Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II

Targeting peptide-mediated interactions in omics

Peptide-mediated interactions (PMIs) play a crucial role in cell signaling network, which are responsible for about half of cellular protein-protein associations in the human interactome and have recently been recognized as a new kind of promising druggable target for drug development and disease therapy. In this article, we give a systematic review regarding the proteome-wide discovery of PMIs and targeting druggable PMIs (dPMIs) with chemical drugs, self-inhibitory peptides (SIPs) and protein agents, particularly focusing on their implications and applications for therapeutic purpose in omics. We also introduce computational peptidology strategies used to model, analyze, and design PMI-targeted molecular entities and further extend the concepts of protein context, direct/indirect readout, and enthalpy/entropy effect involved in PMIs. Current issues and future perspective on this topic are discussed. There is still a long way to go before establishment of efficient therapeutic strategies to target PMIs on the omics scale.

Structural Mapping of BMP Conformational Epitopes and Bioengineering Design of Osteogenic Peptides to Specifically Target the Epitope-Binding Sites

Introduction

Human bone morphogenetic proteins (BMPs) constitute a large family of cytokines related to members of the transforming growth factor-β superfamily, which fulfill biological functions by specificity binding to their cognate type I (BRI) and type II (BRII) receptors through conformational wrist and linear knuckle epitopes, respectively.

Methods and Results

We systematically examined the intermolecular recognition and interaction between the BMP proteins and BRI receptor at structural, energetic and dynamic levels. The BRI-binding site consists of three hotspot regions on BMP surface, which totally contribute ~70% potency to the BMP-BRI binding events and represent the core sections of BMP conformational wrist epitope; the contribution increases in the order: hotspot 2 (~ 8%) < hotspot 3 (~ 20%) < hotspot 1 (~ 40%). Multiple sequence alignment and structural superposition revealed a consensus sequence pattern and a similar binding mode of the three hotspots shared by most BMP members, indicating a high conservation of wrist epitope in BMP family. The three hotspots are natively folded into wellstructured U-shaped,, loop and double-stranded conformations in BMP proteins, which, however, would become largely disordered when splitting from the protein context to derive osteogenic peptides in free state, thus largely impairing their rebinding capability to BRI receptor. In this respect, cyclization strategy was employed to constrain hotspot 1/3-derived peptides into a native-like conformation, which was conducted by adding a disulfide bond across the ending arms of linear peptides based on their native conformations. Fluorescence-based assays substantiated that the cyclization can effectively improve the binding affinities of osteogenic peptides to BRI receptor by 3-6-fold. The cyclic peptides also exhibit a good selectivity for BRI over BRII (> 5-fold), confirming that they can specifically target the wrist epitope-binding site of BRI receptor.

Conclusion

The rationally designed cyclic peptides can be regarded as the promising lead entities that should be further chemically modified to enhance their in vivo biological stability for further bioengineering therapeutic osteogenic peptides against chondrocyte senescence and bone disorder.

Quantitative structure-activity relationship modeling reveals the minimal sequence requirement and amino acid preference of sirtuin-1's deacetylation substrates in diabetes mellitus

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide (NAD[Formula: see text]-dependent deacetylase involved in multiple glucose metabolism pathways and plays an important role in the pathogenesis of diabetes mellitus (DM). The enzyme specifically recognizes its deacetylation substrates' peptide segments containing a central acetyl-lysine residue as well as a number of amino acids flanking the central residue. In this study, we attempted to ascertain the minimal sequence requirement (MSR) around the central acetyl-lysine residue of SIRT1 substrate-recognition sites as well as the amino acid preference (AAP) at different residues of the MSR window through quantitative structure-activity relationship (QSAR) strategy, which would benefit our understanding of SIRT1 substrate specificity at the molecular level and is also helpful to rationally design substrate-mimicking peptidic agents against DM by competitively targeting SIRT1 active site. In this procedure, a large-scale dataset containing 6801 13-mer acetyl-lysine peptides (and their SIRT1-catalyized deacetylation activities) were compiled to train 10 QSAR regression models developed by systematic combination of machine learning methods (PLS and SVM) and five amino acids descriptors (DPPS, T-scale, MolSurf, [Formula: see text]-score, and FASGAI). The two best QSAR models (PLS+FASGAI and SVM+DPPS) were then employed to statistically examine the contribution of residue positions to the deacetylation activity of acetyl-lysine peptide substrates, revealing that the MSR can be represented by 5-mer acetyl-lysine peptides that meet a consensus motif X[Formula: see text]X[Formula: see text]X[Formula: see text](AcK)₀X[Formula: see text]. Structural analysis found that the X[Formula: see text] and (AcK)₀ residues are tightly packed against the enzyme active site and confer both stability and specificity for the enzyme-substrate complex, whereas the X[Formula: see text], X[Formula: see text] and X[Formula: see text] residues are partially exposed to solvent but can also effectively stabilize the complex system. Subsequently, a systematic deacetylation activity change profile (SDACP) was created based on QSAR modeling, from which the AAP for each residue position of MSR was depicted. With the profile, we were able to rationally design an SDACP combinatorial library with promising deacetylation activity, from which nine MSR acetyl-lysine peptides as well as two known SIRT1 acetyl-lysine peptide substrates were tested by using SIRT1 deacetylation assay. It is revealed that the designed peptides exhibit a comparable or even higher activity than the controls, although the former is considerably shorter than the latter.

