Homo-timeric structural model of human microsomal prostaglandin E synthase-1 and characterization of its substrate/inhibitor binding interactions

Inducible, microsomal prostaglandin E synthase 1 (mPGES-1), the terminal enzyme in the prostaglandin (PG) biosynthetic pathway, constitutes a promising therapeutic target for the development of new anti-inflammatory drugs. To elucidate structure–function relationships and to enable structure-based design, an mPGES-1 homology model was developed using the three-dimensional structure of the closest homologue of the MAPEG family (Membrane Associated Proteins in Eicosanoid and Glutathione metabolism), mGST-1. The ensuing model of mPGES-1 is a homo-trimer, with each monomer consisting of four membrane-spanning segments. Extensive structure refinement revealed an inter-monomer salt bridge (K26-E77) as well as inter-helical interactions within each monomer, including polar hydrogen bonds (e.g. T78-R110-T129) and hydrophobic π-stacking (F82-F103-F106), all contributing to the overall stability of the homo-trimer of mPGES-1. Catalytic co-factor glutathione (GSH) was docked into the mPGES-1 model by flexible optimization of both the ligand and the protein conformations, starting from the initial location ascertained from the mGST-1 structure. Possible binding site for the substrate, prostaglandin H₂ (PGH₂), was identified by systematically probing the refined molecular structure of mPGES-1. A binding model was generated by induced fit docking of PGH₂ in the presence of GSH. The homology model prescribes three potential inhibitor binding sites per mPGES-1 trimer. This was further confirmed experimentally by equilibrium dialysis study which generated a binding stoichiometric ratio of approximately three inhibitor molecules to three mPGES-1 monomers. The structural model that we have derived could serve as a useful tool for structure-guided design of inhibitors for this emergently important therapeutic target.     

Understanding microscopic binding of human microsomal prostaglandin E synthase-1 with substrates and inhibitors by molecular modeling and dynamics simulation

Microsomal prostaglandin E synthase-1 (mPGES-1) is a promising target for development of next-generation anti-inflammatory drugs. It is crucial for rational design of the next-generation anti-inflammatory drugs to know the three-dimensional (3D) structure of mPGES-1 trimer and to understand how mPGES-1 binds with substrates and inhibitors. In the current work, a 3D structural model of human mPGES-1 trimer has been developed, for the first time, by performing combined homology modeling, molecular docking, and molecular dynamics simulation. The 3D structural model enables us to understand how mPGES-1 binds with its substrates/inhibitors, and the key amino acid residues for the mPGES-1 binding with ligands have been identified. The detailed 3D structures and calculated binding free energies for mPGES-1's binding with substrates and inhibitors are all consistent with available experimental data, suggesting that the 3D model of the mPGES-1 trimer and the enzyme-ligand binding modes are reasonable. The new structural insights obtained from this study should be valuable for rational design of next-generation anti-inflammatory drugs.     

Identification of the quinolinedione inhibitor binding site in Cdc25 phosphatase B through docking and molecular dynamics simulations

Cdc25 phosphatase B, a potential target for cancer therapy, is inhibited by a series of quinones. The binding site and mode of quinone inhibitors to Cdc25B remains unclear, whereas this information is important for structure-based drug design. We investigated the potential binding site of NSC663284 [DA3003-1 or 6-chloro-7-(2-morpholin-4-yl-ethylamino)-quinoline-5, 8-dione] through docking and molecular dynamics simulations. Of the two main binding sites suggested by docking, the molecular dynamics simulations only support one site for stable binding of the inhibitor. Binding sites in and near the Cdc25B catalytic site that have been suggested previously do not lead to stable binding in 50 ns molecular dynamics (MD) simulations. In contrast, a shallow pocket between the C-terminal helix and the catalytic site provides a favourable binding site that shows high stability. Two similar binding modes featuring protein-inhibitor interactions involving Tyr428, Arg482, Thr547 and Ser549 are identified by clustering analysis of all stable MD trajectories. The relatively flexible C-terminal region of Cdc25B contributes to inhibitor binding. The binding mode of NSC663284, identified through MD simulation, likely prevents the binding of protein substrates to Cdc25B. The present results provide useful information for the design of quinone inhibitors and their mechanism of inhibition.     

