CHARMM36m: an improved force field for folded and intrinsically disordered proteins

Elucidation of the hydration pattern of trifluoroacetic acid in dilute solutions: FTIR and computational study

The atmospheric partitioning of trifluoroacetic acid (TFA) in aerosol is a complex function of the size of suspended water droplets and their pH value. The unraveling of the affinity of TFA towards basic but not acidic conditions may be accomplished by providing an insight into the hydration pattern of undissociated TFA. Owing to rather scarce details on very dilute aqueous solutions of trifluoroacetic acid (TFA), we examined CF3COOD and CF3COONa solutions in D2O in the concentration range 0.001-0.1 mol dm-3 using transmission FTIR spectroscopy and computational methods. Besides detecting the signals originated from undissociated species in both CF3COOD (1787 cm-1 and 1766 cm-1 at c0 = 0.1 mol dm-3) and CF3COONa (1807 cm-1 at c0 = 0.1 mol dm-3) D2O solutions, through computational techniques we identified different TFA hydrates that contribute to the complexity of the spectral appearance. The combination of experimental and computational data suggested the concentration dependence of the predominant hydrogen bonding pattern of TFA. The results obtained in this work should help in understanding the partitioning of TFA into micron-size water droplets in the atmosphere in molecular and structural terms, i.e. the eventual stability of a hydrated complex for a particular TFA conformer.

Comparison of two peroxidases with high potential for biotechnology applications - HRP vs. APEX2

Peroxidases are essential elements in many biotechnological applications. An especially interesting concept involves split enzymes, where the enzyme is separated into two smaller and inactive proteins that can dimerize into a fully active enzyme. Such split forms were developed for the horseradish peroxidase (HRP) and ascorbate peroxidase (APX) already. Both peroxidases have a high potential for biotechnology applications. In the present study, we performed biophysical comparisons of these two peroxidases and their split analogues. The active site availability is similar for all four structures. The split enzymes are comparable in stability with their native analogues, meaning that they can be used for further biotechnology applications. Also, the tertiary structures of the two peroxidases are similar. However, differences that might help in choosing one system over another for biotechnology applications were noticed. The main difference between the two systems is glycosylation which is not present in the case of APX/sAPEX2, while it has a high impact on the HRP/sHRP stability. Further differences are calcium ions and cysteine bridges that are present only in the case of HRP/sHRP. Finally, computational results identified sAPEX2 as the systems with the smallest structural variations during molecular dynamics simulations showing its dominant stability comparing to other simulated proteins. Taken all together, the sAPEX2 system has a high potential for biotechnological applications due to the lack of glycans and cysteines, as well as due to high stability.

Free energy landscape of the PI3Kα C-terminal activation

The gene PIK3CA, encoding the catalytic subunit p110α of PI3Kα, is the second most frequently mutated gene in cancer, with the highest frequency oncogenic mutants occurring in the C-terminus of the kinase domain. The C-terminus has a dual function in regulating the kinase, playing a putative auto-inhibitory role for kinase activity and being absolutely essential for binding to the cell membrane. However, the molecular mechanisms by which these C-terminal oncogenic mutations cause PI3Kα overactivation remain unclear. To understand how a spectrum of C-terminal mutations of PI3Kα alter kinase activity compared to the WT, we perform unbiased and biased Molecular Dynamics simulations of several C-terminal mutants and report the free energy landscapes for the C-terminal "closed-to-open" transition in the WT, H1047R, G1049R, M1043L and N1068KLKR mutants. Results are consistent with HDX-MS experimental data and provide a molecular explanation why H1047R and G1049R reorient the C-terminus with a different mechanism compared to the WT and M1043L and N1068KLKR mutants. Moreover, we show that in the H1047R mutant, the cavity, where the allosteric ligands STX-478 and RLY-2608 bind, is more accessible contrary to the WT. This study provides insights into the molecular mechanisms underlying activation of oncogenic PI3Kα by C-terminal mutations and represents a valuable resource for continued efforts in the development of mutant selective inhibitors as therapeutics.

DeepSP: Deep learning-based spatial properties to predict monoclonal antibody stability

Therapeutic antibody development faces challenges due to high viscosities and aggregation tendencies. The spatial charge map (SCM) and spatial aggregation propensity (SAP) are computational techniques that aid in predicting viscosity and aggregation, respectively. These methods rely on structural data derived from molecular dynamics (MD) simulations, which are computationally demanding. DeepSCM, a deep learning surrogate model based on sequence information to predict SCM, was recently developed to screen high-concentration antibody viscosity. This study further utilized a dataset of 20,530 antibody sequences to train a convolutional neural network deep learning surrogate model called Deep Spatial Properties (DeepSP). DeepSP directly predicts SAP and SCM scores in different domains of antibody variable regions based solely on their sequences without performing MD simulations. The linear correlation coefficient between DeepSP scores and MD-derived scores for 30 properties achieved values between 0.76 and 0.96 with an average of 0.87. DeepSP descriptors were employed as features to build machine learning models to predict the aggregation rate of 21 antibodies, and the performance is similar to the results obtained from the previous study using MD simulations. This result demonstrates that the DeepSP approach significantly reduces the computational time required compared to MD simulations. The DeepSP model enables the rapid generation of 30 structural properties that can also be used as features in other research to train machine learning models for predicting various antibody stability using sequences only. DeepSP is freely available as an online tool via https://deepspwebapp.onrender.com and the codes and parameters are freely available at https://github.com/Lailabcode/DeepSP.

Phosphopeptide binding to the N-SH2 domain of tyrosine phosphatase SHP2 correlates with the unzipping of its central β-sheet

SHP2 is a tyrosine phosphatase that plays a regulatory role in multiple intracellular signaling cascades and is known to be oncogenic in certain contexts. In the absence of effectors, SHP2 adopts an autoinhibited conformation with its N-SH2 domain blocking the active site. Given the key role of N-SH2 in regulating SHP2, this domain has been extensively studied, often by X-ray crystallography. Using a combination of structural analyses and molecular dynamics (MD) simulations we show that the crystallographic environment can significantly influence the structure of the isolated N-SH2 domain, resulting in misleading interpretations. As an orthogonal method to X-ray crystallography, we use a combination of NMR spectroscopy and MD simulations to accurately determine the conformation of apo N-SH2 in solution. In contrast to earlier reports based on crystallographic data, our results indicate that apo N-SH2 in solution primarily adopts a conformation with a fully zipped central β-sheet, and that partial unzipping of this β-sheet is promoted by binding of either phosphopeptides or even phosphate/sulfate ions.

Isomer-sourced structure iteration methods for in silico development of inhibitors: Inducing GTP-bound NRAS-Q61 oncogenic mutations to an "off-like" state

The NRAS-mutant subset of melanoma represent some of the most aggressive and deadliest types associated with poor overall survival. Unfortunately, for more than 40 years, no therapeutic agent directly targeting NRAS mutations has been clinically approved. In this work, based on microsecond scale molecular dynamics simulations, the effect of Q61 mutations on NRAS conformational characteristics is revealed at the atomic level. The GTP-bound NRAS-Q61R and Q61K mutations show a specific targetable pocket between Switch-II and α-helix 3 whereas the NRAS-Q61L non-polar mutation category shows a different targetable pocket. Moreover, a new isomer-sourced structure iteration method has been developed for the in silico design of potential inhibitor prototypes for oncogenes. We show the possibility of a designed prototype HM-387 to target activated NRAS-Q61R and that it can gradually induce the transition from the activated NRAS-Q61R to an "off-like" state.

