Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 2922 2022-09-30 19:07:41 |
2 layout + 2 word(s) 2924 2022-10-08 07:17:36 | |
3 layout + 2 word(s) 2926 2022-10-08 07:20:50 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Gómez-García, A.;  Medina-Franco, J.L. Progress of Natural Product Databases. Encyclopedia. Available online: https://encyclopedia.pub/entry/28186 (accessed on 23 April 2024).
Gómez-García A,  Medina-Franco JL. Progress of Natural Product Databases. Encyclopedia. Available at: https://encyclopedia.pub/entry/28186. Accessed April 23, 2024.
Gómez-García, Alejandro, José L. Medina-Franco. "Progress of Natural Product Databases" Encyclopedia, https://encyclopedia.pub/entry/28186 (accessed April 23, 2024).
Gómez-García, A., & Medina-Franco, J.L. (2022, September 30). Progress of Natural Product Databases. In Encyclopedia. https://encyclopedia.pub/entry/28186
Gómez-García, Alejandro and José L. Medina-Franco. "Progress of Natural Product Databases." Encyclopedia. Web. 30 September, 2022.
Progress of Natural Product Databases
Edit

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. Computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element of CADD. 

natural product databases NuBBEDB SistematX

1. Natural Product Databases

Between 2000 and 2019, 123 commercial and open access NP (natural product) databases have been published. Of them, 98 are still somehow accessible, 92 are open access, and only 50 contain molecular structures that can be retrieved for a chemoinformatic analysis [1]Table 1 summarizes examples of the most representative NP databases. Among the largest commercial databases is the Dictionary of Natural Products [2]. It contains more than 230,000 compounds and provides names and synonyms, physicochemical properties, spectroscopic data, molecular structures, and biological source and use. Another commercial database is Scifinder [3], assembled and maintained by the American Chemical Society (ACS). It contains arguably the most extensive collection of NPs (natural products), with over 300,000. This is due to the fact that, since 1957, the Chemical Abstracts Service (CAS), a division of the ACS, assigns a unique registry number to every new chemical substance reported in the scientific literature. Another large commercial database is Reaxys [4], collected and maintained by Elsevier. It contains approximately 107 molecules including over 200,000 NPs. The Collection of Open Natural Products (COCONUT) [5] is a major open access database of NPs, containing more than 411,000 NPs collected from 50 open access NP databases. The Universal Natural Product Database [6] is a compilation that tried to gather all the known NPs; it has more than 229,000 NPs. It provides 3D structures with stereochemical information and calculated molecular descriptors. It is not yet accessible through the link in the original publication. Instead, it is contained and maintained on the ISDB website [7]. The SuperNatural Ⅱ [8] database contains over 325,000 NPs and includes information about 2D structures, physicochemical properties, predicted toxicity class, and potential vendors. Nevertheless, it does not provide a bulk download.
ZINC [9] is another open access database with over 80,000 NPs, with approximately 48,000 which are purchasable. It includes information regarding known biological targets and predicted targets. The download of the entire subset of NPs in 1D or 3D notation is straightforward. Some NP databases are no longer accessible through the link provided in the original publication. Fortunately, their structures are in ZINC. Such is the case with the Herbal Ingredient Targets [10] and Herbal Ingredients in vivo Metabolism database [11], which contain NPs mostly from Chinese plants. Specs [12] has an industrial catalog of purchasable NPs, although the website does not allow the downloading of compounds anymore. Nonetheless, the structures are available via ZINC. Despite the Universal Natural Product Database, SuperNatural Ⅱ, and ZINC being among the largest databases of NPs in the public domain, they do not offer information regarding the taxonomic and geographic origin of the organisms that produce the NPs, and there is a lack of literature references [1].
Traditional Chinese medicine (TCM) is part of the public health system [13]. Therefore, the China Government encourages research in the area of NPs, and as a consequence, a large number of NP databases have been published [14][15][16][17][18][19][20]. Nonetheless, TCM@Taiwan is the most extensive database of NPs used in the TCM [21], containing approximately 58,000 molecules. Regarding traditional medicine in India (Indian Ayurveda), there are two open access databases available: IMPPAT [22], which contains more than 10,000 phytochemicals extracted from 1700 medicinal plants; and MedPServer [23], containing 1124 NPs coming from North-East India. Moreover, there are several databases containing compounds from African traditional medicine [24][25][26][27][28][29]. Nevertheless, AfroDB [30] is the most comprehensive, composed of around 1000 NPs, and it is accessible via ZINC.
Table 1. Most representative natural products databases.
Database Name Number of Compounds Accessibility Reference
Collection of Open Natural Products (COCONUT) 411,621 Open access [5]
Universal Natural Product Database ∼229,000 Open access [6]
SuperNatural Ⅱ 325,508 Open access [8]
ZINC ∼80,000 Open access [9]
Dictionary of Natural Products ∼230,000 Commercial [2]
Scifinder ∼300,000 Commercial [3]
Reaxys ∼200,000 Commercial [4]
TCM@Taiwan ∼58,000 Open access [21]
IMPPAT ∼10,000 Open access [22]
AfroDB ∼1000 Open access [30]

