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Journal articles on the topic 'Docking'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 March 2025

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1

Wang, Kai, Nan Lyu, Hongjuan Diao, Shujuan Jin, Tao Zeng, Yaoqi Zhou, and Ruibo Wu. "GM-DockZn: a geometry matching-based docking algorithm for zinc proteins." Bioinformatics 36, no. 13 (May 5, 2020): 4004–11. http://dx.doi.org/10.1093/bioinformatics/btaa292.

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Abstract Motivation Molecular docking is a widely used technique for large-scale virtual screening of the interactions between small-molecule ligands and their target proteins. However, docking methods often perform poorly for metalloproteins due to additional complexity from the three-way interactions among amino-acid residues, metal ions and ligands. This is a significant problem because zinc proteins alone comprise about 10% of all available protein structures in the protein databank. Here, we developed GM-DockZn that is dedicated for ligand docking to zinc proteins. Unlike the existing docking methods developed specifically for zinc proteins, GM-DockZn samples ligand conformations directly using a geometric grid around the ideal zinc-coordination positions of seven discovered coordination motifs, which were found from the survey of known zinc proteins complexed with a single ligand. Results GM-DockZn has the best performance in sampling near-native poses with correct coordination atoms and numbers within the top 50 and top 10 predictions when compared to several state-of-the-art techniques. This is true not only for a non-redundant dataset of zinc proteins but also for a homolog set of different ligand and zinc-coordination systems for the same zinc proteins. Similar superior performance of GM-DockZn for near-native-pose sampling was also observed for docking to apo-structures and cross-docking between different ligand complex structures of the same protein. The highest success rate for sampling nearest near-native poses within top 5 and top 1 was achieved by combining GM-DockZn for conformational sampling with GOLD for ranking. The proposed geometry-based sampling technique will be useful for ligand docking to other metalloproteins. Availability and implementation GM-DockZn is freely available at www.qmclab.com/ for academic users. Supplementary information Supplementary data are available at Bioinformatics online.

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2

Salih, Twana Mohsin. "A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model." Iraqi Journal of Pharmaceutical Sciences ( P-ISSN 1683 - 3597 E-ISSN 2521 - 3512) 31, no. 2 (December 24, 2022): 160–68. http://dx.doi.org/10.31351/vol31iss2pp160-168.

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Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzyme. The tested sets are composed of eight receptor-ligand complexes with high resolution crystal structures downloaded from Protein Data Bank website. Molecular dockings were applied between approved HIV-1 protease inhibitors and the HIV-1 protease using AutoDock Vina, 1-Click Docking, and DOCK6. Then, docking poses of the top-ranked solution was realized using UCSF Chimera. Furthermore, Pearson correlation coefficient (r) and coefficient of determination (r2) between the experimental results and the top scored docking results of each program were calculated using Graphpad prism V9.2. After comparing saquinavir top scored binding poses of each docking program with the crystal structure, various conformational changes were observed. Moreover, according to the relative comparison between the top ranked calculated ?Gbinding values against the experimental results, r2 value of AutoDock Vina, 1-Click Docking, and DOCK6 were 0.65, 0.41, and 0.005, respectively. The outcome of this study shows that the top scored binding free energy could not produce the best pose prediction. In addition, AutoDock Vina results have the highest correlation with the experimental results.

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3

Bebić, Dragan, Ladislav Stazić, Antonija Mišura, and Ivan Komar. "EDD – Economic Benefit Analysis of Extending Dry Docking Interval." Transactions on Maritime Science 7, no. 02 (October 22, 2018): 164–73. http://dx.doi.org/10.7225/toms.v07.n02.006.

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The possibility of interval extension between two dry docking is alternatively offered to the shipowners by classification societies. Although, for now, such a possibility is limited only to certain types of ships, a significant shift has been accomplished in accordance with today's technical and technological capacities. It is quite clear that not all shipowners will accept this option, as either five-year or even mid-interval might suit them well. The option introduces an economic benefit, but requires additional preparation to withstand the full interval without negative consequences, primarily related to the protection of underwater part of the hull. The relationship of economic benefits and the cost of investment to successfully pass the complete period gives a clear view to the shipowner for the decision of accepting an extended dry docking period between two consecutive dry dockings. This paper is presenting one of the approaches to calculate feasibility of prolonging dry docking interval. Calculation example represents an economic indicator, crucial for shipowner’s decision to accept prolonged dry docking interval. The paper presents an analysis of underwater hull condition for the vessel with a composite coating. It is based on a collection of actual data registered in the period of seven years. Significant data have been derived from the analysis, allowing basic set up for theoretical assessment as well as the real justification of extended dry docking period between two consecutive dry dockings of the vessel. Some of the presented facts, related to underwater composite coating, might be used for similar calculations.

