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<p>Toll-like receptors (TLRs) are a unique category of pattern recognition receptors that recognize distinct pathogenic components, often utilizing the same set of downstream adaptors. Specific molecular features of extracellular, transmembrane (TM), and cytoplasmic domains of TLRs are crucial for coordinating the complex, innate immune signaling pathway. Here, we constructed a full-length structural model of TLR4—a widely studied member of the interleukin-1 receptor/TLR superfamily—using homology modeling, protein–protein docking, and molecular dynamics simulations to understand the differential domain organization of TLR4 in a membrane-aqueous environment. Results showed that each functional domain of the membrane-bound TLR4 displayed several structural transitions that are biophysically essential for plasma membrane integration. Specifically, the extracellular and cytoplasmic domains were partially immersed in the upper and lower leaflets of the membrane bilayer. Meanwhile, TM domains tilted considerably to overcome the hydrophobic mismatch with the bilayer core. Our analysis indicates an alternate dimerization or a potential oligomerization interface of TLR4-TM. Moreover, the helical properties of an isolated TM dimer partly agree with that of the full-length receptor. Furthermore, membrane-absorbed or solvent-exposed surfaces of the toll/interleukin-1 receptor domain are consistent with previous X-ray crystallography and biochemical studies. Collectively, we provided a complete structural model of membrane-bound TLR4 that strengthens our current understanding of the complex mechanism of receptor activation and adaptor recruitment in the innate immune signaling pathway.</p

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<p>Toll-like receptors (TLRs) are a unique category of pattern recognition receptors that recognize distinct pathogenic components, often utilizing the same set of downstream adaptors. Specific molecular features of extracellular, transmembrane (TM), and cytoplasmic domains of TLRs are crucial for coordinating the complex, innate immune signaling pathway. Here, we constructed a full-length structural model of TLR4—a widely studied member of the interleukin-1 receptor/TLR superfamily—using homology modeling, protein–protein docking, and molecular dynamics simulations to understand the differential domain organization of TLR4 in a membrane-aqueous environment. Results showed that each functional domain of the membrane-bound TLR4 displayed several structural transitions that are biophysically essential for plasma membrane integration. Specifically, the extracellular and cytoplasmic domains were partially immersed in the upper and lower leaflets of the membrane bilayer. Meanwhile, TM domains tilted considerably to overcome the hydrophobic mismatch with the bilayer core. Our analysis indicates an alternate dimerization or a potential oligomerization interface of TLR4-TM. Moreover, the helical properties of an isolated TM dimer partly agree with that of the full-length receptor. Furthermore, membrane-absorbed or solvent-exposed surfaces of the toll/interleukin-1 receptor domain are consistent with previous X-ray crystallography and biochemical studies. Collectively, we provided a complete structural model of membrane-bound TLR4 that strengthens our current understanding of the complex mechanism of receptor activation and adaptor recruitment in the innate immune signaling pathway.</p

Homology modeling and docking studies of FabH (β-ketoacyl-ACP synthase III) enzyme involved in type II fatty acid biosynthesis of <i>Chlorella variabilis</i>: a potential algal feedstock for biofuel production

<div><p>The concept of using microalgae as an alternative renewable source of biofuel has gained much importance in recent years. However, its commercial feasibility is still an area of concern for researchers. Unraveling the fatty acid metabolic pathway and understanding structural features of various key enzymes regulating the process will provide valuable insights to target microalgae for augmented oil content. FabH (β-ketoacyl-acyl carrier protein synthase; KAS III) is a condensing enzyme catalyzing the initial elongation step of type II fatty acid biosynthetic process and acyl carrier protein (ACP) facilitates the shuttling of the fatty acyl intermediates to the active site of the respective enzymes in the pathway. In the present study, a reliable three-dimensional structure of FabH from <i>Chlorella variabilis</i>, an oleaginous green microalga was modeled and subsequently the key residues involved in substrate binding were determined by employing protein–protein docking and molecular dynamics (MD) simulation protocols. The FabH-ACP complex having the lowest docking energy score showed the binding of ACP to the electropositive FabH surface with strong hydrogen bond interactions. The MD simulation results indicated that the substrate-complexed FabH adopted a more stable conformation than the free enzyme. Further, the FabH structure retained its stability throughout the simulation although noticeable displacements were observed in the loop regions. Molecular simulation studies suggested the importance of crucial hydrogen bonding of the conserved Arg⁹¹ of FabH with Glu⁵³ and Asp⁵⁶ of ACP for exhibiting high affinity between the enzyme and substrate. The molecular modeling results are consistent with available experimental results on the flexibility of FabH and the present study provides first <i>in silico</i> insights into the structural and dynamical aspect of catalytic mechanism of FabH, which could be used for further site-specific mutagenic experiments to develop engineered high oil-yielding microalgal strains for biofuel production.</p> </div