2. Latin American Natural Product Databases

2.1. NuBBEDB

The database is the result of the collaboration between the Nuclei of Bioassays, Biosynthesis and Ecophysiology of Natural Products (NuBBE) research group of the São Paulo State University and the Laboratory of Computational and Medicinal Chemistry of the University of São Paulo. The database was published in 2013 as the first NP library of Brazilian biodiversity, containing 640 compounds [31]; in 2017, an updated version came out with more than 2000 NPs [32]. Currently, the database contains 2223 compounds. The available information regarding the compounds includes the International Union of Pure and Applied Chemistry (IUPAC) name, linear notations (SMILES, InChI, and InChIKey strings), Ro5 and Veber descriptors, and predicted spectroscopic data: nuclear magnetic resonance (NMR), source, therapeutic effect and reference. It is possible to download the whole database in .mol2 format. Additionally, the database can be found in Chemspider and ZINC, and it is part of the COCONUT database.
The website allows users to search compounds by selecting specific criteria: metabolic class (alkaloids, flavonoids, lignoids, etc.), name and location of the species that contain the NP, source (marine, plant, etc.), and drug-like physicochemical properties. Furthermore, one can draw a structure and retrieve the compounds that contain it or search compounds that contain a specific NMR signal.
An absorption, distribution, metabolism, excretion and toxicity (ADMET) profile of the database revealed that 91% of the compounds can permeate through the human intestinal barrier, and 93% of the molecules can efficiently move in systemic circulation and reach their desired site of action. Moreover, it is predicted that most of the compounds do not inhibit five isoforms of CYP450 (CYP 3A4, 2D6, 1A2, 2C9, and 2C19). The CYP450 enzyme is responsible for detoxifying more than 80% of drugs in liver first-pass metabolism, and therefore, any compound that inhibits it may cause toxicity. The clearance prediction revealed that 94% of the compounds are readily excreted from the human body after executing their therapeutic function. Finally, 87% of compounds were shown to have no mutagenicity, tumorigenicity, reproductive effect, and irritant properties [33].
Another study characterized the chemical space and diversity. It was found that NuBBEDB has a focused chemical space within the space of drug-like physicochemical properties. The study also revealed that the larger source of diversity is driven by the side chains. Another finding revealed that the diversity and complexity varies according to the origin of the compounds when comparing NuBBEDB to other NP databases. One conclusion of the study is that NuBBEDB is a promising source of molecules for drug discovery [34].
The NuBBEDB database was employed in a VS study with the purpose of finding compounds against Trypanosoma cruzi. The researchers looked for trypanothione reductase inhibitors: this enzyme is a validated target for the discovery of new antiprotozoal compounds. Ten compounds were identified as potential inhibitors of the enzyme [35]. In another study, 13 compounds against Mycobacterium tuberculosis were identified from NuBBEDB [36]. The molecules are inhibitors of the serine/threonine protein kinase, which is essential for the growth and survival of the pathogen [37].

