Comparative Pore Structure and Dynamics for Bacterial Microcompartment Shell Protein Assemblies in Sheets or Shells.

Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semi-permeable shell proteins, analogous to many membrane-bound organelles. The shell proteins assemble into multimeric tiles; hexamers, trimers, and pentamers, and these tiles self-assemble into larger assemblies with icosahedral symmetry. While icosahedral shells are the predominant form in vivo, the tiles can also form nanoscale cylinders or sheets. The individual multimeric tiles feature central pores that are key to regulating transport across the protein shell. Our primary interest is to quantify pore shape changes in response to alternative component morphologies at the nanoscale. We use molecular modeling tools to develop atomically detailed models for both planar sheets of tiles and curved structures representative of the complete shells found in vivo. Subsequently, these models were animated using classical molecular dynamics simulations. From the resulting trajectories, we analyzed overall structural stability, water accessibility to individual residues, water residence time, and pore geometry for the hexameric and trimeric protein tiles from the Haliangium ochraceum model BMC shell. These exhaustive analyses suggest no substantial variation in pore structure or solvent accessibility between the flat and curved shell geometries. We additionally compare our analysis to hydroxyl radical footprinting data to serve as a check against our simulation results, highlighting specific residues where water molecules are bound for a long time. Although with little variation in morphology or water interaction, we propose that the planar and capsular morphology can be used interchangeably when studying permeability through BMC pores.

Modularly assembled multiplex prime editors for simultaneous editing of agronomically important genes in rice.

Prime editing (PE) technology enables precise alterations in the genetic code of a genome of interest. PE offers great potential for identifying major agronomically important genes in plants and editing them into superior variants, ideally targeting multiple loci simultaneously to realize the collective effects of the edits. Here, we report the development of a modular assembly-based multiplex PE system in rice and demonstrate its efficacy in editing up to four genes in a single transformation experiment. The duplex PE (DPE) system achieved a co-editing efficiency of 46.1% in the T0 generation, converting TFIIAγ5 to xa5 and xa23 to Xa23SW11. The resulting double-mutant lines exhibited robust broad-spectrum resistance against multiple Xanthomonas oryzae pathovar oryzae (Xoo) strains in the T1 generation. In addition, we successfully edited OsEPSPS1 to an herbicide-tolerant variant and OsSWEET11a to a Xoo-resistant allele, achieving a co-editing rate of 57.14%. Furthermore, with the quadruple PE (QPE) system, we edited four genes-two for herbicide tolerance (OsEPSPS1 and OsALS1) and two for Xoo resistance (TFIIAγ5 and OsSWEET11a)-using one construct, with a co-editing efficiency of 43.5% for all four genes in the T0 generation. We performed multiplex PE using five more constructs, including two for triplex PE (TPE) and three for QPE, each targeting a different set of genes. The editing rates were dependent on the activity of pegRNA and/or ngRNA. For instance, optimization of ngRNA increased the PE rates for one of the targets (OsSPL13) from 0% to 30% but did not improve editing at another target (OsGS2). Overall, our modular assembly-based system yielded high PE rates and streamlined the cloning of PE reagents, making it feasible for more labs to utilize PE for their editing experiments. These findings have significant implications for advancing gene editing techniques in plants and may pave the way for future agricultural applications.

Passive permeability controls synthesis for the allelochemical sorgoleone in sorghum root exudate.

