Computational prediction of protein–protein binding affinities

T Siebenmorgen, M Zacharias - Wiley Interdisciplinary Reviews …, 2020 - Wiley Online Library
Protein–protein interactions form central elements of almost all cellular processes.
Knowledge of the structure of protein–protein complexes but also of the binding affinity is of …

The pathobiology of perturbed mutant huntingtin protein–protein interactions in Huntington's disease

EE Wanker, A Ast, F Schindler, P Trepte… - Journal of …, 2019 - Wiley Online Library
Mutations are at the root of many human diseases. Still, we largely do not exactly
understand how they trigger pathogenesis. One, more recent, hypothesis has been that they …

DeepRank: a deep learning framework for data mining 3D protein-protein interfaces

N Renaud, C Geng, S Georgievska… - Nature …, 2021 - nature.com
Abstract Three-dimensional (3D) structures of protein complexes provide fundamental
information to decipher biological processes at the molecular scale. The vast amount of …

Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it?

C Geng, LC Xue, J Roel‐Touris… - Wiley Interdisciplinary …, 2019 - Wiley Online Library
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 …

Spatial organization of hydrophobic and charged residues affects protein thermal stability and binding affinity

F Desantis, M Miotto, L Di Rienzo, E Milanetti… - Scientific Reports, 2022 - nature.com
What are the molecular determinants of protein–protein binding affinity and whether they are
similar to those regulating fold stability are two major questions of molecular biology, whose …

Clustering heterogeneous conformational ensembles of intrinsically disordered proteins with t-distributed stochastic neighbor embedding

R Appadurai, JK Koneru, M Bonomi… - Journal of Chemical …, 2023 - ACS Publications
Intrinsically disordered proteins (IDPs) populate a range of conformations that are best
described by a heterogeneous ensemble. Grouping an IDP ensemble into “structurally …

CSatDTA: Prediction of Drug–Target Binding Affinity Using Convolution Model with Self-Attention

A Ghimire, H Tayara, Z Xuan, KT Chong - International journal of …, 2022 - mdpi.com
Drug discovery, which aids to identify potential novel treatments, entails a broad range of
fields of science, including chemistry, pharmacology, and biology. In the early stages of drug …

Supervised machine learning methods applied to predict ligand-binding affinity

GS Heck, VO Pintro, RR Pereira… - Current medicinal …, 2017 - ingentaconnect.com
Background: Calculation of ligand-binding affinity is an open problem in computational
medicinal chemistry. The ability to computationally predict affinities has a beneficial impact …

Recent advances in metal-organic frameworks for separation and enrichment in proteomics analysis

Q Liu, N Sun, C Deng - TrAC Trends in Analytical Chemistry, 2019 - Elsevier
Metal-organic frameworks (MOFs) have been broadly applied to sample preparation which
is an essential step in proteomics research. Their large surface area provides abundant …

Fast prediction of binding affinities of the SARS-CoV-2 spike protein mutant N501Y (UK variant) with ACE2 and miniprotein drug candidates

AH Williams, CG Zhan - The Journal of Physical Chemistry B, 2021 - ACS Publications
A recently identified variant of SARS-CoV-2 virus, known as the United Kingdom (UK)
variant (lineage B. 1.1. 7), has an N501Y mutation on its spike protein. SARS-CoV-2 spike …