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Journal articles on the topic 'Molecular docking'

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

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1

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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2

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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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

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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6

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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7

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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8

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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9

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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10

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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11

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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12

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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13

Burle, Sushil S., Krishna R. Gupta, Yogeshri J. Jibhkate, Atul T. Hemke, and Milind J. Umekar. "Insights into molecular docking: A comprehensive view." International Journal of Pharmaceutical Chemistry and Analysis 10, no. 3 (September 15, 2023): 175–84. http://dx.doi.org/10.18231/j.ijpca.2023.030.

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Molecular docking software is mainly used in drug development. Molecular docking offers a wide range of useful techniques for the creation and analysis of pharmaceuticals. Before now, predicting the target for a receptor was extremely challenging however, docking the target protein with a ligand is a straightforward and dependable procedure presently and binding affinity is designed. To see a molecule's three-dimensional structure, a variety of docking tools have been created. The docking score can also be examined using a variety of computational techniques. This review mainly emphases on the core idea of molecular docking, as well as its major uses and many kinds of interaction, Basics requirements for molecular docking, Molecular Approach, Application, and Software available for the Docking of molecules.
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14

Naji, Amel Mohson, Ahmed Mutanabbi Abdula, Olfat A. Nief, and Ebtihal K. Abdullah. "Synthesis, Characterization, Antimicrobial and Molecular Docking Study of Benzooxadiazole Derivatives." Chemistry & Chemical Technology 16, no. 1 (February 20, 2022): 25–33. http://dx.doi.org/10.23939/chcht16.01.025.

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In this study, a series of new1,2,5-oxadiazole compounds derived from 4-chloro-7-nitro-benzo 1,2,5-oxadiazole was synthesized using different organic procedures. The resulting derivatives were chemically characterized and their structures were confirmed by FT-IR and NMR analysis. All the compounds were also evaluated for their antibacterial and antifungal activity against four types of pathogenic bacteria: S.aureus, S.epidermidis (as gram-negative bacteria), E.coli, Klebsiella spp. (as gram-positive bacteria) and the fungus Candida albicans using the agar well diffusion method. The synthesized oxadiazole derivatives exhibited significant antibacterial and moderate antifungal activities. Exploring the binding between the potent synthesized derivative 8 within the active site of glucosamine-6-phosphate synthase, the target enzyme for the antimicrobial agents was achieved using Autodock 4.2 package. The interaction modes of the generated conformers inside the binding pocket were found to enhance the in vitro results, and strongly recommended the new derivatives as promising antimicrobial agents.
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15

Chopra, Neetu, Kiranpreet kaur, and Sanjeev Kumar. "Synthesis, Molecular Docking and Antimicrobial Evaluation of New Tetrahydrobenzothienopyrimidine Derivatives." International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (October 31, 2018): 1084–96. http://dx.doi.org/10.31142/ijtsrd18756.

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16

Fan, Mengran, Jian Wang, Huaipan Jiang, Yilin Feng, Mehrdad Mahdavi, Kamesh Madduri, Mahmut T. Kandemir, and Nikolay V. Dokholyan. "GPU-Accelerated Flexible Molecular Docking." Journal of Physical Chemistry B 125, no. 4 (January 26, 2021): 1049–60. http://dx.doi.org/10.1021/acs.jpcb.0c09051.

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17

Atkovska, Kalina, Sergey Samsonov, Maciej Paszkowski-Rogacz, and M. Pisabarro. "Multipose Binding in Molecular Docking." International Journal of Molecular Sciences 15, no. 2 (February 14, 2014): 2622–45. http://dx.doi.org/10.3390/ijms15022622.

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18

Suvannang, Naravut, Chanin Nantasenamat, Chartchalerm Isarankura-Na-Ayudhya, and Virapong Prachayasittikul. "Molecular Docking of Aromatase Inhibitors." Molecules 16, no. 5 (April 28, 2011): 3597–617. http://dx.doi.org/10.3390/molecules16053597.

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19

Brooijmans, Natasja, and Irwin D. Kuntz. "Molecular Recognition and Docking Algorithms." Annual Review of Biophysics and Biomolecular Structure 32, no. 1 (June 2003): 335–73. http://dx.doi.org/10.1146/annurev.biophys.32.110601.142532.

