CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data

Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures

The thermostable α-amylase derived from Bacillus licheniformis (BLA) has multiple advantages, including enhancing the mass transfer rate and by reducing microbial contamination in starch hydrolysis. Nonetheless, the application of BLA is constrained by the accessibility and stability of enzymes capable of achieving high conversion rates at elevated temperatures. Moreover, the thermotolerance of BLA requires further enhancement. Here, we developed a computational strategy for constructing small and smart mutant libraries to identify variants with enhanced thermostability. Initially, molecular dynamics (MD) simulations were employed to identify the regions with high flexibility. Subsequently, FoldX, a computational design predictor, was used to design mutants by rigidifying highly flexible residues, whereas the simultaneous decrease in folding free energy assisted in improving thermostability. Through the utilization of MD and FoldX, residues K251, T277, N278, K319, and E336, situated at a distance of 5 Å from the catalytic triad, were chosen for mutation. Seventeen mutants were identified and characterized by evaluating enzymatic characteristics and kinetic parameters. The catalytic efficiency of the E271L/N278K mutant reached 184.1 g L-1 s-1, which is 1.88-fold larger than the corresponding value determined for the WT. Furthermore, the most thermostable mutant, E336S, exhibited a 1.43-fold improvement in half-life at 95 ℃, compared with that of the WT. This study, by combining computational simulation with experimental verification, establishes that potential sites can be computationally predicted to increase the activity and stability of BLA and thus provide a possible strategy by which to guide protein design.

Far-red light-triggered cargo release from liposomes b ound to a photosensitizer-cellulose nanofiber hydrogel

In our research we used the anionic nanofibrillar cellulose (ANFC) as a platform for far-red light-induced release of cargo from liposomes. In contrast to previous works, where photosensitizers are usually in the liposomal bilayers, we used a cellulose-binding dye. Our phthalocyanine derivative has been shown to bind very strongly to cellulose and cellulose nanofiber hydrogels, allowing us to place it outside of the liposomes. Both the sensitizer and cationic liposomes bind strongly to the ANFC after mixing, making the system easy to fabricate. Upon light activation, the photosensitizer generates reactive oxygen species (ROS) within the ANFC hydrogel, where the reactive oxygen species oxidize unsaturated lipids in the liposomal membrane, which makes the liposomes more permeable, resulting in on-demand cargo release. We were able to achieve ca. 70 % release of model hydrophilic cargo molecule calcein from the hydrogels with a relatively low dose of light (262 J/cm2) while employing the straightforward fabrication techniques. Our system was remarkably responsive to the far-red light (730 nm), enabling deep tissue penetration. Therefore, this very promising novel cellulose-immobilized photosensitizer liposomal platform could be used as a controlled drug delivery system, which can have applications in externally activated coatings or implants.

Development, validation and analysis of a human profurin 3D model using comparative modeling and molecular dynamics simulations

The emergence of new viruses can lead to the outbreak of pandemics as occurred at the end of 2019 with the coronavirus disease (or COVID-19). The fastest way to effectively control viral infections is to develop broad-spectrum antivirals that can fight at least an entire class of viruses. Profurin, the furin precursor propeptide, is responsible for the autoactivation step which is crucial for the maturation of several viral substrates. This role makes the study of furin and profurin interactions interesting for the development of new potential broad-spectrum antivirals for the treatment against several human viral diseases. Since there is no 3D model of profurin published in the literature or deposited in a database, this work reports the development, validation and analysis of a profurin 3D model using comparative modeling and molecular dynamics. The model is available in ModelArchive at https://www.modelarchive.org/doi/10.5452/ma-ct8l7. The usage of this model will make possible further studies of molecular docking and MD simulations of the profurin-furin system, in the design of new potential broad-spectrum antivirals for the treatment against several human viral diseases.Communicated by Ramaswamy H. Sarma.

Differentiating stable and unstable protein using convolution neural network and molecular dynamics simulations

Protein stability is a critical aspect of molecular biology and biochemistry, hinges on an intricate balance of thermodynamic and structural factors. Determining protein stability is crucial for understanding and manipulating biological machineries, as it directly correlated with the protein function. Thus, this study delves into the intricacies of protein stability, highlighting its dependence on various factors, including thermodynamics, thermal conditions, and structural properties. Moreover, a notable focus is placed on the free energy change of unfolding (ΔGunfolding), change in heat capacity (ΔCp) with protein structural transition, melting temperature (Tm) and number of disulfide bonds, which are critical parameters in understanding protein stability. In this study, a machine learning (ML) predictive model was developed to estimate these four parameters using the primary sequence of the protein. The shortfall of available tools for protein stability prediction based on multiple parameters propelled the completion of this study. Convolutional Neural Network (CNN) with multiple layers was adopted to develop a more reliable ML model. Individual predictive models were prepared for each property, and all the prepared models showed results with high accuracy. The R2 (coefficient of determination) of these models were 0.79, 0.78, 0.92 and 0.92, respectively, for ΔG, ΔCp, Tm and disulfide bonds. A case study on stability analysis of two homologous proteins was presented to validate the results predicted through the developed model. The case study included in silico analysis of protein stability using molecular docking and molecular dynamic simulations. This validation study assured the accuracy of each model in predicting the stability associated properties. The alignment of physics-based principles with ML models has provided an opportunity to develop a fast machine learning solution to replace the computationally demanding physics-based calculations used to determine protein stability. Furthermore, this work provided valuable insights into the impact of mutation on protein stability, which has implications for the field of protein engineering. The source codes are available at https://github.com/Growdeatechnology.

Exploring the structural assembly of rice ADP-glucose pyrophosphorylase subunits using MD simulation

ADP-glucose pyrophosphorylase plays a pivotal role as an allosteric enzyme, essential for starch biosynthesis in plants. The higher plant AGPase comparises of a pair of large and a pair of small subunits to form a heterotetrameric complex. Growing evidence indicates that each subunit plays a distinct role in regulating the underlying mechanism of starch biosynthesis. In the rice genome, there are four large subunit genes (OsL1-L4) and three small subunit genes (OsS1, OsS2a, and OsS2b). While the structural assembly of cytosolic rice AGPase subunits (OsL2:OsS2b) has been elucidated, there is currently no such documented research available for plastidial rice AGPases (OsL1:OsS1). In this study, we employed protein modeling and MD simulation approaches to gain insights into the structural association of plastidial rice AGPase subunits. Our results demonstrate that the heterotetrameric association of OsL1:OsS1 is very similar to that of cytosolic OsL2:OsS2b and potato AGPase heterotetramer (StLS:StSS). Moreover, the yeast-two-hybrid results on OsL1:OsS1, which resemble StLS:StSS, suggest a differential protein assembly for OsL2:OsS2b. Thus, the regulatory and catalytic mechanisms for plastidial AGPases (OsL1:OsS1) could be different in rice culm and developing endosperm compared to those of OsL2:OsS2b, which are predominantly found in rice endosperm.

Structural and thermodynamic properties of conserved water molecules in Mpro native: A combined approach by MD simulation and Grid Inhomogeneous Solvation Theory

The new viral strains of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are continuously rising, becoming more virulent, and transmissible. Therefore, the development of new antiviral drugs is essential. Due to its significant role in the viral life cycle of SARS-CoV-2, the main protease (Mpro) enzyme is a leading target for antiviral drug design. The Mpro monomer consists of domain DI, DII, and DI-DII interface. Twenty-one conserved water molecules (W4-W24) are occupied at these domains according to multiple crystal structure analyses. The crystal and MD structures reveal the presence of eight conserved water sites in domain DI, DII and remaining in the DI-DII interface. Grid-based inhomogeneous fluid solvation theory (GIST) was employed on MD structures of Mpro native to predict structural and thermodynamic properties of each conserved water site for focusing to identify the specific conserved water molecules that can easily be displaced by proposed ligands. Finally, MD water W13 is emerged as a promising candidate for water mimic drug design due to its low mean interaction energy, loose binding character with the protein, and its involvement in a water-mediated H-bond with catalytic His41 via the interaction Thr25(OG)---W13---W---His41(NE2). In this context, water occupancy, relative interaction energy, entropy, and topologies of W13 are thermodynamically acceptable for the water displacement method. Therefore, the strategic use of W13's geometrical position in the DI domain may be implemented for drug discovery against COVID disease by designing new ligands with appropriately oriented chemical groups to mimic its structural, electronic, and thermodynamic properties.

