Background: Coleus amboinicus (Lour.) (syn Plectranthus amboinicus) from the Lamiaceae family—a large family of aromatic herbs with many medicinally important species—is a frequently cited species within the Plectranthus genus, renowned for its traditional uses, phytochemical composition, biological activities, and applications in skin care. Methods: A systematic review was conducted following PRISMA guidelines to provide an in-depth understanding of P. amboinicus’ phytochemical composition and biological activity, particularly in dermatological contexts, underscoring its significance in traditional medicine and modern phytochemical research. Results: P. amboinicus extracts and essential oils exhibit significant antimicrobial activity against both Gram-positive and Gram-negative bacteria, and notable antifungal properties, particularly against dermatophytes. Additionally, the species demonstrates remarkable mosquito repellent and anti-parasitic effects, comparable to DEET, and potent anti-inflammatory properties by inhibiting pro-inflammatory cytokines. The plant’s rich polyphenolic content contributes to its significant antioxidant properties, preventing conditions like hyperpigmentation and premature aging. P. amboinicus also exhibits cytotoxic activity against various cancer cell lines and promotes wound healing through its analgesic, anti-inflammatory, and antioxidant abilities. Conclusions: This comprehensive exploration of P. amboinicus validates its diverse therapeutic potential across infectious diseases, oncology, and wound care. Further research and clinical trials are warranted to fully elucidate its mechanisms of action and optimize its therapeutic applications, paving the way for its integration into mainstream medical practices.

The Neocarya macrophylla plant is used traditionally for food, medicinal, spiritual and industrial purposes. It is also used as a soap, dye, glue, fodder, termite repellent, firewood and for structural materials. Few studies on the physicochemical, nutritional content, phytochemical and pharmacological activities have validated the benefits of N. macrophylla to humanity as a food, in cosmetics or pharmaceutical products. The major bioactive constituents identified in the plant so far are steroids and flavonoids, such as, stigmasterol, quercetin, catechin and its related glycosides, as well as glucosamines. Extracts of the plant have shown good antivenom, antimicrobial, analgesic, anti-inflammatory, antimycobacterial, anthelmintic and antioxidant activities. Acute toxicity studies have confirmed the plant to be toxic. More studies on the plant are required in order to exploit other biological activities as claimed by traditional healers and also to isolate more bioactive compounds. In addition, the safety and tolerability assessment of N. macrophylla should be undertaken due to its widespread usage.

Multidrug resistance (MDR) presents a significant challenge in modern pharmacotherapy, greatly diminishing the effectiveness of chemotherapeutic agents. A primary mechanism contributing to MDR is the overexpression of P-glycoprotein (P-gp), also known as MDR1, encoded by the ABCB1 gene, which hampers the success of cancer treatments. Plants from the Plectranthus genus (Lamiaceae) have been traditionally acknowledged for their diverse therapeutic applications. The principal diterpene from Plectranthus grandidentatus Gürke, 7α-acetoxy-6β-hydroxyroyleanone (Roy), has demonstrated anticancer properties against various cancer cell lines. Previously synthesized ester derivatives of Roy have shown improved binding affinity to P-gp. This study employs previously acquired in vitro data on the P-gp activity of Roy derivatives to develop a ligand-based pharmacophore model, highlighting critical features necessary for P-gp modulation. Utilizing these data, we predict the potential of five novel ester derivatives of Roy to modulate P-gp in vitro against resistant NCI-H460 cells. In silico structure–activity relationship (SAR) studies were conducted on 17 previously synthesized royleanone derivatives. A binary classification model was constructed, distinguishing inactive from active compounds, generating 11,016 molecular interaction field (MIF) descriptors from structures optimized at the DFT level. After variable reduction and selection, 12 descriptors were chosen, resulting in a model with two latent variables (LV), using only 34.14% of the encoded information for calibration (LV1: 26.82%; LV2: 7.32%). The activity prediction of new derivatives suggested that four of them have a high likelihood of activity, which will be validated in future in vitro biological assays.