Method for the prediction of binding targets and the design of ligands

Abstract

A computer-based method for the identification of binding targets in proteins and other macromolecules. More particularly, the invention includes an algorithm aimed at predicting binding targets in proteins. This algorithm, named Woolford, requires knowledge of the high resolution structure of the protein but no knowledge of the location or identity of natural binding sites or ligands. Binding targets in the protein are identified and classified according to their expected optimal affinities. Binding targets can be located at the protein surface or at internal surfaces that become exposed as a result of partial unfolding, conformational changes, subunit dissociation, or other events. The entire protein is mapped according to the binding potential of its constituent atoms. Once binding targets are identified, optimal ligands are designed and progressively built by the addition of individual atoms that complement structurally and energetically the selected target. This algorithm is expected to have significant applications in structure-based drug design since it allows: 1) identification of binding targets in proteins; 2) identification of additional targets if the primary target is known; 3) design of ligand molecules with optimal binding affinities for the selected target; and 4) refinement of lead compounds by defining the location and nature of chemical groups for optimal binding affinity.

1 - 2 . (cancelled)  
   
   
       3 . A computer-assisted method for building a model of an ideal ligand for binding to a selected binding site of a selected molecule, using a programmed computer including a processor, an input device, and an output device, including the steps of: 
 (a) inputting into the programmed computer, through the input device, data including the identity and three-dimensional coordinates of each of the atoms in the binding target, wherein the binding target has been selected from a plurality of predicted binding targets generated by    (a) inputting into the programmed computer, through the input device, data including the identity and three-dimensional coordinates of each of the atoms in the selected binding site of the selected molecule;    (b) determining, using the processor, the identify and location of a set of ligand atoms that are energetically complementary to each of the atoms in the selected binding site of the selected molecule based on global optimization of the Gibbs energy of binding of each of the ligand atoms in the set of ligand atoms;    (c) generating, using the processor, a three-dimensional prediction model of the set of ligand atoms bound to the selected binding site;    (d) outputting, to the output device, the three-dimensional model of the set of ligand atoms bound to the selected binding site.    
   
   
       4 - 5 . (Cancelled)  
   
   
       6 . A computer-assisted method for predicting the binding affinity of a selected peptide ligand for binding to a selected binding site of a selected molecule, using a programmed computer including a processor, an input device, and an output device, including the steps of: 
 (a) inputting into the programmed computer, through the input device, data including the identity and three-dimensional coordinates of each of the atoms in a selected binding site of a selected molecule;    (b) inputting into the programmed computer, through the input device, data including, the identity and three-dimensional coordinates of each of the atoms in a selected dipeptide;    (c) generating, using the processor, a model of the selected dipeptide bound to the selected binding site;    (d) determining, using the processor, the three-dimensional coordinates of an energy minimized structure of the selected dipeptide when the selected dipeptide is bound to the selected binding site; and    (e) determining, using the processor, a predicted binding affinity of the energy minimized dipeptide for the selected binding site.    
   
   
       7 . The method of  claim 6 , further including: 
 repeating steps (a)-(e) for a plurality of selected dipeptides and identifying as a lead dipeptide the selected dipeptide having the highest determined binding affinity.    
   
   
       8 . The method of  claim 6 , further including: 
 (f) selecting a first polypeptide of three or more amino acids, the polypeptide including the dipeptide;    (g) generating, using the processor, a model of the selected first polypeptide bound to the selected binding site;    (h) determining, using the processor, the three-dimensional coordinates of an energy minimized structure of the selected first polypeptide when the selected first polypeptide is bound to the selected binding site; and    (i) determining, using the processor, a predicted binding affinity of the energy minimized first polypeptide for the selected binding site.    
   
   
       9 . The method of  claim 8 , further including: 
 (j) selecting a second polypeptide including the first polypeptide;    (k) generating, using the processor, a model of the selected second polypeptide bound to the selected binding site;    (l) determining, using the processor, the three-dimensional coordinates of an energy minimized structure of the selected second polypeptide when the second selected polypeptide is bound to the selected binding site; and    (m) determining, using the processor, a predicted binding affinity of the energy minimized second polypeptide for the selected binding site.    
   
   
       10 . The method of  claim 8 , further including: 
 (j) selecting a variant of the selected polypeptide;    (k) generating, using the processor, a model of the selected variant polypeptide bound to the selected binding site;    (l) determining, using the processor, the three-dimensional coordinates of an energy minimized structure of the selected variant polypeptide when the selected variant polypeptide is bound to the selected binding site; and    (m) determining, using the processor, a predicted binding affinity of the energy minimized selected variant polypeptide for the selected binding site.    
   
   
       11 - 13 . (Cancelled) 
   14 . A computer program, residing on a computer-readable medium, for building a model of an ideal ligand for binding to a selected binding site of a selected molecule, the computer program including instructions for causing a computer to: 
 (a) receive data including the identity and three-dimensional coordinates of each of the atoms in the selected binding site of the selected molecule;    (b) determine the identity and location of a set of ligand atoms that are energetically complementary to each of the atoms in the selected binding site of the selected molecule based on global optimization of the Gibbs energy of binding of each of the ligand atoms in the set of ligand atoms;    (c) generate a three-dimensional model of the set of ligand atoms bound to the selected binding site; and    (d) output the three-dimensional model of the set of ligand atoms bound to the selected binding site.      
   
   
       15 - 16 . (Cancelled)  
   
   
       17 . A computer program, residing on a computer-readable medium, for predicting the binding affinity of a selected peptide ligand for binding to a selected binding site of a selected molecule, the computer program comprising instructions for causing a computer to: 
 (a) receive data including the identity and three-dimensional coordinates of each of the atoms in a selected binding site of a selected molecule;    (b) receive data including, the identity and three-dimensional coordinates of each of the atoms in a selected dipeptide;    (c) generate a model of the selected dipeptide bound to the selected binding site;    (d) determine the three-dimensional coordinates of an energy minimized structure of the selected dipeptide when the selected dipeptide is bound to the selected binding site; and    (e) determine a predicted binding affinity of the energy minimized dipeptide for the selected binding site.