Energy transduction and alternating access of the mammalian ABC transporter P-glycoprotein.

ATP binding cassette (ABC) transporters of the exporter class harness the energy of ATP hydrolysis in the nucleotide-binding domains (NBDs) to power the energetically uphill efflux of substrates by a dedicated transmembrane domain (TMD). Although numerous investigations have described the mechanism of ATP hydrolysis and defined the architecture of ABC exporters, a detailed structural dynamic understanding of the transduction of ATP energy to the work of substrate translocation remains elusive. Here we used double electron-electron resonance and molecular dynamics simulations to describe the ATP- and substrate-coupled conformational cycle of the mouse ABC efflux transporter P-glycoprotein (Pgp; also known as ABCB1), which has a central role in the clearance of xenobiotics and in cancer resistance to chemotherapy. Pairs of spin labels were introduced at residues selected to track the putative inward-facing to outward-facing transition. Our findings illuminate how ATP energy is harnessed in the NBDs in a two-stroke cycle and elucidate the consequent conformational motion that reconfigures the TMD, two critical aspects of Pgp transport mechanism. Along with a fully atomistic model of the outward-facing conformation in membranes, the insight into Pgp conformational dynamics harmonizes mechanistic and structural data into a novel perspective on ATP-coupled transport and reveals mechanistic divergence within the efflux class of ABC transporters.

Mass spectrometry-based cross-linking study shows that the Psb28 protein binds to cytochrome b559 in Photosystem II.

Photosystem II (PSII), a large pigment protein complex, undergoes rapid turnover under natural conditions. During assembly of PSII, oxidative damage to vulnerable assembly intermediate complexes must be prevented. Psb28, the only cytoplasmic extrinsic protein in PSII, protects the RC47 assembly intermediate of PSII and assists its efficient conversion into functional PSII. Its role is particularly important under stress conditions when PSII damage occurs frequently. Psb28 is not found, however, in any PSII crystal structure, and its structural location has remained unknown. In this study, we used chemical cross-linking combined with mass spectrometry to capture the transient interaction of Psb28 with PSII. We detected three cross-links between Psb28 and the α- and ß-subunits of cytochrome b559, an essential component of the PSII reaction-center complex. These distance restraints enable us to position Psb28 on the cytosolic surface of PSII directly above cytochrome b559, in close proximity to the QB site. Protein-protein docking results also support Psb28 binding in this region. Determination of the Psb28 binding site and other biochemical evidence allow us to propose a mechanism by which Psb28 exerts its protective effect on the RC47 intermediate. This study also shows that isotope-encoded cross-linking with the "mass tags" selection criteria allows confident identification of more cross-linked peptides in PSII than has been previously reported. This approach thus holds promise to identify other transient protein-protein interactions in membrane protein complexes.

The cellular membrane as a mediator for small molecule interaction with membrane proteins.

The cellular membrane constitutes the first element that encounters a wide variety of molecular species to which a cell might be exposed. Hosting a large number of structurally and functionally diverse proteins associated with this key metabolic compartment, the membrane not only directly controls the traffic of various molecules in and out of the cell, it also participates in such diverse and important processes as signal transduction and chemical processing of incoming molecular species. In this article, we present a number of cases where details of interaction of small molecular species such as drugs with the membrane, which are often experimentally inaccessible, have been studied using advanced molecular simulation techniques. We have selected systems in which partitioning of the small molecule with the membrane constitutes a key step for its final biological function, often binding to and interacting with a protein associated with the membrane. These examples demonstrate that membrane partitioning is not only important for the overall distribution of drugs and other small molecules into different compartments of the body, it may also play a key role in determining the efficiency and the mode of interaction of the drug with its target protein. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Binding Site Recognition and Docking Dynamics of a Single Electron Transport Protein: Cytochrome c2.

