Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function

An enzyme of the mammalian amino-sugar metabolism pathway, N-acetylglucosamine kinase (NAGK), that synthesizes N-acetylglucosamine (GlcNAc)-6-phosphate, is reported to promote dynein functions during mitosis, axonal and dendritic growth, cell migration, and selective autophagy, which all are unrelated to its enzyme activity. As non-enzymatic structural functions can be altered by genetic variation, we made an effort in this study aimed at deciphering the pathological effect of nonsynonymous single-nucleotide polymorphisms (nsSNPs) in NAGK gene. An integrated computational approach, including molecular dynamics (MD) simulation and protein–protein docking simulation, was used to identify the damaging nsSNPs and their detailed structural and functional consequences. The analysis revealed the four most damaging variants (G11R, G32R, G120E, and A156D), which are highly conserved and functional, positioned in both small (G11R and G32R) and large (G120E and A156D) domains of NAGK. G11R is located in the ATP binding region, while variants present in the large domain (G120E and A156D) were found to induce substantial alterations in the structural organizations of both domains, including the ATP and substrate binding sites. Furthermore, all variants were found to reduce binding energy between NAGK and dynein subunit DYNLRB1, as revealed by protein–protein docking and MM-GBSA binding energy calculation supporting their deleteriousness on non-canonical function. We hope these findings will direct future studies to gain more insight into the role of these variants in the loss of NAGK function and their role in neurodevelopmental disorders.     

Anion and Cation Permeability of the Mouse TMEM16F Calcium-Activated Channel

TMEM16F is involved in several physiological processes, such as blood coagulation, bone development and virus infections. This protein acts both as a Ca²⁺-dependent phospholipid scramblase and a Ca²⁺-activated ion channel but several studies have reported conflicting results about the ion selectivity of the TMEM16F-mediated current. Here, we have performed a detailed side-by-side comparison of the ion selectivity of TMEM16F using the whole-cell and inside-out excised patch configurations to directly compare the results. In inside-out configuration, Ca²⁺-dependent activation was fast and the TMEM16F-mediated current was activated in a few milliseconds, while in whole-cell recordings full activation required several minutes. We determined the relative permeability between Na⁺ and Cl¯ (P_Na/P_Cl) using the dilution method in both configurations. The TMEM16F-mediated current was highly nonselective, but there were differences depending on the configuration of the recordings. In whole-cell recordings, P_Na/P_Cl was approximately 0.5, indicating a slight preference for Cl¯ permeation. In contrast, in inside-out experiments the TMEM16F channel showed a higher permeability for Na⁺ with P_Na/P_Cl reaching 3.7. Our results demonstrate that the time dependence of Ca²⁺ activation and the ion selectivity of TMEM16F depend on the recording configuration.     

The Effects of One-Point Mutation on the New Delhi Metallo Beta-Lactamase-1 Resistance toward Carbapenem Antibiotics and β-Lactamase Inhibitors: An In Silico Systematic Approach

Antibiotic resistance has been becoming more and more critical due to bacteria’s evolving hydrolysis enzymes. The NDM-1 enzyme could hydrolyze not only carbapenems but also most of β-lactam’s antibiotics and inhibitors. In fact, variant strains could impose a high impact on the resistance of bacteria producing NDM-1. Although previous studies showed the effect of some variants toward antibiotics and inhibitors binding, there has been no research systematically evaluating the effects of alternative one-point mutations on the hydrolysis capacity of NDM-1. This study aims to identify which mutants could increase or decrease the effectiveness of antibiotics and β-lactamase inhibitors toward bacteria. Firstly, 35 different variants with a high probability of emergence based on the PAM-1 matrix were constructed and then docked with 5 ligands, namely d-captopril, l-captopril, thiorphan, imipenem, and meropenem. The selected complexes underwent molecular dynamics simulation and free energy binding estimation, with the results showing that the substitutions at residues 122 and 124 most influenced the binding ability of NDM-1 toward inhibitors and antibiotics. The H122R mutant decreases the binding ability between d-captopril and NDM-1 and diminishes the effectiveness of this antibiotic toward Enterobacteriaceae. However, the H122R mutant has a contrary impact on thiorphan, which should be tested in vitro and in vivo in further experiments.     

