Literature DB >> 17692498

A review of high throughput technology for the screening of natural products.

K P Mishra1, L Ganju, M Sairam, P K Banerjee, R C Sawhney.   

Abstract

High throughput screening is commonly defined as automatic testing of potential drug candidates at a rate in excess of 10,000 compounds per week. The aim of high throughput drug discovery is to test large compound collections for potentially active compounds ('hits') in order to allow further development of compounds for pre-clinical testing ('leads'). High throughput technology has emerged over the last few years as an important tool for drug discovery and lead optimisation. In this approach, the molecular diversity and range of biological properties displayed by secondary metabolites constitutes a challenge to combinatorial strategies for natural products synthesis and derivatization. This article reviews the approach of High throughput technique for the screening of natural products for drug discovery.

Mesh:

Substances:

Year:  2007        PMID: 17692498     DOI: 10.1016/j.biopha.2007.06.012

Source DB:  PubMed          Journal:  Biomed Pharmacother        ISSN: 0753-3322            Impact factor:   6.529


  18 in total

1.  Type IV traffic ATPase TrwD as molecular target to inhibit bacterial conjugation.

Authors:  Jorge Ripoll-Rozada; Yolanda García-Cazorla; María Getino; Cristina Machón; David Sanabria-Ríos; Fernando de la Cruz; Elena Cabezón; Ignacio Arechaga
Journal:  Mol Microbiol       Date:  2016-03-22       Impact factor: 3.501

2.  Proteoform-Specific Protein Binding of Small Molecules in Complex Matrices.

Authors:  Geuncheol Gil; Pan Mao; Bharathi Avula; Zulfiqar Ali; Amar G Chittiboyina; Ikhlas A Khan; Larry A Walker; Daojing Wang
Journal:  ACS Chem Biol       Date:  2016-12-21       Impact factor: 5.100

3.  Machine-learning techniques applied to antibacterial drug discovery.

Authors:  Jacob D Durrant; Rommie E Amaro
Journal:  Chem Biol Drug Des       Date:  2015-01       Impact factor: 2.817

4.  A convolutional neural network for the prediction and forward design of ribozyme-based gene-control elements.

Authors:  Calvin M Schmidt; Christina D Smolke
Journal:  Elife       Date:  2021-04-16       Impact factor: 8.140

Review 5.  Advances in mass spectrometry-based post-column bioaffinity profiling of mixtures.

Authors:  Jeroen Kool; Martin Giera; Hubertus Irth; Wilfried M A Niessen
Journal:  Anal Bioanal Chem       Date:  2010-11-24       Impact factor: 4.142

6.  NNScore 2.0: a neural-network receptor-ligand scoring function.

Authors:  Jacob D Durrant; J Andrew McCammon
Journal:  J Chem Inf Model       Date:  2011-11-03       Impact factor: 4.956

7.  Efficient screening of marine extracts for protease inhibitors by combining FRET based activity assays and surface plasmon resonance spectroscopy based binding assays.

Authors:  Tony Christopeit; Kersti Øverbø; U Helena Danielson; Inge W Nilsen
Journal:  Mar Drugs       Date:  2013-10-30       Impact factor: 5.118

8.  Antioxidant and antiproliferative activities of Abrus precatorius leaf extracts--an in vitro study.

Authors:  Mir Z Gul; Farhan Ahmad; Anand K Kondapi; Insaf A Qureshi; Irfan A Ghazi
Journal:  BMC Complement Altern Med       Date:  2013-03-02       Impact factor: 3.659

9.  Miniaturized bioaffinity assessment coupled to mass spectrometry for guided purification of bioactives from toad and cone snail.

Authors:  Ferry Heus; Reka A Otvos; Ruud L E G Aspers; Rene van Elk; Jenny I Halff; Andreas W Ehlers; Sébastien Dutertre; Richard J Lewis; Sybren Wijmenga; August B Smit; Wilfried M A Niessen; Jeroen Kool
Journal:  Biology (Basel)       Date:  2014-02-13

10.  In vitro antioxidant, antiproliferative, and phytochemical study in different extracts of Nyctanthes arbortristis flowers.

Authors:  Manjulatha Khanapur; Ravi K Avadhanula; Oruganti H Setty
Journal:  Biomed Res Int       Date:  2014-05-20       Impact factor: 3.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.