Discovering novel Cathepsin L inhibitors from natural products using artificial intelligence

Cathepsin L (CTSL) is a promising therapeutic target for metabolic disorders. Current pharmacological interventions targeting CTSL have demonstrated potential in reducing body weight gain, serum insulin levels, and improving glucose tolerance. However, the clinical application of CTSL inhibitors remains limited. In this study, we used a combination of artificial intelligence and experimental methods to identify new CTSL inhibitors from natural products. Through a robust deep learning model and molecular docking, we screened 150 molecules from natural products for experimental validation. At a concentration of 100 µM, we found that 36 of them exhibited more than 50 % inhibition of CTSL. Notably, 13 molecules displayed over 90 % inhibition and exhibiting concentration-dependent effects. The molecular dynamics simulation on the two most potent inhibitors, Plumbagin and Beta-Lapachone, demonstrated stable interaction at the CTSL active site. Enzyme kinetics studies have shown that these inhibitors exert an uncompetitive inhibitory effect on CTSL. In conclusion, our research identifies Plumbagin and Beta-Lapachone as potential CTSL inhibitors, offering promising candidates for the treatment of metabolic disorders and illustrating the effectiveness of artificial intelligence in drug discovery.

Unraveling the mechanism of carbonic anhydrase IX inhibition by alkaloids from Ruta chalepensis: A synergistic analysis of in vitro and in silico data

Due to the pivotal role of carbonic anhydrase IX (CA IX) in pathological conditions, there's a pressing need for novel inhibitors to improve patient outcomes and clinical management. Herein, we investigated the inhibitory efficacy of six alkaloids from Ruta chalepensis against CA IX through in vitro inhibition assay and computational modeling. Skimmianine and maculosidine displayed significant inhibitory activity in vitro, with low IC50 values of 105.2 ± 3.2 and 295.7 ± 14.1 nM, respectively. Enzyme kinetics analyses revealed that skimmianine exhibited a mixed inhibition mode, contrasting with the noncompetitive inhibition mechanism observed for the reference drug (acetazolamide), as indicated by intersecting lines in the Lineweaver-Burk plots. The findings of docking calculations revealed that skimmianine and maculosidine exhibited extensive polar interactions with the enzyme. These alkaloids demonstrate substantial binding interactions and occupy identical binding site as acetazolamide, thereby enhancing their efficacy as inhibitors of CA IX. Utilizing a 100 ns molecular dynamics (MD) simulation, the dynamic interactions between isolated alkaloids and CA IX were intensively assessed. Analysis of diverse MD parameters revealed that skimmianine and maculosidine displayed consistent trajectories and notable energy stabilization during their interaction with CA IX. The findings of MM/PBSA analysis depicted the minimum binding free energy for skimmianine and maculosidine. In addition, the Potential Energy Landscape (PEL) analysis revealed distinct and stable conformational states for the CA IX-ligand complexes, with Skimmianine showing the most stable and lowest energy configuration. These computational findings align with experimental results, emphasizing the potential efficacy of skimmianine and maculosidine as inhibitors of CA IX.

Effects and risk assessment of halogenated bisphenol A derivatives on human follicle stimulating hormone receptor: An interdisciplinary study

Halogenated bisphenol A (BPA) derivatives are produced during disinfection treatment of drinking water or are synthesized as flame retardants (TCBPA or TBBPA). BPA is considered as an endocrine disruptor especially on human follicle-stimulating hormone receptor (FSHR). Using a global experimental approach, we assessed the effect of halogenated BPA derivatives on FSHR activity and estimated the risk of halogenated BPA derivatives to the reproductive health of exposed populations. For the first time, we show that FSHR binds halogenated BPA derivatives, at 10 nM, a concentration lower than those requires to modulate the activity of nuclear receptors and/or steroidogenesis enzymes. Indeed, bioluminescence assays show that FSHR response is lowered up to 42.36 % in the presence of BPA, up to 32.79 % by chlorinated BPA derivatives and up to 27.04 % by brominated BPA derivatives, at non-cytotoxic concentrations and without modification of basal receptor activity. Moreover, molecular docking, molecular dynamics simulations, and site-directed mutagenesis experiments demonstrate that the halogenated BPA derivatives bind the FSHR transmembrane domain reducing the signal transduction efficiency which lowers the cellular cAMP production and in fine disrupts the physiological effect of FSH. The potential reproductive health risk of exposed individuals was estimated by comparing urinary concentrations (through a collection of human biomonitoring data) with the lowest effective concentrations derived from in vitro cell assays. Our results suggest a potentially high concern for the risk of inhibition of the FSHR pathway. This global approach based on FSHR activity could enable the rapid characterization of the toxicity of halogenated BPA derivatives (or other compounds) and assess the associated risk of exposure to these halogenated BPA derivatives.

Structure based computational RNA design towards MafA transcriptional repressor implicated in multiple myeloma

Multiple myeloma is recognized as the second most common hematological cancer. MafA transcriptional repressor is an established mediator of myelomagenesis. While there are multitude of drugs available for targeting various effectors in multiple myeloma, current literature lacks a candidate RNA based MafA modulator. Thus, using the structure of MafA homodimer-consensus target DNA, a computational effort was implemented to design a novel RNA based chemical modulator against MafA. First, available MafA-consensus DNA structure was employed to generate an RNA library. This library was further subjected to global docking to select the most plausible RNA candidates, preferring to bind DNA binding region of MafA. Following global docking, MD-ready complexes that were prepared via local docking program, were subjected to 500 ns of MD simulations. First, each of these MD simulations were analyzed for relative binding free energy through MM-PBSA method, which pointed towards a strong RNA based MafA binder, RNA1. Second, through a detailed MD analysis, RNA1 was shown to prefer binding to a single monomer of the dimeric DNA binding domain of MafA using higher number of hydrophobic interactions compared with positive control MafA-DNA complex. At the final phase, a principal component analyses was conducted, which led us to identify the actual interaction region of RNA1 and MafA monomer. Overall, to our knowledge, this is the first computational study that presents an RNA molecule capable of potentially targeting MafA protein. Furthermore, limitations of our study together with possible future implications of RNA1 in multiple myeloma were also discussed.

Exploring ligands that target von Willebrand factor selectively under oxidizing conditions through docking and molecular dynamics simulations

The blood protein von Willebrand factor (VWF) is a large multimeric protein that, when activated, binds to blood platelets, tethering them to the site of vascular injury and initiating blood coagulation. This process is critical for the normal hemostatic response, but especially under inflammatory conditions, it is thought to be a major player in pathological thrombus formation. For this reason, VWF has been the target for the development of anti-thrombotic therapeutics. However, it is challenging to prevent pathological thrombus formation while still allowing normal physiological blood coagulation, as currently available anti-thrombotic therapeutics are known to cause unwanted bleeding, in particular intracranial hemorrhage. This work explores the possibility of inhibiting VWF selectively under the inflammatory conditions present during pathological thrombus formation. In particular, the A2 domain of VWF is known to inhibit the neighboring A1 domain from binding to the platelet surface receptor GpIbα, and this auto-inhibitory mechanism has been shown to be removed by oxidizing agents released during inflammation. Hence, finding drug molecules that bind at the interface between A1 and A2 only under oxidizing conditions could restore such an auto-inhibitory mechanism. Here, by using a combination of computational docking, molecular dynamics simulations, and free energy perturbation calculations, a ligand from the ZINC15 database was identified that binds at the A1A2 interface, with the interaction being stronger under oxidizing conditions. The results provide a framework for the discovery of drug molecules that bind to a protein selectively in the presence of inflammatory conditions.

Screening of protein-based inhibitors for the intracellular domain of epidermal growth factor receptor by directed evolution using the yeast Gγ recruitment system

Protein-based therapeutics, including antibodies and antibody-like-proteins, have increasingly attracted attention due to their high specificity compared to small-molecular drugs. The Gγ recruitment system, one of the in vivo yeast two-hybrid systems for detecting protein-protein interactions, has been previously developed using yeast signal transduction machinery. In this study, we modified the Gγ recruitment system to screen the protein mutants that efficiently bind to the intracellular domain of the epidermal growth factor receptor L858R mutant (cytoEGFRL858R). Using the modified platform, we performed in vivo directed evolution for growth factor receptor-bound protein 2 (Grb2) and its truncated variant containing only the Src-homology 2 (SH2) domain, successfully identifying several mutants that more strongly bound to cytoEGFRL858R than their parental proteins. Some of them contained novel beneficial mutations (F108Y and Q144H) and specifically bound to the recombinant cytosolic phosphorylated EGFR in vitro, highlighting the utility of the evolutionary platform.

