Recent advances in mass spectrometry (MS)-based proteomics have enabled tremendous progress in the understanding of cellular mechanisms, disease progression, and the relationship between genotype and phenotype. Though many popular bioinformatics methods in proteomics are derived from other omics studies, novel analysis strategies are required to deal with the unique characteristics of proteomics data. In this review, we discuss the current developments in the bioinformatics methods used in proteomics and how they facilitate the mechanistic understanding of biological processes. We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods that have been developed to perform comprehensive analysis in proteomics studies. We conclude with a discussion of how quantitative protein data can be used to reconstruct protein interactions and signaling networks.

New drug production, from target identification to marketing approval, takes over 12 years and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the urgent need for more powerful computational methods for drug discovery. Here, we review the computational approaches to predicting protein–ligand interactions in the context of drug discovery, focusing on methods using artificial intelligence (AI). We begin with a brief introduction to proteins (targets), ligands (e.g. drugs) and their interactions for nonexperts. Next, we review databases that are commonly used in the domain of protein–ligand interactions. Finally, we survey and analyze the machine learning (ML) approaches implemented to predict protein–ligand binding sites, ligand-binding affinity and binding pose (conformation) including both classical ML algorithms and recent deep learning methods. After exploring the correlation between these three aspects of protein–ligand interaction, it has been proposed that they should be studied in unison. We anticipate that our review will aid exploration and development of more accurate ML-based prediction strategies for studying protein–ligand interactions.

Retroviral capsids in their native form: Capsid proteins of retroviruses form protective lattices around viral RNA molecules. The precise molecular details of how individual, full-length capsid proteins assemble to shield the viral genome; however, are not well understood. Obal et al. and Gres et al. now report high resolution crystal structures of the full length capsid proteins from Bovine Leukemia Virus and HIV-1, respectively. The two studies complement each other to reveal the dynamic nature of capsid protein assembly and of how individual capsid proteins interact in the lattice. The findings may have relevance for drug design. Science , this issue p. 95 ; see also p. 99

Protein tyrosine phosphatases (PTPs) are important targets of the H ₂ O ₂ that is produced during mammalian signal transduction. H ₂ O ₂ -mediated inactivation of PTPs also may be important in various pathophysiological conditions involving oxidative stress. Here we review the chemical and structural biology of redox-regulated PTPs. Reactions of H ₂ O ₂ with PTPs convert the catalytic cysteine thiol to a sulfenic acid. In PTPs, the initially generated sulfenic acid residues have the potential to undergo secondary reactions with a neighboring amide nitrogen or cysteine thiol residue to yield a sulfenyl amide or disulfide, respectively. The chemical mechanisms by which formation of sulfenyl amide and disulfide linkages can protect the catalytic cysteine residue against irreversible overoxidation to sulfinic and sulfonic oxidation states are described. Due to the propensity for back-door and distal cysteine residues to engage with the active-site cysteine after oxidative inactivation, differences in the structures of the oxidatively inactivated PTPs may stem, to a large degree, from differences in the number and location of cysteine residues surrounding the active site of the enzymes. PTPs with key cysteine residues in structurally similar locations may be expected to share similar mechanisms of oxidative inactivation. Antioxid. Redox Signal. 15, 77–97.