ProDy 2.0: Increased Scale and Scope after 10 Years of Protein Dynamics Modelling with Python

Structural shifts in TolC facilitate Efflux-Mediated β-lactam resistance

Efflux-mediated β-lactam resistance is a major public health concern, reducing the effectiveness of β-lactam antibiotics against many bacteria. Structural analyses show the efflux protein TolC in Gram-negative bacteria acts as a channel for antibiotics, impacting bacterial susceptibility and virulence. This study examines β-lactam drug efflux mediated by TolC using experimental and computational methods. Molecular dynamics simulations of drug-free TolC reveal essential movements and key residues involved in TolC opening. A whole-gene-saturation mutagenesis assay, mutating each TolC residue and measuring fitness effects under β-lactam selection, is performed. Here we show the TolC-mediated efflux of three antibiotics: oxacillin, piperacillin, and carbenicillin. Steered molecular dynamics simulations identify general and drug-specific efflux mechanisms, revealing key positions at TolC's periplasmic entry affecting efflux motions. Our findings provide insights into TolC's structural dynamics, aiding the design of new antibiotics to overcome bacterial efflux mechanisms.

Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis

Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in silico mutational scanning for all possible single mutations, along with 2 μs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. In sum, our findings highlight the potential of MuMi as a reliable and computationally efficient tool for predicting protein fitness landscapes, offering significant advantages over traditional methods. The methodologies and results presented in this study pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.

Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders

In the post-COVID-19 era, treatment options for potential SARS-CoV-2 outbreaks remain limited. An increased incidence of central nervous system (CNS) disorders has been observed in long-term COVID-19 patients. Understanding the shared molecular mechanisms between these conditions may provide new insights for developing effective therapies. This study developed an integrative drug-repurposing framework for COVID-19, leveraging comorbidity data with CNS disorders, network-based modular analysis, and dynamic perturbation analysis to identify potential drug targets and candidates against SARS-CoV-2. We constructed a comorbidity network based on the literature and data collection, including COVID-19-related proteins and genes associated with Alzheimer's disease, Parkinson's disease, multiple sclerosis, and autism spectrum disorder. Functional module detection and annotation identified a module primarily involved in protein synthesis as a key target module, utilizing connectivity map drug perturbation data. Through the construction of a weighted drug-target network and dynamic network-based drug-repurposing analysis, ubiquitin-carboxy-terminal hydrolase L1 emerged as a potential drug target. Molecular dynamics simulations suggested pregnenolone and BRD-K87426499 as two drug candidates for COVID-19. This study introduces a dynamic-perturbation-network-based drug-repurposing approach to identify COVID-19 drug targets and candidates by incorporating the comorbidity conditions of CNS disorders.

Identify Regioselective Residues of Ginsenoside Hydrolases by Graph-Based Active Learning from Molecular Dynamics

Identifying the catalytic regioselectivity of enzymes remains a challenge. Compared to experimental trial-and-error approaches, computational methods like molecular dynamics simulations provide valuable insights into enzyme characteristics. However, the massive data generated by these simulations hinder the extraction of knowledge about enzyme catalytic mechanisms without adequate modeling techniques. Here, we propose a computational framework utilizing graph-based active learning from molecular dynamics to identify the regioselectivity of ginsenoside hydrolases (GHs), which selectively catalyze C6 or C20 positions to obtain rare deglycosylated bioactive compounds from Panax plants. Experimental results reveal that the dynamic-aware graph model can excellently distinguish GH regioselectivity with accuracy as high as 96-98% even when different enzyme-substrate systems exhibit similar dynamic behaviors. The active learning strategy equips our model to work robustly while reducing the reliance on dynamic data, indicating its capacity to mine sufficient knowledge from short multi-replica simulations. Moreover, the model's interpretability identified crucial residues and features associated with regioselectivity. Our findings contribute to the understanding of GH catalytic mechanisms and provide direct assistance for rational design to improve regioselectivity. We presented a general computational framework for modeling enzyme catalytic specificity from simulation data, paving the way for further integration of experimental and computational approaches in enzyme optimization and design.

Combining the Fragment Molecular Orbital and GRID Approaches for the Prediction of Ligand-Metalloenzyme Binding Affinity: The Case Study of hCA II Inhibitors

Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.

Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning

Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of ∼5,764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We identified common resistance sites across type I, type II, and type I ½ inhibitors, unveiled unique resistance and sensitizing mutations for each inhibitor, and validated non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.

MinActionPath2: path generation between different conformations of large macromolecular assemblies by action minimization

Recent progress in solving macromolecular structures and assemblies by cryogenic electron microscopy techniques enables sampling of their conformations in different states that are relevant to their biological function. Knowing the transition path between these conformations would provide new avenues for drug discovery. While the experimental study of transition paths is intrinsically difficult, in-silico methods can be used to generate an initial guess for those paths. The Elastic Network Model (ENM), along with a coarse-grained representation (CG) of the structures are among the most popular models to explore such possible paths. Here we propose an update to our software platform MinActionPath that generates non-linear transition paths based on ENM and CG models, using action minimization to solve the equations of motion. The new website enables the study of large structures such as ribosomes or entire virus envelopes. It provides direct visualization of the trajectories along with quantitative analyses of their behaviors at http://dynstr.pasteur.fr/servers/minactionpath/minactionpath2_submission.

β-sheets mediate the conformational change and allosteric signal transmission between the AsLOV2 termini

Avena sativa phototropin 1 light-oxygen-voltage 2 domain (AsLOV2) is a model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change begins with the unfolding of the N-terminal A'α helix in the dark state followed by the unfolding of the C-terminal Jα helix. The light state is characterized by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, β-sheets are identified as crucial components for mediating allosteric signal transmission between the two termini. Through combined experimental and computational investigations, the Hβ and Iβ strands are recognized as the most critical and influential β-sheets in AsLOV2's allosteric mechanism. To elucidate the role of these β-sheets, we introduced 13 distinct mutations (F490L, N492A, L493A, F494L, H495L, L496F, Q497A, R500A, F509L, Q513A, L514A, D515V, and T517V) and conducted comprehensive molecular dynamics simulations. In-depth hydrogen bond analyses emphasized the role of two hydrogen bonds, Asn482-Leu453 and Gln479-Val520, in the observed distinct behaviors of L493A, L496F, Q497A, and D515V mutants. This illustrates the role of β-sheets in the transmission of the allosteric signal upon the photoactivation of the light state.