Competition for soil nutrients and water with other plants foster competition within the biosphere for access to these limited resources. The roots for the common grain sorghum produce multiple small molecules that are released via root exudates into the soil to compete with other plants. Sorgoleone is one such compound, which suppresses weed growth near sorghum by acting as a quinone analog and interferes with photosynthesis. Since sorghum also grows photosynthetically, and may be susceptible to sorgoleone action if present in tissues above ground, it is essential to exude sorgoleone efficiently. However, since the P450 enzymes that synthesize sorgoleone are intracellular, the release mechanism for sorgoleone remain unclear. In this study, we conducted an in silico assessment for sorgoleone and its precursors to passively permeate biological membranes. To facilitate accurate simulation, CHARMM parameters were newly optimized for sorgoleone and its precursors. These parameters were used to conduct 1 µs of unbiased molecular dynamics simulations to compare the permeability of sorgoleone with its precursors molecules. We find that interleaflet transfer is maximized for sorgoleone, suggesting that the precursor molecules may remain in the same leaflet for access by biosynthetic P450 enzymes. Since no sorgoleone was extracted during unbiased simulations, we compute a permeability coefficient using the inhomogeneous solubility diffusion model. The requisite free energy and diffusivity profiles for sorgoleone through a sorghum membrane model were determined through Replica Exchange Umbrella Sampling (REUS) simulations. The REUS calculations highlight that any soluble sorgoleone would quickly insert into a lipid bilayer, and would readily transit. When sorgoleone forms aggregates in root exudate as indicated by our equilibrium simulations, aggregate formation would lower the effective concentration in aqueous solution, creating a concentration gradient that would facilitate passive transport. This suggests that sorgoleone synthesis occurs within sorghum root cells and that sorgoleone is exuded by permeating through the cell membrane without the need for a transport protein once the extracellular sorgoleone aggregate is formed.

Plant Terpenoid Permeability through Biological Membranes Explored via Molecular Simulations.

Plants synthesize small molecule diterpenes composed of 20 carbons from precursor isopentenyl diphosphate and dimethylallyl disphosphate, manufacturing diverse compounds used for defense, signaling, and other functions. Industrially, diterpenes are used as natural aromas and flavoring, as pharmaceuticals, and as natural insecticides or repellents. Despite diterpene ubiquity in plant systems, it remains unknown how plants control diterpene localization and transport. For many other small molecules, plant cells maintain transport proteins that control compound compartmentalization. However, for most diterpene compounds, specific transport proteins have not been identified, and so it has been hypothesized that diterpenes may cross biological membranes passively. Through molecular simulation, we study membrane transport for three complex diterpenes from among the many made by members of the Lamiaceae family to determine their permeability coefficient across plasma membrane models. To facilitate accurate simulation, the intermolecular interactions for leubethanol, abietic acid, and sclareol were parametrized through the standard CHARMM methodology for incorporation into molecular simulations. To evaluate the effect of membrane composition on permeability, we simulate the three diterpenes in two membrane models derived from sorghum and yeast lipidomics data. We track permeation events within our unbiased simulations, and compare implied permeation coefficients with those calculated from Replica Exchange Umbrella Sampling calculations using the inhomogeneous solubility diffusion model. The diterpenes are observed to permeate freely through these membranes, indicating that a transport protein may not be needed to export these small molecules from plant cells. Moreover, the permeability is observed to be greater for plant-like membrane compositions when compared against animal-like membrane models. Increased permeability for diterpene molecules in plant membranes suggest that plants have tailored their membranes to facilitate low-energy transport processes for signaling molecules.

Structure Based in Silico Screening Revealed a Potent Acinetobacter Baumannii Ftsz Inhibitor From Asinex Antibacterial Library.

The superbug Acinetobacter baumannii is an increasingly prevalent pathogen of the intensive care units where its treatment is challenging. The identification of newer drug targets and the development of propitious therapeutics against this pathogen is of utmost importance. A drug target, cell division enzyme (FtsZ), involved in A. baumannii cytokinesis is a promising avenue for antibacterial therapy. Structure based virtual screening illustrated a lead-like molecule from Asinex antibacterial library to have the best binding affinity for the FtsZ active pocket. Computational pharmacokinetics predicted the compound to have the safest pharmacokinetics profile, thus maximizing the chances of the molecule reaching the market with enhanced efficacy and lesser toxicity. Molecular dynamics simulations in an aqueous environment revealed the flexibility of protein loop regions, and upward extension followed by the backward movement of the inhibitor N, N-dimethylpyridazin-3-amine ring on its axis. The active pocket residue Thr310 demonstrated to play significant role in inhibitor binding. The binding free energy predicted by MM/GBSA and MM/PBSA reflected system stability with a total value of -62.15 kcal/mol and -10.60 kcal/mol, respectively. The absolute binding free energy estimated by WaterSwap was -16 kcal/mol that validates and affirms complex stability. The inhibitor represents a promising scaffold as a lead optimization for the FtsZ enzyme.