Small diffusible redox proteins facilitate electron transfer in respiration and photosynthesis by alternately binding to their redox partners and integral membrane proteins and exchanging electrons. Diffusive search, recognition, binding, and unbinding of these proteins often amount to kinetic bottlenecks in cellular energy conversion, but despite the availability of structures and intense study, the physical mechanisms controlling redox partner interactions remain largely unknown. The present molecular dynamics study provides an all-atom description of the cytochrome c2-docked bc1 complex in Rhodobacter sphaeroides in terms of an ensemble of favorable docking conformations and reveals an intricate series of conformational changes that allow cytochrome c2 to recognize the bc1 complex and bind or unbind in a redox state-dependent manner. In particular, the role of electron transfer in triggering a molecular switch and in altering water-mediated interface mobility, thereby strengthening and weakening complex formation, is described. The results resolve long-standing discrepancies between structural and functional data.

New insights in the activation of human cholesterol esterase to design potent anti-cholesterol drugs.

Primary hypercholesterolemia is the root cause for major health issues like coronary heart disease and atherosclerosis. Regulating plasma cholesterol level, which is the product of biosynthesis as well as dietary intake, has become one of the major therapeutic strategies to effectively control these diseases. Human cholesterol esterase (hCEase) is an interesting target involved in the regulation of plasma cholesterol level and thus inhibition of this enzyme is highly effective in the treatment of hypercholesterolemia. This study was designed to understand the activation mechanism that enables the enzyme to accommodate long chain fatty acids and to identify the structural elements for the successful catalysis. Primarily the activation efficiencies of three different bile salts were studied and compared using molecular dynamics simulations. Based on the conformations of major surface loops, hydrogen bond interactions, and distance analyses, taurocholate was concluded as the preferred activator of the enzyme. Furthermore, the importance of two bile salt binding sites (proximal and remote) and the crucial role of 7α-OH group of the bile salts in the activation of hCEase was examined and evidenced. The results of our study explain the structural insights of the activation mechanism and show the key features of the bile salts responsible for the enzyme activation which are very useful in hypolipidemic drug designing strategies.

Potent BACE-1 inhibitor design using pharmacophore modeling, in silico screening and molecular docking studies.

BACKGROUND: Beta-site amyloid precursor protein cleaving enzyme (BACE-1) is a single-membrane protein belongs to the aspartyl protease class of catabolic enzymes. This enzyme involved in the processing of the amyloid precursor protein (APP). The cleavage of APP by BACE-1 is the rate-limiting step in the amyloid cascade leading to the production of two peptide fragments Aß40 and Aß42. Among two peptide fragments Aß42 is the primary species thought to be responsible for the neurotoxicity and amyloid plaque formation that lead to memory and cognitive defects in Alzheimer's disease (AD). AD is a ravaging neurodegenerative disorder for which no disease-modifying treatment is currently available. Inhibition of BACE-1 is expected to stop amyloid plaque formation and emerged as an interesting and attractive therapeutic target for AD. METHODS: Ligand-based computational approach was used to identify the molecular chemical features required for the inhibition of BACE-1 enzyme. A training set of 20 compounds with known experimental activity was used to generate pharmacophore hypotheses using 3D QSAR Pharmacophore Generation module available in Discovery studio. The hypothesis was validated by four different methods and the best hypothesis was utilized in database screening of four chemical databases like Maybridge, Chembridge, NCI and Asinex. The retrieved hit compounds were subjected to molecular docking study using GOLD 4.1 program. RESULTS: Among ten generated pharmacophore hypotheses, Hypo 1 was chosen as best pharmacophore hypothesis. Hypo 1 consists of one hydrogen bond donor, one positive ionizable, one ring aromatic and two hydrophobic features with high correlation coefficient of 0.977, highest cost difference of 121.98 bits and lowest RMSD value of 0.804. Hypo 1 was validated using Fischer randomization method, test set with a correlation coefficient of 0.917, leave-one-out method and decoy set with a goodness of hit score of 0.76. The validated Hypo 1 was used as a 3D query in database screening and retrieved 773 compounds with the estimated activity value <100 nM. These hits were docked into the active site of BACE-1 and further refined based on molecular interactions with the essential amino acids and good GOLD fitness score. CONCLUSION: The best pharmacophore hypothesis, Hypo 1, with high predictive ability contains chemical features required for the effective inhibition of BACE-1. Using Hypo 1, we have identified two compounds with diverse chemical scaffolds as potential virtual leads which, as such or upon further optimization, can be used in the designing of new BACE-1 inhibitors.