2.2. SistematX

The database was developed at the Laboratory of Cheminformatics of the Federal University of Paraiba, Brazil. The first version came out in 2018 containing 2150 secondary metabolites [38], and a second version was published in 2021 with a total of 9514 unique secondary metabolites [39]. The information for every compound includes the IUPAC name, SMILES, InChI and InChIKey strings, CAS registry number, physicochemical drug-like descriptors, predicted NMR spectra, predicted biological activities, and the bibliographic reference. A unique feature is the information regarding the taxonomic rank, from family to species, and the global positioning system (GPS) coordinates of the plant from which the compound was isolated. On the website (Table 2), the search of specific compounds can be through the 2D drawing of the structure, by the SMILES strings, compound name, taxonomic rank, and physicochemical properties. It is possible to download the entire database in .csv or .sdf format.
Table 2. Latin American natural products databases.
Database Size Country Source Database Website Reference
NuBBEDB 2223 Brazil Plants
Microorganisms
Terrestrial animals
Marine animals
http://nubbe.iq.unesp.br/portal/nubbe-search.html [31][32]
SistematX 9514 Brazil Plants https://sistematx.ufpb.br/ [38][39]
UEFS 503 Brazil Plants http://zinc12.docking.org/catalogs/uefsnp [40]
CIFPMA 454 Panama Plants Not available.
Structures accessible under request.
[41][42]
UNIIQUIM Unknown Mexico Plants https://uniiquim.iquimica.unam.mx/ [43]
BIOFACQUIM 553 Mexico Plants
Fungus
Propolis
Marine animals
Database version 1
https://biofacquim.herokuapp.com/
Database version 2
https://figshare.com/articles/dataset/BIOFAQUIM_V2_sdf/11312702
[44][45]
SistematX has been employed in five VS studies. In the first study, compounds with potential antichagasic activity were identified from 1306 sesquiterpene lactones on the database. (Chagas disease is an endemic disease caused by Trypanosoma cruzi.) The study employed two approaches, LBVS and SBVS. From LBVS, the most prominent compound showed a probability of 0.82 of inhibition. From SBVS, 13 potential inhibitors were identified [46]. In another VS study, with the purpose of identifying compounds against the intracellular parasitic protozoan Leishmania donovani which causes Leishmaniasis, 13 promising, enzyme-targeting, antileishmanial compounds were identified from the sesquiterpene lactones on SistematX [47]. In the third VS study, the researchers looked for compounds against Schistosoma mansoni, which causes the chronic parasitic disease Schistosomiasis. From the 1000 alkaloids on SistematX, five compounds were identified with potential multitarget schistosomicidal activity [48]. In the fourth VS study, 1955 diterpenes on SistematX were employed to search for compounds against SARS-CoV-2. Nineteen compounds were identified as potential SARS-CoV-2 inhibitors [49]. In the most recent VS campaign, the researchers were seeking acetylcholinesterase (AChE) inhibitors, which is an approach for the treatment of Alzheimer’s disease. They employed a combined approach in which machine learning classification models and molecular docking calculations were used to identify two promising AChE inhibitors [50]. Other applications of SistematX include chemotaxonomic studies using self-organizing map algorithms [51] and the profile of over 2000 metabolites from the Asteraceae family while screening for inhibitors of Leishmania major dihydroorotate dehydrogenase [52].

2.3. UEFS

The NP database of the State University of Feira de Santana [40] was developed and is maintained by the State University of Feira de Santana in Bahia, Brazil (UEFS, for its acronym in Portuguese: Universidade Estadual de Feira de Santana). The database contains NPs that have been separately published, but there is no common publication nor public database for it. Nevertheless, it is accessible via ZINC. There are 503 NPs in the database. It is possible to download the whole database in .mol2 or .sdf format, and it provides a bulk download of the SMILES strings. The available information of the NPs includes calculated physicochemical properties, biological targets, and binding affinity, together with the bibliographic reference. There is a cross-reference for the biological targets to Reactome which is an open source, open access, manually curated and peer-reviewed pathway database [53]. Finally, it is possible to find information about the vendors of individual compounds.

2.4. CIFPMA

The NP database of CIFLORPAN from the University of Panama, Republic of Panama (CIFPMA) was developed by the Center for Pharmacognostic Research on Panamanian Flora (CIFLORPAN, for its acronym in Spanish: Centro de Investigaciones Farmacognósticas de la Flora Panameña), College of Pharmacy of the University of Panama. The first version was published in 2017 [41], containing 354 molecules; in 2019, the database was updated to 454 compounds [42]. The compounds have been tested in over 25 in vitro and in vivo bioassays, for different therapeutic targets including anti-HIV (human immunodeficiency virus), antioxidants, and anticancer. In fact, the compound structures are available upon request.
A chemoinformatic analysis of the database suggested that, in general, the compounds have drug-like properties. The database was compared to the TCM@Taiwan and UEFS databases. It was found that CIFPMA has the largest scaffold diversity compared to other databases. Moreover, unique scaffolds were found in the CIFPMA database. Finally, it was established which scaffolds are present in compounds with experimental cytotoxic effect, anti-HIV-1, antimalarial, anti-trypanosomatid, and antifungal activities [41].
The database was part of another chemoinformatics study, which involved a comparison of several NP databases against other databases with compounds of synthetic origin. The study revealed that so many of the NPs and synthetic compounds share the same chemical space. Moreover, the NPs present a larger fingerprint-based diversity than the synthetic compounds. Furthermore, the study revealed that NPs have a higher proportion of chiral carbons and atoms with sp3 hybridization and greater complexity, while synthetic products contain a greater proportion of aromatic atoms. Lastly, cyclicity, relative shape, and flexibility are very similar in NPs and synthetic compounds [42].