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4

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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5

Tessaro, Francesca, and Leonardo Scapozza. "How ‘Protein-Docking’ Translates into the New Emerging Field of Docking Small Molecules to Nucleic Acids?" Molecules 25, no. 12 (June 13, 2020): 2749. http://dx.doi.org/10.3390/molecules25122749.

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In this review, we retraced the ‘40-year evolution’ of molecular docking algorithms. Over the course of the years, their development allowed to progress from the so-called ‘rigid-docking’ searching methods to the more sophisticated ‘semi-flexible’ and ‘flexible docking’ algorithms. Together with the advancement of computing architecture and power, molecular docking’s applications also exponentially increased, from a single-ligand binding calculation to large screening and polypharmacology profiles. Recently targeting nucleic acids with small molecules has emerged as a valuable therapeutic strategy especially for cancer treatment, along with bacterial and viral infections. For example, therapeutic intervention at the mRNA level allows to overcome the problematic of undruggable proteins without modifying the genome. Despite the promising therapeutic potential of nucleic acids, molecular docking programs have been optimized mostly for proteins. Here, we have analyzed literature data on nucleic acid to benchmark some of the widely used docking programs. Finally, the comparison between proteins and nucleic acid targets docking highlighted similarity and differences, which are intrinsically related to their chemical and structural nature.

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6

Cakici, Serdar, Selcuk Sumengen, Ugur Sezerman, and Selim Balcisoy. "DockPro: A VR-Based Tool for Protein-Protein Docking Problem." International Journal of Virtual Reality 8, no. 2 (January 1, 2009): 19–23. http://dx.doi.org/10.20870/ijvr.2009.8.2.2720.

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Proteins are large molecules that are vital for all living organisms and they are essential components of many industrial products. The process of binding a protein to another is called protein-protein docking. Many automated algorithms have been proposed to find docking configurations that might yield promising protein-protein complexes. However, these automated methods are likely to come up with false positives and have high computational costs. Consequently, Virtual Reality has been used to take advantage of user's experience on the problem; and proposed applications can be further improved. Haptic devices have been used for molecular docking problems; but they are inappropriate for protein-protein docking due to their workspace limitations. Instead of haptic rendering of forces, we provide a novel visual feedback for simulating physicochemical forces of proteins. We propose an interactive 3D application, DockPro, which enables domain experts to come up with dockings of protein-protein couples by using magnetic trackers and gloves in front of a large display.

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7

Sellers, Michael S., and Margaret M. Hurley. "XPairIt Docking Protocolfor peptide docking and analysis." Molecular Simulation 42, no. 2 (April 23, 2015): 149–61. http://dx.doi.org/10.1080/08927022.2015.1025267.

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8

Rabar, Denis, Danijela Rabar, and Duško Pavletić. "Two-Step Manufacturing Process Measurement Model Using Qualitative and Quantitative Data—A Case of Newbuilding Dry-Docking." Journal of Marine Science and Engineering 9, no. 5 (April 25, 2021): 464. http://dx.doi.org/10.3390/jmse9050464.

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Newbuilding dry-docking is a part of the shipbuilding manufacturing process, common for vessels built on slipways. The subject of this research is steel-built vessels intended for non-restricted sea-going navigation. Based on former experience, the necessity of the dry-docking projects measurement has been noted as a managerial tool for performance estimation and project comparison. The dry-docking project is a complex task which includes the first self-propelled sea passage and the transfer of the manufacturing process to a remote place. The dry-docking result is a surveyed and coated vessel ready for sea trials and five-year service until the next dry-docking. This paper deals with a model which enables process measurement using the analytic hierarchy process (AHP) method for qualitative data related to the dry-docking places and data envelopment analysis (DEA) for quantitative data related to the vessels’ technical and cost data. The modelled data are collected from the completed dry-dockings, and the twenty-nine studied vessels represent the decision-making units (DMU) used in two-step process measurement calculations. The obtained results can distinguish the efficient DMUs, which create an efficient frontier as benchmarks or “the best practice units” in the given DMU set. For the non-efficient DMUs, the efficiency score and rate of improvements needed to reach the efficient frontier will be calculated, and the sources of inefficiency will be recognized.