Influence of protonation on substrate and inhibitor interactions at the active site of human monoamine oxidase-A

Although substrate conversion mediated by human monoaminooxidase (hMAO) has been associated with the deprotonated state of their amine moiety, data regarding the influence of protonation on substrate binding at the active site are scarce. Thus, in order to assess protonation influence, steered molecular dynamics (SMD) runs were carried out. These simulations revealed that the protonated form of the substrate serotonin (5-HT) exhibited stronger interactions at the protein surface compared to the neutral form. The latter displayed stronger interactions in the active site cavity. These observations support the possible role of the deprotonated form in substrate conversion. Multigrid docking studies carried out to rationalize the role of 5-HT protonation in other sites besides the active site indicated two energetically favored docking sites for the protonated form of 5-HT on the enzyme surface. These sites seem to be interconnected with the substrate/inhibitor cavity, as revealed by the tunnels observed by means of CAVER program. pK(a) calculations in the surface loci pointed to Glu32?, Asp32?, His???, and Asp132 as candidates for a possible in situ deprotonation step. Docking analysis of a group of inhibitors (structurally related to substrates) showed further interactions with the same two docking access sites. Interestingly, the protonated/deprotonated amine moiety of almost all compounds attained different docking poses in the active site, none of them oriented to the flavin moiety, thus producing a more variable and less productive orientations to act as substrates. Our results highlight the role of deprotonation in facilitating substrate conversion and also might reflect the necessity of inhibitor molecules to adopt specific orientations to achieve enzyme inhibition.     

Modeling Steroid 5alpha-reductase and Characterizing Its Potential Active Sites

Steroid 5alpha-reductase of human is an enzyme in the biosynthetic pathway from testosterone (T) to dihydrotestosterone (DHT). Up to now, no crystal structure of this enzyme has been reported. However, knowledge of the tertiary structure and possible active sites is essential for understanding the catalysis mechanism and for the design of inhibitors. A model with putative active sites has been created and evaluated by using homology modeling and molecular docking techniques based on the bioinformatics knowledge. The homology model is optimized in Swiss PDB Viewer with MM method and substrate structures before docking are also optimized on HF/6-31G. The active site for the docking of NADP, T, DHT and Finasteride is located near the N-terminus of enzyme. Four active amino acids in the active site are identified as Ala26, Arg53, Arg176 and Lys177. Reaction procedure, binding pattern of active sites, the types of weak interaction and so on are also discussed.     

Investigation of binding features: Effects on the interaction between CYP2A6 and inhibitors

A computational investigation has been carried out on CYP2A6 and its naphthalene inhibitors to explore the crucial molecular features contributing to binding specificity. The molecular bioactive orientations were obtained by docking (FlexX) these compounds into the active site of the enzyme. And the density functional theory method was further used to optimize the molecular structures with the subsequent analysis of molecular lipophilic potential (MLP) and molecular electrostatic potential (MEP). The minimal MLPs, minimal MEPs, and the band gap energies (the energy difference between the highest occupied molecular orbital and lowest unoccupied molecular orbital) showed high correlations with the inhibition activities (pIC₅₀s), illustrating their significant roles in driving the inhibitor to adopt an appropriate bioactive conformation oriented in the active site of CYP2A6 enzyme. The differences in MLPs, MEPs, and the orbital energies have been identified as key features in determining the binding specificity of this series of compounds to CYP2A6 and the consequent inhibitory effects. In addition, the combinational use of the docking, MLP and MEP analysis is also demonstrated as a good attempt to gain an insight into the interaction between CYP2A6 and its inhibitors. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Studying enzyme binding specificity in acetylcholinesterase using a combined molecular dynamics and multiple docking approach

A combined molecular dynamics simulation and multiple ligand docking approach is applied to study the binding specificity of acetylcholinesterase (AChE) with its natural substrate acetylcholine (ACh), a family of substrate analogues, and choline. Calculated docking energies are well correlated to experimental k(cat)/K(M) values, as well as to experimental binding affinities of a related series of TMTFA inhibitors. The "esteratic" and "anionic" subsites are found to act together to achieve substrate binding specificity. We find that the presence of ACh in the active site of AChE not only stabilizes the setup of the catalytic triad but also tightens both subsites to achieve better binding. The docking energy gained from this induced fit is 0.7 kcal/mol for ACh. For the binding of the substrate tailgroup to the anionic subsite, both the size and the positive charge of the tailgroup are important. The removal of the positive charge leads to a weaker binding of 1 kcal/mol loss in docking energy. Substituting each tail methyl group with hydrogen results in both an incremental loss in docking energy and also a decrease in the percentage of structures docked in the active site correctly set up for catalysis.     

