1. A field-based similarity search system, comprising: an input device which inputs a query molecule; and a processor which: partitions a conformational space of said query molecule into a fragment graph comprising an acyclic graph including plural fragment nodes connected by rotatable bond edges; computes a property field on fragment pairs of fragments of said query molecule from said fragment graph, said property field comprising a local approximation of a property field of said query molecule; constructs a set of fragment pairs for description of each candidate molecule wherein each set is known as a set of candidate molecule fragment pairs; constructs a set of features of said fragment pairs based on said property field, said features comprising a set of local, rotationally invariant, and moment-based descriptors generated from all conformations of said fragment graph of said query molecule; and weights said descriptors according to importance as perceived from a training set of descriptors to generate a context-adapted descriptor-to-key mapping which maps said set of descriptors to a set of feature keys comprising indices that label grid cells in discriminant space, wherein a candidate molecule fragment pair is within a set of candidate molecule fragment pairs that describe a candidate molecule stored in a feature database to said query molecule, and wherein the number of candidate molecule fragment pairs in the set, C fp , is given by C fp =(n−1)×(C frag ) 2 ×C rbe , where n is the number of fragments in said candidate molecule and n−1 is the number of rotatable bond edges connecting n fragments, C frag is a number of conformations in a fragment of said fragments and C rbe is a number of steps in which said rotatable bond edges are sampled.
1. A field-based similarity search system, comprising: an input device which inputs a query molecule; and a processor which: partitions a conformational space of said query molecule into a fragment graph comprising an acyclic graph including plural fragment nodes connected by rotatable bond edges; computes a property field on fragment pairs of fragments of said query molecule from said fragment graph, said property field comprising a local approximation of a property field of said query molecule; constructs a set of fragment pairs for description of each candidate molecule wherein each set is known as a set of candidate molecule fragment pairs; constructs a set of features of said fragment pairs based on said property field, said features comprising a set of local, rotationally invariant, and moment-based descriptors generated from all conformations of said fragment graph of said query molecule; and weights said descriptors according to importance as perceived from a training set of descriptors to generate a context-adapted descriptor-to-key mapping which maps said set of descriptors to a set of feature keys comprising indices that label grid cells in discriminant space, wherein a candidate molecule fragment pair is within a set of candidate molecule fragment pairs that describe a candidate molecule stored in a feature database to said query molecule, and wherein the number of candidate molecule fragment pairs in the set, C fp , is given by C fp =(n−1)×(C frag ) 2 ×C rbe , where n is the number of fragments in said candidate molecule and n−1 is the number of rotatable bond edges connecting n fragments, C frag is a number of conformations in a fragment of said fragments and C rbe is a number of steps in which said rotatable bond edges are sampled. 5. The field-based similarity search system of claim 1 , wherein said processor partitions said conformational space by selecting of a set of bonds in said molecule to cleave.