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.

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.

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.

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.