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Journal articles on the topic 'AutoDock VinaXB'

Author: Grafiati

Published: 10 September 2021

Last updated: 17 July 2025

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1

Mustapha, M. T., D. R. Flower, and A. K. Chattopadhyay. "Virtual Screening of Kinase Based Drugs: Statistical Learning Towards Drug Repositioning." Journal of Nanotechnology in Diagnosis and Treatment 8 (December 12, 2022): 23–34. http://dx.doi.org/10.12974/2311-8792.2022.08.03.

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Kinases are phosphate catalysing enzymes that have traditionally proved difficult to target against ligands,and hence inefficacious in drug development. There are two colluding reasons for this. First is the issue of specificity. The homogeneity that exists between the kinase ATP-binding pockets makes it a non-realisable target to developcompounds that would inhibit only one out of 538 protein kinases encoded by the human genome, without inhibitingsome of the others. Second, producing compounds with the required efficacy to rival the millimolar ATP concentrations present in cells is stoichiome

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2

Kurczab, Rafał. "The evaluation of QM/MM-driven molecular docking combined with MM/GBSA calculations as a halogen-bond scoring strategy." Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials 73, no. 2 (2017): 188–94. http://dx.doi.org/10.1107/s205252061700138x.

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The combination of quantum mechanics/molecular mechanics-driven (QM/MM) molecular docking with binding free-energy calculations was successfully used to reproduce the X-ray geometries of protein–ligand complexes with halogen bonding. The procedure involves quantum-polarized ligand docking (QPLD) to obtain the QM-derived ligand atomic charges in the protein environment at the B3PW91/cc-pVTZ level and the MM/GBSA (generalized-Born/surface area) algorithm to calculate the binding free energies of resultant complexes. The performance was validated using a set of 106 X-ray complexes and compared wi

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3

Mustapha, M.T., D.R. Flower, and A.K. Chattopadhyay. "Virtual Screening of Kinase Based Drugs: Statistical Learning Towards Drug Repositioning." Journal of Nanotechnology in Diagnosis and Treatment 8 (December 12, 2022): 23–34. https://doi.org/10.12974/2311-8792.2022.08.03.

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Kinases are phosphate catalysing enzymes that have traditionally proved difficult to target against ligands, and hence inefficacious in drug development. There are two colluding reasons for this. First is the issue of specificity. The homogeneity that exists between the kinase ATP-binding pockets makes it a non-realisable target to developcompounds that would inhibit only one out of 538 protein kinases encoded by the human genome, without inhibiting some of the others. Second, producing compounds with the required efficacy to rival the millimolar ATP concentrations present in ce

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4

Hassan, Heba H. A., Muhammad I. Ismail, Mohammed A. S. Abourehab, Frank M. Boeckler, Tamer M. Ibrahim, and Reem K. Arafa. "In Silico Targeting of Fascin Protein for Cancer Therapy: Benchmarking, Virtual Screening and Molecular Dynamics Approaches." Molecules 28, no. 3 (2023): 1296. http://dx.doi.org/10.3390/molecules28031296.

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Fascin is an actin-bundling protein overexpressed in various invasive metastatic carcinomas through promoting cell migration and invasion. Therefore, blocking Fascin binding sites is considered a vital target for antimetastatic drugs. This inspired us to find new Fascin binding site blockers. First, we built an active compound set by collecting reported small molecules binding to Fascin’s binding site 2. Consequently, a high-quality decoys set was generated employing DEKOIS 2.0 protocol to be applied in conducting the benchmarking analysis against the selected Fascin structures. Four docking p

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5

Sarthak, Pal1 Meenu Chaudhary*2 Kanishak Kala3. "Autodock & Autodock Vina: Development, Capabilities, & Applications in Molecular Docking." International Journal of Pharmaceutical Sciences 3, no. 5 (2025): 3005–19. https://doi.org/10.5281/zenodo.15458275.