Allostery Inhibition of BACE1 by Psychotic and Meroterpenoid Drugs in Alzheimer’s Disease Therapy

In over a century since its discovery, Alzheimer’s disease (AD) has continued to be a global health concern due to its incurable nature and overwhelming increase among older people. In this paper, we give an overview of the efforts of researchers towards identifying potent BACE1 exosite-binding antibodies and allosteric inhibitors. Herein, we apply computer-aided drug design (CADD) methods to unravel the interactions of some proposed psychotic and meroterpenoid BACE1 allosteric site inhibitors. This study is aimed at validating the allosteric potentials of these selected compounds targeted at BACE1 inhibition. Molecular docking, molecular dynamic (MD) simulations, and post-MD analyses are carried out on these selected compounds, which have been experimentally proven to exhibit allosteric inhibition on BACE1. The SwissDock software enabled us to identify more than five druggable pockets on the BACE1 structural surface using docking. Besides the active site region, a melatonin derivative (compound 1) previously proposed as a BACE1 allostery inhibitor showed appreciable stability at eight different subsites on BACE1. Refinement with molecular dynamic (MD) simulations shows that the identified non-catalytic sites are potential allostery sites for compound 1. The allostery and binding mechanism of the selected potent inhibitors show that the smaller the molecule, the easier the attachment to several enzyme regions. This finding hereby establishes that most of these selected compounds failed to exhibit strong allosteric binding with BACE1 except for compound 1. We hereby suggest that further studies and additional identification/validation of other BACE1 allosteric compounds be done. Furthermore, this additional allosteric site investigation will help in reducing the associated challenges with designing BACE1 inhibitors while exploring the opportunities in the design of allosteric BACE1 inhibitors.     

Use of MM-PBSA in reproducing the binding free energies to HIV-1 RT of TIBO derivatives and predicting the binding mode to HIV-1 RT of efavirenz by docking and MM-PBSA.

In this work, a new ansatz is presented that combines molecular dynamics simulations with MM-PBSA (Molecular Mechanics Poisson-Boltzmann/surface area) to rank the binding affinities of 12 TIBO-like HIV-1 RT inhibitors. Encouraging results have been obtained not only for the relative binding free energies, but also for the absolute ones, which have a root-mean-square deviation of 1.0 kcal/mol (the maximum error is 1.89 kcal/mol). Since the root-mean-square error is rather small, this approach can be reliably applied in ranking the ligands from the databases for this important target. Encouraged by the results, we decided to apply MM-PBSA combined with molecular docking to determine the binding mode of efavirenz SUSTIVA(TM) another promising HIV-1 RT inhibitor for which no ligand-protein crystal structure had been published at the time of this work. To proceed, we define the following ansatz: Five hundred picosecond molecular dynamics simulations were first performed for the five binding modes suggested by DOCK 4.0, and then MM-PBSA was carried out for the collected snapshots. MM-PBSA successfully identified the correct binding mode, which has a binding free energy about 7 kcal/mol more favorable than the second best mode. Moreover, the calculated binding free energy (-13.2 kcal/mol) is in reasonable agreement with experiment (-11.6 kcal/mol). In addition, this procedure was also quite successful in modeling the complex and the structure of the last snapshot was quite close to that of the measured 2,3 A resolution crystal (structure the root-mean-square deviation of the 54 C(alpha) around the binding site and the inhibitor is 1.1 A). We want to point out that this result was achieved without prior knowledge of the structure of the efavirenz/RT complex. Therefore, molecular docking combined with MD simulations followed by MM-PBSA analysis is an attractive approach for modeling protein complexes a priori.     

