Computational Approaches for Decoding Select Odorant-Olfactory Receptor Interactions Using Mini-Virtual Screening

PubMed Central

Harini, K.; Sowdhamini, Ramanathan

2015-01-01

Olfactory receptors (ORs) belong to the class A G-Protein Coupled Receptor superfamily of proteins. Unlike G-Protein Coupled Receptors, ORs exhibit a combinatorial response to odors/ligands. ORs display an affinity towards a range of odor molecules rather than binding to a specific set of ligands and conversely a single odorant molecule may bind to a number of olfactory receptors with varying affinities. The diversity in odor recognition is linked to the highly variable transmembrane domains of these receptors. The purpose of this study is to decode the odor-olfactory receptor interactions using in silico docking studies. In this study, a ligand (odor molecules) dataset of 125 molecules was used to carry out in silico docking using the GLIDE docking tool (SCHRODINGER Inc Pvt LTD). Previous studies, with smaller datasets of ligands, have shown that orthologous olfactory receptors respond to similarly-tuned ligands, but are dramatically different in their efficacy and potency. Ligand docking results were applied on homologous pairs (with varying sequence identity) of ORs from human and mouse genomes and ligand binding residues and the ligand profile differed among such related olfactory receptor sequences. This study revealed that homologous sequences with high sequence identity need not bind to the same/ similar ligand with a given affinity. A ligand profile has been obtained for each of the 20 receptors in this analysis which will be useful for expression and mutation studies on these receptors. PMID:26221959

Molecular Docking Studies of Catechin and Its Derivatives as Anti-bacterial Inhibitor for Glucosamine-6-Phosphate Synthase

NASA Astrophysics Data System (ADS)

Fikrika, H.; Ambarsari, L.; Sumaryada, T.

2016-01-01

Molecular docking simulation of catechin and its derivatives on Glucosamine-6- Phosphate Synthase (GlmS) has been performed in this research. GlmS inhibition by a particular ligand will suppress the production of bacterial cell wall and significantly reduce the population of invading bacteria. In this study, catechin derivatives i.e epicatechin, galloatechin and epigalloatechin were found to have stronger binding affinities as compared to natural ligand of GlmS, Fructose-6-Phosphate (F6P). Those three ligands were docked on the same pocket in GlmS target as F6P, with 70% binding sites similarity. Based on the docking results, gallocatechin turns out to be the most potent ligand for anti-bacterial agent with ΔG= -8.00 kcal/mol. The docking between GlmS and catechin derivatives are characterized by a constant present of a strong hydrogen bond between functional group O3 and Ser-349. This hydrogen bond most likely plays a significant role in the docking mechanism and binding modes selection. The surprising result is catechin itself exhibited a quite strong binding with GlmS (ΔG= -7.80 kcal.mol), but docked on a completely different pocket compared to other ligands. This results suggest that catechin might still have a curing effect but with a completely different pathway and mechanism as compared to its derivatives.

Knowledge-Guided Docking of WW Domain Proteins and Flexible Ligands

NASA Astrophysics Data System (ADS)

Lu, Haiyun; Li, Hao; Banu Bte Sm Rashid, Shamima; Leow, Wee Kheng; Liou, Yih-Cherng

Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling. We present a knowledge-guided approach for docking protein domains and flexible ligands. The approach is applied to the WW domain, a small protein module mediating signaling complexes which have been implicated in diseases such as muscular dystrophy and Liddle’s syndrome. The first stage of the approach employs a substring search for two binding grooves of WW domains and possible binding motifs of peptide ligands based on known features. The second stage aligns the ligand’s peptide backbone to the two binding grooves using a quasi-Newton constrained optimization algorithm. The backbone-aligned ligands produced serve as good starting points to the third stage which uses any flexible docking algorithm to perform the docking. The experimental results demonstrate that the backbone alignment method in the second stage performs better than conventional rigid superposition given two binding constraints. It is also shown that using the backbone-aligned ligands as initial configurations improves the flexible docking in the third stage. The presented approach can also be applied to other protein domains that involve binding of flexible ligand to two or more binding sites.

Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

PubMed

Brylinski, Michal

2013-11-25

A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. In this communication, we describe eSimDock, a new approach to ligand docking and binding affinity prediction. eSimDock employs nonlinear machine learning-based scoring functions to improve the accuracy of ligand ranking and similarity-based binding pose prediction, and to increase the tolerance to structural imperfections in the target structures. In large-scale benchmarking using the Astex/CCDC data set, we show that 53.9% (67.9%) of the predicted ligand poses have RMSD of <2 Å (<3 Å). Moreover, using binding sites predicted by recently developed eFindSite, eSimDock models ligand binding poses with an RMSD of 4 Å for 50.0-39.7% of the complexes at the protein homology level limited to 80-40%. Simulations against non-native receptor structures, whose mean backbone rearrangements vary from 0.5 to 5.0 Å Cα-RMSD, show that the ratio of docking accuracy and the estimated upper bound is at a constant level of ∼0.65. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. Finally, two case studies demonstrate that eSimDock can be customized to specific applications as well. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models. eSimDock is freely available to the academic community as a Web server at http://www.brylinski.org/esimdock .

[Supercomputer investigation of the protein-ligand system low-energy minima].

PubMed

Oferkin, I V; Sulimov, A V; Katkova, E V; Kutov, D K; Grigoriev, F V; Kondakova, O A; Sulimov, V B

2015-01-01

The accuracy of the protein-ligand binding energy calculations and ligand positioning is strongly influenced by the choice of the docking target function. This work demonstrates the evaluation of the five different target functions used in docking: functions based on MMFF94 force field and functions based on PM7 quantum-chemical method accounting or without accounting the implicit solvent model (PCM, COSMO or SGB). For these purposes the ligand positions corresponding to the minima of the target function and the experimentally known ligand positions in the protein active site (crystal ligand positions) were compared. Each function was examined on the same test-set of 16 protein-ligand complexes. The new parallelized docking program FLM based on Monte Carlo search algorithm was developed to perform the comprehensive low-energy minima search and to calculate the protein-ligand binding energy. This study demonstrates that the docking target function based on the MMFF94 force field can be used to detect the crystal or near crystal positions of the ligand by the finding the low-energy local minima spectrum of the target function. The importance of solvent accounting in the docking process for the accurate ligand positioning is also shown. The accuracy of the ligand positioning as well as the correlation between the calculated and experimentally determined protein-ligand binding energies are improved when the MMFF94 force field is substituted by the new PM7 method with implicit solvent accounting.

Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening

NASA Astrophysics Data System (ADS)

Zavodszky, Maria I.; Sanschagrin, Paul C.; Kuhn, Leslie A.; Korde, Rajesh S.

2002-12-01

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen-bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S-transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a ˜15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.

AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility

PubMed Central

Ravindranath, Pradeep Anand; Forli, Stefano; Goodsell, David S.; Olson, Arthur J.; Sanner, Michel F.

2015-01-01

Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1) exponential growth of the search space, demanding more efficient search methods; and 2) increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR–AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1) SEQ17 –a receptor diversity set containing 17 pairs of apo-holo structures; and 2) CDK2 –a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added. PMID:26629955

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms.

PubMed

Sulimov, Alexey V; Zheltkov, Dmitry A; Oferkin, Igor V; Kutov, Danil C; Katkova, Ekaterina V; Tyrtyshnikov, Eugene E; Sulimov, Vladimir B

2017-01-01

We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.

Ligand- and receptor-based docking with LiBELa

NASA Astrophysics Data System (ADS)

dos Santos Muniz, Heloisa; Nascimento, Alessandro S.

2015-08-01

Methodologies on molecular docking are constantly improving. The problem consists on finding an optimal interplay between the computational cost and a satisfactory physical description of ligand-receptor interaction. In pursuit of an advance in current methods we developed a mixed docking approach combining ligand- and receptor-based strategies in a docking engine, where tridimensional descriptors for shape and charge distribution of a reference ligand guide the initial placement of the docking molecule and an interaction energy-based global minimization follows. This hybrid docking was evaluated with soft-core and force field potentials taking into account ligand pose and scoring. Our approach was found to be competitive to a purely receptor-based dock resulting in improved logAUC values when evaluated with DUD and DUD-E. Furthermore, the smoothed potential as evaluated here, was not advantageous when ligand binding poses were compared to experimentally determined conformations. In conclusion we show that a combination of ligand- and receptor-based strategy docking with a force field energy model results in good reproduction of binding poses and enrichment of active molecules against decoys. This strategy is implemented in our tool, LiBELa, available to the scientific community.

Surflex-Dock: Docking benchmarks and real-world application

NASA Astrophysics Data System (ADS)

Spitzer, Russell; Jain, Ajay N.

2012-06-01

Benchmarks for molecular docking have historically focused on re-docking the cognate ligand of a well-determined protein-ligand complex to measure geometric pose prediction accuracy, and measurement of virtual screening performance has been focused on increasingly large and diverse sets of target protein structures, cognate ligands, and various types of decoy sets. Here, pose prediction is reported on the Astex Diverse set of 85 protein ligand complexes, and virtual screening performance is reported on the DUD set of 40 protein targets. In both cases, prepared structures of targets and ligands were provided by symposium organizers. The re-prepared data sets yielded results not significantly different than previous reports of Surflex-Dock on the two benchmarks. Minor changes to protein coordinates resulting from complex pre-optimization had large effects on observed performance, highlighting the limitations of cognate ligand re-docking for pose prediction assessment. Docking protocols developed for cross-docking, which address protein flexibility and produce discrete families of predicted poses, produced substantially better performance for pose prediction. Performance on virtual screening performance was shown to benefit by employing and combining multiple screening methods: docking, 2D molecular similarity, and 3D molecular similarity. In addition, use of multiple protein conformations significantly improved screening enrichment.

A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

PubMed

Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M

2012-07-01

We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Structural study of biologically significant ligands with major birch pollen allergen Betv1 by docking and molecular dynamics simulation

PubMed Central

Kundu, Sangeeta; Roy, Debjani

2010-01-01

The major birch pollen allergen, Betv1 of Betula verrucosa is the main causative agent of birch pollen allergy in humans. Betv1 is capable of binding several physiological ligands including fatty acids, flavones, cytokinins and sterols. Until now, no structural information from crystallography or NMR is available regarding binding mode of any of these ligands into the binding pocket of Betv1. In the present study thirteen ligands have been successfully docked into the hydrophobic cavity of Betv1 and binding free energies of the complexes have been calculated using AutoDock 3.0.5. A linear relationship with correlation coefficient (R2) of 0.6 is obtained between ΔGbs values plotted against their corresponding IC50 values. The complex formed between Betv1 and the best docking pose for each ligand has been optimized by molecular dynamics simulation. Here, we describe the ligand binding of Betv1, which provides insight into the biological function of this protein. This knowledge is required for structural alteration or inhibition of some of these ligands in order to modify the allergenic properties of this protein. PMID:20978606

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.

istar: a web platform for large-scale protein-ligand docking.

PubMed

Li, Hongjian; Leung, Kwong-Sak; Ballester, Pedro J; Wong, Man-Hon

2014-01-01

Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock.

PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

PubMed

Ng, Marcus C K; Fong, Simon; Siu, Shirley W I

2015-06-01

Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

Multiple ligand simultaneous docking: orchestrated dancing of ligands in binding sites of protein.

PubMed

Li, Huameng; Li, Chenglong

2010-07-30

Present docking methodologies simulate only one single ligand at a time during docking process. In reality, the molecular recognition process always involves multiple molecular species. Typical protein-ligand interactions are, for example, substrate and cofactor in catalytic cycle; metal ion coordination together with ligand(s); and ligand binding with water molecules. To simulate the real molecular binding processes, we propose a novel multiple ligand simultaneous docking (MLSD) strategy, which can deal with all the above processes, vastly improving docking sampling and binding free energy scoring. The work also compares two search strategies: Lamarckian genetic algorithm and particle swarm optimization, which have respective advantages depending on the specific systems. The methodology proves robust through systematic testing against several diverse model systems: E. coli purine nucleoside phosphorylase (PNP) complex with two substrates, SHP2NSH2 complex with two peptides and Bcl-xL complex with ABT-737 fragments. In all cases, the final correct docking poses and relative binding free energies were obtained. In PNP case, the simulations also capture the binding intermediates and reveal the binding dynamics during the recognition processes, which are consistent with the proposed enzymatic mechanism. In the other two cases, conventional single-ligand docking fails due to energetic and dynamic coupling among ligands, whereas MLSD results in the correct binding modes. These three cases also represent potential applications in the areas of exploring enzymatic mechanism, interpreting noisy X-ray crystallographic maps, and aiding fragment-based drug design, respectively. 2010 Wiley Periodicals, Inc.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling.

PubMed

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Ligand-protein docking using a quantum stochastic tunneling optimization method.

PubMed

Mancera, Ricardo L; Källblad, Per; Todorov, Nikolay P

2004-04-30

A novel hybrid optimization method called quantum stochastic tunneling has been recently introduced. Here, we report its implementation within a new docking program called EasyDock and a validation with the CCDC/Astex data set of ligand-protein complexes using the PLP score to represent the ligand-protein potential energy surface and ScreenScore to score the ligand-protein binding energies. When taking the top energy-ranked ligand binding mode pose, we were able to predict the correct crystallographic ligand binding mode in up to 75% of the cases. By using this novel optimization method run times for typical docking simulations are significantly shortened. Copyright 2004 Wiley Periodicals, Inc. J Comput Chem 25: 858-864, 2004

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand

PubMed Central

DeLuca, Samuel; Khar, Karen; Meiler, Jens

2015-01-01

RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial ‘low-resolution’ docking step. It combines the translational and rotational adjustments to the ligand pose in a single transformation step. The new algorithm is both more accurate and more time-efficient. The docking success rate is improved by 10–15% in a benchmark set of 43 protein/ligand complexes, reducing the number of models that typically need to be generated from 1000 to 150. The average time to generate a model is reduced from 50 seconds to 10 seconds. As a result we observe an effective 30-fold speed increase, making RosettaLigand appropriate for docking medium sized ligand libraries. We demonstrate that this improved initial placement of the ligand is critical for successful prediction of an accurate binding position in the ‘high-resolution’ full atom refinement step. PMID:26207742

DOCLASP - Docking ligands to target proteins using spatial and electrostatic congruence extracted from a known holoenzyme and applying simple geometrical transformations.

PubMed

Chakraborty, Sandeep

2014-01-01

The ability to accurately and effectively predict the interaction between proteins and small drug-like compounds has long intrigued researchers for pedagogic, humanitarian and economic reasons. Protein docking methods (AutoDock, GOLD, DOCK, FlexX and Glide to name a few) rank a large number of possible conformations of protein-ligand complexes using fast algorithms. Previously, it has been shown that structural congruence leading to the same enzymatic function necessitates the congruence of electrostatic properties (CLASP). The current work presents a methodology for docking a ligand into a target protein, provided that there is at least one known holoenzyme with ligand bound - DOCLASP (Docking using CLASP). The contact points of the ligand in the holoenzyme defines a motif, which is used to query the target enzyme using CLASP. If there are significant matches, the holoenzyme and the target protein are superimposed based on congruent atoms. The same linear and rotational transformations are also applied to the ligand, thus creating a unified coordinate framework having the holoenzyme, the ligand and the target enzyme. In the current work, the dipeptidyl peptidase-IV inhibitor vildagliptin was docked to the PI-PLC structure complexed with myo-inositol using DOCLASP. Also, corroboration of the docking of phenylthiourea to the modelled structure of polyphenol oxidase (JrPPO1) from walnut is provided based on the subsequently solved structure of JrPPO1 (PDBid:5CE9). Analysis of the binding of the antitrypanosomial drug suramin to nine non-homologous proteins in the PDB database shows a diverse set of binding motifs, and multiple binding sites in the phospholipase A2-likeproteins from the Bothrops genus of pitvipers. The conformational changes in the suramin molecule on binding highlights the challenges in docking flexible ligands into an already 'plastic' binding site. Thus, DOCLASP presents a method for 'soft docking' ligands to proteins with low computational requirements.

Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking

NASA Astrophysics Data System (ADS)

Tsvetkov, Vladimir B.; Serbin, Alexander V.

2014-06-01

In previous works we reported the design, synthesis and in vitro evaluations of synthetic anionic polymers modified by alicyclic pendant groups (hydrophobic anchors), as a novel class of inhibitors of the human immunodeficiency virus type 1 ( HIV-1) entry into human cells. Recently, these synthetic polymers interactions with key mediator of HIV-1 entry-fusion, the tri-helix core of the first heptad repeat regions [ HR1]3 of viral envelope protein gp41, were pre-studied via docking in terms of newly formulated algorithm for stepwise approximation from fragments of polymeric backbone and side-group models toward real polymeric chains. In the present article the docking results were verified under molecular dynamics ( MD) modeling. In contrast with limited capabilities of the docking, the MD allowed of using much more large models of the polymeric ligands, considering flexibility of both ligand and target simultaneously. Among the synthesized polymers the dinorbornen anchors containing alternating copolymers of maleic acid were selected as the most representative ligands (possessing the top anti-HIV activity in vitro in correlation with the highest binding energy in the docking). To verify the probability of binding of the polymers with the [HR1]3 in the sites defined via docking, various starting positions of polymer chains were tried. The MD simulations confirmed the main docking-predicted priority for binding sites, and possibilities for axial and belting modes of the ligands-target interactions. Some newly MD-discovered aspects of the ligand's backbone and anchor units dynamic cooperation in binding the viral target clarify mechanisms of the synthetic polymers anti-HIV activity and drug resistance prevention.

Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem.

PubMed

Ban, Tomohiro; Ohue, Masahito; Akiyama, Yutaka

2018-04-01

The identification of comprehensive drug-target interactions is important in drug discovery. Although numerous computational methods have been developed over the years, a gold standard technique has not been established. Computational ligand docking and structure-based drug design allow researchers to predict the binding affinity between a compound and a target protein, and thus, they are often used to virtually screen compound libraries. In addition, docking techniques have also been applied to the virtual screening of target proteins (inverse docking) to predict target proteins of a drug candidate. Nevertheless, a more accurate docking method is currently required. In this study, we proposed a method in which a predicted ligand-binding site is covered by multiple grids, termed multiple grid arrangement. Notably, multiple grid arrangement facilitates the conformational search for a grid-based ligand docking software and can be applied to the state-of-the-art commercial docking software Glide (Schrödinger, LLC). We validated the proposed method by re-docking with the Astex diverse benchmark dataset and blind binding site situations, which improved the correct prediction rate of the top scoring docking pose from 27.1% to 34.1%; however, only a slight improvement in target prediction accuracy was observed with inverse docking scenarios. These findings highlight the limitations and challenges of current scoring functions and the need for more accurate docking methods. The proposed multiple grid arrangement method was implemented in Glide by modifying a cross-docking script for Glide, xglide.py. The script of our method is freely available online at http://www.bi.cs.titech.ac.jp/mga_glide/. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

In-Silico molecular docking and simulation studies on novel chalcone and flavone hybrid derivatives with 1, 2, 3-triazole linkage as vital inhibitors of Plasmodium falciparum dihydroorotate dehydrogenase.

PubMed

Thillainayagam, Mahalakshmi; Malathi, Kullappan; Ramaiah, Sudha

2017-11-27

The structural motifs of chalcones, flavones, and triazoles with varied substitutions have been studied for the antimalarial activity. In this study, 25 novel derivatives of chalcone and flavone hybrid derivatives with 1, 2, 3-triazole linkage are docked with Plasmodium falciparum dihydroorotate dehydrogenase to establish their inhibitory activity against Plasmodium falciparum. The best binding conformation of the ligands at the catalytic site of dihydroorotate dehydrogenase are selected to characterize the best bound ligand using the best consensus score and the number of hydrogen bond interactions. The ligand namely (2E)-3-(4-{[1-(3-chloro-4-fluorophenyl)-1H-1, 2, 3-triazol-4-yl]methoxy}-3-methoxyphenyl-1-(2-hydroxy-4,6-dimethoxyphenyl)prop-2-en-1-one, is one the among the five best docked ligands, which interacts with the protein through nine hydrogen bonds and with a consensus score of five. To refine and confirm the docking study results, the stability of complexes is verified using Molecular Dynamics Simulations, Molecular Mechanics /Poisson-Boltzmann Surface Area free binding energy analysis, and per residue contribution for the binding energy. The study implies that the best docked Plasmodium falciparum dihydroorotate dehydrogenase-ligand complex is having high negative binding energy, most stable, compact, and rigid with nine hydrogen bonds. The study provides insight for the optimization of chalcone and flavone hybrids with 1, 2, 3-triazole linkage as potent inhibitors.

Molecular docking.

PubMed

Morris, Garrett M; Lim-Wilby, Marguerita

2008-01-01

Molecular docking is a key tool in structural molecular biology and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode(s) of a ligand with a protein of known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compounds, rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discusses the background and theory of molecular docking software, and covers the usage of some of the most-cited docking software.

Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking

PubMed Central

2012-01-01

A key metric to assess molecular docking remains ligand enrichment against challenging decoys. Whereas the directory of useful decoys (DUD) has been widely used, clear areas for optimization have emerged. Here we describe an improved benchmarking set that includes more diverse targets such as GPCRs and ion channels, totaling 102 proteins with 22886 clustered ligands drawn from ChEMBL, each with 50 property-matched decoys drawn from ZINC. To ensure chemotype diversity, we cluster each target’s ligands by their Bemis–Murcko atomic frameworks. We add net charge to the matched physicochemical properties and include only the most dissimilar decoys, by topology, from the ligands. An online automated tool (http://decoys.docking.org) generates these improved matched decoys for user-supplied ligands. We test this data set by docking all 102 targets, using the results to improve the balance between ligand desolvation and electrostatics in DOCK 3.6. The complete DUD-E benchmarking set is freely available at http://dude.docking.org. PMID:22716043

Testing inhomogeneous solvation theory in structure-based ligand discovery.

PubMed

Balius, Trent E; Fischer, Marcus; Stein, Reed M; Adler, Thomas B; Nguyen, Crystal N; Cruz, Anthony; Gilson, Michael K; Kurtzman, Tom; Shoichet, Brian K

2017-08-15

Binding-site water is often displaced upon ligand recognition, but is commonly neglected in structure-based ligand discovery. Inhomogeneous solvation theory (IST) has become popular for treating this effect, but it has not been tested in controlled experiments at atomic resolution. To do so, we turned to a grid-based version of this method, GIST, readily implemented in molecular docking. Whereas the term only improves docking modestly in retrospective ligand enrichment, it could be added without disrupting performance. We thus turned to prospective docking of large libraries to investigate GIST's impact on ligand discovery, geometry, and water structure in a model cavity site well-suited to exploring these terms. Although top-ranked docked molecules with and without the GIST term often overlapped, many ligands were meaningfully prioritized or deprioritized; some of these were selected for testing. Experimentally, 13/14 molecules prioritized by GIST did bind, whereas none of the molecules that it deprioritized were observed to bind. Nine crystal complexes were determined. In six, the ligand geometry corresponded to that predicted by GIST, for one of these the pose without the GIST term was wrong, and three crystallographic poses differed from both predictions. Notably, in one structure, an ordered water molecule with a high GIST displacement penalty was observed to stay in place. Inclusion of this water-displacement term can substantially improve the hit rates and ligand geometries from docking screens, although the magnitude of its effects can be small and its impact in drug binding sites merits further controlled studies.

BP-Dock: A Flexible Docking Scheme for Exploring Protein–Ligand Interactions Based on Unbound Structures

PubMed Central

Bolia, Ashini; Gerek, Z. Nevin; Ozkan, S. Banu

2016-01-01

Molecular docking serves as an important tool in modeling protein–ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein–ligand interactions as well as virtual screening of novel targets for rational drug design. PMID:24380381

Ligand Shaping in Induced Fit Docking of MraY Inhibitors. Polynomial Discriminant and Laplacian Operator as Biological Activity Descriptors

PubMed Central

Diudea, Mircea V.; Putz, Mihai V.

2017-01-01

Docking—i.e., interaction of a small molecule (ligand) with a proteic structure (receptor)—represents the ground of drug action mechanism of the vast majority of bioactive chemicals. Ligand and receptor accommodate their geometry and energy, within this interaction, in the benefit of receptor–ligand complex. In an induced fit docking, the structure of ligand is most susceptible to changes in topology and energy, comparative to the receptor. These changes can be described by manifold hypersurfaces, in terms of polynomial discriminant and Laplacian operator. Such topological surfaces were represented for each MraY (phospho-MurNAc-pentapeptide translocase) inhibitor, studied before and after docking with MraY. Binding affinities of all ligands were calculated by this procedure. For each ligand, Laplacian and polynomial discriminant were correlated with the ligand minimum inhibitory concentration (MIC) retrieved from literature. It was observed that MIC is correlated with Laplacian and polynomial discriminant. PMID:28653980

Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands

PubMed Central

King, Matthew D.; Phillips, Paul; Turner, Matthew W.; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; Mcdougal, Owen M.

2017-01-01

Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. PMID:26537635

Scoring ligand similarity in structure-based virtual screening.

PubMed

Zavodszky, Maria I; Rohatgi, Anjali; Van Voorst, Jeffrey R; Yan, Honggao; Kuhn, Leslie A

2009-01-01

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds. (c) 2009 John Wiley & Sons, Ltd.

CoMSIA and Docking Study of Rhenium Based Estrogen Receptor Ligand Analogs

PubMed Central

Wolohan, Peter; Reichert, David E.

2007-01-01

OPLS all atom force field parameters were developed in order to model a diverse set of novel rhenium based estrogen receptor ligands whose relative binding affinities (RBA) to the estrogen receptor alpha isoform (ERα) with respect to 17β-Estradiol were available. The binding properties of these novel rhenium based organometallic complexes were studied with a combination of Comparative Molecular Similarity Indices Analysis (CoMSIA) and docking. A total of 29 estrogen receptor ligands consisting of 11 rhenium complexes and 18 organic ligands were docked inside the ligand-binding domain (LBD) of ERα utilizing the program Gold. The top ranked pose was used to construct CoMSIA models from a training set of 22 of the estrogen receptor ligands which were selected at random. In addition scoring functions from the docking runs and the polar volume (PV) were also studied to investigate their ability to predict RBA ERα. A partial least-squares analysis consisting of the CoMSIA steric, electrostatic and hydrophobic indices together with the polar volume proved sufficiently predictive having a correlation coefficient, r2, of 0.94 and a cross-validated correlation coefficient, q2, utilizing the leave one out method of 0.68. Analysis of the scoring functions from Gold showed particularly poor correlation to RBA ERα which did not improve when the rhenium complexes were extracted to leave the organic ligands. The combined CoMSIA and polar volume model ranked correctly the ligands in order of increasing RBA ERα, illustrating the utility of this method as a prescreening tool in the development of novel rhenium based estrogen receptor ligands. PMID:17280694

Identification of Novel Aldose Reductase Inhibitors from Spices: A Molecular Docking and Simulation Study.

PubMed

Antony, Priya; Vijayan, Ranjit

2015-01-01

Hyperglycemia in diabetic patients results in a diverse range of complications such as diabetic retinopathy, neuropathy, nephropathy and cardiovascular diseases. The role of aldose reductase (AR), the key enzyme in the polyol pathway, in these complications is well established. Due to notable side-effects of several drugs, phytochemicals as an alternative has gained considerable importance for the treatment of several ailments. In order to evaluate the inhibitory effects of dietary spices on AR, a collection of phytochemicals were identified from Zingiber officinale (ginger), Curcuma longa (turmeric) Allium sativum (garlic) and Trigonella foenum graecum (fenugreek). Molecular docking was performed for lead identification and molecular dynamics simulations were performed to study the dynamic behaviour of these protein-ligand interactions. Gingerenones A, B and C, lariciresinol, quercetin and calebin A from these spices exhibited high docking score, binding affinity and sustained protein-ligand interactions. Rescoring of protein ligand interactions at the end of MD simulations produced binding scores that were better than the initially docked conformations. Docking results, ligand interactions and ADMET properties of these molecules were significantly better than commercially available AR inhibitors like epalrestat, sorbinil and ranirestat. Thus, these natural molecules could be potent AR inhibitors.

Identification of Novel Aldose Reductase Inhibitors from Spices: A Molecular Docking and Simulation Study

PubMed Central

Antony, Priya; Vijayan, Ranjit

2015-01-01

Hyperglycemia in diabetic patients results in a diverse range of complications such as diabetic retinopathy, neuropathy, nephropathy and cardiovascular diseases. The role of aldose reductase (AR), the key enzyme in the polyol pathway, in these complications is well established. Due to notable side-effects of several drugs, phytochemicals as an alternative has gained considerable importance for the treatment of several ailments. In order to evaluate the inhibitory effects of dietary spices on AR, a collection of phytochemicals were identified from Zingiber officinale (ginger), Curcuma longa (turmeric) Allium sativum (garlic) and Trigonella foenum graecum (fenugreek). Molecular docking was performed for lead identification and molecular dynamics simulations were performed to study the dynamic behaviour of these protein-ligand interactions. Gingerenones A, B and C, lariciresinol, quercetin and calebin A from these spices exhibited high docking score, binding affinity and sustained protein-ligand interactions. Rescoring of protein ligand interactions at the end of MD simulations produced binding scores that were better than the initially docked conformations. Docking results, ligand interactions and ADMET properties of these molecules were significantly better than commercially available AR inhibitors like epalrestat, sorbinil and ranirestat. Thus, these natural molecules could be potent AR inhibitors. PMID:26384019

JADOPPT: java based AutoDock preparing and processing tool.

PubMed

García-Pérez, Carlos; Peláez, Rafael; Therón, Roberto; Luis López-Pérez, José

2017-02-15

AutoDock is a very popular software package for docking and virtual screening. However, currently it is hard work to visualize more than one result from the virtual screening at a time. To overcome this limitation we have designed JADOPPT, a tool for automatically preparing and processing multiple ligand-protein docked poses obtained from AutoDock. It allows the simultaneous visual assessment and comparison of multiple poses through clustering methods. Moreover, it permits the representation of reference ligands with known binding modes, binding site residues, highly scoring regions for the ligand, and the calculated binding energy of the best ranked results. JADOPPT, supplementary material (Case Studies 1 and 2) and video tutorials are available at http://visualanalytics.land/cgarcia/JADOPPT.html. carlosgarcia@usal.es or pelaez@usal.es. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

In Silico Screening for Biothreat Countermeasures

DTIC Science & Technology

2006-02-03

drug candidates to each kinase structure using the well-known docking algorithm LibDock . This population of 1200 ligands includes ~400 ligands with...mentioned previously, each of the known p38 inhibitors in the population was docked to its target using the LibDock application. This method resulted

Docking of Natural Products against Neurodegenerative Diseases: General Concepts.

PubMed

Ribeiro, Frederico F; Mendonca Junior, Francisco J B; Ghasemi, Jahan B; Ishiki, Hamilton M; Scotti, Marcus T; Scotti, Luciana

2018-01-01

Since antiquity, humanity has used medicinal plant preparations to cure its ills, and, as research has progressed, new technologies have enabled more investigations on natural compounds which originate from plants, fungi, and marine species. The health benefits that these natural products provide have become a motive for treatment studies of various diseases. Among them, the neurodegenerative diseases like Alzheimer's and Parkinson's, a major age-related neurodegenerative disorder. Studies with natural products for neurodegenerative diseases (particularly through molecular docking) search for, and then focus on those ligands which offer effective inhibition of the enzymes monoamine oxidase and acetylcholinesterase. This review introduces the main concepts involved in docking studies with natural products: and also in our group, which has conducted a docking study of natural products isolated from Tetrapterys mucronata for inhibition of acetylcholinesterase. We observed that compounds 4 and 5 formed more interactions than the theoretical ligand, but that ligands with greater activity also interacted with residues HIS 381 and GLN 527. We have reported on our docking study performed with AChE and alkaloids isolated from the plant Tetrapterys mucronata. Our docking results corroborate the experiments conducted, and emphasize the positive contribution that these theoretical studies involving natural products bring to the fight against neurodegenerative diseases. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking: anchors modified polyanions interference with the HIV-1 fusion mediator.

PubMed

Tsvetkov, Vladimir B; Serbin, Alexander V

2014-06-01

In previous works we reported the design, synthesis and in vitro evaluations of synthetic anionic polymers modified by alicyclic pendant groups (hydrophobic anchors), as a novel class of inhibitors of the human immunodeficiency virus type 1 (HIV-1) entry into human cells. Recently, these synthetic polymers interactions with key mediator of HIV-1 entry-fusion, the tri-helix core of the first heptad repeat regions [HR1]3 of viral envelope protein gp41, were pre-studied via docking in terms of newly formulated algorithm for stepwise approximation from fragments of polymeric backbone and side-group models toward real polymeric chains. In the present article the docking results were verified under molecular dynamics (MD) modeling. In contrast with limited capabilities of the docking, the MD allowed of using much more large models of the polymeric ligands, considering flexibility of both ligand and target simultaneously. Among the synthesized polymers the dinorbornen anchors containing alternating copolymers of maleic acid were selected as the most representative ligands (possessing the top anti-HIV activity in vitro in correlation with the highest binding energy in the docking). To verify the probability of binding of the polymers with the [HR1]3 in the sites defined via docking, various starting positions of polymer chains were tried. The MD simulations confirmed the main docking-predicted priority for binding sites, and possibilities for axial and belting modes of the ligands-target interactions. Some newly MD-discovered aspects of the ligand's backbone and anchor units dynamic cooperation in binding the viral target clarify mechanisms of the synthetic polymers anti-HIV activity and drug resistance prevention.

Structural insights into transient receptor potential vanilloid type 1 (TRPV1) from homology modeling, flexible docking, and mutational studies.

PubMed

Lee, Jin Hee; Lee, Yoonji; Ryu, HyungChul; Kang, Dong Wook; Lee, Jeewoo; Lazar, Jozsef; Pearce, Larry V; Pavlyukovets, Vladimir A; Blumberg, Peter M; Choi, Sun

2011-04-01

The transient receptor potential vanilloid subtype 1 (TRPV1) is a non-selective cation channel composed of four monomers with six transmembrane helices (TM1-TM6). TRPV1 is found in the central and peripheral nervous system, and it is an important therapeutic target for pain relief. We describe here the construction of a tetrameric homology model of rat TRPV1 (rTRPV1). We experimentally evaluated by mutational analysis the contribution of residues of rTRPV1 contributing to ligand binding by the prototypical TRPV1 agonists, capsaicin and resiniferatoxin (RTX). We then performed docking analysis using our homology model. The docking results with capsaicin and RTX showed that our homology model was reliable, affording good agreement with our mutation data. Additionally, the binding mode of a simplified RTX (sRTX) ligand as predicted by the modeling agreed well with those of capsaicin and RTX, accounting for the high binding affinity of the sRTX ligand for TRPV1. Through the homology modeling, docking and mutational studies, we obtained important insights into the ligand-receptor interactions at the molecular level which should prove of value in the design of novel TRPV1 ligands.

Structural insights into transient receptor potential vanilloid type 1 (TRPV1) from homology modeling, flexible docking, and mutational studies

NASA Astrophysics Data System (ADS)

Lee, Jin Hee; Lee, Yoonji; Ryu, HyungChul; Kang, Dong Wook; Lee, Jeewoo; Lazar, Jozsef; Pearce, Larry V.; Pavlyukovets, Vladimir A.; Blumberg, Peter M.; Choi, Sun

2011-04-01

The transient receptor potential vanilloid subtype 1 (TRPV1) is a non-selective cation channel composed of four monomers with six transmembrane helices (TM1-TM6). TRPV1 is found in the central and peripheral nervous system, and it is an important therapeutic target for pain relief. We describe here the construction of a tetrameric homology model of rat TRPV1 (rTRPV1). We experimentally evaluated by mutational analysis the contribution of residues of rTRPV1 contributing to ligand binding by the prototypical TRPV1 agonists, capsaicin and resiniferatoxin (RTX). We then performed docking analysis using our homology model. The docking results with capsaicin and RTX showed that our homology model was reliable, affording good agreement with our mutation data. Additionally, the binding mode of a simplified RTX (sRTX) ligand as predicted by the modeling agreed well with those of capsaicin and RTX, accounting for the high binding affinity of the sRTX ligand for TRPV1. Through the homology modeling, docking and mutational studies, we obtained important insights into the ligand-receptor interactions at the molecular level which should prove of value in the design of novel TRPV1 ligands.

Plasticity of the Binding Site of Renin: Optimized Selection of Protein Structures for Ensemble Docking.

PubMed

Strecker, Claas; Meyer, Bernd

2018-05-29

Protein flexibility poses a major challenge to docking of potential ligands in that the binding site can adopt different shapes. Docking algorithms usually keep the protein rigid and only allow the ligand to be treated as flexible. However, a wrong assessment of the shape of the binding pocket can prevent a ligand from adapting a correct pose. Ensemble docking is a simple yet promising method to solve this problem: Ligands are docked into multiple structures, and the results are subsequently merged. Selection of protein structures is a significant factor for this approach. In this work we perform a comprehensive and comparative study evaluating the impact of structure selection on ensemble docking. We perform ensemble docking with several crystal structures and with structures derived from molecular dynamics simulations of renin, an attractive target for antihypertensive drugs. Here, 500 ns of MD simulations revealed binding site shapes not found in any available crystal structure. We evaluate the importance of structure selection for ensemble docking by comparing binding pose prediction, ability to rank actives above nonactives (screening utility), and scoring accuracy. As a result, for ensemble definition k-means clustering appears to be better suited than hierarchical clustering with average linkage. The best performing ensemble consists of four crystal structures and is able to reproduce the native ligand poses better than any individual crystal structure. Moreover this ensemble outperforms 88% of all individual crystal structures in terms of screening utility as well as scoring accuracy. Similarly, ensembles of MD-derived structures perform on average better than 75% of any individual crystal structure in terms of scoring accuracy at all inspected ensembles sizes.

Computational exploration of a protein receptor binding space with student proposed peptide ligands.

PubMed

King, Matthew D; Phillips, Paul; Turner, Matthew W; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M

2016-01-01

Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. © 2015 The International Union of Biochemistry and Molecular Biology.

Identifying Potential Protein Targets for Toluene Using a Molecular Similarity Search, in Silico Docking and in Vitro Validation

DTIC Science & Technology

2015-01-01

the Protein Data Bank (http://www.rcsb.org/ pdb /). These structures are the most accurate and can be used for molecular docking. Target flexibility is...crystallized with the different ligands. In total, 240 files with the structures of 37 proteins were downloaded from PDB and used for docking...total, 240 files with protein structures were downloaded from the PDB and used for protein–ligand docking. It is widely accepted that ligand binding

Computational analysis of the binding ability of heterocyclic and conformationally constrained epibatidine analogs in the neuronal nicotinic acetylcholine receptor.

PubMed

Soriano, Elena; Marco-Contelles, José; Colmena, Inés; Gandía, Luis

2010-05-01

One of the most critical issues on the study of ligand-receptor interactions in drug design is the knowledge of the bioactive conformation of the ligand. In this study, we describe a computational approach aimed at estimating the binding ability of epibatidine analogs to interact with the neuronal nicotinic acetylcholine receptor (nAChR) and get insights into the bioactive conformation. The protocol followed consists of a docking analysis and evaluation of pharmacophore parameters of the docked structures. On the basis of the biological data, the results have revealed that the docking analysis is able to predict active ligands, whereas further efforts are needed to develop a suitable and solid pharmacophore model.

S4MPLE--Sampler for Multiple Protein-Ligand Entities: Methodology and Rigid-Site Docking Benchmarking.

PubMed

Hoffer, Laurent; Chira, Camelia; Marcou, Gilles; Varnek, Alexandre; Horvath, Dragos

2015-05-19

This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications-docking of fragment-like compounds, simultaneous docking of multiple ligands, including free crystallographic waters-were published elsewhere. This paper discusses: (a) methodology, (b) set-up of the force field energy functions and (c) their validation in classical redocking tests. More than 80% success in redocking was achieved (RMSD of top-ranked pose < 2.0 Å).

DOVIS 2.0: an efficient and easy to use parallel virtual screening tool based on AutoDock 4.0.

PubMed

Jiang, Xiaohui; Kumar, Kamal; Hu, Xin; Wallqvist, Anders; Reifman, Jaques

2008-09-08

Small-molecule docking is an important tool in studying receptor-ligand interactions and in identifying potential drug candidates. Previously, we developed a software tool (DOVIS) to perform large-scale virtual screening of small molecules in parallel on Linux clusters, using AutoDock 3.05 as the docking engine. DOVIS enables the seamless screening of millions of compounds on high-performance computing platforms. In this paper, we report significant advances in the software implementation of DOVIS 2.0, including enhanced screening capability, improved file system efficiency, and extended usability. To keep DOVIS up-to-date, we upgraded the software's docking engine to the more accurate AutoDock 4.0 code. We developed a new parallelization scheme to improve runtime efficiency and modified the AutoDock code to reduce excessive file operations during large-scale virtual screening jobs. We also implemented an algorithm to output docked ligands in an industry standard format, sd-file format, which can be easily interfaced with other modeling programs. Finally, we constructed a wrapper-script interface to enable automatic rescoring of docked ligands by arbitrarily selected third-party scoring programs. The significance of the new DOVIS 2.0 software compared with the previous version lies in its improved performance and usability. The new version makes the computation highly efficient by automating load balancing, significantly reducing excessive file operations by more than 95%, providing outputs that conform to industry standard sd-file format, and providing a general wrapper-script interface for rescoring of docked ligands. The new DOVIS 2.0 package is freely available to the public under the GNU General Public License.

DOVIS 2.0: An Efficient and Easy to Use Parallel Virtual Screening Tool Based on AutoDock 4.0

DTIC Science & Technology

2008-09-08

under the GNU General Public License. Background Molecular docking is a computational method that pre- dicts how a ligand interacts with a receptor...Hence, it is an important tool in studying receptor-ligand interactions and plays an essential role in drug design. Particularly, molecular docking has...libraries from OpenBabel and setup a molecular data structure as a C++ object in our program. This makes handling of molecular structures (e.g., atoms

Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins

PubMed Central

Kurkcuoglu, Zeynep; Doruker, Pemra

2016-01-01

Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7–15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4–3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its “parents” up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5–2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions. PMID:27348230

ConsDock: A new program for the consensus analysis of protein-ligand interactions.

PubMed

Paul, Nicodème; Rognan, Didier

2002-06-01

Protein-based virtual screening of chemical libraries is a powerful technique for identifying new molecules that may interact with a macromolecular target of interest. Because of docking and scoring limitations, it is more difficult to apply as a lead optimization method because it requires that the docking/scoring tool is able to propose as few solutions as possible and all of them with a very good accuracy for both the protein-bound orientation and the conformation of the ligand. In the present study, we present a consensus docking approach (ConsDock) that takes advantage of three widely used docking tools (Dock, FlexX, and Gold). The consensus analysis of all possible poses generated by several docking tools is performed sequentially in four steps: (i) hierarchical clustering of all poses generated by a docking tool into families represented by a leader; (ii) definition of all consensus pairs from leaders generated by different docking programs; (iii) clustering of consensus pairs into classes, represented by a mean structure; and (iv) ranking the different means starting from the most populated class of consensus pairs. When applied to a test set of 100 protein-ligand complexes from the Protein Data Bank, ConsDock significantly outperforms single docking with respect to the docking accuracy of the top-ranked pose. In 60% of the cases investigated here, ConsDock was able to rank as top solution a pose within 2 A RMSD of the X-ray structure. It can be applied as a postprocessing filter to either single- or multiple-docking programs to prioritize three-dimensional guided lead optimization from the most likely docking solution. Copyright 2002 Wiley-Liss, Inc.

A Hadoop-based Molecular Docking System

NASA Astrophysics Data System (ADS)

Dong, Yueli; Guo, Quan; Sun, Bin

2017-10-01

Molecular docking always faces the challenge of managing tens of TB datasets. It is necessary to improve the efficiency of the storage and docking. We proposed the molecular docking platform based on Hadoop for virtual screening, it provides the preprocessing of ligand datasets and the analysis function of the docking results. A molecular cloud database that supports mass data management is constructed. Through this platform, the docking time is reduced, the data storage is efficient, and the management of the ligand datasets is convenient.

Investigation of MM-PBSA rescoring of docking poses.

PubMed

Thompson, David C; Humblet, Christine; Joseph-McCarthy, Diane

2008-05-01

Target-based virtual screening is increasingly used to generate leads for targets for which high quality three-dimensional (3D) structures are available. To allow large molecular databases to be screened rapidly, a tiered scoring scheme is often employed whereby a simple scoring function is used as a fast filter of the entire database and a more rigorous and time-consuming scoring function is used to rescore the top hits to produce the final list of ranked compounds. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approaches are currently thought to be quite effective at incorporating implicit solvation into the estimation of ligand binding free energies. In this paper, the ability of a high-throughput MM-PBSA rescoring function to discriminate between correct and incorrect docking poses is investigated in detail. Various initial scoring functions are used to generate docked poses for a subset of the CCDC/Astex test set and to dock one set of actives/inactives from the DUD data set. The effectiveness of each of these initial scoring functions is discussed. Overall, the ability of the MM-PBSA rescoring function to (i) regenerate the set of X-ray complexes when docking the bound conformation of the ligand, (ii) regenerate the X-ray complexes when docking conformationally expanded databases for each ligand which include "conformation decoys" of the ligand, and (iii) enrich known actives in a virtual screen for the mineralocorticoid receptor in the presence of "ligand decoys" is assessed. While a pharmacophore-based molecular docking approach, PhDock, is used to carry out the docking, the results are expected to be general to use with any docking method.

Flexible ligand docking using a genetic algorithm

NASA Astrophysics Data System (ADS)

Oshiro, C. M.; Kuntz, I. D.; Dixon, J. Scott

1995-04-01

Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.

Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM

PubMed Central

Gagnon, Jessica K.; Law, Sean M.; Brooks, Charles L.

2016-01-01

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an inter-converting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. PMID:26691274

Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM.

PubMed

Gagnon, Jessica K; Law, Sean M; Brooks, Charles L

2016-03-30

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an interconverting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. © 2015 Wiley Periodicals, Inc.

Protein tyrosine phosphatases: Ligand interaction analysis and optimisation of virtual screening.

PubMed

Ghattas, Mohammad A; Atatreh, Noor; Bichenkova, Elena V; Bryce, Richard A

2014-07-01

Docking-based virtual screening is an established component of structure-based drug discovery. Nevertheless, scoring and ranking of computationally docked ligand libraries still suffer from many false positives. Identifying optimal docking parameters for a target protein prior to virtual screening can improve experimental hit rates. Here, we examine protocols for virtual screening against the important but challenging class of drug target, protein tyrosine phosphatases. In this study, common interaction features were identified from analysis of protein-ligand binding geometries of more than 50 complexed phosphatase crystal structures. It was found that two interactions were consistently formed across all phosphatase inhibitors: (1) a polar contact with the conserved arginine residue, and (2) at least one interaction with the P-loop backbone amide. In order to investigate the significance of these features on phosphatase-ligand binding, a series of seeded virtual screening experiments were conducted on three phosphatase enzymes, PTP1B, Cdc25b and IF2. It was observed that when the conserved arginine and P-loop amide interactions were used as pharmacophoric constraints during docking, enrichment of the virtual screen significantly increased in the three studied phosphatases, by up to a factor of two in some cases. Additionally, the use of such pharmacophoric constraints considerably improved the ability of docking to predict the inhibitor's bound pose, decreasing RMSD to the crystallographic geometry by 43% on average. Constrained docking improved enrichment of screens against both open and closed conformations of PTP1B. Incorporation of an ordered water molecule in PTP1B screening was also found to generally improve enrichment. The knowledge-based computational strategies explored here can potentially inform structure-based design of new phosphatase inhibitors using docking-based virtual screening. Copyright © 2014 Elsevier Inc. All rights reserved.

Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets.

PubMed

Feinstein, Wei P; Brylinski, Michal

2015-01-01

Computational approaches have emerged as an instrumental methodology in modern research. For example, virtual screening by molecular docking is routinely used in computer-aided drug discovery. One of the critical parameters for ligand docking is the size of a search space used to identify low-energy binding poses of drug candidates. Currently available docking packages often come with a default protocol for calculating the box size, however, many of these procedures have not been systematically evaluated. In this study, we investigate how the docking accuracy of AutoDock Vina is affected by the selection of a search space. We propose a new procedure for calculating the optimal docking box size that maximizes the accuracy of binding pose prediction against a non-redundant and representative dataset of 3,659 protein-ligand complexes selected from the Protein Data Bank. Subsequently, we use the Directory of Useful Decoys, Enhanced to demonstrate that the optimized docking box size also yields an improved ranking in virtual screening. Binding pockets in both datasets are derived from the experimental complex structures and, additionally, predicted by eFindSite. A systematic analysis of ligand binding poses generated by AutoDock Vina shows that the highest accuracy is achieved when the dimensions of the search space are 2.9 times larger than the radius of gyration of a docking compound. Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking. For instance, using predicted ligand binding sites, the average enrichment factor calculated for the top 1 % (10 %) of the screening library is 8.20 (3.28) for the optimized protocol, compared to 7.67 (3.19) for the default procedure. Depending on the evaluation metric, the optimal docking box size gives better ranking in virtual screening for about two-thirds of target proteins. This fully automated procedure can be used to optimize docking protocols in order to improve the ranking accuracy in production virtual screening simulations. Importantly, the optimized search space systematically yields better results than the default method not only for experimental pockets, but also for those predicted from protein structures. A script for calculating the optimal docking box size is freely available at www.brylinski.org/content/docking-box-size. Graphical AbstractWe developed a procedure to optimize the box size in molecular docking calculations. Left panel shows the predicted binding pose of NADP (green sticks) compared to the experimental complex structure of human aldose reductase (blue sticks) using a default protocol. Right panel shows the docking accuracy using an optimized box size.

The 3D Structure of the Binding Pocket of the Human Oxytocin Receptor for Benzoxazine Antagonists, Determined by Molecular Docking, Scoring Functions and 3D-QSAR Methods

NASA Astrophysics Data System (ADS)

Jójárt, Balázs; Martinek, Tamás A.; Márki, Árpád

2005-05-01

Molecular docking and 3D-QSAR studies were performed to determine the binding mode for a series of benzoxazine oxytocin antagonists taken from the literature. Structural hypotheses were generated by docking the most active molecule to the rigid receptor by means of AutoDock 3.05. The cluster analysis yielded seven possible binding conformations. These structures were refined by using constrained simulated annealing, and the further ligands were aligned in the refined receptor by molecular docking. A good correlation was found between the estimated Δ G bind and the p K i values for complex F. The Connolly-surface analysis, CoMFA and CoMSIA models q CoMFA 2 = 0.653, q CoMSA 2 = 0.630 and r pred,CoMFA 2 = 0.852 , r pred,CoMSIA 2 = 0.815) confirmed the scoring function results. The structural features of the receptor-ligand complex and the CoMFA and CoMSIA fields are in closely connected. These results suggest that receptor-ligand complex F is the most likely binding hypothesis for the studied benzoxazine analogs.

Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.

Protein-ligand docking with multiple flexible side chains

NASA Astrophysics Data System (ADS)

Zhao, Yong; Sanner, Michel F.

2008-09-01

In this work, we validate and analyze the results of previously published cross docking experiments and classify failed dockings based on the conformational changes observed in the receptors. We show that a majority of failed experiments (i.e. 25 out of 33, involving four different receptors: cAPK, CDK2, Ricin and HIVp) are due to conformational changes in side chains near the active site. For these cases, we identify the side chains to be made flexible during docking calculation by superimposing receptors and analyzing steric overlap between various ligands and receptor side chains. We demonstrate that allowing these side chains to assume rotameric conformations enables the successful cross docking of 19 complexes (ligand all atom RMSD < 2.0 Å) using our docking software FLIPDock. The number of side receptor side chains interacting with a ligand can vary according to the ligand's size and shape. Hence, when starting from a complex with a particular ligand one might have to extend the region of potential interacting side chains beyond the ones interacting with the known ligand. We discuss distance-based methods for selecting additional side chains in the neighborhood of the known active site. We show that while using the molecular surface to grow the neighborhood is more efficient than Euclidian-distance selection, the number of side chains selected by these methods often remains too large and additional methods for reducing their count are needed. Despite these difficulties, using geometric constraints obtained from the network of bonded and non-bonded interactions to rank residues and allowing the top ranked side chains to be flexible during docking makes 22 out of 25 complexes successful.

Ligand-based and structure-based approaches in identifying ideal pharmacophore against c-Jun N-terminal kinase-3.

PubMed

Kumar, B V S Suneel; Kotla, Rohith; Buddiga, Revanth; Roy, Jyoti; Singh, Sardar Shamshair; Gundla, Rambabu; Ravikumar, Muttineni; Sarma, Jagarlapudi A R P

2011-01-01

Structure and ligand based pharmacophore modeling and docking studies carried out using diversified set of c-Jun N-terminal kinase-3 (JNK3) inhibitors are presented in this paper. Ligand based pharmacophore model (LBPM) was developed for 106 inhibitors of JNK3 using a training set of 21 compounds to reveal structural and chemical features necessary for these molecules to inhibit JNK3. Hypo1 consisted of two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), and a hydrophobic (HY) feature with a correlation coefficient (r²) of 0.950. This pharmacophore model was validated using test set containing 85 inhibitors and had a good r² of 0.846. All the molecules were docked using Glide software and interestingly, all the docked conformations showed hydrogen bond interactions with important hinge region amino acids (Gln155 and Met149)and these interactions were compared with Hypo1 features. The results of ligand based pharmacophore model (LBPM)and docking studies are validated each other. The structure based pharmacophore model (SBPM) studies have identified additional features, two hydrogen bond donors and one hydrogen bond acceptor. The combination of these methodologies is useful in designing ideal pharmacophore which provides a powerful tool for the discovery of novel and selective JNK3 inhibitors.

Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets.

PubMed

Xu, Weijun; Lucke, Andrew J; Fairlie, David P

2015-04-01

Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson>0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches. Copyright © 2015 Elsevier Inc. All rights reserved.

Studies on interaction of insect repellent compounds with odorant binding receptor proteins by in silico molecular docking approach.

PubMed

Gopal, J Vinay; Kannabiran, K

2013-12-01

The aim of the study was to identify the interactions between insect repellent compounds and target olfactory proteins. Four compounds, camphor (C10H16O), carvacrol (C10H14O), oleic acid (C18H34O2) and firmotox (C22H28O5) were chosen as ligands. Seven olfactory proteins of insects with PDB IDs: 3K1E, 1QWV, 1TUJ, 1OOF, 2ERB, 3R1O and OBP1 were chosen for docking analysis. Patch dock was used and pymol for visualizing the structures. The interactions of these ligands with few odorant binding proteins showed binding energies. The ligand camphor had showed a binding energy of -136 kcal/mol with OBP1 protein. The ligand carvacrol interacted with 1QWV and 1TUJ proteins with a least binding energy of -117.45 kcal/mol and -21.78 kcal/mol respectively. The ligand oleic acid interacted with 1OOF, 2ERB, 3R1O and OBP1 with least binding energies. Ligand firmotox interacted with OBP1 and showed least binding energies. Three ligands (camphor, oleic acid and firmotox) had one, two, three interactions with a single protein OBP1 of Nilaparvatha lugens (Rice pest). From this in silico study we identified the interaction patterns for insect repellent compounds with the target insect odarant proteins. The results of our study revealed that the chosen ligands showed hydrogen bond interactions with the target olfactory receptor proteins.

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2018-01-01

Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions.

Quantum mechanical/molecular mechanical and docking study of the novel analogues based on hybridization of common pharmacophores as potential anti-breast cancer agents

PubMed Central

Asadi, Parvin; Khodarahmi, Ghadamali; Farrokhpour, Hossein; Hassanzadeh, Farshid; Saghaei, Lotfollah

2017-01-01

In an attempt to identify some new potential leads as anti-breast cancer agents, novel hybrid compounds were designed by molecular hybridization approach. These derivatives were structurally derived from hybrid benzofuran–imidazole and quinazolinone derivatives, which had shown good cytotoxicity against the breast cancer cell line (MCF-7). Since aromatase enzyme (CYP19) is highly expressed in the MCF-7 cell line, the binding of these novel hybrid compounds to aromatase was investigated using the docking method. In this study, due to the positive charge on the imidazole ring of the designed ligands and also, the presence of heme iron in the active site of the enzyme, it was decided to optimize the ligand inside the protein to obtain more realistic atomic charges for it. Quantum mechanical/molecular mechanical (QM/MM) method was used to obtain more accurate atomic charges of ligand for docking calculations by considering the polarization effects of CYP19 on ligands. It was observed that the refitted charge improved the binding energy of the docked compounds. Also, the results showed that these novel hybrid compounds were adopted properly within the aromatase binding site, thereby suggesting that they could be potential inhibitors of aromatase. The main binding modes in these complexes were through hydrophobic and H bond interactions showing agreement with the basic physicochemical features of known anti aromatase compounds. Finally, the complex structures obtained from the docking study were used for single point QM/MM calculations to obtain more accurate electronic interaction energy, considering the electronic polarization of the ligand by its protein environment. PMID:28626481

Insight into the Meligethes aeneus voltage-sensitive sodium channel structure and an attempt to select the best pyrethroid ligands.

PubMed

Obrępalska-Stęplowska, Aleksandra; Czerwoniec, Anna; Wieczorek, Przemysław; Wrzesińska, Barbara

2016-01-01

The voltage-sensitive sodium channel (VSSC) is a target for the pharmacological action of pyrethroids which are used in controlling pests, including those of agricultural importance. Among these is the pollen beetle (Meligethes aeneus F.) - the most serious pest of Brassica napus. Owing to the heavy use of pyrethroids, a widespread build-up of resistance has occurred. The main cause of pyrethroid insensitivity in M. aeneus is considered to be an increased oxidative metabolism; however, the additional mechanism of resistance associated with mutations in the VSSC might contribute to this phenomenon. We generated a VSSC 3D model to study the docking affinities of pyrethroids to their target site within the channel. Our goal was to identify the pyrethroids for which docking affinity scores were high and not affected by potential mutations in the VSSC. We found that the docking scores of cypermethrin are hardly influenced by the appearance of point mutations. Additionally, tau-fluvalinate, deltamethrin and bifenthrin are VSSC ligands with high affinity scores. Our docking models suggest that point mutations in the VSSC binding pocket might affect the stability of ligand interactions and change the pattern of ligand docking locations, which might have a potential effect on VSSC gating properties. © 2015 Society of Chemical Industry.

Discover binding pathways using the sliding binding-box docking approach: application to binding pathways of oseltamivir to avian influenza H5N1 neuraminidase

NASA Astrophysics Data System (ADS)

Tran, Diem-Trang T.; Le, Ly T.; Truong, Thanh N.

2013-08-01

Drug binding and unbinding are transient processes which are hardly observed by experiment and difficult to analyze by computational techniques. In this paper, we employed a cost-effective method called "pathway docking" in which molecular docking was used to screen ligand-receptor binding free energy surface to reveal possible paths of ligand approaching protein binding pocket. A case study was applied on oseltamivir, the key drug against influenza a virus. The equilibrium pathways identified by this method are found to be similar to those identified in prior studies using highly expensive computational approaches.

CDOCKER and lambda λ -dynamics for prospective prediction in D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Ding, Xinqiang; Hayes, Ryan L.; Vilseck, Jonah Z.; Charles, Murchtricia K.; Brooks, Charles L.

2018-01-01

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and λ-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 Å. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 Å for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For λ-dynamics techniques, including multisite λ-dynamics (MSλD), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

CDOCKER and λ-dynamics for prospective prediction in D₃R Grand Challenge 2.

PubMed

Ding, Xinqiang; Hayes, Ryan L; Vilseck, Jonah Z; Charles, Murchtricia K; Brooks, Charles L

2018-01-01

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and [Formula: see text]-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 [Formula: see text]. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 [Formula: see text] for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For [Formula: see text]-dynamics techniques, including multisite [Formula: see text]-dynamics (MS[Formula: see text]D), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems.

PubMed

Kellenberger, Esther; Foata, Nicolas; Rognan, Didier

2008-05-01

Structure-based virtual screening is a promising tool to identify putative targets for a specific ligand. Instead of docking multiple ligands into a single protein cavity, a single ligand is docked in a collection of binding sites. In inverse screening, hits are in fact targets which have been prioritized within the pool of best ranked proteins. The target rate depends on specificity and promiscuity in protein-ligand interactions and, to a considerable extent, on the effectiveness of the scoring function, which still is the Achilles' heel of molecular docking. In the present retrospective study, virtual screening of the sc-PDB target library by GOLD docking was carried out for four compounds (biotin, 4-hydroxy-tamoxifen, 6-hydroxy-1,6-dihydropurine ribonucleoside, and methotrexate) of known sc-PDB targets and, several ranking protocols based on GOLD fitness score and topological molecular interaction fingerprint (IFP) comparison were evaluated. For the four investigated ligands, the fusion of GOLD fitness and two IFP scores allowed the recovery of most targets, including the rare proteins which are not readily suitable for statistical analysis, while significantly filtering out most false positive entries. The current survey suggests that selecting a small number of targets (<20) for experimental evaluation is achievable with a pure structure-based approach.

A High Performance Cloud-Based Protein-Ligand Docking Prediction Algorithm

PubMed Central

Chen, Jui-Le; Yang, Chu-Sing

2013-01-01

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result. PMID:23762864

A cross docking pipeline for improving pose prediction and virtual screening performance

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2018-01-01

Pose prediction and virtual screening performance of a molecular docking method depend on the choice of protein structures used for docking. Multiple structures for a target protein are often used to take into account the receptor flexibility and problems associated with a single receptor structure. However, the use of multiple receptor structures is computationally expensive when docking a large library of small molecules. Here, we propose a new cross-docking pipeline suitable to dock a large library of molecules while taking advantage of multiple target protein structures. Our method involves the selection of a suitable receptor for each ligand in a screening library utilizing ligand 3D shape similarity with crystallographic ligands. We have prospectively evaluated our method in D3R Grand Challenge 2 and demonstrated that our cross-docking pipeline can achieve similar or better performance than using either single or multiple-receptor structures. Moreover, our method displayed not only decent pose prediction performance but also better virtual screening performance over several other methods.

Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.

Exploring the Stability of Ligand Binding Modes to Proteins by Molecular Dynamics Simulations: A Cross-docking Study.

PubMed

Liu, Kai; Kokubo, Hironori

2017-10-23

Docking has become an indispensable approach in drug discovery research to predict the binding mode of a ligand. One great challenge in docking is to efficiently refine the correct pose from various putative docking poses through scoring functions. We recently examined the stability of self-docking poses under molecular dynamics (MD) simulations and showed that equilibrium MD simulations have some capability to discriminate between correct and decoy poses. Here, we have extended our previous work to cross-docking studies for practical applications. Three target proteins (thrombin, heat shock protein 90-alpha, and cyclin-dependent kinase 2) of pharmaceutical interest were selected. Three comparable poses (one correct pose and two decoys) for each ligand were then selected from the docking poses. To obtain the docking poses for the three target proteins, we used three different protocols, namely: normal docking, induced fit docking (IFD), and IFD against the homology model. Finally, five parallel MD equilibrium runs were performed on each pose for the statistical analysis. The results showed that the correct poses were generally more stable than the decoy poses under MD. The discrimination capability of MD depends on the strategy. The safest way was to judge a pose as being stable if any one run among five parallel runs was stable under MD. In this case, 95% of the correct poses were retained under MD, and about 25-44% of the decoys could be excluded by the simulations for all cases. On the other hand, if we judge a pose as being stable when any two or three runs were stable, with the risk of incorrectly excluding some correct poses, approximately 31-53% or 39-56% of the two decoys could be excluded by MD, respectively. Our results suggest that simple equilibrium simulations can serve as an effective filter to exclude decoy poses that cannot be distinguished by docking scores from the computationally expensive free-energy calculations.

Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes.

PubMed

Uchikoga, Nobuyuki; Hirokawa, Takatsugu

2010-05-11

Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG), CaM kinase kinase (CaMKK) and the plasma membrane Ca2+ ATPase pump (PMCA), and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

Biologically active ligands for yersinia outer protein H (YopH): feature based pharmacophore screening, docking and molecular dynamics studies.

PubMed

Tamilvanan, Thangaraju; Hopper, Waheeta

2014-01-01

Yersinia pestis, a Gram negative bacillus, spreads via lymphatic to lymph nodes and to all organs through the bloodstream, causing plague. Yersinia outer protein H (YopH) is one of the important effector proteins, which paralyzes lymphocytes and macrophages by dephosphorylating critical tyrosine kinases and signal transduction molecules. The purpose of the study is to generate a three-dimensional (3D) pharmacophore model by using diverse sets of YopH inhibitors, which would be useful for designing of potential antitoxin. In this study, we have selected 60 biologically active inhibitors of YopH to perform Ligand based pharmacophore study to elucidate the important structural features responsible for biological activity. Pharmacophore model demonstrated the importance of two acceptors, one hydrophobic and two aromatic features toward the biological activity. Based on these features, different databases were screened to identify novel compounds and these ligands were subjected for docking, ADME properties and Binding energy prediction. Post docking validation was performed using molecular dynamics simulation for selected ligands to calculate the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF). The ligands, ASN03270114, Mol_252138, Mol_31073 and ZINC04237078 may act as inhibitors against YopH of Y. pestis.

Conformational analysis, X-ray crystallographic, FT-IR, FT-Raman, DFT, MEP and molecular docking studies on 1-(1-(3-methoxyphenyl) ethylidene) thiosemicarbazide

NASA Astrophysics Data System (ADS)

Saravanan, R. R.; Seshadri, S.; Gunasekaran, S.; Mendoza-Meroño, R.; Garcia-Granda, S.

2015-03-01

Conformational analysis, X-ray crystallographic, FT-IR, FT-Raman, DFT, MEP and molecular docking studies on 1-(1-(3-methoxyphenyl) ethylidene) thiosemicarbazide (MPET) are investigated. From conformational analysis the examination of the positions of a molecule taken and the energy changes is observed. The docking studies of the ligand MPET with target protein showed that this is a good molecule which docks well with target related to HMG-CoA. Hence MPET can be considered for developing into a potent anti-cholesterol drug. MEP assists in optimization of electrostatic interactions between the protein and the ligand. The MEP surface displays the molecular shape, size and electrostatic potential values. The optimized geometry of the compound was calculated from the DFT-B3LYP gradient calculations employing 6-31G (d, p) basis set and calculated vibrational frequencies are evaluated via comparison with experimental values.

Molecular modeling, dynamics studies and density functional theory approaches to identify potential inhibitors of SIRT4 protein from Homo sapiens : a novel target for the treatment of type 2 diabetes.

PubMed

Choubey, Sanjay K; Prabhu, Dhamodharan; Nachiappan, Mutharasappan; Biswal, Jayshree; Jeyakanthan, Jeyaraman

2017-11-01

Type 2 diabetes is one of the biggest health challenges in the world and WHO projects it to be the 7th leading cause of death in 2030. It is a chronic condition affecting the way our body metabolizes sugar. Insulin resistance is high risk factor marked by expression of Lipoprotein Lipases and Peroxisome Proliferator-Activated Receptor that predisposes to type 2 diabetes. AMP-dependent protein kinase in AMPK signaling pathway is a central sensor of energy status. Deregulation of AMPK signaling leads to inflammation, oxidative stress, and deactivation of autophagy which are implicated in pathogenesis of insulin resistance. SIRT4 protein deactivates AMPK as well as directly inhibits insulin secretion. SIRT4 overexpression leads to dyslipidimeia, decreased fatty acid oxidation, and lipogenesis which are the characteristic features of insulin resistance promoting type 2 diabetes. This makes SIRT4 a novel therapeutic target to control type 2 diabetes. Virtual screening and molecular docking studies were performed to obtain potential ligands. To further optimize the geometry of protein-ligand complexes Quantum Polarized Ligand Docking was performed. Binding Free Energy was calculated for the top three ligand molecules. In view of exploring the stereoelectronic features of the ligand, density functional theory approach was implemented at B3LYP/6-31G* level. 30 ns MD simulation studies of the protein-ligand complexes were done. The present research work proposes ZINC12421989 as potential inhibitor of SIRT4 with docking score (-7.54 kcal/mol), docking energy (-51.34 kcal/mol), binding free energy (-70.21 kcal/mol), and comparatively low energy gap (-0.1786 eV) for HOMO and LUMO indicating reactivity of the lead molecule.

Chemical system biology based molecular interactions to identify inhibitors against Q151M mutant of HIV-1 reverse transcriptase.

PubMed

Pandey, Rajan Kumar; Sharma, Drista; Ojha, Rupal; Bhatt, Tarun Kumar; Prajapati, Vijay Kumar

2018-05-09

The emergence of mutations leading to drug resistance is the main cause of therapeutic failure in the human HIV infection. Chemical system biology approach has drawn great attention to discover new antiretroviral hits with high efficacy and negligible toxicity, which can be used as a prerequisite for HIV drug resistance global action plan 2017-21. To discover potential hits, we docked 49 antiretroviral analogs (n = 6294) against HIV-1 reverse transcriptase Q151M mutant & its wild-type form and narrow downed their number in three sequential modes of docking using Schrödinger suite. Later on, 80 ligands having better docking score than reference ligands (tenofovir and lamivudine) were screened for ADME, toxicity prediction, and binding energy estimation. Simultaneously, the area under the curve (AUC) was estimated using receiver operating characteristics (ROC) curve analysis to validate docking protocols. Finally, single point energy and molecular dynamics simulation approaches were performed for best two ligands (L3 and L14). This study reveals the antiretroviral efficacy of obtained two best ligands and delivers the hits against HIV-1 reverse transcriptase Q151M mutant. Copyright © 2018 Elsevier B.V. All rights reserved.

Distinguishing Binders from False Positives by Free Energy Calculations: Fragment Screening Against the Flap Site of HIV Protease

PubMed Central

2015-01-01

Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand–receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein–ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets. PMID:25189630

Influence of protonation, tautomeric, and stereoisomeric states on protein-ligand docking results.

PubMed

ten Brink, Tim; Exner, Thomas E

2009-06-01

In this work, we present a systematical investigation of the influence of ligand protonation states, stereoisomers, and tautomers on results obtained with the two protein-ligand docking programs GOLD and PLANTS. These different states were generated with a fully automated tool, called SPORES (Structure PrOtonation and Recognition System). First, the most probable protonations, as defined by this rule based system, were compared to the ones stored in the well-known, manually revised CCDC/ASTEX data set. Then, to investigate the influence of the ligand protonation state on the docking results, different protonation states were created. Redocking and virtual screening experiments were conducted demonstrating that both docking programs have problems in identifying the correct protomer for each complex. Therefore, a preselection of plausible protomers or the improvement of the scoring functions concerning their ability to rank different molecules/states is needed. Additionally, ligand stereoisomers were tested for a subset of the CCDC/ASTEX set, showing similar problems regarding the ranking of these stereoisomers as the ranking of the protomers.

Knowing when to give up: early-rejection stratagems in ligand docking

NASA Astrophysics Data System (ADS)

Skone, Gwyn; Voiculescu, Irina; Cameron, Stephen

2009-10-01

Virtual screening is an important resource in the drug discovery community, of which protein-ligand docking is a significant part. Much software has been developed for this purpose, largely by biochemists and those in related disciplines, who pursue ever more accurate representations of molecular interactions. The resulting tools, however, are very processor-intensive. This paper describes some initial results from a project to review computational chemistry techniques for docking from a non-chemistry standpoint. An abstract blueprint for protein-ligand docking using empirical scoring functions is suggested, and this is used to discuss potential improvements. By introducing computer science tactics such as lazy function evaluation, dramatic increases to throughput can and have been realized using a real-world docking program. Naturally, they can be extended to any system that approximately corresponds to the architecture outlined.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860

Role of binding entropy in the refinement of protein-ligand docking predictions: analysis based on the use of 11 scoring functions.

PubMed

Ruvinsky, Anatoly M

2007-06-01

We present results of testing the ability of eleven popular scoring functions to predict native docked positions using a recently developed method (Ruvinsky and Kozintsev, J Comput Chem 2005, 26, 1089) for estimation the entropy contributions of relative motions to protein-ligand binding affinity. The method is based on the integration of the configurational integral over clusters obtained from multiple docked positions. We use a test set of 100 PDB protein-ligand complexes and ensembles of 101 docked positions generated by (Wang et al. J Med Chem 2003, 46, 2287) for each ligand in the test set. To test the suggested method we compared the averaged root-mean square deviations (RMSD) of the top-scored ligand docked positions, accounting and not accounting for entropy contributions, relative to the experimentally determined positions. We demonstrate that the method increases docking accuracy by 10-21% when used in conjunction with the AutoDock scoring function, by 2-25% with G-Score, by 7-41% with D-Score, by 0-8% with LigScore, by 1-6% with PLP, by 0-12% with LUDI, by 2-8% with F-Score, by 7-29% with ChemScore, by 0-9% with X-Score, by 2-19% with PMF, and by 1-7% with DrugScore. We also compared the performance of the suggested method with the method based on ranking by cluster occupancy only. We analyze how the choice of a clustering-RMSD and a low bound of dense clusters impacts on docking accuracy of the scoring methods. We derive optimal intervals of the clustering-RMSD for 11 scoring functions.

WScore: A Flexible and Accurate Treatment of Explicit Water Molecules in Ligand-Receptor Docking.

PubMed

Murphy, Robert B; Repasky, Matthew P; Greenwood, Jeremy R; Tubert-Brohman, Ivan; Jerome, Steven; Annabhimoju, Ramakrishna; Boyles, Nicholas A; Schmitz, Christopher D; Abel, Robert; Farid, Ramy; Friesner, Richard A

2016-05-12

We have developed a new methodology for protein-ligand docking and scoring, WScore, incorporating a flexible description of explicit water molecules. The locations and thermodynamics of the waters are derived from a WaterMap molecular dynamics simulation. The water structure is employed to provide an atomic level description of ligand and protein desolvation. WScore also contains a detailed model for localized ligand and protein strain energy and integrates an MM-GBSA scoring component with these terms to assess delocalized strain of the complex. Ensemble docking is used to take into account induced fit effects on the receptor conformation, and protein reorganization free energies are assigned via fitting to experimental data. The performance of the method is evaluated for pose prediction, rank ordering of self-docked complexes, and enrichment in virtual screening, using a large data set of PDB complexes and compared with the Glide SP and Glide XP models; significant improvements are obtained.

A Critical Assessment of the Performance of Protein-ligand Scoring Functions Based on NMR Chemical Shift Perturbations

PubMed Central

Wang, Bing; Westerhoff, Lance M.; Merz, Kenneth M.

2008-01-01

We have generated docking poses for the FKBP-GPI complex using eight docking programs, and compared their scoring functions with scoring based on NMR chemical shift perturbations (NMRScore). Because the chemical shift perturbation (CSP) is exquisitely sensitive on the orientation of ligand inside the binding pocket, NMRScore offers an accurate and straightforward approach to score different poses. All scoring functions were inspected by their abilities to highly rank the native-like structures and separate them from decoy poses generated for a protein-ligand complex. The overall performance of NMRScore is much better than that of energy-based scoring functions associated with docking programs in both aspects. In summary, we find that the combination of docking programs with NMRScore results in an approach that can robustly determine the binding site structure for a protein-ligand complex, thereby, providing a new tool facilitating the structure-based drug discovery process. PMID:17867664

Molecular Docking, Molecular Dynamics Simulations, Computational Screening to Design Quorum Sensing Inhibitors Targeting LuxP of Vibrio harveyi and Its Biological Evaluation.

PubMed

Rajamanikandan, Sundaraj; Jeyakanthan, Jeyaraman; Srinivasan, Pappu

2017-01-01

Quorum sensing (QS) plays an important role in the biofilm formation, production of virulence factors and stress responses in Vibrio harveyi. Therefore, interrupting QS is a possible approach to modulate bacterial behavior. In the present study, three docking protocols, such as Rigid Receptor Docking (RRD), Induced Fit Docking (IFD), and Quantum Polarized Ligand Docking (QPLD) were used to elucidate the binding mode of boronic acid derivatives into the binding pocket of LuxP protein in V. harveyi. Among the three docking protocols, IFD accurately predicted the correct binding mode of the studied inhibitors. Molecular dynamics (MD) simulations of the protein-ligand complexes indicates that the inter-molecular hydrogen bonds formed between the protein and ligand complex remains stable during the simulation time. Pharmacophore and shape-based virtual screening were performed to find selective and potent compounds from ChemBridge database. Five hit compounds were selected and subjected to IFD and MD simulations to validate the binding mode. In addition, enrichment calculation was performed to discriminate and separate active compounds from the inactive compounds. Based on the computational studies, the potent Bicyclo [2.2.1] hept-5-ene-2,3-dicarboxylic acid-2,6-dimethylpyridine 1-oxide (ChemBridge_5144368) was selected for in vitro assays. The compound exhibited dose dependent inhibition in bioluminescence and also inhibits biofilm formation in V. harveyi to the level of 64.25 %. The result from the study suggests that ChemBridge_5144368 could serve as an anti-quorum sensing molecule for V. harveyi.

Accuracy of binding mode prediction with a cascadic stochastic tunneling method.

PubMed

Fischer, Bernhard; Basili, Serena; Merlitz, Holger; Wenzel, Wolfgang

2007-07-01

We investigate the accuracy of the binding modes predicted for 83 complexes of the high-resolution subset of the ASTEX/CCDC receptor-ligand database using the atomistic FlexScreen approach with a simple forcefield-based scoring function. The median RMS deviation between experimental and predicted binding mode was just 0.83 A. Over 80% of the ligands dock within 2 A of the experimental binding mode, for 60 complexes the docking protocol locates the correct binding mode in all of ten independent simulations. Most docking failures arise because (a) the experimental structure clashed in our forcefield and is thus unattainable in the docking process or (b) because the ligand is stabilized by crystal water. 2007 Wiley-Liss, Inc.

Application of Shape Similarity in Pose Selection and Virtual Screening in CSARdock2014 Exercise.

PubMed

Kumar, Ashutosh; Zhang, Kam Y J

2016-06-27

To evaluate the applicability of shape similarity in docking-based pose selection and virtual screening, we participated in the CSARdock2014 benchmark exercise for identifying the correct docking pose of inhibitors targeting factor XA, spleen tyrosine kinase, and tRNA methyltransferase. This exercise provides a valuable opportunity for researchers to test their docking programs, methods, and protocols in a blind testing environment. In the CSARdock2014 benchmark exercise, we have implemented an approach that uses ligand 3D shape similarity to facilitate docking-based pose selection and virtual screening. We showed here that ligand 3D shape similarity between bound poses could be used to identify the native-like pose from an ensemble of docking-generated poses. Our method correctly identified the native pose as the top-ranking pose for 73% of test cases in a blind testing environment. Moreover, the pose selection results also revealed an excellent correlation between ligand 3D shape similarity scores and RMSD to X-ray crystal structure ligand. In the virtual screening exercise, the average RMSD for our pose prediction was found to be 1.02 Å, and it was one of the top performances achieved in CSARdock2014 benchmark exercise. Furthermore, the inclusion of shape similarity improved virtual screening performance of docking-based scoring and ranking. The coefficient of determination (r(2)) between experimental activities and docking scores for 276 spleen tyrosine kinase inhibitors was found to be 0.365 but reached 0.614 when the ligand 3D shape similarity was included.

SKATE: a docking program that decouples systematic sampling from scoring.

PubMed

Feng, Jianwen A; Marshall, Garland R

2010-11-15

SKATE is a docking prototype that decouples systematic sampling from scoring. This novel approach removes any interdependence between sampling and scoring functions to achieve better sampling and, thus, improves docking accuracy. SKATE systematically samples a ligand's conformational, rotational and translational degrees of freedom, as constrained by a receptor pocket, to find sterically allowed poses. Efficient systematic sampling is achieved by pruning the combinatorial tree using aggregate assembly, discriminant analysis, adaptive sampling, radial sampling, and clustering. Because systematic sampling is decoupled from scoring, the poses generated by SKATE can be ranked by any published, or in-house, scoring function. To test the performance of SKATE, ligands from the Asetex/CDCC set, the Surflex set, and the Vertex set, a total of 266 complexes, were redocked to their respective receptors. The results show that SKATE was able to sample poses within 2 A RMSD of the native structure for 98, 95, and 98% of the cases in the Astex/CDCC, Surflex, and Vertex sets, respectively. Cross-docking accuracy of SKATE was also assessed by docking 10 ligands to thymidine kinase and 73 ligands to cyclin-dependent kinase. 2010 Wiley Periodicals, Inc.

Application of the docking program SOL for CSAR benchmark.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Vladimir B

2013-08-26

This paper is devoted to results obtained by the docking program SOL and the post-processing program DISCORE at the CSAR benchmark. SOL and DISCORE programs are described. SOL is the original docking program developed on the basis of the genetic algorithm, MMFF94 force field, rigid protein, precalculated energy grid including desolvation in the frame of simplified GB model, vdW, and electrostatic interactions and taking into account the ligand internal strain energy. An important SOL feature is the single- or multi-processor performance for up to hundreds of CPUs. DISCORE improves the binding energy scoring by the local energy optimization of the ligand docked pose and a simple linear regression on the base of available experimental data. The docking program SOL has demonstrated a good ability for correct ligand positioning in the active sites of the tested proteins in most cases of CSAR exercises. SOL and DISCORE have not demonstrated very exciting results on the protein-ligand binding free energy estimation. Nevertheless, for some target proteins, SOL and DISCORE were among the first in prediction of inhibition activity. Ways to improve SOL and DISCORE are discussed.

The Importance of Ligand Conformational Energies in Carbohydrate Docking: Sorting the Wheat from the Chaff

PubMed Central

Nivedha, Anita K.; Makeneni, Spandana; Foley, B. Lachele; Tessier, Matthew B.; Woods, Robert J.

2014-01-01

Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand-specific conformational energies. Here, we develop internal energy functions, Carbohydrate Intrinsic (CHI), to account for the rotational preferences of the glycosidic torsion angles in carbohydrates. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide-protein complexes in the Protein Data Bank. Addition of CHI energies to the standard docking scores in Autodock 3, 4.2, and Vina consistently improves pose ranking of oligosaccharides docked to a set of anti-carbohydrate antibodies. The CHI energy functions are also independent of docking algorithm, and with minor modifications, may be incorporated into both theoretical modeling methods, and experimental NMR or X-ray structure refinement programs. PMID:24375430

Improving Docking Performance Using Negative Image-Based Rescoring.

PubMed

Kurkinen, Sami T; Niinivehmas, Sanna; Ahinko, Mira; Lätti, Sakari; Pentikäinen, Olli T; Postila, Pekka A

2018-01-01

Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases.

New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Katkova, Ekaterina V; Ilin, Ivan S; Sulimov, Vladimir B

2017-11-01

Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field. Copyright © 2017 Elsevier Inc. All rights reserved.

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

PubMed

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

LigandRNA: computational predictor of RNA–ligand interactions

PubMed Central

Philips, Anna; Milanowska, Kaja; Łach, Grzegorz; Bujnicki, Janusz M.

2013-01-01

RNA molecules have recently become attractive as potential drug targets due to the increased awareness of their importance in key biological processes. The increase of the number of experimentally determined RNA 3D structures enabled structure-based searches for small molecules that can specifically bind to defined sites in RNA molecules, thereby blocking or otherwise modulating their function. However, as of yet, computational methods for structure-based docking of small molecule ligands to RNA molecules are not as well established as analogous methods for protein-ligand docking. This motivated us to create LigandRNA, a scoring function for the prediction of RNA–small molecule interactions. Our method employs a grid-based algorithm and a knowledge-based potential derived from ligand-binding sites in the experimentally solved RNA–ligand complexes. As an input, LigandRNA takes an RNA receptor file and a file with ligand poses. As an output, it returns a ranking of the poses according to their score. The predictive power of LigandRNA favorably compares to five other publicly available methods. We found that the combination of LigandRNA and Dock6 into a “meta-predictor” leads to further improvement in the identification of near-native ligand poses. The LigandRNA program is available free of charge as a web server at http://ligandrna.genesilico.pl. PMID:24145824

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

NASA Astrophysics Data System (ADS)

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations.

PubMed

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

GENIUS In Silico Screening Technology for HCV Drug Discovery.

PubMed

Patil, Vaishali M; Masand, Neeraj; Gupta, Satya P

2016-01-01

The various reported in silico screening protocols such as molecular docking are associated with various drawbacks as well as benefits. In molecular docking, on interaction with ligand, the protein or receptor molecule gets activated by adopting conformational changes. These conformational changes cannot be utilized to predict the 3D structure of a protein-ligand complex from unbound protein conformations rigid docking, which necessitates the demand for understanding protein flexibility. Therefore, efficiency and accuracy of docking should be achieved and various available/developed protocols may be adopted. One such protocol is GENIUS induced-fit docking and it is used effectively for the development of anti-HCV NS3-4A serine protease inhibitors. The present review elaborates the GENIUS docking protocol along with its benefits and drawbacks.

Exploring the binding energy profiles of full agonists, partial agonists, and antagonists of the α7 nicotinic acetylcholine receptor.

PubMed

Tabassum, Nargis; Ma, Qianyun; Wu, Guanzhao; Jiang, Tao; Yu, Rilei

2017-09-01

Nicotinic acetylcholine receptors (nAChRs) belong to the Cys-loop receptor family and are important drug targets for the treatment of neurological diseases. However, the precise determinants of the binding efficacies of ligands for these receptors are unclear. Therefore, in this study, the binding energy profiles of various ligands (full agonists, partial agonists, and antagonists) were quantified by docking those ligands with structural ensembles of the α7 nAChR exhibiting different degrees of C-loop closure. This approximate treatment of interactions suggested that full agonists, partial agonists, and antagonists of the α7 nAChR possess distinctive binding energy profiles. Results from docking revealed that ligand binding efficacy may be related to the capacity of the ligand to stabilize conformational states with a closed C loop.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

PubMed Central

Frimurer, Thomas M.; Meiler, Jens

2013-01-01

The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 103 fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes. PMID:23844000

Homology modeling, molecular docking and electrostatic potential analysis of MurF ligase from Klebsiella pneumonia

PubMed Central

Sivaramakrishnan, Venkatabalasubramanian; Thiyagarajan, Chinnaiyan; Kalaivanan, Sivakumaran; Selvakumar, Raj; Anusuyadevi, Muthuswamy; Jayachandran, Kesavan Swaminathan

2012-01-01

In spite of availability of moderately protective vaccine and antibiotics, new antibacterial agents are urgently needed to decrease the global incidence of Klebsiella pneumonia infections. MurF ligase, a key enzyme, which participates in the bacterial cell wall assembly, is indispensable to existence of K. pneumonia. MurF ligase lack mammalian vis-à-vis and have high specificity, uniqueness, and occurrence only in eubacteria, epitomizing them as promising therapeutic targets for intervention. In this study, we present a unified approach involving homology modeling and molecular docking studies on MurF ligase enzyme. As part of this study, a homology model of K. pneumonia (MurF ligase) enzyme was predicted for the first time in order to carry out structurebased drug design. The accuracy of the model was further validated using different computational approaches. The comparative molecular docking study on this enzyme was undertaken using different phyto-ligands from Desmodium sp. and a known antibiotic Ciprofloxacin. The docking analysis indicated the importance of hotspots (HIS 281 and ASN 282) within the MurF binding pocket. The Lipinski's rule of five was analyzed for all ligands considered for this study by calculating the ADME/Tox, drug likeliness using Qikprop simulation. Only ten ligands were found to comply with the Lipinski rule of five. Based on the molecular docking results and Lipinki values 6-Methyltetrapterol A was confirmed as a promising lead compound. The present study should therefore play a guiding role in the experimental design and development of 6-Methyltetrapterol A as a bactericidal agent. PMID:22715301

Docking screens: right for the right reasons?

PubMed

Kolb, Peter; Irwin, John J

2009-01-01

Whereas docking screens have emerged as the most practical way to use protein structure for ligand discovery, an inconsistent track record raises questions about how well docking actually works. In its favor, a growing number of publications report the successful discovery of new ligands, often supported by experimental affinity data and controls for artifacts. Few reports, however, actually test the underlying structural hypotheses that docking makes. To be successful and not just lucky, prospective docking must not only rank a true ligand among the top scoring compounds, it must also correctly orient the ligand so the score it receives is biophysically sound. If the correct binding pose is not predicted, a skeptic might well infer that the discovery was serendipitous. Surveying over 15 years of the docking literature, we were surprised to discover how rarely sufficient evidence is presented to establish whether docking actually worked for the right reasons. The paucity of experimental tests of theoretically predicted poses undermines confidence in a technique that has otherwise become widely accepted. Of course, solving a crystal structure is not always possible, and even when it is, it can be a lot of work, and is not readily accessible to all groups. Even when a structure can be determined, investigators may prefer to gloss over an erroneous structural prediction to better focus on their discovery. Still, the absence of a direct test of theory by experiment is a loss for method developers seeking to understand and improve docking methods. We hope this review will motivate investigators to solve structures and compare them with their predictions whenever possible, to advance the field.

Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015.

PubMed

Deng, Nanjie; Flynn, William F; Xia, Junchao; Vijayan, R S K; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Deng, Nanjie; Flynn, William F.; Xia, Junchao; Vijayan, R. S. K.; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M.

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

The application of quantum mechanics in structure-based drug design.

PubMed

Mucs, Daniel; Bryce, Richard A

2013-03-01

Computational chemistry has become an established and valuable component in structure-based drug design. However the chemical complexity of many ligands and active sites challenges the accuracy of the empirical potentials commonly used to describe these systems. Consequently, there is a growing interest in utilizing electronic structure methods for addressing problems in protein-ligand recognition. In this review, the authors discuss recent progress in the development and application of quantum chemical approaches to modeling protein-ligand interactions. The authors specifically consider the development of quantum mechanics (QM) approaches for studying large molecular systems pertinent to biology, focusing on protein-ligand docking, protein-ligand binding affinities and ligand strain on binding. Although computation of binding energies remains a challenging and evolving area, current QM methods can underpin improved docking approaches and offer detailed insights into ligand strain and into the nature and relative strengths of complex active site interactions. The authors envisage that QM will become an increasingly routine and valued tool of the computational medicinal chemist.

How to benchmark methods for structure-based virtual screening of large compound libraries.

PubMed

Christofferson, Andrew J; Huang, Niu

2012-01-01

Structure-based virtual screening is a useful computational technique for ligand discovery. To systematically evaluate different docking approaches, it is important to have a consistent benchmarking protocol that is both relevant and unbiased. Here, we describe the designing of a benchmarking data set for docking screen assessment, a standard docking screening process, and the analysis and presentation of the enrichment of annotated ligands among a background decoy database.

Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016

NASA Astrophysics Data System (ADS)

Fradera, Xavier; Verras, Andreas; Hu, Yuan; Wang, Deping; Wang, Hongwu; Fells, James I.; Armacost, Kira A.; Crespo, Alejandro; Sherborne, Brad; Wang, Huijun; Peng, Zhengwei; Gao, Ying-Duo

2018-01-01

We describe the performance of multiple pose prediction methods for the D3R 2016 Grand Challenge. The pose prediction challenge includes 36 ligands, which represent 4 chemotypes and some miscellaneous structures against the FXR ligand binding domain. In this study we use a mix of fully automated methods as well as human-guided methods with considerations of both the challenge data and publicly available data. The methods include ensemble docking, colony entropy pose prediction, target selection by molecular similarity, molecular dynamics guided pose refinement, and pose selection by visual inspection. We evaluated the success of our predictions by method, chemotype, and relevance of publicly available data. For the overall data set, ensemble docking, visual inspection, and molecular dynamics guided pose prediction performed the best with overall mean RMSDs of 2.4, 2.2, and 2.2 Å respectively. For several individual challenge molecules, the best performing method is evaluated in light of that particular ligand. We also describe the protein, ligand, and public information data preparations that are typical of our binding mode prediction workflow.

Insights into the binding modes of CC chemokine receptor 4 (CCR4) inhibitors: a combined approach involving homology modelling, docking, and molecular dynamics simulation studies.

PubMed

Gadhe, Changdev G; Kim, Mi-hyun

2015-02-01

CC chemokine receptor 4 (CCR4), a G protein-coupled receptor (GPCR), plays a vital role in the progression of asthma, T-cell lymphoma, inflammation, and Alzheimer's disease. To date, the structure of CCR4 has not been determined. Therefore, the nature of the interactions between inhibitors and CCR4 is not well known. In this study, we used CCR5 as a template to model the structure of CCR4. Docking studies were performed for four naphthalene-sulphonamide derivatives and crucial ligand-protein interactions were analysed. Molecular dynamics (MD) simulations of these complexes (100 ns each) were carried out to gain insights into the interactions between ligands and CCR4. MD simulations revealed that the residues identified by the docking were displaced and new residues were inserted near the ligands. Results of a principal component analysis (PCA) suggested that CCR4 unfolds at the extracellular site surrounding the ligands. Our simulations identified crucial residues involved in CCR4 antagonism, which were supported by previous mutational studies. Additionally, we identified Ser3.29, Leu3.33, Ser5.39, Phe6.47, Ile7.35, Thr7.38, Thr7.40, and Ala7.42 as residues that play crucial roles in CCR4 antagonism. Mutational studies will help elucidate the significance of these residues in CCR4 antagonism. An understanding of ligand-CCR4 interactions might aid in the design of novel CCR4 inhibitors.

PyPLIF: Python-based Protein-Ligand Interaction Fingerprinting.

PubMed

Radifar, Muhammad; Yuniarti, Nunung; Istyastono, Enade Perdana

2013-01-01

Structure-based virtual screening (SBVS) methods often rely on docking score. The docking score is an over-simplification of the actual ligand-target binding. Its capability to model and predict the actual binding reality is limited. Recently, interaction fingerprinting (IFP) has come and offered us an alternative way to model reality. IFP provides us an alternate way to examine protein-ligand interactions. The docking score indicates the approximate affinity and IFP shows the interaction specificity. IFP is a method to convert three dimensional (3D) protein-ligand interactions into one dimensional (1D) bitstrings. The bitstrings are subsequently employed to compare the protein-ligand interaction predicted by the docking tool against the reference ligand. These comparisons produce scores that can be used to enhance the quality of SBVS campaigns. However, some IFP tools are either proprietary or using a proprietary library, which limits the access to the tools and the development of customized IFP algorithm. Therefore, we have developed PyPLIF, a Python-based open source tool to analyze IFP. In this article, we describe PyPLIF and its application to enhance the quality of SBVS in order to identify antagonists for estrogen α receptor (ERα). PyPLIF is freely available at http://code.google.com/p/pyplif.

Effect of the explicit flexibility of the InhA enzyme from Mycobacterium tuberculosis in molecular docking simulations.

PubMed

Cohen, Elisangela M L; Machado, Karina S; Cohen, Marcelo; de Souza, Osmar Norberto

2011-12-22

Protein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors' real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano(isoniazid)ferrate(II) (PIF). The use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner. Protein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor's binding site. Utilization of the intrinsic flexibility of Mtb's InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamical-structure-based drug design of novel inhibitors for Mtb's InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs.br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm.

A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis, molecular docking, density functional and molecular dynamics simulation study.

PubMed

Choubey, Sanjay K; Jeyaraman, Jeyakanthan

2016-11-01

Deregulated epigenetic activity of Histone deacetylase 1 (HDAC1) in tumor development and carcinogenesis pronounces it as promising therapeutic target for cancer treatment. HDAC1 has recently captured the attention of researchers owing to its decisive role in multiple types of cancer. In the present study a multistep framework combining ligand based 3D-QSAR, molecular docking and Molecular Dynamics (MD) simulation studies were performed to explore potential compound with good HDAC1 binding affinity. Four different pharmacophore hypotheses Hypo1 (AADR), Hypo2 (AAAH), Hypo3 (AAAR) and Hypo4 (ADDR) were obtained. The hypothesis Hypo1 (AADR) with two hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatics ring (R) was selected to build 3D-QSAR model on the basis of statistical parameter. The pharmacophore hypothesis produced a statistically significant QSAR model, with co-efficient of correlation r 2 =0.82 and cross validation correlation co-efficient q 2 =0.70. External validation result displays high predictive power with r 2 (o) value of 0.88 and r 2 (m) value of 0.58 to carry out further in silico studies. Virtual screening result shows ZINC70450932 as the most promising lead where HDAC1 interacts with residues Asp99, His178, Tyr204, Phe205 and Leu271 forming seven hydrogen bonds. A high docking score (-11.17kcal/mol) and lower docking energy -37.84kcal/mol) displays the binding efficiency of the ligand. Binding free energy calculation was done using MM/GBSA to access affinity of ligands towards protein. Density Functional Theory was employed to explore electronic features of the ligands describing intramolcular charge transfer reaction. Molecular dynamics simulation studies at 50ns display metal ion (Zn)-ligand interaction which is vital to inhibit the enzymatic activity of the protein. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparative evaluation of several docking tools for docking small molecule ligands to DC-SIGN.

PubMed

Jug, Gregor; Anderluh, Marko; Tomašič, Tihomir

2015-06-01

Five docking tools, namely AutoDock, FRED, CDOCKER, FlexX and GOLD, have been critically examined, with the aim of selecting those most appropriate for use as docking tools for docking molecules to the lectin dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN). This lectin has been selected for its rather non-druggable binding site, which enables complex interactions that guide the binding of the core monosaccharide. Since optimal orientation is crucial for forming coordination bonds, it was important to assess whether the selected docking tools could reproduce the optimal binding conformation for several oligosaccharides that are known to bind DC-SIGN. Our results show that even widely used docking programs have certain limitations when faced with a rather shallow and featureless binding site, as is the case of DC-SIGN. The FRED docking software (OpenEye Scientific Software, Inc.) was found to score as the best tool for docking ligands to DC-SIGN. The performance of FRED was further assessed on another lectin, Langerin. We have demonstrated that this validated docking protocol could be used for docking to other lectins similar to DC-SIGN.

A method for fast energy estimation and visualization of protein-ligand interaction

NASA Astrophysics Data System (ADS)

Tomioka, Nobuo; Itai, Akiko; Iitaka, Yoichi

1987-10-01

A new computational and graphical method for facilitating ligand-protein docking studies is developed on a three-dimensional computer graphics display. Various physical and chemical properties inside the ligand binding pocket of a receptor protein, whose structure is elucidated by X-ray crystal analysis, are calculated on three-dimensional grid points and are stored in advance. By utilizing those tabulated data, it is possible to estimate the non-bonded and electrostatic interaction energy and the number of possible hydrogen bonds between protein and ligand molecules in real time during an interactive docking operation. The method also provides a comprehensive visualization of the local environment inside the binding pocket. With this method, it becomes easier to find a roughly stable geometry of ligand molecules, and one can therefore make a rapid survey of the binding capability of many drug candidates. The method will be useful for drug design as well as for the examination of protein-ligand interactions.

pK(a) based protonation states and microspecies for protein-ligand docking.

PubMed

ten Brink, Tim; Exner, Thomas E

2010-11-01

In this paper we present our reworked approach to generate ligand protonation states with our structure preparation tool SPORES (Structure PrOtonation and REcognition System). SPORES can be used for the preprocessing of proteins and protein-ligand complexes as e.g. taken from the Protein Data Bank as well as for the setup of 3D ligand databases. It automatically assigns atom and bond types, generates different protonation, tautomeric states as well as different stereoisomers. In the revised version, pKa calculations with the ChemAxon software MARVIN are used either to determine the likeliness of a combinatorial generated protonation state or to determine the titrable atoms used in the combinatorial approach. Additionally, the MARVIN software is used to predict microspecies distributions of ligand molecules. Docking studies were performed with our recently introduced program PLANTS (Protein-Ligand ANT System) on all protomers resulting from the three different selection methods for the well established CCDC/ASTEX clean data set demonstrating the usefulness of especially the latter approach.

pKa based protonation states and microspecies for protein-ligand docking

NASA Astrophysics Data System (ADS)

ten Brink, Tim; Exner, Thomas E.

2010-11-01

In this paper we present our reworked approach to generate ligand protonation states with our structure preparation tool SPORES (Structure PrOtonation and REcognition System). SPORES can be used for the preprocessing of proteins and protein-ligand complexes as e.g. taken from the Protein Data Bank as well as for the setup of 3D ligand databases. It automatically assigns atom and bond types, generates different protonation, tautomeric states as well as different stereoisomers. In the revised version, pKa calculations with the ChemAxon software MARVIN are used either to determine the likeliness of a combinatorial generated protonation state or to determine the titrable atoms used in the combinatorial approach. Additionally, the MARVIN software is used to predict microspecies distributions of ligand molecules. Docking studies were performed with our recently introduced program PLANTS (Protein-Ligand ANT System) on all protomers resulting from the three different selection methods for the well established CCDC/ASTEX clean data set demonstrating the usefulness of especially the latter approach.

Computation-based virtual screening for designing novel antimalarial drugs by targeting falcipain-III: a structure-based drug designing approach.

PubMed

Kesharwani, Rajesh Kumar; Singh, Durg Vijay; Misra, Krishna

2013-01-01

Cysteine proteases (falcipains), a papain-family of enzymes of Plasmodium falciparum, are responsible for haemoglobin degradation and thus necessary for its survival during asexual life cycle phase inside the human red blood cells while remaining non-functional for the human body. Therefore, these can act as potential targets for designing antimalarial drugs. The P. falciparum cysteine proteases, falcipain-II and falcipain- III are the enzymes which initiate the haemoglobin degradation, therefore, have been selected as targets. In the present study, we have designed new leupeptin analogues and subjected to virtual screening using Glide at the active site cavity of falcipain-II and falcipain-III to select the best docked analogues on the basis of Glide score and also compare with the result of AutoDock. The proposed analogues can be synthesized and tested in vivo as future potent antimalarial drugs. Protein falcipain-II and falcipain-III together with bounds inhibitors epoxysuccinate E64 (E64) and leupeptin respectively were retrieved from protein data bank (PDB) and latter leupeptin was used as lead molecule to design new analogues by using Ligbuilder software and refined the molecules on the basis of Lipinski rule of five and fitness score parameters. All the designed leupeptin analogues were screened via docking simulation at the active site cavity of falcipain-II and falcipain-III by using Glide software and AutoDock. The 104 new leupeptin-based antimalarial ligands were designed using structure-based drug designing approach with the help of Ligbuilder and subjected for virtual screening via docking simulation method against falcipain-II and falcipain-III receptor proteins. The Glide docking results suggest that the ligands namely result_037 shows good binding and other two, result_044 and result_042 show nearly similar binding than naturally occurring PDB bound ligand E64 against falcipain-II and in case of falcipain-III, 15 designed leupeptin analogues having better binding affinity compared to the PDB bound inhibitor of falcipain-III. The docking simulation results of falcipain-III with designed leupeptin analogues using Glide compared with AutoDock and find 80% similarity as better binder than leupeptin. These results further highlight new leupeptin analogues as promising future inhibitors for chemotherapeutic prevention of malaria. The result of Glide for falcipain-III has been compared with the result of AutoDock and finds very less differences in their order of binding affinity. Although there are no extra hydrogen bonds, however, equal number of hydrogen bonds with variable strength as compared to leupeptin along with the enhanced hydrophobic and electrostatic interactions in case of analogues supports our study that it holds the ligand molecules strongly within the receptor. The comparative e-pharmacophoric study also suggests and supports our predictions regarding the minimum features required in ligand molecule to behave as falcipain- III inhibitors and is also helpful in screening the large database as future antimalarial inhibitors.

Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations.

PubMed

Uehara, Shota; Tanaka, Shigenori

2017-04-24

Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.

COMPARATIVE DOCKING STUDIES OF THE BINDING OF POLYCYCLIC AROMATIC HYDROCARBONS TO THE ESTROGEN RECEPTOR

EPA Science Inventory

The interactions of several PAHs, and some of their possible metabolites, with the ligand binding domain of the estrogen receptor have been examined using molecular docking and quantum mechanical methods. The geometries of the PAHs were optimized at the Hartree-Fock level and the...

Comparison of ligand migration and binding in heme proteins of the globin family

NASA Astrophysics Data System (ADS)

Karin, Nienhaus; Ulrich Nienhaus, G.

2015-12-01

The binding of small diatomic ligands such as carbon monoxide or dioxygen to heme proteins is among the simplest biological processes known. Still, it has taken many decades to understand the mechanistic aspects of this process in full detail. Here, we compare ligand binding in three heme proteins of the globin family, myoglobin, a dimeric hemoglobin, and neuroglobin. The combination of structural, spectroscopic, and kinetic experiments over many years by many laboratories has revealed common properties of globins and a clear mechanistic picture of ligand binding at the molecular level. In addition to the ligand binding site at the heme iron, a primary ligand docking site exists that ensures efficient ligand binding to and release from the heme iron. Additional, secondary docking sites can greatly facilitate ligand escape after its dissociation from the heme. Although there is only indirect evidence at present, a preformed histidine gate appears to exist that allows ligand entry to and exit from the active site. The importance of these features can be assessed by studies involving modified proteins (via site-directed mutagenesis) and comparison with heme proteins not belonging to the globin family.

Virtual Screening of Novel Glucosamine-6-Phosphate Synthase Inhibitors.

PubMed

Lather, Amit; Sharma, Sunil; Khatkar, Anurag

2018-01-01

Infections caused by microorganisms are the major cause of death today. The tremendous and improper use of antimicrobial agents leads to antimicrobial resistance. Various currently available antimicrobial drugs are inadequate to control the infections and lead to various adverse drug reactions. Efforts based on computer-aided drug design (CADD) can excavate a large number of databases to generate new, potent hits and minimize the requirement of time as well as money for the discovery of newer antimicrobials. Pharmaceutical sciences also have made development with advances in drug designing concepts. The current research article focuses on the study of various G-6-P synthase inhibitors from literature cited molecular database. Docking analysis was conducted and ADMET data of various molecules was evaluated by Schrodinger Glide and PreADMET software, respectively. Here, the results presented efficacy of various inhibitors towards enzyme G-6-P synthase. Docking scores, binding energy and ADMET data of various molecules showed good inhibitory potential toward G-6-P synthase as compared to standard antibiotics. This novel antimicrobial drug target G-6-P synthase has not so extensively been explored for its application in antimicrobial therapy, so the work done so far proved highly essential. This article has helped the drug researchers and scientists to intensively explore about this wonderful antimicrobial drug target. The Schrodinger, Inc. (New York, USA) software was utilized to carry out the computational calculations and docking studies. The hardware configuration was Intel® core (TM) i5-4210U CPU @ 2.40GHz, RAM memory 4.0 GB under 64-bit window operating system. The ADMET data was calculated by using the PreADMET tool (PreADMET ver. 2.0). All the computational work was completed in the Laboratory for Enzyme Inhibition Studies, Department of Pharmaceutical Sciences, M.D. University, Rohtak, INDIA. Molecular docking studies were carried out to identify the binding affinities and interaction between the inhibitors and the target proteins (G-6-P synthase) by using Glide software (Schrodinger Inc. U.S.A.-Maestro version 10.2). Grid-based Ligand Docking with Energetic (Glide) is one of the most accurate docking softwares available for ligand-protein, protein-protein binding studies. A library of hundreds of available ligands was docked against targeted proteins G-6-P synthase having PDB ID 1moq. Results of docking are shown in Table 1 and Table 2. Results of G-6-P synthase docking showed that some compounds were found to have comparable docking score and binding energy (kj/mol) as compared to standard antibiotics. Many of the ligands showed hydrogen bond interaction, hydrophobic interactions, electrostatic interactions, ionic interactions and π- π stacking with the various amino acid residues in the binding pockets of G-6-P synthase. The docking study estimated free energy of binding, binding pose andglide score and all these parameters provide a promising tool for the discovery of new potent natural inhibitors of G-6-P synthase. These G-6-P synthase inhibitors could further be used as antimicrobials. Here, a detailed binding analysis and new insights of inhibitors from various classes of molecules were docked in binding cavity of G-6-P synthase. ADME and toxicity prediction of these compounds will further accentuate us to study these compounds in vivo. This information will possibly present further expansion of effective antimicrobials against several microbial infections. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing.

PubMed

Patil, Rohan; Das, Suranjana; Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K

2010-08-16

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

PubMed Central

Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K.

2010-01-01

Background Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. Methodology In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. Conclusions The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy. PMID:20808434

Small-molecule ligand docking into comparative models with Rosetta

PubMed Central

Combs, Steven A; DeLuca, Samuel L; DeLuca, Stephanie H; Lemmon, Gordon H; Nannemann, David P; Nguyen, Elizabeth D; Willis, Jordan R; Sheehan, Jonathan H; Meiler, Jens

2017-01-01

Structure-based drug design is frequently used to accelerate the development of small-molecule therapeutics. Although substantial progress has been made in X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, the availability of high-resolution structures is limited owing to the frequent inability to crystallize or obtain sufficient NMR restraints for large or flexible proteins. Computational methods can be used to both predict unknown protein structures and model ligand interactions when experimental data are unavailable. This paper describes a comprehensive and detailed protocol using the Rosetta modeling suite to dock small-molecule ligands into comparative models. In the protocol presented here, we review the comparative modeling process, including sequence alignment, threading and loop building. Next, we cover docking a small-molecule ligand into the protein comparative model. In addition, we discuss criteria that can improve ligand docking into comparative models. Finally, and importantly, we present a strategy for assessing model quality. The entire protocol is presented on a single example selected solely for didactic purposes. The results are therefore not representative and do not replace benchmarks published elsewhere. We also provide an additional tutorial so that the user can gain hands-on experience in using Rosetta. The protocol should take 5–7 h, with additional time allocated for computer generation of models. PMID:23744289

Naringenin and quercetin--potential anti-HCV agents for NS2 protease targets.

PubMed

Lulu, S Sajitha; Thabitha, A; Vino, S; Priya, A Mohana; Rout, Madhusmita

2016-01-01

Nonstructural proteins of hepatitis C virus had drawn much attention for the scientific fraternity in drug discovery due to its important role in the disease. 3D structure of the protein was predicted using molecular modelling protocol. Docking studies of 10 medicinal plant compounds and three drugs available in the market (control) with NS2 protease were employed by using rigid docking approach of AutoDock 4.2. Among the molecules tested for docking study, naringenin and quercetin revealed minimum binding energy of - 7.97 and - 7.95 kcal/mol with NS2 protease. All the ligands were docked deeply within the binding pocket region of the protein. The docking study results showed that these compounds are potential inhibitors of the target; and also all these docked compounds have good inhibition constant, vdW+Hbond+desolv energy with best RMSD value.

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase.

PubMed

Shukla, Rohit; Shukla, Harish; Sonkar, Amit; Pandey, Tripti; Tripathi, Timir

2018-06-01

Mycobacterium tuberculosis is the etiological agent of tuberculosis in humans and is responsible for more than two million deaths annually. M. tuberculosis isocitrate lyase (MtbICL) catalyzes the first step in the glyoxylate cycle, plays a pivotal role in the persistence of M. tuberculosis, which acts as a potential target for an anti-tubercular drug. To identify the potential anti-tuberculosis compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,748) against the MtbICL structure. The ligands were docked against MtbICL in three sequential docking modes that resulted in 340 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 27 compounds were found to fit well with re-docking studies. After refinement by molecular docking and drug-likeness analyses, three potential inhibitors (ZINC1306071, ZINC2111081, and ZINC2134917) were identified. These three ligands and the reference compounds were further subjected to molecular dynamics simulation and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the MtbICL and bound complexes. The binding free energy analyses were calculated to validate and capture the intermolecular interactions. The results suggested that the three compounds had a negative binding energy with -96.462, -143.549, and -122.526 kJ mol -1 for compounds with IDs ZINC1306071, ZINC2111081, and ZINC2134917, respectively. These lead compounds displayed substantial pharmacological and structural properties to be drug candidates. We concluded that ZINC2111081 has a great potential to inhibit MtbICL and would add to the drug discovery process against tuberculosis.

Potential interaction of natural dietary bioactive compounds with COX-2.

PubMed

Maldonado-Rojas, Wilson; Olivero-Verbel, Jesus

2011-09-01

Bioactive natural products present in the diet play an important role in several biological processes, and many have been involved in the alleviation and control of inflammation-related diseases. These actions have been linked to both gene expression modulation of pro-inflammatory enzymes, such as cyclooxygenase 2 (COX-2), and to an action involving a direct inhibitory binding on this protein. In this study, several food-related compounds with known gene regulatory action on inflammation have been examined in silico as COX-2 ligands, utilizing AutoDock Vina, GOLD and Surflex-Dock (SYBYL) as docking protocols. Curcumin and all-trans retinoic acid presented the maximum absolute AutoDock Vina-derived binding affinities (9.3 kcal/mol), but genistein, apigenin, cyanidin, kaempferol, and docosahexaenoic acid, were close to this value. AutoDock Vina affinities and GOLD scores for several known COX-2 inhibitors significatively correlated with reported median inhibitory concentrations (R² = 0.462, P < 0.001 and R² = 0.238, P = 0.029, respectively), supporting the computational reliability of the predictions made by our docking simulations. Moreover, docking analysis insinuate the synergistic action of curcumin on celecoxib-induced inhibition of COX-2 may occur allosterically, as this natural compound docks to a place different from the inhibitor binding site. These results suggest that the anti-inflammatory properties of some food-derived molecules could be the result of their direct binding capabilities to COX-2, and this process can be modeled using protein-ligand docking methodologies. Copyright © 2011 Elsevier Inc. All rights reserved.

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.

Investigation of potent lead for acquired immunodeficiency syndrome from traditional Chinese medicine.

PubMed

Hung, Tzu-Chieh; Lee, Wen-Yuan; Chen, Kuen-Bao; Chan, Yueh-Chiu; Chen, Calvin Yu-Chian

2014-01-01

Acquired immunodeficiency syndrome (AIDS), caused by human immunodeficiency virus (HIV), has become, because of the rapid spread of the disease, a serious global problem and cannot be treated. Recent studies indicate that VIF is a protein of HIV to prevent all of human immunity to attack HIV. Molecular compounds of traditional Chinese medicine (TCM) database filtered through molecular docking and molecular dynamics simulations to inhibit VIF can protect against HIV. Glutamic acid, plantagoguanidinic acid, and Aurantiamide acetate based docking score higher with other TCM compounds selected. Molecular dynamics are useful for analysis and detection ligand interactions. According to the docking position, hydrophobic interactions, hydrogen bonding changes, and structure variation, the study try to select the efficacy of traditional Chinese medicine compound Aurantiamide acetate is better than the other for protein-ligand interactions to maintain the protein composition, based on changes in the structure.

Transient Ligand Docking Sites in Cerebratulus lacteus Mini-Hemoglobin

PubMed Central

Deng, Pengchi; Nienhaus, Karin; Palladino, Pasquale; Olson, John S.; Blouin, George; Moens, Luc; Dewilde, Sylvia; Geuens, Eva; Nienhaus, G. Ulrich

2007-01-01

The monomeric hemoglobin of the nemertean worm Cerebratulus lacteus functions as an oxygen storage protein to maintain neural activity under hypoxic conditions. It shares a large, apolar matrix tunnel with other small hemoglobins, which has been implicated as a potential ligand migration pathway. Here we explore ligand migration and binding within the distal heme pocket, to which the tunnel provides access to ligands from the outside. FTIR/TDS experiments performed at cryogenic temperatures reveal the presence of three transient ligand docking sites within the distal pocket, the primary docking site B on top of pyrrole C and secondary sites C and D. Site C is assigned to a cavity adjacent to the distal portion of the heme pocket, surrounded by the B and E helices. It has an opening to the apolar tunnel and is expected to be on the pathway for ligand entry and exit, whereas site D, circumscribed by TyrB10, GlnE7, and the CD corner, most likely is located on a side pathway of ligand migration. Flash photolysis experiments at ambient temperatures indicate that the rate-limiting step for ligand binding to CerHb is migration through the apolar channel to site C. Movement from C to B and iron-ligand bond formation involve low energy barriers and thus are very rapid processes in the wt protein. PMID:17531406

Aromatic interactions impact ligand binding and function at serotonin 5-HT2C G protein-coupled receptors: receptor homology modelling, ligand docking, and molecular dynamics results validated by experimental studies

NASA Astrophysics Data System (ADS)

Córdova-Sintjago, Tania; Villa, Nancy; Fang, Lijuan; Booth, Raymond G.

2014-02-01

The serotonin (5-hydroxytryptamine, 5-HT) 5-HT2 G protein-coupled receptor (GPCR) family consists of types 2A, 2B, and 2C that share ∼75% transmembrane (TM) sequence identity. Agonists for 5-HT2C receptors are under development for psychoses; whereas, at 5-HT2A receptors, antipsychotic effects are associated with antagonists - in fact, 5-HT2A agonists can cause hallucinations and 5-HT2B agonists cause cardiotoxicity. It is known that 5-HT2A TM6 residues W6.48, F6.51, and F6.52 impact ligand binding and function; however, ligand interactions with these residues at the 5-HT2C receptor have not been reported. To predict and validate molecular determinants for 5-HT2C-specific activation, results from receptor homology modelling, ligand docking, and molecular dynamics simulation studies were compared with experimental results for ligand binding and function at wild type and W6.48A, F6.51A, and F6.52A point-mutated 5-HT2C receptors.

Conformational study on cyclic melanocortin ligands and new insight into their binding mode at the MC4 receptor.

PubMed

Grieco, Paolo; Brancaccio, Diego; Novellino, Ettore; Hruby, Victor J; Carotenuto, Alfonso

2011-09-01

The melanocortin receptors are involved in many physiological functions, including pigmentation, sexual function, feeding behavior, and energy homeostasis, making them potential targets to treat obesity, sexual dysfunction, etc. Understanding the basis of the ligand-receptor interactions is crucial for the design of potent and selective ligands for these receptors. The conformational preferences of the cyclic melanocortin ligands MTII (Ac-Nle(4)-c[Asp(5)-His(6)-DPhe(7)-Arg(8)-Trp(9)-Lys(10)]-NH(2)) and SHU9119 (Ac-Nle(4)-c[Asp(5)-His(6)-DNal(2')(7)-Arg(8)-Trp(9)-Lys(10)]-NH(2)), which show agonist and antagonist activity at the h-MC4R, respectively, were comprehensively investigated by solution NMR spectroscopy in different environments. In particular, water and water/DMSO (8:2) solutions were used as isotropic solutions and an aqueous solution of DPC (dodecylphosphocholine) micelles was used as a membrane mimetic environment. NMR-derived conformations of these two ligands were docked within h-MC4R models. NMR and docking studies revealed intriguing differences which can help explain the different activities of these two ligands. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Molecular Docking and Drug Discovery in β-Adrenergic Receptors.

PubMed

Vilar, Santiago; Sobarzo-Sanchez, Eduardo; Santana, Lourdes; Uriarte, Eugenio

2017-01-01

Evolution in computer engineering, availability of increasing amounts of data and the development of new and fast docking algorithms and software have led to improved molecular simulations with crucial applications in virtual high-throughput screening and drug discovery. Moreover, analysis of protein-ligand recognition through molecular docking has become a valuable tool in drug design. In this review, we focus on the applicability of molecular docking on a particular class of G protein-coupled receptors: the β-adrenergic receptors, which are relevant targets in clinic for the treatment of asthma and cardiovascular diseases. We describe the binding site in β-adrenergic receptors to understand key factors in ligand recognition along with the proteins activation process. Moreover, we focus on the discovery of new lead compounds that bind the receptors, on the evaluation of virtual screening using the active/ inactive binding site states, and on the structural optimization of known families of binders to improve β-adrenergic affinity. We also discussed strengths and challenges related to the applicability of molecular docking in β-adrenergic receptors. Molecular docking is a valuable technique in computational chemistry to deeply analyze ligand recognition and has led to important breakthroughs in drug discovery and design in the field of β-adrenergic receptors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Modification of S-Adenosyl-l-Homocysteine as Inhibitor of Nonstructural Protein 5 Methyltransferase Dengue Virus Through Molecular Docking and Molecular Dynamics Simulation

PubMed Central

Tambunan, Usman Sumo Friend; Nasution, Mochammad Arfin Fardiansyah; Azhima, Fauziah; Parikesit, Arli Aditya; Toepak, Erwin Prasetya; Idrus, Syarifuddin; Kerami, Djati

2017-01-01

Dengue fever is still a major threat worldwide, approximately threatening two-fifths of the world’s population in tropical and subtropical countries. Nonstructural protein 5 (NS5) methyltransferase enzyme plays a vital role in the process of messenger RNA capping of dengue by transferring methyl groups from S-adenosyl-l-methionine to N7 atom of the guanine bases of RNA and the RNA ribose group of 2′OH, resulting in S-adenosyl-l-homocysteine (SAH). The modification of SAH compound was screened using molecular docking and molecular dynamics simulation, along with computational ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) test. The 2 simulations were performed using Molecular Operating Environment (MOE) 2008.10 software, whereas the ADME-Tox test was performed using various software. The modification of SAH compound was done using several functional groups that possess different polarities and properties, resulting in 3460 ligands to be docked. After conducting docking simulation, we earned 3 best ligands (SAH-M331, SAH-M2696, and SAH-M1356) based on ΔGbinding and molecular interactions, which show better results than the standard ligands. Moreover, the results of molecular dynamics simulation show that the best ligands are still able to maintain the active site residue interaction with the binding site until the end of the simulation. After a series of molecular docking and molecular dynamics simulation were performed, we concluded that SAH-M1356 ligand is the most potential SAH-based compound to inhibit NS5 methyltransferase enzyme for treating dengue fever. PMID:28469408

Modeling ligand recognition at the P2Y12 receptor in light of X-ray structural information

NASA Astrophysics Data System (ADS)

Paoletta, Silvia; Sabbadin, Davide; von Kügelgen, Ivar; Hinz, Sonja; Katritch, Vsevolod; Hoffmann, Kristina; Abdelrahman, Aliaa; Straßburger, Jens; Baqi, Younis; Zhao, Qiang; Stevens, Raymond C.; Moro, Stefano; Müller, Christa E.; Jacobson, Kenneth A.

2015-08-01

The G protein-coupled P2Y12 receptor (P2Y12R) is an important antithrombotic target and of great interest for pharmaceutical discovery. Its recently solved, highly divergent crystallographic structures in complex either with nucleotides (full or partial agonist) or with a nonnucleotide antagonist raise the question of which structure is more useful to understand ligand recognition. Therefore, we performed extensive molecular modeling studies based on these structures and mutagenesis, to predict the binding modes of major classes of P2Y12R ligands previously reported. Various nucleotide derivatives docked readily to the agonist-bound P2Y12R, but uncharged nucleotide-like antagonist ticagrelor required a hybrid receptor resembling the agonist-bound P2Y12R except for the top portion of TM6. Supervised molecular dynamics (SuMD) of ticagrelor binding indicated interactions with the extracellular regions of P2Y12R, defining possible meta-binding sites. Ureas, sulfonylureas, sulfonamides, anthraquinones and glutamic acid piperazines docked readily to the antagonist-bound P2Y12R. Docking dinucleotides at both agonist- and antagonist-bound structures suggested interactions with two P2Y12R pockets. Thus, our structure-based approach consistently rationalized the main structure-activity relationships within each ligand class, giving useful information for designing improved ligands.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

PubMed Central

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928–0.988,  = 0.894–0.954, RMSE = 0.002–0.412, s = 0.001–0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery. PMID:28059133

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme.

PubMed

Leong, Max K; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-06

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r 2  = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK i values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r 2  = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q 2  = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

NASA Astrophysics Data System (ADS)

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Steric and thermodynamic limits of design for the incorporation of large unnatural amino acids in aminoacyl-tRNA synthetase enzymes.

