Literature DB >> 34888721

Computational Methods for Structure-Based Drug Design Through System Biology.

Aman Chandra Kaushik1, Shakti Sahi2, Dong-Qing Wei3,4.   

Abstract

The advances in computational chemistry and biology, computer science, structural biology, and molecular biology go in parallel with the rapid progress in target-based systems. This technique has become a powerful tool in medicinal chemistry for the identification of hit molecules. The recent developments in target-based systems have played a major role in the creation of libraries of compounds, and it has also been widely applied for the design of molecular docking methods. The main advantage of this method is that it hits the fragment that has the strongest binding, has relatively small size, and leads to better compounds in terms of pharmacokinetic properties when compared with virtual screening (VS) and high-throughput screening (HTS) hits. De novo design is an essential aspect of target-based systems and requires the synthesis of chemical to allow the design of promising compound.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Computational chemistry; Molecular biology; Structural biology; Target-based systems

Mesh:

Substances:

Year:  2022        PMID: 34888721     DOI: 10.1007/978-1-0716-1767-0_9

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  55 in total

Review 1.  Target-biased scoring approaches and expert systems in structure-based virtual screening.

Authors:  Johanna M Jansen; Eric J Martin
Journal:  Curr Opin Chem Biol       Date:  2004-08       Impact factor: 8.822

Review 2.  Network systems biology for drug discovery.

Authors:  D K Arrell; A Terzic
Journal:  Clin Pharmacol Ther       Date:  2010-06-02       Impact factor: 6.875

Review 3.  Can cell systems biology rescue drug discovery?

Authors:  Eugene C Butcher
Journal:  Nat Rev Drug Discov       Date:  2005-06       Impact factor: 84.694

Review 4.  Drugs for bad bugs: confronting the challenges of antibacterial discovery.

Authors:  David J Payne; Michael N Gwynn; David J Holmes; David L Pompliano
Journal:  Nat Rev Drug Discov       Date:  2006-12-08       Impact factor: 84.694

Review 5.  Model-based drug development.

Authors:  R L Lalonde; K G Kowalski; M M Hutmacher; W Ewy; D J Nichols; P A Milligan; B W Corrigan; P A Lockwood; S A Marshall; L J Benincosa; T G Tensfeldt; K Parivar; M Amantea; P Glue; H Koide; R Miller
Journal:  Clin Pharmacol Ther       Date:  2007-05-23       Impact factor: 6.875

Review 6.  Trends in risks associated with new drug development: success rates for investigational drugs.

Authors:  J A DiMasi; L Feldman; A Seckler; A Wilson
Journal:  Clin Pharmacol Ther       Date:  2010-02-03       Impact factor: 6.875

7.  Target identification using drug affinity responsive target stability (DARTS).

Authors:  Brett Lomenick; Rui Hao; Nao Jonai; Randall M Chin; Mariam Aghajan; Sarah Warburton; Jianing Wang; Raymond P Wu; Fernando Gomez; Joseph A Loo; James A Wohlschlegel; Thomas M Vondriska; Jerry Pelletier; Harvey R Herschman; Jon Clardy; Catherine F Clarke; Jing Huang
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-07       Impact factor: 11.205

8.  An Improved CAD System for Breast Cancer Diagnosis Based on Generalized Pseudo-Zernike Moment and Ada-DEWNN Classifier.

Authors:  Satya P Singh; Shabana Urooj
Journal:  J Med Syst       Date:  2016-02-18       Impact factor: 4.460

Review 9.  Nanotechnology: intelligent design to treat complex disease.

Authors:  Patrick Couvreur; Christine Vauthier
Journal:  Pharm Res       Date:  2006-06-21       Impact factor: 4.580

10.  A perspective on multi-target drug discovery and design for complex diseases.

Authors:  Rona R Ramsay; Marija R Popovic-Nikolic; Katarina Nikolic; Elisa Uliassi; Maria Laura Bolognesi
Journal:  Clin Transl Med       Date:  2018-01-17
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.