2.5. UNIIQUIM

The database was created at the National Autonomous University of Mexico (UNAM, for its acronym in Spanish: Universidad Nacional Autónoma de México) by The Informatics Unit of the Institute of Chemistry (UNIIQUIM, for its acronym in Spanish: Unidad de Informática del Instituto de Química). The database [43] is composed of NPs from Mexico and mainly NPs isolated and characterized by the Department of Natural Products of the Institute of Chemistry, UNAM. The number of NPs on the database is not clear, and the website is only in Spanish. The information on the NPs includes the IUPAC name, CAS registry number, physicochemical properties, the species that synthesizes the NP, the spectroscopic techniques employed to characterize the compound, experimental biological activity, and reference to either the article where the NP is reported or to the articles that report the biological activities. In the current version, it is not possible to make a bulk download. The content can be browsed displaying a table either with the chemical structures or with the producing organism. Furthermore, the content can be browsed in a table that contains the bibliographic references.
In a study, the chemical and toxicological profile of molecules with analgesic activity was described. The results showed that most of the compounds probably interact with the opioid receptor. Moreover, the predicted acute toxicity is low, and none is predicted to be mutagenic. The study concludes that due to the structural diversity, the common nociception activity and the predicted safety profile as nonmutagenic agents highlights the importance of the molecules for further studies on the search of analgesic and nociception effects [54].

2.6. BIOFACQUIM

The database was curated and constructed in Mexico by the Computer-Aided Drug Design at the School of Chemistry (DIFACQUIM, for its acronym in Spanish: Diseño de Fármacos Asistido por Computadora) research group, UNAM. The first version came out in 2019 [44] and contained 423 NPs isolated and characterized in Mexico at the School of Chemistry, UNAM, between the years 2000 and 2018. Later, in 2020, a second version came out [45], and the database was updated with NPs isolated and characterized by research groups of other Mexican institutions, reaching a total of 531 molecules. Nowadays, the database contains 553 NPs. The database is composed mainly of NPs that come from plants, followed by fungus, and to a lesser extent, propolis and marine animals. There is a website for the first version of the database, and it allows the user to search the compounds by name. Moreover, it is possible to retrieve compounds by kingdom (plant, fungus, propolis). The entire database can be downloaded in .csv format. The latest version of the database is available on a different website [45], and it is possible to download the whole database in .sdf format. Information on the NPs includes the compound name, SMILES strings, bibliographic reference, taxonomic rank (kingdom, genus, species), place where it is found, the source from which the NP was isolated, biological activity, and IC50 value. The database is also available at ZINC, and it is part of the COCONUT database.
A chemoinformatics analysis of the first version of the database concluded that the compounds have a broad coverage in the chemical space and overlap regions in the drug-like space. Furthermore, compounds very similar to drugs approved for clinical use were identified [44]. In another study, a structural content analysis of the second version was performed. BIOFACQUIM was compared to ChEMBL 25 (1,667,509 molecules) and a database with 169,839 NPs. The researchers concluded that 44.3% of the unique compounds contained in BIOFACQUIM are focused on drug-like space in terms of physicochemical properties. Additionally, a significant number of compounds and scaffolds (79 and 29, respectively) were identified that were not present in the two large reference sets [45]. Finally, an in silico absorption, distribution, metabolism, excretion and toxicological (ADMET) profile of the second version of BIOFACQUIM was performed. The study concluded that the absorption and distribution profiles of the compounds in BIOFACQUIM are similar to those of approved drugs, while the metabolism profile is comparable to that in other NP databases. The excretion profile of the compounds is different from that of the approved drugs, but their predicted toxicity profile is comparable [55].
An independent VS study looked for beta-glucosidase inhibitors. The pharmacological applications of these compounds include obesity, diabetes, hyperlipoproteinemia, cancer, HIV, and hepatitis B and C. Employing classification models (two-variable artificial network), eight compounds were identified from BIOFACQUIM as active [56]. In addition, in an independent study, Barrera-Vázquez et al. looked for senolytic compounds which selectively eliminate senescent cells. Cellular senescence is a cellular condition that involves significant changes in gene expression and the arrest of cell proliferation. The elimination of senescent cells delays, prevents, and improves multiple adverse outcomes related to age. Through the use of chemoinformatics tools (fingerprinting and network pharmacology), and employing two NP databases, InflamNat and BIOFACQUIM, three senolytic compounds were identified [57].
Table 3 summarizes the main applications of databases of representative Latin American natural products to identify bioactive compounds.
Table 3. Practical applications of the databases of Latin American natural products.
Database Name Disease or Symptom Causative Agent Number of Identified Compounds Reference
NuBBEDB Chagas disease Trypanosoma cruzi 10 [35]
Tuberculosis Mycobacterium tuberculosis 13 [36]
SistematX Chagas disease Trypanosoma cruzi 13 [46]
Leishmaniasis Leishmania donovani 13 [47]
Schistosomiasis Schistosoma mansoni 5 [48]
Coronavirus disease 2019 SARS-CoV-2 19 [49]
Alzheimer’s disease   2 [50]
UNIIQUIM Pain   6 [54]
BIOFACQUIM Obesity   8 [56]
Diabetes    
Hyperlipoproteinemia    
Cancer    
HIV/AIDS *    
Hepatitis B and C.    
Age-related diseases 3 [57]
* Human immunodeficiency virus infection and acquired immunodeficiency syndrome (HIV/AIDS). Although CIFPMA does not appear in the table, their compounds have been assayed in a wide range of in vitro and in vivo bioassays.