Screening Pipeline for Flavivirus Based Inhibitors for Zika Virus NS1.

In-silico pipeline is applied for identifying and designing novel inhibitors against ZIKV NS1 protein. Comparative molecular docking studies are performed to explore the binding of structurally diverse compounds to ZIKV NS1 by AutoDock/Vina and GOLD. The Zika virus (ZIKV) is a flavivirus, responsible for life-threatening infections and transmitted by Aedes mosquitoes in other organisms. It is associated with Guillain Barre Syndrome (GBS) and microcephaly. This epidemic increase in GBS and microcephaly convoyed the World Health Organization to affirm ZIKV a public health crisis. To combat the ZIKV infections, non-structural protein 1 (NS1), a major host-interaction molecule contributing towards replication, pathogenesis and immune evasion is targeted in the current study. For this purpose, a comprehensive study is required to develop potential novel antiviral inhibitors. Three compounds were identified through docking programs exhibiting properties which are non-toxic to human host and could inhibit the elusive ZIKV. Significant interaction with active site residues and H-bond interactions with the key residues were analyzed for these compounds using molecular dynamics simulation. Free energy calculation predicted higher affinity of Deoxycalyxin-A for ZIKV NS1. This study contributes towards fighting ZIKV infections and can help researchers in designing drug for the treatment of ZIKV.

Visualizing protein-ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site.

Kallikrein-8, a serine protease, is a target for structure-based drug design due to its therapeutic potential in treating Alzheimer's disease and is also useful as a biomarker in ovarian cancer. We present a binding assessment of ligands to kallikrein-8 using a residue-wise decomposition of the binding energy. Binding of four putative inhibitors of kallikrein-8 is investigated through molecular dynamics simulation and ligand binding energy evaluation with two methods (MM/PBSA and WaterSwap). For visualization of the residue-wise decomposition of binding energies, chemical energy-wise decomposition or CHEWD is introduced as a plugin to UCSF Chimera and Pymol. CHEWD allows easy comparison between ligands using individual residue contributions to the binding energy. Molecular dynamics simulations indicate one ligand binds stably to the kallikrein-8 S1 binding site. Comparison with other members of the kallikrein family shows that residues responsible for binding are specific to kallikrein-8. Thus, ZINC02927490 is a promising lead for development of novel kallikrein-8 inhibitors.

Toward novel inhibitors against KdsB: a highly specific and selective broad-spectrum bacterial enzyme.

KdsB (3-deoxy-manno-octulosonate cytidylyltransferase) is a highly specific and selective bacterial enzyme that catalyzes KDO (3-Deoxy-D-mano-oct-2-ulosonic acid) activation in KDO biosynthesis pathway. Failure in KDO biosynthesis causes accumulation of lipid A in the bacterial outer membrane that leads to cell growth arrest. This study reports a combinatorial approach comprising virtual screening of natural drugs library, molecular docking, computational pharmacokinetics, molecular dynamics simulation, and binding free energy calculations for the identification of potent lead compounds against the said enzyme. Virtual screening demonstrated 1460 druglike compounds in a total of 4800, while molecular docking illustrated Ser13, Arg14, and Asp236 as the anchor amino acids for recognizing and binding the inhibitors. Functional details of the enzyme in complex with the best characterized compound-226 were explored through two hundred nanoseconds of MD simulation. The ligand after initial adjustments jumps into the active cavity, followed by the deep cavity, and ultimately backward rotating movement toward the initial docked site of the pocket. During the entire simulation period, Asp236 remained in contact with the ligand and can be considered as a major catalytic residue of the enzyme. Radial distribution function confirmed that toward the end of the simulation, strengthening of ligand-receptor occurred with ligand and enzyme active residues in close proximity. Binding free energy calculations via MM(PB/GB)SA and Waterswap reaction coordinates, demonstrated the high affinity of the compound for enzyme active site residues. These findings can provide new avenues for designing potent compounds against notorious bacterial pathogens.