Structural definition of the discrete hotspot sites of BMP-2 conformational wrist epitope and rational design of the hotspot-derived osteogenic peptides against chondrocyte senescence

The bone morphogenetic protein-2 (BMP-2) is an essential regulator of bone formation and remodeling, which has also been implicated in the pathogenesis of osteoarthritis and its closely related chondrocyte senescence. The BMP-2 uses a conformational wrist epitope and a linear knuckle epitope to interact with type-I (BMPR-I) and type-II (BMPR-II) receptors, respectively. Previously, the knuckle epitope has been intensely studied, but the wrist epitope still remains largely unexplored due to its discontinuous nature. In the present work, the intermolecular interaction of BMP-2 with BMPR-I was investigated systematically at structural, energetic and dynamic levels. Three discrete hotspots that represent the key BMPR-I recognition sites of BMP-2 were identified; they are spatially dispersed over the two monomers of BMP-2 dimer and totally account for 83.5 % binding potency of BMP-2 to BMPR-I (hotspot 1: residues 49-70 in monomer 1; hotspot 2: residues 24-31 in monomer 2; hotspot 3: residues 88-107 in monomer 2). Therefore, we defined the three discrete hotspot sites as the core region of wrist epitope; their contribution to the binding increases in the order: hotspot 2 < hotspot 3 < hotspot 1. We demonstrated that the primary hotspot 1 site has a native U-shaped conformation in the full-length BMP-2 protein context, but it cannot maintain in the native conformation when split from the context to obtain a free hotspot-1 peptide, thus largely impairing its binding potency to BMPR-I. We further employed disulfide-bonded cyclization and head-to-tail cyclization to constrain the peptide conformation, and found that only the former can effectively constrain the peptide into native conformation, thus considerably improving its binding affinity to BMPR-I, whereas the latter totally disorders the native conformation, thus rendering the peptide as a full nonbinder of BMPR-I.

Peptides and pseudopeptide ligands: a powerful toolbox for the affinity purification of current and next-generation biotherapeutics

Following the consolidation of therapeutic proteins in the fight against cancer, autoimmune, and neurodegenerative diseases, recent advancements in biochemistry and biotechnology have introduced a host of next-generation biotherapeutics, such as CRISPR-Cas nucleases, stem and car-T cells, and viral vectors for gene therapy. With these drugs entering the clinical pipeline, a new challenge lies ahead: how to manufacture large quantities of high-purity biotherapeutics that meet the growing demand by clinics and biotech companies worldwide. The protein ligands employed by the industry are inadequate to confront this challenge: while featuring high binding affinity and selectivity, these ligands require laborious engineering and expensive manufacturing, are prone to biochemical degradation, and pose safety concerns related to their bacterial origin. Peptides and pseudopeptides make excellent candidates to form a new cohort of ligands for the purification of next-generation biotherapeutics. Peptide-based ligands feature excellent target biorecognition, low or no toxicity and immunogenicity, and can be manufactured affordably at large scale. This work presents a comprehensive and systematic review of the literature on peptide-based ligands and their use in the affinity purification of established and upcoming biological drugs. A comparative analysis is first presented on peptide engineering principles, the development of ligands targeting different biomolecular targets, and the promises and challenges connected to the industrial implementation of peptide ligands. The reviewed literature is organized in (i) conventional (α-)peptides targeting antibodies and other therapeutic proteins, gene therapy products, and therapeutic cells; (ii) cyclic peptides and pseudo-peptides for protein purification and capture of viral and bacterial pathogens; and (iii) the forefront of peptide mimetics, such as β-/γ-peptides, peptoids, foldamers, and stimuli-responsive peptides for advanced processing of biologics.