Thus nowadays, people aren't so concerned with randomly scanning huge databases but rather on systematically identifying specific chemical space for specific targets . To achieve this, chemography has emerged as a promising approach for creating targeted libraries based on the chemical and physical characteristics of molecules . By leveraging physicochemical descriptors such as molecular weight, logP, and polar surface area, chemography can be used to filter and reduce the size of large databases, as well as to differentiate between different molecules . Most diverse molecules are deemed inactive during screening because the concept of molecular similarity predicts that similar molecules will have similar biological activity. Studies have shown that physicochemical descriptors can be used to successfully design molecules with drug-like oral drug-like properties, as well as to optimise a molecule's solubility, permeability, and other properties . Lipinski's rule of five is the gold standard for implementing physicochemical descriptors studies, and similar implementations have been performed for non-oral routes of drug delivery systems . Numerous research studies heavily rely on physicochemical descriptors such as molecular weight, hydrogen bond acceptors and donors, logP, polar surface area, and rotatable bonds to filter and shrink large databases for screening. These descriptors aid in distinguishing between various types of molecules, including human metabolites, toxins, and lead-like molecules . Physicochemical descriptors such as hydrogen bond acceptors (HBA), hydrogen bond donors (HBD), the number of nitrogen atoms (nN), and the number of oxygen atoms (nO) are utilized in drug discovery to filter out non-inhibitory molecules for kinases . Additionally, studies have been conducted to compare the physical-chemical properties of CNS drugs to all drugs and metabolic drugs, providing attributes of successful CNS drugs .