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.

tICA-Metadynamics for Identifying Slow Dynamics in Membrane Permeation.

Molecular simulations are commonly used to understand the mechanism of membrane permeation of small molecules, particularly for biomedical and pharmaceutical applications. However, despite significant advances in computing power and algorithms, calculating an accurate permeation free energy profile remains elusive for many drug molecules because it can require identifying the rate-limiting degrees of freedom (i.e., appropriate reaction coordinates). To resolve this issue, researchers have developed machine learning approaches to identify slow system dynamics. In this work, we apply time-lagged independent component analysis (tICA), an unsupervised dimensionality reduction algorithm, to molecular dynamics simulations with well-tempered metadynamics to find the slowest collective degrees of freedom of the permeation process of trimethoprim through a multicomponent membrane. We show that tICA-metadynamics yields translational and orientational collective variables (CVs) that increase convergence efficiency ∼1.5 times. However, crossing the periodic boundary is shown to introduce artifacts in the translational CV that can be corrected by taking absolute values of molecular features. Additionally, we find that the convergence of the tICA CVs is reached with approximately five membrane crossings and that data reweighting is required to avoid deviations in the translational CV.

Mycolactone A vs. B: Multiscale Simulations Reveal the Roles of Localization and Association in Isomer-Specific Toxicity.

Mycolactone is an exotoxin produced by Mycobacterium ulcerans that causes the neglected tropical skin disease Buruli ulcer. This toxin inhibits the Sec61 translocon in the endoplasmic reticulum (ER), preventing the host cell from producing several secretory and transmembrane proteins, resulting in cytotoxic and immunomodulatory effects. Interestingly, only one of the two dominant isoforms of mycolactone is cytotoxic. Here, we investigate the origin of this specificity by performing extensive molecular dynamics (MD) simulations with enhanced free energy sampling to query the association trends of the two isoforms with both the Sec61 translocon, using two distinct cryo-electron microscopy (cryo-EM) models as references, and the ER membrane, which serves as a toxin reservoir prior to association. Our results suggest that mycolactone B (the cytotoxic isoform) has a stronger association with the ER membrane than mycolactone A due to more favorable interactions with membrane lipids and water molecules. This could increase the reservoir of toxin proximal to the Sec61 translocon. In one model of Sec61 inhibited by mycolactone, we find that isomer B interacts more closely with residues thought to play a key role in signal peptide recognition and, thus, are essential for subsequent protein translocation. In the other model, we find that isomer B interacts more closely with the lumenal and lateral gates of the translocon, the dynamics of which are essential for protein translocation. These interactions induce a more closed conformation, which has been suggested to block signal peptide insertion and subsequent protein translocation. Collectively, these findings suggest that isomer B's unique cytotoxicity is a consequence of both increased localization to the ER membrane and channel-locking association with the Sec61 translocon, facets that could be targeted in the development of Buruli Ulcer diagnostics and Sec61-targeted therapeutics.

tICA-Metadynamics for Identifying Slow Dynamics in Membrane Permeation.

Molecular simulations are commonly used to understand the mechanism of membrane permeation of small molecules, particularly for biomedical and pharmaceutical applications. However, despite significant advances in computing power and algorithms, calculating an accurate permeation free energy profile remains elusive for many drug molecules because it can require identifying the rate-limiting degrees of freedom (i.e., appropriate reaction coordinates). To resolve this issue, researchers have developed machine learning approaches to identify slow system dynamics. In this work, we apply time-lagged independent component analysis (tICA), an unsupervised dimensionality reduction algorithm, to molecular dynamics simulations with well-tempered metadynamics to find the slowest collective degrees of freedom of the permeation process of trimethoprim through a multicomponent membrane. We show that tICA-metadynamics yields translational and orientational collective variables (CVs) that increase convergence efficiency ∼1.5 times. However, crossing the periodic boundary is shown to introduce artefacts in the translational CV that can be corrected by taking absolute values of molecular features. Additionally, we find that the convergence of the tICA CVs is reached with approximately five membrane crossings, and that data reweighting is required to avoid deviations in the translational CV.

Mycolactone A vs. B: Does localization or association explain isomer-specific toxicity?

Mycolactone is an exotoxin produced by Mycobacterium ulcerans that causes the neglected tropical skin disease Buruli ulcer. This toxin inhibits the Sec61 translocon in the endoplasmic reticulum (ER), preventing the host cell from producing many secretory and transmembrane proteins, resulting in cytotoxic and immunomodulatory effects. Interestingly, only one of the two dominant isoforms of mycolactone is cytotoxic. Here, we investigate the origin of this specificity by performing extensive molecular dynamics (MD) simulations with enhanced free energy sampling to query the association trends of the two isoforms with both the Sec61 translocon and the ER membrane, which serves as a toxin reservoir prior to association. Our results suggest that mycolactone B (the cytotoxic isoform) has a stronger association with the ER membrane than mycolactone A due to more favorable interactions with membrane lipids and water molecules. This could increase the reservoir of toxin proximal to the Sec61 translocon. Isomer B also interacts more closely with the lumenal and lateral gates of the translocon, the dynamics of which are essential for protein translocation. These interactions induce a more closed conformation, which has been suggested to block signal peptide insertion and subsequent protein translocation. Collectively, these findings suggest that isomer B's unique cytotoxicity is a consequence of both increased localization to the ER membrane and channel-locking association with the Sec61 translocon, facets that could be targeted in the development of Buruli Ulcer diagnostics and Sec61-targeted therapeutics.

