Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it?
Predicting the structure and thermodynamics of protein–protein interactions (PPIs) are key to
a proper understanding and modulation of their function. Since experimental methods might …
a proper understanding and modulation of their function. Since experimental methods might …
Protein interaction networks revealed by proteome coevolution
Residue-residue coevolution has been observed across a number of protein-protein
interfaces, but the extent of residue coevolution between protein families on the whole …
interfaces, but the extent of residue coevolution between protein families on the whole …
Implications of disease-related mutations at protein–protein interfaces
Protein–protein interfaces have been attracting great attention owing to their critical roles in
protein–protein interactions and the fact that human disease-related mutations are generally …
protein–protein interactions and the fact that human disease-related mutations are generally …
Updates to the integrated protein–protein interaction benchmarks: docking benchmark version 5 and affinity benchmark version 2
We present an updated and integrated version of our widely used protein–protein docking
and binding affinity benchmarks. The benchmarks consist of non-redundant, high-quality …
and binding affinity benchmarks. The benchmarks consist of non-redundant, high-quality …
SKEMPI 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation
J Jankauskaitė, B Jiménez-García, J Dapkūnas… - …, 2019 - academic.oup.com
Motivation Understanding the relationship between the sequence, structure, binding energy,
binding kinetics and binding thermodynamics of protein–protein interactions is crucial to …
binding kinetics and binding thermodynamics of protein–protein interactions is crucial to …
Flex ddG: Rosetta ensemble-based estimation of changes in protein–protein binding affinity upon mutation
Computationally modeling changes in binding free energies upon mutation (interface ΔΔ G)
allows large-scale prediction and perturbation of protein–protein interactions. Additionally …
allows large-scale prediction and perturbation of protein–protein interactions. Additionally …
[HTML][HTML] An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants
Accurate predictive modeling of antibody-antigen complex structures and structure-based
antibody design remain major challenges in computational biology, with implications for …
antibody design remain major challenges in computational biology, with implications for …
[HTML][HTML] Predicting the effect of mutations on protein-protein binding interactions through structure-based interface profiles
JR Brender, Y Zhang - PLoS computational biology, 2015 - journals.plos.org
The formation of protein-protein complexes is essential for proteins to perform their
physiological functions in the cell. Mutations that prevent the proper formation of the correct …
physiological functions in the cell. Mutations that prevent the proper formation of the correct …
Persistent spectral based ensemble learning (PerSpect-EL) for protein–protein binding affinity prediction
Protein–protein interactions (PPIs) play a significant role in nearly all cellular and biological
activities. Data-driven machine learning models have demonstrated great power in PPIs …
activities. Data-driven machine learning models have demonstrated great power in PPIs …
Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2
The association of the receptor binding domain (RBD) of severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 …
coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 …