Virtual screening methods as tools for drug lead discovery from large chemical libraries

X. H. Ma; F. Zhu; X. Liu; Z. Shi; J. X. Zhang; S. Y. Yang; Y. Q. Wei; Y. Z. Chen

doi:10.2174/092986712803833245

Virtual screening methods as tools for drug lead discovery from large chemical libraries

X. H. Ma, F. Zhu, X. Liu, Z. Shi, J. X. Zhang, S. Y. Yang, Y. Q. Wei, Y. Z. Chen^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

26 Citations (Scopus)

Abstract

Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ∼ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.

Original language	English
Pages (from-to)	5562-5571
Number of pages	10
Journal	Current Medicinal Chemistry
Volume	19
Issue number	32
DOIs	https://doi.org/10.2174/092986712803833245
Publication status	Published - Nov 2012
Externally published	Yes

Keywords

Machine learning
Molecular docking
Pharmacophore
Quantitative structure activity relationship
Similarity searching
Support vector machines

Access to Document

10.2174/092986712803833245

Cite this

@article{fbd14f4ce1244fd0a229b87537b78b15,

title = "Virtual screening methods as tools for drug lead discovery from large chemical libraries",

abstract = "Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ∼ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.",

keywords = "Machine learning, Molecular docking, Pharmacophore, Quantitative structure activity relationship, Similarity searching, Support vector machines",

author = "Ma, {X. H.} and F. Zhu and X. Liu and Z. Shi and Zhang, {J. X.} and Yang, {S. Y.} and Wei, {Y. Q.} and Chen, {Y. Z.}",

year = "2012",

month = nov,

doi = "10.2174/092986712803833245",

language = "English",

volume = "19",

pages = "5562--5571",

journal = "Current Medicinal Chemistry",

issn = "0929-8673",

number = "32",

}

TY - JOUR

T1 - Virtual screening methods as tools for drug lead discovery from large chemical libraries

AU - Ma, X. H.

AU - Zhu, F.

AU - Liu, X.

AU - Shi, Z.

AU - Zhang, J. X.

AU - Yang, S. Y.

AU - Wei, Y. Q.

AU - Chen, Y. Z.

PY - 2012/11

Y1 - 2012/11

N2 - Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ∼ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.

AB - Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ∼ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.

KW - Machine learning

KW - Molecular docking

KW - Pharmacophore

KW - Quantitative structure activity relationship

KW - Similarity searching

KW - Support vector machines

UR - http://www.scopus.com/inward/record.url?scp=84870443681&partnerID=8YFLogxK

U2 - 10.2174/092986712803833245

DO - 10.2174/092986712803833245

M3 - Article

C2 - 23016548

AN - SCOPUS:84870443681

SN - 0929-8673

VL - 19

SP - 5562

EP - 5571

JO - Current Medicinal Chemistry

JF - Current Medicinal Chemistry

IS - 32

ER -

Virtual screening methods as tools for drug lead discovery from large chemical libraries

Abstract

Keywords

Access to Document

Other files and links

Cite this