Structure-Based Computational Study of Two Disease Resistance Gene Homologues (<i>Hm1</i> and <i>Hm2</i>) in Maize (<i>Zea mays</i> L.) with Implications in Plant-Pathogen Interactions

<div><p>The NADPH-dependent HC-toxin reductases (HCTR1 and 2) encoded by enzymatic class of disease resistance homologous genes (<i>Hm1 and Hm2</i>) protect maize by detoxifying a cyclic tetrapeptide, HC-toxin, secreted by the fungus <i>Cochliobolus carbonum</i> race 1(CCR1). Unlike the other classes' resistance (<i>R</i>) genes, HCTR-mediated disease resistance is an inimitable mechanism where the avirulence (<i>Avr</i>) component from CCR1 is not involved in toxin degradation. In this study, we attempted to decipher cofactor (NADPH) recognition and mode of HC-toxin binding to HCTRs through molecular docking, molecular dynamics (MD) simulations and binding free energy calculation methods. The rationality and the stability of docked complexes were validated by 30-ns MD simulation. The binding free energy decomposition of enzyme-cofactor complex was calculated to find the driving force behind cofactor recognition. The overall binding free energies of HCTR1-NADPH and HCTR2-NADPH were found to be −616.989 and −16.9749 kJ mol⁻¹ respectively. The binding free energy decomposition revealed that the binding of NADPH to the HCTR1 is mainly governed by van der Waals and nonpolar interactions, whereas electrostatic terms play dominant role in stabilizing the binding mode between HCTR2 and NADPH. Further, docking analysis of HC-toxin with HCTR-NADPH complexes showed a distinct mode of binding and the complexes were stabilized by a strong network of hydrogen bond and hydrophobic interactions. This study is the first <i>in silico</i> attempt to unravel the biophysical and biochemical basis of cofactor recognition in enzymatic class of <i>R</i> genes in cereal crop maize.</p></div

Intermolecular interaction observed between HC-toxin and the HCTR1-NADPH and HCTR2-NADPH complexes.

<p>(A) Interaction of HC-toxin with the HCTR1-NADPH complex. The H-bonds formed between HCTR1-NADPH have been marked in black dotted lines whereas H-bonds formed between HCTR1and HC-toxin have been marked in red. (B) Interaction of HC-toxin with the HCTR2-NADPH complex. The H-bonds formed between HCTR2-NADPH has been marked in green dotted lines whereas H-bonds formed between HCTR2 and HC-toxin has been marked in red dotted lines.</p

Binding free energy calculation of enzyme-cofactor complexes (HCTR1-NADPH and HCTR2-NADPH).

<p>ΔG<i>_bind</i>  =  Binding free energy.</p><p>ΔG<i>_coul</i>  =  Electrostatic energy.</p><p>ΔG<i>_ps</i>  =  Polar solvation energy.</p><p>ΔG<i>_polar</i>  =  Polar term (ΔG<i>_coul</i> + ΔG<i>_ps</i>).</p><p>ΔG<i>_vdW</i>  =  van der Waals energy.</p><p>ΔG<i>_nps</i>  =  Nonpolar solvation energy.</p><p>ΔG<i>_nonpolar</i>  =  Nonpolar term (ΔG<i>_vdW</i> + Δ<i>_Gnps</i>).</p

Snapshot of the H-bonds formed between NADPH and HCTR1.

<p>The figure shows the intermolecular H-bonds formed between HCTR1 and NADPH in the final representative structure obtained in the end of 30-ns MD simulation. The figure accompanies the distance of each observed H-bond.</p

Comparison of the stereochemical quality of homology modeled HCTR1, HCTR2 and closest structural homologue (crystal structure of DFR of grape: 2C29 chain D).

<p>Comparison of the stereochemical quality of homology modeled HCTR1, HCTR2 and closest structural homologue (crystal structure of DFR of grape: 2C29 chain D).</p

Autodock scores obtained after docking HC-toxin into HCTR1-NADPH (A) and HCTR2-NADPH (B) complexes.

<p>Autodock scores obtained after docking HC-toxin into HCTR1-NADPH (A) and HCTR2-NADPH (B) complexes.</p

The overall 3D structures of modeled HCTR1 and 2 of maize.

<p>The secondary structure elements were assigned using Pymol.</p