Category Archives: Antibodies

Benford’s law and OAS

Benford’s law is an observation that in numerical data (produced by many kinds of process), the leading digit tends to be small. Wikipedia tells you that it in datasets obeying Benford’s law, the number 1 appears as the leading digit about 30% of the time while 9 appears less than 5% of the time (p(n) = log10(1+1/n) where n is the leading digit). Wikipedia further lists multiple kinds of data where this tends to be true such as electricity bills, population numbers and physical and mathematical constants, and particularly where data can be described by a power law.

Power laws and antibodies have been co-discussed in reference to network descriptions of antigen-experienced BCR repertoires [1], which are often described as scale-free to use the network terminology (following a power law). This means a few highly-connected nodes in the network and lots of nodes with few or no connections. This is an obvious candidate for Benford’s law.

This is of no practical relevance, but I wondered if I could see Benford’s law in other kinds of data besides clone counts in the Observed Antibody Space (OAS). For example, I looked at the leading digit in the number of sequences in all of the data units in OAS. It looks like a good fit for Benford’s law (though with more density at the smaller leading digits) and has a chi-squared value of 0.007 (Figure 1A).

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CryoEM is now the dominant technique for solving antibody structures

Last year, the Structural Antibody Database (SAbDab) listed a record-breaking 894 new antibody structures, driven in no small part by the continued efforts of the researchers to understand SARS-CoV-2.

Fig. 1: The aggregate growth in antibody structure data (all methods) over time. Taken from http://opig.stats.ox.ac.uk/webapps/newsabdab/sabdab/stats/ on 25th May 2022.

In this blog post I wanted to highlight the major driving force behind this curve – the huge increase in cryo electron microscopy (cryoEM) data – and the implications of this for the field of structure-based antibody informatics.

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What is a plantibody?

Plants can be genetically engineered to express non-native proteins, for example, crops can be engineered to produce insect toxins in order to improve disease-resistance. However, I was not aware of their ability to express antibodies until, inspired by my expanding collection of house plants, I googled ‘plant immune systems’. 

Plants don’t naturally produce antibodies – they do not possess an adaptive immune system or any circulating immune defence cells. Despite this, plants can be made to express and assemble full length antibody heavy chains and light chains. This was first published back in 1989, when Hiatt et al. [1] successfully introduced mouse immunoglobulin genes to tobacco plants and produced functional antibodies with reasonable efficiency. The excellent term ‘plantibody‘ was coined soon after, to refer to antibodies and fragments of antibodies produced by plants transformed with antibody-coding genes. 

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