PubMed

Armen, Roger S; Schiller, Stefan M; Brooks, Charles L

2010-06-01

Orthogonal aminoacyl-tRNA synthetase/tRNA pairs from archaea have been evolved to facilitate site specific in vivo incorporation of unnatural amino acids into proteins in Escherichia coli. Using this approach, unnatural amino acids have been successfully incorporated with high translational efficiency and fidelity. In this study, CHARMM-based molecular docking and free energy calculations were used to evaluate rational design of specific protein-ligand interactions for aminoacyl-tRNA synthetases. A series of novel unnatural amino acid ligands were docked into the p-benzoyl-L-phenylalanine tRNA synthetase, which revealed that the binding pocket of the enzyme does not provide sufficient space for significantly larger ligands. Specific binding site residues were mutated to alanine to create additional space to accommodate larger target ligands, and then mutations were introduced to improve binding free energy. This approach was used to redesign binding sites for several different target ligands, which were then tested against the standard 20 amino acids to verify target specificity. Only the synthetase designed to bind Man-alpha-O-Tyr was predicted to be sufficiently selective for the target ligand and also thermodynamically stable. Our study suggests that extensive redesign of the tRNA synthatase binding pocket for large bulky ligands may be quite thermodynamically unfavorable.

A strategy for screening of α-glucosidase inhibitors from Morus alba root bark based on the ligand fishing combined with high-performance liquid chromatography mass spectrometer and molecular docking.

PubMed

Wang, Zhen; Li, Xiaoqing; Chen, Menghan; Liu, Feiyan; Han, Chao; Kong, Lingyi; Luo, Jianguang

2018-04-01

A new method based on ligand fishing combined with high-performance liquid chromatography quadrupole-time-of-flight mass spectrometer and molecular docking was established to screen α-glucosidase inhibitors from a traditional Chinese medicine Morus alba root bark. α-Glucosidase was immobilized on magnetic nanoparticles, used as a solid support to incubate with crude extract. After ligand fishing, the eluates were analyzed by high-performance liquid chromatography quadrupole-time-of-flight mass spectrometer, obtaining eleven ligands (1-4, 6-12) eventually. In order to discriminate the non-specific binders and discover powerful enzyme inhibitors, molecular docking was further performed and three of the eleven ligands were optimized to be excellent α-glucosidase inhibitors by the confirmation of isolation and bioassay of individual compounds. These three ligands, sanggenons G (6), O (7) and sanggenol G (12) exhibited striking inhibitory activities with extremely low IC 50 values. The results suggest that established method will be applied to a wide range of target protein to screen potential bioactive constituents from herbal medicines. Copyright © 2017 Elsevier B.V. All rights reserved.

Docking simulations suggest that all-trans retinoic acid could bind to retinoid X receptors.

PubMed

Tsuji, Motonori; Shudo, Koichi; Kagechika, Hiroyuki

2015-10-01

Retinoid X receptors (RXRs) are ligand-controlled transcription factors which heterodimerize with other nuclear receptors to regulate gene transcriptions associated with crucial biological events. 9-cis retinoic acid (9cRA), which transactivates RXRs, is believed to be an endogenous RXR ligand. All-trans retinoic acid (ATRA) is a natural ligand for retinoic acid receptors (RARs), which heterodimerize with RXRs. Although the concentration of 9cRA in tissues is very low, ATRA is relatively abundant and some reports show that ATRA activates RXRs. We computationally studied the possibility of ATRA binding to RXRs using two different docking methods with our developed programs to assess the binding affinities of naturally occurring retinoids. The simulations showed good correlations to the reported binding affinities of these molecules for RXRs and RARs.

Elucidation of the binding sites of sodium dodecyl sulfate to β-lactoglobulin using hydrogen/deuterium exchange mass spectrometry combined with docking simulation.

PubMed

Hu, Wenbing; Liu, Jianan; Luo, Qun; Han, Yumiao; Wu, Kui; Lv, Shuang; Xiong, Shaoxiang; Wang, Fuyi

2011-05-30

Hydrogen/deuterium exchange mass spectrometry (H/DX MS) has become a powerful tool to investigate protein-protein and protein-ligand interactions, but it is still challenging to localize the interaction regions/sites of ligands with pepsin-resistant proteins such as lipocalins. β-Lactoglobulin (BLG), a member of the lipocalin family, can bind a variety of small hydrophobic molecules including retinols, retinoic acids, and long linear fatty acids. However, whether the binding site of linear molecules locates in the external groove or internal cavity of BLG is controversial. In this study we used H/DX MS combined with docking simulation to localize the interaction sites of a tested ligand, sodium dodecyl sulfate (SDS), binding to BLG. H/DX MS results indicated that SDS can bind to both the external and the internal sites in BLG. However, neither of the sites is saturated with SDS, allowing a dynamic ligand exchange to occur between the sites at equilibrium state. Docking studies revealed that SDS forms H-bonds with Lys69 in the internal site and Lys138 and Lys141 in the external site in BLG via the sulfate group, and interacts with the hydrophobic residues valine, leucine, isoleucine and methionine within both of the sites via its hydrocarbon tail, stabilizing the BLG-SDS complex. Copyright © 2011 John Wiley & Sons, Ltd.

Blinded evaluation of farnesoid X receptor (FXR) ligands binding using molecular docking and free energy calculations

NASA Astrophysics Data System (ADS)

Selwa, Edithe; Elisée, Eddy; Zavala, Agustin; Iorga, Bogdan I.

2018-01-01

Our participation to the D3R Grand Challenge 2 involved a protocol in two steps, with an initial analysis of the available structural data from the PDB allowing the selection of the most appropriate combination of docking software and scoring function. Subsequent docking calculations showed that the pose prediction can be carried out with a certain precision, but this is dependent on the specific nature of the ligands. The correct ranking of docking poses is still a problem and cannot be successful in the absence of good pose predictions. Our free energy calculations on two different subsets provided contrasted results, which might have the origin in non-optimal force field parameters associated with the sulfonamide chemical moiety.

Molecular simulation and docking studies of Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose: implication for transcriptional activation of GAL genes

NASA Astrophysics Data System (ADS)

Upadhyay, Sanjay K.; Sasidhar, Yellamraju U.

2012-07-01

The Gal4p mediated transcriptional activation of GAL genes requires the interaction between Gal3p bound with ATP and galactose and Gal80p. Though numerous studies suggest that galactose and ATP activate Gal3p/Gal1p interaction with Gal80p, neither the mechanism of activation nor the interacting surface that binds to Gal80p is well understood. In this study we investigated the dynamics of Gal3p and Gal1p in the presence and absence of ligands ATP and galactose to understand the role played by dynamics in the function of these proteins through molecular dynamics simulation and protein-protein docking studies. We performed simulations totaling to 510 ns on both Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose. We find that, while binding of ligands ATP and galactose to Gal3p/Gal1p do not affect the global conformation of proteins, some local conformational changes around upper-lip helix including insertion domain are observed. We observed that only in the presence of ATP and galactose, Gal3p displays opening and closing motion between the two domains. And because of this motion, a binding interface, which is largely hydrophobic, opens up on the surface of Gal3p and this surface can bind to Gal80p. From our simulation studies we infer probable docking sites for Gal80p on Gal3p/Gal1p, which were further ascertained by the docking of Gal80p on to ligand bound Gal1p and Gal3p proteins, and the residues at the interface between Gal3p and Gal80p are identified. Our results correlate quite well with the existing body of literature on functional and dynamical aspects of Gal1p and Gal3p proteins.

Molecular simulation and docking studies of Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose: implication for transcriptional activation of GAL genes.

PubMed

Upadhyay, Sanjay K; Sasidhar, Yellamraju U

2012-07-01

The Gal4p mediated transcriptional activation of GAL genes requires the interaction between Gal3p bound with ATP and galactose and Gal80p. Though numerous studies suggest that galactose and ATP activate Gal3p/Gal1p interaction with Gal80p, neither the mechanism of activation nor the interacting surface that binds to Gal80p is well understood. In this study we investigated the dynamics of Gal3p and Gal1p in the presence and absence of ligands ATP and galactose to understand the role played by dynamics in the function of these proteins through molecular dynamics simulation and protein-protein docking studies. We performed simulations totaling to 510 ns on both Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose. We find that, while binding of ligands ATP and galactose to Gal3p/Gal1p do not affect the global conformation of proteins, some local conformational changes around upper-lip helix including insertion domain are observed. We observed that only in the presence of ATP and galactose, Gal3p displays opening and closing motion between the two domains. And because of this motion, a binding interface, which is largely hydrophobic, opens up on the surface of Gal3p and this surface can bind to Gal80p. From our simulation studies we infer probable docking sites for Gal80p on Gal3p/Gal1p, which were further ascertained by the docking of Gal80p on to ligand bound Gal1p and Gal3p proteins, and the residues at the interface between Gal3p and Gal80p are identified. Our results correlate quite well with the existing body of literature on functional and dynamical aspects of Gal1p and Gal3p proteins.

Improved Evolutionary Hybrids for Flexible Ligand Docking in Autodock

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belew, R.K.; Hart, W.E.; Morris, G.M.

1999-01-27

In this paper we evaluate the design of the hybrid evolutionary algorithms (EAs) that are currently used to perform flexible ligand binding in the Autodock docking software. Hybrid EAs incorporate specialized operators that exploit domain-specific features to accelerate an EA's search. We consider hybrid EAs that use an integrated local search operator to reline individuals within each iteration of the search. We evaluate several factors that impact the efficacy of a hybrid EA, and we propose new hybrid EAs that provide more robust convergence to low-energy docking configurations than the methods currently available in Autodock.

Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation

PubMed Central

Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio

2012-01-01

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands. PMID:22970199

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Slynko, Inna; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2016-09-01

High affinity ligands for a given target tend to share key molecular interactions with important anchoring amino acids and therefore often present quite conserved interaction patterns. This simple concept was formalized in a topological knowledge-based scoring function (GRIM) for selecting the most appropriate docking poses from previously X-rayed interaction patterns. GRIM first converts protein-ligand atomic coordinates (docking poses) into a simple 3D graph describing the corresponding interaction pattern. In a second step, proposed graphs are compared to that found from template structures in the Protein Data Bank. Last, all docking poses are rescored according to an empirical score (GRIMscore) accounting for overlap of maximum common subgraphs. Taking the opportunity of the public D3R Grand Challenge 2015, GRIM was used to rescore docking poses for 36 ligands (6 HSP90α inhibitors, 30 MAP4K4 inhibitors) prior to the release of the corresponding protein-ligand X-ray structures. When applied to the HSP90α dataset, for which many protein-ligand X-ray structures are already available, GRIM provided very high quality solutions (mean rmsd = 1.06 Å, n = 6) as top-ranked poses, and significantly outperformed a state-of-the-art scoring function. In the case of MAP4K4 inhibitors, for which preexisting 3D knowledge is scarce and chemical diversity is much larger, the accuracy of GRIM poses decays (mean rmsd = 3.18 Å, n = 30) although GRIM still outperforms an energy-based scoring function. GRIM rescoring appears to be quite robust with comparison to the other approaches competing for the same challenge (42 submissions for the HSP90 dataset, 27 for the MAP4K4 dataset) as it ranked 3rd and 2nd respectively, for the two investigated datasets. The rescoring method is quite simple to implement, independent on a docking engine, and applicable to any target for which at least one holo X-ray structure is available.

Docking and scoring with ICM: the benchmarking results and strategies for improvement

PubMed Central

Neves, Marco A. C.; Totrov, Maxim; Abagyan, Ruben

2012-01-01

Flexible docking and scoring using the Internal Coordinate Mechanics software (ICM) was benchmarked for ligand binding mode prediction against the 85 co-crystal structures in the modified Astex data set. The ICM virtual ligand screening was tested against the 40 DUD target benchmarks and 11-target WOMBAT sets. The self-docking accuracy was evaluated for the top 1 and top 3 scoring poses at each ligand binding site with near native conformations below 2 Å RMSD found in 91% and 95% of the predictions, respectively. The virtual ligand screening using single rigid pocket conformations provided the median area under the ROC curves equal to 69.4 with 22.0% true positives recovered at 2% false positive rate. Significant improvements up to ROC AUC= 82.2 and ROC(2%)= 45.2 were achieved following our best practices for flexible pocket refinement and out-of-pocket binding rescore. The virtual screening can be further improved by considering multiple conformations of the target. PMID:22569591

Ligand solvation in molecular docking.

PubMed

Shoichet, B K; Leach, A R; Kuntz, I D

1999-01-01

Solvation plays an important role in ligand-protein association and has a strong impact on comparisons of binding energies for dissimilar molecules. When databases of such molecules are screened for complementarity to receptors of known structure, as often occurs in structure-based inhibitor discovery, failure to consider ligand solvation often leads to putative ligands that are too highly charged or too large. To correct for the different charge states and sizes of the ligands, we calculated electrostatic and non-polar solvation free energies for molecules in a widely used molecular database, the Available Chemicals Directory (ACD). A modified Born equation treatment was used to calculate the electrostatic component of ligand solvation. The non-polar component of ligand solvation was calculated based on the surface area of the ligand and parameters derived from the hydration energies of apolar ligands. These solvation energies were subtracted from the ligand-receptor interaction energies. We tested the usefulness of these corrections by screening the ACD for molecules that complemented three proteins of known structure, using a molecular docking program. Correcting for ligand solvation improved the rankings of known ligands and discriminated against molecules with inappropriate charge states and sizes.

Molecular docking and simulation studies of 3-(1-chloropiperidin-4-yl)-6-fluoro benzisoxazole 2 against VP26 and VP28 proteins of white spot syndrome virus.

PubMed

Sudharsana, S; Rajashekar Reddy, C B; Dinesh, S; Rajasekhara Reddy, S; Mohanapriya, A; Itami, T; Sudhakaran, R

2016-10-01

White spot syndrome virus (WSSV), an aquatic virus infecting shrimps and other crustaceans, is widely distributed in Asian subcontinents including India. The infection has led to a serious economic loss in shrimp farming. The WSSV genome is approximately 300 kb and codes for several proteins mediating the infection. The envelope proteins VP26 and VP28 play a major role in infection process and also in the interaction with the host cells. A comprehensive study on the viral proteins leading to the development of safe and potent antiviral therapeutic is of adverse need. The novel synthesized compound 3-(1-chloropiperidin-4-yl)-6-fluoro benzisoxazole 2 is proved to have potent antiviral activity against WSSV. The compound antiviral activity is validated in freshwater crabs (Paratelphusa hydrodomous). An in silico molecular docking and simulation analysis of the envelope proteins VP26 and VP28 with the ligand 3-(1-chloropiperidin-4-yl)-6-fluoro benzisoxazole 2 are carried out. The docking analysis reveals that the polar amino acids in the pore region of the envelope proteins were involved in the ligand binding. The influence of the ligand binding on the proteins is validated by the molecular dynamics and simulation study. These in silico approaches together demonstrate the ligand's efficiency in preventing the trimers from exhibiting their physiological function. © 2016 John Wiley & Sons Ltd.

Binding Site and Potency Prediction of Teixobactin and other Lipid II Ligands by Statistical Base Scoring of Conformational Space Maps.

PubMed

Lungu, Claudiu N; Diudea, Mircea V

2018-01-01

Lipid II, a peptidoglycan, is a precursor in bacterial cell synthesis. It has both hydrophilic and lipophilic properties. The molecule translocates a bacterial membrane to deliver and incorporate "building blocks" from disaccharide-pentapeptide into the peptidoglican wall. Lipid II is a valid antibiotic target. A receptor binding pocket may be occupied by a ligand in various plausible conformations, among which only few ones are energetically related to a biological activity in the physiological efficiency domain. This paper reports the mapping of the conformational space of Lipid II in its interaction with Teixobactin and other Lipid II ligands. In order to study computationally the complex between Lipid II and ligands, a docking study was first carried on. Docking site was retrieved form literature. After docking, 5 ligand conformations and further 5 complexes (denoted 00 to 04) for each molecule were taken into account. For each structure, conformational studies were performed. Statistical analysis, conformational analysis and molecular dynamics based clustering were used to predict the potency of these compounds. A score for potency prediction was developed. Appling lipid II classification according to Lipid II conformational energy, a conformation of Teixobactin proved to be energetically favorable, followed by Oritravicin, Dalbavycin, Telvanicin, Teicoplamin and Vancomycin, respectively. Scoring of molecules according to cluster band and PCA produced the same result. Molecules classified according to standard deviations showed Dalbavycin as the most favorable conformation, followed by Teicoplamin, Telvanicin, Teixobactin, Oritravicin and Vancomycin, respectively. Total score showing best energetic efficiency of complex formation shows Teixobactin to have the best conformation (a score of 15 points) followed by Dalbavycin (14 points), Oritravicin (12v points), Telvanicin (10 points), Teicoplamin (9 points), Vancomycin (3 points). Statistical analysis of conformations can be used to predict the efficiency of ligand - target interaction and consecutively to find insight regarding ligand potency and postulate about favorable conformation of ligand and binding site. In this study it was shown that Teixobactin is more efficient in binding with Lipid II compared to Vancomycin, results confirmed by experimental data reported in literature. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Molecular docking and 3D-QSAR studies on triazolinone and pyridazinone, non-nucleoside inhibitor of HIV-1 reverse transcriptase.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2010-06-01

Nonnucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors of the HIV-1 reverse transcriptase. Recently a series of Triazolinone and Pyridazinone were reported as potent inhibitors of HIV-1 wild type reverse transcriptase. In the present study, docking and 3D quantitative structure activity relationship (3D QSAR) studies involving comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 31 molecules. Ligands were built and minimized using Tripos force field and applying Gasteiger-Hückel charges. These ligands were docked into protein active site using GLIDE 4.0. The docked poses were analyzed; the best docked poses were selected and aligned. CoMFA and CoMSIA fields were calculated using SYBYL6.9. The molecules were divided into training set and test set, a PLS analysis was performed and QSAR models were generated. The model showed good statistical reliability which is evident from the r2 nv, q2 loo and r2 pred values. The CoMFA model provides the most significant correlation of steric and electrostatic fields with biological activities. The CoMSIA model provides a correlation of steric, electrostatic, acceptor and hydrophobic fields with biological activities. The information rendered by 3D QSAR model initiated us to optimize the lead and design new potential inhibitors.

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

PubMed Central

Gallicchio, Emilio; Deng, Nanjie; He, Peng; Wickstrom, Lauren; Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Olson, Arthur J.; Levy, Ronald M.

2014-01-01

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization. PMID:24504704

Virtual screening using the ligand ZINC database for novel lipoxygenase-3 inhibitors.

PubMed

Monika; Kour, Janmeet; Singh, Kulwinder

2013-01-01

The leukotrienes constitute a group of arachidonic acid-derived compounds with biologic activities suggesting important roles in inflammation and immediate hypersensitivity. Epidermis-type lipoxygenase-3 (ALOXE3), a distinct subclass within the multigene family of mammalian lipoxygenases, is a novel isoenzyme involved in the metabolism of leukotrienes and plays a very important role in skin barrier functions. Lipoxygenase selective inhibitors such as azelastine and zileuton are currently used to reduce inflammatory response. Nausea, pharyngolaryngeal pain, headache, nasal burning and somnolence are the most frequently reported adverse effects of these drugs. Therefore, there is still a need to develop more potent lipoxygenase inhibitors. In this paper, we report the screening of various compounds from the ZINC database (contains over 21 million compounds) using the Molegro Virtual Docker software against the ALOXE3 protein. Screening was performed using molecular constraints tool to filter compounds with physico-chemical properties similar to the 1N8Q bound ligand protocatechuic acid. The analysis resulted in 4319 Lipinski compliant hits which are docked and scored to identify structurally novel ligands that make similar interactions to those of known ligands or may have different interactions with other parts of the binding site. Our screening approach identified four molecules ZINC84299674; ZINC76643455; ZINC84299122 & ZINC75626957 with MolDock score of -128.901, -120.22, -116.873 & - 102.116 kcal/mol, respectively. Their energy scores were better than the 1N8Q bound co-crystallized ligand protocatechuic acid (with MolDock score of -77.225 kcal/mol). All the ligands were docked within the binding pocket forming interactions with amino acid residues.

Non-nucleosidic inhibition of Herpes simplex virus DNA polymerase: mechanistic insights into the anti-herpetic mode of action of herbal drug withaferin A.

PubMed

Grover, Abhinav; Agrawal, Vibhuti; Shandilya, Ashutosh; Bisaria, Virendra S; Sundar, Durai

2011-01-01

Herpes Simplex Virus 1 and 2 causes several infections in humans including cold sores and encephalitis. Previous antiviral studies on herpes viruses have focussed on developing nucleoside analogues that can inhibit viral polymerase and terminate the replicating viral DNA. However, these drugs bear an intrinsic non-specificity as they can also inhibit cellular polymerase apart from the viral one. The present study is an attempt to elucidate the action mechanism of naturally occurring withaferin A in inhibiting viral DNA polymerase, thus providing an evidence for its development as a novel anti-herpetic drug. Withaferin A was found to bind very similarly to that of the previously reported 4-oxo-DHQ inhibitor. Withaferin A was observed binding to the residues Gln 617, Gln 618, Asn 815 and Tyr 818, all of which are crucial to the proper functioning of the polymerase. A comparison of the conformation obtained from docking and the molecular dynamics simulations shows that substantial changes in the binding conformations have occurred. These results indicate that the initial receptor-ligand interaction observed after docking can be limited due to the receptor rigid docking algorithm and that the conformations and interactions observed after simulation runs are more energetically favoured. We have performed docking and molecular dynamics simulation studies to elucidate the binding mechanism of prospective herbal drug withaferin A onto the structure of DNA polymerase of Herpes simplex virus. Our docking simulations results give high binding affinity of the ligand to the receptor. Long de novo MD simulations for 10 ns performed allowed us to evaluate the dynamic behaviour of the system studied and corroborate the docking results, as well as identify key residues in the enzyme-inhibitor interactions. The present MD simulations support the hypothesis that withaferin A is a potential ligand to target/inhibit DNA polymerase of the Herpes simplex virus. Results of these studies will also guide the design of selective inhibitors of DNA POL with high specificity and potent activity in order to strengthen the therapeutic arsenal available today against the dangerous biological warfare agent represented by Herpes Simplex Virus.

Non-nucleosidic inhibition of Herpes simplex virus DNA polymerase: mechanistic insights into the anti-herpetic mode of action of herbal drug withaferin A

PubMed Central

2011-01-01

Background Herpes Simplex Virus 1 and 2 causes several infections in humans including cold sores and encephalitis. Previous antiviral studies on herpes viruses have focussed on developing nucleoside analogues that can inhibit viral polymerase and terminate the replicating viral DNA. However, these drugs bear an intrinsic non-specificity as they can also inhibit cellular polymerase apart from the viral one. The present study is an attempt to elucidate the action mechanism of naturally occurring withaferin A in inhibiting viral DNA polymerase, thus providing an evidence for its development as a novel anti-herpetic drug. Results Withaferin A was found to bind very similarly to that of the previously reported 4-oxo-DHQ inhibitor. Withaferin A was observed binding to the residues Gln 617, Gln 618, Asn 815 and Tyr 818, all of which are crucial to the proper functioning of the polymerase. A comparison of the conformation obtained from docking and the molecular dynamics simulations shows that substantial changes in the binding conformations have occurred. These results indicate that the initial receptor-ligand interaction observed after docking can be limited due to the receptor rigid docking algorithm and that the conformations and interactions observed after simulation runs are more energetically favoured. Conclusions We have performed docking and molecular dynamics simulation studies to elucidate the binding mechanism of prospective herbal drug withaferin A onto the structure of DNA polymerase of Herpes simplex virus. Our docking simulations results give high binding affinity of the ligand to the receptor. Long de novo MD simulations for 10 ns performed allowed us to evaluate the dynamic behaviour of the system studied and corroborate the docking results, as well as identify key residues in the enzyme-inhibitor interactions. The present MD simulations support the hypothesis that withaferin A is a potential ligand to target/inhibit DNA polymerase of the Herpes simplex virus. Results of these studies will also guide the design of selective inhibitors of DNA POL with high specificity and potent activity in order to strengthen the therapeutic arsenal available today against the dangerous biological warfare agent represented by Herpes Simplex Virus. PMID:22373101

Seeking potential anticonvulsant agents that target GABAA receptors using experimental and theoretical procedures

NASA Astrophysics Data System (ADS)

Saavedra-Vélez, Margarita Virginia; Correa-Basurto, José; Matus, Myrna H.; Gasca-Pérez, Eloy; Bello, Martiniano; Cuevas-Hernández, Roberto; García-Rodríguez, Rosa Virginia; Trujillo-Ferrara, José; Ramos-Morales, Fernando Rafael

2014-12-01

The aim of this study was to identify compounds that possess anticonvulsant activity by using a pentylenetetrazol (PTZ)-induced seizure model. Theoretical studies of a set of ligands, explored the binding affinities of the ligands for the GABAA receptor (GABAAR), including some benzodiazepines. The ligands satisfy the Lipinski rules and contain a pharmacophore core that has been previously reported to be a GABAAR activator. To select the ligands with the best physicochemical properties, all of the compounds were analyzed by quantum mechanics and the energies of the highest occupied molecular orbital and lowest unoccupied molecular orbital were determined. Docking calculations between the ligands and the GABAAR were used to identify the complexes with the highest Gibbs binding energies. The identified compound D1 (dibenzo( b,f)(1,4)diazocine-6,11(5H,12H)-dione) was synthesized, experimentally tested, and the GABAAR-D1 complex was submitted to 12-ns-long molecular dynamics (MD) simulations to corroborate the binding conformation obtained by docking techniques. MD simulations were also used to analyze the decomposition of the Gibbs binding energy of the residues involved in the stabilization of the complex. To validate our theoretical results, molecular docking and MD simulations were also performed for three reference compounds that are currently in commercial use: clonazepam (CLZ), zolpidem and eszopiclone. The theoretical results show that the GABAAR-D1, and GABAAR-CLZ complexes bind to the benzodiazepine binding site, share a similar map of binding residues, and have similar Gibbs binding energies and entropic components. Experimental studies using a PTZ-induced seizure model showed that D1 possesses similar activity to CLZ, which corroborates the predicted binding free energy identified by theoretical calculations.

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2016-09-01

Structure-based drug design (SBDD) has matured within the last two decades as a valuable tool for the optimization of low molecular weight lead compounds to highly potent drugs. The key step in SBDD requires knowledge of the three-dimensional structure of the target-ligand complex, which is usually determined by X-ray crystallography. In the absence of structural information for the complex, SBDD relies on the generation of plausible molecular docking models. However, molecular docking protocols suffer from inaccuracies in the description of the interaction energies between the ligand and the target molecule, and often fail in the prediction of the correct binding mode. In this context, the appropriate selection of the most accurate docking protocol is absolutely relevant for the final molecular docking result, even if addressing this point is absolutely not a trivial task. D3R Grand Challenge 2015 has represented a precious opportunity to test the performance of DockBench, an integrate informatics platform to automatically compare RMDS-based molecular docking performances of different docking/scoring methods. The overall performance resulted in the blind prediction are encouraging in particular for the pose prediction task, in which several complex were predicted with a sufficient accuracy for medicinal chemistry purposes.

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015.

PubMed

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2016-09-01

Structure-based drug design (SBDD) has matured within the last two decades as a valuable tool for the optimization of low molecular weight lead compounds to highly potent drugs. The key step in SBDD requires knowledge of the three-dimensional structure of the target-ligand complex, which is usually determined by X-ray crystallography. In the absence of structural information for the complex, SBDD relies on the generation of plausible molecular docking models. However, molecular docking protocols suffer from inaccuracies in the description of the interaction energies between the ligand and the target molecule, and often fail in the prediction of the correct binding mode. In this context, the appropriate selection of the most accurate docking protocol is absolutely relevant for the final molecular docking result, even if addressing this point is absolutely not a trivial task. D3R Grand Challenge 2015 has represented a precious opportunity to test the performance of DockBench, an integrate informatics platform to automatically compare RMDS-based molecular docking performances of different docking/scoring methods. The overall performance resulted in the blind prediction are encouraging in particular for the pose prediction task, in which several complex were predicted with a sufficient accuracy for medicinal chemistry purposes.

Automated Docking with Protein Flexibility in the Design of Femtomolar “Click Chemistry” Inhibitors of Acetylcholinesterase

PubMed Central

Morris, Garrett M.; Green, Luke G.; Radić, Zoran; Taylor, Palmer; Sharpless, K. Barry; Olson, Arthur J.; Grynszpan, Flavio

2013-01-01

The use of computer-aided structure-based drug design prior to synthesis has proven to be generally valuable in suggesting improved binding analogues of existing ligands.1 Here we describe the application of the program AutoDock2 to the design of a focused library that was used in the “click chemistry in-situ” generation of the most potent non-covalent inhibitor of the enzyme acetylcholinesterase (AChE) yet developed (Kd = ~100 fM).3 AutoDock version 3.0.5 has been widely distributed and successfully used to predict bound conformations of flexible ligands. Here, we also used a version of AutoDock which permits additional conformational flexibility in selected amino acid sidechains of the target protein. PMID:23451944

Accounting for Intraligand Interactions in Flexible Ligand Docking with a PMF-Based Scoring Function.

PubMed

Lizunov, A Y; Gonchar, A L; Zaitseva, N I; Zosimov, V V

2015-10-26

We analyzed the frequency with which intraligand contacts occurred in a set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. Our analysis showed that flexible ligands often form intraligand hydrophobic contacts, while intraligand hydrogen bonds are rare. The test set was also thoroughly investigated and classified. We suggest a universal method for enhancement of a scoring function based on a potential of mean force (PMF-based score) by adding a term accounting for intraligand interactions. The method was implemented via in-house developed program, utilizing an Algo_score scoring function [ Ramensky et al. Proteins: Struct., Funct., Genet. 2007 , 69 , 349 - 357 .] based on the Tarasov-Muryshev PMF [ Muryshev et al. J. Comput.-Aided Mol. Des. 2003 , 17 , 597 - 605 .]. The enhancement of the scoring function was shown to significantly improve the docking and scoring quality for flexible ligands in the test set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. We then investigated the correlation of the docking results with two parameters of intraligand interactions estimation. These parameters are the weight of intraligand interactions and the minimum number of bonds between the ligand atoms required to take their interaction into account.

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

PubMed

Liu, Kai; Watanabe, Etsurou; Kokubo, Hironori

2017-02-01

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.

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes.

PubMed

Marzaro, Giovanni; Ferrarese, Alessandro; Chilin, Adriana

2014-08-01

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.

Energy minimization on manifolds for docking flexible molecules

PubMed Central

Mirzaei, Hanieh; Zarbafian, Shahrooz; Villar, Elizabeth; Mottarella, Scott; Beglov, Dmitri; Vajda, Sandor; Paschalidis, Ioannis Ch.; Vakili, Pirooz; Kozakov, Dima

2015-01-01

In this paper we extend a recently introduced rigid body minimization algorithm, defined on manifolds, to the problem of minimizing the energy of interacting flexible molecules. The goal is to integrate moving the ligand in six dimensional rotational/translational space with internal rotations around rotatable bonds within the two molecules. We show that adding rotational degrees of freedom to the rigid moves of the ligand results in an overall optimization search space that is a manifold to which our manifold optimization approach can be extended. The effectiveness of the method is shown for three different docking problems of increasing complexity. First we minimize the energy of fragment-size ligands with a single rotatable bond as part of a protein mapping method developed for the identification of binding hot spots. Second, we consider energy minimization for docking a flexible ligand to a rigid protein receptor, an approach frequently used in existing methods. In the third problem we account for flexibility in both the ligand and the receptor. Results show that minimization using the manifold optimization algorithm is substantially more efficient than minimization using a traditional all-atom optimization algorithm while producing solutions of comparable quality. In addition to the specific problems considered, the method is general enough to be used in a large class of applications such as docking multidomain proteins with flexible hinges. The code is available under open source license (at http://cluspro.bu.edu/Code/Code_Rigtree.tar), and with minimal effort can be incorporated into any molecular modeling package. PMID:26478722

Spectroscopic and molecular docking studies on the interaction of human serum albumin with copper(II) complexes

NASA Astrophysics Data System (ADS)

Guhathakurta, Bhargab; Pradhan, Ankur Bikash; Das, Suman; Bandyopadhyay, Nirmalya; Lu, Liping; Zhu, Miaoli; Naskar, Jnan Prakash

2017-02-01

Two osazone based ligands, butane-2,3-dione bis(2‧-pyridylhydrazone) (BDBPH) and hexane-3,4-dione bis(2‧-pyridylhydrazone) (HDBPH), were synthesized out of the 2:1 M Schiff base condensation of 2-hydrazino pyridine respectively with 2,3-butanedione and 3,4-hexanedione. The X-ray crystal structures of both the ligands have been determined. The copper(II) complex of HDBPH has also been synthesized and structurally characterized. HDBPH and its copper(II) complex have thoroughly been characterized through various spectroscopic and analytical techniques. The X-ray crystal structure of the copper complex of HDBPH shows that it is a monomeric Cu(II) complex having 'N4O2' co-ordination chromophore. Interaction of human serum albumin (HSA) with these ligands and their monomeric copper(II) complexes have been studied by various spectroscopic means. The experimental findings show that the ligands as well as their copper complexes are good HSA binders. Molecular docking investigations have also been done to unravel the mode of binding of the species with HSA.

Docking studies of antidepressants against single crystal structure of tryptophan 2, 3-dioxygenase using Molegro Virtual Docker software.

PubMed

Dawood, Shazia; Zarina, Shamshad; Bano, Samina

2014-09-01

Tryptophan 2, 3-dioxygenase (TDO) a heme containing enzyme found in mammalian liver is responsible for tryptophan (Trp) catabolism. Trp is an essential amino acid that is degraded in to N-formylkynurenine by the action of TDO. The protein ligand interaction plays a significant role in structural based drug designing. The current study illustrates the binding of established antidepressants (ADs) against TDO enzyme using in-silico docking studies. For this purpose, Fluoxetine, Paroxetine, Sertraline, Fluvoxamine, Seproxetine, Citalopram, Moclobamide, Hyperforin and Amoxepine were selected. In-silico docking studies were carried out using Molegro Virtual Docker (MVD) software. Docking results show that all ADs fit well in the active site of TDO moreover Hyperforin and Paroxetine exhibited high docking scores of -152.484k cal/mol and -139.706k cal/mol, respectively. It is concluded that Hyperforin and Paroxetine are possible lead molecules because of their high docking scores as compared to other ADs examined. Therefore, these two ADs stand as potent inhibitors of TDO enzyme.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

PubMed

Pérez, Germán M; Salomón, Luis A; Montero-Cabrera, Luis A; de la Vega, José M García; Mascini, Marcello

2016-05-01

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

Steric and Thermodynamic Limits of Design for the Incorporation of Large UnNatural Amino Acids in Aminoacyl-tRNA Synthetase Enzymes

PubMed Central

Armen, Roger S.; Schiller, Stefan M.; Brooks, Charles L.

2015-01-01

Orthogonal aminoacyl-tRNA synthetase/tRNA pairs from archaea have been evolved to facilitate site specific in vivo incorporation of unnatural amino acids into proteins in Escherichia coli. Using this approach, unnatural amino acids have been successfully incorporated with high translational efficiency and fidelity. In this study, CHARMM-based molecular docking and free energy calculations were used to evaluate rational design of specific protein-ligand interactions for aminoacyl-tRNA synthetases. A series of novel unnatural amino acid ligands were docked into the p-benzoyl-L-phenylalanine tRNA synthetase, which revealed that the binding pocket of the enzyme does not provide sufficient space for significantly larger ligands. Specific binding site residues were mutated to alanine to create additional space to accommodate larger target ligands, and then mutations were introduced to improve binding free energy. This approach was used to redesign binding sites for several different target ligands, which were then tested against the standard 20 amino acids to verify target specificity. Only the synthetase designed to bind Man-α-O-Tyr was predicted to be sufficiently selective for the target ligand and also thermodynamically stable. Our study suggests that extensive redesign of the tRNA synthatase binding pocket for large bulky ligands may be quite thermodynamically unfavorable. PMID:20310065

Diverse, high-quality test set for the validation of protein-ligand docking performance.

PubMed

Hartshorn, Michael J; Verdonk, Marcel L; Chessari, Gianni; Brewerton, Suzanne C; Mooij, Wijnand T M; Mortenson, Paul N; Murray, Christopher W

2007-02-22

A procedure for analyzing and classifying publicly available crystal structures has been developed. It has been used to identify high-resolution protein-ligand complexes that can be assessed by reconstructing the electron density for the ligand using the deposited structure factors. The complexes have been clustered according to the protein sequences, and clusters have been discarded if they do not represent proteins thought to be of direct interest to the pharmaceutical or agrochemical industry. Rules have been used to exclude complexes containing non-drug-like ligands. One complex from each cluster has been selected where a structure of sufficient quality was available. The final Astex diverse set contains 85 diverse, relevant protein-ligand complexes, which have been prepared in a format suitable for docking and are to be made freely available to the entire research community (http://www.ccdc.cam.ac.uk). The performance of the docking program GOLD against the new set is assessed using a variety of protocols. Relatively unbiased protocols give success rates of approximately 80% for redocking into native structures, but it is possible to get success rates of over 90% with some protocols.

O-desmethylquinine as a cyclooxygenase-2 (COX-2) inhibitors using AutoDock Vina

NASA Astrophysics Data System (ADS)

Damayanti, Sophi; Mahardhika, Andhika Bintang; Ibrahim, Slamet; Chong, Wei Lim; Lee, Vannajan Sanghiran; Tjahjono, Daryono Hadi

2014-10-01

Computational approach was employed to evaluate the biological activity of novel cyclooxygenase-2 COX-2 inhibitor, O-desmethylquinine, in comparison to quinine as common inhibitor which can also be used an agent of antipyretic, antimalaria, analgesic and antiinflamation. The molecular models of the compound were constructed and optimized with the density function theory with at the B3LYP/6-31G (d,p) level using Gaussian 09 program. Molecular docking studies of the compounds were done to obtain the COX-2 complex structures and their binding energies were analyzed using the AutoDock Vina. The results of docking of the two ligands were comparable and cannot be differentiated from the energy scoring function with AutoDock Vina.

Structural, thermogravimetric, B3LYP and biological studies on some heterocyclic thiosemicarbazide copper (II) complexes and evaluation of their molecular docking

NASA Astrophysics Data System (ADS)

Gaber, Mohamed; Fayed, Tarek A.; El-Gamil, Mohammed M.; Abu El-Reash, Gaber M.

2018-01-01

Two copper (II) complexes of ligands H2L1 and H2L2 have been prepared and investigated. The ligands were prepared by the individually addition of picolinic acid hydrazide and 2-(2-aminothiazol-4-yl) acetohydrazide into benzoyl isothiocyanate. The results of analytical and spectroscopic equipments revealed that H2L1 act as monobasic bidentate with square planner environment. While H2L2 behaves as monobasic tetradentate with Oh geometry. The geometries of ligands and their complexes being carefully studied using Jaguar 9.1 program based on the density functional theory (DFT) to predict properties of materials performed by the hybrid density functional method B3LYP. Additionally, thermal degradation data were evaluated to determine the kinetic and thermodynamic parameters by different methods. Moreover, the anti-oxidant (using DPPH and SOD methods), and anti-bacterial activities of the compounds have been studied. Furthermore, the docking study of ligands and their complexes were applied against gram-positive S. Aureus, negative E. Coli bacterial and C. Albicans fungal strains by Schrödinger suite program using XP glide protocol.

Ultrafast protein structure-based virtual screening with Panther

NASA Astrophysics Data System (ADS)

Niinivehmas, Sanna P.; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T.

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Ultrafast protein structure-based virtual screening with Panther.

PubMed

Niinivehmas, Sanna P; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Evaluating the Predictivity of Virtual Screening for Abl Kinase Inhibitors to Hinder Drug Resistance

PubMed Central

Gani, Osman A B S M; Narayanan, Dilip; Engh, Richard A

2013-01-01

Virtual screening methods are now widely used in early stages of drug discovery, aiming to rank potential inhibitors. However, any practical ligand set (of active or inactive compounds) chosen for deriving new virtual screening approaches cannot fully represent all relevant chemical space for potential new compounds. In this study, we have taken a retrospective approach to evaluate virtual screening methods for the leukemia target kinase ABL1 and its drug-resistant mutant ABL1-T315I. ‘Dual active’ inhibitors against both targets were grouped together with inactive ligands chosen from different decoy sets and tested with virtual screening approaches with and without explicit use of target structures (docking). We show how various scoring functions and choice of inactive ligand sets influence overall and early enrichment of the libraries. Although ligand-based methods, for example principal component analyses of chemical properties, can distinguish some decoy sets from active compounds, the addition of target structural information via docking improves enrichment, and explicit consideration of multiple target conformations (i.e. types I and II) achieves best enrichment of active versus inactive ligands, even without assuming knowledge of the binding mode. We believe that this study can be extended to other therapeutically important kinases in prospective virtual screening studies. PMID:23746052

Computational predictive models for P-glycoprotein inhibition of in-house chalcone derivatives and drug-bank compounds.

PubMed

Ngo, Trieu-Du; Tran, Thanh-Dao; Le, Minh-Tri; Thai, Khac-Minh

2016-11-01

The human P-glycoprotein (P-gp) efflux pump is of great interest for medicinal chemists because of its important role in multidrug resistance (MDR). Because of the high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of this transmembrane protein, ligand-based, and structure-based approaches which were machine learning, homology modeling, and molecular docking were combined for this study. In ligand-based approach, individual two-dimensional quantitative structure-activity relationship models were developed using different machine learning algorithms and subsequently combined into the Ensemble model which showed good performance on both the diverse training set and the validation sets. The applicability domain and the prediction quality of the developed models were also judged using the state-of-the-art methods and tools. In our structure-based approach, the P-gp structure and its binding region were predicted for a docking study to determine possible interactions between the ligands and the receptor. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening using prediction models and molecular docking in an attempt to restore cancer cell sensitivity to cytotoxic drugs.

Molecular interactions of agonist and inverse agonist ligands at serotonin 5-HT2C G protein-coupled receptors: computational ligand docking and molecular dynamics studies validated by experimental mutagenesis results

NASA Astrophysics Data System (ADS)

Córdova-Sintjago, Tania C.; Liu, Yue; Booth, Raymond G.

2015-02-01

To understand molecular determinants for ligand activation of the serotonin 5-HT2C G protein-coupled receptor (GPCR), a drug target for obesity and neuropsychiatric disorders, a 5-HT2C homology model was built according to an adrenergic β2 GPCR (β2AR) structure and validated using a 5-HT2B GPCR crystal structure. The models were equilibrated in a simulated phosphatidyl choline membrane for ligand docking and molecular dynamics studies. Ligands included (2S, 4R)-(-)-trans-4-(3'-bromo- and trifluoro-phenyl)-N,N-dimethyl-1,2,3,4-tetrahydronaphthalene-2-amine (3'-Br-PAT and 3'-CF3-PAT), a 5-HT2C agonist and inverse agonist, respectively. Distinct interactions of 3'-Br-PAT and 3'-CF3-PAT at the wild-type (WT) 5-HT2C receptor model were observed and experimental 5-HT2C receptor mutagenesis studies were undertaken to validate the modelling results. For example, the inverse agonist 3'-CF3-PAT docked deeper in the WT 5-HT2C binding pocket and altered the orientation of transmembrane helices (TM) 6 in comparison to the agonist 3'-Br-PAT, suggesting that changes in TM orientation that result from ligand binding impact function. For both PATs, mutation of 5-HT2C residues S3.36, T3.37, and F5.47 to alanine resulted in significantly decreased affinity, as predicted from modelling results. It was concluded that upon PAT binding, 5-HT2C residues T3.37 and F5.47 in TMs 3 and 5, respectively, engage in inter-helical interactions with TMs 4 and 6, respectively. The movement of TMs 5 and 6 upon agonist and inverse agonist ligand binding observed in the 5-HT2C receptor modelling studies was similar to movements reported for the activation and deactivation of the β2AR, suggesting common mechanisms among aminergic neurotransmitter GPCRs.

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

PubMed

Satpathy, Raghunath; Guru, R K; Behera, R; Nayak, B

2015-01-01

Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

A Comprehensive Docking and MM/GBSA Rescoring Study of Ligand Recognition upon Binding Antithrombin

DOE PAGES

Zhang, Xiaohua; Perez-Sanchez, Horacio; C. Lightstone, Felice

2017-04-06

A high-throughput virtual screening pipeline has been extended from single energetically minimized structure Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) rescoring to ensemble-average MM/GBSA rescoring. The correlation coefficient (R2) of calculated and experimental binding free energies for a series of antithrombin ligands has been improved from 0.36 to 0.69 when switching from the single-structure MM/GBSA rescoring to ensemble-average one. The electrostatic interactions in both solute and solvent are identified to play an important role in determining the binding free energy after the decomposition of the calculated binding free energy. Furthermore, the increasing negative charge of the compounds provides a more favorablemore » electrostatic energy change but creates a higher penalty for the solvation free energy. Such a penalty is compensated by the electrostatic energy change, which results in a better binding affinity. A highly hydrophobic ligand is determined by the docking program to be a non-specific binder. Finally, these results have demonstrated that it is very important to keep a few top poses for rescoring, if the binding is non-specific or the binding mode is not well determined by the docking calculation.« less

Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark.

PubMed

Grinter, Sam Z; Yan, Chengfei; Huang, Sheng-You; Jiang, Lin; Zou, Xiaoqin

2013-08-26

In this study, we use the recently released 2012 Community Structure-Activity Resource (CSAR) data set to evaluate two knowledge-based scoring functions, ITScore and STScore, and a simple force-field-based potential (VDWScore). The CSAR data set contains 757 compounds, most with known affinities, and 57 crystal structures. With the help of the script files for docking preparation, we use the full CSAR data set to evaluate the performances of the scoring functions on binding affinity prediction and active/inactive compound discrimination. The CSAR subset that includes crystal structures is used as well, to evaluate the performances of the scoring functions on binding mode and affinity predictions. Within this structure subset, we investigate the importance of accurate ligand and protein conformational sampling and find that the binding affinity predictions are less sensitive to non-native ligand and protein conformations than the binding mode predictions. We also find the full CSAR data set to be more challenging in making binding mode predictions than the subset with structures. The script files used for preparing the CSAR data set for docking, including scripts for canonicalization of the ligand atoms, are offered freely to the academic community.

Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations

PubMed Central

2017-01-01

Computational screening is a method to prioritize small-molecule compounds based on the structural and biochemical attributes built from ligand and target information. Previously, we have developed a scalable virtual screening workflow to identify novel multitarget kinase/bromodomain inhibitors. In the current study, we identified several novel N-[3-(2-oxo-pyrrolidinyl)phenyl]-benzenesulfonamide derivatives that scored highly in our ensemble docking protocol. We quantified the binding affinity of these compounds for BRD4(BD1) biochemically and generated cocrystal structures, which were deposited in the Protein Data Bank. As the docking poses obtained in the virtual screening pipeline did not align with the experimental cocrystal structures, we evaluated the predictions of their precise binding modes by performing molecular dynamics (MD) simulations. The MD simulations closely reproduced the experimentally observed protein–ligand cocrystal binding conformations and interactions for all compounds. These results suggest a computational workflow to generate experimental-quality protein–ligand binding models, overcoming limitations of docking results due to receptor flexibility and incomplete sampling, as a useful starting point for the structure-based lead optimization of novel BRD4(BD1) inhibitors. PMID:28884163

A Comprehensive Docking and MM/GBSA Rescoring Study of Ligand Recognition upon Binding Antithrombin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xiaohua; Perez-Sanchez, Horacio; C. Lightstone, Felice

A high-throughput virtual screening pipeline has been extended from single energetically minimized structure Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) rescoring to ensemble-average MM/GBSA rescoring. The correlation coefficient (R2) of calculated and experimental binding free energies for a series of antithrombin ligands has been improved from 0.36 to 0.69 when switching from the single-structure MM/GBSA rescoring to ensemble-average one. The electrostatic interactions in both solute and solvent are identified to play an important role in determining the binding free energy after the decomposition of the calculated binding free energy. Furthermore, the increasing negative charge of the compounds provides a more favorablemore » electrostatic energy change but creates a higher penalty for the solvation free energy. Such a penalty is compensated by the electrostatic energy change, which results in a better binding affinity. A highly hydrophobic ligand is determined by the docking program to be a non-specific binder. Finally, these results have demonstrated that it is very important to keep a few top poses for rescoring, if the binding is non-specific or the binding mode is not well determined by the docking calculation.« less

Implementation of the Hungarian Algorithm to Account for Ligand Symmetry and Similarity in Structure-Based Design

PubMed Central

2015-01-01

False negative docking outcomes for highly symmetric molecules are a barrier to the accurate evaluation of docking programs, scoring functions, and protocols. This work describes an implementation of a symmetry-corrected root-mean-square deviation (RMSD) method into the program DOCK based on the Hungarian algorithm for solving the minimum assignment problem, which dynamically assigns atom correspondence in molecules with symmetry. The algorithm adds only a trivial amount of computation time to the RMSD calculations and is shown to increase the reported overall docking success rate by approximately 5% when tested over 1043 receptor–ligand systems. For some families of protein systems the results are even more dramatic, with success rate increases up to 16.7%. Several additional applications of the method are also presented including as a pairwise similarity metric to compare molecules during de novo design, as a scoring function to rank-order virtual screening results, and for the analysis of trajectories from molecular dynamics simulation. The new method, including source code, is available to registered users of DOCK6 (http://dock.compbio.ucsf.edu). PMID:24410429

FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols.

PubMed

Bohari, Mohammed H; Sastry, G Narahari

2012-09-01

Efficient drug discovery programs can be designed by utilizing existing pools of knowledge from the already approved drugs. This can be achieved in one way by repositioning of drugs approved for some indications to newer indications. Complex of drug to its target gives fundamental insight into molecular recognition and a clear understanding of putative binding site. Five popular docking protocols, Glide, Gold, FlexX, Cdocker and LigandFit have been evaluated on a dataset of 199 FDA approved drug-target complexes for their accuracy in predicting the experimental pose. Performance for all the protocols is assessed at default settings, with root mean square deviation (RMSD) between the experimental ligand pose and the docked pose of less than 2.0 Å as the success criteria in predicting the pose. Glide (38.7 %) is found to be the most accurate in top ranked pose and Cdocker (58.8 %) in top RMSD pose. Ligand flexibility is a major bottleneck in failure of docking protocols to correctly predict the pose. Resolution of the crystal structure shows an inverse relationship with the performance of docking protocol. All the protocols perform optimally when a balanced type of hydrophilic and hydrophobic interaction or dominant hydrophilic interaction exists. Overall in 16 different target classes, hydrophobic interactions dominate in the binding site and maximum success is achieved for all the docking protocols in nuclear hormone receptor class while performance for the rest of the classes varied based on individual protocol.

Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

PubMed

Arcon, Juan Pablo; Defelipe, Lucas A; Modenutti, Carlos P; López, Elias D; Alvarez-Garcia, Daniel; Barril, Xavier; Turjanski, Adrián G; Martí, Marcelo A

2017-04-24

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015.

PubMed

Slynko, Inna; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2016-09-01

High affinity ligands for a given target tend to share key molecular interactions with important anchoring amino acids and therefore often present quite conserved interaction patterns. This simple concept was formalized in a topological knowledge-based scoring function (GRIM) for selecting the most appropriate docking poses from previously X-rayed interaction patterns. GRIM first converts protein-ligand atomic coordinates (docking poses) into a simple 3D graph describing the corresponding interaction pattern. In a second step, proposed graphs are compared to that found from template structures in the Protein Data Bank. Last, all docking poses are rescored according to an empirical score (GRIMscore) accounting for overlap of maximum common subgraphs. Taking the opportunity of the public D3R Grand Challenge 2015, GRIM was used to rescore docking poses for 36 ligands (6 HSP90α inhibitors, 30 MAP4K4 inhibitors) prior to the release of the corresponding protein-ligand X-ray structures. When applied to the HSP90α dataset, for which many protein-ligand X-ray structures are already available, GRIM provided very high quality solutions (mean rmsd = 1.06 Å, n = 6) as top-ranked poses, and significantly outperformed a state-of-the-art scoring function. In the case of MAP4K4 inhibitors, for which preexisting 3D knowledge is scarce and chemical diversity is much larger, the accuracy of GRIM poses decays (mean rmsd = 3.18 Å, n = 30) although GRIM still outperforms an energy-based scoring function. GRIM rescoring appears to be quite robust with comparison to the other approaches competing for the same challenge (42 submissions for the HSP90 dataset, 27 for the MAP4K4 dataset) as it ranked 3rd and 2nd respectively, for the two investigated datasets. The rescoring method is quite simple to implement, independent on a docking engine, and applicable to any target for which at least one holo X-ray structure is available.

Biological evaluation, docking and molecular dynamic simulation of some novel diaryl urea derivatives bearing quinoxalindione moiety

PubMed Central

Sadeghian-Rizi, Sedighe; Khodarahmi, Ghadamali Ali; Sakhteman, Amirhossein; Jahanian-Najafabadi, Ali; Rostami, Mahboubeh; Mirzaei, Mahmoud; Hassanzadeh, Farshid

2017-01-01

In this study a series of diarylurea derivatives containing quinoxalindione group were biologically evaluated for their cytotoxic activities using MTT assay against MCF-7 and HepG2 cell lines. Antibacterial activities of these compounds were also evaluated by Microplate Alamar Blue Assay (MABA) against three Gram-negative (Escherichia coli, Pseudomonas aeruginosa and Salmonella typhi), three Gram-positive (Staphylococcus aureus, Bacillus subtilis and Listeria monocitogenes) and one yeast-like fungus (Candida albicans) strain. Furthermore, molecular docking was carried out to study the binding pattern of the compounds to the active site of B-RAF kinase (PDB code: 1UWH). Molecular dynamics simulation was performed on the best ligand (16e) to investigate the ligand binding dynamics in the physiological environment. Cytotoxic evaluation revealed the most prominent cytotoxicity for 6 compounds with IC50 values of 10-18 μM against two mentioned cell lines. None of the synthesized compounds showed significant antimicrobial activity. The obtained results of the molecular docking study showed that all compounds fitted in the binding site of enzyme with binding energy range of -11.22 to -12.69 kcal/mol vs sorafenib binding energy -11.74 kcal/mol as the lead compound. Molecular dynamic simulation indicated that the binding of ligand (16e) was stable in the active site of B-RAF during the simulation. PMID:29204178

Application of binding free energy calculations to prediction of binding modes and affinities of MDM2 and MDMX inhibitors.

PubMed

Lee, Hui Sun; Jo, Sunhwan; Lim, Hyun-Suk; Im, Wonpil

2012-07-23

Molecular docking is widely used to obtain binding modes and binding affinities of a molecule to a given target protein. Despite considerable efforts, however, prediction of both properties by docking remains challenging mainly due to protein's structural flexibility and inaccuracy of scoring functions. Here, an integrated approach has been developed to improve the accuracy of binding mode and affinity prediction and tested for small molecule MDM2 and MDMX antagonists. In this approach, initial candidate models selected from docking are subjected to equilibration MD simulations to further filter the models. Free energy perturbation molecular dynamics (FEP/MD) simulations are then applied to the filtered ligand models to enhance the ability in predicting the near-native ligand conformation. The calculated binding free energies for MDM2 complexes are overestimated compared to experimental measurements mainly due to the difficulties in sampling highly flexible apo-MDM2. Nonetheless, the FEP/MD binding free energy calculations are more promising for discriminating binders from nonbinders than docking scores. In particular, the comparison between the MDM2 and MDMX results suggests that apo-MDMX has lower flexibility than apo-MDM2. In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions.

Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets

NASA Astrophysics Data System (ADS)

Selwa, Edithe; Martiny, Virginie Y.; Iorga, Bogdan I.

2016-09-01

The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.

Advances in the treatment of explicit water molecules in docking and binding free energy calculations.

PubMed

Hu, Xiao; Maffucci, Irene; Contini, Alessandro

2018-05-13

The inclusion of direct effects mediated by water during the ligand-receptor recognition is a hot-topic of modern computational chemistry applied to drug discovery and development. Docking or virtual screening with explicit hydration is still debatable, despite the successful cases that have been presented in the last years. Indeed, how to select the water molecules that will be included in the docking process or how the included waters should be treated remain open questions. In this review, we will discuss some of the most recent methods that can be used in computational drug discovery and drug development when the effect of a single water, or of a small network of interacting waters, needs to be explicitly considered. Here, we analyse software to aid the selection, or to predict the position, of water molecules that are going to be explicitly considered in later docking studies. We also present software and protocols able to efficiently treat flexible water molecules during docking, including examples of applications. Finally, we discuss methods based on molecular dynamics simulations that can be used to integrate docking studies or to reliably and efficiently compute binding energies of ligands in presence of interfacial or bridging water molecules. Software applications aiding the design of new drugs that exploit water molecules, either as displaceable residues or as bridges to the receptor, are constantly being developed. Although further validation is needed, workflows that explicitly consider water will probably become a standard for computational drug discovery soon. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Conserved Binding Mode of Human [beta subscript 2] Adrenergic Receptor Inverse Agonists and Antagonist Revealed by X-ray Crystallography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wacker, Daniel; Fenalti, Gustavo; Brown, Monica A.

2010-11-15

G protein-coupled receptors (GPCRs) represent a large fraction of current pharmaceutical targets, and of the GPCRs, the {beta}{sub 2} adrenergic receptor ({beta}{sub 2}AR) is one of the most extensively studied. Previously, the X-ray crystal structure of {beta}{sub 2}AR has been determined in complex with two partial inverse agonists, but the global impact of additional ligands on the structure or local impacts on the binding site are not well-understood. To assess the extent of such ligand-induced conformational differences, we determined the crystal structures of a previously described engineered {beta}{sub 2}AR construct in complex with two inverse agonists: ICI 118,551 (2.8 {angstrom}),more » a recently described compound (2.8 {angstrom}) (Kolb et al, 2009), and the antagonist alprenolol (3.1 {angstrom}). The structures show the same overall fold observed for the previous {beta}{sub 2}AR structures and demonstrate that the ligand binding site can accommodate compounds of different chemical and pharmacological properties with only minor local structural rearrangements. All three compounds contain a hydroxy-amine motif that establishes a conserved hydrogen bond network with the receptor and chemically diverse aromatic moieties that form distinct interactions with {beta}{sub 2}AR. Furthermore, receptor ligand cross-docking experiments revealed that a single {beta}{sub 2}AR complex can be suitable for docking of a range of antagonists and inverse agonists but also indicate that additional ligand-receptor structures may be useful to further improve performance for in-silico docking or lead-optimization in drug design.« less

Binding affinities of the farnesoid X receptor in the D3R Grand Challenge 2 estimated by free-energy perturbation and docking

NASA Astrophysics Data System (ADS)

Olsson, Martin A.; García-Sosa, Alfonso T.; Ryde, Ulf

2018-01-01

We have studied the binding of 102 ligands to the farnesoid X receptor within the D3R Grand Challenge 2016 blind-prediction competition. First, we employed docking with five different docking software and scoring functions. The selected docked poses gave an average root-mean-squared deviation of 4.2 Å. Consensus scoring gave decent results with a Kendall's τ of 0.26 ± 0.06 and a Spearman's ρ of 0.41 ± 0.08. For a subset of 33 ligands, we calculated relative binding free energies with free-energy perturbation. Five transformations between the ligands involved a change of the net charge and we implemented and benchmarked a semi-analytic correction (Rocklin et al., J Chem Phys 139:184103, 2013) for artifacts caused by the periodic boundary conditions and Ewald summation. The results gave a mean absolute deviation of 7.5 kJ/mol compared to the experimental estimates and a correlation coefficient of R 2 = 0.1. These results were among the four best in this competition out of 22 submissions. The charge corrections were significant (7-8 kJ/mol) and always improved the results. By employing 23 intermediate states in the free-energy perturbation, there was a proper overlap between all states and the precision was 0.1-0.7 kJ/mol. However, thermodynamic cycles indicate that the sampling was insufficient in some of the perturbations.

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches

NASA Astrophysics Data System (ADS)

Thangsunan, Patcharapong; Kittiwachana, Sila; Meepowpan, Puttinan; Kungwan, Nawee; Prangkio, Panchika; Hannongbua, Supa; Suree, Nuttee

2016-06-01

Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is an attractive option that provides better predictions. Herein we present the first development of rapid and simple tuning models for predicting and scoring inhibitory activity of investigated ligands docked into catalytic core domain structures of HIV-1 integrase (IN) enzyme. We developed the models using all energetic terms obtained from flexible ligand-rigid receptor dockings by AutoDock4, followed by a data analysis using either partial least squares (PLS) or self-organizing maps (SOMs). The models were established using 66 and 64 ligands of mercaptobenzenesulfonamides for the PLS-based and the SOMs-based inhibitory activity predictions, respectively. The models were then evaluated for their predictability quality using closely related test compounds, as well as five different unrelated inhibitor test sets. Weighting constants for each energy term were also optimized, thus customizing the scoring function for this specific target protein. Root-mean-square error (RMSE) values between the predicted and the experimental inhibitory activities were determined to be <1 (i.e. within a magnitude of a single log scale of actual IC50 values). Hence, we propose that, as a pre-functional assay screening step, AutoDock4 docking in combination with these subsequent rapid weighted energy tuning methods via PLS and SOMs analyses is a viable approach to predict the potential inhibitory activity and to discriminate among small drug-like molecules to target a specific protein of interest.

Molecular modeling and molecular dynamics simulation studies on the interactions of hydroxylated polychlorinated biphenyls with estrogen receptor-β.

PubMed

Li, Xiaolin; Ye, Li; Wang, Xiaoxiang; Shi, Wei; Qian, XiangPing; Zhu, YongLiang; Yu, HongXia

2013-10-01

Endocrine-disrupting chemicals have attracted great concern. As major metabolites of polychlorinated biphenyls (PCBs), hydroxylated polychlorinated biphenyls (HO-PCBs) may disrupt estrogen hormone status because of their structural similarity to estrogen endogenous compounds. However, interactions between HO-PCBs and estrogen receptors (ERs) are not fully understood. In the present work, a molecular modeling study combining molecular docking, molecular dynamics simulations, and binding free energy calculations was performed to characterize the interactions of three HO-PCBs (4'-HO-PCB50, 2'-HO-PCB65, and 4'-HO-PCB69) having much different estrogenic activities with ERβ. Docking results showed that binding between ligands and ERβ was stabilized by hydrogen bond and hydrophobic interactions. The binding free energies of three ligands with ERβ were calculated, and further binding free energy decomposition analysis indicated that the dominating driving force of the binding between the ligands and ERβ was the van der Waals interaction. Some key residues, such as Leu298, Phe356, Gly472, His475, and Leu476, played important roles in ligand-receptor interactions by forming hydrophobic and hydrogen bond interactions with ligands. The results may be beneficial to increase understanding of the interactions between HO-PCBs and ERβ.