A novel Imidazo[1,2-a]pyridine derivative modulates active KRASG12D through off-like conformational shifts in switch-I and switch-II regions, mimicking inactive KRASG12D

KRASG12D are the most prevalent oncogenic mutations and a promising target for solid tumor therapies. However, its inhibition exhibits tremendous challenge due to the necessity of high binding affinity to obviate the need for covalent binders. Here we report the evidence of a novel class of Imidazo[1,2-a]pyridine derivative as potentially significant novel inhibitors of KRASG12D, discovered through extensive ligand-based screening against 2-[(2R)-piperidin-2-yl]-1H-indole, an important scaffold for KRASG12D inhibition via switch-I/II (S-I/II) pocket. The proposed compounds exhibited similar binding affinities and overlapped pose configurations to 2-[(2R)-piperidin-2-yl]-1H-indole, serving as a reliable starting point for drug discovery. Comparative free energy profiles demonstrated that C4 [2-methyl-3-((5-phenyl-1H-1,2,4-triazol-3-yl)methyl)imidazo[1,2-a]pyridine] effectively shifted the protein to a stable low-energy conformation via a prominent transition state. The conformational changes across the transition revealed the conformational shift of switch-I and II to a previously known off-like conformation of inactive KRASG12D with rmsd of 0.91 Å. These conformations were even more prominent than the privileged scaffold 2-[(2R)-piperidin-2-yl]-1H-indole. The representative structure overlay of C4 and another X-ray crystallography solved BI-2852 bound inactive KRASG12D revealed that Switch-I and II exhibited off-like conformations. The cumulative variance across the first eigenvalue that accounted for 57 % of the collective variance validated this on-to-off transition. In addition, the relative interaction of C4 binding showed consistent patterns with BI-2852. Taken together, our results support the inhibitory activity of [2-methyl-3-((5-phenyl-1H-1,2,4-triazol-3-yl)methyl)imidazo[1,2-a]pyridine] by shifting active KRASG12D to an inactive conformation.

A computational study to identify Sesamol derivatives as NRF2 activator for protection against drug-induced liver injury (DILI)

Drug-induced liver injury can be caused by any drugs, their metabolites, or natural products due to the inefficient functioning of drug-metabolizing enzymes, resulting in reactive oxygen species generation and leading to oxidative stress-induced cell death. For protection against oxidative stress, our cell has various defense mechanisms. One of the mechanisms is NRF2 pathway, when activated, protects the cell against oxidative stress. Natural antioxidants such as Sesamol have reported pharmacological activity (hepatoprotective & cardioprotective) and signaling pathways (NRF2 & CREM) altering potential. A Computational analysis was done using molecular docking, IFD, ADMET, MM-GBSA, and Molecular dynamic simulation of the Schrödinger suite. A total of 63,345 Sesamol derivatives were downloaded for the PubChem database. The protein structure of KEAP1-NRF2 (PDB: 4L7D) was downloaded from the RCSB protein database. The molecular docking technique was used to screen compounds that can form an interaction similar to the co-crystalized ligand (1VX). Based on MM-GBSA, docking score, and interactions, ten compounds were selected for ADMET profiling and IFD. After IFD, five compounds (66867225, 46148111, 12444939, 123892179, & 94817569) were selected for molecular dynamics simulation (MDS). Protein-ligand complex stability was assessed during MDS. The selected compounds (66867225, 46148111, 12444939, 123892179, & 94817569) complex with KEAP1 protein shows good stability and bond retentions. In our study, we observed that the selected compounds show good interaction, PCA, Rg, binding free energy, and ADMET profile. We can conclude that the selected compounds can act as NRF2 activators, which should be validated using proper in-vivo/in-vitro models.

An interaction network in the polymerase active site is a prerequisite for Watson-Crick base pairing in Pol γ

The replication accuracy of DNA polymerase gamma (Pol γ) is essential for mitochondrial genome integrity. Mutation of human Pol γ arginine-853 has been linked to neurological diseases. Although not a catalytic residue, Pol γ arginine-853 mutants are void of polymerase activity. To identify the structural basis for the disease, we determined a crystal structure of the Pol γ mutant ternary complex with correct incoming nucleotide 2'-deoxycytidine 5'-triphosphate (dCTP). Opposite to the wild type that undergoes open-to-closed conformational changes when bound to a correct nucleotide that is essential for forming a catalytically competent active site, the mutant complex failed to undergo the conformational change, and the dCTP did not base pair with its Watson-Crick complementary templating residue. Our studies revealed that arginine-853 coordinates an interaction network that aligns the 3'-end of primer and dCTP with the catalytic residues. Disruption of the network precludes the formation of Watson-Crick base pairing and closing of the active site, resulting in an inactive polymerase.

Genome structural dynamics: insights from Gaussian network analysis of Hi-C data

Characterization of the spatiotemporal properties of the chromatin is essential to gaining insights into the physical bases of gene co-expression, transcriptional regulation and epigenetic modifications. The Gaussian network model (GNM) has proven in recent work to serve as a useful tool for modeling chromatin structural dynamics, using as input high-throughput chromosome conformation capture data. We focus here on the exploration of the collective dynamics of chromosomal structures at hierarchical levels of resolution, from single gene loci to topologically associating domains or entire chromosomes. The GNM permits us to identify long-range interactions between gene loci, shedding light on the role of cross-correlations between distal regions of the chromosomes in regulating gene expression. Notably, GNM analysis performed across diverse cell lines highlights the conservation of the global/cooperative movements of the chromatin across different types of cells. Variations driven by localized couplings between genomic loci, on the other hand, underlie cell differentiation, underscoring the significance of the four-dimensional properties of the genome in defining cellular identity. Finally, we demonstrate the close relation between the cell type-dependent mobility profiles of gene loci and their gene expression patterns, providing a clear demonstration of the role of chromosomal 4D features in defining cell-specific differential expression of genes.

Structural mechanisms for VMAT2 inhibition by tetrabenazine

The vesicular monoamine transporter 2 (VMAT2) is a proton-dependent antiporter responsible for loading monoamine neurotransmitters into synaptic vesicles. Dysregulation of VMAT2 can lead to several neuropsychiatric disorders including Parkinson's disease and schizophrenia. Furthermore, drugs such as amphetamine and MDMA are known to act on VMAT2, exemplifying its role in the mechanisms of actions for drugs of abuse. Despite VMAT2's importance, there remains a critical lack of mechanistic understanding, largely driven by a lack of structural information. Here, we report a 3.1 Å resolution cryo-electron microscopy (cryo-EM) structure of VMAT2 complexed with tetrabenazine (TBZ), a non-competitive inhibitor used in the treatment of Huntington's chorea. We find TBZ interacts with residues in a central binding site, locking VMAT2 in an occluded conformation and providing a mechanistic basis for non-competitive inhibition. We further identify residues critical for cytosolic and lumenal gating, including a cluster of hydrophobic residues which are involved in a lumenal gating strategy. Our structure also highlights three distinct polar networks that may determine VMAT2 conformational dynamics and play a role in proton transduction. The structure elucidates mechanisms of VMAT2 inhibition and transport, providing insights into VMAT2 architecture, function, and the design of small-molecule therapeutics.

Coiled-coil domains are sufficient to drive liquid-liquid phase separation in protein models

Liquid-liquid phase separation (LLPS) is thought to be a main driving force in the formation of membraneless organelles. Examples of such organelles include the centrosome, central spindle, and stress granules. Recently, it has been shown that coiled-coil (CC) proteins, such as the centrosomal proteins pericentrin, spd-5, and centrosomin, might be capable of LLPS. CC domains have physical features that could make them the drivers of LLPS, but it is unknown if they play a direct role in the process. We developed a coarse-grained simulation framework for investigating the LLPS propensity of CC proteins, in which interactions that support LLPS arise solely from CC domains. We show, using this framework, that the physical features of CC domains are sufficient to drive LLPS of proteins. The framework is specifically designed to investigate how the number of CC domains, as well as the multimerization state of CC domains, can affect LLPS. We show that small model proteins with as few as two CC domains can phase separate. Increasing the number of CC domains up to four per protein can somewhat increase LLPS propensity. We demonstrate that trimer-forming and tetramer-forming CC domains have a dramatically higher LLPS propensity than dimer-forming coils, which shows that multimerization state has a greater effect on LLPS than the number of CC domains per protein. These data support the hypothesis of CC domains as drivers of protein LLPS, and have implications in future studies to identify the LLPS-driving regions of centrosomal and central spindle proteins.