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20

Liu, Yu, Lei Zhao, Mingli Li, and Changfei Zhao. "Swarm intelligence for molecular docking." International Journal of Modelling, Identification and Control 18, no. 4 (2013): 357. http://dx.doi.org/10.1504/ijmic.2013.053541.

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21

Bastos, M., M. H. dos Santos, and I. Camps. "Molecular docking vs structure optimization." Journal of Organic Chemistry Research 1, no. 1 (May 1, 2013): 1–9. http://dx.doi.org/10.12785/jocr/010101.

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22

Huang, Niu, Brian K. Shoichet, and John J. Irwin. "Benchmarking Sets for Molecular Docking." Journal of Medicinal Chemistry 49, no. 23 (November 2006): 6789–801. http://dx.doi.org/10.1021/jm0608356.

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23

Shoichet, Brian K., Susan L. McGovern, Binqing Wei, and John J. Irwin. "Lead discovery using molecular docking." Current Opinion in Chemical Biology 6, no. 4 (August 2002): 439–46. http://dx.doi.org/10.1016/s1367-5931(02)00339-3.

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24

Ouh-young, Michael Pique, Mark Harris, John Hughes, Neela Srinivasan, and FrederickP Brooks. "Force display in molecular docking." Journal of Molecular Graphics 6, no. 4 (December 1988): 224. http://dx.doi.org/10.1016/s0263-7855(98)80039-8.

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25

Salo, Jukka-Pekka, Ari Yliniemelä, and Jyrki Taskinen. "Parameter Refinement for Molecular Docking." Journal of Chemical Information and Computer Sciences 38, no. 5 (September 1998): 832–39. http://dx.doi.org/10.1021/ci9801825.

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Sturlese, Mattia, Massimo Bellanda, and Stefano Moro. "NMR-Assisted Molecular Docking Methodologies." Molecular Informatics 34, no. 8 (June 19, 2015): 513–25. http://dx.doi.org/10.1002/minf.201500012.

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27

Gschwend, Daniel A., Andrew C. Good, and Irwin D. Kuntz. "Molecular docking towards drug discovery." Journal of Molecular Recognition 9, no. 2 (March 1996): 175–86. http://dx.doi.org/10.1002/(sici)1099-1352(199603)9:2<175::aid-jmr260>3.0.co;2-d.

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28

Sobolev, Vladimir, Rebecca C. Wade, Gert Vriend, and Marvin Edelman. "Molecular docking using surface complementarity." Proteins: Structure, Function, and Bioinformatics 25, no. 1 (May 1996): 120–29. http://dx.doi.org/10.1002/(sici)1097-0134(199605)25:1<120::aid-prot10>3.0.co;2-m.

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Sobolev, Vladimir, Rebecca C. Wade, Gert Vriend, and Marvin Edelman. "Molecular docking using surface complementarity." Proteins: Structure, Function, and Genetics 25, no. 1 (May 1996): 120–29. http://dx.doi.org/10.1002/(sici)1097-0134(199605)25:1<120::aid-prot10>3.3.co;2-1.

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Shoichet, Brian K., Andrew R. Leach, and Irwin D. Kuntz. "Ligand solvation in molecular docking." Proteins: Structure, Function, and Genetics 34, no. 1 (January 1, 1999): 4–16. http://dx.doi.org/10.1002/(sici)1097-0134(19990101)34:1<4::aid-prot2>3.0.co;2-6.

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31

Shoichet, Brian K., Irwin D. Kuntz, and Dale L. Bodian. "Molecular docking using shape descriptors." Journal of Computational Chemistry 13, no. 3 (April 1992): 380–97. http://dx.doi.org/10.1002/jcc.540130311.

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32

Rudnitskaya, Aleksandra, Béla Török, and Marianna Török. "Molecular docking of enzyme inhibitors." Biochemistry and Molecular Biology Education 38, no. 4 (August 5, 2010): 261–65. http://dx.doi.org/10.1002/bmb.20392.