Analysis of cholesterol-recognition motifs of the plasma membrane Ca2+-ATPase

The plasma membrane Ca2+-ATPase (PMCA) is crucial for the fine tuning of intracellular calcium levels in eukaryotic cells. In this study, we show the presence of CARC sequences in all human and rat PMCA isoforms and we performed further analysis by molecular dynamics simulations. This analysis focuses on PMCA1, containing three CARC motifs, and PMCA4, with four CARC domains. In PMCA1, two CARC motifs reside within transmembrane domains, while the third is situated at the intracellular interface. The simulations depict more stable RMSD values and lower RMSF fluctuations in the presence of cholesterol, emphasizing its potential stabilizing effect. In PMCA4, a distinct dynamic was found. Notably, the total energy differences between simulations with cholesterol and phospholipids are pronounced in PMCA4 compared to PMCA1. RMSD values for PMCA4 indicate a more energetically favorable conformation in the presence of cholesterol, suggesting a robust interaction between CARCs and this lipid in the membranes. Furthermore, RMSF analysis for CARCs in both PMCA isoforms exhibit lower values in the presence of cholesterol compared to POPC alone. The analysis of H-bond occupancy and total energy values strongly suggests the potential interaction of CARCs with cholesterol. Given the crucial role of PMCAs in physiological calcium regulation and their involvement in diverse pathological processes, this study underscores the significance of CARC motifs and their interaction with cholesterol in elucidating PMCA function. These insights into the energetic preferences associated with CARC-cholesterol interactions offer valuable implications for understanding PMCA function in maintaining calcium homeostasis and addressing potential associated pathologies.

Multiscale modeling of unfolding and bond dissociation of rubredoxin metalloprotein

Mechanical properties of proteins that have a crucial effect on their operation. This study used a molecular dynamics simulation package to investigate rubredoxin unfolding on the atomic scale. Different simulation techniques were applied, and due to the dissociation of covalent/hydrogen bonds, this protein demonstrates several intermediate states in force-extension behavior. A conceptual model based on the cohesive finite element method was developed to consider the intermediate damages that occur during unfolding. This model is based on force-displacement curves derived from molecular dynamics results. The proposed conceptual model is designed to accurately identify bond rupture points and determine the associated forces. This is achieved by conducting a thorough comparison between molecular dynamics and cohesive finite element results. The utilization of a viscoelastic cohesive zone model allows for the consideration of loading rate effects. This rate-dependent model can be further developed and integrated into the multiscale modeling of large assemblies of metalloproteins, providing a comprehensive understanding of mechanical behavior while maintaining a reduced computational cost.

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region's significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

Multi-targeted therapeutic potential of stigmasterol from the Euphorbia ammak plant in treating lung and breast cancer

Cancer is the most prevalent disease globally, which presents a significant challenge to the healthcare industry, with breast and lung cancer being predominant malignancies. This study used RNA-seq data from the TCGA database to identify potential biomarkers for lung and breast cancer. Tumor Necrosis Factor (TNFAIP8) and Sulfite Oxidase (SUOX) showed significant expression variation and were selected for further study using structure-based drug discovery (SBDD). Compounds derived from the Euphorbia ammak plant were selected for in-silico study with both TNFAIP8 and SUOX. Stigmasterol had the greatest binding scores (normalized scores of -8.53 kcal/mol and -9.69 kcal/mol) with both proteins, indicating strong stability in their binding pockets throughout the molecular dynamics' simulation. Although Stigmasterol first changed its initial conformation (RMSD = 0.5 nm with the starting conformation) in SUOX, it eventually reached a stable conformation (RMSD of 1.5 nm). The compound on TNFAIP8 showed a persistent shape (RMSD of 0.35 nm), indicating strong protein stability. The binding free energy of the complex was calculated using the MM/GBSA technique; TNFAIP8 had a ΔGTOTAL of -24.98 kcal/mol, with TYR160 being the most significant residue, contributing -2.52 kcal/mol. On the other hand, the SUOX complex had a binding free energy of -16.87 kcal/mol, with LEU151 being the primary contributor (-1.17 kcal/mol). Analysis of the complexes' free energy landscape unveiled several states with minimum free energy, indicating robust interactions between the protein and ligand. In its conclusion, this work emphasises the favourable ability of Stigmasterol to bind with prospective targets for lung and breast cancer, indicating the need for more experimental study.

AlPaCas: allele-specific CRISPR gene editing through a protospacer-adjacent-motif (PAM) approach

Gene therapy of dominantly inherited genetic diseases requires either the selective disruption of the mutant allele or the editing of the specific mutation. The CRISPR-Cas system holds great potential for the genetic correction of single nucleotide variants (SNVs), including dominant mutations. However, distinguishing between single-nucleotide variations in a pathogenic genomic context remains challenging. The presence of a PAM in the disease-causing allele can guide its precise targeting, preserving the functionality of the wild-type allele. The AlPaCas (Aligning Patients to Cas) webserver is an automated pipeline for sequence-based identification and structural analysis of SNV-derived PAMs that satisfy this demand. When provided with a gene/SNV input, AlPaCas can: (i) identify SNV-derived PAMs; (ii) provide a list of available Cas enzymes recognizing the SNV (s); (iii) propose mutational Cas-engineering to enhance the selectivity towards the SNV-derived PAM. With its ability to identify allele-specific genetic variants that can be targeted using already available or engineered Cas enzymes, AlPaCas is at the forefront of advancements in genome editing. AlPaCas is open to all users without a login requirement and is freely available at https://schubert.bio.uniroma1.it/alpacas.

Computational method for designing vaccines applied to virus-like particles (VLPs) as epitope carriers

Nonenveloped virus-like particles (VLPs) are self-assembled oligomeric structures composed of one or more proteins that originate from diverse viruses. Because these VLPs have similar antigenicity to the parental virus, they are successfully used as vaccines against cognate virus infection. Furthermore, after foreign antigenic sequences are inserted in their protein components (chimVLPs), some VLPs are also amenable to producing vaccines against pathogens other than the virus it originates from (these VLPs are named platform or epitope carrier). Designing chimVLP vaccines is challenging because the immunogenic response must be oriented against a given antigen without altering stimulant properties inherent to the VLP. An important step in this process is choosing the location of the sequence modifications because this must be performed without compromising the assembly and stability of the original VLP. Currently, many immunogenic data and computational tools can help guide the design of chimVLPs, thus reducing experimental costs and work. In this study, we analyze the structure of a novel VLP that originate from an insect virus and describe the putative regions of its three structural proteins amenable to insertion. For this purpose, we employed molecular dynamics (MD) simulations to assess chimVLP stability by comparing mutated and wild-type (WT) VLP protein trajectories. We applied this procedure to design a chimVLP that can serve as a prophylactic vaccine against the SARS-CoV-2 virus. The methodology described in this work is generally applicable for VLP-based vaccine development.

Py-CoMFA, docking, and molecular dynamics simulations of Leishmania (L.) amazonensis arginase inhibitors

Leishmaniasis is a disease caused by a protozoan of the genus Leishmania, affecting millions of people, mainly in tropical countries, due to poor social conditions and low economic development. First-line chemotherapeutic agents involve highly toxic pentavalent antimonials, while treatment failure is mainly due to the emergence of drug-resistant strains. Leishmania arginase (ARG) enzyme is vital in pathogenicity and contributes to a higher infection rate, thus representing a potential drug target. This study helps in designing ARG inhibitors for the treatment of leishmaniasis. Py-CoMFA (3D-QSAR) models were constructed using 34 inhibitors from different chemical classes against ARG from L. (L.) amazonensis (LaARG). The 3D-QSAR predictions showed an excellent correlation between experimental and calculated pIC50 values. The molecular docking study identified the favorable hydrophobicity contribution of phenyl and cyclohexyl groups as substituents in the enzyme allosteric site. Molecular dynamics simulations of selected protein-ligand complexes were conducted to understand derivatives' interaction modes and affinity in both active and allosteric sites. Two cinnamide compounds, 7g and 7k, were identified, with similar structures to the reference 4h allosteric site inhibitor. These compounds can guide the development of more effective arginase inhibitors as potential antileishmanial drugs.

ASM variants in the spotlight: A structure-based atlas for unraveling pathogenic mechanisms in lysosomal acid sphingomyelinase

Lysosomal acid sphingomyelinase (ASM), a critical enzyme in lipid metabolism encoded by the SMPD1 gene, plays a crucial role in sphingomyelin hydrolysis in lysosomes. ASM deficiency leads to acid sphingomyelinase deficiency, a rare genetic disorder with diverse clinical manifestations, and the protein can be found mutated in other diseases. We employed a structure-based framework to comprehensively understand the functional implications of ASM variants, integrating pathogenicity predictions with molecular insights derived from a molecular dynamics simulation in a lysosomal membrane environment. Our analysis, encompassing over 400 variants, establishes a structural atlas of missense variants of lysosomal ASM, associating mechanistic indicators with pathogenic potential. Our study highlights variants that influence structural stability or exert local and long-range effects at functional sites. To validate our predictions, we compared them to available experimental data on residual catalytic activity in 135 ASM variants. Notably, our findings also suggest applications of the resulting data for identifying cases suited for enzyme replacement therapy. This comprehensive approach enhances the understanding of ASM variants and provides valuable insights for potential therapeutic interventions.

