Structure-based virtual screening: an overview

Lyne, Paul

doi:10.1016/s1359-6446(02)02483-2

“…Thus, despite the potential loss of discrimination, scores are frequently converted to ranks prior to fusion. Similar comments apply to consensus scoring, where the identification of accurate scoring functions continues to be problematic [6][7][8].…”

Section: For Each Of the Scoring Functions Imentioning

confidence: 83%

Enhancing the Effectiveness of Ligand‐Based Virtual Screening Using Data Fusion

Willett

¹

2006

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Data fusion is being increasingly used to combine the outputs of different types of sensor. This paper reviews the application of the approach to ligand-based virtual screening, where the sensors to be combined are functions that score molecules in a database on their likelihood of exhibiting some required biological activity. Much of the literature to date involves the combination of multiple similarity searches, although there is also increasing interest in the combination of multiple machine learning techniques. Both approaches are reviewed here, focusing on the extent to which fusion can improve the effectiveness of searching when compared with a single screening mechanism, and on the reasons that have been suggested for the observed performance enhancement.

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“…Virtual screening of molecular compound libraries has recently emerged as a powerful method for drug discovery [12,13]. Based on the crystal structure of the target protein and highthroughput molecular docking using compound database, virtual screening allows for scanning a large number of compounds with reasonable accuracy and speed.…”

Section: Ligand Identification For Orphan Nuclear Receptorsmentioning

confidence: 99%

Orphan nuclear receptors in drug discovery

Shi

¹

2007

Drug Discovery Today

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SummaryOrphan nuclear receptors provide a unique resource for uncovering novel regulatory systems that impact human health and provide excellent drug targets for a variety of human diseases. Ligands of nuclear receptors have been used in a number of important therapeutic areas, such as breast cancers, skin disorders, and diabetes. Orphan nuclear receptors, therefore, represent a tremendous opportunity in understanding and treating human diseases. This review highlights advances and potentials of using orphan nuclear receptors, in particular PPARs, Nurr1, RORs, and TLX as targets for drug discovery in diabetes and obesity, neurodegenerative diseases, and other related disorders.

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“…Structure-based virtual screening using proteinligand docking is the method of choice when the 3D structure of the biological target is available from X-ray or NMR studies [6][7][8]. Ligand-based virtual screening is appropriate when there is information relating to known (or predicted) ligands; examples of this approach are machine learning methods, in which a classification rule is developed from a training-set containing known active and known inactive molecules [9][10][11], and similarity methods, in which molecules are ranked in order of decreasing similarity to a known active (or actives) [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Effectiveness of Ligand‐Based Virtual Screening Using Data Fusion

Willett

¹

2007

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Data fusion is being increasingly used to combine the outputs of different types of sensor. This paper reviews the application of the approach to ligand-based virtual screening, where the sensors to be combined are functions that score molecules in a database on their likelihood of exhibiting some required biological activity. Much of the literature to date involves the combination of multiple similarity searches, although there is also increasing interest in the combination of multiple machine learning techniques. Both approaches are reviewed here, focusing on the extent to which fusion can improve the effectiveness of searching when compared with a single screening mechanism, and on the reasons that have been suggested for the observed performance enhancement.

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Structure-based virtual screening: an overview

Cited by 588 publications

References 73 publications

Enhancing the Effectiveness of Ligand‐Based Virtual Screening Using Data Fusion

Enhancing the Effectiveness of Ligand‐Based Virtual Screening Using Data Fusion

Orphan nuclear receptors in drug discovery

Enhancing the Effectiveness of Ligand‐Based Virtual Screening Using Data Fusion

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