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33

Kaur, Kiranpreet, Paranjeet Kaur, Amit Mittal, Surendra Kumar Nayak, and Gopal L. Khatik. "DESIGN AND MOLECULAR DOCKING STUDIES OF NOVEL ANTIMICROBIAL PEPTIDES USING AUTODOCK MOLECULAR DOCKING SOFTWARE." Asian Journal of Pharmaceutical and Clinical Research 10, no. 16 (September 16, 2017): 28. http://dx.doi.org/10.22159/ajpcr.2017.v10s4.21332.

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Objective: Design of novel antimicrobial peptides and study through the molecular docking.Methods: The molecular structures were drawn in ChemBiodraw ultra and by the help of ChemBiodraw 3D, all structures were energy minimized by theMM2 method and converted to pdbextension file which is readable at the ADT interface. The AutoDock Vina (ADT) 1.5.6 software is used for molecular docking purposes.Results: Eight antimicrobial peptides (AMPs) were designed based on theMP196antimicrobial peptide. Among these KP_03R (FWRWRW-NH2) showed good binding affinity. These peptides also showed the stereochemical influence on affinity toward the3vma protein of E. coli, where AMP with R stereochemistry showed better activity than its opposite stereochemistry. Conclusion: Novel AMPs were designed by modifications on the MP196 a short chain of amino acids antimicrobial peptides. Molecular docking software was used to determine the binding affinity between drug and receptor protein. Among all the designed peptides KP_03R(FWRWRW-NH2) showed the maximum binding affinity against thepenicillin-binding protein of E.coli and also exhibited stereoselective activity.
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34

Anand, S. Athavan Alias, C. Loganathan, K. Saravanan, and S. Kabilan. "Comparison of Molecular Docking and Molecular Dynamics Simulations of 1,3-Thiazin-4-One with MDM2 Protein." International Letters of Chemistry, Physics and Astronomy 60 (September 2015): 161–67. http://dx.doi.org/10.18052/www.scipress.com/ilcpa.60.161.

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The molecular docking and molecular dynamics simulations studies of 1,3–thiazin–4–one derivative with a bonafide oncogene protein MDM2 (PDB ID: 4HBM) was investigated. Both the docking and dynamics simulations were performed in Schrödinger software suite 2014 using Glide and Desmond modules. The results of docking and dynamics were compared to investigate the possible binding modes of the thiazinone derivative with 4HBM. The tested molecule shows critical interactions with the important amino acid His 96 which is necessary for the inhibition of MDM2 in both docking and dynamic studies.
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Anand, S. Athavan Alias, C. Loganathan, K. Saravanan, and S. Kabilan. "Comparison of Molecular Docking and Molecular Dynamics Simulations of 1,3-Thiazin-4-One with MDM2 Protein." International Letters of Chemistry, Physics and Astronomy 60 (September 30, 2015): 161–67. http://dx.doi.org/10.56431/p-m93n64.

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The molecular docking and molecular dynamics simulations studies of 1,3–thiazin–4–one derivative with a bonafide oncogene protein MDM2 (PDB ID: 4HBM) was investigated. Both the docking and dynamics simulations were performed in Schrödinger software suite 2014 using Glide and Desmond modules. The results of docking and dynamics were compared to investigate the possible binding modes of the thiazinone derivative with 4HBM. The tested molecule shows critical interactions with the important amino acid His 96 which is necessary for the inhibition of MDM2 in both docking and dynamic studies.
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Bastos, Luana Luiza, and Giovana Fiorini. "Re-docking Molecular Utilizando o PyMOL e AutoDock VINA." BIOINFO 3, no. 1 (September 21, 2023): 21. http://dx.doi.org/10.51780/bioinfo-03-21.

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O tutorial a seguir aborda a técnica de re-docking utilizada como etapa inicial em simulações de docking molecular para validar a ferramenta utilizada, bem como suas funções de pontuação. O re-docking consiste em separar um complexo proteína-ligante resolvido experimentalmente e buscar encontrar uma conformação parecida através do docking. Neste tutorial utilizaremos o PyMOL como uma ferramenta visual auxiliar para o re-docking utilizando o Vina.
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Das, Paramita, Rahim Bagwan, Syed Sohaila, Anjali Nayak, Ishika Sanyasi, Padma P. Prabhu, and M. K. Ranganath. "Anti-Tuberculosis and Molecular Docking Study of – Rhizomes of Curcuma caesia." Indian Journal Of Science And Technology 16, no. 47 (January 4, 2024): 4504–11. http://dx.doi.org/10.17485/ijst/v16i47.2996.