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9

Yoon. "Docking Time." Transition, no. 115 (2014): 116. http://dx.doi.org/10.2979/transition.115.116.

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10

Sheppard, Terry L. "Docking PCNA." Nature Chemical Biology 8, no. 5 (April 17, 2012): 410. http://dx.doi.org/10.1038/nchembio.948.

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11

Brummer, Tilman, Carsten Schmitz-Peiffer, and Roger J. Daly. "Docking proteins." FEBS Journal 277, no. 21 (September 30, 2010): 4356–69. http://dx.doi.org/10.1111/j.1742-4658.2010.07865.x.

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12

Edwards, A. "Tail docking." Veterinary Record 119, no. 13 (September 27, 1986): 339–40. http://dx.doi.org/10.1136/vr.119.13.339.

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13

Brown, S., and M. Leggett. "Tail docking." Veterinary Record 119, no. 5 (August 2, 1986): 119. http://dx.doi.org/10.1136/vr.119.5.119-a.

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14

Grantham, C. "Tail docking." Veterinary Record 134, no. 23 (June 4, 1994): 608. http://dx.doi.org/10.1136/vr.134.23.608.

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15

Ferens, P. "Tail docking." Veterinary Record 134, no. 23 (June 4, 1994): 608. http://dx.doi.org/10.1136/vr.134.23.608-b.

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16

Buckwell, A. "Tail docking." Veterinary Record 134, no. 25 (June 18, 1994): 658–59. http://dx.doi.org/10.1136/vr.134.25.658.

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17

DAVEY, C. "Tail docking." Australian Veterinary Journal 74, no. 6 (December 1996): 476. http://dx.doi.org/10.1111/j.1751-0813.1996.tb07578.x.

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18

Grace, John. "Docking - "congratulations"." Australian Veterinary Journal 77, no. 6 (June 1999): 409–10. http://dx.doi.org/10.1111/j.1751-0813.1999.tb10331.x.

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19

Barril, Xavier. "Docking points." Nature Chemistry 6, no. 7 (June 20, 2014): 560–61. http://dx.doi.org/10.1038/nchem.1986.

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20

Stephan, Konrad, and Nils Boysen. "Cross-docking." Journal of Management Control 22, no. 1 (July 12, 2011): 129–37. http://dx.doi.org/10.1007/s00187-011-0124-9.

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21

Bell, Elaine. "TCR docking." Nature Reviews Immunology 2, no. 9 (September 2002): 626. http://dx.doi.org/10.1038/nri898.

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22

Kuntz, Irwin D. "Darwinian Docking." Journal of Computer-Aided Molecular Design 26, no. 1 (December 6, 2011): 73–75. http://dx.doi.org/10.1007/s10822-011-9503-4.

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23

N. Cavasotto, Claudio. "Homology Models in Docking and High-Throughput Docking." Current Topics in Medicinal Chemistry 11, no. 12 (June 1, 2011): 1528–34. http://dx.doi.org/10.2174/156802611795860951.

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24

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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25

Pérez, Carlos, and Angel R. Ortiz. "Evaluation of Docking Functions for Protein−Ligand Docking." Journal of Medicinal Chemistry 44, no. 23 (November 2001): 3768–85. http://dx.doi.org/10.1021/jm010141r.

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26

Rizzi, Andrea, Andrea Ciacci, and Anna Maria Capelli. "GLIMPSED: An Improved Docking Protocol for Cognate Docking." Molecular Informatics 35, no. 8-9 (May 12, 2016): 350–57. http://dx.doi.org/10.1002/minf.201501025.

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27

Cao, Bin, Jia Jin Yuan, Tao Zhang, Shen Tian Weng, and Jian Yao. "FPGA - Based Docking Mechanism Prototype Docking Ring Control Research." Procedia Computer Science 166 (2020): 252–57. http://dx.doi.org/10.1016/j.procs.2020.02.104.

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28

Kontoyianni, Maria, Laura M. McClellan, and Glenn S. Sokol. "Evaluation of Docking Performance: Comparative Data on Docking Algorithms." Journal of Medicinal Chemistry 47, no. 3 (January 2004): 558–65. http://dx.doi.org/10.1021/jm0302997.

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29

UNNO, Mikuru, and Masayoshi WADA. "Study on Reducing Docking Time in Plug-in Docking." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2022 (2022): 2P1—F12. http://dx.doi.org/10.1299/jsmermd.2022.2p1-f12.

