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Effortless Binding Predictions in 2 Minutes with CB-Dock2 & AutoDock Vina.
weblink: cadd.labshare.cn/cb-dock2/ind...
Example Protein and Ligand: www.rcsb.org/structure/4hg7
Results -Example: cadd.labshare.cn/cb-dock2/php...
1. CB-Dock2 combines multiple features to facilitate molecular docking.
CB-Dock2 is an improved version of the CB-Dock server for protein-ligand blind docking, integrating cavity detection, docking, and homologous template fitting. Given the three-dimensional (3D) structure of a protein and a ligand, we can predict their binding sites and affinity for computer-aided drug discovery. A diverse community of developers and researchers are using CB-Dock2 to solve biological problems.
2. How it works?
CB-Dock2 is an improved version of the protein-ligand blind docking tool that inherits the curvature-based cavity detection procedure and the AutoDock Vina-based molecular docking procedure in CB-Dock server (see CB-Dock for details). On this foundation, we future integrated a homologous template-based blind docking procedure, considering that the pocket information on the templates can provide valuable references for binding sites prediction in the presence of homologous templates. The complete workflow of CB-Dock2 is shown below. For the protein and ligand submitted by user, CB-Dock2 will retrieve from the protein-ligand complexes database stored on our server for template ligands with high topology similarity (FP2 ≥ 0.4) at the first time. If present, the similarity between the query protein and the proteins complexed with the selected template ligands will be calculated. The complexes with greater than 40% sequence identity (and pocket RMSD ≤ 4Å) in the template ligand binding site will be retained for the subsequent template-based cavity detection and molecular docking. The docking method utilized in this procedure is FitDock, an in-house developed method that fits initial conformation to the given template using a hierarchical multi-feature alignment approach, subsequently explores the possible conformations, and finally outputs refined docking poses.
After submitting the required files, a perl script will process these files automatically as shown above. We employ the latest version (1.2.0) of AutoDock Vina for template-independent blind docking. The pipeline of template-based blind docking employs the BioLip database (version of 2021.09.15) as the template database.
About Dr. Muhammad Naveed
(HoD, Biotechnology, University of Central Punjab, Lahore)
With distinction, Dr. Muhammad Naveed obtained a Ph.D. degree in Biotechnology (Genomics & Bioinformatics) from Quaid-e-Azam University, Islamabad. He has won Ph.D. indigenous & IRSIP scholarships from HEC. He has done Pre-Doc research at the University of Ghent, Belgium. HEC awarded him the best Ph.D. (IRSIP) Scholar of the Year in 2013 & QAU honored him as a “Distinguished Alumni” in 2017. He is doing research projects in Bioinformatics, Molecular Biotechnology, Nano-informatics and vaccine designing, and Drug designing against infectious diseases. He has supervised 90 MSc. and 80 MPhil. & 02 Ph.D. students. He has published 152 Research articles with 1186 impact factors, 6260 citations, 01 book, 06 book chapters, and filed 05 Patents. He was awarded the distinguished “Researcher of the Year” in 2016 (UoG) and 2018, 2019 & 2021 (UCP).
Contact link:
1. Official website: ucp.edu.pk/member/dr-muhammad...
2. Facebook: / drmuhammadnaveed22
3. LinkedIn: www.linkedin.com/in/dr-muhamm...
4. Instagram: / prof.dr.naveed
5. Google Scholar: scholar.google.com/citations?...
6. ResearchGate: www.researchgate.net/profile/...
7. Twitter: / naveedqau
#docking #protein #ligands #bioinformatics #CB-Dock2 #drmuhammadnaveed