Lanmodulin's EF 2-3 Domain: Insights from Infrared Spectroscopy and Simulations

Lanmodulins are small, ∼110-residue proteins with four EF-hand motifs that demonstrate a picomolar affinity for lanthanide ions, making them efficient in the recovery and separation of these technologically important metals. In this study, we examine the thermodynamic and structural complexities of lanthanide ion binding to a 41-residue domain, EF 2-3, that constitutes the two highest-affinity metal-binding sites in the lanmodulin protein from Methylorubrum extorquens. Using a combination of circular dichroism (CD) spectroscopy, isothermal titration calorimetry (ITC), two-dimensional infrared (2D IR) spectroscopy, and molecular dynamics (MD) simulations, we characterize the metal binding capabilities of EF 2-3. ITC demonstrates that binding occurs between peptide and lanthanides with conditional dissociation constants (Kd) in the range 20-30 μM, with no significant differences in the Kd values for La3+, Eu3+, and Tb3+ at pH 7.4. In addition, CD spectroscopy suggests that only one binding site of EF 2-3 undergoes a significant conformational change in the presence of lanthanides. 2D IR spectroscopy demonstrates the presence of both mono- and bidentate binding configurations in EF 2-3 with all three lanthanides. MD simulations, supported by Eu3+ luminescence measurements, explore these results, suggesting a competition between water-lanthanide and carboxylate-lanthanide interactions in the EF 2-3 domain. These results underscore the role of the core helical bundle of the protein architecture in influencing binding affinities and communication between the metal-binding sites in the full-length protein.

Critical assessment of popular biomolecular force fields for molecular dynamics simulations of folding and enzymatic activity of main protease of coronavirus SARS-CoV-2

The main cysteine protease (Mpro) of coronavirus SARS-CoV-2 has become a promising target for computational development in anti-COVID-19 treatments. Here, we benchmarked the performance of six biomolecular molecular dynamics (MD) force fields (OPLS-AA, CHARMM27, CHARMM36, AMBER03, AMBER14SB and GROMOS G54A7) and three water models (TIP3P, TIP4P and SPC) for reproducing the native fold and the enzymatic activity of Mpro as monomeric and dimeric units. The MD sampling up to 1 μs suggested that the proper choice of the force fields and water models plays an essential role in reproducing the tertiary structure and the inter-residue distance between the catalytic dyad His41-Cys145. We found that while most benchmarked all-atom force fields reproduce well the native fold of Mpro, the CHARMM27/TIP3P and OPLS-AA/TIP4P setups revealed a good performance in reproducing the structure of the catalytic domain. In addition, these FF setups were also well-adopted for MD sampling of Mpro at the physiologic conditions by mimicking the presence of 100 mM NaCl and the elevated temperature of 310 K. Finally, both FFs were also performed well in reproducing the native fold of Mpro in a dimeric form. Therefore, comparing the preservation of the native fold of Mpro and the stability of its catalytic site architecture, our MD benchmarking suggests that the OPLS-AA/TIP4P and CHARMM27/TIP3P MD setups at the physiologic conditions may be well-suited for rapid in silico screening and developing broad-spectrum anti-coronaviral therapeutic agents.

Significance of Zn2+ in RyR1 for Structural Integrity and Ligand Binding: Insight from Molecular Dynamics

Ryanodine receptor type 1 (RyR1) is a Ca2+-release channel central to skeletal muscle excitation-contraction (EC) coupling. RyR1's cryo-EM structures reveal a zinc-finger motif positioned within the cytoplasmic C-terminal domain (CTD). Yet, owing to limitations in cryo-EM resolution, RyR1 structures lack precision in detailing the metal coordination structure, prompting the need for an accurate model. In this study, we employed molecular dynamics (MD) simulations and the density functional theory (DFT) method to refine the binding characteristics of Zn2+ in the zinc-finger site of the RyR1 channel. Our findings also highlight substantial conformational changes in simulations conducted in the absence of Zn2+. Notably, we observed a loss of contact at the interface between protein domains proximal to the zinc-finger site, indicating a crucial role of Zn2+ in maintaining structural integrity and interdomain interactions within RyR1. Furthermore, this study provides valuable insights into the modulation of ATP, Ca2+, and caffeine binding, shedding light on the intricate relationship between Zn2+ coordination and the dynamic behavior of RyR1. Our integrative approach combining MD simulations and DFT calculations enhances our understanding of the molecular mechanisms governing ligand binding in RyR1.

On the Validation of Protein Force Fields Based on Structural Criteria

Molecular dynamics simulations depend critically on the quality of the force field used to describe the interatomic interactions and the extent to which it has been validated for use in a specific application. Using a curated test set of 52 high-resolution structures, 39 derived from X-ray diffraction and 13 solved using NMR, we consider the extent to which different parameter sets of the GROMOS protein force field can be distinguished based on comparing a range of structural criteria, including the number of backbone hydrogen bonds, the number of native hydrogen bonds, polar and nonpolar solvent-accessible surface area, radius of gyration, the prevalence of secondary structure elements, J-coupling constants, nuclear Overhauser effect (NOE) intensities, positional root-mean-square deviations (RMSD), and the distribution of backbone ϕ and ψ dihedral angles. It is shown that while statistically significant differences between the average values of individual metrics could be detected, these were in general small. Furthermore, improvements in agreement in one metric were often offset by loss of agreement in another. The work establishes a framework and test set against which protein force fields can be validated. It also highlights the danger of inferring the relative quality of a given force field based on a small range of structural properties or small number of proteins.

Improved Enzymatic Production of the Fucosylated Human Milk Oligosaccharide LNFP II with GH29B α-1,3/4-l-Fucosidases

Five GH29B α-1,3/4-l-fucosidases (EC 3.2.1.111) were investigated for their ability to catalyze the formation of the human milk oligosaccharide lacto-N-fucopentaose II (LNFP II) from lacto-N-tetraose (LNT) and 3-fucosyllactose (3FL) via transglycosylation. We studied the effect of pH on transfucosylation and hydrolysis and explored the impact of specific mutations using molecular dynamics simulations. LNFP II yields of 91 and 65% were obtained for the wild-type SpGH29C and CpAfc2 enzymes, respectively, being the highest LNFP II transglycosylation yields reported to date. BbAfcB and BiAfcB are highly hydrolytic enzymes. The results indicate that the effects of pH and buffer systems are enzyme-dependent yet relevant to consider when designing transglycosylation reactions. Replacing Thr284 in BiAfcB with Val resulted in increased transglycosylation yields, while the opposite replacement of Val258 in SpGH29C and Val289 CpAfc2 with Thr decreased the transfucosylation, confirming a role of Thr and Val in controlling the flexibility of the acid/base loop in the enzymes, which in turn affects transglycosylation. The substitution of an Ala residue with His almost abolished secondary hydrolysis in CpAfc2 and BbAfcB. The results are directly applicable in the enhancement of transglycosylation and may have significant implications for manufacturing of LNFP II as a new infant formula ingredient.

Interplay between Mg2+ and Ca2+ at multiple sites of the ryanodine receptor

RyR1 is an intracellular Ca2+ channel important in excitable cells such as neurons and muscle fibers. Ca2+ activates it at low concentrations and inhibits it at high concentrations. Mg2+ is the main physiological RyR1 inhibitor, an effect that is overridden upon activation. Despite the significance of Mg2+-mediated inhibition, the molecular-level mechanisms remain unclear. In this work we determined two cryo-EM structures of RyR1 with Mg2+ up to 2.8 Å resolution, identifying multiple Mg2+ binding sites. Mg2+ inhibits at the known Ca2+ activating site and we propose that the EF hand domain is an inhibitory divalent cation sensor. Both divalent cations bind to ATP within a crevice, contributing to the precise transmission of allosteric changes within the enormous channel protein. Notably, Mg2+ inhibits RyR1 by interacting with the gating helices as validated by molecular dynamics. This structural insight enhances our understanding of how Mg2+ inhibition is overcome during excitation.

