Name Modified Size InfoDownloads / Week
smina.osx 2018-01-11 6.6 MB
smina.static 2017-11-09 8.7 MB
custom_scoring.pdf 2015-03-12 2.9 MB
README 2015-01-07 9.2 kB
multi_smina.py 2013-05-24 15.4 kB
Totals: 5 Items   18.2 MB 24
smina is a fork of Autodock Vina (http://vina.scripps.edu/) that focuses on improving scoring and minimization. Changes from the standard Vina (version 1.1.2) include: -comprehensive support for ligand molecular formats (via OpenBabel)* -support for multi-ligand files (e.g., an sdf file)* -support for addition term types (e.g., desolvation, electrostatics) -support for custom, user-parameterized scoring functions (see --custom_scoring) -automatic box creation based on a user-specified bound ligand -allow the output of more than 20 docking poses -vastly improved minimization algorithms (--minimize goes to convergence) For workflows where AutoDock Vina is used for minimization (local_only) as opposed to of docking, these changes make Vina much easer to use and 10-20x faster. Docking performance is about the same since partial charge calculation and file i/o isn't such a big part of the performance. If you find smina useful, please cite our paper: http://pubs.acs.org/doi/abs/10.1021/ci300604z *Non-pdbqt ligand files must have partial charges added. This is done using OpenBabel and will get different results than the prepare_ligand4.py script that comes with AutoDock Tools. Pre-built binaries are provided that were built on Ubuntu 14.04. The main dependencies are boost (1.54) and openbabel. A static binary is provided in case these dependencies cannot be met (however, it probably still will not work if the kernel is older than 2.6.24). Input: -r [ --receptor ] arg rigid part of the receptor (PDBQT) --flex arg flexible side chains, if any (PDBQT) -l [ --ligand ] arg ligand(s) --flexres arg flexible side chains specified by comma separated list of chain:resid --flexdist_ligand arg Ligand to use for flexdist --flexdist arg set all side chains within specified distance to flexdist_ligand to flexible Search space (required): --center_x arg X coordinate of the center --center_y arg Y coordinate of the center --center_z arg Z coordinate of the center --size_x arg size in the X dimension (Angstroms) --size_y arg size in the Y dimension (Angstroms) --size_z arg size in the Z dimension (Angstroms) --autobox_ligand arg Ligand to use for autobox --autobox_add arg Amount of buffer space to add to auto-generated box (default +4 on all six sides) --no_lig no ligand; for sampling/minimizing flexible residues Scoring and minimization options: --custom_scoring arg custom scoring function file --score_only score provided ligand pose --local_only local search only using autobox (you probably want to use --minimize) --minimize energy minimization --randomize_only generate random poses, attempting to avoid clashes --minimize_iters arg (=0) number iterations of steepest descent; default scales with rotors and usually isn't sufficient for convergence --accurate_line use accurate line search --minimize_early_term Stop minimization before convergence conditions are fully met. --approximation arg approximation (linear, spline, or exact) to use --factor arg approximation factor: higher results in a finer-grained approximation --force_cap arg max allowed force; lower values more gently minimize clashing structures --user_grid arg Autodock map file for user grid data based calculations --user_grid_lambda arg (=-1) Scales user_grid and functional scoring --print_terms Print all available terms with default parameterizations --print_atom_types Print all available atom types Output (optional): -o [ --out ] arg output file name, format taken from file extension --out_flex arg output file for flexible receptor residues --log arg optionally, write log file --atom_terms arg optionally write per-atom interaction term values --atom_term_data embedded per-atom interaction terms in output sd data Misc (optional): --cpu arg the number of CPUs to use (the default is to try to detect the number of CPUs or, failing that, use 1) --seed arg explicit random seed --exhaustiveness arg (=8) exhaustiveness