Relevant bibliographies by topics / Molecular docking

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Molecular docking'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 March 2025

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Journal articles on the topic "Molecular docking"

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Dias, Raquel, and Walter de Azevedo Jr. "Molecular Docking Algorithms." Current Drug Targets 9, no. 12 (December 1, 2008): 1040–47. http://dx.doi.org/10.2174/138945008786949432.

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Sabrina Benouis, Sabrina Benouis, Fouad Ferkous Fouad Ferkous, Khairedine Kraim Khairedine Kraim, Ahmed Allali Ahmed Allali, and Youcef Saihi Youcef Saihi. "Molecular Docking Studies on Gingerol Analogues toward Mushroom Tyrosinase." Journal of the chemical society of pakistan 42, no. 2 (2020): 214. http://dx.doi.org/10.52568/000630.

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The gingerol presents the starting point of our work which aims to discover new inhibitors of the tyrosinase enzyme. Therefore, we have studied the activity of gingerol derivatives as inhibitors against mushroom tyrosinase based on the molecular docking. Molecular docking studies were performed on a series of gingerol analogues retrieved from Zinc database (with 70% as similarity threshold). The gingerol analogues were docked within the active site region of mushroom tyrosinase (PDB: 2Y9X) using Molegro Virtual Docker V.5.0. The results of molecular docking studies revealed that some analogues of gingerol have higher Moldock score (in terms of negative energy) than gingerol and the experimentally known inhibitors of tyrosinase, and showed favourable molecular interactions exhibiting common molecular interaction with Ala323, Met280 and Asn260 residues of tyrosinase. Furthermore, the top docked compounds used in this work do not violate the Lipinsky rule of five.
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Sabrina Benouis, Sabrina Benouis, Fouad Ferkous Fouad Ferkous, Khairedine Kraim Khairedine Kraim, Ahmed Allali Ahmed Allali, and Youcef Saihi Youcef Saihi. "Molecular Docking Studies on Gingerol Analogues toward Mushroom Tyrosinase." Journal of the chemical society of pakistan 42, no. 2 (2020): 214. http://dx.doi.org/10.52568/000630/jcsp/42.02.2020.

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The gingerol presents the starting point of our work which aims to discover new inhibitors of the tyrosinase enzyme. Therefore, we have studied the activity of gingerol derivatives as inhibitors against mushroom tyrosinase based on the molecular docking. Molecular docking studies were performed on a series of gingerol analogues retrieved from Zinc database (with 70% as similarity threshold). The gingerol analogues were docked within the active site region of mushroom tyrosinase (PDB: 2Y9X) using Molegro Virtual Docker V.5.0. The results of molecular docking studies revealed that some analogues of gingerol have higher Moldock score (in terms of negative energy) than gingerol and the experimentally known inhibitors of tyrosinase, and showed favourable molecular interactions exhibiting common molecular interaction with Ala323, Met280 and Asn260 residues of tyrosinase. Furthermore, the top docked compounds used in this work do not violate the Lipinsky rule of five.
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Berenger, Francois, Ashutosh Kumar, Kam Y. J. Zhang, and Yoshihiro Yamanishi. "Lean-Docking: Exploiting Ligands’ Predicted Docking Scores to Accelerate Molecular Docking." Journal of Chemical Information and Modeling 61, no. 5 (April 16, 2021): 2341–52. http://dx.doi.org/10.1021/acs.jcim.0c01452.

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Elokely, Khaled M., and Robert J. Doerksen. "Docking Challenge: Protein Sampling and Molecular Docking Performance." Journal of Chemical Information and Modeling 53, no. 8 (April 15, 2013): 1934–45. http://dx.doi.org/10.1021/ci400040d.

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Rani, Nidhi, Prerna Sharma, Vikas Kumar Sharma, and Praveen Kumar. "Molecular Docking Approach to Identify Potential AntiCandidal Potential of Curcumin." Journal of Pharmaceutical Technology, Research and Management 8, no. 2 (November 17, 2020): 67–71. http://dx.doi.org/10.15415/jptrm.2020.82008.

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Background: Candida albicans is a kind of fungus that can lead to mortality. In the presence of the enzyme Lanosterol-demethylase, Ergosterol, the major sterol in the fungal cell membrane, is the resulting product of Lanosterol (Cytochrome P450DM). Purpose: Azole antifungal drugs target this enzyme as a target enzyme. The work included selecting and modelling the target enzyme. Cucumin’s inhibitory effect on Cytochrome P450 was tested utilising molecular docking experiments. Methods: Chem sketch was used to create compound structures, and Molergo Virtual Docker was used to do molecular docking. Results: All of the curcumin and conventional medicines, such as Ketoconazole, Clotrimazole, and Miconazole, have interaction with 14-demethylase amino acid residues, Haem and water molecules in the target site, as per the docking research.
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Morris, Connor J., and Dennis Della Corte. "Using molecular docking and molecular dynamics to investigate protein-ligand interactions." Modern Physics Letters B 35, no. 08 (February 18, 2021): 2130002. http://dx.doi.org/10.1142/s0217984921300027.

