Accessible high-throughput virtual screening molecular docking software for students and educators.
Jacob, Reed B; Andersen, Tim; McDougal, Owen M
2012-05-01
We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.
On the computation of molecular surface correlations for protein docking using fourier techniques.
Sakk, Eric
2007-08-01
The computation of surface correlations using a variety of molecular models has been applied to the unbound protein docking problem. Because of the computational complexity involved in examining all possible molecular orientations, the fast Fourier transform (FFT) (a fast numerical implementation of the discrete Fourier transform (DFT)) is generally applied to minimize the number of calculations. This approach is rooted in the convolution theorem which allows one to inverse transform the product of two DFTs in order to perform the correlation calculation. However, such a DFT calculation results in a cyclic or "circular" correlation which, in general, does not lead to the same result as the linear correlation desired for the docking problem. In this work, we provide computational bounds for constructing molecular models used in the molecular surface correlation problem. The derived bounds are then shown to be consistent with various intuitive guidelines previously reported in the protein docking literature. Finally, these bounds are applied to different molecular models in order to investigate their effect on the correlation calculation.
Pevzner, Yuri; Frugier, Emilie; Schalk, Vinushka; Caflisch, Amedeo; Woodcock, H Lee
2014-09-22
Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser. One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing's capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of "re-dockings" with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing's docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening.
2015-01-01
Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser.1 One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing’s capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of “re-dockings” with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing’s docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening. PMID:25151852
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.
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
AnchorDock: Blind and Flexible Anchor-Driven Peptide Docking.
Ben-Shimon, Avraham; Niv, Masha Y
2015-05-05
The huge conformational space stemming from the inherent flexibility of peptides is among the main obstacles to successful and efficient computational modeling of protein-peptide interactions. Current peptide docking methods typically overcome this challenge using prior knowledge from the structure of the complex. Here we introduce AnchorDock, a peptide docking approach, which automatically targets the docking search to the most relevant parts of the conformational space. This is done by precomputing the free peptide's structure and by computationally identifying anchoring spots on the protein surface. Next, a free peptide conformation undergoes anchor-driven simulated annealing molecular dynamics simulations around the predicted anchoring spots. In the challenging task of a completely blind docking test, AnchorDock produced exceptionally good results (backbone root-mean-square deviation ≤ 2.2Å, rank ≤15) for 10 of 13 unbound cases tested. The impressive performance of AnchorDock supports a molecular recognition pathway that is driven via pre-existing local structural elements. Copyright © 2015 Elsevier Ltd. All rights reserved.
Molecular Docking and Drug Discovery in β-Adrenergic Receptors.
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.
DOVIS 2.0: An Efficient and Easy to Use Parallel Virtual Screening Tool Based on AutoDock 4.0
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
Multilevel Parallelization of AutoDock 4.2.
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.
Bharatham, Nagakumar; Finch, Kristin E; Min, Jaeki; Mayasundari, Anand; Dyer, Michael A; Guy, R Kiplin; Bashford, Donald
2017-06-01
A virtual screening protocol involving docking and molecular dynamics has been tested against the results of fluorescence polarization assays testing the potency of a series of compounds of the nutlin class for inhibition of the interaction between p53 and Mdmx, an interaction identified as a driver of certain cancers. The protocol uses a standard docking method (AutoDock) with a cutoff based on the AutoDock score (ADscore), followed by molecular dynamics simulation with a cutoff based on root-mean-square-deviation (RMSD) from the docked pose. An analysis of the experimental and computational results shows modest performance of ADscore alone, but dramatically improved performance when RMSD is also used. Published by Elsevier Inc.
DockScreen: A database of in silico biomolecular interactions to support computational toxicology
We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...
Computational exploration of a protein receptor binding space with student proposed peptide ligands.
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.
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…
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.
Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan
2014-01-01
Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets. PMID:24498255
Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan
2014-01-01
Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.
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.
Bio-inspired algorithms applied to molecular docking simulations.
Heberlé, G; de Azevedo, W F
2011-01-01
Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.
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.
Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands
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
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.
Schumann, Marcel; Armen, Roger S
2013-05-30
Molecular docking of small-molecules is an important procedure for computer-aided drug design. Modeling receptor side chain flexibility is often important or even crucial, as it allows the receptor to adopt new conformations as induced by ligand binding. However, the accurate and efficient incorporation of receptor side chain flexibility has proven to be a challenge due to the huge computational complexity required to adequately address this problem. Here we describe a new docking approach with a very fast, graph-based optimization algorithm for assignment of the near-optimal set of residue rotamers. We extensively validate our approach using the 40 DUD target benchmarks commonly used to assess virtual screening performance and demonstrate a large improvement using the developed side chain optimization over rigid receptor docking (average ROC AUC of 0.693 vs. 0.623). Compared to numerous benchmarks, the overall performance is better than nearly all other commonly used procedures. Furthermore, we provide a detailed analysis of the level of receptor flexibility observed in docking results for different classes of residues and elucidate potential avenues for further improvement. Copyright © 2013 Wiley Periodicals, Inc.
Morgnanesi, Dante; Heinrichs, Eric J; Mele, Anthony R; Wilkinson, Sean; Zhou, Suzanne; Kulp, John L
2015-11-01
Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B." Copyright © 2015 Elsevier B.V. All rights reserved.
Barakat, Assem; Ghabbour, Hazem A; Al-Majid, Abdullah Mohammed; Soliman, Saied M; Ali, M; Mabkhot, Yahia Nasser; Shaik, Mohammed Rafi; Fun, Hoong-Kun
2015-07-21
The synthesis of 2,6-bis(hydroxy(phenyl)methyl)cyclohexanone 1 is described. The molecular structure of the title compound 1 was confirmed by NMR, FT-IR, MS, CHN microanalysis, and X-ray crystallography. The molecular structure was also investigated by a set of computational studies and found to be in good agreement with the experimental data obtained from the various spectrophotometric techniques. The antimicrobial activity and molecular docking of the synthesized compound was investigated.
Moghadam, Neda Hosseinpour; Salehzadeh, Sadegh; Shahabadi, Nahid
2017-09-02
The interaction of calf thymus DNA with nevirapine at physiological pH was studied by using absorption, circular dichroism, viscosity, differential pulse voltammetry, fluorescence techniques, salt effect studies and computational methods. The drug binds to ct-DNA in a groove binding mode, as shown by slight variation in the viscosity of ct-DNA. Furthermore, competitive fluorimetric studies with Hoechst 33258 indicate that nevirapine binds to DNA via groove binding. Moreover, the structure of nevirapine was optimized by DFT calculations and was used for the molecular docking calculations. The molecular docking results suggested that nevirapine prefers to bind on the minor groove of ct-DNA.
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.
Berlin, Konstantin; O’Leary, Dianne P.; Fushman, David
2011-01-01
We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. PMID:21604302
Berlin, Konstantin; O'Leary, Dianne P; Fushman, David
2011-07-01
We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. Copyright © 2011 Wiley-Liss, Inc.
NASA Astrophysics Data System (ADS)
Leenaraj, D. R.; Hubert Joe, I.
2017-06-01
Spectral features of non-opioid analgesic drug flupirtine have been explored by the Fourier transform infrared, Raman and Nuclear magnetic resonance spectroscopic techniques combined with density functional theory computations. The bioactive conformer of flupirtine is stabilized by an intramolecular Csbnd H⋯N hydrogen bonding resulting by the steric strain of hydrogen atoms. Natural bond orbital and natural population analysis support this result. The charge redistribution also has been analyzed. Antimicrobial activities of flupirtine have been screened by agar well disc diffusion and molecular docking methods, which exposes the importance of triaminopyridine in flupirtine.
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
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.
NASA Astrophysics Data System (ADS)
Suresh, D. M.; Amalanathan, M.; Hubert Joe, I.; Bena Jothy, V.; Diao, Yun-Peng
2014-09-01
The molecular structure, vibrational analysis and molecular docking analysis of the 3-Methyl-1,4-dioxo-1,4-dihydronaphthalen-2-yl 4-aminobenzoate (MDDNAB) molecule have been carried out using FT-IR and FT-Raman spectroscopic techniques and DFT method. The equilibrium geometry, harmonic vibrational wave numbers, various bonding features have been computed using density functional method. The calculated molecular geometry has been compared with experimental data. The detailed interpretation of the vibrational spectra has been carried out by using VEDA program. The hyper-conjugative interactions and charge delocalization have been analyzed using natural bond orbital (NBO) analysis. The simulated FT-IR and FT-Raman spectra satisfactorily coincide with the experimental spectra. The PES and charge analysis have been made. The molecular docking was done to identify the binding energy and the Hydrogen bonding with the cancer protein molecule.
Tiwari, Sameeksha; Awasthi, Manika; Singh, Swati; Pandey, Veda P; Dwivedi, Upendra N
2017-10-23
Protein-protein interactions (PPI) are a new emerging class of novel therapeutic targets. In order to probe these interactions, computational tools provide a convenient and quick method towards the development of therapeutics. Keeping this in view the present study was initiated to analyse interaction of tumour suppressor protein p53 (TP53) and breast cancer associated protein (BRCA1) as promising target against breast cancer. Using computational approaches such as protein-protein docking, hot spot analyses, molecular docking and molecular dynamics simulation (MDS), stepwise analyses of the interactions of the wild type and mutant TP53 with that of wild type BRCA1 and their modulation by alkaloids were done. Protein-protein docking method was used to generate both wild type and mutant complexes of TP53-BRCA1. Subsequently, the complexes were docked using sixteen different alkaloids, fulfilling ADMET and Lipinski's rule of five criteria, and were compared with that of a well-known inhibitor of PPI, namely nutlin. The alkaloid dicentrine was found to be the best docked alkaloid among all the docked alklaloids as well as that of nutlin. Furthermore, MDS analyses of both wild type and mutant complexes with the best docked alkaloid i.e. dicentrine, revealed higher stability of mutant complex than that of the wild one, in terms of average RMSD, RMSF and binding free energy, corroborating the results of docking. Results suggested more pronounced interaction of BRCA1 with mutant TP53 leading to increased expression of mutated TP53 thus showing a dominant negative gain of function and hampering wild type TP53 function leading to tumour progression.
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.
GPU.proton.DOCK: Genuine Protein Ultrafast proton equilibria consistent DOCKing.
Kantardjiev, Alexander A
2011-07-01
GPU.proton.DOCK (Genuine Protein Ultrafast proton equilibria consistent DOCKing) is a state of the art service for in silico prediction of protein-protein interactions via rigorous and ultrafast docking code. It is unique in providing stringent account of electrostatic interactions self-consistency and proton equilibria mutual effects of docking partners. GPU.proton.DOCK is the first server offering such a crucial supplement to protein docking algorithms--a step toward more reliable and high accuracy docking results. The code (especially the Fast Fourier Transform bottleneck and electrostatic fields computation) is parallelized to run on a GPU supercomputer. The high performance will be of use for large-scale structural bioinformatics and systems biology projects, thus bridging physics of the interactions with analysis of molecular networks. We propose workflows for exploring in silico charge mutagenesis effects. Special emphasis is given to the interface-intuitive and user-friendly. The input is comprised of the atomic coordinate files in PDB format. The advanced user is provided with a special input section for addition of non-polypeptide charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. The output is comprised of docked complexes in PDB format as well as interactive visualization in a molecular viewer. GPU.proton.DOCK server can be accessed at http://gpudock.orgchm.bas.bg/.
Yu, Shuling; Yuan, Jintao; Zhang, Yi; Gao, Shufang; Gan, Ying; Han, Meng; Chen, Yuewen; Zhou, Qiaoqiao; Shi, Jiahua
2017-06-01
Sodium-glucose cotransporter 2 (SGLT2) is a promising target for diabetes therapy. We aimed to develop computational approaches to identify structural features for more potential SGLT2 inhibitors. In this work, 46 triazole derivatives as SGLT2 inhibitors were studied using a combination of several approaches, including hologram quantitative structure-activity relationships (HQSAR), topomer comparative molecular field analysis (CoMFA), homology modeling, and molecular docking. HQSAR and topomer CoMFA were used to construct models. Molecular docking was conducted to investigate the interaction of triazole derivatives and homology modeling of SGLT2, as well as to validate the results of the HQSAR and topomer CoMFA models. The most effective HQSAR and topomer CoMFA models exhibited noncross-validated correlation coefficients of 0.928 and 0.891 for the training set, respectively. External predictions were made successfully on a test set and then compared with previously reported models. The graphical results of HQSAR and topomer CoMFA were proven to be consistent with the binding mode of the inhibitors and SGLT2 from molecular docking. The models and docking provided important insights into the design of potent inhibitors for SGLT2.
NASA Astrophysics Data System (ADS)
Abdelhameed, Ali S.; Alanazi, Amer M.; Bakheit, Ahmed H.; Darwish, Hany W.; Ghabbour, Hazem A.; Darwish, Ibrahim A.
2017-01-01
Binding of the recently introduced anti-cancer drug, crizotinib (CRB) with the bovine serum albumin (BSA) was comprehensively studied with the aid of fluorescence and UV-Vis spectroscopic as well as molecular docking techniques. The collective results of the study under the simulated physiological conditions proposed a static type of binding occurring between the CRB and BSA with binding constants of 104 L mol- 1. BSA conformational changes were investigated using three dimensional (3D) and synchronous fluorescence measurements. Moreover, the results of site marker competitive experiments and molecular docking, it could be deduced that CRB was inserted into the subdomain IIA (site I) of BSA yielding a more stabilized system. This was further confirmed with the molecular docking results which revealed that CRB is located in the active site residues Try149, Glu152, Ser191, Arg194, Arg198, Trp213, Arg217, Arg256, His287, Ala290, Glu291, Ser343, Asp450 within a radius of 6 Å. Combining the molecular docking studies and the computed thermodynamic parameters, it can be inferred that hydrophobic and electrostatic interactions are the major binding forces involved in formation of the CRB-BSA complex.
Rampogu, Shailima; Baek, Ayoung; Gajula, Rajesh Goud; Zeb, Amir; Bavi, Rohit S; Kumar, Raj; Kim, Yongseong; Kwon, Yong Jung; Lee, Keun Woo
2018-04-02
Antibiotic resistance is a defense mechanism, harbored by pathogens to survive under unfavorable conditions. Among several antibiotic resistant microbial consortium, Staphylococcus aureus is one of the most havoc microorganisms. Staphylococcus aureus encodes a unique enzyme 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (SaHPPK), against which, none of existing antibiotics have been reported. Computational approaches have been instrumental in designing and discovering new drugs for several diseases. The present study highlights the impact of ginger phytochemicals on Staphylococcus aureus SaHPPK. Herein, we have retrieved eight ginger phytochemicals from published literature and investigated their inhibitory interactions with SaHPPK. To authenticate our work, the investigation proceeds considering the known antibiotics alongside the phytochemicals. Molecular docking was performed employing GOLD and CDOCKER. The compounds with the highest dock score from both the docking programmes were tested for their inhibitory capability in vitro. The binding conformations that were seated within the binding pocket showing strong interactions with the active sites residues rendered by highest dock score were forwarded towards the molecular dynamic (MD) simulation analysis. Based on molecular dock scores, molecular interaction with catalytic active residues and MD simulations studies, two ginger phytochemicals, gingerenone-A and shogaol have been proposed as candidate inhibitors against Staphylococcus aureus. They have demonstrated higher dock scores than the known antibiotics and have represented interactions with the key residues within the active site. Furthermore, these compounds have rendered considerable inhibitory activity when tested in vitro. Additionally, their superiority was corroborated by stable MD results conducted for 100 ns employing GROMACS package. Finally, we suggest that gingerenone-A and shogaol may either be potential SaHPPK inhibitors or can be used as fundamental platforms for novel SaHPPK inhibitor development.
NASA Astrophysics Data System (ADS)
Aouidate, Adnane; Ghaleb, Adib; Ghamali, Mounir; Chtita, Samir; Choukrad, M'barek; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar
2017-07-01
A series of nineteen DHFR inhibitors was studied based on the combination of two computational techniques namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were developed using 19 molecules having pIC50 ranging from 9.244 to 5.839. The best CoMFA and CoMSIA models show conventional determination coefficients R2 of 0.96 and 0.93 as well as the Leave One Out cross-validation determination coefficients Q2 of 0.64 and 0.72, respectively. The predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R2test of 0.92 and 0.94, respectively. The binding mode between this kind of compounds and the DHFR enzyme in addition to the key amino acid residues were explored by molecular docking simulation. Contour maps and molecular docking identified that the R1 and R2 natures at the pyrazole moiety are the important features for the optimization of the binding affinity to the DHFR receptor. According to the good concordance between the CoMFA/CoMSIA contour maps and docking results, the obtained information was explored to design novel molecules.
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.
Power transformations improve interpolation of grids for molecular mechanics interaction energies.
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.
Suresh, D M; Amalanathan, M; Joe, I Hubert; Jothy, V Bena; Diao, Yun-Peng
2014-09-15
The molecular structure, vibrational analysis and molecular docking analysis of the 3-Methyl-1,4-dioxo-1,4-dihydronaphthalen-2-yl 4-aminobenzoate (MDDNAB) molecule have been carried out using FT-IR and FT-Raman spectroscopic techniques and DFT method. The equilibrium geometry, harmonic vibrational wave numbers, various bonding features have been computed using density functional method. The calculated molecular geometry has been compared with experimental data. The detailed interpretation of the vibrational spectra has been carried out by using VEDA program. The hyper-conjugative interactions and charge delocalization have been analyzed using natural bond orbital (NBO) analysis. The simulated FT-IR and FT-Raman spectra satisfactorily coincide with the experimental spectra. The PES and charge analysis have been made. The molecular docking was done to identify the binding energy and the Hydrogen bonding with the cancer protein molecule. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Isvoran, Adriana
2016-03-01
Assessment of the effects of the herbicides nicosulfuron and chlorsulfuron and the fungicides difenoconazole and drazoxlone upon catalase produced by soil microorganism Proteus mirabilis is performed using the molecular docking technique. The interactions of pesticides with the enzymes are predicted using SwissDock and PatchDock docking tools. There are correlations for predicted binding energy values for enzyme-pesticide complexes obtained using the two docking tools, all the considered pesticides revealing favorable binding to the enzyme, but only the herbicides bind to the catalytic site. These results suggest the inhibitory potential of chlorsulfuron and nicosulfuron on the catalase activity in soil.
Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein-Protein Encounters.
Pallara, Chiara; Rueda, Manuel; Abagyan, Ruben; Fernández-Recio, Juan
2016-07-12
To understand cellular processes at the molecular level we need to improve our knowledge of protein-protein interactions, from a structural, mechanistic, and energetic point of view. Current theoretical studies and computational docking simulations show that protein dynamics plays a key role in protein association and support the need for including protein flexibility in modeling protein interactions. Assuming the conformational selection binding mechanism, in which the unbound state can sample bound conformers, one possible strategy to include flexibility in docking predictions would be the use of conformational ensembles originated from unbound protein structures. Here we present an exhaustive computational study about the use of precomputed unbound ensembles in the context of protein docking, performed on a set of 124 cases of the Protein-Protein Docking Benchmark 3.0. Conformational ensembles were generated by conformational optimization and refinement with MODELLER and by short molecular dynamics trajectories with AMBER. We identified those conformers providing optimal binding and investigated the role of protein conformational heterogeneity in protein-protein recognition. Our results show that a restricted conformational refinement can generate conformers with better binding properties and improve docking encounters in medium-flexible cases. For more flexible cases, a more extended conformational sampling based on Normal Mode Analysis was proven helpful. We found that successful conformers provide better energetic complementarity to the docking partners, which is compatible with recent views of binding association. In addition to the mechanistic considerations, these findings could be exploited for practical docking predictions of improved efficiency.
Hathout, Rania M; Metwally, Abdelkader A
2016-11-01
This study represents one of the series applying computer-oriented processes and tools in digging for information, analysing data and finally extracting correlations and meaningful outcomes. In this context, binding energies could be used to model and predict the mass of loaded drugs in solid lipid nanoparticles after molecular docking of literature-gathered drugs using MOE® software package on molecularly simulated tripalmitin matrices using GROMACS®. Consequently, Gaussian processes as a supervised machine learning artificial intelligence technique were used to correlate the drugs' descriptors (e.g. M.W., xLogP, TPSA and fragment complexity) with their molecular docking binding energies. Lower percentage bias was obtained compared to previous studies which allows the accurate estimation of the loaded mass of any drug in the investigated solid lipid nanoparticles by just projecting its chemical structure to its main features (descriptors). Copyright © 2016 Elsevier B.V. All rights reserved.
Machine learning in computational docking.
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.
Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.
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.
Clustering molecular dynamics trajectories for optimizing docking experiments.
De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C
2015-01-01
Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.
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.
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
Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki
2013-01-01
Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846
Xia, Pu; Mou, Fei-Fei; Wang, Li-Wei
2012-01-01
Non-small-cell lung cancer (NSCLC) is a leading cause of cancer deaths worldwide. Crizotinib has been approved by the U.S. Food and Drug Administration for the treatment of patients with advanced NSCLC. However, understanding of mechanisms of action is still limited. In our studies, we confirmed crizotinib-induced apoptosis in A549 lung cancer cells. In order to assess mechanisms, small molecular docking technology was used as a preliminary simulation of signaling pathways. Interesting, our results of experiments were consistent with the results of computer simulation. This indicates that small molecular docking technology should find wide use for its reliability and convenience.
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
Xie, Huiding; Li, Yupeng; Yu, Fang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun
2015-11-16
In the recent cancer treatment, B-Raf kinase is one of key targets. Nowadays, a group of imidazopyridines as B-Raf kinase inhibitors have been reported. In order to investigate the interaction between this group of inhibitors and B-Raf kinase, molecular docking, molecular dynamic (MD) simulation and binding free energy (ΔGbind) calculation were performed in this work. Molecular docking was carried out to identify the key residues in the binding site, and MD simulations were performed to determine the detail binding mode. The results obtained from MD simulation reveal that the binding site is stable during the MD simulations, and some hydrogen bonds (H-bonds) in MD simulations are different from H-bonds in the docking mode. Based on the obtained MD trajectories, ΔGbind was computed by using Molecular Mechanics Generalized Born Surface Area (MM-GBSA), and the obtained energies are consistent with the activities. An energetic analysis reveals that both electrostatic and van der Waals contributions are important to ΔGbind, and the unfavorable polar solvation contribution results in the instability of the inhibitor with the lowest activity. These results are expected to understand the binding between B-Raf and imidazopyridines and provide some useful information to design potential B-Raf inhibitors.
Developing and evaluating prediactive strategies to elucidate the mode of biological activity of environmental chemicals is a major objective of the concerted efforts of the US-EPA's computational toxicology program.
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.
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.
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
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.
Computational Optimization and Characterization of Molecularly Imprinted Polymers
NASA Astrophysics Data System (ADS)
Terracina, Jacob J.
Molecularly imprinted polymers (MIPs) are a class of materials containing sites capable of selectively binding to the imprinted target molecule. Computational chemistry techniques were used to study the effect of different fabrication parameters (the monomer-to-target ratios, pre-polymerization solvent, temperature, and pH) on the formation of the MIP binding sites. Imprinted binding sites were built in silico for the purposes of better characterizing the receptor - ligand interactions. Chiefly, the sites were characterized with respect to their selectivities and the heterogeneity between sites. First, a series of two-step molecular mechanics (MM) and quantum mechanics (QM) computational optimizations of monomer -- target systems was used to determine optimal monomer-to-target ratios for the MIPs. Imidazole- and xanthine-derived target molecules were studied. The investigation included both small-scale models (one-target) and larger scale models (five-targets). The optimal ratios differed between the small and larger scales. For the larger models containing multiple targets, binding-site surface area analysis was used to evaluate the heterogeneity of the sites. The more fully surrounded sites had greater binding energies. Molecular docking was then used to measure the selectivities of the QM-optimized binding sites by comparing the binding energies of the imprinted target to that of a structural analogue. Selectivity was also shown to improve as binding sites become more fully encased by the monomers. For internal sites, docking consistently showed selectivity favoring the molecules that had been imprinted via QM geometry optimizations. The computationally imprinted sites were shown to exhibit size-, shape-, and polarity-based selectivity. This represented a novel approach to investigate the selectivity and heterogeneity of imprinted polymer binding sites, by applying the rapid orientation screening of MM docking to the highly accurate QM-optimized geometries. Next, we sought to computationally construct and investigate binding sites for their enantioselectivity. Again, a two-step MM [special characters removed] QM optimization scheme was used to "computationally imprint" chiral molecules. Using docking techniques, the imprinted binding sites were shown to exhibit an enantioselective preference for the imprinted molecule over its enantiomer. Docking of structurally similar chiral molecules showed that the sites computationally imprinted with R- or S-tBOC-tyrosine were able to differentiate between R- and S-forms of other tyrosine derivatives. The cross-enantioselectivity did not hold for chiral molecules that did not share the tyrosine H-bonding functional group orientations. Further analysis of the individual monomer - target interactions within the binding site led us to conclude that H-bonding functional groups that are located immediately next to the target's chiral center, and therefore spatially fixed relative to the chiral center, will have a stronger contribution to the enantioselectivity of the site than those groups separated from the chiral center by two or more rotatable bonds. These models were the first computationally imprinted binding sites to exhibit this enantioselective preference for the imprinted target molecules. Finally, molecular dynamics (MD) was used to quantify H-bonding interactions between target molecules, monomers, and solvents representative of the pre-polymerization matrix. It was found that both target dimerization and solvent interference decrease the number of monomer - target H-bonds present. Systems were optimized via simulated annealing to create binding sites that were then subjected to molecular docking analysis. Docking showed that the presence of solvent had a detrimental effect on the sensitivity and selectivity of the sites, and that solvents with more H-bonding capabilities were more disruptive to the binding properties of the site. Dynamic simulations also showed that increasing the temperature of the solution can significantly decrease the number of H-bonds formed between the targets and monomers. It is believed that the monomer - target complexes formed within the pre-polymerization matrix are translated into the selective binding cavities formed during polymerization. Elucidating the nature of these interactions in silico improves our understanding of MIPs, ultimately allowing for more optimized sensing materials.
Zhou, Jing; Ma, Hong-yue; Fan, Xin-sheng; Xiao, Wei; Wang, Tuan-jie
2012-10-01
To investigate the mechanism of binding of human serum albumin (HSA) with potential sensitinogen, including chlorogenic acid and two isochlorogenic acids (3,4-di-O-caffeoylquinic acid and 3,5-di-O-caffeoylquinic acid). By using the docking algorithm of computer-aided molecular design and the Molegro Virtual Docker, the crystal structures of HSA with warfarin and diazepam (Protein Data Bank ID: 2BXD and 2BXF) were selected as molecular docking receptors of HSA sites I and II. According to docking scores, key residues and H-bond, the molecular docking mode was selected and confirmed. The molecular docking of chlorogenic acid and two isochlorogenic acids on sites I and II was compared based on the above design. The results from molecular docking indicated that chlorogenic acid, 3,4-di-O-caffeoylquinic acid and 3,5-di-O-caffeoylquinic acid could bind to HSA site I by high affinity scores of -112.3, -155.3 and -153.1, respectively. They could bind to site II on HSA by high affinity scores of -101.7, -138.5 and -133.4, respectively. In site I, two isochlorogenic acids interacted with the key apolar side-chains of Leu238 and Ala291 by higher affinity scores than chlorogenic acid. Furthermore, the H-bonds of isochlorogenic acids with polar residues inside the pocket and at the entrance of the pocket were different from chlorogenic acid. Moreover, the second coffee acyl of isochlorogenic acid occupied the right-hand apolar compartment in the pocket of HSA site I. In site I, the second coffee acyl of isochlorogenic acid formed the H-bonds with polar side-chains, which contributed isochlorogenic acid to binding with site II of HSA. The isochlorogenic acids with two coffee acyls have higher binding abilities with HSA than chlorogenic acid with one coffee acyl, suggesting that isochlorogenic acids binding with HSA may be sensitinogen.
Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments
De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.
2015-01-01
Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944
Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei
2017-06-09
p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.
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.
GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing
Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal
2016-01-01
Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300
GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.
Fang, Ye; Ding, Yun; Feinstein, Wei P; Koppelman, David M; Moreno, Juana; Jarrell, Mark; Ramanujam, J; Brylinski, Michal
2016-01-01
Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.
NASA Astrophysics Data System (ADS)
Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola
2002-06-01
Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.
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…
Fragment-based drug discovery and molecular docking in drug design.
Wang, Tao; Wu, Mian-Bin; Chen, Zheng-Jie; Chen, Hua; Lin, Jian-Ping; Yang, Li-Rong
2015-01-01
Fragment-based drug discovery (FBDD) has caused a revolution in the process of drug discovery and design, with many FBDD leads being developed into clinical trials or approved in the past few years. Compared with traditional high-throughput screening, it displays obvious advantages such as efficiently covering chemical space, achieving higher hit rates, and so forth. In this review, we focus on the most recent developments of FBDD for improving drug discovery, illustrating the process and the importance of FBDD. In particular, the computational strategies applied in the process of FBDD and molecular-docking programs are highlighted elaborately. In most cases, docking is used for predicting the ligand-receptor interaction modes and hit identification by structurebased virtual screening. The successful cases of typical significance and the hits identified most recently are discussed.
Protein-Protein Docking with F2Dock 2.0 and GB-Rerank
Chowdhury, Rezaul; Rasheed, Muhibur; Keidel, Donald; Moussalem, Maysam; Olson, Arthur; Sanner, Michel; Bajaj, Chandrajit
2013-01-01
Motivation Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F2 Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA) based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error. Results The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F2 Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F2 Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F2 Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F2 Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other. Availability The docking protocol has been implemented as a server with a graphical client (TexMol) which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dock.shtml. Client: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dockclient.shtml. PMID:23483883
Wu, Guosheng; Robertson, Daniel H; Brooks, Charles L; Vieth, Michal
2003-10-01
The influence of various factors on the accuracy of protein-ligand docking is examined. The factors investigated include the role of a grid representation of protein-ligand interactions, the initial ligand conformation and orientation, the sampling rate of the energy hyper-surface, and the final minimization. A representative docking method is used to study these factors, namely, CDOCKER, a molecular dynamics (MD) simulated-annealing-based algorithm. A major emphasis in these studies is to compare the relative performance and accuracy of various grid-based approximations to explicit all-atom force field calculations. In these docking studies, the protein is kept rigid while the ligands are treated as fully flexible and a final minimization step is used to refine the docked poses. A docking success rate of 74% is observed when an explicit all-atom representation of the protein (full force field) is used, while a lower accuracy of 66-76% is observed for grid-based methods. All docking experiments considered a 41-member protein-ligand validation set. A significant improvement in accuracy (76 vs. 66%) for the grid-based docking is achieved if the explicit all-atom force field is used in a final minimization step to refine the docking poses. Statistical analysis shows that even lower-accuracy grid-based energy representations can be effectively used when followed with full force field minimization. The results of these grid-based protocols are statistically indistinguishable from the detailed atomic dockings and provide up to a sixfold reduction in computation time. For the test case examined here, improving the docking accuracy did not necessarily enhance the ability to estimate binding affinities using the docked structures. Copyright 2003 Wiley Periodicals, Inc.
Ramírez, David; Caballero, Julio
2018-04-28
Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.
Bajaj, Chandrajit; Chen, Shun-Chuan; Rand, Alexander
2011-01-01
In order to compute polarization energy of biomolecules, we describe a boundary element approach to solving the linearized Poisson-Boltzmann equation. Our approach combines several important features including the derivative boundary formulation of the problem and a smooth approximation of the molecular surface based on the algebraic spline molecular surface. State of the art software for numerical linear algebra and the kernel independent fast multipole method is used for both simplicity and efficiency of our implementation. We perform a variety of computational experiments, testing our method on a number of actual proteins involved in molecular docking and demonstrating the effectiveness of our solver for computing molecular polarization energy. PMID:21660123
USDA-ARS?s Scientific Manuscript database
Molecular field topology analysis, scaffold hopping, and molecular docking were used as complementary computational tools for the design of repellents for Aedes aegypti, the insect vector for yellow fever, West Nile fever, and dengue fever. A large number of analogues were evaluated by virtual scree...
Erickson, Jon A; Jalaie, Mehran; Robertson, Daniel H; Lewis, Richard A; Vieth, Michal
2004-01-01
The key to success for computational tools used in structure-based drug design is the ability to accurately place or "dock" a ligand in the binding pocket of the target of interest. In this report we examine the effect of several factors on docking accuracy, including ligand and protein flexibility. To examine ligand flexibility in an unbiased fashion, a test set of 41 ligand-protein cocomplex X-ray structures were assembled that represent a diversity of size, flexibility, and polarity with respect to the ligands. Four docking algorithms, DOCK, FlexX, GOLD, and CDOCKER, were applied to the test set, and the results were examined in terms of the ability to reproduce X-ray ligand positions within 2.0A heavy atom root-mean-square deviation. Overall, each method performed well (>50% accuracy) but for all methods it was found that docking accuracy decreased substantially for ligands with eight or more rotatable bonds. Only CDOCKER was able to accurately dock most of those ligands with eight or more rotatable bonds (71% accuracy rate). A second test set of structures was gathered to examine how protein flexibility influences docking accuracy. CDOCKER was applied to X-ray structures of trypsin, thrombin, and HIV-1-protease, using protein structures bound to several ligands and also the unbound (apo) form. Docking experiments of each ligand to one "average" structure and to the apo form were carried out, and the results were compared to docking each ligand back to its originating structure. The results show that docking accuracy falls off dramatically if one uses an average or apo structure. In fact, it is shown that the drop in docking accuracy mirrors the degree to which the protein moves upon ligand binding.
Computational fishing of new DNA methyltransferase inhibitors from natural products.
Maldonado-Rojas, Wilson; Olivero-Verbel, Jesus; Marrero-Ponce, Yovani
2015-07-01
DNA methyltransferase inhibitors (DNMTis) have become an alternative for cancer therapies. However, only two DNMTis have been approved as anticancer drugs, although with some restrictions. Natural products (NPs) are a promising source of drugs. In order to find NPs with novel chemotypes as DNMTis, 47 compounds with known activity against these enzymes were used to build a LDA-based QSAR model for active/inactive molecules (93% accuracy) based on molecular descriptors. This classifier was employed to identify potential DNMTis on 800 NPs from NatProd Collection. 447 selected compounds were docked on two human DNA methyltransferase (DNMT) structures (PDB codes: 3SWR and 2QRV) using AutoDock Vina and Surflex-Dock, prioritizing according to their score values, contact patterns at 4 Å and molecular diversity. Six consensus NPs were identified as virtual hits against DNMTs, including 9,10-dihydro-12-hydroxygambogic, phloridzin, 2',4'-dihydroxychalcone 4'-glucoside, daunorubicin, pyrromycin and centaurein. This method is an innovative computational strategy for identifying DNMTis, useful in the identification of potent and selective anticancer drugs. Copyright © 2015 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Almutairi, Maha S.; Zakaria, Azza S.; Ignasius, P. Primsa; Al-Wabli, Reem I.; Joe, Isaac Hubert; Attia, Mohamed I.
2018-02-01
Indole-isatin molecular hybrids 5a-i have been synthesized and characterized by different spectroscopic methods to be evaluated as new antimicrobial agents against a panel of Gram positive bacteria, Gram negative bacteria, and moulds. Compound 5h was selected as a representative example of the prepared compounds 5a-i to perform computational investigations. Its vibrational properties have been studied using FT-IR and FT-Raman with the aid of density functional theory approach. The natural bond orbital analysis as well as HOMO and LUMO molecular orbitals investigations of compound 5h were carried out to explore its possible intermolecular delocalization or hyperconjugation and its possible interactions with the target protein. Molecular docking of compound 5h predicted its binding mode with the fungal target protein.
Recent progress and future directions in protein-protein docking.
Ritchie, David W
2008-02-01
This article gives an overview of recent progress in protein-protein docking and it identifies several directions for future research. Recent results from the CAPRI blind docking experiments show that docking algorithms are steadily improving in both reliability and accuracy. Current docking algorithms employ a range of efficient search and scoring strategies, including e.g. fast Fourier transform correlations, geometric hashing, and Monte Carlo techniques. These approaches can often produce a relatively small list of up to a few thousand orientations, amongst which a near-native binding mode is often observed. However, despite the use of improved scoring functions which typically include models of desolvation, hydrophobicity, and electrostatics, current algorithms still have difficulty in identifying the correct solution from the list of false positives, or decoys. Nonetheless, significant progress is being made through better use of bioinformatics, biochemical, and biophysical information such as e.g. sequence conservation analysis, protein interaction databases, alanine scanning, and NMR residual dipolar coupling restraints to help identify key binding residues. Promising new approaches to incorporate models of protein flexibility during docking are being developed, including the use of molecular dynamics snapshots, rotameric and off-rotamer searches, internal coordinate mechanics, and principal component analysis based techniques. Some investigators now use explicit solvent models in their docking protocols. Many of these approaches can be computationally intensive, although new silicon chip technologies such as programmable graphics processor units are beginning to offer competitive alternatives to conventional high performance computer systems. As cryo-EM techniques improve apace, docking NMR and X-ray protein structures into low resolution EM density maps is helping to bridge the resolution gap between these complementary techniques. The use of symmetry and fragment assembly constraints are also helping to make possible docking-based predictions of large multimeric protein complexes. In the near future, the closer integration of docking algorithms with protein interface prediction software, structural databases, and sequence analysis techniques should help produce better predictions of protein interaction networks and more accurate structural models of the fundamental molecular interactions within the cell.
NASA Astrophysics Data System (ADS)
Asath, R. Mohamed; Rekha, T. N.; Premkumar, S.; Mathavan, T.; Benial, A. Milton Franklin
2016-12-01
Conformational analysis was carried out for N-(5-aminopyridin-2-yl)acetamide (APA) molecule. The most stable, optimized structure was predicted by the density functional theory calculations using the B3LYP functional with cc-pVQZ basis set. The optimized structural parameters and vibrational frequencies were calculated. The experimental and theoretical vibrational frequencies were assigned and compared. Ultraviolet-visible spectrum was simulated and validated experimentally. The molecular electrostatic potential surface was simulated. Frontier molecular orbitals and related molecular properties were computed, which reveals that the higher molecular reactivity and stability of the APA molecule and further density of states spectrum was simulated. The natural bond orbital analysis was also performed to confirm the bioactivity of the APA molecule. Antidiabetic activity was studied based on the molecular docking analysis and the APA molecule was identified that it can act as a good inhibitor against diabetic nephropathy.
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
Pahari, Biswapathik; Chakraborty, Sandipan; Sengupta, Pradeep K
2018-09-15
We explored the encapsulation of dietary plant flavonols fisetin and its chromophore 3-hydroxyflavone, within 2-hydroxypropyl-γ-cyclodextrin (HPγ-CDx) nano-cavity in aqueous solution using multi-spectroscopic approaches and molecular docking. Upon addition of HPγ-CDx, dramatic changes occur in the intrinsic 'two color' fluorescence behavior of the fluorophores. This is manifested by significant increase in the steady state fluorescence intensities, anisotropies, average fluorescence lifetimes and rotational correlation times. Furthermore, in the CDx environment, intrinsically achiral flavonols exhibit prominent induced circular dichroism bands. These findings indicate that the flavonol molecules spontaneously enter the relatively hydrophobic, chiral environment of the HPγ-CDx nano-cavities. Molecular docking computations corroborate the spectroscopic findings, and predict selectivity in orientation of the encapsulated flavonols. HPγ-CDx inclusion increases the aqueous solubility of individual flavonols ∼100-1000 times. The present study demonstrates that the hydroxypropyl substituent in γ-CDx controls the inclusion mode of the flavonols, leading to their enhanced solubilization and altered spectral signatures. Copyright © 2018 Elsevier Ltd. All rights reserved.
Abreu, Rui Mv; Froufe, Hugo Jc; Queiroz, Maria João Rp; Ferreira, Isabel Cfr
2010-10-28
Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a potential maximum speed-up of 10x, the parallel algorithm of MOLA performed with a speed-up of 8,64× using AutoDock4 and 8,60× using Vina.
NASA Astrophysics Data System (ADS)
Thomas, Renjith; Hossain, Mossaraf; Mary, Y. Sheena; Resmi, K. S.; Armaković, Stevan; Armaković, Sanja J.; Nanda, Ashis Kumar; Ranjan, Vivek Kumar; Vijayakumar, G.; Van Alsenoy, C.
2018-04-01
Solvent-free synthesis pathway for obtaining two imidazole derivatives (2-chloro-1-(4-methoxyphenyl)-4,5-dimethyl-1H-imidazole (CLMPDI) and 1-(4-bromophenyl)-2-chloro-4,5-dimethyl-1H-imidazole (BPCLDI) has been reported in this work, followed by detailed experimental and computational spectroscopic characterization and reactivity study. Spectroscopic methods encompassed IR, FT-Raman and NMR techniques, with the mutual comparison of experimentally and computationally obtained results at DFT/B3LYP level of theory. Reactivity study based on DFT calculations encompassed molecular orbitals analysis, followed by calculations of molecular electrostatic potential (MEP) and average local ionization energy (ALIE) values, Fukui functions and bond dissociation energies (BDE). Additionally, the stability of title molecules in water has been investigated via molecular dynamics (MD) simulations, while interactivity with aspulvinonedimethylallyl transferase protein has been evaluated by molecular docking procedure. CLMPDI compound showed antimicrobial activity against all four bacterial strain in both gram positive and gram negative bacteria while, BPCLDI showed only in gram positive bacteria, Staphylococcus Aureus (MTCC1144). The first order hyperpolarizability of CLMPDI and BPCLDI are 20.15 and 6.10 times that of the standard NLO material urea.
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.
Krishnaraj, R Navanietha; Chandran, Saravanan; Pal, Parimal; Berchmans, Sheela
2013-12-01
There is an immense interest among the researchers to identify new herbicides which are effective against the herbs without affecting the environment. In this work, photosynthetic pigments are used as the ligands to predict their herbicidal activity. The enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase is a good target for the herbicides. Homology modeling of the target enzyme is done using Modeler 9.11 and the model is validated. Docking studies were performed with AutoDock Vina algorithm to predict the binding of the natural pigments such as β-carotene, chlorophyll a, chlorophyll b, phycoerythrin and phycocyanin to the target. β-carotene, phycoerythrin and phycocyanin have higher binding energies indicating the herbicidal activity of the pigments. This work reports a procedure to screen herbicides with computational molecular approach. These pigments will serve as potential bioherbicides in the future.
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.
Molecular Docking Studies of Flavonoids Derivatives on the Flavonoid 3- O-Glucosyltransferase.
Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V; Janezic, Dusanka
2015-01-01
A study of 30 flavonoid derivatives, taken from PubChem database and docked on flavonoid 3-O-glucosyltransferase 3HBF, next submitted to a QSAR study, performed within a hypermolecule frame, to model their LD50 values, is reported. The initial set of molecules was split into a training set and the test set (taken from the best scored molecules in the docking test); the predicted LD50 values, computed on similarity clusters, built up for each of the molecules of the test set, surpassed in accuracy the best model. The binding energies to 3HBF protein, provided by the docking step, are not related to the LD50 of these flavonoids, more protein targets are to be investigated in this respect. However, the docking step was useful in choosing the test set of molecules.
Jiang, Hanlun; Zhu, Lizhe; Héliou, Amélie; Gao, Xin; Bernauer, Julie; Huang, Xuhui
2017-01-01
MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.
Identifying the binding mode of a molecular scaffold
NASA Astrophysics Data System (ADS)
Chema, Doron; Eren, Doron; Yayon, Avner; Goldblum, Amiram; Zaliani, Andrea
2004-01-01
We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our `nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.
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.
High performance in silico virtual drug screening on many-core processors.
McIntosh-Smith, Simon; Price, James; Sessions, Richard B; Ibarra, Amaurys A
2015-05-01
Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel's Xeon Phi and multi-core CPUs with SIMD instruction sets.
High performance in silico virtual drug screening on many-core processors
Price, James; Sessions, Richard B; Ibarra, Amaurys A
2015-01-01
Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel’s Xeon Phi and multi-core CPUs with SIMD instruction sets. PMID:25972727
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.
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
NASA Astrophysics Data System (ADS)
Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian
2011-06-01
The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.
Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian
2011-06-01
The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.
Atomistic models for free energy evaluation of drug binding to membrane proteins.
Durdagi, S; Zhao, C; Cuervo, J E; Noskov, S Y
2011-01-01
The binding of various molecules to integral membrane proteins with optimal affinity and specificity is central to normal function of cell. While membrane proteins represent about one third of the whole cell proteome, they are a majority of common drug targets. The quest for the development of computational models capable of accurate evaluation of binding affinities, decomposition of the binding into its principal components and thus mapping molecular mechanisms of binding remains one of the main goals of modern computational biophysics and related drug development. The primary scope of this review will be on the recent extension of computational methods for the study of drug binding to membrane proteins. Several examples of such applications will be provided ranging from secondary transporters to voltage gated channels. In this mini-review, we will provide a short summary on the breadth of different methods for binding affinity evaluation. These methods include molecular docking with docking scoring functions, molecular dynamics (MD) simulations combined with post-processing analysis using Molecular Mechanics/Poisson Boltzmann (Generalized Born) Surface Area (MM/PB(GB)SA), as well as direct evaluation of free energies from Free Energy Perturbation (FEP) with constraining schemes, and Potential of Mean Force (PMF) computations. We will compare advantages and shortcomings of popular techniques and provide discussion on the integrative strategies for drug development aimed at targeting membrane proteins.
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…
A large scale virtual screen of DprE1.
Wilsey, Claire; Gurka, Jessica; Toth, David; Franco, Jimmy
2013-12-01
Tuberculosis continues to plague the world with the World Health Organization estimating that about one third of the world's population is infected. Due to the emergence of MDR and XDR strains of TB, the need for novel therapeutics has become increasing urgent. Herein we report the results of a virtual screen of 4.1 million compounds against a promising drug target, DrpE1. The virtual compounds were obtained from the Zinc docking site and screened using the molecular docking program, AutoDock Vina. The computational hits have led to the identification of several promising lead compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.
Thillainayagam, Mahalakshmi; Anbarasu, Anand; Ramaiah, Sudha
2016-08-21
The computational studies namely molecular docking simulations and Comparative Molecular Field Analysis (CoMFA) are executed on series of 52 novel aryl chalcones derivatives using Plasmodium falciparum cysteine proteases (falcipain - 2) as vital target. In the present study, the correlation between different molecular field effects namely steric and electrostatic interactions and chemical structures to the inhibitory activities of novel aryl chalcone derivatives is inferred to perceive the major structural prerequisites for the rational design and development of potent and novel lead anti-malarial compound. The apparent binding conformations of all the compounds at the active site of falcipain - 2 and the hydrogen-bond interactions which could be used to modify the inhibitory activities are identified by using Surflex-dock study. Statistically significant CoMFA model has been developed with the cross-validated correlation coefficient (q(2)) of 0.912 and the non-cross-validated correlation coefficient (r(2)) of 0.901. Standard error of estimation (SEE) of 0.210, with the optimum number of components is ten. The predictability of the derived model is examined with a test set consists of sixteen compounds and the predicted r(2) value is found to be 0.924. The docking and QSAR study results confer crucial suggestions for the optimization of novel 1,3-diphenyl-2-propen-1-one derivatives and synthesis of effective anti- malarial compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.