Unraveling the ligand specificity and promiscuity of the Staphylococcus aureus NorA efflux pump: a computational study

Staphylococcus aureus, a gram-positive bacterial pathogen, develops antibiotic resistance partly through enhanced activity of transmembrane multi-drug efflux pump proteins like NorA. Being a prominent member of the Major Facilitator Superfamily (MFS), NorA transports various small molecules including hydrophilic fluoroquinolone antibiotics across the cell membrane. Intriguingly, NorA is inhibited by a structurally diverse set of small molecule inhibitors as well, indicating a highly promiscuous ligand/inhibitor recognition. Our study aims to elucidate the structural facets of this promiscuity. Known NorA inhibitors were grouped into five clusters based on chemical class and docked into ligand binding pockets on NorA conformations generated via molecular dynamics simulations. We discovered that several key residues, such as I23, E222, and F303, are involved in inhibitor binding. Additionally, residues I244, T223, F303, and F140 were identified as prominent in interactions with specific ligand clusters. Our findings suggest that NorA's substrate binding site, encompassing residues aiding ligand recognition based on chemical nature, facilitates the recognition of chemically diverse ligands. This insight into NorA's structural promiscuity in ligand recognition not only enhances understanding of antibiotic resistance mechanisms in S. aureus but also sets the stage for the development of more effective efflux pump inhibitors, vital for combating multidrug resistance.Communicated by Ramaswamy H. Sarma.

Allosteric modulation of serotonin and dopamine transporters: New insights from computations and experiments

Human monoamine transporters (MATs) are critical to regulating monoaminergic neurotransmission by translocating their substrates from the synaptic space back into the presynaptic neurons. As such, their primary substrate binding site S1 has been targeted by a wide range of compounds for treating neuropsychiatric and neurodegenerative disorders including depression, ADHD, neuropathic pain, and anxiety disorders. We present here a comparative study of the structural dynamics and ligand-binding properties of two MATs, dopamine transporter (DAT) and serotonin transporter (SERT), with focus on the allosteric modulation of their transport function by drugs or substrates that consistently bind a secondary site S2, proposed to serve as an allosteric site. Our systematic analysis of the conformational space and dynamics of a dataset of 50 structures resolved for DAT and SERT in the presence of one or more ligands/drugs reveals the specific residues playing a consistent role in coordinating the small molecules bound to subsites S2-I and S2-II within S2, such as R476 and Y481 in dDAT and E494, P561, and F556 in hSERT. Further analysis reveals how DAT and SERT differ in their two principal modes of structural changes, PC1 and PC2. Notably, PC1 underlies the transition between outward- and inward-facing states of the transporters as well as their gating; whereas PC2 supports the rearrangements of TM helices near the S2 site. Finally, the examination of cross-correlations between structural elements lining the respective sites S1 and S2 point to the crucial role of coupled motions between TM6a and TM10. In particular, we note the involvement of hSERT residues F335 and G338, and E493-E494-T497 belonging to these two respective helices, in establishing the allosteric communication between S1 and S2. These results help understand the molecular basis of the action of drugs that bind to the S2 site of DAT or SERT. They also provide a basis for designing allosteric modulators that may provide better control of specific interactions and cellular pathways, rather than indiscriminately inhibiting the transporter by targeting its orthosteric site.

A three-level regulatory mechanism of the aldo-keto reductase subfamily AKR12D

Modulation of protein function through allosteric regulation is central in biology, but biomacromolecular systems involving multiple subunits and ligands may exhibit complex regulatory mechanisms at different levels, which remain poorly understood. Here, we discover an aldo-keto reductase termed AKRtyl and present its three-level regulatory mechanism. Specifically, by combining steady-state and transient kinetics, X-ray crystallography and molecular dynamics simulation, we demonstrate that AKRtyl exhibits a positive synergy mediated by an unusual Monod-Wyman-Changeux (MWC) paradigm of allosteric regulation at low concentrations of the cofactor NADPH, but an inhibitory effect at high concentrations is observed. While the substrate tylosin binds at a remote allosteric site with positive cooperativity. We further reveal that these regulatory mechanisms are conserved in AKR12D subfamily, and that substrate cooperativity is common in AKRs across three kingdoms of life. This work provides an intriguing example for understanding complex allosteric regulatory networks.

Protein ensemble modeling and analysis with MMMx

Proteins, especially of eukaryotes, often have disordered domains and may contain multiple folded domains whose relative spatial arrangement is distributed. The MMMx ensemble modeling and analysis toolbox (https://github.com/gjeschke/MMMx) can support the design of experiments to characterize the distributed structure of such proteins, starting from AlphaFold2 predictions or folded domain structures. Weak order can be analyzed with reference to a random coil model or to peptide chains that match the residue-specific Ramachandran angle distribution of the loop regions and are otherwise unrestrained. The deviation of the mean square end-to-end distance of chain sections from their average over sections of the same sequence length reveals localized compaction or expansion of the chain. The shape sampled by disordered chains is visualized by superposition in the principal axes frame of their inertia tensor. Ensembles of different sizes and with weighted conformers can be compared based on a similarity parameter that abstracts from the ensemble width.

Strikingly High Activity of 15-Lipoxygenase Towards Di-Polyunsaturated Arachidonoyl/Adrenoyl-Phosphatidylethanolamines Generates Peroxidation Signals of Ferroptotic Cell Death

The vast majority of membrane phospholipids (PLs) include two asymmetrically positioned fatty acyls: oxidizable polyunsaturated fatty acids (PUFA) attached predominantly at the sn2 position, and non-oxidizable saturated/monounsaturated acids (SFA/MUFA) localized at the sn1 position. The peroxidation of PUFA-PLs, particularly sn2-arachidonoyl(AA)- and sn2-adrenoyl(AdA)-containing phosphatidylethanolamines (PE), has been associated with the execution of ferroptosis, a program of regulated cell death. There is a minor subpopulation (≈1-2 mol %) of doubly PUFA-acylated phospholipids (di-PUFA-PLs) whose role in ferroptosis remains enigmatic. Here we report that 15-lipoxygenase (15LOX) exhibits unexpectedly high pro-ferroptotic peroxidation activity towards di-PUFA-PEs. We revealed that peroxidation of several molecular species of di-PUFA-PEs occurred early in ferroptosis. Ferrostatin-1, a typical ferroptosis inhibitor, effectively prevented peroxidation of di-PUFA-PEs. Furthermore, co-incubation of cells with di-AA-PE and 15LOX produced PUFA-PE peroxidation and induced ferroptotic death. The decreased contents of di-PUFA-PEs in ACSL4 KO A375 cells was associated with lower levels of di-PUFA-PE peroxidation and enhanced resistance to ferroptosis. Thus, di-PUFA-PE species are newly identified phospholipid peroxidation substrates and regulators of ferroptosis, representing a promising therapeutic target for many diseases related to ferroptotic death.

