Synthesis of portimines reveals the basis of their anti-cancer activity.

Marine-derived cyclic imine toxins, portimine A and portimine B, have attracted attention because of their chemical structure and notable anti-cancer therapeutic potential1-4. However, access to large quantities of these toxins is currently not feasible, and the molecular mechanism underlying their potent activity remains unknown until now. To address this, a scalable and concise synthesis of portimines is presented, which benefits from the logic used in the two-phase terpenoid synthesis5,6 along with other tactics such as exploiting ring-chain tautomerization and skeletal reorganization to minimize protecting group chemistry through self-protection. Notably, this total synthesis enabled a structural reassignment of portimine B and an in-depth functional evaluation of portimine A, revealing that it induces apoptosis selectively in human cancer cell lines with high potency and is efficacious in vivo in tumour-clearance models. Finally, practical access to the portimines and their analogues simplified the development of photoaffinity analogues, which were used in chemical proteomic experiments to identify a primary target of portimine A as the 60S ribosomal export protein NMD3.

Enhancing luciferase activity and stability through generative modeling of natural enzyme sequences.

The availability of natural protein sequences synergized with generative AI provides new paradigms to engineer enzymes. Although active enzyme variants with numerous mutations have been designed using generative models, their performance often falls short of their wild type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase (RLuc) homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate to improve either luciferase activity or stability of designed single mutants is ~50%. This finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in RLuc toward emitting blue light that holds advantages in terms of water penetration compared to other light spectra. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

O-Glycosylation Induces Amyloid-ß To Form New Fibril Polymorphs Vulnerable for Degradation.

Brain accumulation of amyloid-ß (Aß) peptides (resulting from a disrupted balance between biosynthesis and clearance) occurs during the progression of Alzheimer's disease (AD). Aß peptides have diverse posttranslational modifications (PTMs) that variously modulate Aß aggregation into fibrils, but understanding the mechanistic roles of PTMs in these processes remains a challenge. Here, we chemically synthesized three homogeneously modified isoforms of Aß (1-42) peptides bearing Tyr10 O-glycosylation, an unusual PTM initially identified from the cerebrospinal fluid samples of AD patients. We discovered that O-glycans significantly affect both the aggregation and degradation of Aß42. By combining cryo-EM and various biochemical assays, we demonstrate that a Galß1-3GalNAc modification redirects Aß42 to form a new fibril polymorphic structure that is less stable and more vulnerable to Aß-degrading enzymes (e.g., insulin-degrading enzyme). Thus, beyond showing how particular O-glycosylation modifications affect Aß42 aggregation at the molecular level, our study provides powerful experimental tools to support further investigations about how PTMs affect Aß42 fibril aggregation and AD-related neurotoxicity.

Chemical Syntheses and Biological Evaluation of CXCL14 and Its Site-Selectively Modified Methionine Sulfoxide-Containing Derivatives.

The access to methionine sulfoxide [Met(O)]-containing proteins is particularly valuable for studying this important type of post-translational modification (PTM). However, the lack of selective in vitro oxidation methods makes it difficult to obtain homogeneous proteins with accurate and controllable incorporation of Met(O), particularly the ones with multiple methionines. Here, we report a chemical approach to synthesize methionine-oxidized human chemokine CXCL14 in a site-selective manner. The in vitro chemotaxis activities of synthetic proteins have also been evaluated.

Enhancing Luciferase Activity and Stability through Generative Modeling of Natural Enzyme Sequences.

The availability of natural protein sequences synergized with generative artificial intelligence (AI) provides new paradigms to create enzymes. Although active enzyme variants with numerous mutations have been produced using generative models, their performance often falls short compared to their wild-type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate of designed single mutants is ~50% to improve either luciferase activity or stability. These finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in Renilla luciferase towards emitting blue light that holds advantages in terms of water penetration compared to other light spectrum. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

Vascular Endothelial Growth Factor Mimetic Peptide and Parathyroid Hormone (1-34) Delivered via a Blue-Light-Curable Hydrogel Synergistically Accelerate Bone Regeneration.

Safe and effective biomaterials are in urgent clinical need for tissue regeneration and bone repair. While numerous advances have been made on hydrogels promoting osteogenesis in bone formation, co-stimulation of the angiogenic pathways in this process remains to be exploited. Here, we have developed a gelatin-based blue-light-curable hydrogel system, functionalized with an angiogenic vascular endothelial growth factor (VEGF) mimetic peptide, KLTWQELYQLKYKGI (KLT), and an osteoanabolic peptide, parathyroid hormone (PTH) 1-34. We have discovered that the covalent modification of gelatin scaffold with peptides can modulate the physical properties and biological activities of the produced hydrogels. Furthermore, we have demonstrated that those two peptides orchestrate synergistically and promote bone regeneration in a rat cranial bone defect model with remarkable efficacy. This dual-peptide-functionalized hydrogel system may serve as a promising lead to functional biomaterials in bone repair and tissue engineering.