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
[Study on anti-hyperlipidemia mechanism of high frequency herb pairs by molecular docking method].
Jiang, Lu-di; He, Yu-su; Chen, Xi; Tao, Ou; Li, Gong-Yu; Zhang, Yan-ling
2015-06-01
Traditional Chinese medicine (TCM) has definitely clinical effect in treating hyperlipidemia, but the action mechanism still need to be explored. Based on consulting Chinese Pharmacopoeia (2010), all the lipid-lowering Chinese patent medicines were analyzed by associated rules data mining method to explore high frequency herb pairs. The top three couplet medicines with high support degree were Puerariae Lobatae Radix-Crataegi Fructus, Salviae Miltiorrhizae Radix et Rhizoma-Crataegi Fructus, and Polygoni Multiflori Radix-Crataegi Fructus. The 20 main ingredients were selected from the herb pairs and docked with 3 key hyperlipidemia targets, namely 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA reductase), peroxisome proliferator activated receptor-α (PPAR-α ) and niemann-pick C1 like 1 (NPC1L1) to further discuss the molecular mechanism of the high frequency herb pairs, by using the docking program, LibDock. To construct evaluation rules for the ingredients of herb pairs, the root-mean-square deviation (RMSD) value between computed and initial complexes was first calculated to validate the fitness of LibDock models. Then, the key residues were also confirmed by analyzing the interactions of those 3 proteins and corresponding marketed drugs. The docking results showed that hyperin, puerarin, salvianolic acid A and polydatin can interact with two targets, and the other five compounds may be potent for at least one of the three targets. In this study, the multi-target effect of high frequency herb pairs for lipid-lowering was discussed on the molecular level, which can help further researching new multi-target anti-hyperlipidemia drug.
Yim, Wen-Wai; Chien, Shu; Kusumoto, Yasuyuki; Date, Susumu; Haga, Jason
2010-01-01
Large-scale in-silico screening is a necessary part of drug discovery and Grid computing is one answer to this demand. A disadvantage of using Grid computing is the heterogeneous computational environments characteristic of a Grid. In our study, we have found that for the molecular docking simulation program DOCK, different clusters within a Grid organization can yield inconsistent results. Because DOCK in-silico virtual screening (VS) is currently used to help select chemical compounds to test with in-vitro experiments, such differences have little effect on the validity of using virtual screening before subsequent steps in the drug discovery process. However, it is difficult to predict whether the accumulation of these discrepancies over sequentially repeated VS experiments will significantly alter the results if VS is used as the primary means for identifying potential drugs. Moreover, such discrepancies may be unacceptable for other applications requiring more stringent thresholds. This highlights the need for establishing a more complete solution to provide the best scientific accuracy when executing an application across Grids. One possible solution to platform heterogeneity in DOCK performance explored in our study involved the use of virtual machines as a layer of abstraction. This study investigated the feasibility and practicality of using virtual machine and recent cloud computing technologies in a biological research application. We examined the differences and variations of DOCK VS variables, across a Grid environment composed of different clusters, with and without virtualization. The uniform computer environment provided by virtual machines eliminated inconsistent DOCK VS results caused by heterogeneous clusters, however, the execution time for the DOCK VS increased. In our particular experiments, overhead costs were found to be an average of 41% and 2% in execution time for two different clusters, while the actual magnitudes of the execution time costs were minimal. Despite the increase in overhead, virtual clusters are an ideal solution for Grid heterogeneity. With greater development of virtual cluster technology in Grid environments, the problem of platform heterogeneity may be eliminated through virtualization, allowing greater usage of VS, and will benefit all Grid applications in general.
Ritchie, David W; Kozakov, Dima; Vajda, Sandor
2008-09-01
Predicting how proteins interact at the molecular level is a computationally intensive task. Many protein docking algorithms begin by using fast Fourier transform (FFT) correlation techniques to find putative rigid body docking orientations. Most such approaches use 3D Cartesian grids and are therefore limited to computing three dimensional (3D) translational correlations. However, translational FFTs can speed up the calculation in only three of the six rigid body degrees of freedom, and they cannot easily incorporate prior knowledge about a complex to focus and hence further accelerate the calculation. Furthemore, several groups have developed multi-term interaction potentials and others use multi-copy approaches to simulate protein flexibility, which both add to the computational cost of FFT-based docking algorithms. Hence there is a need to develop more powerful and more versatile FFT docking techniques. This article presents a closed-form 6D spherical polar Fourier correlation expression from which arbitrary multi-dimensional multi-property multi-resolution FFT correlations may be generated. The approach is demonstrated by calculating 1D, 3D and 5D rotational correlations of 3D shape and electrostatic expansions up to polynomial order L=30 on a 2 GB personal computer. As expected, 3D correlations are found to be considerably faster than 1D correlations but, surprisingly, 5D correlations are often slower than 3D correlations. Nonetheless, we show that 5D correlations will be advantageous when calculating multi-term knowledge-based interaction potentials. When docking the 84 complexes of the Protein Docking Benchmark, blind 3D shape plus electrostatic correlations take around 30 minutes on a contemporary personal computer and find acceptable solutions within the top 20 in 16 cases. Applying a simple angular constraint to focus the calculation around the receptor binding site produces acceptable solutions within the top 20 in 28 cases. Further constraining the search to the ligand binding site gives up to 48 solutions within the top 20, with calculation times of just a few minutes per complex. Hence the approach described provides a practical and fast tool for rigid body protein-protein docking, especially when prior knowledge about one or both binding sites is available.
Blessy, J Jino; Sharmila, D Jeya Sundara
2015-02-01
Molecular modeling of synthetic methyl-α-Neu5Ac analogues modified in C-9 position was investigated by molecular docking and molecular dynamics (MD) simulation methods. Methyl-α-Neu5Ac analogues were docked against cholera toxin (CT) B subunit protein and MD simulations were carried out for three Methyl-α-Neu5Ac analogue-CT complexes (30, 10 and 10 ns) to estimate the binding activity of cholera toxin-Methyl-α-Neu5Ac analogues using OPLS_2005 force field. In this study, direct and water mediated hydrogen bonds play a vital role that exist between the methyl-α-9-N-benzoyl-amino-9-deoxy-Neu5Ac (BENZ)-cholera toxin active site residues. The Energy plot, RMSD and RMSF explain that the simulation was stable throughout the simulation run. Transition of phi, psi and omega angle for the complex was calculated. Molecular docking studies could be able to identify the binding mode of methyl-α-Neu5Ac analogues in the binding site of cholera toxin B subunit protein. MD simulation for Methyl-α-9-N-benzoyl-amino-9-deoxy-Neu5Ac (BENZ), Methyl-α-9-N-acetyl-9-deoxy-9-amino-Neu5Ac and Methyl-α-9-N-biphenyl-4-acetyl-deoxy-amino-Neu5Ac complex with CT B subunit protein was carried out, which explains the stable nature of interaction. These methyl-α-Neu5Ac analogues that have computationally acceptable pharmacological properties may be used as novel candidates for drug design for cholera disease.
NASA Astrophysics Data System (ADS)
Resmi, K. S.; Mary, Y. Sheena; Varghese, Hema Tresa; Panicker, C. Yohannan; Pakosińska-Parys, Magdalena; Alsenoy, C. Van
2015-10-01
The optimized molecular structure, vibrational frequencies, corresponding vibrational assignments of the title compound have been investigated experimentally and theoretically. The HOMO and LUMO analysis is used to determine the charge transfer within the molecule. The stability of the molecule arising from hyper-conjugative interaction and charge delocalization has been analysed using NBO analysis. The hyperpolarisability calculation reveals the present material has a reasonably good propensity for nonlinear optical activity. Due to the different potential biological activity of the title compound, molecular docking study is also reported and the compound might exhibit inhibitory activity against human M2 muscarinic acetylcholine receptor.
Ramshankar, Vijayalakshmi; Yegnaswamy, Subha; P, Kumarasamy; Arvind, Krishnamurthy
2014-01-01
Identification of activating mutations in non-small cell lung cancers (NSCLC) has been a focus in recent years. This led to successful evidence of using tyrosine kinase inhibitors (TKIs) over the standard platinum doublet based chemotherapy as the first line treatment in the metastatic setting.The rearrangements of fusion protein EML4-ALK in NSCLC lead to the use of crizotinib for this class of tumors. Preclinical and Phase 1 clinical studies show that ceritinib is more effective against both crizotinib sensitive and resistant tumors. Although robust responses to crizotinib are observed in NSCLC harboring ALK mutations, majority of tumors eventually become resistant, posing a major challenge in treatment course. Thus, there is a need for the identification and development of second-generation of ALK inhibitors. Computer aided molecular docking data show Tivozanib and Lapatinib bind EML4-ALK with high score. Tivozanib is in clinical trials for renal cell cancer and Lapatinib is a known dual tyrosine kinase inhibitor effective in breast cancer patients with HER2 over-expression. Additional data on these compounds for use in EML4-ALK positive NSCLC will provide evidence for use in patients treated with crizotinib. Data shows the importance of computer aided molecular docking in developing candidates with improved activity for further consideration in vitro and in vivo validation.
Ramshankar, Vijayalakshmi; Yegnaswamy, Subha; P, Kumarasamy; Arvind, Krishnamurthy
2014-01-01
Identification of activating mutations in non-small cell lung cancers (NSCLC) has been a focus in recent years. This led to successful evidence of using tyrosine kinase inhibitors (TKIs) over the standard platinum doublet based chemotherapy as the first line treatment in the metastatic setting.The rearrangements of fusion protein EML4-ALK in NSCLC lead to the use of crizotinib for this class of tumors. Preclinical and Phase 1 clinical studies show that ceritinib is more effective against both crizotinib sensitive and resistant tumors. Although robust responses to crizotinib are observed in NSCLC harboring ALK mutations, majority of tumors eventually become resistant, posing a major challenge in treatment course. Thus, there is a need for the identification and development of second-generation of ALK inhibitors. Computer aided molecular docking data show Tivozanib and Lapatinib bind EML4-ALK with high score. Tivozanib is in clinical trials for renal cell cancer and Lapatinib is a known dual tyrosine kinase inhibitor effective in breast cancer patients with HER2 over-expression. Additional data on these compounds for use in EML4-ALK positive NSCLC will provide evidence for use in patients treated with crizotinib. Data shows the importance of computer aided molecular docking in developing candidates with improved activity for further consideration in vitro and in vivo validation. PMID:25489176
BiGGER: a new (soft) docking algorithm for predicting protein interactions.
Palma, P N; Krippahl, L; Wampler, J E; Moura, J J
2000-06-01
A new computationally efficient and automated "soft docking" algorithm is described to assist the prediction of the mode of binding between two proteins, using the three-dimensional structures of the unbound molecules. The method is implemented in a software package called BiGGER (Bimolecular Complex Generation with Global Evaluation and Ranking) and works in two sequential steps: first, the complete 6-dimensional binding spaces of both molecules is systematically searched. A population of candidate protein-protein docked geometries is thus generated and selected on the basis of the geometric complementarity and amino acid pairwise affinities between the two molecular surfaces. Most of the conformational changes observed during protein association are treated in an implicit way and test results are equally satisfactory, regardless of starting from the bound or the unbound forms of known structures of the interacting proteins. In contrast to other methods, the entire molecular surfaces are searched during the simulation, using absolutely no additional information regarding the binding sites. In a second step, an interaction scoring function is used to rank the putative docked structures. The function incorporates interaction terms that are thought to be relevant to the stabilization of protein complexes. These include: geometric complementarity of the surfaces, explicit electrostatic interactions, desolvation energy, and pairwise propensities of the amino acid side chains to contact across the molecular interface. The relative functional contribution of each of these interaction terms to the global scoring function has been empirically adjusted through a neural network optimizer using a learning set of 25 protein-protein complexes of known crystallographic structures. In 22 out of 25 protein-protein complexes tested, near-native docked geometries were found with C(alpha) RMS deviations < or =4.0 A from the experimental structures, of which 14 were found within the 20 top ranking solutions. The program works on widely available personal computers and takes 2 to 8 hours of CPU time to run any of the docking tests herein presented. Finally, the value and limitations of the method for the study of macromolecular interactions, not yet revealed by experimental techniques, are discussed.
Carbohydrate-protein interactions: molecular modeling insights.
Pérez, Serge; Tvaroška, Igor
2014-01-01
The article reviews the significant contributions to, and the present status of, applications of computational methods for the characterization and prediction of protein-carbohydrate interactions. After a presentation of the specific features of carbohydrate modeling, along with a brief description of the experimental data and general features of carbohydrate-protein interactions, the survey provides a thorough coverage of the available computational methods and tools. At the quantum-mechanical level, the use of both molecular orbitals and density-functional theory is critically assessed. These are followed by a presentation and critical evaluation of the applications of semiempirical and empirical methods: QM/MM, molecular dynamics, free-energy calculations, metadynamics, molecular robotics, and others. The usefulness of molecular docking in structural glycobiology is evaluated by considering recent docking- validation studies on a range of protein targets. The range of applications of these theoretical methods provides insights into the structural, energetic, and mechanistic facets that occur in the course of the recognition processes. Selected examples are provided to exemplify the usefulness and the present limitations of these computational methods in their ability to assist in elucidation of the structural basis underlying the diverse function and biological roles of carbohydrates in their dialogue with proteins. These test cases cover the field of both carbohydrate biosynthesis and glycosyltransferases, as well as glycoside hydrolases. The phenomenon of (macro)molecular recognition is illustrated for the interactions of carbohydrates with such proteins as lectins, monoclonal antibodies, GAG-binding proteins, porins, and viruses. © 2014 Elsevier Inc. All rights reserved.
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.
DOCKSCORE: a webserver for ranking protein-protein docked poses.
Malhotra, Sony; Mathew, Oommen K; Sowdhamini, Ramanathan
2015-04-24
Proteins interact with a variety of other molecules such as nucleic acids, small molecules and other proteins inside the cell. Structure-determination of protein-protein complexes is challenging due to several reasons such as the large molecular weights of these macromolecular complexes, their dynamic nature, difficulty in purification and sample preparation. Computational docking permits an early understanding of the feasibility and mode of protein-protein interactions. However, docking algorithms propose a number of solutions and it is a challenging task to select the native or near native pose(s) from this pool. DockScore is an objective scoring scheme that can be used to rank protein-protein docked poses. It considers several interface parameters, namely, surface area, evolutionary conservation, hydrophobicity, short contacts and spatial clustering at the interface for scoring. We have implemented DockScore in form of a webserver for its use by the scientific community. DockScore webserver can be employed, subsequent to docking, to perform scoring of the docked solutions, starting from multiple poses as inputs. The results, on scores and ranks for all the poses, can be downloaded as a csv file and graphical view of the interface of best ranking poses is possible. The webserver for DockScore is made freely available for the scientific community at: http://caps.ncbs.res.in/dockscore/ .
Improving Docking Performance Using Negative Image-Based Rescoring.
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.
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.
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.
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.
Yan, Yumeng; Tao, Huanyu; Huang, Sheng-You
2018-05-26
A major subclass of protein-protein interactions is formed by homo-oligomers with certain symmetry. Therefore, computational modeling of the symmetric protein complexes is important for understanding the molecular mechanism of related biological processes. Although several symmetric docking algorithms have been developed for Cn symmetry, few docking servers have been proposed for Dn symmetry. Here, we present HSYMDOCK, a web server of our hierarchical symmetric docking algorithm that supports both Cn and Dn symmetry. The HSYMDOCK server was extensively evaluated on three benchmarks of symmetric protein complexes, including the 20 CASP11-CAPRI30 homo-oligomer targets, the symmetric docking benchmark of 213 Cn targets and 35 Dn targets, and a nonredundant test set of 55 transmembrane proteins. It was shown that HSYMDOCK obtained a significantly better performance than other similar docking algorithms. The server supports both sequence and structure inputs for the monomer/subunit. Users have an option to provide the symmetry type of the complex, or the server can predict the symmetry type automatically. The docking process is fast and on average consumes 10∼20 min for a docking job. The HSYMDOCK web server is available at http://huanglab.phys.hust.edu.cn/hsymdock/.
NASA Astrophysics Data System (ADS)
Singh, Ashok Kumar; Singh, Ravindra Kumar
2016-10-01
A new coumarin derivative 2-(2-mercaptophenylimino)-4-methyl-2H-chromen-7-ol (COMSB) was synthesized and characterized with the help of 1H,13C NMR, FT-IR, FT-Raman and mass spectrometry. All quantum calculations were performed at DFT level of theory using B3LYP functional and 6-31G (d,p) as basis set. The UV-Vis spectrum studied by TD-DFT theory, with a hybrid exchange-correlation functional using Coulomb-attenuating method (CAM-B3LYP) in solvent phase gives similar pattern of bands, at energies and is consistent with that of experimental findings. The detailed analysis of vibrational (IR and Raman) spectra and their assignments has been done by computing Potential Energy Distribution (PED) using Gar2ped. Intra-molecular interactions were analyzed by 'Atoms in molecule' (AIM) approach. Computed first static hyperpolarizability (β0 = 8.583 × 10-30 esu) indicates non-linear optical (NLO) response of the molecule. Molecular docking studies show that the title molecule may act as potential acetylcholine esterase (AChE) inhibitor.
Panicker, C Yohannan; Varghese, Hema Tresa; Nayak, Prakash S; Narayana, B; Sarojini, B K; Fun, H K; War, Javeed Ahamad; Srivastava, S K; Van Alsenoy, C
2015-09-05
FT-IR spectrum of (2E)-3-(3-nitrophenyl)-1-[4-piperidin-1-yl]prop-2-en-1-one was recorded and analyzed. The vibrational wavenumbers were computed using HF and DFT quantum chemical calculations. The data obtained from wavenumber calculations are used to assign IR bands. Potential energy distribution was done using GAR2PED software. The geometrical parameters of the title compound are in agreement with the XRD results. NBO analysis, HOMO-LUMO, first and second hyperpolarizability and molecular electrostatic potential results are also reported. The possible electrophile attacking sites of the title molecule is identified using MEP surface plot study. Molecular docking results predicted the anti-leishmanic activity for the compound. Copyright © 2015. Published by Elsevier B.V.
Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang
2012-01-01
Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346
Liu, Zekun; Zhao, Junpeng; Li, Weichen; Shen, Li; Huang, Shengbo; Tang, Jingjing; Duan, Jie; Fang, Fang; Huang, Yuelong; Chang, Haiyan; Chen, Ze; Zhang, Ran
2016-01-01
The Influenza A virus is a great threat for human health, while various subtypes of the virus made it difficult to develop drugs. With the development of state-of-art computational chemistry, computational molecular docking could serve as a virtual screen of potential leading compound. In this study, we performed molecular docking for influenza A H1N1 (A/PR/8/34) with small molecules such as quercetin and chlorogenic acid, which were derived from traditional Chinese medicine. The results showed that these small molecules have strong binding abilities with neuraminidase from H1N1 (A/PR/8/34). Further details showed that the structural features of the molecules might be helpful for further drug design and development. The experiments in vitro, in vivo have validated the anti-influenza effect of quercetin and chlorogenic acid, which indicating comparable protection effects as zanamivir. Taken together, it was proposed that chlorogenic acid and quercetin could be employed as the effective lead compounds for anti-influenza A H1N1. PMID:26754609
NASA Astrophysics Data System (ADS)
Liu, Zekun; Zhao, Junpeng; Li, Weichen; Shen, Li; Huang, Shengbo; Tang, Jingjing; Duan, Jie; Fang, Fang; Huang, Yuelong; Chang, Haiyan; Chen, Ze; Zhang, Ran
2016-01-01
The Influenza A virus is a great threat for human health, while various subtypes of the virus made it difficult to develop drugs. With the development of state-of-art computational chemistry, computational molecular docking could serve as a virtual screen of potential leading compound. In this study, we performed molecular docking for influenza A H1N1 (A/PR/8/34) with small molecules such as quercetin and chlorogenic acid, which were derived from traditional Chinese medicine. The results showed that these small molecules have strong binding abilities with neuraminidase from H1N1 (A/PR/8/34). Further details showed that the structural features of the molecules might be helpful for further drug design and development. The experiments in vitro, in vivo have validated the anti-influenza effect of quercetin and chlorogenic acid, which indicating comparable protection effects as zanamivir. Taken together, it was proposed that chlorogenic acid and quercetin could be employed as the effective lead compounds for anti-influenza A H1N1.
A thermodynamic study of Abeta(16-21) dissociation from a fibril using computer simulations
NASA Astrophysics Data System (ADS)
Dias, Cristiano; Mahmoudinobar, Farbod; Su, Zhaoqian
Here, I will discuss recent all-atom molecular dynamics simulations with explicit water in which we studied the thermodynamic properties of Abeta(16-21) dissociation from an amyloid fibril. Changes in thermodynamics quantities, e.g., entropy, enthalpy, and volume, are computed from the temperature dependence of the free-energy computed using the umbrella sampling method. We find similarities and differences between the thermodynamics of peptide dissociation and protein unfolding. Similarly to protein unfolding, Abeta(16-21) dissociation is characterized by an unfavorable change in enthalpy, a favorable change in the entropic energy, and an increase in the heat capacity. A main difference is that peptide dissociation is characterized by a weak enthalpy-entropy compensation. We characterize dock and lock states of the peptide based on the solvent accessible surface area. The Lennard-Jones energy of the system is observed to increase continuously in lock and dock states as the peptide dissociates. The electrostatic energy increases in the lock state and it decreases in the dock state as the peptide dissociates. These results will be discussed as well as their implication for fibril growth.
Kasam, Vinod; Salzemann, Jean; Botha, Marli; Dacosta, Ana; Degliesposti, Gianluca; Isea, Raul; Kim, Doman; Maass, Astrid; Kenyon, Colin; Rastelli, Giulio; Hofmann-Apitius, Martin; Breton, Vincent
2009-05-01
Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase. In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.
istar: a web platform for large-scale protein-ligand docking.
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.
NASA Astrophysics Data System (ADS)
El-Azab, Adel S.; Mary, Y. Sheena; Abdel-Aziz, Alaa A. M.; Miniyar, Pankaj B.; Armaković, Stevan; Armaković, Sanja J.
2018-03-01
The Fourier transform infrared spectra of the compounds 2-(5-phenyl-1,3,4-oxadiazol-2-yl)pyrazine (PHOXPY), 2-(5-styryl-1,3,4-oxadiazol-2-yl)pyrazine (STOXPY) and 2-(5-(furan-2-yl)-1,3,4-oxadiazol-2-yl)pyrazine (FUOXPY) have been recorded and the wavenumbers are computed at the density functional theory level. The assignments of all the fundamental bands of each molecule are made using potential energy distribution. The computed values of dipole moment, polarizability and hyperpolarizability values indicate that the title molecules exhibit NLO properties. The HOMO and LUMO energies demonstrate the chemical stability of the molecules and NBO analysis is made to study the stability of molecules arising from hyper conjugative interactions and charge delocalization. Detailed computational analysis and spectroscopic characterization has been performed for three newly synthesized oxadiazole derivatives. Obtained computational and experimental results have been mutually compared in order to understand the influence of structural parts specific for each derivative. From the MIC determination, MTb H37Rv was found to be sensitive to compounds, PHOXPY, STOXPY and FUOXPY. The results obtained from anti-TB activity are more promising as the compounds were found to be more potent than reference standards, streptomycin and pyrazinamide. Efforts were made in order to predict both global and local reactive properties of the title oxadiazole derivatives, including their sensitivity towards autoxidation mechanism and influence of water. The results obtained from anti-TB activity are more promising for the title compounds. Interaction with representative protein Pterindeaminase inhibitor asricin A was also investigated using the molecular docking procedure. The docked ligands form stable complexes with the receptor ricin A and the docking results suggest that these compounds can be developed as new anti-cancer drugs.
Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong K; Lee, Keun W
2012-12-01
To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. © 2012 John Wiley & Sons A/S.
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.
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
Ramamoorthy, Divya; Turos, Edward; Guida, Wayne C
2013-05-24
FabH (Fatty acid biosynthesis, enzyme H, also referred to as β-ketoacyl-ACP-synthase III) is a key condensing enzyme in the type II fatty acid synthesis (FAS) system. The FAS pathway in bacteria is essential for growth and survival and vastly differs from the human FAS pathway. Enzymes involved in this pathway have arisen as promising biomolecular targets for discovery of new antibacterial drugs. However, currently there are no clinical drugs that selectively target FabH, and known inhibitors of FabH all act within the active site. FabH exerts its catalytic function as a dimer, which could potentially be exploited in developing new strategies for inhibitor design. The aim of this study was to elucidate structural details of the dimer interface region by means of computational modeling, including molecular dynamics (MD) simulations, in order to derive information for the structure-based design of new FabH inhibitors. The dimer interface region was analyzed by MD simulations, trajectory snapshots were collected for further analyses, and docking studies were performed with potential small molecule disruptors. Alanine mutation and docking studies strongly suggest that the dimer interface could be a potential target for anti-infection drug discovery.
Computational study of some fluoroquinolones: Structural, spectral and docking investigations
NASA Astrophysics Data System (ADS)
Sayin, Koray; Karakaş, Duran; Kariper, Sultan Erkan; Sayin, Tuba Alagöz
2018-03-01
Quantum chemical calculations are performed over norfloxacin, tosufloxacin and levofloxacin. The most stable structures for each molecule are determined by thermodynamic parameters. Then the best level for calculations is determined by benchmark analysis. M062X/6-31 + G(d) level is used in calculations. IR, UV-VIS and NMR spectrum are calculated and examined in detail. Some quantum chemical parameters are calculated and the tendency of activity is recommended. Additionally, molecular docking calculations are performed between related compounds and a protein (ID: 2J9N).
Higo, Junichi; Dasgupta, Bhaskar; Mashimo, Tadaaki; Kasahara, Kota; Fukunishi, Yoshifumi; Nakamura, Haruki
2015-07-30
A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35 ) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did. © 2015 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Murugavel, S.; Vetri velan, V.; Kannan, Damodharan; Bakthadoss, Manickam
2017-01-01
The title compound methyl(2E)-2-{[N-(2-formylphenyl)(4-methylbenzene)sulfonamido] methyl}-3-(2-methoxyphenyl)prop-2-enoate (MFMSM) has been synthesized and single crystals were grown by slow evaporation solution growth technique at room temperature. XRD, FT-IR and NMR spectra of MFMSM in the solid phase were recorded and analyzed. The optimized geometry and vibrational wave numbers were computed using DFT method. The NLO, Mulliken, MEP, HOMO-LUMO energy gap and thermodynamic properties were theoretically predicted. The NBO analysis explained the intramolecular hydrogen bonding. The global chemical reactivity descriptors are calculated for MFMSM and used to predict their relative stability and reactivity. All the calculations were carried out by B3LYP/6-311G (d,p) method. MFMSM has been screened for its antimicrobial activity and found to exhibit antifungal and antibacterial effects. Docking simulation has been performed.
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.
Armen, Roger S; Chen, Jianhan; Brooks, Charles L
2009-10-13
Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.
Armen, Roger S.; Chen, Jianhan; Brooks, Charles L.
2009-01-01
Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and “noise” that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds. PMID:20160879
DOT2: Macromolecular Docking With Improved Biophysical Models
Roberts, Victoria A.; Thompson, Elaine E.; Pique, Michael E.; Perez, Martin S.; Eyck, Lynn Ten
2015-01-01
Computational docking is a useful tool for predicting macromolecular complexes, which are often difficult to determine experimentally. Here we present the DOT2 software suite, an updated version of the DOT intermolecular docking program. DOT2 provides straightforward, automated construction of improved biophysical models based on molecular coordinates, offering checkpoints that guide the user to include critical features. DOT has been updated to run more quickly, allow flexibility in grid size and spacing, and generate a complete list of favorable candidate configu-rations. Output can be filtered by experimental data and rescored by the sum of electrostatic and atomic desolvation energies. We show that this rescoring method improves the ranking of correct complexes for a wide range of macromolecular interactions, and demonstrate that biologically relevant models are essential for biologically relevant results. The flexibility and versatility of DOT2 accommodate realistic models of complex biological systems, improving the likelihood of a successful docking outcome. PMID:23695987
jMetalCpp: optimizing molecular docking problems with a C++ metaheuristic framework.
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/.
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.
Structure and Sequence Search on Aptamer-Protein Docking
NASA Astrophysics Data System (ADS)
Xiao, Jiajie; Bonin, Keith; Guthold, Martin; Salsbury, Freddie
2015-03-01
Interactions between proteins and deoxyribonucleic acid (DNA) play a significant role in the living systems, especially through gene regulation. However, short nucleic acids sequences (aptamers) with specific binding affinity to specific proteins exhibit clinical potential as therapeutics. Our capillary and gel electrophoresis selection experiments show that specific sequences of aptamers can be selected that bind specific proteins. Computationally, given the experimentally-determined structure and sequence of a thrombin-binding aptamer, we can successfully dock the aptamer onto thrombin in agreement with experimental structures of the complex. In order to further study the conformational flexibility of this thrombin-binding aptamer and to potentially develop a predictive computational model of aptamer-binding, we use GPU-enabled molecular dynamics simulations to both examine the conformational flexibility of the aptamer in the absence of binding to thrombin, and to determine our ability to fold an aptamer. This study should help further de-novo predictions of aptamer sequences by enabling the study of structural and sequence-dependent effects on aptamer-protein docking specificity.
Reddy, Pulakuntla Swetha; Lokhande, Kiran Bharat; Nagar, Shuchi; Reddy, Vaddi Damodara; Murthy, P Sushma; Swamy, K Venkateswara
2018-02-27
Gefitinib (lressa) is the most prescribed drug, highly effective to treat of non-small cell lung cancer; primarily it was considered targeted therapy is a kinase inhibitor. The non-small cell lung cancer caused by the mutation in the Epithelial Growth Factor Receptor (EGFR) gene, Iressa works by blocking the EGFR protein that helps the cancer cell growth. EGFR protein has lead to the development of anticancer therapeutics directed against EGFR inhibitor including Gefitinib for non-small cell lung cancer. To explore research on Gefitinib and its derivatives interaction with crystal structure EGFR to understand the better molecular insights interaction strategies. Molecular modeling of ligands (Gefitinib and its derivatives) was carried out by Avogadro software till atomic angle stable confirmation obtained. The partial charges for the ligands were assigned as per standard protocol for molecular docking. All docking simulations were performed with AutoDockVina. Virtual screening carried out based on binding energy and hydrogen bonding affinity. Molecular dynamics (MD) and Simulation EGFR was done using GROMACS 5.1.1 software to explore the interaction stability in a cell. The stable conformation for EGFR protein trajectories were captured at various time intervals 0-20ns. Few compounds screen based on high affinity as the inhibitor for EGFR may inhibit the cell cycle signalling in non-small cell lung cancer. These result suggested that a computer aided screening approach of a Gefitinib derivatives compounds with regard to their binding to EGFR for identifying novel drugs for the treatment of non-small cell lung cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
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.
Mukherjee, Sudipto; Rizzo, Robert C.
2014-01-01
Scoring functions are a critically important component of computer-aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multi-grid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per-residue basis in a way that resembles a known reference. The grid-based FPS method is much faster than its Cartesian-space counterpart which makes it computationally tractable for on-the-fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co-crystal structures, for crossdocking, and for database enrichment, and (iii) grid-based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method will be made available in the program DOCK6. PMID:23436713
DOVIS: an implementation for high-throughput virtual screening using AutoDock.
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.
Fu, Junjie; Xia, Amy; Dai, Yao; Qi, Xin
2016-01-01
Discovering molecules capable of binding to HIV trans-activation responsive region (TAR) RNA thereby disrupting its interaction with Tat protein is an attractive strategy for developing novel antiviral drugs. Computational docking is considered as a useful tool for predicting binding affinity and conducting virtual screening. Although great progress in predicting protein-ligand interactions has been achieved in the past few decades, modeling RNA-ligand interactions is still largely unexplored due to the highly flexible nature of RNA. In this work, we performed molecular docking study with HIV TAR RNA using previously identified cyclic peptide L22 and its analogues with varying affinities toward HIV-1 TAR RNA. Furthermore, sarcosine scan was conducted to generate derivatives of CGP64222, a peptide-peptoid hybrid with inhibitory activity on Tat/TAR RNA interaction. Each compound was docked using CDOCKER, Surflex-Dock and FlexiDock to compare the effectiveness of each method. It was found that FlexiDock energy values correlated well with the experimental Kd values and could be used to predict the affinity of the ligands toward HIV-1 TAR RNA with a superior accuracy. Our results based on comparative analysis of different docking methods in RNA-ligand modeling will facilitate the structure-based discovery of HIV TAR RNA ligands for antiviral therapy.
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
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.
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.
Liu, Yingting; Purvis, Jeremy; Shih, Andrew; Weinstein, Joshua; Agrawal, Neeraj; Radhakrishnan, Ravi
2007-06-01
We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.
Doss, C George Priya; Chakraborty, Chiranjib; Chen, Luonan; Zhu, Hailong
2014-01-01
Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype.
Agarwal, Shivangi; Verma, Ekta; Kumar, Vivek; Lall, Namrita; Sau, Samaresh; Iyer, Arun K; Kashaw, Sushil K
2018-05-03
Tuberculosis is an infectious chronic disease caused by obligate pathogen Mycobacterium tuberculosis that affects millions of people worldwide. Although many first and second line drugs are available for its treatment, but their irrational use has adversely lead to the emerging cases of multiple drug resistant and extensively drug-resistant tuberculosis. Therefore, there is an intense need to develop novel potent analogues for its treatment. This has prompted us to develop potent analogues against TB. The Mycobacterium tuberculosis genome provides us with number of validated targets to combat against TB. Study of Mtb genome disclosed six epoxide hydrolases (A to F) which convert harmful epoxide into diols and act as a potential drug target for rational drug design. Our current strategy is to develop such analogues which inhibits epoxide hydrolase enzyme present in Mtb genome. To achieve this, we adopted an integrated computational approach involving QSAR, pharmacophore mapping, molecular docking and molecular dynamics simulation studies. The approach envisaged vital information about the role of molecular descriptors, essential pharmacophoric features and binding energy for compounds to bind into the active site of epoxide hydrolase. Molecular docking analysis revealed that analogues exhibited significant binding to Mtb epoxide hydrolase. Further, three docked complexes 2s, 37s and 15s with high, moderate and low docking scores respectively were selected for molecular dynamics simulation studies. RMSD analysis revealed that all complexes are stable with average RMSD below 2 Å throughout the 10 ns simulations. The B-factor analysis showed that the active site residues of epoxide hydrolase are flexible enough to interact with inhibitor. Moreover, to confirm the binding of these urea derivatives, MM-GBSA binding energy analysis were performed. The calculations showed that 37s has more binding affinity (ΔGtotal = -52.24 kcal/mol) towards epoxide hydrolase compared to 2s (ΔGtotal = -51.70 kcal/mol) and 15s (ΔGtotal = -49.97 kcal/mol). The structural features inferred in our study may provide the future directions to the scientists towards the discovery of new chemical entity exhibiting anti-TB property. Copyright © 2018 Elsevier Inc. All rights reserved.
Schindler, Christina E M; de Vries, Sjoerd J; Zacharias, Martin
2015-02-01
Protein-protein interactions are abundant in the cell but to date structural data for a large number of complexes is lacking. Computational docking methods can complement experiments by providing structural models of complexes based on structures of the individual partners. A major caveat for docking success is accounting for protein flexibility. Especially, interface residues undergo significant conformational changes upon binding. This limits the performance of docking methods that keep partner structures rigid or allow limited flexibility. A new docking refinement approach, iATTRACT, has been developed which combines simultaneous full interface flexibility and rigid body optimizations during docking energy minimization. It employs an atomistic molecular mechanics force field for intermolecular interface interactions and a structure-based force field for intramolecular contributions. The approach was systematically evaluated on a large protein-protein docking benchmark, starting from an enriched decoy set of rigidly docked protein-protein complexes deviating by up to 15 Å from the native structure at the interface. Large improvements in sampling and slight but significant improvements in scoring/discrimination of near native docking solutions were observed. Complexes with initial deviations at the interface of up to 5.5 Å were refined to significantly better agreement with the native structure. Improvements in the fraction of native contacts were especially favorable, yielding increases of up to 70%. © 2014 Wiley Periodicals, Inc.
Wang, Jinghui; Yang, Yinfeng; Li, Yan; Wang, Yonghua
2016-07-27
Bovine viral diarrhea virus (BVDV) infections are prevailing in cattle populations on a worldwide scale. The BVDV RNA-dependent RNA polymerase (RdRp), as a promising target for new anti-BVDV drug development, has attracted increasing attention. To explore the interaction mechanism of 65 benzimidazole scaffold-based derivatives as BVDV inhibitors, presently, a computational study was performed based on a combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations. The resultant optimum CoMFA and CoMSIA models present proper reliabilities and strong predictive abilities (with Q(2) = 0. 64, R(2)ncv = 0.93, R(2)pred = 0.80 and Q(2) = 0. 65, R(2)ncv = 0.98, R(2)pred = 0.86, respectively). In addition, there was good concordance between these models, molecular docking, and MD results. Moreover, the MM-PBSA energy analysis reveals that the major driving force for ligand binding is the polar solvation contribution term. Hopefully, these models and the obtained findings could offer better understanding of the interaction mechanism of BVDV inhibitors as well as benefit the new discovery of more potent BVDV inhibitors.
Homology Modeling and Molecular Docking for the Science Curriculum
ERIC Educational Resources Information Center
McDougal, Owen M.; Cornia, Nic; Sambasivarao, S. V.; Remm, Andrew; Mallory, Chris; Oxford, Julia Thom; Maupin, C. Mark; Andersen, Tim
2014-01-01
DockoMatic 2.0 is a powerful open source software program (downloadable from sourceforge.net) that allows users to utilize a readily accessible computational tool to explore biomolecules and their interactions. This manuscript describes a practical tutorial for use in the undergraduate curriculum that introduces students to macromolecular…
1001 Ways to run AutoDock Vina for virtual screening
NASA Astrophysics Data System (ADS)
Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D.
2016-03-01
Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.
1001 Ways to run AutoDock Vina for virtual screening.
Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D
2016-03-01
Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.
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
High performance transcription factor-DNA docking with GPU computing
2012-01-01
Background Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. Methods In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems. Results The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design. Conclusions We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem. PMID:22759575
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.
NASA Astrophysics Data System (ADS)
Sathish, M.; Meenakshi, G.; Xavier, S.; Sebastian, S.; Periandy, S.; Ahmad, NoorAisyah; Jamalis, Joazaizulfazli; Rosli, MohdMustaqim; Fun, Hoong-Kun
2018-07-01
The 3-(5-Bromo-2-thienyl)-1-(4-fluorophenyl)-3-acetyl-2-pyrazoline (2) (BTFA) was synthesized from condensation of thiophenechalcone (1) and hydrazine hydrate. The compound was characterized by FT-IR, 1H and 13C NMR. Crystal structure of this compound was determined using X-ray diffraction technique. The data of the geometry is compared with the optimized structure of the compound obtained using B3LYP functional with 6-311++G (d,p) basis set. The fundamental modes of vibrations are assigned using VEDA software with the PED assignments, and compared with data obtained from theoretical methods. The deviations are widely discussed and analyzed. The intermolecular interaction of the crystal structure was analyzed using Hirshfeld and fingerprint analysis. The chemical shift of the NMR for 13C and 1H are observed and computational data are computed using Gauge independent atomic orbital (GIAO) using B3LYP/6-311++G (d,p). The electronic and optical properties like absorption of wavelengths, excitation energy, dipole moment and frontier molecular orbital energies are computed with TD-SCF method using the above theoretical method. The antiviral nature of the molecule is also analyzed and the compound is docked in non-small cell lung cancer and human collapsin response mediator protein-1study exhibits its activity.
Computational Selection of Inhibitors of A-beta Aggregation and Neuronal Toxicity
Chen, Deliang; Martin, Zane S.; Soto, Claudio; Schein, Catherine H.
2009-01-01
Alzheimer’s Disease (AD) is characterized by the cerebral accumulation of misfolded and aggregated amyloid-β protein (Aβ). Disease symptoms can be alleviated, in vitro and in vivo, by “β-sheet breaker” pentapeptides that reduce plaque volume. However the peptide nature of these compounds, made them biologically unstable and unable to penetrate membranes with high efficiency. The main goal of this study was to use computational methods to identify small molecule mimetics with better drug-like properties. For this purpose, the docked conformations of the active peptides were used to identify compounds with similar activities. A series of related β-sheet breaker peptides were docked to solid state NMR structures of a fibrillar form of Aβ. The lowest energy conformations of the active peptides were used to design three dimensional (3D)-pharmacophores, suitable for screening the NCI database with Unity. Small molecular weight compounds with physicochemical features in a conformation similar to the active peptides were selected, ranked by docking solubility parameters. Of 16 diverse compounds selected for experimental screening, 2 prevented and reversed Aβ aggregation at 2–3 μM concentration, as measured by Thioflavin T (ThT) fluorescence and ELISA assays. They also prevented the toxic effects of aggregated Aβ on neuroblastoma cells. Their low molecular weight and aqueous solubility makes them promising lead compounds for treating AD. PMID:19540126
Large-scale virtual screening on public cloud resources with Apache Spark.
Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola
2017-01-01
Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.
HPEPDOCK: a web server for blind peptide-protein docking based on a hierarchical algorithm.
Zhou, Pei; Jin, Bowen; Li, Hao; Huang, Sheng-You
2018-05-09
Protein-peptide interactions are crucial in many cellular functions. Therefore, determining the structure of protein-peptide complexes is important for understanding the molecular mechanism of related biological processes and developing peptide drugs. HPEPDOCK is a novel web server for blind protein-peptide docking through a hierarchical algorithm. Instead of running lengthy simulations to refine peptide conformations, HPEPDOCK considers the peptide flexibility through an ensemble of peptide conformations generated by our MODPEP program. For blind global peptide docking, HPEPDOCK obtained a success rate of 33.3% in binding mode prediction on a benchmark of 57 unbound cases when the top 10 models were considered, compared to 21.1% for pepATTRACT server. HPEPDOCK also performed well in docking against homology models and obtained a success rate of 29.8% within top 10 predictions. For local peptide docking, HPEPDOCK achieved a high success rate of 72.6% on a benchmark of 62 unbound cases within top 10 predictions, compared to 45.2% for HADDOCK peptide protocol. Our HPEPDOCK server is computationally efficient and consumed an average of 29.8 mins for a global peptide docking job and 14.2 mins for a local peptide docking job. The HPEPDOCK web server is available at http://huanglab.phys.hust.edu.cn/hpepdock/.
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.
Virtual Screening of Novel Glucosamine-6-Phosphate Synthase Inhibitors.
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.
Molecular Docking for Prediction and Interpretation of Adverse Drug Reactions.
Luo, Heng; Fokoue-Nkoutche, Achille; Singh, Nalini; Yang, Lun; Hu, Jianying; Zhang, Ping
2018-05-23
Adverse drug reactions (ADRs) present a major burden for patients and the healthcare industry. Various computational methods have been developed to predict ADRs for drug molecules. However, many of these methods require experimental or surveillance data and cannot be used when only structural information is available. We collected 1,231 small molecule drugs and 600 human proteins and utilized molecular docking to generate binding features among them. We developed machine learning models that use these docking features to make predictions for 1,533 ADRs. These models obtain an overall area under the receiver operating characteristic curve (AUROC) of 0.843 and an overall area under the precision-recall curve (AUPR) of 0.395, outperforming seven structural fingerprint-based prediction models. Using the method, we predicted skin striae for fluticasone propionate, dermatitis acneiform for mometasone, and decreased libido for irinotecan, as demonstrations. Furthermore, we analyzed the top binding proteins associated with some of the ADRs, which can help to understand and/or generate hypotheses for underlying mechanisms of ADRs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N
2016-12-13
Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.
Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun
2016-12-01
Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.
AnchorDock for Blind Flexible Docking of Peptides to Proteins.
Slutzki, Michal; Ben-Shimon, Avraham; Niv, Masha Y
2017-01-01
Due to increasing interest in peptides as signaling modulators and drug candidates, several methods for peptide docking to their target proteins are under active development. The "blind" docking problem, where the peptide-binding site on the protein surface is unknown, presents one of the current challenges in the field. AnchorDock protocol was developed by Ben-Shimon and Niv to address this challenge.This protocol narrows the docking search to the most relevant parts of the conformational space. This is achieved by pre-folding the free peptide and by computationally detecting anchoring spots on the surface of the unbound protein. Multiple flexible simulated annealing molecular dynamics (SAMD) simulations are subsequently carried out, starting from pre-folded peptide conformations, constrained to the various precomputed anchoring spots.Here, AnchorDock is demonstrated using two known protein-peptide complexes. A PDZ-peptide complex provides a relatively easy case due to the relatively small size of the protein, and a typical peptide conformation and binding region; a more challenging example is a complex between USP7 N-term and a p53-derived peptide, where the protein is larger, and the peptide conformation and a binding site are generally assumed to be unknown. AnchorDock returned native-like solutions ranked first and third for the PDZ and USP7 complexes, respectively. We describe the procedure step by step and discuss possible modifications where applicable.
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.
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
Mena-Ulecia, Karel; MacLeod-Carey, Desmond
2018-06-01
2-phenyl-benzotriazole xenobiotic compounds (PBTA-4, PBTA-6, PBTA-7 and PBTA-8) that were previously isolated and identified in waters of the Yodo river, in Japan (Nukaya et al., 2001; Ohe et al., 2004; Watanabe et al., 2001) were characterized as powerful pro-mutagens. In order to predict the activation mechanism of these pro-mutagens, we designed a computational biochemistry protocol, which includes, docking experiments, molecular dynamics simulations and free energy decomposition calculations to obtain information about the interaction of 2-phenyl-benzotriazole molecules into the active center of cytochrome P450-CYP1A1 (CYP1A1). Molecular docking calculations using AutoDock Vina software shows that PBTAs are proportionally oriented in the pocket of CYP1A1, establishing π-π stacking attractive interactions between the triazole group and the Phe224, as well as, the hydrogen bonds of the terminal NH 2 over the benzotriazole units with the Asn255 and Ser116 amino acids. Molecular dynamics simulations using NAMD package showed that these interactions are stable along 100.0 ns of trajectories. Into this context, free binding energy calculations employing the MM-GBSA approach, shows that some differences exists among the interaction of PBTAs with CYP1A1, regarding the solvation, electrostatic and van der Waals interaction energy components. These results suggest that PBTA molecules might be activated by CYP1A1. Thus, enhancing their mutagenicity when compared with the pro-mutagen parent species. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Murthy, P. Krishna; Sheena Mary, Y.; Shyma Mary, Y.; Panicker, C. Yohannan; Suneetha, V.; Armaković, Stevan; Armaković, Sanja J.; Van Alsenoy, C.; Suchetan, P. A.
