In brief 

Natural products, which have been chosen through billions of years for their interactions with biomolecules, have been and continue to be a key source of medications. However, due to key hurdles such as high rediscovery rates, difficult isolation, and poor manufacturing titers, pharmaceutical corporations scaled down their natural product discovery initiatives in the 1990s in favour of synthetic chemical libraries. Insights into secondary microbial metabolism afforded by breakthroughs in DNA sequencing and synthetic biology technology have inspired several techniques to solve these difficulties. The purpose of this Original Research Review Article is to offer an overview of drug development utilizing natural ingredients

Introduction  

Humans have long recognized microbes’ wide repertory of chemicals as a potential source of medicines. Prior to the genomic era, most natural product discovery initiatives had a ‘top-down’ strategy, with biological materials being screened for desirable bioactivities, followed by compound isolation and characterization. By the 1990s, however, pharmaceutical corporations were struggling with high rediscovery rates and had de-emphasized their efforts. With the rapid increase of microbial genomic and metagenomic datasets showing a massive number of biosynthetic gene clusters in nature, recent advances in genomics have reignited interest in natural product discovery. Discovering new natural products is exciting and extremely important in light of today’s growing medication resistance and health issues. 

Genome-mining for natural product BGCs 

With over 30,000 sequenced bacterial genomes already stored in public archives, the introduction of next-generation sequencing has substantially sped the sequencing of microbial genomes at considerably lower costs, resulting in an exponential expansion of genomic sequencing data. However, our existing capacity to easily assess and interpret such massive quantities of data is an obvious obstacle. This implies identifying possible secondary metabolites BGCs that encode for new bioactive compounds from microbial genomes for natural product drug development. In addition, several genome-mining methods have been developed for that purpose. 

Accessing silent natural product gene clusters 

Secondary metabolism is tightly controlled, and the fact that many BGCs stay “silent” in the laboratory provides a significant difficulty in “activating” these BGCs and assessing the therapeutic potential of their encoded natural products. As metabolic profiling using advanced analytical methods continues to uncover new compounds that have eluded detection due to low production yields, the activation of BGCs that are not or inadequately expressed in laboratory conditions has resulted in the discovery of a diverse range of natural products with a variety of bioactivities. The various research methodologies for activating BGC expression are highlighted below, focusing on natural product discovery. For further information on the metabolic, route, and genomeengineering techniques in native and heterologous host systems for secondary metabolism, readers are directed to recent reviews. 

• Activation of silent BGCs in native hosts 
• Variation of growth conditions and small molecule inducers 
• Manipulation of regulators 
• Perturbation of epigenetic control 
• Activation of silent BGCs in heterologous hosts 
• Direct capturing and refactoring of gene clusters 
• Optimization of heterologous hosts 

Metagenomics-driven drug discovery 

More than 99% of environmental microorganisms have resisted laboratory cultivation, and this uncultured microbial majority represents a tremendous chemical treasure trove. Metagenomics, which involves the direct capture and analysis of environmental DNA (eDNA), provides culture-independent and unbiased access to the microbial biosynthetic potential that would otherwise be overlooked by traditional methods that require the isolation and cultivation of pure microbial cultures. This section highlights the technological and conceptual developments in metagenomics that resulted in identifying novel natural products from varied environmental niches such as soil, marine habitats, and the human body^(2). 

Combinatorial biosynthesis 

The explosion of BGC sequence data provides vital insights into how extraordinarily complex natural products comprising huge physiologically relevant chemical structure space are formed from a small number of basic building blocks. BGCs typically encode two types of biosynthetic enzymes: one that creates important biosynthetic precursors and assembles the core scaffold and another that derivatizes the scaffolds. Understanding nature’s reasoning for encoding chemical variety will allow for rational engineering of biosynthetic pathways to produce analogues of favoured natural product scaffolds or innovative natural product-like scaffolds that may be difficult to synthesize for New product drug development chemically. 

Conclusion 

Despite pharmaceutical corporations’ mid-1990s reduction in natural product research activities, natural products remain a crucial source of inspiration for clinical medications. Natural product research has been revitalized in recent years due to breakthroughs in DNA sequencing, genomics/metagenomics, synthetic biology, and genome editing technologies. Analyses of microbial genomes and metagenomes show that humans have only scratched the surface of microorganisms’ chemical and functional diversity. To prioritize and identify relevant BGCs from genomes/metagenomes, predict the structures of their chemical products, integrate genomics with metabolomic and biological data to identify genotype-chemotype relationships, and prioritize downstream characterization efforts, bioinformatic tools have been developed. In addition, new DNA capture and assembly methods and multiplexed genome engineering technologies make it possible to optimize heterologous expression systems and biosynthetic pathways for secondary metabolite synthesis. These advancements pave the path for more systematic reviews and focused identification of new natural compounds based on genetic data⁽³⁾. 

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