Development, evaluation and application of 3D QSAR Pharmacophore model in the discovery of potential human renin inhibitors.

BACKGROUND: Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study. METHODS: Ligand-based quantitative pharmacophore modeling methodology was used in identifying the important molecular chemical features present in the set of already known active compounds and the missing features from the set of inactive compounds. A training set containing 18 compounds including active and inactive compounds with a substantial degree of diversity was used in developing the pharmacophore models. A test set containing 93 compounds, Fischer randomization, and leave-one-out methods were used in the validation of the pharmacophore model. Database screening was performed using the best pharmacophore model as a 3D structural query. Molecular docking and density functional theory calculations were used to select the hit compounds with strong molecular interactions and favorable electronic features. RESULTS: The best quantitative pharmacophore model selected was made of one hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptor features with high a correlation value of 0.944. Upon validation using an external test set of 93 compounds, Fischer randomization, and leave-one-out methods, this model was used in database screening to identify chemical compounds containing the identified pharmacophoric features. Molecular docking and density functional theory studies have confirmed that the identified hits possess the essential binding characteristics and electronic properties of potent inhibitors. CONCLUSION: A quantitative pharmacophore model of predictive ability was developed with essential molecular features of a potent renin inhibitor. Using this pharmacophore model, two potential inhibitory leads were identified to be used in designing novel and future renin inhibitors as antihypertensive drugs.

Molecular docking and pharmacophore filtering in the discovery of dual-inhibitors for human leukotriene A4 hydrolase and leukotriene C4 synthase.

Combination of drugs for multiple targets has been a standard treatment in treating various diseases. A single chemical entity that acts upon multiple targets is emerging nowadays because of their predictable pharmacokinetic and pharmacodynamic properties. We have employed a computer-aided methodology combining molecular docking and pharmacophore filtering to identify chemical compounds that can simultaneously inhibit the human leukotriene hydrolase (hLTA4H) and the human leukotriene C4 synthase (hLTC4S) enzymes. These enzymes are the members of arachidonic acid pathway and act upon the same substrate, LTA4, producing different inflammatory products. A huge set of 4966 druglike compounds from the Maybridge database were docked into the active site of hLTA4H using the GOLD program. Common feature pharmacophore models were developed from the known inhibitors of both the targets using Accelrys Discovery Studio 2.5. The hits from the hLTA4H docking were filtered to match the chemical features of both the pharmacophore models. The compounds that resulted from the pharmacophore filtering were docked into the active site of hLTC4S and the hits those bind well at both the active sites and matched the pharmacophore models were identified as possible dual inhibitors for hLTA4H and hLTC4S enzymes. Reverse validation was performed to ensure the results of the study.

Discovery of potential pancreatic cholesterol esterase inhibitors using pharmacophore modelling, virtual screening, and optimization studies.

Pancreatic cholesterol esterase (CEase) is a serine hydrolase involved in the hydrolysis of variety of lipids and transport of free cholesterol. In this study, pharmacophore hypotheses based on known inhibitors were generated using common feature pharmacophore generation protocol available in Discovery Studio program. The best pharmacophore model containing two hydrogen bond acceptor and three hydrophobic features was selected and validated. It was further used in screening three diverse chemical databases. Hit compounds were subjected to drug-likeness and molecular docking studies. Four hits, namely SEW00846, NCI0040784, GK03167, and CD10645, were selected based on the GOLD fitness score and interaction with active site amino acids. All hit compounds were further optimized to improve their binding in the active site. The optimized compounds were found to have improved binding at the active site. Strongly binding optimized hits at the active site can act as virtual leads in potent CEase inhibitor designing.