Supramolecular complexes of GCAP1: implications for inherited retinal dystrophies

Guanylate Cyclase Activating Protein 1 (GCAP1) is a calcium sensor that regulates the enzymatic activity of retinal Guanylate Cyclase 1 (GC1) in photoreceptors in a Ca2+/Mg2+ dependent manner. While point mutations in GCAP1 have been associated with inherited retinal dystrophies (IRDs), their impact on protein dimerization or on the possible interaction with the potent GC1 inhibitor RD3 (retinal degeneration protein 3) has never been investigated. Here, we integrate exhaustive in silico investigations with biochemical assays to evaluate the effects of the p.(E111V) substitution, associated with a severe form of IRD, on GCAP1 homo- and hetero-dimerization, and demonstrate that wild type (WT) GCAP1 directly interacts with RD3. Although inducing constitutive activation in GC1, the E111V substitution only slightly affects the dimerization of GCAP1. Both WT- and E111V-GCAP1 are predominantly monomeric in the absence of the GC1 target, however E111V-GCAP1 shows a stronger tendency to be monomeric in the Ca2+-bound form, corresponding to GC1 inhibiting state. Reconstitution experiments performed in the co-presence of WT-GCAP1, E111V-GCAP1 and RD3 restored nearly physiological regulation of the GC1 enzymatic activity in terms of cGMP synthesis and Ca2+-sensitivity, suggesting new scenarios for biologics-mediated treatment of GCAP1-associated IRDs.

Grb2 Y160F mutant mimics the wild-type monomeric state dynamics and the monomer-dimer equilibrium

The Growth factor receptor-bound protein 2 (Grb2) participates in early signaling complexes and regulates tyrosine kinase-mediated signal transduction through a monomer-dimer equilibrium. Grb2 dimeric state inhibits signal transduction whereas the monomer promotes signaling downstream. Since Grb2 dimer KD is ∼0.8 μM, studies focused on the monomer are still challenging and require mutations or interaction with phosphotyrosine peptides. However, these mutants were never characterized considering their effects on protein structure and dynamics in solution. Here, we present the biophysical characterization of Grb2Y160F, the first Grb2 mutant to induce protein monomerization without disrupting its native behavior in solution due to net charge modifications or interaction with peptides. We also identified that Grb2Y160F exists in a monomer-dimer equilibrium. Grb2Y160F ability to dimerize implies that different dimerization interfaces might regulate signaling pathways in distinct ways and raises an important question about the role of the Y160 residue in other dimerization interfaces.

Molecular motion behaviors of starch affect starch-polyphenol inclusion complex and digestibility among different stilbenes polyphenol structures

Starch-polyphenol V-type inclusion complex has become a hot topic due to its anti-digestibility and nutritional function. This paper aimed to explore the molecular motion behavior of starch affects starch-polyphenol inclusion complex and digestibility among different stilbene polyphenol structures (resveratrol (RA), pterostilbene (PB) and polydatin (PD) via the high-pressure homogenization (HPH) and heat moisture treatment (HMT) processes), which represented the fully extended and limited molecular motion behavior of starch, respectively. These results revealed distinct trends in complex formation among different stilbenes polyphenol structures, highlighting RA as particularly conducive to increasing single helix and V-type crystalline structures with the highest resistant starch (RS) content of 28.11 % due to its smaller steric hindrance. Novelty, in HPH environments with extended molecular motion behavior, the steric hindrance and hydrophobicity/CH-π interactions of polyphenols influence complex formation in the order of RA > PB > PD. Conversely, in HMT systems with limited molecular motion behavior, the limited movement of molecules emphasized the importance of hydrogen bond interactions between polyphenols and starch. Thus, the glucoside in PD enhanced its interaction with starch compared to methoxy-modified PB, leading to increased formation of inclusion complex with RS content of 18.61 %. Overall, these findings deepen the understanding of starch-polyphenol interactions.

Conformational dynamics and ribosomal interactions of Bacillus subtilis Obg in various nucleotide-bound states: Insights from molecular dynamics simulation

Obg, a GTPase, binds to the premature 50S ribosomal subunit and facilitates recruitment of rproteins and rRNA processing to form the mature 50S subunit. This binding depends on nucleotide-induced conformational changes (GDP/GTP). However, the mechanism by which Obg undergoes conformational changes to associate with the premature 50S subunit is unknown. Therefore, 1000 ns molecular dynamics simulations were conducted to investigate this mechanism. Visualization of the simulated trajectory showed that in GDP and GTP-bound states, the C-domain moved towards the SwI region, while in GTP-Mg2+ and ppGpp-bound states, the C-domain shifted towards the N-tails. Further, positioning these conformations of Obg on the 50S subunit suggests possible mechanisms by which the GTP-Mg2+ bound state is responsible for recruiting rprotein, as well as the impact of the absence of Mg2+ in the GTP-bound state. Furthermore, the study provides insights into the conformational changes that may lead to the dissociation of the GDP-bound state from the 50S subunit and explores the potential role of the ppGpp-bound state in inhibiting 70S ribosome formation. Additionally, RMSF and community network analyses reveal how internal dynamics and intricate connections within Obg affect C-domain motion.

Molecular Basis of MC1R Activation: Mutation-Induced Alterations in Structural Dynamics

The MC1R protein is a receptor found in melanocytes that plays a role in melanin synthesis. Mutations in this protein can impact hair color, skin tone, tanning ability, and increase the risk of skin cancer. The MC1R protein is activated by the alpha-melanocyte-stimulating hormone (α-MSH). Previous studies have shown that mutations affect the interaction between MC1R and α-MSH; however, the mechanism behind this process is poorly understood. Our study aims to shed light on this mechanism using molecular dynamics (MD) simulations to analyze the Asp84Glu and Asp294His variants. We simulated both the wild-type (WT) protein and the mutants with and without ligand. Our results reveal that mutations induce unique conformations during state transitions, hindering the switch between active and inactive states and decreasing cellular levels of cAMP. Interestingly, Asp294His showed increased ligand affinity but decreased protein activity, highlighting that tighter binding does not always lead to increased activation. Our study provides insights into the molecular mechanisms underlying the impact of MC1R mutations on protein activity.

Yop1 stability and membrane curvature generation propensity are controlled by its oligomerisation interface

The DP1 family of integral membrane proteins stabilize high membrane curvature in the endoplasmic reticulum and phagophores. Mutations in the human DP1 gene REEP1 are associated with Hereditary Spastic Paraplegia type 31 and distal hereditary motor neuropathy. Four missense mutations map to a putative dimerization interface but the impact of these mutations on DP1 structure and tubule formation are unknown. Combining biophysical measurements, functional assays, and computational modeling in the context of the model protein Yop1, we found that missense mutations have variable effects on DP1 dimer structure and in vitro tubulation activity, and provide mechanistic insights into the role of DP1 oligomerisation on membrane curvature stabilization. Whereas the mutations P71L and S75F decreased dimer homogeneity and led to polydisperse oligomerization and impaired membrane curving activity, A72E introduced new polar interactions between subunits that stabilized the Yop1 dimer and allowed robust tubule formation but prevented formation of more highly-curved lipoprotein particles (LPP). The introduction of a BRIL domain to the cytoplasmic loop of A72E rescued LPP formation, consistent with a requirement for dimer splaying in highly curved membranes. These results suggest that the membrane curving activity of DP1 proteins requires both dimer stability and conformational plasticity at the intermolecular interface.

Charge Scaling in Classical Force Fields for Lithium Ions in Polymers

Polymer electrolytes are of interest for applications in energy storage. Molecular simulations of ion transport in polymer electrolytes have been widely used to study the conductivity in these materials. Such simulations have generally relied on classical force fields. A peculiar feature of such force fields has been that in the particular case of lithium ions (Li+), their charge must be scaled down by approximately 20% to achieve agreement with experimental measurements of ion diffusivity. In this work, we present first-principles calculations that serve to justify the charge-scaling factor and van der Waals interaction parameters for Li+ diffusion in poly(ethylene glycol) (PEO) with bistriflimide (TFSI-) counterions. Our results indicate that a scaling factor of 0.79 provides good agreement with DFT calculations over a relatively wide range of Li+ concentrations and temperatures, consistent with past reports where that factor was adjusted by trial and error. We also show that such a scaling factor leads to diffusivities that are in quantitative agreement with experimental measurements.