Molecular Mechanism of Small-Molecule Inhibitors in Blocking the PD-1/PD-L1 Pathway through PD-L1 Dimerization

Programmed cell death-1 (PD-1), which is a molecule involved in the inhibitory signal in the immune system and is important due to blocking of the interactions between PD-1 and programmed cell death ligand-1 (PD-L1), has emerged as a promising immunotherapy for treating cancer. In this work, molecular dynamics simulations were performed on complex systems consisting of the PD-L1 dimer with (S)-BMS-200, (R)-BMS-200 and (MOD)-BMS-200 (i.e., S, R and MOD systems) to systematically evaluate the inhibitory mechanism of BMS-200-related small-molecule inhibitors in detail. Among them, (MOD)-BMS-200 was modified from the original (S)-BMS-200 by replacing the hydroxyl group with a carbonyl to remove its chirality. Binding free energy analysis indicates that BMS-200-related inhibitors can promote the dimerization of PD-L1. Meanwhile, no significant differences were observed between the S and MOD systems, though the R system exhibited a slightly higher energy. Residue energy decomposition, nonbonded interaction, and contact number analyses show that the inhibitors mainly bind with the C, F and G regions of the PD-L1 dimer, while nonpolar interactions of key residues Ile54, Tyr56, Met115, Ala121 and Tyr123 on both PD-L1 monomers are the dominant binding-related stability factors. Furthermore, compared with (S)-BMS-200, (R)-BMS-200 is more likely to form hydrogen bonds with charged residues. Finally, free energy landscape and protein–protein interaction analyses show that the key residues of the PD-L1 dimer undergo remarkable conformational changes induced by (S)-BMS-200, which boosts its intimate interactions. This systematic investigation provides a comprehensive molecular insight into the ligand recognition process, which will benefit the design of new small-molecule inhibitors targeting PD-L1 for use in anticancer therapy.     

Mutation-Specific Differences in Kv7.1 (KCNQ1) and Kv11.1 (KCNH2) Channel Dysfunction and Long QT Syndrome Phenotypes

The electrocardiogram (ECG) empowered clinician scientists to measure the electrical activity of the heart noninvasively to identify arrhythmias and heart disease. Shortly after the standardization of the 12-lead ECG for the diagnosis of heart disease, several families with autosomal recessive (Jervell and Lange-Nielsen Syndrome) and dominant (Romano–Ward Syndrome) forms of long QT syndrome (LQTS) were identified. An abnormally long heart rate-corrected QT-interval was established as a biomarker for the risk of sudden cardiac death. Since then, the International LQTS Registry was established; a phenotypic scoring system to identify LQTS patients was developed; the major genes that associate with typical forms of LQTS were identified; and guidelines for the successful management of patients advanced. In this review, we discuss the molecular and cellular mechanisms for LQTS associated with missense variants in KCNQ1 (LQT1) and KCNH2 (LQT2). We move beyond the “benign” to a “pathogenic” binary classification scheme for different KCNQ1 and KCNH2 missense variants and discuss gene- and mutation-specific differences in K⁺ channel dysfunction, which can predispose people to distinct clinical phenotypes (e.g., concealed, pleiotropic, severe, etc.). We conclude by discussing the emerging computational structural modeling strategies that will distinguish between dysfunctional subtypes of KCNQ1 and KCNH2 variants, with the goal of realizing a layered precision medicine approach focused on individuals.     