QSAR analyses on avian influenza virus neuraminidase inhibitors using CoMFA, CoMSIA, and HQSAR

The recent wide spreading of the H5N1 avian influenza virus (AIV) in Asia, Europe and Africa and its ability to cause fatal infections in human has raised serious concerns about a pending global flu pandemic. Neuraminidase (NA) inhibitors are currently the only option for treatment or prophylaxis in humans infected with this strain. However, drugs currently on the market often meet with rapidly emerging resistant mutants and only have limited application as inadequate supply of synthetic material. To dig out helpful information for designing potent inhibitors with novel structures against the NA, we used automated docking, CoMFA, CoMSIA, and HQSAR methods to investigate the quantitative structure-activity relationship for 126 NA inhibitors (NIs) with great structural diversities and wide range of bioactivities against influenza A virus. Based on the binding conformations discovered via molecular docking into the crystal structure of NA, CoMFA and CoMSIA models were successfully built with the cross-validated q (2) of 0.813 and 0.771, respectively. HQSAR was also carried out as a complementary study in that HQSAR technique does not require 3D information of these compounds and could provide a detailed molecular fragment contribution to the inhibitory activity. These models also show clearly how steric, electrostatic, hydrophobicity, and individual fragments affect the potency of NA inhibitors. In addition, CoMFA and CoMSIA field distributions are found to be in well agreement with the structural characteristics of the corresponding binding sites. Therefore, the final 3D-QSAR models and the information of the inhibitor-enzyme interaction should be useful in developing novel potent NA inhibitors.     

取代脱氧脲苷的量子化学计算及分子对接

5取代6氮杂2’脱氧脲苷是一类疱疹单纯一型病毒胸苷激酶(ＨＳＶ1ＴＫ)抑制剂.研究此类化合物的合成、结构、杀菌活性及构效关系一直为科学界所关注[1-3].ＨＳＶ1ＴＫ可以催化胸苷的磷酸化反应,使生成胸苷磷酸脂,在ＤＮＡ合成的控制中起着重要的作用.其晶体结构的发表[4],使得我们能从分子水平上研究此类酶抑制剂与酶活性中心的作用机制,模拟其作用方式,从而实现ＨＳＶ1ＴＫ抑制剂的全新设计.本文从化合物(Ｉ)和(ＩＩ)(见图1)晶体结构出发,使用美国Ｔｒｉｐｏｓ公司开发的三维分子模拟软件包ＳＹＢＹＬ63[5],采用ＭＯＰＡＣ界面中ＰＭ3[6]程…     

Protein-protein binding sites prediction by 3D structural similarities

Identifying the location of binding sites on proteins is of fundamental importance for a wide range of applications including molecular docking, de novo drug design, structure identification, and comparison of functional sites. In this paper, we develop an efficient approach for finding binding sites between proteins. Our approach consists of four steps: local sequence alignment, protein surface detection, 3D structure comparison, and candidate binding site selection. A comparison of our method with the LSA algorithm shows that the binding sites predicted by our method are somewhat closer to the actual binding sites in the protein-protein complexes. The software package is available at http://sites.google.com/site/guofeics/pro-bs for noncommercial use.     

Understanding the inhibitory effect of highly potent and selective archazolides binding to the vacuolar ATPase

Vacuolar ATPases are a potential therapeutic target because of their involvement in a variety of severe diseases such as osteoporosis or cancer. Archazolide A (1) and related analogs have been previously identified as selective inhibitors of V-ATPases with potency down to the subnanomolar range. Herein we report on the determination of the ligand binding mode by a combination of molecular docking, molecular dynamics simulations, and biochemical experiments, resulting in a sound model for the inhibitory mechanism of this class of putative anticancer agents. The binding site of archazolides was confirmed to be located in the equatorial region of the membrane-embedded V(O)-rotor, as recently proposed on the basis of site-directed mutagenesis. Quantification of the bioactivity of a series of archazolide derivatives, together with the docking-derived binding mode of archazolides to the V-ATPase, revealed favorable ligand profiles, which can guide the development of a simplified archazolide analog with potential therapeutic relevance.     

Human microsomal prostaglandin E synthase-1 (mPGES-1) binding with inhibitors and the quantitative structure-activity correlation

The detailed structures of microsomal prostaglandin E synthase-1 (mPGES-1) binding with inhibitors have been studied, for the first time, by using a newly developed computational three-dimensional (3D) structural model of mPGES-1 along with a 3D-quantitative structure--activity relationship (3D-QSAR) analysis. The obtained satisfactory binding structures and 3D-QSAR models strongly suggest that the 3D structural model of mPGES-1 is reasonable for study of mPGES-1 binding with inhibitors and for future design of novel mPGES-1 inhibitors.     