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Adhilakshmi, A., and S. Darlin Quine. "Design, Molecular Docking, DFT and Antimicrobial Studies of Novel Benzimdazole Derivatives." International Journal of Science and Research (IJSR) 11, no. 1 (January 5, 2022): 1319–24. http://dx.doi.org/10.21275/sr22121144929.

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Santos, Lorena Limao Vieira dos, Jhonatas Rodrigues Barbosa, Renato Araújo da Costa, and Lourenço Lúcia de Fátima Henriques. "Antimicrobial packaging based on molecular docking of natural products." Peer Review 6, no. 15 (August 25, 2024): 203–16. http://dx.doi.org/10.53660/prw-2493-4518.

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For a long time, studies on food packaging focused on antimicrobial agents, without, however, explaining the mechanisms. Therefore, in this analysis and opinion text, we approach the promising scenario, regarding the use of molecular docking techniques in the development of antimicrobial packaging. Molecular docking was identified as an important guidance tool, showing researchers which molecules had effective antimicrobial activity and their mechanisms. Furthermore, based on molecular docking studies, researchers were able to optimize in vitro and in vivo antimicrobial experiments. The targeted approach was efficient in developing antimicrobial packaging, which increased the shelf life of several foods. We consider molecular docking an indispensable tool for studies on antimicrobial packaging and a promising field of research. Keywords: Molecular docking; Food packaging; Antimicrobial potential; Shelf life; Molecular docking. Durante muito tempo, os estudos sobre embalagens de alimentos focaram-se nos agentes antimicrobianos, sem, no entanto, explicar os mecanismos. Portanto, neste texto de análise e opinião, abordamos o cenário promissor, no que diz respeito à utilização de técnicas de docking molecular no desenvolvimento de embalagens antimicrobianas. O docking molecular foi identificado como uma importante ferramenta de orientação, mostrando aos pesquisadores quais moléculas tinham atividade antimicrobiana eficaz e seus mecanismos. Além disso, com base em estudos de acoplamento molecular, os pesquisadores conseguiram otimizar experimentos antimicrobianos in vitro e in vivo. A abordagem direcionada foi eficiente no desenvolvimento de embalagens antimicrobianas, o que aumentou a vida útil de diversos alimentos. Consideramos o docking molecular uma ferramenta indispensável para estudos sobre embalagens antimicrobianas e um campo de pesquisa promissor. Palavras-chave: Docagem molecular; Embalagem de alimentos; Potencial antimicrobiano; Vida útil; Acoplamento molecular.
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Jakhar, Ritu, Mehak Dangi, Alka Khichi, and Anil Kumar Chhillar. "Relevance of Molecular Docking Studies in Drug Designing." Current Bioinformatics 15, no. 4 (June 11, 2020): 270–78. http://dx.doi.org/10.2174/1574893615666191219094216.

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Molecular Docking is used to positioning the computer-generated 3D structure of small ligands into a receptor structure in a variety of orientations, conformations and positions. This method is useful in drug discovery and medicinal chemistry providing insights into molecular recognition. Docking has become an integral part of Computer-Aided Drug Design and Discovery (CADDD). Traditional docking methods suffer from limitations of semi-flexible or static treatment of targets and ligand. Over the last decade, advances in the field of computational, proteomics and genomics have also led to the development of different docking methods which incorporate protein-ligand flexibility and their different binding conformations. Receptor flexibility accounts for more accurate binding pose predictions and a more rational depiction of protein binding interactions with the ligand. Protein flexibility has been included by generating protein ensembles or by dynamic docking methods. Dynamic docking considers solvation, entropic effects and also fully explores the drug-receptor binding and recognition from both energetic and mechanistic point of view. Though in the fast-paced drug discovery program, dynamic docking is computationally expensive but is being progressively used for screening of large compound libraries to identify the potential drugs. In this review, a quick introduction is presented to the available docking methods and their application and limitations in drug discovery.
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Dawood, A. A., M. A. A. Altobje, and Z. T. Al-Rrassam. "Molecular Docking of SARS-CoV-2 Nucleocapsid Protein with Angiotensin-Converting Enzyme II." Mikrobiolohichnyi Zhurnal 83, no. 2 (April 17, 2021): 82–92. http://dx.doi.org/10.15407/microbiolj83.02.082.

