![]() Z-matrix template-based substitution approach Comparison of this approach to other existing methods and future work are discussed in the last section. The concept and tutorial (template construction, generation of tuples for substitution sites, removal of duplicate tuples and substitution on the template) are described in the next section. Based on these previous reports, this is our first paper devoted to the methodology of generic structure generation using Z-matrix template-based substitution. 1), we successfully applied it to 26 classes of compounds to exhaustively generate over ten thousand 3D structures for further investigation by quantum chemical methods, ,. Inspired by the use of this approach in dichlorodiphenyltrichloroethane (DDT) analogues ( Fig. The Markush structures, represented as templates with defined substitution points, can be enumerated for the combinatorial investigation of compounds. There are ad hoc solutions to overcome these limitations but, alternatively, a new method may be used instead or in combination with the existing methods.Ĭhemists, by their manual intuition and labour, have been able to identify Markush or generic structures that represent a group of compounds with common chemical and/or physical properties. Molecular graph-based methods may also suffer from resonance, unusual bond types or infeasible structures. Most of the existing methods are based on molecular graphs for representation of molecular structures and intrinsically lack crucial spatial information in terms of configuration and conformation of generated structures. However, there are still no consistent one-size-fits-all standard for structural enumeration. Robust and exhaustive processes to generate chemical structures have been described previously in different contexts, ,, ,, ,. The second option is the cleanest procedure and would require to build a reference frame from the first molecule that is used for transformations of the second one.Initial structures (Z-matrix or Cartesian coordinate) are important starting points for the in silico investigation of chemical species. a host guest complex), either add a bond between them or build the Z matrices for each molecule separately. In case you want to process more than one molecule (e.g. If the RDkit molecule object contains more than one molecule, you won't be able to build the ZMatrix. Peptides are still ok, but computing proteins might take a while. The algorithm is quite inefficient for large molecules. Requirementsĭifferent examples for how to use this python class can be found in examples. The calculation of all these virtual coordinates can be carried out with this python class. By convention, the Cartesian coordinates of our molecule A-B-C-D-E will be shifted to the position of Z. Second, we need the torsion angles X-Y-Z-A, Y-Z-A-B, Z-A-B-C, the angles Y-Z-A, Z-A-B and the bond length Z-A. First, we need 3 Cartesian coordinates X, Y, and Z in the reference frame, which can be basically anything in the lab coordinate system, as long as it is well defined. a ligand) with 5 atoms: A-B-C-D-E and we want to convert them back to Cartesian space. For instance, let's say we have the Zmatrix coordinates for a molecule (e.g. ![]() These coordinates are also called 'virtual coordinates'. coordinates in a host or protein molecule) and 3 torsion angles, 2 angles and 1 bond length with respect to these coordinates. The algorithm is described in detail in these two articles and Ī general remark on transformations is that the conversion from ZMatrix coordinates to Cartesian coordinates requires 3 reference Cartesian coordinates (e.g. ![]() In order to circumvent this, I implemented the Natural Extension Reference Frame algorithm, which minimizes these errors. One difficulty in this context is to avoid numerical instabilities (for instance through round-offs), since these might propagate through the Z-Matrix during the conversion. However, the back conversion is more tricky and somewhat error prone. The transformation from Cartesian coordinates to ZMatrix coordinates is straightforward. Therefore, the openmm package is used for dealing with units and enforcing the correct ones during every step. If one has Cartesian coordinates for the RDKit molecule, one can also generate the Z-Matrix coordinates or convert the Z-Matrix coordinates back to Cartesian coordinates.ĭuring all conversions, one easily can make a mistake by using wrong units. With this little python implementation, RDkit molecules can be converted to a Z-Matrix topology representation. ![]()
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