SPACE peptide

Rapid advancements in genomics have brought a better understanding of molecular mechanisms for various pathologies and identified a number of highly attractive target classes. Some of these targets include intracellular protein-protein interactions (PPIs), which control many essential biological pathways. Their surfaces are part of a diverse and unexplored biological space, where traditional small molecule scaffolds are not always successful. While large biologics can effectively modulate PPIs in the extracellular region, their limitation in crossing the cellular membrane leaves intracellular protein targets outside of their reach. There is a growing need in the pharmaceutical field to push the boundaries of traditional drug design and discover innovative molecules that are able to modulate key biological pathways by inhibiting intracellular PPIs. Peptides are one of the most promising classes of molecules that could deliver such therapeutics in the near future. In this review, we describe technological advancements and emerging chemical approaches for stabilizing active peptide conformations, including stapling, hydrogen bond surrogates, beta-hairpin mimetics, grafting on stable scaffolds, and macrocyclization. These design strategies carry the promise of opening the doors for peptide therapeutics to reach the currently "undruggable" space.

Molecular self-assembly is a ubiquitous process in nature and central to bottom-up nanotechnology. In particular, the organization of peptide building blocks into ordered supramolecular structures has gained much interest due to the unique properties of the products, including biocompatibility, chemical and structural diversity, robustness and ease of large-scale synthesis. In addition, peptides, as short as dipeptides, contain all the molecular information needed to spontaneously form well-ordered structures at both the nano- and the micro-scale. Therefore, peptide supramolecular assembly has been effectively utilized to produce novel materials with tailored properties for various applications in the fields of material science, engineering, medicine, and biology. To further expand the conformational space of peptide assemblies in terms of structural and functional complexity, multicomponent (two or more) peptide supramolecular co-assembly has recently evolved as a promising extended approach, similar to the structural diversity of natural sequence-defined biopolymers (proteins) as well as of synthetic covalent co-polymers. The use of this methodology was recently demonstrated in various applications, such as nanostructure physical dimension control, the creation of non-canonical complex topologies, mechanical strength modulation, the design of light harvesting soft materials, fabrication of electrically conducting devices, induced fluorescence, enzymatic catalysis and tissue engineering. In light of these significant advancements in the field of peptide supramolecular co-assembly in the last few years, in this tutorial review, we provide an updated overview and future prospects of this emerging subject.

Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.