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AutoDock and AutoDock Vina are popular molecular docking technologies that are essential to structure-based drug discovery because they can predict ligand-receptor interactions. Their theoretical underpinnings, methods of application, and comparative effectiveness across several biological targets are assessed in this study. Vina's multicore support and empirical scoring are compared to AutoDock4's semi-empirical scoring function and flexible docking strategy. Furthermore, the impact of developments like AutoGridFR and GPU-accelerated versions on computational efficiency is examined. The benef

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6

Nguyen, Nguyen Thanh, Trung Hai Nguyen, T. Ngoc Han Pham, et al. "Autodock Vina Adopts More Accurate Binding Poses but Autodock4 Forms Better Binding Affinity." Journal of Chemical Information and Modeling 60, no. 1 (2019): 204–11. http://dx.doi.org/10.1021/acs.jcim.9b00778.

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7

Tanisa, Asti Anna, and Rezi Riadhi. "VIRTUAL SCREENING OF BETA-SECRETASE 1 (BACE1) INHIBITORS IN THE INDONESIAN HERBAL DATABASE AS USING AUTODOCK AND AUTODOCK VINA." Asian Journal of Pharmaceutical and Clinical Research 10, no. 17 (2017): 148. http://dx.doi.org/10.22159/ajpcr.2017.v10s5.23119.

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Objective: Alzheimer’s is a neurodegenerative disease caused by the accumulation of senile plaque in the brain that affects neuronal system leading to a less sensitive cellular response from neurons. Previous research has found that beta-secretase 1 (BACE1) plays an important role in the senile plaque formation, become a target in Alzheimer’s medication.Methods: In this study, virtual screening of BACE1 inhibitors on the Indonesian Herbal Database was done using AutoDock and AutoDock Vina. The screening was validated using the directory of useful decoys: Enhanced database. Parameters for valid

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8

Tang, Shidi, Ruiqi Chen, Mengru Lin, et al. "Accelerating AutoDock Vina with GPUs." Molecules 27, no. 9 (2022): 3041. http://dx.doi.org/10.3390/molecules27093041.

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AutoDock Vina is one of the most popular molecular docking tools. In the latest benchmark CASF-2016 for comparative assessment of scoring functions, AutoDock Vina won the best docking power among all the docking tools. Modern drug discovery is facing a common scenario of large virtual screening of drug hits from huge compound databases. Due to the seriality characteristic of the AutoDock Vina algorithm, there is no successful report on its parallel acceleration with GPUs. Current acceleration of AutoDock Vina typically relies on the stack of computing power as well as the allocation of resourc

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9

Gaillard, Thomas. "Evaluation of AutoDock and AutoDock Vina on the CASF-2013 Benchmark." Journal of Chemical Information and Modeling 58, no. 8 (2018): 1697–706. http://dx.doi.org/10.1021/acs.jcim.8b00312.

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10

Macari, Gabriele, Daniele Toti, Andrea Pasquadibisceglie, and Fabio Polticelli. "DockingApp RF: A State-of-the-Art Novel Scoring Function for Molecular Docking in a User-Friendly Interface to AutoDock Vina." International Journal of Molecular Sciences 21, no. 24 (2020): 9548. http://dx.doi.org/10.3390/ijms21249548.

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Motivation: Bringing a new drug to the market is expensive and time-consuming. To cut the costs and time, computer-aided drug design (CADD) approaches have been increasingly included in the drug discovery pipeline. However, despite traditional docking tools show a good conformational space sampling ability, they are still unable to produce accurate binding affinity predictions. This work presents a novel scoring function for molecular docking seamlessly integrated into DockingApp, a user-friendly graphical interface for AutoDock Vina. The proposed function is based on a random forest model and

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11

Tanchuk, Vsevolod, Volodymyr Tanin, Andriy Vovk, and Gennady Poda. "A New Scoring Function for Molecular Docking Based on AutoDock and AutoDock Vina." Current Drug Discovery Technologies 12, no. 3 (2015): 170–78. http://dx.doi.org/10.2174/1570163812666150825110208.

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12

Salamah, Nabilah Nurtika, Widya Dwi Aryati, and Arry Yanuar. "Virtual Screening of Indonesian Herbal Database as Adenosine A2A Antagonist using AutoDock and AutoDock Vina." Pharmacognosy Journal 11, no. 6 (2019): 1219–24. http://dx.doi.org/10.5530/pj.2019.11.189.

