Molecular docking study and development of an empirical binding free energy model for phosphodiesterase 4 inhibitors

In the present work, several computational methodologies were combined to develop a model for the prediction of PDE4B inhibitors' activity. The adequacy of applying the ligand docking approach, keeping the enzyme rigid, to the study of a series of PDE4 inhibitors was confirmed by a previous molecular dynamics analysis of the complete enzyme. An exhaustive docking procedure was performed to identify the most probable binding modes of the ligands to the enzyme, including the active site metal ions and the surrounding structural water molecules. The enzyme-inhibitor interaction enthalpies, refined by using the semiempirical molecular orbital approach, were combined with calculated solvation free energies and entropy considerations in an empirical free energy model that enabled the calculation of binding free energies that correlated very well with experimentally derived binding free energies. Our results indicate that both the inclusion of the structural water molecules close to the ions in the binding site and the use of a free energy model with a quadratic dependency on the ligand free energy of solvation are important aspects to be considered for molecular docking investigations involving the PDE4 enzyme family.     

Understanding the molecular basis of MK2-p38α signaling complex assembly: insights into protein-protein interaction by molecular dynamics and free energy studies

The formation of a p38 MAPK and MAPK-activated protein kinase 2 (MK2) signaling complex is physiologically relevant to cellular responses such as the proinflammatory cytokine production. The interaction between p38α isoform and MK2 is of great importance for this signaling. In this study, molecular dynamics simulation and binding free energy calculation were performed on the MK2-p38α signaling complex to investigate the protein-protein interaction between the two proteins. Dynamic domain motion analyses were performed to analyze the conformational changes between the unbound and bound states of proteins during the interaction. The activation loop, αF-I helices, and loops among α helices in the C-lobe of MK2 are found to be highly flexible and exhibit significant changes upon p38α binding. The results also show that after the binding of p38α, the N- and C-terminal domains of MK2 display an opening and twisting motion centered on the activation loop. The molecular mechanics Poisson-Boltzmann and generalized-Born surface area (MM-PB/GBSA) methods were used to calculate binding free energies between MK2 and p38α. The analysis of the components of binding free energy calculation indicates that the van der Waals interaction and the nonpolar solvation energy provide the driving force for the binding process, while the electrostatic interaction contributes critically to the specificity, rather than to MK2-p38α binding affinity. The contribution of each residue at the interaction interface to the binding affinity of MK2 with p38α was also analyzed by free energy decomposition. Several important residues responsible for the protein-protein interaction were also identified.