2017-04-01
4-benzyl-5-oxomorpholine-3-carbamide has been synthesized; single crystals were grown by slow evaporation solution growth technique at room temperature and characterized by single crystal X-ray diffraction, FT-IR, FT-Raman and 1H-NMR. The compound crystallizes in the monoclinic space group P21/n. The molecular geometry of the compound was optimized by using Density Functional Theory (DFT/B3LYP) method with 6-311++G(d,p) basis set in the ground state and geometric parameters are in agreement with the X-ray analysis results of the structure. The experimental vibrational spectra were compared with the calculated spectra and each vibrational wave number was assigned on the basis of potential energy distribution (PED). The electronic and charge transfer properties have been explained on the basis of highest occupied molecular orbital's (HOMOs) and lowest unoccupied molecular orbital's (LUMOs). Besides molecular electrostatic potential (MEP), frontier molecular orbital's (FMOs), some global reactivity descriptors, thermodynamic properties, non-linear optical (NLO) behavior and Mullikan charge analysis of the title compound were computed with the same method in gas phase, theoretically. Potential reactive sites of the title compound have been identified by average local ionization energy and Fukui functions, both mapped to the electron density surface. Bond dissociation energies for all single acyclic bonds have been calculated in order to investigate autoxidation and degradation properties of the title compound. Atoms with pronounced interactions with water molecules have been detected by calculations of radial distribution functions after molecular dynamics simulations. The experimental results are compared with the theoretical calculations using DFT methods for the fortification of the paper. Further the docking studies revealed that the title compound as a docked ligand forms a stable complex with pyrrole inhibitor with a binding affinity value of -7.5 kcal/mol. This suggests that the title compound might exhibit inhibitory activity against pyrrole inhibitor. To confirm the potential practical applicability of the title compound antimicrobial activity was tested against gram negative and gram positive bacteria.
[Regression analysis to select native-like structures from decoys of antigen-antibody docking].
Chen, Zhengshan; Chi, Xiangyang; Fan, Pengfei; Zhang, Guanying; Wang, Meirong; Yu, Changming; Chen, Wei
2018-06-25
Given the increasing exploitation of antibodies in different contexts such as molecular diagnostics and therapeutics, it would be beneficial to unravel properties of antigen-antibody interaction with modeling of computational protein-protein docking, especially, in the absence of a cocrystal structure. However, obtaining a native-like antigen-antibody structure remains challenging due in part to failing to reliably discriminate accurate from inaccurate structures among tens of thousands of decoys after computational docking with existing scoring function. We hypothesized that some important physicochemical and energetic features could be used to describe antigen-antibody interfaces and identify native-like antigen-antibody structure. We prepared a dataset, a subset of Protein-Protein Docking Benchmark Version 4.0, comprising 37 nonredundant 3D structures of antigen-antibody complexes, and used it to train and test multivariate logistic regression equation which took several important physicochemical and energetic features of decoys as dependent variables. Our results indicate that the ability to identify native-like structures of our method is superior to ZRANK and ZDOCK score for the subset of antigen-antibody complexes. And then, we use our method in workflow of predicting epitope of anti-Ebola glycoprotein monoclonal antibody-4G7 and identify three accurate residues in its epitope.
Nongonierma, Alice B; Mooney, Catherine; Shields, Denis C; FitzGerald, Richard J
2014-07-01
Molecular docking of a library of all 8000 possible tripeptides to the active site of DPP-IV was used to determine their binding potential. A number of tripeptides were selected for experimental testing, however, there was no direct correlation between the Vina score and their in vitro DPP-IV inhibitory properties. While Trp-Trp-Trp, the peptide with the best docking score, was a moderate DPP-IV inhibitor (IC50 216μM), Lineweaver and Burk analysis revealed its action to be non-competitive. This suggested that it may not bind to the active site of DPP-IV as assumed in the docking prediction. Furthermore, there was no significant link between DPP-IV inhibition and the physicochemical properties of the peptides (molecular mass, hydrophobicity, hydrophobic moment (μH), isoelectric point (pI) and charge). LIGPLOTs indicated that competitive inhibitory peptides were predicted to have both hydrophobic and hydrogen bond interactions with the active site of DPP-IV. DPP-IV inhibitory peptides generally had a hydrophobic or aromatic amino acid at the N-terminus, preferentially a Trp for non-competitive inhibitors and a broader range of residues for competitive inhibitors (Ile, Leu, Val, Phe, Trp or Tyr). Two of the potent DPP-IV inhibitors, Ile-Pro-Ile and Trp-Pro (IC50 values of 3.5 and 44.2μM, respectively), were predicted to be gastrointestinally/intestinally stable. This work highlights the needs to test the assumptions (i.e. competitive binding) of any integrated strategy of computational and experimental screening, in optimizing screening. Future strategies targeting allosteric mechanisms may need to rely more on structure-activity relationship modeling, rather than on docking, in computationally selecting peptides for screening. Copyright © 2014 Elsevier Inc. All rights reserved.
Performance Studies on Distributed Virtual Screening
Krüger, Jens; de la Garza, Luis; Kohlbacher, Oliver; Nagel, Wolfgang E.
2014-01-01
Virtual high-throughput screening (vHTS) is an invaluable method in modern drug discovery. It permits screening large datasets or databases of chemical structures for those structures binding possibly to a drug target. Virtual screening is typically performed by docking code, which often runs sequentially. Processing of huge vHTS datasets can be parallelized by chunking the data because individual docking runs are independent of each other. The goal of this work is to find an optimal splitting maximizing the speedup while considering overhead and available cores on Distributed Computing Infrastructures (DCIs). We have conducted thorough performance studies accounting not only for the runtime of the docking itself, but also for structure preparation. Performance studies were conducted via the workflow-enabled science gateway MoSGrid (Molecular Simulation Grid). As input we used benchmark datasets for protein kinases. Our performance studies show that docking workflows can be made to scale almost linearly up to 500 concurrent processes distributed even over large DCIs, thus accelerating vHTS campaigns significantly. PMID:25032219
Molecular docking, spectroscopic studies and quantum calculations on nootropic drug.
Uma Maheswari, J; Muthu, S; Sundius, Tom
2014-04-05
A systematic vibrational spectroscopic assignment and analysis of piracetam [(2-oxo-1-pyrrolidineacetamide)] have been carried out using FT-IR and FT-Raman spectral data. The vibrational analysis was aided by an electronic structure calculation based on the hybrid density functional method B3LYP using a 6-311G++(d,p) basis set. Molecular equilibrium geometries, electronic energies, IR and Raman intensities, and harmonic vibrational frequencies have been computed. The assignments are based on the experimental IR and Raman spectra, and a complete assignment of the observed spectra has been proposed. The UV-visible spectrum of the compound was recorded and the electronic properties, such as HOMO and LUMO energies and the maximum absorption wavelengths λmax were determined by the time-dependent DFT (TD-DFT) method. The geometrical parameters, vibrational frequencies and absorption wavelengths were compared with the experimental data. The complete vibrational assignments are performed on the basis of the potential energy distributions (PED) of the vibrational modes in terms of natural internal coordinates. The simulated FT-IR, FT-Raman, and UV spectra of the title compound have been constructed. Molecular docking studies have been carried out in the active site of piracetam by using Argus Lab. In addition, the potential energy surface, HOMO and LUMO energies, first-order hyperpolarizability and the molecular electrostatic potential have been computed. Copyright © 2014 Elsevier B.V. All rights reserved.
Sharifi, Tayebeh; Ghayeb, Yousef
2018-05-01
Peroxisome proliferator-activated receptors (PPARs) compose a family of nuclear receptors, PPARα, PPARβ, and PPARγ, which mediate the effects of lipidic ligands at the transcriptional level. Among these, the PPARγ has been known to regulate adipocyte differentiation, fatty acid storage and glucose metabolism, and is a target of antidiabetic drugs. In this work, the interactions between PPARγ and its six known antagonists were investigated using computational methods such as molecular docking, molecular dynamics (MD) simulations, and the hybrid quantum mechanics/molecular mechanics (QM/MM). The binding energies evaluated by molecular docking varied between -22.59 and -35.15 kJ mol - 1 . In addition, MD simulations were performed to investigate the binding modes and PPARγ conformational changes upon binding of antagonists. Analysis of the root-mean-square fluctuations (RMSF) of backbone atoms shows that H3 of PPARγ has a higher mobility in the absence of antagonists and moderate conformational changes were observed. The interaction energies between antagonists and each PPARγ residue involved in the interactions were studied by QM/MM calculations. These calculations reveal that antagonists with different structures show different interaction energies with the same residue of PPARγ. Therefore, it can be concluded that the key residues vary depending on the structure of the ligand, which binds to PPARγ.
NASA Astrophysics Data System (ADS)
Fathima Rizwana, B.; Prasana, Johanan Christian; Abraham, Christina Susan; Muthu, S.
2018-07-01
Entecavir, a new deoxyguanine nucleoside analogue, is a selective inhibitor of the replication of the hepatitis B virus. In the present study, Quantum mechanical approach was carried out on the title compound to study the vibrational spectrum, the stability of the compound, the intermolecular and intramolecular interactions by using Density Functional Theory (DFT) with B3LYP 6-311++G(d,p) basis set. The B3LYP/DFT method was chosen because diverse studies have shown that the results obtained with it are in good agreement with those determined by other costly computational methods. The computational methods were aided by the experimental spectroscopic techniques, namely FTIR and FT Raman spectroscopies. The optimized molecular geometry, vibrational wavenumbers, infrared intensities and Raman scattering activities were calculated. The calculated HOMO and LUMO energies were found to be -6.397 eV and -1.504 eV which indicate the charge transfer within the molecule. The maximum absorption wavelength and the band gap energy of the title compound were obtained from the UV absorption spectrum computed theoretically. Natural Bond Orbital analysis has been carried out to explain the charge transfer (or) delocalization of charge due to the intra molecular interactions. The molecule orbital contributions are studied by using the total (TDOS), partial (PDOS), and overlap population (OPDOS) density of states. Molecular electrostatic potential (MEP), First order hyperpolarizability, Hirshfield surface analysis and Fukui functions calculation were also performed. From the calculations the first order hyperpolarizability was found to be 2.3854 × 10-30 esu. The thermodynamic properties (heat capacity, entropy, and enthalpy) of the title compound at different temperatures have been calculated. Molecular docking studies were made on the title compound to study the hydrogen bond interactions and the minimum binding energy was calculated.
Computer Aided Drug Design: Success and Limitations.
Baig, Mohammad Hassan; Ahmad, Khurshid; Roy, Sudeep; Ashraf, Jalaluddin Mohammad; Adil, Mohd; Siddiqui, Mohammad Haris; Khan, Saif; Kamal, Mohammad Amjad; Provazník, Ivo; Choi, Inho
2016-01-01
Over the last few decades, computer-aided drug design has emerged as a powerful technique playing a crucial role in the development of new drug molecules. Structure-based drug design and ligand-based drug design are two methods commonly used in computer-aided drug design. In this article, we discuss the theory behind both methods, as well as their successful applications and limitations. To accomplish this, we reviewed structure based and ligand based virtual screening processes. Molecular dynamics simulation, which has become one of the most influential tool for prediction of the conformation of small molecules and changes in their conformation within the biological target, has also been taken into account. Finally, we discuss the principles and concepts of molecular docking, pharmacophores and other methods used in computer-aided drug design.
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.
Camacho, Carlos J
2005-08-01
The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.
2014-01-01
Background The complement protein C5a acts by primarily binding and activating the G-protein coupled C5a receptor C5aR (CD88), and is implicated in many inflammatory diseases. The cyclic hexapeptide PMX53 (sequence Ace-Phe-[Orn-Pro-dCha-Trp-Arg]) is a full C5aR antagonist of nanomolar potency, and is widely used to study C5aR function in disease. Results We construct for the first time molecular models for the C5aR:PMX53 complex without the a priori use of experimental constraints, via a computational framework of molecular dynamics (MD) simulations, docking, conformational clustering and free energy filtering. The models agree with experimental data, and are used to propose important intermolecular interactions contributing to binding, and to develop a hypothesis for the mechanism of PMX53 antagonism. Conclusion This work forms the basis for the design of improved C5aR antagonists, as well as for atomic-detail mechanistic studies of complement activation and function. Our computational framework can be widely used to develop GPCR-ligand structural models in membrane environments, peptidomimetics and other chemical compounds with potential clinical use. PMID:25170421
ZHENG, CHUN-SONG; WU, YIN-SHENG; BAO, HONG-JUAN; XU, XIAO-JIE; CHEN, XING-QIANG; YE, HONG-ZHI; WU, GUANG-WEN; XU, HUI-FENG; LI, XI-HAI; CHEN, JIA-SHOU; LIU, XIAN-XIANG
2014-01-01
Xiao Chai Hu Tang (XCHT), a traditional herbal formula, is widely administered as a cancer treatment. However, the underlying molecular mechanisms of its anticancer effects are not fully understood. In the present study, a computational pharmacological model that combined chemical space mapping, molecular docking and network analysis was employed to predict which chemical compounds in XCHT are potential inhibitors of cancer-associated targets, and to establish a compound-target (C-T) network and compound-compound (C-C) association network. The identified compounds from XCHT demonstrated diversity in chemical space. Furthermore, they occupied regions of chemical space that were the same, or close to, those occupied by drug or drug-like compounds that are associated with cancer, according to the Therapeutic Targets Database. The analysis of the molecular docking and the C-T network demonstrated that the potential inhibitors possessed the properties of promiscuous drugs and combination therapies. The C-C network was classified into four clusters and the different clusters contained various multi-compound combinations that acted on different targets. The study indicated that XCHT has a polypharmacological role in treating cancer and the potential inhibitory components of XCHT require further investigation as potential therapeutic strategies for cancer patients. PMID:24926384
Nisha, J; Shanthi, V
2015-07-01
Mycobacterium leprae, the etiologic agent of leprosy, is non-cultivable in vitro. Consequently, the assessment of antibiotic activity against M. leprae hinge mainly upon the time consuming mouse footpad system. As M. leprae develops resistance against most of the drugs, the evolution of new long acting antimycobacterial compounds stand in need for leprosy control. The rpoB of M. leprae is the target of antimycobacterial drug, rifampicin. Recently, cases were reported that rpoB mutation (S425L) became resistant to rifampicin and the mechanism of resistance is still not well understood. The present study is aimed at studying the molecular and structural mechanism of the rifampicin binding to both native and mutant rpoB through computational approaches. From molecular docking, we demonstrated the stable binding of rifampicin through two hydrogen bonding with His420 residue of native than with mutant rpoB where one hydrogen bonding was found with Ser406. The difference in binding energies observed in the docking study evidently signifies that rifampicin is less effective in the treatment of patients with S425L variant. Moreover, the molecular dynamics studies also highlight the stable binding of rifampicin with native than mutant (S425L) rpoB. © 2015 Wiley Periodicals, Inc.
Chintakrindi, Anand S; Martis, Elvis A F; Gohil, Devanshi J; Kothari, Sweta T; Chowdhary, Abhay S; Coutinho, Evans C; Kanyalkar, Meena A
2016-01-01
With cases of emergence of drug resistance to the current competitive inhibitors of neuraminidase (NA) such as oseltamivir and zanamavir, there is a present need for an alternative approach in the treatment of avian influenza. With this in view, some flavones and chalcones were designed based on quercetin, the most active naturally occurring noncompetitive inhibitor. We attempt to understand the binding of quercetin to H5N1-NA, and synthetic analogs of quercetin namely flavones and its precursors the chalcones using computational tools. Molecular docking was done using Libdock. Molecular dynamics (MD) simulations were performed using Amber14. We synthesized the two compounds; their structures were confirmed by infrared spectroscopy, 1H-NMR, and mass spectrometry. These molecules were then tested for H5N1-NA inhibition and kinetics of inhibition. Molecular docking studies yielded two compounds i.e., 4'-methoxyflavone and 2'-hydroxy-4-methoxychalcone, as promising leads which identified them as binders of the 150-cavity of NA. Furthermore, MD simulation studies revealed that quercetin and the two compounds bind and hold the 150 loop in its open conformation, which ultimately perturbs the binding of sialic acid in the catalytic site. Estimation of the free energy of binding by MM-PBSA portrays quercetin as more potent than chalcone and flavone. These molecules were then determined as non-competitive inhibitors from the Lineweaver-Burk plots rendered from the enzyme kinetic studies. We conclude that non-competitive type of inhibition, as shown in this study, can serve as an effective method to block NA and evade the currently seen drug resistance.
Chen, Hanyong; Yao, Ke; Chang, Xiaoyu; Shim, Jung-Hyun; Kim, Hong-Gyum; Malakhova, Margarita; Kim, Dong-Joon; Bode, Ann M; Dong, Zigang
2015-01-01
The most active anticancer component in green tea is epigallocatechin-3-gallate (EGCG). Protein interaction with EGCG is a critical step for mediating the effects of EGCG on the regulation of various key molecules involved in signal transduction. By using computational docking screening methods for protein identification, we identified a serine/threonine kinase, 90-kDa ribosomal S6 kinase (RSK2), as a novel molecular target of EGCG. RSK2 includes two kinase catalytic domains in the N-terminal (NTD) and the C-terminal (CTD) and RSK2 full activation requires phosphorylation of both terminals. The computer prediction was confirmed by an in vitro kinase assay in which EGCG inhibited RSK2 activity in a dose-dependent manner. Pull-down assay results showed that EGCG could bind with RSK2 at both kinase catalytic domains in vitro and ex vivo. Furthermore, results of an ATP competition assay and a computer-docking model showed that EGCG binds with RSK2 in an ATP-dependent manner. In RSK2+/+ and RSK2-/- murine embryonic fibroblasts, EGCG decreased viability only in the presence of RSK2. EGCG also suppressed epidermal growth factor-induced neoplastic cell transformation by inhibiting phosphorylation of histone H3 at Ser10. Overall, these results indicate that RSK2 is a novel molecular target of EGCG.
Hot-spot analysis for drug discovery targeting protein-protein interactions.
Rosell, Mireia; Fernández-Recio, Juan
2018-04-01
Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.
PyGOLD: a python based API for docking based virtual screening workflow generation.
Patel, Hitesh; Brinkjost, Tobias; Koch, Oliver
2017-08-15
Molecular docking is one of the successful approaches in structure based discovery and development of bioactive molecules in chemical biology and medicinal chemistry. Due to the huge amount of computational time that is still required, docking is often the last step in a virtual screening approach. Such screenings are set as workflows spanned over many steps, each aiming at different filtering task. These workflows can be automatized in large parts using python based toolkits except for docking using the docking software GOLD. However, within an automated virtual screening workflow it is not feasible to use the GUI in between every step to change the GOLD configuration file. Thus, a python module called PyGOLD was developed, to parse, edit and write the GOLD configuration file and to automate docking based virtual screening workflows. The latest version of PyGOLD, its documentation and example scripts are available at: http://www.ccb.tu-dortmund.de/koch or http://www.agkoch.de. PyGOLD is implemented in Python and can be imported as a standard python module without any further dependencies. oliver.koch@agkoch.de, oliver.koch@tu-dortmund.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Investigation of binding features: effects on the interaction between CYP2A6 and inhibitors.
Ai, Chunzhi; Li, Yan; Wang, Yonghua; Li, Wei; Dong, Peipei; Ge, Guangbo; Yang, Ling
2010-07-15
A computational investigation has been carried out on CYP2A6 and its naphthalene inhibitors to explore the crucial molecular features contributing to binding specificity. The molecular bioactive orientations were obtained by docking (FlexX) these compounds into the active site of the enzyme. And the density functional theory method was further used to optimize the molecular structures with the subsequent analysis of molecular lipophilic potential (MLP) and molecular electrostatic potential (MEP). The minimal MLPs, minimal MEPs, and the band gap energies (the energy difference between the highest occupied molecular orbital and lowest unoccupied molecular orbital) showed high correlations with the inhibition activities (pIC(50)s), illustrating their significant roles in driving the inhibitor to adopt an appropriate bioactive conformation oriented in the active site of CYP2A6 enzyme. The differences in MLPs, MEPs, and the orbital energies have been identified as key features in determining the binding specificity of this series of compounds to CYP2A6 and the consequent inhibitory effects. In addition, the combinational use of the docking, MLP and MEP analysis is also demonstrated as a good attempt to gain an insight into the interaction between CYP2A6 and its inhibitors. Copyright 2010 Wiley Periodicals, Inc.
In Silico Analyses of Substrate Interactions with Human Serum Paraoxonase 1
2008-01-01
substrate interactions of HuPON1 remains elusive. In this study, we apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the...mod- eling; docking; molecular dynamics simulations ; binding free energy decomposition. 486 PROTEINS Published 2008 WILEY-LISS, INC. yThis article is a...apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the binding interactions of HuPON1 with representative substrates. The
Simulation of carbohydrates, from molecular docking to dynamics in water.
Sapay, Nicolas; Nurisso, Alessandra; Imberty, Anne
2013-01-01
Modeling of carbohydrates is particularly challenging because of the variety of structures resulting for the high number of monosaccharides and possible linkages and also because of their intrinsic flexibility. The development of carbohydrate parameters for molecular modeling is still an active field. Nowadays, main carbohydrates force fields are GLYCAM06, CHARMM36, and GROMOS 45A4. GLYCAM06 includes the largest choice of compounds and is compatible with the AMBER force fields and associated. Furthermore, AMBER includes tools for the implementation of new parameters. When looking at protein-carbohydrate interaction, the choice of the starting structure is of importance. Such complex can be sometimes obtained from the Protein Data Bank-although the stereochemistry of sugars may require some corrections. When no experimental data is available, molecular docking simulation is generally used to the obtain protein-carbohydrate complex coordinates. As molecular docking parameters are not specifically dedicated to carbohydrates, inaccuracies should be expected, especially for the docking of polysaccharides. This issue can be addressed at least partially by combining molecular docking with molecular dynamics simulation in water.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Kuruvilla, Tintu K.; Prasana, Johanan Christian; Muthu, S.; George, Jacob; Mathew, Sheril Ann
2018-01-01
Quantum chemical techniques such as density functional theory (DFT) have become a powerful tool in the investigation of the molecular structure and vibrational spectrum and are finding increasing use in application related to biological systems. The Fourier transform infrared (FT-IR) and Fourier transform Raman (FT-Raman) techniques are employed to characterize the title compound. The vibrational frequencies were obtained by DFT/B3LYP calculations with 6-31G(d,p) and 6-311 ++G(d,p) as basis sets. The geometry of the title compound was optimized. The vibrational assignments and the calculation of Potential Energy Distribution (PED) were carried out using the Vibrational Energy Distribution Analysis (VEDA) software. Molecular electrostatic potential was calculated for the title compound to predict the reactive sites for electrophilic and nucleophilic attack. In addition, the first-order hyperpolarizability, HOMO and LUMO energies, Fukui function and NBO were computed. The thermodynamic properties of the title compound were calculated at different temperatures, revealing the correlations between heat capacity (C), entropy (S) and enthalpy changes (H) with temperatures. Molecular docking studies were also conducted as part of this study. The paper further explains the experimental results which are in line with the theoretical calculations and provide optimistic evidence through molecular docking that the title compound can act as a good antidepressant. It also provides sufficient justification for the title compound to be selected as a good candidate for further studies related to NLO properties.
Computer-aided rational design of novel EBF analogues with an aromatic ring.
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.
A High Performance Cloud-Based Protein-Ligand Docking Prediction Algorithm
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
HackaMol: An Object-Oriented Modern Perl Library for Molecular Hacking on Multiple Scales
Riccardi, Demian M.; Parks, Jerry M.; Johs, Alexander; ...
2015-03-20
HackaMol is an open source, object-oriented toolkit written in Modern Perl that organizes atoms within molecules and provides chemically intuitive attributes and methods. The library consists of two components: HackaMol, the core that contains classes for storing and manipulating molecular information, and HackaMol::X, the extensions that use the core. We tested the core; it is well-documented and easy to install across computational platforms. Our goal for the extensions is to provide a more flexible space for researchers to develop and share new methods. In this application note, we provide a description of the core classes and two extensions: HackaMol::X::Calculator, anmore » abstract calculator that uses code references to generalize interfaces with external programs, and HackaMol::X::Vina, a structured class that provides an interface with the AutoDock Vina docking program.« less
HackaMol: An Object-Oriented Modern Perl Library for Molecular Hacking on Multiple Scales.
Riccardi, Demian; Parks, Jerry M; Johs, Alexander; Smith, Jeremy C
2015-04-27
HackaMol is an open source, object-oriented toolkit written in Modern Perl that organizes atoms within molecules and provides chemically intuitive attributes and methods. The library consists of two components: HackaMol, the core that contains classes for storing and manipulating molecular information, and HackaMol::X, the extensions that use the core. The core is well-tested, well-documented, and easy to install across computational platforms. The goal of the extensions is to provide a more flexible space for researchers to develop and share new methods. In this application note, we provide a description of the core classes and two extensions: HackaMol::X::Calculator, an abstract calculator that uses code references to generalize interfaces with external programs, and HackaMol::X::Vina, a structured class that provides an interface with the AutoDock Vina docking program.
HackaMol: An Object-Oriented Modern Perl Library for Molecular Hacking on Multiple Scales
DOE Office of Scientific and Technical Information (OSTI.GOV)
Riccardi, Demian M.; Parks, Jerry M.; Johs, Alexander
HackaMol is an open source, object-oriented toolkit written in Modern Perl that organizes atoms within molecules and provides chemically intuitive attributes and methods. The library consists of two components: HackaMol, the core that contains classes for storing and manipulating molecular information, and HackaMol::X, the extensions that use the core. We tested the core; it is well-documented and easy to install across computational platforms. Our goal for the extensions is to provide a more flexible space for researchers to develop and share new methods. In this application note, we provide a description of the core classes and two extensions: HackaMol::X::Calculator, anmore » abstract calculator that uses code references to generalize interfaces with external programs, and HackaMol::X::Vina, a structured class that provides an interface with the AutoDock Vina docking program.« less
Saenz-Méndez, Patricia; Katz, Aline; Pérez-Kempner, María Lucía; Ventura, Oscar N; Vázquez, Marta
2017-04-01
A new homology model of human microsomal epoxide hydrolase was derived based on multiple templates. The model obtained was fully evaluated, including MD simulations and ensemble-based docking, showing that the quality of the structure is better than that of only previously known model. Particularly, a catalytic triad was clearly identified, in agreement with the experimental information available. Analysis of intermediates in the enzymatic mechanism led to the identification of key residues for substrate binding, stereoselectivity, and intermediate stabilization during the reaction. In particular, we have confirmed the role of the oxyanion hole and the conserved motif (HGXP) in epoxide hydrolases, in excellent agreement with known experimental and computational data on similar systems. The model obtained is the first one that fully agrees with all the experimental observations on the system. Proteins 2017; 85:720-730. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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
The application of quantum mechanics in structure-based drug design.
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.
Multi-Conformer Ensemble Docking to Difficult Protein Targets
Ellingson, Sally R.; Miao, Yinglong; Baudry, Jerome; ...
2014-09-08
We investigate large-scale ensemble docking using five proteins from the Directory of Useful Decoys (DUD, dud.docking.org) for which docking to crystal structures has proven difficult. Molecular dynamics trajectories are produced for each protein and an ensemble of representative conformational structures extracted from the trajectories. Docking calculations are performed on these selected simulation structures and ensemble-based enrichment factors compared with those obtained using docking in crystal structures of the same protein targets or random selection of compounds. We also found simulation-derived snapshots with improved enrichment factors that increased the chemical diversity of docking hits for four of the five selected proteins.more » A combination of all the docking results obtained from molecular dynamics simulation followed by selection of top-ranking compounds appears to be an effective strategy for increasing the number and diversity of hits when using docking to screen large libraries of chemicals against difficult protein targets.« less
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.
A Computational Approach to Finding Novel Targets for Existing Drugs
Li, Yvonne Y.; An, Jianghong; Jones, Steven J. M.
2011-01-01
Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. We have developed a computational drug repositioning pipeline to perform large-scale molecular docking of small molecule drugs against protein drug targets, in order to map the drug-target interaction space and find novel interactions. Our method emphasizes removing false positive interaction predictions using criteria from known interaction docking, consensus scoring, and specificity. In all, our database contains 252 human protein drug targets that we classify as reliable-for-docking as well as 4621 approved and experimental small molecule drugs from DrugBank. These were cross-docked, then filtered through stringent scoring criteria to select top drug-target interactions. In particular, we used MAPK14 and the kinase inhibitor BIM-8 as examples where our stringent thresholds enriched the predicted drug-target interactions with known interactions up to 20 times compared to standard score thresholds. We validated nilotinib as a potent MAPK14 inhibitor in vitro (IC50 40 nM), suggesting a potential use for this drug in treating inflammatory diseases. The published literature indicated experimental evidence for 31 of the top predicted interactions, highlighting the promising nature of our approach. Novel interactions discovered may lead to the drug being repositioned as a therapeutic treatment for its off-target's associated disease, added insight into the drug's mechanism of action, and added insight into the drug's side effects. PMID:21909252
Martínez, José Mario; Martínez, Leandro
2003-05-01
Molecular Dynamics is a powerful methodology for the comprehension at molecular level of many chemical and biochemical systems. The theories and techniques developed for structural and thermodynamic analyses are well established, and many software packages are available. However, designing starting configurations for dynamics can be cumbersome. Easily generated regular lattices can be used when simple liquids or mixtures are studied. However, for complex mixtures, polymer solutions or solid adsorbed liquids (for example) this approach is inefficient, and it turns out to be very hard to obtain an adequate coordinate file. In this article, the problem of obtaining an adequate initial configuration is treated as a "packing" problem and solved by an optimization procedure. The initial configuration is chosen in such a way that the minimum distance between atoms of different molecules is greater than a fixed tolerance. The optimization uses a well-known algorithm for box-constrained minimization. Applications are given for biomolecule solvation, many-component mixtures, and interfaces. This approach can reduce the work of designing starting configurations from days or weeks to few minutes or hours, in an automated fashion. Packing optimization is also shown to be a powerful methodology for space search in docking of small ligands to proteins. This is demonstrated by docking of the thyroid hormone to its nuclear receptor. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 819-825, 2003
A COMPUTER MODELING STUDY OF BINDING PROPERTIES OF CHIRAL NUCLEOPEPTIDE FOR BIOMEDICAL APPLICATIONS.
Pirtskhalava, M; Egoyan, A; Mirtskhulava, M; Roviello, G
2017-12-01
Nucleopeptides often show interesting properties of molecular binding that render them good candidates for development of innovative drugs for anticancer and antiviral therapies. In this work we present results of computer modeling of interactions between the molecules of hexathymine nucleopeptide (T6) and poly rA RNA (A18). The results of geometry optimization calculated using Hyperchem software and our own computer program for molecular docking show that molecules establish stable complexes due to the complementary-nucleobase interaction and the electrostatic interaction between the negative phosphate group of poly rA and the positively-charged residues present in the cationic nucleopeptide structure. Computer modeling makes it possible to find the optimal binding configuration of the molecules of a nucleopeptide and poly rA RNA and to estimate the binding energy between the molecules.
Protein-protein docking using region-based 3D Zernike descriptors
2009-01-01
Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods. PMID:20003235
Protein-protein docking using region-based 3D Zernike descriptors.
Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke
2009-12-09
Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.
Arodola, Olayide A; Soliman, Mahmoud E S
2015-01-01
Based on experimental data, the anticancer activity of nelfinavir (NFV), a US Food and Drug Administration (FDA)-approved HIV-1 protease inhibitor (PI), was reported. Nevertheless, the mechanism of action of NFV is yet to be verified. It was hypothesized that the anticancer activity of NFV is due to its inhibitory effect on heat shock protein 90 (Hsp90), a promising target for anticancer therapy. Such findings prompted us to investigate the potential anticancer activity of all other FDA-approved HIV-1 PIs against human Hsp90. To accomplish this, "loop docking" - an enhanced in-house developed molecular docking approach - followed by molecular dynamic simulations and postdynamic analyses were performed to elaborate on the binding mechanism and relative binding affinities of nine FDA-approved HIV-1 PIs against human Hsp90. Due to the lack of the X-ray crystal structure of human Hsp90, homology modeling was performed to create its 3D structure for subsequent simulations. Results showed that NFV has better binding affinity (ΔG =-9.2 kcal/mol) when compared with other PIs: this is in a reasonable accordance with the experimental data (IC50 3.1 μM). Indinavir, saquinavir, and ritonavir have close binding affinity to NFV (ΔG =-9.0, -8.6, and -8.5 kcal/mol, respectively). Per-residue interaction energy decomposition analysis showed that hydrophobic interaction (most importantly with Val534 and Met602) played the most predominant role in drug binding. To further validate the docking outcome, 5 ns molecular dynamic simulations were performed in order to assess the stability of the docked complexes. To our knowledge, this is the first account of detailed computational investigations aimed to investigate the potential anticancer activity and the binding mechanism of the FDA-approved HIV PIs binding to human Hsp90. Information gained from this study should also provide a route map toward the design, optimization, and further experimental investigation of potential derivatives of PIs to treat HER2+ breast cancer.
Balupuri, Anand; Balasubramanian, Pavithra K; Cho, Seung J
2016-01-01
Checkpoint kinase 1 (Chk1) has emerged as a potential therapeutic target for design and development of novel anticancer drugs. Herein, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses on a series of diazacarbazoles to design potent Chk1 inhibitors. 3D-QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Docking studies were performed using AutoDock. The best CoMFA and CoMSIA models exhibited cross-validated correlation coefficient (q2) values of 0.631 and 0.585, and non-cross-validated correlation coefficient (r2) values of 0.933 and 0.900, respectively. CoMFA and CoMSIA models showed reasonable external predictabilities (r2 pred) of 0.672 and 0.513, respectively. A satisfactory performance in the various internal and external validation techniques indicated the reliability and robustness of the best model. Docking studies were performed to explore the binding mode of inhibitors inside the active site of Chk1. Molecular docking revealed that hydrogen bond interactions with Lys38, Glu85 and Cys87 are essential for Chk1 inhibitory activity. The binding interaction patterns observed during docking studies were complementary to 3D-QSAR results. Information obtained from the contour map analysis was utilized to design novel potent Chk1 inhibitors. Their activities and binding affinities were predicted using the derived model and docking studies. Designed inhibitors were proposed as potential candidates for experimental synthesis.
Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie
2011-03-22
Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.
Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie
2011-01-01
Background Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. Methodology We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. Conclusions This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. PMID:21445339
Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi
2016-01-01
Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.
Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi
2016-01-01
Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578
NASA Astrophysics Data System (ADS)
Xavier, S.; Periandy, S.; Carthigayan, K.; Sebastian, S.
2016-12-01
Vibrational spectral analysis of Diphenyl Carbonate (DPC) is carried out by using FT-IR and FT-Raman spectroscopic techniques. It is found that all vibrational modes are in the expected region. Gaussian computational calculations were performed using B3LYP method with 6-311++G (d, p) basis set. The computed geometric parameters are in good agreement with XRD data. The observation shows that the structure of the carbonate group is unsymmetrical by ∼5° due to the attachment of the two phenyl rings. The stability of the molecule arising from hyperconjugative interaction and charge delocalization are analyzed by Natural Bond Orbital (NBO) study and the results show the lone pair transition has higher stabilization energy compared to all other. The 1H and 13C NMR chemical shifts are calculated using the Gauge-Including Atomic Orbital (GIAO) method with B3LYP/6-311++G (d, p) method. The chemical shifts computed theoretically go very closer to the experimental results. A study on the electronic and optical properties; absorption wavelengths, excitation energy, dipole moment and frontier molecular orbital energies and Molecular electrostatic potential (MEP) exhibit the high reactivity nature of the molecule. The non-linear optical property of the DPC molecule predicted theoretically found to be good candidate for NLO material. TG/DTA analysis was made and decomposition of the molecule with respect to the temperature was studied. DPC having the anthelmintic activity is docked in the Hemoglobin of Fasciola hepatica protein. The DPC has been screened to antimicrobial activity and found to exhibit antibacterial effects.
Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha
2017-10-01
Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r 2 ncv and q 2 loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r 2 Pred ) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.
NASA Astrophysics Data System (ADS)
Ahmad, Faheem; Parveen, Mehtab; Alam, Mahboob; Azaz, Shaista; Malla, Ali Mohammed; Alam, Mohammad Jane; Lee, Dong-Ung; Ahmad, Shabbir
2016-07-01
The present study reports the synthesis of 7-Hydroximinocholest-5-en-3-ol acetate (syn. 3β-acetoxycholest-5-en-7-one oxime; in general, steroidal oxime). The identity of steroidal molecule was confirmed by NMR, FT-IR, MS, CHN microanalysis and X-ray crystallography. DFT calculations on the titled molecule have been performed. The molecular structure and spectra interpreted by Gaussian hybrid computational analysis theory (B3LYP) are found to be in good correlation with the experimental data obtained from the various spectrophotometric techniques. The vibrational bands appearing in the FTIR are assigned with great accuracy using harmonic frequencies along with intensities and animated modes. Molecular properties like HOMO-LUMO analysis, chemical reactivity descriptors, MEP mapping, dipole moment and natural atomic charges have been presented at the same level of theory. Moreover, the Hirshfeld analysis was carried out to ascertain the secondary interactions and associated 2D fingerprint plots. The percentages of various interactions are pictorialized by fingerprint plots of Hirshfeld surface. Steroidal oxime exhibited promising inhibitory activity against acetylcholinesterase (AChE) as compared to the reference drug, tacrine. Molecular docking was performed to introduce steroidal molecules into the X-ray crystal structures of acetylcholinesterase at the active site to find out the probable binding mode. The results of molecular docking admitted that steroidal oxime may exhibit enzyme inhibitor activity.
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
Sabbah, Dima A; Zhong, Haizhen A
2016-07-01
β-secretase (BACE1) is an aspartyl protease that processes the β-amyloid peptide in the human brain in patients with Alzheimer's disease. There are two catalytic aspartates (ASP32 and ASP228) in the active domain of BACE1. Although it is believed that the net charge of the Asp dyad is -1, the exact protonation state still remains a matter of debate. We carried out molecular dynamic (MD) simulations for the four protonation states of BACE1 proteins. We applied Glide docking studies to 21 BACE1 inhibitors against the MD extracted conformations. The dynamic results infer that the protein/ligand complex remains stable during the entire simulation course for HD32D228 model. The results show that the hydrogen bonds between the inhibitor and the Asp dyad are maintained in the 10,000th ps snapshot of HD32D228 model. Our results also reveal the significant loop residues in maintaining the active binding conformation in the HD32D228 model. Molecular docking results show that the HD32D228 model provided the best enrichment factor score, suggesting that this model was able to recognize the most active compounds. Our observations provide an evidence for the preference of the anionic state (HD32D228) in BACE1 binding site and are in accord with reported computational data. The protonation state study would provide significant information to assign the correct protonation state for structure-based drug design and docking studies targeting the BACE1 proteins as a tactic to develop potential AD inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Harrison, Jason Gordon
2013-01-01
Quantum mechanical (QM) and molecular docking methods are used to probe systems of biological and synthetic interest. Probing interactions of nucleobases within proteins, and properly modeling said interactions toward novel nucleobase development, is extremely difficult, and of great utility in RNA interference (RNAi) therapeutics. The issues in…
Comparison of computational methods to model DNA minor groove binders.
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.
Protein-Protein Docking in Drug Design and Discovery.
Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana
2018-01-01
Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.
GENIUS In Silico Screening Technology for HCV Drug Discovery.
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.
"Soft docking": matching of molecular surface cubes.
Jiang, F; Kim, S H
1991-05-05
Molecular recognition is achieved through the complementarity of molecular surface structures and energetics with, most commonly, associated minor conformational changes. This complementarity can take many forms: charge-charge interaction, hydrogen bonding, van der Waals' interaction, and the size and shape of surfaces. We describe a method that exploits these features to predict the sites of interactions between two cognate molecules given their three-dimensional structures. We have developed a "cube representation" of molecular surface and volume which enables us not only to design a simple algorithm for a six-dimensional search but also to allow implicitly the effects of the conformational changes caused by complex formation. The present molecular docking procedure may be divided into two stages. The first is the selection of a population of complexes by geometric "soft docking", in which surface structures of two interacting molecules are matched with each other, allowing minor conformational changes implicitly, on the basis of complementarity in size and shape, close packing, and the absence of steric hindrance. The second is a screening process to identify a subpopulation with many favorable energetic interactions between the buried surface areas. Once the size of the subpopulation is small, one may further screen to find the correct complex based on other criteria or constraints obtained from biochemical, genetic, and theoretical studies, including visual inspection. We have tested the present method in two ways. First is a control test in which we docked the components of a molecular complex of known crystal structure available in the Protein Data Bank (PDB). Two molecular complexes were used: (1) a ternary complex of dihydrofolate reductase, NADPH and methotrexate (3DFR in PDB) and (2) a binary complex of trypsin and trypsin inhibitor (2PTC in PDB). The components of each complex were taken apart at an arbitrary relative orientation and then docked together again. The results show that the geometric docking alone is sufficient to determine the correct docking solutions in these ideal cases, and that the cube representation of the molecules does not degrade the docking process in the search for the correct solution. The second is the more realistic experiment in which we docked the crystal structures of uncomplexed molecules and then compared the structures of docked complexes with the crystal structures of the corresponding complexes. This is to test the capability of our method in accommodating the effects of the conformational changes in the binding sites of the molecules in docking.(ABSTRACT TRUNCATED AT 400 WORDS)
Spectroscopic, structural and drug docking studies of carbocysteine
NASA Astrophysics Data System (ADS)
Manivannan, M.; Rajeshwaran, K.; Govindhan, R.; Karthikeyan, B.
2017-09-01
Carbocysteine or carbocisteine having the empirical formula C5H9NO4S,is one of the most therapeutically prescribed expectorant, sold under the brand name viz., Mucodyne (UK and India), Rhinathiol and Mucolite. In pediatric respiratory pathology, it can relieve the symptoms of obstructive pulmonary disease (COPD) and bronchiectasis. On the consideration of its extensive pharmaceutical usage and medicinal value, we have investigated its chemical structure and composition by employing various spectral techniques like 1H, 13C NMR, FT-IR,Raman, UV-Visible spectroscopy and powder X-ray diffraction method. Density Functional Theoretical (DFT) studies on its electronic structure is also carried out. Drug docking studies were carried out to ascertain the nature of molecular interaction with the biological protein system. Furthermore theoretical Raman spectrum of this molecule has been computed and compared with the experimental Raman spectrum. The forbidden energy gap between its frontier molecular orbitals, viz., HOMO-LUMO is calculated and correlated with its observed λmax value. Atomic orbitals which are mainly contributes to the frontier molecular orbitals were identified. Molecular electrostatic potential diagram has been mapped to explain its chemical activity. Based on the results, a suitable mechanism of its protein binding mode and drug action has been discussed.
Raghi, K R; Sherin, D R; Saumya, M J; Arun, P S; Sobha, V N; Manojkumar, T K
2018-04-05
Chronic myeloid leukemia (CML), a hematological malignancy arises due to the spontaneous fusion of the BCR and ABL gene, resulting in a constitutively active tyrosine kinase (BCR-ABL). Pharmacological activity of Gallic acid and 1,3,4-Oxadiazole as potential inhibitors of ABL kinase has already been reported. Objective of this study is to evaluate the ABL kinase inhibitory activity of derivatives of Gallic acid fused with 1,3,4-Oxadiazole moieties. Attempts have been made to identify the key structural features responsible for drug likeness of the Gallic acid and the 1,3,4-Oxadiazole ring using molecular electrostatic potential maps (MESP). To investigate the inhibitory activity of Gallic acid derivatives towards the ABL receptor, we have applied molecular docking and molecular dynamics (MD) simulation approaches. A comparative study was performed using Bosutinib as the standard which is an approved CML drug acting on the same receptor. Furthermore, the novel compounds designed and reported here in were evaluated for ADME properties and the results indicate that they show acceptable pharmacokinetic properties. Accordingly these compounds are predicted to be drug like with low toxicity potential. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Abraham, Christina Susan; Prasana, Johanan Christian; Muthu, S.; Rizwana B, Fathima; Raja, M.
2018-05-01
The research exploration will comprise of investigating the molecular structure, vibrational assignments, bonding and anti-bonding nature, nonlinear optical, electronic and thermodynamic nature of the molecule. The research is conducted at two levels: First level employs the spectroscopic techniques - FT-IR, FT-Raman and UV-Vis characterizing techniques; at second level the data attained experimentally is analyzed through theoretical methods using and Density Function Theories which involves the basic principle of solving the Schrodinger equation for many body systems. A comparison is drawn between the two levels and discussed. The probability of the title molecule being bio-active theoretically proved by the electrophilicity index leads to further property analyzes of the molecule. The target molecule is found to fit well with Centromere associated protein inhibitor using molecular docking techniques. Higher basis set 6-311++G(d,p) is used to attain results more concurrent to the experimental data. The results of the organic amine 2, 4 Dibromoaniline is analyzed and discussed.
Kawai, Ryoko; Araki, Mitsugu; Yoshimura, Masashi; Kamiya, Narutoshi; Ono, Masahiro; Saji, Hideo; Okuno, Yasushi
2018-05-16
Development of new diagnostic imaging probes for Alzheimer's disease, such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) probes, has been strongly desired. In this study, we investigated the most accessible amyloid β (Aβ) binding site of [ 123 I]IMPY, a Thioflavin-T-derived SPECT probe, using experimental and computational methods. First, we performed a competitive inhibition assay with Orange-G, which recognizes the KLVFFA region in Aβ fibrils, suggesting that IMPY and Orange-G bind to different sites in Aβ fibrils. Next, we precisely predicted the IMPY binding site on a multiple-protofilament Aβ fibril model using computational approaches, consisting of molecular dynamics and docking simulations. We generated possible IMPY-binding structures using docking simulations to identify candidates for probe-binding sites. The binding free energy of IMPY with the Aβ fibril was calculated by a free energy simulation method, MP-CAFEE. These computational results suggest that IMPY preferentially binds to an interfacial pocket located between two protofilaments and is stabilized mainly through hydrophobic interactions. Finally, our computational approach was validated by comparing it with the experimental results. The present study demonstrates the possibility of computational approaches to screen new PET/SPECT probes for Aβ imaging.
Pandini, Alessandro; Fraccalvieri, Domenico; Bonati, Laura
2013-01-01
The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.
