Improving molecular fingerprint similarity via enhanced folding

Drug discovery depends on scientists finding compounds with molecular fingerprints similar to the target drug, or pharmacophore. A new way of improving the accuracy of molecular fingerprint folding is presented. The goal is to alleviate the growing challenge of excessively long fingerprints. This improved method generates a new shorter fingerprint that is more accurate than the basic folded fingerprint. Information gathered during preprocessing is used to determine an optimal attribute order. The most commonly used blocks of bits can then be organized and used to generate a new improved fingerprint for more optimal folding. The authors then applied the widely used Tanimoto similarity search algorithm to benchmark the results. The authors showed an improvement in the final results using this method to generate an improved fingerprint compared to other traditional folding methods.