Surflex-Sim

The Surflex-Sim method operates significantly differently [104]. Each of the molecules is surrounded by a set of observer points that characterizes the local character of the surface and potential interactions. Two similar molecules will have a common subset of comparable observer points. A optimal alignment occurs when the differences in pharmacophore character and molecular surface inferred from the observer points are minimized between two molecules. To speed up the algorithm, large molecules can be fragmented into parts which are then compared, and then tested for consistency. This feature also makes the method capable of identifying alignments when one molecule is much smaller than the other. 

In a volume-oriented density function such as that used by ROCS, Gaussian functions are atom-centered. In the surface-oriented formulation, the M. of Equation 2.2.1 are Gaussians with peaks at the atomic surface (set by the atomic radii, denoted fi). By itself, the sum over the M produces internal molecular surfaces in addition to external ones. The E[ of Equation 2.2.2 defines Gaussians on local radial co-ordinates around each observer point from set P, with peaks at the molecular surface (set by the minimum distances from the observers to the molecule, denoted d,). When yis chosen carefully, the integral of the product of two molecules surface-density functions R (defined in Eq. 2.2.3) is very closely approximated by the morphological similarity function used by Surflex-Sim [31]. 

Here, the two surface-density functions are defined with respect to a single set of observations points P. The spheres that pack around each of the two molecules A and B share the same centers, but they have different radii, depending on the minimum distance to each molecular surface. As with the ROCS approach, one can define a similarity metric in terms of the overlap integral of the product of the two surface-density functions. This function is very closely approximated by the function computed by Surflex-Sim, simplified slightly in what follows. 

---