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Abstract  Molecular shape is a useful tool for identifying small-molecules for therapeutics. Shape similarity can be found through both computed using either  alignment methods, a computationally demanding approach, orthrough  feature vector methods, which are  computationally less demanding. Maximization of both volume overlap and various feature points makes alignment methods computationally intensive. demanding but less accurate.  The computational burden cost  of alignment can be reduced by pre-aligning shapes, as is done with the Volumetric-Aligned Molecular Shapes (VAMS) method. Here we introduce and evaluate Fragment Oriented Molecular Shapes (FOMS), where shapes are aligned based on molecular fragments. FOMS performs equivalently or better than both VAMS and an optimizing alignment method. More significantly, FOMS enables the use of \textit{shape constraints}, a novel method for precisely specifying molecular shape queries that provides the ability to perform partial shape matching and supports search algorithms that function on an interactive time scale.