Allo-targeting of the kinase domain: Insights from in silico studies and comparison with experiments

The eukaryotic protein kinase domain has been a broadly explored target for drug discovery, despite limitations imposed by its high sequence conservation as a shared modular domain and the development of resistance to drugs. One way of addressing those limitations has been to target its potential allosteric sites, shortly called allo-targeting, in conjunction with, or separately from, its conserved catalytic/orthosteric site that has been widely exploited. Allosteric regulation has gained importance as an alternative to overcome the drawbacks associated with the indiscriminate effect of targeting the active site, and it turned out to be particularly useful for these highly promiscuous and broadly shared kinase domains. Yet, allo-targeting often faces challenges as the allosteric sites are not as clearly defined as its orthosteric sites, and the effect on the protein function may not be unambiguously assessed. A robust understanding of the consequence of site-specific allo-targeting on the conformational dynamics of the target protein is essential to design effective allo-targeting strategies. Recent years have seen important advances in in silico identification of druggable sites and distinguishing among them those sites expected to allosterically mediate conformational switches essential to signal transmission. The present opinion underscores the utility of such computational approaches applied to the kinase domain, with the help of comparison between computational predictions and experimental observations.

Structural mechanisms for VMAT2 inhibition by tetrabenazine

The vesicular monoamine transporter 2 (VMAT2) is a proton-dependent antiporter responsible for loading monoamine neurotransmitters into synaptic vesicles. Dysregulation of VMAT2 can lead to several neuropsychiatric disorders including Parkinson's disease and schizophrenia. Furthermore, drugs such as amphetamine and MDMA are known to act on VMAT2, exemplifying its role in the mechanisms of actions for drugs of abuse. Despite VMAT2's importance, there remains a critical lack of mechanistic understanding, largely driven by a lack of structural information. Here we report a 3.1 Å resolution cryo-EM structure of VMAT2 complexed with tetrabenazine (TBZ), a non-competitive inhibitor used in the treatment of Huntington's chorea. We find TBZ interacts with residues in a central binding site, locking VMAT2 in an occluded conformation and providing a mechanistic basis for non-competitive inhibition. We further identify residues critical for cytosolic and lumenal gating, including a cluster of hydrophobic residues which are involved in a lumenal gating strategy. Our structure also highlights three distinct polar networks that may determine VMAT2 conformational dynamics and play a role in proton transduction. The structure elucidates mechanisms of VMAT2 inhibition and transport, providing insights into VMAT2 architecture, function, and the design of small-molecule therapeutics.

Tandem-repeat proteins conformational mechanics are optimized to facilitate functional interactions and complexations

The architectures of tandem-repeat proteins are distinct from those of globular proteins. Individual modules, each comprising small structural motifs of 20-40 residues, are arrayed in a quasi one-dimensional fashion to form striking, elongated, horseshoe-like, and superhelical architectures, stabilized solely by short-range interaction. The spring-like shapes of repeat arrays point to elastic modes of action, and these proteins function as adapter molecules or 'hubs,' propagating signals within multi-subunit assemblies in diverse biological contexts. This flexibility is apparent in the dramatic variability observed in the structures of tandem-repeat proteins in different complexes. Here, using computational analysis, we demonstrate the striking ability of just one or a few global motions to recapitulate these structures. These findings show how the mechanics of repeat arrays are robustly enabled by their unique architecture. Thus, the repeating architecture has been optimized by evolution to favor functional modes of motions. The global motions enabling functional transitions can be fully visualized at http://bahargroup.org/tr_web.

Antibodies from dengue patients with prior exposure to Japanese encephalitis virus are broadly neutralizing against Zika virus

Exposure to multiple mosquito-borne flaviviruses within a lifetime is not uncommon; however, how sequential exposures to different flaviviruses shape the cross-reactive humoral response against an antigen from a different serocomplex has yet to be explored. Here, we report that dengue-infected individuals initially primed with the Japanese encephalitis virus (JEV) showed broad, highly neutralizing potencies against Zika virus (ZIKV). We also identified a rare class of ZIKV-cross-reactive human monoclonal antibodies with increased somatic hypermutation and broad neutralization against multiple flaviviruses. One huMAb, K8b, binds quaternary epitopes with heavy and light chains separately interacting with overlapping envelope protein dimer units spanning domains I, II, and III through cryo-electron microscopy and structure-based mutagenesis. JEV virus-like particle immunization in mice further confirmed that such cross-reactive antibodies, mainly IgG3 isotype, can be induced and proliferate through heterologous dengue virus (DENV) serotype 2 virus-like particle stimulation. Our findings highlight the role of prior immunity in JEV and DENV in shaping the breadth of humoral response and provide insights for future vaccination strategies in flavivirus-endemic countries.

ATLAS: protein flexibility description from atomistic molecular dynamics simulations

Dynamical behaviour is one of the most crucial protein characteristics. Despite the advances in the field of protein structure resolution and prediction, analysis and prediction of protein dynamic properties remains a major challenge, mostly due to the low accessibility of data and its diversity and heterogeneity. To address this issue, we present ATLAS, a database of standardised all-atom molecular dynamics simulations, accompanied by their analysis in the form of interactive diagrams and trajectory visualisation. ATLAS offers a large-scale view and valuable insights on protein dynamics for a large and representative set of proteins, by combining data obtained through molecular dynamics simulations with information extracted from experimental structures. Users can easily analyse dynamic properties of functional protein regions, such as domain limits (hinge positions) and residues involved in interaction with other biological molecules. Additionally, the database enables exploration of proteins with uncommon dynamic properties conditioned by their environment such as chameleon subsequences and Dual Personality Fragments. The ATLAS database is freely available at https://www.dsimb.inserm.fr/ATLAS.

pyCapsid: identifying dominant dynamics and quasi-rigid mechanical units in protein shells

SUMMARY

pyCapsid is a Python package developed to facilitate the characterization of the dynamics and quasi-rigid mechanical units of protein shells and other protein complexes. The package was developed in response to the rapid increase of high-resolution structures, particularly capsids of viruses, requiring multiscale biophysical analyses. Given a protein shell, pyCapsid generates the collective vibrations of its amino-acid residues, identifies quasi-rigid mechanical regions associated with the disassembly of the structure, and maps the results back to the input proteins for interpretation. pyCapsid summarizes the main results in a report that includes publication-quality figures.

AVAILABILITY AND IMPLEMENTATION

pyCapsid's source code is available under MIT License on GitHub. It is compatible with Python 3.8-3.10 and has been deployed in two leading Python package-management systems, PIP and Conda. Installation instructions and tutorials are available in the online documentation and in the pyCapsid's YouTube playlist. In addition, a cloud-based implementation of pyCapsid is available as a Google Colab notebook. pyCapsid Colab does not require installation and generates the same report and outputs as the installable version. Users can post issues regarding pyCapsid in the repository's issues section.