Can membrane composition traffic toxins? Mycolactone and preferential membrane interactions.

Mycolactone is a cytotoxic and immunosuppressive macrolide produced by Mycobacterium ulcerans and the sole causative agent of the neglected tropical skin disease Buruli ulcer. The toxin acts by invading host cells and interacting with intracellular targets to disrupt multiple fundamental cellular processes. Mycolactone's amphiphilic nature enables strong interactions with lipophilic environments, including cellular membranes; however, the specificity of these interactions and the role of membranes in the toxin's pathogenicity remain unknown. It is likely that preferential interactions with lipophilic carriers play a key role in the toxin's distribution in the host, which, if understood, could provide insights to aid in the development of needed diagnostics for Buruli ulcer disease. In this work, molecular dynamics simulations were combined with enhanced free-energy sampling to characterize mycolactone's association with and permeation through models of the mammalian endoplasmic reticulum (ER) and plasma membranes (PMs). We find that increased order in the PMs not only leads to a different permeation mechanism compared with that in the ER membrane but also an energetic driving force for ER localization. Increased hydration, membrane deformation, and preferential interactions with unsaturated lipid tails stabilize the toxin in the ER membrane, while disruption of lipid packing is a destabilizing force in the PMs.

A review on the antimicrobial properties of lectins.

Lectins are biologically versatile biomolecules with remarkable antimicrobial effects, notably against bacteria, fungi and protozoa, in addition to modulating host immunity. For this, the lectins bind to carbohydrates on the surface of the pathogen, which can cause damage to the cell wall and prevent the attachment of microorganisms to host cells. Thus, this study intends to review the biological activities of lectins, with an emphasis on antimicrobial activity. Lectins of plant stood out for its antimicrobial effects, demonstrating that they act against a variety of strains, where in vitro were able to inhibit their development and affect their morphology. In vivo, they modulated host immunity, signaling and activating defense cells. Some of these lectins were capable to modulate the action of antibiotics, indicating their potential to minimize the antibiotic resistance. The results suggest that lectins have antimicrobial activity with potential to be used in drug development.

Improving the accuracy and convergence of drug permeation simulations via machine-learned collective variables.

Understanding the permeation of biomolecules through cellular membranes is critical for many biotechnological applications, including targeted drug delivery, pathogen detection, and the development of new antibiotics. To this end, computer simulations are routinely used to probe the underlying mechanisms of membrane permeation. Despite great progress and continued development, permeation simulations of realistic systems (e.g., more complex drug molecules or biologics through heterogeneous membranes) remain extremely challenging if not intractable. In this work, we combine molecular dynamics simulations with transition-tempered metadynamics and techniques from the variational approach to conformational dynamics to study the permeation mechanism of a drug molecule, trimethoprim, through a multicomponent membrane. We show that collective variables (CVs) obtained from an unsupervised machine learning algorithm called time-structure based Independent Component Analysis (tICA) improve performance and substantially accelerate convergence of permeation potential of mean force (PMF) calculations. The addition of cholesterol to the lipid bilayer is shown to increase both the width and height of the free energy barrier due to a condensing effect (lower area per lipid) and increase bilayer thickness. Additionally, the tICA CVs reveal a subtle effect of cholesterol increasing the resistance to permeation in the lipid head group region, which is not observed when canonical CVs are used. We conclude that the use of tICA CVs can enable more efficient PMF calculations with additional insight into the permeation mechanism.

Antimicrobial peptide induced colloidal transformations in bacteria-mimetic vesicles: Combining in silico tools and experimental methods.

With the growing challenges of bacteria becoming resistant to conventional antibiotics, antimicrobial peptides (AMPs) may offer a potential alternative. One of the most studied AMPs, the human cathelicidin derived AMP LL-37 is notable for its antimicrobial activity even though its mechanism of action is not fully understood yet. This work investigates the interaction of LL-37 with 1-Palmitoyl-2-oleoyl-sn-glycero-3-phospho-rac-(1-glycerol) (POPG) vesicles, which were employed as a bacterial membrane model given the common presence of this phospholipid in the bacterial membrane. Experimental techniques including small angle X-ray scattering, transmission electron microscopy and dynamic light scattering were used to characterize the interactions among LL-37 and POPG. Molecular dynamics simulations complement the experimental studies with molecular-level insights into the process. LL-37 was discovered to actively and critically interact with the POPG vesicles, modifying the membrane curvature that eventually leads to structural transformations from vesicles to mixed micelles. The results shed light on the mechanisms underlying the interactions among LL-37 and bacteria mimetic vesicles and can guide the further development of AMP based antimicrobial materials and therapies.

