Protein–Protein Interaction Methods and Protein Phase Separation

Abstract

In the last decade, newly developed experimental methods have made it possible to highlight that macromolecules in the cell milieu physically interact to support physiology. This has shifted the problem of protein–protein interaction from a microscopic, electron-density scale to a mesoscopic one. Further, nowadays there is increasing evidence that proteins in the nucleus and in the cytoplasm can aggregate in membraneless organelles for different physiological reasons. In this scenario, it is urgent to face the problem of biomolecule functional annotation with efficient computational methods, suited to extract knowledge from reliable data and transfer information across different domains of investigation. Here, we revise the present state of the art of our knowledge of protein–protein interaction and the computational methods that differently implement it. Furthermore, we explore experimental and computational features of a set of proteins involved in phase separation.

Highlighting Human Enzymes Active in Different Metabolic Pathways and Diseases: The Case Study of EC 1.2.3.1 and EC 2.3.1.9

“…For the sake of completeness, we computed the likelihood of all the protein variations to affect protein stability (Table S2) and found as expected [2] that variations that are not always diseaserelated are perturbing the protein folding.…”

“…It is common knowledge that enzymes are proteins characterized by specific molecular functions that, when performed in a concerted manner, give rise to the richness of biological processes at the basis of the cell complex physiology [1]. It is still a matter of debate whether different enzyme molecules tend to transiently aggregate in the cell environment, for generating the proper concerted action [2], and references therein. In the case of enzymes, any concerted biological process is modelled by a metabolic network/pathway that describes the biochemical sequential interactions and/or cycles at the basis of the cell metabolism [3].…”

“…Hyphens in table cells refer to lack of information 1. The list of functional activity names corresponding to EC numbers is available inTable S1A 2. Number of metabolic KEGG associated to the EC number and list of corresponding IDs; the list of names of KEGG pathways is available in…”

Solvent Accessibility of Residues Undergoing Pathogenic Variations in Humans: From Protein Structures to Protein Sequences

“…ASA is routinely computed as an absolute value or as Relative Solvent Accessibility (RSA), when the ASA value is divided by the maximum possible solvent accessible surface area of the residue (Tien et al, 2013 ). ASA gained also a pivot role in detecting protein-protein interfaces of molecular complexes in the Protein Data Bank (PDB) [for review see Savojardo et al ( 2020 ), and references therein].…”

Engineering protein fragments via evolutionary and protein–protein interaction algorithms: de novo design of peptide inhibitors for FOF1‐ATP synthase

“…The main approaches used to develop sequence‐based PPI predictors encompass motif/domain‐based searches, global sequence similarity, and codon usage in genes encoding interacting and noninteracting proteins [18]. Comprehensive revisions on this topic, as well as a list of available predictors of PPI sites, have been published by Ding and Kihara [18] and Casadio and colleagues [19]. The main shortcoming faced by sequence‐based PPI predictors has been their poor precision, originated by an overproduction of false‐positive hits [20].…”