Structure and Dynamics of the CCCH-Type Tandem Zinc Finger Domain of POS-1 and Implications for RNA Binding Specificity

CCCH-type tandem zinc finger (TZF) motifs are found in many RNA-binding proteins involved in regulating mRNA stability, translation, and splicing. In Caenorhabditis elegans, several RNA-binding proteins that regulate embryonic development and cell fate determination contain CCCH TZF domains, including POS-1. Previous biochemical studies have shown that despite high levels of sequence conservation, POS-1 recognizes a broader set of RNA sequences compared to the human homologue tristetraprolin. However, the molecular basis of these differences remains unknown. In this study, we refined the consensus RNA sequence and determined the differing binding specificities of the two zinc fingers of POS-1. We also determined the solution structure and characterized the internal dynamics of the TZF domain of POS-1. From the structure, we identified unique features that define the RNA binding specificity of POS-1. We also observed that the TZF domain of POS-1 is in equilibrium between interconverting conformations. Transitions between these conformations require internal motions involving many residues with correlated dynamics in each ZF. We propose that the correlated dynamics are necessary to allow allosteric communication between the nucleotide-binding pockets observed in the N-terminal ZF. Our study shows that both the structure and conformational plasticity of POS-1 are important in ensuring recognition of its RNA binding targets.

Small Molecule NS11021 Promotes BK Channel Activation by Increasing Inner Pore Hydration

The Ca2+ and voltage-gated big potassium (BK) channels are implicated in various diseases, including heart disease, asthma, epilepsy, and cancer, but remain an elusive drug target. A class of negatively charged activators (NCAs) have been demonstrated to promote the activation of several potassium channels including BK channels by binding to the hydrophobic inner pore, yet the underlying molecular mechanism of action remains poorly understood. In this work, we analyze the binding mode and potential activation mechanism of a specific NCA named NS11021 using atomistic simulations. The results show that NS11021 binding to the pore in deactivated BK channels is nonspecific and dynamic. The binding free energy of -8.3 ± 0.7 kcal/mol (KD = 0.3-3.1 μM) calculated using umbrella sampling agrees quantitatively with the experimental EC50 range of 0.4-2.1 μM. The bound NS11021 remains dynamic and is distal from the filter to significantly impact its conformation. Instead, NS11021 binding significantly enhances the pore hydration due to the charged tetrazol-phenyl group, thereby promoting the opening of the hydrophobic gate. We further show that the free energy barrier to K+ permeation is reduced by ∼3 kcal/mol regardless of the binding pose, which could explain the ∼62-fold increase in the intrinsic opening of BK channels measured experimentally. Taken together, these results support the idea that the molecular mechanism of NS11021 derives from increasing the hydration level of the conformationally closed pore, which does not depend on specific binding and likely explains the ability of NCAs to activate multiple K+ channels.

Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots

Identifying druggable binding sites on proteins is an important and challenging problem, particularly for cryptic, allosteric binding sites that may not be obvious from X-ray, cryo-EM, or predicted structures. The Site-Identification by Ligand Competitive Saturation (SILCS) method accounts for the flexibility of the target protein using all-atom molecular simulations that include various small molecule solutes in aqueous solution. During the simulations, the combination of protein flexibility and comprehensive sampling of the water and solute spatial distributions can identify buried binding pockets absent in experimentally determined structures. Previously, we reported a method for leveraging the information in the SILCS sampling to identify binding sites (termed Hotspots) of small mono- or bicyclic compounds, a subset of which coincide with known binding sites of drug-like molecules. Here, we build on that physics-based approach and present a ML model for ranking the Hotspots according to the likelihood they can accommodate drug-like molecules (e.g., molecular weight >200 Da). In the independent validation set, which includes various enzymes and receptors, our model recalls 67% and 89% of experimentally validated ligand binding sites in the top 10 and 20 ranked Hotspots, respectively. Furthermore, we show that the model's output Decision Function is a useful metric to predict binding sites and their potential druggability in new targets. Given the utility the SILCS method for ligand discovery and optimization, the tools presented represent an important advancement in the identification of orthosteric and allosteric binding sites and the discovery of drug-like molecules targeting those sites.

Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules and targets, quantified as binding free energy. Among various estimation methods, alchemical transformation methods stand out for their theoretical rigor. Despite challenges in force field accuracy and sampling efficiency, advancements in algorithms, software, and hardware have increased the application of free energy perturbation (FEP) calculations in the pharmaceutical industry. Here, we review the practical applications of FEP in drug discovery projects since 2018, covering both ligand-centric and residue-centric transformations. We show that relative binding free energy calculations have steadily achieved chemical accuracy in real-world applications. In addition, we discuss alternative physics-based simulation methods and the incorporation of deep learning into free energy calculations.

Capturing Autoinhibited PDK1 Reveals the Linker's Regulatory Role, Informing Innovative Inhibitor Design

PDK1 is crucial for PI3K/AKT/mTOR and Ras/MAPK cancer signaling. It phosphorylates AKT in a PIP3-dependent but S6K, SGK, and RSK kinases in a PIP3-independent manner. Unlike its substrates, its autoinhibited monomeric state has been unclear, likely due to its low population time, and phosphorylation in the absence of PIP3 has been puzzling too. Here, guided by experimental data, we constructed models and performed all-atom molecular dynamics simulations. In the autoinhibited PDK1 conformation that resembles autoinhibited AKT, binding of the linker between the kinase and PH domains to the PIF-binding pocket promotes the formation of the Glu130-Lys111 salt bridge and weakens the association of the kinase domain with the PH domain, shifting the population from the autoinhibited state to states accessible to the membrane and its kinase substrates. The interaction of the substrates' hydrophobic motif and the PDK1 PIF-binding pocket facilitates the release of the autoinhibition even in the absence of PIP3. Phosphorylation of the serine-rich motif within the linker further attenuates the association of the PH domain with the kinase domain. These suggest that while the monomeric autoinhibited state is relatively stable, it can readily shift to its active, catalysis-prone state to phosphorylate its diverse substrates. Our findings reveal the PDK1 activation mechanism and discover the regulatory role of PDK1's linker, which lead to two innovative linker-based inhibitor strategies: (i) locking the autoinhibited PDK1 through optimization of the interactions of AKT inhibitors with the PH domain of PDK1 and (ii) analogs (small molecules or peptidomimetics) that mimic the linker interactions with the PIF-binding pocket.

Cosolvent Molecular Dynamics Applied to DPP4, DPP8 and DPP9: Reproduction of Important Binding Features and Use in Inhibitor Design

We present our efforts in computational drug design against dipeptidyl peptidase 4 (DPP4), DPP8 and DPP9. We applied cosolvent molecular dynamics (MD) simulations to these three protein targets of interest. Our primary motivation is the growing interest in DPP8 and DPP9 as emerging drug targets. Due to the high similarity between DPP4, DPP8 and DPP9, DPP4 was also included in these analyses. The cosolvent molecular dynamics simulations reproduce key ligand binding features and known binding pockets, while also highlighting interesting fragment positions for future ligand optimization. The resulting fragment maps from the cosolvent molecular dynamics are freely available for use in future research (https://github.com/UAMC-Olivier/DPP489_cosolvent_MD/). Detailed instructions for easy visualization of the fragment maps are provided, ensuring that the results are usable by both computational and medicinal chemists. Additionally, we used the fragment maps to search for the binding pockets with significant potential using an algorithmic approach combining top fragment locations. To discover novel binding scaffolds, a limited pharmacophore screening was performed, where the pharmacophores were based on the analyses of the cosolvent simulations. Unfortunately, inhibitory potencies were in the higher micromolar range, but we optimized the resulting scaffolds in silico using relative binding free energy calculations for future inhibitor design and synthesis.