Effect of Vitamin K3 Inhibiting the Function of NorA Efflux Pump and Its Gene Expression on Staphylococcus aureus.

Resistance to antibiotics has made diseases that previously healed easily become more difficult to treat. Staphylococcus aureus is an important cause of hospital-acquired infections and multi-drug resistant. NorA efflux pump, present in bacteria S. aureus, is synthesized by the expression of the norA gene. Menadione, also known as vitamin K3, is one of the synthetic forms of vitamin K. Therefore, the aim of this study is to verify the menadione effect on efflux inhibition through NorA pump gene expression inhibition and assess the effects of menadione in bacterial membrane. The effect of menadione as an efflux pump inhibitor (EPI) was evaluated by the microdilution method, fluorimetry, electron microscopy, and by RT-qPCR to evaluate gene expression. In the molecular docking, association with menadione induces increased fluorescence intensity. Menadione was observed (100% of the clusters) interacting with residues ILE12, ILE15, PHE16, ILE19, PHE47, GLN51, ALA105, and MET109 from NorA. The results showed the norA gene had its expression significantly diminished in the presence of menadione. The simulation showed that several menadione molecules were able to go through the bilayer and allow the entry of water molecules into the hydrophobic regions of the bilayer. When present within membranes, menadione may have caused membrane structural changes resulting in a decline of the signaling pathways involved in norA expression. Menadione demonstrated to be an efflux pump inhibitor with dual mechanism: affecting the efflux pump by direct interaction with protein NorA and indirectly inhibiting the norA gene expression, possibly by affecting regulators present in the membrane altered by menadione.

The "pre-assembled state" of magainin 2 lysine-linked dimer determines its enhanced antimicrobial activity.

Antimicrobial peptides (AMPs) are alternatives to conventional antibiotics against multi-drug resistant bacteria with low potential for developing microbial resistance. The design of such molecules requires understanding of the mechanisms of action, particularly the interaction with bacteria cell membranes. In this work, we determine the mechanism responsible for the higher activity against Escherichia coli of the C-terminal lysine dimer of magainin 2, (MG2)2K, in comparison to the monomeric peptide magainin 2 (MG2). Langmuir monolayers and vesicles made with the E. coli lipid extract were used to address the two possible states for the peptide-membrane interaction, namely the "binding state" and "pore state", respectively. The incorporation of MG2 and (MG2)2K in lipid monolayers at the air-water interface caused slight differences in surface pressure isotherms and polarization-modulated infrared reflection absorption (PM-IRRAS) spectra, and therefore the difference in activity is not associated with the binding state. In contrast, large differences were observed in the leakage experiments where (MG2)2K was shown to disrupt the large unilamellar vesicles to a much higher extent owing to efficient pore formation. The binding and penetration of MG2 and (MG2)2K were also probed with molecular dynamics (MD) simulations for bilayers made with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine:1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPE:POPG). (MG2)2K forms disordered toroidal pores at a significant lower concentration than for MG2. In summary, the combination of experimental and computational simulation results indicated that the "pre-assembling state" of (MG2)2K dimer leads to a reduced number of molecules and shorter time being required to kill E. coli.

Outer Membrane Remodeling: The Structural Dynamics and Electrostatics of Rough Lipopolysaccharide Chemotypes.

Lipopolysaccharides (LPS) are the primary constituent of the outer membrane of Gram-negative bacteria such as Pseudomonas aeruginosa. Gram-negative bacteria can synthesize modified forms of LPS in response to environmental stimuli or due to genetic mutations, a process known as outer membrane remodeling. Chemical modifications of the LPS modulate the integrity and antibiotic susceptibility of bacterial outer membranes. It also governs microbial adhesion to tissues and artificial material surfaces. We have extended a previous model of the rough LPS to include four novel chemotypes rmlC, galU, LPS Re, and Lipid-A. Atomistic molecular dynamics (MD) simulations were performed for outer membrane models constituted of each LPS chemotypes and 1,2-dipalmitoyl-3-phosphatidylethanolamine. It is shown that the decrease in the LPS polysaccharide chain length leads to a significant increase in the diffusion coefficients for the Ca(2+) counterions, increase in acyl chain packing (decrease in membrane fluidity), and attenuation of the negative potential across the LPS surface as positive counterions becomes more exposed to the solvent. The electrostatic potential on the LPS surfaces reflects heterogeneous charge distributions with increasingly larger patches of positive and negative potentials as the polysaccharide chain length decreases. Such a pattern originates from the spatial arrangement of charged phosphate-Ca(2+) clusters in the LPS inner-core that becomes exposed in the membrane surface as monosaccharide units are lost in the shortest chemotypes LPS Re and Lipid-A. These MD-derived conformational ensembles reproduce experimental trends and provide atom-level structural information on the rough LPS chemotypes that can help to rationalize antibiotic resistance and bacterial adhesion processes.