The impact of in silico screening in the discovery of novel and safer drug candidates
Publication type: Journal Article
Publication date: 2017-07-01
scimago Q1
wos Q1
SJR: 3.800
CiteScore: 26.2
Impact factor: 12.5
ISSN: 01637258, 1879016X
PubMed ID:
28223231
Pharmacology
Pharmacology (medical)
Abstract
Drug discovery is a multidisciplinary and multivariate optimization endeavor. As such, in silico screening tools have gained considerable importance to archive, analyze and exploit the vast and ever-increasing amount of experimental data generated throughout the process. The current review will focus on the computer-aided prediction of the numerous properties that need to be controlled during the discovery of a preliminary hit and its promotion to a viable clinical candidate. It does not pretend to the almost impossible task of an exhaustive report but will highlight a few key points that need to be collectively addressed both by chemists and biologists to fuel the drug discovery pipeline with innovative and safe drug candidates.
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89
Total citations:
89
Citations from 2025:
3
(3.37%)
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GOST
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Rognan D. The impact of in silico screening in the discovery of novel and safer drug candidates // Pharmacology and Therapeutics. 2017. Vol. 175. pp. 47-66.
GOST all authors (up to 50)
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Rognan D. The impact of in silico screening in the discovery of novel and safer drug candidates // Pharmacology and Therapeutics. 2017. Vol. 175. pp. 47-66.
Cite this
RIS
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TY - JOUR
DO - 10.1016/j.pharmthera.2017.02.034
UR - https://doi.org/10.1016/j.pharmthera.2017.02.034
TI - The impact of in silico screening in the discovery of novel and safer drug candidates
T2 - Pharmacology and Therapeutics
AU - Rognan, Didier
PY - 2017
DA - 2017/07/01
PB - Elsevier
SP - 47-66
VL - 175
PMID - 28223231
SN - 0163-7258
SN - 1879-016X
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2017_Rognan,
author = {Didier Rognan},
title = {The impact of in silico screening in the discovery of novel and safer drug candidates},
journal = {Pharmacology and Therapeutics},
year = {2017},
volume = {175},
publisher = {Elsevier},
month = {jul},
url = {https://doi.org/10.1016/j.pharmthera.2017.02.034},
pages = {47--66},
doi = {10.1016/j.pharmthera.2017.02.034}
}