In the same context, different types of molecular representations have enabled improved searches and expanded applications in various areas of chemistry. Examples include the development of new chemical compounds (de novo design), properties prediction such as absorption, distribution, metabolism, and excretion (ADME), structure-activity relationships (SAR), and structure-properties relationships (SPR), and development of new chemical descriptors. Notable examples of molecular descriptors commonly employed in drug discovery applications include structural fingerprints and molecular properties. Fingerprints encode a molecule's molecular fragments or functional groups, such as Molecular ACCes System (MACCS) Keys and extended connectivity fingerprint (ECFP). Typical molecular properties calculated are whole molecular properties of pharmaceutical interest that are part of empirical rules to assess drug-likeness. Chemical space analysis, molecular docking, and applying similarity concepts are prominent topics in computer-aided drug design (CADD). These topics are widely utilized in the pharmaceutical industry, universities, and research centers, demonstrating high-frequency drug discovery and development applications. The chemical space is the conceptual basis of Chemoinformatics. Several definitions of chemical space are reviewed elsewhere. Recently, the notion of the chemical multiverse has emerged, representing a collection of chemical spaces for a given set of compounds, each characterized by a distinct set of descriptors. This concept finds applications in drug design, encompassing diversity analysis, SAR and SPR analysis, and the design of molecular libraries. Applications of the similarity concept, such as SAR/SPR analysis and activity landscapes, have been very useful in describing changes in biological activity associated with changes in chemical structures and the subsequent design of new compounds with improved activities. Often, these differences can be confirmed with tools such as molecular docking, which take into account the mechanism of action at te structural level. However, their application is limited to the availability of information related to the therapeutic target.