Computational Modeling of Conformer Stability in Benenodin-1, a Thermally Actuated Lasso Peptide Switch

In silico design of foldable lasso peptides

Lasso peptides are a unique class of natural products with distinctively threaded structures, conferring exceptional stability against thermal and proteolytic degradation. Despite their promising biotechnological and pharmaceutical applications, reported attempts to prepare them by chemical synthesis result in forming the nonthreaded branched-cyclic isomer, rather than the desired lassoed structure. This is likely due to the entropic challenge of folding a short, threaded motif before chemically mediated cyclization. Accordingly, this study aims to better understand and enhance the relative stability of pre-lasso conformations-the essential precursor to lasso peptide formation-through sequence optimization, chemical modification, and disulfide incorporation. Using Rosetta fixed backbone design, optimal sequences for several class II lasso peptides are identified. Enhanced sampling with well-tempered metadynamics confirmed that designed sequences derived from the lasso structures of rubrivinodin and microcin J25 exhibit a notable improvement in pre-lasso stability relative to the competing nonthreaded conformations. Chemical modifications to the isopeptide bond-forming residues of microcin J25 further increase the probability of pre-lasso formation, highlighting the beneficial role of noncanonical amino acid residues. Counterintuitively, the introduction of a disulfide cross-link decreased pre-lasso stability. Although cross-linking inherently constrains the peptide structure, decreasing the entropic dominance of unfolded phase space, it hinders the requisite wrapping of the N-terminal end around the tail to adopt the pre-lasso conformation. However, combining chemical modifications with the disulfide cross-link results in further pre-lasso stabilization, indicating that the ring modifications counteract the constraints and provide a cooperative benefit with cross-linking. These findings lay the groundwork for further design efforts to enable synthetic access to the lasso peptide scaffold.

Tying the Knot: In Silico Design of Foldable Lasso Peptides

Lasso peptides are a unique class of natural products with distinctively threaded structures, conferring exceptional stability against thermal and proteolytic degradation. Despite their promising biotechnological and pharmaceutical applications, reported attempts to prepare them by chemical synthesis result in forming the nonthreaded branched-cyclic isomer, rather than the desired lassoed structure. This is likely due to the entropic challenge of folding a short, threaded motif prior to chemically mediated cyclization. Accordingly, this study aims to better understand and enhance the relative stability of pre-lasso conformations-the essential precursor to lasso peptide formation-through sequence optimization, chemical modification, and disulfide incorporation. Using Rosetta fixed backbone design, optimal sequences for several class II lasso peptides are identified. Enhanced sampling with well-tempered metadynamics confirmed that designed sequences derived from the lasso structures of rubrivinodin and microcin J25 exhibit a notable improvement in pre-lasso stability relative to the competing nonthreaded conformations. Chemical modifications to the isopeptide bond-forming residues of microcin J25 further increase the probability of pre-lasso formation, highlighting the beneficial role of non-canonical amino acid residues. Counterintuitively, the introduction of a disulfide cross-link decreased pre-lasso stability. Although cross-linking inherently constrains the peptide structure, decreasing the entropic dominance of unfolded phase space, it hinders the requisite wrapping of the N-terminal end around the tail to adopt the pre-lasso conformation. However, combining chemical modifications with the disulfide cross-link results in further pre-lasso stabilization, indicating that the ring modifications counteract the constraints and provide a cooperative benefit with cross-linking. These findings lay the groundwork for further design efforts to enable synthetic access to the lasso peptide scaffold.

SIGNIFICANCE

Lasso peptides are a unique class of ribosomally synthesized and post-translationally modified natural products with diverse biological activities and potential for therapeutic applications. Although direct synthesis would facilitate therapeutic design, it has not yet been possible to fold these short sequences to their threaded architecture without the help of biosynthetic enzyme stabilization. Our work explores strategies to enhance the stability of the pre-lasso structure, the essential precursor to de novo lasso peptide formation. We find that sequence design, incorporating non-canonical amino acid residues, and design-guided cross-linking can augment stability to increase the likelihood of lasso motif accessibility. This work presents several strategies for the continued design of foldable lasso peptides.