References

  1. Sorokina, M.; Steinbeck, C. Review on natural products databases: Where to find data in 2020. J. Cheminform. 2020, 12, 20.
  2. Dictionary of Natural Products 31.1. Available online: https://dnp.chemnetbase.com/faces/chemical/ChemicalSearch.xhtml (accessed on 30 June 2022).
  3. Gabrielson, S.W. SciFinder. J. Med. Libr. Assoc. 2018, 106, 588–590.
  4. Reaxys. Available online: https://www.reaxys.com (accessed on 30 June 2022).
  5. Sorokina, M.; Merseburger, P.; Rajan, K.; Yirik, M.A.; Steinbeck, C. COCONUT online: Collection of Open Natural Products database. J. Cheminform. 2021, 13, 2.
  6. Gu, J.; Gui, Y.; Chen, L.; Yuan, G.; Lu, H.-Z.; Xu, X. Use of natural products as chemical library for drug discovery and network pharmacology. PLoS ONE 2013, 8, e62839.
  7. ISDB. A Database of In-Silico Predicted MS/MS Spectrum of Natural Products. Available online: http://oolonek.github.io/ISDB/ (accessed on 30 June 2022).
  8. Banerjee, P.; Erehman, J.; Gohlke, B.-O.; Wilhelm, T.; Preissner, R.; Dunkel, M. Super Natural II—A database of natural products. Nucleic Acids Res. 2015, 43, D935–D939.
  9. Sterling, T.; Irwin, J.J. ZINC 15-Ligand Discovery for Everyone. J. Chem. Inf. Model. 2015, 55, 2324–2337.
  10. Ye, H.; Ye, L.; Kang, H.; Zhang, D.; Tao, L.; Tang, K.; Liu, X.; Zhu, R.; Liu, Q.; Chen, Y.Z.; et al. HIT: Linking herbal active ingredients to targets. Nucleic Acids Res. 2011, 39, D1055–D1059.
  11. Kang, H.; Tang, K.; Liu, Q.; Sun, Y.; Huang, Q.; Zhu, R.; Gao, J.; Zhang, D.; Huang, C.; Cao, Z. HIM-herbal ingredients in-vivo metabolism database. J. Cheminform. 2013, 5, 28.
  12. Specs. Compound Management Services and Supplier of Research Compounds to the Life Science Industry. Available online: https://www.specs.net/ (accessed on 30 June 2022).
  13. Xu, J.; Yang, Y. Traditional Chinese medicine in the Chinese health care system. Health Policy 2009, 90, 133–139.
  14. Li, B.; Ma, C.; Zhao, X.; Hu, Z.; Du, T.; Xu, X.; Wang, Z.; Lin, J. YaTCM: Yet another Traditional Chinese Medicine Database for Drug Discovery. Comput. Struct. Biotechnol. J. 2018, 16, 600–610.
  15. Ru, J.; Li, P.; Wang, J.; Zhou, W.; Li, B.; Huang, C.; Li, P.; Guo, Z.; Tao, W.; Yang, Y.; et al. TCMSP: A database of systems pharmacology for drug discovery from herbal medicines. J. Cheminform. 2014, 6, 13.
  16. Kim, S.-K.; Nam, S.; Jang, H.; Kim, A.; Lee, J.-J. TM-MC: A database of medicinal materials and chemical compounds in Northeast Asian traditional medicine. BMC Complement. Altern. Med. 2015, 15, 218.
  17. Xu, H.-Y.; Zhang, Y.-Q.; Liu, Z.-M.; Chen, T.; Lv, C.-Y.; Tang, S.-H.; Zhang, X.-B.; Zhang, W.; Li, Z.-Y.; Zhou, R.-R.; et al. ETCM: An encyclopaedia of traditional Chinese medicine. Nucleic Acids Res. 2019, 47, D976–D982.
  18. Fang, X.; Shao, L.; Zhang, H.; Wang, S. CHMIS-C: A comprehensive herbal medicine information system for cancer. J. Med. Chem. 2005, 48, 1481–1488.