Dynamic structure-based pharmacophore model development: a new and effective addition in the histone deacetylase 8 (HDAC8) inhibitor discovery.

Histone deacetylase 8 (HDAC8) is an enzyme involved in deacetylating the amino groups of terminal lysine residues, thereby repressing the transcription of various genes including tumor suppressor gene. The over expression of HDAC8 was observed in many cancers and thus inhibition of this enzyme has emerged as an efficient cancer therapeutic strategy. In an effort to facilitate the future discovery of HDAC8 inhibitors, we developed two pharmacophore models containing six and five pharmacophoric features, respectively, using the representative structures from two molecular dynamic (MD) simulations performed in Gromacs 4.0.5 package. Various analyses of trajectories obtained from MD simulations have displayed the changes upon inhibitor binding. Thus utilization of the dynamically-responded protein structures in pharmacophore development has the added advantage of considering the conformational flexibility of protein. The MD trajectories were clustered based on single-linkage method and representative structures were taken to be used in the pharmacophore model development. Active site complimenting structure-based pharmacophore models were developed using Discovery Studio 2.5 program and validated using a dataset of known HDAC8 inhibitors. Virtual screening of chemical database coupled with drug-like filter has identified drug-like hit compounds that match the pharmacophore models. Molecular docking of these hits reduced the false positives and identified two potential compounds to be used in future HDAC8 inhibitor design.

3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors.

Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating "Hypo1", it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC(50)) data thus successfully validating "Hypo1" by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors.

Adaptable Small Ligand of CYP1 Enzymes for Use in Understanding the Structural Features Determining Isoform Selectivity.

Although several families of compounds have been identified as scaffolds for inhibitors of the CYP1 family, the isoform selectivity determining structural features has not been fully clarified at the molecular interaction level. We studied the CYP1 isoform selectivity for stilbenoid inhibitors using integrated induced fit docking and molecular dynamics simulations. The hydrophobic interactions with the specific phenylalanine residues in the F helix are correlated with inhibitory potency in the CYP1 family. Through this study, we found that the adaptable, small, and semirigid ligand is a promising starting point for the development of isoform-selective inhibitors and investigation of selectivity-determining features.

QSAR modeling to design selective histone deacetylase 8 (HDAC8) inhibitors.

HDAC8 inhibitors have become an attractive treatment for cancer. This study aimed to facilitate the identification of potential chemical scaffolds for the selective inhibition of histone deacetylase 8 (HDAC8) using in silico approaches. Non-linear QSAR classification and regression models of HDAC8 inhibitors were developed with support vector machine. Mean impact value-based sequential forward feature selection and grid search strategy were used for molecular descriptor selection and parameter optimization, respectively. The generated QSAR models were validated by leave-one-out cross validation and an external test set. The best QSAR classification model yielded 84 % of accuracy on the external test prediction and Matthews correlation coefficient is 0.69. The best QSAR regression model showed low root-mean-square error (0.63) and high squared correlation coefficient (0.53) for the test set. The validated QSAR models together with various drug-like properties, molecular docking and molecular dynamics simulation were sequentially used as a multi-step query in chemical database virtual screening. Finally, two hit compounds were discovered as new structural scaffolds which can be used for further in vitro and in vivo activity analyses. The strategy used in this study could be a promising computational strategy which can be utilized for other target drug design.

Molecular dynamics simulations of sonic hedgehog-receptor and inhibitor complexes and their applications for potential anticancer agent discovery.