Clustering of RNA Polymerase II C-Terminal Domain Models upon Phosphorylation

RNA polymerase II (Pol II) C-terminal domain (CTD) is known to have crucial roles in regulating transcription. CTD has also been highly recognized for undergoing phase separation, which is further associated with its regulatory functions. However, the molecular interactions that the CTD forms to induce clustering to drive phase separations and how the phosphorylation of the CTD affects clustering are not entirely known. In this work, we studied the concentrated solutions of two heptapeptide repeat (2CTD) models at different phosphorylation patterns and protein and ion concentrations using all-atom molecular dynamics simulations to investigate clustering behavior and molecular interactions driving the cluster formation. Our results show that salt concentration and phosphorylation patterns play an important role in determining the clustering pattern, specifically at low protein concentrations. The balance between inter- and intrapeptide interactions and counterion coordination together impact the clustering behavior upon phosphorylation.

Formation of atmospheric molecular clusters containing nitric acid with ammonia, methylamine, and dimethylamine

This study investigates the formation of atmospheric molecular clusters containing ammonia (NH3, A), methylamine (CH3NH2, MA), or dimethylamine (CH3NHCH3, DMA) with nitric acid (HNO3, NA) using quantum mechanics. The Atmospheric Cluster Dynamic Code (ACDC) was employed to simulate the total evaporation rate, formation rate, and growth pathways of three types of clusters under dry and hydrated conditions. This study evaluates the enhancing potential of A/MA/DMA for NA-based new particle formation (NPF) at parts per trillion (ppt) levels. The results indicate that A/MA/DMA can enhance NA-based NPF at high nitric acid concentrations and low temperatures in the atmosphere. The enhancing potential of MA is weaker than that of DMA but stronger than that of A. Cluster growth predominantly follows the lowest free energy pathways on the acid-base grid, with the formation of initial acid-base dimers (NA)(A), (NA)(MA), and (NA)(DMA) being crucial. Hydration influences the evaporation rate and formation rate of clusters, especially for initial clusters. When the humidity is at 100%, the formation rate for NA-A, NA-MA, and NA-DMA clusters can increase by approximately 109, 107, and 104-fold compared to the corresponding unhydrated clusters, respectively. These results highlight the significance of nitric acid nucleation in NPF events in low-temperature, high-humidity atmospheres, particularly in regions like China with significant automobile exhaust pollution.

The critical role of aromatic residues in the binding of the SARS-CoV-2 fusion peptide to phospholipid bilayer membranes

Based on the SARS-CoV-2 fusion peptide (FP) structure determined from the NMR experiment, we created six FP models under different environmental conditions to explore the effects of salt and cholesterol on FP-membrane binding. The all-atom molecular dynamics (MD) simulation results indicated that ionic environments notably impact the FP structure as well as the stability of the helical elements within the peptide. Our findings highlighted the unpredictable influence of ions on the secondary structures and dynamics of the FP, emphasizing the complexity and sensitivity of the peptide's conformations to ionic conditions. When exploring the peptide's interaction with a cholesterol-free phospholipid bilayer membrane, we found that the helical elements of the FP remain stable irrespective of the salt type (Na+ or Ca2+). This result emphasizes the crucial role of phospholipid bilayer membranes in supporting the secondary structures of the FP. The MD simulation results showed that Ca2+ ions facilitated deeper membrane penetration than Na+ ions, highlighting the critical role of calcium ions in the FP-membrane binding. Our study indicates the essential role of the aromatic residues (such as Phe833 and Tyr837) in the FP-membrane binding process. Finally, we investigated the FP-membrane binding patterns in the presence of cholesterol. The MD simulation results demonstrated that the coupling of Ca2+ ions and cholesterol would also benefit the FP-membrane binding. Furthermore, our findings reveal that while the type of ion and cholesterol content exert varied and unpredictable influences on FP-membrane binding patterns, aromatic residues like tyrosine (Tyr) and phenylalanine (Phe) play an essential role in FP-membrane binding. In particular, deep mutational scanning (DMS) experiments have confirmed that mutating phenylalanine in the FP significantly decreases viral mutational fitness, emphasizing the pivotal role of phenylalanine residues in membrane fusion. This knowledge can aid in developing more effective therapeutic strategies targeting the viral fusion peptide and its key amino acids, ultimately contributing to developing treatments and vaccines against the virus.

Initiation of Medial Calcification: Revisiting Calcium Ion Binding to Elastin

Pathological calcification of elastin, a key connective tissue protein in the medial layers of blood vessels, starts with the binding of calcium ions. This Mini-Review focuses on understanding how calcium ions interact with elastin to initiate calcification at a molecular level, and emphasizes water's critical role in mediating this interaction. In the past decade, great strides have been made in understanding and modeling ion-specific hydration and its effects on biomolecule interactions. However, these advances have been largely absent from our understanding of elastin calcification. Historically, charge-neutral backbone carbonyls and negatively charged carboxyl groups have been proposed as elastin's calcium binding sites. Recently, tropoelastin's only four carboxyl groups have been identified as binding sites from classical molecular dynamics (MD). While carboxyl groups have a much higher affinity for binding calcium ions than backbone carbonyls, conflicting evidence persists for both functional group's importance in elastin calcification. This can be attributed to the fact that divalent ions strongly polarize water, leading to a hydration shell that shields electrostatic forces. The hydration shell surrounding both a calcium ion and either of the proposed binding sites must be displaced to enable binding. Providing our own extended X-ray absorption fine structure (EXAFS) data and complementary simulations, we discuss the potential structures of calcium binding in elastin and review prior knowledge regarding the relative importance of the two proposed binding sites.

Deciphering the Interdomain Coupling in a Gram-Negative Bacterial Membrane Insertase

YidC is a membrane protein that plays an important role in inserting newly generated proteins into lipid membranes. The Sec-dependent complex is responsible for inserting proteins into the lipid bilayer in bacteria. YidC facilitates the insertion and folding of membrane proteins, both in conjunction with the Sec complex and independently. Additionally, YidC acts as a chaperone during the folding of proteins. Multiple investigations have conclusively shown that Gram-positive bacterial YidC has Sec-independent insertion mechanisms. Through the use of microsecond-level all-atom molecular dynamics (MD) simulations, we have carried out an in-depth investigation of the YidC protein originating from Gram-negative bacteria. This research sheds light on the significance of multiple domains of the YidC structure at a detailed molecular level by utilizing equilibrium MD simulations. Specifically, multiple models of YidC embedded in the lipid bilayer were constructed to characterize the critical role of the C2 loop and the periplasmic domain (PD) present in Gram-negative YidC, which is absent in its Gram-positive counterpart. Based on our results, the C2 loop plays a role in the overall stabilization of the protein, most notably in the transmembrane (TM) region, and it also has an allosteric influence on the PD region. We have found critical inter- and intradomain interactions that contribute to the stability of the protein and its function. Finally, our study provides a hypothetical Sec-independent insertion mechanism for Gram-negative bacterial YidC.

Multidomain Protein-Urea Interactions: Differences in Binding Behavior Lead to Different Destabilization Tendencies for Monoclonal Antibodies

We study the influence of urea on the stability of monoclonal antibodies (mAbs) using molecular dynamics (MD) simulations in combination with differential scanning fluorimetry (DSF). We show that a denaturing cosolute such as urea binds strongly to the protein, which can lead to denaturation and enhanced aggregation behavior at high temperatures. The interaction between protein and urea crucially depends on the surface properties of the individual mAb domains and therefore affects the general binding to the protein differently. The study of these mechanisms for proteins with multiple domains, such as mAbs, encounters significant limitations in experimental analysis methods due to their complexity. Using computational and experimental methods, we are able to separate the protein-urea interaction by domain and show that Lennard-Jones interactions are mainly responsible for significant binding effects. Our results emphasize the potential of MD simulations in combination with Kirkwood-Buff theory to study the interactions between proteins with multiple domains and cosolutes as formulation excipients for drug discovery and development.

