Identification of BKCa channel openers by molecular field alignment and patent data-driven analysis

In Drug discovery, a combinatorial chemical library is a pre-chosen plurality of compounds designed simultaneously to have a common structural scaffold within each structure to represent a unique configuration of substitution at specific positions (1). Therefore, this directed diversity is aimed at pattern comparisons to find related and matching chemical structures explore how chemical structures are associated to various biological processes (2). However, the current techniques behind chemical structure mining applications have mainly focused on the ability of the system to correctly identify the structure name and biological processes in text, while less effort has been spent on the correct identification and matching (3). This is about to change as more and more chemical resources are becoming available and easily accessible. In recent years, theoretical chemistry and molecular modelling have become increasingly important in both lead finding and optimization. Computational Biologists have been attempting to generate new leads by examination of the common features of existing active compounds or of a single structure itself, of the target protein if it is known. These methodologies assist in the process of lead optimization by predicting what changes to the scaffold are likely to be beneficial since a molecule's affinity to a target is estimated by reference to its similarity to active compounds. It is possible to predict the binding properties of an untested molecule by representing the properties of a molecule which are important in its binding to other molecules, and then assessing the similarity between two such sets, one for the untested molecule and one for a well characterised molecule (4). In traditional molecular mechanics, the electrostatic properties of a molecule are defined by placing a point charge at the centre of each atom. Many different methods for calculating or estimating the value of such point charges have been described in the literature. The aim of this method is to distribute the point charges in such a way that the resulting electrostatic field is as Abstract In this work, we present the first comprehensive molecular field analysis of patent structures on how the chemical structure of drugs impacts the biological binding. This task was formulated as searching for drug structures to reveal shared effects of substitutions across a common scaffold and the chemical features that may be responsible. We used the SureChEMBL patent database, which provides search of the patent literature using keyword-based functionality, as a query engine. The extraction of data of the BKCa channel openers and aligning them for molecular field similarity with newly designed structures did provide a probable validation method with accurate values. Therefore, in an attempt to increase the true positives, we report a procedure that functions on a multiple analyses modeled on molecular field similarity and common sub-structural search with consensus scoring and high confidence values to obtain greater accuracy during conventional virtual screening.