of the global search (roughly proportional to time) --num_modes arg (=9) maximum number of binding modes to generate --energy_range arg (=3) maximum energy difference between the best binding mode and the worst one displayed (kcal/mol) --min_rmsd_filter arg (=1) rmsd value used to filter final poses to remove redundancy -q [ --quiet ] Suppress output messages --addH arg automatically add hydrogens in ligands (on by default) --flex_hydrogens Enable torsions effecting only hydrogens (e.g. OH groups). This is stupid but provides compatibility with Vina. Configuration file (optional): --config arg the above options can be put here Information (optional): --help display usage summary --help_hidden display usage summary with hidden options --version display program version The custom scoring file consists of a weight, term description, and optional comments on each line. The numeric parameters of the term description can be varied to parameterize the scoring function. Use --print_terms to see all available terms. Example (all weights 1.0, all term types listed): 1.0 ad4_solvation(d-sigma=3.6,_s/q=0.01097,_c=8) desolvation, q determines whether value is charge dependent 1.0 ad4_solvation(d-sigma=3.6,_s/q=0.01097,_c=8) in all terms, c is a distance cutoff 1.0 electrostatic(i=1,_^=100,_c=8) i is the exponent of the distance, see everything.h for details 1.0 electrostatic(i=2,_^=100,_c=8) 1.0 gauss(o=0,_w=0.5,_c=8) o is offset, w is width of gaussian 1.0 gauss(o=3,_w=2,_c=8) 1.0 repulsion(o=0,_c=8) o is offset of squared distance repulsion 1.0 hydrophobic(g=0.5,_b=1.5,_c=8) g is a good distance, b the bad distance 1.0 non_hydrophobic(g=0.5,_b=1.5,_c=8) value is linearly interpolated between g and b 1.0 vdw(i=4,_j=8,_s=0,_^=100,_c=8) i and j are LJ exponents 1.0 vdw(i=6,_j=12,_s=1,_^=100,_c=8) s is the smoothing, ^ is the cap 1.0 non_dir_h_bond(g=-0.7,_b=0,_c=8) good and bad 1.0 non_dir_h_bond_quadratic(o=0.4,_c=8) like repulsion, but for hbond, don't use 1.0 non_dir_h_bond_lj(o=-0.7,_^=100,_c=8) LJ 10-12 potential, capped at ^ 1.0 acceptor_acceptor_quadratic(o=0,_c=8) quadratic potential between hydrogen bond acceptors 1.0 donor_donor_quadratic(o=0,_c=8) quadratic potential between hydroben bond donors 1.0 num_tors_div div constant terms are not linearly independent 1.0 num_heavy_atoms_div 1.0 num_heavy_atoms these terms are just added 1.0 num_tors_add 1.0 num_tors_sqr 1.0 num_tors_sqrt 1.0 num_hydrophobic_atoms 1.0 ligand_length Atom Type Terms You can define custom functionals between pairs of specific atom types: atom_type_gaussian(t1=,t2=,o=0,_w=0,_c=8) guassian potential between specified atom types atom_type_linear(t1=,t2=,g=0,_b=0,_c=8) linear potential between specified atom types atom_type_quadratic(t1=,t2=,o=0,_c=8) quadratic potential between specified atom types atom_type_inverse_power(t1=,t2=,i=0,_^=100,_c=8) inverse power potential between specified atom types Use --print_atom_types to see all available atom types. Note that hydrogens are always ignored despite having atom types. Note that these are all symmetric - you do not need to specify a term for (t1,t2) and (t2,t1) (doing so will just double the value of the potential). Example: Faking covalent docking. Consider this custom scoring function: -0.035579 gauss(o=0,_w=0.5,_c=8) -0.005156 gauss(o=3,_w=2,_c=8) 0.840245 repulsion(o=0,_c=8) -0.035069 hydrophobic(g=0.5,_b=1.5,_c=8) -0.587439 non_dir_h_bond(g=-0.7,_b=0,_c=8) 1.923 num_tors_div -100.0 atom_type_gaussian(t1=Chlorine,t2=Sulfur,o=0,_w=3,_c=8) All but the last term are the default Vina scoring function. That last term applys a very strong guassian potential between Cl and S. In the system we were docking, we modified the two atoms we wanted to be next to each other (because they are known form a covalent bond) to be a chlorine and a sulfur (the system is not physical, but that's okay). Since these were the only Cl and S in the system and the term has a large weight, the best docking solutions all placed these atoms together. The final poses could then be rescored/minimized using just the default scoring function.
Source: README, updated 2015-01-07