Applications of Chemoinformatics in Drug Discovery

Gillet, Valerie J.

doi:10.1002/9781119483977.ch2

Cited by 3 publications

(5 citation statements)

References 79 publications

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“…In addition, it can computationally process a large set of compounds from virtual combinatorial libraries and high-throughput screening to guide rational decision-making in drug discovery and development. This technique of processing large chemical bioactivity data is called cheminformatics [ 39 ].…”

Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

“…Cheminformatic is a data mining technique that uses computer and information strategies to solve chemical problems by processing raw data into information and information into knowledge [ 39 , 40 ]. Chemical data processing in this context involves working with chemical structures [ 41 ].…”

Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

“…Chemical data processing in this context involves working with chemical structures [ 41 ]. Therefore, this strategy for drug developers aims to provide better and faster decision-making processes in discovery and lead optimization [ 39 ]. Cheminformatics is gaining much acceptance in the field of computational chemistry.…”

Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

“…Cheminformatics is gaining much acceptance in the field of computational chemistry. It has great potential, especially in the retrieval and extraction of chemical information, database search for compounds, interactive data mining for molecular graphs, and analyses of chemical diversity [ 39 , 41 , 42 , 43 ]. It is relevant, particularly in processing hit compounds from virtual and actual high throughput screenings.…”

Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

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

2021

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The growing antimicrobial resistance (AMR) of pathogenic organisms to currently prescribed drugs has resulted in the failure to treat various infections caused by these superbugs. Therefore, to keep pace with the increasing drug resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have been shown to display promising in vitro activities against multidrug-resistant pathogens. Still, only a few of these compounds have been studied as prospective drug candidates. This may be due to the expensive and time-consuming process of conducting important studies on these compounds. The present review focuses on applying cheminformatics strategies to characterize, prioritize, and optimize NPs to develop new lead compounds against antimicrobial resistance pathogens. Moreover, case studies where these strategies have been used to identify potential drug candidates, including a few selected open-access tools commonly used for these studies, are briefly outlined.

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Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

Section: Cheminformatics Techniques In Antimicrobial Drug Discovery and Developmentmentioning

confidence: 99%

See 2 more Smart Citations

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

2021

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“…Accordingly, the use of novel and better algorithms have led to a large number of publications showing the extent of their applicability in computer-aided drug design projects [15][16][17]. The impact of chemoinformatics, understood nowadays as a discipline intersecting chemistry and computer science [18], has been moreover boosted by the development of machine learning algorithms in recent years [19][20][21]. Its use has extended across all levels of a typical drug discovery pipeline.…”

Section: Introductionmentioning

confidence: 99%

Colombian Contributions Fighting Leishmaniasis: A Systematic Review on Antileishmanials Combined with Chemoinformatics Analysis

2020

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Leishmaniasis is a parasitic morbid/fatal disease caused by Leishmania protozoa. Twelve million people worldwide are appraised to be currently infected, including ca. two million infections each year, and 350 million people in 88 countries are at risk of becoming infected. In Colombia, cutaneous leishmaniasis (CL) is a public health problem in some tropical areas. Therapeutics is based on traditional antileishmanial drugs, but this practice has several drawbacks for patients. Thus, the search for new antileishmanial agents is a serious need, but the lack of adequately funded research programs on drug discovery has hampered its progress. Some Colombian researchers have conducted different research projects focused on the assessment of the antileishmanial activity of naturally occurring and synthetic compounds against promastigotes and/or amastigotes. Results of such studies have separately demonstrated important hits and reasonable potential, but a holistic view of them is lacking. Hence, we present the outcome from a systematic review of the literature (under PRISMA guidelines) on those Colombian studies investigating antileishmanials during the last thirty-two years. In order to combine the general efforts aiming at finding a lead against Leishmania panamensis (one of the most studied and incident parasites in Colombia causing CL) and to recognize structural features of representative compounds, fingerprint-based analyses using conventional machine learning algorithms and clustering methods are shown. Abstraction from such a meta-description led to describe some function-determining molecular features and simplify the clustering of plausible isofunctional hits. This systematic review indicated that the Colombian efforts for the antileishmanials discovery are increasingly intensified, though improvements in the followed pathways must be definitively pursued. In this context, a brief discussion about scope, strengths and limitations of such advances and relationships is addressed.

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