The Reduced Graph Descriptor in Virtual Screening and Data-Driven Clustering of High-Throughput Screening Data

2004 ◽  
Vol 44 (6) ◽  
pp. 2145-2156 ◽  
Author(s):  
G. Harper ◽  
G. S. Bravi ◽  
S. D. Pickett ◽  
J. Hussain ◽  
D. V. S. Green
Keyword(s):  
Virtual Screening ◽  
High Throughput ◽  
High Throughput Screening ◽  
Data Driven

The Reduced Graph Descriptor in Virtual Screening and Data-Driven Clustering of High-Throughput Screening Data.

ChemInform ◽  
2005 ◽  
Vol 36 (7) ◽  
Author(s):  
G. Harper ◽  
G. S. Bravi ◽  
S. D. Pickett ◽  
J. Hussain ◽  
D. V. S. Green
Keyword(s):  
Virtual Screening ◽  
High Throughput ◽  
High Throughput Screening ◽  
Data Driven

scholarly journals ChemSpaX: Exploration of Chemical Space by Automated Functionalization of Molecular Scaffold

2021 ◽  
Author(s):  
Adarsh Kalikadien ◽  
Evgeny A. Pidko ◽  
Vivek Sinha
Keyword(s):  
Force Field ◽  
High Throughput ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Space Exploration ◽  
Molecular Structures ◽  
Data Driven ◽  
Pincer Complexes ◽  
Cobalt Porphyrin ◽  
Input Structure

<div>Local chemical space exploration of an experimentally synthesized material can be done by making slight structural</div><div>variations of the synthesized material. This generation of many molecular structures with reasonable quality,</div><div>that resemble an existing (chemical) purposeful material, is needed for high-throughput screening purposes in</div><div>material design. Large databases of geometry and chemical properties of transition metal complexes are not</div><div>readily available, although these complexes are widely used in homogeneous catalysis. A Python-based workflow,</div><div>ChemSpaX, that is aimed at automating local chemical space exploration for any type of molecule, is introduced.</div><div>The overall computational workflow of ChemSpaX is explained in more detail. ChemSpaX uses 3D information,</div><div>to place functional groups on an input structure. For example, the input structure can be a catalyst for which one</div><div>wants to use high-throughput screening to investigate if the catalytic activity can be improved. The newly placed</div><div>substituents are optimized using a computationally cheap force-field optimization method. After placement of</div><div>new substituents, higher level optimizations using xTB or DFT instead of force-field optimization are also possible</div><div>in the current workflow. In representative applications of ChemSpaX, it is shown that the structures generated by</div><div>ChemSpaX have a reasonable quality for usage in high-throughput screening applications. Representative applications</div><div>of ChemSpaX are shown by investigating various adducts on functionalized Mn-based pincer complexes,</div><div>hydrogenation of Ru-based pincer complexes, functionalization of cobalt porphyrin complexes and functionalization</div><div>of a bipyridyl functionalized cobalt-porphyrin trapped in a M2L4 type cage complex. Descriptors such as</div><div>the Gibbs free energy of reaction and HOMO-LUMO gap, that can be used in data-driven design and discovery</div><div>of catalysts, were selected and studied in more detail for the selected use cases. The relatively fast GFN2-xTB</div><div>method was used to calculate these descriptors and a comparison was done against DFT calculated descriptors.</div><div>ChemSpaX is open-source and aims to bolster the efforts of the scientific community towards data-driven material</div><div>discovery.</div>

scholarly journals Improved method of structure-based virtual screening based on ensemble learning

RSC Advances ◽  
2020 ◽  
Vol 10 (13) ◽  
pp. 7609-7618
Author(s):  
Jin Li ◽  
WeiChao Liu ◽  
Yongping Song ◽  
JiYi Xia
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Ensemble Learning ◽  
High Throughput ◽  
High Throughput Screening ◽  
Screening Method ◽  
Improved Method ◽  
Complementary Technique

Virtual screening has become a successful alternative and complementary technique to experimental high-throughput screening technologies for drug design. This paper proposed a target-specific virtual screening method based on ensemble learning named ENS-VS.

Virtual screening: a real screening complement to high-throughput screening

2002 ◽  
Vol 30 (4) ◽  
pp. 797-799 ◽  
Author(s):  
J. Mestres
Keyword(s):  
Virtual Screening ◽  
High Throughput ◽  
High Throughput Screening ◽  
Oestrogen Receptor ◽  
Essential Elements ◽  
The Other ◽  
Receptor Subtype ◽  
Other Hand ◽  
Hit Identification

Virtual screening is being routinely used as an integral part of today's hit-identification strategies for, on one hand, prioritizing large corporate screening collections and, on the other hand, to extend the scope of screening to external databases. A brief description of the essential elements required for virtual screening and an application example to the identification of agonist hits for the oestrogen receptor subtype ERα are presented.

scholarly journals ChemSpaX: Exploration of Chemical Space by Automated Functionalization of Molecular Scaffold

2021 ◽  
Author(s):  
Adarsh Kalikadien ◽  
Evgeny A. Pidko ◽  
Vivek Sinha
Keyword(s):  
Force Field ◽  
High Throughput ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Space Exploration ◽  
Molecular Structures ◽  
Data Driven ◽  
Pincer Complexes ◽  
Cobalt Porphyrin ◽  
Input Structure

