Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Chemical analysis
Reexamination Certificate
2002-08-05
2003-12-30
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Chemical analysis
C703S011000
Reexamination Certificate
active
06671628
ABSTRACT:
FIELD OF THE INVENTION
Methods and systems described in this patent generally relate to methods and systems for identifying candidate molecules that may bind to a target molecule. Methods described in this patent may be implemented in a computer system and may be embodied as computer programs in an article of manufacture. The methods and systems described in this patent also relate to methods and systems for determining from a set of candidate molecules those molecules that may bind to a target molecule.
BACKGROUND OF THE INVENTION
Drug discovery may be conceptually understood in two steps: 1) target identification and 2) lead identification and optimization. In the first step of target identification, a large molecule, which may be but is not limited to a cell-surface receptor or intra-cellular protein, referred to as the target, may be identified with a particular biological pathway or structure of interest. Once a potential target has been identified, it must be screened against a large number of small molecules to determine whether the target is drugable—i.e. whether any small molecules can be found to bind or interact with the target. Lead identification is very expensive and time consuming, often involving experimentally screening a target against many millions of small molecules to determine binding affinities. Once one or more drug leads to a target have been identified, it is still often necessary to optimize a lead in order to improve its pharmacological efficacy. In this step, referred to as lead optimization, synthetic chemists chemically modify the lead in order to increase or decrease its binding to the target, modify its susceptibility to degradative pathways, or modify its pharmacokinetics.
The current combinatorial methods of lead identification and to a lesser extent, lead optimization, could be improved if rationalized. Rational lead optimization, as used herein, refers to using theoretical methods to determine a set of likely lead candidates to a given target before experimentally screening lead-target binding. Rational lead optimization offers the possibility of reducing drug discovery time and expenses by reducing the number of potential lead-target screens.
Early methods of rational lead optimization sought to find a set of potential leads from a database of small molecules chemically similar to a known lead. The earliest of these techniques was performed by the synthetic chemist in the process of producing the next substance to test. The chemist would make a set of small changes to the structure and determine if those changes had a beneficial or detrimental effect on the efficacy. This process, called analog synthesis, is effective, although time-consuming and expensive. Analog synthesis is the basis for medicinal chemistry, and remains an important part of drug discovery today.
Early attempts at using computers to make the lead optimization process more efficient involved determining chemical similarity between a potential lead and a known lead using graph-theoretical treatments. Methods of this type include searching a database of compounds for those that contain the same core structure as the lead compound—called substructure searching or two-dimensional (2-D) searching—and searching for compounds that are generally similar based on the presence of a large number of common fragments between the potential lead expansion compound and the lead compound—called 2-D similarity searching. These techniques are somewhat effective, but are limited to finding compounds that are obviously similar to the lead, thus affording the medicinal chemist few new insights for directing the synthesis project.
Another technique using computers makes use of the knowledge of how the small molecules bind to the large molecule. There are often special groups called pharmacophore groups that are responsible for most of the stabilization energy of the complex. The three-dimensional (3-D) searching techniques try to find from a large database of potential lead compounds those that have essentially the same geometrical arrangement of pharmacophore groups as the lead compound. The 3-D arrangement of the pharmacophore groups required for interaction with the large molecule is called a pharmacophore model or 3-D query. Compounds that are found to contain the correct arrangement are called “hits,” and are candidates for screening. These hits differ from the substructure or 2-D similarity hits in that the backbone of the structure may be quite different from that of the original lead compound, and often represents an important new area of chemistry to be explored.
The simplest of the 3-D searching techniques compares the position and arrangement of the pharmacophore groups of 3-D structures as stored in the database. This is referred to as static 3-D searching. A fairly obvious shortcoming to determining chemical similarity from a database of small molecules of fixed geometry is that molecules often do not have rigid structures, but rather have a large number of accessible conformations formed from rotating the molecular framework of a molecule about its single bonds. These bonds that can easily be rotated are referred to as rotatable bonds. As used herein, molecular configurations defined by rotations about the dihedral angles of its rotatable bonds will be referred to as rotomers. Small molecules in pharmaceutical database typically contain an average of six to eight rotatable bonds per molecule. This can easily afford a set of accessible rotomers that number in the millions. Searching just one static conformation (rotomer) from among millions of possible rotomers for the correct arrangement of groups will cause many compounds that could be good leads to be missed.
In order to consider energetically accessible rotomers, early small molecule databases often contained a small subset of the accessible rotomers of each small molecule. Herein, this technique is called multi-conformational 3-D searching. However, attempting to define individually each rotomer for a given small molecule quickly becomes impractical as the number of atoms in a given small molecule increases. Accordingly, other early methods of searching small molecule databases for potential target leads attempted to define a conformation space for each small molecule. See U.S. Pat. No. 5,752,019.
A further extension of 3-D search technology involves investigation of the accessible conformational space of the potential hits as part of the searching process. These techniques, called conformationally flexible 3-D searching techniques, adjust the conformation of the potential hit according to the requirements of the 3-D pharmacophore query. One such technique that has been found to be effective uses a method called “Directed Tweak”. See Hurst, T.
Flexible
3
D Searching: The Directed Tweak Technique,
34, J. Chem. Inf. Comput. Sci. 190 (1994). This method is very effective for finding molecules of interest when the geometry of the binding site of the large molecule is not known. Directed Tweak adjusts the conformation of the small molecule by changing the angle values of the rotatable bonds. This method therefore ignores changes in conformation because of bond stretching and bond bending. Bond stretching vibrations for molecules near room temperature typically change the length of a bond by about 0.05 Angstroms (Å). Bond bending between three connected atoms typically moves one of the atoms by about 0.1 Å. Rotation about rotatable bonds often moves atoms by several Ås or tens of Ås. Thus, adjusting only the rotatable bond values includes essentially all of the accessible conformational flexibility of a small molecule.
When the binding site of the target protein is known, another way to identity potential leads is by docking potential leads into the binding site. Docking approaches can be classified based on how they characterize the ligand-binding site of the protein. Grid-search techniques fill the space around the binding site with a 3-D grid, precompute the potentials (van de Waals, electrostatic, etc
ChemNavigator, Inc.
Morrison & Foerster / LLP
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