Lasso peptides realm: Insights and applications

Lasso peptides exhibit a range of bioactivities, including antiviral effects, inhibition of the glucagon receptor, blockade of the endothelin type B receptor, inhibition of myosin light chain kinase, and modulation of the atrial natriuretic factor, as well as notable antimicrobial properties. Intriguingly, lasso peptides exhibit remarkable proteolytic and thermal stability, addressing one of the key challenges that traditional peptides often face. The challenge in producing those valuable peptides remains the main hurdle in the way of producing larger quantities or even modifying them with more potent analogues. Genome mining and heterologous expression approaches have greatly facilitated the production of lasso peptides, moving beyond mere isolation techniques. This advancement not only allows for larger quantities but also enables the creation of additional analogues with improved stability and potency. This review aims to explore the unique bioactivities and stability of lasso peptides, along with recent advancements in genome mining and heterologous expression that address production challenges and open pathways for engineering potent analogues.

One Descriptor to Fold Them All: Harnessing Intuition and Machine Learning to Identify Transferable Lasso Peptide Reaction Coordinates

Identifying optimal reaction coordinates for complex conformational changes and protein folding remains an outstanding challenge. This study combines collective variable (CV) discovery based on chemical intuition and machine learning with enhanced sampling to converge the folding free energy landscape of lasso peptides, a unique class of natural products with knot-like tertiary structures. This knotted scaffold imparts remarkable stability, making lasso peptides resistant to proteolytic degradation, thermal denaturation, and extreme pH conditions. Although their direct synthesis would enable therapeutic design, it has not yet been possible due to the improbable occurrence of spontaneous lasso folding. Thus, simulations characterizing the folding propensity are needed to identify strategies for increasing access to the lasso architecture by stabilizing the pre-lasso ensemble before isopeptide bond formation. Herein, harmonic linear discriminant analysis (HLDA) is combined with metadynamics-enhanced sampling to discover CVs capable of distinguishing the pre-lasso fold and converging the folding propensity. Intuitive CVs are compared to iterative rounds of HLDA to identify CVs that not only accomplish these goals for one lasso peptide but also seem to be transferable to others, establishing a protocol for the identification of folding reaction coordinates for lasso peptides.

Lasso Peptides: Exploring the Folding Landscape of Nature's Smallest Interlocked Motifs

Lasso peptides make up a class of natural products characterized by a threaded structure. Given their small size and stability, chemical synthesis would offer tremendous potential for the development of novel therapeutics. However, the accessibility of the pre-folded lasso architecture has limited this advance. To better understand the folding process de novo, simulations are used herein to characterize the folding propensity of microcin J25 (MccJ25), a lasso peptide known for its antimicrobial properties. New algorithms are developed to unambiguously distinguish threaded from nonthreaded precursors and determine handedness, a key feature in natural lasso peptides. We find that MccJ25 indeed forms right-handed pre-lassos, in contrast to past predictions but consistent with all natural lasso peptides. Additionally, the native pre-lasso structure is shown to be metastable prior to ring formation but to readily transition to entropically favored unfolded and nonthreaded structures, suggesting that de novo lasso folding is rare. However, by altering the ring forming residues and appending thiol and thioester functionalities, we are able to increase the stability of pre-lasso conformations. Furthermore, conditions leading to protonation of a histidine imidazole side chain further stabilize the modified pre-lasso ensemble. This work highlights the use of computational methods to characterize lasso folding and demonstrates that de novo access to lasso structures can be facilitated by optimizing sequence, unnatural modifications, and reaction conditions like pH.

