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Adaptation and Application of Cheminformatics Methods in Toxicity Assessment of Nanomaterials
Published on Nov 17, 2017720 Views
For the last two decades, breakthrough research has been going on in all aspects of materials science, including nanotechnology. New materials of unprecedented functionality and performance are being
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Adaptation and Application of Cheminformatics Methods in Toxicity Assessment of Nanomaterials00:00
North Dakota - 101:35
North Dakota - 202:42
North Dakota - 303:21
North Dakota - 403:35
North Dakota - 504:03
North Dakota - 604:24
North Dakota - 704:33
North Dakota - 804:41
North Dakota - 904:52
North Dakota - 1005:07
North Dakota - 1105:11
North Dakota - 1205:16
North Dakota - 1306:05
North Dakota - 1406:11
North Dakota - 1506:17
North Dakota - 1606:39
North Dakota - 1707:15
Fargo - 107:28
Fargo - 208:03
North Dakota - 1808:24
North Dakota - 1908:45
North Dakota - 2009:01
North Dakota - 2109:03
Department of Coatings and Polymeric Materials - 109:19
Department of Coatings and Polymeric Materials - 211:02
Department of Coatings and Polymeric Materials - 311:15
Department of Coatings and Polymeric Materials - 411:25
Nanomaterials Applications11:38
Nanomaterials in Consumer Products12:09
All nanomaterials are not the same12:33
Same structure – different shapes13:10
The properties can vary with size13:29
Properties of nanoparticles13:57
The importance of characterization14:41
“Orthogonal dimensions” for nanoparticles15:19
Agglomeration and aggregation of nanoparticles16:04
Experimental techniques that can help to get nano-properties16:21
Mass-based “dose” may be inadequate16:39
Effects may be related to surface area based “dose”17:19
Can we predict properties of nanomaterials?18:17
The steps towards modeling of nanoparticles properties and toxicity19:03
Two types of nanomaterials20:09
Combination of computational methods to predict nano-properties20:22
In silico methods20:25
Computational approaches21:33
Quantum Chemistry - 122:00
Quantum Chemistry - 222:03
Gold nanoclusters22:49
Quantum-Mechanical Properties of Metal Oxide clusters - 124:11
Quantum-Mechanical Properties of Metal Oxide clusters - 225:09
Size-Dependence of Quantum-Mechanical Properties25:23
Corwin Hansch - 126:21
Corwin Hansch - 226:53
(Q)SAR - 128:08
(Q)SAR - 228:36
(Q)SAR - 329:19
QSAR – what is this?29:37
QSAR methodology29:50
Types of Molecular Descriptors30:14
Examples of successful QSAR applications in industry30:34
Extending QSAR to nanoparticles31:29
Data for “Classic” QSAR and nano-QSAR32:10
Materials’ descriptors (Nano-descriptors) - 132:34
Materials’ descriptors (Nano-descriptors) - 233:08
Fingerprint descriptors for materials33:40
“Liquid drop” model as a nano-descriptor34:39
Nano-QSAR based on SiRMS descriptors and “liquid drop” nanodescriptor35:54
Toxicity of nanomaterials36:16
An Example of Toxicity Pathway for Nanoparticles - 136:18
An Example of Toxicity Pathway for Nanoparticles - 236:58
Do you know what you're eating? - 137:16
Do you know what you're eating? - 238:08
Donuts38:32
Donuts, Toxicity… and Solar cells - 139:25
Donuts, Toxicity… and Solar cells - 240:06
Donuts, Toxicity… and Solar cells - 340:12
Donuts, Toxicity… and Solar cells - 440:40
Donuts, Toxicity… and Solar cells - 540:56
Nano-QSAR for metal oxide nanoparticles41:30
Main strategy41:34
QSAR model of toxicity towards E.coli bacteria42:31
Final model with only one parameter42:49
Splitting a dataset43:43
Cytotoxicity nano-QSAR model for MeOx nanomaterials43:56
Results – Cytotoxicity trend44:45
The way to cover prediction for cytotoxicity - 144:57
The way to cover prediction for cytotoxicity - 245:41
Carbon nanostructures fullerene C60 and carbon nanotubes46:20
Immunotoxicity of nanoparticles46:27
Pattern Recognition Receptors signaling pathway46:46
Toll-like Receptors: TLR1/TLR247:06
Identification of Hydrophobic Binding Sites47:50
Glide XP docking: TLR1/TLR2 - 148:13
Glide XP docking: TLR1/TLR2 - 248:30
Inhibitors or toxins?48:53
Ligand-Protein Inverse Docking49:21
Overall Schematic Diagram of the Study - 149:25
Overall Schematic Diagram of the Study - 249:56
Binding Score50:04
Top target proteins51:09
Descriptors + Data Mining51:17
Acknowledgements51:45
North Dakota State University52:04
Thanks for your attention!52:22