Many natural substances have previously been authorized for use in treating diseases, including cancer, heart disease, neurological disorders, and microbial infections. Plant extracts have been employed for millennia in medical research. Because purified chemicals used in drug research have not proven effective, there has been a recent interest in natural products (NPs) and the use of medicinal plants to treat disease. The development of scientific research in the fields of structural biology, genomics, proteomics, therapeutic biology, biochemistry, systems biology, and computer science has caused a paradigm shift away from the herbal medicine system and toward contemporary methods in medication planning and treatment. The sophisticated procedures for isolating these molecules, such as solvent extraction and supercritical fluid extraction, are highlighted in this chapter along with the state-of-the-art chromatographic and spectroscopic approaches employed for structural elucidation. Additionally, a number of contemporary techniques, such as database mining, virtual screening, NP libraries, and molecular modeling, are being applied to enhance NP drug discovery research. Target-based drug discovery, high-throughput screening, in silico methods for virtual ligand screening, and faster and more efficient analytical techniques are some of the ways that pharmacognosy has evolved into a multidisciplinary, high-tech science of natural medicines in the 21st century. Standardization, repeatability, the complexity of phytochemical mixes, and regulatory limitations are some of the issues that still exist despite the advancements. The approaches used, the advancements made, and the present constraints are critically reviewed in this chapter, which also offers insights into possible future paths and ways to overcome the difficulties in this developing sector.

Botanical Extracts in Drug Screening Progress and Persistent Challenges

Hayat S.
Writing – Review & Editing
;
Naeem S.
Writing – Original Draft Preparation
;
2026

Abstract

Many natural substances have previously been authorized for use in treating diseases, including cancer, heart disease, neurological disorders, and microbial infections. Plant extracts have been employed for millennia in medical research. Because purified chemicals used in drug research have not proven effective, there has been a recent interest in natural products (NPs) and the use of medicinal plants to treat disease. The development of scientific research in the fields of structural biology, genomics, proteomics, therapeutic biology, biochemistry, systems biology, and computer science has caused a paradigm shift away from the herbal medicine system and toward contemporary methods in medication planning and treatment. The sophisticated procedures for isolating these molecules, such as solvent extraction and supercritical fluid extraction, are highlighted in this chapter along with the state-of-the-art chromatographic and spectroscopic approaches employed for structural elucidation. Additionally, a number of contemporary techniques, such as database mining, virtual screening, NP libraries, and molecular modeling, are being applied to enhance NP drug discovery research. Target-based drug discovery, high-throughput screening, in silico methods for virtual ligand screening, and faster and more efficient analytical techniques are some of the ways that pharmacognosy has evolved into a multidisciplinary, high-tech science of natural medicines in the 21st century. Standardization, repeatability, the complexity of phytochemical mixes, and regulatory limitations are some of the issues that still exist despite the advancements. The approaches used, the advancements made, and the present constraints are critically reviewed in this chapter, which also offers insights into possible future paths and ways to overcome the difficulties in this developing sector.
2026
Ahmad, A.; Khattak, M.; Hayat, S.; Naeem, S.; Ahmad, J.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/592824
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