The molecular interaction of six single-stranded DNA aptamers to cardiac troponin I revealed by docking and molecular dynamics simulation

Cardiac troponin I (cTnI) is a cardiac biomarker for diagnosing ischemic heart disease and acute myocardial infarction. Current biochemical assays use antibodies (Abs) due to their high specificity and sensitivity. However, there are some limitations, such as the high-cost production of Abs due to complex instruments, reagents, and steps; the variability of Abs quality from batch to batch; the low stability at high temperatures; and the difficulty of chemical modification. Aptamer overcomes the limitations of antibodies, such as relatively lower cost, high reproducibility, high stability, and ease of being chemically modified. Aptamers are three-dimensional architectures of single-stranded RNA or DNA that bind to targets such as proteins. Six aptamers (Tro1-Tro6) with higher binding affinity than an antibody have been identified, but the molecular interaction has not been studied. In this study, six DNA aptamers were modeled and docked to cTnI protein. Molecular docking revealed that the interaction between all aptamer and cTnI happened in the similar cTnI region. The interaction between aptamer and cTnI involved hydrophobic interaction, hydrogen bonds, π-cation interactions, π-stack interactions, and salt-bridge formation. The calculated binding energy of all complexes was negative, which means that the complex formation was thermodynamically favorable. The electrostatic energy term was the main driving force of the interaction between all aptamer and cTnI. This study could be used to predict the behavior of further modified aptamer to improve aptamer performance.

Exploring the Interactions between two Ligands, UCB-J and UCB-F, and Synaptic Vesicle Glycoprotein 2 Isoforms

In silico modeling was applied to study the efficiency of two ligands, namely, UCB-J and UCB-F, to bind to isoforms of the synaptic vesicle glycoprotein 2 (SV2) that are involved in the regulation of synaptic function in the nerve terminals, with the ultimate goal to understand the selectivity of the interaction between UCB-J and UCB-F to different isoforms of SV2. Docking and large-scale molecular dynamics simulations were carried out to unravel various binding patterns, types of interactions, and binding free energies, covering hydrogen bonding and nonspecific hydrophobic interactions, water bridge, π-π, and cation-π interactions. The overall preference for bonding types of UCB-J and UCB-F with particular residues in the protein pockets can be disclosed in detail. A unique interaction fingerprint, namely, hydrogen bonding with additional cation-π interaction with the pyridine moiety of UCB-J, could be established as an explanation for its high selectivity over the SV2 isoform A (SV2A). Other molecular details, primarily referring to the presence of π-π interactions and hydrogen bonding, could also be analyzed as sources of selectivity of the UCB-F tracer for the three isoforms. The simulations provide atomic details to support future development of new selective tracers targeting synaptic vesicle glycoproteins and their associated diseases.

Nanoactuator for Neuronal Optoporation

Light-driven modulation of neuronal activity at high spatial-temporal resolution is becoming of high interest in neuroscience. In addition to optogenetics, nongenetic membrane-targeted nanomachines that alter the electrical state of the neuronal membranes are in demand. Here, we engineered and characterized a photoswitchable conjugated compound (BV-1) that spontaneously partitions into the neuronal membrane and undergoes a charge transfer upon light stimulation. The activity of primary neurons is not affected in the dark, whereas millisecond light pulses of cyan light induce a progressive decrease in membrane resistance and an increase in inward current matched to a progressive depolarization and action potential firing. We found that illumination of BV-1 induces oxidation of membrane phospholipids, which is necessary for the electrophysiological effects and is associated with decreased membrane tension and increased membrane fluidity. Time-resolved atomic force microscopy and molecular dynamics simulations performed on planar lipid bilayers revealed that the underlying mechanism is a light-driven formation of pore-like structures across the plasma membrane. Such a phenomenon decreases membrane resistance and increases permeability to monovalent cations, namely, Na+, mimicking the effects of antifungal polyenes. The same effect on membrane resistance was also observed in nonexcitable cells. When sustained light stimulations are applied, neuronal swelling and death occur. The light-controlled pore-forming properties of BV-1 allow performing "on-demand" light-induced membrane poration to rapidly shift from cell-attached to perforated whole-cell patch-clamp configuration. Administration of BV-1 to ex vivo retinal explants or in vivo primary visual cortex elicited neuronal firing in response to short trains of light stimuli, followed by activity silencing upon prolonged light stimulations. BV-1 represents a versatile molecular nanomachine whose properties can be exploited to induce either photostimulation or space-specific cell death, depending on the pattern and duration of light stimulation.

Adaptive Workflows of Machine Learning Illuminate the Sequential Operation Mechanism of the TAK1's Allosteric Network

Allostery is a fundamental mechanism driving biomolecular processes that holds significant therapeutic concern. Our study rigorously investigates how two distinct machine-learning algorithms uniquely classify two already close-to-active DFG-in states of TAK1, differing just by the presence or absence of its allosteric activator TAB1, from an ensemble mixture of conformations (obtained from 2.4 μs molecular dynamics (MD) simulations). The novelty, however, lies in understanding the deeper algorithmic potentials to systematically derive a diverse set of differential residue connectivity features that reconstruct the essential mechanistic architecture for TAK1-TAB1 allostery in such a close-to-active biochemical scenario. While the recursive, random forest-based workflow displays the potential of conducting discretized, hierarchical derivation of allosteric features, a multilayer perceptron-based approach gains considerable efficacy in revealing fluid connected patterns of features when hybridized with mutual information scoring. Interestingly, both pipelines benchmark similar directions of functional conformational changes for TAK1's activation. The findings significantly advance the depth of mechanistic understanding by highlighting crucial activation signatures along a directed C-lobe → activation loop → ATP pocket channel of information flow, including (1) the αF-αE biterminal alignments and (2) the "catalytic" drift of the activation loop toward kinase active site. Besides, some novel allosteric hotspots (K253, Y206, N189, etc.) are further recognized as TAB1 sensors, transducers, and responders, including a benchmark E70 mutation site, precisely mapping the important structural segments for sequential allosteric execution. Hence, our work demonstrates how to navigate through greater structural depths and dimensions of dynamic allosteric machineries just by leveraging standard ML methods in suitable streamlined workflows adaptive to the specific system and objectives.

Molecular Insights into the Effect of Cholesterol on the Binding of Bicarbonate Ions in Band 3 Protein

Band 3, or anion exchanger 1 (AE1), is one of the indispensable transmembrane proteins involved in the effective respiratory process of the human body and is primarily responsible for the exchange of bicarbonate and chloride anions across the plasma membrane of erythrocyte. However, the molecular mechanism of ion transport of Band 3 is not completely understood, yet. In this work, we systematically investigate the key binding sites of bicarbonate ions in Band 3 and the impact of cholesterol (CHOL) in lipid bilayers on bicarbonate ion binding using all-atom molecular dynamics (MD) simulations. We examine the dynamics of interactions of bicarbonate ions with Band 3 in the microsecond time scale and calculate the binding free energy of the anion in Band 3. The results indicate that the residue R730 of Band 3 is the most probable binding site for bicarbonate ions. CHOL enhances the bicarbonate ion binding by influencing the conformational stability of Band 3 and compressing the volume of the Band 3 cavity. These findings provide some insights into the bicarbonate ion binding in Band 3 and are helpful for understanding the anion exchange of Band 3.

A Pseudo-Surfactant Chemical Permeation Enhancer to Treat Otitis Media via Sustained Transtympanic Delivery of Antibiotics

Chemical permeation enhancers (CPEs) represent a prevalent and safe strategy to enable noninvasive drug delivery across skin-like biological barriers such as the tympanic membrane (TM). While most existing CPEs interact strongly with the lipid bilayers in the stratum corneum to create defects as diffusion paths, their interactions with the delivery system, such as polymers forming a hydrogel, can compromise gelation, formulation stability, and drug diffusion. To overcome this challenge, differing interactions between CPEs and the hydrogel system are explored, especially those with sodium dodecyl sulfate (SDS), an ionic surfactant and a common CPE, and those with methyl laurate (ML), a nonionic counterpart with a similar length alkyl chain. Notably, the use of ML effectively decouples permeation enhancement from gelation, enabling sustained delivery across TMs to treat acute otitis media (AOM), which is not possible with the use of SDS. Ciprofloxacin and ML are shown to form a pseudo-surfactant that significantly boosts transtympanic permeation. The middle ear ciprofloxacin concentration is increased by 70-fold in vivo in a chinchilla AOM model, yielding superior efficacy and biocompatibility than the previous highest-performing formulation. Beyond improved efficacy and biocompatibility, this single-CPE formulation significantly accelerates its progression toward clinical deployment.