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SARS-CoV-2 remains life-threatening human pathogen witnessed in the present world. Purpose. The key objective of this research was to incorporate a bioinformatics technique to forecast the molecular docking of the ACE2-associated SARS-CoVs nucleocapsid protein. Methods. Different bioinformatics tools were used in this study in order to compare the chemical structures with their biological behaviour at the levels of atoms and the ligand-binding affinity. This research sought to investigate new data analysis. Results. It was computed the basic 2D structure that occurs in all models, requiring ion ligand binding sites to be predicted. The highlights of the analysis and the associated characteristics are largely responsible for nucleocapsid protein and ACE2 receptor that can be further changed for improved binding and selectivity. Conclusions. The precise functional importance of protein-protein docking cannot be established. But the detection of molecular docking can aid in self-association proteins in our summary, serving as a regulatory switch for the protein’s localization.
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Nurisso, Alessandra, Juan Bravo, Pierre-Alain Carrupt, and Antoine Daina. "Molecular Docking Using the Molecular Lipophilicity Potential as Hydrophobic Descriptor: Impact on GOLD Docking Performance." Journal of Chemical Information and Modeling 52, no. 5 (April 21, 2012): 1319–27. http://dx.doi.org/10.1021/ci200515g.

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43

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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Sulimov, Alexey, Danil Kutov, Ivan Ilin, and Vladimir Sulimov. "Quantum-Chemical Quasi-Docking for Molecular Dynamics Calculations." Nanomaterials 12, no. 2 (January 15, 2022): 274. http://dx.doi.org/10.3390/nano12020274.

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The quantum quasi-docking procedure is used to compare the docking accuracies of two quantum-chemical semiempirical methods, namely, PM6-D3H4X and PM7. Quantum quasi-docking is an approximation to quantum docking. In quantum docking, it is necessary to search directly for the global minimum of the energy of the protein-ligand complex calculated by the quantum-chemical method. In quantum quasi-docking, firstly, we look for a wide spectrum of low-energy minima, calculated using the MMFF94 force field, and secondly, we recalculate the energies of all these minima using the quantum-chemical method, and among these recalculated energies we determine the lowest energy and the corresponding ligand position. Both PM6-D3H4X and PM7 are novel methods that describe well-dispersion interactions, hydrogen and halogen bonds. The PM6-D3H4X and PM7 methods are used with the COSMO implicit solvent model as it is implemented in the MOPAC program. The comparison is made for 25 high quality protein-ligand complexes. Firstly, the docking positioning accuracies have been compared, and we demonstrated that PM7+COSMO provides better positioning accuracy than PM6-D3H4X. Secondly, we found that PM7+COSMO demonstrates a much higher correlation between the calculated and measured protein–ligand binding enthalpies than PM6-D3H4X. For future quantum docking PM7+COSMO is preferable, but the COSMO model must be improved.
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Deshmukh, Harshada S., Vaishnavi M. Dhangude, Tanvi A. Bhosale,, Raksha V. Patil, Rukhsar R. Bagwan, Rupali G. Ghule, Pranali A. Tate Deshmukh, Rachana B. Lamkane, and Shivraj S. Shivpuje. "Precision in Binding: An Insightful Review on Molecular Docking Techniques and their Applications." South Asian Research Journal of Pharmaceutical Sciences 7, no. 01 (February 11, 2025): 29–42. https://doi.org/10.36346/sarjps.2025.v07i01.005.