Kuruvilla, Tintu K; Prasana, Johanan Christian; Muthu, S; George, Jacob; Mathew, Sheril Ann
2018-01-05
Quantum chemical techniques such as density functional theory (DFT) have become a powerful tool in the investigation of the molecular structure and vibrational spectrum and are finding increasing use in application related to biological systems. The Fourier transform infrared (FT-IR) and Fourier transform Raman (FT-Raman) techniques are employed to characterize the title compound. The vibrational frequencies were obtained by DFT/B3LYP calculations with 6-31G(d,p) and 6-311++G(d,p) as basis sets. The geometry of the title compound was optimized. The vibrational assignments and the calculation of Potential Energy Distribution (PED) were carried out using the Vibrational Energy Distribution Analysis (VEDA) software. Molecular electrostatic potential was calculated for the title compound to predict the reactive sites for electrophilic and nucleophilic attack. In addition, the first-order hyperpolarizability, HOMO and LUMO energies, Fukui function and NBO were computed. The thermodynamic properties of the title compound were calculated at different temperatures, revealing the correlations between heat capacity (C), entropy (S) and enthalpy changes (H) with temperatures. Molecular docking studies were also conducted as part of this study. The paper further explains the experimental results which are in line with the theoretical calculations and provide optimistic evidence through molecular docking that the title compound can act as a good antidepressant. It also provides sufficient justification for the title compound to be selected as a good candidate for further studies related to NLO properties. Copyright © 2017. Published by Elsevier B.V.
Jimenez-Lopez, J C; Robles-Bolivar, P; Lopez-Valverde, F J; Lima-Cabello, E; Kotchoni, S O; Alché, J D
2016-05-01
Thaumatin-like proteins (TLPs) are enzymes with important functions in pathogens defense and in the response to biotic and abiotic stresses. Last identified olive allergen (Ole e 13) is a TLP, which may also importantly contribute to food allergy and cross-allergenicity to pollen allergen proteins. The goals of this study are the characterization of the structural-functionality of Ole e 13 with a focus in its catalytic mechanism, and its molecular allergenicity by extensive analysis using different molecular computer-aided approaches covering a) functional-regulatory motifs, b) comparative study of linear sequence, 2-D and 3D structural homology modeling, c) molecular docking with two different β-D-glucans, d) conservational and evolutionary analysis, e) catalytic mechanism modeling, and f) IgE-binding, B- and T-cell epitopes identification and comparison to other allergenic TLPs. Sequence comparison, structure-based features, and phylogenetic analysis identified Ole e 13 as a thaumatin-like protein. 3D structural characterization revealed a conserved overall folding among plants TLPs, with mayor differences in the acidic (catalytic) cleft. Molecular docking analysis using two β-(1,3)-glucans allowed to identify fundamental residues involved in the endo-1,3-β-glucanase activity, and defining E84 as one of the conserved residues of the TLPs responsible of the nucleophilic attack to initiate the enzymatic reaction and D107 as proton donor, thus proposing a catalytic mechanism for Ole e 13. Identification of IgE-binding, B- and T-cell epitopes may help designing strategies to improve diagnosis and immunotherapy to food allergy and cross-allergenic pollen TLPs. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Sebastian, S. H. Rosline; Al-Alshaikh, Monirah A.; El-Emam, Ali A.; Panicker, C. Yohannan; Zitko, Jan; Dolezal, Martin; VanAlsenoy, C.
2016-09-01
The molecular structural parameters and vibrational frequencies of 5-chloro-N-(3-nitrophenyl)pyrazine-2-carboxamide have been obtained using density functional theory technique in the B3LYP approximation and CC-pVDZ (5D, 7F) basis set. Detailed vibrational assignments of observed FT-IR and FT-Raman bands have been proposed on the basis of potential energy distribution and most of the modes have wavenumbers in the expected range. In the present case, the NH stretching mode is a doublet in the IR spectrum with a difference of 138 cm-1 and is red shifted by 76 cm-1 from the computed value, which indicates the weakening of NH bond resulting in proton transfer to the neighboring oxygen atom. The molecular electrostatic potential has been mapped for predicting sites and relative reactivities towards electrophilic and nucleophilic attack. The hyperpolarizability values are calculated in order to find its role in nonlinear optics. From the molecular docking study, amino acids Asn161, His162 forms H-bond with pyrazine ring and Trp184, Gln19 shows H-bond with Cdbnd O group and the docked ligand, title compound forms a stable complex with cathepsin K and the results suggest that the compound might exhibit inhibitory activity against cathepsin K. Moderate in vitro antiviral activity with EC50 at tens of μM was detected against feline herpes virus, coxsackie virus B4, and influenza A/H1N1 and A/H3N2.
Spectroscopic and theoretical investigation of oxali-palladium interactions with β-lactoglobulin.
Ghalandari, Behafarid; Divsalar, Adeleh; Saboury, Ali Akbar; Haertlé, Thomas; Parivar, Kazem; Bazl, Roya; Eslami-Moghadam, Mahbube; Amanlou, Massoud
2014-01-24
The possibility of using a small cheap dairy protein, β-lactoglobulin (β-LG), as a carrier for oxali-palladium for drug delivery was studied. Their binding in an aqueous solution at two temperatures of 25 and 37°C was investigated using spectroscopic techniques in combination with a molecular docking study. Fluorescence intensity changes showed combined static and dynamic quenching during β-LG oxali-palladium binding, with the static mode being predominant in the quenching mechanism. The binding and thermodynamic parameters were determined by analyzing the results of quenching and those of the van't Hoff equation. According to obtained results the binding constants at two temperatures of 25 and 37°C are 3.3×10(9) M(-1) and 18.4×10(6) M(-1) respectively. Fluorescence resonance energy transfer (FRET) showed that the experimental results and the molecular docking results were coherent. An absence change of β-LG secondary structure was confirmed by the CD results. Molecular docking results agreed fully with the experimental results since the fluorescence studies also revealed the presence of two binding sites with a negative value for the Gibbs free energy of binding of oxali-palladium to β-LG. Furthermore, molecular docking and experimental results suggest that the hydrophobic effect plays a critical role in the formation of the oxali-palladium complex with β-LG. This agreement between molecular docking and experimental results implies that docking studies may be a suitable method for predicting and confirming experimental results, as shown in this study. Hence, the combination of molecular docking and spectroscopy methods is an effective innovative approach for binding studies, particularly for pharmacophores. Copyright © 2013 Elsevier B.V. All rights reserved.
Yu, Haijing; Fang, Yu; Lu, Xia; Liu, Yongjuan; Zhang, Huabei
2014-01-01
The NS5B RNA-dependent RNA polymerase (RdRP) is a promising therapeutic target for developing novel anti-hepatitis C virus (HCV) drugs. In this work, a combined molecular modeling study was performed on a series of 193 5-hydroxy-2H-pyridazin-3-one derivatives as inhibitors of HCV NS5B Polymerase. The best 3D-QSAR models, including CoMFA and CoMSIA, are based on receptor (or docking). Furthermore, a 40-ns molecular dynamics (MD) simulation and binding free energy calculations using docked structures of NS5B with ten compounds, which have diverse structures and pIC50 values, were employed to determine the detailed binding process and to compare the binding modes of the inhibitors with different activities. On one side, the stability and rationality of molecular docking and 3D-QSAR results were validated by MD simulation. The binding free energies calculated by the MM-PBSA method gave a good correlation with the experimental biological activity. On the other side, by analyzing some differences between the molecular docking and the MD simulation results, we can find that the MD simulation could also remedy the defects of molecular docking. The analyses of the combined molecular modeling results have identified that Tyr448, Ser556, and Asp318 are the key amino acid residues in the NS5B binding pocket. The results from this study can provide some insights into the development of novel potent NS5B inhibitors. © 2013 John Wiley & Sons A/S.
Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha
2018-02-01
Filamentous temperature-sensitive protein Z (FtsZ) is a protein encoded by the FtsZ gene that assembles into a Z-ring at the future site of the septum of bacterial cell division. Structurally, FtsZ is a homolog of eukaryotic tubulin but has low sequence similarity; this makes it possible to obtain FtsZ inhibitors without affecting the eukaryotic cell division. Computational studies were performed on a series of substituted 3-arylalkoxybenzamide derivatives reported as inhibitors of FtsZ activity in Staphylococcus aureus. Quantitative structure-activity relationship models (QSAR) models generated showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of these models was determined and an acceptable predictive correlation (r 2 Pred ) values were obtained. Finally, we performed molecular dynamics simulations in order to examine the stability of protein-ligand interactions. This facilitated us to compare free binding energies of cocrystal ligand and newly designed molecule B1. The good concordance between the docking results and comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) contour maps afforded obliging clues for the rational modification of molecules to design more potent FtsZ inhibitors.
NASA Astrophysics Data System (ADS)
Gianti, Eleonora; Messick, Troy E.; Lieberman, Paul M.; Zauhar, Randy J.
2016-04-01
The Epstein-Barr Nuclear Antigen 1 (EBNA1) is a critical protein encoded by the Epstein-Barr Virus (EBV). During latent infection, EBNA1 is essential for DNA replication and transcription initiation of viral and cellular genes and is necessary to immortalize primary B-lymphocytes. Nonetheless, the concept of EBNA1 as drug target is novel. Two EBNA1 crystal structures are publicly available and the first small-molecule EBNA1 inhibitors were recently discovered. However, no systematic studies have been reported on the structural details of EBNA1 "druggable" binding sites. We conducted computational identification and structural characterization of EBNA1 binding pockets, likely to accommodate ligand molecules (i.e. "druggable" binding sites). Then, we validated our predictions by docking against a set of compounds previously tested in vitro for EBNA1 inhibition (PubChem AID-2381). Finally, we supported assessments of pocket druggability by performing induced fit docking and molecular dynamics simulations paired with binding affinity predictions by Molecular Mechanics Generalized Born Surface Area calculations for a number of hits belonging to druggable binding sites. Our results establish EBNA1 as a target for drug discovery, and provide the computational evidence that active AID-2381 hits disrupt EBNA1:DNA binding upon interacting at individual sites. Lastly, structural properties of top scoring hits are proposed to support the rational design of the next generation of EBNA1 inhibitors.
DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina.
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.
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).
Pirali, Tracey; Faccio, Valeria; Mossetti, Riccardo; Grolla, Ambra A; Di Micco, Simone; Bifulco, Giuseppe; Genazzani, Armando A; Tron, Gian Cesare
2010-02-01
Novel macrocyclic peptide mimetics have been synthesized by exploiting a three-component reaction and an azide-alkyne [3 + 2] cycloaddition. The prepared compounds were screened as HDAC inhibitors allowing us to identify a new compound with promising biological activity. In order to rationalize the biological results, computational studies have also been performed.
Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.; ...
2015-08-26
The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.
The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less
Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations.
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.
NASA Astrophysics Data System (ADS)
Kaur, Amandeep; Khan, Imran Ahmd; Banipal, Parampaul Kaur; Banipal, Tarlok Singh
2018-02-01
The current work aims to explore the thermodynamic and conformational aspects for the binding of fluoroquinolone antibacterial drug, levofloxacin (LFC), with bovine serum albumin (BSA) using calorimetric, spectroscopic (UV-visible, fluorescence, circular dichroism, and 1H NMR), dynamic light scattering (DLS) and computational methods (molecular docking). The binding of LFC with BSA at two sequential sites with higher affinity ( 103 M- 1) at the first site has been explored by calorimetry whereas the binding at a single site with affinity of the order of 104 M- 1 has been observed from fluorescence spectroscopy. The calorimetric study in the presence of additives along with docking analysis reveals the significant role of electrostatic, hydrogen bonding, and hydrophobic interactions in the association process. The slight conformational changes in protein as well as the changes in the water network structure around the binding cavity of protein have been observed from spectroscopic and DLS measurements. The LFC induced quenching of BSA fluorescence was observed to be initiated mainly through the static quenching process and this suggests the formation of ground state LFC-BSA association complex. The stronger interactions of LFC in the cavity of Sudlow site I (subdomain IIA) of protein have been explored from site marker calorimetric and molecular docking study.
Muthusamy, Karthikeyan; Chinnasamy, Sathishkumar; Nagarajan, Subbiah; Sivaraman, Thirunavukkarasu
2017-12-14
Ikshusterol3-O-glucoside was isolated from Clematis gouriana Roxb. ex DC. root. A structure of the isolated compound was determined on the basis of various spectroscopic interpretations (UV, NMR, FTIR, and GC-MS-EI). This structure was submitted in the PubChem compound database (SID 249494133). SID 249494133 was carried out by density functional theory calculation to observe the chemical stability and electrostatic potential of this compound. The absorption, distribution, metabolism, and excretion property of this compound was predicted to evaluate the drug likeness and toxicity. In addition, molecular docking, quantum polarized ligand docking, prime MMGBSA calculation, and induced fit docking were performed to predict the binding status of SID 249494133 with the active site of phospholipase A 2 (PLA 2 ) (PDB ID: 1A3D). The stability of the compound in the active site of PLA 2 was carried out using molecular dynamics simulation. Further, the anti-venom activity of the compound was assessed using the PLA 2 assay against Naja naja (Indian cobra) crude venom. The results strongly show that Ikshusterol3-O-glucoside has a potent snake-venom neutralizing capacity and it might be a potential molecule for the therapeutic treatment for snakebites.
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.
Garro Martinez, Juan C; Vega-Hissi, Esteban G; Andrada, Matías F; Duchowicz, Pablo R; Torrens, Francisco; Estrada, Mario R
2014-01-01
Lacosamide is an anticonvulsant drug which presents carbonic anhydrase inhibition. In this paper, we analyzed the apparent relationship between both activities performing a molecular modeling, docking and QSAR studies on 18 lacosamide derivatives with known anticonvulsant activity. Docking results suggested the zinc-binding site of carbonic anhydrase is a possible target of lacosamide and lacosamide derivatives making favorable Van der Waals interactions with Asn67, Gln92, Phe131 and Thr200. The mathematical models revealed a poor relationship between the anticonvulsant activity and molecular descriptors obtained from DFT and docking calculations. However, a QSAR model was developed using Dragon software descriptors. The statistic parameters of the model are: correlation coefficient, R=0.957 and standard deviation, S=0.162. Our results provide new valuable information regarding the relationship between both activities and contribute important insights into the essential molecular requirements for the anticonvulsant activity.
Kazemi, Zahra; Rudbari, Hadi Amiri; Sahihi, Mehdi; Mirkhani, Valiollah; Moghadam, Majid; Tangestaninejad, Shahram; Mohammadpoor-Baltork, Iraj; Gharaghani, Sajjad
2016-09-01
Novel metal-based drug candidate including VOL2, NiL2, CuL2 and PdL2 have been synthesized from 2-hydroxy-1-allyliminomethyl-naphthalen ligand and have been characterized by means of elemental analysis (CHN), FT-IR and UV-vis spectroscopies. In addition, (1)H and (13)C NMR techniques were employed for characterization of the PdL2 complex. Single-crystal X-ray diffraction technique was utilized to characterise the structure of the complexes. The Cu(II), Ni(II) and Pd(II) complexes show a square planar trans-coordination geometry, while in the VOL2, the vanadium center has a distorted tetragonal pyramidal N2O3 coordination sphere. The HSA-binding was also determined, using fluorescence quenching, UV-vis spectroscopy, and circular dichroism (CD) titration method. The obtained results revealed that the HSA affinity for binding the synthesized compounds follows as PdL2>CuL2>VOL2>NiL2, indicating the effect of metal ion on binding constant. The distance between these compounds and HSA was obtained based on the Förster's theory of non-radiative energy transfer. Furthermore, computational methods including molecular docking and our Own N-layered Integrated molecular Orbital and molecular Mechanics (ONIOM) were carried out to investigate the HSA-binding of the compounds. Molecular docking calculation indicated the existence of hydrogen bond between amino acid residues of HSA and all synthesized compounds. The formation of the hydrogen bond in the HSA-compound systems leads to their stabilization. The ONIOM method was utilized in order to investigate HSA binding of compounds more precisely in which molecular mechanics method (UFF) and semi empirical method (PM6) were selected for the low layer and the high layer, respectively. The results show that the structural parameters of the compounds changed along with binding to HSA, indicating the strong interaction between the compounds and HSA. The value of binding constant depends on the extent of the resultant changes. This should be mentioned that both theoretical methods calculated the Kb values in the same sequence and are in a good agreement with the experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.
Assessing the binding of cholinesterase inhibitors by docking and molecular dynamics studies.
Ali, M Rejwan; Sadoqi, Mostafa; Møller, Simon G; Boutajangout, Allal; Mezei, Mihaly
2017-09-01
In this report we assessed by docking and molecular dynamics the binding mechanisms of three FDA-approved Alzheimer drugs, inhibitors of the enzyme acetylcholinesterase (AChE): donepezil, galantamine and rivastigmine. Dockings by the softwares Autodock-Vina, PatchDock and Plant reproduced the docked conformations of the inhibitor-enzyme complexes within 2Å of RMSD of the X-ray structure. Free-energy scores show strong affinity of the inhibitors for the enzyme binding pocket. Three independent Molecular Dynamics simulation runs indicated general stability of donepezil, galantamine and rivastigmine in their respective enzyme binding pocket (also referred to as gorge) as well as the tendency to form hydrogen bonds with the water molecules. The binding of rivastigmine in the Torpedo California AChE binding pocket is interesting as it eventually undergoes carbamylation and breaks apart according to the X-ray structure of the complex. Similarity search in the ZINC database and targeted docking on the gorge region of the AChE enzyme gave new putative inhibitor molecules with high predicted binding affinity, suitable for potential biophysical and biological assessments. Copyright © 2017 Elsevier Inc. All rights reserved.
Rapid computational identification of the targets of protein kinase inhibitors.
Rockey, William M; Elcock, Adrian H
2005-06-16
We describe a method for rapidly computing the relative affinities of an inhibitor for all individual members of a family of homologous receptors. The approach, implemented in a new program, SCR, models inhibitor-receptor interactions in full atomic detail with an empirical energy function and includes an explicit account of flexibility in homology-modeled receptors through sampling of libraries of side chain rotamers. SCR's general utility was demonstrated by application to seven different protein kinase inhibitors: for each inhibitor, relative binding affinities with panels of approximately 20 protein kinases were computed and compared with experimental data. For five of the inhibitors (SB203580, purvalanol B, imatinib, H89, and hymenialdisine), SCR provided excellent reproduction of the experimental trends and, importantly, was capable of identifying the targets of inhibitors even when they belonged to different kinase families. The method's performance in a predictive setting was demonstrated by performing separate training and testing applications, and its key assumptions were tested by comparison with a number of alternative approaches employing the ligand-docking program AutoDock (Morris et al. J. Comput. Chem. 1998, 19, 1639-1662). These comparison tests included using AutoDock in nondocking and docking modes and performing energy minimizations of inhibitor-kinase complexes with the molecular mechanics code GROMACS (Berendsen et al. Comput. Phys. Commun. 1995, 91, 43-56). It was found that a surprisingly important aspect of SCR's approach is its assumption that the inhibitor be modeled in the same orientation for each kinase: although this assumption is in some respects unrealistic, calculations that used apparently more realistic approaches produced clearly inferior results. Finally, as a large-scale application of the method, SB203580, purvalanol B, and imatinib were screened against an almost full complement of 493 human protein kinases using SCR in order to identify potential new targets; the predicted targets of SB203580 were compared with those identified in recent proteomics-based experiments. These kinome-wide screens, performed within a day on a small cluster of PCs, indicate that explicit computation of inhibitor-receptor binding affinities has the potential to promote rapid discovery of new therapeutic targets for existing inhibitors.
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.
Khoshneviszadeh, Mehdi; Shahraki, Omolbanin; Khoshneviszadeh, Mahsima; Foroumadi, Alireza; Firuzi, Omidreza; Edraki, Najmeh; Nadri, Hamid; Moradi, Alireza; Shafiee, Abbas; Miri, Ramin
2016-12-01
A set of 1,2,4-triazine derivatives were designed as cyclooxygenase-2 (COX-2) inhibitors. These compounds were synthesized and screened for inhibition of cyclooxygenases (COX-1 and COX-2) based on a cellular assay using human whole blood (HWB) and lipoxygenase (LOX-15) that are key enzymes in inflammation. The results showed that 3-(2-(benzo[d][1,3]dioxol-5-ylmethylene)hydrazinyl)-5,6-bis(4-methoxyphenyl)-1,2,4-triazine (G11) was identified as the most potent COX-2 inhibitor (78%) relative to COX-1 (50%). Ferric reducing anti-oxidant power (FRAP) assay revealed that compound G10 possesses the highest anti-oxidant activity. The compound G3 with IC50 value of 124 μM was the most potent compound in LOX inhibitory assay. Molecular docking was performed and a good agreement was observed between computational and experimental results.
Rodríguez, Yeray A; Gutiérrez, Margarita; Ramírez, David; Alzate-Morales, Jans; Bernal, Cristian C; Güiza, Fausto M; Romero Bohórquez, Arnold R
2016-10-01
New N-allyl/propargyl 4-substituted 1,2,3,4-tetrahydroquinolines derivatives were efficiently synthesized using acid-catalyzed three components cationic imino Diels-Alder reaction (70-95%). All compounds were tested in vitro as dual acetylcholinesterase and butyryl-cholinesterase inhibitors and their potential binding modes, and affinity, were predicted by molecular docking and binding free energy calculations (∆G) respectively. The compound 4af (IC50 = 72 μm) presented the most effective inhibition against acetylcholinesterase despite its poor selectivity (SI = 2), while the best inhibitory activity on butyryl-cholinesterase was exhibited by compound 4ae (IC50 = 25.58 μm) with considerable selectivity (SI = 0.15). Molecular docking studies indicated that the most active compounds fit in the reported acetylcholinesterase and butyryl-cholinesterase active sites. Moreover, our computational data indicated a high correlation between the calculated ∆G and the experimental activity values in both targets. © 2016 The Authors Chemical Biology & Drug Design Published by John Wiley & Sons Ltd.
Hu, Juan; Pang, Wen-Sheng; Han, Jing; Zhang, Kuan; Zhang, Ji-Zhou; Chen, Li-Dian
2018-12-01
Stroke is a disease of the leading causes of mortality and disability across the world, but the benefits of drugs curative effects look less compelling, intracellular calcium overload is considered to be a key pathologic factor for ischemic stroke. Gualou Guizhi decoction (GLGZD), a classical Chinese medicine compound prescription, it has been used to human clinical therapy of sequela of cerebral ischemia stroke for 10 years. This work investigated the GLGZD improved prescription against intracellular calcium overload could decreased the concentration of [Ca 2+ ] i in cortex and striatum neurone of MCAO rats. GLGZD contains Trichosanthin and various small molecular that they are the potential active ingredients directed against NR2A, NR2B, FKBP12 and Calnodulin target proteins/enzyme have been screened by computer simulation. "Multicomponent systems" is capable to create pharmacological superposition effects. The Chinese medicine compound prescriptions could be considered as promising sources of candidates for discovery new agents.
Molecular insights into the binding of phosphoinositides to the TH domain region of TIPE proteins.
Antony, Priya; Baby, Bincy; Vijayan, Ranjit
2016-11-01
Phosphatidylinositols and their phosphorylated derivatives, phosphoinositides, play a central role in regulating diverse cellular functions. These phospholipids have been shown to interact with the hydrophobic TH domain of the tumor necrosis factor (TNF)-α-induced protein 8 (TIPE) family of proteins. However, the precise mechanism of interaction of these lipids is unclear. Here we report the binding mode and interactions of these phospholipids in the TH domain, as elucidated using molecular docking and simulations. Results indicate that phosphoinositides bind to the TH domain in a similar way by inserting their lipid tails in the hydrophobic cavity. The exposed head group is stabilized by interactions with critical positively charged residues on the surface of these proteins. Further MD simulations confirmed the dynamic stability of these lipids in the TH domain. This computational analysis thus provides insight into the binding mode of phospholipids in the TH domain of the TIPE family of proteins. Graphical abstract A phosphoinositide (phosphatidylinositol 4-phosphate; PtdIns4P) docked to TIPE2.
NASA Astrophysics Data System (ADS)
Das, Dipankar; Sahu, Nilima; Roy, Suman; Dutta, Paramita; Mondal, Sudipa; Torres, Elena L.; Sinha, Chittaranjan
2015-02-01
Sulfamethoxazole (SMX) [4-amino-N-(5-methyl-1,2-oxazol-3-yl)benzenesulfonamide] is structurally established by single crystal X-ray diffraction measurement. The crystal packing shows H-bonded 2D polymer through N(7)sbnd H(7A)---O(2), N(7)sbnd H(7B)---O(3), N(1)sbnd H(1)---N(2), C(5)sbnd H(5)---O(3)sbnd S(1) and N(7)sbnd (H7A)---O(2)sbnd S(1). Density Functional Theory (DFT) and Time Dependent-DFT (TD-DFT) computations of optimized structure of SMX determine the electronic structure and has explained the electronic spectral transitions. The interaction of SMX with CT-DNA has been studied by absorption spectroscopy and the binding constant (Kb) is 4.37 × 104 M-1. The in silico test of SMX with DHPS from Escherichia coli and Streptococcus pneumoniae helps to understand drug metabolism and accounts the drug-molecule interactions. The molecular docking of SMX-DNA also helps to predict the interaction feature.
A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking
Trellet, Mikael; Melquiond, Adrien S. J.; Bonvin, Alexandre M. J. J.
2013-01-01
Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking. PMID:23516555
A unified conformational selection and induced fit approach to protein-peptide docking.
Trellet, Mikael; Melquiond, Adrien S J; Bonvin, Alexandre M J J
2013-01-01
Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.
Investigation of MM-PBSA rescoring of docking poses.
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.
Using computer-aided drug design and medicinal chemistry strategies in the fight against diabetes.
Semighini, Evandro P; Resende, Jonathan A; de Andrade, Peterson; Morais, Pedro A B; Carvalho, Ivone; Taft, Carlton A; Silva, Carlos H T P
2011-04-01
The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics, ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.
Velázquez, Claudia; Correa-Basurto, José; Garcia-Hernandez, Normand; Barbosa, Elizabeth; Tesoro-Cruz, Emiliano; Calzada, Samuel; Calzada, Fernando
2012-09-28
Chiranthodendron pentadactylon Larreat is frequently used in Mexican traditional medicine as well as in Guatemalan for several medicinal purposes, including their use in the control of diarrhea. This work was undertaken to obtain additional information that support the traditional use of Chiranthodendron pentadactylon Larreat, on pharmacological basis using the major antisecretory isolated compound from computational, in vitro and in vivo experiments. (-)-Epicatechin was isolated from ethyl acetate fraction of the plant crude extract. In vivo toxin (Vibrio cholera or Escherichia coli)-induced intestinal secretion in rat jejunal loops models and sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on Vibrio cholera toxin were used in experimental studies while the molecular docking technique was used to conduct computational study. The antisecretory activity of epicatechin was tested against Vibrio cholera and Escherichia coli toxins at oral dose 10 mg/kg in the rat model. It exhibited the most potent activity on Vibrio cholera toxin (56.9% of inhibition). In the case of Escherichia coli toxin its effect was moderate (24.1% of inhibition). SDS-PAGE analysis revealed that both (-)-epicatechin and Chiranthodendron pentadactylon extract interacted with the Vibrio cholera toxin at concentration from 80 μg/mL and 300 μg/mL, respectively. Computational molecular docking showed that epicatechin interacted with four amino acid residues (Asn 103, Phe 31, Phe 223 and The 78) in the catalytic site of Vibrio cholera toxin, revealing its potential binding mode at molecular level. The results derived from computational, in vitro and in vivo experiments on Vibrio cholera and Escherichia coli toxins confirm the potential of epicatechin as a new antisecretory compound and give additional scientific support to anecdotal use of Chiranthodendron pentadactylon Larreat in Mexican traditional medicine to treat gastrointestinal disorders such as diarrhea. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Combined spectroscopic and quantum chemical studies of ezetimibe
NASA Astrophysics Data System (ADS)
Prajapati, Preeti; Pandey, Jaya; Shimpi, Manishkumar R.; Srivastava, Anubha; Tandon, Poonam; Velaga, Sitaram P.; Sinha, Kirti
2016-12-01
Ezetimibe (EZT) is a hypocholesterolemic agent used for the treatment of elevated blood cholesterol levels as it lowers the blood cholesterol by blocking the absorption of cholesterol in intestine. Study aims to combine experimental and computational methods to provide insights into the structural and vibrational spectroscopic properties of EZT which is important for explaining drug substance physical and biological properties. Computational study on molecular properties of ezetimibe is presented using density functional theory (DFT) with B3LYP functional and 6-311++G(d,p) basis set. A detailed vibrational assignment has been done for the observed IR and Raman spectra of EZT. In addition to the conformational study, hydrogen bonding and molecular docking studies have been also performed. For conformational studies, the double well potential energy curves have been plotted for the rotation around the six flexible bonds of the molecule. UV absorption spectrum was examined in methanol solvent and compared with calculated one in solvent environment (IEF-PCM) using TD-DFT/6-31G basis set. HOMO-LUMO energy gap of both the conformers have also been calculated in order to predict its chemical reactivity and stability. The stability of the molecule was also examined by means of natural bond analysis (NBO) analysis. To account for the chemical reactivity and site selectivity of the molecules, molecular electrostatic potential (MEPS) map has been plotted. The combination of experimental and calculated results provide an insight into the structural and vibrational spectroscopic properties of EZT. In order to give an insight for the biological activity of EZT, molecular docking of EZT with protein NPC1L1 has been done.
Sokkar, Pandian; Sathis, Vani; Ramachandran, Murugesan
2012-05-01
Hypoxia inducible factor-1 (HIF-1) is a bHLH-family transcription factor that controls genes involved in glycolysis, angiogenesis, migration, as well as invasion factors that are important for tumor progression and metastasis. HIF-1, a heterodimer of HIF-1α and HIF-1β, binds to the hypoxia responsive element (HRE) present in the promoter regions of hypoxia responsive genes, such as vascular endothelial growth factor (VEGF). Neither the structure of free HIF-1 nor that of its complex with HRE is available. Computational modeling of the transcription factor-DNA complex has always been challenging due to their inherent flexibility and large conformational space. The present study aims to model the interaction between the DNA-binding domain of HIF-1 and HRE. Experiments showed that rigid macromolecular docking programs (HEX and GRAMM-X) failed to predict the optimal dimerization of individually modeled HIF-1 subunits. Hence, the HIF-1 heterodimer was modeled based on the phosphate system positive regulatory protein (PHO4) homodimer. The duplex VEGF-DNA segment containing HRE with flanking nucleotides was modeled in the B form and equilibrated via molecular dynamics (MD) simulation. A rigid docking approach was used to predict the crude binding mode of HIF-1 dimer with HRE, in which the putative contacts were found to be present. An MD simulation (5 ns) of the HIF-1-HRE complex in explicit water was performed to account for its flexibility and to optimize its interactions. All of the conserved amino acid residues were found to play roles in the recognition of HRE. The present work, which sheds light on the recognition of HRE by HIF-1, could be beneficial in the design of peptide or small molecule therapeutics that can mimic HIF-1 and bind with the HRE sequence.
NASA Astrophysics Data System (ADS)
Aziz, Hamid; Saeed, Aamer; Jabeen, Farukh; Simpson, Jim; Munawar, Amna; Qasim, Muhammad
2018-03-01
Amide derivatives have gained considerable attention because of their extensive range of biological activities and pharmaceutical applications. The current paper presents the synthesis of N, N‧-(ethane-1,2-diyl) bis (3-methylbenzamide), (I), its molecular and crystal structure and an evaluation of its likely biological activity, including cytotoxicity (LD50 = 37.21 μg/ml) and antileishmanial activity (IC50 = 5.77 μg/ml). Moreover, a docking simulation was used to determine the possible interaction sites of the compound (I) with TryR, an enzyme involved in the redox metabolism of the leishmania parasite. Docking computations demonstrate that the compound established prominent binding interactions with the key residues of the TryR and possess the potential to effectively inhibit the catalytic activities of the enzyme. Thus the results suggest that this compound can serve as a potential scaffold for the treatment of leishmaniasis and deserves further development.
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.
Peptide docking of HIV-1 p24 with single chain fragment variable (scFv) by CDOCKER algorithm
NASA Astrophysics Data System (ADS)
Karim, Hana Atiqah Abdul; Tayapiwatana, Chatchai; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abdul; Lee, Vannajan Sanghiran
2014-10-01
In search for the important residues that might have involve in the binding interaction between the p24 caspid protein of HIV-1 fragment (MET68 - PRO90) with the single chain fragment variable (scFv) of FAB23.5, modern computational chemistry approach has been conducted and applied. The p24 fragment was initially taken out from the 1AFV protein molecule consisting of both light (VL) and heavy (VH) chains of FAB23.5 as well as the HIV-1 caspid protein. From there, the p24 (antigen) fragment was made to dock back into the protein pocket receptor (antibody) by using the CDOCKER algorithm to conduct the molecular docking process. The score calculated from the CDOCKER gave 15 possible docked poses with various docked ligand's positions, the interaction energy as well as the binding energy. The best docked pose that imitates the original antigen's position was determined and further processed to the In Situ minimization to obtain the residues interaction energy as well as to observe the hydrogen bonds interaction in the protein-peptide complex. Based on the results demonstrated, the specific residues in the complex that have shown immense lower interaction energies in the 5Å vicinity region from the peptide are from the heavy chain (VH:TYR105) and light chain (VL: ASN31, TYR32, and GLU97). Those residues play vital roles in the binding mechanism of Antibody-Antigen (Ab-Ag) complex of p24 with FAB23.5.
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.
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.
Liu, Jianling; Liu, Mengmeng; Yao, Yao; Wang, Jinan; Li, Yan; Li, Guohui; Wang, Yonghua
2012-01-01
Chitinolytic β-N-acetyl-d-hexosaminidases, as a class of chitin hydrolysis enzyme in insects, are a potential species-specific target for developing environmentally-friendly pesticides. Until now, pesticides targeting chitinolytic β-N-acetyl-d-hexosaminidase have not been developed. This study demonstrates a combination of different theoretical methods for investigating the key structural features of this enzyme responsible for pesticide inhibition, thus allowing for the discovery of novel small molecule inhibitors. Firstly, based on the currently reported crystal structure of this protein (OfHex1.pdb), we conducted a pre-screening of a drug-like compound database with 8 × 106 compounds by using the expanded pesticide-likeness criteria, followed by docking-based screening, obtaining 5 top-ranked compounds with favorable docking conformation into OfHex1. Secondly, molecular docking and molecular dynamics simulations are performed for the five complexes and demonstrate that one main hydrophobic pocket formed by residues Trp424, Trp448 and Trp524, which is significant for stabilization of the ligand–receptor complex, and key residues Asp477 and Trp490, are respectively responsible for forming hydrogen-bonding and π–π stacking interactions with the ligands. Finally, the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) analysis indicates that van der Waals interactions are the main driving force for the inhibitor binding that agrees with the fact that the binding pocket of OfHex1 is mainly composed of hydrophobic residues. These results suggest that screening the ZINC database can maximize the identification of potential OfHex1 inhibitors and the computational protocol will be valuable for screening potential inhibitors of the binding mode, which is useful for the future rational design of novel, potent OfHex1-specific pesticides. PMID:22605995
Capoferri, Luigi; Leth, Rasmus; ter Haar, Ernst; Mohanty, Arun K; Grootenhuis, Peter D J; Vottero, Eduardo; Commandeur, Jan N M; Vermeulen, Nico P E; Jørgensen, Flemming Steen; Olsen, Lars; Geerke, Daan P
2016-03-01
Cytochrome P450 BM3 (CYP102A1) mutant M11 is able to metabolize a wide range of drugs and drug-like compounds. Among these, M11 was recently found to be able to catalyze formation of human metabolites of mefenamic acid and other nonsteroidal anti-inflammatory drugs (NSAIDs). Interestingly, single active-site mutations such as V87I were reported to invert regioselectivity in NSAID hydroxylation. In this work, we combine crystallography and molecular simulation to study the effect of single mutations on binding and regioselective metabolism of mefenamic acid by M11 mutants. The heme domain of the protein mutant M11 was expressed, purified, and crystallized, and its X-ray structure was used as template for modeling. A multistep approach was used that combines molecular docking, molecular dynamics (MD) simulation, and binding free-energy calculations to address protein flexibility. In this way, preferred binding modes that are consistent with oxidation at the experimentally observed sites of metabolism (SOMs) were identified. Whereas docking could not be used to retrospectively predict experimental trends in regioselectivity, we were able to rank binding modes in line with the preferred SOMs of mefenamic acid by M11 and its mutants by including protein flexibility and dynamics in free-energy computation. In addition, we could obtain structural insights into the change in regioselectivity of mefenamic acid hydroxylation due to single active-site mutations. Our findings confirm that use of MD and binding free-energy calculation is useful for studying biocatalysis in those cases in which enzyme binding is a critical event in determining the selective metabolism of a substrate. © 2016 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Singh, Ravindra Kumar; Singh, Ashok Kumar
2017-02-01
A new flavanol-2,4-dinitrophenylhydrazone (FDNP) was synthesized and its structure was confirmed by FT-IR, FT-Raman, 1H NMR, mass spectrometry and elemental analysis. All quantum chemical calculations were carried out at level of density functional theory (DFT) with B3LYP functional using 6-311++ G (d,p) basis atomic set. UV-Vis absorption spectra for the singlet-singlet transition computed for fully optimized ground state geometry using Time-Dependent-Density Functional Theory (TD-DFT) with CAM-B3LYP functional was found to be in consistent with that of experimental findings. Analysis of vibrational (FT-IR and FT-Raman) spectrum and their assignments has been done by computing Potential Energy Distribution (PED) using Gar2ped. HOMO-LUMO analysis was performed and reactivity descriptors were calculated. Calculated global electrophilicity index (ω = 7.986 eV) shows molecule to be a strong electrophile. 1H NMR chemical shift calculated with the help of gauge-including atomic orbital (GIAO) approach shows agreement with experimental data. Various intramolecular interactions were analysed by AIM approach. DFT computed total first static hyperpolarizability (β0 = 189.03 × 10-30 esu) indicates that title molecule can be used as attractive future NLO material. Solvent induced effects on the NLO properties studied by using self-consistent reaction field (SCRF) method shows that β0 value increases with increase in solvent polarity. To study the thermal behaviour of title molecule, thermodynamic properties such as heat capacity, entropy and enthalpy change at various temperatures have been calculated and reported. Molecular docking results suggests title molecule to be a potential kinase inhibitor and might be used in future for designing of new anticancer drug.
A Novel Peptide Thrombopoietin Mimetic Designing and Optimization Using Computational Approach
Singh, Vimal Kishor; Kumar, Neeraj; Kalsan, Manisha; Saini, Abhishek; Chandra, Ramesh
2016-01-01
Thrombopoietin receptor (TPOR) is a cytokine receptor protein present on the cell surface. The activation of TPOR by thrombopoietin (TPO) (a glycoprotein hormone) triggers an intracellular cascade of megakaryocytopoiesis for the formation of platelets. Recent studies on ex vivo megakaryocytopoiesis have evolved the possibilities of therapeutics uses. These findings have paved the way for the development of various TPO alternatives (recombinant TPO, peptide, and non-peptide TPO mimetics), which are useful in regenerative medicine. However, these alternatives possess various limitations such as induction of autoimmune effects, high production cost, low specificity, and hence activity. In the present study, a novel peptidic TPO mimetic was designed through computational studies by studying the binding sites of TPO and TMP to TPOR and analogs of known mimetics. Screening of combinatorial library was done through molecular docking using ClusPro. These studies indicated mimetic-9 as a significant molecule since it was found to have better binding score of −938.8 kcal/mol with seven hydrogen bonds and a high number of hydrophobic interactions, than known mimetic TMP with docking score of −798.4 kcal/mol and TMP dimer with docking score of −811.9 kcal/mol for TPOR. Mimetic9-TPOR complex was further assessed by the molecular dynamics simulation, and their complex was found to be stable with an RMSD value of 0.091 Å. While studying the parameters, mimetic-9 was found to have overall good physiochemical properties with positive grand average hydropathy (GRAVY) score and high instability index score and was found to be localized in the extracellular region. The designed mimetic-9 might prove to be a useful lead molecule for mimicking the role of TPO for in vitro platelet production with higher efficiency. PMID:27630985
A Novel Peptide Thrombopoietin Mimetic Designing and Optimization Using Computational Approach.
Singh, Vimal Kishor; Kumar, Neeraj; Kalsan, Manisha; Saini, Abhishek; Chandra, Ramesh
2016-01-01
Thrombopoietin receptor (TPOR) is a cytokine receptor protein present on the cell surface. The activation of TPOR by thrombopoietin (TPO) (a glycoprotein hormone) triggers an intracellular cascade of megakaryocytopoiesis for the formation of platelets. Recent studies on ex vivo megakaryocytopoiesis have evolved the possibilities of therapeutics uses. These findings have paved the way for the development of various TPO alternatives (recombinant TPO, peptide, and non-peptide TPO mimetics), which are useful in regenerative medicine. However, these alternatives possess various limitations such as induction of autoimmune effects, high production cost, low specificity, and hence activity. In the present study, a novel peptidic TPO mimetic was designed through computational studies by studying the binding sites of TPO and TMP to TPOR and analogs of known mimetics. Screening of combinatorial library was done through molecular docking using ClusPro. These studies indicated mimetic-9 as a significant molecule since it was found to have better binding score of -938.8 kcal/mol with seven hydrogen bonds and a high number of hydrophobic interactions, than known mimetic TMP with docking score of -798.4 kcal/mol and TMP dimer with docking score of -811.9 kcal/mol for TPOR. Mimetic9-TPOR complex was further assessed by the molecular dynamics simulation, and their complex was found to be stable with an RMSD value of 0.091 Å. While studying the parameters, mimetic-9 was found to have overall good physiochemical properties with positive grand average hydropathy (GRAVY) score and high instability index score and was found to be localized in the extracellular region. The designed mimetic-9 might prove to be a useful lead molecule for mimicking the role of TPO for in vitro platelet production with higher efficiency.
Extracellular domains play different roles in gap junction formation and docking compatibility.
Bai, Donglin; Wang, Ao Hong
2014-02-15
GJ (gap junction) channels mediate direct intercellular communication and play an important role in many physiological processes. Six connexins oligomerize to form a hemichannel and two hemichannels dock together end-to-end to form a GJ channel. Connexin extracellular domains (E1 and E2) have been shown to be important for the docking, but the molecular mechanisms behind the docking and formation of GJ channels are not clear. Recent developments in atomic GJ structure and functional studies on a series of connexin mutants revealed that E1 and E2 are likely to play different roles in the docking. Non-covalent interactions at the docking interface, including hydrogen bonds, are predicted to form between interdocked extracellular domains. Protein sequence alignment analysis on the docking compatible/incompatible connexins indicate that the E1 domain is important for the formation of the GJ channel and the E2 domain is important in the docking compatibility in heterotypic channels. Interestingly, the hydrogen-bond forming or equivalent residues in both E1 and E2 domains are mutational hot spots for connexin-linked human diseases. Understanding the molecular mechanisms of GJ docking can assist us to develop novel strategies in rescuing the disease-linked connexin mutants.
Molecular docking of superantigens with class II major histocompatibility complex proteins.
Olson, M A; Cuff, L
1997-01-01
The molecular recognition of two superantigens with class II major histocompatibility complex molecules was simulated by using protein-protein docking. Superantigens studied were staphylococcal enterotoxin B (SEB) and toxic shock syndrome toxin-1 (TSST-1) in their crystallographic assemblies with HLA-DR1. Rigid-body docking was performed sampling configurational space of the interfacial surfaces by employing a strategy of partitioning the contact regions on HLA-DR1 into separate molecular recognition units. Scoring of docked conformations was based on an electrostatic continuum model evaluated with the finite-difference Poisson-Boltzmann method. Estimates of nonpolar contributions were derived from the buried molecular surface areas. We found for both superantigens that docking the HLA-DR1 surface complementary with the SEB and TSST-1 contact regions containing a homologous hydrophobic surface loop provided sufficient recognition for the reconstitution of native-like conformers exhibiting the highest-scoring free energies. For the SEB complex, the calculations were successful in reproducing the total association free energy. A comparison of the free-energy determinants of the conserved hydrophobic contact residue indicates functional similarity between the two proteins for this interface. Though both superantigens share a common global association mode, differences in binding topology distinguish the conformational specificities underlying recognition.
NASA Astrophysics Data System (ADS)
Putra, R. P.; Imaniastuti, R.; Nasution, M. A. F.; Kerami, Djati; Tambunan, U. S. F.
2018-04-01
Oseltamivir resistance as an inhibitor of neuraminidase influenza A virus subtype H1N1 has been reported lately. Therefore, to solve this problem, several kinds of research has been conducted to design and discover disulfide cyclic peptide ligands through molecular docking method, to find the potential inhibitors for neuraminidase H1N1 which then can disturb the virus replication. This research was studied and evaluated the interaction of ligands toward enzyme using molecular docking simulation, which was performed on three disulfide cyclic peptide inhibitors (DNY, LRL, and NNT), along with oseltamivir and zanamivir as the standard ligands using MOE 2008.10 software. The docking simulation shows that all disulfide cyclic peptide ligands have lower Gibbs free binding energies (ΔGbinding) than the standard ligands, with DNY ligand has the lowest ΔGbinding at -7.8544 kcal/mol. Furthermore, these ligands were also had better molecular interactions with neuraminidase than the standards, owing by the hydrogen bonds that were formed during the docking simulation. In the end, we concluded that DNY, LRL and NNT ligands have the potential to be developed as the inhibitor of neuraminidase H1N1.
Theoretical and experimental study of polycyclic aromatic compounds as β-tubulin inhibitors.
Olazarán, Fabian E; García-Pérez, Carlos A; Bandyopadhyay, Debasish; Balderas-Rentería, Isaias; Reyes-Figueroa, Angel D; Henschke, Lars; Rivera, Gildardo
2017-03-01
In this work, through a docking analysis of compounds from the ZINC chemical library on human β-tubulin using high performance computer cluster, we report new polycyclic aromatic compounds that bind with high energy on the colchicine binding site of β-tubulin, suggesting three new key amino acids. However, molecular dynamic analysis showed low stability in the interaction between ligand and receptor. Results were confirmed experimentally in in vitro and in vivo models that suggest that molecular dynamics simulation is the best option to find new potential β-tubulin inhibitors. Graphical abstract Bennett's acceptance ratio (BAR) method.
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.
Molecular Dynamics, Monte Carlo Simulations, and Langevin Dynamics: A Computational Review
Paquet, Eric; Viktor, Herna L.