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13

Ivonie, Ulfa, Arry Yanuar, and Firdayani . "VIRTUAL SCREENING OF INDONESIAN HERBAL DATABASE FOR CP ALLOSTERIC MODULATOR OF HEPATITIS B VIRUS." International Journal of Applied Pharmaceutics 10, no. 1 (2018): 190. http://dx.doi.org/10.22159/ijap.2018.v10s1.42.

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Objective: This study performed a virtual screening of the Indonesian Herbal Database for the core protein allosteric modulator of the hepatitis Bvirus (HBV) using AutoDock and AutoDock Vina software, to discover novel safe drugs for patients.Methods: The method was validated using the parameters enrichment factor (EF), receiver operating characteristics, and area under the curve (AUC).The grid box size used in virtual screening with AutoDock was 55 × 55 × 55 with EF10% of 0.7652 and AUC of 0.6709, whereas that used in virtualscreening with AutoDock Vina was 20.625 × 20.625 × 20.625 with EF5%

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14

Jaghoori, Mohammad Mahdi, Boris Bleijlevens, and Silvia D. Olabarriaga. "1001 Ways to run AutoDock Vina for virtual screening." Journal of Computer-Aided Molecular Design 30, no. 3 (2016): 237–49. http://dx.doi.org/10.1007/s10822-016-9900-9.

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15

Bastos, Luana Luiza, and Giovana Fiorini. "Re-docking Molecular Utilizando o PyMOL e AutoDock VINA." BIOINFO 3, no. 1 (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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16

Tanchuk, Vsevolod Yu, Volodymyr O. Tanin, Andriy I. Vovk, and Gennady Poda. "A New, Improved Hybrid Scoring Function for Molecular Docking and Scoring Based on AutoDock and AutoDock Vina." Chemical Biology & Drug Design 87, no. 4 (2015): 618–25. http://dx.doi.org/10.1111/cbdd.12697.

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17

Vieira, Tatiana F., and Sérgio F. Sousa. "Comparing AutoDock and Vina in Ligand/Decoy Discrimination for Virtual Screening." Applied Sciences 9, no. 21 (2019): 4538. http://dx.doi.org/10.3390/app9214538.

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AutoDock and Vina are two of the most widely used protein–ligand docking programs. The fact that these programs are free and available under an open source license, also makes them a very popular first choice for many users and a common starting point for many virtual screening campaigns, particularly in academia. Here, we evaluated the performance of AutoDock and Vina against an unbiased dataset containing 102 protein targets, 22,432 active compounds and 1,380,513 decoy molecules. In general, the results showed that the overall performance of Vina and AutoDock was comparable in discriminating

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18

Xue, Qiao, Xian Liu, Paul Russell, et al. "Evaluation of the binding performance of flavonoids to estrogen receptor alpha by Autodock, Autodock Vina and Surflex-Dock." Ecotoxicology and Environmental Safety 233 (March 2022): 113323. http://dx.doi.org/10.1016/j.ecoenv.2022.113323.

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19

Chawsheen, Mahmoud. "Predicting the efficacy of Akt inhibitors using AutoDock Vina software." Journal of Garmian University 5, no. 4 (2018): 1–10. http://dx.doi.org/10.24271/garmian.610.

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20

Reznichenko, Liliia V. "ПРОГРАМА AUTODOCK VINA ЯК ЗАСІБ НАВЧАННЯ МАЙБУТНІХ УЧИТЕЛІВ ПРИРОДНИЧИХ ДИСЦИПЛІН". Information Technologies and Learning Tools 38, № 6 (2013): 149–61. http://dx.doi.org/10.33407/itlt.v38i6.928.