  19. Qiao, X.; Hou, T.; Zhang, W.; Guo, S.; Xu, X. A 3D structure database of components from Chinese traditional medicinal herbs. J. Chem. Inf. Comput. Sci. 2002, 42, 481–489.
  20. Huang, J.; Zheng, Y.; Wu, W.; Xie, T.; Yao, H.; Pang, X.; Sun, F.; Ouyang, L.; Wang, J. CEMTDD: The database for elucidating the relationships among herbs, compounds, targets and related diseases for Chinese ethnic minority traditional drugs. Oncotarget 2015, 6, 17675–17684.
  21. Chen, C.Y.-C. TCM : The world’s largest traditional Chinese medicine database for drug screening in silico. PLoS ONE 2011, 6, e15939.
  22. Mohanraj, K.; Karthikeyan, B.S.; Vivek-Ananth, R.P.; Chand, R.P.B.; Aparna, S.R.; Mangalapandi, P.; Samal, A. IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics. Sci. Rep. 2018, 8, 4329.
  23. Potshangbam, A.M.; Polavarapu, R.; Rathore, R.S.; Naresh, D.; Prabhu, N.P.; Potshangbam, N.; Kumar, P.; Vindal, V. MedPServer: A database for identification of therapeutic targets and novel leads pertaining to natural products. Chem. Biol. Drug Des. 2019, 93, 438–446.
  24. Bultum, L.E.; Woyessa, A.M.; Lee, D. ETM-DB: Integrated Ethiopian traditional herbal medicine and phytochemicals database. BMC Complement. Altern. Med. 2019, 19, 212.
  25. Ntie-Kang, F.; Onguéné, P.A.; Scharfe, M.; Owono Owono, L.C.; Megnassan, E.; Mbaze, L.M.; Sippl, W.; Efange, S.M.N. ConMedNP: A natural product library from Central African medicinal plants for drug discovery. RSC Adv. 2014, 4, 409–419.
  26. Ibezim, A.; Debnath, B.; Ntie-Kang, F.; Mbah, C.J.; Nwodo, N.J. Binding of anti-Trypanosoma natural products from African flora against selected drug targets: A docking study. Med. Chem. Res. 2017, 26, 562–579.
  27. Onguéné, P.A.; Ntie-Kang, F.; Mbah, J.A.; Lifongo, L.L.; Ndom, J.C.; Sippl, W.; Mbaze, L.M. The potential of anti-malarial compounds derived from African medicinal plants, part III: An in silico evaluation of drug metabolism and pharmacokinetics profiling. Org. Med. Chem. Lett. 2014, 4, 6.
  28. Ntie-Kang, F.; Nwodo, J.N.; Ibezim, A.; Simoben, C.V.; Karaman, B.; Ngwa, V.F.; Sippl, W.; Adikwu, M.U.; Mbaze, L.M. Molecular modeling of potential anticancer agents from African medicinal plants. J. Chem. Inf. Model. 2014, 54, 2433–2450.
  29. Ntie-Kang, F.; Amoa Onguéné, P.; Fotso, G.W.; Andrae-Marobela, K.; Bezabih, M.; Ndom, J.C.; Ngadjui, B.T.; Ogundaini, A.O.; Abegaz, B.M.; Meva’a, L.M. Virtualizing the p-ANAPL library: A step towards drug discovery from African medicinal plants. PLoS ONE 2014, 9, e90655.
  30. Ntie-Kang, F.; Zofou, D.; Babiaka, S.B.; Meudom, R.; Scharfe, M.; Lifongo, L.L.; Mbah, J.A.; Mbaze, L.M.; Sippl, W.; Efange, S.M.N. AfroDb: A select highly potent and diverse natural product library from African medicinal plants. PLoS ONE 2013, 8, e78085.
  31. Valli, M.; dos Santos, R.N.; Figueira, L.D.; Nakajima, C.H.; Castro-Gamboa, I.; Andricopulo, A.D.; Bolzani, V.S. Development of a natural products database from the biodiversity of Brazil. J. Nat. Prod. 2013, 76, 439–444.