The IbeA protein from adherent invasive Escherichia coli is a flavoprotein sharing structural homology with FAD-dependent oxidoreductases

Invasion of brain endothelium protein A (IbeA) is a virulence factor specific to pathogenic Escherichia coli. Originally identified in the K1 strain causing neonatal meningitis, it was more recently found in avian pathogenic Escherichia coli (APEC) and adherent invasive Escherichia coli (AIEC). In these bacteria, IbeA facilitates host cell invasion and intracellular survival, in particular, under harsh conditions like oxidative stress. Furthermore, IbeA from AIEC contributes to intramacrophage survival and replication, thus enhancing the inflammatory response within the intestine. Therefore, this factor is a promising drug target for anti-AIEC strategies in the context of Crohn's disease. Despite such an important role, the biological function of IbeA remains largely unknown. In particular, its exact nature and cellular localization, i.e., membrane-bound invasin versus cytosolic factor, are still of debate. Here, we developed an efficient protocol for recombinant expression of IbeA under native conditions and demonstrated that IbeA from AIEC is a soluble, homodimeric flavoprotein. Using mass spectrometry and tryptophan fluorescence measurements, we further showed that IbeA preferentially binds flavin adenine dinucleotide (FAD), with an affinity in the one-hundred nanomolar range and optimal binding under reducing conditions. 3D-modeling with AlphaFold revealed that IbeA shares strong structural homology with FAD-dependent oxidoreductases. Finally, we used ligand docking, mutational analyses, and molecular dynamics simulations to identify the FAD binding pocket within IbeA and characterize possible conformational changes occurring upon ligand binding. Overall, we suggest that the role of IbeA in the survival of AIEC within host cells, notably macrophages, is linked to modulation of redox processes.

Microsecond Molecular Dynamics Simulations and Markov State Models of Mutation-Induced Allosteric Mechanisms for the Light-Oxygen-Voltage 2 Protein : Revealing Structural Basis of Signal Transmission Induced by Photoactivation of the Light Protein State

Avena Sativa phototropin 1 Light-oxygen-voltage 2 domain (AsLOV2) is the model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change is initiated by the unfolding of the N-terminal helix in the dark state followed by the unfolding of the C-terminal helix. The light state is defined by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, β-sheets have been identified as crucial components for mediating allosteric signal transmission between the two termini. In this study, we combined microsecond all-atm molecular dynamics simulations and Markov state modeling of conformational states to quantify molecular basis of mutation-induced allostery in the AsLOV2 protein. Through a combination of computational investigations, we determine that the Hβ and Iβ strands are the most critical structural elements involved in the allosteric mechanism. To elucidate the role of these β-sheets, we introduced 13 distinct mutations (F490L, N492A, L493A, F494L, H495L, L496F, Q497A, R500A, F509L, Q513A, L514A, D515V, and T517V) and conducted comprehensive simulation analysis. The results highlighted the role of two hydrogen bond Asn482-Leu453 and Gln479-Val520 in the observed distinct behaviors of L493A, L496F, Q497A, and D515V mutants. The comprehensive atomistic-level analysis of the conformational landscapes revealed the critical functional role of β-sheet segments in the transmission of the allosteric signal upon the photoactivation of the light state.

Open-ComBind: harnessing unlabeled data for improved binding pose prediction

Determination of the bound pose of a ligand is a critical first step in many in silico drug discovery tasks. Molecular docking is the main tool for the prediction of non-covalent binding of a protein and ligand system. Molecular docking pipelines often only utilize the information of one ligand binding to the protein despite the commonly held hypothesis that different ligands share binding interactions when bound to the same receptor. Here we describe Open-ComBind, an easy-to-use, open-source version of the ComBind molecular docking pipeline that leverages information from multiple ligands without known bound structures to enhance pose selection. We first create distributions of feature similarities between ligand pose pairs, comparing near-native poses with all sampled docked poses. These distributions capture the likelihood of observing similar features, such as hydrogen bonds or hydrophobic contacts, in different pose configurations. These similarity distributions are then combined with a per-ligand docking score to enhance overall pose selection by 5% and 4.5% for high-affinity and congeneric series helper ligands, respectively. Open-ComBind reduces the average RMSD of ligands in our benchmark dataset by 9.0%. We provide Open-ComBind as an easy-to-use command line and Python API to increase pose prediction performance at www.github.com/drewnutt/open_combind .

Membrane regulation of 15LOX-1/PEBP1 complex prompts the generation of ferroptotic signals, oxygenated PEs

Ferroptosis is a regulated form of cell death, the mechanism of which is still to be understood. 15-lipoxygenase (15LOX) complex with phosphatidylethanolamine (PE)-binding protein 1 (PEBP1) catalyzes the generation of pro-ferroptotic cell death signals, hydroperoxy-polyunsaturated PE. We focused on gaining new insights into the molecular basis of these pro-ferroptotic interactions using computational modeling and liquid chromatography-mass spectrometry experiments. Simulations of 15LOX-1/PEBP1 complex dynamics and interactions with lipids revealed that association with the membrane triggers a conformational change in the complex. This conformational change facilitates the access of stearoyl/arachidonoyl-PE (SAPE) substrates to the catalytic site. Furthermore, the binding of SAPE promotes tight interactions within the complex and induces further conformational changes that facilitate the oxidation reaction. The reaction yields two hydroperoxides as products, 15-HpETE-PE and 12-HpETE-PE, at a ratio of 5:1. A significant effect of PEBP1 is observed only on the predominant product. Moreover, combined experiments and simulations consistently demonstrate the significance of PEBP1 P112E mutation in generating ferroptotic cell death signals.

L protein characterization and in silico screening of putative broad range target molecules for pathogenic mammarenaviruses from South America

The genus Mammarenavirus belonging to the family Arenaviridae encompasses pathogenic viral species capable of triggering severe diseases in humans, causing concern for the health system due to the high fatality rate associated with them. Currently, there is a dearth of specific therapies against pathogens of the genus. Natural products isolated from plants have impacted the development of drugs against several diseases. The Núcleo de Bioensaios, Biossíntese e Ecofisiologia de Produtos Naturais (NuBBE) database offers several natural compounds with antimicrobial activities that can be used in the development of new antiviral drugs. In this context, here we modeled the arenavirus L protein, multifunctional machinery essential for the viral replicative cycle, making this enzyme a potential candidate for targeting the development of antivirals against genus pathogens. Using the modeled L protein, a virtual screening was performed, which suggested eleven molecules from the NuBBE database that binds to the active site of the L protein, which was promising in the in silico predictions of absorption and toxicity analysis. The NuBBE 1642 molecule proved to be the best candidate for four of the five species evaluated, acting as a possible broad-spectrum molecule. Additionally, our results showed that the L protein is highly conserved among species of the genus, as well as presenting close phylogenetic relationships between many of the species studied, strengthening its candidacy as a therapeutic target. The data presented here demonstrate that some NuBBE molecules are potential ligands for the L protein of arenaviruses, which may help to contain possible outbreaks.Communicated by Ramaswamy H. Sarma.

Characterizing the transmembrane domains of ADAM10 and BACE1 and the impact of membrane composition

The β-secretase, BACE1, and the α-secretase, ADAM10, are known to competitively cleave amyloid precursor protein (APP) in the amyloid cascades of Alzheimer's disease. Cleavage of APP by BACE1 produces a 99-residue C-terminal peptide (APP-C99) that is subsequently cleaved by γ-secretase to form amyloid-β (Aβ) protein, whereas cleavage of APP by ADAM10 is nonamyloidogenic. It has been speculated that ADAM10/APP and BACE1/APP interactions are regulated by colocalization within and outside of liquid-ordered membrane domains; however, the mechanism of this regulation and the character of the proteins' transmembrane domains are not well understood. In this work, we have developed and characterized minimal congener sequences for the transmembrane domains of ADAM10 and BACE1 using a multiscale modeling approach combining both temperature replica exchange and conventional molecular dynamics simulations based on the coarse-grained Martini2.2 and all-atom CHARMM36 force fields. Our results show that membrane composition impacts the character of the transmembrane domains of BACE1 and ADAM10, adding credence to the speculation that membrane domains are involved in the etiology of Alzheimer's disease.