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30

Wang, Xu-Feng, Jian-Min Li, Xing-Wei Kong, Xin-Min Dong, and Bo Zhang. "Towards docking safety analysis for unmanned aerial vehicle probe-drogue autonomous aerial refueling based on docking success-probability and docking reachability." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 11 (October 16, 2018): 3893–905. http://dx.doi.org/10.1177/0954410018806804.

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Docking safety is a key problem during the docking phase of the unmanned aerial vehicle probe-drogue autonomous aerial refueling (UAV-PD-AAR). To solve this problem, a novel and effective method based on docking success-probability and docking reachability is presented in this paper. Firstly, by employing the location of the drogue with respect to the probe, a docking success-probability estimation algorithm is proposed to give the probe-drogue docking success-probability in real time, with UAV control and drogue attitude considered. Secondly, considering UAV longitudinal dynamics, a docking reachability calculation algorithm for docking reachable set is designed to ensure the UAV can safely reach the docking target set, by using Hamilton–Jacobi equation. Finally, the docking safety algorithm during the docking phase of UAV-PD-AAR is constructed, based on the estimated docking success-probability and the calculated docking reachability. The experiments of docking success-probability estimation and docking reachability calculation were conducted, which can be used towards docking safety analysis during the docking phase of UAV-PD-AAR.

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31

El-Nahas, Ahmed M., Yasmine S. Moemen, and Serry, A. El-Beily Serry, A. El-Beily. "Docking Studies on Novel HCVNS5b Inhibitors." Indian Journal of Applied Research 3, no. 5 (October 1, 2011): 64–67. http://dx.doi.org/10.15373/2249555x/may2013/18.

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32

Hou, Shu Ping, Xiao Yan Wang, and Jian Nan Zhang. "A Method of Rendezvous and Docking Based on the 6-DOF Parallel Mechanism in Subsea Environment." Applied Mechanics and Materials 574 (July 2014): 651–57. http://dx.doi.org/10.4028/www.scientific.net/amm.574.651.

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According to the condition of the docking of the oceanic space with low visibility,strong sea current and large declining attitude, the rendezvous and docking device based on the 6-DOF parallel mechanism is proposed. A method of the rendezvous and docking operation is discussed between subsea vehicle and deep-sea space station. The mathematic model of the docking device is established after analyzing the structural characteristics and operational principle of subsea vehicle docking device, the momentum of the docking device. In order to satisfy the need of the subsea docking, a moving path is brought forward for the docking device. The impacting analysis of the docking device is conducted under its docking trait, which shows that the docking device could achieve the rendezvous and docking in case of the serious condition in subsea environment.

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33

Sulimov, Vladimir B., Danil C. Kutov, and Alexey V. Sulimov. "Advances in Docking." Current Medicinal Chemistry 26, no. 42 (January 8, 2020): 7555–80. http://dx.doi.org/10.2174/0929867325666180904115000.

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Background: Design of small molecules which are able to bind to the protein responsible for a disease is the key step of the entire process of the new medicine discovery. Atomistic computer modeling can significantly improve effectiveness of such design. The accurate calculation of the free energy of binding a small molecule (a ligand) to the target protein is the most important problem of such modeling. Docking is one of the most popular molecular modeling methods for finding ligand binding poses in the target protein and calculating the protein-ligand binding energy. This energy is used for finding the most active compounds for the given target protein. This short review aims to give a concise description of distinctive features of docking programs focusing on computation methods and approximations influencing their accuracy. Methods: This review is based on the peer-reviewed research literature including author’s own publications. The main features of several representative docking programs are briefly described focusing on their characteristics influencing docking accuracy: force fields, energy calculations, solvent models, algorithms of the best ligand pose search, global and local optimizations, ligand and target protein flexibility, and the simplifications made for the docking accelerating. Apart from other recent reviews focused mainly on the performance of different docking programs, in this work, an attempt is made to extract the most important functional characteristics defining the docking accuracy. Also a roadmap for increasing the docking accuracy is proposed. This is based on the new generation of docking programs which have been realized recently. These programs and respective new global optimization algorithms are described shortly. Results: Several popular conventional docking programs are considered. Their search of the best ligand pose is based explicitly or implicitly on the global optimization problem. Several algorithms are used to solve this problem, and among them, the heuristic genetic algorithm is distinguished by its popularity and an elaborate design. All conventional docking programs for their acceleration use the preliminary calculated grids of protein-ligand interaction potentials or preferable points of protein and ligand conjugation. These approaches and commonly used fitting parameters restrict strongly the docking accuracy. Solvent is considered in exceedingly simplified approaches in the course of the global optimization and the search for the best ligand poses. More accurate approaches on the base of implicit solvent models are used frequently for more careful binding energy calculations after docking. The new generation of docking programs are developed recently. They find the spectrum of low energy minima of a protein-ligand complex including the global minimum. These programs should be more accurate because they do not use a preliminary calculated grid of protein-ligand interaction potentials and other simplifications, the energy of any conformation of the molecular system is calculated in the frame of a given force field and there are no fitting parameters. A new docking algorithm is developed and fulfilled specially for the new docking programs. This algorithm allows docking a flexible ligand into a flexible protein with several dozen mobile atoms on the base of the global energy minimum search. Such docking results in improving the accuracy of ligand positioning in the docking process. The adequate choice of the method of molecular energy calculations also results in the better docking positioning accuracy. An advancement in the application of quantum chemistry methods to docking and scoring is revealed. Conclusion: The findings of this review confirm the great demand in docking programs for discovery of new medicine substances with the help of molecular modeling. New trends in docking programs design are revealed. These trends are focused on the increase of the docking accuracy at the expense of more accurate molecular energy calculations without any fitting parameters, including quantum-chemical methods and implicit solvent models, and by using new global optimization algorithms which make it possible to treat flexibility of ligands and mobility of protein atoms simultaneously. Finally, it is shown that all the necessary prerequisites for increasing the docking accuracy can be accomplished in practice.

