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E-raamat: Artificial Intelligence in Drug Design

  • Formaat: PDF+DRM
  • Sari: Methods in Molecular Biology 2390
  • Ilmumisaeg: 03-Nov-2021
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781071617878
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  • Formaat: PDF+DRM
  • Sari: Methods in Molecular Biology 2390
  • Ilmumisaeg: 03-Nov-2021
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781071617878

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This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as:  structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future? Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. 

Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.
Preface v
Contributors ix
1 Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
1(60)
Morgan Thomas
Andrew Boardman
Miguel Garcia-Ortegon
Hongbin Tang
Chris de Graaf
Andreas Bender
2 Machine Learning Applied to the Modeling of Pharmacological and ADMET Endpoints
61(42)
Andreas H. Gbller
Lara Kuhnke
Antonius ter Laak
Katharina Meier
Alexander Hillisch
3 Fighting COVID-19 with Artificial Intelligence
103(10)
Stefania Monteleone
Tahsin F. Kellici
Michelle Southey
Michael J. Bodkin
Alexander Heifetz
4 Application of Artificial Intelligence and Machine Learning in Drug Discovery
113(12)
Rishi R. Gupta
5 Deep Learning and Computational Chemistry
125(28)
Tim James
Dimitar Hristozov
6 Has Artificial Intelligence Impacted Drug Discovery?
153(24)
Atanas Patronov
Kostas Papadopoulos
Ola Engkvist
7 Network-Driven Drug Discovery
177(14)
Jonny Wray
Alan Whitmore
8 Predicting Residence Time of GPCR Ligands with Machine Learning
191(16)
Andrew Potterton
Alexander Heifetz
Andrea Townsend-Nicholson
9 De Novo Molecular Design with Chemical Language Models
207(26)
Francesca Grisoni
Gisbert Schneider
10 Deep Neural Networks for QSAR
233(28)
Tuting Xu
11 Deep Learning in Structure-Based Drug Design
261(12)
Andrew Anighoro
12 Deep Learning Applied to Ligand-Based De Novo Drug Design
273(28)
Ferruccio Palazzesi
Alfonso Pozzan
13 Ultrahigh Throughput Protein-Ligand Docking with Deep Learning
301(20)
Austin Clyde
14 Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors
321(28)
Tania Cava
Carla Vitorino
Mdrcio Ferreira
Sandra Nunes
Paola Rondon-Villarreal
Alberto Pais
15 Artificial Intelligence in Compound Design
349(34)
Christoph Grebner
Hans Matter
Gerhard Hessler
16 Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases
383(26)
Christophe Muller
Obdulia Kabul
Constantino Diaz Gonzalez
17 Artificial Intelligence-Enabled De Novo Design of Novel Compounds that Are Synthesizable
409(12)
Govinda Bhisetti
Cheng Fang
18 Machine Learning from Omics Data
421(12)
Rene Rex
19 Deep Learning in Therapeutic Antibody Development
433(14)
Jeremy M. Shaver
Joshua Smith
Tileli Amimeur
20 Machine Learning for In Silico ADMET Prediction
447(14)
Leijia
Hua Gao
21 Opportunities and Considerations in the Application of Artificial Intelligence to Pharmacokinetic Prediction
461(22)
Matthew R. Wright
22 Artificial Intelligence in Drug Safety and Metabolism
483(20)
Graham F. Smith
23 Molecule Ideation Using Matched Molecular Pairs
503(20)
Sandeep Pal
Peter Pogdny
James Andrew Lumley
Index 523