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

Application of molecular docking for the degradation of organic pollutants in the environmental remediation: A review.

PubMed

Liu, Zhifeng; Liu, Yujie; Zeng, Guangming; Shao, Binbin; Chen, Ming; Li, Zhigang; Jiang, Yilin; Liu, Yang; Zhang, Yu; Zhong, Hua

2018-07-01

The molecular docking has been employed successfully to study the mechanism of biodegradation in the environmental remediation in the past few years, although medical science and biology are the main application areas for it. Molecular docking is a very convenient and low cost method to understand the reaction mechanism of proteins or enzymes with ligands with a high accuracy. This paper mainly provides a review for the application of molecular docking between organic pollutants and enzymes. It summarizes the fundamental knowledge of molecular docking, such as its theory, available softwares and main databases. Moreover, five types of pollutants, including phenols, BTEX (benzene, toluene, ethylbenzene, and xylenes), nitrile, polycyclic aromatic hydrocarbons (PAHs), and high polymer (e.g., lignin and cellulose), are discussed from molecular level. Different removal mechanisms are also explained in detail via docking technology. Even though this method shows promising application in the research of biodegradation, further studies are still needed to relate with actual condition. Copyright © 2018 Elsevier Ltd. All rights reserved.

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

PubMed

Therrien, Eric; Weill, Nathanael; Tomberg, Anna; Corbeil, Christopher R; Lee, Devin; Moitessier, Nicolas

2014-11-24

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

Molecular Dynamic Studies of the Complex Polyethylenimine and Glucose Oxidase.

PubMed

Szefler, Beata; Diudea, Mircea V; Putz, Mihai V; Grudzinski, Ireneusz P

2016-10-27

Glucose oxidase (GOx) is an enzyme produced by Aspergillus, Penicillium and other fungi species. It catalyzes the oxidation of β-d-glucose (by the molecular oxygen or other molecules, like quinones, in a higher oxidation state) to form d-glucono-1,5-lactone, which hydrolyses spontaneously to produce gluconic acid. A coproduct of this enzymatic reaction is hydrogen peroxide (H₂O₂). GOx has found several commercial applications in chemical and pharmaceutical industries including novel biosensors that use the immobilized enzyme on different nanomaterials and/or polymers such as polyethylenimine (PEI). The problem of GOx immobilization on PEI is retaining the enzyme native activity despite its immobilization onto the polymer surface. Therefore, the molecular dynamic (MD) study of the PEI ligand (C14N8_07_B22) and the GOx enzyme (3QVR) was performed to examine the final complex PEI-GOx stabilization and the affinity of the PEI ligand to the docking sites of the GOx enzyme. The docking procedure showed two places/regions of major interaction of the protein with the polymer PEI: (LIG1) of -5.8 kcal/mol and (LIG2) of -4.5 kcal/mol located inside the enzyme and on its surface, respectively. The values of enthalpy for the PEI-enzyme complex, located inside of the protein (LIG1) and on its surface (LIG2) were computed. Docking also discovered domains of the GOx protein that exhibit no interactions with the ligand or have even repulsive characteristics. The structural data clearly indicate some differences in the ligand PEI behavior bound at the two places/regions of glucose oxidase.

Computational Insight into Protein Tyrosine Phosphatase 1B Inhibition: A Case Study of the Combined Ligand- and Structure-Based Approach.

PubMed

Zhang, Xiangyu; Jiang, Hailun; Li, Wei; Wang, Jian; Cheng, Maosheng

2017-01-01

Protein tyrosine phosphatase 1B (PTP1B) is an attractive target for treating cancer, obesity, and type 2 diabetes. In our work, the way of combined ligand- and structure-based approach was applied to analyze the characteristics of PTP1B enzyme and its interaction with competitive inhibitors. Firstly, the pharmacophore model of PTP1B inhibitors was built based on the common feature of sixteen compounds. It was found that the pharmacophore model consisted of five chemical features: one aromatic ring (R) region, two hydrophobic (H) groups, and two hydrogen bond acceptors (A). To further elucidate the binding modes of these inhibitors with PTP1B active sites, four docking programs (AutoDock 4.0, AutoDock Vina 1.0, standard precision (SP) Glide 9.7, and extra precision (XP) Glide 9.7) were used. The characteristics of the active sites were then described by the conformations of the docking results. In conclusion, a combination of various pharmacophore features and the integration information of structure activity relationship (SAR) can be used to design novel potent PTP1B inhibitors.

jMetalCpp: optimizing molecular docking problems with a C++ metaheuristic framework.

PubMed

López-Camacho, Esteban; García Godoy, María Jesús; Nebro, Antonio J; Aldana-Montes, José F

2014-02-01

Molecular docking is a method for structure-based drug design and structural molecular biology, which attempts to predict the position and orientation of a small molecule (ligand) in relation to a protein (receptor) to produce a stable complex with a minimum binding energy. One of the most widely used software packages for this purpose is AutoDock, which incorporates three metaheuristic techniques. We propose the integration of AutoDock with jMetalCpp, an optimization framework, thereby providing both single- and multi-objective algorithms that can be used to effectively solve docking problems. The resulting combination of AutoDock + jMetalCpp allows users of the former to easily use the metaheuristics provided by the latter. In this way, biologists have at their disposal a richer set of optimization techniques than those already provided in AutoDock. Moreover, designers of metaheuristic techniques can use molecular docking for case studies, which can lead to more efficient algorithms oriented to solving the target problems.  jMetalCpp software adapted to AutoDock is freely available as a C++ source code at http://khaos.uma.es/AutodockjMetal/.

Structural insights of a PI3K/mTOR dual inhibitor with the morpholino-triazine scaffold

NASA Astrophysics Data System (ADS)

Takeda, Takako; Wang, Yanli; Bryant, Stephen H.

2016-04-01

Stimulation of the PI3K/Akt/mTOR pathway, which controls cell proliferation and growth, is often observed in cancer cell. Inhibiting both PI3K and mTOR in this pathway can switch off Akt activation and hence, plays a powerful role for modulating this pathway. PKI-587, a drug containing the structure of morpholino-triazines, shows a dual and nano-molar inhibition activity and is currently in clinical trial. To provide an insight into the mechanism of this dual inhibition, pharmacophore and QSAR models were developed in this work using compounds based on the morpholino-triazines scaffold, followed by a docking study. Pharmacophore model suggested the mechanism of the inhibition of PI3Kα and mTOR by the compounds were mostly the same, which was supported by the docking study showing similar docking modes. The analysis also suggested the importance of the flat plane shape of the ligands, the space surrounding the ligands in the binding pocket, and the slight difference in the shape of the binding sites between PI3Kα and mTOR.

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

PubMed

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

@TOME-2: a new pipeline for comparative modeling of protein–ligand complexes

PubMed Central

Pons, Jean-Luc; Labesse, Gilles

2009-01-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein–protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein–ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/ PMID:19443448

Docking, synthesis, and NMR studies of mannosyl trisaccharide ligands for DC-SIGN lectin.

PubMed

Reina, José J; Díaz, Irene; Nieto, Pedro M; Campillo, Nuria E; Páez, Juan A; Tabarani, Georges; Fieschi, Franck; Rojo, Javier

2008-08-07

DC-SIGN, a lectin, which presents at the surface of immature dendritic cells, constitutes nowadays a promising target for the design of new antiviral drugs. This lectin recognizes highly glycosylated proteins present at the surface of several pathogens such as HIV, Ebola virus, Candida albicans, Mycobacterium tuberculosis, etc. Understanding the binding mode of this lectin is a topic of tremendous interest and will permit a rational design of new and more selective ligands. Here, we present computational and experimental tools to study the interaction of di- and trisaccharides with DC-SIGN. Docking analysis of complexes involving mannosyl di- and trisaccharides and the carbohydrate recognition domain (CRD) of DC-SIGN have been performed. Trisaccharides Manalpha1,2[Manalpha1,6]Man 1 and Manalpha1,3[Manalpha1,6]Man 2 were synthesized from an orthogonally protected mannose as a common intermediate. Using these ligands and the soluble extracellular domain (ECD) of DC-SIGN, NMR experiments based on STD and transfer-NOE were performed providing additional information. Conformational analysis of the mannosyl ligands in the free and bound states was done. These studies have demonstrated that terminal mannoses at positions 2 or 3 in the trisaccharides are the most important moiety and present the strongest contact with the binding site of the lectin. Multiple binding modes could be proposed and therefore should be considered in the design of new ligands.

Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition.

PubMed

Chakraborty, Sandipan; Ramachandran, Balaji; Basu, Soumalee

2014-10-01

Mimicking receptor flexibility during receptor-ligand binding is a challenging task in computational drug design since it is associated with a large increase in the conformational search space. In the present study, we have devised an in silico design strategy incorporating receptor flexibility in virtual screening to identify potential lead compounds as inhibitors for flexible proteins. We have considered BACE1 (β-secretase), a key target protease from a therapeutic perspective for Alzheimer's disease, as the highly flexible receptor. The protein undergoes significant conformational transitions from open to closed form upon ligand binding, which makes it a difficult target for inhibitor design. We have designed a hybrid structure-activity model containing both ligand based descriptors and energetic descriptors obtained from molecular docking based on a dataset of structurally diverse BACE1 inhibitors. An ensemble of receptor conformations have been used in the docking study, further improving the prediction ability of the model. The designed model that shows significant prediction ability judged by several statistical parameters has been used to screen an in house developed 3-D structural library of 731 phytochemicals. 24 highly potent, novel BACE1 inhibitors with predicted activity (Ki) ≤ 50 nM have been identified. Detailed analysis reveals pharmacophoric features of these novel inhibitors required to inhibit BACE1.

CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma.

PubMed

Carlson, Heather A; Smith, Richard D; Damm-Ganamet, Kelly L; Stuckey, Jeanne A; Ahmed, Aqeel; Convery, Maire A; Somers, Donald O; Kranz, Michael; Elkins, Patricia A; Cui, Guanglei; Peishoff, Catherine E; Lambert, Millard H; Dunbar, James B

2016-06-27

The 2014 CSAR Benchmark Exercise was the last community-wide exercise that was conducted by the group at the University of Michigan, Ann Arbor. For this event, GlaxoSmithKline (GSK) donated unpublished crystal structures and affinity data from in-house projects. Three targets were used: tRNA (m1G37) methyltransferase (TrmD), Spleen Tyrosine Kinase (SYK), and Factor Xa (FXa). A particularly strong feature of the GSK data is its large size, which lends greater statistical significance to comparisons between different methods. In Phase 1 of the CSAR 2014 Exercise, participants were given several protein-ligand complexes and asked to identify the one near-native pose from among 200 decoys provided by CSAR. Though decoys were requested by the community, we found that they complicated our analysis. We could not discern whether poor predictions were failures of the chosen method or an incompatibility between the participant's method and the setup protocol we used. This problem is inherent to decoys, and we strongly advise against their use. In Phase 2, participants had to dock and rank/score a set of small molecules given only the SMILES strings of the ligands and a protein structure with a different ligand bound. Overall, docking was a success for most participants, much better in Phase 2 than in Phase 1. However, scoring was a greater challenge. No particular approach to docking and scoring had an edge, and successful methods included empirical, knowledge-based, machine-learning, shape-fitting, and even those with solvation and entropy terms. Several groups were successful in ranking TrmD and/or SYK, but ranking FXa ligands was intractable for all participants. Methods that were able to dock well across all submitted systems include MDock,1 Glide-XP,2 PLANTS,3 Wilma,4 Gold,5 SMINA,6 Glide-XP2/PELE,7 FlexX,8 and MedusaDock.9 In fact, the submission based on Glide-XP2/PELE7 cross-docked all ligands to many crystal structures, and it was particularly impressive to see success across an ensemble of protein structures for multiple targets. For scoring/ranking, submissions that showed statistically significant achievement include MDock1 using ITScore1,10 with a flexible-ligand term,11 SMINA6 using Autodock-Vina,12,13 FlexX8 using HYDE,14 and Glide-XP2 using XP DockScore2 with and without ROCS15 shape similarity.16 Of course, these results are for only three protein targets, and many more systems need to be investigated to truly identify which approaches are more successful than others. Furthermore, our exercise is not a competition.

Chiral halogenated Schiff base compounds: green synthesis, anticancer activity and DNA-binding study

NASA Astrophysics Data System (ADS)

Ariyaeifar, Mahnaz; Amiri Rudbari, Hadi; Sahihi, Mehdi; Kazemi, Zahra; Kajani, Abolghasem Abbasi; Zali-Boeini, Hassan; Kordestani, Nazanin; Bruno, Giuseppe; Gharaghani, Sajjad

2018-06-01

Eight enantiomerically pure halogenated Schiff base compounds were synthesized by reaction of halogenated salicylaldehydes with 3-Amino-1,2-propanediol (R or S) in water as green solvent at ambient temperature. All compounds were characterized by elemental analyses, NMR (1H and 13C), circular dichroism (CD) and FT-IR spectroscopy. FS-DNA binding studies of these compounds carried out by fluorescence quenching and UV-vis spectroscopy. The obtained results revealed that the ligands bind to DNA as: (Rsbnd ClBr) > (Rsbnd Cl2) > (Rsbnd Br2) > (Rsbnd I2) and (Ssbnd ClBr) > (Ssbnd Cl2) > (Ssbnd Br2) > (Ssbnd I2), indicating the effect of halogen on binding constant. In addition, DNA-binding constant of the Ssbnd and R-enantiomers are different from each other. The ligands can form halogen bonds with DNA that were confirmed by molecular docking. This method was also measured the bond distances and bond angles. The study of obtained data can have concluded that binding affinity of the ligands to DNA depends on strength of halogen bonds. The potential anticancer activity of ligands were also evaluated on MCF-7 and HeLa cancer cell lines by using MTT assay. The results showed that the anticancer activity and FS-DNA interaction is significantly dependent on the stereoisomers of Schiff base compounds as R-enantiomers displayed significantly higher activity than S-enantiomers. The molecular docking was also used to illustrate the specific DNA-binding of synthesized compounds and groove binding mode of DNA interaction was proposed for them. In addition, molecular docking results indicated that there are three types of bonds (Hsbnd and X-bond and hX-bond) between synthesized compounds and base pairs of DNA.

Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

PubMed

Kirchmair, Johannes; Markt, Patrick; Distinto, Simona; Wolber, Gerhard; Langer, Thierry

2008-01-01

Within the last few years a considerable amount of evaluative studies has been published that investigate the performance of 3D virtual screening approaches. Thereby, in particular assessments of protein-ligand docking are facing remarkable interest in the scientific community. However, comparing virtual screening approaches is a non-trivial task. Several publications, especially in the field of molecular docking, suffer from shortcomings that are likely to affect the significance of the results considerably. These quality issues often arise from poor study design, biasing, by using improper or inexpressive enrichment descriptors, and from errors in interpretation of the data output. In this review we analyze recent literature evaluating 3D virtual screening methods, with focus on molecular docking. We highlight problematic issues and provide guidelines on how to improve the quality of computational studies. Since 3D virtual screening protocols are in general assessed by their ability to discriminate between active and inactive compounds, we summarize the impact of the composition and preparation of test sets on the outcome of evaluations. Moreover, we investigate the significance of both classic enrichment parameters and advanced descriptors for the performance of 3D virtual screening methods. Furthermore, we review the significance and suitability of RMSD as a measure for the accuracy of protein-ligand docking algorithms and of conformational space sub sampling algorithms.

Rational approach to identify newer caspase-1 inhibitors using pharmacophore based virtual screening, docking and molecular dynamic simulation studies.

PubMed

Patel, Shivani; Modi, Palmi; Chhabria, Mahesh

2018-05-01

Caspase-1 is a key endoprotease responsible for the post-translational processing of pro-inflammatory cytokines IL-1β, 18 & 33. Excessive secretion of IL-1β leads to numerous inflammatory and autoimmune diseases. Thus caspase-1 inhibition would be considered as an important therapeutic strategy for development of newer anti-inflammatory agents. Here we have employed an integrated virtual screening by combining pharmacophore mapping and docking to identify small molecules as caspase-1 inhibitors. The ligand based 3D pharmacophore model was generated having the essential structural features of (HBA, HY & RA) using a data set of 27 compounds. A validated pharmacophore hypothesis (Hypo 1) was used to screen ZINC and Minimaybridge chemical databases. The retrieved virtual hits were filtered by ADMET properties and molecular docking analysis. Subsequently, the cross-docking study was also carried out using crystal structure of caspase-1, 3, 7 and 8 to identify the key residual interaction for specific caspase-1 inhibition. Finally, the best mapped and top scored (ZINC00885612, ZINC72003647, BTB04175 and BTB04410) molecules were subjected to molecular dynamics simulation for accessing the dynamic structure of protein after ligand binding. This study identifies the most promising hits, which can be leads for the development of novel caspase-1 inhibitors as anti-inflammatory agents. Copyright © 2018 Elsevier Inc. All rights reserved.

Screening of synthetic and natural product databases: Identification of novel androgens and antiandrogens.

PubMed

Bobach, Claudia; Tennstedt, Stephanie; Palberg, Kristin; Denkert, Annika; Brandt, Wolfgang; de Meijere, Armin; Seliger, Barbara; Wessjohann, Ludger A

2015-01-27

The androgen receptor is an important pharmaceutical target for a variety of diseases. This paper presents an in silico/in vitro screening procedure to identify new androgen receptor ligands. The two-step virtual screening procedure uses a three-dimensional pharmacophore model and a docking/scoring routine. About 39,000 filtered compounds were docked with PLANTS and scored by Chemplp. Subsequent to virtual screening, 94 compounds, including 28 steroidal and 66 nonsteroidal compounds, were tested by an androgen receptor fluorescence polarization ligand displacement assay. As a result, 30 compounds were identified that show a relative binding affinity of more than 50% in comparison to 100 nM dihydrotestosterone and were classified as androgen receptor binders. For 11 androgen receptor binders of interest IC50 and Ki values were determined. The compound with the highest affinity exhibits a Ki value of 10.8 nM. Subsequent testing of the 11 compounds in a PC-3 and LNCaP multi readout proliferation assay provides insights into the potential mode of action. Further steroid receptor ligand displacement assays and docking studies on estrogen receptors α and β, glucocorticoid receptor, and progesterone receptor gave information about the specificity of the 11 most active compounds. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Search for β2 Adrenergic Receptor Ligands by Virtual Screening via Grid Computing and Investigation of Binding Modes by Docking and Molecular Dynamics Simulations

PubMed Central

Bai, Qifeng; Shao, Yonghua; Pan, Dabo; Zhang, Yang; Liu, Huanxiang; Yao, Xiaojun

2014-01-01

We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com. PMID:25229694

In Silico Screening for Inhibitors of P-Glycoprotein That Target the Nucleotide Binding Domains

PubMed Central

Brewer, Frances K.; Follit, Courtney A.; Vogel, Pia D.

2014-01-01

Multidrug resistances and the failure of chemotherapies are often caused by the expression or overexpression of ATP-binding cassette transporter proteins such as the multidrug resistance protein, P-glycoprotein (P-gp). P-gp is expressed in the plasma membrane of many cell types and protects cells from accumulation of toxins. P-gp uses ATP hydrolysis to catalyze the transport of a broad range of mostly hydrophobic compounds across the plasma membrane and out of the cell. During cancer chemotherapy, the administration of therapeutics often selects for cells which overexpress P-gp, thereby creating populations of cancer cells resistant to a variety of chemically unrelated chemotherapeutics. The present study describes extremely high-throughput, massively parallel in silico ligand docking studies aimed at identifying reversible inhibitors of ATP hydrolysis that target the nucleotide-binding domains of P-gp. We used a structural model of human P-gp that we obtained from molecular dynamics experiments as the protein target for ligand docking. We employed a novel approach of subtractive docking experiments that identified ligands that bound predominantly to the nucleotide-binding domains but not the drug-binding domains of P-gp. Four compounds were found that inhibit ATP hydrolysis by P-gp. Using electron spin resonance spectroscopy, we showed that at least three of these compounds affected nucleotide binding to the transporter. These studies represent a successful proof of principle demonstrating the potential of targeted approaches for identifying specific inhibitors of P-gp. PMID:25270578

Molecular interactions between fenoterol stereoisomers and derivatives and the β₂-adrenergic receptor binding site studied by docking and molecular dynamics simulations.

PubMed

Plazinska, Anita; Kolinski, Michal; Wainer, Irving W; Jozwiak, Krzysztof

2013-11-01

The β2 adrenergic receptor (β2-AR) has become a model system for studying the ligand recognition process and mechanism of the G protein coupled receptors activation. In the present study stereoisomers of fenoterol and some of its derivatives (N = 94 molecules) were used as molecular probes to identify differences in stereo-recognition interactions between β2-AR and structurally similar agonists. The present study aimed at determining the 3D molecular models of the fenoterol derivative-β2-AR complexes. Molecular models of β2-AR have been developed by using the crystal structure of the human β2-AR T4 lysozyme fusion protein with bound (S)-carazolol (PDB ID: 2RH1) and more recently reported structure of a nanobody-stabilized active state of the β2-AR with the bound full agonist BI-167107 (PDB ID: 3P0G). The docking procedure allowed us to study the similarities and differences in the recognition binding site(s) for tested ligands. The agonist molecules occupied the same binding region, between TM III, TM V, TM VI and TM VII. The residues identified by us during docking procedure (Ser203, Ser207, Asp113, Lys305, Asn312, Tyr308, Asp192) were experimentally indicated in functional and biophysical studies as being very important for the agonist-receptor interactions. Moreover, the additional space, an extension of the orthosteric pocket, was identified and described. Furthermore, the molecular dynamics simulations were used to study the molecular mechanism of interaction between ligands ((R,R')- and (S,S')-fenoterol) and β2-AR. Our research offers new insights into the ligand stereoselective interaction with one of the most important GPCR member. This study may also facilitate the design of improved selective medications, which can be used to treat, prevent and control heart failure symptoms.

Molecular docking and simulation studies of gustatory receptor of Aedes aegypti: A potent drug target to distract host-seeking behaviour in mosquitoes.

PubMed

Gupta, Krishna Kant; Sethi, Guneswar; Jayaraman, Manikandan

2016-01-01

It is well reported that exhaled CO 2 and skin odour from human being assist female mosquitoes to locate human host. Basically, the receptors for this activity are expressed in cpA neurons. In both Aedes aegypti and Anopheles gambiae, this CO 2-sensitive olfactory neuron detects myriad number of chemicals present in human skin. Therefore, manipulation of gustatory receptors housing these neurons may serve as important targets for behavioural intervention. The study was aimed towards virtual screening of small molecules in the analyzed conserved active site residues of gustatory receptor and molecular dynamics simulation study of optimum protein-ligand complex to identify a suitable lead molecule for distracting host-seeking behaviour of mosquitoes. The conserved residue analysis of gustatory receptor (GR) of Ae. aegypti and An. gambiae was performed. The structure of GR protein from Ae. aegypti was modeled and validated, and then molecular docking was performed to screen 2903 small molecules against the predicted active residues of GR. Further, simulation studies were also carried out to prove protein-ligand stability. The glutamine 154 residue of GR was found to be highly conserved in Ae. aegypti and An. gambiae. Docking results indicated that the dodecanoic acid, 1,2,3-propanetriyl ester (dynasan 112) was interacting with this residue, as it showed better LibDock score than previously reported ethyl acetate used as mosquito repellant. Simulation studies indicated the structural instability of GR protein in docked form with dynasan 112 suggesting its involvement in structural changes. Based on the interaction energies and stability, this compound has been proposed to be used in mosquitoes' repellant. A novel effective odorant acting as inhibitor of GR is proposed based on its stability, docking score, interactions and RMSD, considering ethyl pyruvate as a standard inhibitor. Host preference and host-seeking ability of mosquito vectors play key roles in disease transmission, a clear understanding of these aspects is essential for preventing the spread of the disease.

Coumarin derivatives bearing benzoheterocycle moiety: synthesis, cholinesterase inhibitory, and docking simulation study

PubMed Central

Hirbod, Kimia; Jalili-baleh, Leili; Nadri, Hamid; ebrahimi, Seyed esmaeil Sadat; Moradi, Alireza; Pakseresht, Bahar; Foroumadi, Alireza; Shafiee, Abbas; Khoobi, Mehdi

2017-01-01

Objective(s): To investigate the efficiency of a novel series of coumarin derivatives bearing benzoheterocycle moiety as novel cholinesterase inhibitors. Materials and Methods: Different 7-hydroxycoumarin derivatives were synthesized via Pechmann or Knoevenagel condensation and conjugated to different benzoheterocycle (8-hydroxyquinoline, 2-mercaptobenzoxazole or 2-mercaptobenzimidazole) using dibromoalkanes 3a-m: Final compounds were evaluated against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) by Ellman’s method. Kinetic study of AChE inhibition and ligand-protein docking simulation were also carried out for the most potent compound 3b. Results: Some of the compounds revealed potent and selective activity against AChE. Compound 3b containing the quinoline group showed the best activity with an IC50 value of 8.80 μM against AChE. Kinetic study of AChE inhibition revealed the mixed-type inhibition of the enzyme by compound 3b. Ligand-protein docking simulation also showed that the flexibility of the hydrophobic five carbons linker allows the quinoline ring to form π-π interaction with Trp279 in the PAS. Conclusion: We suggest these synthesized compounds could become potential leads for AChE inhibition and prevention of AD symptoms. PMID:28868119

In silico insight into voltage-gated sodium channel 1.7 inhibition for anti-pain drug discovery.

PubMed

Wang, Mingxing; Li, Wei; Wang, Ying; Song, Yongbo; Wang, Jian; Cheng, Maosheng

2018-05-18

Studies on human genetics have implicated the voltage-gated sodium channel Nav1.7 as an appealing target for the treatment of pain. In this study, we put forward a ligand-based pharmacophore for the first time, which was generated by a set of multiple chemical scaffolds including sulfonamide and non-sulfonamide derivatives and consisted of four chemical features: an aromatic ring, a hydrophobic group and two hydrogen acceptors. The active cavity was divided into three regions according to the properties of the amino acids surrounded and was used for the docking of 16 known active inhibitors. Four accurate docking methods were employed to analyze the ligand-protein interactions in our molecular simulation study. Combining pharmacophore model with docking results, an interaction model was obtained with four features that were consistent with one another, which was more powerful in illuminating the binding site. The research elucidated a valuable relationship between structure and activity, at the same time it proposed an accurate binding model that was instructive in the development of novel and potent Nav1.7 inhibitors in the future. Copyright © 2018 Elsevier Inc. All rights reserved.

Ligand and receptor dynamics contribute to the mechanism of graded PPARγ agonism

PubMed Central

Hughes, Travis S.; Chalmers, Michael J.; Novick, Scott; Kuruvilla, Dana S.; Chang, Mi Ra; Kamenecka, Theodore M.; Rance, Mark; Johnson, Bruce A.; Burris, Thomas P.; Griffin, Patrick R.; Kojetin, Douglas J.

2011-01-01

SUMMARY Ligand binding to proteins is not a static process, but rather involves a number of complex dynamic transitions. A flexible ligand can change conformation upon binding its target. The conformation and dynamics of a protein can change to facilitate ligand binding. The conformation of the ligand, however, is generally presumed to have one primary binding mode, shifting the protein conformational ensemble from one state to another. We report solution NMR studies that reveal peroxisome proliferator-activated receptor γ (PPARγ) modulators can sample multiple binding modes manifesting in multiple receptor conformations in slow conformational exchange. Our NMR, hydrogen/deuterium exchange and docking studies reveal that ligand-induced receptor stabilization and binding mode occupancy correlate with the graded agonist response of the ligand. Our results suggest that ligand and receptor dynamics affect the graded transcriptional output of PPARγ modulators. PMID:22244763

Identification of small molecular ligands as potent inhibitors of fatty acid metabolism in Mycobacterium tuberculosis

NASA Astrophysics Data System (ADS)

Malikanti, Ramesh; Vadija, Rajender; Veeravarapu, Hymavathi; Mustyala, Kiran Kumar; Malkhed, Vasavi; Vuruputuri, Uma

2017-12-01

Tuberculosis (Tb) is one of the major health challenges for the global scientific community. The 3-hydroxy butyryl-CoA dehydrogenase (Fad B2) protein belongs to 3-hydroxyl acetyl-CoA dehydrogenase family, which plays a key role in the fatty acid metabolism and β-oxidation in the cell membrane of Mycobacterium tuberculosis (Mtb). In the present study the Fad B2 protein is targeted for the identification of potential drug candidates for tuberculosis. The 3D model of the target protein Fad B2, was generated using homology modeling approach and was validated. The plausible binding site of the Fad B2 protein was identified from computational binding pocket prediction tools, which ranges from ASN120 to VAL150 amino acid residues. Virtual screening was carried out with the databases, Ligand box UOS and hit definder, at the binding site region. 133 docked complex structures were generated as an output. The identified ligands show good glide scores and glide energies. All the ligand molecules contain benzyl amine pharmacophore in common, which show specific and selective binding interactions with the SER122 and ASN146 residues of the Fad B2 protein. The ADME properties of all the ligand molecules were observed to be within the acceptable range. It is suggested from the result of the present study that the docked molecular structures with a benzyl amine pharmacophore act as potential ligands for Fad B2 protein binding and as leads in Tb drug discovery.

Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study

NASA Astrophysics Data System (ADS)

Réau, Manon; Langenfeld, Florent; Zagury, Jean-François; Montes, Matthieu

2018-01-01

The Drug Design Data Resource (D3R) Grand Challenges are blind contests organized to assess the state-of-the-art methods accuracy in predicting binding modes and relative binding free energies of experimentally validated ligands for a given target. The second stage of the D3R Grand Challenge 2 (GC2) was focused on ranking 102 compounds according to their predicted affinity for Farnesoid X Receptor. In this task, our workflow was ranked 5th out of the 77 submissions in the structure-based category. Our strategy consisted in (1) a combination of molecular docking using AutoDock 4.2 and manual edition of available structures for binding poses generation using SeeSAR, (2) the use of HYDE scoring for pose selection, and (3) a hierarchical ranking using HYDE and MM/GBSA. In this report, we detail our pose generation and ligands ranking protocols and provide guidelines to be used in a prospective computer aided drug design program.

Computational analysis for selectivity of histone deacetylase inhibitor by replica-exchange umbrella sampling molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Tsukamoto, Shuichiro; Sakae, Yoshitake; Itoh, Yukihiro; Suzuki, Takayoshi; Okamoto, Yuko

2018-03-01

We performed protein-ligand docking simulations with a ligand T247, which has been reported as a selective inhibitor of a histone deacetylase HDAC3, by the replica-exchange umbrella sampling method in order to estimate the free energy profiles along ligand docking pathways of HDAC3-T247 and HDAC2-T247 systems. The simulation results showed that the docked state of the HDAC3-T247 system is more stable than that of the HDAC2-T247 system although the amino-acid sequences and structures of HDAC3 and HDAC2 are very similar. By comparing structures obtained from the simulations of both systems, we found the difference between structures of hydrophobic residues at the entrance of the catalytic site. Moreover, we performed conventional molecular dynamics simulations of HDAC3 and HDAC2 systems without T247, and the results also showed the same difference of the hydrophobic structures. Therefore, we consider that this hydrophobic structure contributes to the stabilization of the docked state of the HDAC3-T247 system. Furthermore, we show that Tyr209, which is one of the hydrophobic residues in HDAC2, plays a key role in the instability from the simulation results of a mutated-HDAC2 system.

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

Newer mixed ligand Schiff base complexes from aquo-N-(2‧-hydroxy acetophenone) glycinatocopper(II) as synthon: DFT, antimicrobial activity and molecular docking study

NASA Astrophysics Data System (ADS)

Pramanik, Harun A. R.; Das, Dharitri; Paul, Pradip C.; Mondal, Paritosh; Bhattacharjee, Chira R.

2014-02-01

Synthesis of a series of newer mixed ligand copper(II) complexes of aminoacid Schiff base of the type [CuL(X)] (L = N-(2‧-hydroxy acetophenone) glycinate, X = imidazole (im) 2, benzimidazole (benz) 3, pyridine (py) 4, hydrazine (hz) 5,8-hydroxyquinoline (8-hq) 6, pyrrolidine (pyrr) 7, piperidine (pip) 8, and nicotinamide (nic) 9) have been accomplished from the interaction of an aquated Schiff base complex, [CuL(H2O)]·H2O, 1 with some selected neutral nitrogen-donor ligands. The copper(II) Schiff base complex, [CuL(H2O)]·H2O, L = N-(2‧-hydroxy acetophenone) glycinate was synthesized from the reaction of glycine and 2‧ hydroxy acetophenone and copper(II) acetate. The compounds were characterised by elemental analysis, spectral, magnetic and thermal studies. The density functional theory calculations were performed using LANL2DZ and 6-311 G(d, p) basis sets with B3LYP correlation functional to ascertain the stable electronic structure, HOMO-LUMO energy gap, chemical hardness and dipole moment of the mixed ligand complexes. A distorted square planar geometry has been conjectured for the complexes. Antibacterial activities of the ligand and its metal complexes have been tested against selected gram-positive and gram-negative strains and correlated with computational docking scores.

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

Task-parallel message passing interface implementation of Autodock4 for docking of very large databases of compounds using high-performance super-computers.

PubMed

Collignon, Barbara; Schulz, Roland; Smith, Jeremy C; Baudry, Jerome

2011-04-30

A message passing interface (MPI)-based implementation (Autodock4.lga.MPI) of the grid-based docking program Autodock4 has been developed to allow simultaneous and independent docking of multiple compounds on up to thousands of central processing units (CPUs) using the Lamarkian genetic algorithm. The MPI version reads a single binary file containing precalculated grids that represent the protein-ligand interactions, i.e., van der Waals, electrostatic, and desolvation potentials, and needs only two input parameter files for the entire docking run. In comparison, the serial version of Autodock4 reads ASCII grid files and requires one parameter file per compound. The modifications performed result in significantly reduced input/output activity compared with the serial version. Autodock4.lga.MPI scales up to 8192 CPUs with a maximal overhead of 16.3%, of which two thirds is due to input/output operations and one third originates from MPI operations. The optimal docking strategy, which minimizes docking CPU time without lowering the quality of the database enrichments, comprises the docking of ligands preordered from the most to the least flexible and the assignment of the number of energy evaluations as a function of the number of rotatable bounds. In 24 h, on 8192 high-performance computing CPUs, the present MPI version would allow docking to a rigid protein of about 300K small flexible compounds or 11 million rigid compounds.

Power transformations improve interpolation of grids for molecular mechanics interaction energies.

PubMed

Minh, David D L

2018-02-18

A common strategy for speeding up molecular docking calculations is to precompute nonbonded interaction energies between a receptor molecule and a set of three-dimensional grids. The grids are then interpolated to compute energies for ligand atoms in many different binding poses. Here, I evaluate a smoothing strategy of taking a power transformation of grid point energies and inverse transformation of the result from trilinear interpolation. For molecular docking poses from 85 protein-ligand complexes, this smoothing procedure leads to significant accuracy improvements, including an approximately twofold reduction in the root mean square error at a grid spacing of 0.4 Å and retaining the ability to rank docking poses even at a grid spacing of 0.7 Å. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Molecular Docking, Molecular Dynamics, and Structure–Activity Relationship Explorations of 14-Oxygenated N-Methylmorphinan-6-ones as Potent μ-Opioid Receptor Agonists

PubMed Central

2017-01-01

Among opioids, morphinans are of major importance as the most effective analgesic drugs acting primarily via μ-opioid receptor (μ-OR) activation. Our long-standing efforts in the field of opioid analgesics from the class of morphinans led to N-methylmorphinan-6-ones differently substituted at positions 5 and 14 as μ-OR agonists inducing potent analgesia and fewer undesirable effects. Herein we present the first thorough molecular modeling study and structure–activity relationship (SAR) explorations aided by docking and molecular dynamics (MD) simulations of 14-oxygenated N-methylmorphinan-6-ones to gain insights into their mode of binding to the μ-OR and interaction mechanisms. The structure of activated μ-OR provides an essential model for how ligand/μ-OR binding is encoded within small chemical differences in otherwise structurally similar morphinans. We reveal important molecular interactions that these μ-agonists share and distinguish them. The molecular docking outcomes indicate the crucial role of the relative orientation of the ligand in the μ-OR binding site, influencing the propensity of critical non-covalent interactions that are required to facilitate ligand/μ-OR interactions and receptor activation. The MD simulations point out minor differences in the tendency to form hydrogen bonds by the 4,5α-epoxy group, along with the tendency to affect the 3–7 lock switch. The emerged SARs reveal the subtle interplay between the substituents at positions 5 and 14 in the morphinan scaffold by enabling the identification of key structural elements that determine the distinct pharmacological profiles. This study provides a significant structural basis for understanding ligand binding and μ-OR activation by the 14-oxygenated N-methylmorphinan-6-ones, which should be useful for guiding drug design. PMID:28125215

Molecular Docking, Molecular Dynamics, and Structure-Activity Relationship Explorations of 14-Oxygenated N-Methylmorphinan-6-ones as Potent μ-Opioid Receptor Agonists.

PubMed

Noha, Stefan M; Schmidhammer, Helmut; Spetea, Mariana

2017-06-21

Among opioids, morphinans are of major importance as the most effective analgesic drugs acting primarily via μ-opioid receptor (μ-OR) activation. Our long-standing efforts in the field of opioid analgesics from the class of morphinans led to N-methylmorphinan-6-ones differently substituted at positions 5 and 14 as μ-OR agonists inducing potent analgesia and fewer undesirable effects. Herein we present the first thorough molecular modeling study and structure-activity relationship (SAR) explorations aided by docking and molecular dynamics (MD) simulations of 14-oxygenated N-methylmorphinan-6-ones to gain insights into their mode of binding to the μ-OR and interaction mechanisms. The structure of activated μ-OR provides an essential model for how ligand/μ-OR binding is encoded within small chemical differences in otherwise structurally similar morphinans. We reveal important molecular interactions that these μ-agonists share and distinguish them. The molecular docking outcomes indicate the crucial role of the relative orientation of the ligand in the μ-OR binding site, influencing the propensity of critical non-covalent interactions that are required to facilitate ligand/μ-OR interactions and receptor activation. The MD simulations point out minor differences in the tendency to form hydrogen bonds by the 4,5α-epoxy group, along with the tendency to affect the 3-7 lock switch. The emerged SARs reveal the subtle interplay between the substituents at positions 5 and 14 in the morphinan scaffold by enabling the identification of key structural elements that determine the distinct pharmacological profiles. This study provides a significant structural basis for understanding ligand binding and μ-OR activation by the 14-oxygenated N-methylmorphinan-6-ones, which should be useful for guiding drug design.

Insights into the structural basis of N2 and O6 substituted guanine derivatives as cyclin-dependent kinase 2 (CDK2) inhibitors: prediction of the binding modes and potency of the inhibitors by docking and ONIOM calculations.

PubMed

Alzate-Morales, Jans H; Caballero, Julio; Vergara Jague, Ariela; González Nilo, Fernando D

2009-04-01

N2 and O6 substituted guanine derivatives are well-known as potent and selective CDK2 inhibitors. The ability of molecular docking using the program AutoDock3 and the hybrid method ONIOM, to obtain some quantum chemical descriptors with the aim to successfully rank these inhibitors, was assessed. The quantum chemical descriptors were used to explain the affinity, of the series studied, by a model of the CDK2 binding site. The initial structures were obtained from docking studies and the ONIOM method was applied with only a single point energy calculation on the protein-ligand structure. We obtained a good correlation model between the ONIOM derived quantum chemical descriptor "H-bond interaction energy" and the experimental biological activity, with a correlation coefficient value of R = 0.80 for 75 compounds. To the best of our knowledge, this is the first time that both methodologies are used in conjunction in order to obtain a correlation model. The model suggests that electrostatic interactions are the principal driving force in this protein-ligand interaction. Overall, the approach was successful for the cases considered, and it suggests that could be useful for the design of inhibitors in the lead optimization phase of drug discovery.

Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

PubMed

de Ávila, Maurício Boff; Xavier, Mariana Morrone; Pintro, Val Oliveira; de Azevedo, Walter Filgueira

2017-12-09

Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) for which half-maximal inhibitory concentration (IC 50 ) data is available. Polynomial scoring functions were built using as explanatory variables the energy terms present in the MolDock and PLANTS scoring functions. Prediction performance was tested and the supervised machine learning models showed improvement in the prediction power, when compared with PLANTS and MolDock scoring functions. In addition, the machine-learning model was applied to predict binding affinity of CDK2, which showed a better performance when compared with AutoDock4, AutoDock Vina, MolDock, and PLANTS scores. Copyright © 2017 Elsevier Inc. All rights reserved.

7TM X-ray structures for class C GPCRs as new drug-discovery tools. 1. mGluR5.

PubMed

Topiol, Sid; Sabio, Michael

2016-01-15

We illustrate, with a focus on mGluR5, how the recently published, first X-ray structures of mGluR 7TM domains, specifically those of mGluR1 and mGluR5 complexed with negative allosteric modulators (NAMs), will begin to influence ligand- (e.g., drug- or sweetener-) discovery efforts involving class C GPCRs. With an extensive docking study allowing full ligand flexibility and full side chain flexibility of all residues in the ligand-binding cavity, we have predicted and analyzed the binding modes of a variety of structurally diverse mGluR5 NAM ligands, showing how the X-ray structures serve to effectively rationalize each ligand's binding characteristics. We demonstrated that the features that are inherent in our earlier overlay model are preserved in the protein structure-based docking models. We identified structurally diverse compounds, which potentially act as mGluR NAMs, and revealed binding-site differences by performing high-throughput docking using a database of approximately six million structures of commercially available compounds and the mGluR1 and mGluR5 X-ray structures. By comparing the 7TM domains of the mGluR5 and mGluR1 X-rays structures, we identified selectivity factors within group I of the mGluRs. Similarly, using homology models that we built for mGluR2 and mGluR4, we have identified the factors leading to the selectivity between group I and groups II and III for ligands occupying the deepest portion of the mGluR5 binding cavity. Finally, we have proposed a structure-based explanation of the pharmacological switching within a set of positive allosteric modulators (PAMs) and their corresponding, very close NAM analogs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Understanding the molecular differential recognition of muramyl peptide ligands by LRR domains of human NOD receptors.

PubMed

Vijayrajratnam, Sukhithasri; Pushkaran, Anju Choorakottayil; Balakrishnan, Aathira; Vasudevan, Anil Kumar; Biswas, Raja; Mohan, Chethampadi Gopi

2017-07-27

Human nucleotide-binding oligomerization domain proteins, hNOD1 and hNOD2, are host intracellular receptors with C-terminal leucine-rich repeat (LRR) domains, which recognize specific bacterial peptidoglycan (PG) fragments as their ligands. The specificity of this recognition is dependent on the third amino acid of the stem peptide of the PG ligand, which is usually meso -diaminopimelic acid ( meso DAP) or l-lysine (l-Lys). Since the LRR domains of hNOD receptors had been experimentally shown to confer the PG ligand-sensing specificity, we developed three-dimensional structures of hNOD1-LRR and the hNOD2-LRR to understand the mechanism of differential recognition of muramyl peptide ligands by hNOD receptors. The hNOD1-LRR and hNOD2-LRR receptor models exhibited right-handed curved solenoid shape. The hot-spot residues experimentally proved to be critical for ligand recognition were located in the concavity of the NOD-LRR and formed the recognition site. Our molecular docking analyses and molecular electrostatic potential mapping studies explain the activation of hNOD-LRRs, in response to effective molecular interactions of PG ligands at the recognition site; and conversely, the inability of certain PG ligands to activate hNOD-LRRs, by deviations from the recognition site. Based on molecular docking studies using PG ligands, we propose few residues - G825, D826 and N850 in hNOD1-LRR and L904, G905, W931, L932 and S933 in hNOD2-LRR, evolutionarily conserved across different host species, which may play a major role in ligand recognition. Thus, our integrated experimental and computational approach elucidates the molecular basis underlying the differential recognition of PG ligands by hNOD receptors. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands

ERIC Educational Resources Information Center

King, Matthew D.; Phillips, Paul; Turner, Matthew W.; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M.

2016-01-01

Computational molecular docking is a fast and effective "in silico" method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The…

Molecular evaluation of herbal compounds as potent inhibitors of acetylcholinesterase for the treatment of Alzheimer's disease.

PubMed

Chen, Yan-Xiu; Li, Guan-Zeng; Zhang, Bin; Xia, Zhang-Yong; Zhang, Mei

2016-07-01

Alzheimer's disease (AD) is a progressive disease and the predominant cause of dementia. Common symptoms include short-term memory loss, and confusion with time and place. Individuals with AD depend on their caregivers for assistance, and may pose a burden to them. The acetylcholinesterase (AChE) enzyme is a key target in AD and inhibition of this enzyme may be a promising strategy in the drug discovery process. In the present study, an inhibitory assay was carried out against AChE using total alkaloidal plants and herbal extracts commonly available in vegetable markets. Subsequently, molecular docking simulation analyses of the bioactive compounds present in the plants were conducted, as well as a protein‑ligand interaction analysis. The stability of the docked protein‑ligand complex was assessed by 20 ns molecular dynamics simulation. The inhibitory assay demonstrated that Uncaria rhynchophylla and Portulaca oleracea were able to inhibit AChE. In addition, molecular docking simulation analyses indicated that catechin present in Uncaria rhynchophylla, and dopamine and norepinephrine present in Portulaca oleracea, had the best docking scores and interaction energy. In conclusion, catechin in Uncaria rhynchophylla, and dopamine and norepinephrine in Portulaca oleracea may be used to treat AD.

Docking and QSAR comparative studies of polycyclic aromatic hydrocarbons and other procarcinogen interactions with cytochromes P450 1A1 and 1B1.

PubMed

Gonzalez, J; Marchand-Geneste, N; Giraudel, J L; Shimada, T

2012-01-01

To obtain chemical clues on the process of bioactivation by cytochromes P450 1A1 and 1B1, some QSAR studies were carried out based on cellular experiments of the metabolic activation of polycyclic aromatic hydrocarbons and heterocyclic aromatic compounds by those enzymes. Firstly, the 3D structures of cytochromes 1A1 and 1B1 were built using homology modelling with a cytochrome 1A2 template. Using these structures, 32 ligands including heterocyclic aromatic compounds, polycyclic aromatic hydrocarbons and corresponding diols, were docked with LigandFit and CDOCKER algorithms. Binding mode analysis highlighted the importance of hydrophobic interactions and the hydrogen bonding network between cytochrome amino acids and docked molecules. Finally, for each enzyme, multilinear regression and artificial neural network QSAR models were developed and compared. These statistical models highlighted the importance of electronic, structural and energetic descriptors in metabolic activation process, and could be used for virtual screening of ligand databases. In the case of P450 1A1, the best model was obtained with artificial neural network analysis and gave an r (2) of 0.66 and an external prediction [Formula: see text] of 0.73. Concerning P450 1B1, artificial neural network analysis gave a much more robust model, associated with an r (2) value of 0.73 and an external prediction [Formula: see text] of 0.59.

DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites

PubMed Central

Gowthaman, Ragul; Lyskov, Sergey; Karanicolas, John

2015-01-01

Over the past decade, protein-protein interactions have emerged as attractive but challenging targets for therapeutic intervention using small molecules. Due to the relatively flat surfaces that typify protein interaction sites, modern virtual screening tools developed for optimal performance against “traditional” protein targets perform less well when applied instead at protein interaction sites. Previously, we described a docking method specifically catered to the shallow binding modes characteristic of small-molecule inhibitors of protein interaction sites. This method, called DARC (Docking Approach using Ray Casting), operates by comparing the topography of the protein surface when “viewed” from a vantage point inside the protein against the topography of a bound ligand when “viewed” from the same vantage point. Here, we present five key enhancements to DARC. First, we use multiple vantage points to more accurately determine protein-ligand surface complementarity. Second, we describe a new scheme for rapidly determining optimal weights in the DARC scoring function. Third, we incorporate sampling of ligand conformers “on-the-fly” during docking. Fourth, we move beyond simple shape complementarity and introduce a term in the scoring function to capture electrostatic complementarity. Finally, we adjust the control flow in our GPU implementation of DARC to achieve greater speedup of these calculations. At each step of this study, we evaluate the performance of DARC in a “pose recapitulation” experiment: predicting the binding mode of 25 inhibitors each solved in complex with its distinct target protein (a protein interaction site). Whereas the previous version of DARC docked only one of these inhibitors to within 2 Å RMSD of its position in the crystal structure, the newer version achieves this level of accuracy for 12 of the 25 complexes, corresponding to a statistically significant performance improvement (p < 0.001). Collectively then, we find that the five enhancements described here – which together make up DARC 2.0 – lead to dramatically improved speed and performance relative to the original DARC method. PMID:26181386

Structure-based drug design: docking and scoring.

PubMed

Kroemer, Romano T

2007-08-01

This review gives an introduction into ligand - receptor docking and illustrates the basic underlying concepts. An overview of different approaches and algorithms is provided. Although the application of docking and scoring has led to some remarkable successes, there are still some major challenges ahead, which are outlined here as well. Approaches to address some of these challenges and the latest developments in the area are presented. Some aspects of the assessment of docking program performance are discussed. A number of successful applications of structure-based virtual screening are described.

New modulated design, docking and synthesis of carbohydrate-conjugate heterobimetallic CuII-SnIV complex as potential topoisomerase II inhibitor: in vitro DNA binding, cleavage and cytotoxicity against human cancer cell lines.

PubMed

Tabassum, Sartaj; Afzal, Mohd; Arjmand, Farukh

2014-03-03

New carbohydrate-conjugate heterobimetallic complexes [C₂₂H₅₀N₆O₁₃CuSnCl₂] (3) and [C₂₂H₅₈N₆O₁₇NiSnCl₂] (4) were synthesized from their monometallic analogs [C₂₂H₅₂N₆O₁₃Cu] (1) and [C₂₂H₆₀N₆O₁₇Ni] (2) containing N-glycoside ligand (L). In vitro DNA binding studies of L and complexes (1-4) with CT DNA were carried out by employing various biophysical and molecular docking techniques which revealed that heterobimetallic complex 3 strongly binds to DNA in comparison to 4, monometallic complexes (1 and 2) and the free ligand. Complex 3 cleaves pBR322 DNA via hydrolytic pathway (confirmed by T4 DNA ligase assay) and inhibited Topo-II activity in a dose-dependent manner. Furthermore, complex 3 was docked into the ATPase domain of human-Topo-II in order to probe the possible mechanism of inhibition. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Modeling, docking and dynamics simulations of a non-specific lipid transfer protein from Peganum harmala L.

PubMed

Shi, Zheng; Wang, Zi-jie; Xu, Huai-long; Tian, Yang; Li, Xin; Bao, Jin-ku; Sun, Su-rong; Yue, Bi-song

2013-12-01

Non-specific lipid transfer proteins (ns-LTPs), ubiquitously found in various types of plants, have been well-known to transfer amphiphilic lipids and promote the lipid exchange between mitochondria and microbody. In this study, an in silico analysis was proposed to study ns-LTP in Peganum harmala L., which may belong to ns-LTP1 family, aiming at constructing its three-dimensional structure. Moreover, we adopted MEGA to analyze ns-LTPs and other species phylogenetically, which brought out an initial sequence alignment of ns-LTPs. In addition, we used molecular docking and molecular dynamics simulations to further investigate the affinities and stabilities of ns-LTP with several ligands complexes. Taken together, our results about ns-LTPs and their ligand-binding activities can provide a better understanding of the lipid-protein interactions, indicating some future applications of ns-LTP-mediated transport. Copyright © 2013 Elsevier Ltd. All rights reserved.

Molecular docking and molecular dynamics studies on the interactions of hydroxylated polybrominated diphenyl ethers to estrogen receptor alpha.

PubMed

Lu, Qun; Cai, Zhengqing; Fu, Jie; Luo, Siyi; Liu, Chunsheng; Li, Xiaolin; Zhao, Dongye

2014-03-01

Environmental estrogens have attracted great concerns. Recent studies have indicated that some hydroxylated polybrominated diphenyl ethers (HO-PBDEs) can interact with estrogen receptor (ER), and exhibit estrogenic activity. However, interactions between HO-PBDEs and ER are not well understood. In this work, molecular docking and molecular dynamics (MD) simulations were performed to characterize interactions of two HO-PBDEs (4'-HO-BDE30 and 4'-HO-BDE121) with ERα. Surflex-Dock was employed to reveal the probable binding conformations of the compounds at the active site of ERα; MD simulation was used to determine the detailed binding process. The driving forces of the binding between HO-PBDEs and ERα were van der Waals and electrostatic interactions. The decomposition of the binding free energy indicated that the hydrogen bonds between the residues Glu353, Gly521 and ligands were crucial for anchoring the ligands into the active site of ERα and stabilizing their conformations. The results showed that different interaction modes and different specific interactions with some residues were responsible for the different estrogenic activities of the two HO-PBDEs. Copyright © 2013 Elsevier Inc. All rights reserved.

In-Silico Analysis of Amotosalen Hydrochloride Binding to CD-61 of Platelets.

PubMed

Chaudhary, Hammad Tufail

2016-11-01

To determine the docking of Amotosalen hydrochloride (AH) at CD-61 of platelets, and to suggest the cause of bleeding in AH treated platelets transfusion. Descriptive study. Medical College, Taif University, Taif, Saudi Arabia, from October 2014 to May 2015. The study was carried out in-silico. PDB (protein data bank) code of Tirofiban bound to CD-61 was 2vdm. CD-61 was docked with Tirofiban using online docking tools, i.e. Patchdock and Firedock. Then, Amotosalen hydrochloride and CD-61 were also docked. Best docking poses to active sites of 2vdm were found. Ligplot of interactions of ligands and CD-61 were obtained. Then comparison of hydrogen bonds, hydrogen bond lengths, and hydrophobic bonds of 2vdm molecule and best poses of docking results were done. Patchdock and Firedock results of best poses were also analysed using SPSS version 16. More amino acids were involved in hydrogen and hydrophobic bonds in Patchdock and Firedock docking of Amotosalen hydrochloride with CD-61 than Patchdock and Firedock docking of CD-61 with Tirofiban. The binding energy was more in latter than former. Amotosalen hydrochloride binds to the active site of CD-61 with weaker binding force. Haemorrhage seen in Amotosalen hydrochloride-treated platelets might be due to binding of Amotosalen hydrochloride to CD-61.

Spectrophotometric studies on the interaction between (-)-epigallocatechin gallate and lysozyme

NASA Astrophysics Data System (ADS)

Ghosh, Kalyan Sundar; Sahoo, Bijaya Ketan; Dasgupta, Swagata

2008-02-01

Various reported antibacterial activities of (-)-epigallocatechin-3-gallate (EGCG), the major polyphenol of green tea prompted us to study its binding with lysozyme. This has been investigated by fluorescence, circular dichroism (CD) and protein-ligand docking. The binding parameters were determined using a modified Stern-Volmer equation. The thermodynamic parameters are indicative of an initial hydrophobic association. The complex is, however, held together predominantly by van der Waals interactions and hydrogen bonding. CD studies do not indicate any significant changes in the secondary structure of lysozyme. Docking studies revealed that specific interactions are observed with residues Trp 62 and Trp 63.

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2018-01-01

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

PubMed

Zhang, Changsheng; Tang, Bo; Wang, Qian; Lai, Luhua

2014-10-01

Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we used a protein-protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all-to-all protein-protein docking run on a large dataset was performed. The three-dimensional rigid docking program SDOCK was used to examine protein-protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z-score, and convergency of the low-score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all-to-all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor-α (TNFα), which is a well-known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top-ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein-protein docking for the discovery of novel binding proteins for specific protein targets. © 2014 Wiley Periodicals, Inc.

In silico screening for inhibitors of p-glycoprotein that target the nucleotide binding domains.

PubMed

Brewer, Frances K; Follit, Courtney A; Vogel, Pia D; Wise, John G

2014-12-01

Multidrug resistances and the failure of chemotherapies are often caused by the expression or overexpression of ATP-binding cassette transporter proteins such as the multidrug resistance protein, P-glycoprotein (P-gp). P-gp is expressed in the plasma membrane of many cell types and protects cells from accumulation of toxins. P-gp uses ATP hydrolysis to catalyze the transport of a broad range of mostly hydrophobic compounds across the plasma membrane and out of the cell. During cancer chemotherapy, the administration of therapeutics often selects for cells which overexpress P-gp, thereby creating populations of cancer cells resistant to a variety of chemically unrelated chemotherapeutics. The present study describes extremely high-throughput, massively parallel in silico ligand docking studies aimed at identifying reversible inhibitors of ATP hydrolysis that target the nucleotide-binding domains of P-gp. We used a structural model of human P-gp that we obtained from molecular dynamics experiments as the protein target for ligand docking. We employed a novel approach of subtractive docking experiments that identified ligands that bound predominantly to the nucleotide-binding domains but not the drug-binding domains of P-gp. Four compounds were found that inhibit ATP hydrolysis by P-gp. Using electron spin resonance spectroscopy, we showed that at least three of these compounds affected nucleotide binding to the transporter. These studies represent a successful proof of principle demonstrating the potential of targeted approaches for identifying specific inhibitors of P-gp. Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics.

In silico study of carvone derivatives as potential neuraminidase inhibitors.

PubMed

Jusoh, Noorakmar; Zainal, Hasanuddin; Abdul Hamid, Azzmer Azzar; Bunnori, Noraslinda M; Abd Halim, Khairul Bariyyah; Abd Hamid, Shafida

2018-03-15

Recent outbreaks of highly pathogenic influenza strains have highlighted the need to develop new anti-influenza drugs. Here, we report an in silico study of carvone derivatives to analyze their binding modes with neuraminidase (NA) active sites. Two proposed carvone analogues, CV(A) and CV(B), with 36 designed ligands were predicted to inhibit NA (PDB ID: 3TI6) using molecular docking. The design is based on structural resemblance with the commercial inhibitor, oseltamivir (OTV), ligand polarity, and amino acid residues in the NA active sites. Docking simulations revealed that ligand A18 has the lowest energy binding (∆G bind ) value of -8.30 kcal mol -1 , comparable to OTV with ∆G bind of -8.72 kcal mol -1 . A18 formed seven hydrogen bonds (H-bonds) at residues Arg292, Arg371, Asp151, Trp178, Glu227, and Tyr406, while eight H-bonds were formed by OTV with amino acids Arg118, Arg292, Arg371, Glu119, Asp151, and Arg152. Molecular dynamics (MD) simulation was conducted to compare the stability between ligand A18 and OTV with NA. Our simulation study showed that the A18-NA complex is as stable as the OTV-NA complex during the MD simulation of 50 ns through the analysis of RMSD, RMSF, total energy, hydrogen bonding, and MM/PBSA free energy calculations.

Structure-Based Predictions of Activity Cliffs

PubMed Central

Husby, Jarmila; Bottegoni, Giovanni; Kufareva, Irina; Abagyan, Ruben; Cavalli, Andrea

2015-01-01

In drug discovery, it is generally accepted that neighboring molecules in a given descriptors' space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as ‘activity cliffs’. In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming co-crystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods. PMID:25918827

First report on 3D-QSAR and molecular dynamics based docking studies of GCPII inhibitors for targeted drug delivery applications

NASA Astrophysics Data System (ADS)

Pandit, Amit; Sengupta, Sagnik; Krishnan, Mena Asha; Reddy, Ramesh B.; Sharma, Rajesh; Venkatesh, Chelvam

2018-05-01

Prostate Specific Membrane Antigen (PSMA) or Glutamate carboxypeptidase II (GCPII) has been identified as an important target in diagnosis and therapy of prostate cancer. Among several types of inhibitors, urea based inhibitors are the most common and widely employed in preclinical and clinical studies. Computational studies have been carried out to uncover active sites and interaction of PSMA inhibitors with the protein by modifying the core structure of the ligand. Analysis of the literature, however, show lack of 3-D quantitative structure activity relationship (QSAR) and molecular dynamics based molecular docking study to identify structural modifications responsible for better GCPII inhibitory activity. The present study aims to fulfil this gap by analysing well known PSMA inhibitors reported in the literature with known experimental PSMA inhibition constants. Also in order to validate the in silico study, a new GCPII inhibitor 7 was designed, synthesized and experimental PSMA enzyme inhibition was evaluated by using freshly isolated PSMA protein from human cancer cell line derived from lymph node, LNCaP. 3D-QSAR CoMFA models on 58 urea based GCPII inhibitors were generated, and the best correlation was obtained in Gast-Huck charge assigning method with q2, r2 and predictive r2 values as 0.592, 0.995 and 0.842 respectively. Moreover, steric, electrostatic, and hydrogen bond donor field contribution analysis provided best statistical values from CoMSIA model (q2, r2 and predictive r2 as 0.527, 0.981 and 0.713 respectively). Contour maps study revealed that electrostatic field contribution is the major factor for discovering better binding affinity ligands. Further molecular dynamic assisted molecular docking was also performed on GCPII receptor (PDB ID 4NGM) and most active GCPII inhibitor, DCIBzL. 4NGM co-crystallised ligand, JB7 was used to validate the docking procedure and the amino acid interactions present in JB7 are compared with DCIBzL. The results suggest that Arg210, Asn257, Gly518, Tyr552, Lys699, and Tyr700 amino acid residues may play a crucial role in GCPII inhibition. Molecular Dynamics Simulation provides information about docked pose stability of DCIBzL. By combination of CoMFA-CoMSIA field analysis and docking interaction analysis studies, conclusive SAR was generated for urea based derivatives based on which GCPII inhibitor 7 was designed and chemically synthesized in our laboratory. Evaluation of GCPII inhibitory activity of 7 by performing NAALADase assay provided IC50 value of 113 nM which is in close agreement with in silico predicted value (119 nM). Thus we have successfully validated our 3D-QSAR and molecular docking based designing of GCPII inhibitors methodology through biological experiments. This conclusive SAR would be helpful to generate novel and more potent GCPII inhibitors for drug delivery applications.