Molecular Dynamics Mappings of the CCT/TRiC Complex-Mediated Protein Folding Cycle Using Diffracted X-ray Tracking

The CCT/TRiC complex is a type II chaperonin that undergoes ATP-driven conformational changes during its functional cycle. Structural studies have provided valuable insights into the mechanism of this process, but real-time dynamics analyses of mammalian type II chaperonins are still scarce. We used diffracted X-ray tracking (DXT) to investigate the intramolecular dynamics of the CCT complex. We focused on three surface-exposed loop regions of the CCT1 subunit: the loop regions of the equatorial domain (E domain), the E and intermediate domain (I domain) juncture near the ATP-binding region, and the apical domain (A domain). Our results showed that the CCT1 subunit predominantly displayed rotational motion, with larger mean square displacement (MSD) values for twist (χ) angles compared with tilt (θ) angles. Nucleotide binding had a significant impact on the dynamics. In the absence of nucleotides, the region between the E and I domain juncture could act as a pivotal axis, allowing for greater motion of the E domain and A domain. In the presence of nucleotides, the nucleotides could wedge into the ATP-binding region, weakening the role of the region between the E and I domain juncture as the rotational axis and causing the CCT complex to adopt a more compact structure. This led to less expanded MSD curves for the E domain and A domain compared with nucleotide-absent conditions. This change may help to stabilize the functional conformation during substrate binding. This study is the first to use DXT to probe the real-time molecular dynamics of mammalian type II chaperonins at the millisecond level. Our findings provide new insights into the complex dynamics of chaperonins and their role in the functional folding cycle.

SBILib: a handle for protein modeling and engineering

SUMMARY

The SBILib Python library provides an integrated platform for the analysis of macromolecular structures and interactions. It combines simple 3D file parsing and workup methods with more advanced analytical tools. SBILib includes modules for macromolecular interactions, loops, super-secondary structures, and biological sequences, as well as wrappers for external tools with which to integrate their results and facilitate the comparative analysis of protein structures and their complexes. The library can handle macromolecular complexes formed by proteins and/or nucleic acid molecules (i.e. DNA and RNA). It is uniquely capable of parsing and calculating protein super-secondary structure and loop geometry. We have compiled a list of example scenarios which SBILib may be applied to and provided access to these within the library.

AVAILABILITY AND IMPLEMENTATION

SBILib is made available on Github at https://github.com/structuralbioinformatics/SBILib.

Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

Structural mobility tunes signalling of the GluA1 AMPA glutamate receptor

AMPA glutamate receptors (AMPARs), the primary mediators of excitatory neurotransmission in the brain, are either GluA2 subunit-containing and thus Ca2+-impermeable, or GluA2-lacking and Ca2+-permeable1. Despite their prominent expression throughout interneurons and glia, their role in long-term potentiation and their involvement in a range of neuropathologies2, structural information for GluA2-lacking receptors is currently absent. Here we determine and characterize cryo-electron microscopy structures of the GluA1 homotetramer, fully occupied with TARPγ3 auxiliary subunits (GluA1/γ3). The gating core of both resting and open-state GluA1/γ3 closely resembles GluA2-containing receptors. However, the sequence-diverse N-terminal domains (NTDs) give rise to a highly mobile assembly, enabling domain swapping and subunit re-alignments in the ligand-binding domain tier that are pronounced in desensitized states. These transitions underlie the unique kinetic properties of GluA1. A GluA2 mutant (F231A) increasing NTD dynamics phenocopies this behaviour, and exhibits reduced synaptic responses, reflecting the anchoring function of the AMPAR NTD at the synapse. Together, this work underscores how the subunit-diverse NTDs determine subunit arrangement, gating properties and ultimately synaptic signalling efficiency among AMPAR subtypes.

Probing conformational landscapes of binding and allostery in the SARS-CoV-2 omicron variant complexes using microsecond atomistic simulations and perturbation-based profiling approaches: hidden role of omicron mutations as modulators of allosteric signaling and epistatic relationships

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 spike protein complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which can be contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using the dynamics-based mutational scanning of spike residues, we identified structural stability and binding affinity hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational profiling approaches probed the effect of the Omicron mutations on allosteric interactions and communications in the complexes. The results of this analysis revealed specific roles of Omicron mutations as conformationally plastic and evolutionary adaptable modulators of binding and allostery which are coupled to the major regulatory positions through interaction networks. Through perturbation network scanning of allosteric residue potentials in the Omicron variant complexes performed in the background of the original strain, we characterized regions of epistatic couplings that are centered around the binding affinity hotspots N501Y and Q498R. Our results dissected the vital role of these epistatic centers in regulating protein stability, efficient ACE2 binding and allostery which allows for accumulation of multiple Omicron immune escape mutations at other sites. Through integrative computational approaches, this study provides a systematic analysis of the effects of Omicron mutations on thermodynamics, binding and allosteric signaling in the complexes with ACE2 receptor.

Coiled-coil domains are sufficient to drive liquid-liquid phase separation of proteins in molecular models

Liquid-liquid phase separation (LLPS) is thought to be a main driving force in the formation of membraneless organelles. Examples of such organelles include the centrosome, central spindle, and stress granules. Recently, it has been shown that coiled-coil (CC) proteins, such as the centrosomal proteins pericentrin, spd-5, and centrosomin, might be capable of LLPS. CC domains have physical features that could make them the drivers of LLPS, but it is unknown if they play a direct role in the process. We developed a coarse-grained simulation framework for investigating the LLPS propensity of CC proteins, in which interactions which support LLPS arise solely from CC domains. We show, using this framework, that the physical features of CC domains are sufficient to drive LLPS of proteins. The framework is specifically designed to investigate how the number of CC domains, as well as multimerization state of CC domains, can affect LLPS. We show that small model proteins with as few as two CC domains can phase separate. Increasing the number of CC domains up to four per protein can somewhat increase LLPS propensity. We demonstrate that trimer-forming and tetramer-forming CC domains have a dramatically higher LLPS propensity than dimer-forming coils, which shows that multimerization state has a greater effect on LLPS than the number of CC domains per protein. These data support the hypothesis of CC domains as drivers of protein LLPS, and has implications in future studies to identify the LLPS-driving regions of centrosomal and central spindle proteins.

EnGens: a computational framework for generation and analysis of representative protein conformational ensembles

Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in the number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing representative protein conformational ensembles. In this work, we: (1) provide an overview of existing methods and tools for representative protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples from the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations.

Structural delineation and computational design of SARS-CoV-2-neutralizing antibodies against Omicron subvariants

SARS-CoV-2 Omicron subvariants have evolved to evade receptor-binding site (RBS) antibodies that exist in diverse individuals as public antibody clones. We rationally selected RBS antibodies resilient to mutations in emerging Omicron subvariants. Y489 was identified as a site of virus vulnerability and a common footprint of broadly neutralizing antibodies against the subvariants. Multiple Y489-binding antibodies were encoded by public clonotypes and additionally recognized F486, potentially accounting for the emergence of Omicron subvariants harboring the F486V mutation. However, a subclass of antibodies broadly neutralized BA.4/BA.5 variants via hydrophobic binding sites of rare clonotypes along with high mutation-resilience under escape mutation screening. A computationally designed antibody based on one of the Y489-binding antibodies, NIV-10/FD03, was able to bind XBB with any 486 mutation and neutralized XBB.1.5. The structural basis for the mutation-resilience of this Y489-binding antibody group may provide important insights into the design of therapeutics resistant to viral escape.