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Molecular docking and molecular dynamics (MD) are powerful tools used to investigate protein-ligand interactions. Molecular docking programs predict the binding pose and affinity of a protein-ligand complex, while MD can be used to incorporate flexibility into docking calculations and gain further information on the kinetics and stability of the protein-ligand bond. This review covers state-of-the-art methods of using molecular docking and MD to explore protein-ligand interactions, with emphasis on application to drug discovery. We also call for further research on combining common molecular docking and MD methods.
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Fan, Jiyu, Ailing Fu, and Le Zhang. "Progress in molecular docking." Quantitative Biology 7, no. 2 (June 2019): 83–89. http://dx.doi.org/10.1007/s40484-019-0172-y.

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Guedes, Isabella A., Camila S. de Magalhães, and Laurent E. Dardenne. "Receptor–ligand molecular docking." Biophysical Reviews 6, no. 1 (December 21, 2013): 75–87. http://dx.doi.org/10.1007/s12551-013-0130-2.

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Mitchell, Julie C., Sharokina Shahbaz, and Lynn F. Ten Eyck. "Interfaces in Molecular Docking." Molecular Simulation 30, no. 2-3 (February 15, 2004): 97–106. http://dx.doi.org/10.1080/0892702031000152217.

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Dissertations / Theses on the topic "Molecular docking"

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Iakovou, Georgios. "Simulating molecular docking with haptics." Thesis, University of East Anglia, 2015. https://ueaeprints.uea.ac.uk/59468/.

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Intermolecular binding underlies various metabolic and regulatory processes of the cell, and the therapeutic and pharmacological properties of drugs. Molecular docking systems model and simulate these interactions in silico and allow the study of the binding process. In molecular docking, haptics enables the user to sense the interaction forces and intervene cognitively in the docking process. Haptics-assisted docking systems provide an immersive virtual docking environment where the user can interact with the molecules, feel the interaction forces using their sense of touch, identify visually the binding site, and guide the molecules to their binding pose. Despite a forty-year research e�ort however, the docking community has been slow to adopt this technology. Proprietary, unreleased software, expensive haptic hardware and limits on processing power are the main reasons for this. Another signi�cant factor is the size of the molecules simulated, limited to small molecules. The focus of the research described in this thesis is the development of an interactive haptics-assisted docking application that addresses the above issues, and enables the rigid docking of very large biomolecules and the study of the underlying interactions. Novel methods for computing the interaction forces of binding on the CPU and GPU, in real-time, have been developed. The force calculation methods proposed here overcome several computational limitations of previous approaches, such as precomputed force grids, and could potentially be used to model molecular exibility at haptic refresh rates. Methods for force scaling, multipoint collision response, and haptic navigation are also reported that address newfound issues, particular to the interactive docking of large systems, e.g. force stability at molecular collision. The i ii result is a haptics-assisted docking application, Haptimol RD, that runs on relatively inexpensive consumer level hardware, (i.e. there is no need for specialized/proprietary hardware).
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Atkovska, Kalina, Sergey A. Samsonov, Maciej Paszkowski-Rogacz, and M. Teresa Pisabarro. "Multipose Binding in Molecular Docking." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-147177.

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Molecular docking has been extensively applied in virtual screening of small molecule libraries for lead identification and optimization. A necessary prerequisite for successful differentiation between active and non-active ligands is the accurate prediction of their binding affinities in the complex by use of docking scoring functions. However, many studies have shown rather poor correlations between docking scores and experimental binding affinities. Our work aimed to improve this correlation by implementing a multipose binding concept in the docking scoring scheme. Multipose binding, i.e., the property of certain protein-ligand complexes to exhibit different ligand binding modes, has been shown to occur in nature for a variety of molecules. We conducted a high-throughput docking study and implemented multipose binding in the scoring procedure by considering multiple docking solutions in binding affinity prediction. In general, improvement of the agreement between docking scores and experimental data was observed, and this was most pronounced in complexes with large and flexible ligands and high binding affinities. Further developments of the selection criteria for docking solutions for each individual complex are still necessary for a general utilization of the multipose binding concept for accurate binding affinity prediction by molecular docking.
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Landaverde, Raphael J. "GPU optimizations for a production molecular docking code." Thesis, Boston University, 2014. https://hdl.handle.net/2144/21199.