An Atomic and Molecular Insight into How PFOA Reduces α-Helicity, Compromises Substrate Binding, and Creates Binding Pockets in a Model Globular Protein

Per- and polyfluoroalkyl substances (PFAS) pose significant health risks due to their widespread presence in various environmental and biological matrices. However, the molecular-level mechanisms underlying the interactions between PFAS and biological constituents, including proteins, carbohydrates, lipids, and DNA, remain poorly understood. Here, we investigate the interactions between a legacy PFAS, viz. perfluorooctanoic acid (PFOA), and the milk protein β-lactoglobulin (BLG) obtained using a combination of experimental and computational techniques. Circular dichroism studies reveal that PFOA perturbs the secondary structure of BLG, by driving a dose-dependent loss of α-helicity and alterations in its β-sheet content. Furthermore, exposure of the protein to PFOA attenuates the on-rate constant for the binding of the hydrophobic probe 8-anilino-1-naphthalene sulfonic acid (ANS), suggesting potential functional impairment of BLG by PFOA. Steered molecular dynamics and umbrella sampling calculations reveal that PFOA binding leads to the formation of an energetically favorable novel binding pocket within the protein, when residues 129-142 are steered to unfold from their initial α-helical structure, wherein a host of intermolecular interactions between PFOA and BLG's residues serve to insert the PFOA into the region between the unfolded helix and beta-sheets. Together, the data provide a novel understanding of the atomic and molecular mechanism(s) by which PFAS modulates structure and function in a globular protein, leading to a beginning of our understanding of altered biological outcomes.

A molecular and computational study of galbanic acid as a regulator of Sirtuin1 pathway in inhibiting lipid accumulation in HepG2 cells

INTRODUCTION

Sirtuin1 (SIRT1) plays a crucial role in the pathophysiology of non-alcoholic fatty liver disease. We investigated the mechanistic role of galbanic acid (Gal) as a regulator of SIRT1 in silico and in vitro.

METHODS

HepG2 cells were treated with Gal in the presence or absence of EX-527, a SIRT1-specific inhibitor, for 24 h. Sirtuin1 gene and protein expression were measured by RT-PCR and Western blotting, respectively. It has been docked to the allosteric reign of SIRT1 (PDB ID: 4ZZJ) to study the effect of Gal on SIRT1, and then the protein and complex molecular dynamic (MD) simulations had been studied in 100 ns.

RESULTS

The semi-quantitative results of Oil red (p < .03) and TG level (p < .009) showed a significant reduction in lipid accumulation by treatment with Gal. Also, a significant increase was observed in the gene and protein expression of SIRT1 (p < .05). MD studies have shown that the average root mean square deviation (RMSD) was about 0.51 Å for protein structure and 0.66 Å for the complex. The average of radius of gyration (Rg) is 2.33 and 2.32 Å for protein and complex, respectively, and the pattern of root mean square fluctuation (RMSF) was almost similar.

CONCLUSION

Computational studies show that Gal can be a great candidate to use as a SIRT1 ligand because it does not interfere with the structure of the protein, and other experimental studies showed that Gal treatment with SIRT1 inhibitor increases fat accumulation in HepG2 cells.

Natural Compounds for Bone Remodeling: A Computational and Experimental Approach Targeting Bone Metabolism-Related Proteins

Osteoporosis, characterized by reduced bone density and increased fracture risk, affects over 200 million people worldwide, predominantly older adults and postmenopausal women. The disruption of the balance between bone-forming osteoblasts and bone-resorbing osteoclasts underlies osteoporosis pathophysiology. Standard treatment includes lifestyle modifications, calcium and vitamin D supplementation and specific drugs that either inhibit osteoclasts or stimulate osteoblasts. However, these treatments have limitations, including side effects and compliance issues. Natural products have emerged as potential osteoporosis therapeutics, but their mechanisms of action remain poorly understood. In this study, we investigate the efficacy of natural compounds in modulating molecular targets relevant to osteoporosis, focusing on the Mitogen-Activated Protein Kinase (MAPK) pathway and the gut microbiome's influence on bone homeostasis. Using an in silico and in vitro methodology, we have identified quercetin as a promising candidate in modulating MAPK activity, offering a potential therapeutic perspective for osteoporosis treatment.

Sinefungin analogs targeting VP39 methyltransferase as potential anti-monkeypox therapeutics: a multi-step computational approach

The increasing spread of the Monkeypox virus (MPXV) presents a significant public health challenge, emphasising the urgent requirement for effective treatments. Our study focuses on the VP39 Methyltransferase enzyme of MPXV as a critical target for therapy. By utilising virtual screening, we investigated natural compounds with structural similarities to sinefungin, a broad-acting MTase inhibitor. From an initial set of 177 compounds, we identified three promising compounds-CNP0346326, CNP0343532, and CNP008361, whose binding scores were notably close to that of sinefungin. These candidates bonded strongly to the VP39 enzyme, hinting at a notable potential to impede the virus. Our rigorous computational assays, including re-docking, extended molecular dynamics simulations, and energetics analyses, validate the robustness of these interactions. The data paint a promising picture of these natural compounds as front-runners in the ongoing race to develop MPXV therapeutics and set the stage for subsequent empirical trials to refine these discoveries into actionable medical interventions.

Antibiotic discovery with artificial intelligence for the treatment of Acinetobacter baumannii infections

Global challenges presented by multidrug-resistant Acinetobacter baumannii infections have stimulated the development of new treatment strategies. We reported that outer membrane protein W (OmpW) is a potential therapeutic target in A. baumannii. Here, a library of 11,648 natural compounds was subjected to a primary screening using quantitative structure-activity relationship (QSAR) models generated from a ChEMBL data set with >7,000 compounds with their reported minimal inhibitory concentration (MIC) values against A. baumannii followed by a structure-based virtual screening against OmpW. In silico pharmacokinetic evaluation was conducted to assess the drug-likeness of these compounds. The ten highest-ranking compounds were found to bind with an energy score ranging from -7.8 to -7.0 kcal/mol where most of them belonged to curcuminoids. To validate these findings, one lead compound exhibiting promising binding stability as well as favorable pharmacokinetics properties, namely demethoxycurcumin, was tested against a panel of A. baumannii strains to determine its antibacterial activity using microdilution and time-kill curve assays. To validate whether the compound binds to the selected target, an OmpW-deficient mutant was studied and compared with the wild type. Our results demonstrate that demethoxycurcumin in monotherapy and in combination with colistin is active against all A. baumannii strains. Finally, the compound was found to significantly reduce the A. baumannii interaction with host cells, suggesting its anti-virulence properties. Collectively, this study demonstrates machine learning as a promising strategy for the discovery of curcuminoids as antimicrobial agents for combating A. baumannii infections.

IMPORTANCE

Acinetobacter baumannii presents a severe global health threat, with alarming levels of antimicrobial resistance rates resulting in significant morbidity and mortality in the USA, ranging from 26% to 68%, as reported by the Centers for Disease Control and Prevention (CDC). To address this threat, novel strategies beyond traditional antibiotics are imperative. Computational approaches, such as QSAR models leverage molecular structures to predict biological effects, expediting drug discovery. We identified OmpW as a potential therapeutic target in A. baumannii and screened 11,648 natural compounds. We employed QSAR models from a ChEMBL bioactivity data set and conducted structure-based virtual screening against OmpW. Demethoxycurcumin, a lead compound, exhibited promising antibacterial activity against A. baumannii, including multidrug-resistant strains. Additionally, demethoxycurcumin demonstrated anti-virulence properties by reducing A. baumannii interaction with host cells. The findings highlight the potential of artificial intelligence in discovering curcuminoids as effective antimicrobial agents against A. baumannii infections, offering a promising strategy to address antibiotic resistance.

Molecular Dynamics Studies of Atomistically Determined Fibrillar Assemblies: Comparison of the Rippled β-Sheet, Pleated β-Sheet, and Herringbone Structures

Pauling and Corey expected that a racemic mixture would result in a rippled β-sheet, however, it has been known from experiments that the racemic mixtures of triphenylalanine lead to a herringbone structure. Because of the theoretical limitations concerning crystal structures such as rippled β-sheet, it is inevitable to understand how the interplay of the amino acids prefers a specific structural motif. In this paper we use molecular dynamics to understand the sequence- and enantiomer-dependent structures by comparisons between rippled β-sheet and pleated β-sheet, solvated and anhydrous rippled β-sheet, and rippled β-sheet and the herringbone structure, based on thermodynamics and structures at the atomic level. The tripeptides select the favored structure that can be stabilized through aromatic or hydrogen bonding interactions between tripeptides. Furthermore, the solubility is determined by the environment of space that is created around the side chains. Our findings provide comprehensive insight into the crystallized fibril motif of the polypeptide.

