We are eye-witnessing tremendous progresses made recently in the understanding of their structure–function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some ...
Protein structure comparison: implications for the nature of 'fold space', and structure and function prediction. Curr. Opin. Struct. Biol. 16, 393–398 (2006). 15. Shindyalov, I. N. & Bourne, P. E. An alternative view of protein fold space. Proteins 38, 247–260 (2000). 16. ...
Prediction of function of proteins on the basis of structure and vice versa is a partially solved problem, largely in the domain of biophysics and biochemistry. This underlies the need of computational and bioinformatics approach to solve the problem. Large and organized latent knowledge on protein ...
Fortunately, with the help of faster X-ray crystallography and NMR in structural biology, there has been an increase in the number of known three-dimensional protein structures. This 3D structure information is a good source of data for the study of protein interfaces. Here, we introduce a ...
All proteins share the same backbone, with their structure and function determined solely by the side chains of the 20 different amino acids. Therefore, a precise modelling of residue-residue and residue-backbone interactions is a crucial aspect in computational evaluation of proteins. Computational me...
Crosslinking and Mass Spectrometry: An Integrated Technology to Understand the Structure and Function of Molecular Machines 2016, Trends in Biochemical Sciences Citation Excerpt : For the same reason, interactions of different copies of the same subunit with different partners cannot yet be deconvoluted;...
Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Thoug
structure, and then construct a sequence of subgraphs, where each subgraph is a subset of the next one. They then define a permutation-invariant descriptor function for each subgraph that is related to curvature. This function is designed to be invariant to the order in which the nodes are ...
Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function paradig
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