Docking analysis of gallic acid derivatives as HIV-1 protease inhibitors.

PubMed

Singh, Anjali; Pal, Tapan Kumar

2015-01-01

HIV-1 Protease (HIV-1 PR) enzymes are essential for accurate assembly and maturation of infectious HIV retroviruses. The significant role of HIV-1 protease in viral replication has made it a potential drug target. In the recent past, phytochemical Gallic Acid (GA) derivatives have been screened for protease inhibitor activity. The present work aims to design and evaluate potential GA-based HIV-1 PR phytoinhibitors by docking approach. The ligands were prepared by ChemDraw and docking was performed in HEX software. In this present study, one of the GA analogues (GA4) emerged as a potent drug candidate for HIV-1 PR inhibition, and docking results showed it to be comparable with anti-HIV drugs, darunavir and amprenavir. The GA4 derivative provided a lead for designing more effective HIV-1 PR inhibitors.

Exploring Molecular Mechanisms of Ligand Recognition by Opioid Receptors with Metadynamics†

PubMed Central

Provasi, Davide; Bortolato, Andrea; Filizola, Marta

2009-01-01

Opioid receptors are G protein-coupled receptors (GPCRs) of utmost significance in the development of potent analgesic drugs for the treatment of severe pain. An accurate evaluation at the molecular level of the ligand binding pathways into these receptors may play a key role in the design of new molecules with more desirable properties and reduced side effects. The recent characterization of high-resolution X-ray crystal structures of non-rhodopsin GPCRs for diffusible hormones and neurotransmitters presents an unprecedented opportunity to build improved homology models of opioid receptors, and to study in more detail their molecular mechanisms of ligand recognition. In this study, possible entry pathways of the non-selective antagonist naloxone (NLX) from the water environment into the well-accepted alkaloid binding pocket of a delta opioid receptor (DOR) molecular model based on the β2-adrenergic receptor crystal structure are explored using microsecond-scale well-tempered metadynamics simulations. Using as collective variables distances that account for the position of NLX and of the receptor extracellular loop 2 in relation to the DOR binding pocket, we were able to distinguish between the different states visited by the ligand (i.e., docked, undocked, and metastable bound intermediates), and to predict a free energy of binding close to experimental values after correcting for possible drawbacks of the sampling approach. The strategy employed herein holds promise for its application to the docking of diverse ligands to the opioid receptors as well as to other GPCRs. PMID:19785461

Exploring molecular mechanisms of ligand recognition by opioid receptors with metadynamics.

PubMed

Provasi, Davide; Bortolato, Andrea; Filizola, Marta

2009-10-27

Opioid receptors are G protein-coupled receptors (GPCRs) of utmost significance in the development of potent analgesic drugs for the treatment of severe pain. An accurate evaluation at the molecular level of the ligand binding pathways into these receptors may play a key role in the design of new molecules with more desirable properties and reduced side effects. The recent characterization of high-resolution X-ray crystal structures of non-rhodopsin GPCRs for diffusible hormones and neurotransmitters presents an unprecedented opportunity to build improved homology models of opioid receptors, and to study in more detail their molecular mechanisms of ligand recognition. In this study, possible pathways for entry of the nonselective antagonist naloxone (NLX) from the water environment into the well-accepted alkaloid binding pocket of a delta opioid receptor (DOR) molecular model based on the beta2-adrenergic receptor crystal structure are explored using microsecond-scale well-tempered metadynamics simulations. Using as collective variables distances that account for the position of NLX and of the receptor extracellular loop 2 in relation to the DOR binding pocket, we were able to distinguish between the different states visited by the ligand (i.e., docked, undocked, and metastable bound intermediates) and to predict a free energy of binding close to experimental values after correcting for possible drawbacks of the sampling approach. The strategy employed herein holds promise for its application to the docking of diverse ligands to the opioid receptors as well as to other GPCRs.

3D-QSAR (CoMFA, CoMSIA), molecular docking and molecular dynamics simulations study of 6-aryl-5-cyano-pyrimidine derivatives to explore the structure requirements of LSD1 inhibitors.

PubMed

Ding, Lina; Wang, Zhi-Zheng; Sun, Xu-Dong; Yang, Jing; Ma, Chao-Ya; Li, Wen; Liu, Hong-Min

2017-08-01

Recently, Histone Lysine Specific Demethylase 1 (LSD1) was regarded as a promising anticancer target for the novel drug discovery. And several small molecules as LSD1 inhibitors in different structures have been reported. In this work, we carried out a molecular modeling study on the 6-aryl-5-cyano-pyrimidine fragment LSD1 inhibitors using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. The results show that the best CoMFA model has q 2 =0.802, r 2 ncv =0.979, and the best CoMSIA model has q 2 =0.799, r 2 ncv =0.982. The electrostatic, hydrophobic and H-bond donor fields play important roles in the models. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. Molecular dynamics simulations results reveal that the complex of the ligand and the receptor protein are stable at 300K. All the results can provide us more useful information for our further drug design. Copyright © 2017. Published by Elsevier Ltd.

Three Co(II) complexes with a sexidentate N2O4-donor bis-Schiff base ligand: Synthesis, crystal structures, DFT studies, urease inhibition and molecular docking studies

NASA Astrophysics Data System (ADS)

Wang, Hu; Zhang, Xia; Zhao, Yu; Zhang, Dongmei; Jin, Fan; Fan, Yuhua

2017-11-01

Three new N2O4-donor bis-Schiff base Co(II) complexes, Co(C36H34N2O8)·2CH3OH (1), Co(C28H34N2O8S2)·H2O (2) and Co(C40H36N4O8)·3CH3OH (3) with distorted octahedral six-coordinate Co(II) centers were synthesized and determined by single crystal X-ray analysis. The X-ray crystallography shows that the metal atoms of three complexes are all six-coordinate with two nitrogen atoms from Cdbnd N groups, two oxygen atoms from ether groups and two carboxylic oxygen atoms in the mono-ligand, forming a distorted octahedral geometry. Theoretical studies of the three complexes were carried out by density functional theory (DFT) Becke's three-parameter hybrid (B3LYP) method employing the 6-31G basis set. The DFT studies indicate that the calculation is in accordance with the experimental results. Moreover, inhibition of jack bean urease by Co(II) complexes 1-3 have also been investigated. At the same time, a docking analysis using a DOCK program was conducted to determine the probable binding mode by inserting the complexes into the active site of jack bean urease. The experimental values and docking simulation exhibited that the complex 3 showed strong inhibitory activity (IC50 = 16.43 ± 2.35 μM) and the structure-activity relationships were further discussed.

α2A- and α2C-Adrenoceptors as Potential Targets for Dopamine and Dopamine Receptor Ligands.

PubMed

Sánchez-Soto, Marta; Casadó-Anguera, Verònica; Yano, Hideaki; Bender, Brian Joseph; Cai, Ning-Sheng; Moreno, Estefanía; Canela, Enric I; Cortés, Antoni; Meiler, Jens; Casadó, Vicent; Ferré, Sergi

2018-03-18

The poor norepinephrine innervation and high density of Gi/o-coupled α 2A - and α 2C -adrenoceptors in the striatum and the dense striatal dopamine innervation have prompted the possibility that dopamine could be an effective adrenoceptor ligand. Nevertheless, the reported adrenoceptor agonistic properties of dopamine are still inconclusive. In this study, we analyzed the binding of norepinephrine, dopamine, and several compounds reported as selective dopamine D 2 -like receptor ligands, such as the D 3 receptor agonist 7-OH-PIPAT and the D 4 receptor agonist RO-105824, to α 2 -adrenoceptors in cortical and striatal tissue, which express α 2A -adrenoceptors and both α 2A - and α 2C -adrenoceptors, respectively. The affinity of dopamine for α 2 -adrenoceptors was found to be similar to that for D 1 -like and D 2 -like receptors. Moreover, the exogenous dopamine receptor ligands also showed high affinity for α 2A - and α 2C -adrenoceptors. Their ability to activate Gi/o proteins through α 2A - and α 2C -adrenoceptors was also analyzed in transfected cells with bioluminescent resonance energy transfer techniques. The relative ligand potencies and efficacies were dependent on the Gi/o protein subtype. Furthermore, dopamine binding to α 2 -adrenoceptors was functional, inducing changes in dynamic mass redistribution, adenylyl cyclase activity, and ERK1/2 phosphorylation. Binding events were further studied with computer modeling of ligand docking. Docking of dopamine at α 2A - and α 2C -adrenoceptors was nearly identical to its binding to the crystallized D 3 receptor. Therefore, we provide conclusive evidence that α 2A - and α 2C -adrenoceptors are functional receptors for norepinephrine, dopamine, and other previously assumed selective D 2 -like receptor ligands, which calls for revisiting previous studies with those ligands.

A Novel Non-agonist Peroxisome Proliferator-activated Receptor γ (PPARγ) Ligand UHC1 Blocks PPARγ Phosphorylation by Cyclin-dependent Kinase 5 (CDK5) and Improves Insulin Sensitivity*

PubMed Central

Choi, Sun-Sil; Kim, Eun Sun; Koh, Minseob; Lee, Soo-Jin; Lim, Donghyun; Yang, Yong Ryoul; Jang, Hyun-Jun; Seo, Kyung-ah; Min, Sang-Hyun; Lee, In Hee; Park, Seung Bum; Suh, Pann-Ghill; Choi, Jang Hyun

2014-01-01

Thiazolidinedione class of anti-diabetic drugs which are known as peroxisome proliferator-activated receptor γ (PPARγ) ligands have been used to treat metabolic disorders, but thiazolidinediones can also cause several severe side effects, including congestive heart failure, fluid retention, and weight gain. In this study, we describe a novel synthetic PPARγ ligand UNIST HYUNDAI Compound 1 (UHC1) that binds tightly to PPARγ without the classical agonism and which blocks cyclin-dependent kinase 5 (CDK5)-mediated PPARγ phosphorylation. We modified the non-agonist PPARγ ligand SR1664 chemically to improve its solubility and then developed a novel PPARγ ligand, UHC1. According to our docking simulation, UHC1 occupied the ligand-binding site of PPARγ with a higher docking score than SR1664. In addition, UHC1 more potently blocked CDK5-mediated PPARγ phosphorylation at Ser-273. Surprisingly, UHC1 treatment effectively ameliorated the inflammatory response both in vitro and in high-fat diet-fed mice. Furthermore, UHC1 treatment dramatically improved insulin sensitivity in high-fat diet-fed mice without causing fluid retention and weight gain. Taken together, compared with SR1664, UHC1 exhibited greater beneficial effects on glucose and lipid metabolism by blocking CDK5-mediated PPARγ phosphorylation, and these data indicate that UHC1 could be a novel therapeutic agent for use in type 2 diabetes and related metabolic disorders. PMID:25100724

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Politi, Regina; Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC 27599; Rusyn, Ivan, E-mail: iir@unc.edu

2014-10-01

The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure–Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R{sup 2} = 0.55 and CCR = 0.76, respectively. In addition, for the first time a QSAR model was developed to predict bindingmore » affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R{sup 2} = 0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. - Highlights: • This is the largest curated dataset for ligand binding domain (LBD) of the THRβ. • We report the first QSAR model for antagonists of AF-2 domain of THRβ. • A combination of QSAR and docking enables prediction of both affinity and efficacy. • Models can be used to identify environmental chemicals interacting with THRβ. • Models can be used to eliminate the THRβ-mediated mechanism of action.« less

Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor

NASA Astrophysics Data System (ADS)

Duan, Rui; Xu, Xianjin; Zou, Xiaoqin

2018-01-01

D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound. For the FXR dataset, the template-based method achieved a better performance than the docking-based method on the binding mode prediction. For the binding affinity prediction, an in-house knowledge-based scoring function ITScore2 and MM/PBSA approach were employed. Good performance was achieved for MM/PBSA, whereas the performance of ITScore2 was sensitive to ligand composition, e.g. the percentage of carbon atoms in the compounds. The sensitivity to ligand composition could be a clue for the further improvement of our knowledge-based scoring function.

Docking analysis of verteporfin with YAP WW domain.

PubMed

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis.

Structure-Activity Relationships of Constrained Phenylethylamine Ligands for the Serotonin 5-HT2 Receptors

PubMed Central

Isberg, Vignir; Paine, James; Leth-Petersen, Sebastian; Kristensen, Jesper L.; Gloriam, David E.

2013-01-01

Serotonergic ligands have proven effective drugs in the treatment of migraine, pain, obesity, and a wide range of psychiatric and neurological disorders. There is a clinical need for more highly 5-HT2 receptor subtype-selective ligands and the most attention has been given to the phenethylamine class. Conformationally constrained phenethylamine analogs have demonstrated that for optimal activity the free lone pair electrons of the 2-oxygen must be oriented syn and the 5-oxygen lone pairs anti relative to the ethylamine moiety. Also the ethyl linker has been constrained providing information about the bioactive conformation of the amine functionality. However, combined 1,2-constriction by cyclization has only been tested with one compound. Here, we present three new 1,2-cyclized phenylethylamines, 9–11, and describe their synthetic routes. Ligand docking in the 5-HT2B crystal structure showed that the 1,2-heterocyclized compounds can be accommodated in the binding site. Conformational analysis showed that 11 can only bind in a higher-energy conformation, which would explain its absent or low affinity. The amine and 2-oxygen interactions with D3.32 and S3.36, respectively, can form but shift the placement of the core scaffold. The constraints in 9–11 resulted in docking poses with the 4-bromine in closer vicinity to 5.46, which is polar only in the human 5-HT2A subtype, for which 9–11 have the lowest affinity. The new ligands, conformational analysis and docking expand the structure-activity relationships of constrained phenethylamines and contributes towards the development of 5-HT2 receptor subtype-selective ligands. PMID:24244317

Structure-activity relationships of constrained phenylethylamine ligands for the serotonin 5-HT2 receptors.

PubMed

Isberg, Vignir; Paine, James; Leth-Petersen, Sebastian; Kristensen, Jesper L; Gloriam, David E

2013-01-01

Serotonergic ligands have proven effective drugs in the treatment of migraine, pain, obesity, and a wide range of psychiatric and neurological disorders. There is a clinical need for more highly 5-HT2 receptor subtype-selective ligands and the most attention has been given to the phenethylamine class. Conformationally constrained phenethylamine analogs have demonstrated that for optimal activity the free lone pair electrons of the 2-oxygen must be oriented syn and the 5-oxygen lone pairs anti relative to the ethylamine moiety. Also the ethyl linker has been constrained providing information about the bioactive conformation of the amine functionality. However, combined 1,2-constriction by cyclization has only been tested with one compound. Here, we present three new 1,2-cyclized phenylethylamines, 9-11, and describe their synthetic routes. Ligand docking in the 5-HT2B crystal structure showed that the 1,2-heterocyclized compounds can be accommodated in the binding site. Conformational analysis showed that 11 can only bind in a higher-energy conformation, which would explain its absent or low affinity. The amine and 2-oxygen interactions with D3.32 and S3.36, respectively, can form but shift the placement of the core scaffold. The constraints in 9-11 resulted in docking poses with the 4-bromine in closer vicinity to 5.46, which is polar only in the human 5-HT2A subtype, for which 9-11 have the lowest affinity. The new ligands, conformational analysis and docking expand the structure-activity relationships of constrained phenethylamines and contributes towards the development of 5-HT2 receptor subtype-selective ligands.

Molecular Docking of Enzyme Inhibitors: A Computational Tool for Structure-Based Drug Design

ERIC Educational Resources Information Center

Rudnitskaya, Aleksandra; Torok, Bela; Torok, Marianna

2010-01-01

Molecular docking is a frequently used method in structure-based rational drug design. It is used for evaluating the complex formation of small ligands with large biomolecules, predicting the strength of the bonding forces and finding the best geometrical arrangements. The major goal of this advanced undergraduate biochemistry laboratory exercise…

Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

PubMed

Makeneni, Spandana; Thieker, David F; Woods, Robert J

2018-03-26

In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

Green Chemistry: Strategy in Essential Oils Sustainability by Development of Insecticide Using Docking Method

NASA Astrophysics Data System (ADS)

Warsito; Utomo, EP; Ulfa, SM; Kholila, BN; Nindyasiwi, P.

2018-01-01

Sustainable agricultural applications in green chemistry was associated with the development of insecticide production based on secondary metabolites, such as essential oils. This research used In Silico modeling for insecticide formulation based on essential oils. The insecticidal formula was made on the basis of the Ki value of multiple docking results between the major components of essential oils as ligand with Spodotera litura receptor (2DJC) studied using Autodock Tools software. Insecticide formula activity test was done by contact method of toxic and leaf contact with essential oils concentration at level 0% - 1%. The results of the in silico study showed that the inhibition constants (Ki) of citronellal and anethol ligands combination were 1.6 mM however of citronellal and eugenol as ligands were 1.75 mM and formulated rasio (v/v), respectively 5 : 1 and 4 : 1. In addition, in vitro activity of insecticide formula with the ratio of 5: 1 possess LC50 value 0.10% (toxic contact) and 0.35% (leaf contact). While the formula with a ratio of 4: 1 possess LC50 value 0.05% (toxic contacts) and 0.31% (leaf contact).

Robust scoring functions for protein-ligand interactions with quantum chemical charge models.

PubMed

Wang, Jui-Chih; Lin, Jung-Hsin; Chen, Chung-Ming; Perryman, Alex L; Olson, Arthur J

2011-10-24

Ordinary least-squares (OLS) regression has been used widely for constructing the scoring functions for protein-ligand interactions. However, OLS is very sensitive to the existence of outliers, and models constructed using it are easily affected by the outliers or even the choice of the data set. On the other hand, determination of atomic charges is regarded as of central importance, because the electrostatic interaction is known to be a key contributing factor for biomolecular association. In the development of the AutoDock4 scoring function, only OLS was conducted, and the simple Gasteiger method was adopted. It is therefore of considerable interest to see whether more rigorous charge models could improve the statistical performance of the AutoDock4 scoring function. In this study, we have employed two well-established quantum chemical approaches, namely the restrained electrostatic potential (RESP) and the Austin-model 1-bond charge correction (AM1-BCC) methods, to obtain atomic partial charges, and we have compared how different charge models affect the performance of AutoDock4 scoring functions. In combination with robust regression analysis and outlier exclusion, our new protein-ligand free energy regression model with AM1-BCC charges for ligands and Amber99SB charges for proteins achieve lowest root-mean-squared error of 1.637 kcal/mol for the training set of 147 complexes and 2.176 kcal/mol for the external test set of 1427 complexes. The assessment for binding pose prediction with the 100 external decoy sets indicates very high success rate of 87% with the criteria of predicted root-mean-squared deviation of less than 2 Å. The success rates and statistical performance of our robust scoring functions are only weakly class-dependent (hydrophobic, hydrophilic, or mixed).

Pharmacophore-based virtual screening, biological evaluation and binding mode analysis of a novel protease-activated receptor 2 antagonist

NASA Astrophysics Data System (ADS)

Cho, Nam-Chul; Seo, Seoung-Hwan; Kim, Dohee; Shin, Ji-Sun; Ju, Jeongmin; Seong, Jihye; Seo, Seon Hee; Lee, Iiyoun; Lee, Kyung-Tae; Kim, Yun Kyung; No, Kyoung Tai; Pae, Ae Nim

2016-08-01

Protease-activated receptor 2 (PAR2) is a G protein-coupled receptor, mediating inflammation and pain signaling in neurons, thus it is considered to be a potential therapeutic target for inflammatory diseases. In this study, we performed a ligand-based virtual screening of 1.6 million compounds by employing a common-feature pharmacophore model and two-dimensional similarity search to identify a new PAR2 antagonist. The common-feature pharmacophore model was established based on the biological screening results of our in-house library. The initial virtual screening yielded a total number of 47 hits, and additional biological activity tests including PAR2 antagonism and anti-inflammatory effects resulted in a promising candidate, compound 43, which demonstrated an IC50 value of 8.22 µM against PAR2. In next step, a PAR2 homology model was constructed using the crystal structure of the PAR1 as a template to explore the binding mode of the identified ligands. A molecular docking method was optimized by comparing the binding modes of a known PAR2 agonist GB110 and antagonist GB83, and applied to predict the binding mode of our hit compound 43. In-depth docking analyses revealed that the hydrophobic interaction with Phe2435.39 is crucial for PAR2 ligands to exert antagonistic activity. MD simulation results supported the predicted docking poses that PAR2 antagonist blocked a conformational rearrangement of Na+ allosteric site in contrast to PAR2 agonist that showed Na+ relocation upon GPCR activation. In conclusion, we identified new a PAR2 antagonist together with its binding mode, which provides useful insights for the design and development of PAR2 ligands.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0

NASA Astrophysics Data System (ADS)

Vistoli, Giulio; Pedretti, Alessandro; Mazzolari, Angelica; Testa, Bernard

2010-09-01

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (≅73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r 2 = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pKm values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

Computational Design of Apolipoprotein E4 Inhibitors for Alzheimer's Disease Therapy from Traditional Chinese Medicine

PubMed Central

Huang, Hung-Jin; Chen, Hsin-Yi; Lee, Cheng-Chun

2014-01-01

Apolipoprotein E4 (Apo E4) is the major genetic risk factor in the causation of Alzheimer's disease (AD). In this study we utilize virtual screening of the world's largest traditional Chinese medicine (TCM) database and investigate potential compounds for the inhibition of ApoE4. We present the top three TCM candidates: Solapalmitine, Isodesacetyluvaricin, and Budmunchiamine L5 for further investigation. Dynamics analysis and molecular dynamics (MD) simulation were used to simulate protein-ligand complexes for observing the interactions and protein variations. Budmunchiamine L5 did not have the highest score from virtual screening; however, the dynamics pose is similar to the initial docking pose after MD simulation. Trajectory analysis reveals that Budmunchiamine L5 was stable over all simulation times. The migration distance of Budmunchiamine L5 illustrates that docked ligands are not variable from the initial docked site. Interestingly, Arg158 was observed to form H-bonds with Budmunchiamine L5 in the docking pose and MD snapshot, which indicates that the TCM compounds could stably bind to ApoE4. Our results show that Budmunchiamine L5 has good absorption, blood brain barrier (BBB) penetration, and less toxicity according to absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction and could, therefore, be safely used for developing novel ApoE4 inhibitors. PMID:24967370

Natural Products as New Treatment Options for Trichomoniasis: A Molecular Docking Investigation.

PubMed

Setzer, Mary Snow; Byler, Kendall G; Ogungbe, Ifedayo Victor; Setzer, William N

2017-01-27

Trichomoniasis, caused by the parasitic protozoan Trichomonas vaginalis, is the most common non-viral sexually-transmitted disease, and there can be severe complications from trichomoniasis. Antibiotic resistance in T. vaginalis is increasing, but there are currently no alternatives treatment options. There is a need to discover and develop new chemotherapeutic alternatives. Plant-derived natural products have long served as sources for new medicinal agents, as well as new leads for drug discovery and development. In this work, we have carried out an in silico screening of 952 antiprotozoal phytochemicals with specific protein drug targets of T. vaginalis. A total of 42 compounds showed remarkable docking properties to T. vaginalis methionine gamma-lyase (TvMGL) and to T. vaginalis purine nucleoside phosphorylase (TvPNP). The most promising ligands were polyphenolic compounds, and several of these showed docking properties superior to either co-crystallized ligands or synthetic enzyme inhibitors.

Novel ligands of Choline Acetyltransferase designed by in silico molecular docking, hologram QSAR and lead optimization

NASA Astrophysics Data System (ADS)

Kumar, Rajnish; Långström, Bengt; Darreh-Shori, Taher

2016-08-01

Recent reports have brought back the acetylcholine synthesizing enzyme, choline acetyltransferase in the mainstream research in dementia and the cholinergic anti-inflammatory pathway. Here we report, a specific strategy for the design of novel ChAT ligands based on molecular docking, Hologram Quantitative Structure Activity Relationship (HQSAR) and lead optimization. Molecular docking was performed on a series of ChAT inhibitors to decipher the molecular fingerprint of their interaction with the active site of ChAT. Then robust statistical fragment HQSAR models were developed. A library of novel ligands was generated based on the pharmacophoric and shape similarity scoring function, and evaluated in silico for their molecular interactions with ChAT. Ten of the top scoring invented compounds are reported here. We confirmed the activity of α-NETA, the only commercially available ChAT inhibitor, and one of the seed compounds in our model, using a new simple colorimetric ChAT assay (IC50 ~ 88 nM). In contrast, α-NETA exhibited an IC50 of ~30 μM for the ACh-degrading cholinesterases. In conclusion, the overall results may provide useful insight for discovering novel ChAT ligands and potential positron emission tomography tracers as in vivo functional biomarkers of the health of central cholinergic system in neurodegenerative disorders, such as Alzheimer’s disease.

Protein–protein docking by fast generalized Fourier transforms on 5D rotational manifolds

PubMed Central

Padhorny, Dzmitry; Kazennov, Andrey; Zerbe, Brandon S.; Porter, Kathryn A.; Xia, Bing; Mottarella, Scott E.; Kholodov, Yaroslav; Ritchie, David W.; Vajda, Sandor; Kozakov, Dima

2016-01-01

Energy evaluation using fast Fourier transforms (FFTs) enables sampling billions of putative complex structures and hence revolutionized rigid protein–protein docking. However, in current methods, efficient acceleration is achieved only in either the translational or the rotational subspace. Developing an efficient and accurate docking method that expands FFT-based sampling to five rotational coordinates is an extensively studied but still unsolved problem. The algorithm presented here retains the accuracy of earlier methods but yields at least 10-fold speedup. The improvement is due to two innovations. First, the search space is treated as the product manifold SO(3)×(SO(3)∖S1), where SO(3) is the rotation group representing the space of the rotating ligand, and (SO(3)∖S1) is the space spanned by the two Euler angles that define the orientation of the vector from the center of the fixed receptor toward the center of the ligand. This representation enables the use of efficient FFT methods developed for SO(3). Second, we select the centers of highly populated clusters of docked structures, rather than the lowest energy conformations, as predictions of the complex, and hence there is no need for very high accuracy in energy evaluation. Therefore, it is sufficient to use a limited number of spherical basis functions in the Fourier space, which increases the efficiency of sampling while retaining the accuracy of docking results. A major advantage of the method is that, in contrast to classical approaches, increasing the number of correlation function terms is computationally inexpensive, which enables using complex energy functions for scoring. PMID:27412858

CovalentDock Cloud: a web server for automated covalent docking.

PubMed

Ouyang, Xuchang; Zhou, Shuo; Ge, Zemei; Li, Runtao; Kwoh, Chee Keong

2013-07-01

Covalent binding is an important mechanism for many drugs to gain its function. We developed a computational algorithm to model this chemical event and extended it to a web server, the CovalentDock Cloud, to make it accessible directly online without any local installation and configuration. It provides a simple yet user-friendly web interface to perform covalent docking experiments and analysis online. The web server accepts the structures of both the ligand and the receptor uploaded by the user or retrieved from online databases with valid access id. It identifies the potential covalent binding patterns, carries out the covalent docking experiments and provides visualization of the result for user analysis. This web server is free and open to all users at http://docking.sce.ntu.edu.sg/.

CovalentDock Cloud: a web server for automated covalent docking

PubMed Central

Ouyang, Xuchang; Zhou, Shuo; Ge, Zemei; Li, Runtao; Kwoh, Chee Keong

2013-01-01

Covalent binding is an important mechanism for many drugs to gain its function. We developed a computational algorithm to model this chemical event and extended it to a web server, the CovalentDock Cloud, to make it accessible directly online without any local installation and configuration. It provides a simple yet user-friendly web interface to perform covalent docking experiments and analysis online. The web server accepts the structures of both the ligand and the receptor uploaded by the user or retrieved from online databases with valid access id. It identifies the potential covalent binding patterns, carries out the covalent docking experiments and provides visualization of the result for user analysis. This web server is free and open to all users at http://docking.sce.ntu.edu.sg/. PMID:23677616

Pharmacophore modeling, molecular docking and molecular dynamics studies on natural products database to discover novel skeleton as non-purine xanthine oxidase inhibitors.

PubMed

Peng, Jiale; Li, Yaping; Zhou, Yeheng; Zhang, Li; Liu, Xingyong; Zuo, Zhili

2018-05-29

Gout is a common inflammatory arthritis caused by the deposition of urate crystals within joints. It is increasingly in prevalence during the past few decades as shown by the epidemiological survey results. Xanthine oxidase (XO) is a key enzyme to transfer hypoxanthine and xanthine to uric acid, whose overproduction leads to gout. Therefore, inhibiting the activity of xanthine oxidase is an important way to reduce the production of urate. In the study, in order to identify the potential natural products targeting XO, pharmacophore modeling was employed to filter databases. Here, two methods, pharmacophore based on ligand and pharmacophore based on receptor-ligand, were constructed by Discovery Studio. Then GOLD was used to refine the potential compounds with higher fitness scores. Finally, molecular docking and dynamics simulations were employed to analyze the interactions between compounds and protein. The best hypothesis was set as a 3D query to screen database, returning 785 and 297 compounds respectively. A merged set of the above 1082 molecules was subjected to molecular docking, which returned 144 hits with high-fitness scores. These molecules were clustered in four main kinds depending on different backbones. What is more, molecular docking showed that the representative compounds established key interactions with the amino acid residues in the protein, and the RMSD and RMSF of molecular dynamics results showed that these compounds can stabilize the protein. The information represented in the study confirmed previous reports. And it may assist to discover and design new backbones as potential XO inhibitors based on natural products.

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

PubMed Central

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J. P.; Chen, Yu-Ching

2016-01-01

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes. PMID:27304951

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation.

PubMed

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J P; Chen, Yu-Ching

2016-06-13

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Flexible docking of a ligand peptide to a receptor protein by multicanonical molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Nakajima, Nobuyuki; Higo, Junichi; Kidera, Akinori; Nakamura, Haruki

1997-10-01

A new method for flexible docking by multicanonical molecular dynamics simulation is presented. The method was applied to the binding of a short proline-rich peptide to a Src homology 3 (SH3) domain. The peptide and the side-chains at the ligand binding cleft of SH3 were completely flexible and the large number of possible conformations and dispositions of the peptide were sampled. The reweighted canonical resemble at 300 K resulted in only a few predominant binding modes, one of which was similar to the complex crystal structure. The inverted peptide orientation was also observed in the other binding modes.

Sampling protein motion and solvent effect during ligand binding

PubMed Central

Limongelli, Vittorio; Marinelli, Luciana; Cosconati, Sandro; La Motta, Concettina; Sartini, Stefania; Mugnaini, Laura; Da Settimo, Federico; Novellino, Ettore; Parrinello, Michele

2012-01-01

An exhaustive description of the molecular recognition mechanism between a ligand and its biological target is of great value because it provides the opportunity for an exogenous control of the related process. Very often this aim can be pursued using high resolution structures of the complex in combination with inexpensive computational protocols such as docking algorithms. Unfortunately, in many other cases a number of factors, like protein flexibility or solvent effects, increase the degree of complexity of ligand/protein interaction and these standard techniques are no longer sufficient to describe the binding event. We have experienced and tested these limits in the present study in which we have developed and revealed the mechanism of binding of a new series of potent inhibitors of Adenosine Deaminase. We have first performed a large number of docking calculations, which unfortunately failed to yield reliable results due to the dynamical character of the enzyme and the complex role of the solvent. Thus, we have stepped up the computational strategy using a protocol based on metadynamics. Our approach has allowed dealing with protein motion and solvation during ligand binding and finally identifying the lowest energy binding modes of the most potent compound of the series, 4-decyl-pyrazolo[1,5-a]pyrimidin-7-one. PMID:22238423

Synthesis of 4-aminophenyl substituted indole derivatives for the instrumental analysis and molecular docking evaluation studies

NASA Astrophysics Data System (ADS)

Singh, Navneet; Kumar, Keshav

2017-07-01

The Indole has been known to maintain celebrity status since so many decades and has been a centre point at the spectrum of pharmacological research. The present work stimulates an idea of generating a pool of library of lead compounds. The data collected can be used for the mapping of biologically active compounds. The reported derivatives of 4-aminophenyl substituted Indole were prepared by the methods of Fischer Indole synthesis and Vilsemeier reaction followed by screening for instrumental analysis and molecular docking studies. The synthesized compounds 4-(1-(2-phenylhydrazono)ethyl)aniline, 1, 4-(1H-indol-2-yl)aniline, 2 and 2-(4-aminophenyl)-1H-indole-3-carbaldehyde, 3 were found to have remarkable yield and instrumental data analysis and also showed remarkable docked characteristic. The molecular docking studies revealed that ligand (amino acids) of comp. 1, 2 and 3 had been docked successfully on the binding site of the 3JUS protein selected from PDB with H bonding. The molecular docking data showed that compound 1, would possess remarkable biological activity and compd. 2 and 3 would possess mild to moderate biological activity. Thus this research work paves the way to synthesize new derivatives and thus to develop new compounds in future with accurate prediction.

Determination of genotypic and clinical characteristics of Colombian patients with mucopolysaccharidosis IVA

PubMed Central

Tapiero-Rodriguez, Sandra M; Acosta Guio, Johanna C; Porras-Hurtado, Gloria Liliana; García, Natalia; Solano, Martha; Pachajoa, Harry; Velasco, Harvy M

2018-01-01

Background As mucopolysaccharidosis IVA (MPS IVA) is the most frequent MPS in Colombia, this paper aims to describe its clinical and mutational characteristics in 32 diagnosed patients included in this study. Methods Genotyping was completed by amplification and Sanger sequencing of the GALNS gene. The SWISS-model platform was used for bioinformatic analysis, and mutant proteins were generated by homology from the wild-type GALNS code 4FDI template from the Protein Data Bank (PDB) database. Docking was performed using the GalNAc6S ligand (PubChem CID: 193456) by AutoDock Vina 1.0 and visualized in PyMOL and LigPlot+. Results Eleven variants were identified, and one new pathogenic variant was described in the heterozygous state, which is consistent with genotype c. 319 G> T or p.Ala107Ser. The pathogenic variant c.901G>T or p.Gly301Cys was the most frequent mutation with 51.6% of alleles. Docking revealed affinity energy of −5.9 Kcal/mol between wild-type GALNS and the G6S ligand. Some changes were evidenced at the intermolecular interaction level, and affinity energy for each mutant decreased. Conclusion Clinical variables and genotypic analysis were similar to those reported for other world populations. Genotypic data showed greater allelic heterogeneity than those previously reported. Bioinformatics tools showed differences in the binding interactions of mutant proteins with the G6S ligand, in regard the wild-type GALNS. PMID:29731656

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products.

PubMed

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-wai

2016-01-25

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products

NASA Astrophysics Data System (ADS)

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-Wai

2016-01-01

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

DOCKTITE-a highly versatile step-by-step workflow for covalent docking and virtual screening in the molecular operating environment.

PubMed

Scholz, Christoph; Knorr, Sabine; Hamacher, Kay; Schmidt, Boris

2015-02-23

The formation of a covalent bond with the target is essential for a number of successful drugs, yet tools for covalent docking without significant restrictions regarding warhead or receptor classes are rare and limited in use. In this work we present DOCKTITE, a highly versatile workflow for covalent docking in the Molecular Operating Environment (MOE) combining automated warhead screening, nucleophilic side chain attachment, pharmacophore-based docking, and a novel consensus scoring approach. The comprehensive validation study includes pose predictions of 35 protein/ligand complexes which resulted in a mean RMSD of 1.74 Å and a prediction rate of 71.4% with an RMSD below 2 Å, a virtual screening with an area under the curve (AUC) for the receiver operating characteristics (ROC) of 0.81, and a significant correlation between predicted and experimental binding affinities (ρ = 0.806, R(2) = 0.649, p < 0.005).

Blind Pose Prediction, Scoring, and Affinity Ranking of the CSAR 2014 Dataset.

PubMed

Martiny, Virginie Y; Martz, François; Selwa, Edithe; Iorga, Bogdan I

2016-06-27

The 2014 CSAR Benchmark Exercise was focused on three protein targets: coagulation factor Xa, spleen tyrosine kinase, and bacterial tRNA methyltransferase. Our protocol involved a preliminary analysis of the structural information available in the Protein Data Bank for the protein targets, which allowed the identification of the most appropriate docking software and scoring functions to be used for the rescoring of several docking conformations datasets, as well as for pose prediction and affinity ranking. The two key points of this study were (i) the prior evaluation of molecular modeling tools that are most adapted for each target and (ii) the increased search efficiency during the docking process to better explore the conformational space of big and flexible ligands.

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

PubMed

Cappel, Daniel; Wahlström, Rickard; Brenk, Ruth; Sotriffer, Christoph A

2011-10-24

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.

Application of molecular docking and ONIOM methods for the description of interactions between anti-quorum sensing active (AHL) analogues and the Pseudomonas aeruginosa LasR binding site.

PubMed

Ahumedo, Maicol; Drosos, Juan Carlos; Vivas-Reyes, Ricardo

2014-05-01

Molecular docking methods were applied to simulate the coupling of a set of nineteen acyl homoserine lactone analogs into the binding site of the transcriptional receptor LasR. The best pose of each ligand was explored and a qualitative analysis of the possible interactions present in the complex was performed. From the results of the protein-ligand complex analysis, it was found that residues Tyr-64 and Tyr-47 are involved in important interactions, which mainly determine the antagonistic activity of the AHL analogues considered for this study. The effect of different substituents on the aromatic ring, the common structure to all ligands, was also evaluated focusing on how the interaction with the two previously mentioned tyrosine residues was affected. Electrostatic potential map calculations based on the electron density and the van der Waals radii were performed on all ligands to graphically aid in the explanation of the variation of charge density on their structures when the substituent on the aromatic ring is changed through the elements of the halogen group series. A quantitative approach was also considered and for that purpose the ONIOM method was performed to estimate the energy change in the different ligand-receptor complex regions. Those energy values were tested for their relationship with the corresponding IC50 in order to establish if there is any correlation between energy changes in the selected regions and the biological activity. The results obtained using the two approaches may contribute to the field of quorum sensing active molecules; the docking analysis revealed the role of some binding site residues involved in the formation of a halogen bridge with ligands. These interactions have been demonstrated to be responsible for the interruption of the signal propagation needed for the quorum sensing circuit. Using the other approach, the structure-activity relationship (SAR) analysis, it was possible to establish which structural characteristics and chemical requirements are necessary to classify a compound as a possible agonist or antagonist against the LasR binding site.

Predicting the Accuracy of Protein–Ligand Docking on Homology Models

PubMed Central

BORDOGNA, ANNALISA; PANDINI, ALESSANDRO; BONATI, LAURA

2011-01-01

Ligand–protein docking is increasingly used in Drug Discovery. The initial limitations imposed by a reduced availability of target protein structures have been overcome by the use of theoretical models, especially those derived by homology modeling techniques. While this greatly extended the use of docking simulations, it also introduced the need for general and robust criteria to estimate the reliability of docking results given the model quality. To this end, a large-scale experiment was performed on a diverse set including experimental structures and homology models for a group of representative ligand–protein complexes. A wide spectrum of model quality was sampled using templates at different evolutionary distances and different strategies for target–template alignment and modeling. The obtained models were scored by a selection of the most used model quality indices. The binding geometries were generated using AutoDock, one of the most common docking programs. An important result of this study is that indeed quantitative and robust correlations exist between the accuracy of docking results and the model quality, especially in the binding site. Moreover, state-of-the-art indices for model quality assessment are already an effective tool for an a priori prediction of the accuracy of docking experiments in the context of groups of proteins with conserved structural characteristics. PMID:20607693

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

PubMed

Moitessier, Nicolas; Pottel, Joshua; Therrien, Eric; Englebienne, Pablo; Liu, Zhaomin; Tomberg, Anna; Corbeil, Christopher R

2016-09-20

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Spectroscopic and molecular docking studies on the charge transfer complex of bovine serum albumin with quinone in aqueous medium and its influence on the ligand binding property of the protein.

PubMed

Satheshkumar, Angupillai; Elango, Kuppanagounder P

2014-09-15

The spectral techniques such as UV-Vis, (1)H NMR and fluorescence and electrochemical experiments have been employed to investigate the interaction between 2-methoxy-3,5,6-trichloro-1,4-benzoquinone (MQ; a water soluble quinone) and bovine serum albumin (BSA) in aqueous medium. The fluorescence of BSA was quenched by MQ via formation of a 1:1 BSA-MQ charge transfer adduct with a formation constant of 3.3×10(8) L mol(-1). Based on the Forster's theory the binding distance between them is calculated as 2.65 nm indicating high probability of binding. For the first time, influence of quinone on the binding property of various types of ligands such as aspirin, ascorbic acid, nicotinimide and sodium stearate has also been investigated. The results indicated that the strong and spontaneous binding existing between BSA and MQ, decreased the intensity of binding of these ligands with BSA. Since Tryptophan (Trp) is the basic residue present in BSA, a comparison between binding property of Trp-MQ adduct with that of BSA-MQ with these ligands has also been attempted. 1H NMR titration study indicated that the Trp forms a charge transfer complex with MQ, which reduces the interaction of Trp with the ligands. Molecular docking study supported the fact that the quinone interacts with the Trp212 unit of the BSA and the free energy change of binding (ΔG) for the BSA-MQ complex was found to be -46 kJ mol(-1), which is comparable to our experimental free energy of binding (-49 kJ mol(-1)) obtained from fluorescence study. Copyright © 2014 Elsevier B.V. All rights reserved.

Spectroscopic and molecular docking studies on the charge transfer complex of bovine serum albumin with quinone in aqueous medium and its influence on the ligand binding property of the protein

NASA Astrophysics Data System (ADS)

Satheshkumar, Angupillai; Elango, Kuppanagounder P.

2014-09-01

The spectral techniques such as UV-Vis, 1H NMR and fluorescence and electrochemical experiments have been employed to investigate the interaction between 2-methoxy-3,5,6-trichloro-1,4-benzoquinone (MQ; a water soluble quinone) and bovine serum albumin (BSA) in aqueous medium. The fluorescence of BSA was quenched by MQ via formation of a 1:1 BSA-MQ charge transfer adduct with a formation constant of 3.3 × 108 L mol-1. Based on the Forster’s theory the binding distance between them is calculated as 2.65 nm indicating high probability of binding. For the first time, influence of quinone on the binding property of various types of ligands such as aspirin, ascorbic acid, nicotinimide and sodium stearate has also been investigated. The results indicated that the strong and spontaneous binding existing between BSA and MQ, decreased the intensity of binding of these ligands with BSA. Since Tryptophan (Trp) is the basic residue present in BSA, a comparison between binding property of Trp-MQ adduct with that of BSA-MQ with these ligands has also been attempted. 1H NMR titration study indicated that the Trp forms a charge transfer complex with MQ, which reduces the interaction of Trp with the ligands. Molecular docking study supported the fact that the quinone interacts with the Trp212 unit of the BSA and the free energy change of binding (ΔG) for the BSA-MQ complex was found to be -46 kJ mol-1, which is comparable to our experimental free energy of binding (-49 kJ mol-1) obtained from fluorescence study.

Synthesis, stereochemistry, crystal structure, docking study and biological evaluation of some new N-benzylpiperidin-4-ones

NASA Astrophysics Data System (ADS)

Ponnuswamy, S.; Kayalvizhi, R.; Sethuvasan, S.; Sugumar, P.; Ponnuswamy, M. N.

2018-03-01

Two new N-benzylpiperidin-4-ones 3 and 4 have been synthesized and characterized using IR, 1D and 2D NMR spectral studies. The NMR data of N-benzylpiperidin-4-ones 3 and 4 reveal that the compounds prefer to exist in chair conformation with equatorial orientation of the bulky substituents and the single crystal X-ray structure of compound 4 also reveals a similar conformation in solid state. Furthermore, the antimicrobial studies carried out for the compounds 1-4 indicate moderate activities with the selected strains. The antioxidant potency of 3 is superior whereas 4 exhibits moderate activity when compared to that of standard drug. The results of molecular docking studies with the AmpC β-lactamase enzyme indicate that compound 3 shows better docking score and binding energy than the co-crystal ligand.

Docking analysis of verteporfin with YAP WW domain

PubMed Central

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis. PMID:28943729

DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

PubMed

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L

2013-08-26

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

Refined docking as a valuable tool for lead optimization: application to histamine H3 receptor antagonists.

PubMed

Levoin, Nicolas; Calmels, Thierry; Poupardin-Olivier, Olivia; Labeeuw, Olivier; Danvy, Denis; Robert, Philippe; Berrebi-Bertrand, Isabelle; Ganellin, C Robin; Schunack, Walter; Stark, Holger; Capet, Marc

2008-10-01

Drug-discovery projects frequently employ structure-based information through protein modeling and ligand docking, and there is a plethora of reports relating successful use of them in virtual screening. Hit/lead optimization, which represents the next step and the longest for the medicinal chemist, is very rarely considered. This is not surprising because lead optimization is a much more complex task. Here, a homology model of the histamine H(3) receptor was built and tested for its ability to discriminate ligands above a defined threshold of affinity. In addition, drug safety is also evaluated during lead optimization, and "antitargets" are studied. So, we have used the same benchmarking procedure with the HERG channel and CYP2D6 enzyme, for which a minimal affinity is strongly desired. For targets and antitargets, we report here an accuracy as high as at least 70%, for ligands being classified above or below the chosen threshold. Such a good result is beyond what could have been predicted, especially, since our test conditions were particularly stringent. First, we measured the accuracy by means of AUC of ROC plots, i. e. considering both false positive and false negatives. Second, we used as datasets extensive chemical libraries (nearly a thousand ligands for H(3)). All molecules considered were true H(3) receptor ligands with moderate to high affinity (from microM to nM range). Third, the database is issued from concrete SAR (Bioprojet H(3) BF2.649 library) and is not simply constituted by few active ligands buried in a chemical catalogue.

Molecular modeling and simulation of FabG, an enzyme involved in the fatty acid pathway of Streptococcus pyogenes.

PubMed

Shafreen, Rajamohmed Beema; Pandian, Shunmugiah Karutha

2013-09-01

Streptococcus pyogenes (SP) is the major cause of pharyngitis accompanied by strep throat infections in humans. 3-keto acyl reductase (FabG), an important enzyme involved in the elongation cycle of the fatty acid pathway of S. pyogenes, is essential for synthesis of the cell-membrane, virulence factors and quorum sensing-related mechanisms. Targeting SPFabG may provide an important aid for the development of drugs against S. pyogenes. However, the absence of a crystal structure for FabG of S. pyogenes limits the development of structure-based drug designs. Hence, in the present study, a homology model of FabG was generated using the X-ray crystallographic structure of Aquifex aeolicus (PDB ID: 2PNF). The modeled structure was refined using energy minimization. Furthermore, active sites were predicted, and a large dataset of compounds was screened against SPFabG. The ligands were docked using the LigandFit module that is available from Discovery Studio version 2.5. From this list, 13 best hit ligands were chosen based on the docking score and binding energy. All of the 13 ligands were screened for Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties. From this, the two best descriptors, along with one descriptor that lay outside the ADMET plot, were selected for molecular dynamic (MD) simulation. In vitro testing of the ligands using biological assays further substantiated the efficacy of the ligands that were screened based on the in silico methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Structure-Guided Screening for Functionally Selective D2 Dopamine Receptor Ligands from a Virtual Chemical Library.

PubMed

Männel, Barbara; Jaiteh, Mariama; Zeifman, Alexey; Randakova, Alena; Möller, Dorothee; Hübner, Harald; Gmeiner, Peter; Carlsson, Jens

2017-10-20

Functionally selective ligands stabilize conformations of G protein-coupled receptors (GPCRs) that induce a preference for signaling via a subset of the intracellular pathways activated by the endogenous agonists. The possibility to fine-tune the functional activity of a receptor provides opportunities to develop drugs that selectively signal via pathways associated with a therapeutic effect and avoid those causing side effects. Animal studies have indicated that ligands displaying functional selectivity at the D 2 dopamine receptor (D 2 R) could be safer and more efficacious drugs against neuropsychiatric diseases. In this work, computational design of functionally selective D 2 R ligands was explored using structure-based virtual screening. Molecular docking of known functionally selective ligands to a D 2 R homology model indicated that such compounds were anchored by interactions with the orthosteric site and extended into a common secondary pocket. A tailored virtual library with close to 13 000 compounds bearing 2,3-dichlorophenylpiperazine, a privileged orthosteric scaffold, connected to diverse chemical moieties via a linker was docked to the D 2 R model. Eighteen top-ranked compounds that occupied both the orthosteric and allosteric site were synthesized, leading to the discovery of 16 partial agonists. A majority of the ligands had comparable maximum effects in the G protein and β-arrestin recruitment assays, but a subset displayed preference for a single pathway. In particular, compound 4 stimulated β-arrestin recruitment (EC 50 = 320 nM, E max = 16%) but had no detectable G protein signaling. The use of structure-based screening and virtual libraries to discover GPCR ligands with tailored functional properties will be discussed.

Hybrid Steered Molecular Dynamics-Docking: An Efficient Solution to the Problem of Ranking Inhibitor Affinities Against a Flexible Drug Target.

PubMed

Whalen, Katie L; Chang, Kevin M; Spies, M Ashley

2011-05-16

Existing techniques which attempt to predict the affinity of protein-ligand interactions have demonstrated a direct relationship between computational cost and prediction accuracy. We present here the first application of a hybrid ensemble docking and steered molecular dynamics scheme (with a minimized computational cost), which achieves a binding affinity rank-ordering of ligands with a Spearman correlation coefficient of 0.79 and an RMS error of 0.7 kcal/mol. The scheme, termed Flexible Enzyme Receptor Method by Steered Molecular Dynamics (FERM-SMD), is applied to an in-house collection of 17 validated ligands of glutamate racemase. The resulting improved accuracy in affinity prediction allows elucidation of the key structural components of a heretofore unreported glutamate racemase inhibitor (K(i) = 9 µM), a promising new lead in the development of antibacterial therapeutics.

Virtual screening and pharmacophore studies for ftase inhibitors using Indian plant anticancer compounds database.

PubMed

Khan, Abdul Hafeez; Prakash, Alok; Kumar, Dinesh; Rawat, Anil Kumar; Srivastava, Rajeev; Srivastava, Shipra

2010-07-06

Farnesyl transferase (FTase) is an enzyme responsible for post-translational modification in proteins having a carboxy-terminal CaaX motif in human. It catalyzes the attachment of a lipid group in proteins of RAS superfamily, which is essential in signal transduction. FTase has been recognized as an important target for anti cancer therapeutics. In this work, we performed virtual screening against FTase with entire 125 compounds from Indian Plant Anticancer Database using AutoDock 3.0.5 software. All compounds were docked within binding pocket containing Lys164, Tyr300, His248 and Tyr361 residues in crystal structure of FTase. These complexes were ranked according to their docking score, using methodology that was shown to achieve maximum accuracy. Finally we got three potent compounds with the best Autodock docking Score (Vinorelbine: -21.28 Kcal/mol, Vincristine: -21.74 Kcal/mol and Vinblastine: -22.14 Kcal/mol) and their energy scores were better than the FTase bound co-crystallized ligand (L- 739: -7.9 kcal/mol). These three compounds belong to Vinca alkaloids were analyzed through Python Molecular Viewer for their interaction studies. It predicted similar orientation and binding modes for these compounds with L-739 in FTase.Thus from the complex scoring and binding ability it is concluded that these Vinca alkaloids could be promising inhibitors for FTase. A 2-D pharmacophore was generated for these alkaloids using LigandScout to confirm it. A shared feature pharmacophore was also constructed that shows four common features (one hydogen bond Donar, Two hydrogen bond Acceptor and one ionizable area) help compounds to interact with this enzyme.

A ligand-based comparative molecular field analysis (CoMFA) and homology model based molecular docking studies on 3', 4'-dihydroxyflavones as rat 5-lipoxygenase inhibitors: Design of new inhibitors.

PubMed

Ahamed, T K Shameera; Muraleedharan, K

2017-12-01

In this study, ligand based comparative molecular field analysis (CoMFA) with five principal components was performed on class of 3', 4'-dihydroxyflavone derivatives for potent rat 5-LOX inhibitors. The percentage contributions in building of CoMFA model were 91.36% for steric field and 8.6% for electrostatic field. R 2 values for training and test sets were found to be 0.9320 and 0.8259, respectively. In case of LOO, LTO and LMO cross validation test, q 2 values were 0.6587, 0.6479 and 0.5547, respectively. These results indicate that the model has high statistical reliability and good predictive power. The extracted contour maps were used to identify the important regions where the modification was necessary to design a new molecule with improved activity. The study has developed a homology model for rat 5-LOX and recognized the key residues at the binding site. Docking of most active molecule to the binding site of 5-LOX confirmed the stability and rationality of CoMFA model. Based on molecular docking results and CoMFA contour plots, new inhibitors with higher activity with respect to the most active compound in data set were designed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Molecular docking and QSAR study on steroidal compounds as aromatase inhibitors.

PubMed

Dai, Yujie; Wang, Qiang; Zhang, Xiuli; Jia, Shiru; Zheng, Heng; Feng, Dacheng; Yu, Peng

2010-12-01

In order to develop more potent, selective and less toxic steroidal aromatase (AR) inhibitors, molecular docking, 2D and 3D hybrid quantitative structure-activity relationship (QSAR) study have been conducted using topological, molecular shape, spatial, structural and thermodynamic descriptors on 32 steroidal compounds. The molecular docking study shows that one or more hydrogen bonds with MET374 are one of the essential requirements for the optimum binding of ligands. The QSAR model obtained indicates that the aromatase inhibitory activity can be enhanced by increasing SIC, SC_3_C, Jurs_WNSA_1, Jurs_WPSA_1 and decreasing CDOCKER interaction energy (ECD), IAC_Total and Shadow_XZfrac. The predicted results shows that this model has a comparatively good predictive power which can be used in prediction of activity of new steroidal aromatase inhibitors. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Deciphering the GPER/GPR30-agonist and antagonists interactions using molecular modeling studies, molecular dynamics, and docking simulations.

PubMed

Méndez-Luna, D; Martínez-Archundia, M; Maroun, Rachid C; Ceballos-Reyes, G; Fragoso-Vázquez, M J; González-Juárez, D E; Correa-Basurto, J

2015-01-01

The G-protein coupled estrogen receptor 1 GPER/GPR30 is a transmembrane seven-helix (7TM) receptor involved in the growth and proliferation of breast cancer. Due to the absence of a crystal structure of GPER/GPR30, in this work, molecular modeling studies have been carried out to build a three-dimensional structure, which was subsequently refined by molecular dynamics (MD) simulations (up to 120 ns). Furthermore, we explored GPER/GPR30's molecular recognition properties by using reported agonist ligands (G1, estradiol (E2), tamoxifen, and fulvestrant) and the antagonist ligands (G15 and G36) in subsequent docking studies. Our results identified the E2 binding site on GPER/GPR30, as well as other receptor cavities for accepting large volume ligands, through GPER/GPR30 π-π, hydrophobic, and hydrogen bond interactions. Snapshots of the MD trajectory at 14 and 70 ns showed almost identical binding motifs for G1 and G15. It was also observed that C107 interacts with the acetyl oxygen of G1 (at 14 ns) and that at 70 ns the residue E275 interacts with the acetyl group and with the oxygen from the other agonist whereas the isopropyl group of G36 is oriented toward Met141, suggesting that both C107 and E275 could be involved in the protein activation. This contribution suggest that GPER1 has great structural changes which explain its great capacity to accept diverse ligands, and also, the same ligand could be recognized in different binding pose according to GPER structural conformations.

Inhibitors of SARS-3CLpro: Virtual Screening, Biological Evaluation and Molecular Dynamics Simulation Studies

PubMed Central

Mukherjee, Prasenjit; Shah, Falgun; Desai, Prashant; Avery, Mitchell

2011-01-01

SARS-CoV from the coronaviridae family has been identified as the etiological agent of Severe Acute Respiratory Syndrome (SARS), a highly contagious upper respiratory disease that reached epidemic status in 2002. SARS-3CLpro, a cysteine protease indispensible to the viral life cycle, has been identified as one of the key therapeutic target against SARS. A combined ligand and structure based virtual screening was carried out against the Asinex Platinum collection. Multiple low micromolar inhibitors of the enzyme were identified through this search, one of which also showed activity against SARS-CoV in a whole cell CPE assay. Furthermore, multi nanosecond explicit solvent simulations were carried out using the docking poses of the identified hits to study the overall stability of the binding site interactions as well as identify important changes in the interaction profile that were not apparent from the docking study. Cumulative analysis of the evaluated compounds and the simulation studies led to the identification of certain protein-ligand interaction patterns which would be useful in further structure based design efforts. PMID:21604711

Synthesis, characterization, DFT calculations and molecular docking studies of metal (II) complexes

NASA Astrophysics Data System (ADS)

Ekennia, Anthony C.; Osowole, Aderoju A.; Olasunkanmi, Lukman O.; Onwudiwe, Damian C.; Olubiyi, Olujide O.; Ebenso, Eno E.

2017-12-01

Two novel ligands, 2-methyl-6-[(5-methyl benzothiazol-2-ylimino)-methyl]-2-methoxycyclohexa-1,5-dienol (HL1) and 2-methyl-6-[(5-floro-benzothiazol-2-ylimino)-methyl]-2-methoxycyclohexa-1,5-dienol (HL2) were synthesized from the condensation reaction of 2-hydroxy-3-methoxybenzaldehyde with 2-amino-6-methylbenzothiazole and 2-amino-6-florobenzothiazole respectively. Mononuclear Cu(II), Ni(II) and Co(II) complexes of the ligands were synthesized and characterized using elemental analysis, magnetic susceptibility, thermogravimetric, conductance, infrared and UV-visible spectroscopic measurements. The 1H NMR, 13C NMR, Dept-90 NMR spectroscopy of the ligands was also recorded to establish the formation of the Schiff bases. The analytical data of the complexes showed that the metal to ligand ratio was 1:1 for Cu(II), Ni(II) and Co(II) complexes of HL1 and Cu(II) complexes of HL2, while Ni(II) and Co(II) complexes of HL2 was 1:2. The infrared spectral data showed that the chelation behaviour of the ligands towards transition metal ions was through phenolic oxygen and azomethine nitrogen atoms. Molar conductivity revealed the non-electrolytic nature of all chelates in DMSO solution. The geometry of the complexes was deduced from thermal, magnetic susceptibility and UV-visible spectroscopic results and was further confirmed with DFT calculations. The compounds were subjected to in-vitro antibacterial screening using agar well diffusion method on some clinically isolated Gram positive and Gram negative bacteria strains. The compounds showed varied antibacterial activities. Molecular docking studies were carried out to study the molecular interaction between the compounds and different enzymes of the bacterial strains. The antioxidant potentials of the compounds were studied using ferrous ion chelating assay and 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay. However, the complexes had better antioxidant potentials compared to the ligands.

A general approach for developing system-specific functions to score protein-ligand docked complexes using support vector inductive logic programming.

PubMed

Amini, Ata; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2007-12-01

Despite the increased recent use of protein-ligand and protein-protein docking in the drug discovery process due to the increases in computational power, the difficulty of accurately ranking the binding affinities of a series of ligands or a series of proteins docked to a protein receptor remains largely unsolved. This problem is of major concern in lead optimization procedures and has lead to the development of scoring functions tailored to rank the binding affinities of a series of ligands to a specific system. However, such methods can take a long time to develop and their transferability to other systems remains open to question. Here we demonstrate that given a suitable amount of background information a new approach using support vector inductive logic programming (SVILP) can be used to produce system-specific scoring functions. Inductive logic programming (ILP) learns logic-based rules for a given dataset that can be used to describe properties of each member of the set in a qualitative manner. By combining ILP with support vector machine regression, a quantitative set of rules can be obtained. SVILP has previously been used in a biological context to examine datasets containing a series of singular molecular structures and properties. Here we describe the use of SVILP to produce binding affinity predictions of a series of ligands to a particular protein. We also for the first time examine the applicability of SVILP techniques to datasets consisting of protein-ligand complexes. Our results show that SVILP performs comparably with other state-of-the-art methods on five protein-ligand systems as judged by similar cross-validated squares of their correlation coefficients. A McNemar test comparing SVILP to CoMFA and CoMSIA across the five systems indicates our method to be significantly better on one occasion. The ability to graphically display and understand the SVILP-produced rules is demonstrated and this feature of ILP can be used to derive hypothesis for future ligand design in lead optimization procedures. The approach can readily be extended to evaluate the binding affinities of a series of protein-protein complexes. (c) 2007 Wiley-Liss, Inc.

Identification of novel tyrosine kinase inhibitors for drug resistant T315I mutant BCR-ABL: a virtual screening and molecular dynamics simulations study

NASA Astrophysics Data System (ADS)

Banavath, Hemanth Naick; Sharma, Om Prakash; Kumar, Muthuvel Suresh; Baskaran, R.

2014-11-01

BCR-ABL tyrosine kinase plays a major role in the pathogenesis of chronic myeloid leukemia (CML) and is a proven target for drug development. Currently available drugs in the market are effective against CML; however, side-effects and drug-resistant mutations in BCR-ABL limit their full potential. Using high throughput virtual screening approach, we have screened several small molecule databases and docked against wild-type and drug resistant T315I mutant BCR-ABL. Drugs that are currently available, such as imatinib and ponatinib, were also docked against BCR-ABL protein to set a cutoff value for our screening. Selected lead compounds were further evaluated for chemical reactivity employing density functional theory approach, all selected ligands shows HLG value > 0.09900 and the binding free energy between protein-ligand complex interactions obtained was rescored using MM-GBSA. The selected compounds showed least ΔG score -71.53 KJ/mol to maximum -126.71 KJ/mol in both wild type and drug resistant T315I mutant BCR-ABL. Following which, the stability of the docking complexes were evaluated by molecular dynamics simulation (MD) using GROMACS4.5.5. Results uncovered seven lead molecules, designated with Drug-Bank and PubChem ids as DB07107, DB06977, ST013616, DB04200, ST007180 ST019342, and DB01172, which shows docking scores higher than imatinib and ponatinib.

