Rational derivation, extension, and cyclization of self-inhibitory peptides to target TGF-β/BMP signaling in ONFH

Emerging roles of growth factors in osteonecrosis of the femoral head

Osteonecrosis of the femoral head (ONFH) is a potentially disabling orthopedic condition that requires total hip arthroplasty in most late-stage cases. However, mechanisms underlying the development of ONFH remain unknown, and the therapeutic strategies remain limited. Growth factors play a crucial role in different physiological processes, including cell proliferation, invasion, metabolism, apoptosis, and stem cell differentiation. Recent studies have reported that polymorphisms of growth factor-related genes are involved in the pathogenesis of ONFH. Tissue and genetic engineering are attractive strategies for treating early-stage ONFH. In this review, we summarized dysregulated growth factor-related genes and their role in the occurrence and development of ONFH. In addition, we discussed their potential clinical applications in tissue and genetic engineering for the treatment of ONFH.

Molecular conversion of MIG6 hotspot-3 peptide from the nonbinder to a moderate binder of HER2 by rational design of an orthogonal interaction system at the HER2-peptide interface

Human epidermal growth factor receptor 2 (HER2) has been established as an approved druggable target for the treatment of patients with diverse gynecological tumors such as ovarian, cervical and breast cancers. The mitogen-inducible gene 6 (MIG6) protein is a negative regulator of HER2 signaling by using its Seg1 segment to disrupt the allosteric dimerization of HER2 kinase domain. Previous studies found that the Seg1 adopts three separated hotspots to interact with the HER2 dimerization interface, in which the third hotspot (H3) is located at the core region of the interface but its derived H3 peptide (³⁵⁶PKYVS³⁶⁰) and Tyr358Phe mutant (³⁵⁶PKFVS³⁶⁰) cannot bind effectively to the interface in an independent manner. In this study, we demonstrate that the H3 peptide can be converted from nonbinder to a moderate binder of HER2 by just adding an orthogonal noncovalent interaction system (X⋯O┄H) between a halogen bond (X⋯O) and a hydrogen bond (H┄O) involving peptide Phe358 residue and HER2 Val948/Trp951 residues. High-level calculations are utilized to rigorously characterize and rationally design the X⋯O┄H system, which is then optimized with different halogen atoms and at different substituting positions. It is revealed that there is a synergistic effect between the X⋯O and H┄O of the orthogonal interaction system; formation of the halogen bond can enhance the interaction strength of the hydrogen bond. In silico analysis and in vitro assay reach a consistence that Br-substitution at the m-position of peptide Phe358 phenyl moiety is the best choice that can render strong interaction for the X⋯O┄H system, which also makes the peptide 'bindable' to HER2 kinase domain, while F/Cl/I-substitution at the same position can only improve the peptide affinity moderately or modestly. In contrast, the Br-substitution at the o- and p-positions of peptide Phe358 phenyl moiety cannot define effective X⋯O┄H interaction and thus does not confer additional affinity to the HER2-peptide complex.

Computational Approaches and Challenges to Developing Universal Influenza Vaccines

The traditional design of effective vaccines for rapidly-evolving pathogens, such as influenza A virus, has failed to provide broad spectrum and long-lasting protection. With low cost whole genome sequencing technology and powerful computing capabilities, novel computational approaches have demonstrated the potential to facilitate the design of a universal influenza vaccine. However, few studies have integrated computational optimization in the design and discovery of new vaccines. Understanding the potential of computational vaccine design is necessary before these approaches can be implemented on a broad scale. This review summarizes some promising computational approaches under current development, including computationally optimized broadly reactive antigens with consensus sequences, phylogenetic model-based ancestral sequence reconstruction, and immunomics to compute conserved cross-reactive T-cell epitopes. Interactions between virus-host-environment determine the evolvability of the influenza population. We propose that with the development of novel technologies that allow the integration of data sources such as protein structural modeling, host antibody repertoire analysis and advanced phylodynamic modeling, computational approaches will be crucial for the development of a long-lasting universal influenza vaccine. Taken together, computational approaches are powerful and promising tools for the development of a universal influenza vaccine with durable and broad protection.