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Thesis (M.Sc.Eng.) -- Boston University
Scientists have always felt the desire to perform computationally intensive tasks that surpass the capabilities of conventional single core computers. As a result of this trend, Graphics Processing Units (GPUs) have come to be increasingly used for general computation in scientific research. This field of GPU acceleration is now a vast and mature discipline. Molecular docking, the modeling of the interactions between two molecules, is a particularly computationally intensive task that has been the subject of research for many years. It is a critical simulation tool used for the screening of protein compounds for drug design and in research of the nature of life itself. The PIPER molecular docking program was previously accelerated using GPUs, achieving a notable speedup over conventional single core implementation. Since its original release the development of the CPU based PIPER has not ceased, and it is now a mature and fast parallel code. The GPU version, however, still contains many potential points for optimization. In the current work, we present a new version of GPU PIPER that attains a 3.3x speedup over a parallel MPI version of PIPER running on an 8 core machine and using the optimized Intel Math Kernel Library. We achieve this speedup by optimizing existing kernels for modern GPU architectures and migrating critical code segments to the GPU. In particular, we both improve the runtime of the filtering and scoring stages by more than an order of magnitude, and move all molecular data permanently to the GPU to improve data locality. This new speedup is obtained while retaining a computational accuracy virtually identical to the CPU based version. We also demonstrate that, due to the algorithmic dependencies of the PIPER algorithm on the 3D Fast Fourier Transform, our GPU PIPER will likely remain proportionally faster than equivalent CPU based implementations, and with little room for further optimizations. This new GPU accelerated version of PIPER is integrated as part of the ClusPro molecular docking and analysis server at Boston University. ClusPro has over 4000 registered users and more than 50000 jobs run over the past 4 years.
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De, Youngster Dela. "An Isometry-Invariant Spectral Approach for Macro-Molecular Docking." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/30226.

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Proteins and the formation of large protein complexes are essential parts of living organisms. Proteins are present in all aspects of life processes, performing a multitude of various functions ranging from being structural components of cells, to facilitating the passage of certain molecules between various regions of cells. The 'protein docking problem' refers to the computational method of predicting the appropriate matching pair of a protein (receptor) with respect to another protein (ligand), when attempting to bind to one another to form a stable complex. Research shows that matching the three-dimensional (3D) geometric structures of candidate proteins plays a key role in determining a so-called docking pair, which is one of the key aspects of the Computer Aided Drug Design process. However, the active sites which are responsible for binding do not always present a rigid-body shape matching problem. Rather, they may undergo sufficient deformation when docking occurs, which complicates the problem of finding a match. To address this issue, we present an isometry-invariant and topologically robust partial shape matching method for finding complementary protein binding sites, which we call the ProtoDock algorithm. The ProtoDock algorithm comes in two variations. The first version performs a partial shape complementarity matching by initially segmenting the underlying protein object mesh into smaller portions using a spectral mesh segmentation approach. The Heat Kernel Signature (HKS), the underlying basis of our shape descriptor, is subsequently computed for the obtained segments. A final descriptor vector is constructed from the Heat Kernel Signatures and used as the basis for the segment matching. The three different descriptor methods employed are, the accepted Bag of Features (BoF) technique, and our two novel approaches, Closest Medoid Set (CMS) and Medoid Set Average (MSA). The second variation of our ProtoDock algorithm aims to perform the partial matching by utilizing the pointwise HKS descriptors. The use of the pointwise HKS is mainly motivated by the suggestion that, at adequate times, the Heat Kernel Signature of a point on a surface sufficiently describes its neighbourhood. Hence, the HKS of a point may serve as the representative descriptor of its given region of which it forms a part. We propose three (3) sampling methods---Uniform, Random, and Segment-based Random sampling---for selecting these points for the partial matching. Random and Segment-based Random sampling both prove superior to the Uniform sampling method. Our experimental results, run against the Protein-Protein Benchmark 4.0, demonstrate the viability of our approach, in that, it successfully returns known binding segments for known pairing proteins. Furthermore, our ProtoDock-1 algorithm still still yields good results for low resolution protein meshes. This results in even faster processing and matching times with sufficiently reduced computational requirements when obtaining the HKS.
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Tantar, Alexandru-Adrian. "Hybrid parallel metaheuristics for molecular docking on computational grids." Thesis, Lille 1, 2009. http://www.theses.fr/2009LIL10166.

