Literature DB >> 32143476

Repositioning Natural Products in Drug Discovery.

Giulio Rastelli1, Federica Pellati1, Luca Pinzi1, Maria Cristina Gamberini1.   

Abstract

Drug repositioning (o repurposing) has become one of the most popular and successful strategies to reduce failures typically associated with drug discovery [...].

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Year:  2020        PMID: 32143476      PMCID: PMC7179106          DOI: 10.3390/molecules25051154

Source DB:  PubMed          Journal:  Molecules        ISSN: 1420-3049            Impact factor:   4.411


Drug repositioning (o repurposing) has become one of the most popular and successful strategies to reduce failures typically associated with drug discovery [1]. It involves the identification of novel biological targets and different therapeutic uses of already approved and/or investigational drugs, including drugs that did not meet the primary therapeutic expectations. As such, many preclinical development and optimization issues, including adverse toxicology profiles, can be prevented or at least minimized. Although most drug repurposing success stories derived from serendipity, current research efforts focus on predicting repurposing possibilities on rational grounds [2]. Interestingly, while most drug repurposing campaigns rely on compounds derived from chemical synthesis, natural products can provide significant opportunities. Natural products are characterized by unique and favorable properties, a significant structural diversity, and by a high number of pharmacological activities [3]. Therefore, they are privileged chemical entities for drug (re)discovery strategies, which can highlight novel therapeutic utilities potentially unrelated to their original biological space [4]. Natural products have recently seen a resurgence of interest in drug discovery, but the way this is happening is significantly different from the past. Newer and emergent technologies, such as computational screening, proteomics, metabolomics and big data analysis have come into play to drive and speed up the “repurposing” of natural compounds and, more generally speaking, of nature-inspired compounds. In light of all the above, this Special Issue will focus on computational and experimental approaches in the research area of repurposing natural products, including studies on, but not limited to, the identification of new biological targets of natural compounds, the discovery of bioactive natural and/or nature-inspired compounds by in silico screening, their isolation and characterization, de-replication of natural extracts, analysis of structure–activity relationships of natural bioactive compounds. Overall, this collection will provide a multi-disciplinary view of how different research fields can interact in either the discovery or the repurposing of bioactive nature-inspired compounds. This issue is connected to the “Repositioning Natural Products in Drug Discovery” meeting held at the University of Modena (Italy) on Jan 17th, 2020 (http://www.mmddlab.unimore.it/site/home/rnpdd-meeting.html).
  4 in total

Review 1.  Natural Products as Sources of New Drugs from 1981 to 2014.

Authors:  David J Newman; Gordon M Cragg
Journal:  J Nat Prod       Date:  2016-02-07       Impact factor: 4.050

Review 2.  Underexplored Opportunities for Natural Products in Drug Discovery.

Authors:  Bart L DeCorte
Journal:  J Med Chem       Date:  2016-07-11       Impact factor: 7.446

Review 3.  Drug repurposing: progress, challenges and recommendations.

Authors:  Sudeep Pushpakom; Francesco Iorio; Patrick A Eyers; K Jane Escott; Shirley Hopper; Andrew Wells; Andrew Doig; Tim Guilliams; Joanna Latimer; Christine McNamee; Alan Norris; Philippe Sanseau; David Cavalla; Munir Pirmohamed
Journal:  Nat Rev Drug Discov       Date:  2018-10-12       Impact factor: 84.694

4.  On the Integration of In Silico Drug Design Methods for Drug Repurposing.

Authors:  Eric March-Vila; Luca Pinzi; Noé Sturm; Annachiara Tinivella; Ola Engkvist; Hongming Chen; Giulio Rastelli
Journal:  Front Pharmacol       Date:  2017-05-23       Impact factor: 5.810

  4 in total
  9 in total

Review 1.  Teaching an old dog new tricks: Drug discovery by repositioning natural products and their derivatives.

Authors:  Boshi Huang; Yan Zhang
Journal:  Drug Discov Today       Date:  2022-02-16       Impact factor: 8.369

2.  Anti-Inflammatory Effects of Psoralen Derivatives on RAW264.7 Cells via Regulation of the NF-κB and MAPK Signaling Pathways.

Authors:  Yeji Lee; Chang-Gu Hyun
Journal:  Int J Mol Sci       Date:  2022-05-22       Impact factor: 6.208

3.  Natural Products Extracted from Fungal Species as New Potential Anti-Cancer Drugs: A Structure-Based Drug Repurposing Approach Targeting HDAC7.

Authors:  Annalisa Maruca; Roberta Rocca; Raffaella Catalano; Francesco Mesiti; Giosuè Costa; Delia Lanzillotta; Alessandro Salatino; Francesco Ortuso; Francesco Trapasso; Stefano Alcaro; Anna Artese
Journal:  Molecules       Date:  2020-11-25       Impact factor: 4.411

4.  LigAdvisor: a versatile and user-friendly web-platform for drug design.

Authors:  Luca Pinzi; Annachiara Tinivella; Luca Gagliardelli; Domenico Beneventano; Giulio Rastelli
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

Review 5.  Plants in Anticancer Drug Discovery: From Molecular Mechanism to Chemoprevention.

Authors:  Arif Jamal Siddiqui; Sadaf Jahan; Ritu Singh; Juhi Saxena; Syed Amir Ashraf; Andleeb Khan; Ranjay Kumar Choudhary; Santhanaraj Balakrishnan; Riadh Badraoui; Fevzi Bardakci; Mohd Adnan
Journal:  Biomed Res Int       Date:  2022-03-02       Impact factor: 3.411

6.  On the development of B-Raf inhibitors acting through innovative mechanisms.

Authors:  Luca Pinzi
Journal:  F1000Res       Date:  2022-02-25

Review 7.  Potential clinical applications of phytopharmaceuticals for the in-patient management of coagulopathies in COVID-19.

Authors:  Ashis K Mukherjee; Dhruba J Chattopadhyay
Journal:  Phytother Res       Date:  2022-02-11       Impact factor: 6.388

8.  Solamargine Inhibits the Development of Hypopharyngeal Squamous Cell Carcinoma by Decreasing LncRNA HOXA11-As Expression.

Authors:  Ying Meng; Mengli Jin; Dai Yuan; Yicheng Zhao; Xiangri Kong; Xuerui Guo; Xingye Wang; Juan Hou; Bingmei Wang; Wu Song; Yong Tang
Journal:  Front Pharmacol       Date:  2022-07-12       Impact factor: 5.988

9.  A machine learning regression model for the screening and design of potential SARS-CoV-2 protease inhibitors.

Authors:  Gabriela Ilona B Janairo; Derrick Ethelbhert C Yu; Jose Isagani B Janairo
Journal:  Netw Model Anal Health Inform Bioinform       Date:  2021-07-24
  9 in total

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