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

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.

Structurally Observed Electrostatic Features of the COVID-19 Coronavirus-Related Experimental Structures inside Protein Data Bank: A Brief Update

“…For the first time, this article reports a comprehensive set of electrostatic features sucked out of the currently (as of March 4, 2020) available COVID-19 coronavirus-related structures inside PDB [9] in both PDF format (supplementary file supplementary.pdf) and also L A T E X format, i.e., a series of machine-readable -importable and -analyzable .tex files zipped in the supplementary file scan.zip. In supplementary file scan.zip, a simple python-based analysis tool and a L A T E X-based editing tool [11] were included to extract and summarize the electrostatic features from experimentally determined structures, where a set of PDB files (representing experimentally determined protein structures) are to be plugged into a set of python scripts included in cmd.py. Afterwards, cmd.py is to be executed with a simple command (python cmd.py) on a Linux machine terminal to produce the final supplementary file supplementary.pdf, summarizing the structurally observed electrostatic features of the four COVID-19 coronavirus-related experimental structures as of March 4, 2020.…”

“…Finally, along with the python-based analysis tool and a L A T E X-based editing tool [11], the structurally observed electrostatic features of the four COVID-19 coronavirus-related experimental structures constitute a preliminary starting point pointing towards a clear, coherent and comprehensive map of COVID-19's structure and function and also machine-learning and structure-based computational design of neutralizing antibodies [11] and/or small molecule(s) as potential therapeutic candidates against future outbreaks of the COVID-19 coronavirus diseases.…”

Two Achilles' Heels of the Ebolavirus Glycoprotein?

“…For the first time, this article reports a comprehensive set of electrostatic features embedded inside currently (as of March 10, 2020) available Ebolavirus GP structures inside PDB [128] in both PDF format (supplementary file supplementary.pdf) and also L A T E X format, i.e., a series of machine-readable -importable and -analyzable .tex files zipped in the supplementary file scan.zip. In supplementary file scan.zip, a simple python-based analysis tool and a L A T E X-based editing tool [143] were included to extract and summarize the electrostatic features from experimentally determined structures, where a set of PDB files (representing experimentally determined protein structures) are to be plugged into a set of python scripts included in cmd.py. Afterwards, cmd.py is to be executed with a simple command (python cmd.py) on a Linux machine terminal to produce the final supplementary file supplementary.pdf, summarizing the structurally observed electrostatic features of the 36 Ebolavirus GP-related experimental structures as of March 10, 2020.…”

Towards a General Intermolecular Binding Affinity Calculator

“…Take Prodigy [2,34] for instance, protein-protein or protein-ligand K d is calculated using the binary interfacial features, i.e., interfacial contacts between the two interacting partners (Equation 2), including interstructural hydrogen bonding, electrostatics, hydrophobics and Van der Waals forces between the two binding molecules [5,6,35,36]. A flow chart of experimental (wet-lab approach) determination and computational (dry-lab approach) prediction of K d (Equation 2).…”