Endonuclease PvuII (1PVI) DNA - GATTACAGATTACA
CAP - Catabolite gene Activating Protein (1BER)
DNA - GATTACAGATTACAGATTACA Endonuclease PvuII bound to palindromic DNA recognition site CAGCTG (1PVI) DNA - GATTACAGATTACAGATTACA TBP - TATA box Binding Protein (1C9B)
CAP - Catabolite gene Activating Protein (1BER)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
TBP - TATA box Binding Protein (1C9B)
 

Small molecule docking in YASARA

YASARA Structure provides everything you need to dock ligands with proteins at the touch of a button. Two different approaches are currently available:

Approach 1: Autodock

AutoDockAutodock is a highly cited docking program developed at the Scripps Research Institute by Dr. Garrett M. Morris et al. [1]. YASARA Structure includes a tuned derivative of the original Autodock, which provides a number of advantages:

  • Docking at the touch of a button: select ligand, receptor and go.
  • Possibility to interactively place the simulation cell around the active site to focus docking on the most important region.
  • Possibility to interactively fix certain internal degrees of freedom of the ligand to perform anything from rigid to flexible docking.
  • Automatic typing of ligands, assignment of pH dependent bond orders and hydrogen atoms.
  • Semi-empirical QM calculations to assign high-quality RESP-like AutoSMILES charges, which are further tuned for maximum compatibility with the Autodock scoring function.
  • Automatic ligand structure analysis to determine the core fragment and its flexible attachments.
  • Consideration of receptor flexibility via automatic generation of a receptor ensemble with alternative high-scoring solutions of the side-chain rotamer network.
  • Keep selected active-site residues flexible during docking.
  • Parallel docking: make full use of today's multi core CPUs by docking on all your cores in parallel (in Windows maximally 32 cores).
  • Covalent docking: if the ligand forms a covalent bond with a known receptor atom, this is handled automatically using AutoDock's flexible side-chain approach.
  • Interruptible docking: run on your notebook, exit YASARA and continue docking next day.
  • Easy result analysis: concise docking report, all ligand conformers superposed and sorted by binding energy, interactive docking result player.

Approach 2: VINA

Docking Result PlayerVINA (Vina Is Not Autodock) has also been developed at the Scripps Research Institute, by different authors, Dr. Oleg Trott  and Dr. Arthur J. Olson [2]. It is tightly related to the original AutoDock, so everything written above also applies to VINA (with one exception: interruptible docking is currently not supported, but also not really needed due to VINA's significantly higher performance).



R E F E R E N C E S

[1] Automated Docking Using a Lamarckian Genetic Algorithm and and Empirical Binding Free Energy Function
Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK and Olson AJ (1998), J.Comput.Chem. 19,1639-1662
[2] AutoDock VINA: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading
Trott O, Olson AJ (2010), J.Comput.Chem. 31, 455-461