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The numerical modelling of structural compounds made up of two or more interacting molecules is known as molecular docking. Predicting the desired three-dimensional structure is the aim of molecular docking. Software for molecular docking is mostly utilised in drug development. Easy access to structural databases and molecules have become crucial mechanisms. Molecular docking is a potent computer technique that is essential for structural biology, drug development, and bio-molecular interaction research, giving a comprehensive understanding of its significance in contemporary scientific research. Predicting how a small molecule, frequently a possible drug, would interact with a target biomolecule, such as DNA or a protein, is known as molecular docking. In order to help find novel drug candidates, improve already-existing molecules, and comprehend the complex interactions between medications and receptors, this procedure looks at the ligand's energetic and spatial compatibility with the receptor's active site. Because it predicts how well two molecules will bind after docking and identifies the optimal places for molecules to occupy when linked together, molecular docking is a crucial step in the drug development process.
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Serrano, Antonio, Baldomero Imbernón, Horacio Pérez-Sánchez, José M. Cecilia, Andrés Bueno-Crespo, and José L. Abellán. "QN-Docking: An innovative molecular docking methodology based on Q-Networks." Applied Soft Computing 96 (November 2020): 106678. http://dx.doi.org/10.1016/j.asoc.2020.106678.

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47

Pinzi, Luca, and Giulio Rastelli. "Molecular Docking: Shifting Paradigms in Drug Discovery." International Journal of Molecular Sciences 20, no. 18 (September 4, 2019): 4331. http://dx.doi.org/10.3390/ijms20184331.

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Molecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest, predicting ligand-target interactions at a molecular level, or delineating structure-activity relationships (SAR), without knowing a priori the chemical structure of other target modulators. Although it was originally developed to help understanding the mechanisms of molecular recognition between small and large molecules, uses and applications of docking in drug discovery have heavily changed over the last years. In this review, we describe how molecular docking was firstly applied to assist in drug discovery tasks. Then, we illustrate newer and emergent uses and applications of docking, including prediction of adverse effects, polypharmacology, drug repurposing, and target fishing and profiling, discussing also future applications and further potential of this technique when combined with emergent techniques, such as artificial intelligence.
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李, 博. "Progress in Molecular Docking and Molecular Dynamics Simulation." Journal of Comparative Chemistry 03, no. 01 (2019): 1–10. http://dx.doi.org/10.12677/cc.2019.31001.

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Dong, Dong, Zhijian Xu, Wu Zhong, and Shaoliang Peng. "Parallelization of Molecular Docking: A Review." Current Topics in Medicinal Chemistry 18, no. 12 (September 18, 2018): 1015–28. http://dx.doi.org/10.2174/1568026618666180821145215.

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Molecular docking, as one of the widely used virtual screening methods, aims to predict the binding-conformations of small molecule ligands to the appropriate target binding site. Because of the computational complexity and the arrival of the big data era, molecular docking requests High- Performance Computing (HPC) to improve its performance and accuracy. We discuss, in detail, the advances in accelerating molecular docking software in parallel, based on the different common HPC platforms, respectively. Not only the existing suitable programs have been optimized and ported to HPC platforms, but also many novel parallel algorithms have been designed and implemented. This review focuses on the techniques and methods adopted in parallelizing docking software. Where appropriate, we refer readers to exemplary case studies.
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Raval, Keval, and Tejas Ganatra. "Basics, types and applications of molecular docking: A review." IP International Journal of Comprehensive and Advanced Pharmacology 7, no. 1 (March 15, 2022): 12–16. http://dx.doi.org/10.18231/j.ijcaap.2022.003.

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From hit discovery through lead optimization and beyond, computational methods have become an essential part of many drugs development processes. There are typically several steps in the docking process, and each one provides a new level of complexity. Docking methods are used to place small molecules in the active region of the enzyme. In addition to these methods, scoring functions are used to estimate a compound's biological activity by looking at how it interacts with prospective targets. Molecular docking is considered to be the most widely utilized computational phenomenon in the field of computer-aided drug design (CADD). It is being utilized at the academic level as well as in pharmaceutical companies for the lead discovery process. Molecular docking is mainly associated with two terms: ligand and protein. Protein is the target site where ligand may bind to give specific activity. Molecular docking provides information on the ability of the ligand to bind with protein which is known as binding affinity. Applications of molecular docking in drug development have evolved significantly since it was first created to aid in the study of molecular recognition processes between small and large compounds. This review emphasizes the basic features of molecular docking along with the types, approaches and applications.
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