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Cette thèse porte sur les méta-heuristiques hiérarchiques parallèles adaptatives pour l'échantillonnage conformationnel. Étant un problème hautement combinatoire et multlmodal, l'échantillonnage conformationnel requière la construction d'approches hybrides à large échelle. Après une analyse dei modèles mathématiques, nécessitant l'examen des différentes formulations du champ de force, nous avons proposé une étude des opérateurs de variation et des méthodes de recherche locale adaptés au problème ainsi que leur hybridation dynamique et adaptative. Cette étude nous a conduit à la proposition de mécanismes d'adaptation des paramètres des algorithmes utilisés en fonction du processus d'évolution. Dans cette thèse, nous proposons également des algorithmes adaptatifs hybndes hiérarchiques distribués, fortement extensibles. L'expérimentation, basée sur l'utilisation de multiples modèles parallèles, démontre la grande efficacité de ces algorithmes. En effet, les résultats obtenus montrent que des RMSD moyens en dessous de 1.0 A peuvent être obtenus sur des instances difficiles des problèmes de prédiction de la structure des protéines et de docking moléculaire. La validation des approches hybrides proposées a été effectuée sur Grid'5000, une grille expérimentale d'échelle nationale composée d'environ 5000 coeurs de calcul. Une image système a été développée en utilisant Globus pour permettre des déploiements distribués à large échelle. L'approche hiérarchique distribuée construite a été ainsi déployée sur plusieurs grappes, avec près de 1000 coeurs de calcul
The thesis proposes an extensive analysis of adaptive hierarchical parallel metaheuristics for ab initio conformational sampling. Standing as an NP, combinatorial, highly multi-modal optimization problem, conformational sampling requires for high-performance large scale hybrid approaches to be constructed. Following an incremental definition, minimum complexity conformational sampling mathematical models are first analyzed, entailing a review of different force field formulations. A comprehensive analysis is conducted on a large set of operators and local search algorithms including adaptive and dynamic mechanisms. As determined by the analysis outcomes, complex a priori and online parameter tuning stages are designed. finally, highly scalable hierarchical hybrid distributed algorithm designs are proposed. Experimentation is carried over multiple parallelization models with afferent cooperation topologies. Expenmentations resulted in unprecedented results to be obtained. Multiple perfect conformational matches have been determined, on highly difficult protein structure prediction and molecular docking benchmarks, with RMSD average values below 1.0A. The validation of the proposed hybrid approaehes was performed on Grid'5000, a French computational grid, with almost 5000 computational cores. A Globus Toolkit hased Grid'SOOO system image has been developed, sustaining large scale distributed deployments. The constructed hierarchical hybrid distributed algorithm has been deployed on multiple clusters, with almost 1000 computing cores. Finally, a parallel AutoDock version was developed using the ParadisEO framework, integrating the developed algorithms
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BASCIU, ANDREA. "An enhanced-sampling MD-based protocol for molecular docking." Doctoral thesis, Università degli Studi di Cagliari, 2020. http://hdl.handle.net/11584/284135.

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Understanding molecular recognition of small molecules by proteins in atomistic detail is key for drug design. Molecular docking is a widely used computational method to mimic ligand-protein association in silico. However, predicting conformational changes occurring in proteins upon ligand binding is still a major challenge. Ensemble docking approaches address this issue by considering a set of different conformations of the protein obtained either experimentally or from computer simulations, e.g. from molecular dynamics. However, holo structures prone to host (the correct) ligands are generally poorly sampled by standard molecular dynamics simulations of the unbound (apo) protein. In order to address this limitation, we introduce a computational approach based on metadynamics simulations called ensemble docking with enhanced sampling of pocket shape (EDES) that allows holo-like conformations of proteins to be generated by exploiting only their apo structures. This is achieved by defining a set of collective variables able to sample different shapes of the binding site, ultimately mimicking the steric effect due to the ligand. In this work, we assessed the method on re-docking and cross-docking calculations. In first case, we selected three different protein targets undergoing different extent of conformational changes upon binding and, for each of them, we docked the experimental ligand conformation into an ensemble of receptor structures generated by EDES. In the second case, in the contest of a blind docking challenge, we generated the 3D structures of a set of different ligands of the same receptor and docked them into a set of EDES-generated conformations of that receptor. In all cases, for both re-docking and cross-docking experiments, our protocol generates a significant fraction of structures featuring a low RMSD from the experimental holo geometry of the receptor. Moreover, ensemble docking calculations using those conformations yielded in almost all cases to native-like poses among the top-ranked ones. Finally, we also tested an improved EDES recipe on a further target, known to be extremely challenging due to its extended binding region and the large extent of conformational changes accompanying the binding of its ligands.
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DI, DOMIZIO ALESSANDRO. "Development of methodologies for molecular docking and their applications." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2009. http://hdl.handle.net/10281/7460.