Moleculer dynamics simulaiton revealed reciever domain of Acinetobacter baumannii BfmR enzyme as the hot spot for future antibiotics designing.

Acinetobacter baumannii is an alarming nosocomial pathogen that is resistant to multiple drugs. The pathogen is forefront of scientific attention because of high mortality and morbidity found for its complications in the past decade. As a consequence, identification of novel drug candidates and subsequent designing of novel chemical scaffolds is an imperative need of time. In the present study, we used a recently reported structure of BfmR enzyme and performed structure based virtual screening, MD simulation and binding free energies calculations. MD simulation revealed a profound movement of the best-characterized inhibitor towards the α4-ß5-α5 face of the enzyme receiver domain, thus indicating its high affinity for this site compared to phosphorylation. Furthermore, it was observed that the enzyme and enzyme-inhibitor complex have high structure stability with mean RMSD of 1.2 and 1.1 Å, respectively. Binding free energy calculations for the complex unraveled high stability with MMGBSA score of -26.21 kcal/mol and MMPBSA score of -1.47 kcal/mol. Van der Waal energy was found highly favorable with value of -30.25 kcal/mol and dominated significantly the overall binding energy. Furthermore, a novel WaterSwap assay was used to circumvent the limitations of MMGB/PBSA that complements the inhibitor affinity for enzyme active pocket as depicted by the low convergence of Bennett, TI and FEP algorithms. Results yielded from this study will not only give insight into the phenomena of inhibitor movement towards the enzyme receiver domain, but will also provide a useful baseline for designing derivatives with improved biological and pharmacokinetics profiles. Communicated by Ramaswamy H. Sarma.

Comparative subtractive proteomics based ranking for antibiotic targets against the dirtiest superbug: Acinetobacter baumannii.

Multidrug-resistant Acinetobacter baumannii is indeed to be the most successful nosocomial pathogen responsible for myriad infections in modern health care system. Computational methodologies based on genomics and proteomics proved to be powerful tools for providing substantial information about different aspects of A. baumannii biology that made it possible to design new approaches for treating multi, extensive and total drug resistant isolates of A. baumannii. In this current approach, 35 completely annotated proteomes of A. bauamnnii were filtered through a comprehensive subtractive proteomics pipeline for broad-spectrum drug candidates. In total, 10 proteins (KdsA, KdsB, LpxA, LpxC, LpxD, GpsE, PhoB, UvrY, KdpE and OmpR) could serve as ideal candidates for designing novel antibiotics. The work was extended with KdsA enzyme for structure information, prediction of intrinsic disorders, active site details, and structure based virtual screening of library containing natural product-like scaffolds. Most of the enzyme structure has fixed three-dimensional conformation. The selection of inhibitor for KdsA enzyme was based on druglikeness, pharmacokinetics and docking scores. Compound-4636 (5-((3-chloro-5-methyl-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)methoxy)-2-(((1-hydroxy-4-methylpentan-2-yl)amino)methyl)phenol) was revealed as the most potent inhibitor against A. baumannii KdsA enzyme having Gold fitness score of 77.68 and Autodock binding energy of -6.2 kcal/mol. The inhibitor completely follows Lipinski rule of five, Ghose rule, and Egan rule. Molecular dynamics simulation for KdsA and KdsA-4636 complex was performed for 100 ns to unveil what conformational changes the enzyme underwent in the absence and presence of the inhibitor, respectively. The average root means square deviation (RMSD) for both systems was found 3.5 Å, which signifies stable structure of the enzyme in both bounded and unbounded states. Absolute binding energy using Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) reflected high affinity and vigorous interactions of the inhibitor with enzyme active residues. Findings of the current study could open up new avenues for experimentalists to design new potent antibiotics by targeting the targets screened in this study.

AFD: an application for bi-molecular interaction using axial frequency distribution.