2015-01-01
Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262
NASA Astrophysics Data System (ADS)
Oberhauser, Nils; Nurisso, Alessandra; Carrupt, Pierre-Alain
2014-05-01
The molecular lipophilicity potential (MLP) is a well-established method to calculate and visualize lipophilicity on molecules. We are here introducing a new computational tool named MLP Tools, written in the programming language Python, and conceived as a free plugin for the popular open source molecular viewer PyMOL. The plugin is divided into several sub-programs which allow the visualization of the MLP on molecular surfaces, as well as in three-dimensional space in order to analyze lipophilic properties of binding pockets. The sub-program Log MLP also implements the virtual log P which allows the prediction of the octanol/water partition coefficients on multiple three-dimensional conformations of the same molecule. An implementation on the recently introduced MLP GOLD procedure, improving the GOLD docking performance in hydrophobic pockets, is also part of the plugin. In this article, all functions of the MLP Tools will be described through a few chosen examples.
Flavin Charge Transfer Transitions Assist DNA Photolyase Electron Transfer
NASA Astrophysics Data System (ADS)
Skourtis, Spiros S.; Prytkova, Tatiana; Beratan, David N.
2007-12-01
This contribution describes molecular dynamics, semi-empirical and ab-initio studies of the primary photo-induced electron transfer reaction in DNA photolyase. DNA photolyases are FADH--containing proteins that repair UV-damaged DNA by photo-induced electron transfer. A DNA photolyase recognizes and binds to cyclobutatne pyrimidine dimer lesions of DNA. The protein repairs a bound lesion by transferring an electron to the lesion from FADH-, upon photo-excitation of FADH- with 350-450 nm light. We compute the lowest singlet excited states of FADH- in DNA photolyase using INDO/S configuration interaction, time-dependent density-functional, and time-dependent Hartree-Fock methods. The calculations identify the lowest singlet excited state of FADH- that is populated after photo-excitation and that acts as the electron donor. For this donor state we compute conformationally-averaged tunneling matrix elements to empty electron-acceptor states of a thymine dimer bound to photolyase. The conformational averaging involves different FADH--thymine dimer confromations obtained from molecular dynamics simulations of the solvated protein with a thymine dimer docked in its active site. The tunneling matrix element computations use INDO/S-level Green's function, energy splitting, and Generalized Mulliken-Hush methods. These calculations indicate that photo-excitation of FADH- causes a π→π* charge-transfer transition that shifts electron density to the side of the flavin isoalloxazine ring that is adjacent to the docked thymine dimer. This shift in electron density enhances the FADH--to-dimer electronic coupling, thus inducing rapid electron transfer.
Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha
2018-04-01
Staphylococcus aureus is a gram positive bacterium. It is the leading cause of skin and respiratory infections, osteomyelitis, Ritter's disease, endocarditis, and bacteraemia in the developed world. We employed combined studies of 3D QSAR, molecular docking which are validated by molecular dynamics simulations and in silico ADME prediction have been performed on Isothiazoloquinolones inhibitors against methicillin resistance Staphylococcus aureus. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was applied using comparative molecular field analysis (CoMFA) with Q 2 of 0.578, R 2 of 0.988, and comparative molecular similarity indices analysis (CoMSIA) with Q 2 of 0.554, R 2 of 0.975. The predictive ability of these model was determined using a test set of molecules that gave acceptable predictive correlation (r 2 Pred) values 0.55 and 0.57 of CoMFA and CoMSIA respectively. Docking, simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed models and Docking methods provide guidance to design molecules with enhanced activity. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Sakkiah, Sugunadevi; Thangapandian, Sundarapandian; John, Shalini; Lee, Keun Woo
2011-01-01
This study was performed to find the selective chemical features for Aurora kinase-B inhibitors using the potent methods like Hip-Hop, virtual screening, homology modeling, molecular dynamics and docking. The best hypothesis, Hypo1 was validated toward a wide range of test set containing the selective inhibitors of Aurora kinase-B. Homology modeling and molecular dynamics studies were carried out to perform the molecular docking studies. The best hypothesis Hypo1 was used as a 3D query to screen the chemical databases. The screened molecules from the databases were sorted based on ADME and drug like properties. The selective hit compounds were docked and the hydrogen bond interactions with the critical amino acids present in Aurora kinase-B were compared with the chemical features present in the Hypo1. Finally, we suggest that the chemical features present in the Hypo1 are vital for a molecule to inhibit the Aurora kinase-B activity.
Panda, Dulal; Kunwar, Ambarish
2016-01-01
Tubulin isotypes are found to play an important role in regulating microtubule dynamics. The isotype composition is also thought to contribute in the development of drug resistance as tubulin isotypes show differential binding affinities for various anti-cancer agents. Tubulin isotypes αβII, αβIII and αβIV show differential binding affinity for colchicine. However, the origin of differential binding affinity is not well understood at the molecular level. Here, we investigate the origin of differential binding affinity of a colchicine analogue N-deacetyl-N-(2-mercaptoacetyl)-colchicine (DAMA-colchicine) for human αβII, αβIII and αβIV isotypes, employing sequence analysis, homology modeling, molecular docking, molecular dynamics simulation and MM-GBSA binding free energy calculations. The sequence analysis study shows that the residue compositions are different in the colchicine binding pocket of αβII and αβIII, whereas no such difference is present in αβIV tubulin isotypes. Further, the molecular docking and molecular dynamics simulations results show that residue differences present at the colchicine binding pocket weaken the bonding interactions and the correct binding of DAMA-colchicine at the interface of αβII and αβIII tubulin isotypes. Post molecular dynamics simulation analysis suggests that these residue variations affect the structure and dynamics of αβII and αβIII tubulin isotypes, which in turn affect the binding of DAMA-colchicine. Further, the binding free-energy calculation shows that αβIV tubulin isotype has the highest binding free-energy and αβIII has the lowest binding free-energy for DAMA-colchicine. The order of binding free-energy for DAMA-colchicine is αβIV ≃ αβII >> αβIII. Thus, our computational approaches provide an insight into the effect of residue variations on differential binding of αβII, αβIII and αβIV tubulin isotypes with DAMA-colchicine and may help to design new analogues with higher binding affinities for tubulin isotypes. PMID:27227832
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.
Islam, Md Ataul; Pillay, Tahir S
2017-08-01
In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.
Ajloo, Davood; Mahmoodabadi, Najmeh; Ghadamgahi, Maryam; Saboury, Ali Akbar
2016-07-01
Effects of sodium (octyl, dodecyl, hexadecyl) sulfate and their cationic analogous on the structure of adenosine deaminase (ADA) were investigated by fluorescence and circular dichroism spectroscopy as well as molecular dynamics simulation and docking calculation. Root-mean-square derivations, radius of gyration, solvent accessible surface area, and radial distribution function were obtained. The results showed that anionic and cationic surfactants reduce protein stability. Cationic surfactants have more effect on the ADA structure in comparison with anionic surfactants. More concentration and longer surfactants are parallel to higher denaturation. Furthermore, aggregation in the presence of anionic surfactants is more than cationic surfactants. Docking data showed that longer surfactants have more interaction energy and smaller ones bound to the active site.
Mottin, Melina; Souza, Paulo C T; Skaf, Munir S
2015-07-02
The peroxisome proliferator-activated receptor γ (PPARγ) is an important transcription factor that plays a major role in the regulation of glucose and lipid metabolisms and has, therefore, many implications in modern-life metabolic disorders such as diabetes, obesity, and cardiovascular diseases. Phosphorylation of PPARγ by the cyclin-dependent kinase 5 (Cdk5) has been recently proved to promote obesity and loss of insulin sensitivity. The inhibition of this reaction is currently being pursued to develop PPARγ ligands for type 2 diabetes treatments. The knowledge of the protein-protein interactions between Cdk5/p25 and PPARγ can be an important asset for better understanding of the molecular basis of the Cdk5-meditated phosphorylation of PPARγ and its inhibition. By means of a computational approach that combines protein-protein docking and adaptive biasing force molecular dynamics simulations, we obtained PPARγ-Cdk5/p25 structural models that are consistent with the mechanism of the enzymatic reaction and with overall structural features of the full length PPARγ-RXRα heterodimer bound to DNA. In addition to the active site, our model shows that the interacting regions between the two proteins should involve two distal docking sites, comprising the PPARγ Ω-loop and Cdk5 N-terminal lobe and the PPARγ β-sheet and Cdk5 C-terminal lobe. These sites are related to PPARγ transactivation and directly interact with PPARγ ligands. Our results suggest that β-sheets and Ω-loop stabilization promoted by PPARγ agonists could be important to inhibit Cdk5-mediated phosphorylation.
Molecular Dynamic Studies of the Complex Polyethylenimine and Glucose Oxidase.
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.
Electrostatics in protein–protein docking
Heifetz, Alexander; Katchalski-Katzir, Ephraim; Eisenstein, Miriam
2002-01-01
A novel geometric-electrostatic docking algorithm is presented, which tests and quantifies the electrostatic complementarity of the molecular surfaces together with the shape complementarity. We represent each molecule to be docked as a grid of complex numbers, storing information regarding the shape of the molecule in the real part and information regarding the electrostatic character of the molecule in the imaginary part. The electrostatic descriptors are derived from the electrostatic potential of the molecule. Thus, the electrostatic character of the molecule is represented as patches of positive, neutral, or negative values. The potential for each molecule is calculated only once and stored as potential spheres adequate for exhaustive rotation/translation scans. The geometric-electrostatic docking algorithm is applied to 17 systems, starting form the structures of the unbound molecules. The results—in terms of the complementarity scores of the nearly correct solutions, their ranking in the lists of sorted solutions, and their statistical uniqueness—are compared with those of geometric docking, showing that the inclusion of electrostatic complementarity in docking is very important, in particular in docking of unbound structures. Based on our results, we formulate several "good electrostatic docking rules": The geometric-electrostatic docking procedure is more successful than geometric docking when the potential patches are large and when the potential extends away from the molecular surface and protrudes into the solvent. In contrast, geometric docking is recommended when the electrostatic potential around the molecules to be docked appears homogenous, that is, with a similar sign all around the molecule. PMID:11847280
Padariya, Monikaben; Kalathiya, Umesh
2016-10-01
Fat mass and obesity-associated (FTO) protein contributes to non-syndromic human obesity which refers to excessive fat accumulation in human body and results in health risk. FTO protein has become a promising target for anti-obesity medicines as there is an immense need for the rational design of potent inhibitors to treat obesity. In our study, a new scaffold N-phenyl-1H-indol-2-amine was selected as a base for FTO protein inhibitors by applying scaffold hopping approach. Using this novel scaffold, different derivatives were designed by extending scaffold structure with potential functional groups. Molecular docking simulations were carried out by using two different docking algorithm implemented in CDOCKER (flexible docking) and AutoDock programs (rigid docking). Analyzing results of rigid and flexible docking, compound MU06 was selected based on different properties and predicted binding affinities for further analysis. Molecular dynamics simulation of FTO/MU06 complex was performed to characterize structure rationale and binding stability. Certainly, Arg96 and His231 residue of FTO protein showed stable interaction with inhibitor MU06 throughout the production dynamics phase. Three residues of FTO protein (Arg96, Asp233, and His231) were found common in making H-bond interactions with MU06 during molecular dynamics simulation and CDOCKER docking. Copyright © 2016 Elsevier Ltd. All rights reserved.
Mo, Sui-Lin; Liu, Wei-Feng; Li, Chun-Guang; Zhou, Zhi-Wei; Luo, Hai-Bin; Chew, Helen; Liang, Jun; Zhou, Shu-Feng
2012-07-01
The highly polymorphic human cytochrome P450 2D6 (CYP2D6) metabolizes about 25% of currently used drugs. In this study, we have explored the interaction of a large number of substrates (n = 120) with wild-type and mutated CYP2D6 by molecular docking using the CDOCKER module. Before we conducted the molecular docking and virtual mutations, the pharmacophore and QSAR models of CYP2D6 substrates were developed and validated. Finally, we explored the interaction of a traditional Chinese herbal formula, Fangjifuling decoction, with CYP2D6 by virtual screening. The optimized pharmacophore model derived from 20 substrates of CYP2D6 contained two hydrophobic features and one hydrogen bond acceptor feature, giving a relevance ratio of 76% when a validation set of substrates were tested. However, our QSAR models gave poor prediction of the binding affinity of substrates. Our docking study demonstrated that 117 out of 120 substrates could be docked into the active site of CYP2D6. Forty one out of 117 substrates (35.04%) formed hydrogen bonds with various active site residues of CYP2D6 and 53 (45.30%) substrates formed a strong π-π interaction with Phe120 (53/54), with only carvedilol showing π-π interaction with Phe483. The active site residues involving hydrogen bond formation with substrates included Leu213, Lys214, Glu216, Ser217, Gln244, Asp301, Ser304, Ala305, Phe483, and Phe484. Furthermore, the CDOCKER algorithm was further applied to study the impact of mutations of 28 active site residues (mostly non-conserved) of CYP2D6 on substrate binding modes using five probe substrates including bufuralol, debrisoquine, dextromethorphan, sparteine, and tramadol. All mutations of the residues examined altered the hydrogen bond formation and/or aromatic interactions, depending on the probe used in molecular docking. Apparent changes of the binding modes have been observed with the Glu216Asp and Asp301Glu mutants. Overall, 60 compounds out of 130 from Fangjifuling decoction matched our pharmacophore model for CYP2D6 substrates. Fifty four out of these 60 compounds could be docked into the active site of CYP2D6 and 24 of 54 compounds formed hydrogen bonds with Glu216, Asp301, Ser304, and Ala305 in CYP2D6. These results have provided further insights into the factors that determining the binding modes of substrates to CYP2D6. Screening of high-affinity ligands for CYP2D6 from herbal formula using computational models is a useful approach to identify potential herb-drug interactions.
Development of an autonomous video rendezvous and docking system, phase 2
NASA Technical Reports Server (NTRS)
Tietz, J. C.; Richardson, T. E.
1983-01-01
The critical elements of an autonomous video rendezvous and docking system were built and used successfully in a physical laboratory simulation. The laboratory system demonstrated that a small, inexpensive electronic package and a flight computer of modest size can analyze television images to derive guidance information for spacecraft. In the ultimate application, the system would use a docking aid consisting of three flashing lights mounted on a passive target spacecraft. Television imagery of the docking aid would be processed aboard an active chase vehicle to derive relative positions and attitudes of the two spacecraft. The demonstration system used scale models of the target spacecraft with working docking aids. A television camera mounted on a 6 degree of freedom (DOF) simulator provided imagery of the target to simulate observations from the chase vehicle. A hardware video processor extracted statistics from the imagery, from which a computer quickly computed position and attitude. Computer software known as a Kalman filter derived velocity information from position measurements.
NASA Astrophysics Data System (ADS)
Siahaan, P.; Wuning, S.; Manna, A.; Prasasty, V. D.; Hudiyanti, D.
2018-04-01
Deeply understanding that intermolecular interaction between molecules on the paracellular pathway has given insight to its microscopic and macroscopic properties. In the paracellular pathway, synthetic cyclic ADTC1 (Ac-CADTPPVC-NH2) peptide has been studied to modulate EC1-EC2 domain, computationally using molecular docking method. The aim of this research is to probe the effect of amino acid alanine (A) of ADTC1 on its interaction properties. The study carried out in two steps: 1. the optimization using GROMACS v4.6.5 program and; 2. Determination of the interaction properties using AutoDock 4.2 program. The interaction was done for A-J box, and the best position of the binding site and binding energy on the OC and CC ADTC1 peptides against the EC1-EC2 domain of E-cadherin was selected. The result showed that the CC of the F box ADTC1 has the best interaction with binding energy of - 26.36 kJ/mol and its energy was lower than ADTC5 without alanine amino acid. ADTC1 interacted with EC1 of EC1-EC2 on Asp1, Trp2, Val3, Ile4, Ile24, Lys25, Ser26, Asn27, and Met92 residues.
Molecular interactions between general anesthetics and the 5HT2B receptor.
Matsunaga, Felipe; Gao, Lu; Huang, Xi-Ping; Saven, Jeffery G; Roth, Bryan L; Liu, Renyu
2015-01-01
Serotonin modulates many processes through a family of seven serotonin receptors. However, no studies have screened for interactions between general anesthetics currently in clinical use and serotonergic G-protein-coupled receptors (GPCRs). Given that both intravenous and inhalational anesthetics have been shown to target other classes of GPCRs, we hypothesized that general anesthetics might interact directly with some serotonin receptors and thus modify their function. Radioligand binding assays were performed to screen serotonin receptors for interactions with propofol and isoflurane as well as for affinity determinations. Docking calculations using the crystal structure of 5-HT2B were performed to computationally confirm the binding assay results and locate anesthetic binding sites. The 5-HT2B class of receptors interacted significantly with both propofol and isoflurane in the primary screen. The affinities for isoflurane and propofol were determined to be 7.78 and .95 μM, respectively, which were at or below the clinical concentrations for both anesthetics. The estimated free energy derived from docking calculations for propofol (-6.70 kcal/mol) and isoflurane (-5.10 kcal/mol) correlated with affinities from the binding assay. The anesthetics were predicted to dock at a pharmacologically relevant binding site of 5HT2B. The molecular interactions between propofol and isoflurane with the 5-HT2B class of receptors were discovered and characterized. This finding implicates the serotonergic GPCRs as potential anesthetic targets.
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.
Dynamic Docking Test System (DDTS) active table computer program NASA Advanced Docking System (NADS)
NASA Technical Reports Server (NTRS)
Gates, R. M.; Jantz, R. E.
1974-01-01
A computer program was developed to describe the three-dimensional motion of the Dynamic Docking Test System active table. The input consists of inertia and geometry data, actuator structural data, forcing function data, hydraulics data, servo electronics data, and integration control data. The output consists of table responses, actuator bending responses, and actuator responses.
A molecular docking study of phytochemical estrogen mimics from dietary herbal supplements.
Powers, Chelsea N; Setzer, William N
2015-01-01
The purpose of this study is to use a molecular docking approach to identify potential estrogen mimics or anti-estrogens in phytochemicals found in popular dietary herbal supplements. In this study, 568 phytochemicals found in 17 of the most popular herbal supplements sold in the United States were built and docked with two isoforms of the estrogen receptor, ERα and ERβ (a total of 27 different protein crystal structures). The docking results revealed six strongly docking compounds in Echinacea, three from milk thistle (Silybum marianum), three from Gingko biloba, one from Sambucus nigra, none from maca (Lepidium meyenii), five from chaste tree (Vitex agnus-castus), two from fenugreek (Trigonella foenum-graecum), and two from Rhodiola rosea. Notably, of the most popular herbal supplements for women, there were numerous compounds that docked strongly with the estrogen receptor: Licorice (Glycyrrhiza glabra) had a total of 26 compounds strongly docking to the estrogen receptor, 15 with wild yam (Dioscorea villosa), 11 from black cohosh (Actaea racemosa), eight from muira puama (Ptychopetalum olacoides or P. uncinatum), eight from red clover (Trifolium pratense), three from damiana (Turnera aphrodisiaca or T. diffusa), and three from dong quai (Angelica sinensis). Of possible concern were the compounds from men's herbal supplements that exhibited strong docking to the estrogen receptor: Gingko biloba had three compounds, gotu kola (Centella asiatica) had two, muira puama (Ptychopetalum olacoides or P. uncinatum) had eight, and Tribulus terrestris had six compounds. This molecular docking study has revealed that almost all popular herbal supplements contain phytochemical components that may bind to the human estrogen receptor and exhibit selective estrogen receptor modulation. As such, these herbal supplements may cause unwanted side effects related to estrogenic activity.
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.
NASA Astrophysics Data System (ADS)
Fayaz, S. M.; Rajanikant, G. K.
2014-07-01
Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.
Thermodynamic perspective on the dock-lock growth mechanism of amyloid fibrils.
O'Brien, Edward P; Okamoto, Yuko; Straub, John E; Brooks, Bernard R; Thirumalai, D
2009-10-29
The mechanism of addition of a soluble unstructured monomer to a preformed ordered amyloid fibril is a complex process. On the basis of the kinetics of monomer disassociation of Abeta(1-40) from the amyloid fibril, it has been suggested that deposition is a multistep process involving a rapid reversible association of the unstructured monomer to the fibril surface (docking) followed by a slower conformational rearrangement leading to the incorporation onto the underlying fibril lattice (locking). By exploiting the vast time scale separation between the dock and lock processes and using molecular dynamics simulation of deposition of the disordered peptide fragment (35)MVGGVV(40) from the Abeta peptide onto the fibril with known crystal structure, we provide a thermodynamic basis for the dock-lock mechanism of fibril growth. Free energy profiles, computed using implicit solvent model and enhanced sampling methods with the distance (delta(C)) between the center of mass of the peptide and the fibril surface as the order parameter, show three distinct basins of attraction. When delta(C) is large, the monomer is compact and unstructured and the favorable interactions with the fibril results in stretching of the peptide at delta(C) approximately 13 A. As delta(C) is further decreased, the peptide docks onto the fibril surface with a structure that is determined by a balance between intrapeptide and peptide fibril interactions. At delta(C) approximately 4 A, a value that is commensurate with the spacing between beta-strands in the fibril, the monomer expands and locks onto the fibril. Using simulations with implicit solvent model and all atom molecular dynamics in explicit water, we show that the locked monomer, which interacts with the underlying fibril, undergoes substantial conformational fluctuations and is not stable. The cosolutes urea and TMAO destabilize the unbound phase and stabilize the docked phase. Interestingly, small crowding particles enhance the stability of the fibril-bound monomer only marginally. We predict that the experimentally measurable critical monomer concentration, C(R), at which the soluble unbound monomer is in equilibrium with the ordered fibril, increases sharply as temperature is increased under all solution conditions.
Tertiary structure-based analysis of microRNA–target interactions
Gan, Hin Hark; Gunsalus, Kristin C.
2013-01-01
Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods. PMID:23417009
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.
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.
Ahmed, Danish; Kumar, Vikas; Sharma, Manju; Verma, Amita
2014-05-13
Albizzia Lebbeck Benth. is traditionally important plant and is reported to possess a variety of pharmacological actions. The present research exertion was undertaken to isolate and characterized the flavonoids from the extract of stem bark of Albizzia Lebbeck Benth. and to evaluate the efficacy of the isolated flavonoids on in-vitro models of type-II diabetes. Furthermore, the results of in-vitro experimentation inveterate by the molecular docking studies of the isolated flavonoids on α-glucosidase and α-amylase enzymes. Isolation of the flavonoids from the methanolic extract of stem bark of A. Lebbeck Benth was executed by the Silica gel (Si) column chromatography to yield different fractions. These fractions were then subjected to purification to obtain three important flavonoids. The isolated flavonoids were then structurally elucidated with the assist of 1H-NMR, 13C-NMR, and Mass spectroscopy. In-vitro experimentation was performed with evaluation of α-glucosidase, α-amylase and DPPH inhibition capacity. Molecular docking study was performed with GLIDE docking software. Three flavonoids, (1) 5-deoxyflavone (geraldone), (2) luteolin and (3) Isookanin were isolated from the EtOAc fraction of the methanolic extract of Albizzia lebbeck Benth bark. (ALD). All the compounds revealed to inhibit the α-glucosidase and α-amylase enzymes in in-vitro investigation correlating to reduce the plasma glucose level. Molecular docking study radically corroborates the binding affinity and inhibition of α-glucosidase and α-amylase enzymes. The present research exertion demonstrates the anti-diabetic and antioxidant activity of the important isolated flavonoids with inhibition of α-glucosidase, α-amylase and DPPH which is further supported by molecular docking analysis.
2014-01-01
Background Albizzia Lebbeck Benth. is traditionally important plant and is reported to possess a variety of pharmacological actions. The present research exertion was undertaken to isolate and characterized the flavonoids from the extract of stem bark of Albizzia Lebbeck Benth. and to evaluate the efficacy of the isolated flavonoids on in-vitro models of type-II diabetes. Furthermore, the results of in-vitro experimentation inveterate by the molecular docking studies of the isolated flavonoids on α-glucosidase and α-amylase enzymes. Methods Isolation of the flavonoids from the methanolic extract of stem bark of A. Lebbeck Benth was executed by the Silica gel (Si) column chromatography to yield different fractions. These fractions were then subjected to purification to obtain three important flavonoids. The isolated flavonoids were then structurally elucidated with the assist of 1H-NMR, 13C-NMR, and Mass spectroscopy. In-vitro experimentation was performed with evaluation of α-glucosidase, α-amylase and DPPH inhibition capacity. Molecular docking study was performed with GLIDE docking software. Results Three flavonoids, (1) 5-deoxyflavone (geraldone), (2) luteolin and (3) Isookanin were isolated from the EtOAc fraction of the methanolic extract of Albizzia lebbeck Benth bark. (ALD). All the compounds revealed to inhibit the α-glucosidase and α-amylase enzymes in in-vitro investigation correlating to reduce the plasma glucose level. Molecular docking study radically corroborates the binding affinity and inhibition of α-glucosidase and α-amylase enzymes. Conclusion The present research exertion demonstrates the anti-diabetic and antioxidant activity of the important isolated flavonoids with inhibition of α-glucosidase, α-amylase and DPPH which is further supported by molecular docking analysis. PMID:24886138
NASA Astrophysics Data System (ADS)
Li, Peizhen; Tian, Yueli; Zhai, Honglin; Deng, Fangfang; Xie, Meihong; Zhang, Xiaoyun
2013-11-01
Non-purine derivatives have been shown to be promising novel drug candidates as xanthine oxidase inhibitors. Based on three-dimensional quantitative structure-activity relationship (3D-QSAR) methods including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), two 3D-QSAR models for a series of non-purine xanthine oxidase (XO) inhibitors were established, and their reliability was supported by statistical parameters. Combined 3D-QSAR modeling and the results of molecular docking between non-purine xanthine oxidase inhibitors and XO, the main factors that influenced activity of inhibitors were investigated, and the obtained results could explain known experimental facts. Furthermore, several new potential inhibitors with higher activity predicted were designed, which based on our analyses, and were supported by the simulation of molecular docking. This study provided some useful information for the development of non-purine xanthine oxidase inhibitors with novel structures.
Wright, Bernice; Watson, Kimberly A; McGuffin, Liam J; Lovegrove, Julie A; Gibbins, Jonathan M
2015-11-01
Flavonoids reduce cardiovascular disease risk through anti-inflammatory, anti-coagulant and anti-platelet actions. One key flavonoid inhibitory mechanism is blocking kinase activity that drives these processes. Flavonoids attenuate activities of kinases including phosphoinositide-3-kinase, Fyn, Lyn, Src, Syk, PKC, PIM1/2, ERK, JNK and PKA. X-ray crystallographic analyses of kinase-flavonoid complexes show that flavonoid ring systems and their hydroxyl substitutions are important structural features for their binding to kinases. A clearer understanding of structural interactions of flavonoids with kinases is necessary to allow construction of more potent and selective counterparts. We examined flavonoid (quercetin, apigenin and catechin) interactions with Src family kinases (Lyn, Fyn and Hck) applying the Sybyl docking algorithm and GRID. A homology model (Lyn) was used in our analyses to demonstrate that high-quality predicted kinase structures are suitable for flavonoid computational studies. Our docking results revealed potential hydrogen bond contacts between flavonoid hydroxyls and kinase catalytic site residues. Identification of plausible contacts indicated that quercetin formed the most energetically stable interactions, apigenin lacked hydroxyl groups necessary for important contacts and the non-planar structure of catechin could not support predicted hydrogen bonding patterns. GRID analysis using a hydroxyl functional group supported docking results. Based on these findings, we predicted that quercetin would inhibit activities of Src family kinases with greater potency than apigenin and catechin. We validated this prediction using in vitro kinase assays. We conclude that our study can be used as a basis to construct virtual flavonoid interaction libraries to guide drug discovery using these compounds as molecular templates. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
In Silico Design of Smart Binders to Anthrax PA
2012-09-01
nanosecond(ns) molecular dynamics simulation in the NPT ensemble (constant particle number, pressure, and temperature) at 300K, with the CHARMM force...protective antigen (PA). Before the docking runs, the DS23 peptide was simulated using molecular dynamics to generate an ensemble of structures...structure), we do not see a large amount of structural change when using molecular dynamics after Rosetta docking. We note that this RMSD does not take
Balakrishnan, C; Subha, L; Neelakantan, M A; Mariappan, S S
2015-11-05
A propargyl arms containing Schiff base (L) was synthesized by the condensation of 1-[2-hydroxy-4-(prop-2-yn-1-yloxy)phenyl]ethanone with trans-1,2-diaminocyclohexane. The structure of L was characterized by IR, (1)H NMR, (13)C NMR and UV-Vis spectroscopy and by single crystal X-ray diffraction analysis. The UV-Visible spectral behavior of L in different solvents exhibits positive solvatochromism. Density functional calculation of the L in gas phase was performed by using DFT (B3LYP) method with 6-31G basis set. The computed vibrational frequencies and NMR signals of L were compared with the experimental data. Tautomeric stability study inferred that the enolimine is more stable than the ketoamine form. The charge delocalization has been analyzed using natural bond orbital (NBO) analysis. Electronic absorption and emission spectral studies were used to study the binding of L with CT-DNA. The molecular docking was done to identify the interaction of L with A-DNA and B-DNA. Copyright © 2015 Elsevier B.V. All rights reserved.
Manoharan, Prabu; Sridhar, J
2018-05-01
The organophosphorus hydrolase enzyme is involved in the catalyzing reaction that involve hydrolysis of organophosphate toxic compounds. An enzyme from Deinococcus radiodurans reported as homologous to phosphotriesterase and show activity against organophosphate. In the past activity of this enzyme is low and efforts made to improve the activity by experimental mutation study. However only very few organophosphates tested against very few catalytic site mutations. In order to improve the catalytic power of the organophosphorus hydrolase enzyme, we carried out systematic functional hotspot based protein engineering strategy. The mutants tested against 46 know organophosphate compounds using molecular docking study. Finally, we carried out an extensive molecular docking study to predict the binding of 46 organophosphate compounds to wild-type protein and mutant organophosphorus hydrolase enzyme. At the end we are able to improve the degrading potential of organophosphorus hydrolase enzyme against organophosphate toxic compounds. This preliminary study and the outcome would be useful guide for the experimental scientist involved in the bioremediation of toxic organophosphate compounds. Copyright © 2018 Elsevier Inc. All rights reserved.
Kwong, Huey Chong; Chidan Kumar, C S; Mah, Siau Hui; Chia, Tze Shyang; Quah, Ching Kheng; Loh, Zi Han; Chandraju, Siddegowda; Lim, Gin Keat
2017-01-01
Biphenyl-based compounds are clinically important for the treatments of hypertension and inflammatory, while many more are under development for pharmaceutical uses. In the present study, a series of 2-([1,1'-biphenyl]-4-yl)-2-oxoethyl benzoates, 2(a-q), and 2-([1,1'-biphenyl]-4-yl)-2-oxoethyl pyridinecarboxylate, 2(r-s) were synthesized by reacting 1-([1,1'-biphenyl]-4-yl)-2-bromoethan-1-one with various carboxylic acids using potassium carbonate in dimethylformamide at ambient temperature. Single-crystal X-ray diffraction studies revealed a more closely packed crystal structure can be produced by introduction of biphenyl moiety. Five of the compounds among the reported series exhibited significant anti-tyrosinase activities, in which 2p, 2r and 2s displayed good inhibitions which are comparable to standard inhibitor kojic acid at concentrations of 100 and 250 μg/mL. The inhibitory effects of these active compounds were further confirmed by computational molecular docking studies and the results revealed the primary binding site is active-site entrance instead of inner copper binding site which acted as the secondary binding site.
Ramalho, Teodorico C; de Castro, Alexandre A; Silva, Daniela R; Silva, Maria Cristina; Franca, Tanos C C; Bennion, Brian J; Kuca, Kamil
2016-01-01
The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.
Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis
Gherib, Rami; Dokainish, Hisham M.; Gauld, James W.
2014-01-01
Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. PMID:24384841
NASA Astrophysics Data System (ADS)
Serçinoğlu, Onur; Özcan, Gülin; Kabaş, Zeynep Kutlu; Ozbek, Pemra
2016-07-01
A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.
Serçinoğlu, Onur; Özcan, Gülin; Kabaş, Zeynep Kutlu; Ozbek, Pemra
2016-07-01
A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.
NASA Astrophysics Data System (ADS)
Thakur, Amitha; Kumar, Dinesh; Thipparaboina, Rajesh; Shastri, Nalini R.
2014-11-01
Control of crystal morphology during crystallization is a paramount challenge in pharmaceutical processing. Hence, there is need to introduce computational methods for morphology prediction to manage production cost of drugs and improve related pharmaceutical and biopharmaceutical properties. Layer docking approach with molecular dynamics opens a new avenue for crystal habit prediction in presence of solvent. In the present study, attempts were made to correlate predicted and experimental crystal habits of fluconazole considering solvent interactions using layer docking approach. Simulated results from layer docking approach with methanol as solvent gave two dominant facets (0 1 1) and (1 0 1) with a surface area 22.43% and 19.82% respectively, which were in agreement with the experimental results. Experimentally grown modified crystal habit of fluconazole in methanol showed enhanced dissolution rate (p<0.05) when compared to plain drug. This was attributed to the increased surface area on the specified facets caused by interactions with the solvent. Furthermore, Differential Scanning Calorimetry, Fourier Transform Infrared (FTIR) Spectroscopy and powder X-ray Diffraction of recrystallized samples confirmed only a habit change and absence of any polymorphs, hydrates or solvates. Flow and compressibility of fluconazole recrystallized in methanol was significantly improved when compared to plain drug. This study demonstrates a methodical approach using computational tools for prediction and modification of crystal habit, to enhance dissolution of poorly soluble drugs, for future pharmaceutical applications.
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.
Gayathri, N K; Aparna, V; Maya, S; Biswas, Raja; Jayakumar, R; Mohan, C Gopi
2017-12-01
We present a computational investigation of binding affinity of different types of drugs with chitin nanocarriers. Understanding the chitn polymer-drug interaction is important to design and optimize the chitin based drug delivery systems. The binding affinity of three different types of anti-bacterial drugs Ethionamide (ETA) Methacycline (MET) and Rifampicin (RIF) with amorphous chitin nanoparticles (AC-NPs) were studied by integrating computational and experimental techniques. The binding energies (BE) of hydrophobic ETA, hydrophilic MET and hydrophobic RIF were -7.3kcal/mol, -5.1kcal/mol and -8.1kcal/mol respectively, with respect to AC-NPs, using molecular docking studies. This theoretical result was in good correlation with the experimental studies of AC-drug loading and drug entrapment efficiencies of MET (3.5±0.1 and 25± 2%), ETA (5.6±0.02 and 45±4%) and RIF (8.9±0.20 and 53±5%) drugs respectively. Stability studies of the drug encapsulated nanoparticles showed stable values of size, zeta and polydispersity index at 6°C temperature. The correlation between computational BE and experimental drug entrapment efficiencies of RIF, ETA and MET drugs with four AC-NPs strands were 0.999 respectively, while that of the drug loading efficiencies were 0.854 respectively. Further, the molecular docking results predict the atomic level details derived from the electrostatic, hydrogen bonding and hydrophobic interactions of the drug and nanoparticle for its encapsulation and loading in the chitin-based host-guest nanosystems. The present results thus revealed the drug loading and drug delivery insights and has the potential of reducing the time and cost of processing new antibiotic drug delivery nanosystem optimization, development and discovery. Copyright © 2017 Elsevier Ltd. All rights reserved.
Computational screening and molecular dynamics simulation of disease associated nsSNPs in CENP-E.
Kumar, Ambuj; Purohit, Rituraj
2012-01-01
Aneuploidy and chromosomal instability (CIN) are hallmarks of most solid tumors. Mutations in centroemere proteins have been observed in promoting aneuploidy and tumorigenesis. Recent studies reported that Centromere-associated protein-E (CENP-E) is involved in inducing cancers. In this study we investigated the pathogenic effect of 132 nsSNPs reported in CENP-E using computational platform. Y63H point mutation found to be associated with cancer using SIFT, Polyphen, PhD-SNP, MutPred, CanPredict and Dr. Cancer tools. Further we investigated the binding affinity of ATP molecule to the CENP-E motor domain. Complementarity scores obtained from docking studies showed significant loss in ATP binding affinity of mutant structure. Molecular dynamics simulation was carried to examine the structural consequences of Y63H mutation. Root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (R(g)), solvent accessibility surface area (SASA), energy value, hydrogen bond (NH Bond), eigenvector projection, trace of covariance matrix and atom density analysis results showed notable loss in stability for mutant structure. Y63H mutation was also shown to disrupt the native conformation of ATP binding region in CENP-E motor domain. Docking studies for remaining 18 mutations at 63rd residue position as well as other two computationally predicted disease associated mutations S22L and P69S were also carried to investigate their affect on ATP binding affinity of CENP-E motor domain. Our study provided a promising computational methodology to study the tumorigenic consequences of nsSNPs that have not been characterized and clear clue to the wet lab scientist. Copyright © 2012 Elsevier B.V. All rights reserved.
GPU acceleration of Dock6's Amber scoring computation.
Yang, Hailong; Zhou, Qiongqiong; Li, Bo; Wang, Yongjian; Luan, Zhongzhi; Qian, Depei; Li, Hanlu
2010-01-01
Dressing the problem of virtual screening is a long-term goal in the drug discovery field, which if properly solved, can significantly shorten new drugs' R&D cycle. The scoring functionality that evaluates the fitness of the docking result is one of the major challenges in virtual screening. In general, scoring functionality in docking requires a large amount of floating-point calculations, which usually takes several weeks or even months to be finished. This time-consuming procedure is unacceptable, especially when highly fatal and infectious virus arises such as SARS and H1N1, which forces the scoring task to be done in a limited time. This paper presents how to leverage the computational power of GPU to accelerate Dock6's (http://dock.compbio.ucsf.edu/DOCK_6/) Amber (J. Comput. Chem. 25: 1157-1174, 2004) scoring with NVIDIA CUDA (NVIDIA Corporation Technical Staff, Compute Unified Device Architecture - Programming Guide, NVIDIA Corporation, 2008) (Compute Unified Device Architecture) platform. We also discuss many factors that will greatly influence the performance after porting the Amber scoring to GPU, including thread management, data transfer, and divergence hidden. Our experiments show that the GPU-accelerated Amber scoring achieves a 6.5× speedup with respect to the original version running on AMD dual-core CPU for the same problem size. This acceleration makes the Amber scoring more competitive and efficient for large-scale virtual screening problems.
Anesthetic Binding in a Pentameric Ligand-Gated Ion Channel: GLIC
Chen, Qiang; Cheng, Mary Hongying; Xu, Yan; Tang, Pei
2010-01-01
Cys-loop receptors are molecular targets of general anesthetics, but the knowledge of anesthetic binding to these proteins remains limited. Here we investigate anesthetic binding to the bacterial Gloeobacter violaceus pentameric ligand-gated ion channel (GLIC), a structural homolog of cys-loop receptors, using an experimental and computational hybrid approach. Tryptophan fluorescence quenching experiments showed halothane and thiopental binding at three tryptophan-associated sites in the extracellular (EC) domain, transmembrane (TM) domain, and EC-TM interface of GLIC. An additional binding site at the EC-TM interface was predicted by docking analysis and validated by quenching experiments on the N200W GLIC mutant. The binding affinities (KD) of 2.3 ± 0.1 mM and 0.10 ± 0.01 mM were derived from the fluorescence quenching data of halothane and thiopental, respectively. Docking these anesthetics to the original GLIC crystal structure and the structures relaxed by molecular dynamics simulations revealed intrasubunit sites for most halothane binding and intersubunit sites for thiopental binding. Tryptophans were within reach of both intra- and intersubunit binding sites. Multiple molecular dynamics simulations on GLIC in the presence of halothane at different sites suggested that anesthetic binding at the EC-TM interface disrupted the critical interactions for channel gating, altered motion of the TM23 linker, and destabilized the open-channel conformation that can lead to inhibition of GLIC channel current. The study has not only provided insights into anesthetic binding in GLIC, but also demonstrated a successful fusion of experiments and computations for understanding anesthetic actions in complex proteins. PMID:20858424
Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering.
Pottel, Joshua; Moitessier, Nicolas
2015-12-28
Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.
Zhou, Yuchen; McGillick, Brian E.; Teng, Yu-Han Gary; ...
2016-07-18
Botulinum neurotoxins (BoNT) are among the most poisonous substances known, and of the 7 serotypes (A–G) identified thus far at least 4 can cause death in humans. Here, the goal of this work was identification of inhibitors that specifically target the light chain catalytic site of the highly pathogenic but lesser-studied E serotype (BoNT/E). Large-scale computational screening, employing the program DOCK, was used to perform atomic-level docking of 1.4 million small molecules to prioritize those making favorable interactions with the BoNT/E site. In particular, ‘footprint similarity’ (FPS) scoring was used to identify compounds that could potentially mimic features on themore » known substrate tetrapeptide RIME. Among 92 compounds purchased and experimentally tested, compound C562-1101 emerged as the most promising hit with an apparent IC 50 value three-fold more potent than that of the first reported BoNT/E small molecule inhibitor NSC-77053. Additional analysis showed the predicted binding pose of C562-1101 was geometrically and energetically stable over an ensemble of structures generated by molecular dynamic simulations and that many of the intended interactions seen with RIME were maintained. Finally, several analogs were also computationally designed and predicted to have further molecular mimicry thereby demonstrating the potential utility of footprint-based scoring protocols to help guide hit refinement.« less
Mehta, Pakhuri; Srivastava, Shubham; Choudhary, Bhanwar Singh; Sharma, Manish; Malik, Ruchi
2017-12-01
Multidrug resistance along with side-effects of available anti-epileptic drugs and unavailability of potent and effective agents in submicromolar quantities presents the biggest therapeutic challenges in anti-epileptic drug discovery. The molecular modeling techniques allow us to identify agents with novel structures to match the continuous urge for its discovery. KCNQ2 channel represents one of the validated targets for its therapy. The present study involves identification of newer anti-epileptic agents by means of a computer-aided drug design adaptive protocol involving both structure-based virtual screening of Asinex library using homology model of KCNQ2 and 3D-QSAR based virtual screening with docking analysis, followed by dG bind and ligand efficiency calculations with ADMET studies, of which 20 hits qualified all the criterions. The best ligands of both screenings with least potential for toxicity predicted computationally were then taken for molecular dynamic simulations. All the crucial amino acid interactions were observed in hits of both screenings such as Glu130, Arg207, Arg210 and Phe137. Robustness of docking protocol was analyzed through Receiver operating characteristic (ROC) curve values 0.88 (Area under curve AUC = 0.87) in Standard Precision and 0.84 (AUC = 0.82) in Extra Precision modes. Novelty analysis indicates that these compounds have not been reported previously as anti-epileptic agents.
Zhou, Yuchen; McGillick, Brian E; Teng, Yu-Han Gary; Haranahalli, Krupanandan; Ojima, Iwao; Swaminathan, Subramanyam; Rizzo, Robert C
2016-10-15
Botulinum neurotoxins (BoNT) are among the most poisonous substances known, and of the 7 serotypes (A-G) identified thus far at least 4 can cause death in humans. The goal of this work was identification of inhibitors that specifically target the light chain catalytic site of the highly pathogenic but lesser-studied E serotype (BoNT/E). Large-scale computational screening, employing the program DOCK, was used to perform atomic-level docking of 1.4 million small molecules to prioritize those making favorable interactions with the BoNT/E site. In particular, 'footprint similarity' (FPS) scoring was used to identify compounds that could potentially mimic features on the known substrate tetrapeptide RIME. Among 92 compounds purchased and experimentally tested, compound C562-1101 emerged as the most promising hit with an apparent IC 50 value three-fold more potent than that of the first reported BoNT/E small molecule inhibitor NSC-77053. Additional analysis showed the predicted binding pose of C562-1101 was geometrically and energetically stable over an ensemble of structures generated by molecular dynamic simulations and that many of the intended interactions seen with RIME were maintained. Several analogs were also computationally designed and predicted to have further molecular mimicry thereby demonstrating the potential utility of footprint-based scoring protocols to help guide hit refinement. Copyright © 2016 Elsevier Ltd. All rights reserved.
Computational Study on Substrate Specificity of a Novel Cysteine Protease 1 Precursor from Zea mays
Liu, Huimin; Chen, Liangcheng; Li, Quan; Zheng, Mingzhu; Liu, Jingsheng
2014-01-01
Cysteine protease 1 precursor from Zea mays (zmCP1) is classified as a member of the C1A family of peptidases (papain-like cysteine protease) in MEROPS (the Peptidase Database). The 3D structure and substrate specificity of the zmCP1 is still unknown. This study is the first one to build the 3D structure of zmCP1 by computer-assisted homology modeling. In order to determine the substrate specificity of zmCP1, docking study is used for rapid and convenient analysis of large populations of ligand–enzyme complexes. Docking results show that zmCP1 has preference for P1 position and P2 position for Arg and a large hydrophobic residue (such as Phe). Gly147, Gly191, Cys189, and Asp190 are predicted to function as active residues at the S1 subsite, and the S2 subsite contains Leu283, Leu193, Ala259, Met194, and Ala286. SIFt results indicate that Gly144, Arg268, Trp308, and Ser311 play important roles in substrate binding. Then Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) method was used to explain the substrate specificity for P1 position of zmCp1. This study provides insights into the molecular basis of zmCP1 activity and substrate specificity. PMID:24921705
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhou, Yuchen; McGillick, Brian E.; Teng, Yu-Han Gary
Botulinum neurotoxins (BoNT) are among the most poisonous substances known, and of the 7 serotypes (A–G) identified thus far at least 4 can cause death in humans. Here, the goal of this work was identification of inhibitors that specifically target the light chain catalytic site of the highly pathogenic but lesser-studied E serotype (BoNT/E). Large-scale computational screening, employing the program DOCK, was used to perform atomic-level docking of 1.4 million small molecules to prioritize those making favorable interactions with the BoNT/E site. In particular, ‘footprint similarity’ (FPS) scoring was used to identify compounds that could potentially mimic features on themore » known substrate tetrapeptide RIME. Among 92 compounds purchased and experimentally tested, compound C562-1101 emerged as the most promising hit with an apparent IC 50 value three-fold more potent than that of the first reported BoNT/E small molecule inhibitor NSC-77053. Additional analysis showed the predicted binding pose of C562-1101 was geometrically and energetically stable over an ensemble of structures generated by molecular dynamic simulations and that many of the intended interactions seen with RIME were maintained. Finally, several analogs were also computationally designed and predicted to have further molecular mimicry thereby demonstrating the potential utility of footprint-based scoring protocols to help guide hit refinement.« less
NASA Astrophysics Data System (ADS)
Hurley, Margaret M.; Sellers, Michael S.
2013-05-01
As software and methodology develop, key aspects of molecular interactions such as detailed energetics and flexibility are continuously better represented in docking simulations. In the latest iteration of the XPairIt API and Docking Protocol, we perform a blind dock of a peptide into the cleavage site of the Anthrax lethal factor (LF) metalloprotein. Molecular structures are prepared from RCSB:1JKY and we demonstrate a reasonably accurate docked peptide through analysis of protein motion and, using NCI Plot, visualize and characterize the forces leading to binding. We compare our docked structure to the 1JKY crystal structure and the more recent 1PWV structure, and discuss both captured and overlooked interactions. Our results offer a more detailed look at secondary contact and show that both van der Waals and electrostatic interactions from peptide residues further from the enzyme's catalytic site are significant.