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Virtual High Throughput Screening (vHTS) has an increasingly important role in lowering both costs and time in drug discovery. The present work deals with the development (C++ programming language) of a new molecular docking software (semi-flexible model) to be used for vHTS. It would improve some of the main aspects of this type of softwares in current use, with particular reference to the program AutoDock: a particular importance is given to the calculation of the ligand conformational energy variation in passing from the unbound to the bound state, which represents a crucial term in the docking energy definition. Two real cases to which the new software modules were applied are then presented: the first belonging to drug discovery, concerning the study of new Ras oncogenic protein inhibitors; the second belonging to virtual protein engineering (VPE), concerning the design of a modified enzyme to be used in the manufacturing of semisynthetic antibiotics.
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Boyce, Sarah Emily. "Model systems for molecular docking: Understanding molecular recognition in polar and charged binding sites." Diss., Search in ProQuest Dissertations & Theses. UC Only, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3390113.

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Salmaso, Veronica. "Exploring protein flexibility during docking to investigate ligand-target recognition." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3421817.

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Ligand-protein binding models have experienced an evolution during time: from the lock-key model to induced-fit and conformational selection, the role of protein flexibility has become more and more relevant. Understanding binding mechanism is of great importance in drug-discovery, because it could help to rationalize the activity of known binders and to optimize them. The application of computational techniques to drug-discovery has been reported since the 1980s, with the advent computer-aided drug design. During the years several techniques have been developed to address the protein flexibility issue. The present work proposes a strategy to consider protein structure variability in molecular docking, through a ligand-based/structure-based integrated approach and through the development of a fully automatic cross-docking benchmark pipeline. Moreover, a full exploration of protein flexibility during the binding process is proposed through the Supervised Molecular Dynamics. The application of a tabu-like algorithm to classical molecular dynamics accelerates the binding process from the micro-millisecond to the nanosecond timescales. In the present work, an implementation of this algorithm has been performed to study peptide-protein recognition processes.
I modelli di riconoscimento ligando-proteina si sono evoluti nel corso degli anni: dal modello chiave-serratura a quello di fit-indotto e selezione conformazionale, il ruolo della flessibilità proteica è diventato via via più importante. Capire il meccanismo di riconoscimento è di grande importanza nella progettazione di nuovi farmaci, perchè può dare la possibilità di razionalizzare l’attività di ligandi noti e di ottimizzarli. L’applicazione di tecniche computazionali alla scoperta di nuovi farmaci risale agli anni ‘80, con l’avvento del cosiddetto “Computer-Aided Drug Design”, o, tradotto, progettazione di farmaci aiutata dal computer. Negli anni sono state sviluppate molte tecniche che hanno affrontato il problema della flessibilità proteica. Questo lavoro propone una strategia per considerare la variabilità delle strutture proteiche nel docking, attraverso un approccio combinato ligand-based/structure-based e attraverso lo sviluppo di una procedura completamente automatizzata di docking incrociato. In aggiunta, viene proposta una piena esplorazione della flessibilità proteica durante il processo di legame attraverso la Dinamica Molecolare Supervisionata. L’applicazione di un algoritmo simil-tabu alla dinamica molecolare classica accelera il processo di riconoscimento dalla scala dei micro-millisecondi a quella dei nanosecondi. Nel presente lavoro è stata fatta un’implementazione di questa algoritmica per studiare il processo di riconoscimento peptide-proteina.
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Genheden, Samuel. "A fast protein-ligand docking method." Thesis, University of Skövde, School of Humanities and Informatics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-69.

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In this dissertation a novel approach to protein-ligand docking is presented. First an existing method to predict putative active sites is employed. These predictions are then used to cut down the search space of an algorithm that uses the fast Fourier transform to calculate the geometrical and electrostatic complementarity between a protein and a small organic ligand. A simplified hydrophobicity score is also calculated for each active site. The docking method could be applied either to dock ligands in a known active site or to rank several putative active sites according to their biological feasibility. The method was evaluated on a set of 310 protein-ligand complexes. The results show that with respect to docking the method with its initial parameter settings is too coarse grained. The results also show that with respect to ranking of putative active sites the method works quite well.

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Books on the topic "Molecular docking"

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Goldfeld, Dahlia A. Advances in structure and small molecule docking predictions for crystallized G-Protein coupled receptors. [New York, N.Y.?]: [publisher not identified], 2013.

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Vlachakis, Dimitrios P., ed. Molecular Docking. InTech, 2018. http://dx.doi.org/10.5772/intechopen.69830.

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Stefaniu, Amalia, ed. Molecular Docking and Molecular Dynamics. IntechOpen, 2019. http://dx.doi.org/10.5772/intechopen.77898.