Formation of protein adducts with Hydroperoxy-PE electrophilic cleavage products during ferroptosis

Ferroptosis is an iron dependent form of cell death, that is triggered by the discoordination of iron, lipids, and thiols. Its unique signature that distinguishes it from other forms of cell death is the formation and accumulation of lipid hydroperoxides, particularly oxidized forms of polyunsaturated phosphatidylethanolamines (PEs), which drives cell death. These readily undergo iron-catalyzed secondary free radical reactions leading to truncated products which retain the signature PE headgroup and which can readily react with nucleophilic moieties in proteins via their truncated electrophilic acyl chains. Using a redox lipidomics approach, we have identified oxidatively-truncated PE species (trPEox) in enzymatic and non-enzymatic model systems. Further, using a model peptide we demonstrate adduct formation with Cys as the preferred nucleophilic residue and PE(26:2) +2 oxygens, as one of the most reactive truncated PE-electrophiles produced. In cells stimulated to undergo ferroptosis we identified PE-truncated species with sn-2 truncations ranging from 5 to 9 carbons. Taking advantage of the free PE headgroup, we have developed a new technology using the lantibiotic duramycin, to enrich and identify the PE-lipoxidated proteins. Our results indicate that several dozens of proteins for each cell type, are PE-lipoxidated in HT-22, MLE, and H9c2 cells and M2 macrophages after they were induced to undergo ferroptosis. Pretreatment of cells with the strong nucleophile, 2-mercaptoethanol, prevented the formation of PE-lipoxidated proteins and blocked ferroptotic death. Finally, our docking simulations showed that the truncated PE species bound at least as good to several of the lantibiotic-identified proteins, as compared to the non-truncated parent molecule, stearoyl-arachidonoyl PE (SAPE), indicating that these oxidatively-truncated species favor/promote the formation of PEox-protein adducts. The identification of PEox-protein adducts during ferroptosis suggests that they are participants in the ferroptotic process preventable by 2-mercaptoethanol and may contribute to a point of no return in the ferroptotic death process.

Discovering selective antiferroptotic inhibitors of the 15LOX/PEBP1 complex noninterfering with biosynthesis of lipid mediators

Programmed ferroptotic death eliminates cells in all major organs and tissues with imbalanced redox metabolism due to overwhelming iron-catalyzed lipid peroxidation under insufficient control by thiols (Glutathione (GSH)). Ferroptosis has been associated with the pathogenesis of major chronic degenerative diseases and acute injuries of the brain, cardiovascular system, liver, kidneys, and other organs, and its manipulation offers a promising new strategy for anticancer therapy. This explains the high interest in designing new small-molecule-specific inhibitors against ferroptosis. Given the role of 15-lipoxygenase (15LOX) association with phosphatidylethanolamine (PE)-binding protein 1 (PEBP1) in initiating ferroptosis-specific peroxidation of polyunsaturated PE, we propose a strategy of discovering antiferroptotic agents as inhibitors of the 15LOX/PEBP1 catalytic complex rather than 15LOX alone. Here we designed, synthesized, and tested a customized library of 26 compounds using biochemical, molecular, and cell biology models along with redox lipidomic and computational analyses. We selected two lead compounds, FerroLOXIN-1 and 2, which effectively suppressed ferroptosis in vitro and in vivo without affecting the biosynthesis of pro-/anti-inflammatory lipid mediators in vivo. The effectiveness of these lead compounds is not due to radical scavenging or iron-chelation but results from their specific mechanisms of interaction with the 15LOX-2/PEBP1 complex, which either alters the binding pose of the substrate [eicosatetraenoyl-PE (ETE-PE)] in a nonproductive way or blocks the predominant oxygen channel thus preventing the catalysis of ETE-PE peroxidation. Our successful strategy may be adapted to the design of additional chemical libraries to reveal new ferroptosis-targeting therapeutic modalities.

Toward Overcoming Pyrethroid Resistance in Mosquito Control: The Role of Sodium Channel Blocker Insecticides

Diseases spread by mosquitoes lead to the death of 700,000 people each year. The main way to reduce transmission is vector control by biting prevention with chemicals. However, the most commonly used insecticides lose efficacy due to the growing resistance. Voltage-gated sodium channels (VGSCs), membrane proteins responsible for the depolarizing phase of an action potential, are targeted by a broad range of neurotoxins, including pyrethroids and sodium channel blocker insecticides (SCBIs). Reduced sensitivity of the target protein due to the point mutations threatened malaria control with pyrethroids. Although SCBIs-indoxacarb (a pre-insecticide bioactivated to DCJW in insects) and metaflumizone-are used in agriculture only, they emerge as promising candidates in mosquito control. Therefore, a thorough understanding of molecular mechanisms of SCBIs action is urgently needed to break the resistance and stop disease transmission. In this study, by performing an extensive combination of equilibrium and enhanced sampling molecular dynamics simulations (3.2 μs in total), we found the DIII-DIV fenestration to be the most probable entry route of DCJW to the central cavity of mosquito VGSC. Our study revealed that F1852 is crucial in limiting SCBI access to their binding site. Our results explain the role of the F1852T mutation found in resistant insects and the increased toxicity of DCJW compared to its bulkier parent compound, indoxacarb. We also delineated residues that contribute to both SCBIs and non-ester pyrethroid etofenprox binding and thus could be involved in the target site cross-resistance.

Structural Dynamics Predominantly Determine the Adaptability of Proteins to Amino Acid Deletions

The insertion or deletion (indel) of amino acids has a variety of effects on protein function, ranging from disease-forming changes to gaining new functions. Despite their importance, indels have not been systematically characterized towards protein engineering or modification goals. In the present work, we focus on deletions composed of multiple contiguous amino acids (mAA-dels) and their effects on the protein (mutant) folding ability. Our analysis reveals that the mutant retains the native fold when the mAA-del obeys well-defined structural dynamics properties: localization in intrinsically flexible regions, showing low resistance to mechanical stress, and separation from allosteric signaling paths. Motivated by the possibility of distinguishing the features that underlie the adaptability of proteins to mAA-dels, and by the rapid evaluation of these features using elastic network models, we developed a positive-unlabeled learning-based classifier that can be adopted for protein design purposes. Trained on a consolidated set of features, including those reflecting the intrinsic dynamics of the regions where the mAA-dels occur, the new classifier yields a high recall of 84.3% for identifying mAA-dels that are stably tolerated by the protein. The comparative examination of the relative contribution of different features to the prediction reveals the dominant role of structural dynamics in enabling the adaptation of the mutant to mAA-del without disrupting the native fold.

