Characterizing sequence-structure-function relationships: A multi-dimensional approach for evaluating similarity in structural biology data

Understanding the similarity between the sequence and/or structure of biomolecules has been key to inferring evolutionary relationships and predicting the function of biomolecules. We propose a novel approach for defining and evaluating the similarity between biomolecules. The approach is based on representing structural biology data as a square matrix of biomolecular structure elements and their properties; we then define similarity as the result of comparing the eigenvalues and eigenvector spaces determined for the biomolecules compared. Such a test of statistical similarity is intended to determine whether the compared biomolecules share features of structure, function, biological pathway, or affinity for a certain range of binding partners.
https://www.ceitec.eu/computational-chemistry-jaroslav-koca/rg64/tab?tabId=7

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