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Stefaniu, Amalia. Molecular Docking and Molecular Dynamics. IntechOpen, 2019.

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Pospíšil, Pavel. Current problems in molecular docking. 2002.

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Molecular Docking - Recent Advances [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.100665.

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Molecular Docking for Computer-Aided Drug Design. Elsevier, 2021. http://dx.doi.org/10.1016/c2019-0-04960-6.

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De Brevern, Alexandre G., Ramanathan Sowdhamini, Agnel Praveen Joseph, and Joseph Rebehmed, eds. Advances in Molecular Docking and Structure-Based Modelling. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88974-509-8.

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B, Hari Prasath. Molecular Docking Studies of Plant Derived Compounds: Bioinformatics. LAP Lambert Academic Publishing, 2012.

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Wani, Tanveer A., Seema Zargar, and Afzal Hussain, eds. Spectroscopic, Thermodynamic and Molecular Docking Studies on Molecular Mechanisms of Drug Binding to Proteins. MDPI, 2023. http://dx.doi.org/10.3390/books978-3-0365-6225-4.

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Book chapters on the topic "Molecular docking"

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Morris, Garrett M., and Marguerita Lim-Wilby. "Molecular Docking." In Methods in Molecular Biology, 365–82. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-177-2_19.

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Banaganapalli, Babajan, Fatima A. Morad, Muhammadh Khan, Chitta Suresh Kumar, Ramu Elango, Zuhier Awan, and Noor Ahmad Shaik. "Molecular Docking." In Essentials of Bioinformatics, Volume I, 335–53. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02634-9_15.

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Bhandari, Amit, and Vibin Ramakrishnan. "Molecular Docking." In Springer Protocols Handbooks, 7–16. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3405-9_2.

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Kumar, T. Durai Ananda. "Molecular Docking." In Drug Design: A Conceptual Overview, 243–70. London: CRC Press, 2022. http://dx.doi.org/10.1201/9781003298755-8.

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Bortolato, Andrea, Marco Fanton, Jonathan S. Mason, and Stefano Moro. "Molecular Docking Methodologies." In Methods in Molecular Biology, 339–60. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-017-5_13.

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Cieślak, Dominika, Ivo Kabelka, and Damian Bartuzi. "Molecular Dynamics Simulations in Protein–Protein Docking." In Protein-Protein Docking, 91–106. New York, NY: Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3985-6_6.

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Bitencourt-Ferreira, Gabriela, and Walter Filgueira de Azevedo. "Docking with GemDock." In Methods in Molecular Biology, 169–88. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9752-7_11.

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Bitencourt-Ferreira, Gabriela, and Walter Filgueira de Azevedo. "Docking with SwissDock." In Methods in Molecular Biology, 189–202. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9752-7_12.

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Bitencourt-Ferreira, Gabriela, Val Oliveira Pintro, and Walter Filgueira de Azevedo. "Docking with AutoDock4." In Methods in Molecular Biology, 125–48. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9752-7_9.

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Eyck, Lynn F. Ten, Jeffrey Mandell, Vladimir Kotlovyi, and Igor Tsigelny. "Fast Molecular Docking Methods." In Structure and Function of Cholinesterases and Related Proteins, 357–66. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4899-1540-5_98.

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Conference papers on the topic "Molecular docking"

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Lancellotti, Giacomo, Gianmarco Accordi, and Gianluca Palermo. "An Experimental Approach to Quantum Molecular Docking." In 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 512–18. IEEE, 2024. https://doi.org/10.1109/qce60285.2024.00066.

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Atanu, Francis O., Estari Mamidala, Charles O. Nwonuma, and Omookolade O. Alejolowo. "Molecular interactions between β-lactoglobulin protein and phytocannabinoids: a molecular docking and dynamics simulation study." In 2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG), 1–4. IEEE, 2024. http://dx.doi.org/10.1109/seb4sdg60871.2024.10630272.

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Ribeiro, Flávio Vinícius da Silva, Ricardo Morais de Miranda, and Solange Maria Vinagre Corrêa. "Aplicação do Docking Molecular para o melhoramento de fármacos." In VIII Simpósio de Estrutura Eletrônica e Dinâmica Molecular. Universidade de Brasília, 2020. http://dx.doi.org/10.21826/viiiseedmol202052.

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Molecular docking uses theoretical chemistry and computer science resources to simulate, at the level of reality, chemical reactions involving molecules and macromolecules. Molecular docking was applied in the study of the interaction of an FX-CNT, evaluating the technique in the optimization of drugs.
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Ellingson, Sally R., and Jerome Baudry. "High-throughput virtual molecular docking." In the second international workshop. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1996023.1996028.