ZINC: A Free Tool to Discover Chemistry for Biology

PubMed Central

2012-01-01

ZINC is a free public resource for ligand discovery. The database contains over twenty million commercially available molecules in biologically relevant representations that may be downloaded in popular ready-to-dock formats and subsets. The Web site also enables searches by structure, biological activity, physical property, vendor, catalog number, name, and CAS number. Small custom subsets may be created, edited, shared, docked, downloaded, and conveyed to a vendor for purchase. The database is maintained and curated for a high purchasing success rate and is freely available at zinc.docking.org. PMID:22587354

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

PubMed

Jończyk, Jakub; Malawska, Barbara; Bajda, Marek

2017-01-01

The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

How to deal with multiple binding poses in alchemical relative protein-ligand binding free energy calculations.

PubMed

Kaus, Joseph W; Harder, Edward; Lin, Teng; Abel, Robert; McCammon, J Andrew; Wang, Lingle

2015-06-09

Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the ligands. This improved the root-mean-square error (RMSE) for the predicted binding free energy from 1.9 kcal/mol with the original partial charges to 1.3 kcal/mol with the corrected partial charges.

How To Deal with Multiple Binding Poses in Alchemical Relative Protein–Ligand Binding Free Energy Calculations

PubMed Central

2016-01-01

Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the ligands. This improved the root-mean-square error (RMSE) for the predicted binding free energy from 1.9 kcal/mol with the original partial charges to 1.3 kcal/mol with the corrected partial charges. PMID:26085821

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina.

PubMed

Di Muzio, Elena; Toti, Daniele; Polticelli, Fabio

2017-02-01

Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina

NASA Astrophysics Data System (ADS)

Di Muzio, Elena; Toti, Daniele; Polticelli, Fabio

2017-02-01

Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

SAMPL4 & DOCK3.7: lessons for automated docking procedures

NASA Astrophysics Data System (ADS)

Coleman, Ryan G.; Sterling, Teague; Weiss, Dahlia R.

2014-03-01

The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.

Docking studies on NSAID/COX-2 isozyme complexes using Contact Statistics analysis

NASA Astrophysics Data System (ADS)

Ermondi, Giuseppe; Caron, Giulia; Lawrence, Raelene; Longo, Dario

2004-11-01

The selective inhibition of COX-2 isozymes should lead to a new generation of NSAIDs with significantly reduced side effects; e.g. celecoxib (Celebrex®) and rofecoxib (Vioxx®). To obtain inhibitors with higher selectivity it has become essential to gain additional insight into the details of the interactions between COX isozymes and NSAIDs. Although X-ray structures of COX-2 complexed with a small number of ligands are available, experimental data are missing for two well-known selective COX-2 inhibitors (rofecoxib and nimesulide) and docking results reported are controversial. We use a combination of a traditional docking procedure with a new computational tool (Contact Statistics analysis) that identifies the best orientation among a number of solutions to shed some light on this topic.

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

PubMed

Boppana, Kiran; Dubey, P K; Jagarlapudi, Sarma A R P; Vadivelan, S; Rambabu, G

2009-09-01

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

Improving database enrichment through ensemble docking

NASA Astrophysics Data System (ADS)

Rao, Shashidhar; Sanschagrin, Paul C.; Greenwood, Jeremy R.; Repasky, Matthew P.; Sherman, Woody; Farid, Ramy

2008-09-01

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.

Bis[(1S)-1 4-azanediyl-1-(9-deazaadenin-9-yl)-1 4-dideoxy-5-methylsulfanyl-D-ribitol] tetrakis(hydrochloride) monohydrate: structure DFT energy and ligand docking results of a potent methylthioadenosine phosphorylase inhibitor found in different

DOE Office of Scientific and Technical Information (OSTI.GOV)

G Gainsford; G Evans; K Johnston

2011-12-31

The title compound, abbreviated as 5'ThiomethylImmA, is a potent inhibitor of methylthioadenosine phosphorylase [Singh et al. (2004). Biochemistry, 43, 9-18]. The synchrotron study reported here shows that the hydrochloride salt crystallizes with two independent, nearly superimposable, dications as a monohydrate with formula 2C{sub 12}H{sub 19}N{sub 5}O{sub 2}S{sup 2+}{center_dot}4Cl{sup -}{center_dot}H{sub 2}O. Hydrogen bonding utilizing the H atoms of the dication is found to favor certain molecular conformations in the salt, which are significantly different from those found as bound in the enzyme. Ligand docking studies starting from either of these dications or related neutral structures successfully place the conformationally revised structuresmore » in the enzyme active site but only under particular hydrogen-bonding and molecular flexibility criteria. Density functional theory calculations verify the energy similarity of the indendent cations and confirm the significant energy cost of the required conformation change to the enzyme bound form. The results suggest the using crystallographically determined free ligand coordinates as starting parameters for modelling may have serious limitations.« less

Comparison of computational methods to model DNA minor groove binders.

PubMed

Srivastava, Hemant Kumar; Chourasia, Mukesh; Kumar, Devesh; Sastry, G Narahari

2011-03-28

There has been a profound interest in designing small molecules that interact in sequence-selective fashion with DNA minor grooves. However, most in silico approaches have not been parametrized for DNA ligand interaction. In this regard, a systematic computational analysis of 57 available PDB structures of noncovalent DNA minor groove binders has been undertaken. The study starts with a rigorous benchmarking of GOLD, GLIDE, CDOCKER, and AUTODOCK docking protocols followed by developing QSSR models and finally molecular dynamics simulations. In GOLD and GLIDE, the orientation of the best score pose is closer to the lowest rmsd pose, and the deviation in the conformation of various poses is also smaller compared to other docking protocols. Efficient QSSR models were developed with constitutional, topological, and quantum chemical descriptors on the basis of B3LYP/6-31G* optimized geometries, and with this ΔT(m) values of 46 ligands were predicted. Molecular dynamics simulations of the 14 DNA-ligand complexes with Amber 8.0 show that the complexes are stable in aqueous conditions and do not undergo noticeable fluctuations during the 5 ns production run, with respect to their initial placement in the minor groove region.

Analysis of hydrophobic interactions of antagonists with the beta2-adrenergic receptor.

PubMed

Novoseletsky, V N; Pyrkov, T V; Efremov, R G

2010-01-01

The adrenergic receptors mediate a wide variety of physiological responses, including vasodilatation and vasoconstriction, heart rate modulation, and others. Beta-adrenergic antagonists ('beta-blockers') thus constitute a widely used class of drugs in cardiovascular medicine as well as in management of anxiety, migraine, and glaucoma. The importance of the hydrophobic effect has been evidenced for a wide range of beta-blocker properties. To better understand the role of the hydrophobic effect in recognition of beta-blockers by their receptor, we carried out a molecular docking study combined with an original approach to estimate receptor-ligand hydrophobic interactions. The proposed method is based on automatic detection of molecular fragments in ligands and the analysis of their interactions with receptors separately. A series of beta-blockers, based on phenylethanolamines and phenoxypropanolamines, were docked to the beta2-adrenoceptor binding site in the crystal structure. Hydrophobic complementarity between the ligand and the receptor was calculated using the PLATINUM web-server (http://model.nmr.ru/platinum). Based on the analysis of the hydrophobic match for molecular fragments of beta-blockers, we have developed a new scoring function which efficiently predicts dissociation constant (pKd) with strong correlations (r(2) approximately 0.8) with experimental data.

Probing ligand binding modes of Mycobacterium tuberculosis MurC ligase by molecular modeling, dynamics simulation and docking.

PubMed

Anuradha, C M; Mulakayala, Chaitanya; Babajan, Banaganapalli; Naveen, M; Rajasekhar, Chikati; Kumar, Chitta Suresh

2010-01-01

Multi drug resistance capacity for Mycobacterium tuberculosis (MDR-Mtb) demands the profound need for developing new anti-tuberculosis drugs. The present work is on Mtb-MurC ligase, which is an enzyme involved in biosynthesis of peptidoglycan, a component of Mtb cell wall. In this paper the 3-D structure of Mtb-MurC has been constructed using the templates 1GQQ and 1P31. Structural refinement and energy minimization of the predicted Mtb-MurC ligase model has been carried out by molecular dynamics. The streochemical check failures in the energy minimized model have been evaluated through Procheck, Whatif ProSA, and Verify 3D. Further torsion angles for the side chains of amino acid residues of the developed model were determined using Predictor. Docking analysis of Mtb-MurC model with ligands and natural substrates enabled us to identify specific residues viz. Gly125, Lys126, Arg331, and Arg332, within the Mtb-MurC binding pocket to play an important role in ligand and substrate binding affinity and selectivity. The availability of Mtb-MurC ligase built model, together with insights gained from docking analysis will promote the rational design of potent and selective Mtb-MurC ligase inhibitors as antituberculosis therapeutics.

Molecular dynamics simulation analysis of Focal Adhesive Kinase (FAK) docked with solanesol as an anti-cancer agent

PubMed Central

Daneial, Betty; Joseph, Jacob Paul Vazhappilly; Ramakrishna, Guruprasad

2017-01-01

Focal adhesion kinase (FAK) plays a primary role in regulating the activity of many signaling molecules. Increased FAK expression has been associated in a series of cellular processes like cell migration and survival. FAK inhibition by an anti cancer agent is critical. Therefore, it is of interest to identify, modify, design, improve and develop molecules to inhibit FAK. Solanesol is known to have inhibitory activity towards FAK. However, the molecular principles of its binding with FAK is unknown. Solanesol is a highly flexible ligand (25 rotatable bonds). Hence, ligand-protein docking was completed using AutoDock with a modified contact based scoring function. The FAK-solanesol complex model was further energy minimized and simulated in GROMOS96 (53a6) force field followed by post simulation analysis such as Root mean square deviation (RMSD), root mean square fluctuations (RMSF) and solvent accessible surface area (SASA) calculations to explain solanesol-FAK binding. PMID:29081606

Molecular dynamics simulation analysis of Focal Adhesive Kinase (FAK) docked with solanesol as an anti-cancer agent.

PubMed

Daneial, Betty; Joseph, Jacob Paul Vazhappilly; Ramakrishna, Guruprasad

2017-01-01

Focal adhesion kinase (FAK) plays a primary role in regulating the activity of many signaling molecules. Increased FAK expression has been associated in a series of cellular processes like cell migration and survival. FAK inhibition by an anti cancer agent is critical. Therefore, it is of interest to identify, modify, design, improve and develop molecules to inhibit FAK. Solanesol is known to have inhibitory activity towards FAK. However, the molecular principles of its binding with FAK is unknown. Solanesol is a highly flexible ligand (25 rotatable bonds). Hence, ligand-protein docking was completed using AutoDock with a modified contact based scoring function. The FAK-solanesol complex model was further energy minimized and simulated in GROMOS96 (53a6) force field followed by post simulation analysis such as Root mean square deviation (RMSD), root mean square fluctuations (RMSF) and solvent accessible surface area (SASA) calculations to explain solanesol-FAK binding.

wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model

PubMed Central

De Paris, Renata; Frantz, Fábio A.; Norberto de Souza, Osmar; Ruiz, Duncan D. A.

2013-01-01

Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern. PMID:23691504

Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent.

PubMed

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.

Molecular dynamics approach to probe PKCβII-ligand interactions and influence of crystal water molecules on these interactions.

PubMed

Grewal, Baljinder K; Bhat, Jyotsna; Sobhia, Masilamani Elizabeth

2015-01-01

PKCβII is a potential target for therapeutic intervention against pandemic diabetic complications. Present study probes the molecular interactions of PKCβII with its clinically important ligands, viz. ruboxistaurin, enzastaurin and co-crystallized ligand, 2-methyl-1H-indol-3-yl-BIM-1. The essentials of PKCβII-ligand interaction, crystal water-induced alterations in these interactions and key interacting flexible residues are analyzed. Computational methodologies, viz. molecular docking and molecular simulation coupled with molecular mechanics-Poisson-Boltzmann surface area and generalized born surface area (MM-PB[GB]SA) are employed. The structural changes in the presence and absence of crystal water molecules in PKCβII ATP binding site residues, and its interaction with bound ligand, are identified. Difference in interaction of selective and nonselective ligand with ATP binding site residues of PKCβII is reported. The study showed that the nonbonding interactions contribute significantly in PKCβII-ligand binding and presence of crystal water molecules affects the interactions. The findings of present work may integrate the new aspects in the drug design process of PKCβII inhibitors.

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

NASA Astrophysics Data System (ADS)

Baumgartner, Matthew P.; Evans, David A.

2018-01-01

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling

PubMed Central

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T.; McDougal, Owen M.; Andersen, Timothy L.

2013-01-01

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly Graphical User Interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to: (1) conduct high throughput Inverse Virtual Screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying a receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories, and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELLER programs, and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education. PMID:23808933

Identification of the antiepileptic racetam binding site in the synaptic vesicle protein 2A by molecular dynamics and docking simulations.

PubMed

Correa-Basurto, José; Cuevas-Hernández, Roberto I; Phillips-Farfán, Bryan V; Martínez-Archundia, Marlet; Romo-Mancillas, Antonio; Ramírez-Salinas, Gema L; Pérez-González, Óscar A; Trujillo-Ferrara, José; Mendoza-Torreblanca, Julieta G

2015-01-01

Synaptic vesicle protein 2A (SV2A) is an integral membrane protein necessary for the proper function of the central nervous system and is associated to the physiopathology of epilepsy. SV2A is the molecular target of the anti-epileptic drug levetiracetam and its racetam analogs. The racetam binding site in SV2A and the non-covalent interactions between racetams and SV2A are currently unknown; therefore, an in silico study was performed to explore these issues. Since SV2A has not been structurally characterized with X-ray crystallography or nuclear magnetic resonance, a three-dimensional (3D) model was built. The model was refined by performing a molecular dynamics simulation (MDS) and the interactions of SV2A with the racetams were determined by docking studies. A reliable 3D model of SV2A was obtained; it reached structural equilibrium during the last 15 ns of the MDS (50 ns) with remaining structural motions in the N-terminus and long cytoplasmic loop. The docking studies revealed that hydrophobic interactions and hydrogen bonds participate importantly in ligand recognition within the binding site. Residues T456, S665, W666, D670 and L689 were important for racetam binding within the trans-membrane hydrophilic core of SV2A. Identifying the racetam binding site within SV2A should facilitate the synthesis of suitable radio-ligands to study treatment response and possibly epilepsy progression.

Identification of the antiepileptic racetam binding site in the synaptic vesicle protein 2A by molecular dynamics and docking simulations

PubMed Central

Correa-Basurto, José; Cuevas-Hernández, Roberto I.; Phillips-Farfán, Bryan V.; Martínez-Archundia, Marlet; Romo-Mancillas, Antonio; Ramírez-Salinas, Gema L.; Pérez-González, Óscar A.; Trujillo-Ferrara, José; Mendoza-Torreblanca, Julieta G.

2015-01-01

Synaptic vesicle protein 2A (SV2A) is an integral membrane protein necessary for the proper function of the central nervous system and is associated to the physiopathology of epilepsy. SV2A is the molecular target of the anti-epileptic drug levetiracetam and its racetam analogs. The racetam binding site in SV2A and the non-covalent interactions between racetams and SV2A are currently unknown; therefore, an in silico study was performed to explore these issues. Since SV2A has not been structurally characterized with X-ray crystallography or nuclear magnetic resonance, a three-dimensional (3D) model was built. The model was refined by performing a molecular dynamics simulation (MDS) and the interactions of SV2A with the racetams were determined by docking studies. A reliable 3D model of SV2A was obtained; it reached structural equilibrium during the last 15 ns of the MDS (50 ns) with remaining structural motions in the N-terminus and long cytoplasmic loop. The docking studies revealed that hydrophobic interactions and hydrogen bonds participate importantly in ligand recognition within the binding site. Residues T456, S665, W666, D670 and L689 were important for racetam binding within the trans-membrane hydrophilic core of SV2A. Identifying the racetam binding site within SV2A should facilitate the synthesis of suitable radio-ligands to study treatment response and possibly epilepsy progression. PMID:25914622

Medicinal plant phytochemicals and their inhibitory activities against pancreatic lipase: molecular docking combined with molecular dynamics simulation approach.

PubMed

Ahmed, Bilal; Ali Ashfaq, Usman; Usman Mirza, Muhammad

2018-05-01

Obesity is the worst health risk worldwide, which is linked to a number of diseases. Pancreatic lipase is considered as an affective cause of obesity and can be a major target for controlling the obesity. The present study was designed to find out best phytochemicals against pancreatic lipase through molecular docking combined with molecular dynamics (MD) simulation. For this purpose, a total of 3770 phytochemicals were docked against pancreatic lipase and ranked them on the basis of binding affinity. Finally, 10 molecules (Kushenol K, Rosmarinic acid, Reserpic acid, Munjistin, Leachianone G, Cephamycin C, Arctigenin, 3-O-acetylpadmatin, Geniposide and Obtusin) were selected that showed strong bonding with the pancreatic lipase. MD simulations were performed on top five compounds using AMBER16. The simulated complexes revealed stability and ligands remained inside the binding pocket. This study concluded that these finalised molecules can be used as drug candidate to control obesity.

Comparative study of the interaction of meso-tetrakis (N-para-trimethyl-anilium) porphyrin (TMAP) in its free base and Fe derivative form with oligo(dA.dT)15 and oligo(dG.dC)15.

PubMed

Bathaie, S Zahra; Ajloo, Davood; Daraie, Marzieh; Ghadamgahi, Maryam

2015-01-01

Interaction between a cationic porphyrin and its ferric derivative with oligo(dA.dT)15 and oligo(dG.dC)15 was studied by UV-vis spectroscopy, resonance light scattering (RLS), and circular dichroism (CD) at different ionic strengths; molecular docking and molecular dynamics simulation were also used for completion. Followings are the observed changes in the spectral properties of meso-tetrakis (N-para-trimethyl-anilium) porphyrin (TMAP), as a free-base porphyrin with no axial ligand, and its Fe derivative (FeTMAP) upon interaction with oligo(dA.dT)15 and oligo(dG.dC)15: (1) the substantial red shift and hypochromicity at the Soret maximum in the UV-vis spectra; (2) the increased RLS intensity by increasing the ionic strength; and (3) an intense bisignate excitonic CD signal. All of them are the reasons for TMAP and FeTMAP binding to oligo(dA.dT)15 and oligo(dG.dC)15 with the outside binding mode, accompanied by the self-stacking of the ligands along the oligonucleotide helix. The CD results demonstrated a drastic change from excitonic in monomeric behavior at higher ionic strengths, which indicates the groove binding of the ligands with oligonucleotides. Molecular docking also confirmed the groove binding mode of the ligands and estimated the binding constants and energies of the interactions. Their interaction trend was further confirmed by molecular dynamics technique and structure parameters obtained from simulation. It showed that TMAP reduced the number of intermolecular hydrogen bonds and increased the solvent accessible surface area in the oligonucleotide. The self-aggregation of ligands at lower concentrations was also confirmed.

Structural Insight Into the Role of Mutual Polymorphism and Conservatism in the Contact Zone of the NFR5-K1 Heterodimer With the Nod Factor.

PubMed

Igolkina, A A; Porozov, Yu B; Chizhevskaya, E P; Andronov, E E

2018-01-01

Sandwich-like docking configurations of the heterodimeric complex of NFR5 and K1 Vicia sativa receptor-like kinases together with the putative ligand, Nod factor (NF) of Rhizobium leguminosarum bv. viciae , were modeled and two of the most probable configurations were assessed through the analysis of the mutual polymorphisms and conservatism. We carried out this analysis based on the hypothesis that in a contact zone of two docked components (proteins or ligands) the population polymorphism or conservatism is mutual, i.e., the variation in one component has a reflected variation in the other component. The population material of 30 wild-growing V. sativa (leaf pieces) was collected from a large field (uncultivated for the past 25-years) and pooled; form this pool, 100 randomly selected cloned fragments of NFR5 gene and 100 of K1 gene were sequenced by the Sanger method. Congruence between population trees of NFR5 and K1 haplotypes allowed us to select two respective haplotypes, build their 3D structures, and perform protein-protein docking. In a separate simulation, the protein-ligand docking between NFR5 and NF was carried out. We merged the results of the two docking experiments and extracted NFR5-NF-K1 complexes, in which NF was located within the cavity between two receptors. Molecular dynamics simulations indicated two out of six complexes as stable. Regions of mutual polymorphism in the contact zone of one complex overlapped with known NF structural variations produced by R. leguminosarum bv. viciae . A total of 74% of the contact zone of another complex contained mutually polymorphic and conservative areas. Common traits of the obtained two stable structures allowed us to hypothesize the functional role of three-domain structure of plant LysM-RLKs in their heteromers.

Discovery of Selective Inhibitors of Imidazoleglycerol-Phosphate Dehydratase from Mycobacterium tuberculosis by Virtual Screening

NASA Astrophysics Data System (ADS)

Podshivalov, D.; Mandzhieva, Yu. B.; Sidorov-Biryukov, D. D.; Timofeev, V. I.; Kuranova, I. P.

2018-01-01

Bacterial imidazoleglycerol-phosphate dehydratase from Mycobacterium tuberculosis (HisB- Mt) is a convenient target for the discovery of selective inhibitors as potential antituberculosis drugs. The virtual screening was performed to find compounds suitable for the design of selective inhibitors of HisB- Mt. The positions of four ligands, which were selected based on the docking scoring function and docked to the activesite region of the enzyme, were refined by molecular dynamics simulation. The nearest environment of the ligands was determined. These compounds selectively bind to functionally essential active-site residues, thus blocking access of substrates to the active site of the enzyme, and can be used as lead compounds for the design of selective inhibitors of HisB- M.

Molecular modeling and docking studies of human 5-hydroxytryptamine 2A (5-HT2A) receptor for the identification of hotspots for ligand binding.

PubMed

Kanagarajadurai, Karuppiah; Malini, Manoharan; Bhattacharya, Aditi; Panicker, Mitradas M; Sowdhamini, Ramanathan

2009-12-01

The serotonergic system has been implicated in emotional and cognitive function. In particular, 5-HT(2A) (5-hydroxytrytamine receptor 2A) is attributed to a number of disorders like schizophrenia, depression, eating disorders and anxiety. 5-HT(2A), being a GPCR (G-protein coupled receptor), is important in the pharmaceutical industry as a proven target for these disorders. Despite their extensive clinical importance, the structural studies of this protein is lacking due to difficulties in determining its crystal structure. We have performed sequence analysis and molecular modeling of 5-HT(2A) that has revealed a set of conserved residues and motifs considered to play an important role in maintaining structural integrity and function of the receptor. The analysis also revealed a set of residues specific to the receptor which distinguishes them from other members of the subclass and their orthologs. Further, starting from the model structure of human 5-HT(2A) receptor, docking studies were attempted to envisage how it might interact with eight of its ligands (such as serotonin, dopamine, DOI, LSD, haloperidol, ketanserin, risperidone and clozapine). The binding studies of dopamine to 5-HT(2A) receptor can bring up better understanding in the etiology of a number of neurological disorders involving both these two receptors. Our sequence analysis and study of interactions of this receptor with other ligands reveal additional residue hotspots such as Asn 363 and Tyr 370. The function of these residues can be further analyzed by rational design of site-directed mutagenesis. Two distinct binding sites are identified which could play important roles in ligand binding and signaling.

Computer-Aided Drug Discovery: Molecular Docking of Diminazene Ligands to DNA Minor Groove

ERIC Educational Resources Information Center

Kholod, Yana; Hoag, Erin; Muratore, Katlynn; Kosenkov, Dmytro

2018-01-01

The reported project-based laboratory unit introduces upper-division undergraduate students to the basics of computer-aided drug discovery as a part of a computational chemistry laboratory course. The students learn to perform model binding of organic molecules (ligands) to the DNA minor groove with computer-aided drug discovery (CADD) tools. The…

A molecular description of ligand binding to the two overlapping binding pockets of the nuclear vitamin D receptor (VDR): structure-function implications

PubMed Central

Mizwicki, Mathew T.; Menegaz, Danusa; Yaghmaei, Sepideh; Henry, Helen L.; Norman, Anthony W.

2010-01-01

Molecular modeling results indicate that the VDR contains two overlapping ligand binding pockets (LBP). Differential ligand stability and fractional occupancy of the two LBP has been physiochemically linked to the regulation of VDR-dependent genomic and non-genomic cellular responses. The purpose of this report is to develop an unbiased molecular modeling protocol that serves as a good starting point in simulating the dynamic interaction between 1α,25(OH)2-vitamin D3 (1,25D3) and the VDR LBP. To accomplish this goal, the flexible docking protocol developed allowed for flexibility in the VDR ligand and the VDR atoms that form the surfaces of the VDR LBP. This approach blindly replicated the 1,25D3 conformation and side-chain dynamics observed in the VDR x-ray structure. The results are also consistent with the previously published tenants of the vitamin D sterol (VDS)-VDR conformational ensemble model. Furthermore, we used flexible docking in combination with whole cell patch clamp electrophysiology and steroid competition assays to demonstrate that a) new non-vitamin D VDR ligands show a different pocket selectivity when compared to 1,25D3 that is qualitatively consistent with their ability to stimulate chloride channels and b) a new route of ligand binding provides a novel hypothesis describing the structural nuances that underlie hypercalceamia. PMID:20398762

In silico design of fragment-based drug targeting host processing α-glucosidase i for dengue fever

NASA Astrophysics Data System (ADS)

Toepak, E. P.; Tambunan, U. S. F.

2017-02-01

Dengue is a major health problem in the tropical and sub-tropical regions. The development of antiviral that targeting dengue’s host enzyme can be more effective and efficient treatment than the viral enzyme. Host enzyme processing α-glucosidase I has an important role in the maturation process of dengue virus envelope glycoprotein. The inhibition of processing α-glucosidase I can become a promising target for dengue fever treatment. The antiviral approach using in silico fragment-based drug design can generate drug candidates with high binding affinity. In this research, 198.621 compounds were obtained from ZINC15 Biogenic Database. These compounds were screened to find the favorable fragments according to Rules of Three and pharmacological properties. The screening fragments were docked into the active site of processing α-glucosidase I. The potential fragment candidates from the molecular docking simulation were linked with castanospermine (CAST) to generate ligands with a better binding affinity. The Analysis of ligand - enzyme interaction showed ligands with code LRS 22, 28, and 47 have the better binding free energy than the standard ligand. Ligand LRS 28 (N-2-4-methyl-5-((1S,3S,6S,7R,8R,8aR)-1,6,7,8-tetrahydroxyoctahydroindolizin-3-yl) pentyl) indolin-1-yl) propionamide) itself among the other ligands has the lowest binding free energy. Pharmacological properties prediction also showed the ligands LRS 22, 28, and 47 can be promising as the dengue fever drug candidates.

Molecular dynamics simulations and docking studies on 3D models of the heterodimeric and homodimeric 5-HT(2A) receptor subtype.

PubMed

Bruno, Agostino; Beato, Claudia; Costantino, Gabriele

2011-04-01

G-protein coupled receptors may exist as functional homodimers, heterodimers and even as higher aggregates. In this work, we investigate the 5-HT(2A) receptor, which is a known target for antipsychotic drugs. Recently, 5-HT(2A) has been shown to form functional homodimers and heterodimers with the mGluR2 receptor. The objective of this study is to build up 3D models of the 5-HT(2A)/mGluR2 heterodimer and of the 5-HT(2A)-5-HT(2A) homodimer, and to evaluate the impact of the dimerization interface on the shape of the 5-HT(2A) binding pocket by using molecular dynamics simulations and docking studies. The heterodimer, homodimer and monomeric 5-HT(2A) receptors were simulated by molecular dynamics for 40 ns each. The trajectories were clustered and representative structures of six clusters for each system were generated. Inspection of the these representative structures clearly indicate an effect of the dimerization interface on the topology of the binding pocket. Docking studies allowed to generate receiver operating characteristic curves for a set of 5-HT(2A) ligands, indicating that different complexes prefer different classes of 5-HT(2A) ligands. This study clearly indicates that the presence of a dimerization interface must explicitly be considered when studying G-protein coupled receptors known to exist as dimers. Molecular dynamics simulation and cluster analysis are appropriate tools to study the phenomenon.

The Movable Type Method Applied to Protein-Ligand Binding.

PubMed

Zheng, Zheng; Ucisik, Melek N; Merz, Kenneth M

2013-12-10

Accurately computing the free energy for biological processes like protein folding or protein-ligand association remains a challenging problem. Both describing the complex intermolecular forces involved and sampling the requisite configuration space make understanding these processes innately difficult. Herein, we address the sampling problem using a novel methodology we term "movable type". Conceptually it can be understood by analogy with the evolution of printing and, hence, the name movable type. For example, a common approach to the study of protein-ligand complexation involves taking a database of intact drug-like molecules and exhaustively docking them into a binding pocket. This is reminiscent of early woodblock printing where each page had to be laboriously created prior to printing a book. However, printing evolved to an approach where a database of symbols (letters, numerals, etc.) was created and then assembled using a movable type system, which allowed for the creation of all possible combinations of symbols on a given page, thereby, revolutionizing the dissemination of knowledge. Our movable type (MT) method involves the identification of all atom pairs seen in protein-ligand complexes and then creating two databases: one with their associated pairwise distant dependent energies and another associated with the probability of how these pairs can combine in terms of bonds, angles, dihedrals and non-bonded interactions. Combining these two databases coupled with the principles of statistical mechanics allows us to accurately estimate binding free energies as well as the pose of a ligand in a receptor. This method, by its mathematical construction, samples all of configuration space of a selected region (the protein active site here) in one shot without resorting to brute force sampling schemes involving Monte Carlo, genetic algorithms or molecular dynamics simulations making the methodology extremely efficient. Importantly, this method explores the free energy surface eliminating the need to estimate the enthalpy and entropy components individually. Finally, low free energy structures can be obtained via a free energy minimization procedure yielding all low free energy poses on a given free energy surface. Besides revolutionizing the protein-ligand docking and scoring problem this approach can be utilized in a wide range of applications in computational biology which involve the computation of free energies for systems with extensive phase spaces including protein folding, protein-protein docking and protein design.

Exploring inhibitory potential of Curcumin against various cancer targets by in silico virtual screening.

PubMed

Mahajanakatti, Arpitha Badarinath; Murthy, Geetha; Sharma, Narasimha; Skariyachan, Sinosh

2014-03-01

Various types of cancer accounts for 10% of total death worldwide which necessitates better therapeutic strategies. Curcumin, a curcuminoid present in Curcuma longa, shown to exhibit antioxidant, anti-inflammatory and anticarcinogenic properties. Present study, we aimed to analyze inhibitory properties of curcumin towards virulent proteins for various cancers by computer aided virtual screening. Based on literature studies, twenty two receptors were selected which have critical virulent functions in various cancer. The binding efficiencies of curcumin towards selected targets were studied by molecular docking. Out of all, curcumin showed best results towards epidermal growth factor (EGF), virulent protein of gastric cancer; glutathione-S-transferase Pi gene (GST-PI), virulent protein for prostate cancer; platelet-derived growth factor alpha (PDGFA), virulent protein for mesothelioma and glioma compared with their natural ligands. The calculated binding energies of their docked conformations with curcumin found to be -7.59 kcal/mol, -7.98 kcal/mol and -7.93 kcal/mol respectively. Further, a comparative study was performed to screen binding efficiency of curcumin with two conventional antitumor agents, litreol and triterpene. Docking studies revealed that calculated binding energies of docked complex of litreol and EGF, GST-PI and PDGFA were found to be -5.08 kcal/mol, -3.69 kcal/mol and -1.86 kcal/mol respectively. The calculated binding energies of triterpene with EGF and PDGFA were found to be -4.02 kcal/mol and -3.11 kcal/mol respectively, whereas GST-PI showed +6.07 kcal/mol, indicate poor binding. The predicted pharmacological features of curcumin found to be better than litreol and triterpene. Our study concluded that curcumin has better interacting properties towards these cancer targets than their normal ligands and conventional antitumor agents. Our data pave insight for designing of curcumin as novel inhibitors against various types of cancer.

Identification of Biomarkers for Resistance to Fusarium oxysporum f. sp. cubense Infection and in Silico Studies in Musa paradisiaca Cultivar Puttabale through Proteomic Approach.

PubMed

Ramu, Venkatesh; Venkatarangaiah, Krishna; Krishnappa, Pradeepa; Shimoga Rajanna, Santosh Kumar; Deeplanaik, Nagaraja; Chandra Pal, Anup; Kini, Kukkundoor Ramachandra

2016-02-24

Panama wilt caused by Fusarium oxysporum f. sp. cubense (Foc) is one of the major disease constraints of banana production. Previously, we reported the disease resistance Musa paradisiaca cv. puttabale clones developed from Ethylmethanesulfonate and Foc culture filtrate against Foc inoculation. Here, the same resistant clones and susceptible clones were used for the study of protein accumulation against Foc inoculation by two-dimensional gel electrophoresis (2-DE), their expression pattern and an in silico approach. The present investigation revealed mass-spectrometry identified 16 proteins that were over accumulated and 5 proteins that were under accumulated as compared to the control. The polyphosphoinositide binding protein ssh2p (PBPssh2p) and Indoleacetic acid-induced-like (IAA) protein showed significant up-regulation and down-regulation. The docking of the pathogenesis-related protein (PR) with the fungal protein endopolygalacturonase (PG) exemplify the three ionic interactions and seven hydrophobic residues that tends to good interaction at the active site of PG with free energy of assembly dissociation (1.5 kcal/mol). The protein-ligand docking of the Peptide methionine sulfoxide reductase chloroplastic-like protein (PMSRc) with the ligand β-1,3 glucan showed minimum binding energy (-6.48 kcal/mol) and docking energy (-8.2 kcal/mol) with an interaction of nine amino-acid residues. These explorations accelerate the research in designing the host pathogen interaction studies for the better management of diseases.

Identification of Biomarkers for Resistance to Fusarium oxysporum f. sp. cubense Infection and in Silico Studies in Musa paradisiaca Cultivar Puttabale through Proteomic Approach

PubMed Central

Ramu, Venkatesh; Venkatarangaiah, Krishna; Krishnappa, Pradeepa; Shimoga Rajanna, Santosh Kumar; Deeplanaik, Nagaraja; Chandra Pal, Anup; Kini, Kukkundoor Ramachandra

2016-01-01

Panama wilt caused by Fusarium oxysporum f. sp. cubense (Foc) is one of the major disease constraints of banana production. Previously, we reported the disease resistance Musa paradisiaca cv. puttabale clones developed from Ethylmethanesulfonate and Foc culture filtrate against Foc inoculation. Here, the same resistant clones and susceptible clones were used for the study of protein accumulation against Foc inoculation by two-dimensional gel electrophoresis (2-DE), their expression pattern and an in silico approach. The present investigation revealed mass-spectrometry identified 16 proteins that were over accumulated and 5 proteins that were under accumulated as compared to the control. The polyphosphoinositide binding protein ssh2p (PBPssh2p) and Indoleacetic acid-induced-like (IAA) protein showed significant up-regulation and down-regulation. The docking of the pathogenesis-related protein (PR) with the fungal protein endopolygalacturonase (PG) exemplify the three ionic interactions and seven hydrophobic residues that tends to good interaction at the active site of PG with free energy of assembly dissociation (1.5 kcal/mol). The protein-ligand docking of the Peptide methionine sulfoxide reductase chloroplastic-like protein (PMSRc) with the ligand β-1,3 glucan showed minimum binding energy (−6.48 kcal/mol) and docking energy (−8.2 kcal/mol) with an interaction of nine amino-acid residues. These explorations accelerate the research in designing the host pathogen interaction studies for the better management of diseases. PMID:28248219

Binding site exploration of CCR5 using in silico methodologies: a 3D-QSAR approach.

PubMed

Gadhe, Changdev G; Kothandan, Gugan; Cho, Seung Joo

2013-01-01

Chemokine receptor 5 (CCR5) is an important receptor used by human immunodeficiency virus type 1 (HIV-1) to gain viral entry into host cell. In this study, we used a combined approach of comparative modeling, molecular docking, and three dimensional quantitative structure activity relationship (3D-QSAR) analyses to elucidate detailed interaction of CCR5 with their inhibitors. Docking study of the most potent inhibitor from a series of compounds was done to derive the bioactive conformation. Parameters such as random selection, rational selection, different charges and grid spacing were utilized in the model development to check their performance on the model predictivity. Final comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were chosen based on the rational selection method, Gasteiger-Hückel charges and a grid spacing of 0.5 Å. Rational model for CoMFA (q(2) = 0.722, r(2) = 0.884, Q(2) = 0.669) and CoMSIA (q(2) = 0.712, r(2) = 0.825, Q(2) = 0.522) was obtained with good statistics. Mapping of contour maps onto CCR5 interface led us to better understand of the ligand-protein interaction. Docking analysis revealed that the Glu283 is crucial for interaction. Two new amino acid residues, Tyr89 and Thr167 were identified as important in ligand-protein interaction. No site directed mutagenesis studies on these residues have been reported.

Virtual Dual inhibition of COX-2 / 5-LOX enzymes based on binding properties of alpha-amyrins, the anti-inflammatory compound as a promising anti-cancer drug.

PubMed

Ranjbar, Mohammad Mehdi; Assadolahi, Vahideh; Yazdani, Mohsen; Nikaein, Donya; Rashidieh, Behnam

2016-01-01

Hydro-alcoholic fruit extract of Cordia myxa was considerably effective on curing acute inflammation in mouse model. Previous studies suggested significant anti-inflammatory activities as well as potential anticancer agent of α-amyrins in seeds. Inhibition of Cyclooxygenase-2 (COX-2) and 5-Lipooxygenase (5-LOX) is significant in cancer prevention and therapeutics although this inhibition with chemo-drugs has its own side-effects. It is shown that these enzymes pathways are related to several cancers including colon, breast and lung cancer. This study was conducted based on Cordia species' α-amyrins as a safer natural anti-cancer compound for inhibition of COX-2 and 5-LOX enzymes by molecular docking. The X-ray crystal structure of COX2 / 5-LOX enzymes and α-amyrins was retrieved and energetically minimized respectively. The binding site and surface of enzymes were detected. Docking studies were performed by AutoDock 4.2 using Lamarckian genetic algorithm (LGA). Finally drug likeness, molecular pharmacokinetic properties and toxicity of α-amyrins was calculated. Molecular Docking revealed hydrogen and hydrophobic interactions between α-amyrins with both active sites of COX-2 and 5-LOX enzymes. Interestingly, it covalently bonded to Fe cofactor of 5-LOX enzyme and chelated this molecule. Base on binding energies (∆G) α-amyrin has more inhibitory effects on 5-LOX (-10.45 Kcal/mol) than COX-2 (-8.02 Kcal/mol). Analysis of molecular pharmacokinetic parameters suggested that α-amyrins complied with most sets of Lipinski's rules, and so it could be a suitable ligand for docking studies. Eventually, bioactivity score showed α-amyrins possess considerable biological activities as nuclear receptor, enzyme inhibitor, GPCR and protease inhibitor ligand. These results clearly demonstrate that α-amyrins could act as potential highly selective COX-/5-LOX inhibitor. Also, it is a safe compound in comparison with classical non-steroidal anti-inflammatory drugs (NSAIDs) that are known as cancer preventive agents, since it is free of side effects on human body and it can be a promising drug for cancer therapeutics.

Virtual Dual inhibition of COX-2 / 5-LOX enzymes based on binding properties of alpha-amyrins, the anti-inflammatory compound as a promising anti-cancer drug

PubMed Central

Ranjbar, Mohammad Mehdi; Assadolahi, Vahideh; Yazdani, Mohsen; Nikaein, Donya; Rashidieh, Behnam

2016-01-01

Hydro-alcoholic fruit extract of Cordia myxa was considerably effective on curing acute inflammation in mouse model. Previous studies suggested significant anti-inflammatory activities as well as potential anticancer agent of α-amyrins in seeds. Inhibition of Cyclooxygenase-2 (COX-2) and 5-Lipooxygenase (5-LOX) is significant in cancer prevention and therapeutics although this inhibition with chemo-drugs has its own side-effects. It is shown that these enzymes pathways are related to several cancers including colon, breast and lung cancer. This study was conducted based on Cordia species' α-amyrins as a safer natural anti-cancer compound for inhibition of COX-2 and 5-LOX enzymes by molecular docking. The X-ray crystal structure of COX2 / 5-LOX enzymes and α-amyrins was retrieved and energetically minimized respectively. The binding site and surface of enzymes were detected. Docking studies were performed by AutoDock 4.2 using Lamarckian genetic algorithm (LGA). Finally drug likeness, molecular pharmacokinetic properties and toxicity of α-amyrins was calculated. Molecular Docking revealed hydrogen and hydrophobic interactions between α-amyrins with both active sites of COX-2 and 5-LOX enzymes. Interestingly, it covalently bonded to Fe cofactor of 5-LOX enzyme and chelated this molecule. Base on binding energies (∆G) α-amyrin has more inhibitory effects on 5-LOX (-10.45 Kcal/mol) than COX-2 (-8.02 Kcal/mol). Analysis of molecular pharmacokinetic parameters suggested that α-amyrins complied with most sets of Lipinski's rules, and so it could be a suitable ligand for docking studies. Eventually, bioactivity score showed α-amyrins possess considerable biological activities as nuclear receptor, enzyme inhibitor, GPCR and protease inhibitor ligand. These results clearly demonstrate that α-amyrins could act as potential highly selective COX-/5-LOX inhibitor. Also, it is a safe compound in comparison with classical non-steroidal anti-inflammatory drugs (NSAIDs) that are known as cancer preventive agents, since it is free of side effects on human body and it can be a promising drug for cancer therapeutics. PMID:27231478

Application of a post-docking procedure based on MM-PBSA and MM-GBSA on single and multiple protein conformations.

PubMed

Sgobba, Miriam; Caporuscio, Fabiana; Anighoro, Andrew; Portioli, Corinne; Rastelli, Giulio

2012-12-01

In the last decades, molecular docking has emerged as an increasingly useful tool in the modern drug discovery process, but it still needs to overcome many hurdles and limitations such as how to account for protein flexibility and poor scoring function performance. For this reason, it has been recognized that in many cases docking results need to be post-processed to achieve a significant agreement with experimental activities. In this study, we have evaluated the performance of MM-PBSA and MM-GBSA scoring functions, implemented in our post-docking procedure BEAR, in rescoring docking solutions. For the first time, the performance of this post-docking procedure has been evaluated on six different biological targets (namely estrogen receptor, thymidine kinase, factor Xa, adenosine deaminase, aldose reductase, and enoyl ACP reductase) by using i) both a single and a multiple protein conformation approach, and ii) two different software, namely AutoDock and LibDock. The assessment has been based on two of the most important criteria for the evaluation of docking methods, i.e., the ability of known ligands to enrich the top positions of a ranked database with respect to molecular decoys, and the consistency of the docking poses with crystallographic binding modes. We found that, in many cases, MM-PBSA and MM-GBSA are able to yield higher enrichment factors compared to those obtained with the docking scoring functions alone. However, for only a minority of the cases, the enrichment factors obtained by using multiple protein conformations were higher than those obtained by using only one protein conformation. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Theoretical study of zeatin - A plant hormone and potential drug for neural diseases - On the basis of DFT, MP2 and target docking

NASA Astrophysics Data System (ADS)

Liu, Xueping; Bereźniak, Tomasz; Panek, Jarosław Jan; Jezierska-Mazzarello, Aneta

2013-02-01

Zeatin, a cytokinin of the adenine family, originally isolated from Zea mays L., exhibits also bioeffects towards human cells: it is a potent acetylcholinesterase inhibitor and can potentially inhibit amyloid β-protein formation. The role of zeatin in neural disease treatment is yet to be established. This computational study describes a hierarchy of interactions between zeatin and a receptor, a protein from the nodulin family. DFT in hybrid and dispersion-corrected form as well as MP2 approaches were used to derive interaction energies. Docking procedure was employed to investigate the role of selected interaction for anchoring the ligand.

Rapid and accurate prediction and scoring of water molecules in protein binding sites.

PubMed

Ross, Gregory A; Morris, Garrett M; Biggin, Philip C

2012-01-01

Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

Dynamic undocking and the quasi-bound state as tools for drug discovery

NASA Astrophysics Data System (ADS)

Ruiz-Carmona, Sergio; Schmidtke, Peter; Luque, F. Javier; Baker, Lisa; Matassova, Natalia; Davis, Ben; Roughley, Stephen; Murray, James; Hubbard, Rod; Barril, Xavier

2017-03-01

There is a pressing need for new technologies that improve the efficacy and efficiency of drug discovery. Structure-based methods have contributed towards this goal but they focus on predicting the binding affinity of protein-ligand complexes, which is notoriously difficult. We adopt an alternative approach that evaluates structural, rather than thermodynamic, stability. As bioactive molecules present a static binding mode, we devised dynamic undocking (DUck), a fast computational method to calculate the work necessary to reach a quasi-bound state at which the ligand has just broken the most important native contact with the receptor. This non-equilibrium property is surprisingly effective in virtual screening because true ligands form more-resilient interactions than decoys. Notably, DUck is orthogonal to docking and other 'thermodynamic' methods. We demonstrate the potential of the docking-undocking combination in a fragment screening against the molecular chaperone and oncology target Hsp90, for which we obtain novel chemotypes and a hit rate that approaches 40%.

Modeling and Proposed Molecular Mechanism of Hydroxyurea Through Docking and Molecular Dynamic Simulation to Curtail the Action of Ribonucleotide Reductase.

PubMed

Iman, Maryam; Khansefid, Zeynab; Davood, Asghar

2016-01-01

Ribonucleotide Reductase (RNR) is an important anticancer chemotherapy target. It has main key role in DNA synthesis and cell growth. Therefore several RNR inhibitors, such as hydroxyurea, have entered the clinical trials. Based on our proposed mechanism, radical site of RNR protein reacts with hydroxyurea in which hydroxyurea is converted into its oxidized form compound III, and whereby the tyrosyl radical is converted into a normal tyrosine residue. In this study, docking and molecular dynamics simulations were used for proposed molecular mechanism of hydroxyurea in RNR inhibition as anticancer agent. The binding affinity of hydroxyurea and compound III to RNR was studied by docking method. The docking study was performed for the crystal structure of human RNR with the radical scavenger Hydroxyurea and its oxidized form to inhibit the human RNR. hydroxyurea and compound III bind at the active site with Tyr-176, which are essential for free radical formation. This helps to understand the functional aspects and also aids in the development of novel inhibitors for the human RNR2. To confirm the binding mode of inhibitors, the molecular dynamics (MD) simulations were performed using GROMACS 4.5.5, based upon the docked conformation of inhibitors. Both of the studied compounds stayed in the active site. The results of MD simulations confirmed the binding mode of ligands, accuracy of docking and the reliability of active conformations which were obtained by AutoDock. MD studies confirm our proposed mechanism in which compound III reacts with the active site residues specially Tyr-176, and inhibits the radical generation and subsequently inhibits the RNR enzyme.

Secondary metabolites of Cynodon dactylon as an antagonist to angiotensin II type1 receptor: Novel in silico drug targeting approach for diabetic retinopathy

PubMed Central

Jananie, R. K.; Priya, V.; Vijayalakshmi, K.

2012-01-01

Objectives: To study the ability of the secondary metabolites of Cynodon dactylon to serve as an antagonist to angiotensin II type 1 receptor (AT1); activation of this receptor plays a vital role in diabetic retinopathy (DR). Materials and Methods: In silico methods are mainly harnessed to reduce time, cost and risk associated with drug discovery. Twenty-four compounds were identified as the secondary metabolites of hydroalcoholic extract of C. dactylon using the GCMS technique. These were considered as the ligands or inhibitors that would serve as an antagonist to the AT1. The ACD/Chemsketch tool was used to generate 3D structures of the ligands. A molecular file format converter tool was used to convert the generated data to the PDB format (Protein Data Bank) and was used for docking studies. The AT1 structure was retrieved from the Swissprot data base and PDB and visualized using the Rasmol tool. Domain analysis was carried from the Pfam data base; following this, the active site of the target protein was identified using a Q-site finder tool. The ability of the ligands to bind with the active site of AT1 was studied using the Autodocking tool. The docking results were analyzed using the WebLab viewer tool. Results: Sixteen ligands showed effective binding with the target protein; diazoprogesteron, didodecyl phthalate, and 9,12-octadecadienoyl chloride (z,z) may be considered as compounds that could be used to bind with the active site sequence of AT1. Conclusions: The present study shows that the metabolites of C. dactylon could serve as a natural antagonist to AT1 that could be used to treat diabetic retinopathy. PMID:22368412

Structural Changes Due to Antagonist Binding in Ligand Binding Pocket of Androgen Receptor Elucidated Through Molecular Dynamics Simulations.

PubMed

Sakkiah, Sugunadevi; Kusko, Rebecca; Pan, Bohu; Guo, Wenjing; Ge, Weigong; Tong, Weida; Hong, Huixiao

2018-01-01

When a small molecule binds to the androgen receptor (AR), a conformational change can occur which impacts subsequent binding of co-regulator proteins and DNA. In order to accurately study this mechanism, the scientific community needs a crystal structure of the Wild type AR (WT-AR) ligand binding domain, bound with antagonist. To address this open need, we leveraged molecular docking and molecular dynamics (MD) simulations to construct a structure of the WT-AR ligand binding domain bound with antagonist bicalutamide. The structure of mutant AR (Mut-AR) bound with this same antagonist informed this study. After molecular docking analysis pinpointed the suitable binding orientation of a ligand in AR, the model was further optimized through 1 μs of MD simulations. Using this approach, three molecular systems were studied: (1) WT-AR bound with agonist R1881, (2) WT-AR bound with antagonist bicalutamide, and (3) Mut-AR bound with bicalutamide. Our structures were very similar to the experimentally determined structures of both WT-AR with R1881 and Mut-AR with bicalutamide, demonstrating the trustworthiness of this approach. In our model, when WT-AR is bound with bicalutamide, Val716/Lys720/Gln733, or Met734/Gln738/Glu897 move and thus disturb the positive and negative charge clumps of the AF2 site. This disruption of the AF2 site is key for understanding the impact of antagonist binding on subsequent co-regulator binding. In conclusion, the antagonist induced structural changes in WT-AR detailed in this study will enable further AR research and will facilitate AR targeting drug discovery.

Modeling the inhibition of quadruple mutant Plasmodium falciparum dihydrofolate reductase by pyrimethamine derivatives

NASA Astrophysics Data System (ADS)

Fogel, Gary B.; Cheung, Mars; Pittman, Eric; Hecht, David

2008-01-01

Modeling studies were performed on known inhibitors of the quadruple mutant Plasmodium falciparum dihydrofolate reductase (DHFR). GOLD was used to dock 32 pyrimethamine derivatives into the active site of DHFR obtained from the x-ray crystal structure 1J3K.pdb. Several scoring functions were evaluated and the Molegro Protein-Ligand Interaction Score was determined to have one of the best correlation to experimental p K i . In conjunction with Protein-Ligand Interaction scores, predicted binding modes and key protein-ligand interactions were evaluated and analyzed in order to develop criteria for selecting compounds having a greater chance of activity versus resistant strains of Plasmodium falciparum. This methodology will be used in future studies for selection of compounds for focused screening libraries.

Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xiaolin; Ye, Li; Wang, Xiaoxiang

2012-12-15

Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q{sup 2}) was 0.571 andmore » non-cross-validation correlation coefficient (r{sup 2}) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results. -- Highlights: ► The thyroid hormone activities of HO-PBDEs were studied by 3D-QSAR. ► The binding modes between HO-PBDEs and TRβ were explored. ► 3D-QSAR, molecular docking, and molecular dynamics (MD) methods were performed.« less

Mapping of ligand-binding cavities in proteins.

PubMed

Andersson, C David; Chen, Brian Y; Linusson, Anna

2010-05-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterize and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity, and charge). This approach can provide valuable information on the similarities and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterization and mapping of "orphan structures", selection of protein structures for docking studies in structure-based design, and identification of proteins for selectivity screens in drug design programs. 2009 Wiley-Liss, Inc.

Mapping of Ligand-Binding Cavities in Proteins

PubMed Central

Andersson, C. David; Chen, Brian Y.; Linusson, Anna

2010-01-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterise and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity and charge). This approach can provide valuable information on the similarities, and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterisation and mapping of “orphan structures”, selection of protein structures for docking studies in structure-based design and identification of proteins for selectivity screens in drug design programs. PMID:20034113

An in silico high-throughput screen identifies potential selective inhibitors for the non-receptor tyrosine kinase Pyk2

PubMed Central

Meirson, Tomer; Samson, Abraham O; Gil-Henn, Hava

2017-01-01

The non-receptor tyrosine kinase proline-rich tyrosine kinase 2 (Pyk2) is a critical mediator of signaling from cell surface growth factor and adhesion receptors to cell migration, proliferation, and survival. Emerging evidence indicates that signaling by Pyk2 regulates hematopoietic cell response, bone density, neuronal degeneration, angiogenesis, and cancer. These physiological and pathological roles of Pyk2 warrant it as a valuable therapeutic target for invasive cancers, osteoporosis, Alzheimer’s disease, and inflammatory cellular response. Despite its potential as a therapeutic target, no potent and selective inhibitor of Pyk2 is available at present. As a first step toward discovering specific potential inhibitors of Pyk2, we used an in silico high-throughput screening approach. A virtual library of six million lead-like compounds was docked against four different high-resolution Pyk2 kinase domain crystal structures and further selected for predicted potency and ligand efficiency. Ligand selectivity for Pyk2 over focal adhesion kinase (FAK) was evaluated by comparative docking of ligands and measurement of binding free energy so as to obtain 40 potential candidates. Finally, the structural flexibility of a subset of the docking complexes was evaluated by molecular dynamics simulation, followed by intermolecular interaction analysis. These compounds may be considered as promising leads for further development of highly selective Pyk2 inhibitors. PMID:28572720

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies

PubMed Central

Son, Minky; Park, Chanin; Kim, Hyong-Ha; Suh, Jung-Keun

2017-01-01

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1. PMID:29312992

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies.

PubMed

Rampogu, Shailima; Son, Minky; Park, Chanin; Kim, Hyong-Ha; Suh, Jung-Keun; Lee, Keun Woo

2017-01-01

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1.

Performance of MDockPP in CAPRI rounds 28-29 and 31-35 including the prediction of water-mediated interactions.

PubMed

Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Ma, Zhiwei; Grinter, Sam Z; Zou, Xiaoqin

2017-03-01

Protein-protein interactions are either through direct contacts between two binding partners or mediated by structural waters. Both direct contacts and water-mediated interactions are crucial to the formation of a protein-protein complex. During the recent CAPRI rounds, a novel parallel searching strategy for predicting water-mediated interactions is introduced into our protein-protein docking method, MDockPP. Briefly, a FFT-based docking algorithm is employed in generating putative binding modes, and an iteratively derived statistical potential-based scoring function, ITScorePP, in conjunction with biological information is used to assess and rank the binding modes. Up to 10 binding modes are selected as the initial protein-protein complex structures for MD simulations in explicit solvent. Water molecules near the interface are clustered based on the snapshots extracted from independent equilibrated trajectories. Then, protein-ligand docking is employed for a parallel search for water molecules near the protein-protein interface. The water molecules generated by ligand docking and the clustered water molecules generated by MD simulations are merged, referred to as the predicted structural water molecules. Here, we report the performance of this protocol for CAPRI rounds 28-29 and 31-35 containing 20 valid docking targets and 11 scoring targets. In the docking experiments, we predicted correct binding modes for nine targets, including one high-accuracy, two medium-accuracy, and six acceptable predictions. Regarding the two targets for the prediction of water-mediated interactions, we achieved models ranked as "excellent" in accordance with the CAPRI evaluation criteria; one of these two targets is considered as a difficult target for structural water prediction. Proteins 2017; 85:424-434. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Study on the interaction of artificial and natural food colorants with human serum albumin: A computational point of view.

PubMed

Masone, Diego; Chanforan, Céline

2015-06-01

Due to the high amount of artificial food colorants present in infants' diets, their adverse effects have been of major concern among the literature. Artificial food colorants have been suggested to affect children's behavior, being hyperactivity the most common disorder. In this study we compare binding affinities of a group of artificial colorants (sunset yellow, quinoline yellow, carmoisine, allura red and tartrazine) and their natural industrial equivalents (carminic acid, curcumin, peonidin-3-glucoside, cyanidin-3-glucoside) to human serum albumin (HSA) by a docking approach and further refinement through atomistic molecular dynamics simulations. Due to the protein-ligand conformational interface complexity, we used collective variable driven molecular dynamics to refine docking predictions and to score them according to a hydrogen-bond criterion. With this protocol, we were able to rank ligand affinities to HSA and to compare between the studied natural and artificial food additives. Our results show that the five artificial colorants studied bind better to HSA than their equivalent natural options, in terms of their H-bonding network, supporting the hypothesis of their potential risk to human health. Copyright © 2015 Elsevier Ltd. All rights reserved.

In silico modelling and molecular dynamics simulation studies of thiazolidine based PTP1B inhibitors.

PubMed

Mahapatra, Manoj Kumar; Bera, Krishnendu; Singh, Durg Vijay; Kumar, Rajnish; Kumar, Manoj

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) has been identified as a negative regulator of insulin and leptin signalling pathway; hence, it can be considered as a new therapeutic target of intervention for the treatment of type 2 diabetes. Inhibition of this molecular target takes care of both diabetes and obesity, i.e. diabestiy. In order to get more information on identification and optimization of lead, pharmacophore modelling, atom-based 3D QSAR, docking and molecular dynamics studies were carried out on a set of ligands containing thiazolidine scaffold. A six-point pharmacophore model consisting of three hydrogen bond acceptor (A), one negative ionic (N) and two aromatic rings (R) with discrete geometries as pharmacophoric features were developed for a predictive 3D QSAR model. The probable binding conformation of the ligands within the active site was studied through molecular docking. The molecular interactions and the structural features responsible for PTP1B inhibition and selectivity were further supplemented by molecular dynamics simulation study for a time scale of 30 ns. The present investigation has identified some of the indispensible structural features of thiazolidine analogues which can further be explored to optimize PTP1B inhibitors.

Multilevel Parallelization of AutoDock 4.2.

PubMed

Norgan, Andrew P; Coffman, Paul K; Kocher, Jean-Pierre A; Katzmann, David J; Sosa, Carlos P

2011-04-28

Virtual (computational) screening is an increasingly important tool for drug discovery. AutoDock is a popular open-source application for performing molecular docking, the prediction of ligand-receptor interactions. AutoDock is a serial application, though several previous efforts have parallelized various aspects of the program. In this paper, we report on a multi-level parallelization of AutoDock 4.2 (mpAD4). Using MPI and OpenMP, AutoDock 4.2 was parallelized for use on MPI-enabled systems and to multithread the execution of individual docking jobs. In addition, code was implemented to reduce input/output (I/O) traffic by reusing grid maps at each node from docking to docking. Performance of mpAD4 was examined on two multiprocessor computers. Using MPI with OpenMP multithreading, mpAD4 scales with near linearity on the multiprocessor systems tested. In situations where I/O is limiting, reuse of grid maps reduces both system I/O and overall screening time. Multithreading of AutoDock's Lamarkian Genetic Algorithm with OpenMP increases the speed of execution of individual docking jobs, and when combined with MPI parallelization can significantly reduce the execution time of virtual screens. This work is significant in that mpAD4 speeds the execution of certain molecular docking workloads and allows the user to optimize the degree of system-level (MPI) and node-level (OpenMP) parallelization to best fit both workloads and computational resources.

Discovery of CREBBP Bromodomain Inhibitors by High-Throughput Docking and Hit Optimization Guided by Molecular Dynamics.

PubMed

Xu, Min; Unzue, Andrea; Dong, Jing; Spiliotopoulos, Dimitrios; Nevado, Cristina; Caflisch, Amedeo

2016-02-25

We have identified two chemotypes of CREBBP bromodomain ligands by fragment-based high-throughput docking. Only 17 molecules from the original library of two-million compounds were tested in vitro. Optimization of the two low-micromolar hits, the 4-acylpyrrole 1 and acylbenzene 9, was driven by molecular dynamics results which suggested improvement of the polar interactions with the Arg1173 side chain at the rim of the binding site. The synthesis of only two derivatives of 1 yielded the 4-acylpyrrole 6 which shows a single-digit micromolar affinity for the CREBBP bromodomain and a ligand efficiency of 0.34 kcal/mol per non-hydrogen atom. Optimization of the acylbenzene hit 9 resulted in a series of derivatives with nanomolar potencies, good ligand efficiency and selectivity (see Unzue, A.; Xu, M.; Dong, J.; Wiedmer, L.; Spiliotopoulos, D.; Caflisch, A.; Nevado, C.Fragment-Based Design of Selective Nanomolar Ligands of the CREBBP Bromodomain. J. Med. Chem. 2015, DOI: 10.1021/acs.jmedchem.5b00172). The in silico predicted binding mode of the acylbenzene derivative 10 was validated by solving the structure of the complex with the CREBBP bromodomain.

Molecular docking, molecular modeling, and molecular dynamics studies of azaisoflavone as dual COX-2 inhibitors and TP receptor antagonists.

PubMed

Hadianawala, Murtuza; Mahapatra, Amarjyoti Das; Yadav, Jitender K; Datta, Bhaskar

2018-02-26

Designed multi-target ligand (DML) is an emerging strategy for the development of new drugs and involves the engagement of multiple targets with the same moiety. In the context of NSAIDs it has been suggested that targeting the thromboxane prostanoid (TP) receptor along with cyclooxygenase-2 (COX-2) may help to overcome cardiovascular (CVS) complications associated with COXIBs. In the present work, azaisoflavones were studied for their COX-2 and TP receptor binding activities using structure based drug design (SBDD) techniques. Flavonoids were selected as a starting point based on their known COX-2 inhibitory and TP receptor antagonist activity. Iterative design and docking studies resulted in the evolution of a new class scaffold replacing the benzopyran-4-one ring of flavonoids with quinolin-4-one. The docking and binding parameters of these new compounds are found to be promising in comparison to those of selective COX-2 inhibitors, such as SC-558 and celecoxib. Owing to the lack of structural information, a model for the TP receptor was generated using a threading base alignment method with loop optimization performed using an ab initio method. The model generated was validated against known antagonists for TP receptor using docking/MMGBSA. Finally, the molecules that were designed for selective COX-2 inhibition were docked into the active site of the TP receptor. Iterative structural modifications and docking on these molecules generated a series which displays optimum docking scores and binding interaction for both targets. Molecular dynamics studies on a known TP receptor antagonist and a designed molecule show that both molecules remain in contact with protein throughout the simulation and interact in similar binding modes. Graphical abstract ᅟ.

