Literature DB >> 34914045

Artificial Intelligence in Vaccine and Drug Design.

Sunil Thomas1, Ann Abraham2, Jeremy Baldwin3, Sakshi Piplani3,4, Nikolai Petrovsky3,4.   

Abstract

Knowledge in the fields of biochemistry, structural biology, immunological principles, microbiology, and genomics has all increased dramatically in recent years. There has also been tremendous growth in the fields of data science, informatics, and artificial intelligence needed to handle this immense data flow. At the intersection of wet lab and data science is the field of bioinformatics, which seeks to apply computational tools to better understanding of the biological sciences. Like so many other areas of biology, bioinformatics has transformed immunology research leading to the discipline of immunoinformatics. Within this field, many new databases and computational tools have been created that increasingly drive immunology research, in many cases drawing upon artificial intelligence and machine learning to predict complex immune system behaviors, for example, prediction of B cell and T cell epitopes. In this book chapter, we provide an overview of computational tools and artificial intelligence being used for protein modeling, drug screening, vaccine design, and highlight how these tools are being used to transform approaches to pandemic countermeasure development, by reference to the current COVID-19 pandemic.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Artificial intelligence, AI; Artificial neural networks; Deep learning; Machine learning; Vaccine design

Mesh:

Year:  2022        PMID: 34914045     DOI: 10.1007/978-1-0716-1884-4_6

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  31 in total

1.  Quantifying the chemical beauty of drugs.

Authors:  G Richard Bickerton; Gaia V Paolini; Jérémy Besnard; Sorel Muresan; Andrew L Hopkins
Journal:  Nat Chem       Date:  2012-01-24       Impact factor: 24.427

2.  Deep neural nets as a method for quantitative structure-activity relationships.

Authors:  Junshui Ma; Robert P Sheridan; Andy Liaw; George E Dahl; Vladimir Svetnik
Journal:  J Chem Inf Model       Date:  2015-02-17       Impact factor: 4.956

Review 3.  The coming of age of de novo protein design.

Authors:  Po-Ssu Huang; Scott E Boyken; David Baker
Journal:  Nature       Date:  2016-09-15       Impact factor: 49.962

Review 4.  From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

Authors:  Lu Zhang; Jianjun Tan; Dan Han; Hao Zhu
Journal:  Drug Discov Today       Date:  2017-09-04       Impact factor: 7.851

5.  Recurrent Neural Network Model for Constructive Peptide Design.

Authors:  Alex T Müller; Jan A Hiss; Gisbert Schneider
Journal:  J Chem Inf Model       Date:  2018-01-22       Impact factor: 4.956

6.  Improved protein structure prediction using predicted interresidue orientations.

Authors:  Jianyi Yang; Ivan Anishchenko; Hahnbeom Park; Zhenling Peng; Sergey Ovchinnikov; David Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2020-01-02       Impact factor: 11.205

7.  Improved protein structure prediction using potentials from deep learning.

Authors:  Andrew W Senior; Richard Evans; John Jumper; James Kirkpatrick; Laurent Sifre; Tim Green; Chongli Qin; Augustin Žídek; Alexander W R Nelson; Alex Bridgland; Hugo Penedones; Stig Petersen; Karen Simonyan; Steve Crossan; Pushmeet Kohli; David T Jones; David Silver; Koray Kavukcuoglu; Demis Hassabis
Journal:  Nature       Date:  2020-01-15       Impact factor: 49.962

8.  Model-based machine learning.

Authors:  Christopher M Bishop
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2012-12-31       Impact factor: 4.226

Review 9.  Artificial intelligence in drug discovery and development.

Authors:  Debleena Paul; Gaurav Sanap; Snehal Shenoy; Dnyaneshwar Kalyane; Kiran Kalia; Rakesh K Tekade
Journal:  Drug Discov Today       Date:  2020-10-21       Impact factor: 7.851

10.  Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks.

Authors:  Marwin H S Segler; Thierry Kogej; Christian Tyrchan; Mark P Waller
Journal:  ACS Cent Sci       Date:  2017-12-28       Impact factor: 14.553

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  2 in total

1.  Covax-19/Spikogen® vaccine based on recombinant spike protein extracellular domain with Advax-CpG55.2 adjuvant provides single dose protection against SARS-CoV-2 infection in hamsters.

Authors:  Lei Li; Yoshikazu Honda-Okubo; Jeremy Baldwin; Richard Bowen; Helle Bielefeldt-Ohmann; Nikolai Petrovsky
Journal:  Vaccine       Date:  2022-04-18       Impact factor: 4.169

2.  Artificial intelligence-inspired comprehensive framework for Covid-19 outbreak control.

Authors:  Munish Bhatia; Ankush Manocha; Tariq Ahamed Ahanger; Abdullah Alqahtani
Journal:  Artif Intell Med       Date:  2022-03-26       Impact factor: 7.011

  2 in total

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