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34

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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35

Ackerman, Nicola. "The docking debate." Veterinary Nursing Journal 21, no. 5 (May 2006): 23–24. http://dx.doi.org/10.1080/17415349.2006.11013477.

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36

Maher, Kelly. "Anti-docking website." Australian Veterinary Journal 78, no. 3 (March 2000): 206. http://dx.doi.org/10.1111/j.1751-0813.2000.tb10611.x.

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37

Suda, Takashi. "Pre-docking procedure." ASVIDE 3 (July 2016): 277. http://dx.doi.org/10.21037/asvide.2016.277.

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38

Scheidereit, Claus. "Docking IκB kinases." Nature 395, no. 6699 (September 1998): 225–26. http://dx.doi.org/10.1038/26121.

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39

Humphreys, P. "Castration and docking." Veterinary Record 124, no. 19 (May 13, 1989): 520. http://dx.doi.org/10.1136/vr.124.19.520-c.

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40

Mellor, D. "Castration and docking." Veterinary Record 125, no. 1 (July 1, 1989): 24–25. http://dx.doi.org/10.1136/vr.125.1.24.

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41

Dean, S., W. Miller, J. Webster, G. Averis, A. Logan, R. Keizer, I. Sladden, and I. Macadam. "Docking of dogs." Veterinary Record 130, no. 23 (June 6, 1992): 519. http://dx.doi.org/10.1136/vr.130.23.519.

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Leach, T. "Docking of dogs." Veterinary Record 130, no. 24 (June 13, 1992): 543. http://dx.doi.org/10.1136/vr.130.24.543-b.

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Fearn, A., S. Crawford, M. Fraser, and M. Petersen-Jones. "Docking of dogs." Veterinary Record 130, no. 25 (June 20, 1992): 562. http://dx.doi.org/10.1136/vr.130.25.562.

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Turner, T. "Docking of dogs." Veterinary Record 130, no. 25 (June 20, 1992): 562. http://dx.doi.org/10.1136/vr.130.25.562-a.

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Bate, T. "Docking of dogs." Veterinary Record 130, no. 26 (June 27, 1992): 582. http://dx.doi.org/10.1136/vr.130.26.582.

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46

Cunningham, J. "Docking of dogs." Veterinary Record 131, no. 1 (July 4, 1992): 20. http://dx.doi.org/10.1136/vr.131.1.20.

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Stirling, J. "Docking of dogs." Veterinary Record 131, no. 15 (October 10, 1992): 351. http://dx.doi.org/10.1136/vr.131.15.351.

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Mercer, P. "Docking of dogs." Veterinary Record 131, no. 16 (October 17, 1992): 374–75. http://dx.doi.org/10.1136/vr.131.16.374.

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Webster, J. "Docking of dogs." Veterinary Record 131, no. 16 (October 17, 1992): 374. http://dx.doi.org/10.1136/vr.131.16.374-a.

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Neal, K. "Docking of dogs." Veterinary Record 131, no. 17 (October 24, 1992): 399. http://dx.doi.org/10.1136/vr.131.17.399-b.

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