Understanding Antimicrobial Peptide Synergy: Differential Binding Interactions and Their Impact on Membrane Integrity

Research on antimicrobial peptides (AMPs) has been conducted as a solution to overcome antibiotic resistance. In particular, the synergistic effect that appears when two or more AMPs are used in combination has been observed. To find an effective synergistic combination, it is necessary to understand the underlying mechanism. However, a consistent explanation for this phenomenon has not yet been provided due to limitations in experimentally determining or predicting the structure of the heteroaggregates formed by the interactions between different AMPs and the interaction of the aggregate surface with the lipid membrane surface. In this study, we conducted molecular dynamics simulations for two heterogeneous aggregates of melittin-indolicidin and pexiganan-indolicidin to observe their structures in the solution phase and their interactions with the lipid membrane. We aimed to determine how the surfaces of these aggregates interact with the lipid membrane. Due to the different amino acid residue sequence characteristics of melittin and pexiganan, we found that when the two AMPs bind to indolicidin, they form aggregates with completely different structural characteristics. Accordingly, the sequence characteristics of pexiganan, which exhibits a relatively unstable structure compared to melittin in aqueous solution or on lipid membranes, allow for a more stable interaction with the lipid membrane when forming aggregates with indolicidin, effectively inhibiting the integrity of the lipid membranes. We also found that the amino acid residues forming the surface of the AMP aggregate show differential binding strengths to different lipid species forming the lipid membrane, thereby disrupting the membrane in a way that weakens its integrity. Through this, we provided insight into the basic principle of how the synergistic effect of AMPs occurs.

The Landscape of Osteocalcin Proteoforms Reveals Distinct Structural and Functional Roles of Its Carboxylation Sites

Human osteocalcin (OC) undergoes reversible, vitamin K-dependent γ-carboxylation at three glutamic acid residues, modulating its release from bones and its hormonal roles. A complete understanding of OC roles and structure-activity relationships is still lacking, as only uncarboxylated and few differently carboxylated variants have been considered so far. To fill this lack of knowledge, a comprehensive experimental and computational investigation of the structural properties and calcium-binding activity of all the OC variants is reported here. Such a comparative study indicates that the carboxylation sites are not equivalent and differently affect the OC structure and interaction with calcium, properties that are relevant for the modulation of OC functions. This study also discloses cooperative effects and provides structural and mechanistic interpretation. The disclosed peculiar features of each carboxylated proteoform strongly suggest that considering all eight possible OC variants in future studies may help rationalize some of the conflicting hypotheses observed in the literature.

Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning

Biomolecular simulations often suffer from the "time scale problem", hindering the study of rare events occurring over extended time scales. Enhanced sampling techniques aim to alleviate this issue by accelerating conformational transitions, yet they typically necessitate well-defined collective variables (CVs), posing a significant challenge. Machine learning offers promising solutions but typically requires rich training data encompassing the entire free energy surface (FES). In this work, we introduce an automated iterative pipeline designed to mitigate these limitations. Our protocol first utilizes a CV-free count-based adaptive sampling method to generate a data set rich in rare events. From this data set, slow modes are identified using Koopman-reweighted time-lagged independent component analysis (KTICA), which are subsequently leveraged by on-the-fly probability enhanced sampling (OPES) to efficiently explore the FES. The effectiveness of our pipeline is demonstrated and further compared with the common Markov State Model (MSM) approach on two model systems with increasing complexity: alanine dipeptide (Ala2) and deca-alanine (Ala10), underscoring its applicability across diverse biomolecular simulations.

Destabilisation of Alzheimer's amyloid-β protofibrils by Baicalein: mechanistic insights from all-atom molecular dynamics simulations

Alzheimer's disease (AD) is the most common form of dementia and the fifth leading cause of death globally. Aggregation and deposition of neurotoxic Aβ fibrils in the neural tissues of the brain is a key hallmark in AD pathogenesis. Destabilisation studies of the amyloid-peptide by various natural molecules are highly relevant due to their neuroprotective and therapeutic potential for AD. We performed molecular dynamics (MD) simulation to investigate the destabilisation mechanism of amyloidogenic protofilament intermediate by Baicalein (BCL), a naturally occurring flavonoid. We found that the BCL molecule formed strong hydrophobic contacts with non-polar residues, specifically F19, A21, V24, and I32 of Chain A and B of the pentameric protofibril. Upon binding, it competed with the native hydrophobic contacts of the Aβ protein. BCL loosened the tight packing of the hydrophobic core by disrupting the hydrogen bonds and the prominent D23-K28 inter-chain salt bridges of the protofibril. The decrease in the structural stability of Aβ protofibrils was confirmed by the increased RMSD, radius of gyration, solvent accessible surface area (SASA), and reduced β-sheet content. PCA indicated that the presence of the BCL molecule intensified protofibril motions, particularly affecting residues in Chain A and B regions. Our findings propose that BCL would be a potent destabiliser of Aβ protofilament, and may be considered as a therapeutic agent in treating AD.

Conformational Selection of α-Synuclein Tetramers at Biological Interfaces

Controlling the polymorphic assemblies of α-synuclein (αS) oligomers is crucial to reroute toxic protein aggregation implicated in Parkinson's disease (PD). One potential mediator is the interaction of αS tetramers with cell membranes, which may regulate the dynamic balance between aggregation-prone disordered monomers and aggregation-resistant helical tetramers. Here, we model diverse tetramer-cell interactions and compare the structure-function relations at the supramolecular-biological interface with available experimental data. The models predict preferential interaction of compact αS tetramers with highly charged membrane surfaces, which may further stabilize this aggregation-resistant conformer. On moderately charged membranes, extended structures are preferred. In addition to surface charge, curvature influences tetramer thermodynamic stability and aggregation, with potential for selective isolation of tetramers via regio-specific interactions with strongly negatively charged micelles that screen further aggregation. Our modeling data set highlights diverse beneficial nano-bio interactions to redirect biomolecule assembly, supporting new therapeutic approaches for PD based on lipid-mediated conformational selection and inhibition.

Charge transfer characteristics in rhodopsin mimics during photoexcitation

To gain insights into the light-harvesting capabilities of the chromophores, it is essential to understand their molecular and electronic structures within their natural chemical or biological contexts. Rhodopsins display varied absorption characteristics due to the interaction between the chromophore retinal and its surrounding protein environments. In this study, we employed a quantum mechanics/molecular mechanics approach to examine a series of artificially designed rhodopsin mimics based on human cellular retinol acid binding protein 2 (hCRABP II). We elucidated the electron transfer within the all-trans protonated Schiff base upon light excitation, and our calculated absorption spectra show well consistency with the experimental result. Furthermore, the interaction mechanisms between the chromophore and the protein were investigated, and the relationship between the blueshifts and redshifts in the absorption spectra was analyzed. Our calculation demonstrates that the blueshifts and redshifts in the rhodopsin mimics correlate well with attractive (such as the hydrogen bonds or electrostatic interactions) and repulsive interactions (such as the steric effects) between the chromophore and the protein environment, respectively. These findings could provide hints for designing rhodopsin with absorption spectra at different wavelengths.

Molecular permeation through large pore channels: computational approaches and insights

Computational methods such as molecular dynamics (MD) have illuminated how single-atom ions permeate membrane channels and how selectivity among them is achieved. Much less is understood about molecular permeation through eukaryotic channels that mediate the flux of small molecules (e.g. connexins, pannexins, LRRC8s, CALHMs). Here we describe computational methods that have been profitably employed to explore the movements of molecules through wide pores, revealing mechanistic insights, guiding experiments, and suggesting testable hypotheses. This review illustrates MD techniques such as voltage-driven flux, potential of mean force, and mean first-passage-time calculations, as applied to molecular permeation through wide pores. These techniques have enabled detailed and quantitative modeling of molecular interactions and movement of permeants at the atomic level. We highlight novel contributors to the transit of molecules through these wide pathways. In particular, the flexibility and anisotropic nature of permeant molecules, coupled with the dynamics of pore-lining residues, lead to bespoke permeation dynamics. As more eukaryotic large-pore channel structures and functional data become available, these insights and approaches will be important for understanding the physical principles underlying molecular permeation and as guides for experimental design.