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Samarskaya, Viktoriya, Aleksandr Kovalenko, Galina Sroslova, Margarita Postnova, Aleksandr Shiroky, and Andrei Serov. "Molecular docking data preparation tool." In Saratov Fall Meeting 2018: Computations and Data Analysis: from Nanoscale Tools to Brain Functions, edited by Dmitry E. Postnov. SPIE, 2019. http://dx.doi.org/10.1117/12.2522533.

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Xiao, Yong L., and Donald E. Williams. "Molecular docking using genetic algorithms." In the 1994 ACM symposium. New York, New York, USA: ACM Press, 1994. http://dx.doi.org/10.1145/326619.326721.

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Brindha, M., R. Shelishiyah, and S. Vasanthavalli. "Molecular Docking Analysis Of CFTR Inhibitors." In 2020 Sixth International Conference on Bio Signals, Images, and Instrumentation (ICBSII). IEEE, 2020. http://dx.doi.org/10.1109/icbsii49132.2020.9167624.

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Solis-Vasquez, Leonardo, Diogo Santos-Martins, Andreas F. Tillack, Andreas Koch, Jerome Eberhardt, and Stefano Forli. "Parallelizing Irregular Computations for Molecular Docking." In 2020 IEEE/ACM 10th Workshop on Irregular Applications: Architectures and Algorithms (IA3). IEEE, 2020. http://dx.doi.org/10.1109/ia351965.2020.00008.

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Roh, Youngtae, Jun Lee, Sungjun Park, and Jee-In Kim. "A molecular docking system using CUDA." In the 2009 International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1644993.1644999.

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Silva Moraes, Rafael, and Fernando Gomes de Souza Junior. "Mineração de dados sobre molecular docking." In 2a Conferência Brasileira de Planejamento Experimental e Análise de Dados. ,: Even3, 2022. http://dx.doi.org/10.29327/conbrapa2022.558289.

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Reports on the topic "Molecular docking"

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Kotwal, Shashikant. Grant: Automation of BitterX Molecular Docking of Bitter taste compounds to Human Bitter Taste Receptors (TAS2R). ResearchHub Technologies, Inc., January 2025. https://doi.org/10.55277/researchhub.b0nzqfac.

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Benial. A, Milton Franklin, Pandi Meena. G, Mathavan Thangapandian, and James Jebaseelan Samuel. E. Quantum chemical, spectroscopic and molecular docking investigations of potential pulmonary fibrosis drug methyl 2-chloro 4-iodonicotinate. Peeref, June 2023. http://dx.doi.org/10.54985/peeref.2306p9633440.

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Rafaeli, Ada, Russell Jurenka, and Chris Sander. Molecular characterisation of PBAN-receptors: a basis for the development and screening of antagonists against Pheromone biosynthesis in moth pest species. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7695862.bard.

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The original objectives of the approved proposal included: (a) The determination of species- and tissue-specificity of the PBAN-R; (b) the elucidation of the role of juvenile hormone in gene regulation of the PBAN-R; (c) the identificationof the ligand binding domains in the PBAN-R and (d) the development of efficient screening assays in order to screen potential antagonists that will block the PBAN-R. Background to the topic: Moths constitute one of the major groups of pest insects in agriculture and their reproductive behavior is dependent on chemical communication. Sex-pheromone blends are utilised by a variety of moth species to attract conspecific mates. In most of the moth species sex-pheromone biosynthesis is under circadian control by the neurohormone, PBAN (pheromone-biosynthesis-activating neuropeptide). In order to devise ideal strategies for mating disruption/prevention, we proposed to study the interactions between PBAN and its membrane-bound receptor in order to devise potential antagonists. Major conclusions: Within the framework of the planned objectives we have confirmed the similarities between the two Helicoverpa species: armigera and zea. Receptor sequences of the two Helicoverpa spp. are 98% identical with most changes taking place in the C-terminal. Our findings indicate that PBAN or PBAN-like receptors are also present in the neural tissues and may represent a neurotransmitter-like function for PBAN-like peptides. Surprisingly the gene encoding the PBAN-receptor was also present in the male homologous tissue, but it is absent at the protein level. The presence of the receptor (at the gene- and protein-levels), and the subsequent pheromonotropic activity are age-dependent and up-regulated by Juvenile Hormone in pharate females but down-regulated by Juvenile Hormone in adult females. Lower levels of pheromonotropic activity were observed when challenged with pyrokinin-like peptides than with HezPBAN as ligand. A model of the 3D structure of the receptor was created using the X-ray structure of rhodopsin as a template after sequence alignment of the HezPBAN-R with several other GPCRs and computer simulated docking with the model predicted putative binding sites. Using in silico mutagenesis the predicted docking model was validated with experimental data obtained from expressed chimera receptors in Sf9 cells created by exchanging between the three extracellular loops of the HezPBAN-R and the Drosophila Pyrokinin-R (CG9918). The chimera receptors also indicated that the 3ʳᵈ extracellular loop is important for recognition of PBAN or Diapause hormone ligands. Implications: The project has successfully completed all the objectives and we are now in a position to be able to design and screen potential antagonists for pheromone production. The successful docking simulation-experiments encourage the use of in silico experiments for initial (high-throughput) screening of potential antagonists. However, the differential responses between the expressed receptor (Sf9 cells) and the endogenous receptor (pheromone glands) emphasize the importance of assaying lead compounds using several alternative bioassays (at the cellular, tissue and organism levels). The surprising discovery of the presence of the gene encoding the PBAN-R in the male homologous tissue, but its absence at the protein level, launches opportunities for studying molecular regulation pathways and the evolution of these GPCRs. Overall this research will advance research towards the goal of finding antagonists for this important class of receptors that might encompass a variety of essential insect functions.
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Judson, R. S., E. P. Jaeger, and A. M. Treasurywala. A genetic algorithm based method for docking flexible molecules. Office of Scientific and Technical Information (OSTI), November 1993. http://dx.doi.org/10.2172/10132318.