Evaluating the binding efficiency of pheromone binding protein with its natural ligand using molecular docking and fluorescence analysis

NASA Astrophysics Data System (ADS)

Ilayaraja, Renganathan; Rajkumar, Ramalingam; Rajesh, Durairaj; Muralidharan, Arumugam Ramachandran; Padmanabhan, Parasuraman; Archunan, Govindaraju

2014-06-01

Chemosignals play a crucial role in social and sexual communication among inter- and intra-species. Chemical cues are bound with protein that is present in the pheromones irrespective of sex are commonly called as pheromone binding protein (PBP). In rats, the pheromone compounds are bound with low molecular lipocalin protein α2u-globulin (α2u). We reported farnesol is a natural endogenous ligand (compound) present in rat preputial gland as a bound volatile compound. In the present study, an attempt has been made through computational method to evaluating the binding efficiency of α2u with the natural ligand (farnesol) and standard fluorescent molecule (2-naphthol). The docking analysis revealed that the binding energy of farnesol and 2-naphthol was almost equal and likely to share some binding pocket of protein. Further, to extrapolate the results generated through computational approach, the α2u protein was purified and subjected to fluorescence titration and binding assay. The results showed that the farnesol is replaced by 2-naphthol with high hydrophobicity of TYR120 in binding sites of α2u providing an acceptable dissociation constant indicating the binding efficiency of α2u. The obtained results are in corroboration with the data made through computational approach.

Using physics-based pose predictions and free energy perturbation calculations to predict binding poses and relative binding affinities for FXR ligands in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Athanasiou, Christina; Vasilakaki, Sofia; Dellis, Dimitris; Cournia, Zoe

2018-01-01

Computer-aided drug design has become an integral part of drug discovery and development in the pharmaceutical and biotechnology industry, and is nowadays extensively used in the lead identification and lead optimization phases. The drug design data resource (D3R) organizes challenges against blinded experimental data to prospectively test computational methodologies as an opportunity for improved methods and algorithms to emerge. We participated in Grand Challenge 2 to predict the crystallographic poses of 36 Farnesoid X Receptor (FXR)-bound ligands and the relative binding affinities for two designated subsets of 18 and 15 FXR-bound ligands. Here, we present our methodology for pose and affinity predictions and its evaluation after the release of the experimental data. For predicting the crystallographic poses, we used docking and physics-based pose prediction methods guided by the binding poses of native ligands. For FXR ligands with known chemotypes in the PDB, we accurately predicted their binding modes, while for those with unknown chemotypes the predictions were more challenging. Our group ranked #1st (based on the median RMSD) out of 46 groups, which submitted complete entries for the binding pose prediction challenge. For the relative binding affinity prediction challenge, we performed free energy perturbation (FEP) calculations coupled with molecular dynamics (MD) simulations. FEP/MD calculations displayed a high success rate in identifying compounds with better or worse binding affinity than the reference (parent) compound. Our studies suggest that when ligands with chemical precedent are available in the literature, binding pose predictions using docking and physics-based methods are reliable; however, predictions are challenging for ligands with completely unknown chemotypes. We also show that FEP/MD calculations hold predictive value and can nowadays be used in a high throughput mode in a lead optimization project provided that crystal structures of sufficiently high quality are available.

GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking.

PubMed

Heo, Lim; Lee, Hasup; Seok, Chaok

2016-08-18

Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex.

The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators

NASA Astrophysics Data System (ADS)

Taha, Mutasem O.; Habash, Maha; Khanfar, Mohammad A.

2014-05-01

Glucokinase (GK) is involved in normal glucose homeostasis and therefore it is a valid target for drug design and discovery efforts. GK activators (GKAs) have excellent potential as treatments of hyperglycemia and diabetes. The combined recent interest in GKAs, together with docking limitations and shortages of docking validation methods prompted us to use our new 3D-QSAR analysis, namely, docking-based comparative intermolecular contacts analysis (dbCICA), to validate docking configurations performed on a group of GKAs within GK binding site. dbCICA assesses the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models were validated by receiver operating characteristic curve analysis and comparative molecular field analysis. dbCICA models were also converted into valid pharmacophores that were used as search queries to mine 3D structural databases for new GKAs. The search yielded several potent bioactivators that experimentally increased GK bioactivity up to 7.5-folds at 10 μM.

Empirical scoring functions for advanced protein-ligand docking with PLANTS.

PubMed

Korb, Oliver; Stützle, Thomas; Exner, Thomas E

2009-01-01

In this paper we present two empirical scoring functions, PLANTS(CHEMPLP) and PLANTS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). They are related, regarding their functional form, to parts of already published scoring functions and force fields. The parametrization procedure described here was able to identify several parameter settings showing an excellent performance for the task of pose prediction on two test sets comprising 298 complexes in total. Up to 87% of the complexes of the Astex diverse set and 77% of the CCDC/Astex clean listnc (noncovalently bound complexes of the clean list) could be reproduced with root-mean-square deviations of less than 2 A with respect to the experimentally determined structures. A comparison with the state-of-the-art docking tool GOLD clearly shows that this is, especially for the druglike Astex diverse set, an improvement in pose prediction performance. Additionally, optimized parameter settings for the search algorithm were identified, which can be used to balance pose prediction reliability and search speed.

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure based modeling methods

PubMed Central

Politi, Regina; Rusyn, Ivan; Tropsha, Alexander

2016-01-01

The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure-Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R2=0.55 and CCR=0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R2=0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. PMID:25058446

The binding domain of the HMGB1 inhibitor carbenoxolone: Theory and experiment

NASA Astrophysics Data System (ADS)

Mollica, Luca; Curioni, Alessandro; Andreoni, Wanda; Bianchi, Marco E.; Musco, Giovanna

2008-05-01

We present a combined computational and experimental study of the interaction of the Box A of the HMGB1 protein and carbenoxolone, an inhibitor of its pro-inflammatory activity. The computational approach consists of classical molecular dynamics (MD) simulations based on the GROMOS force field with quantum-refined (QRFF) atomic charges for the ligand. Experimental data consist of fluorescence intensities, chemical shift displacements, saturation transfer differences and intermolecular Nuclear Overhauser Enhancement signals. Good agreement is found between observations and the conformation of the ligand-protein complex resulting from QRFF-MD. In contrast, simple docking procedures and MD based on the unrefined force field provide models inconsistent with experiment. The ligand-protein binding is dominated by non-directional interactions.

Protein-ligand docking using FFT based sampling: D3R case study.

PubMed

Padhorny, Dzmitry; Hall, David R; Mirzaei, Hanieh; Mamonov, Artem B; Moghadasi, Mohammad; Alekseenko, Andrey; Beglov, Dmitri; Kozakov, Dima

2018-01-01

Fast Fourier transform (FFT) based approaches have been successful in application to modeling of relatively rigid protein-protein complexes. Recently, we have been able to adapt the FFT methodology to treatment of flexible protein-peptide interactions. Here, we report our latest attempt to expand the capabilities of the FFT approach to treatment of flexible protein-ligand interactions in application to the D3R PL-2016-1 challenge. Based on the D3R assessment, our FFT approach in conjunction with Monte Carlo minimization off-grid refinement was among the top performing methods in the challenge. The potential advantage of our method is its ability to globally sample the protein-ligand interaction landscape, which will be explored in further applications.

Investigation on the interaction of Rutin with serum albumins: Insights from spectroscopic and molecular docking techniques.

PubMed

Sengupta, Priti; Sardar, Pinki Saha; Roy, Pritam; Dasgupta, Swagata; Bose, Adity

2018-06-01

The binding interaction of Rutin, a flavonoid, with model transport proteins, bovine serum albumin (BSA) and human serum albumin (HSA), were investigated using different spectroscopic techniques, such as fluorescence, time-resolved single photon counting (TCSPC) and circular dichroism (CD) spectroscopy as well as molecular docking method. The emission studies revealed that the fluorescence quenching of BSA/HSA by Rutin occurred through a simultaneous static and dynamic quenching process, and we have evaluated both the quenching constants individually. The binding constants of Rutin-BSA and Rutin-HSA system were found to be 2.14 × 10 6  M -1 and 2.36 × 10 6  M -1 at 298 K respectively, which were quite high. Further, influence of some biologically significant metal ions (Ca 2+ , Zn 2+ and Mg 2+ ) on binding of Rutin to BSA and HSA were also investigated. Thermodynamic parameters justified the involvement of hydrogen bonding and weak van der Waals forces in the interaction of Rutin with both BSA and HSA. Further a site-marker competitive experiment was performed to evaluate Rutin binding site in the albumins. Additionally, the CD spectra of BSA and HSA revealed that the secondary structure of the proteins was perturbed in the presence of Rutin. Finally protein-ligand docking studies have also been performed to determine the probable location of the ligand molecule. Copyright © 2018 Elsevier B.V. All rights reserved.

Pharmacophore-Based Similarity Scoring for DOCK

PubMed Central

2015-01-01

Pharmacophore modeling incorporates geometric and chemical features of known inhibitors and/or targeted binding sites to rationally identify and design new drug leads. In this study, we have encoded a three-dimensional pharmacophore matching similarity (FMS) scoring function into the structure-based design program DOCK. Validation and characterization of the method are presented through pose reproduction, crossdocking, and enrichment studies. When used alone, FMS scoring dramatically improves pose reproduction success to 93.5% (∼20% increase) and reduces sampling failures to 3.7% (∼6% drop) compared to the standard energy score (SGE) across 1043 protein–ligand complexes. The combined FMS+SGE function further improves success to 98.3%. Crossdocking experiments using FMS and FMS+SGE scoring, for six diverse protein families, similarly showed improvements in success, provided proper pharmacophore references are employed. For enrichment, incorporating pharmacophores during sampling and scoring, in most cases, also yield improved outcomes when docking and rank-ordering libraries of known actives and decoys to 15 systems. Retrospective analyses of virtual screenings to three clinical drug targets (EGFR, IGF-1R, and HIVgp41) using X-ray structures of known inhibitors as pharmacophore references are also reported, including a customized FMS scoring protocol to bias on selected regions in the reference. Overall, the results and fundamental insights gained from this study should benefit the docking community in general, particularly researchers using the new FMS method to guide computational drug discovery with DOCK. PMID:25229837

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

PubMed

Ballante, Flavio; Marshall, Garland R

2016-01-25

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes.

PubMed

Chang, Max W; Belew, Richard K; Carroll, Kate S; Olson, Arthur J; Goodsell, David S

2008-08-01

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments. 2008 Wiley Periodicals, Inc.

Multiple ligand-binding modes in bacterial R67 dihydrofolate reductase

NASA Astrophysics Data System (ADS)

Alonso, Hernán; Gillies, Malcolm B.; Cummins, Peter L.; Bliznyuk, Andrey A.; Gready, Jill E.

2005-03-01

R67 dihydrofolate reductase (DHFR), a bacterial plasmid-encoded enzyme associated with resistance to the drug trimethoprim, shows neither sequence nor structural homology with the chromosomal DHFR. It presents a highly symmetrical toroidal structure, where four identical monomers contribute to the unique central active-site pore. Two reactants (dihydrofolate, DHF), two cofactors (NADPH) or one of each (R67•DHF•NADPH) can be found simultaneously within the active site, the last one being the reactive ternary complex. As the positioning of the ligands has proven elusive to empirical determination, we addressed the problem from a theoretical perspective. Several potential structures of the ternary complex were generated using the docking programs AutoDock and FlexX. The variability among the final poses, many of which conformed to experimental data, prompted us to perform a comparative scoring analysis and molecular dynamics simulations to assess the stability of the complexes. Analysis of ligand-ligand and ligand-protein interactions along the 4 ns trajectories of eight different structures allowed us to identify important inter-ligand contacts and key protein residues. Our results, combined with published empirical data, clearly suggest that multipe binding modes of the ligands are possible within R67 DHFR. While the pterin ring of DHF and the nicotinamide ring of NADPH assume a stacked endo-conformation at the centre of the pore, probably assisted by V66, Q67 and I68, the tails of the molecules extend towards opposite ends of the cavity, adopting multiple configurations in a solvent rich-environment where hydrogen-bond interactions with K32 and Y69 may play important roles.

The Binding Mode of the Sonic Hedgehog Inhibitor Robotnikinin, a combined Docking and QM/MM MD Study.

NASA Astrophysics Data System (ADS)

Hitzenberger, Manuel; Schuster, Daniela; Hofer, Thomas S.

2017-10-01

Erroneous activation of the Hedgehog pathway has been linked to a great amount of cancerous diseases and therefore a large number of studies aiming at its inhibition have been carried out. One leverage point for novel therapeutic strategies targeting the proteins involved, is the prevention of complex formation between the extracellular signaling protein Sonic Hedgehog and the transmembrane protein Patched 1. In 2009 robotnikinin, a small molecule capable of binding to and inhibiting the activity of Sonic Hedgehog has been identified, however in the absence of X-ray structures of the Sonic Hedgehog-robotnikinin complex, the binding mode of this inhibitor remains unknown. In order to aid with the identification of novel Sonic Hedgehog inhibitors, the presented investigation elucidates the binding mode of robotnikinin by performing an extensive docking study, including subsequent molecular mechanical as well as quantum mechanical/molecular mechanical molecular dynamics simulations. The attained configurations enabled the identification of a number of key protein-ligand interactions, aiding complex formation and providing stabilizing contributions to the binding of the ligand. The predicted structure of the Sonic Hedgehog-robotnikinin complex is provided via a PDB file as supplementary material and can be used for further reference.

Virtual Screening and Pharmacophore Design for a Novel Theoretical Inhibitor of Macrophage Stimulating Factor as a Metastatic Agent

PubMed Central

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Introduction: Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Methods: Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. Results: The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Conclusion: Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies. PMID:24163807

Crystal structure of Pisum arvense seed lectin (PAL) and characterization of its interaction with carbohydrates by molecular docking and dynamics.

PubMed

Pinto-Junior, Vanir Reis; Santiago, Mayara Queiroz; Nobre, Camila Bezerra; Osterne, Vinicius Jose Silva; Leal, Rodrigo Bainy; Cajazeiras, Joao Batista; Lossio, Claudia Figueiredo; Rocha, Bruno Anderson Matias; Martins, Maria Gleiciane Queiroz; Nobre, Clareane Avelino Simplicio; Silva, Mayara Torquato Lima; Nascimento, Kyria Santiago; Cavada, Benildo Sousa

2017-09-15

The Pisum arvense lectin (PAL), a legume protein belonging to the Vicieae tribe, is capable of specific recognition of mannose, glucose and its derivatives without altering its structure. In this work, the three-dimensional structure of PAL was determined by X-ray crystallography and studied in detail by a combination of molecular docking and molecular dynamics (MD). Crystals belonging to monoclinic space group P2 1 were grown by the vapor diffusion method at 293 K. The structure was solved at 2.16 Å and was similar to that of other Vicieae lectins. The structure presented R factor and R free of 17.04% and 22.08%, respectively, with all acceptable geometric parameters. Molecular docking was performed to analyze interactions of the lectin with monosaccharides, disaccharides and high-mannose N-glycans. PAL demonstrated different affinities on carbohydrates, depending on bond orientation and glycosidic linkage present in ligands. Furthermore, the lectin interacted with representative N-glycans in a manner consistent with the biological effects described for Vicieae lectins. Carbohydrate-recognition domain (CRD) in-depth analysis was performed by MD, describing the behavior of CRD residues in complex with ligand, stability, flexibility of the protein over time, CRD volume and topology. This is a first report of its kind for a lectin of the Vicieae tribe. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of a focused virtual library of heterobifunctional ligands for Clostridium difficile toxins.

PubMed

Sanhueza, Carlos A; Cartmell, Jonathan; El-Hawiet, Amr; Szpacenko, Adam; Kitova, Elena N; Daneshfar, Rambod; Klassen, John S; Lang, Dean E; Eugenio, Luiz; Ng, Kenneth K-S; Kitov, Pavel I; Bundle, David R

2015-01-07

A focused library of virtual heterobifunctional ligands was generated in silico and a set of ligands with recombined fragments was synthesized and evaluated for binding to Clostridium difficile toxins. The position of the trisaccharide fragment was used as a reference for filtering docked poses during virtual screening to match the trisaccharide ligand in a crystal structure. The peptoid, a diversity fragment probing the protein surface area adjacent to a known binding site, was generated by a multi-component Ugi reaction. Our approach combines modular fragment-based design with in silico screening of synthetically feasible compounds and lays the groundwork for future efforts in development of composite bifunctional ligands for large clostridial toxins.

Insights into molecular interactions between CaM and its inhibitors from molecular dynamics simulations and experimental data.

PubMed

González-Andrade, Martin; Rodríguez-Sotres, Rogelio; Madariaga-Mazón, Abraham; Rivera-Chávez, José; Mata, Rachel; Sosa-Peinado, Alejandro; Del Pozo-Yauner, Luis; Arias-Olguín, Imilla I

2016-01-01

In order to contribute to the structural basis for rational design of calmodulin (CaM) inhibitors, we analyzed the interaction of CaM with 14 classic antagonists and two compounds that do not affect CaM, using docking and molecular dynamics (MD) simulations, and the data were compared to available experimental data. The Ca(2+)-CaM-Ligands complexes were simulated 20 ns, with CaM starting in the "open" and "closed" conformations. The analysis of the MD simulations provided insight into the conformational changes undergone by CaM during its interaction with these ligands. These simulations were used to predict the binding free energies (ΔG) from contributions ΔH and ΔS, giving useful information about CaM ligand binding thermodynamics. The ΔG predicted for the CaM's inhibitors correlated well with available experimental data as the r(2) obtained was 0.76 and 0.82 for the group of xanthones. Additionally, valuable information is presented here: I) CaM has two preferred ligand binding sites in the open conformation known as site 1 and 4, II) CaM can bind ligands of diverse structural nature, III) the flexibility of CaM is reduced by the union of its ligands, leading to a reduction in the Ca(2+)-CaM entropy, IV) enthalpy dominates the molecular recognition process in the system Ca(2+)-CaM-Ligand, and V) the ligands making more extensive contact with the protein have higher affinity for Ca(2+)-CaM. Despite their limitations, docking and MD simulations in combination with experimental data continue to be excellent tools for research in pharmacology, toward a rational design of new drugs.

Machine learning in computational docking.

PubMed

Khamis, Mohamed A; Gomaa, Walid; Ahmed, Walaa F

2015-03-01

The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of computational docking which is the process of predicting the best pose (orientation + conformation) of a small molecule (drug candidate) when bound to a target larger receptor molecule (protein) in order to form a stable complex molecule. In computational docking, a large number of binding poses are evaluated and ranked using a scoring function. The scoring function is a mathematical predictive model that produces a score that represents the binding free energy, and hence the stability, of the resulting complex molecule. Generally, such a function should produce a set of plausible ligands ranked according to their binding stability along with their binding poses. In more practical terms, an effective scoring function should produce promising drug candidates which can then be synthesized and physically screened using high throughput screening process. Therefore, the key to computer-aided drug design is the design of an efficient highly accurate scoring function (using ML techniques). The methods presented in this paper are specifically based on ML techniques. Despite many traditional techniques have been proposed, the performance was generally poor. Only in the last few years started the application of the ML technology in the design of scoring functions; and the results have been very promising. The ML-based techniques are based on various molecular features extracted from the abundance of protein-ligand information in the public molecular databases, e.g., protein data bank bind (PDBbind). In this paper, we present this paradigm shift elaborating on the main constituent elements of the ML approach to molecular docking along with the state-of-the-art research in this area. For instance, the best random forest (RF)-based scoring function on PDBbind v2007 achieves a Pearson correlation coefficient between the predicted and experimentally determined binding affinities of 0.803 while the best conventional scoring function achieves 0.644. The best RF-based ranking power ranks the ligands correctly based on their experimentally determined binding affinities with accuracy 62.5% and identifies the top binding ligand with accuracy 78.1%. We conclude with open questions and potential future research directions that can be pursued in smart computational docking; using molecular features of different nature (geometrical, energy terms, pharmacophore), advanced ML techniques (e.g., deep learning), combining more than one ML models. Copyright © 2015 Elsevier B.V. All rights reserved.

In silico molecular docking studies of new potential 4-phthalazinyl-hydrazones on selected Trypanosoma cruzi and Leishmania enzyme targets.

PubMed

Romero, Angel H; López, Simón E

2017-09-01

Recently, a series of 4-phthalazinyl-hydrazones under its E-configuration have exhibited excellent in vitro antichagasic and antileishmanial profiles. Preliminary assays on both parasites suggested that the most active derivatives act through oxidative and nitrosative stress mechanisms; however, their exact mode of actions as anti-trypanosomal and anti-leishmanial agents have not been completely elucidated. This motivated to perform a molecular docking study on essential trypanosomatid enzymes such as superoxide dismutase (SOD), trypanothione reductase (TryR), cysteine-protease (CP) and pteridine reductase 1 (PTR1). In addition, to understand the experimental results of nitric oxide production obtained for infected macrophages with Leishmania parasite, a molecular docking was evaluated on nitric oxide synthase (iNOS) enzyme of Rattus norvegicus. Both diastereomers (E and Z) of the 4-phthalazinyl-hydrazones were docked on the mentioned targets. In general, molecular docking on T. cruzi enzymes revealed that the E-diastereomers exhibited lower binding energies than Z-diastereomers on the Fe-SOD and CP enzymes, while Z-diastereomers showed lower docking energies than E-isomers on TryR enzyme. For the Leishmania docking studies, the Z-isomers exhibited the best binding affinities on the PTR1 and iNOS enzymes, while the TryR enzyme showed a minor dependence with the stereoselectivity of the tested phthalazines. However, either the structural information of the ligand-enzyme complexes or the experimental data suggest that the significant antitrypanosomatid activity of the most active derivatives is not associated to the inhibition of the SOD, CP and PTR1 enzymes, while the TryR inhibition and nitric oxide generation in host cells emerge as interesting antitrypanosomatid therapeutic targets. Copyright © 2017 Elsevier Inc. All rights reserved.

Synthesis, characterization, crystal structure and HSA binding of two new N,O,O-donor Schiff-base ligands derived from dihydroxybenzaldehyde and tert-butylamine

NASA Astrophysics Data System (ADS)

Khosravi, Iman; Hosseini, Farnaz; Khorshidifard, Mahsa; Sahihi, Mehdi; Rudbari, Hadi Amiri

2016-09-01

Two new o-hydroxy Schiff-bases compounds, L1 and L2, were derived from the 1:1 M condensation of 2,3-dihydroxybenzaldehyde and 2,4-dihydroxybenzaldehyde with tert-butylamine and were characterized by elemental analysis, FT-IR, 1H and 13C NMR spectroscopies. The crystal structure of L2 was also determined by single crystal X-ray analysis. The crystal structure of L2 showed that the compound exists as a zwitterionic form in the solid state, with the H atom of the phenol group being transferred to the imine N atom. It adopts an E configuration about the central Cdbnd N double bond. Furthermore, binding of these Schiff base ligands to Human Serum Albumin (HSA) was investigated by fluorescence quenching, absorption spectroscopy, molecular docking and molecular dynamics (MD) simulation methods. The fluorescence emission of HSA was quenched by ligands. Also, suitable models were used to analyze the UV-vis absorption spectroscopy data for titration of HSA solution by various amounts of Schiff bases. The spectroscopic studies revealed that these Schiff bases formed 1:1 complex with HSA. Energy transfer mechanism of quenching was discussed and the values of 3.35 and 1.57 nm as the mean distances between the bound ligands and the HSA were calculated for L1 and L2, respectively. Molecular docking results indicated that the main active binding site for these Schiff bases ligands is in subdomain IB. Moreover, MD simulation results suggested that this Schiff base complex can interact with HSA, with a slight modification of its tertiary structure.

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

NASA Astrophysics Data System (ADS)

Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

2017-06-01

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

From Molecular Docking to 3D-Quantitative Structure-Activity Relationships (3D-QSAR): Insights into the Binding Mode of 5-Lipoxygenase Inhibitors.

PubMed

Eren, Gokcen; Macchiarulo, Antonio; Banoglu, Erden

2012-02-01

Pharmacological intervention with 5-Lipoxygenase (5-LO) is a promising strategy for treatment of inflammatory and allergic ailments, including asthma. With the aim of developing predictive models of 5-LO affinity and gaining insights into the molecular basis of ligand-target interaction, we herein describe QSAR studies of 59 diverse nonredox-competitive 5-LO inhibitors based on the use of molecular shape descriptors and docking experiments. These studies have successfully yielded a predictive model able to explain much of the variance in the activity of the training set compounds while predicting satisfactorily the 5-LO inhibitory activity of an external test set of compounds. The inspection of the selected variables in the QSAR equation unveils the importance of specific interactions which are observed from docking experiments. Collectively, these results may be used to design novel potent and selective nonredox 5-LO inhibitors. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of novel peroxisome proliferator-activated receptor-gamma (PPARγ) agonists using molecular modeling method

NASA Astrophysics Data System (ADS)

Gee, Veronica M. W.; Wong, Fiona S. L.; Ramachandran, Lalitha; Sethi, Gautam; Kumar, Alan Prem; Yap, Chun Wei

2014-11-01

Peroxisome proliferator-activated receptor-gamma (PPARγ) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by activation of PPARγ, have been used extensively as insulin-sensitizers for the management of type 2 diabetes. In this study, a combination of QSAR and docking methods were utilised to perform virtual screening of more than 25 million compounds in the ZINC library. The QSAR model was developed using 1,517 compounds and it identified 42,378 potential PPARγ agonists from the ZINC library, and 10,000 of these were selected for docking with PPARγ based on their diversity. Several steps were used to refine the docking results, and finally 30 potentially highly active ligands were identified. Four compounds were subsequently tested for their in vitro activity, and one compound was found to have a K i values of <5 μM.

Antagonist-perturbation mechanism for activation function-2 fixed motifs: active conformation and docking mode of retinoid X receptor antagonists

NASA Astrophysics Data System (ADS)

Tsuji, Motonori

2017-06-01

HX531, which contains a dibenzodiazepine skeleton, is one of the first retinoid X receptor (RXR) antagonists. Functioning via RXR-PPARγ heterodimer, this compound is receiving a lot of attention as a therapeutic drug candidate for diabetic disease controlling differentiation of adipose tissue. However, the active conformation of HX531 for RXRs is not well established. In the present study, quantum mechanics calculations and molecular mechanical docking simulations were carried out to precisely study the docking mode of HX531 with the human RXRα ligand-binding domain, as well as to provide a new approach to drug design using a structure-based perspective. It was suggested that HX531, which has the R configuration for the bent dibenzodiazepine plane together with the equatorial configuration for the N-methyl group attached to the nitrogen atom in the seven-membered diazepine ring, is a typical activation function-2 (AF-2) fixed motif perturbation type antagonist, which destabilizes the formation of AF-2 fixed motifs. On the other hand, the docking simulations supported the experimental result that LG100754 is an RXR homodimer antagonist and an RXR heterodimer agonist.

Molecular docking, 3D QSAR and dynamics simulation studies of imidazo-pyrrolopyridines as janus kinase 1 (JAK 1) inhibitors.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2016-10-01

Janus kinase 1 (JAK 1) plays a critical role in initiating responses to cytokines by the JAK-signal transducer and activator of transcription (JAK-STAT). This controls survival, proliferation and differentiation of a variety of cells. Docking, 3D quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) studies were performed on a series of Imidazo-pyrrolopyridine derivatives reported as JAK 1 inhibitors. QSAR model was generated using 30 molecules in the training set; developed model showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r 2 Pred ) values. Finally, molecular dynamics simulation was performed to validate docking results and MM/GBSA calculations. This facilitated us to compare binding free energies of cocrystal ligand and newly designed molecule R1. The good concordance between the docking results and CoMFA/CoMSIA contour maps afforded obliging clues for the rational modification of molecules to design more potent JAK 1 inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular docking and in vitro studies of soap nut trypsin inhibitor (SNTI) against phospholipase A2 isoforms in therapeutic intervention of inflammatory diseases.

PubMed

Sirisha, Gandreddi V D; Vijaya Rachel, K; Zaveri, Kunal; Yarla, Nagendra Sastry; Kiranmayi, P; Ganash, Magdah; Alkreathy, Huda Mohammad; Rajeh, Nisreen; Ashraf, Ghulam Md

2018-07-15

Therapeutic value of allelochemicals in inflammatory disorders and the potential drug targets need to be elucidated to alleviate tissue and vascular injury. Natural anti-inflammatory agents are known to cause minimal adverse effects. Presence of different secondary metabolites (allelochemicals), protease inhibitors like soap nut trypsin inhibitor (SNTI) from Sapindus trifoliatus and allied compounds from natural sources cannot be blithely ignored as natural therapeutics. In the present study, SNTI, a prospective protease inhibitor isolated from the seeds of Sapindus trifoliatus were subjected to docking against three isoforms of Phospholipase A 2 (PLA 2 ) molecules of the inflammatory pathways which are localized in the membrane, cytosol and pancreas. Eleven ligand molecules were selected from Sapindus trifoliatus and docked against membrane, cytosolic and pancreatic PLA 2 . Cytosolic PLA 2 showed a strong inhibition by Kampferol, a secondary metabolite from seed endosperm of Sapindus trifoliatus. SNTI showed best interaction with membrane PLA 2 in both in silico as well as in in vitro studies. SNTI showed IC 50 value of 29.02 μM in in vitro assay. Docking interaction profiles and in vitro studies validate selected molecules from Sapindus trifoliatus as immunomodulators and can mollify inflammatory responses. Copyright © 2018 Elsevier B.V. All rights reserved.

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer.

PubMed

Ren, Ji-Xia; Li, Cheng-Ping; Zhou, Xiu-Ling; Cao, Xue-Song; Xie, Yong

2017-08-22

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using 'Receptor-Ligand Pharmacophore Generation' method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r 2 of 0.996; for the test set, the correlation coefficient r 2 was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.

Covalent docking of selected boron-based serine beta-lactamase inhibitors

NASA Astrophysics Data System (ADS)

Sgrignani, Jacopo; Novati, Beatrice; Colombo, Giorgio; Grazioso, Giovanni

2015-05-01

AmpC β-lactamase is a hydrolytic enzyme conferring resistance to β-lactam antibiotics in multiple Gram-negative bacteria. Therefore, identification of non-β-lactam compounds able to inhibit the enzyme is crucial for the development of novel antibacterial therapies. In general, AmpC inhibitors have to engage the highly solvent-exposed catalytic site of the enzyme. Therefore, understanding the implications of ligand-protein induced-fit and water-mediated interactions behind the inhibitor-enzyme recognition process is fundamental for undertaking structure-based drug design process. Here, we focus on boronic acids, a promising class of beta-lactamase covalent inhibitors. First, we optimized a docking protocol able to reproduce the experimentally determined binding mode of AmpC inhibitors bearing a boronic group. This goal was pursued (1) performing rigid and flexible docking calculations aiming to establish the role of the side chain conformations; and (2) investigating the role of specific water molecules in shaping the enzyme active site and mediating ligand protein interactions. Our calculations showed that some water molecules, conserved in the majority of the considered X-ray structures, are needed to correctly predict the binding pose of known covalent AmpC inhibitors. On this basis, we formalized our findings in a docking and scoring protocol that could be useful for the structure-based design of new boronic acid AmpC inhibitors.

Molecular docking based screening of compounds against VP40 from Ebola virus.

PubMed

M Alam El-Din, Hanaa; A Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process.

Molecular docking based screening of compounds against VP40 from Ebola virus

PubMed Central

M Alam El-Din, Hanaa; A. Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process. PMID:28149054

In silico identification of novel ligands for G-quadruplex in the c- MYC promoter

NASA Astrophysics Data System (ADS)

Kang, Hyun-Jin; Park, Hyun-Ju

2015-04-01

G-quadruplex DNA formed in NHEIII1 region of oncogene promoter inhibits transcription of the genes. In this study, virtual screening combining pharmacophore-based search and structure-based docking screening was conducted to discover ligands binding to G-quadruplex in promoter region of c- MYC. Several hit ligands showed the selective PCR-arresting effects for oligonucleotide containing c- MYC G-quadruplex forming sequence. Among them, three hits selectively inhibited cell proliferation and decreased c- MYC mRNA level in Ramos cells, where NHEIII1 is included in translocated c- MYC gene for overexpression. Promoter assay using two kinds of constructs with wild-type and mutant sequences showed that interaction of these ligands with the G-quadruplex resulted in turning-off of the reporter gene. In conclusion, combined virtual screening methods were successfully used for discovery of selective c- MYC promoter G-quadruplex binders with anticancer activity.

Watching proteins function with 150-ps time-resolved X-ray crystallography

NASA Astrophysics Data System (ADS)

Anfinrud, Philip

2007-03-01

We have used time-resolved Laue crystallography to characterize ligand migration pathways and dynamics in wild-type and several mutant forms of myoglobin (Mb), a ligand-binding heme protein found in muscle tissue. In these pump-probe experiments, which were conducted on the ID09B time-resolved beamline at the European Synchrotron and Radiation Facility, a laser pulse photodissociates CO from an MbCO crystal and a suitably delayed X-ray pulse probes its structure via Laue diffraction. Single-site mutations in the vicinity of the heme pocket docking site were found to have a dramatic effect on ligand migration. To visualize this process, time-resolved electron density maps were stitched together into movies that unveil with <2-å spatial resolution and 150-ps time-resolution the correlated protein motions that accompany and/or mediate ligand migration. These studies help to illustrate at an atomic level relationships between protein structure, dynamics, and function.

Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines.

PubMed

Zhang, Xiaohua; Wong, Sergio E; Lightstone, Felice C

2013-04-30

A mixed parallel scheme that combines message passing interface (MPI) and multithreading was implemented in the AutoDock Vina molecular docking program. The resulting program, named VinaLC, was tested on the petascale high performance computing (HPC) machines at Lawrence Livermore National Laboratory. To exploit the typical cluster-type supercomputers, thousands of docking calculations were dispatched by the master process to run simultaneously on thousands of slave processes, where each docking calculation takes one slave process on one node, and within the node each docking calculation runs via multithreading on multiple CPU cores and shared memory. Input and output of the program and the data handling within the program were carefully designed to deal with large databases and ultimately achieve HPC on a large number of CPU cores. Parallel performance analysis of the VinaLC program shows that the code scales up to more than 15K CPUs with a very low overhead cost of 3.94%. One million flexible compound docking calculations took only 1.4 h to finish on about 15K CPUs. The docking accuracy of VinaLC has been validated against the DUD data set by the re-docking of X-ray ligands and an enrichment study, 64.4% of the top scoring poses have RMSD values under 2.0 Å. The program has been demonstrated to have good enrichment performance on 70% of the targets in the DUD data set. An analysis of the enrichment factors calculated at various percentages of the screening database indicates VinaLC has very good early recovery of actives. Copyright © 2013 Wiley Periodicals, Inc.

Synthesis, characterization, thermal and biological evaluation of Cu (II), Co (II) and Ni (II) complexes of azo dye ligand containing sulfamethaxazole moiety

NASA Astrophysics Data System (ADS)

Mallikarjuna, N. M.; Keshavayya, J.; Maliyappa, M. R.; Shoukat Ali, R. A.; Venkatesh, Talavara

2018-08-01

A novel bioactive Cu (II), Co (II) and Ni (II) complexes of the azo dye ligand (L) derived from sulfamethoxazole were synthesized. The structures of the newly synthesized compounds were characterized by elemental analysis, molar conductance, magnetic susceptibility, FTIR, UV-visible, 1H NMR, mass, thermal and powder XRD spectral techniques. Molar conductivity measurements in DMSO solution confirmed the non-electrolytic nature of the complexes. All the synthesized metal complexes were found to be monomeric and showed square planar geometry except the Co (II) complex which has six coordinate, octahedral environment. The metal complexes have exhibited potential growth inhibitory effect against tested bacterial strains as compared to the free ligand. The ligand and complexes have also shown significant antioxidant and Calf Thymus DNA cleavage activities. Further, the in silico molecular docking studies were performed to predict the possible binding sites of the ligand (L) and its metal complexes with target receptor Glu-6P.

RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite.

PubMed

Fleishman, Sarel J; Leaver-Fay, Andrew; Corn, Jacob E; Strauch, Eva-Maria; Khare, Sagar D; Koga, Nobuyasu; Ashworth, Justin; Murphy, Paul; Richter, Florian; Lemmon, Gordon; Meiler, Jens; Baker, David

2011-01-01

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.

Epitope-based immunoinformatics and molecular docking studies of nucleocapsid protein and ovarian tumor domain of crimean-congo hemorrhagic Fever virus.

PubMed

Srinivasan, Pappu; Kumar, Sivakumar Prasanth; Karthikeyan, Muthusamy; Jeyakanthan, Jeyaram; Jasrai, Yogesh T; Pandya, Himanshu A; Rawal, Rakesh M; Patel, Saumya K

2011-01-01

Crimean-Congo hemorrhagic fever virus (CCHFV), the fatal human pathogen is transmitted to humans by tick bite, or exposure to infected blood or tissues of infected livestock. The CCHFV genome consists of three RNA segments namely, S, M, and L. The unusual large viral L protein has an ovarian tumor (OTU) protease domain located in the N terminus. It is likely that the protein may be autoproteolytically cleaved to generate the active virus L polymerase with additional functions. Identification of the epitope regions of the virus is important for the diagnosis, phylogeny studies, and drug discovery. Early diagnosis and treatment of CCHF infection is critical to the survival of patients and the control of the disease. In this study, we undertook different in silico approaches using molecular docking and immunoinformatics tools to predict epitopes which can be helpful for vaccine designing. Small molecule ligands against OTU domain and protein-protein interaction between a viral and a host protein have been studied using docking tools.

An evaluation of neonicotinoids' potential to inhibit human cholinesterases: Protein-ligand docking and interaction profiling studies.

PubMed

Teralı, Kerem

2018-06-16

Many so-called neuroactive insecticides target invertebrate neurotransmitter systems, including the cholinergic system. With their relatively low toxicity to vertebrates, neonicotinoids represent a new class of neuroactive insecticides that bind to nicotinic receptors for acetylcholine in the insect central nervous system and result in paralysis and eventual death due to receptor overstimulation. On the understanding that, today, cholinesterase inhibitors are used to obtain the symptomatic relief of Alzheimer disease (AD), the aforementioned direct cholinomimetic action of neonicotinoids could, perhaps, confer anti-AD drug-like attributes to these compounds. It is shown here, using protein-ligand docking and interaction profiling, that neonicotinoids penetrate deep into the active-site gorge of both acetylcholinesterase and butyrylcholinesterase and that they form relatively strong noncovalent bonds with multiple critical residues that normally bind/hydrolyze choline esters. With their gorge-spanning shape and dual-binding specificity, neonicotinoids (first-generation compounds in particular) represent promising leads for the development of reversible, mixed-type cholinesterase inhibitors in the fight against AD. Copyright © 2018 Elsevier Inc. All rights reserved.

CYPSI: a structure-based interface for cytochrome P450s and ligands in Arabidopsis thaliana

PubMed Central

2012-01-01

Background The cytochrome P450 (CYP) superfamily enables terrestrial plants to adapt to harsh environments. CYPs are key enzymes involved in a wide range of metabolic pathways. It is particularly useful to be able to analyse the three-dimensional (3D) structure when investigating the interactions between CYPs and their substrates. However, only two plant CYP structures have been resolved. In addition, no currently available databases contain structural information on plant CYPs and ligands. Fortunately, the 3D structure of CYPs is highly conserved and this has made it possible to obtain structural information from template-based modelling (TBM). Description The CYP Structure Interface (CYPSI) is a platform for CYP studies. CYPSI integrated the 3D structures for 266 A. thaliana CYPs predicted by three TBM methods: BMCD, which we developed specifically for CYP TBM; and two well-known web-servers, MUSTER and I-TASSER. After careful template selection and optimization, the models built by BMCD were accurate enough for practical application, which we demonstrated using a docking example aimed at searching for the CYPs responsible for ABA 8′-hydroxylation. CYPSI also provides extensive resources for A. thaliana CYP structure and function studies, including 400 PDB entries for solved CYPs, 48 metabolic pathways associated with A. thaliana CYPs, 232 reported CYP ligands and 18 A. thaliana CYPs docked with ligands (61 complexes in total). In addition, CYPSI also includes the ability to search for similar sequences and chemicals. Conclusions CYPSI provides comprehensive structure and function information for A. thaliana CYPs, which should facilitate investigations into the interactions between CYPs and their substrates. CYPSI has a user-friendly interface, which is available at http://bioinfo.cau.edu.cn/CYPSI. PMID:23256889

Computational approaches to screen candidate ligands with anti- Parkinson's activity using R programming.

PubMed

Jayadeepa, R M; Niveditha, M S

2012-01-01

It is estimated that by 2050 over 100 million people will be affected by the Parkinson's disease (PD). We propose various computational approaches to screen suitable candidate ligand with anti-Parkinson's activity from phytochemicals. Five different types of dopamine receptors have been identified in the brain, D1-D5. Dopamine receptor D3 was selected as the target receptor. The D3 receptor exists in areas of the brain outside the basal ganglia, such as the limbic system, and thus may play a role in the cognitive and emotional changes noted in Parkinson's disease. A ligand library of 100 molecules with anti-Parkinson's activity was collected from literature survey. Nature is the best combinatorial chemist and possibly has answers to all diseases of mankind. Failure of some synthetic drugs and its side effects have prompted many researches to go back to ancient healing methods which use herbal medicines to give relief. Hence, the candidate ligands with anti-Parkinson's were selected from herbal sources through literature survey. Lipinski rules were applied to screen the suitable molecules for the study, the resulting 88 molecules were energy minimized, and subjected to docking using Autodock Vina. The top eleven molecules were screened according to the docking score generated by Autodock Vina Commercial drug Ropinirole was computed similarly and was compared with the 11 phytochemicals score, the screened molecules were subjected to toxicity analysis and to verify toxic property of phytochemicals. R Programming was applied to remove the bias from the top eleven molecules. Using cluster analysis and Confusion Matrix two phytochemicals were computationally selected namely Rosmarinic acid and Gingkolide A for further studies on the disease Parkinson's.

Comparative analysis the binding affinity of mycophenolic sodium and meprednisone with human serum albumin: Insight by NMR relaxation data and docking simulation.

PubMed

Ma, Xiaoli; He, Jiawei; Yan, Jin; Wang, Qing; Li, Hui

2016-03-25

Mycophenolic sodium is an immunosuppressive agent that is always combined administration with corticosteroid in clinical practice. Considering the distribution and side-effect of the drug may change when co-administrated drug exist, this paper comparatively analyzed the binding ability of mycophenolic sodium and meprednisone toward human serum albumin by nuclear magnetic resonance relaxation data and docking simulation. The nuclear magnetic resonance approach was based on the analysis of proton selective and non-selective relaxation rate enhancement of the ligand in the absence and presence of macromolecules. The contribution of the bound ligand fraction to the observed relaxation rate in relation to protein concentration allowed the calculation of the affinity index. This approach allowed the comparison of the binding affinity of mycophenolic sodium and meprednisone. Molecular modeling was operated to simulate the binding model of ligand and albumin through Autodock 4.2.5. Competitive binding of mycophenolic sodium and meprednisone was further conducted through fluorescence spectroscopy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A structure-based approach to ligand discovery for 2C-methyl-D-erythritol-2,4-cyclodiphosphate synthase: a target for antimicrobial therapy.

PubMed

Ramsden, Nicola L; Buetow, Lori; Dawson, Alice; Kemp, Lauris A; Ulaganathan, Venkatsubramanian; Brenk, Ruth; Klebe, Gerhard; Hunter, William N

2009-04-23

The nonmevalonate route to isoprenoid biosynthesis is essential in Gram-negative bacteria and apicomplexan parasites. The enzymes of this pathway are absent from mammals, contributing to their appeal as chemotherapeutic targets. One enzyme, 2C-methyl-d-erythritol-2,4-cyclodiphosphate synthase (IspF), has been validated as a target by genetic approaches in bacteria. Virtual screening against Escherichia coli IspF (EcIspF) was performed by combining a hierarchical filtering methodology with molecular docking. Docked compounds were inspected and 10 selected for experimental validation. A surface plasmon resonance assay was developed and two weak ligands identified. Crystal structures of EcIspF complexes were determined to support rational ligand development. Cytosine analogues and Zn(2+)-binding moieties were characterized. One of the putative Zn(2+)-binding compounds gave the lowest measured K(D) to date (1.92 +/- 0.18 muM). These data provide a framework for the development of IspF inhibitors to generate lead compounds of therapeutic potential against microbial pathogens.

Computational Methods in Drug Discovery

PubMed Central

Sliwoski, Gregory; Kothiwale, Sandeepkumar; Meiler, Jens

2014-01-01

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature. PMID:24381236

Molecular Docking and Prediction of Pharmacokinetic Properties of Dual Mechanism Drugs that Block MAO-B and Adenosine A2A Receptors for the Treatment of Parkinson's Disease

PubMed Central

Azam, Faizul; Madi, Arwa M.; Ali, Hamed I.

2012-01-01

Monoamine oxidase B (MAO-B) inhibitory potential of adenosine A2A receptor (AA2AR) antagonists has raised the possibility of designing dual-target–directed drugs that may provide enhanced symptomatic relief and that may also slow the progression of Parkinson's disease (PD) by protecting against further neurodegeneration. To explain the dual inhibition of MAO-B and AA2AR at the molecular level, molecular docking technique was employed. Lamarckian genetic algorithm methodology was used for flexible ligand docking studies. A good correlation (R2= 0.524 and 0.627 for MAO-B and AA2AR, respectively) was established between docking predicted and experimental Ki values, which confirms that the molecular docking approach is reliable to study the mechanism of dual interaction of caffeinyl analogs with MAO-B and AA2AR. Parameters for Lipinski's “Rule-of-Five” were also calculated to estimate the pharmacokinetic properties of dual-target–directed drugs where both MAO-B inhibition and AA2AR antagonism exhibited a positive correlation with calculated LogP having a correlation coefficient R2 of 0.535 and 0.607, respectively. These results provide some beneficial clues in structural modification for designing new inhibitors as dual-target–directed drugs with desired pharmacokinetic properties for the treatment of PD. PMID:23112538

Virtual screening studies of Chinese medicine Coptidis Rhizoma as alpha7 nicotinic acetylcholine receptor agonists for treatment of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Xiang, Li; Xu, Youdong; Zhang, Yan; Meng, Xianli; Wang, Ping

2015-04-01

Alzheimer's disease (AD) is an age-related neurodegenerative disease. Extensive in vitro and in vivo experiments have proved that the decreased activity of the cholinergic neuron is responsible for the memory and cognition deterioration. The alpha7 nicotinic acetylcholine receptor (α7-nAChR) is proposed to a drug target of AD, and compounds which acting as α7-nAChR agonists are considered as candidates in AD treatment. Chinese medicine CoptidisRhizoma and its compounds are reported in various anti-AD effects. In this study, virtual screening, docking approaches and hydrogen bond analyses were applied to screen potential α7-nAChR agonists from CoptidisRhizome. The 3D structure of the protein was obtained from PDB database. 87 reported compounds were included in this research and their structures were accessed by NCBI Pubchem. Docking analysis of the compounds was performed using AutoDock 4.2 and AutoDock Vina. The images of the binding modes hydrogen bonds and the hydrophobic interaction were rendered with PyMOL1.5.0.4. and LigPlot+ respectively. Finally, N-tran-feruloyltyramine, isolariciresinol, flavanone, secoisolariciresinol, (+)-lariciresinol and dihydrochalcone, exhibited the lowest docking energy of protein-ligand complex. The results indicate these 6 compounds are potential α7 nAChR agonists, and expected to be effective in AD treatment.

Mechanism of sodium channel block by local anesthetics, antiarrhythmics, and anticonvulsants

PubMed Central

Tikhonov, Denis B.

2017-01-01

Local anesthetics, antiarrhythmics, and anticonvulsants include both charged and electroneutral compounds that block voltage-gated sodium channels. Prior studies have revealed a common drug-binding region within the pore, but details about the binding sites and mechanism of block remain unclear. Here, we use the x-ray structure of a prokaryotic sodium channel, NavMs, to model a eukaryotic channel and dock representative ligands. These include lidocaine, QX-314, cocaine, quinidine, lamotrigine, carbamazepine (CMZ), phenytoin, lacosamide, sipatrigine, and bisphenol A. Preliminary calculations demonstrated that a sodium ion near the selectivity filter attracts electroneutral CMZ but repels cationic lidocaine. Therefore, we further docked electroneutral and cationic drugs with and without a sodium ion, respectively. In our models, all the drugs interact with a phenylalanine in helix IVS6. Electroneutral drugs trap a sodium ion in the proximity of the selectivity filter, and this same site attracts the charged group of cationic ligands. At this position, even small drugs can block the permeation pathway by an electrostatic or steric mechanism. Our study proposes a common pharmacophore for these diverse drugs. It includes a cationic moiety and an aromatic moiety, which are usually linked by four bonds. PMID:28258204

Systematic study of imidazoles inhibiting IDO1 via the integration of molecular mechanics and quantum mechanics calculations.

PubMed

Zou, Yi; Wang, Fang; Wang, Yan; Guo, Wenjie; Zhang, Yihua; Xu, Qiang; Lai, Yisheng

2017-05-05

Indoleamine 2,3-dioxygenase 1 (IDO1) is regarded as an attractive target for cancer immunotherapy. To rationalize the detailed interactions between IDO1 and its inhibitors at the atomic level, an integrated computational approach by combining molecular mechanics and quantum mechanics methods was employed in this report. Specifically, the binding modes of 20 inhibitors was initially investigated using the induced fit docking (IFD) protocol, which outperformed other two docking protocols in terms of correctly predicting ligand conformations. Secondly, molecular dynamics (MD) simulations and MM/PBSA free energy calculations were employed to determine the dynamic binding process and crucial residues were confirmed through close contact analysis, hydrogen-bond analysis and binding free energy decomposition calculations. Subsequent quantum mechanics and nonbonding interaction analysis were carried out to provide in-depth explanations on the critical role of those key residues, and Arg231 and 7-propionate of the heme group were major contributors to ligand binding, which lowed a great amount of interaction energy. We anticipate that these findings will be valuable for enzymatic studies and rational drug design. Copyright © 2017. Published by Elsevier Masson SAS.

Mechanism of sodium channel block by local anesthetics, antiarrhythmics, and anticonvulsants.

PubMed

Tikhonov, Denis B; Zhorov, Boris S

2017-04-03

Local anesthetics, antiarrhythmics, and anticonvulsants include both charged and electroneutral compounds that block voltage-gated sodium channels. Prior studies have revealed a common drug-binding region within the pore, but details about the binding sites and mechanism of block remain unclear. Here, we use the x-ray structure of a prokaryotic sodium channel, NavMs, to model a eukaryotic channel and dock representative ligands. These include lidocaine, QX-314, cocaine, quinidine, lamotrigine, carbamazepine (CMZ), phenytoin, lacosamide, sipatrigine, and bisphenol A. Preliminary calculations demonstrated that a sodium ion near the selectivity filter attracts electroneutral CMZ but repels cationic lidocaine. Therefore, we further docked electroneutral and cationic drugs with and without a sodium ion, respectively. In our models, all the drugs interact with a phenylalanine in helix IVS6. Electroneutral drugs trap a sodium ion in the proximity of the selectivity filter, and this same site attracts the charged group of cationic ligands. At this position, even small drugs can block the permeation pathway by an electrostatic or steric mechanism. Our study proposes a common pharmacophore for these diverse drugs. It includes a cationic moiety and an aromatic moiety, which are usually linked by four bonds. © 2017 Tikhonov and Zhorov.

Exploration of enzyme-ligand interactions in CYP2D6 & 3A4 homology models and crystal structures using a novel computational approach.

PubMed

Kjellander, Britta; Masimirembwa, Collen M; Zamora, Ismael

2007-01-01

New crystal structures of human CYP2D6 and CYP3A4 have recently been reported, and in this study, we wanted to compare them with previously used homology models with respect to predictions of site of metabolism and ligand-enzyme interactions. The data set consisted of a family of synthetic opioid analgesics with the aim to cover both CYP2D6 and CYP3A4, as most of these compounds are metabolized by both isoforms. The program MetaSite was used for the site of metabolism predictions, and the results were validated by experimental assessment of the major metabolites formed with recombinant CYP450s. This was made on a selection of 14 compounds in the data set. The prediction rates for MetaSite were 79-100% except for the CYP3A4 homology model, which picked the correct site in half of the cases. Despite differences in orientation of some important amino acids in the active sites, the MetaSite-predicted sites were the same for the different structures, with the exception of the CYP3A4 homology model. Further exploration of interactions with ligands was done by docking substrates/inhibitors in the different structures with the docking program GLUE. To address the challenge in interpreting patterns of enzyme-ligand interactions for the large number of different docking poses, a new computational tool to handle the results from the dockings was developed, in which the output highlights the relative importance of amino acids in CYP450-substrate/inhibitor interactions. The method is based on calculations of the interaction energies for each pose with the surrounding amino acids. For the CYP3A4 structures, this method was compared with consensus principal component analysis (CPCA), a commonly used method for structural comparison to evaluate the usefulness of the new method. The results from the two methods were comparable with each other, and the highlighted amino acids resemble those that were identified to have a different orientation in the compared structures. The new method has clear advantages over CPCA in that it is far simpler to interpret and there is no need for protein alignment. The methodology enables structural comparison but also gives insights on important amino acid substrate/inhibitor interactions and can therefore be very useful when suggesting modifications of new chemical entities to improve their metabolic profiles.

Molecular modeling of ligand-receptor interactions in the OR5 olfactory receptor.

PubMed

Singer, M S; Shepherd, G M

1994-06-02

Olfactory receptors belong to the superfamily of seven transmembrane domain, G protein-coupled receptors. In order to begin analysis of mechanisms of receptor activation, a computer model of the OR5 olfactory receptor has been constructed and compared with other members of this superfamily. We have tested docking of the odor molecule lyral, which is known to activate the OR5 receptor. The results point to specific ligand-binding residues on helices III through VII that form a binding pocket in the receptor. Some of these residues occupy sequence positions identical to ligand-binding residues conserved among other superfamily members. The results provide new insights into possible molecular mechanisms of odor recognition and suggest hypotheses to guide future experimental studies using site-directed mutagenesis.

Synthesis, spectroscopic, molecular orbital calculation, cytotoxic, molecular docking of DNA binding and DNA cleavage studies of transition metal complexes with N-benzylidene-N'-salicylidene-1,1-diaminopropane

NASA Astrophysics Data System (ADS)

Al-Mogren, Muneerah M.; Alaghaz, Abdel-Nasser M. A.; Elbohy, Salwa A. H.

2013-10-01

Eight mononuclear chromium(III), manganese(II), iron(III), cobalt(II), nickel(II), copper(II), zinc(II) and cadmium(II) complexes of Schiff's base ligand were synthesized and determined by different physical techniques. The complexes are insoluble in common organic solvents but soluble in DMF and DMSO. The measured molar conductance values in DMSO indicate that the complexes are non-electrolytic in nature. All the eight metal complexes have been fully characterized with the help of elemental analyses, molecular weights, molar conductance values, magnetic moments and spectroscopic data. The analytical data helped to elucidate the structure of the metal complexes. The Schiff base is found to act as tridentate ligand using N2O donor set of atoms leading to an octahedral geometry for the complexes around all the metal ions. Quantum chemical calculations were performed with semi-empirical method to find the optimum geometry of the ligand and its complexes. Additionally in silico, the docking studies and the calculated pharmacokinetic parameters show promising futures for application of the ligand and complexes as high potency agents for DNA binding activity. The interaction of the complexes with calf thymus DNA (CT-DNA) has been investigated by UV absorption method, and the mode of CT-DNA binding to the complexes has been explored. Furthermore, the DNA cleavage activity by the complexes was performed. The Schiff base and their complexes have been screened for their antibacterial activity against bacterial strains [Staphylococcus aureus (RCMB010027), Staphylococcus epidermidis (RCMB010024), Bacillis subtilis (RCMB010063), Proteous vulgaris (RCMB 010085), Klebsiella pneumonia (RCMB 010093) and Shigella flexneri (RCMB 0100542)] and fungi [(Aspergillus fumigates (RCMB 02564), Aspergillus clavatus (RCMB 02593) and Candida albicans (RCMB05035)] by disk diffusion method. All the metal complexes have potent biocidal activity than the free ligand.

Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions

PubMed Central

Johnson, David K.; Karanicolas, John

2016-01-01

Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased “pocket optimization” simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its “exemplar”: a perfect, but non-physical, pseudo-ligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 minutes on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a “pocket-optimized” ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target. PMID:26726827

Statistical analysis of EGFR structures' performance in virtual screening

NASA Astrophysics Data System (ADS)

Li, Yan; Li, Xiang; Dong, Zigang

2015-11-01

In this work the ability of EGFR structures to distinguish true inhibitors from decoys in docking and MM-PBSA is assessed by statistical procedures. The docking performance depends critically on the receptor conformation and bound state. The enrichment of known inhibitors is well correlated with the difference between EGFR structures rather than the bound-ligand property. The optimal structures for virtual screening can be selected based purely on the complex information. And the mixed combination of distinct EGFR conformations is recommended for ensemble docking. In MM-PBSA, a variety of EGFR structures have identically good performance in the scoring and ranking of known inhibitors, indicating that the choice of the receptor structure has little effect on the screening.

In-silico Investigation of Antitrypanosomal Phytochemicals from Nigerian Medicinal Plants

PubMed Central

Setzer, William N.; Ogungbe, Ifedayo V.

2012-01-01

Background Human African trypanosomiasis (HAT), a parasitic protozoal disease, is caused primarily by two subspecies of Trypanosoma brucei. HAT is a re-emerging disease and currently threatens millions of people in sub-Saharan Africa. Many affected people live in remote areas with limited access to health services and, therefore, rely on traditional herbal medicines for treatment. Methods A molecular docking study has been carried out on phytochemical agents that have been previously isolated and characterized from Nigerian medicinal plants, either known to be used ethnopharmacologically to treat parasitic infections or known to have in-vitro antitrypanosomal activity. A total of 386 compounds from 19 species of medicinal plants were investigated using in-silico molecular docking with validated Trypanosoma brucei protein targets that were available from the Protein Data Bank (PDB): Adenosine kinase (TbAK), pteridine reductase 1 (TbPTR1), dihydrofolate reductase (TbDHFR), trypanothione reductase (TbTR), cathepsin B (TbCatB), heat shock protein 90 (TbHSP90), sterol 14α-demethylase (TbCYP51), nucleoside hydrolase (TbNH), triose phosphate isomerase (TbTIM), nucleoside 2-deoxyribosyltransferase (TbNDRT), UDP-galactose 4′ epimerase (TbUDPGE), and ornithine decarboxylase (TbODC). Results This study revealed that triterpenoid and steroid ligands were largely selective for sterol 14α-demethylase; anthraquinones, xanthones, and berberine alkaloids docked strongly to pteridine reductase 1 (TbPTR1); chromenes, pyrazole and pyridine alkaloids preferred docking to triose phosphate isomerase (TbTIM); and numerous indole alkaloids showed notable docking energies with UDP-galactose 4′ epimerase (TbUDPGE). Polyphenolic compounds such as flavonoid gallates or flavonoid glycosides tended to be promiscuous docking agents, giving strong docking energies with most proteins. Conclusions This in-silico molecular docking study has identified potential biomolecular targets of phytochemical components of antitrypanosomal plants and has determined which phytochemical classes and structural manifolds likely target trypanosomal enzymes. The results could provide the framework for synthetic modification of bioactive phytochemicals, de novo synthesis of structural motifs, and lead to further phytochemical investigations. PMID:22848767

Molecular characterization of human ABHD2 as TAG lipase and ester hydrolase

PubMed Central

M., Naresh Kumar; V.B.S.C., Thunuguntla; G.K., Veeramachaneni; B., Chandra Sekhar; Guntupalli, Swapna; J.S., Bondili

2016-01-01

Alterations in lipid metabolism have been progressively documented as a characteristic property of cancer cells. Though, human ABHD2 gene was found to be highly expressed in breast and lung cancers, its biochemical functionality is yet uncharacterized. In the present study we report, human ABHD2 as triacylglycerol (TAG) lipase along with ester hydrolysing capacity. Sequence analysis of ABHD2 revealed the presence of conserved motifs G205XS207XG209 and H120XXXXD125. Phylogenetic analysis showed homology to known lipases, Drosophila melanogaster CG3488. To evaluate the biochemical role, recombinant ABHD2 was expressed in Saccharomyces cerevisiae using pYES2/CT vector and His-tag purified protein showed TAG lipase activity. Ester hydrolase activity was confirmed with pNP acetate, butyrate and palmitate substrates respectively. Further, the ABHD2 homology model was built and the modelled protein was analysed based on the RMSD and root mean square fluctuation (RMSF) of the 100 ns simulation trajectory. Docking the acetate, butyrate and palmitate ligands with the model confirmed covalent binding of ligands with the Ser207 of the GXSXG motif. The model was validated with a mutant ABHD2 developed with alanine in place of Ser207 and the docking studies revealed loss of interaction between selected ligands and the mutant protein active site. Based on the above results, human ABHD2 was identified as a novel TAG lipase and ester hydrolase. PMID:27247428

Molecular docking and dynamic simulation studies evidenced plausible immunotherapeutic anticancer property by Withaferin A targeting indoleamine 2,3-dioxygenase.