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Стаття присвячена проблемі впровадження засобів комп’ютерних технологій у процес навчання майбутніх учителів природничих дисциплін, зокрема учителів хімії. Обґрунтовано важливість комп’ютерного моделювання під час дослідження хімічних процесів і явищ. Висвітлено особливості процесу молекулярного докінгу, як одного з методів комп’ютерного моделювання. Запропонована програма для молекулярного докінгу AutoDock Vina розглядається як засіб підвищення ефективності навчання майбутніх учителів хімії. Окреслено теоретичні положення і запропоновано практичні рекомендації щодо формування у студентів нави

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21

Butt, Sania Safdar, Yasmin Badshah, Maria Shabbir, and Mehak Rafiq. "Molecular Docking Using Chimera and Autodock Vina Software for Nonbioinformaticians." JMIR Bioinformatics and Biotechnology 1, no. 1 (2020): e14232. http://dx.doi.org/10.2196/14232.

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In the field of drug discovery, many methods of molecular modeling have been employed to study complex biological and chemical systems. Experimental strategies are integrated with computational approaches for the identification, characterization, and development of novel drugs and compounds. In modern drug designing, molecular docking is an approach that explores the confirmation of a ligand within the binding site of a macromolecule. To date, many software and tools for docking have been employed. AutoDock Vina (in UCSF [University of California, San Francisco] Chimera) is one of the computat

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22

Sandeep, Gaddam, Kurre Purna Nagasree, Muppaneni Hanisha, and Muthyala Murali Krishna Kumar. "AUDocker LE: A GUI for virtual screening with AUTODOCK Vina." BMC Research Notes 4, no. 1 (2011): 445. http://dx.doi.org/10.1186/1756-0500-4-445.

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23

Pham, T. Ngoc Han, Trung Hai Nguyen, Nguyen Minh Tam, et al. "Improving ligand‐ranking of AutoDock Vina by changing the empirical parameters." Journal of Computational Chemistry 43, no. 3 (2021): 160–69. http://dx.doi.org/10.1002/jcc.26779.

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24

Handoko, Stephanus Daniel, Xuchang Ouyang, Chinh Tran To Su, Chee Keong Kwoh, and Yew Soon Ong. "QuickVina: Accelerating AutoDock Vina Using Gradient-Based Heuristics for Global Optimization." IEEE/ACM Transactions on Computational Biology and Bioinformatics 9, no. 5 (2012): 1266–72. http://dx.doi.org/10.1109/tcbb.2012.82.

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25

Rauf, Mohd Ahmar, Swaleha Zubair, and Asim Azhar. "Ligand docking and binding site analysis with pymol and autodock/vina." International Journal of Basic and Applied Sciences 4, no. 2 (2015): 168. http://dx.doi.org/10.14419/ijbas.v4i2.4123.

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<p>Docking of various therapeutically important chemical entities to the specific target sites offers a meaningful strategy that may have tremendous scope in a drug design process. For a thorough understanding of the structural features that determine the strength of bonding between a ligand with its receptor, an insight to visualize binding geometries and interaction is mandatory. Bioinformatical as well as graphical software ‘PyMOL’ in combination with the molecular docking suites Autodock and Vina allows the study of molecular combination to visualize and understand the structure-base

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26

Masters, Lily, Scott Eagon, and Michael Heying. "Evaluation of consensus scoring methods for AutoDock Vina, smina and idock." Journal of Molecular Graphics and Modelling 96 (May 2020): 107532. http://dx.doi.org/10.1016/j.jmgm.2020.107532.

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27

Seeliger, Daniel, and Bert L. de Groot. "Ligand docking and binding site analysis with PyMOL and Autodock/Vina." Journal of Computer-Aided Molecular Design 24, no. 5 (2010): 417–22. http://dx.doi.org/10.1007/s10822-010-9352-6.

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28

Santoso, Broto. "DOCKING ANALOG KURKUMIN TURUNAN PIPERAZINDION DENGAN TUBULIN (1TUB) RANTAI  MENGGUNAKAN VINA DAN AUTODOCK1." Pharmacon: Jurnal Farmasi Indonesia 12, no. 1 (2015): 14–18. http://dx.doi.org/10.23917/pharmacon.v12i1.43.