Conformational flexibility and generalized structural features are responsible for specific phenomena existing in biological pathways. With advancements in computational chemistry, novel approaches and new methods are required to compare the dynamic nature of biomolecules, which are crucial not only to address dynamic functional relationships but also to gain detailed insights into the disturbance and positional fluctuation responsible for functional shifts. Keeping this in mind, axial frequency distribution (AFD) has been developed, designed, and implemented. AFD can profoundly represent distribution and density of ligand atom around a particular atom or set of atoms. It enabled us to obtain an explanation of local movements and rotations, which are not significantly highlighted by any other structural and dynamical parameters. AFD can be implemented on biological models representing ligand and protein interactions. It shows a comprehensive view of the binding pattern of ligand by exploring the distribution of atoms relative to the x-y plane of the system. By taking a relative centroid on protein or ligand, molecular interactions like hydrogen bonds, van der Waals, polar or ionic interaction can be analyzed to cater the ligand movement, stabilization or flexibility with respect to the protein. The AFD graph resulted in the residual depiction of bi-molecular interaction in gradient form which can yield specific information depending upon the system of interest.

Improvement in thermostability of xylanase from Geobacillus thermodenitrificans C5 by site directed mutagenesis.

Enzymes activity and stability at extreme temperature can be intensified by regularly applying protein engineering. In the present study, two amino acids were perceived to mark the temperature dependability of xylanase from Geobacillus thermodenitrificans C5. Six mutants of G. thermodenitrificans C5 were built through site-directed mutagenesis by interchanging the residue with proline and glutamic acid (R81P, H82E, W185P, D186E, double mutant W185P/D186E and triple mutant H82E/W185P/D186E). Both mutant and wild type enzymes were quantified in host E. coli BL21. In comparison to wild type, the temperature was enhanced by 4 °C, 5 °C and 11 °C in H82E, W185P/D186E and H82E/W185P/D186E mutant models, respectively. The mutant H82E and the combined substitutions (H82E/W185P/D186E) showed the most pronounced shifts in their half-lives for thermal inactivation. Half-life was increased 13 times at 60 °C, 15 times at 65 °C, 9 times at 70 °C and 5 times at 75 °C by H82E/W185P/D186E mutant. Mutations in xylanase enzyme causes rigidification of essential chain and filling of groove that leads to stabilization of mutants and finally resulted into enhancement in their thermostability.

Binding mode analysis, dynamic simulation and binding free energy calculations of the MurF ligase from Acinetobacter baumannii.

MurF ligase catalyzes the final cytoplasmic step of bacterial peptidoglycan biosynthesis and, as such, is a validated target for therapeutic intervention. Herein, we performed molecular docking to identify putative inhibitors of Acinetobacter baumannii MurF (AbMurF). Based on comparative docking analysis, compound 114 (ethyl pyridine substituted 3-cyanothiophene) was predicted to potentially be the most active ligand. Computational pharmacokinetic characterization of drug-likeness of the compound showed it to fulfil all the parameters of Muegge and the MDDR rule. A molecular dynamic simulation of 114 indicated the complex to be stable on the basis of an average root mean square deviation (RMSD) value of 2.09Å for the ligand. The stability of the complex was further supported by root mean square fluctuation (RMSF), beta factor and radius of gyration values. Analyzing the complex using radial distribution function (RDF) and a novel analytical tool termed the axial frequency distribution (AFD) illustrated that after simulation the ligand is positioned in close vicinity of the protein active site where Thr42 and Asp43 participate in hydrogen bonding and stabilization of the complex. Binding free energy calculations based on the Poisson-Boltzmann or Generalized-Born Surface Area Continuum Solvation (MM(PB/GB)SA) method indicated the van der Waals contribution to the overall binding energy of the complex to be dominant along with electrostatic contributions involving the hot spot amino acids from the protein active site. The present results indicate that the screened compound 114 may act as a parent structure for designing potent derivatives against AbMurF in specific and MurF of other bacterial pathogens in general.

Molecular dynamics simulation studies of novel ß-lactamase inhibitor.