Inactivation induced by pathogenic Cav1.3 L-type Ca2+-channel variants enhances sensitivity for dihydropyridine Ca2+ channel blockers

BACKGROUND AND PURPOSE

Pathogenic gain-of-function mutations in Cav1.3 L-type voltage-gated Ca2+-channels (CACNA1D) cause neurodevelopmental disorders with or without endocrine symptoms. We aimed to confirm a pathogenic gain-of function phenotype of CACNA1D de novo missense mutations A749T and L271H, and investigated the molecular mechanism causing their enhanced sensitivity for the Ca2+-channel blocker isradipine, a potential therapeutic for affected patients.

EXPERIMENTAL APPROACH

Wildtype and mutant channels were expressed in tsA-201 cells and their gating analysed using whole-cell and single-channel patch-clamp recordings. The voltage-dependence of isradipine action was quantified using protocols inducing variable fractions of inactivated channels. The molecular basis for altered channel gating in the mutants was investigated using in silico modelling and molecular dynamics simulations.

KEY RESULTS

Both mutations were confirmed pathogenic due to characteristic shifts of voltage-dependent activation and inactivation towards negative potentials (~20 mV). At negative holding potentials both mutations showed significantly higher isradipine sensitivity compared to wildtype. The affinity for wildtype and mutant channels increased with channel inactivation as predicted by the modulated receptor hypothesis (30- to 40-fold). The IC50 was indistinguishable for wildtype and mutants when >50% of channels were inactivated.

CONCLUSIONS AND IMPLICATIONS

Mutations A749T and L271H induce pathogenic gating changes. Like wildtype, isradipine inhibition is strongly voltage-dependent. Our data explains their apparent higher drug sensitivity at a given negative voltage by the availability of more inactivated channels due to their more negative inactivation voltage range. Low nanomolar isradipine concentrations will only inhibit Cav1.3 channels in neurons during prolonged depolarized states without selectivity for mutant channels.

Investigating the Mechanisms of Antibody Binding to Alpha-Synuclein for the Treatment of Parkinson's Disease

Parkinson's disease (PD) is an idiopathic neurodegenerative disorder with the second-highest prevalence rate behind Alzheimer's disease. The pathophysiological hallmarks of PD are both degeneration of dopaminergic neurons in the substantia nigra pars compacta and the inclusion of misfolded α-synuclein (α-syn) aggregates known as Lewy bodies. Despite decades of research for potential PD treatments, none have been developed, and developing new therapeutic agents is a time-consuming and expensive process. Computational methods can be used to investigate the properties of drug candidates currently undergoing clinical trials to determine their theoretical efficiency at targeting α-syn. Monoclonal antibodies (mAbs) are biological drugs with high specificity, and Prasinezumab (PRX002) is an mAb currently in Phase II, which targets the C-terminus (AA 118-126) of α-syn. We utilized BioLuminate and PyMol for the structure prediction and preparation of the fragment antigen-binding (Fab) region of PRX002 and 34 different conformations of α-syn. Protein-protein docking simulations were performed using PIPER, and 3 of the docking poses were selected based on the best fit. Molecular dynamics simulations were conducted on the docked protein structures in triplicate for 1000 ns, and hydrogen bonds and electrostatic and hydrophobic interactions were analyzed using MDAnalysis to determine which residues were interacting and how often. Hydrogen bonds were shown to form frequently between the HCDR2 region of PRX002 and α-syn. Free energy was calculated to determine the binding affinity. The predicted binding affinity shows a strong antibody-antigen attraction between PRX002 and α-syn. RMSD was calculated to determine the conformational change of these regions throughout the simulation. The mAb's developability was determined using computational screening methods. Our results demonstrate the efficiency and developability of this therapeutic agent.

Dy-SheHeRASADe: A representation of the β sheet dynamics through surface descriptors

Molecular dynamics (MD) simulations are important tools for studying the dynamic motions of macromolecules at the atomic level. With the increasing capabilities of high performance computing, MD simulations are becoming more widely used. This allows molecular modelers to simulate the molecular behavior of large molecular architectures for much longer trajectories. Appropriate visualization of MD trajectories is becoming essential to provide an immediate and intuitive understanding of a molecule's dynamics and function. In this study, we implement a novel 3D graphical representation, Dynamical Sheets Helper for RepresentAtion of SurfAce Descriptors (Dy-SheHeRASADe), to visualize the β sheet secondary structures of proteins in the context of molecular dynamics. Dy-SheHeRASADe is developed in UnityMol, an open source molecular viewer and prototyping platform. We considered β sheet fluctuations and hydrogen bond formation during molecular dynamics simulations to characterize the parts of β sheets with large motions or with labile bonds. We propose two visualization modes based on a surface representation of the β sheets calculated according to the positions of the α carbons and the hydrogen bonds between the β strands. The volumetric mode, in which this surface is enclosed in a semi-transparent volume that represents the fluctuation zone of the sheet during dynamics. The heatmap mode, in which the surface is colored according to the amplitude values of the α carbons. In addition, we quantify the β sheet fluctuations by displaying the values of the largest and smallest movements of the β sheets, the surface area of the sheets, and the number of hydrogen bonds.

In silico vaccine design for Yersinia enterocolitica: A comprehensive approach to enhanced immunogenicity, efficacy and protection

Yersinia enterocolitica, a foodborne pathogen, has emerged as a significant public health concern due to its increased prevalence and multidrug resistance. This study employed reverse vaccinology to identify novel vaccine candidates against Y. enterocolitica through comprehensive in silico analyses. The core genome's conserved protein translocase subunit SecY was selected as the target, and potential B-cell, MHC class I, and MHC class II epitopes were mapped. 3B-cell epitopes, 3 MHCI and 11 MHCII epitopes were acquired. A multi-epitope vaccine construct was designed by incorporating the identified epitopes, TLR4 Agonist was used as adjuvants to enhance the immunogenic response. EAAAK, CPGPG and AYY linkers were used to form a vaccine construct, followed by extensive computational evaluations. The vaccine exhibited desirable physicochemical properties, stable secondary and tertiary structures as evaluated by PDBSum and trRosetta. Moreover, favorable interactions with the human Toll-like receptor 4 (TLR4) was observed by ClusPro. Population coverage analysis estimated the vaccine's applicability across 99.74 % in diverse populations. In addition, molecular dynamics simulations and normal mode analysis confirmed the vaccine's structural stability and dynamics in a simulated biological environment. Furthermore, codon optimization and in silico cloning facilitated the evaluation of the vaccine's expression potential in E. coli and pET-28a was used a recombinant plasmid. This study provides a promising foundation for the development of an efficacious vaccine against Y. enterocolitica infections.

Structural analysis of microtubule binding by minus-end targeting protein Spiral2

Microtubules (MTs) are dynamic cytoskeletal polymers that play a critical role in determining cell polarity and shape. In plant cells, acentrosomal MTs are localized on the cell surface and are referred to as cortical MTs. Cortical MTs nucleate in the cell cortex and detach from nucleation sites. The released MT filaments perform treadmilling, with the plus-ends of MTs polymerizing and the minus-ends depolymerizing. Minus-end targeting proteins, -TIPs, include Spiral2, which regulates the minus-end dynamics of acentrosomal MTs. Spiral2 accumulates autonomously at MT minus-ends and inhibits filament shrinkage, but the mechanism by which Spiral2 specifically recognizes minus-ends of MTs remains unknown. Here we describe the crystal structure of Spiral2's N-terminal MT-binding domain. The structural properties of this domain resemble those of the HEAT repeat structure of the tumor overexpressed gene (TOG) domain, but the number of HEAT repeats is different and the conformation is highly arched. Gel filtration and co-sedimentation analyses demonstrate that the domain binds preferentially to MT filaments rather than the tubulin dimer, and that the tubulin-binding mode of Spiral2 via the basic surface is similar to that of the TOG domain. We constructed an in silico model of the Spiral2-tubulin complex to identify residues that potentially recognize tubulin. Mutational analysis revealed that the key residues inferred in the model are involved in microtubule recognition, and provide insight into the mechanism by which end-targeting proteins stabilize MT ends.

