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Omega is composed of two main components; model building and torsion driving. The components are independant and can be used separately from each other. Models can be generated without performing a torsion search. Model generation may be bypassed by importing structures from external sources.
Omega builds initial models of structures by assembling fragment
templates along sigma bonds. Input molecules graphs are fragmented at
exocyclic sigma, and carbon to heteroatom acyclic (but not exocyclic)
sigma bonds. Conformations for the fragments are either retrieved
from pregenerated libraries built with makefraglib, or
constructed on-the-fly using the same distance constraints followed by
geometry optimization protocol that makefraglib uses. Molecule
assembly is accomplished by simple vector alignment since all
inter-fragment joints are along sigma bonds.
Once an initial model of a structure is constructed, or given as input, Omega generates additional models by enumerating ring conformations and invertible nitrogen atoms. Ring conformations are taken from the same fragment library used to build an initial model. Omega detaches all exocyclic substituents from a ring system, aligns and attaches them relative to the new ring conformation. Omega attempts to generate every possible combination of ring conformations possible for a given structure.
The next step in model generation is to detect and enumerate invertible nitrogens. Nitrogens that have pyramidal geometry, no stereochemistry specified, no more than one hydrogen, are three valent, and have no more than three ring bonds are considered by Omega to be invertible. Invertible in this context simply means that at room temperature a pyramidal nitrogen is likely to be able to rapidly (on an NMR timescale) interconvert between two puckered forms. All multiconformer ring models are further expanded by enumerating all possible nitrogen puckers. The resulting model set is the starting point for conformer search by torsion driving.
Omega begins the torsion search process by examining the molecular graph and determining the bonds may freely rotate. By default, Omega selects acyclic sigma bonds that have at least one non-hydrogen atom attached to each end of the bond. Hydrogen rotors (i.e. hydroxyl groups) are not altered during the torsion search. Doing so would make a combinatorially nasty problem even worse with no affect on the final ensemble. The final ensemble selection is based on heavy atom RMS distance which is unaffected by hydrogen positions. A list of possible dihedral angles are then assigned to each rotatable bond. The current mechanism for assignment is based on SMARTS matching, although alternate strategies for assigning angles based on experimental (i.e. X-ray) or theoretical (i.e. fragment optimization studies) are possible. The molecular graph is then subjected to pattern and geometric symmetry detection. Common patterns such as para-disubstituted benzene are used to reduce the number of symmetry equivalent dihedral angles that need to be searched. All torsions are altered by 120 and 180 degrees, and an RMS calculation is performed taking into account symmetry equivalent atoms in order to detect two and three fold symmetries. Torsions are then grouped into fragments of sets of up to five contiguous rotatable bonds. Exhaustive depth first torsion search is performed on each of the fragments, and the resulting conformers are placed into list sorted by energy. Entire structures are assembled by combining the lowest energy set of fragments, and then the next lowest set, until the search is terminated. Termination conditions include a limit on the total number of conformers that may be generated, fragment list may be exhausted, or the sum of the fragment energies exceeds the energy window of the global minimum structure. The best conformers identified in the torsion search are rank ordered base on energy. A final ensemble is selected by sequentially testing the conformers using the RMS distance cutoff. To be accepted in to the final ensemble, a conformer must have an RMS distance to every other member of the ensemble that exceeds the user defined cutoff value. The final ensemble is populated up to the user defined maximum ensemble size limit, or until the list of low energy conformers is exhausted.
Input File Preparation
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