PPI-Hotspot^DB: Database of Protein–Protein Interaction Hot Spots

Abstract

Single-point mutations of certain residues (so-called hot spots) impair/disrupt protein−protein interactions (PPIs), leading to pathogenesis and drug resistance. Conventionally, a PPIhot spot is identified when its replacement decreased the binding free energy significantly, generally by ≥2 kcal/mol. The relatively few mutations with such a significant binding free energy drop limited the number of distinct PPI-hot spots. By defining PPI-hot spots based on mutations that have been manually curated in UniProtKB to significantly impair/disrupt PPIs in addition to binding free energy changes, we have greatly expanded the number of distinct PPI-hot spots by an order of magnitude. These experimentally determined PPI-hot spots along with available structures have been collected in a database called PPI-Hotspot DB . We have applied the PPI-Hotspot DB to create a nonredundant benchmark, PPI-Hotspot+PDB BM , for assessing methods to predict PPI-hot spots using the free structure as input. PPI-Hotspot DB will benefit the design of mutagenesis experiments and development of PPI-hot spot prediction methods. The database and benchmark are freely available at https://ppihotspot.limlab.dnsalias.org.

Exploring the pharmacological mechanism of Duhuo Jisheng Decoction in treating intervertebral disc degeneration based on network pharmacology

“…The collected set of intersecting genes in the current study was subjected to protein-protein interaction (PPI) network analysis utilizing the string database (http://string-db.org/), which was confined to “Homo sapiens” and had confidence values > 0.4. [28] Cytoscape 3.9.1 software was used to create the PPI network. Additionally, the top 10 nodes were chosen to locate hub genes using the CytoHubba algorithm (Density of Maximum Neighborhood Component, Maximum Neighborhood Component, Edge Percolated Component, Closeness, Betweenness, ClusteringCoefficient, EcCentricity, Radiality, Stress, BottleNeck, Degree, Maximal Clique Centrality), a Cytoscape plug-in.…”

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence

“…Given the fact that a disease can initiate or progress if some protein interaction goes bad, drug discovery starts with the identification of such protein interaction sites: specifically, a small group of amino acids at the protein interfaces, known as the hot spot residues. , Following that, the identification of small molecule(s) that alter protein–protein interactions through their binding with the protein interaction site has significant therapeutic effects. Current research indicates that hot spots are specific targets for druglike small molecules in protein–protein interfaces .…”

“…Not all residues at protein–protein interactions contribute equally to the binding energy. Hot spot residues contribute mostly toward the protein–protein binding affinity and constitute less than 50% of the total interacting surfaces but undertake a significant amount of total binding energy. , To identify them, alanine scanning mutagenesis experiments can be used to observe binding free energy changes (ΔΔ G ). These experiments on the whole protein interactome are difficult.…”

COVID-19 and Osteoporosis: Shared Mechanisms and Crosstalk via Vitamin D

“…The relevant feature data were recorded for subsequent analysis. After the completion of the DTD network construction, the analysis les were downloaded and imported into Cytoscape 3.7.2 software 22 , and the core targets of VitD in the treatment of osteoporosis and COVID-19 were obtained by screening according to set the value of twice the nodal degree (degree ≥ 10.2) 25 .…”