Preprint Dataset Version 1 Preserved in Portico This version is not peer-reviewed

Extracting the Interfacial Electrostatic Features from Experimentally Determined Antigen and/or Antibody-Related Structures inside Protein Data Bank for Machine Learning-Based Antibody Design

Wei Li * ORCID logo
Version 1 : Received: 29 February 2020 / Approved: 1 March 2020 / Online: 1 March 2020 (12:39:55 CET)

How to cite: Li, W. Extracting the Interfacial Electrostatic Features from Experimentally Determined Antigen and/or Antibody-Related Structures inside Protein Data Bank for Machine Learning-Based Antibody Design. Preprints 2020, 2020030011 (doi: 10.20944/preprints202003.0011.v1). Li, W. Extracting the Interfacial Electrostatic Features from Experimentally Determined Antigen and/or Antibody-Related Structures inside Protein Data Bank for Machine Learning-Based Antibody Design. Preprints 2020, 2020030011 (doi: 10.20944/preprints202003.0011.v1).

Abstract

The importance of antibodies in health care and the biotechnology research and development demands not only knowledge of their experimental structures at high resolution, but also practical implementation of this knowledge for both effective and efficient design and production of antibody for its use in both medical and research applications. While the experimental wet-lab approach is usually costly, laborious and time-consuming, computational (dry-lab) approaches, in spite of their intrinsic limitations in comparison with its experimental (wet-lab) counterpart, provide a cheaper and faster alternative option. For the first time, this article reports a comprehensive set of structural electrostatic features extracted from experimentally determined antigen-antibody-related structures, including especially those structural electrostatic features at the interfaces of all experimentally determined antigen-antibody complex structures as of February 29, 2020, to facilitate effective and efficient machine learning-based computational antibody design using currently available experimental structures inside Protein Data Bank.

Subject Areas

antigen-antibody complex structure; interfacial electrostatic feature; Machine Learning-Based Antibody Design; Protein Data Bank

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