  32. Pilon, A.C.; Valli, M.; Dametto, A.C.; Pinto, M.E.F.; Freire, R.T.; Castro-Gamboa, I.; Andricopulo, A.D.; Bolzani, V.S. NuBBEDB: An updated database to uncover chemical and biological information from Brazilian biodiversity. Sci. Rep. 2017, 7, 7215.
  33. Fatima, S.; Gupta, P.; Sharma, S.; Sharma, A.; Agarwal, S.M. ADMET profiling of geographically diverse phytochemical using chemoinformatic tools. Future Med. Chem. 2020, 12, 69–87.
  34. Saldívar-González, F.I.; Valli, M.; Andricopulo, A.D.; da Silva Bolzani, V.; Medina-Franco, J.L. Chemical space and diversity of the nubbe database: A chemoinformatic characterization. J. Chem. Inf. Model. 2019, 59, 74–85.
  35. do Carmo Santos, N.; da Paixão, V.G.; da Rocha Pita, S.S. New Trypanosoma cruzi Trypanothione Reductase Inhibitors Identification using the Virtual Screening in Database of Nucleus Bioassay, Biosynthesis and Ecophysiology (NuBBE). Antiinfect Agents 2019, 17, 138–149.
  36. Antunes, S.S.; Won-Held Rabelo, V.; Romeiro, N.C. Natural products from Brazilian biodiversity identified as potential inhibitors of PknA and PknB of M. tuberculosis using molecular modeling tools. Comput. Biol. Med. 2021, 136, 104694.
  37. Chawla, Y.; Upadhyay, S.; Khan, S.; Nagarajan, S.N.; Forti, F.; Nandicoori, V.K. Protein kinase B (PknB) of Mycobacterium tuberculosis is essential for growth of the pathogen in vitro as well as for survival within the host. J. Biol. Chem. 2014, 289, 13858–13875.
  38. Scotti, M.T.; Herrera-Acevedo, C.; Oliveira, T.B.; Costa, R.P.O.; Santos, S.Y.K.D.O.; Rodrigues, R.P.; Scotti, L.; Da-Costa, F.B. SistematX, an Online Web-Based Cheminformatics Tool for Data Management of Secondary Metabolites. Molecules 2018, 23, 103.
  39. Costa, R.P.O.; Lucena, L.F.; Silva, L.M.A.; Zocolo, G.J.; Herrera-Acevedo, C.; Scotti, L.; Da-Costa, F.B.; Ionov, N.; Poroikov, V.; Muratov, E.N.; et al. The sistematx web portal of natural products: An update. J. Chem. Inf. Model. 2021, 61, 2516–2522.
  40. UEFS Natural Products. Available online: http://zinc12.docking.org/catalogs/uefsnp (accessed on 30 June 2022).
  41. Olmedo, D.A.; González-Medina, M.; Gupta, M.P.; Medina-Franco, J.L. Cheminformatic characterization of natural products from Panama. Mol. Divers. 2017, 21, 779–789.
  42. Olmedo, D.A.; Medina-Franco, J.L. Chemoinformatic approach: The case of natural products of panama. In Cheminformatics and Its Applications; IntechOpen: London, UK, 2019.
  43. UNIIQUIM. Available online: https://uniiquim.iquimica.unam.mx/ (accessed on 19 July 2022).
  44. Pilón-Jiménez, B.A.; Saldívar-González, F.I.; Díaz-Eufracio, B.I.; Medina-Franco, J.L. BIOFACQUIM: A mexican compound database of natural products. Biomolecules 2019, 9, 31.
  45. Sánchez-Cruz, N.; Pilón-Jiménez, B.A.; Medina-Franco, J.L. Functional group and diversity analysis of BIOFACQUIM: A Mexican natural product database. F1000Research 2019, 8, 2071.