Protein-lipid acyl chain interactions: Depth-dependent changes of segmental mobility of phospholipid in contact with bacteriorhodopsin

Boundary lipids surrounding membrane proteins play an essential role in protein function and structure. These protein-lipid interactions are mainly divided into electrostatic interactions between the polar amino acids of proteins and polar heads of phospholipids, and hydrophobic interactions between protein transmembrane sites and phospholipid acyl chains. Our previous report (Kawatake et al., Biochim. Biophys. Acta 1858 [2016] 2106-2115) covered a method for selectively analyzing boundary lipid interactions and showed differences in membrane protein-peripheral lipid interactions due to differences in their head group. Interactions in the hydrophobic acyl chains of phospholipids are relatively consistent among proteins, but the details of these interactions have not been elucidated. In this study, we reconstituted bacteriorhodopsin as a model protein into phospholipid membranes labeled with 2H and 13C for solid-state NMR measurement to investigate the depth-dependent effect of the head group structure on the lipid bilayer. The results showed that the position of the phospholipid near the carbonyl carbon was affected by the head group in terms of selectivity for protein surfaces, whereas in the deep interior of the bilayer near the leaflet interface, there was little difference between the head groups, indicating that the dependence of their interactions on the head group was much reduced.

Proteins Can Withstand More Extensive Labeling while Providing Accurate Structural Information in Covalent Labeling-Mass Spectrometry

Diethylpyrocarbonate (DEPC) covalent labeling-mass spectrometry (CL-MS) has been extensively utilized to study protein structure and interactions owing to its ease of use, commercial availability, and broad labeling of nucleophilic residues. During typical CL-MS experiments with DEPC, the extent of labeling is kept low to avoid any structural perturbations resulting from covalent modification of the protein. In this study, we demonstrate that proteins can be labeled more extensively via DEPC and still provide accurate structural information. To show this, we modeled labeling kinetics over a range of DEPC concentrations and used molecular dynamics simulations to investigate the molecular-level effects of extensive labeling on the protein structure. Our results indicate that higher extents of DEPC labeling do not significantly perturb the protein structure and can lead to improved precision, detectability of labeled peptides, and protein structural resolution. Furthermore, higher extents of labeling enable better identification of protein-ligand binding sites where lower extents of modification provide ambiguous results.

Elucidating Daptomycin's Antibacterial Efficacy: Insights into the Tripartite Complex with Lipid II and Phospholipids in Bacterial Septum Membrane

This study elucidated the mechanism of formation of a tripartite complex containing daptomycin (Dap), lipid II, and phospholipid phosphatidylglycerol in the bacterial septum membrane, which was previously reported as the cause of the antibacterial action of Dap against gram-positive bacteria via molecular dynamics and enhanced sampling methods. Others have suggested that this transient complex ushers in the inhibition of cell wall synthesis by obstructing the downstream polymerization and cross-linking processes involving lipid II, which is absent in the presence of cardiolipin lipid in the membrane. In this work, we observed that the complex was stabilized by Ca2+-mediated electrostatic interactions between Dap and lipid head groups, hydrophobic interaction, hydrogen bonds, and salt bridges between the lipopeptide and lipids and was associated with Dap concentration-dependent membrane depolarization, thinning of the bilayer, and increased lipid tail disorder. Residues Orn6 and Kyn13, along with the DXDG motif, made simultaneous contact with constituent lipids, hence playing a crucial role in the formation of the complex. Incorporating cardiolipin into the membrane model led to its competitively displacing lipid II away from the Dap, reducing the lifetime of the complex and the nonexistence of lipid tail disorder and membrane depolarization. No evidence of water permeation inside the membrane hydrophobic interior was noted in all of the systems studied. Additionally, it was shown that using hydrophobic contacts between Dap and lipids as collective variables for enhanced sampling gave rise to a free energy barrier for the translocation of the lipopeptide. A better understanding of Dap's antibacterial mechanism, as studied through this work, will help develop lipopeptide-based antibiotics for rising Dap-resistant bacteria.

Computational and experimental identification of keystone interactions in Ebola virus matrix protein VP40 dimer formation

The Ebola virus (EBOV) is a lipid-enveloped virus with a negative sense RNA genome that can cause severe and often fatal viral hemorrhagic fever. The assembly and budding of EBOV is regulated by the matrix protein, VP40, which is a peripheral protein that associates with anionic lipids at the inner leaflet of the plasma membrane. VP40 is sufficient to form virus-like particles (VLPs) from cells, which are nearly indistinguishable from authentic virions. Due to the restrictions of studying EBOV in BSL-4 facilities, VP40 has served as a surrogate in cellular studies to examine the EBOV assembly and budding process from the host cell plasma membrane. VP40 is a dimer where inhibition of dimer formation halts budding and formation of new VLPs as well as VP40 localization to the plasma membrane inner leaflet. To better understand VP40 dimer stability and critical amino acids to VP40 dimer formation, we integrated computational approaches with experimental validation. Site saturation/alanine scanning calculation, combined with molecular mechanics-based generalized Born with Poisson-Boltzmann surface area (MM-GB/PBSA) method and molecular dynamics simulations were used to predict the energetic contribution of amino acids to VP40 dimer stability and the hydrogen bonding network across the dimer interface. These studies revealed several previously unknown interactions and critical residues predicted to impact VP40 dimer formation. In vitro and cellular studies were then pursued for a subset of VP40 mutations demonstrating reduction in dimer formation (in vitro) or plasma membrane localization (in cells). Together, the computational and experimental approaches revealed critical residues for VP40 dimer stability in an alpha-helical interface (between residues 106-117) as well as in a loop region (between residues 52-61) below this alpha-helical region. This study sheds light on the structural origins of VP40 dimer formation and may inform the design of a small molecule that can disrupt VP40 dimer stability.

In silico design of high-affinity antigenic peptides for HLA-B44

Cancer cell-killing by CD8+ T cells demands effective tumor antigen presentation by human leukocyte antigen class I (HLA-I) molecules. Screening and designing highly immunogenic neoantigens require quantitative computations to reliably predict HLA-peptide binding affinities. Here, with all-atom molecular dynamics (MD) simulations and free energy perturbation (FEP) methods, we design a collection of antigenic peptide candidates through in silico mutagenesis studies on immunogenic neoantigens, yielding enhanced binding affinities to HLA-B*44:02. In-depth structural dissection shows that introducing positively charged residues such as arginine to position 6 or lysine to position 7 of the candidates triggers conformational shifts in both peptides and the antigen-binding groove of the HLA, following the "induced-fit" mechanism. Enhancement in binding affinities compared to the wild-type was found in three out of five mutated candidates. The HLA pocket, capable of accommodating positively charged residues in positions from 5 to 7, is designated as the "dynamic pocket". Taken together, we showcase an effective structure-based binding affinity optimization framework for antigenic peptides of HLA-B*44:02 and underscore the importance of dynamic nature of the antigen-binding groove in concert with the anchoring motifs. This work provides structural insights for rational design of favorable HLA-peptide bindings and future developments in neoantigen-based therapeutics.

Machine learning and classical MD simulation to identify inhibitors against the P37 envelope protein of monkeypox virus

Monkeypox virus (MPXV) outbreak is a serious public health concern that requires international attention. P37 of MPXV plays a pivotal role in DNA replication and acts as one of the promising targets for antiviral drug design. In this study, we intent to screen potential analogs of existing FDA approved drugs of MPXV against P37 using state-of-the-art machine learning and computational biophysical techniques. AlphaFold2 guided all-atoms molecular dynamics simulations optimized P37 structure is used for molecular docking and binding free energy calculations. Similar to members of Phospholipase-D family , the predicted P37 structure also adopts a β-α-β-α-β sandwich fold, harbouring strongly conserved HxKxxxxD motif. The binding pocket comprises of Tyr48, Lys86, His115, Lys117, Ser130, Asn132, Trp280, Asn240, His325, Lys327 and Tyr346 forming strong hydrogen bonds and dense hydrophobic contacts with the screened analogs and is surrounded by positively charged patches. Loops connecting the two domains and C-terminal region exhibit high degree of flexibility. In some structural ensembles, the partial disorderness in the C-terminal region is presumed to be due to its low confidence score, acquired during structure prediction. Transition from loop to β-strands (244-254 aa) in P37-Cidofovir and its analog complexes advocates the need for further investigations. MD simulations support the accuracy of the molecular docking results, indicating the potential of analogs as potent binders of P37. Taken together, our results provide preferable understanding of molecular recognition and dynamics of ligand-bound states of P37, offering opportunities for development of new antivirals against MPXV. However, the need of in vitro and in vivo assays for confirmation of these results still persists.Communicated by Ramaswamy H. Sarma.

