Abstract

Inflammation is a natural reaction to external stimuli to protect the organism. However, if it is exaggerated, it can cause severe physiopathological damage, linked to diseases like rheumatoid arthritis, cancer, diabetes, allergies, and infections. Inflammation is mainly characterized by pain, increased temperature, flushing, and edema, which can be controlled using anti-inflammatory drugs. In this context, prostaglandin E2 (PGE2) inhibition has been targeted for designing new compounds with anti-inflammatory properties. It is a bioactive lipid overproduced during an inflammatory process, in which its increased production is carried out mainly by COX-1, COX-2, and microsomal prostaglandin E2 synthase-1 (mPGES-1). Recently, studies have demonstrated that mPGES-1 inhibition is a safe strategy for developing anti-inflammatory agents, which could protect against pain, acute inflammation, arthritis, autoimmune diseases, and different types of cancers. Thus, in recent years, computer-aided drug design (CADD) approaches have been increasingly used to design new inhibitors, decreasing costs and increasing the probability of discovering active substances. Finally, this review will cover all aspects involving high-throughput virtual screening, molecular docking, dynamics, fragment-based drug design, and quantitative structure-activity relationship in seeking new promising mPGES-1 inhibitors.

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