  46. Acevedo, C.H.; Scotti, L.; Scotti, M.T. In Silico Studies Designed to Select Sesquiterpene Lactones with Potential Antichagasic Activity from an In-House Asteraceae Database. ChemMedChem 2018, 13, 634–645.
  47. Herrera-Acevedo, C.; Dos Santos Maia, M.; Cavalcanti, É.B.V.S.; Coy-Barrera, E.; Scotti, L.; Scotti, M.T. Selection of antileishmanial sesquiterpene lactones from SistematX database using a combined ligand-/structure-based virtual screening approach. Mol. Divers. 2021, 25, 2411–2427.
  48. Menezes, R.P.B.D.; Viana, J.D.O.; Muratov, E.; Scotti, L.; Scotti, M.T. Computer-Assisted Discovery of Alkaloids with Schistosomicidal Activity. Curr. Issues Mol. Biol. 2022, 44, 383–408.
  49. Rodrigues, G.C.S.; Dos Santos Maia, M.; de Menezes, R.P.B.; Cavalcanti, A.B.S.; de Sousa, N.F.; de Moura, É.P.; Monteiro, A.F.M.; Scotti, L.; Scotti, M.T. Ligand and Structure-based Virtual Screening of Lamiaceae Diterpenes with Potential Activity against a Novel Coronavirus (2019-nCoV). Curr. Top. Med. Chem. 2020, 20, 2126–2145.
  50. Herrera-Acevedo, C.; Perdomo-Madrigal, C.; Herrera-Acevedo, K.; Coy-Barrera, E.; Scotti, L.; Scotti, M.T. Machine learning models to select potential inhibitors of acetylcholinesterase activity from SistematX: A natural products database. Mol. Divers. 2021, 25, 1553–1568.
  51. Barbosa Silva Cavalcanti, A.; Costa Barros, R.P.; Costa, V.C.D.O.; Sobral da Silva, M.; Fechine Tavares, J.; Scotti, L.; Scotti, M.T. Computer-Aided Chemotaxonomy and Bioprospecting Study of Diterpenes of the Lamiaceae Family. Molecules 2019, 24, 3908.
  52. Chibli, L.A.; Rosa, A.L.; Nonato, M.C.; Da Costa, F.B. Untargeted LC-MS metabolomic studies of Asteraceae species to discover inhibitors of Leishmania major dihydroorotate dehydrogenase. Metabolomics 2019, 15, 59.
  53. Reactome. Available online: https://reactome.org/ (accessed on 18 July 2022).
  54. Martinez-Mayorga, K.; Marmolejo-Valencia, A.F.; Cortes-Guzman, F.; García-Ramos, J.C.; Sánchez-Flores, E.I.; Barroso-Flores, J.; Medina-Franco, J.L.; Esquivel-Rodriguez, B. Toxicity Assessment of Structurally Relevant Natural Products from Mexican Plants with Antinociceptive Activity. J. Mex. Chem. Soc. 2017, 61, 186–196.
  55. Durán-Iturbide, N.A.; Díaz-Eufracio, B.I.; Medina-Franco, J.L. In silico adme/tox profiling of natural products: A focus on BIOFACQUIM. ACS Omega 2020, 5, 16076–16084.
  56. Przybyłek, M. Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening. Molecules 2020, 25, 5942.
  57. Barrera-Vázquez, O.S.; Gómez-Verjan, J.C.; Magos-Guerrero, G.A. Chemoinformatic Screening for the Selection of Potential Senolytic Compounds from Natural Products. Biomolecules 2021, 11, 467.
More
Information
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : ,
View Times: 460
Revisions: 3 times (View History)
Update Date: 08 Oct 2022
1000/1000