New Delhi Metallo-ß-Lactamase-1 (NDM-1) has drawn great attention due to its diverse antibiotic resistant activity. It can hydrolyze almost all clinically available ß-lactam antibiotics. To inhibit the activity of NDM-1 a new strategy is proposed using computational methods. Molecular dynamics (MD) simulations are used to analyze the molecular interactions between selected inhibitor candidates and NDM-1 structure. The enzyme-ligand complex is subject to binding free energy calculations using MM(PB/GB)SA methods. The role of each residue of the active site contributing in ligand binding affinity is explored using energy decomposition analysis. Furthermore, a hydrogen bonding network between ligand and enzyme active site is observed and key residues are identified ensuring that the ligand stays inside the active site and maintains its movement towards the active site pocket. A production run of 150ns is carried out and results are analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (Rg) to explain the stability of enzyme ligand complex. Important active site residue e.g. PHE70, VAL73, TRP93, HIS122, GLN123, ASP124, HIS189, LYS216, CYS208, LYS211, ALA215, HIS250, and SER251 were observed to be involved in ligand attachemet inside the active site pocket, hence depicting its inhibitor potential. Hydrogen bonds involved in structural stability are analyzed through radial distribution function (RDF) and contribution of important residues involved in ligand movement is explained using a novel analytical tool, axial frequency distribution (AFD) to observe the role of important hydrogen bonding partners between ligand atoms and active site residues.

Binding pattern analysis and structural insight into the inhibition mechanism of Sterol 24-C methyltransferase by docking and molecular dynamics approach.

Sterol 24-C methyltransferase (SMT) plays a major role during the production of steroids, especially in the biosynthesis of ergosterol, which is the major membrane sterol in leishmania parasite, and the etiological basis of leishmaniasis. Mechanism-based inactivators bind irreversibly to SMT and interfere with its activity to provide leads for the design of antileishmanial inhibitors. In this study, computational methods are used for studying enzyme-inhibitor interactions. fifty-seven mechanism-based inactivators are docked using 3 docking/scoring approaches (FRED, GoldScore, and ChemScore). A consensus is generated from the results of different scoring functions which are also validated with already reported experimental values. The most active compound thus obtained is subjected to molecular dynamics simulation of length 20 ns. Stability of simulation is analyzed through root-mean-square deviation, beta factor (B-factor), and radius of gyration (Rg). Hydrogen bonds and their involvement in the structural stability of the enzyme are evaluated through radial distribution function. Newly developed application of axial frequency distribution that determines three-particle correlation on frequency distributions before and after simulation has provided a clear evidence for the movement of the inhibitor into active pocket of the enzyme. Results yielded strong interaction between enzyme and the inhibitor throughout the simulation. Binding of the inhibitor with enzyme has stabilized the enzyme structure; thus, the inhibitor has the potential to become a lead compound.

Structure and dynamics studies of sterol 24-C-methyltransferase with mechanism based inactivators for the disruption of ergosterol biosynthesis.

The enzyme sterol 24-C-methyltransferase (SMT) belongs to the family of transferases, specifically to the one-carbon transferring methyltransferases. SMT has been found playing a major role during the production of steroids, especially for the biosynthesis of ergosterol, which is the major membrane sterol in leishmania parasites, causing leishmaniasis. However, SMT and ergosterol are not found in mammals, so, an extensive study has been carried out over the susceptible SMT protein, which is found to be highly conserved among all the Leishmania species and holds a significant anti-leishmanial drug target. To date, there is no computational data available for SMT, due to its highly unexplored profile. In this work, a complete set of structural attributes have been examined through the available computational procedures, along with an attempt to characterize the most capable modeling server available. The exploration ranges from physicochemical characterization, pairwise alignment, secondary structure prediction, to active site detection. With this information, a docking study was carried out to find the compound that best binds into the active site. Moreover, molecular dynamics simulation was conducted to examine the stability of the homology modeled protein and the ligand-enzyme complex. The results indicate that the ligand-enzyme complex is more stable.