Sensing steroid hormone 17α-hydroxypregnenolone by GPR56 enables protection from ferroptosis-induced liver injury

G protein-coupled receptors (GPCRs) mediate most cellular responses to hormones, neurotransmitters, and environmental stimulants. However, whether GPCRs participate in tissue homeostasis through ferroptosis remains unclear. Here we identify that GPR56/ADGRG1 renders cells resistant to ferroptosis and deficiency of GPR56 exacerbates ferroptosis-mediated liver injury induced by doxorubicin (DOX) or ischemia-reperfusion (IR). Mechanistically, GPR56 decreases the abundance of phospholipids containing free polyunsaturated fatty acids (PUFAs) by promoting endocytosis-lysosomal degradation of CD36. By screening a panel of steroid hormones, we identified that 17α-hydroxypregnenolone (17-OH PREG) acts as an agonist of GPR56 to antagonize ferroptosis and efficiently attenuates liver injury before or after insult. Moreover, disease-associated GPR56 mutants were unresponsive to 17-OH PREG activation and insufficient to defend against ferroptosis. Together, our findings uncover that 17-OH PREG-GPR56 axis-mediated signal transduction works as a new anti-ferroptotic pathway to maintain liver homeostasis, providing novel insights into the potential therapy for liver injury.

Structural Insight into Melatonin's Influence on the Conformation of Aβ42 Dimer Studied by Molecular Dynamics Simulation

The accumulation of amyloid-beta (Aβ) oligomers is recognized as a potential culprit in Alzheimer's disease (AD). Experimental studies show that melatonin, a hormone that mainly regulates circadian rhythm and sleep, can interact with Aβ peptides and disrupt the formation of oligomers. However, how melatonin inhibits the oligomerization of soluble Aβ is unclear. Here, by computational simulations, we investigate the effect of different levels of melatonin on the conformation of the Aβ42 dimer. We find that the conformation of the Aβ42 dimer is dependent on melatonin levels. When melatonin is absent, the dimer mainly forms a parallel β-sheet in the CHC region. When one melatonin molecule is present, the overall conformation of the dimer does not change much, but the N-terminal of the dimer tends to adopt antiparallel β-sheets. When two melatoinin molecules are present, the Aβ42 dimer exhibits significant structural change, especially in its central region, resulting in a more compact conformation, and forms parallel β-sheets in the C-terminal. This conformational difference induced by different levels of melatoinin can shed light on the protective role of melatonin.

Evolution of the conformational dynamics of the molecular chaperone Hsp90

Hsp90 is a molecular chaperone of central importance for protein homeostasis in the cytosol of eukaryotic cells, with key functional and structural traits conserved from yeast to man. During evolution, Hsp90 has gained additional functional importance, leading to an increased number of interacting co-chaperones and client proteins. Here, we show that the overall conformational transitions coupled to the ATPase cycle of Hsp90 are conserved from yeast to humans, but cycle timing as well as the dynamics are significantly altered. In contrast to yeast Hsp90, the human Hsp90 is characterized by broad ensembles of conformational states, irrespective of the absence or presence of ATP. The differences in the ATPase rate and conformational transitions between yeast and human Hsp90 are based on two residues in otherwise conserved structural elements that are involved in triggering structural changes in response to ATP binding. The exchange of these two mutations allows swapping of the ATPase rate and of the conformational transitions between human and yeast Hsp90. Our combined results show that Hsp90 evolved to a protein with increased conformational dynamics that populates ensembles of different states with strong preferences for the N-terminally open, client-accepting states.

An internal linker and pH biosensing by phosphatidylinositol 5-phosphate regulate the function of the ESCRT-0 component TOM1

Target of Myb1 (TOM1) facilitates the transport of endosomal ubiquitinated proteins destined for lysosomal degradation; however, the mechanisms regulating TOM1 during this process remain unknown. Here, we identified an adjacent DXXLL motif-containing region to the TOM1 VHS domain, which enhances its affinity for ubiquitin and can be modulated by phosphorylation. TOM1 is an endosomal phosphatidylinositol 5-phosphate (PtdIns5P) effector under Shigella flexneri infection. We pinpointed a consensus PtdIns5P-binding motif in the VHS domain. We show that PtdIns5P binding by TOM1 is pH-dependent, similarly observed in its binding partner TOLLIP. Under acidic conditions, TOM1 retained its complex formation with TOLLIP, but was unable to bind ubiquitin. S. flexneri infection inhibits pH-dependent endosomal maturation, leading to reduced protein degradation. We propose a model wherein pumping of H+ to the cytosolic side of endosomes contributes to the accumulation of TOM1, and possibly TOLLIP, at these sites, thereby promoting PtdIns5P- and pH-dependent signaling, facilitating bacterial survival.

Introductory Tutorials for Simulating Protein Dynamics with GROMACS

Atomistic molecular dynamics (MD) simulations have become an indispensable tool for investigating the structure, dynamics, and energetics of biomolecules. Continual optimization of software algorithms and hardware has enabled investigators to access biologically relevant time scales in feasible amounts of computing time. Given the widespread use and utility of MD simulations, there is considerable interest in learning essential skills in performing them. Here, we present a set of introductory tutorials for performing MD simulations of proteins in the popular, open-source GROMACS package. Three exercises are detailed, including simulating a single protein, setting up a protein complex, and performing umbrella sampling simulations to model the unfolding of a short polypeptide. Essential features and input settings are illustrated throughout. The purpose of these tutorials is to provide new users with a general understanding of foundational workflows, from which they can design their own simulations.

Ca2+-dependent lipid preferences shape synaptotagmin-1 C2A and C2B dynamics: Insights from experiments and simulations

Signal transmission between neurons requires exocytosis of neurotransmitters from the lumen of synaptic vesicles into the synaptic cleft. Following an influx of Ca2+, this process is facilitated by the Ca2+ sensor synaptotagmin-1. The underlying mechanisms involve electrostatic and hydrophobic interactions tuning the lipid preferences of the two C2 domains of synaptotagmin-1; however, the details are still controversially discussed. We, therefore, follow a multidisciplinary approach and characterize lipid and membrane binding of the isolated C2A and C2B domains. We first target interactions with individual lipid species, and then study interactions with model membranes of liposomes. Finally, we perform molecular dynamics simulations to unravel differences in membrane binding. We found that both C2 domains, as a response to Ca2+, insert into the lipid membrane; however, C2A adopts a more perpendicular orientation while C2B remains parallel. These findings allow us to propose a mechanism for synaptotagmin-1 during membrane fusion.

Structural Rearrangement of the AT1 Receptor Modulated by Membrane Thickness and Tension

Membrane-embedded mechanosensitive (MS) proteins, including ion channels and G-protein coupled receptors (GPCRs), are essential for the transduction of external mechanical stimuli into biological signals. The angiotensin II type 1 (AT1) receptor plays many important roles in cardiovascular regulation and is associated with diseases such as hypertension and congestive heart failure. The membrane-mediated activation of the AT1 receptor is not well understood, despite this being one of the most widely studied GPCRs within the context of biased agonism. Here, we use extensive molecular dynamics (MD) simulations to characterize the effect of the local membrane environment on the activation of the AT1 receptor. We show that membrane thickness plays an important role in the stability of active and inactive states of the receptor, as well as the dynamic interchange between states. Furthermore, our simulation results show that membrane tension is effective in driving large-scale structural changes in the inactive state such as the outward movement of transmembrane helix 6 to stabilize intermediate active-like conformations. We conclude by comparing our simulation observations with AlphaFold 2 predictions, as a proxy to experimental structures, to provide a framework for how membrane mediated stimuli can facilitate activation of the AT1 receptor through the β-arrestin signaling pathway.