The sonic hedgehog (Shh) signaling pathway is necessary for a variety of development and differentiation during embryogenesis as well as maintenance and renascence of diverse adult tissues. However, an abnormal activation of the signaling pathway is related to various cancers. In this pathway, the Shh signaling transduction is facilitated by binding of Shh to its receptor protein, Ptch. In this study, we modeled the 3D structure of functionally important key loop peptides of Ptch based on homologous proteins. Using this loop model, the molecular interactions between the structural components present in the pseudo-active site of Shh and key residues of Ptch was investigated in atomic level through molecular dynamics (MD) simulations. For the purpose of developing inhibitor candidates of the Shh signaling pathway, the Shh pseudo-active site of this interface region was selected as a target to block the direct binding between Shh and Ptch. Two different structure-based pharmacophore models were generated considering the key loop of Ptch and known inhibitor-induced conformational changes of the Shh through MD simulations. Finally two hit compounds were retrieved through a series of virtual screening combined with molecular docking simulations and we propose two hit compounds as potential inhibitory lead candidates to block the Shh signaling pathway based on their strong interactions to receptor or inhibitor induced conformations of the Shh.

Development of predictive quantitative structure-activity relationship model and its application in the discovery of human leukotriene A4 hydrolase inhibitors.

BACKGROUND: Human LTA4H catalyzes the conversion of LTA4 to LTB4 and plays a key role in innate immune responses. Inhibition of this enzyme can be a valid method in the treatment of inflammatory response exhibited through LTB4. RESULTS & DISCUSSION: The quantitative structure-activity relationship (QSAR) models were developed using genetic function approximation and validated. A training set of 26 diverse compounds and their molecular descriptors were used to develop highly correlating QSAR models. A six-descriptor model explaining the biological activity of the training and test sets with correlation values of 0.846 and 0.502, respectively, was selected as the best model and used in a database screening of drug-like Maybridge database followed by molecular docking. CONCLUSION: Based on the predicted potent inhibitory activities, expected binding mode and molecular interactions at the active site of hLTA4H final leads were selected as to be utilized in designing future hLTA4H inhibitors.

Multi-conformation dynamic pharmacophore modeling of the peroxisome proliferator-activated receptor γ for the discovery of novel agonists.

Activation of the peroxisome proliferator-activated receptor γ (PPARγ) is important for the treatment of type 2 diabetes and obesity through the regulation of glucose metabolism and fatty acid accumulation. Hence, the discovery of novel PPARγ agonists is necessary to overcome these diseases. In this study, a newly developed approach, multi-conformation dynamic pharmacophore modeling (MCDPM), was used for screening candidate compounds that can properly bind PPARγ. Highly populated structures obtained from molecular dynamics (MD) simulations were selected by clustering analysis. Based on these structures, pharmacophore models were generated from the ligand-binding pocket and then validated to check the rationality. Consequently, two hits were retrieved as final candidates by utilizing virtual screening and molecular docking simulations. These compounds can be used in the design of novel PPARγ agonists.

Molecular dynamics simulation study explaining inhibitor selectivity in different class of histone deacetylases.

Histone deacetylases (HDACs) are key regulators of gene expression and thereby compelling targets in the treatment of various cancers. Class- and isoform-selective HDAC inhibitors targeting the particular isoform to treat cancers without affecting the normal expression of other isoforms are highly desirable. Molecular dynamics simulations were performed with the set of selective inhibitors and HDAC isoforms of three different classes. The results were compared both within and across the isoforms. The hydrogen bonds between protein and inhibitors are directly correlated with the selective experimental activity. The calculated distances between important amino acids and the metal binding part of inhibitors have disclosed the optimal distance to be maintained by a selective inhibitor. In addition, the calculated non-bonded interaction energies between inhibitor and catalytic residues revealed that the subtle difference in the amino acids at the highly conserved active sites of HDAC isoforms effectively scripts the selectivity story observed experimentally. The results of this study provide valuable information in designing highly selective HDAC inhibitors.

Pharmacophore modeling, molecular docking, and molecular dynamics simulation approaches for identifying new lead compounds for inhibiting aldose reductase 2.