<div>Local chemical space exploration of an experimentally synthesized material can be done by making slight structural</div><div>variations of the synthesized material. This generation of many molecular structures with reasonable quality,</div><div>that resemble an existing (chemical) purposeful material, is needed for high-throughput screening purposes in</div><div>material design. Large databases of geometry and chemical properties of transition metal complexes are not</div><div>readily available, although these complexes are widely used in homogeneous catalysis. A Python-based workflow,</div><div>ChemSpaX, that is aimed at automating local chemical space exploration for any type of molecule, is introduced.</div><div>The overall computational workflow of ChemSpaX is explained in more detail. ChemSpaX uses 3D information,</div><div>to place functional groups on an input structure. For example, the input structure can be a catalyst for which one</div><div>wants to use high-throughput screening to investigate if the catalytic activity can be improved. The newly placed</div><div>substituents are optimized using a computationally cheap force-field optimization method. After placement of</div><div>new substituents, higher level optimizations using xTB or DFT instead of force-field optimization are also possible</div><div>in the current workflow. In representative applications of ChemSpaX, it is shown that the structures generated by</div><div>ChemSpaX have a reasonable quality for usage in high-throughput screening applications. Representative applications</div><div>of ChemSpaX are shown by investigating various adducts on functionalized Mn-based pincer complexes,</div><div>hydrogenation of Ru-based pincer complexes, functionalization of cobalt porphyrin complexes and functionalization</div><div>of a bipyridyl functionalized cobalt-porphyrin trapped in a M2L4 type cage complex. Descriptors such as</div><div>the Gibbs free energy of reaction and HOMO-LUMO gap, that can be used in data-driven design and discovery</div><div>of catalysts, were selected and studied in more detail for the selected use cases. The relatively fast GFN2-xTB</div><div>method was used to calculate these descriptors and a comparison was done against DFT calculated descriptors.</div><div>ChemSpaX is open-source and aims to bolster the efforts of the scientific community towards data-driven material</div><div>discovery.</div>

scholarly journals ChemSpaX: Exploration of Chemical Space by Automated Functionalization of Molecular Scaffold

2021 ◽  
Author(s):  
Adarsh Kalikadien ◽  
Evgeny A. Pidko ◽  
Vivek Sinha
Keyword(s):  
Force Field ◽  
High Throughput ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Space Exploration ◽  
Molecular Structures ◽  
Data Driven ◽  
Pincer Complexes ◽  
Cobalt Porphyrin ◽  
Input Structure

<div>Local chemical space exploration of an experimentally synthesized material can be done by making slight structural</div><div>variations of the synthesized material. This generation of many molecular structures with reasonable quality,</div><div>that resemble an existing (chemical) purposeful material, is needed for high-throughput screening purposes in</div><div>material design. Large databases of geometry and chemical properties of transition metal complexes are not</div><div>readily available, although these complexes are widely used in homogeneous catalysis. A Python-based workflow,</div><div>ChemSpaX, that is aimed at automating local chemical space exploration for any type of molecule, is introduced.</div><div>The overall computational workflow of ChemSpaX is explained in more detail. ChemSpaX uses 3D information,</div><div>to place functional groups on an input structure. For example, the input structure can be a catalyst for which one</div><div>wants to use high-throughput screening to investigate if the catalytic activity can be improved. The newly placed</div><div>substituents are optimized using a computationally cheap force-field optimization method. After placement of</div><div>new substituents, higher level optimizations using xTB or DFT instead of force-field optimization are also possible</div><div>in the current workflow. In representative applications of ChemSpaX, it is shown that the structures generated by</div><div>ChemSpaX have a reasonable quality for usage in high-throughput screening applications. Representative applications</div><div>of ChemSpaX are shown by investigating various adducts on functionalized Mn-based pincer complexes,</div><div>hydrogenation of Ru-based pincer complexes, functionalization of cobalt porphyrin complexes and functionalization</div><div>of a bipyridyl functionalized cobalt-porphyrin trapped in a M2L4 type cage complex. Descriptors such as</div><div>the Gibbs free energy of reaction and HOMO-LUMO gap, that can be used in data-driven design and discovery</div><div>of catalysts, were selected and studied in more detail for the selected use cases. The relatively fast GFN2-xTB</div><div>method was used to calculate these descriptors and a comparison was done against DFT calculated descriptors.</div><div>ChemSpaX is open-source and aims to bolster the efforts of the scientific community towards data-driven material</div><div>discovery.</div>

Integration of virtual screening with high-throughput screening for the identification of novel Rho-kinase I inhibitors

2010 ◽  
Vol 145 (3) ◽  
pp. 295-303 ◽  
Author(s):  
Li-Li Gong ◽  
Lian-Hua Fang ◽  
Jian-Hao Peng ◽  
Ai-Lin Liu ◽  
Guan-Hua Du
Keyword(s):  
Virtual Screening ◽  
High Throughput ◽  
High Throughput Screening ◽  
Rho Kinase

scholarly journals Data-Driven Derivation of an “Informer Compound Set” for Improved Selection of Active Compounds in High-Throughput Screening

2016 ◽  
Vol 56 (9) ◽  
pp. 1622-1630 ◽  
Author(s):  
Shardul Paricharak ◽  
Adriaan P. IJzerman ◽  
Jeremy L. Jenkins ◽  
Andreas Bender ◽  
Florian Nigsch
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Data Driven ◽  
Active Compounds ◽  
Selection Of
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