FFParam-v2.0: A Comprehensive Tool for CHARMM Additive and Drude Polarizable Force-Field Parameter Optimization and Validation

Developing production quality CHARMM force-field (FF) parameters is a very detailed process involving a variety of calculations, many of which are specific for the molecule of interest. The first version of FFParam was developed as a standalone Python package designed for the optimization of electrostatic and bonded parameters of the CHARMM additive and polarizable Drude FFs by using quantum mechanical (QM) target data. The new version of FFParam has multiple new capabilities for FF parameter optimization and validation, with an emphasis on the ability to use condensed-phase target data in optimization. FFParam-v2 allows optimization of Lennard-Jones (LJ) parameters using potential energy scans of interactions between selected atoms in a molecule and noble gases, viz., He and Ne, and through condensed-phase calculations, from which experimental observables such as heats of vaporization and free energies of solvation may be obtained. This functionality serves as a gold standard for both optimizing parameters and validating the performance of the final parameters. A new bonded parameter optimization algorithm has been introduced to account for simultaneously optimizing multiple molecules sharing parameters. FFParam-v2 also supports the comparison of normal modes and the potential energy distribution of internal coordinates towards each normal mode obtained from QM and molecular mechanics calculations. Such comparison capability is vital to validate the balance among various bonded parameters that contribute to the complex normal modes of molecules. User interaction has been extended beyond the original graphical user interface to include command-line interface capabilities that allow for integration of FFParam in workflows, thereby facilitating the automation of parameter optimization. With these new functionalities, FFParam is a more comprehensive parameter optimization tool for both beginners and advanced users.

Unlocking bacterial defense: Exploring the potent inhibition of NorA efflux pump by coumarin derivatives in Staphylococcus aureus

The occurrence of bacterial resistance has been increasing, compromising the treatment of various infections. The high virulence of Staphylococcus aureus allows for the maintenance of the infectious process, causing many deaths and hospitalizations. The MepA and NorA efflux pumps are transporter proteins responsible for expelling antimicrobial agents such as fluoroquinolones from the bacterial cell. Coumarins are phenolic compounds that have been studied for their diverse biological actions, including against bacteria. A pharmacokinetic in silico characterization of compounds C10, C11, C13, and C14 was carried out according to the principles of Lipinski's Rule of Five, in addition to searching for similarity in ChemBL and subsequent search for publications in CAS SciFinder. All compounds were evaluated for their in vitro antibacterial and modulatory activity against standard and multidrug-resistant Gram-positive and Gram-negative strains. The effect of coumarins C9, C10, C11, C13, and C14 as efflux pump inhibitors in Staphylococcus aureus strains was evaluated using the microdilution method (MepA or NorA) and fluorimetry (NorA). The behavior of coumarins regarding the efflux pump was determined from their interaction properties with the membrane and coumarin-protein using molecular docking and molecular dynamics simulations. Only the isolated coumarin compound C13 showed antibacterial activity against standard strains of Staphylococcus aureus and Escherichia coli. However, the other tested coumarins showed modulatory capacity for fluoroquinolone and aminoglycoside antibacterials. Compounds C10, C13, and C14 were effective in reducing the MIC of both antibiotics for both multidrug-resistant strains, while C11 potentiated the effect of norfloxacin and gentamicin for Gram-positive and Gram-negative bacteria and only norfloxacin for Gram-negative. Only coumarin C14 produced synergistic effects when associated with ciprofloxacin in MepA-carrying strains. All tested coumarins have the ability to inhibit the NorA efflux pump present in Staphylococcus aureus, both in reducing the MIC and inducing increased ethidium bromide fluorescence emission in fluorimetry. The findings of this study offer an atomistic perspective on the potential of coumarins as active inhibitors of the NorA pump, highlighting their specific mode of action mainly targeting protein inhibition. In molecular docking, it was observed that coumarins are capable of interacting with various amino acid residues of the NorA pump. The simulation showed that coumarin C10 can cross the bilayer; however, the other coumarins interacted with the membrane but were unable to cross it. Coumarins demonstrated their potentiating role in the effect of norfloxacin through a dual mechanism: efflux pump inhibition through direct interaction with the protein (C9, C10, C11, and C13) and increased interaction with the membrane (C10 and C13). In the context of pharmacokinetic prediction studies, the studied structures have a suitable chemical profile for possible oral use. We suggest that coumarin derivatives may be an interesting alternative in the future for the treatment of resistant bacterial infections, with the possibility of a synergistic effect with other antibacterials, although further studies are needed to characterize their therapeutic effects and toxicity.

Novel Inhibitory Site Revealed by Mode of Action on the Metabotropic Glutamate 7 Receptor Venus Flytrap Domain

Metabotropic glutamate (mGlu) receptors play a key role in modulating most synapses in the brain. The mGlu7 receptors inhibit presynaptic neurotransmitter release and offer therapeutic possibilities for post-traumatic stress disorders or epilepsy. Screening campaigns provided mGlu7-specific allosteric modulators as the inhibitor XAP044 (Gee et al. J. Biol. Chem. 2014). In contrast to other mGlu receptor allosteric modulators, XAP044 does not bind in the transmembrane domain but to the extracellular domain of the mGlu7 receptor and not at the orthosteric site. Here, we identified the mode of action of XAP044, combining synthesis of derivatives, modeling and docking experiments, and mutagenesis. We propose a unique mode of action of these inhibitors, preventing the closure of the Venus flytrap agonist binding domain. While acting as a noncompetitive antagonist of L-AP4, XAP044 and derivatives act as apparent competitive antagonists of LSP4-2022. These data revealed more potent XAP044 analogues and new possibilities to target mGluRs.

Lactobacilli-derived adjuvants combined with immunoinformatics-driven multi-epitope antigens based approach protects against Clostridium perfringens in a mouse model

Clostridium perfringens is ubiquitously distributed and capable of secreting toxins, posing a significant threat to animal health. Infections caused by Clostridium perfringens, such as Necrotic Enteritis (NE), result in substantial economic losses to the livestock industry annually. However, there is no effective commercial vaccine available. Hence, we set out to propose an effective approach for multi-epitope subunit vaccine construction utilizing biomolecules. We utilized immunoinformatics to design a novel multi-epitope antigen against C. perfringens (CPMEA). Furthermore, we innovated novel bacterium-like particles (BLPs) through thermal acid treatment of various Lactobacillus strains and selected BLP23017 among them. Then, we detailed the structure of CPMEA and BLPs and utilized them to prepare a multi-epitope vaccine. Here, we showed that our vaccine provided full protection against C. perfringens infection after a single dose in a mouse model. Additionally, BLP23017 notably augmented the secretion of secretory immunoglobulin A (sIgA) and enhanced antibody production. We conclude that our vaccine possess safety and high efficacy, making it an excellent candidate for preventing C. perfringens infection. Moreover, we demonstrate our approach to vaccine construction and the preparation of BLP23017 with distinct advantages may contribute to the prevention of a wider array of diseases and the novel vaccine development.

SARS-CoV-2 Mpro oligomerization as a potential target for therapy

The main protease (Mpro) of SARS-CoV-2 is critical in the virus's replication cycle, facilitating the maturation of polyproteins into functional units. Due to its conservation across taxa, Mpro is a promising target for broad-spectrum antiviral drugs. Targeting Mpro with small molecule inhibitors, such as nirmatrelvir combined with ritonavir (Paxlovid™), which the FDA has approved for post-exposure treatment and prophylaxis, can effectively interrupt the replication process of the virus. A key aspect of Mpro's function is its ability to form a functional dimer. However, the mechanics of dimerization and its influence on proteolytic activity remain less understood. In this study, we utilized biochemical, structural, and molecular modelling approaches to explore Mpro dimerization. We evaluated critical residues, specifically Arg4 and Arg298, that are essential for dimerization. Our results show that changes in the oligomerization state of Mpro directly affect its enzymatic activity and dimerization propensity. We discovered a synergistic relationship influencing dimer formation, involving both intra- and intermolecular interactions. These findings highlight the potential for developing allosteric inhibitors targeting Mpro, offering promising new directions for therapeutic strategies.