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Jha, Ramesh, Sang-Min Shin, and Taraka Dale. Rosetta Comparative Modeling and Ligand Docking for a Transcription Factor Library Design to Select Biosensor for an Anthropogenic Molecule. Office of Scientific and Technical Information (OSTI), June 2022. http://dx.doi.org/10.2172/1871442.

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Gurevitz, Michael, William A. Catterall, and Dalia Gordon. face of interaction of anti-insect selective toxins with receptor site-3 on voltage-gated sodium channels as a platform for design of novel selective insecticides. United States Department of Agriculture, December 2013. http://dx.doi.org/10.32747/2013.7699857.bard.

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Voltage-gated sodium channels (Navs) play a pivotal role in excitability and are a prime target of insecticides like pyrethroids. Yet, these insecticides are non-specific due to conservation of Navs in animals, raising risks to the environment and humans. Moreover, insecticide overuse leads to resistance buildup among insect pests, which increases misuse and risks. This sad reality demands novel, more selective, insect killers whose alternative use would avoid or reduce this pressure. As highly selective insect toxins exist in venomous animals, why not exploit this gift of nature and harness them in insect pest control? Many of these peptide toxins target Navs, and since their direct use via transformed crop plants or mediator microorganisms is problematic in public opinion, we focus on the elucidation of their receptor binding sites with the incentive of raising knowledge for design of toxin peptide mimetics. This approach is preferred nowadays by agro-industries in terms of future production expenses and public concern. However, characterization of a non-continuous epitope, that is the channel receptor binding site for such toxins, requires a suitable experimental system. We have established such a system within more than a decade and reached the stage where we employ a number of different insect-selective toxins for the identification of their receptor sites on Navs. Among these toxins we wish to focus on those that bind at receptor site-3 and inhibit Nav inactivation because: (1) We established efficient experimental systems for production and manipulation of site-3 toxins from scorpions and sea anemones. These peptides vary in size and structure but compete for site-3 on insect Navs. Moreover, these toxins exhibit synergism with pyrethroids and with other channel ligands; (2) We determined their bioactive surfaces towards insect and mammalian receptors (see list of publications); (3) We found that despite the similar mode of action on channel inactivation, the preference of the toxins for insect and mammalian channel subtypes varies greatly, which can direct us to structural features in the basis of selectivity; (4) We have identified by channel loop swapping and point mutagenesis extracellular segments of the Navinvolved with receptor site-3. On this basis and using channel scanning mutagenesis, neurotoxin binding, electrophysiological analyses, and structural data we offer: (i) To identify the residues that form receptor site-3 at insect and mammalian Navs; (ii) To identify by comparative analysis differences at site-3 that dictate selectivity toward various Navs; (iii) To exploit the known toxin structures and bioactive surfaces for modeling their docking at the insect and mammalian channel receptors. The results of this study will enable rational design of novel anti-insect peptide mimetics with minimized risks to human health and to the environment. We anticipate that the release of receptor site-3 molecular details would initiate a worldwide effort to design peptide mimetics for that site. This will establish new strategies in insect pest control using alternative insecticides and the combined use of compounds that interact allosterically leading to increased efficiency and reduced risks to humans or resistance buildup among insect pests.
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