Exploring a model of a chemokine receptor/ligand complex in an explicit membrane environment by molecular dynamics simulation: the human CCR1 receptor

The seven transmembrane helices G-protein-coupled receptors (GPCRs) form one of the largest superfamilies of signaling proteins found in humans. Homology modeling, molecular docking, and molecular dynamics (MD) simulation were carried out to construct a reliable model for CCR1 as one of the GPCRs and to explore the structural features and the binding mechanism of BX471 as one of the most potent CCR1 inhibitors. In this study, BX471 has been docked into the active site of the CCR1 protein. After docking, one 20 ns MD simulation was performed on the CCR1-ligand complex to explore effects of the presence of lipid membrane in the vicinity of the CCR1-ligand complex. At the end of the MD simulation, a change in the position and orientation of the ligand in the binding site was observed. This important observation indicated that the application of MD simulation after docking of ligands is useful. Explorative runs of molecular dynamics simulation on the receptor-ligand complex revealed that except for Phe85, Phe112, Tyr113, and Ile259, the rest of the residues in the active site determined by docking are changed. The results obtained are in good agreement with most of the experimental data reported by others. Our results show that molecular modeling and rational drug design for chemokine targets is a possible approach.     

Pose prediction accuracy in docking studies and enrichment of actives in the active site of GSK-3beta

We present molecular docking studies on the inhibitors of GSK-3beta kinase in the enzyme binding sites of the X-ray complexes (1H8F, 1PYX, 1O9U, 1Q4L, 1Q5K, and 1UV5) using the Schr?dinger docking tool Glide. Cognate and cross-docking studies using standard precision (SP) and extraprecision (XP) algorithms have been carried out. Cognate docking studies demonstrate that docked poses similar to X-ray poses (root-mean-square deviations of less than 2 A) are found within the top four ranks of the GlideScore and E-model scores. However, cross-docking studies typically produce poses that are significantly deviated from X-ray poses in all but a couple of cases, implying potential for induced fit effects in ligand binding. In this light, we have also carried out induced fit docking studies in the active sites of 1O9U, 1Q4L, and 1Q5K. Specifically, conformational changes have been effected in the active sites of these three protein structures to dock noncognate ligands. Thus, for example, the active site of 1O9U has been induced to fit the ligands of 1Q4L, 1Q5K, and 1UV5. These studies produce ligand docked poses which have significantly lower root-mean-square deviations relative to their X-ray crystallographic poses, when compared to the corresponding values from the cross-docking studies. Furthermore, we have used an ensemble of the induced fit models and X-ray structures to enhance the retrieval of active GSK-3beta inhibitors seeded in a decoy database, normally used in Glide validation studies. Thus, our studies provide valuable insights into computational strategies useful for the identification of potential GSK-3beta inhibitors.     

Structure-based design, synthesis, and in vitro evaluation of bisubstrate inhibitors for catechol O-methyltransferase (COMT)

The enzyme catechol O-methyltransferase (COMT) catalyzes the Me group transfer from the cofactor S-adenosylmethionine (SAM) to the hydroxy group of catechol substrates. Potential bisubstrate inhibitors of COMT were developed by structure-based design and synthesized. The compounds were tested for in vitro inhibitory activity against COMT obtained from rat liver, and the inhibition kinetics were examined with regard to the binding sites of cofactor and substrate. One of the designed molecules was found to be a bisubstrate inhibitor of COMT with an IC50 = 2 microM. It exhibits competitive kinetics for the SAM and noncompetitive kinetics for the catechol binding site. Useful structure-activity relationships were established which provide important guidelines for the design of future generations of bisubstrate inhibitors of COMT.     

Probing the dynamic nature of water molecules and their influences on ligand binding in a model binding site

The model binding site of the cytochrome c peroxidase (CCP) W191G mutant is used to investigate the structural and dynamic properties of the water network at the buried cavity using computational methods supported by crystallographic analysis. In particular, the differences of the hydration pattern between the uncomplexed state and various complexed forms are analyzed as well as the differences between five complexes of CCP W191G with structurally closely related ligands. The ability of docking programs to correctly handle the water molecules in these systems is studied in detail. It is found that fully automated prediction of water replacement or retention upon docking works well if some additional preselection is carried out but not necessarily if the entire water network in the cavity is used as input. On the other hand, molecular interaction fields for water calculated from static crystal structures and hydration density maps obtained from molecular dynamics simulations agree very well with crystallographically observed water positions. For one complex, the docking and MD results sensitively depend on the quality of the starting structure, and agreement is obtained only after redetermination of the crystal structure and refinement at higher resolution.