Cheminformatics to Characterize Pharmacologically Active Natural Products

Abstract

Natural products have a significant role in drug discovery. Natural products have distinctive chemical structures that have contributed to identifying and developing drugs for different therapeutic areas. Moreover, natural products are significant sources of inspiration or starting points to develop new therapeutic agents. Natural products such as peptides and macrocycles, and other compounds with unique features represent attractive sources to address complex diseases. Computational approaches that use chemoinformatics and molecular modeling methods contribute to speed up natural product-based drug discovery. Several research groups have recently used computational methodologies to organize data, interpret results, generate and test hypotheses, filter large chemical databases before the experimental screening, and design experiments. This review discusses a broad range of chemoinformatics applications to support natural product-based drug discovery. We emphasize profiling natural product data sets in terms of diversity; complexity; acid/base; absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties; and fragment analysis. Novel techniques for the visual representation of the chemical space are also discussed.

GCMS Profile of Bioactive Secondary Metabolites with Therapeutic Potential in the Ethanolic Leaf Extracts of Azadirachta indica¬: A Sacred Traditional Medicinal Plant of INDIA

“…Literature reveals that most of the bioactive secondary metabolites identified in the crude extracts of Neem leaves are of therapeutic potential 64 . Literature contains lots and lots of information on the chemical and biological investigations on Azadirachta indica 66 .…”

“…Recently, Azadirachtin -A, bioactive secondary metabolite from A. indica has been identified as potential inhibitor of SARS-CoV-2 main protease [59][60][61] and is expected to play a major role in the management of COVID-19 once through with clinical trials. Furthermore, pharmacological characterization, and ADMET profiling [62][63][64][65] is expected to validate this natural drug lead.…”

Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products

“…Currently, artificial intelligence algorithms (Wolfe et al, 2018 ; Lima et al, 2020 ; Stokes et al, 2020 ) and omics-based technologies (Floros et al, 2016 ; Huang et al, 2017 ; Jones and Bunnage, 2017 ; Merwin et al, 2020 ) have emerged as approaches to characterize and select interesting chemo-structures with appropriate physicochemical properties and biological activities as well as to prioritize the isolation of natural compounds from biological sources (Chen et al, 2018 ; Wolfender et al, 2019 ), which open up new opportunities to explore their industrial applications. Combined with other in silico analyses, artificial intelligence and cheminformatics methods can screen a high diversity of chemo-structures isolated from natural sources or deposited in public databases (Chen and Kirchmair, 2020 ), analyzing their bioactivity, pharmacodynamics, and their pharmacokinetic properties, thus reducing the financial efforts involved in research programs that aim to find new chemical agents (Chen et al, 2018 ; Al Sharie et al, 2020 ; Medina-Franco and Saldívar-González, 2020 ).…”

Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds

“…For example, various structural and molecular representations in cheminformatics have proven to help study the molecular complexity and quantify the chemical diversity of a library of compounds. This computational approach has also allowed for profiling, prioritization, and comparison of the molecular descriptors, physicochemical, and pharmacokinetic properties of a group of NPs and others or with those of known drugs [ 44 , 45 , 46 , 47 ].…”