QM/MM-Based Energy Decomposition Analysis Method for Large Systems

In this work, a QM/MM-based EDA method, called GKS-EDA(QM/MM), is proposed. As an extension of GKS-EDA, this scheme divides the total interaction energy into electrostatic, exchange-repulsion, polarization, and correlation/dispersion terms. GKS-EDA(QM/MM) can be applied to describe the interactions of large-scale systems combined with various QM/MM platforms. By using the examples of a hydrated hydronium ion complex in water solution, the barnase-barstar complex, and MMP-13-pyrimidinetrione in a metalloprotein, the capability of GKS-EDA(QM/MM) for various interactions in large systems is validated.

Molecular and Functional Profiling of Gαi as an Intracellular pH Sensor

Heterotrimeric G proteins (Gα, Gβ and Gγ) act downstream of G-protein-coupled receptors (GPCRs) to mediate signaling pathways that regulate various physiological processes and human disease conditions. Previously, human Gαi and its yeast homolog Gpa1 have been reported to function as intracellular pH sensors, yet the pH sensing capabilities of Gαi and the underlying mechanism remain to be established. Herein, we identify a pH sensing network within Gαi, and evaluate the consequences of pH modulation on the structure and stability of the G-protein. We find that changes over the physiological pH range significantly alter the structure and stability of Gαi-GDP, with the protein undergoing a disorder-to-order transition as the pH is raised from 6.8 to 7.5. Further, we find that modulation of intracellular pH in HEK293 cells regulates Gαi-Gβγ release. Identification of key residues in the pH-sensing network allowed the generation of low pH mimetics that attenuate Gαi-Gβγ release. Our findings, taken together, indicate that pH-dependent structural changes in Gαi alter the agonist-mediated Gβγ dissociation necessary for proper signaling.

A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity

NanoLuc (NLuc) luciferase has found extensive application in designing a range of biological assays, including gene expression analysis, protein-protein interaction, and protein conformational changes due to its enhanced brightness and small size. However, questions related to its mechanism of interaction with the substrate, furimazine, as well as bioluminescence activity remain elusive. Here, we combined molecular dynamics (MD) simulation and mutational analysis to show that the R162A mutation results in a decreased but stable bioluminescence activity of NLuc in living cells and in vitro. Specifically, we performed multiple, all-atom, explicit solvent MD simulations of the apo and furimazine-docked (holo) NLuc structures revealing differential dynamics of the protein in the absence and presence of the ligand. Further, analysis of trajectories for hydrogen bonds (H-bonds) formed between NLuc and furimazine revealed substantial H-bond interaction between R162 and Q32 residues. Mutation of the two residues in NLuc revealed a decreased but stable activity of the R162A, but not Q32A, mutant NLuc in live cell and in vitro assays performed using lysates prepared from cells expressing the proteins and with the furimazine substrate. In addition to highlighting the role of the R162 residue in NLuc activity, we believe that the mutant NLuc will find wide application in designing in vitro assays requiring extended monitoring of NLuc bioluminescence activity. SIGNIFICANCE: Bioluminescence has been extensively utilized in developing a variety of biological and biomedical assays. In this regard, engineering of brighter bioluminescent proteins, i.e. luciferases, has played a significant role. This is acutely exemplified by the engineering of the NLuc luciferase, which is small in size and displays much enhanced bioluminescence and thermal stability compared to previously available luciferases. While enhanced bioluminescent activity is desirable in a multitude of biological and biomedical assays, it would also be useful to develop variants of the protein that display a prolonged bioluminescence activity. This is specifically relevant in designing assays that require bioluminescence for extended periods, such as in the case of biosensors designed for monitoring slow enzymatic or cellular signaling reactions, without necessitating multiple rounds of luciferase substrate addition or any specialized reagents that result in increased assay costs. In the current manuscript, we report a mutant NLuc that possesses a stable and prolonged bioluminescence activity, albeit lower than the wild-type NLuc, and envisage a wider application of the mutant NLuc in designing biosensors for monitoring slower biological and biomedical events.

Intrinsically disordered membrane anchors of Rheb, RhoA and DiRas3 small GTPases: Molecular dynamics, membrane organization, and interactions

Protein structure has been well established to play a key role in determining function; however, intrinsically disordered proteins and regions (IDPs and IDRs) defy this paradigm. IDPs and IDRs exist as an ensemble of structures rather than a stable 3D structure yet play essential roles in many cell signaling processes. Nearly all Ras Superfamily GTPases are tethered to membranes by a lipid tail at the end of a flexible IDR. The sequence of these IDRs are key determinants of membrane localization, and interactions between the IDR and the membrane have been shown to affect signaling in RAS proteins through modulation of dynamic membrane organization. Here we utilized atomistic molecular dynamics simulations to study the membrane interactions, conformational dynamics, and lipid sorting of three IDRs from small GTPases Rheb, RhoA and DiRas3 in model membranes representing their physiological target membranes. We found that complementarity between lipidated IDR sequence and target membrane lipid composition is a determinant of conformational plasticity. We also show that electrostatic interactions between anionic lipids and basic residues on IDRs generate semi-stable conformational sub-states, and a lack of these residues leads to greater conformational diversity. Finally, we show that small GTPase IDRs with a polybasic domain alter local lipid composition by segregating anionic membrane lipids, and, in some cases, excluding other lipids from their immediate proximity in favor of anionic lipids.

The Damietta Server: a comprehensive protein design toolkit

The growing importance of protein design to various research disciplines motivates the development of integrative computational platforms that enhance the accessibility and interoperability of different design tools. To this end, we describe a web-based toolkit that builds on the Damietta protein design engine, which deploys a tensorized energy calculation framework. The Damietta Server seamlessly integrates different design tools, in addition to other tools such as message-passing neural networks and molecular dynamics routines, allowing the user to perform multiple operations on structural models and forward them across tools. The toolkit can be used for tasks such as core or interface design, symmetric design, mutagenic scanning, or conformational sampling, through an intuitive user interface. With the envisioned integration of more tools, the Damietta Server will provide a central resource for protein design and analysis, benefiting basic and applied biomedical research communities. The toolkit is available with no login requirement through https://damietta.de/.

Solvation dynamics on the diffusion timescale elucidated using energy-represented dynamics theory

Photoexcitation of a solute alters the solute-solvent interaction, resulting in the nonequilibrium relaxation of the solvation structure, often called a dynamic Stokes shift or solvation dynamics. Thanks to the local nature of the solute-solvent interaction, the characteristics of the local solvent environment dissolving the solute can be captured by the observation of this process. Recently, we derived the energy-represented Smoluchowski-Vlasov (ERSV) equation, a diffusion equation for molecular liquids, which can be used to analyze the solvation dynamics on the diffusion timescale. This equation expresses the time development for the solvent distribution on the solute-solvent pair interaction energy (energy coordinate). Since the energy coordinate can effectively treat the solvent flexibility in addition to the position and orientation, the ERSV equation can be utilized in various solvent systems. Here, we apply the ERSV equation to the solvation dynamics of 6-propionyl-2-dimethylamino naphthalene (Prodan) in water and different alcohol solvents (methanol, ethanol, and 1-propanol) for clarifying the differences of the relaxation processes among these solvents. Prodan is a solvent-sensitive fluorescent probe and is thus widely utilized for investigating heterogeneous environments. On the long timescale, the ERSV equation satisfactorily reproduces the relaxation time correlation functions obtained from the molecular dynamics (MD) simulations for these solvents. We reveal that the relaxation time coefficient on the diffusion timescale linearly correlates with the inverse of the translational diffusion coefficients for the alcohol solvents because of the Prodan-solvent energy distributions among the alcohols. In the case of water, the time coefficient deviates from the linear relationship for the alcohols due to the difference in the extent of importance of the collective motion between the water and alcohol solvents.

C-type inactivation and proton modulation mechanisms of the TASK3 channel

The TWIK-related acid-sensitive K+ channel 3 (TASK3) belongs to the two-pore domain (K2P) potassium channel family, which regulates cell excitability by mediating a constitutive "leak" potassium efflux in the nervous system. Extracellular acidification inhibits TASK3 channel, but the molecular mechanism by which channel inactivation is coupled to pH decrease remains unclear. Here, we report the cryo-electron microscopy structures of human TASK3 at neutral and acidic pH. Structural comparison revealed selectivity filter (SF) rearrangements upon acidification, characteristic of C-type inactivation, but with a unique structural basis. The extracellular mouth of the SF was prominently dilated and simultaneously blocked by a hydrophobic gate. His98 protonation shifted the conformational equilibrium between the conductive and C-type inactivated SF toward the latter by engaging a cation-π interaction with Trp78, consistent with molecular dynamics simulations and electrophysiological experiments. Our work illustrated how TASK3 is gated in response to extracellular pH change and implies how physiological stimuli might directly modulate the C-type gating of K2P channels.