Multiple ligand simultaneous docking: orchestrated dancing of ligands in binding sites of protein.
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.
Molecular design of new aggrecanases-2 inhibitors.
Shan, Zhi Jie; Zhai, Hong Lin; Huang, Xiao Yan; Li, Li Na; Zhang, Xiao Yun
2013-10-01
Aggrecanases-2 is a very important potential drug target for the treatment of osteoarthritis. In this study, a series of known aggrecanases-2 inhibitors was analyzed by the technologies of three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking. Two 3D-QSAR models, which based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods, were established. Molecular docking was employed to explore the details of the interaction between inhibitors and aggrecanases-2 protein. According to the analyses for these models, several new potential inhibitors with higher activity predicted were designed, and were supported by the simulation of molecular docking. This work propose the fast and effective approach to design and prediction for new potential inhibitors, and the study of the interaction mechanism provide a better understanding for the inhibitors binding into the target protein, which will be useful for the structure-based drug design and modifications. Copyright © 2013 Elsevier Ltd. All rights reserved.
Chen, Derek E; Willick, Darryl L; Ruckel, Joseph B; Floriano, Wely B
2015-01-01
Directed evolution is a technique that enables the identification of mutants of a particular protein that carry a desired property by successive rounds of random mutagenesis, screening, and selection. This technique has many applications, including the development of G protein-coupled receptor-based biosensors and designer drugs for personalized medicine. Although effective, directed evolution is not without challenges and can greatly benefit from the development of computational techniques to predict the functional outcome of single-point amino acid substitutions. In this article, we describe a molecular dynamics-based approach to predict the effects of single amino acid substitutions on agonist binding (salicin) to a human bitter taste receptor (hT2R16). An experimentally determined functional map of single-point amino acid substitutions was used to validate the whole-protein molecular dynamics-based predictive functions. Molecular docking was used to construct a wild-type agonist-receptor complex, providing a starting structure for single-point substitution simulations. The effects of each single amino acid substitution in the functional response of the receptor to its agonist were estimated using three binding energy schemes with increasing inclusion of solvation effects. We show that molecular docking combined with molecular mechanics simulations of single-point mutants of the agonist-receptor complex accurately predicts the functional outcome of single amino acid substitutions in a human bitter taste receptor.
Khan, Mohammad Firoz; Nahar, Nusrat; Rashid, Ridwan Bin; Chowdhury, Akhtaruzzaman; Rashid, Mohammad A
2018-02-02
Betulinic acid (BA) is a natural triterpenoid compound and exhibits a wide range of biological and medicinal properties including anti-inflammatory activity. Therefore, this theoretical investigation is performed to evaluate (a) physicochemical properties such as acid dissociation constant (pKa), distribution coefficient (logD), partition coefficient (logP), aqueous solubility (logS), solvation free energy, dipole moment, polarizability, hyperpolarizability and different reactivity descriptors, (b) pharmacokinetic properties like human intestinal absorption (HIA), cellular permeability, skin permeability (P Skin ), plasma protein binding (PPB), penetration of the blood brain barrier (BBB), (c) toxicological properties including mutagenicity, carcinogenicity, risk of inhibition of hERG gene and (d) molecular mechanism of anti-inflammatory action which will aid the development of analytical method and the synthesis of BA derivatives. The physicochemical properties were calculated using MarvinSketch 15.6.29 and Gaussian 09 software package. The pharmacokinetic and toxicological properties were calculated on online server PreADMET. Further, the molecular docking study was conducted on AutoDock vina in PyRx 0.8. The aqueous solubility increased with increasing pH due to the ionization of BA leading to decrease in distribution coefficient. The solvation energies in water, dimethyl sulfoxide (DMSO), acetonitrile, n-octanol, chloroform and carbon tetrachloride were - 41.74 kJ/mol, - 53.80 kJ/mol, - 66.27 kJ/mol, - 69.64 kJ/mol, - 65.96 kJ/mol and - 60.13 kJ/mol, respectively. From the results of polarizability and softness, it was clear that BA is less stable and hence, kinetically more reactive in water. BA demonstrated good human intestinal absorption (HIA) and moderate cellular permeability. Further, BA also exhibited positive CNS activity due to high permeability through BBB. The toxicological study revealed that BA was a mutagenic compound but noncarcinogenic in mice model. Moreover, molecular docking study of BA with PLA2 revealed that BA interacts with GLY22 & GLY29 through hydrogen bond formation and LEU2, PHE5, HIS6, ALA17, ALA18, HIS47 and TYR51 through different types of hydrophobic interactions. The binding affinity of BA was - 41.00 kJ/mol which is comparable to the binding affinity of potent inhibitor 6-Phenyl-4(R)-(7-Phenyl-heptanoylamino)-hexanoic acid (BR4) (- 33.89 kJ/mol). Our computed properties may assist the development of analytical method to assay BA or to develop BA derivatives with better pharmacokinetic and toxicological profile.
Paiz-Candia, Bertin; Islas, Angel A; Sánchez-Solano, Alfredo; Mancilla-Simbro, Claudia; Scior, Thomas; Millan-PerezPeña, Lourdes; Salinas-Stefanon, Eduardo M
2017-02-05
Mefloquine constitutes a multitarget antimalaric that inhibits cation currents. However, the effect and the binding site of this compound on Na + channels is unknown. To address the mechanism of action of mefloquine, we employed two-electrode voltage clamp recordings on Xenopus laevis oocytes, site-directed mutagenesis of the rat Na + channel, and a combined in silico approach using Molecular Dynamics and docking protocols. We found that mefloquine: i) inhibited Na v 1.4 currents (IC 50 =60μM), ii) significantly delayed fast inactivation but did not affect recovery from inactivation, iii) markedly the shifted steady-state inactivation curve to more hyperpolarized potentials. The presence of the β1 subunit significantly reduced mefloquine potency, but the drug induced a significant frequency-independent rundown upon repetitive depolarisations. Computational and experimental results indicate that mefloquine overlaps the local anaesthetic binding site by docking at a hydrophobic cavity between domains DIII and DIV that communicates the local anaesthetic binding site with the selectivity filter. This is supported by the fact that mefloquine potency significantly decreased on mutant Na v 1.4 channel F1579A and significantly increased on K1237S channels. In silico this compound docked above F1579 forming stable π-π interactions with this residue. We provide structure-activity insights into how cationic amphiphilic compounds may exert inhibitory effects by docking between the local anaesthetic binding site and the selectivity filter of a mammalian Na + channel. Our proposed synergistic cycle of experimental and computational studies may be useful for elucidating binding sites of other drugs, thereby saving in vitro and in silico resources. Copyright © 2016 Elsevier B.V. All rights reserved.
Computer-aided identification of potential TYK2 inhibitors from drug database
NASA Astrophysics Data System (ADS)
Zhang, Wei; Li, Jianzong; Huang, Zhixin; Wang, Haiyang; Luo, Hao; Wang, Xin; Zhou, Nan; Wu, Chuanfang; Bao, Jinku
2016-10-01
TYK2 is a member of JAKs family protein tyrosine kinase activated in response to various cytokines. It plays a crucial role in transducing signals downstream of various cytokine receptors, which are involved in proinflammatory responses associated with immunological diseases. Thus, the study of selective TYK2 inhibitors is one of the most popular fields in anti-inflammation drug development. Herein, we adopted molecular docking, molecular dynamics simulation and MM-PBSA binding free energy calculation to screen potential TYK2-selective inhibitors from ZINC Drug Database. Finally, three small molecule drugs ZINC12503271 (Gemifloxacin), ZINC05844792 (Nebivolol) and ZINC00537805 (Glyburide) were selected as potential TYK2-selective inhibitors. Compared to known inhibitor 2,6-dichloro-N-{2-[(cyclopropylcarbonyl)amino]pyridin-4-yl}benzamide, these three candidates had better Grid score and Amber score from molecular docking and preferable results from binding free energy calculation as well. What's more, the ATP-binding site and A-loop motif had been identified to play key roles in TYK2-targeted inhibitor discovery. It is expected that our study will pave the way for the design of potent TYK2 inhibitors of new drugs to treat a wide variety of immunological diseases such as inflammatory diseases, multiple sclerosis, psoriasis inflammatory bowel disease (IBD) and so on.
Chiappori, Federica; Merelli, Ivan; Milanesi, Luciano; Colombo, Giorgio; Morra, Giulia
2016-01-01
The Hsp70 is an allosterically regulated family of molecular chaperones. They consist of two structural domains, NBD and SBD, connected by a flexible linker. ATP hydrolysis at the NBD modulates substrate recognition at the SBD, while peptide binding at the SBD enhances ATP hydrolysis. In this study we apply Molecular Dynamics (MD) to elucidate the molecular determinants underlying the allosteric communication from the NBD to the SBD and back. We observe that local structural and dynamical modulation can be coupled to large-scale rearrangements, and that different combinations of ligands at NBD and SBD differently affect the SBD domain mobility. Substituting ADP with ATP in the NBD induces specific structural changes involving the linker and the two NBD lobes. Also, a SBD-bound peptide drives the linker docking by increasing the local dynamical coordination of its C-terminal end: a partially docked DnaK structure is achieved by combining ATP in the NBD and peptide in the SBD. We propose that the MD-based analysis of the inter domain dynamics and structure modulation could be used as a tool to computationally predict the allosteric behaviour and functional response of Hsp70 upon introducing mutations or binding small molecules, with potential applications for drug discovery. PMID:27025773
Pandey, Deeksha; Podder, Avijit; Pandit, Mansi; Latha, Narayanan
2017-09-01
The major causative agent for Acquired Immune Deficiency Syndrome (AIDS) is Human Immunodeficiency Virus-1 (HIV-1). HIV-1 is a predominant subtype of HIV which counts on human cellular mechanism virtually in every aspect of its life cycle. Binding of viral envelope glycoprotein-gp120 with human cell surface CD4 receptor triggers the early infection stage of HIV-1. This study focuses on the interaction interface between these two proteins that play a crucial role for viral infectivity. The CD4-gp120 interaction interface has been studied through a comprehensive protein-protein interaction network (PPIN) analysis and highlighted as a useful step towards identifying potential therapeutic drug targets against HIV-1 infection. We prioritized gp41, Nef and Tat proteins of HIV-1 as valuable drug targets at early stage of viral infection. Lack of crystal structure has made it difficult to understand the biological implication of these proteins during disease progression. Here, computational protein modeling techniques and molecular dynamics simulations were performed to generate three-dimensional models of these targets. Besides, molecular docking was initiated to determine the desirability of these target proteins for already available HIV-1 specific drugs which indicates the usefulness of these protein structures to identify an effective drug combination therapy against AIDS.
Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.
Metwally, Abdelkader A; Hathout, Rania M
2015-08-03
We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).
NASA Astrophysics Data System (ADS)
Fani, Najmeh; Sattarinezhad, Elham; Bordbar, Abdol-Khalegh
2017-06-01
In the first part of this paper, docking method was employed in order to study the binding mechanism of breast cancer resistance protein (BCRP) with a group of previously synthesized TPS-A derivatives which known as potent inhibitors of this protein to get insight into drug binding site of BCRP and to explore structure-activity relationship of these compounds. Molecular docking results showed that most of these compounds bind in the binding site of BCRP at the interface between the membrane and outer environment. In the second part, a group of designed TPS-A derivatives which showed good binding energies in the binding site of αβ-tubulin in the previous study were chosen to study their binding energies in the binding site of BCRP to investigate their simultaneous inhibitory effect on both αβ-tubulin and BCRP. The results showed that all of these compounds bind to the binding site of BCRP with relatively suitable binding energies and therefore could be potential inhibitors of both αβ-tubulin and BCRP proteins. Finally, virtual consensus docking method was utilized with the aim of design of new 2,5-diketopiperazine derivatives with significant inhibitory effect on both αβ-tubulin and BCRP proteins. For this purpose binding energies of a library of 2,5-diketopiperazine derivatives in the binding sites of αβ-tubulin and BCRP was investigated by using AutoDock and AutoDock vina tools. Molecular docking results revealed that a group of 36 compounds among them exhibit strong anti-tubulin and anti-BCRP activity.
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.
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
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.
NASA Astrophysics Data System (ADS)
Azizah, A.; Suselo, Y. H.; Muthmainah, M.; Indarto, D.
2018-05-01
Gestational Hypertension is one of the three main causes of maternal mortality in Indonesia. Nifedipine which blockes the Cav1.2 calcium channel has frequently been used to treat gestational hypertension. However the efficacy of nifedipine has not been established yet and the prevalence of gestational hypertension is still high (27.1 %). Indonesian herbal plants have potential to be developed as natural drugs. Molecular docking, a computational method, is very often used to depict interaction between molecules and target receptor This study was therefore to identify Indonesian herbal plants that could inhibit the calcium channel in silico. This was a bioinformatics study with molecular docking approach. Three-dimensional structure of human calcium channel Cav1.2 was determined by modelling with rabbit calcium channel (ID:5GJW) as template and using the SWISS MODEL software. Nifedipine was used as a standard ligand and obtained from ZINC database with the access code ZINC19594578. Active compounds of Indonesian herbal plants were registered in HerbalDB database and their molecular structure was obtained from PubChem. Binding affinity of human Cav1.2 model-ligand complexes were assesed using AutoDock Vina 1.1.2 software and visualization of molecular conformation used Chimera 1.10 and PyMol 1.3 softwares. The Lipinsky’s rules of five were used to determine active compounds which fullfilled drug criteria. The human Cav1-2 model had 72.35% sequence identity with rabbit Cav1.1. Nifedipine bound to the human Cav1.2 model with -2.1 kcal/mol binding affinity and had binding sites at Gln1060, Phe1129, Ser1132, and Ile1173 residues. A lower binding affinity was observed in 8 phytochemicals but only obtusifolin 2-glucoside (-2.2 kcal/mol) had similar binding sites as nifedipin did. In addition, obtusifolin 2-glucoside met the Lipinsky criteria and the molecule conformation was similar with nifedipine. From the HerbalDB database, obtusifolin 2-glucoside is found in Tectona grandis. Obtusifolin 2-glucoside computationally becomes a potensial candidate of calcium channel blocker. In vitro assays should be performed to evaluate the antagonist effect of obtusifolin 2-glucoside on calcium channel Cav1.2.
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
Dhanavade, Maruti J; Jalkute, Chidambar B; Barage, Sagar H; Sonawane, Kailas D
2013-12-01
Cysteine protease is known to degrade amyloid beta peptide which is a causative agent of Alzheimer's disease. This cleavage mechanism has not been studied in detail at the atomic level. Hence, a three-dimensional structure of cysteine protease from Xanthomonas campestris was constructed by homology modeling using Geno3D, SWISS-MODEL, and MODELLER 9v7. All the predicted models were analyzed by PROCHECK and PROSA. Three-dimensional model of cysteine protease built by MODELLER 9v7 shows similarity with human cathepsin B crystal structure. This model was then used further for docking and simulation studies. The molecular docking study revealed that Cys17, His87, and Gln88 residues of cysteine protease form an active site pocket similar to human cathepsin B. Then the docked complex was refined by molecular dynamic simulation to confirm its stable behavior over the entire simulation period. The molecular docking and MD simulation studies showed that the sulfhydryl hydrogen atom of Cys17 of cysteine protease interacts with carboxylic oxygen of Lys16 of Aβ peptide indicating the cleavage site. Thus, the cysteine protease model from X. campestris having similarity with human cathepsin B crystal structure may be used as an alternate approach to cleave Aβ peptide a causative agent of Alzheimer's disease. © 2013 Elsevier Ltd. All rights reserved.
Investigation of anticancer properties of caffeinated complexes via computational chemistry methods
NASA Astrophysics Data System (ADS)
Sayin, Koray; Üngördü, Ayhan
2018-03-01
Computational investigations were performed for 1,3,7-trimethylpurine-2,6-dione, 3,7-dimethylpurine-2,6-dione, their Ru(II) and Os(III) complexes. B3LYP/6-311 ++G(d,p)(LANL2DZ) level was used in numerical calculations. Geometric parameters, IR spectrum, 1H-, 13C and 15N NMR spectrum were examined in detail. Additionally, contour diagram of frontier molecular orbitals (FMOs), molecular electrostatic potential (MEP) maps, MEP contour and some quantum chemical descriptors were used in the determination of reactivity rankings and active sites. The electron density on the surface was similar to each other in studied complexes. Quantum chemical descriptors were investigated and the anticancer activity of complexes were more than cisplatin and their ligands. Additionally, molecular docking calculations were performed in water between related complexes and a protein (ID: 3WZE). The most interact complex was found as Os complex. The interaction energy was calculated as 342.9 kJ/mol.
Combined 3D-QSAR modeling and molecular docking study on azacycles CCR5 antagonists
NASA Astrophysics Data System (ADS)
Ji, Yongjun; Shu, Mao; Lin, Yong; Wang, Yuanqiang; Wang, Rui; Hu, Yong; Lin, Zhihua
2013-08-01
The beta chemokine receptor 5 (CCR5) is an attractive target for pharmaceutical industry in the HIV-1, inflammation and cancer therapeutic areas. In this study, we have developed quantitative structure activity relationship (QSAR) models for a series of 41 azacycles CCR5 antagonists using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and Topomer CoMFA methods. The cross-validated coefficient q2 values of 3D-QASR (CoMFA, CoMSIA, and Topomer CoMFA) methods were 0.630, 0.758, and 0.852, respectively, the non-cross-validated R2 values were 0.979, 0.978, and 0.990, respectively. Docking studies were also employed to determine the most probable binding mode. 3D contour maps and docking results suggested that bulky groups and electron-withdrawing groups on the core part would decrease antiviral activity. Furthermore, docking results indicated that H-bonds and π bonds were favorable for antiviral activities. Finally, a set of novel derivatives with predicted activities were designed.
Priya, R; Sumitha, Rajendrarao; Doss, C George Priya; Rajasekaran, C; Babu, S; Seenivasan, R; Siva, R
2015-10-01
Acquired immunodeficiency syndrome caused by human immunodeficiency virus (HIV) is an immunosuppressive disease. Over the past decades, it has plagued human health due to the grave consequences in its harness. For this reason, anti-HIV agents are imperative, and the search for the same from natural resources would assure the safety. In this investigation we have performed molecular docking, molecular property prediction, drug-likeness score, and molecular dynamics (MD) simulation to develop a novel anti-HIV drug. We have screened 12 alkaloids from a medicinal plant Toddalia asiatica for its probabilistic binding with the active site of the HIV-1-reverse transcriptase (HIV-1-RT) domain (the major contributor to the onset of the disease). The docking results were evaluated based on free energies of binding (ΔG), and the results suggested toddanol, toddanone, and toddalenone to be potent inhibitors of HIV-1-RT. In addition, the alkaloids were subjected to molecular property prediction analysis. Toddanol and toddanone with more rotatable bonds were found to have a drug-likeness score of 0.23 and 0.11, respectively. These scores were comparable with the standard anti-HIV drug zidovudine with a model score 0.28. Finally, two characteristic protein-ligand complexes were exposed to MD simulation to determine the stability of the predicted conformations. The toddanol-RT complex showed higher stability and stronger H-bonds than toddanone-RT complex. Based on these observations, we firmly believe that the alkaloid toddanol could aid in efficient HIV-1 drug discovery. In the present study, the molecular docking and MD simulations are performed to explore the possible binding mode of HIV 1 RT with 12 alkaloids of T. asiatica. Molecular docking by AutoDock4 revealed three alkaloids toddanol, toddanone, and toddalenone with highest binding affinity towards HIV 1 RT. The drug likeness model score revealed a positive score for toddanol and toddanone which is comparable to the drug likeness score of the standard anti HIV drug zidovudine. Results from simulation analysis revealed that toddanol RT complex is more stable than toddanone RT complex inferring toddanol as a potential anti HIV drug molecule. Abbreviations used: HIV: Human immunodeficiency virus, HIV 1 RT: HIV 1 reverse transcriptase, RNase H: Ribonuclease H, MD: Molecular dynamics, PDB: Protein databank, RMSD: Root mean square deviation, RMSF: Root mean square fluctuation.
Rocco, Alessandro Guerini; Mollica, Luca; Gianazza, Elisabetta; Calabresi, Laura; Franceschini, Guido; Sirtori, Cesare R.; Eberini, Ivano
2006-01-01
In this study, we propose a structure for the heterodimer between apolipoprotein A-IMilano and apolipoprotein A-II (apoA-IM–apoA-II) in a synthetic high-density lipoprotein (HDL) containing L-α-palmitoyloleoyl phosphatidylcholine. We applied bioinformatics/computational tools and procedures, such as molecular docking, molecular and essential dynamics, starting from published crystal structures for apolipoprotein A-I and apolipoprotein A-II. Structural and energetic analyses onto the simulated system showed that the molecular dynamics produced a stabilized synthetic HDL. The essential dynamic analysis showed a deviation from the starting belt structure. Our structural results were validated by limited proteolysis experiments on HDL from apoA-IM carriers in comparison with control HDL. The high sensitivity of apoA-IM–apoA-II to proteases was in agreement with the high root mean-square fluctuation values and the reduction in secondary structure content from molecular dynamics data. Circular dichroism on synthetic HDL containing apoA-IM–apoA-II was consistent with the α-helix content computed on the proposed model. PMID:16891368
Molecular dynamics-based model of VEGF-A and its heparin interactions.
Uciechowska-Kaczmarzyk, Urszula; Babik, Sándor; Zsila, Ferenc; Bojarski, Krzysztof Kamil; Beke-Somfai, Tamás; Samsonov, Sergey A
2018-06-01
We present a computational model of the Vascular Endothelial Growth Factor (VEGF), an important regulator of blood vessels formation, which function is affected by its heparin interactions. Although structures of a receptor binding (RBD) and a heparin binding domain (HBD) of VEGF are known, there are structural data neither on the 12 amino acids interdomain linker nor on its complexes with heparin. We apply molecular docking and molecular dynamics techniques combined with circular dichroism spectroscopy to model the full structure of the dimeric VEGF and to propose putative molecular mechanisms underlying the function of VEGF/VEGF receptors/heparin system. We show that both the conformational flexibility of the linker and the formation of HBD-heparin-HBD sandwich-like structures regulate the mutual disposition of HBDs and so affect the VEGF-mediated signalling. Copyright © 2018 Elsevier Inc. All rights reserved.
Kumar, Anil; Bora, Utpal
2014-12-01
DNA topoisomerase I (topo I) and II (topo II) are essential enzymes that solve the topological problems of DNA by allowing DNA strands or double helices to pass through each other during cellular processes such as replication, transcription, recombination, and chromatin remodeling. Their critical roles make topoisomerases an attractive drug target against cancer. The present molecular docking study provides insights into the inhibition of topo I and II by curcumin natural derivatives. The binding modes suggested that curcumin natural derivatives docked at the site of DNA cleavage parallel to the axis of DNA base pairing. Cyclocurcumin and curcumin sulphate were predicted to be the most potent inhibitors amongst all the curcumin natural derivatives docked. The binding modes of cyclocurcumin and curcumin sulphate were similar to known inhibitors of topo I and II. Residues like Arg364, Asn722 and base A113 (when docked to topo I-DNA complex) and residues Asp479, Gln778 and base T9 (when docked to topo II-DNA complex) seem to play important role in the binding of curcumin natural derivatives at the site of DNA cleavage.
Targeted Approach to Overcoming Treatment Resistance in Advanced Prostate Cancer
2013-07-01
molecular dynamics as in our previous works (Vasilyeva, A et al, 2009; Vasilyeva, A et...results and pitfalls. Molecular docking experiments were performed as follows: The molecular docking was...al, 2010;Salsbury. 2010). However, for this work more extensive simulations
Sahihi, M; Ghayeb, Y
2014-08-01
Citrus flavonoids are natural compounds with important health benefits. The study of their interaction with a transport protein, such as bovine β-lactoglobulin (BLG), at the atomic level could be a valuable factor to control their transport to biological sites. In the present study, molecular docking and molecular dynamics simulation methods were used to investigate the interaction of hesperetin, naringenin, nobiletin and tangeretin as citrus flavonoids and BLG as transport protein. The molecular docking results revealed that these flavonoids bind in the internal cavity of BLG and the BLG affinity for binding the flavonoids follows naringenin>hesperetin>tangeretin>nobiletin. The docking results also indicated that the BLG-flavonoid complexes are stabilized through hydrophobic interactions, hydrogen bond interactions and π-π stacking interactions. The analysis of molecular dynamics (MD) simulation trajectories showed that the root mean square deviation (RMSD) of various systems reaches equilibrium and fluctuates around the mean value at various times. Time evolution of the radius of gyration, total solvent accessible surface of the protein and the second structure of protein showed as well that BLG and BLG-flavonoid complexes were stable around 2500ps, and there was not any conformational change as for BLG-flavonoid complexes. Further, the profiles of atomic fluctuations indicated the rigidity of the ligand binding site during the simulation. Copyright © 2014 Elsevier Ltd. All rights reserved.
Barradas-Bautista, Didier; Fernández-Recio, Juan
2017-01-01
Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.
2017-01-01
Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level. PMID:28841721
Computational search for aflatoxin binding proteins
NASA Astrophysics Data System (ADS)
Wang, Ying; Liu, Jinfeng; Zhang, Lujia; He, Xiao; Zhang, John Z. H.
2017-10-01
Aflatoxin is one of the mycotoxins that contaminate various food products. Among various aflatoxin types (B1, B2, G1, G2 and M1), aflatoxin B1 is the most important and the most toxic one. In this study, through computational screening, we found that several proteins may bind specifically with different type of aflatoxins. Combination of theoretical methods including target fishing, molecular docking, molecular dynamics (MD) simulation, MM/PBSA calculation were utilized to search for new aflatoxin B1 binding proteins. A recently developed method for calculating entropic contribution to binding free energy called interaction entropy (IE) was employed to compute the binding free energy between the protein and aflatoxin B1. Through comprehensive comparison, three proteins, namely, trihydroxynaphthalene reductase, GSK-3b, and Pim-1 were eventually selected as potent aflatoxin B1 binding proteins. GSK-3b and Pim-1 are drug targets of cancers or neurological diseases. GSK-3b is the strongest binder for aflatoxin B1.
Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases
Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun
2016-01-01
Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery. PMID:26959013
Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases.
Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun
2016-03-04
Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery.
Molecular docking and QSAR study on steroidal compounds as aromatase inhibitors.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Gianti, Eleonora
Computer-Aided Drug Design (CADD) has deservedly gained increasing popularity in modern drug discovery (Schneider, G.; Fechner, U. 2005), whether applied to academic basic research or the pharmaceutical industry pipeline. In this work, after reviewing theoretical advancements in CADD, we integrated novel and stateof- the-art methods to assist in the design of small-molecule inhibitors of current cancer drug targets, specifically: Androgen Receptor (AR), a nuclear hormone receptor required for carcinogenesis of Prostate Cancer (PCa); Signal Transducer and Activator of Transcription 5 (STAT5), implicated in PCa progression; and Epstein-Barr Nuclear Antigen-1 (EBNA1), essential to the Epstein Barr Virus (EBV) during latent infections. Androgen Receptor. With the aim of generating binding mode hypotheses for a class (Handratta, V.D. et al. 2005) of dual AR/CYP17 inhibitors (CYP17 is a key enzyme for androgens biosynthesis and therefore implicated in PCa development), we successfully implemented a receptor-based computational strategy based on flexible receptor docking (Gianti, E.; Zauhar, R.J. 2012). Then, with the ultimate goal of identifying novel AR binders, we performed Virtual Screening (VS) by Fragment-Based Shape Signatures, an improved version of the original method developed in our Laboratory (Zauhar, R.J. et al. 2003), and we used the results to fully assess the high-level performance of this innovative tool in computational chemistry. STAT5. The SRC Homology 2 (SH2) domain of STAT5 is responsible for phospho-peptide recognition and activation. As a keystone of Structure-Based Drug Design (SBDD), we characterized key residues responsible for binding. We also generated a model of STAT5 receptor bound to a phospho-peptide ligand, which was validated by docking publicly known STAT5 inhibitors. Then, we performed Shape Signatures- and docking-based VS of the ZINC database (zinc.docking.org), followed by Molecular Mechanics Generalized Born Surface Area (MMGBSA) simulations, paired with Principal Component Analysis (PCA) of top-scoring hits to identify novel lead molecules likely to be active against STAT5. EBNA1 is the only viral protein consistently expressed in the many EBV-associated tumors, and is required for viral genome maintenance during latent infection. To immediately assist SBDD, we computationally identified "druggable" binding sites of EBNA1, and our predictions were later confirmed by experimental evidence (The Wistar Institute proprietary data).
Zhang, Baidong; Li, Yan; Zhang, Huixiao; Ai, Chunzhi
2010-01-01
Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q2 = 0.605, r2pred = 0.826), (q2 = 0.52, r2pred = 0.798) and (q2 = 0.582, r2pred = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors. PMID:21151441
Zhang, Baidong; Li, Yan; Zhang, Huixiao; Ai, Chunzhi
2010-11-02
Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q(2) = 0.605, r(2) (pred) = 0.826), (q(2) = 0.52, r(2) (pred) = 0.798) and (q(2) = 0.582, r(2) (pred) = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.
NASA Astrophysics Data System (ADS)
Hou, J.; Liang, Q.; Shao, S.
2017-03-01
Flavanones are the main compound of licorice, and the C'-4 position substitution is a significant structural feature for their biological activity. The ability of three selected flavanones (liquiritigenin, liquiritin, and liquiritin apioside) bearing different substituents (hydroxyl groups, glucose, and glucose-apiose sugar moiety) at the C'-4 position and a chalcone ( isoliquiritigenin, an isomer of liquiritigenin) to bind bovine serum albumin (BSA) was studied by multispectroscopic and molecular docking methods under physiological conditions. The binding mechanism of fl avonoids to BSA can be explained by the formation of a flavonoids-BSA complex, and the binding affinity is the strongest for isoliquiritigenin, followed by liquiritin apioside, liquiritin, and liquiritigenin. The thermodynamic analysis and the molecular docking indicated that the interaction between flavonoids and BSA was dominated by the hydrophobic force and hydrogen bonds. The competitive experiments as well as the molecular docking results suggested the most possible binding site of licorice flavonoids on BSA at subdomain IIA. These results revealed that the basic skeleton structure and the substituents at the C'-4 position of flavanones significantly affect the structure-affinity relationships of the licorice flavonoid binding to BSA.
Yadav, Saveg; Pandey, Shrish Kumar; Singh, Vinay Kumar; Goel, Yugal; Kumar, Ajay
2017-01-01
Altered metabolism is an emerging hallmark of cancer, as malignant cells display a mammoth up-regulation of enzymes responsible for steering their bioenergetic and biosynthetic machinery. Thus, the recent anticancer therapeutic strategies focus on the targeting of metabolic enzymes, which has led to the identification of specific metabolic inhibitors. One of such inhibitors is 3-bromopyruvate (3-BP), with broad spectrum of anticancer activity due to its ability to inhibit multiple metabolic enzymes. However, the molecular characterization of its binding to the wide spectrum of target enzymes remains largely elusive. Therefore, in the present study we undertook in silico investigations to decipher the molecular nature of the docking of 3-BP with key target enzymes of glycolysis and TCA cycle by PatchDock and YASARA docking tools. Additionally, derivatives of 3-BP, dibromopyruvate (DBPA) and propionic acid (PA), with reported biological activity, were also investigated for docking to important target metabolic enzymes of 3-BP, in order to predict their therapeutic efficacy versus that of 3-BP. A comparison of the docking scores with respect to 3-BP indicated that both of these derivatives display a better binding strength to metabolic enzymes. Further, analysis of the drug likeness of 3-BP, DBPA and PA by Lipinski filter, admetSAR and FAF Drug3 indicated that all of these agents showed desirable drug-like criteria. The outcome of this investigation sheds light on the molecular characteristics of the binding of 3-BP and its derivatives with metabolic enzymes and thus may significantly contribute in designing and optimizing therapeutic strategies against cancer by using these agents. PMID:28463978
Yadav, Saveg; Pandey, Shrish Kumar; Singh, Vinay Kumar; Goel, Yugal; Kumar, Ajay; Singh, Sukh Mahendra
2017-01-01
Altered metabolism is an emerging hallmark of cancer, as malignant cells display a mammoth up-regulation of enzymes responsible for steering their bioenergetic and biosynthetic machinery. Thus, the recent anticancer therapeutic strategies focus on the targeting of metabolic enzymes, which has led to the identification of specific metabolic inhibitors. One of such inhibitors is 3-bromopyruvate (3-BP), with broad spectrum of anticancer activity due to its ability to inhibit multiple metabolic enzymes. However, the molecular characterization of its binding to the wide spectrum of target enzymes remains largely elusive. Therefore, in the present study we undertook in silico investigations to decipher the molecular nature of the docking of 3-BP with key target enzymes of glycolysis and TCA cycle by PatchDock and YASARA docking tools. Additionally, derivatives of 3-BP, dibromopyruvate (DBPA) and propionic acid (PA), with reported biological activity, were also investigated for docking to important target metabolic enzymes of 3-BP, in order to predict their therapeutic efficacy versus that of 3-BP. A comparison of the docking scores with respect to 3-BP indicated that both of these derivatives display a better binding strength to metabolic enzymes. Further, analysis of the drug likeness of 3-BP, DBPA and PA by Lipinski filter, admetSAR and FAF Drug3 indicated that all of these agents showed desirable drug-like criteria. The outcome of this investigation sheds light on the molecular characteristics of the binding of 3-BP and its derivatives with metabolic enzymes and thus may significantly contribute in designing and optimizing therapeutic strategies against cancer by using these agents.
Quantum.Ligand.Dock: protein-ligand docking with quantum entanglement refinement on a GPU system.
Kantardjiev, Alexander A
2012-07-01
Quantum.Ligand.Dock (protein-ligand docking with graphic processing unit (GPU) quantum entanglement refinement on a GPU system) is an original modern method for in silico prediction of protein-ligand interactions via high-performance docking code. The main flavour of our approach is a combination of fast search with a special account for overlooked physical interactions. On the one hand, we take care of self-consistency and proton equilibria mutual effects of docking partners. On the other hand, Quantum.Ligand.Dock is the the only docking server offering such a subtle supplement to protein docking algorithms as quantum entanglement contributions. The motivation for development and proposition of the method to the community hinges upon two arguments-the fundamental importance of quantum entanglement contribution in molecular interaction and the realistic possibility to implement it by the availability of supercomputing power. The implementation of sophisticated quantum methods is made possible by parallelization at several bottlenecks on a GPU supercomputer. The high-performance implementation will be of use for large-scale virtual screening projects, structural bioinformatics, systems biology and fundamental research in understanding protein-ligand recognition. The design of the interface is focused on feasibility and ease of use. Protein and ligand molecule structures are supposed to be submitted as atomic coordinate files in PDB format. A customization section is offered for addition of user-specified charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. Final predicted complexes are ranked according to obtained scores and provided in PDB format as well as interactive visualization in a molecular viewer. Quantum.Ligand.Dock server can be accessed at http://87.116.85.141/LigandDock.html.
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.
NASA Astrophysics Data System (ADS)
Mohammadi, Ali A.; Taheri, Salman; Amouzegar, Ali; Ahdenov, Reza; Halvagar, Mohammad Reza; Sadr, Ahmad Shahir
2017-07-01
An efficient one-pot, catalyst-free, and four-components procedure for the synthesis of novel 10b-hydroxy-4-nitro-5-phenyl-2,3,5,5a-tetrahydro-1H-imidazo[1,2-a]indeno[2,1-e]pyridin-6(10bH)-one derivatives from corresponding diamine, nitro ketene dithioacetal, aldehydes and 1,3-indandione in ethanol has been achieved upon a Knoevenagel condensation-Michael addition-tautomerism-cyclisation sequence. All the newly synthesized compounds were screened for molecular docking studies. Molecular docking studies were carried out using the crystal structure of HIV protease enzyme. Some of the compounds obtain minimum binding energy and good affinity toward the active pocket of HIV protease enzyme in compare with Saquinavir as a standard HIV protease inhibitor.
Benzothiazole analogs as potential anti-TB agents: computational input and molecular dynamics.
Venugopala, Katharigatta N; Khedr, Mohammed A; Pillay, Melendhran; Nayak, Susanta K; Chandrashekharappa, Sandeep; Aldhubiab, Bandar E; Harsha, Sree; Attimard, Mahesh; Odhav, Bharti
2018-05-16
Biotin is very important for the survival of Mycobacterium tuberculosis. 7,8-Diamino pelargonic acid aminotransaminase (DAPA) is a transaminase enzyme involved in the biosynthesis of biotin. The benzothiazole title compounds were investigated for their in vitro anti-tubercular activity against two tubercular strains: H37Rv (ATCC 25,177) and MDR-MTB (multidrug-resistant M. tuberculosis, resistant to isoniazid, rifampicin, and ethambutol) by an agar incorporation method. The possible binding mode and predicted affinity were computed using a molecular docking study. Among the synthesized compounds in the series, the title compound {2-(benzo[d]thiazol-2-yl-methoxy)-5-fluorophenyl}-(4-chlorophenyl)-methanone was found to exhibit significant activity with minimum inhibitory concentrations of 1 μg/mL and 2 μg/mL against H37Rv and MDR-MTB, respectively; this compound showed the highest binding affinity (-24.75 kcal/mol) as well.
Cuya, Teobaldo; Gonçalves, Arlan da Silva; da Silva, Jorge Alberto Valle; Ramalho, Teodorico C; Kuca, Kamil; C C França, Tanos
2017-10-27
The oximes 4-carbamoyl-1-[({2-[(E)-(hydroxyimino) methyl] pyridinium-1-yl} methoxy) methyl] pyridinium (known as HI-6) and 3-carbamoyl-1-[({2-[(E)-(hydroxyimino) methyl] pyridinium-1-yl} methoxy) methyl] pyridinium (known as HS-6) are isomers differing from each other only by the position of the carbamoyl group on the pyridine ring. However, this slight difference was verified to be responsible for big differences in the percentual of reactivation of acetylcholinesterase (AChE) inhibited by the nerve agents tabun, sarin, cyclosarin, and VX. In order to try to find out the reason for this, a computational study involving molecular docking, molecular dynamics, and binding energies calculations, was performed on the binding modes of HI-6 and HS-6 on human AChE (HssAChE) inhibited by those nerve agents.
Chemical and protein structural basis for biological crosstalk between PPAR α and COX enzymes
NASA Astrophysics Data System (ADS)
Cleves, Ann E.; Jain, Ajay N.
2015-02-01
We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPAR α and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPAR α agonists are cyclooxygenase inhibitors.
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
NASA Astrophysics Data System (ADS)
Giełdoń, Artur; Kaźmierkiewicz, Rajmund; Ślusarz, Rafał; Ciarkowski, Jerzy
2001-12-01
The nonapeptide hormones arginine vasopressin (CYFQNCPRG-NH2, AVP) and oxytocin (CYIQNCPLG-NH2, OT), control many essential functions in mammals. Their main activities include the urine concentration (via stimulation of AVP V2 receptors, V2R, in the kidneys), blood pressure regulation (via stimulation of vascular V1a AVP receptors, V1aR), ACTH control (via stimulation of V1b receptors, V1bR, in the pituitary) and labor and lactation control (via stimulation of OT receptors, OTR, in the uterus and nipples, respectively). All four receptor subtypes belong to the GTP-binding (G) protein-coupled receptor (GPCR) family. This work consists of docking of YM087, a potent non-peptide V1aR and V2R - but not OTR - antagonist, into the receptor models based on relatively new theoretical templates of rhodopsin (RD) and opiate receptors, proposed by Mosberg et al. (Univ. of Michigan, Ann Arbor, USA). It is simultaneously demonstrated that this RD template satisfactorily compares with the first historical GPCR structure of bovine rhodopsin (Palczewski et al., 2000) and that homology-modeling of V2R, V1aR and OTR using opiate receptors as templates is rational, based on relatively high (20-60%) sequence homology among the set of 4 neurophyseal and 4 opiate receptors. YM087 was computer-docked to V1aR, V2R and OTR using the AutoDock (Olson et al., Scripps Research Institute, La Jolla, USA) and subsequently relaxed using restrained simulated annealing and molecular dynamics, as implemented in AMBER program (Kollman et al., University of California, San Francisco, USA). From about 80 diverse configurations, sampled for each of the three ligand/receptor systems, 3 best energy-relaxed complexes were selected for mutual comparisons. Similar docking modes were found for the YM087/V1aR and YM087/V2R complexes, diverse from those of the YM087/OTR complexes, in agreement with the molecular affinity data.
Fatima, Sabiha; Jatavath, Mohan Babu; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha
2014-10-01
Poly(ADP-ribose) polymerase-1 (PARP-1) functions as a DNA damage sensor and signaling molecule. It plays a vital role in the repair of DNA strand breaks induced by radiation and chemotherapeutic drugs; inhibitors of this enzyme have the potential to improve cancer chemotherapy or radiotherapy. Three-dimensional quantitative structure activity relationship (3D QSAR) models were developed using comparative molecular field analysis, comparative molecular similarity indices analysis and docking studies. A set of 88 molecules were docked into the active site of six X-ray crystal structures of poly(ADP-ribose)polymerase-1 (PARP-1), by a procedure called multiple receptor conformation docking (MRCD), in order to improve the 3D QSAR models through the analysis of binding conformations. The docked poses were clustered to obtain the best receptor binding conformation. These dock poses from clustering were used for 3D QSAR analysis. Based on MRCD and QSAR information, some key features have been identified that explain the observed variance in the activity. Two receptor-based QSAR models were generated; these models showed good internal and external statistical reliability that is evident from the [Formula: see text], [Formula: see text] and [Formula: see text]. The identified key features enabled us to design new PARP-1 inhibitors.
Flavin binding to the deca-heme cytochrome MtrC: Insights from computational molecular simulation
Breuer, Marian; Rosso, Kevin M.; Blumberger, Jochen
2015-12-15
Here, certain dissimilatory bacteria have the remarkable ability to use extracellular metal oxide minerals instead of oxygen as terminal electron sinks, using a process known as “extracellular respiration”. Specialized multiheme cytochromes located on the outer membrane of the microbe were shown to be crucial for electron transfer from the cell surface to the mineral. This process is facilitated by soluble, biogenic flavins secreted by the organism for the purpose of acting as an electron shuttle. However, their interactions with the outer-membrane cytochromes are not established on a molecular scale. Here, we study the interaction between the outer-membrane deca-heme cytochrome MtrCmore » from Shewanella oneidensis and flavin mononucleotide (FMN in fully oxidized quinone form) using computational docking. We find that interaction of FMN with MtrC is significantly weaker than with known FMN-binding proteins, but identify a mildly preferred interaction site close to heme 2 with a dissociation constant (K d) = 490 μM, in good agreement with recent experimental estimates, K d = 255 μM. The weak interaction with MtrC can be qualitatively explained by the smaller number of hydrogen bonds that the planar headgroup of FMN can form with this protein compared to FMN-binding proteins. Molecular dynamics simulation gives indications for a possible conformational switch upon cleavage of the disulphide bond of MtrC, but without concomitant increase in binding affinities according to this docking study. Overall, our results suggest that binding of FMN to MtrC is reversible and not highly specific, which may be consistent with a role as redox shuttle that facilitates extracellular respiration.« less
Jiang, Ludi; Zhang, Xianbao; Chen, Xi; He, Yusu; Qiao, Liansheng; Zhang, Yanling; Li, Gongyu; Xiang, Yuhong
2015-07-15
The metabotropic glutamate subtype 1 (mGluR1), a member of the metabotropic glutamate receptors, is a therapeutic target for neurological disorders. However, due to the lower subtype selectivity of mGluR1 orthosteric compounds, a new targeted strategy, known as allosteric modulators research, is needed for the treatment of mGluR1-related diseases. Recently, the structure of the seven-transmembrane domain (7TMD) of mGluR1 has been solved, which reveals the binding site of allosteric modulators and provides an opportunity for future subtype-selectivity drug design. In this study, a series of computer-aided drug design methods were utilized to discover potential mGluR1 negative allosteric modulators (NAMs). Pharmacophore models were constructed based on three different structure types of mGluR1 NAMs. After validation using the built-in parameters and test set, the optimal pharmacophore model of each structure type was selected and utilized as a query to screen the Traditional Chinese Medicine Database (TCMD). Then, three different hit lists of compounds were obtained. Molecular docking was used based on the latest crystal structure of mGluR1-7TMD to further filter these hits. As a compound with high QFIT and LibDock Score was preferred, a total of 30 compounds were retained. MD simulation was utilized to confirm the stability of potential compounds binding. From the computational results, thesinine-4'-O-β-d-glucoside, nigrolineaxanthone-P and nodakenin might exhibit negative allosteric moderating effects on mGluR1. This paper indicates the applicability of molecular simulation technologies for discovering potential natural mGluR1 NAMs from Chinese herbs.
Modeling of protein binary complexes using structural mass spectrometry data
Kamal, J.K. Amisha; Chance, Mark R.
2008-01-01
In this article, we describe a general approach to modeling the structure of binary protein complexes using structural mass spectrometry data combined with molecular docking. In the first step, hydroxyl radical mediated oxidative protein footprinting is used to identify residues that experience conformational reorganization due to binding or participate in the binding interface. In the second step, a three-dimensional atomic structure of the complex is derived by computational modeling. Homology modeling approaches are used to define the structures of the individual proteins if footprinting detects significant conformational reorganization as a function of complex formation. A three-dimensional model of the complex is constructed from these binary partners using the ClusPro program, which is composed of docking, energy filtering, and clustering steps. Footprinting data are used to incorporate constraints—positive and/or negative—in the docking step and are also used to decide the type of energy filter—electrostatics or desolvation—in the successive energy-filtering step. By using this approach, we examine the structure of a number of binary complexes of monomeric actin and compare the results to crystallographic data. Based on docking alone, a number of competing models with widely varying structures are observed, one of which is likely to agree with crystallographic data. When the docking steps are guided by footprinting data, accurate models emerge as top scoring. We demonstrate this method with the actin/gelsolin segment-1 complex. We also provide a structural model for the actin/cofilin complex using this approach which does not have a crystal or NMR structure. PMID:18042684
Makarova, Katerina; Siudem, Pawel; Zawada, Katarzyna; Kurkowiak, Justyna
2016-10-01
Bisphenol A (BPA) acts as an endocrine-disrupting compound even at a low concentration. Degradation of BPA could lead to the formation of toxic products. In this study, we compare the toxicity of BPA and seven intermediate products of its degradation. The accuracy of three molecular docking programs (Surflex, Autodock, and Autodock Vina) in predicting the binding affinities of selected compounds to human (ERα, ERβ, and ERRγ) and zebrafish (ERα, ERRγA, and ERRγB) estrogen and estrogen-related receptors was evaluated. The docking experiments showed that 4-isopropylphenol could have similar toxicity to that of BPA due to its high affinity to ERRγ and ERRγB and high octanol-water partitioning coefficient. The least toxic compounds were hydroquinone and phenol. Those compounds as well as BPA were screened in the zebrafish (Danio rerio) embryo test. 4-isopropylphenol had the strongest toxic effect on zebrafish embryos and caused 100% lethality shortly after exposure. BPA caused the delay in development, multiple deformations, and low heartbeats (30 bps), whereas hydroquinone had no impact on the development of the zebrafish embryo. Thus, the results of zebrafish screening are in good agreement with our docking experiment. The molecular docking could be used to screen the toxicity of other xenoestrogens and their products of degradation.
Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun
2014-10-27
In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.
NASA Astrophysics Data System (ADS)
Sherlin, Y. Sheeba; Vijayakumar, T.; Roy, S. D. D.; Jayakumar, V. S.
2018-05-01
Molecular geometry of Parkinson's drug 2-(3,4-Dihydroxyphenyl)ethylamine hydrochloride (Dopamine, DA) has been evaluated and compared with experimental XRD data. Molecular docking and vibrational spectral analysis of DA have been carried out using FT-Raman and FT-IR spectra aided by Density Functional Theory at B3LYP/6-311++G(d,p). The present investigation deals with the analysis of structural and spectral features responsible for drug activities, nature of hydrogen bonding interactions of the molecule and the correlation of Parkinson's nature with its molecular structural features.
NASA Astrophysics Data System (ADS)
Banuppriya, Govindharasu; Sribalan, Rajendran; Padmini, Vediappen
2018-03-01
Curcumin-sulfonamide hybrids (4a-e) were synthesized and their in vitro antioxidant, anti-inflammatory and anticancer activities were studied. The synthesized compounds showed a very good potent activity towards antioxidant and anti-inflammatory studies rather than its parent as well as standard. These compounds have exhibited an excellent toxicity effect to the cancer cell lines such as A549 and AGS. The compounds 4a and 4c have showed good anticancer activity than curcumin. The molecular docking studies were also performed against various Epidermal Growth Factor Receptor (EGFR) enzymes. The DFT calculations were also done in order to support the docking results.
NASA Astrophysics Data System (ADS)
Maheswari, R.; Manjula, J.
2016-07-01
(E)-4-methoxy-N‧-(4-methylbenzylidene)benzohydrazide (4MN'MBH) a novel, organic, hydrazone Schiff base compound was synthesized and its structure was characterized by Fourier Transform Infrared (4000-400 cm-1), Fourier Transform Raman (3500-50 cm-1), Ultraviolet-Visible (200-800 nm) and 1H and 13C NMR spectroscopic analysis. Optimized molecular structure, vibrational frequencies and corresponding vibrational assignments regarding 4MN'MBH has become screened tentatively as well as hypothetically utilizing Gaussian09Wprogram package. Potential energy distributions of the normal modes of vibrations connected with vibrations are generally accomplished by applying VEDA program. Natural Bonding Orbital (NBO) assessment was completed with a reason to clarify charge transfer or conjugative interaction, the intra-molecular-hybridization and delocalization of electron density within the molecule. Electronic transitions were studied employing UV-Visible spectrum and the observed values were compared with theoretical values. 1H and13C NMR spectral assessment had been made with choosing structure property relationship by chemical shifts along with magnetic shielding effects of title compound. The first order hyperpolarizability (β0) and related properties (β, α0 and Δα) of 4MN'MBH were calculated. The computed first order hyperpolarizability commensurate with the documented worth of very similar structure and could be an interesting thing for more experiments on non linear optics. Molecular docking study has been performed by in silico method to analysis their antituberculosis aspects against Enoyl acyl carrier protein reductase (Mycobacterium tuberculosis InhA) protein.
A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus.
Ekins, Sean; Freundlich, Joel S; Coffee, Megan
2014-01-01
We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.
A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus
Ekins, Sean; Freundlich, Joel S.; Coffee, Megan
2014-01-01
We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested. PMID:25653841
Cichero, Elena; D'Ursi, Pasqualina; Moscatelli, Marco; Bruno, Olga; Orro, Alessandro; Rotolo, Chiara; Milanesi, Luciano; Fossa, Paola
2013-12-01
Phosphodiesterase 11 (PDE11) is the latest isoform of the PDEs family to be identified, acting on both cyclic adenosine monophosphate and cyclic guanosine monophosphate. The initial reports of PDE11 found evidence for PDE11 expression in skeletal muscle, prostate, testis, and salivary glands; however, the tissue distribution of PDE11 still remains a topic of active study and some controversy. Given the sequence similarity between PDE11 and PDE5, several PDE5 inhibitors have been shown to cross-react with PDE11. Accordingly, many non-selective inhibitors, such as IBMX, zaprinast, sildenafil, and dipyridamole, have been documented to inhibit PDE11. Only recently, a series of dihydrothieno[3,2-d]pyrimidin-4(3H)-one derivatives proved to be selective toward the PDE11 isoform. In the absence of experimental data about PDE11 X-ray structures, we found interesting to gain a better understanding of the enzyme-inhibitor interactions using in silico simulations. In this work, we describe a computational approach based on homology modeling, docking, and molecular dynamics simulation to derive a predictive 3D model of PDE11. Using a Graphical Processing Unit architecture, it is possible to perform long simulations, find stable interactions involved in the complex, and finally to suggest guideline for the identification and synthesis of potent and selective inhibitors. © 2013 John Wiley & Sons A/S.
Cheng, Peng; Li, Jiaojiao; Wang, Juan; Zhang, Xiaoyun; Zhai, Honglin
2018-05-01
Focal adhesion kinase (FAK) is one kind of tyrosine kinases that modulates integrin and growth factor signaling pathways, which is a promising therapeutic target because of involving in cancer cell migration, proliferation, and survival. To investigate the mechanism between FAK and triazinic inhibitors and design high activity inhibitors, a molecular modeling integrated with 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy calculations was performed. The optimum CoMFA and CoMSIA models showed good reliability and satisfactory predictability (with Q 2 = 0.663, R 2 = 0.987, [Formula: see text] = 0.921 and Q 2 = 0.670, R 2 = 0.981, [Formula: see text] = 0.953). Its contour maps could provide structural features to improve inhibitory activity. Furthermore, a good consistency between contour maps, docking, and molecular dynamics simulations strongly demonstrates that the molecular modeling is reliable. Based on it, we designed several new compounds and their inhibitory activities were validated by the molecular models. We expect our studies could bring new ideas to promote the development of novel inhibitors with higher inhibitory activity for FAK.
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.
Andrade-Ochoa, S; García-Machorro, J; Bello, Martiniano; Rodríguez-Valdez, L M; Flores-Sandoval, C A; Correa-Basurto, J
2017-08-03
Human immunodeficiency virus type-1 (HIV-1) has infected more than 40 million people around the world. HIV-1 treatment still has several side effects, and the development of a vaccine, which is another potential option for decreasing human infections, has faced challenges. This work presents a computational study that includes a quantitative structure activity relationship(QSAR) using density functional theory(DFT) for reported peptides to identify the principal quantum mechanics descriptors related to peptide activity. In addition, the molecular recognition properties of these peptides are explored on major histocompatibility complex I (MHC-I) through docking and molecular dynamics (MD) simulations accompanied by the Molecular Mechanics Generalized Born Surface Area (MMGBSA) approach for correlating peptide activity reported elsewhere vs. theoretical peptide affinity. The results show that the carboxylic acid and hydroxyl groups are chemical moieties that have an inverse relationship with biological activity. The number of sulfides, pyrroles and imidazoles from the peptide structure are directly related to biological activity. In addition, the HOMO orbital energy values of the total absolute charge and the Ghose-Crippen molar refractivity of peptides are descriptors directly related to the activity and affinity on MHC-I. Docking and MD simulation studies accompanied by an MMGBSA analysis show that the binding free energy without considering the entropic contribution is energetically favorable for all the complexes. Furthermore, good peptide interaction with the most affinity is evaluated experimentally for three proteins. Overall, this study shows that the combination of quantum mechanics descriptors and molecular modeling studies could help describe the immunogenic properties of peptides from HIV-1.
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.
Xu, Yingying; Lee, Jinhyuk; Lü, Zhi-Rong; Mu, Hang; Zhang, Qian; Park, Yong-Doo
2016-07-01
Understanding the mechanism of acetaldehyde dehydrogenase 1 (ALDH1) folding is important because this enzyme is directly involved in several types of cancers and other diseases. We investigated the urea-mediated unfolding of ALDH1 by integrating kinetic inhibition studies with computational molecular dynamics (MD) simulations. Conformational changes in the enzyme structure were also analyzed using intrinsic and 1-anilinonaphthalene-8-sulfonate (ANS)-binding fluorescence measurements. Kinetic studies revealed that the direct binding of urea to ALDH1 induces inactivation of ALDH1 in a manner of mixed-type inhibition. Tertiary structural changes associated with regional hydrophobic exposure of the active site were observed. The urea binding regions on ALDH1 were predicted by docking simulations and were partly shared with active site residues of ALDH1 and with interface residues of the oligomerization domain for tetramer formation. The docking results suggest that urea prevents formation of the ALDH1 normal shape for the tetramer state as well as entrance of the substrate into the active site. Our study provides insight into the structural changes that accompany urea-mediated unfolding of ALDH1 and the catalytic role associated with conformational changes.
Hassanzadeh, Malihe; Bagherzadeh, Kowsar; Amanlou, Massoud
2016-11-01
Nowadays the ability to prediction of complex behavior rationally based on the computational approaches has been a successful technique in drug discovery. In the present study interactions of a new series of hybrids, which were made by linking colchicine as a tubulin inhibitor and suberoylanilide hydroxamic acid (SAHA) as a HDAC inhibitor, with HDAC8 and HDAC1 were investigated and compared. This research has been facilitated by the availability of experimental information besides employing docking methodology as well as classical molecular dynamics simulations and binding free energy calculation were performed. The obtained findings indicate different modes of interactions and inhibition strengths of the studied inhibitors for HDAC8 and HDAC1. HDAC8 binding free energies (-34.35 to -26.27kcal/mol) revealed higher binding affinity to HDAC8 compared to HDAC1 (-33.17 to -7.99kcal/mol). The binding energy contribution of each residue with the hybrid compounds 4a-4e within the active site of HDAC1 and HDAC8 was analyzed and the results confirmed the rule of key amino acids in interaction with the hybrid compounds. Copyright © 2016 Elsevier Inc. All rights reserved.
Postprocessing of docked protein-ligand complexes using implicit solvation models.
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.
Computational 3D structures of drug-targeting proteins in the 2009-H1N1 influenza A virus
NASA Astrophysics Data System (ADS)
Du, Qi-Shi; Wang, Shu-Qing; Huang, Ri-Bo; Chou, Kuo-Chen
2010-01-01
The neuraminidase (NA) and M2 proton channel of influenza virus are the drug-targeting proteins, based on which several drugs were developed. However these once powerful drugs encountered drug-resistant problem to the H5N1 and H1N1 flu. To address this problem, the computational 3D structures of NA and M2 proteins of 2009-H1N1 influenza virus were built using the molecular modeling technique and computational chemistry method. Based on the models the structure features of NA and M2 proteins were analyzed, the docking structures of drug-protein complexes were computed, and the residue mutations were annotated. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic.
Usman, Afia; Ahmad, Masood
2017-08-01
BPF (Bisphenol-F), a member of the bisphenol family, having a wide range of industrial applications is gradually replacing Bisphenol-A. It is a recognized endocrine disrupting chemical (EDC). EDCs have been implicated in increased incidences of breast, prostate and testis cancers besides diabetes, obesity and decreased fertility. Due to the adverse effects of EDCs on human health, attempts have been directed towards their mechanism of toxicity especially at the molecular level. Hence, to understand the mechanism at the DNA level, interaction of BPF with calf thymus DNA was studied employing multi-spectroscopic, voltammetric and molecular docking techniques. Fluorescence spectra, cyclic voltammetry (CV), circular dichroism (CD) and molecular docking studies of BPF with DNA were suggestive of minor groove binding of BPF. UV-visible absorption and fluorescence spectra suggested static quenching due to complex formation between BPF and ctDNA. Hoechst 33258 (HO) and ethidium bromide (EB) displacement studies further confirmed such mode of BPF interaction. Thermodynamic and molecular docking parameters revealed the mechanism of binding of BPF with ctDNA to be favorable and spontaneous due to negative ΔG and occurring through hydrogen bonds and van der waals interactions. BPF induced DNA cleavage under in vitro conditions by plasmid nicking assay suggested it to be genotoxic. Copyright © 2017 Elsevier Ltd. All rights reserved.
Gholivand, Khodayar; Ebrahimi Valmoozi, Ali Asghar; Bonsaii, Mahyar
2014-06-01
Novel (thio)phosphoramidate derivatives based on piperidincarboxamide with the general formula of (NH2-C(O)-C5H9N)-P(X=O,S)R1R2 (1-5) and (NH2-C(O)-C5H9N)2-P(O)R (6-9) were synthesized and characterized by (31)P, (13)C, (1)H NMR, IR spectroscopy. Furthermore, the crystal structure of compound (NH2-C(O)-C5H9N)2-P(O)(OC6H5) (6) was investigated. The activities of derivatives on cholinesterases (ChE) were determined using a modified Ellman's method. Also the mixed-type mechanisms of these compounds were evaluated by Lineweaver-Burk plots. Molecular docking and quantitative structure-activity relationship (QSAR) were used to understand the relationship between molecular structural features and anti-ChE activity, and to predict the binding affinity of phosphoramido-piperidinecarboxamides (PAPCAs) to ChE receptors. From molecular docking analysis, noncovalent interactions especially hydrogen bonding as well as hydrophobic was found between PAPCAs and ChE. Based on the docking results, appropriate molecular structural parameters were adopted to develop a QSAR model. DFT-QSAR models for ChE enzymes demonstrated the importance of electrophilicity parameter in describing the anti-AChE and anti-BChE activities of the synthesized compounds. The correlation matrix of QSAR models and docking analysis confirmed that electrophilicity descriptor can control the influence of the hydrophobic properties of P=(O, S) and CO functional groups of PAPCA derivatives in the inhibition of human ChE enzymes. Copyright © 2014 Elsevier Inc. All rights reserved.
Lin, Kai; Zhang, Lanwei; Han, Xue; Meng, Zhaoxu; Zhang, Jianming; Wu, Yifan; Cheng, Dayou
2018-03-28
In this study, Qula casein derived from yak milk casein was hydrolyzed using a two-enzyme combination approach, and high angiotensin I-converting enzyme (ACE) inhibitory activity peptides were screened by quantitative structure-activity relationship (QSAR) modeling integrated with molecular docking analysis. Hydrolysates (<3 kDa) derived from combinations of thermolysin + alcalase and thermolysin + proteinase K demonstrated high ACE inhibitory activities. Peptide sequences in hydrolysates derived from these two combinations were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). On the basis of the QSAR modeling prediction, a total of 16 peptides were selected for molecular docking analysis. The docking study revealed that four of the peptides (KFPQY, MPFPKYP, MFPPQ, and QWQVL) bound the active site of ACE. These four novel peptides were chemically synthesized, and their IC 50 was determined. Among these peptides, KFPQY showed the highest ACE inhibitory activity (IC 50 = 12.37 ± 0.43 μM). Our study indicated that Qula casein presents an excellent source to produce ACE inhibitory peptides.
Calzada, Fernando; Correa-Basurto, Jose; Barbosa, Elizabeth; Mendez-Luna, David; Yepez-Mulia, Lilian
2017-01-01
Background: Annona cherimola Miller (Annonaceae) is a medicinal plant frequently recommended in Mexican traditional medicine for the treatment of gastrointestinal disorders such as diarrhea and dysentery. Objective: This work was undertaken to obtain information that support the traditional use of A. cherimola, on pharmacological basis using in vitro and computational experiments. Material and Methods: Bioassay-guided fractionation of the ethanol extract of the leaves of A. cherimola afforded five phenolic compounds: caffeic acid, quercetin, kaempferol, nicotinflorin, and rutin. Results: The in vitro antiprotozoal assay showed that kaempferol was the most potent antiamoebic and antigiardial compound with IC50 values of 7.9 μg/mL for Entamoeba histolytica and 8.7 μg/mL for Giardia lamblia. Computational molecular docking study showed that kaempferol interacted in a region different than metronidazole in the enzyme pyruvate: ferredoxin oxidoreductase (PFOR). Conclusion: Considering that PFOR is a target of metronidazole; kaempferol may be a lead compound for the development of novel antiprotozoal agent. Also, these findings give support to the use of A. cherimola in the traditional medicine from México for the treatment of diarrhea and dysentery. SUMMARY Bioassay-guided fractionation of the ethanol extract of the leaves of Annona cherimola afforded five phenolic compounds: caffeic acid, quercetin, kaempferol, nicotinflorin and rutin. The in vitro antiprotozoal assay showed that kaempferol was the most potent antiamoebic and antigiardial compound with IC50 values of 7.9 μg/mL for Entamoeba histolytica and 8.7 μg/mL for Giardia lamblia. Computational molecular docking study showed that kaempferol interacted in a region different that metronidazole in the enzyme pyruvate: ferredoxin oxidoreductase. Abbreviations used: PFOR:Pyruvate:ferredoxin oxidoreductase, G: lamblia: Giardia lamblia, E: histolytica: Entamoeba histolytica PMID:28216899
Modeling and docking antibody structures with Rosetta
Weitzner, Brian D.; Jeliazkov, Jeliazko R.; Lyskov, Sergey; Marze, Nicholas; Kuroda, Daisuke; Frick, Rahel; Adolf-Bryfogle, Jared; Biswas, Naireeta; Dunbrack, Roland L.; Gray, Jeffrey J.
2017-01-01
We describe Rosetta-based computational protocols for predicting the three-dimensional structure of an antibody from sequence (RosettaAntibody) and then docking the antibody to protein antigens (SnugDock). Antibody modeling leverages canonical loop conformations to graft large segments from experimentally-determined structures as well as (1) energetic calculations to minimize loops, (2) docking methodology to refine the VL–VH relative orientation, and (3) de novo prediction of the elusive complementarity determining region (CDR) H3 loop. To alleviate model uncertainty, antibody–antigen docking resamples CDR loop conformations and can use multiple models to represent an ensemble of conformations for the antibody, the antigen or both. These protocols can be run fully-automated via the ROSIE web server (http://rosie.rosettacommons.org/) or manually on a computer with user control of individual steps. For best results, the protocol requires roughly 1,000 CPU-hours for antibody modeling and 250 CPU-hours for antibody–antigen docking. Tasks can be completed in under a day by using public supercomputers. PMID:28125104
Priya, R.; Sumitha, Rajendrarao; Doss, C. George Priya; Rajasekaran, C.; Babu, S.; Seenivasan, R.; Siva, R.
2015-01-01
Background: Acquired immunodeficiency syndrome caused by human immunodeficiency virus (HIV) is an immunosuppressive disease. Over the past decades, it has plagued human health due to the grave consequences in its harness. Objective: For this reason, anti-HIV agents are imperative, and the search for the same from natural resources would assure the safety. Materials and Methods: In this investigation we have performed molecular docking, molecular property prediction, drug-likeness score, and molecular dynamics (MD) simulation to develop a novel anti-HIV drug. We have screened 12 alkaloids from a medicinal plant Toddalia asiatica for its probabilistic binding with the active site of the HIV-1-reverse transcriptase (HIV-1-RT) domain (the major contributor to the onset of the disease). Results: The docking results were evaluated based on free energies of binding (ΔG), and the results suggested toddanol, toddanone, and toddalenone to be potent inhibitors of HIV-1-RT. In addition, the alkaloids were subjected to molecular property prediction analysis. Toddanol and toddanone with more rotatable bonds were found to have a drug-likeness score of 0.23 and 0.11, respectively. These scores were comparable with the standard anti-HIV drug zidovudine with a model score 0.28. Finally, two characteristic protein-ligand complexes were exposed to MD simulation to determine the stability of the predicted conformations. Conclusion: The toddanol-RT complex showed higher stability and stronger H-bonds than toddanone-RT complex. Based on these observations, we firmly believe that the alkaloid toddanol could aid in efficient HIV-1 drug discovery. SUMMARY In the present study, the molecular docking and MD simulations are performed to explore the possible binding mode of HIV 1 RT with 12 alkaloids of T. asiatica. Molecular docking by AutoDock4 revealed three alkaloids toddanol, toddanone, and toddalenone with highest binding affinity towards HIV 1 RT. The drug likeness model score revealed a positive score for toddanol and toddanone which is comparable to the drug likeness score of the standard anti HIV drug zidovudine. Results from simulation analysis revealed that toddanol RT complex is more stable than toddanone RT complex inferring toddanol as a potential anti HIV drug molecule. Abbreviations used: HIV: Human immunodeficiency virus, HIV 1 RT: HIV 1 reverse transcriptase, RNase H: Ribonuclease H, MD: Molecular dynamics, PDB: Protein databank, RMSD: Root mean square deviation, RMSF: Root mean square fluctuation. PMID:26929575
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.
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.
Does your model weigh the same as a Duck?
NASA Astrophysics Data System (ADS)
Jain, Ajay N.; Cleves, Ann E.
2012-01-01
Computer-aided drug design is a mature field by some measures, and it has produced notable successes that underpin the study of interactions between small molecules and living systems. However, unlike a truly mature field, fallacies of logic lie at the heart of the arguments in support of major lines of research on methodology and validation thereof. Two particularly pernicious ones are cum hoc ergo propter hoc (with this, therefore because of this) and confirmation bias (seeking evidence that is confirmatory of the hypothesis at hand). These fallacies will be discussed in the context of off-target predictive modeling, QSAR, molecular similarity computations, and docking. Examples will be shown that avoid these problems.
Protocols Utilizing Constant pH Molecular Dynamics to Compute pH-Dependent Binding Free Energies
2015-01-01
In protein–ligand binding, the electrostatic environments of the two binding partners may vary significantly in bound and unbound states, which may lead to protonation changes upon binding. In cases where ligand binding results in a net uptake or release of protons, the free energy of binding is pH-dependent. Nevertheless, conventional free energy calculations and molecular docking protocols typically do not rigorously account for changes in protonation that may occur upon ligand binding. To address these shortcomings, we present a simple methodology based on Wyman’s binding polynomial formalism to account for the pH dependence of binding free energies and demonstrate its use on cucurbit[7]uril (CB[7]) host–guest systems. Using constant pH molecular dynamics and a reference binding free energy that is taken either from experiment or from thermodynamic integration computations, the pH-dependent binding free energy is determined. This computational protocol accurately captures the large pKa shifts observed experimentally upon CB[7]:guest association and reproduces experimental binding free energies at different levels of pH. We show that incorrect assignment of fixed protonation states in free energy computations can give errors of >2 kcal/mol in these host–guest systems. Use of the methods presented here avoids such errors, thus suggesting their utility in computing proton-linked binding free energies for protein–ligand complexes. PMID:25134690
In-silico Investigation of Antitrypanosomal Phytochemicals from Nigerian Medicinal Plants
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
POSE Algorithms for Automated Docking
NASA Technical Reports Server (NTRS)
Heaton, Andrew F.; Howard, Richard T.
2011-01-01
POSE (relative position and attitude) can be computed in many different ways. Given a sensor that measures bearing to a finite number of spots corresponding to known features (such as a target) of a spacecraft, a number of different algorithms can be used to compute the POSE. NASA has sponsored the development of a flash LIDAR proximity sensor called the Vision Navigation Sensor (VNS) for use by the Orion capsule in future docking missions. This sensor generates data that can be used by a variety of algorithms to compute POSE solutions inside of 15 meters, including at the critical docking range of approximately 1-2 meters. Previously NASA participated in a DARPA program called Orbital Express that achieved the first automated docking for the American space program. During this mission a large set of high quality mated sensor data was obtained at what is essentially the docking distance. This data set is perhaps the most accurate truth data in existence for docking proximity sensors in orbit. In this paper, the flight data from Orbital Express is used to test POSE algorithms at 1.22 meters range. Two different POSE algorithms are tested for two different Fields-of-View (FOVs) and two different pixel noise levels. The results of the analysis are used to predict future performance of the POSE algorithms with VNS data.
Chaitanya V, Sundeep; Das, Madhusmita; Bhat, Pritesh; Ebenezer, Mannam
2015-10-01
The molecular basis for determination of resistance to anti-leprosy drugs is the presence of point mutations within the genes of Mycobacterium leprae (M. leprae) that encode active drug targets. The downstream structural and functional implications of these point mutations on drug targets were scarcely studied. In this study, we utilized computational tools to develop native and mutant protein models for 5 point mutations at codon positions 53 and 55 in 6-hydroxymethyl-7, 8-dihydropteroate synthase (DHPS) of M. leprae, an active target for dapsone encoded by folp1 gene, that confer resistance to dapsone. Molecular docking was performed to identify variations in dapsone interaction with mutant DHPS in terms of hydrogen bonding, hydrophobic interactions, and energy changes. Schrodinger Suite 2014-3 was used to build homology models and in performing molecular docking. An increase in volume of the binding cavities of mutant structures was noted when compared to native form indicating a weakening in interaction (60.7 Å(3) in native vs. 233.6 Å(3) in Thr53Ala, 659.9 Å(3) in Thr53Ile, 400 Å(3) for Thr53Val, 385 Å(3) for Pro55Arg, and 210 Å(3) for Pro55Leu). This was also reflected by changes in hydrogen bonds and decrease in hydrophobic interactions in the mutant models. The total binding energy (ΔG) decreased significantly in mutant forms when compared to the native form (-51.92 Kcal/mol for native vs. -35.64, -35.24, -46.47, -47.69, and -41.36 Kcal/mol for mutations Thr53Ala, Thr53Ile, Thr53Val, Pro55Arg, and Pro55Leu, respectively. In brief, this analysis provided structural and mechanistic insights to the degree of dapsone resistance contributed by each of these DHPS mutants in leprosy. © 2015 Wiley Periodicals, Inc.
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.
Liu, Ming; He, Lin; Hu, Xiaopeng; Liu, Peiqing; Luo, Hai-Bin
2010-12-01
The nociceptin/orphanin FQ receptor (NOP) has been implicated in a wide range of biological functions, including pain, anxiety, depression and drug abuse. Especially, its agonists have a great potential to be developed into anxiolytics. However, the crystal structure of NOP is still not available. In the present work, both structure-based and ligand-based modeling methods have been used to achieve a comprehensive understanding on 67N-substituted spiropiperidine analogues as NOP agonists. The comparative molecular-field analysis method was performed to formulate a reasonable 3D-QSAR model (cross-validated coefficient q(2)=0.819 and conventional r(2)=0.950), whose robustness and predictability were further verified by leave-eight-out, Y-randomization, and external test-set validations. The excellent performance of CoMFA to the affinity differences among these compounds was attributed to the contributions of electrostatic/hydrogen-bonding and steric/hydrophobic interactions, which was supported by the Surflex-Dock and CDOCKER molecular-docking simulations based on the 3D model of NOP built by the homology modeling method. The CoMFA contour maps and the molecular docking simulations were integrated to propose a binding mode for the spiropiperidine analogues at the binding site of NOP. Copyright © 2010 Elsevier Ltd. All rights reserved.
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.
InterPred: A pipeline to identify and model protein-protein interactions.
Mirabello, Claudio; Wallner, Björn
2017-06-01
Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Hassan, Mubashir; Shahzadi, Saba; Alashwal, Hany; Zaki, Nazar; Seo, Sung-Yum; Moustafa, Ahmed A
2018-05-22
Cas scaffolding protein family member 4 and protein tyrosine kinase 2 are signaling proteins, which are involved in neuritic plaques burden, neurofibrillary tangles, and disruption of synaptic connections in Alzheimer's disease. In the current study, a computational approach was employed to explore the active binding sites of Cas scaffolding protein family member 4 and protein tyrosine kinase 2 proteins and their significant role in the activation of downstream signaling pathways. Sequential and structural analyses were performed on Cas scaffolding protein family member 4 and protein tyrosine kinase 2 to identify their core active binding sites. Molecular docking servers were used to predict the common interacting residues in both Cas scaffolding protein family member 4 and protein tyrosine kinase 2 and their involvement in Alzheimer's disease-mediated pathways. Furthermore, the results from molecular dynamic simulation experiment show the stability of targeted proteins. In addition, the generated root mean square deviations and fluctuations, solvent-accessible surface area, and gyration graphs also depict their backbone stability and compactness, respectively. A better understanding of CAS and their interconnected protein signaling cascade may help provide a treatment for Alzheimer's disease. Further, Cas scaffolding protein family member 4 could be used as a novel target for the treatment of Alzheimer's disease by inhibiting the protein tyrosine kinase 2 pathway.
Basu, Sankar
2017-12-07
The complementarity plot (CP) is an established validation tool for protein structures, applicable to both globular proteins (folding) as well as protein-protein complexes (binding). It computes the shape and electrostatic complementarities (S m , E m ) for amino acid side-chains buried within the protein interior or interface and plots them in a two-dimensional plot having knowledge-based probabilistic quality estimates for the residues as well as for the whole structure. The current report essentially presents an upgraded version of the plot with the implementation of the advanced multi-dielectric functionality (as in Delphi version 6.2 or higher) in the computation of electrostatic complementarity to make the validation tool physico-chemically more realistic. The two methods (single- and multi-dielectric) agree decently in their resultant E m values, and hence, provisions for both methods have been kept in the software suite. So to speak, the global electrostatic balance within a well-folded protein and/or a well-packed interface seems only marginally perturbed by the choice of different internal dielectric values. However, both from theoretical as well as practical grounds, the more advanced multi-dielectric version of the plot is certainly recommended for potentially producing more reliable results. The report also presents a new methodology and a variant plot, namely CP dock , based on the same principles of complementarity specifically designed to be used in the docking of proteins. The efficacy of the method to discriminate between good and bad docked protein complexes has been tested on a recent state-of-the-art docking benchmark. The results unambiguously indicate that CP dock can indeed be effective in the initial screening phase of a docking scoring pipeline before going into more sophisticated and computationally expensive scoring functions. CP dock has been made available at https://github.com/nemo8130/CPdock . Graphical Abstract An example showing the efficacy of CP dock to be used in the initial screening phase of a protein-protein docking scoring pipeline.
Neveu, Emilie; Ritchie, David W; Popov, Petr; Grudinin, Sergei
2016-09-01
Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the precision of a very detailed data-driven model of the binding free energy used with a global and exhaustive rigid-body search space. As well as being accurate, our computations are among the fastest by virtue of the sparse representation of the pre-computed potentials and FFT-accelerated sampling techniques. Overall, this is the first demonstration of a FFT-accelerated docking method coupled with an arbitrary-shaped distance-dependent interaction potential. First, we present a novel learning process to compute data-driven distant-dependent pairwise potentials, adapted from our previous method used for rescoring of putative protein-protein binding poses. The potential coefficients are learned by combining machine-learning techniques with physically interpretable descriptors. Then, we describe the integration of the deduced potentials into a FFT-accelerated spherical sampling provided by the Hex library. Overall, on a training set of 163 heterodimers, PEPSI-Dock achieves a success rate of 91% mid-quality predictions in the top-10 solutions. On a subset of the protein docking benchmark v5, it achieves 44.4% mid-quality predictions in the top-10 solutions when starting from bound structures and 20.5% when starting from unbound structures. The method runs in 5-15 min on a modern laptop and can easily be extended to other types of interactions. https://team.inria.fr/nano-d/software/PEPSI-Dock sergei.grudinin@inria.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Fujimori, Mitsuki; Sogawa, Haruki; Ota, Shintaro; Karpov, Pavel; Shulga, Sergey; Blume, Yaroslav; Kurita, Noriyuki
2018-01-01
Filamentous temperature-sensitive Z (FtsZ) protein plays essential role in bacteria cell division, and its inhibition prevents Mycobacteria reproduction. Here we adopted curcumin derivatives as candidates of novel inhibitors and investigated their specific interactions with FtsZ, using ab initio molecular simulations based on protein-ligand docking, classical molecular mechanics and ab initio fragment molecular orbital (FMO) calculations. Based on FMO calculations, we specified the most preferable site of curcumin binding to FtsZ and highlighted the key amino acid residues for curcumin binding at an electronic level. The result will be useful for proposing novel inhibitors against FtsZ based on curcumin derivatives.
Shityakov, Sergey; Broscheit, Jens; Förster, Carola
2012-01-01
This paper attempts to predict and emphasize molecular interactions of dopamine, levodopa, and their derivatives (Dopimid compounds) containing 2-phenyl-imidazopyridine moiety with the α-cyclodextrin dimer in order to assess and improve drug delivery to the central nervous system. The molecular docking method is used to determine the energetic profiles, hydrogen bond formation, and hydrophobic effect of 14 host–guest complexes. The results show that the “chemical branching” represented by additional ethyl-acetate residue is energetically unfavorable and promotes a conformational shift due to the high root mean square deviation levels. This phenomenon is characterized by a low number of H-bonds and a significant decrease of the host–guest hydrophobic potential surface. Finally, the overall docking procedure presents a powerful rationale for screening and analyzing various sets of promising drug-like chemical compounds in the fields of supramolecular chemistry, molecular sensing, synthetic receptors, and nanobiotechnology. PMID:22811606
Ghorab, Mostafa M; Alsaid, Mansour S; El-Gaby, Mohamed S A; Elaasser, Mahmoud M; Nissan, Yassin M
2017-04-07
Various thiourea derivatives have been used as starting materials for compounds with better biological activities. Molecular modeling tools are used to explore their mechanism of action. A new series of thioureas were synthesized. Fluorinated pyridine derivative 4a showed the highest antimicrobial activity (with MIC values ranged from 1.95 to 15.63 µg/mL). Interestingly, thiadiazole derivative 4c and coumarin derivative 4d exhibited selective antibacterial activities against Gram positive bacteria. Fluorinated pyridine derivative 4a was the most active against HepG2 with IC50 value of 4.8 μg/mL. Molecular docking was performed on the active site of MK-2 with good results. Novel compounds were obtained with good anticancer and antibacterial activity especially fluorinated pyridine derivative 4a and molecular docking study suggest good activity as mitogen activated protein kinase-2 inhibitor. Graphical abstract Compound 4a in the active site of MK-2.
NASA Astrophysics Data System (ADS)
Dai, Duoqian; Zhou, Lu; Zhu, Xiaohong; You, Rong; Zhong, Liangliang
2017-06-01
MutT homolog 1 (MTH1), a nudix phosphohydrolase enzyme participates in the process of repairing of DNA damage by hydrolyzing oxidized deoxy-ribonucleoside triphosphate in cancer cells, is regarded as a potential target for anticancer therapy. In order to seek for promising inhibitor of MTH1, structured-based pharmacophore and 3D-QSAR pharmacophore hypotheses combine with the ADMET analysis and Lipinski's rule of five were used for screening the public molecules libraries (Asinex, Ibscreen and Natural). Then molecular docking studies were performed on screened hits via various docking programs (Glide SP, GOLD and Glide XP), five molecules with three scaffolds were picked out as potential inhibitors against MTH1. Eventually, 20 ns molecular dynamics simulation was implemented on the potential inhibitors. The RMSD (Root Mean Square Deviation) values were used to illustrate bind stability between potential molecules and MTH1. Therefore, the five hits may be considered as promising MTH1 inhibitors by all above studies.
Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis
NASA Astrophysics Data System (ADS)
Almerico, Anna Maria; Tutone, Marco; Lauria, Antonino
2008-05-01
In this paper we describe a comparative analysis between multivariate and docking methods in the study of the drug resistance to the reverse transcriptase and the protease inhibitors. In our early papers we developed a simple but efficient method to evaluate the features of compounds that are less likely to trigger resistance or are effective against mutant HIV strains, using the multivariate statistical procedures PCA and DA. In the attempt to create a more solid background for the prediction of susceptibility or resistance, we carried out a comparative analysis between our previous multivariate approach and molecular docking study. The intent of this paper is not only to find further support to the results obtained by the combined use of PCA and DA, but also to evidence the structural features, in terms of molecular descriptors, similarity, and energetic contributions, derived from docking, which can account for the arising of drug-resistance against mutant strains.
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).
Lessons in molecular recognition. 2. Assessing and improving cross-docking accuracy.
Sutherland, Jeffrey J; Nandigam, Ravi K; Erickson, Jon A; Vieth, Michal
2007-01-01
Docking methods are used to predict the manner in which a ligand binds to a protein receptor. Many studies have assessed the success rate of programs in self-docking tests, whereby a ligand is docked into the protein structure from which it was extracted. Cross-docking, or using a protein structure from a complex containing a different ligand, provides a more realistic assessment of a docking program's ability to reproduce X-ray results. In this work, cross-docking was performed with CDocker, Fred, and Rocs using multiple X-ray structures for eight proteins (two kinases, one nuclear hormone receptor, one serine protease, two metalloproteases, and two phosphodiesterases). While average cross-docking accuracy is not encouraging, it is shown that using the protein structure from the complex that contains the bound ligand most similar to the docked ligand increases docking accuracy for all methods ("similarity selection"). Identifying the most successful protein conformer ("best selection") and similarity selection substantially reduce the difference between self-docking and average cross-docking accuracy. We identify universal predictors of docking accuracy (i.e., showing consistent behavior across most protein-method combinations), and show that models for predicting docking accuracy built using these parameters can be used to select the most appropriate docking method.
LaBute, Montiago X; Zhang, Xiaohua; Lenderman, Jason; Bennion, Brian J; Wong, Sergio E; Lightstone, Felice C
2014-01-01
Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number of CPUs to tens of thousands of protein targets and millions of potential drug candidates.
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.
Scafuri, Bernardina; Marabotti, Anna; Carbone, Virginia; Minasi, Paola; Dotolo, Serena; Facchiano, Angelo
2016-01-01
We investigated the potential role of apple phenolic compounds in human pathologies by integrating chemical characterization of phenolic compounds in three apple varieties, computational approaches to identify potential protein targets of the compounds, bioinformatics analyses on data from public archive of gene expression data, and functional analyses to hypothesize the effects of the selected compounds in molecular pathways. Starting by the analytic characterization of phenolic compounds in three apple varieties, i.e. Annurca, Red Delicious, and Golden Delicious, we used computational approaches to verify by reverse docking the potential protein targets of the identified compounds. Direct docking validation of the potential protein-ligand interactions has generated a short list of human proteins potentially bound by the apple phenolic compounds. By considering the known chemo-preventive role of apple antioxidants’ extracts against some human pathologies, we performed a functional analysis by comparison with experimental gene expression data and interaction networks, obtained from public repositories. The results suggest the hypothesis that chemo-preventive effects of apple extracts in human pathologies, in particular for colorectal cancer, may be the interference with the activity of nucleotide metabolism and methylation enzymes, similarly to some classes of anticancer drugs. PMID:27587238
Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran
2015-02-06
Gaining access to sequence and structure information of telomere binding proteins helps in understanding the essential biological processes involve in conserved sequence specific interaction between DNA and the proteins. Rice telomere binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix turn helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain but till now there is very less communication on the in silico studies of these complete proteins.Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK web server.Digging up all the facts about the proteins it was reveled that around 120 amino acids in the tail part was showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicates the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and Energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.
Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran
2015-09-01
Gaining access to sequence and structure information of telomere-binding proteins helps in understanding the essential biological processes involve in conserved sequence-specific interaction between DNA and the proteins. Rice telomere-binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix-turn-helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain, but till now there is very less communication on the in silico studies of these complete proteins. Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK Web server. By digging up all the facts about the proteins, it was revealed that around 120 amino acids in the tail part were showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicate the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA-binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.
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.
Docking and molecular dynamics simulation of quinone compounds with trypanocidal activity.
de Molfetta, Fábio Alberto; de Freitas, Renato Ferreira; da Silva, Albérico Borges Ferreira; Montanari, Carlos Alberto
2009-10-01
In this work, two different docking programs were used, AutoDock and FlexX, which use different types of scoring functions and searching methods. The docking poses of all quinone compounds studied stayed in the same region in the trypanothione reductase. This region is a hydrophobic pocket near to Phe396, Pro398 and Leu399 amino acid residues. The compounds studied displays a higher affinity in trypanothione reductase (TR) than glutathione reductase (GR), since only two out of 28 quinone compounds presented more favorable docking energy in the site of human enzyme. The interaction of quinone compounds with the TR enzyme is in agreement with other studies, which showed different binding sites from the ones formed by cysteines 52 and 58. To verify the results obtained by docking, we carried out a molecular dynamics simulation with the compounds that presented the highest and lowest docking energies. The results showed that the root mean square deviation (RMSD) between the initial and final pose were very small. In addition, the hydrogen bond pattern was conserved along the simulation. In the parasite enzyme, the amino acid residues Leu399, Met400 and Lys402 are replaced in the human enzyme by Met406, Tyr407 and Ala409, respectively. In view of the fact that Leu399 is an amino acid of the Z site, this difference could be explored to design selective inhibitors of TR.
Aliebrahimi, Shima; Montasser Kouhsari, Shideh; Ostad, Seyed Nasser; Arab, Seyed Shahriar; Karami, Leila
2018-06-01
c-Met receptor tyrosine kinase is a proto-oncogene whose aberrant activation is attributed to a lower rate of survival in most cancers. Natural product-derived inhibitors known as "fourth generation inhibitors" constitute more than 60% of anticancer drugs. Furthermore, consensus docking approach has recently been introduced to augment docking accuracy and reduce false positives during a virtual screening. In order to obtain novel small-molecule Met inhibitors, consensus docking approach was performed using Autodock Vina and Autodock 4.2 to virtual screen Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database against active and inactive conformation of c-Met kinase domain structure. Two hit molecules that were in line with drug-likeness criteria, desired docking score, and binding pose were subjected to molecular dynamics simulations to elucidate intermolecular contacts in protein-ligand complexes. Analysis of molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area studies showed that ZINC08234189 is a plausible inhibitor for the active state of c-Met, whereas ZINC03871891 may be more effective toward active c-Met kinase domain compared to the inactive form due to higher binding energy. Our analysis showed that both the hit molecules formed hydrogen bonds with key residues of the hinge region (P1158, M1160) in the active form, which is a hallmark of kinase domain inhibitors. Considering the pivotal role of HGF/c-Met signaling in carcinogenesis, our results propose ZINC08234189 and ZINC03871891 as the therapeutic options to surmount Met-dependent cancers.
2007-04-01
optimization methodology we introduce. State-of-the-art protein - protein docking approaches start by identifying conformations with good surface /chemical com...side-chains on the interface ). The protein - protein docking literature (e.g., [8] and the references therein) is predominantly treating the docking...mations by various measures of surface complementarity which can be efficiently computed using fast Fourier correlation tech- niques (FFTs). However, when
Du, Ran-Feng; Zhang, Xiao-Hua; Ye, Xiao-Tong; Yu, Wen-Kang; Wang, Yun
2016-07-01
Dampness evil is the source of all diseases, which is easy to cause disease and promote aging, while aging could also promote the occurence and development of diseases. In this paper, the relationship between the dampness evil and aging would be discussed, to find the anti-aging active ingredients in traditional Chinese medicine (TCM), and analyze the anti-aging mechanism of dampness eliminating drug. Molecular docking technology was used, with aging-related mammalian target of rapamycin as the docking receptors, and chemical components of Fuling, Sangzhi, Mugua, Yiyiren and Houpo as the docking molecules, to preliminarily screen the anti-aging active ingredients in dampness eliminating drug. Through the comparison with active drugs already on the market (temsirolimus and everolimus), 12 kinds of potential anti-aging active ingredients were found, but their drug gability still needs further study. The docking results showed that various components in the dampness eliminating drug can play anti-aging activities by acting on mammalian target of rapamycin. This result provides a new thought and direction for the method of delaying aging by eliminating dampness. Copyright© by the Chinese Pharmaceutical Association.
Chen, Jinfeng; Wang, Jinlong; Lu, Yingyuan; Zhao, Shaoyang; Yu, Qian; Wang, Xuemei; Tu, Pengfei; Zeng, Kewu; Jiang, Yong
2018-05-01
Neuroinflammation is a main factor in the pathogenesis of neurodegenerative diseases, such as Alzheimer disease. Our previous studies indicated that the modified Wuziyanzong Prescription (MWP) can suppress neuroinflammatory responses via nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinases (MAPKs) signaling pathways. However, the anti-neuroinflammatory components of MWP remain unclear. Herein, a target-directed molecular docking fingerprint (TMDF) strategy, via integrating the chemical profiling and molecular docking approaches, was developed to identify the potential anti-neuroinflammatory components of MWP. First, as many as 120 possible structures, including 49 flavonoids, 28 phenylpropionic acids, 18 amides, 10 carotenoids, eight phenylethanoid glycosides, four lignans, two iridoids, and one triterpenoid were deduced by the source attribution and structural classification-assisted strategy. Then, their geometries were docked against five major targets of the NF-κB and MAPKs signaling cascades, including p38-α, IKKβ, ERK1, ERK2, and TRAF6. The docking results revealed diverse contributions of different components towards the protein targets. Collectively, prenylated flavonoids showed intensive or moderate anti-neuroinflammatory activities, while phenylpropanoids, amides, phenylethanoid glycosides, lignans, and triterpenoids exhibited moderate or weak anti-neuroinflammatory effects. The anti-neuroinflammatory activities of four retrieved prenylated flavonoids were tested by Western blotting assay, and the results mostly agreed with those predicted by the docking method. These gained information demonstrates that the established TMDF strategy could be a rapid and feasible methodology to investigate the potential active components in herbal compound prescriptions. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
El-Azab, Adel S.; Mary, Y. Sheena; Mary, Y. Shyma; Panicker, C. Yohannan; Abdel-Aziz, Alaa A.-M.; El-Sherbeny, Magda A.; Armaković, Stevan; Armaković, Sanja J.; Van Alsenoy, Christian
2017-04-01
In this work, spectroscopic characterization of 2-(2-(4-oxo-3-phenethyl-3,4-dihydroquinazolin-2-ylthio)ethyl)isoindoline-1,3-dione have been obtained with experimentally and theoretically. Complete assignments of fundamental vibrations were performed on the basis of the potential energy distribution of the vibrational modes and good agreement between the experimental and scaled wavenumbers has been achieved. Frontier molecular orbitals have been used as indicators of stability and reactivity. Intramolecular interactions have been investigated by NBO analysis. The dipole moment, linear polarizability and first and second order hyperpolarizability values were also computed. In order to determine molecule sites prone to electrophilic attacks DFT calculations of average local ionization energy (ALIE) and Fukui functions have been performed as well. Intra-molecular non-covalent interactions have been determined and analyzed by the analysis of charge density. Stability of title molecule have also been investigated from the aspect of autoxidation, by calculations of bond dissociation energies (BDE), and hydrolysis, by calculations of radial distribution functions after molecular dynamics (MD) simulations. In order to assess the biological potential of the title compound a molecular docking study towards breast cancer type 2 complex has been performed.