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Program Autodock mampu memprediksi energi bebas dan konformasi ikatan antara fleksibel ligan dan makromolekul target yang telah diketahui. Senyawa turunan dan analog kurkumin adalah ligan yang telah banyak dihasilkan dan diuji aktivitasnya. Beberapa diantaranya memiliki khasiat yang lebih baik dari kurkumin. Enam senyawa turunan piperazindion, kurkumin, PGV-0, dan PGV-1 dihitung energi optimasi geometrinya menggunakan density functional theory (DFT) – Gaussian. Ligan hasil optimasi dicari energi ikatan ligan dengan reseptor 1TUB rantai b melalui docking menggunakan Vina dan Autodock dengan met

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29

Eberhardt, Jerome, Diogo Santos-Martins, Andreas F. Tillack, and Stefano Forli. "AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings." Journal of Chemical Information and Modeling 61, no. 8 (2021): 3891–98. http://dx.doi.org/10.1021/acs.jcim.1c00203.

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30

Baba, Natsumi, and Eiichi Akaho. "VSDK: Virtual screening of small molecules using AutoDock Vina on Windows platform." Bioinformation 6, no. 10 (2011): 387–88. http://dx.doi.org/10.6026/97320630006387.

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31

Rentzsch, R., and B. Y. Renard. "Docking small peptides remains a great challenge: an assessment using AutoDock Vina." Briefings in Bioinformatics 16, no. 6 (2015): 1045–56. http://dx.doi.org/10.1093/bib/bbv008.

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32

Di Muzio, Elena, Daniele Toti, and Fabio Polticelli. "DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina." Journal of Computer-Aided Molecular Design 31, no. 2 (2017): 213–18. http://dx.doi.org/10.1007/s10822-016-0006-1.

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33

Mulyati, Budi. "Tempe sebagai Pengganti Hormon Estrogen pada Reseptor Estrogen α Dengan Metode Autodock Vina". CHEESA: Chemical Engineering Research Articles 1, № 1 (2018): 7. http://dx.doi.org/10.25273/cheesa.v1i1.2457.

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<p>Reseptor Estrogen (RE) α akan berinteraksi dengan estrogen dalam tubuh manusia. Bila kadar Estrogen berkurang akan menyebabkan menopause. Isoflavon merupakan fitoestrogen yang dapat terikat pada kedua jenis estrogen reseptor.Tempe merupakan makanan yang mengandung isoflavon yaitu faktor II (6,7,4-trihidroksi isoflavon). Isoflavon bermanfaat antara lain untuk mencegah penyakit tulang, menurunkan kolesterol jahat, dan mencegah kanker. RE α merupakan target penting dalam dunia pengobatan untuk mencari hormon pengganti pada wanita menopause dan obat kemoterapi melawan kanker. Tujuan dari

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34

Handoko, Stephanus Daniel, Xuchang Ouyang, Chinh Tran To Su, Chee Keong Kwoh, and Yew Soon Ong. "Erratum to "QuickVina: Accelerating AutoDock Vina Using Gradient-Based Heuristics for Global Optimization"." IEEE/ACM Transactions on Computational Biology and Bioinformatics 9, no. 6 (2012): 1853. http://dx.doi.org/10.1109/tcbb.2012.156.

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35

Chang, Max W., Christian Ayeni, Sebastian Breuer, and Bruce E. Torbett. "Virtual Screening for HIV Protease Inhibitors: A Comparison of AutoDock 4 and Vina." PLoS ONE 5, no. 8 (2010): e11955. http://dx.doi.org/10.1371/journal.pone.0011955.

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36

Che, Xinhao, Qilei Liu, and Lei Zhang. "An accurate and universal protein-small molecule batch docking solution using Autodock Vina." Results in Engineering 19 (September 2023): 101335. http://dx.doi.org/10.1016/j.rineng.2023.101335.

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37

Sarkar, Arkadeep, Simona Concilio, Lucia Sessa, Francesco Marrafino, and Stefano Piotto. "Advancements and novel approaches in modified AutoDock Vina algorithms for enhanced molecular docking." Results in Chemistry 7 (January 2024): 101319. http://dx.doi.org/10.1016/j.rechem.2024.101319.

