@article {43933,
	title = {Anti-microbial activity of chrysomycin a produced by streptomyces sp. against mycobacterium tuberculosis},
	journal = {RSC Advances},
	volume = {7},
	year = {2017},
	month = {JUL},
	pages = {36335-36339},
	type = {Article},
	abstract = {Limited efficacy of the BCG (Bacillus Calmette{\textendash}Gu{\'e}rin) vaccine against adult tuberculosis and the emergence of resistance to existing anti-tuberculosis drugs compel discovery of novel antibiotics against Mycobacterium tuberculosis. Actinomycetes are still an attractive platform for the discovery of new antimicrobials, especially from untapped natural hotspots, despite the belief that they are an exhausted resource after repeated re-discoveries. Herein we report the isolation and identification of chrysomycin A from an actinomycete isolated from a coastal area in Kerala. We show for the first time that it has antimycobacterial activity. It was found to be bactericidal to planktonic and intracellular M. tuberculosis with an MIC of 3.125 μg mL$^{-}${\textonesuperior}; it is non-hemolytic and has negligible cytotoxicity. The actinomycete that produces chrysomycin A was found to be a Streptomyces sp. through 16S rRNA gene sequencing.},
	doi = {10.1039/C7RA05576E},
	author = {Balaji, Muralikrishnan and Dan, Vipin Mohan and Joseph, Vinodh and Jamsheena, Vellekkatt and Ramachandran, Ranjit and Thomas, Sabu and Dastager, Syed Gulam and Kumar, K. Santhosh and Lankalapalli, Ravi Shankar and Kumar, R. Ajay}
}
@article {48407,
	title = {Artificial intelligence in microbial natural product drug discovery: current and emerging role},
	journal = {Natural Product Reports},
	volume = {39},
	year = {2022},
	month = {DEC},
	pages = {2215-2230},
	type = {Review},
	abstract = {<p>
	Covering: up to the end of 2022 Microorganisms are exceptional sources of a wide array of unique natural products and play a significant role in drug discovery. During the golden era, several life-saving antibiotics and anticancer agents were isolated from microbes; moreover, they are still widely used. However, difficulties in the isolation methods and repeated discoveries of the same molecules have caused a setback in the past. Artificial intelligence (AI) has had a profound impact on various research fields, and its application allows the effective performance of data analyses and predictions. With the advances in omics, it is possible to obtain a wealth of information for the identification, isolation, and target prediction of secondary metabolites. In this review, we discuss drug discovery based on natural products from microorganisms with the help of AI and machine learning.</p>
},
	issn = {0265-0568},
	doi = {10.1039/d2np00035k},
	author = {SahayaSheela, Vinodh J. and Lankadasari, Manendra B. and Dan, Vipin Mohan and Dastager, Syed G. and Pandian, Ganesh N. and Sugiyama, Hiroshi}
}