Efficient Relaxation of Protein-Protein Interfaces by Discrete Molecular Dynamics Simulations.
Emperador, Agusti; Solernou, Albert; Sfriso, Pedro; Pons, Carles; Gelpi, Josep Lluis; Fernandez-Recio, Juan; Orozco, Modesto
2013-02-12
Protein-protein interactions are responsible for the transfer of information inside the cell and represent one of the most interesting research fields in structural biology. Unfortunately, after decades of intense research, experimental approaches still have difficulties in providing 3D structures for the hundreds of thousands of interactions formed between the different proteins in a living organism. The use of theoretical approaches like docking aims to complement experimental efforts to represent the structure of the protein interactome. However, we cannot ignore that current methods have limitations due to problems of sampling of the protein-protein conformational space and the lack of accuracy of available force fields. Cases that are especially difficult for prediction are those in which complex formation implies a non-negligible change in the conformation of the interacting proteins, i.e., those cases where protein flexibility plays a key role in protein-protein docking. In this work, we present a new approach to treat flexibility in docking by global structural relaxation based on ultrafast discrete molecular dynamics. On a standard benchmark of protein complexes, the method provides a general improvement over the results obtained by rigid docking. The method is especially efficient in cases with large conformational changes upon binding, in which structure relaxation with discrete molecular dynamics leads to a predictive success rate double that obtained with state-of-the-art rigid-body docking.
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.
NASA Astrophysics Data System (ADS)
Sureshkumar, B.; Mary, Y. Sheena; Resmi, K. S.; Panicker, C. Yohannan; Armaković, Stevan; Armaković, Sanja J.; Van Alsenoy, C.; Narayana, B.; Suma, S.
2018-03-01
Two 8-hydroxyquinoline derivatives, 5,7-dichloro-8-hydroxyquinoline (57DC8HQ) and 5-chloro-7-iodo-8-hydroxy quinoline (5CL7I8HQ) have been investigated in details by means of spectroscopic characterization and computational molecular modelling techniques. FT-IR and FT-Raman experimental spectroscopic approaches have been utilized in order to obtain detailed spectroscopic signatures of title compounds, while DFT calculations have been used in order to visualize and assign vibrations. The computed values of dipole moment, polarizability and hyperpolarizability indicate that the title molecules exhibit NLO properties. The evaluated HOMO and LUMO energies demonstrate the chemical stability of the molecules. NBO analysis is made to study the stability of the molecules arising from hyperconjugative interactions and charge delocalization. DFT calculations have been also used jointly with MD simulations in order to investigate in details global and local reactivity properties of title compounds. Also, molecular docking has been also used in order to investigate affinity of title compounds against decarboxylase inhibitor and quinoline derivatives can be a lead compounds for developing new antiparkinsonian drug.
Space tug automatic docking control study. LOCDOK users manual
NASA Technical Reports Server (NTRS)
1974-01-01
A users's manual for the computer programs involved in a study of the space tug docking simulation is presented. The following subjects are considered: (1) subroutine narratives, (2) program elements, (3) system subroutines, and (4) Univac 1108 cross reference listing. The functional and operational requirements for the computer programming are explained.
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.
NASA Astrophysics Data System (ADS)
Zhong, M.; Long, R. Q.; Wang, Y. H.; Chen, C. L.
2018-05-01
The quenching mechanism between chelerythrine (CHE) and keyhole limpet hemocyanin (KLH) was investigated using fluorescence spectroscopy and molecular docking. The experiments were conducted at three different temperatures (293, 298, and 303 K). The results revealed that the intrinsic fluorescence of KLH was strongly quenched by CHE through a static quenching mechanism. The thermodynamic parameters (ΔG, ΔH, and ΔS) of the interaction were calculated, indicating that the interaction between CHE and KLH was spontaneous and that van der Waals forces and hydrogen bond formation played major roles in the binding process. The intrinsic fluorescence of the tyrosine and tryptophan residues in KLH was studied by synchronous fluorescence, which suggested that CHE changed the conformation of KLH. Finally, molecular docking was used to obtain detailed information on the binding sites and binding affinities between CHE and KLH.
NASA Astrophysics Data System (ADS)
Ikhlas, Shoeb; Ahmad, Masood
2018-02-01
Guggulsterone, a sterol found in plants is used as an ayurvedic medicine for many diseases such as obesity, internal tumors, ulcers etc. E and Z are two isoforms of guggulsterone, wherein guggulsterone-E (GUGE) has also been shown to have anticancer potential. Most of the anticancer drugs target nucleic acids. Therefore, we studied the mode of interaction between ctDNA and GUGE using UV-Vis, fluorescence and CD spectroscopy, isothermal calorimetry along with molecular docking studies. Hoechst 3325, ethidium bromide and rhodamine-B displacement experiments confirms that GUGE binds in the minor groove of DNA. ITC results further suggest these interactions to be feasible and spontaneous with hydrogen bond formation and van der waals interactions. Lastly, molecular docking also suggests GUGE to be a minor groove binder interacting through a single hydrogen bond formation between OH group of GUGE and nitrogen (N3) of adenosine (A6).
Salmas, Ramin Ekhteiari; Mestanoglu, Mert; Unlu, Ayhan; Yurtsever, Mine; Durdagi, Serdar
2016-11-01
Mutated form (G52E) of diphtheria toxin (DT) CRM197 is an inactive and nontoxic enzyme. Here, we provided a molecular insight using comparative molecular dynamics (MD) simulations to clarify the influence of a single point mutation on overall protein and active-site loop. Post-processing MD analysis (i.e. stability, principal component analysis, hydrogen-bond occupancy, etc.) is carried out on both wild and mutated targets to investigate and to better understand the mechanistic differences of structural and dynamical properties on an atomic scale especially at nicotinamide adenine dinucleotide (NAD) binding site when a single mutation (G52E) happens at the DT. In addition, a docking simulation is performed for wild and mutated forms. The docking scoring analysis and docking poses results revealed that mutant form is not able to properly accommodate the NAD molecule.
NASA Astrophysics Data System (ADS)
Shahabadi, Nahid; Fili, Soraya Moradi
2014-01-01
The interaction of mesalamine (5-aminosalicylic acid (5-ASA)) with bovine serum albumin (BSA) was investigated by fluorescence quenching, absorption spectroscopy, circular dichroism (CD) techniques, and molecular docking. Thermodynamic parameters (ΔH < 0 and ΔS 0) indicated that the hydrogen bond and electrostatic forces played the major role in the binding of 5-ASA to BSA. The results of CD and UV-vis spectroscopy showed that the binding of this drug to BSA induces some conformational changes in BSA. Displacement experiments predicted that the binding of 5-ASA to BSA is located within domain III, Sudlows site 2, that these observations were substantiated by molecular docking studies. In addition, the docking result shows that the 5-ASA in its anionic form mainly interacts with Gln-416 residue through one hydrogen bond between H atom of 5-ASA anion and the adjacent O atom of the hydroxyl group of Gln-416.
Ikhlas, Shoeb; Usman, Afia; Ahmad, Masood
2018-04-24
Interaction studies of bisphenol analogues; biphenol-A (BPA), bisphenol-B (BPB), and bisphenol-F (BPF) with bovine serum albumin (BSA) were performed using multi-spectroscopic and molecular docking studies at the protein level. The mechanism of binding of bisphenols with BSA was dynamic in nature. SDS refolding experiments demonstrated no stabilization of BSA structure denatured by BPB, however, BSA denatured by BPA and BPF was found to get stabilized. Also, CD spectra and molecular docking studies revealed that BPB bound more strongly and induced more conformational changes in BSA in comparison to BPA. Hence, this study throws light on the replacement of BPA by its analogues and whether the replacement is associated with a possible risk, raising a doubt that perhaps BPB is not a good substitute of BPA.
Bandopadhyay, Pathikrit; Halder, Soma; Sarkar, Mrinmoy; Kumar Bhunia, Sujay; Dey, Sananda; Gomes, Antony; Giri, Biplab
2016-01-01
A 6.76 kDa molecular weight cardio and cytotoxic protein of 60 amino acids in length called NK-CT1, was purified from the venom of Indian monocellate cobra (Naja kaouthia) by ion-exchange chromatography and HPLC as described in our earlier report. Therefore it is of interest to utlize the sequence of NK-CT1 for further functional inference using molecular modeling and docking. Thus homology model of NK-CT1 is described in this report. The anti-proliferative activity of the protein, binding with human DNA topoisomerase-II alpha was demonstrated using docking data with AUTODOCK and AUTODOCK MGL tools. Data shows that M26, V27 and S28 of NK-CT1 is in close contact with the nucleotides of the oligonucleotide, bound with topoisomerase-II alpha complex. PMID:28149043
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.
Ensemble-based docking: From hit discovery to metabolism and toxicity predictions
Evangelista, Wilfredo; Weir, Rebecca; Ellingson, Sally; ...
2016-07-29
The use of ensemble-based docking for the exploration of biochemical pathways and toxicity prediction of drug candidates is described. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.
Kalathiya, Umesh; Padariya, M; Baginski, M
2016-11-01
Pancreatic lipase is a potential therapeutic target to treat diet-induced obesity in humans, as obesity-related diseases continue to be a global problem. Despite intensive research on finding potential inhibitors, very few compounds have been introduced to clinical studies. In this work, new chemical scaffold 1H-indene-(1,3,5,6)-tetrol was proposed using knowledge-based approach, and 36 inhibitors were derived by modifying its functional groups at different positions in scaffold. To explore binding affinity and interactions of ligands with protein, CDOCKER and AutoDock programs were used for molecular docking studies. Analyzing results of rigid and flexible docking algorithms, inhibitors C_12, C_24, and C_36 were selected based on different properties and high predicted binding affinities for further analysis. These three inhibitors have different moieties placed at different functional groups in scaffold, and to characterize structural rationales for inhibitory activities of compounds, molecular dynamics simulations were performed (500 nSec). It has been shown through simulations that two structural fragments (indene and indole) in inhibitor can be treated as isosteric structures and their position at binding cleft can be replaced by each other. Taking into account these information, two lines of inhibitors can further be developed, each line based on a different core scaffold, that is, indene/indole. © 2015 International Union of Biochemistry and Molecular Biology, Inc.
NASA Astrophysics Data System (ADS)
Mohamed Asath, R.; Premkumar, R.; Mathavan, T.; Milton Franklin Benial, A.
2017-09-01
Potential energy surface scan was performed and the most stable molecular structure of the N,N-di-tert-butoxycarbonyl (Boc)-2-amino pyridine (DBAP) molecule was predicted. The most stable molecular structure of the molecule was optimized using B3LYP method with cc-pVTZ basis set. Anticancer activity of the DBAP molecule was evaluated by molecular docking analysis. The structural parameters and vibrational wavenumbers were calculated for the optimized molecular structure. The experimental and theoretical wavenumbers were assigned and compared. Ultraviolet-Visible spectrum was simulated and validated experimentally. The molecular electrostatic potential surface was simulated and Fukui function calculations were also carried out to investigate the reactive nature of the DBAP molecule. The natural bond orbital analysis was also performed to probe the intramolecular interactions and confirm the bioactivity of the DBAP molecule. The molecular docking analysis reveals the better inhibitory nature of the DBAP molecule against the epidermal growth factor receptor (EGFR) protein which causes lung cancer. Hence, the present study unveils the structural and bioactive nature of the title molecule. The DBAP molecule was identified as a potential inhibitor against the lung cancer which may be useful in further development of drug designing in the treatment of lung cancer.
Six degree of freedom FORTRAN program, ASTP docking dynamics, users guide
NASA Technical Reports Server (NTRS)
Mount, G. O., Jr.; Mikhalkin, B.
1974-01-01
The digital program ASTP Docking Dynamics as outlined is intended to aid the engineer using the program to determine the docking system loads and attendant vehicular motion resulting from docking two vehicles that have an androgynous, six-hydraulic-attenuator, guide ring, docking interface similar to that designed for the Apollo/Soyuz Test Project (ASTP). This program is set up to analyze two different vehicle combinations: the Apollo CSM docking to Soyuz and the shuttle orbiter docking to another orbiter. The subroutine modifies the vehicle control systems to describe one or the other vehicle combinations; the rest of the vehicle characteristics are changed by input data. To date, the program has been used to predict and correlate ASTP docking loads and performance with docking test program results from dynamic testing. The program modified for use on IBM 360 computers. Parts of the original docking system equations in the areas of hydraulic damping and capture latches are modified to better describe the detail design of the ASTP docking system.
Replica Exchange Improves Sampling in Low-Resolution Docking Stage of RosettaDock
Zhang, Zhe; Lange, Oliver F.
2013-01-01
Many protein-protein docking protocols are based on a shotgun approach, in which thousands of independent random-start trajectories minimize the rigid-body degrees of freedom. Another strategy is enumerative sampling as used in ZDOCK. Here, we introduce an alternative strategy, ReplicaDock, using a small number of long trajectories of temperature replica exchange. We compare replica exchange sampling as low-resolution stage of RosettaDock with RosettaDock's original shotgun sampling as well as with ZDOCK. A benchmark of 30 complexes starting from structures of the unbound binding partners shows improved performance for ReplicaDock and ZDOCK when compared to shotgun sampling at equal or less computational expense. ReplicaDock and ZDOCK consistently reach lower energies and generate significantly more near-native conformations than shotgun sampling. Accordingly, they both improve typical metrics of prediction quality of complex structures after refinement. Additionally, the refined ReplicaDock ensembles reach significantly lower interface energies and many previously hidden features of the docking energy landscape become visible when ReplicaDock is applied. PMID:24009670
Braun, Glaucia H; Jorge, Daniel M M; Ramos, Henrique P; Alves, Raquel M; da Silva, Vinicius B; Giuliatti, Silvana; Sampaio, Suley Vilela; Taft, Carlton A; Silva, Carlos H T P
2008-02-01
Monoamine oxidase is a flavoenzyme bound to the mitochondrial outer membranes of the cells, which is responsible for the oxidative deamination of neurotransmitter and dietary amines. It has two distinct isozymic forms, designated MAO-A and MAO-B, each displaying different substrate and inhibitor specificities. They are the well-known targets for antidepressant, Parkinson's disease, and neuroprotective drugs. Elucidation of the x-ray crystallographic structure of MAO-B has opened the way for the molecular modeling studies. In this work we have used molecular modeling, density functional theory with correlation, virtual screening, flexible docking, molecular dynamics, ADMET predictions, and molecular interaction field studies in order to design new molecules with potential higher selectivity and enzymatic inhibitory activity over MAO-B.
Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun
2011-01-01
Aurora kinases have emerged as attractive targets for the design of anticancer drugs. 3D-QSAR (comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA)) and Surflex-docking studies were performed on a series of pyrrole-indoline-2-ones as Aurora A inhibitors. The CoMFA and CoMSIA models using 25 inhibitors in the training set gave r2cv values of 0.726 and 0.566, and r2 values of 0.972 and 0.984, respectively. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to rationalize the key structural requirements responsible for the activity. Surflex-docking studies revealed that the sulfo group, secondary amine group on indolin-2-one, and carbonyl of 6,7-dihydro-1H-indol-4(5H)-one groups were significant for binding to the receptor, and some essential features were also identified. Based on the 3D-QSAR and docking results, a set of new molecules with high predicted activities were designed. PMID:21673910
Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun
2011-01-01
Aurora kinases have emerged as attractive targets for the design of anticancer drugs. 3D-QSAR (comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA)) and Surflex-docking studies were performed on a series of pyrrole-indoline-2-ones as Aurora A inhibitors. The CoMFA and CoMSIA models using 25 inhibitors in the training set gave r(2) (cv) values of 0.726 and 0.566, and r(2) values of 0.972 and 0.984, respectively. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to rationalize the key structural requirements responsible for the activity. Surflex-docking studies revealed that the sulfo group, secondary amine group on indolin-2-one, and carbonyl of 6,7-dihydro-1H-indol-4(5H)-one groups were significant for binding to the receptor, and some essential features were also identified. Based on the 3D-QSAR and docking results, a set of new molecules with high predicted activities were designed.
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.
Predicting bioactive conformations and binding modes of macrocycles
NASA Astrophysics Data System (ADS)
Anighoro, Andrew; de la Vega de León, Antonio; Bajorath, Jürgen
2016-10-01
Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein-protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.
Docking analysis of verteporfin with YAP WW domain.
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.
A web interface for easy flexible protein-protein docking with ATTRACT.
de Vries, Sjoerd J; Schindler, Christina E M; Chauvot de Beauchêne, Isaure; Zacharias, Martin
2015-02-03
Protein-protein docking programs can give valuable insights into the structure of protein complexes in the absence of an experimental complex structure. Web interfaces can facilitate the use of docking programs by structural biologists. Here, we present an easy web interface for protein-protein docking with the ATTRACT program. While aimed at nonexpert users, the web interface still covers a considerable range of docking applications. The web interface supports systematic rigid-body protein docking with the ATTRACT coarse-grained force field, as well as various kinds of protein flexibility. The execution of a docking protocol takes up to a few hours on a standard desktop computer. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Naringenin and quercetin--potential anti-HCV agents for NS2 protease targets.
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.
Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra
2013-01-01
Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ PMID:24339765
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.
NASA Astrophysics Data System (ADS)
Sheena Mary, Y.; Al-Shehri, Mona M.; Jalaja, K.; Al-Omary, Fatmah A. M.; El-Emam, Ali A.; Yohannan Panicker, C.; Armaković, Stevan; Armaković, Sanja J.; Temiz-Arpaci, Ozlem; Van Alsenoy, C.
2017-04-01
Antimicrobial active 5-[(4-nitrophenyl)acetamido]-2-(4-tert-butylphenyl)benzoxazole (NATPB) was synthesized and observed IR, Raman bands are compared with the theoretically predicted wave numbers. In the IR spectrum the NH stretching wave number splits into a doublet with a noted difference and is red shifted from the computed value, which indicates the weakening of NH bond resulting in proton transfer to the neighbouring oxygen atom. The HOMO-LUMO plots reveal the charge transfer in the molecular system through the conjugated paths. The electrophilic and nucleophilic reactive sites are identified from the MEP plot. Mapping of average local ionization energy (ALIE) values to the electron density surface served us as a tool for prediction of molecule sites possibly prone to electrophilic attacks. Other important reactive centres of the title molecule were detected by calculations of Fukui functions. Calculations of bond dissociation energies (BDE) for hydrogen abstraction were used in order to assess whether the NATPB molecules is prone to autoxidation mechanism or not, while BDE of the remaining single acyclic bonds were used in order to determine the weakest bond. Interaction properties with water were investigated by molecular dynamics (MD) simulations and calculations of radial distribution functions (RDFs). The compound possessed broad spectrum activity against all of the tested Gram-positive and Gram-negative bacteria and yeasts, their minimum inhibitory concentrations (MICs) ranging between 32 and 128 μg/ml. The compound exhibited significant antibacterial activity (32 μg/ml) against an antibiotic resistant E. faecalis isolate, at same potency with the compared standard drugs vancomycin and gentamycin sulfate. The molecular docking studies show that the compound might exhibit inhibitory activity against CDK inhibitors.
NASA Astrophysics Data System (ADS)
Jayasheela, K.; Al-Wahaibi, Lamya H.; Periandy, S.; Hassan, Hanan M.; Sebastian, S.; Xavier, S.; Daniel, Joseph C.; El-Emam, Ali A.; Attia, Mohamed I.
2018-05-01
The promising anti-Candida agent, 4-chlorophenyl ({[1E-3(1H-imidazole-1-yl)-1-phenylpropylidene}oxy)methanone (4-CPIPM) was comprehensively characterized by FT-IR, FT-Raman, UV, as well as 1H and 13C spectroscopic techniques. The theoretical calculations in the current study utilized Gaussian 09 W software with DFT approach of the B3LYP/6-311++G(d,p) method. The experimental X-ray diffraction data of the 4-CPIPM molecule were compared with the optimized structure and showed well agreement. Intermolecular electronic interactions and their stabilization energies have been analyzed by natural bond orbital method. Potential energy distribution confirmed the normal fundamental mode of vibration with the aid of MOLVIB software. The chemical shift values of the 1H and 13C spectra of the title compound were computed using gauge independent atomic orbital and the results were compared with the experimental values. The time-dependent density function theory method was used to predict the electronic, absorption wavelength and frontier molecular orbital energies. The HOMO-LUMO plots proved the charge transfer in the molecular system of the title compound through conjugated paths. The molecular electrostatic potential analysis provided the electrophilic and nucleophilic reactive sites in the title molecule which have been analyzed using Hirshfeld surface and two dimensions fingerprint plots. Non covalent interactions were also studied using reduced density gradient analysis and color filled electron density diagram. Molecular docking studies of the ligand-protein interactions along with their binding energies were carried out aiming to explain the potent anti-Candida activity of the title molecule.
Vadloori, Bharadwaja; Sharath, A K; Prabhu, N Prakash; Maurya, Radheshyam
2018-04-16
Present in silico study was carried out to explore the mode of inhibition of Leishmania donovani dihydrofolate reductase-thymidylate synthase (Ld DHFR-TS) enzyme by Withaferin-A, a withanolide isolated from Withania somnifera. Withaferin-A (WA) is known for its profound multifaceted properties, but its antileishmanial activity is not well understood. The parasite's DHFR-TS enzyme is diverse from its mammalian host and could be a potential drug target in parasites. A 3D model of Ld DHFR-TS enzyme was built and verified using Ramachandran plot and SAVES tools. The protein was docked with WA-the ligand, methotrexate (MTX)-competitive inhibitor of DHFR, and dihydrofolic acid (DHFA)-substrate for DHFR-TS. Molecular docking studies reveal that WA competes for active sites of both Hu DHFR and TS enzymes whereas it binds to a site other than active site in Ld DHFR-TS. Moreover, Lys 173 residue of DHFR-TS forms a H-bond with WA and has higher binding affinity to Ld DHFR-TS than Hu DHFR and Hu TS. The MD simulations confirmed the H-bonding interactions were stable. The binding energies of WA with Ld DHFR-TS were calculated using MM-PBSA. Homology modelling, molecular docking and MD simulations of Ld DHFR-TS revealed that WA could be a potential anti-leishmanial drug.
3D-QSAR and docking studies of flavonoids as potent Escherichia coli inhibitors
Fang, Yajing; Lu, Yulin; Zang, Xixi; Wu, Ting; Qi, XiaoJuan; Pan, Siyi; Xu, Xiaoyun
2016-01-01
Flavonoids are potential antibacterial agents. However, key substituents and mechanism for their antibacterial activity have not been fully investigated. The quantitative structure-activity relationship (QSAR) and molecular docking of flavonoids relating to potent anti-Escherichia coli agents were investigated. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were developed by using the pIC50 values of flavonoids. The cross-validated coefficient (q2) values for CoMFA (0.743) and for CoMSIA (0.708) were achieved, illustrating high predictive capabilities. Selected descriptors for the CoMFA model were ClogP (logarithm of the octanol/water partition coefficient), steric and electrostatic fields, while, ClogP, electrostatic and hydrogen bond donor fields were used for the CoMSIA model. Molecular docking results confirmed that half of the tested flavonoids inhibited DNA gyrase B (GyrB) by interacting with adenosine-triphosphate (ATP) pocket in a same orientation. Polymethoxyl flavones, flavonoid glycosides, isoflavonoids changed their orientation, resulting in a decrease of inhibitory activity. Moreover, docking results showed that 3-hydroxyl, 5-hydroxyl, 7-hydroxyl and 4-carbonyl groups were found to be crucial active substituents of flavonoids by interacting with key residues of GyrB, which were in agreement with the QSAR study results. These results provide valuable information for structure requirements of flavonoids as antibacterial agents. PMID:27049530
Jarmuła, Adam; Wilk, Piotr; Maj, Piotr; Ludwiczak, Jan; Dowierciał, Anna; Banaszak, Katarzyna; Rypniewski, Wojciech; Cieśla, Joanna; Dąbrowska, Magdalena; Frączyk, Tomasz; Bronowska, Agnieszka K; Jakowiecki, Jakub; Filipek, Sławomir; Rode, Wojciech
2017-10-01
Three crystal structures are presented of nematode thymidylate synthases (TS), including Caenorhabditis elegans (Ce) enzyme without ligands and its ternary complex with dUMP and Raltitrexed, and binary complex of Trichinella spiralis (Ts) enzyme with dUMP. In search of differences potentially relevant for the development of species-specific inhibitors of the nematode enzyme, a comparison was made of the present Ce and Ts enzyme structures, as well as binary complex of Ce enzyme with dUMP, with the corresponding mammalian (human, mouse and rat) enzyme crystal structures. To complement the comparison, tCONCOORD computations were performed to evaluate dynamic behaviors of mammalian and nematode TS structures. Finally, comparative molecular docking combined with molecular dynamics and free energy of binding calculations were carried out to search for ligands showing selective affinity to T. spiralis TS. Despite an overall strong similarity in structure and dynamics of nematode vs mammalian TSs, a pool of ligands demonstrating predictively a strong and selective binding to TsTS has been delimited. These compounds, the E63 family, locate in the dimerization interface of TsTS where they exert species-specific interactions with certain non-conserved residues, including hydrogen bonds with Thr174 and hydrophobic contacts with Phe192, Cys191 and Tyr152. The E63 family of ligands opens the possibility of future development of selective inhibitors of TsTS and effective agents against trichinellosis. Copyright © 2017 Elsevier Inc. All rights reserved.
Fani, Najmeh; Bordbar, Abdol-Khalegh; Ghayeb, Yousef; Sepehri, Saghi
2015-01-01
In this work, docking tools were utilized in order to study the binding properties of more than five hundred of proline-based 2,5-diketopiperazine in the binding site of αβ-tubulin. Results revealed that 20 compounds among them showed lower binding energies in comparison with Tryprostatin-A, a well known tubulin inhibitor and therefore could be potential inhibitors of tubulin. However, the precise evaluation of binding poses represents the similar binding modes for all of these compounds and Tryprostatin-A. Finally, the best docked complex was subjected to a 25 ns molecular dynamics simulation to further validate the proposed binding mode of this compound.
Fast and accurate grid representations for atom-based docking with partner flexibility.
de Vries, Sjoerd J; Zacharias, Martin
2017-06-30
Macromolecular docking methods can broadly be divided into geometric and atom-based methods. Geometric methods use fast algorithms that operate on simplified, grid-like molecular representations, while atom-based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid-based and atom-based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom-based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid-based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse-grained forcefield, the average speed improvement was >100x. Grid-based representations may allow atom-based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus
Karp, Peter D.; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard
2015-01-01
Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida). PMID:26097686
ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.
Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard
2015-01-01
Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida).
Interactions of cephalexin with bovine serum albumin: displacement reaction and molecular docking.
Hamishehkar, Hamed; Hosseini, Soheila; Naseri, Abdolhossein; Safarnejad, Azam; Rasoulzadeh, Farzaneh
2016-01-01
Introduction: The drug-plasma protein interaction is a fundamental issue in guessing and checking the serious drug side effects related with other drugs. The purpose of this research was to study the interaction of cephalexin with bovine serum albumin (BSA) and displacement reaction using site probes. Methods: The interaction mechanism concerning cephalexin (CPL) with BSA was investigated using various spectroscopic methods and molecular modeling method. The binding sites number, n, apparent binding constant, K, and thermodynamic parameters, ΔG 0 , ΔH 0 , and ΔS 0 were considered at different temperatures. To evaluate the experimental results, molecular docking modeling was calculated. Results: The distance, r=1.156 nm between BSA and CPL were found in accordance with the Forster theory of non-radiation energy transfer (FRET) indicating energy transfer occurs between BSA and CPL. According to the binding parameters and ΔG 0 = negative values and ΔS 0 = 28.275 j mol -1 K -1 , a static quenching process is effective in the CPL-BSA interaction spontaneously. ΔG 0 for the CPL-BSA complex obtained from the docking simulation is -28.99 kj mol -1 , which is close to experimental ΔG of binding, -21.349 kj mol -1 that indicates a good agreement between the results of docking methods and experimental data. Conclusion: The outcomes of spectroscopic methods revealed that the conformation of BSA changed during drug-BSA interaction. The results of FRET propose that CPL quenches the fluorescence of BSA by static quenching and FRET. The displacement study showed that phenylbutazon and ketoprofen displaced CPL, indicating that its binding site on albumin is site I and Gentamicin cannot be displaced from the binding site of CPL. All results of molecular docking method agreed with the results of experimental data.
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.
NASA Astrophysics Data System (ADS)
Deng, Fangfang; Xie, Meihong; Zhang, Xiaoyun; Li, Peizhen; Tian, Yueli; Zhai, Honglin; Li, Yang
2014-06-01
3,4-Dihydro-2H,6H-pyrimido[1,2-c][1,3]benzothiazin-6-imine is an antiretroviral agent, which can act against human immunodeficiency virus (HIV) infection, but the mechanism of action of pyrimido[1,2-c][1,3]benzothiazin-6-imine derivatives remained ambiguous. In this study, multiple linear regression (MLR) was applied to establish a quite reliable model with the squared correlation coefficient (R2) of 0.8079. We also used chemical information descriptors based on the simplified molecular input line entry system (SMILES) to get a better model with R2 of 0.9086 for the training set, and R2 of 0.8031 for the test set. Molecular docking was utilized to provide more useful information between pyrimido[1,2-c][1,3]benzothiazin-6-imine derivatives and HIV-1 protease, such as active site, binding mode and important residues. Molecular dynamics simulation was employed to further validate the docking results. This work may lead to a better understanding of the mechanism of action and aid to design novel and more potent anti-HIV drugs.
Pradeepkiran, Jangampalli Adi; Kumar, Konidala Kranthi; Kumar, Yellapu Nanda; Bhaskar, Matcha
2015-01-01
The zoonotic disease brucellosis, a chronic condition in humans affecting renal and cardiac systems and causing osteoarthritis, is caused by Brucella, a genus of Gram-negative, facultative, intracellular pathogens. The mode of transmission and the virulence of the pathogens are still enigmatic. Transcription regulatory elements, such as rho proteins, play an important role in the termination of transcription and/or the selection of genes in Brucella. Adverse effects of the transcription inhibitors play a key role in the non-successive transcription challenges faced by the pathogens. In the investigation presented here, we computationally predicted the transcription termination factor rho (TtFRho) inhibitors against Brucella melitensis 16M via a structure-based method. In view the unknown nature of its crystal structure, we constructed a robust three-dimensional homology model of TtFRho’s structure by comparative modeling with the crystal structure of the Escherichia coli TtFRho (Protein Data Bank ID: 1PVO) as a template in MODELLER (v 9.10). The modeled structure was optimized by applying a molecular dynamics simulation for 2 ns with the CHARMM (Chemistry at HARvard Macromolecular Mechanics) 27 force field in NAMD (NAnoscale Molecular Dynamics program; v 2.9) and then evaluated by calculating the stereochemical quality of the protein. The flexible docking for the interaction phenomenon of the template consists of ligand-related inhibitor molecules from the ZINC (ZINC Is Not Commercial) database using a structure-based virtual screening strategy against minimized TtFRho. Docking simulations revealed two inhibitors compounds – ZINC24934545 and ZINC72319544 – that showed high binding affinity among 2,829 drug analogs that bind with key active-site residues; these residues are considered for protein-ligand binding and unbinding pathways via steered molecular dynamics simulations. Arg215 in the model plays an important role in the stability of the protein-ligand complex via a hydrogen bonding interaction by aromatic-π contacts, and the ADMET (absorption, distribution, metabolism, and excretion) analysis of best leads indicate nontoxic in nature with good potential for drug development. PMID:25848225
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.
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.
NASA Astrophysics Data System (ADS)
Nurhidayah, E. S.; Ivansyah, A. L.; Martoprawiro, M. A.; Zulfikar, M. A.
2018-05-01
A molecular docking study, using molecular mechanics calculations with Arguslab, was used to help predict the enantioseparation of some guest molecules of chiral carboxylic acid derivatives by heptakis-2,6-di-O-methyl-β-cyclodextrin (DIMEB) and heptakis-2,3,6-tri-O-methyl-β-cyclodextrin (TRIMEB) as host molecules. The small differences in the binding free energy values (ΔΔG) obtained from Arguslab did not indicate any significant enantioseparation. From the molecular docking simulation results, it is predicted that in the case of DIMEB as host molecule, R-enantiomer of Etodolac, Fenoprofen, Indoprofen, Ketorolac, and Naproxen will be eluted first than S-enantiomer; However, S-enantiomer of Carprofen, Flurbiprofen, Ketoprofen, Pirprofen, Proglumide, Sulindac, Surprofen, and Zaltoprofen will be eluted first than R-enantiomer by DIMEB as host molecule. When TRIMEB is used as a host molecule, R-enantiomer of Carprofen, Flurbiprofen, Indoprofen, Ketoprofen, Naproxen, Pirprofen, and Surprofen will be eluted first than S-enantiomer; However, S-enantiomer of Etodolac, Fenoprofen, Ketorolac, Proglumide, Sulindac and Zaltoprofen will be eluted first than R-enantiomer by TRIMEB as host molecule.
Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1.
Fatima, Sabiha; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha
2012-08-01
Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r², q²(loo) and r²(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r²(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.
Ensemble-based docking: From hit discovery to metabolism and toxicity predictions.
Evangelista, Wilfredo; Weir, Rebecca L; Ellingson, Sally R; Harris, Jason B; Kapoor, Karan; Smith, Jeremy C; Baudry, Jerome
2016-10-15
This paper describes and illustrates the use of ensemble-based docking, i.e., using a collection of protein structures in docking calculations for hit discovery, the exploration of biochemical pathways and toxicity prediction of drug candidates. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials. Copyright © 2016 Elsevier Ltd. All rights reserved.
Identification of Protein–Excipient Interaction Hotspots Using Computational Approaches
Barata, Teresa S.; Zhang, Cheng; Dalby, Paul A.; Brocchini, Steve; Zloh, Mire
2016-01-01
Protein formulation development relies on the selection of excipients that inhibit protein–protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations using force degradation studies. Such methods do not readily provide information on intermolecular interactions responsible for the protective effects of excipients. This study describes a molecular docking approach to screen and rank interactions allowing for the identification of protein–excipient hotspots to aid in the selection of excipients to be experimentally screened. Previously published work with Drosophila Su(dx) was used to develop and validate the computational methodology, which was then used to determine the formulation hotspots for Fab A33. Commonly used excipients were examined and compared to the regions in Fab A33 prone to protein–protein interactions that could lead to aggregation. This approach could provide information on a molecular level about the protective interactions of excipients in protein formulations to aid the more rational development of future formulations. PMID:27258262
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.
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%.
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.
Gueto, Carlos; Torres, Juan; Vivas-Reyes, Ricardo
2009-09-01
Aromatase, the enzyme responsible for estrogen biosynthesis, is an attractive target in the treatment of hormone-dependent breast cancer. In this manuscript, the structure-based drug design approach of sulfonanilide analogues as potential selective aromatase expression regulators (SAERs) is described. Receptor-independent CoMFA (Comparative Molecular Field Analysis) maps were employed for generating a pseudocavity for LeapFrog calculation. A robust model, using 45 and 10 molecules in the training and test sets, respectively, was developed producing statistically significant results with cross-validated and conventional correlation coefficients of 0.656 and 0.956, respectively. This model was used to predict the activity of newly proposed molecules as SAERs candidates being two magnitude orders more potent than the previously reported compounds. Also in the present study, the computational blind docking method using eHiTS is tested on molecules study group and COX-2 enzyme. Future perspectives of the method in the screening of SAERs candidates with no COX-2 inhibitory activity are discussed.
de Beer, Stephanie B A; van Bergen, Laura A H; Keijzer, Karlijn; Rea, Vanina; Venkataraman, Harini; Guerra, Celia Fonseca; Bickelhaupt, F Matthias; Vermeulen, Nico P E; Commandeur, Jan N M; Geerke, Daan P
2012-02-01
Recently, it was found that mutations in the binding cavity of drug-metabolizing Cytochrome P450 BM3 mutants can result in major changes in regioselectivity in testosterone (TES) hydroxylation. In the current work, we report the intrinsic reactivity of TES' C-H bonds and our attempts to rationalize experimentally observed changes in TES hydroxylation using a protein structure-based in silico approach, by setting up and employing a combined Molecular Dynamics (MD) and ligand docking approach to account for the flexibility and plasticity of BM3 mutants. Using this approach, about 100,000 TES binding poses were obtained per mutant. The predicted regioselectivity in TES hydroxylation by the mutants was found to be in disagreement with experiment. As revealed in a detailed structural analysis of the obtained docking poses, this disagreement is due to limitations in correctly scoring hydrogen-bonding and steric interactions with specific active-site residues, which could explain the experimentally observed trends in regioselectivity in TES hydroxylation.
GPU Optimizations for a Production Molecular Docking Code*
Landaverde, Raphael; Herbordt, Martin C.
2015-01-01
Modeling molecular docking is critical to both understanding life processes and designing new drugs. In previous work we created the first published GPU-accelerated docking code (PIPER) which achieved a roughly 5× speed-up over a contemporaneous 4 core CPU. Advances in GPU architecture and in the CPU code, however, have since reduced this relalative performance by a factor of 10. In this paper we describe the upgrade of GPU PIPER. This required an entire rewrite, including algorithm changes and moving most remaining non-accelerated CPU code onto the GPU. The result is a 7× improvement in GPU performance and a 3.3× speedup over the CPU-only code. We find that this difference in time is almost entirely due to the difference in run times of the 3D FFT library functions on CPU (MKL) and GPU (cuFFT), respectively. The GPU code has been integrated into the ClusPro docking server which has over 4000 active users. PMID:26594667
GPU Optimizations for a Production Molecular Docking Code.
Landaverde, Raphael; Herbordt, Martin C
2014-09-01
Modeling molecular docking is critical to both understanding life processes and designing new drugs. In previous work we created the first published GPU-accelerated docking code (PIPER) which achieved a roughly 5× speed-up over a contemporaneous 4 core CPU. Advances in GPU architecture and in the CPU code, however, have since reduced this relalative performance by a factor of 10. In this paper we describe the upgrade of GPU PIPER. This required an entire rewrite, including algorithm changes and moving most remaining non-accelerated CPU code onto the GPU. The result is a 7× improvement in GPU performance and a 3.3× speedup over the CPU-only code. We find that this difference in time is almost entirely due to the difference in run times of the 3D FFT library functions on CPU (MKL) and GPU (cuFFT), respectively. The GPU code has been integrated into the ClusPro docking server which has over 4000 active users.
Al-Wabli, Reem I; Al-Ghamdi, Alwah R; Ghabbour, Hazem A; Al-Agamy, Mohamed H; Monicka, James Clemy; Joe, Issac Hubert; Attia, Mohamed I
2017-02-28
Mycoses are serious health problem, especially in immunocompromised individuals. A new imidazole-bearing compound containing an oxime functionality was synthesized and characterized with different spectroscopic techniques to be used for the preparation of new antifungal agents. The stereochemistry of the oxime double bond was unequivocally determined via the single crystal X-ray technique. The title compound 4 , C 13 H 13 N₃O₃·C₃H₈O, crystallizes in the monoclinic space group P 2₁with a = 9.0963(3) Å, b = 14.7244(6) Å, c = 10.7035(4) Å, β = 94.298 (3)°, V = 1429.57(9) ų, Z = 2. The molecules were packed in the crystal structure by eight intermolecular hydrogen bond interactions. A comprehensive spectral analysis of the title molecule 4 has been performed based on the scaled quantum mechanical (SQM) force field obtained by density-functional theory (DFT) calculations. A molecular docking study illustrated the binding mode of the title compound 4 into its target protein. The preliminary antifungal activity of the title compound 4 was determined using a broth microdilution assay.
NASA Astrophysics Data System (ADS)
Khajeh, Masoumeh Ashrafi; Dehghan, Gholamreza; Dastmalchi, Siavoush; Shaghaghi, Masoomeh; Iranshahi, Mehrdad
2018-03-01
DNA is a major target for a number of anticancer substances. Interaction studies between small molecules and DNA are essential for rational drug designing to influence main biological processes and also introducing new probes for the assay of DNA. Tschimgine (TMG) is a monoterpene derivative with anticancer properties. In the present study we tried to elucidate the interaction of TMG with calf thymus DNA (CT-DNA) using different spectroscopic methods. UV-visible absorption spectrophotometry, fluorescence and circular dichroism (CD) spectroscopies as well as molecular docking study revealed formation of complex between TMG and CT-DNA. Binding constant (Kb) between TMG and DNA was 2.27 × 104 M- 1, that is comparable to groove binding agents. The fluorescence spectroscopic data revealed that the quenching mechanism of fluorescence of TMG by CT-DNA is static quenching. Thermodynamic parameters (ΔH < 0 and ΔS < 0) at different temperatures indicated that van der Waals forces and hydrogen bonds were involved in the binding process of TMG with CT-DNA. Competitive binding assay with methylene blue (MB) and Hoechst 33258 using fluorescence spectroscopy displayed that TMG possibly binds to the minor groove of CT-DNA. These observations were further confirmed by CD spectral analysis, viscosity measurements and molecular docking.
Shi, Jie-Hua; Lou, Yan-Yue; Zhou, Kai-Li; Pan, Dong-Qi
2018-06-18
As a sulfonylurea herbicide, sulfosulfuron is extensively applied in controlling broad-leaves and weeds in agriculture. It may cause a potential risk for human and herbivores health due to its widely application and residue in crops and fruits. The study of the binding characteristics of calf thymus DNA (ct-DNA) with sulfosulfuron was performed through a series of spectroscopic techniques and computer simulation. The experimental results showed sulfosulfuron interacted with ct-DNA through the groove binding. The negative values of thermodynamic parameter (ΔH 0 , ΔS 0 and ΔG 0 ) revealed that the reaction of sulfosulfuron with DNA could proceed spontaneously, and the hydrogen bonding and van der Waals forces were essential to sulfosulfuron-ct-DNA binding, which was further verified by molecular docking study. Meanwhile, the electrostatic and hydrophobic interactions also played a supporting function for the interaction of sulfosulfuron with ct-DNA. The circular dichroism (CD) results exhibited a minor change in the secondary structure of ct-DNA during interaction process. Moreover, the conformation of sulfosulfuron had the obvious change after binding to DNA, which suggested that the flexibility of sulfosulfuron contributed to stabilizing the sulfosulfuron-ct-DNA complex. Copyright © 2018 Elsevier B.V. All rights reserved.
Moretti, Rocco; Lyskov, Sergey; Das, Rhiju; Meiler, Jens; Gray, Jeffrey J
2018-01-01
The Rosetta molecular modeling software package provides a large number of experimentally validated tools for modeling and designing proteins, nucleic acids, and other biopolymers, with new protocols being added continually. While freely available to academic users, external usage is limited by the need for expertise in the Unix command line environment. To make Rosetta protocols available to a wider audience, we previously created a web server called Rosetta Online Server that Includes Everyone (ROSIE), which provides a common environment for hosting web-accessible Rosetta protocols. Here we describe a simplification of the ROSIE protocol specification format, one that permits easier implementation of Rosetta protocols. Whereas the previous format required creating multiple separate files in different locations, the new format allows specification of the protocol in a single file. This new, simplified protocol specification has more than doubled the number of Rosetta protocols available under ROSIE. These new applications include pK a determination, lipid accessibility calculation, ribonucleic acid redesign, protein-protein docking, protein-small molecule docking, symmetric docking, antibody docking, cyclic toxin docking, critical binding peptide determination, and mapping small molecule binding sites. ROSIE is freely available to academic users at http://rosie.rosettacommons.org. © 2017 The Protein Society.
Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M; Loza, Maria Isabel; Munteanu, Cristian R; Pazos, Alejandro; García-Mera, Xerardo; González-Díaz, Humbert
2018-06-25
Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC 50 , EC 50 , K i , etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.
Grolla, Ambra A; Podestà, Valeria; Chini, Maria Giovanna; Di Micco, Simone; Vallario, Antonella; Genazzani, Armando A; Canonico, Pier Luigi; Bifulco, Giuseppe; Tron, Gian Cesare; Sorba, Giovanni; Pirali, Tracey
2009-05-14
HDAC inhibitors show great promise for the treatment of cancer. As part of a broader effort to explore the SAR of HDAC inhibitors, synthesis, biological evaluation, and molecular docking of novel Ugi products containing a zinc-chelating moiety are presented. One compound shows improved inhibitory potencies compared to SAHA, demonstrating that hindered lipophilic residues grafted on the peptide scaffold of the alpha-aminoacylamides can be favorable in the interaction with the enzyme.
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.
NASA Astrophysics Data System (ADS)
Murugavel, S.; Vetri Velan, V.; Kannan, Damodharan; Bakthadoss, Manickam
2016-03-01
The title compound methyl(2E)-2-{[N-(2-formylphenyl) (4-methylbenzene)sulfonamido]methyl}-3-(4-fluorophenyl) prop-2-enoate (MFMSF) has been synthesized and single crystals were grown by slow evaporation solution growth technique at room temperature. The grown crystals were characterized by FTIR, 1H NMR, 13C NMR, and single crystal X-ray diffraction. In the crystal, molecules are linked by intermolecular C-H…O hydrogen bonds forming a two-dimensional supramolecular network along [110] direction. The molecular geometry was also optimized using density functional theory (DFT/B3LYP) method with the 6-311G (d,p) basis set in ground state and compared with the experimental data. The entire vibrational assignments of wave numbers were made on the basis of potential energy distribution (PED) by VEDA 4 programme. Stability of the molecule arising from hyper conjugative interactions, charge delocalization has been analyzed using natural bond orbital (NBO) analysis. In addition, NLO, MEP, Mulliken, thermodynamic properties, HOMO and LUMO energy gap were theoretically predicted. The global chemical reactivity descriptors are calculated for MFMSF and used to predict their relative stability and reactivity. The antibacterial activity of the compound was also tested against various pathogens. The molecular docking studies concede that title compound may exhibit PBP-2X inhibitor activity.
Molecular Docking Study on Galantamine Derivatives as Cholinesterase Inhibitors.
Atanasova, Mariyana; Yordanov, Nikola; Dimitrov, Ivan; Berkov, Strahil; Doytchinova, Irini
2015-06-01
A training set of 22 synthetic galantamine derivatives binding to acetylcholinesterase was docked by GOLD and the protocol was optimized in terms of scoring function, rigidity/flexibility of the binding site, presence/absence of a water molecule inside and radius of the binding site. A moderate correlation was found between the affinities of compounds expressed as pIC50 values and their docking scores. The optimized docking protocol was validated by an external test set of 11 natural galantamine derivatives and the correlation coefficient between the docking scores and the pIC50 values was 0.800. The derived relationship was used to analyze the interactions between galantamine derivatives and AChE. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.