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38

Yanuar, Arry, Rezi Riadhi Syahdi, and Widya Dwi Aryati. "PARAMETER OPTIMIZATION AND VIRTUAL SCREENING INDONESIAN HERBAL DATABASE AS HUMAN IMMUNODEFICIENCY VIRUS -1 INTEGRASE INHIBITOR USING AUTODOCK AND VINA." International Journal of Applied Pharmaceutics 9 (October 30, 2017): 90. http://dx.doi.org/10.22159/ijap.2017.v9s1.51_57.

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Objective: Human immunodeficiency virus (HIV-1) is a virus that causes acquired immunodeficiency syndrome, a disease considered to be one of themost dangerous because of its high mortality, morbidity, and infectivity. The emergence of mutant HIV strains has led treatment to target proteaseas reverse transcriptase and integrase enzyme become less effective. This study aims to provide knowledge about the potential of HIV-1 integraseinhibitors for use as guiding compounds in the development of new anti-HIV drugs.Methods: This study used AutoDock and AutoDock Vina for virtual screening of the Indo

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39

F. Silva, Rodrigo, Victor M. M. Souza, and Géssica E. N. Costa. "Análise In Silico dos Parâmetros Farmacocinéticos e Toxicológicos dos Constituintes da Aroeira do Sertão (Astronium Urundeuva ) e seu Potencial Antimalárico." Revista Processos Químicos 20, no. 37 (2025): 9–20. https://doi.org/10.19142/rpq.v20i37.765.

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A aroeira-do-sertão (A. urundeuva) é uma planta predominante no bioma da caatinga,reconhecida popularmente na medicina tradicional brasileira. Os parâmetros ADMETdessa espécie foram analisados visando evidenciar o potencial farmacológico de seusconstituintes e apresentar novas alternativas para o tratamento da malária. Tendoem vista a resistência desenvolvida devido a mutações genéticas causadas pelospróprios antimaláricos. Utilizou-se programas computacionais como AutoDock Vinae Discovery Studio para analisar as interação receptor-ligante dos alvos maláricosPfENR, PfLDH, PfFP2 e PvPMV com con

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Quiroga, Rodrigo, and Marcos A. Villarreal. "Vinardo: A Scoring Function Based on Autodock Vina Improves Scoring, Docking, and Virtual Screening." PLOS ONE 11, no. 5 (2016): e0155183. http://dx.doi.org/10.1371/journal.pone.0155183.

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41

Abreu, Rui M. V., Hugo J. C. Froufe, Maria-João R. P. Queiroz, and Isabel C. F. R. Ferreira. "Selective Flexibility of Side-Chain Residues Improves VEGFR-2 Docking Score using AutoDock Vina." Chemical Biology & Drug Design 79, no. 4 (2012): 530–34. http://dx.doi.org/10.1111/j.1747-0285.2011.01313.x.

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42

Zalevsky, Arthur, Alexander Zlobin, Vasilina Gedzun, et al. "PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries." Molecules 24, no. 2 (2019): 277. http://dx.doi.org/10.3390/molecules24020277.

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Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein’s ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libr

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43

Istyastono, Enade P., Muhammad Radifar, Nunung Yuniarti, Vivitri D. Prasasty, and Sudi Mungkasi. "PyPLIF HIPPOS: A Molecular Interaction Fingerprinting Tool for Docking Results of AutoDock Vina and PLANTS." Journal of Chemical Information and Modeling 60, no. 8 (2020): 3697–702. http://dx.doi.org/10.1021/acs.jcim.0c00305.

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44

Saji, Christy, Rajeswary K. Balachandran, Aneeza M. Nizar, et al. "MOLECULAR DOCKING STUDIES WITH PHYTOCONSTITUENTS OF TINOSPORA SINENSIS TARGETING SARS-COV-2 PROTEIN USING AUTODOCK VINA." INDIAN DRUGS 62, no. 05 (2025): 22–27. https://doi.org/10.53879/id.62.06.15489.