Mutexa: A Computational Ecosystem for Intelligent Protein Engineering

Protein engineering holds immense promise in shaping the future of biomedicine and biotechnology. This Review focuses on our ongoing development of Mutexa, a computational ecosystem designed to enable "intelligent protein engineering". In this vision, researchers will seamlessly acquire sequences of protein variants with desired functions as biocatalysts, therapeutic peptides, and diagnostic proteins through a finely-tuned computational machine, akin to Amazon Alexa's role as a versatile virtual assistant. The technical foundation of Mutexa has been established through the development of a database that combines and relates enzyme structures and their respective functions (e.g., IntEnzyDB), workflow software packages that enable high-throughput protein modeling (e.g., EnzyHTP and LassoHTP), and scoring functions that map the sequence-structure-function relationship of proteins (e.g., EnzyKR and DeepLasso). We will showcase the applications of these tools in benchmarking the convergence conditions of enzyme functional descriptors across mutants, investigating protein electrostatics and cavity distributions in SAM-dependent methyltransferases, and understanding the role of nonelectrostatic dynamic effects in enzyme catalysis. Finally, we will conclude by addressing the future steps and fundamental challenges in our endeavor to develop new Mutexa applications that assist the identification of beneficial mutants in protein engineering.

LassoHTP: A High-Throughput Computational Tool for Lasso Peptide Structure Construction and Modeling

Lasso peptides are a subclass of ribosomally synthesized and post-translationally modified peptides with a slipknot conformation. With superior thermal stability, protease resistance, and antimicrobial activity, lasso peptides are promising candidates for bioengineering and pharmaceutical applications. To enable high-throughput computational prediction and design of lasso peptides, we developed a software, LassoHTP, for automatic lasso peptide structure construction and modeling. LassoHTP consists of three modules, including the scaffold constructor, mutant generator, and molecular dynamics (MD) simulator. With a user-provided sequence and conformational annotation, LassoHTP can either generate the structure and conformational ensemble as is or conduct random mutagenesis. We used LassoHTP to construct eight known lasso peptide structures de novo and to simulate their conformational ensembles for 100 ns MD simulations. For benchmarking, we calculated the root mean square deviation (RMSD) of these ensembles with reference to their experimental crystal or NMR PDB structures; we also compared these RMSD values against those of the MD ensembles that are initiated from the PDB structures. Dihedral principal component analysis was also conducted. The results show that the LassoHTP-initiated ensembles are similar to those of the PDB-initiated ensembles. LassoHTP offers a computational platform to develop strategies for lasso peptide prediction and design.

Conformational Stability and Denaturation Processes of Proteins Investigated by Electrophoresis under Extreme Conditions

The functional structure of proteins results from marginally stable folded conformations. Reversible unfolding, irreversible denaturation, and deterioration can be caused by chemical and physical agents due to changes in the physicochemical conditions of pH, ionic strength, temperature, pressure, and electric field or due to the presence of a cosolvent that perturbs the delicate balance between stabilizing and destabilizing interactions and eventually induces chemical modifications. For most proteins, denaturation is a complex process involving transient intermediates in several reversible and eventually irreversible steps. Knowledge of protein stability and denaturation processes is mandatory for the development of enzymes as industrial catalysts, biopharmaceuticals, analytical and medical bioreagents, and safe industrial food. Electrophoresis techniques operating under extreme conditions are convenient tools for analyzing unfolding transitions, trapping transient intermediates, and gaining insight into the mechanisms of denaturation processes. Moreover, quantitative analysis of electrophoretic mobility transition curves allows the estimation of the conformational stability of proteins. These approaches include polyacrylamide gel electrophoresis and capillary zone electrophoresis under cold, heat, and hydrostatic pressure and in the presence of non-ionic denaturing agents or stabilizers such as polyols and heavy water. Lastly, after exposure to extremes of physical conditions, electrophoresis under standard conditions provides information on irreversible processes, slow conformational drifts, and slow renaturation processes. The impressive developments of enzyme technology with multiple applications in fine chemistry, biopharmaceutics, and nanomedicine prompted us to revisit the potentialities of these electrophoretic approaches. This feature review is illustrated with published and unpublished results obtained by the authors on cholinesterases and paraoxonase, two physiologically and toxicologically important enzymes.