Aldose reductase 2 (ALR2), which catalyzes the reduction of glucose to sorbitol using NADP as a cofactor, has been implicated in the etiology of secondary complications of diabetes. A pharmacophore model, Hypo1, was built based on 26 compounds with known ALR2-inhibiting activity values. Hypo1 contains important chemical features required for an ALR2 inhibitor, and demonstrates good predictive ability by having a high correlation coefficient (0.95) as well as the highest cost difference (128.44) and the lowest RMS deviation (1.02) among the ten pharmacophore models examined. Hypo1 was further validated by Fisher's randomization method (95%), test set (r = 0.91), and the decoy set shows the goodness of fit (0.70). Furthermore, during virtual screening, Hypo1 was used as a 3D query to screen the NCI database, and the hit leads were sorted by applying Lipinski's rule of five and ADME properties. The best-fitting leads were subjected to docking to identify a suitable orientation at the ALR2 active site. The molecule that showed the strongest interactions with the critical amino acids was used in molecular dynamics simulations to calculate its binding affinity to the candidate molecules. Thus, Hypo1 describes the key structure-activity relationship along with the estimated activities of ALR2 inhibitors. The hit molecules were searched against PubChem to find similar molecules with new scaffolds. Finally, four molecules were found to satisfy all of the chemical features and the geometric constraints of Hypo1, as well as to show good dock scores, PLPs and PMFs. Thus, we believe that Hypo1 facilitates the selection of novel scaffolds for ALR2, allowing new classes of ALR2 inhibitors to be designed.

Ligand-based virtual screening and molecular docking studies to identify the critical chemical features of potent cathepsin D inhibitors.

Cathepsin D is a major component of lysosomes and plays a major role in catabolism and degenerative diseases. The quantitative structure-activity relationship study was used to explore the critical chemical features of cathepsin D inhibitors. Top 10 hypotheses were built based on 36 known cathepsin D inhibitors using HypoGen/Discovery Studio v2.5. The best hypothesis Hypo1 consists of three hydrophobic, one hydrogen bond acceptor lipid, and one hydrogen bond acceptor features. The selected Hypo1 model was cross-validated using Fischer's randomization method to identify the strong correlation between experimental and predicted activity value as well as the test set and decoy sets used to validate its predictability. Moreover, the best hypothesis was used as a 3D query in virtual screening of Scaffold database. Subsequently, the screened hit molecules were filtered by applying Lipinski's rule of five, absorption, distribution, metabolism, and toxicity, and molecular docking studies. Finally, 49 compounds were obtained as potent cathepsin D inhibitors based on the consensus scoring values, critical interactions with protein active site residues, and predicted activity values. Thus, we suggest that the application of Hypo1 could assist in the selection of potent cathepsin D leads from various databases. Hence, this model was used as a valuable tool to design new candidate for cathepsin D inhibitors.

Potential human cholesterol esterase inhibitor design: benefits from the molecular dynamics simulations and pharmacophore modeling studies.

Human pancreatic cholesterol esterase (hCEase) is one of the lipases found to involve in the digestion of large and broad spectrum of substrates including triglycerides, phospholipids, cholesteryl esters, etc. The presence of bile salts is found to be very important for the activation of hCEase. Molecular dynamic simulations were performed for the apoform and bile salt complexed form of hCEase using the co-ordinates of two bile salts from bovine CEase. The stability of the systems throughout the simulation time was checked and two representative structures from the highly populated regions were selected using cluster analysis. These two representative structures were used in pharmacophore model generation. The generated pharmacophore models were validated and used in database screening. The screened hits were refined for their drug-like properties based on Lipinski's rule of five and ADMET properties. The drug-like compounds were further refined by molecular docking simulation using GOLD program based on the GOLD fitness score, mode of binding, and molecular interactions with the active site amino acids. Finally, three hits of novel scaffolds were selected as potential leads to be used in novel and potent hCEase inhibitor design. The stability of binding modes and molecular interactions of these final hits were re-assured by molecular dynamics simulations.