Sites of transcription initiation drive mRNA isoform selection

The generation of distinct messenger RNA isoforms through alternative RNA processing modulates the expression and function of genes, often in a cell-type-specific manner. Here, we assess the regulatory relationships between transcription initiation, alternative splicing, and 3' end site selection. Applying long-read sequencing to accurately represent even the longest transcripts from end to end, we quantify mRNA isoforms in Drosophila tissues, including the transcriptionally complex nervous system. We find that in Drosophila heads, as well as in human cerebral organoids, 3' end site choice is globally influenced by the site of transcription initiation (TSS). "Dominant promoters," characterized by specific epigenetic signatures including p300/CBP binding, impose a transcriptional constraint to define splice and polyadenylation variants. In vivo deletion or overexpression of dominant promoters as well as p300/CBP loss disrupted the 3' end expression landscape. Our study demonstrates the crucial impact of TSS choice on the regulation of transcript diversity and tissue identity.

Cooperative mechanics of PR65 scaffold underlies the allosteric regulation of the phosphatase PP2A

PR65, a horseshoe-shaped scaffold composed of 15 HEAT (observed in Huntingtin, elongation factor 3, protein phosphatase 2A, and the yeast kinase TOR1) repeats, forms, together with catalytic and regulatory subunits, the heterotrimeric protein phosphatase PP2A. We examined the role of PR65 in enabling PP2A enzymatic activity with computations at various levels of complexity, including hybrid approaches that combine full-atomic and elastic network models. Our study points to the high flexibility of this scaffold allowing for end-to-end distance fluctuations of 40-50 Å between compact and extended conformations. Notably, the intrinsic dynamics of PR65 facilitates complexation with the catalytic subunit and is retained in the PP2A complex enabling PR65 to engage the two domains of the catalytic subunit and provide the mechanical framework for enzymatic activity, with support from the regulatory subunit. In particular, the intra-repeat coils at the C-terminal arm play an important role in allosterically mediating the collective dynamics of PP2A, pointing to target sites for modulating PR65 function.

Drug repurposing for Mpox: Discovery of small molecules as potential inhibitors against DNA-dependent RNA polymerase using molecular modeling approach

Mpox (formerly Monkeypox), a zoonotic illness caused by the Mpox virus, belongs to the Orthopoxvirus genus in the family Poxviridae. To design and develop effective antiviral therapeutics against DNA viruses, the DNA-dependent RNA polymerase (DdRp) of poxviruses has emerged as a promising drug target. In the present study, we modeled the three-dimensional (3D) structure of DdRp using a template-based homology approach. After modeling, virtual screening was performed to probe the molecular interactions between 1755 Food and Drug Administration-approved small molecule drugs (≤500 molecular weight) and the DdRp of Mpox. Based on the binding affinity and molecular interaction patterns, five drugs, lumacaftor (-11.7 kcal/mol), conivaptan (-11.7 kcal/mol), betulinic acid (-11.6 kcal/mol), fluspirilene (-11.3 kcal/mol), and imatinib (-11.2 kcal/mol), have been ranked as the top drug compounds interacting with Mpox DdRp. Complexes of these shortlisted drugs with DdRp were further evaluated using state-of-the-art all-atoms molecular dynamics (MD) simulations on 200 nanoseconds followed by principal component analysis (PCA). MD simulations and PCA results revealed highly stable interactions of these small drugs with DdRp. After due validation in wet-lab using available in vitro and in vivo experiments, these repurposed drugs can be further utilized for the treatment of contagious Mpox virus. The outcome of this study may establish a solid foundation to screen repurposed and natural compounds as potential antiviral therapeutics against different highly pathogenic viruses.

EnGens: a computational framework for generation and analysis of representative protein conformational ensembles

Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing protein conformational ensembles. In this work we: (1) provide an overview of existing methods and tools for protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples found in the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations.

Pathogenic Mutations in the C2A Domain of Dysferlin form Amyloid that Activates the Inflammasome

Limb-Girdle Muscular Dystrophy Type-2B/2R is caused by mutations in the dysferlin gene ( DYSF ). This disease has two known pathogenic missense mutations that occur within dysferlin's C2A domain, namely C2A ^W52R and C2A ^V67D . Yet, the etiological rationale to explain the disease linkage for these two mutations is still unclear. In this study, we have presented evidence from biophysical, computational, and immunological experiments which suggest that these missense mutations interfere with dysferlin's ability to repair cells. The failure of C2A ^W52R and C2A ^V67D to initiate membrane repair arises from their propensity to form stable amyloid. The misfolding of the C2A domain caused by either mutation exposes β-strands, which are predicted to nucleate classical amyloid structures. When dysferlin C2A amyloid is formed, it triggers the NLRP3 inflammasome, leading to the secretion of inflammatory cytokines, including IL-1β. The present study suggests that the muscle dysfunction and inflammation evident in Limb-Girdle Muscular Dystrophy types-2B/2R, specifically in cases involving C2A ^W52R and C2A ^V67D , as well as other C2 domain mutations with considerable hydrophobic core involvement, may be attributed to this mechanism.

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach

Monkeypox virus (mpox virus) outbreak has rapidly spread to 82 non-endemic countries. Although it primarily causes skin lesions, secondary complications and high mortality (1-10%) in vulnerable populations have made it an emerging threat. Since there is no specific vaccine/antiviral, it is desirable to repurpose existing drugs against mpox virus. With little knowledge about the lifecycle of mpox virus, identifying potential inhibitors is a challenge. Nevertheless, the available genomes of mpox virus in public databases represent a goldmine of untapped possibilities to identify druggable targets for the structure-based identification of inhibitors. Leveraging this resource, we combined genomics and subtractive proteomics to identify highly druggable core proteins of mpox virus. This was followed by virtual screening to identify inhibitors with affinities for multiple targets. 125 publicly available genomes of mpox virus were mined to identify 69 highly conserved proteins. These proteins were then curated manually. These curated proteins were funnelled through a subtractive proteomics pipeline to identify 4 highly druggable, non-host homologous targets namely; A20R, I7L, Top1B and VETFS. High-throughput virtual screening of 5893 highly curated approved/investigational drugs led to the identification of common as well as unique potential inhibitors with high binding affinities. The common inhibitors, i.e., batefenterol, burixafor and eluxadoline were further validated by molecular dynamics simulation to identify their best potential binding modes. The affinity of these inhibitors suggests their repurposing potential. This work can encourage further experimental validation for possible therapeutic management of mpox.

Dynamics of the personalities of PCSK9 on missense variants (rs505151 and rs562556) from elderly cohort studies in Brazil

The Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) promotes the degradation of the low-density lipoprotein receptors (LDLR). Gain-of-function (GOF) variants of PCSK9 significantly affects lipid metabolism leading to coronary artery disease (CAD), owing to the raising the plasma low-density lipoprotein (LDL). Considering the public health matter, large-scale genomic studies have been conducted worldwide to provide the genetic architecture of populations for the implementation of precision medicine actions. Nevertheless, despite the advances in genomic studies, non-European populations are still underrepresented in public genomic data banks. Despite this, we found two high-frequency variants (rs505151 and rs562556) in the ABraOM databank (Brazilian genomic variants) from a cohort SABE study conducted in the largest city of Brazil, São Paulo. Here, we assessed the structural and dynamical features of these variants against WT through a molecular dynamics study. We sought fundamental dynamical interdomain relations through Perturb Response Scanning (PRS) and we found an interesting change of dynamical relation between prodomain and Cysteine-Histidine-Rich-Domain (CHRD) in the variants. The results highlight the pivotal role of prodomain in the PCSK9 dynamic and the implications for the development of new drugs depending on patient group genotype.