studies have demonstrated the involvement of chymase in the escalation of dermatitis and chronic inflammation pursuing cardiac and pulmonary fibrosis. Therefore, inhibition of chymase is likely to divulge therapeutic ways for the treatment of cardiovascular diseases, allergic inflammation, and fibrotic disorders. Chymase inhibition may also be useful for preventing the progression of type 2 diabetes, along with the prevention of diabetic retinopathy. Moreover, role of chymase in inflammation has prompted its restorative value in diseases such as chronic obstructive pulmonary disease and asthma. Drug discovery and development is a time-consuming and costly procedure. Therefore, application and development of computational methods for lead generation and lead optimization in the drug discovery process are of immense importance in reducing the cycle time and cost as well as to amplify the productivity of drug discovery research. These computational methods are generally categorized as ligand-based methods and structure-based methods. In case of ligand-based methods, when biological activities of multiple hits are known, a more sophisticated class of computational techniques known as MK-7622 pharmacophore identification methods is often employed to deduce the essential features required for the biological activity. A pharmacophore is an abstract description of molecular features which are necessary for molecular recognition of a ligand by a biological macromolecule. Due to the advantage in efficiency in the virtual screening, the pharmacophore model method is now a potent tool in the area of drug discovery. However, the often cited drawback of the ligand-based methods is that they do not provide Flufenamic acid butyl ester detailed structural information to help medicinal chemists in designing new molecules. The availability of the detailed structural information is critical especially during the lead optimization stage of the discovery process. While, structure-based pharmacophore methodology which involves generation of pharmacophore models directly from complex crystal structures is more reliable because it imposes the necessary constraints required for interaction and selectivity. Diverse inhibitor binding modes can be attained from ligand-based and structure-based pharmacophore modeling me