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Drug discovery is time-consuming and resource-intensive, but computational approaches offer a more efficient alternative. The urgency for antiviral treatments became evident during the SARS-CoV-2 pandemic due to the virus’s rapid spread and mutations. This study utilizes computational drug design techniques to assess the antiviral potential of Tinospora sinensis constituents against the SARS-CoV-2 main protease (PDB ID: 6LU7). The target protein was prepared using AutoDock tools, and molecular docking was conducted with AutoDock Vina. Of 37 compounds, 5 exhibited a binding affinity below -7 kc

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Singh, Shilpi, Urmi Bajpai, and Andrew Michael Lynn. "Structure based virtual screening to identify inhibitors against MurE Enzyme of Mycobacterium tuberculosis using AutoDock Vina." Bioinformation 10, no. 11 (2014): 697–702. http://dx.doi.org/10.6026/97320630010697.

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Diyan, Diyan Sakti Purwanto, Hari Susanti, and Nining Sugihartini. "MOLECULAR DOCKING AS POTENTIAL ANTI-INFLAMMED QUERSETIN OF MORINGA LEAVES (Moringa oleifera L.) WITH AUTODOCK-VINA." Jurnal Ilmiah Manusia Dan Kesehatan 4, no. 2 (2021): 309–13. http://dx.doi.org/10.31850/makes.v4i2.818.

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Inflammation is a response to tissue injury that involves a physiological process in the form of activation of the cyclooxygenase (COX) enzyme which has two isoforms, namely the cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2) enzymes. The leaves of Moringa (Moringa oleifera L.) contain quercetin which has shown anti-inflammatory activity by blocking the synthesis and release of histamine and other inflammatory allergic mediators. This study aims to determine the role of quercetin in Moringa leaves as an anti-inflammatory ligand 6 COX cyclooxigenase-2 (COX-2) with the application of autod

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Kadukova, Maria, Vladimir Chupin, and Sergei Grudinin. "Docking rigid macrocycles using Convex-PL, AutoDock Vina, and RDKit in the D3R Grand Challenge 4." Journal of Computer-Aided Molecular Design 34, no. 2 (2019): 191–200. http://dx.doi.org/10.1007/s10822-019-00263-3.

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Abdalfattah, Sara, Caroline Knorz, Akhtar Ayoobi, et al. "Identification of Antagonistic Action of Pyrrolizidine Alkaloids in Muscarinic Acetylcholine Receptor M1 by Computational Target Prediction Analysis." Pharmaceuticals 17, no. 1 (2024): 80. http://dx.doi.org/10.3390/ph17010080.

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Pyrrolizidine alkaloids (PAs) are one of the largest distributed classes of toxins in nature. They have a wide range of toxicity, such as hepatotoxicity, pulmonary toxicity, neuronal toxicity, and carcinogenesis. Yet, biological targets responsible for these effects are not well addressed. Using methods of computational biology for target identification, we tested more than 200 PAs. We used a machine-learning approach that applies structural similarity for target identification, ChemMapper, and SwissTargetPrediction. The predicted targets with high probabilities were muscarinic acetylcholine r

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Saputri, Karisma Enggar, Nurul Fakhmi, Erwinda Kusumaningtyas, Dedy Priyatama, and Broto Santoso. "DOCKING MOLEKULAR POTENSI ANTI DIABETES MELITUS TIPE 2 TURUNAN ZERUMBON SEBAGAI INHIBITOR ALDOSA REDUKTASE DENGAN AUTODOCK-VINA." Chimica et Natura Acta 4, no. 1 (2016): 16. http://dx.doi.org/10.24198/cna.v4.n1.10443.

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Kochnev, Yuri, Erich Hellemann, Kevin C. Cassidy, and Jacob D. Durrant. "Webina: an open-source library and web app that runs AutoDock Vina entirely in the web browser." Bioinformatics 36, no. 16 (2020): 4513–15. http://dx.doi.org/10.1093/bioinformatics/btaa579.

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Abstract Motivation Molecular docking is a computational technique for predicting how a small molecule might bind a macromolecular target. Among docking programs, AutoDock Vina is particularly popular. Like many docking programs, Vina requires users to download/install an executable file and to run that file from a command-line interface. Choosing proper configuration parameters and analyzing Vina output is also sometimes challenging. These issues are particularly problematic for students and novice researchers. Results We created Webina, a new version of Vina, to address these challenges. Web

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