PubMed

Reddy, S V G; Reddy, K Thammi; Kumari, V Valli; Basha, Syed Hussain

2015-01-01

Indoleamine 2,3-dioxygenase (IDO) is emerging as an important new therapeutic drug target for the treatment of cancer characterized by pathological immune suppression. IDO catalyzes the rate-limiting step of tryptophan degradation along the kynurenine pathway. Reduction in local tryptophan concentration and the production of immunomodulatory tryptophan metabolites contribute to the immunosuppressive effects of IDO. Presence of IDO on dentritic cells in tumor-draining lymph nodes leading to the activation of T cells toward forming immunosuppressive microenvironment for the survival of tumor cells has confirmed the importance of IDO as a promising novel anticancer immunotherapy drug target. On the other hand, Withaferin A (WA) - active constituent of Withania Somnifera ayurvedic herb has shown to be having a wide range of targeted anticancer properties. In the present study conducted here is an attempt to explore the potential of WA in attenuating IDO for immunotherapeutic tumor arresting activity and to elucidate the underlying mode of action in a computational approach. Our docking and molecular dynamic simulation results predict high binding affinity of the ligand to the receptor with up to -11.51 kcal/mol of energy and 3.63 nM of IC50 value. Further, de novo molecular dynamic simulations predicted stable ligand interactions with critically important residues SER167; ARG231; LYS377, and heme moiety involved in IDO's activity. Conclusively, our results strongly suggest WA as a valuable small ligand molecule with strong binding affinity toward IDO.

Molecular characterization of human ABHD2 as TAG lipase and ester hydrolase.

PubMed

M, Naresh Kumar; V B S C, Thunuguntla; G K, Veeramachaneni; B, Chandra Sekhar; Guntupalli, Swapna; J S, Bondili

2016-08-01

Alterations in lipid metabolism have been progressively documented as a characteristic property of cancer cells. Though, human ABHD2 gene was found to be highly expressed in breast and lung cancers, its biochemical functionality is yet uncharacterized. In the present study we report, human ABHD2 as triacylglycerol (TAG) lipase along with ester hydrolysing capacity. Sequence analysis of ABHD2 revealed the presence of conserved motifs G(205)XS(207)XG(209) and H(120)XXXXD(125) Phylogenetic analysis showed homology to known lipases, Drosophila melanogaster CG3488. To evaluate the biochemical role, recombinant ABHD2 was expressed in Saccharomyces cerevisiae using pYES2/CT vector and His-tag purified protein showed TAG lipase activity. Ester hydrolase activity was confirmed with pNP acetate, butyrate and palmitate substrates respectively. Further, the ABHD2 homology model was built and the modelled protein was analysed based on the RMSD and root mean square fluctuation (RMSF) of the 100 ns simulation trajectory. Docking the acetate, butyrate and palmitate ligands with the model confirmed covalent binding of ligands with the Ser(207) of the GXSXG motif. The model was validated with a mutant ABHD2 developed with alanine in place of Ser(207) and the docking studies revealed loss of interaction between selected ligands and the mutant protein active site. Based on the above results, human ABHD2 was identified as a novel TAG lipase and ester hydrolase. © 2016 The Author(s).

Mapping a protein recognition centre with chiral photoactive ligands. An integrated approach combining photophysics, reactivity, proteomics and molecular dynamics simulation studies.

PubMed

Limones-Herrero, Daniel; Pérez-Ruiz, Raúl; Lence, Emilio; González-Bello, Concepción; Miranda, Miguel A; Jiménez, M Consuelo

2017-04-01

A multidisciplinary strategy to obtain structural information on the intraprotein region is described here. As probe ligands, ( S )- and ( R )- CPFMe (the methyl esters of the chiral drug carprofen) have been selected, while bovine α 1 -acid glycoprotein (BAAG) has been chosen as a biological host. The procedure involves the separate irradiation of the BAAG/( S )- CPFMe and BAAG/( R )- CPFMe complexes, coupled with fluorescence spectroscopy, laser flash photolysis, proteomic analysis, docking and molecular dynamics simulations. Thus, irradiation of the BAAG/ CPFMe complexes at λ = 320 nm was followed by fluorescence spectroscopy. The intensity of the emission band obtained after irradiation indicated photodehalogenation, whereas its structureless shape suggested covalent binding of the resulting radical CBZMe˙ to the biopolymer. After gel filtration chromatography, the spectra still displayed emission, in agreement with covalent attachment of CBZMe˙ to BAAG. Stereodifferentiation was observed in this process. After trypsin digestion and ESI-MS/MS, the incorporation of CBZMe was detected at Phe68. Docking and molecular dynamics simulation studies, which were carried out using a homology model of BAAG, reveal that the closer proximity of the aromatic moiety of the ( S )-enantiomer to the phenyl group of Phe68 would be responsible for the experimentally observed, more effective chemical modification of the protein. The proposed tridimensional structure of BAAG covalently modified by the two enantiomers is also provided. In principle, this approach can be extended to a variety of protein/ligand complexes.

Molecular modelling studies on the ORL1-receptor and ORL1-agonists

NASA Astrophysics Data System (ADS)

Bröer, Britta M.; Gurrath, Marion; Höltje, Hans-Dieter

2003-11-01

The ORL1 ( opioid receptor like 1)- receptor is a member of the family of rhodopsin-like G protein-coupled receptors (GPCR) and represents an interesting new therapeutical target since it is involved in a variety of biomedical important processes, such as anxiety, nociception, feeding, and memory. In order to shed light on the molecular basis of the interactions of the GPCR with its ligands, the receptor protein and a dataset of specific agonists were examined using molecular modelling methods. For that purpose, the conformational space of a very potent non-peptide ORL1-receptor agonist (Ro 64-6198) with a small number of rotatable bonds was analysed in order to derive a pharmacophoric arrangement. The conformational analyses yielded a conformation that served as template for the superposition of a set of related analogues. Structural superposition was achieved by employing the program FlexS. Using the experimental binding data and the superposition of the ligands, a 3D-QSAR analysis applying the GRID/GOLPE method was carried out. After the ligand-based modelling approach, a 3D model of the ORL1-receptor has been constructed using homology modelling methods based on the crystal structure of bovine rhodopsin. A representative structure of the model taken from molecular dynamics simulations was used for a manual docking procedure. Asp-130 and Thr-305 within the ORL1-receptor model served as important hydrophilic interaction partners. Furthermore, a hydrophobic cavity was identified stabilizing the agonists within their binding site. The manual docking results were supported using FlexX, which identified the same protein-ligand interaction points.

Performance of HADDOCK and a simple contact-based protein-ligand binding affinity predictor in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Kurkcuoglu, Zeynep; Koukos, Panagiotis I.; Citro, Nevia; Trellet, Mikael E.; Rodrigues, J. P. G. L. M.; Moreira, Irina S.; Roel-Touris, Jorge; Melquiond, Adrien S. J.; Geng, Cunliang; Schaarschmidt, Jörg; Xue, Li C.; Vangone, Anna; Bonvin, A. M. J. J.

2018-01-01

We present the performance of HADDOCK, our information-driven docking software, in the second edition of the D3R Grand Challenge. In this blind experiment, participants were requested to predict the structures and binding affinities of complexes between the Farnesoid X nuclear receptor and 102 different ligands. The models obtained in Stage1 with HADDOCK and ligand-specific protocol show an average ligand RMSD of 5.1 Å from the crystal structure. Only 6/35 targets were within 2.5 Å RMSD from the reference, which prompted us to investigate the limiting factors and revise our protocol for Stage2. The choice of the receptor conformation appeared to have the strongest influence on the results. Our Stage2 models were of higher quality (13 out of 35 were within 2.5 Å), with an average RMSD of 4.1 Å. The docking protocol was applied to all 102 ligands to generate poses for binding affinity prediction. We developed a modified version of our contact-based binding affinity predictor PRODIGY, using the number of interatomic contacts classified by their type and the intermolecular electrostatic energy. This simple structure-based binding affinity predictor shows a Kendall's Tau correlation of 0.37 in ranking the ligands (7th best out of 77 methods, 5th/25 groups). Those results were obtained from the average prediction over the top10 poses, irrespective of their similarity/correctness, underscoring the robustness of our simple predictor. This results in an enrichment factor of 2.5 compared to a random predictor for ranking ligands within the top 25%, making it a promising approach to identify lead compounds in virtual screening.

DOVIS: an implementation for high-throughput virtual screening using AutoDock.

PubMed

Zhang, Shuxing; Kumar, Kamal; Jiang, Xiaohui; Wallqvist, Anders; Reifman, Jaques

2008-02-27

Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. However, the development of an integrated HPC system that makes efficient use of its elements is not trivial. We have developed an application termed DOVIS that uses AutoDock (version 3) as the docking engine and runs in parallel on a Linux cluster. DOVIS can efficiently dock large numbers (millions) of small molecules (ligands) to a receptor, screening 500 to 1,000 compounds per processor per day. Furthermore, in DOVIS, the docking session is fully integrated and automated in that the inputs are specified via a graphical user interface, the calculations are fully integrated with a Linux cluster queuing system for parallel processing, and the results can be visualized and queried. DOVIS removes most of the complexities and organizational problems associated with large-scale high-throughput virtual screening, and provides a convenient and efficient solution for AutoDock users to use this software in a Linux cluster platform.

A combined photophysical and computational study on the binding of mycophenolate mofetil and its major metabolite to transport proteins

NASA Astrophysics Data System (ADS)

Vendrell-Criado, Victoria; González-Bello, Concepción; Miranda, Miguel A.; Jiménez, M. Consuelo

2018-06-01

Binding of the immunosuppressive agent mycophenolate mofetil (MMP) and its pharmacologically active metabolite mycophenolic acid (MPA) to human serum albumin (HSA) and α1-acid glycoprotein (HAAG) has been investigated by means of an integrated approach involving selective excitation of the drug fluorophore, following their UV-A triggered fluorescence and docking studies. The formation of the protein/ligand complexes was evidenced by a dramatic enhancement of the fluorescence intensity and a hypsochromic shift of the emission band. In HSA, competitive studies using oleic acid as site I probe revealed site I as the main binding site of the ligands. Binding constants revealed that the affinity of the active metabolite by HSA is four-fold higher than its proactive form. Moreover, the affinity of MMP by HSA is three-fold higher than by HAAG. Docking studies revealed significant molecular binding differences in the binding of MMP and MPA to sub-domain IIA of HSA (site 1). For MPA, the aromatic moiety would be in close contact to Trp214 with the flexible chain pointing to the other end of the sub-domain; on the contrary, for MMP, the carboxylate group of the chain would be fixed nearby Trp214 through electrostatic interactions with residues Arg218 and Arg222.

Modeling G Protein-Coupled Receptors: a Concrete Possibility

PubMed Central

Costanzi, Stefano

2010-01-01

G protein-coupled receptors (GPCRs) are a large superfamily of membrane bound signaling proteins that are involved in the regulation of a wide range of physiological functions and constitute the most common target for therapeutic intervention. Due to the paucity of crystal structures, homology modeling has become a widespread technique for the construction of GPCR models, which have been applied to the study of their structure-function relationships and to the identification of lead ligands through virtual screening. Rhodopsin has been for years the only available template. However, recent breakthroughs in GPCR crystallography have led to the solution of the structures of a few additional receptors. In light of these newly elucidated crystal structures, we have been able to produce a substantial amount of data to demonstrate that accurate models of GPCRs in complex with their ligands can be constructed through homology modeling followed by fully flexible molecular docking. These results have been confirmed by our success in the first blind assessment of GPCR modeling and docking, organized in coordination with the solution of the X-ray structure of the adenosine A2A receptor. Taken together, these data indicate that: a) the transmembrane helical bundle can be modeled with considerable accuracy; b) predicting the binding mode of a ligand, although doable, is challenging; c) modeling of the extracellular and intracellular loops is still problematic. PMID:21253444

Characterization and comparison of perezone with some analogues. Experimental and theoretical study

NASA Astrophysics Data System (ADS)

Escobedo-González, Rene Gerardo; Bahena, Luis; Arias Tellez, José Luis; Hinojosa Torres, Jaime; Ruvalcaba, Rene Miranda; Aceves-Hernández, Juan Manuel

2015-10-01

Perezone had been used for centuries in the traditional Mexican medicine, it is useful and a handful of illness. Perezone and other derivatives also present activity against certain lines of cancer, such as the myeloblastoid leukemia cell line K-562 and carcinoma cell lines (PC-3 and SKLU-1) with IC50 <10 μM. Perezone and isoperezone have shown the major cytotoxic potency. Characterization of perezone was carried out by UV-Visible, IR, DSC, TGA and powder X-ray diffraction, as well as docking studies using caspase-3 structures as receptors. Theoretical studies for optimizing the geometry of perezone were carried out and the results compared with values of single crystal X-ray diffraction. The experimental values of atomic distances, angles and dihedral angles are in good agreement with the theoretical values. Interaction of perezone with the cysteine catalytic site with the caspase-3 was found in the docking studies. A docking study of perezone, with horminone, thymoquinone and isoperezone as ligands and the protein apoptein, caspase-3 as receptor, was carried to demonstrate that the hindrance steric factor, chemical structure and the functional groups are important in the biological activity of these natural products. The docking score energetic values are in good agreement with the experimental cytotoxic results obtained from the experiments when perezone and analogues were studied in different types of cancer.

Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

PubMed Central

Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun

2010-01-01

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r2cv values of 0.747 and 0.518 and r2 values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity. PMID:21152296

Molecular modeling studies of 4,5-dihydro-1H-pyrazolo[4,3-h] quinazoline derivatives as potent CDK2/Cyclin a inhibitors using 3D-QSAR and docking.

PubMed

Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun

2010-09-28

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.

PoLi: A Virtual Screening Pipeline Based On Template Pocket And Ligand Similarity

PubMed Central

Roy, Ambrish; Srinivasan, Bharath; Skolnick, Jeffrey

2015-01-01

Often in pharmaceutical research, the goal is to identify small molecules that can interact with and appropriately modify the biological behavior of a new protein target. Unfortunately, most proteins lack both known structures and small molecule binders, prerequisites of many virtual screening, VS, approaches. For such proteins, ligand homology modeling, LHM, that copies ligands from homologous and perhaps evolutionarily distant template proteins, has been shown to be a powerful VS approach to identify possible binding ligands. However, if we want to target a specific pocket for which there is no homologous holo template protein structure, then LHM will not work. To address this issue, in a new pocket based approach, PoLi, we generalize LHM by exploiting the fact that the number of distinct small molecule ligand binding pockets in proteins is small. PoLi identifies similar ligand binding pockets in a holo-template protein library, selectively copies relevant parts of template ligands and uses them for VS. In practice, PoLi is a hybrid structure and ligand based VS algorithm that integrates 2D fingerprint-based and 3D shape-based similarity metrics for improved virtual screening performance. On standard DUD and DUD-E benchmark databases, using modeled receptor structures, PoLi achieves an average enrichment factor of 13.4 and 9.6 respectively, in the top 1% of the screened library. In contrast, traditional docking based VS using AutoDock Vina and homology-based VS using FINDSITEfilt have an average enrichment of 1.6 (3.0) and 9.0 (7.9) on the DUD (DUD-E) sets respectively. Experimental validation of PoLi predictions on dihydrofolate reductase, DHFR, using differential scanning fluorimetry, DSF, identifies multiple ligands with diverse molecular scaffolds, thus demonstrating the advantage of PoLi over current state-of-the-art VS methods. PMID:26225536

Carboxylic acid derivatives display potential selectivity for human histone deacetylase 6: Structure-based virtual screening, molecular docking and dynamics simulation studies.

PubMed

Uba, Abdullahi Ibrahim; Yelekçi, Kemal

2018-08-01

Human histone deacetylase 6 (HDAC6) has been shown to play a major role in oncogenic cell transformation via deacetylation of α-tubulin, making it a viable target of anticancer drug design and development. The crystal structure of HDAC6 catalytic domain 2 has been recently made available, providing avenues for structure-based drug design campaign. Here, in our continuous effort to identify potentially selective HDAC6 inhibitors, structure-based virtual screening of ∼72 461 compounds was carried out using Autodock Vina. The top 100 compounds with calculated ΔG < -10 kcal/mol were manually inspected for binding mode orientation. Furthermore, the top 20 compounds with reasonable binding modes were evaluated for selectivity by further docking against HDAC6 and HDAC7 using Autodock4. Four compounds with a carboxylic fragment, displayed potential selectivity for HDAC6 over HDAC7, and were found to have good druglike and ADMET properties. Their docking complexes were then submitted to 10 ns-molecular dynamics (MD) simulation using nanoscale MD (NAMD) software, to examine the stability of ligand binding modes. These predicted inhibitors remained bound to HDAC6 in the presence of water and ions, and the root-mean-square deviation (RMSD), radius of gyration (Rg) and nonbond distance (protein-ligand) profiles suggested that they might be stable over time of the simulation. This study may provide scaffolds for further lead optimization towards the design of HDAC6 inhibitors with improved selectivity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Molecular docking guided structure based design of symmetrical N,N'-disubstituted urea/thiourea as HIV-1 gp120-CD4 binding inhibitors.

PubMed

Sivan, Sree Kanth; Vangala, Radhika; Manga, Vijjulatha

2013-08-01

Induced fit molecular docking studies were performed on BMS-806 derivatives reported as small molecule inhibitors of HIV-1 gp120-CD4 binding. Comprehensive study of protein-ligand interactions guided in identification and design of novel symmetrical N,N'-disubstituted urea and thiourea as HIV-1 gp120-CD4 binding inhibitors. These molecules were synthesized in aqueous medium using microwave irradiation. Synthesized molecules were screened for their inhibitory ability by HIV-1 gp120-CD4 capture enzyme-linked immunosorbent assay (ELISA). Designed compounds were found to inhibit HIV-1 gp120-CD4 binding in micromolar (0.013-0.247 μM) concentrations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Molecular modeling study of the differential ligand-receptor interaction at the μ, δ and κ opioid receptors

NASA Astrophysics Data System (ADS)

Filizola, Marta; Carteni-Farina, Maria; Perez, Juan J.

1999-07-01

3D models of the opioid receptors μ, δ and κ were constructed using BUNDLE, an in-house program to build de novo models of G-protein coupled receptors at the atomic level. Once the three opioid receptors were constructed and before any energy refinement, models were assessed for their compatibility with the results available from point-site mutations carried out on these receptors. In a subsequent step, three selective antagonists to each of three receptors (naltrindole, naltrexone and nor-binaltorphamine) were docked onto each of the three receptors and subsequently energy minimized. The nine resulting complexes were checked for their ability to explain known results of structure-activity studies. Once the models were validated, analysis of the distances between different residues of the receptors and the ligands were computed. This analysis permitted us to identify key residues tentatively involved in direct interaction with the ligand.

Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

PubMed

Fang, Cheng; Xiao, Zhiyan

2016-01-01

Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

Quantitative structure-activity relationship and molecular docking of artemisinin derivatives to vascular endothelial growth factor receptor 1.

PubMed

Saeed, Mohamed E M; Kadioglu, Onat; Seo, Ean-Jeong; Greten, Henry Johannes; Brenk, Ruth; Efferth, Thomas

2015-04-01

The antimalarial drug artemisinin has been shown to exert anticancer activity through anti-angiogenic effects. For further drug development, it may be useful to have derivatives with improved anti-angiogenic properties. We performed molecular docking of 52 artemisinin derivatives to vascular endothelial growth factor receptors (VEGFR1, VEGFR2), and VEGFA ligand using Autodock4 and AutodockTools-1.5.7.rc1 using the Lamarckian genetic algorithm. Quantitative structure-activity relationship (QSAR) analyses of the compounds prepared by Corina Molecular Networks were performed using the Molecular Operating Environment MOE 2012.10. A statistically significant inverse relationship was obtained between in silico binding energies to VEGFR1 and anti-angiogenic activity in vivo of a test-set of artemisinin derivatives (R=-0.843; p=0.035). This served as a control experiment to validate molecular docking predicting anti-angiogenc effects. Furthermore, 52 artemisinin derivatives were docked to VEGFR1 and in selected examples also to VEGFR2 and VEGFA. Higher binding affinities were calculated for receptors than for the ligand. The best binding affinities to VEGFR1 were found for an artemisinin dimer, 10-dihydroartemisinyl-2-propylpentanoate, and dihydroartemisinin α-hemisuccinate sodium salt. QSAR analyses revealed significant relationships between VEGFR1 binding energies and defined molecular descriptors of 35 artemisinins assigned to the training set (R=0.0848, p<0.0001) and 17 derivatives assigned to the test set (R=0.761, p<0.001). Molecular docking and QSAR calculations can be used to identify novel artemisinin derivatives with anti-angiogenic effects. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Efficient method for high-throughput virtual screening based on flexible docking: discovery of novel acetylcholinesterase inhibitors.

PubMed

Mizutani, Miho Yamada; Itai, Akiko

2004-09-23

A method of easily finding ligands, with a variety of core structures, for a given target macromolecule would greatly contribute to the rapid identification of novel lead compounds for drug development. We have developed an efficient method for discovering ligand candidates from a number of flexible compounds included in databases, when the three-dimensional (3D) structure of the drug target is available. The method, named ADAM&EVE, makes use of our automated docking method ADAM, which has already been reported. Like ADAM, ADAM&EVE takes account of the flexibility of each molecule in databases, by exploring the conformational space fully and continuously. Database screening has been made much faster than with ADAM through the tuning of parameters, so that computational screening of several hundred thousand compounds is possible in a practical time. Promising ligand candidates can be selected according to various criteria based on the docking results and characteristics of compounds. Furthermore, we have developed a new tool, EVE-MAKE, for automatically preparing the additional compound data necessary for flexible docking calculation, prior to 3D database screening. Among several successful cases of lead discovery by ADAM&EVE, the finding of novel acetylcholinesterase (AChE) inhibitors is presented here. We performed a virtual screening of about 160 000 commercially available compounds against the X-ray crystallographic structure of AChE. Among 114 compounds that could be purchased and assayed, 35 molecules with various core structures showed inhibitory activities with IC(50) values less than 100 microM. Thirteen compounds had IC(50) values between 0.5 and 10 microM, and almost all their core structures are very different from those of known inhibitors. The results demonstrate the effectiveness and validity of the ADAM&EVE approach and provide a starting point for development of novel drugs to treat Alzheimer's disease.

Cyclic mu-opioid receptor ligands containing multiple N-methylated amino acid residues.

PubMed

Adamska-Bartłomiejczyk, Anna; Janecka, Anna; Szabó, Márton Richárd; Cerlesi, Maria Camilla; Calo, Girolamo; Kluczyk, Alicja; Tömböly, Csaba; Borics, Attila

2017-04-15

In this study we report the in vitro activities of four cyclic opioid peptides with various sequence length/macrocycle size and N-methylamino acid residue content. N-Methylated amino acids were incorporated and cyclization was employed to enhance conformational rigidity to various extent. The effect of such modifications on ligand structure and binding properties were studied. The pentapeptide containing one endocyclic and one exocyclic N-methylated amino acid displayed the highest affinity to the mu-opioid receptor. This peptide was also shown to be a full agonist, while the other analogs failed to activate the mu opioid receptor. Results of molecular docking studies provided rationale for the explanation of binding properties on a structural basis. Copyright © 2017 Elsevier Ltd. All rights reserved.

3D-QSAR, molecular dynamics simulations and molecular docking studies of benzoxazepine moiety as mTOR inhibitor for the treatment of lung cancer.

PubMed

Chaube, Udit; Chhatbar, Dhara; Bhatt, Hardik

2016-02-01

According to WHO statistics, lung cancer is one of the leading causes of death among all other types of cancer. Many genes get mutated in lung cancer but involvement of EGFR and KRAS are more common. Unavailability of drugs or resistance to the available drugs is the major problem in the treatment of lung cancer. In the present research, mTOR was selected as an alternative target for the treatment of lung cancer which involves PI3K/AKT/mTOR pathway. 28 synthetic mTOR inhibitors were selected from the literature. Ligand based approach (CoMFA and CoMSIA) and structure based approach (molecular dynamics simulations assisted molecular docking study) were applied for the identification of important features of benzoxazepine moiety, responsible for mTOR inhibition. Three different alignments were tried to obtain best QSAR model, of which, distil was found to be the best method, as it gave good statistical results. In CoMFA, Leave One Out (LOO) cross validated coefficients (q(2)), conventional coefficient (r(2)) and predicted correlation coefficient (r(2)pred) values were found to be 0.615, 0.990 and 0.930, respectively. Similarly in CoMSIA, q(2), r(2)ncv and r(2)pred values were found to be 0.748, 0.986 and 0.933, respectively. Molecular dynamics and simulations study revealed that B-chain of mTOR protein was stable at and above 500 FS with respect to temperature (at and above 298 K), Potential energy (at and above 7669.72 kJ/mol) and kinetic energy (at and above 4009.77 kJ/mol). Molecular docking study was performed on simulated protein of mTOR which helped to correlate interactions of amino acids surrounded to the ligand with contour maps generated by QSAR method. Important features of benzoxazepine were identified by contour maps and molecular docking study which would be useful to design novel molecules as mTOR inhibitors for the treatment of lung cancer. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer-aided rational design of novel EBF analogues with an aromatic ring.

PubMed

Wang, Shanshan; Sun, Yufeng; Du, Shaoqing; Qin, Yaoguo; Duan, Hongxia; Yang, Xinling

2016-06-01

Odorant binding proteins (OBPs) are important in insect olfactory recognition. These proteins bind specifically to insect semiochemicals and induce their seeking, mating, and alarm behaviors. Molecular docking and molecular dynamics simulations were performed to provide computational insight into the interaction mode between AgamOBP7 and novel (E)-β-farnesene (EBF) analogues with an aromatic ring. The ligand-binding cavity in OBP7 was found to be mostly hydrophobic due to the presence of several nonpolar residues. The interactions between the EBF analogues and the hydrophobic residues in the binding cavity increased in strength as the distance between them decreased. The EBF analogues with an N-methyl formamide or ester linkage had higher docking scores than those with an amide linkage. Moreover, delocalized π-π and electrostatic interactions were found to contribute significantly to the binding between the ligand benzene ring and nearby protein residues. To design new compounds with higher activity, four EBF analogues D1-D4 with a benzene ring were synthesized and evaluated based on their docking scores and binding affinities. D2, which had an N-methyl formamide group linkage, exhibited stronger binding than D1, which had an amide linkage. D4 exhibited particularly strong binding due to multiple hydrophobic interactions with the protein. This study provides crucial foundations for designing novel EBF analogues based on the OBP structure. Graphical abstract The design strategy of new EBF analogues based on the OBP7 structure.

Extending RosettaDock with water, sugar, and pH for prediction of complex structures and affinities for CAPRI rounds 20-27.

PubMed

Kilambi, Krishna Praneeth; Pacella, Michael S; Xu, Jianqing; Labonte, Jason W; Porter, Justin R; Muthu, Pravin; Drew, Kevin; Kuroda, Daisuke; Schueler-Furman, Ora; Bonneau, Richard; Gray, Jeffrey J

2013-12-01

Rounds 20-27 of the Critical Assessment of PRotein Interactions (CAPRI) provided a testing platform for computational methods designed to address a wide range of challenges. The diverse targets drove the creation of and new combinations of computational tools. In this study, RosettaDock and other novel Rosetta protocols were used to successfully predict four of the 10 blind targets. For example, for DNase domain of Colicin E2-Im2 immunity protein, RosettaDock and RosettaLigand were used to predict the positions of water molecules at the interface, recovering 46% of the native water-mediated contacts. For α-repeat Rep4-Rep2 and g-type lysozyme-PliG inhibitor complexes, homology models were built and standard and pH-sensitive docking algorithms were used to generate structures with interface RMSD values of 3.3 Å and 2.0 Å, respectively. A novel flexible sugar-protein docking protocol was also developed and used for structure prediction of the BT4661-heparin-like saccharide complex, recovering 71% of the native contacts. Challenges remain in the generation of accurate homology models for protein mutants and sampling during global docking. On proteins designed to bind influenza hemagglutinin, only about half of the mutations were identified that affect binding (T55: 54%; T56: 48%). The prediction of the structure of the xylanase complex involving homology modeling and multidomain docking pushed the limits of global conformational sampling and did not result in any successful prediction. The diversity of problems at hand requires computational algorithms to be versatile; the recent additions to the Rosetta suite expand the capabilities to encompass more biologically realistic docking problems. Copyright © 2013 Wiley Periodicals, Inc.

Integrating structure-based and ligand-based approaches for computational drug design.

PubMed

Wilson, Gregory L; Lill, Markus A

2011-04-01

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

Sequential Application of Ligand and Structure Based Modeling Approaches to Index Chemicals for Their hH4R Antagonism

PubMed Central

Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner. PMID:25330207

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

PubMed

Pappalardo, Matteo; Shachaf, Nir; Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.

Optimization of memory use of fragment extension-based protein-ligand docking with an original fast minimum cost flow algorithm.

PubMed

Yanagisawa, Keisuke; Komine, Shunta; Kubota, Rikuto; Ohue, Masahito; Akiyama, Yutaka

2018-06-01

The need to accelerate large-scale protein-ligand docking in virtual screening against a huge compound database led researchers to propose a strategy that entails memorizing the evaluation result of the partial structure of a compound and reusing it to evaluate other compounds. However, the previous method required frequent disk accesses, resulting in insufficient acceleration. Thus, more efficient memory usage can be expected to lead to further acceleration, and optimal memory usage could be achieved by solving the minimum cost flow problem. In this research, we propose a fast algorithm for the minimum cost flow problem utilizing the characteristics of the graph generated for this problem as constraints. The proposed algorithm, which optimized memory usage, was approximately seven times faster compared to existing minimum cost flow algorithms. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Anibamine and its Analogues as Novel Anti Prostate Cancer Agents

DTIC Science & Technology

2010-06-01

PC- 3, and DU-145 has been conducted continuously to evaluate the efficacy of more ligands. A molecular modeling study (3D QSAR ) protocol has been... Toxicology at Virginia Commonwealth University. Both the PI’s lab and Dr. 10 Selley’s lab have fully functional binding assay facility. The assays is...pursue the docking study and 3D QSAR study. 5.3 3D QSAR (Quantitative Structure-Activity Relationships) Study As proposed in our proposal, we will

Identification of Transthyretin Fibril Formation Inhibitors Using Structure-Based Virtual Screening.

PubMed

Ortore, Gabriella; Martinelli, Adriano

2017-08-22

Transthyretin (TTR) is the primary carrier for thyroxine (T 4 ) in cerebrospinal fluid and a secondary carrier in blood. TTR is a stable homotetramer, but certain factors, genetic or environmental, could promote its degradation to form amyloid fibrils. A docking study using crystal structures of wild-type TTR was planned; our aim was to design new ligands that are able to inhibit TTR fibril formation. The computational protocol was thought to overcome the multiple binding modes of the ligands induced by the peculiarity of the TTR binding site and by the pseudosymmetry of the site pockets, which generally weaken such structure-based studies. Two docking steps, one that is very fast and a subsequent step that is more accurate, were used to screen the Aldrich Market Select database. Five compounds were selected, and their activity toward inhibiting TTR fibril formation was assessed. Three compounds were observed to be actives, two of which have the same potency as the positive control, and the other was found to be a promising lead compound. These results validate a computational protocol that is able to archive information on the key interactions between database compounds and TTR, which is valuable for supporting further studies. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Molecular Docking of Potential Inhibitors of Broccoli Myrosinase.

PubMed

Román, J; Castillo, A; Mahn, A

2018-05-30

Glucosinolates are secondary metabolites occurring in Brassicaceae plants whose hydrolysis may yield isothiocyanates, widely recognized as health-promoting compounds. Myrosinase catalyzes this conversion. The chemical mechanism involves an unstable intermediary (thiohydroxamate- O -sulfonate) that spontaneously decomposes into isothiocyanates or other non-bioactive compounds depending on pH and cofactors. At acidic pH, non-bioactive compounds such as nitriles and thiocyanates are formed, while at neutral pH isothiocyanates are obtained. Broccoli myrosinase has been poorly studied so far. Recently, its amino acidic sequence was elucidated, and a structural model was built. The aim of this work was to study the molecular interaction of broccoli myrosinase with different ligands at acidic pH to propose possible inhibitors that prevent formation of undesirable compounds at acidic pH, and that at neutral pH dissociate from the enzyme, allowing formation of isothiocyanates. The interaction between broccoli myrosinase and 40 ligands was studied by molecular docking simulations. Both the enzyme and each inhibitor were set at pH 3.0. Amygdaline and arbutin showed the highest affinity to broccoli myrosinase in this condition. The residues that stabilize the complexes agree with those that stabilize the substrate (Gln207, Glu429, Tyr352, and Ser433). Accordingly, amygdaline and arbutin would perform as competitive inhibitors of myrosinase at pH 3.0.

Computational design of environmental sensors for the potent opioid fentanyl

DOE PAGES

Bick, Matthew J.; Greisen, Per J.; Morey, Kevin J.; ...

2017-09-19

Here, we describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We also use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment.

Computational design of environmental sensors for the potent opioid fentanyl

PubMed Central

Morey, Kevin J; Antunes, Mauricio S; La, David; Sankaran, Banumathi; Reymond, Luc; Johnsson, Kai; Medford, June I

2017-01-01

We describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment. PMID:28925919

Computational design of environmental sensors for the potent opioid fentanyl

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bick, Matthew J.; Greisen, Per J.; Morey, Kevin J.

Here, we describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We also use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment.

Application of the stochastic tunneling method to high throughput database screening

NASA Astrophysics Data System (ADS)

Merlitz, H.; Burghardt, B.; Wenzel, W.

2003-03-01

The stochastic tunneling technique is applied to screen a database of chemical compounds to the active site of dihydrofolate reductase for lead candidates in the receptor-ligand docking problem. Using an atomistic force field we consider the ligand's internal rotational degrees of freedom. It is shown that the natural ligand (methotrexate) scores best among 10 000 randomly chosen compounds. We analyze the top scoring compounds to identify hot-spots of the receptor. We mutate the amino acids that are responsible for the hot-spots of the receptor and verify that its specificity is lost upon modification.

Pharmacoinformatics exploration of polyphenol oxidases leading to novel inhibitors by virtual screening and molecular dynamic simulation study.

PubMed

Hassan, Mubashir; Abbas, Qamar; Ashraf, Zaman; Moustafa, Ahmed A; Seo, Sung-Yum

2017-06-01

Polyphenol oxidases (PPOs)/tyrosinases are metal-dependent enzymes and known as important targets for melanogenesis. Although considerable attempts have been conducted to control the melanin-associated diseases by using various inhibitors. However, the exploration of the best anti-melanin inhibitor without side effect still remains a challenge in drug discovery. In present study, protein structure prediction, ligand-based pharmacophore modeling, virtual screening, molecular docking and dynamic simulation study were used to screen the strong novel inhibitor to cure melanogenesis. The 3D structures of PPO1 and PPO2 were built through homology modeling, while the 3D crystal structures of PPO3 and PPO4 were retrieved from PDB. Pharmacophore modeling was performed using LigandScout 3.1 software and top five models were selected to screen the libraries (2601 of Aurora and 727, 842 of ZINC). Top 10 hit compounds (C1-10) were short-listed having strong binding affinities for PPO1-4. Drug and synthetic accessibility (SA) scores along with absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment were employed to scrutinize the best lead hit. C4 (name) hit showed the best predicted SA score (5.75), ADMET properties and drug-likeness behavior among the short-listed compounds. Furthermore, docking simulations were performed to check the binding affinity of C1-C10 compounds against target proteins (PPOs). The binding affinity values of complex between C4 and PPOs were higher than those of other complexes (-11.70, -12.1, -9.90 and -11.20kcal/mol with PPO1, PPO2, PPO3, or PPO4, respectively). From comparative docking energy and binding analyses, PPO2 may be considered as better target for melanogenesis than others. The potential binding modes of C4, C8 and C10 against PPO2 were explored using molecular dynamics simulations. The root mean square deviation and fluctuation (RMSD/RMSF) graphs results depict the significance of C4 over the other compounds. Overall, bioactivity and ligand efficiency profiles suggested that the proposed hit may be more effective inhibitors for melanogenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combined QSAR and molecule docking studies on predicting P-glycoprotein inhibitors

NASA Astrophysics Data System (ADS)

Tan, Wen; Mei, Hu; Chao, Li; Liu, Tengfei; Pan, Xianchao; Shu, Mao; Yang, Li

2013-12-01

P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter. The over expression of P-gp leads to the development of multidrug resistance (MDR), which is a major obstacle to effective treatment of cancer. Thus, designing effective P-gp inhibitors has an extremely important role in the overcoming MDR. In this paper, both ligand-based quantitative structure-activity relationship (QSAR) and receptor-based molecular docking are used to predict P-gp inhibitors. The results show that each method achieves good prediction performance. According to the results of tenfold cross-validation, an optimal linear SVM model with only three descriptors is established on 857 training samples, of which the overall accuracy (Acc), sensitivity, specificity, and Matthews correlation coefficient are 0.840, 0.873, 0.813, and 0.683, respectively. The SVM model is further validated by 418 test samples with the overall Acc of 0.868. Based on a homology model of human P-gp established, Surflex-dock is also performed to give binding free energy-based evaluations with the overall accuracies of 0.823 for the test set. Furthermore, a consensus evaluation is also performed by using these two methods. Both QSAR and molecular docking studies indicate that molecular volume, hydrophobicity and aromaticity are three dominant factors influencing the inhibitory activities.

In silico investigation of potential mTOR inhibitors from traditional Chinese medicine for treatment of Leigh syndrome.

PubMed

Chen, Kuan-Chung; Lee, Wen-Yuan; Chen, Hsin-Yi; Chen, Calvin Yu-Chian

2014-01-01

A recent research demonstrates that the inhibition of mammalian target of rapamycin (mTOR) improves survival and health for patients with Leigh syndrome. mTOR proteins can be treated as drug target proteins against Leigh syndrome and other mitochondrial disorders. In this study, we aim to identify potent TCM compounds from the TCM Database@Taiwan as lead compounds of mTOR inhibitors. PONDR-Fit protocol was employed to predict the disordered disposition in mTOR protein before virtual screening. After virtual screening, the MD simulation was employed to validate the stability of interactions between each ligand and mTOR protein in the docking poses from docking simulation. The top TCM compounds, picrasidine M and acerosin, have higher binding affinities with target protein in docking simulation than control. There have H-bonds with residues Val2240 and π interactions with common residue Trp2239. After MD simulation, the top TCM compounds maintain similar docking poses under dynamic conditions. The top two TCM compounds, picrasidine M and acerosin, were extracted from Picrasma quassioides (D. Don) Benn. and Vitex negundo L. Hence, we propose the TCM compounds, picrasidine M and acerosin, as potential candidates as lead compounds for further study in drug development process with the mTOR protein against Leigh syndrome and other mitochondrial disorders.

Pharmacophore modeling, virtual screening and molecular docking of ATPase inhibitors of HSP70.

PubMed

Sangeetha, K; Sasikala, R P; Meena, K S

2017-10-01

Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Covalent Docking of Large Libraries for the Discovery of Chemical Probes

PubMed Central

London, Nir; Miller, Rand M.; Krishnan, Shyam; Uchida, Kenji; Irwin, John J.; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K.; Taunton, Jack

2014-01-01

Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency, and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1, and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org). PMID:25344815

Covalent docking of large libraries for the discovery of chemical probes.

PubMed

London, Nir; Miller, Rand M; Krishnan, Shyam; Uchida, Kenji; Irwin, John J; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K; Taunton, Jack

2014-12-01

Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1 and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including what are to our knowledge the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org/).

D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions

NASA Astrophysics Data System (ADS)

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A.; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2016-09-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (1) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (2) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor.

D3R Grand Challenge 2015: Evaluation of Protein-Ligand Pose and Affinity Predictions

PubMed Central

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2017-01-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (i) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (ii) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor. PMID:27696240

Identification of ligand efficient, fragment-like hits from an HTS library: structure-based virtual screening and docking investigations of 2H- and 3H-pyrazolo tautomers for Aurora kinase A selectivity.

PubMed

Sarvagalla, Sailu; Singh, Vivek Kumar; Ke, Yi-Yu; Shiao, Hui-Yi; Lin, Wen-Hsing; Hsieh, Hsing-Pang; Hsu, John T A; Coumar, Mohane Selvaraj

2015-01-01

Furanopyrimidine 1 (IC50 = 273 nM, LE = 0.36, LELP = 10.28) was recently identified by high-throughput screening (HTS) of an in-house library (125,000 compounds) as an Aurora kinase inhibitor. Structure-based hit optimization resulted in lead molecules with in vivo efficacy in a mouse tumour xenograft model, but no oral bioavailability. This is attributed to "molecular obesity", a common problem during hit to lead evolution during which degradation of important molecular properties such as molecular weight (MW) and lipophilicity occurs. This could be effectively tackled by the right choice of hit compounds for optimization. In this regard, ligand efficiency (LE) and ligand efficiency dependent lipophilicity (LELP) indices are more often used to choose fragment-like hits for optimization. To identify hits with appropriate LE, we used a MW cut-off <250, and pyrazole structure to filter HTS library. Next, structure-based virtual screening using software (Libdock and Glide) in the Aurora A crystal structure (PDB ID: 3E5A) was carried out, and the top scoring 18 compounds tested for Aurora A enzyme inhibition. This resulted in the identification of a novel tetrahydro-pyrazolo-isoquinoline hit 7 (IC50 = 852 nM, LE = 0.44, LELP = 8.36) with fragment-like properties suitable for further hit optimization. Moreover, hit 7 was found to be selective for Aurora A (Aurora B IC50 = 35,150 nM) and the possible reasons for selectivity investigated by docking two tautomeric forms (2H- and 3H-pyrazole) of 7 in Auroras A and B (PDB ID: 4AF3) crystal structures. This docking study shows that the major 3H-pyrazole tautomer of 7 binds in Aurora A stronger than in Aurora B.

Identification of ligand efficient, fragment-like hits from an HTS library: structure-based virtual screening and docking investigations of 2 H- and 3 H-pyrazolo tautomers for Aurora kinase A selectivity

NASA Astrophysics Data System (ADS)

Sarvagalla, Sailu; Singh, Vivek Kumar; Ke, Yi-Yu; Shiao, Hui-Yi; Lin, Wen-Hsing; Hsieh, Hsing-Pang; Hsu, John T. A.; Coumar, Mohane Selvaraj

2015-01-01

Furanopyrimidine 1 (IC50 = 273 nM, LE = 0.36, LELP = 10.28) was recently identified by high-throughput screening (HTS) of an in-house library (125,000 compounds) as an Aurora kinase inhibitor. Structure-based hit optimization resulted in lead molecules with in vivo efficacy in a mouse tumour xenograft model, but no oral bioavailability. This is attributed to "molecular obesity", a common problem during hit to lead evolution during which degradation of important molecular properties such as molecular weight (MW) and lipophilicity occurs. This could be effectively tackled by the right choice of hit compounds for optimization. In this regard, ligand efficiency (LE) and ligand efficiency dependent lipophilicity (LELP) indices are more often used to choose fragment-like hits for optimization. To identify hits with appropriate LE, we used a MW cut-off <250, and pyrazole structure to filter HTS library. Next, structure-based virtual screening using software (Libdock and Glide) in the Aurora A crystal structure (PDB ID: 3E5A) was carried out, and the top scoring 18 compounds tested for Aurora A enzyme inhibition. This resulted in the identification of a novel tetrahydro-pyrazolo-isoquinoline hit 7 (IC50 = 852 nM, LE = 0.44, LELP = 8.36) with fragment-like properties suitable for further hit optimization. Moreover, hit 7 was found to be selective for Aurora A (Aurora B IC50 = 35,150 nM) and the possible reasons for selectivity investigated by docking two tautomeric forms (2 H- and 3 H-pyrazole) of 7 in Auroras A and B (PDB ID: 4AF3) crystal structures. This docking study shows that the major 3 H-pyrazole tautomer of 7 binds in Aurora A stronger than in Aurora B.

Comparing Evolutionary Programs and Evolutionary Pattern Search Algorithms: A Drug Docking Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1999-02-10

Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAS) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and theymore » suggest that EPSAs may be more robust on larger, more complex problems.« less

Generation of the first structure-based pharmacophore model containing a selective "zinc binding group" feature to identify potential glyoxalase-1 inhibitors.

PubMed

Al-Balas, Qosay; Hassan, Mohammad; Al-Oudat, Buthina; Alzoubi, Hassan; Mhaidat, Nizar; Almaaytah, Ammar

2012-11-22

Within this study, a unique 3D structure-based pharmacophore model of the enzyme glyoxalase-1 (Glo-1) has been revealed. Glo-1 is considered a zinc metalloenzyme in which the inhibitor binding with zinc atom at the active site is crucial. To our knowledge, this is the first pharmacophore model that has a selective feature for a "zinc binding group" which has been customized within the structure-based pharmacophore model of Glo-1 to extract ligands that possess functional groups able to bind zinc atom solely from database screening. In addition, an extensive 2D similarity search using three diverse similarity techniques (Tanimoto, Dice, Cosine) has been performed over the commercially available "Zinc Clean Drug-Like Database" that contains around 10 million compounds to help find suitable inhibitors for this enzyme based on known inhibitors from the literature. The resultant hits were mapped over the structure based pharmacophore and the successful hits were further docked using three docking programs with different pose fitting and scoring techniques (GOLD, LibDock, CDOCKER). Nine candidates were suggested to be novel Glo-1 inhibitors containing the "zinc binding group" with the highest consensus scoring from docking.

Methyl group reorientation under ligand binding probed by pseudocontact shifts.

PubMed

Lescanne, Mathilde; Ahuja, Puneet; Blok, Anneloes; Timmer, Monika; Akerud, Tomas; Ubbink, Marcellus

2018-06-02

Liquid-state NMR spectroscopy is a powerful technique to elucidate binding properties of ligands on proteins. Ligands binding in hydrophobic pockets are often in close proximity to methyl groups and binding can lead to subtle displacements of methyl containing side chains to accommodate the ligand. To establish whether pseudocontact shifts can be used to characterize ligand binding and the effects on methyl groups, the N-terminal domain of HSP90 was tagged with caged lanthanoid NMR probe 5 at three positions and titrated with a ligand. Binding was monitored using the resonances of leucine and valine methyl groups. The pseudocontact shifts (PCS) caused by ytterbium result in enhanced dispersion of the methyl spectrum, allowing more resonances to be observed. The effects of tag attachment on the spectrum and ligand binding are small. Significant changes in PCS were observed upon ligand binding, indicating displacements of several methyl groups. By determining the cross-section of PCS iso-surfaces generated by two or three paramagnetic centers, the new position of a methyl group can be estimated, showing displacements in the range of 1-3 Å for methyl groups in the binding site. The information about such subtle but significant changes may be used to improve docking studies and can find application in fragment-based drug discovery.

In Silico Exploration of 1,7-Diazacarbazole Analogs as Checkpoint Kinase 1 Inhibitors by Using 3D QSAR, Molecular Docking Study, and Molecular Dynamics Simulations.

PubMed

Gao, Xiaodong; Han, Liping; Ren, Yujie

2016-05-05

Checkpoint kinase 1 (Chk1) is an important serine/threonine kinase with a self-protection function. The combination of Chk1 inhibitors and anti-cancer drugs can enhance the selectivity of tumor therapy. In this work, a set of 1,7-diazacarbazole analogs were identified as potent Chk1 inhibitors through a series of computer-aided drug design processes, including three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, and molecular dynamics simulations. The optimal QSAR models showed significant cross-validated correlation q² values (0.531, 0.726), fitted correlation r² coefficients (higher than 0.90), and standard error of prediction (less than 0.250). These results suggested that the developed models possess good predictive ability. Moreover, molecular docking and molecular dynamics simulations were applied to highlight the important interactions between the ligand and the Chk1 receptor protein. This study shows that hydrogen bonding and electrostatic forces are key interactions that confer bioactivity.

Combined spectroscopic, molecular docking and quantum mechanics study of β-casein and p-coumaric acid interactions following thermal treatment.

PubMed

Kaur, Jasmeet; Katopo, Lita; Hung, Andrew; Ashton, John; Kasapis, Stefan

2018-06-30

The molecular nature of interactions between β-casein and p-coumaric acid was studied following exposure of their solutions to ultra-high temperature (UHT at 145 °C). Interactions were characterised by employing multi-spectroscopic methods, molecular docking and quantum mechanics calculations. FTIR demonstrates that the ligand lies in the vicinity of the protein, hence inverting the absorbance spectrum of the complex. This outcome changes the conformational characteristics of the protein leading to a flexible and open structure that accommodates the phenolic microconstituent. Results are supported by UV-vis, CD and fluorescence quenching showing considerable shifts in spectra with complexation. Molecular docking indicates that there is at least a hydrogen bond between p-coumaric acid and the peptide backbone of isoleucine (Ile27). Quantum mechanics calculations further argue that changes in experimental observations are also due to a covalent interaction in the protein-phenolic adduct, which according to the best predicted binding pose involves the side chain of lysine 47. Copyright © 2018. Published by Elsevier Ltd.

Using Surface Enhanced Raman Scattering to Analyze the Interactions of Protein Receptors with Bacterial Quorum Sensing Modulators

PubMed Central

2015-01-01

Many members of the LuxR family of quorum sensing (QS) transcriptional activators, including LasR of Pseudomonas aeruginosa, are believed to require appropriate acyl-homoserine lactone (acyl-HSL) ligands to fold into an active conformation. The failure to purify ligand-free LuxR homologues in nonaggregated form at the high concentrations required for their structural characterization has limited the understanding of the mechanisms by which QS receptors are activated. Surface-enhanced Raman scattering (SERS) is a vibrational spectroscopy technique that can be applied to study proteins at extremely low concentrations in their active state. The high sensitivity of SERS has allowed us to detect molecular interactions between the ligand-binding domain of LasR (LasRLBD) as a soluble apoprotein and modulators of P. aeruginosa QS. We found that QS activators and inhibitors produce differential SERS fingerprints in LasRLBD, and in combination with molecular docking analysis provide insight into the relevant interaction mechanism. This study reveals signal-specific structural changes in LasR upon ligand binding, thereby confirming the applicability of SERS to analyze ligand-induced conformational changes in proteins. PMID:25927541

Exploration of N-arylpiperazine Binding Sites of D2 Dopaminergic Receptor.

PubMed

Soskic, Vukic; Sukalovic, Vladimir; Kostic-Rajacic, Sladjana

2015-01-01

The crystal structures of the D3 dopamine receptor and several other G-protein coupled receptors (GPCRs) were published in recent times. Those 3D structures are used by us and other scientists as a template for the homology modeling and ligand docking analysis of related GPCRs. Our main scientific interest lies in the field of pharmacologically active N-arylpiperazines that exhibit antipsychotic and/or antidepressant properties, and as such are dopaminergic and serotonergic receptor ligands. In this short review article we are presenting synthesis and biological data on the new N-arylpipereazine as well our results on molecular modeling of the interactions of those N-arylpiperazines with the model of D2 dopamine receptors. To obtain that model the crystal structure of the D3 dopamine receptor was used. Our results show that the N-arylpiperazines binding site consists of two pockets: one is the orthosteric binding site where the N-arylpiperazine part of the ligand is docked and the second is a non-canonical accessory binding site for N-arylpipereazine that is formed by a second extracellular loop (ecl2) of the receptor. Until now, the structure of this receptor region was unresolved in crystal structure analyses of the D3 dopamine receptor. To get a more complete picture of the ligand - receptor interaction, DFT quantum mechanical calculations on N-arylpiperazine were performed and the obtained models were used to examine those interactions.

From small sweeteners to sweet proteins: anatomy of the binding sites of the human T1R2_T1R3 receptor.

PubMed

Morini, Gabriella; Bassoli, Angela; Temussi, Piero A

2005-08-25

The sweet taste receptor, a heterodimeric G protein coupled receptor (GPCR) protein, formed by the T1R2 and T1R3 subunits, recognizes several sweet compounds including carbohydrates, amino acids, peptides, proteins, and synthetic sweeteners. Its similarity with the metabotropic glutamate mGluR1 receptor allowed us to build homology models. All possible dimers formed by combinations of the human T1R2 and T1R3 subunits, modeled on the A (closed) or B (open) chains of the extracellular ligand binding domain of the mGluR1 template, yield four ligand binding sites for low-molecular-weight sweeteners. These sites were probed by docking a set of molecules representative of all classes of sweet compounds and calculating the free energy of ligand binding. These sites are not easily accessible to sweet proteins, but docking experiments in silico showed that sweet proteins can bind to a secondary site without entering the deep cleft. Our models account for many experimental observations on the tastes of sweeteners, including sweetness synergy, and can help to design new sweeteners.

Quantum-Mechanics Methodologies in Drug Discovery: Applications of Docking and Scoring in Lead Optimization.

PubMed

Crespo, Alejandro; Rodriguez-Granillo, Agustina; Lim, Victoria T

2017-01-01

The development and application of quantum mechanics (QM) methodologies in computer- aided drug design have flourished in the last 10 years. Despite the natural advantage of QM methods to predict binding affinities with a higher level of theory than those methods based on molecular mechanics (MM), there are only a few examples where diverse sets of protein-ligand targets have been evaluated simultaneously. In this work, we review recent advances in QM docking and scoring for those cases in which a systematic analysis has been performed. In addition, we introduce and validate a simplified QM/MM expression to compute protein-ligand binding energies. Overall, QMbased scoring functions are generally better to predict ligand affinities than those based on classical mechanics. However, the agreement between experimental activities and calculated binding energies is highly dependent on the specific chemical series considered. The advantage of more accurate QM methods is evident in cases where charge transfer and polarization effects are important, for example when metals are involved in the binding process or when dispersion forces play a significant role as in the case of hydrophobic or stacking interactions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Structure-based CoMFA as a predictive model - CYP2C9 inhibitors as a test case.

PubMed

Yasuo, Kazuya; Yamaotsu, Noriyuki; Gouda, Hiroaki; Tsujishita, Hideki; Hirono, Shuichi

2009-04-01

In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.

A new insight into mushroom tyrosinase inhibitors: docking, pharmacophore-based virtual screening, and molecular modeling studies.

PubMed

Bagherzadeh, Kowsar; Shirgahi Talari, Faezeh; Sharifi, Amirhossein; Ganjali, Mohammad Reza; Saboury, Ali Akbar; Amanlou, Massoud

2015-01-01

Tyrosinase, a widely spread enzyme in micro-organisms, animals, and plants, participates in two rate-limiting steps in melanin formation pathway which is responsible for skin protection against UV lights' harm whose functional deficiency result in serious dermatological diseases. This enzyme seems to be responsible for neuromelanin formation in human brain as well. In plants, the enzyme leads the browning pathway which is commonly observed in injured tissues that is economically very unfavorable. Among different types of tyrosinase, mushroom tyrosinase has the highest homology with the mammalian tyrosinase and the only commercial tyrosinase available. In this study, ligand-based pharmacophore drug discovery method was applied to rapidly identify mushroom tyrosinase enzyme inhibitors using virtual screening. The model pharmacophore of essential interactions was developed and refined studying already experimentally discovered potent inhibitors employing Docking analysis methodology. After pharmacophore virtual screening and binding modes prediction, 14 compounds from ZINC database were identified as potent inhibitors of mushroom tyrosinase which were classified into five groups according to their chemical structures. The inhibition behavior of the discovered compounds was further studied through Classical Molecular Dynamic Simulations and the conformational changes induced by the presence of the studied ligands were discussed and compared to those of the substrate, tyrosine. According to the obtained results, five novel leads are introduced to be further optimized or directly used as potent inhibitors of mushroom tyrosinase.

Mapping multiple potential ATP binding sites on the matrix side of the bovine ADP/ATP carrier by the combined use of MD simulation and docking.

PubMed

Di Marino, Daniele; Oteri, Francesco; della Rocca, Blasco Morozzo; D'Annessa, Ilda; Falconi, Mattia

2012-06-01

The mitochondrial adenosine diphosphate/adenosine triphosphate (ADP/ATP) carrier-AAC-was crystallized in complex with its specific inhibitor carboxyatractyloside (CATR). The protein consists of a six-transmembrane helix bundle that defines the nucleotide translocation pathway, which is closed towards the matrix side due to sharp kinks in the odd-numbered helices. In this paper, we describe the interaction between the matrix side of the AAC transporter and the ATP(4-) molecule using carrier structures obtained through classical molecular dynamics simulation (MD) and a protein-ligand docking procedure. Fifteen structures were extracted from a previously published MD trajectory through clustering analysis, and 50 docking runs were carried out for each carrier conformation, for a total of 750 runs ("MD docking"). The results were compared to those from 750 docking runs performed on the X-ray structure ("X docking"). The docking procedure indicated the presence of a single interaction site in the X-ray structure that was conserved in the structures extracted from the MD trajectory. MD docking showed the presence of a second binding site that was not found in the X docking. The interaction strategy between the AAC transporter and the ATP(4-) molecule was analyzed by investigating the composition and 3D arrangement of the interaction pockets, together with the orientations of the substrate inside them. A relationship between sequence repeats and the ATP(4-) binding sites in the AAC carrier structure is proposed.

Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and 2.

PubMed

Ritchie, David W

2003-07-01

This article describes and reviews our efforts using Hex 3.1 to predict the docking modes of the seven target protein-protein complexes presented in the CAPRI (Critical Assessment of Predicted Interactions) blind docking trial. For each target, the structure of at least one of the docking partners was given in its unbound form, and several of the targets involved large multimeric structures (e.g., Lactobacillus HPr kinase, hemagglutinin, bovine rotavirus VP6). Here we describe several enhancements to our original spherical polar Fourier docking correlation algorithm. For example, a novel surface sphere smothering algorithm is introduced to generate multiple local coordinate systems around the surface of a large receptor molecule, which may be used to define a small number of initial ligand-docking orientations distributed over the receptor surface. High-resolution spherical polar docking correlations are performed over the resulting receptor surface patches, and candidate docking solutions are refined by using a novel soft molecular mechanics energy minimization procedure. Overall, this approach identified two good solutions at rank 5 or less for two of the seven CAPRI complexes. Subsequent analysis of our results shows that Hex 3.1 is able to place good solutions within a list of

The Binding Mode Prediction and Similar Ligand Potency in the Active Site of Vitamin D Receptor with QM/MM Interaction, MESP, and MD Simulation.

PubMed

Selvaraman, Nagamani; Selvam, Saravana Kumar; Muthusamy, Karthikeyan

2016-08-01

Non-secosteroidal ligands are well-known vitamin D receptor (VDR) agonists. In this study, we described a combined QM/MM to define the protein-ligand interaction energy a strong positive correlation in both QM-MM interaction energy and binding free energy against the biological activity. The molecular dynamics simulation study was performed, and specific interactions were extensively studied. The molecular docking results and surface analysis shed light on steric and electrostatic complementarities of these non-secosteroidal ligands to VDR. Finally, the drug likeness properties were also calculated and found within the acceptable range. The results show that bulky group substitutions in side chain decrease the VDR activity, whereas a small substitution increased it. Functional analyses of H393A and H301A mutations substantiate their roles in the VDR agonistic and antagonistic activities. Apart from the His393 and His301, two other amino acids in the hinge region viz. Ser233 and Arg270 acted as an electron donor/acceptor specific to the agonist in the distinct ligand potency. The results from this study disclose the binding mechanism of VDR agonists and structural modifications required to improve the selectivity. © 2016 John Wiley & Sons A/S.

Critical evaluation of methods to incorporate entropy loss upon binding in high-throughput docking.

PubMed

Salaniwal, Sumeet; Manas, Eric S; Alvarez, Juan C; Unwalla, Rayomand J

2007-02-01

Proper accounting of the positional/orientational/conformational entropy loss associated with protein-ligand binding is important to obtain reliable predictions of binding affinity. Herein, we critically examine two simplified statistical mechanics-based approaches, namely a constant penalty per rotor method, and a more rigorous method, referred to here as the partition function-based scoring (PFS) method, to account for such entropy losses in high-throughput docking calculations. Our results on the estrogen receptor beta and dihydrofolate reductase proteins demonstrate that, while the constant penalty method over-penalizes molecules for their conformational flexibility, the PFS method behaves in a more "DeltaG-like" manner by penalizing different rotors differently depending on their residual entropy in the bound state. Furthermore, in contrast to no entropic penalty or the constant penalty approximation, the PFS method does not exhibit any bias towards either rigid or flexible molecules in the hit list. Preliminary enrichment studies using a lead-like random molecular database suggest that an accurate representation of the "true" energy landscape of the protein-ligand complex is critical for reliable predictions of relative binding affinities by the PFS method. Copyright 2006 Wiley-Liss, Inc.

Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR.

PubMed

Westermaier, Yvonne; Ruiz-Carmona, Sergio; Theret, Isabelle; Perron-Sierra, Françoise; Poissonnet, Guillaume; Dacquet, Catherine; Boutin, Jean A; Ducrot, Pierre; Barril, Xavier

2017-08-01

The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

Antiprotozoal Nitazoxanide Derivatives: Synthesis, Bioassays and QSAR Study Combined with Docking for Mechanistic Insight

PubMed Central

Scior, Thomas; Lozano-Aponte, Jorge; Ajmani, Subhash; Hernández-Montero, Eduardo; Chávez-Silva, Fabiola; Hernández-Núñez, Emanuel; Moo-Puc, Rosa; Fraguela-Collar, Andres; Navarrete-Vázquez, Gabriel

2015-01-01

In view of the serious health problems concerning infectious diseases in heavily populated areas, we followed the strategy of lead compound diversification to evaluate the near-by chemical space for new organic compounds. To this end, twenty derivatives of nitazoxanide (NTZ) were synthesized and tested for activity against Entamoeba histolytica parasites. To ensure drug-likeliness and activity relatedness of the new compounds, the synthetic work was assisted by a quantitative structure-activity relationships study (QSAR). Many of the inherent downsides – well-known to QSAR practitioners – we circumvented thanks to workarounds which we proposed in prior QSAR publication. To gain further mechanistic insight on a molecular level, ligand-enzyme docking simulations were carried out since NTZ is known to inhibit the protozoal pyruvate ferredoxin oxidoreductase (PFOR) enzyme as its biomolecular target. PMID:25872791