Computational Study on Substrate Specificity of a Novel Cysteine Protease 1 Precursor from Zea mays

Cysteine protease 1 precursor from Zea mays (zmCP1) is classified as a member of the C1A family of peptidases (papain-like cysteine protease) in MEROPS (the Peptidase Database). The 3D structure and substrate specificity of the zmCP1 is still unknown. This study is the first one to build the 3D structure of zmCP1 by computer-assisted homology modeling. In order to determine the substrate specificity of zmCP1, docking study is used for rapid and convenient analysis of large populations of ligand–enzyme complexes. Docking results show that zmCP1 has preference for P1 position and P2 position for Arg and a large hydrophobic residue (such as Phe). Gly147, Gly191, Cys189, and Asp190 are predicted to function as active residues at the S1 subsite, and the S2 subsite contains Leu283, Leu193, Ala259, Met194, and Ala286. SIFt results indicate that Gly144, Arg268, Trp308, and Ser311 play important roles in substrate binding. Then Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) method was used to explain the substrate specificity for P1 position of zmCp1. This study provides insights into the molecular basis of zmCP1 activity and substrate specificity.     

A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ

Fragment-Based Drug Discovery (FBDD) has become, in recent years, a consolidated approach in the drug discovery process, leading to several drug candidates under investigation in clinical trials and some approved drugs. Among these successful applications of the FBDD approach, kinases represent a class of targets where this strategy has demonstrated its real potential with the approved kinase inhibitor Vemurafenib. In the Kinase family, protein kinase CK1 isoform δ (CK1δ) has become a promising target in the treatment of different neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. In the present work, we set up and applied a computational workflow for the identification of putative fragment binders in large virtual databases. To validate the method, the selected compounds were tested in vitro to assess the CK1δ inhibition.     

Computational Analysis of Structure-Based Interactions for Novel H1-Antihistamines

As a chronic disorder, insomnia affects approximately 10% of the population at some time during their lives, and its treatment is often challenging. Since the antagonists of the H₁ receptor, a protein prevalent in human central nervous system, have been proven as effective therapeutic agents for treating insomnia, the H₁ receptor is quite possibly a promising target for developing potent anti-insomnia drugs. For the purpose of understanding the structural actors affecting the antagonism potency, presently a theoretical research of molecular interactions between 129 molecules and the H₁ receptor is performed through three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques. The ligand-based comparative molecular similarity indices analysis (CoMSIA) model (Q² = 0.525, R²_ncv = 0.891, R²_pred = 0.807) has good quality for predicting the bioactivities of new chemicals. The cross-validated result suggests that the developed models have excellent internal and external predictability and consistency. The obtained contour maps were appraised for affinity trends for the investigated compounds, which provides significantly useful information in the rational drug design of novel anti-insomnia agents. Molecular docking was also performed to investigate the mode of interaction between the ligand and the active site of the receptor. Furthermore, as a supplementary tool to study the docking conformation of the antagonists in the H₁ receptor binding pocket, molecular dynamics simulation was also applied, providing insights into the changes in the structure. All of the models and the derived information would, we hope, be of help for developing novel potent histamine H₁ receptor antagonists, as well as exploring the H₁-antihistamines interaction mechanism.     

CH4在PVDF中渗透行为及机理的分子模拟研究

采用巨正则蒙特卡洛法(GCMC)和分子动力学法(MD)相结合的方法模拟研究了典型气体CH4在聚偏氟乙烯(PVDF)中的吸附扩散行为,探讨了温度及压力对气体吸附扩散能力的影响,分析了CH4在PVDF中的吸附位点及扩散轨迹.模拟结果表明,CH4在PVDF中的溶解系数、渗透系数随温度的升高先增大后减小,随压力的升高而增大;扩...     

Controlling the Heterodimerisation of the Phytosulfokine Receptor 1 (PSKR1) via Island Loop Modulation

Phytosulfokine (PSK) is a phytohormone responsible for cell-to-cell communication in plants, playing a pivotal role in plant development and growth. The binding of PSK to its cognate receptor, PSKR1, is modulated by the formation of a binding site located between a leucine-rich repeat (LRR) domain of PSKR1 and the loop located in the receptor’s island domain (ID). The atomic resolution structure of the extracellular PSKR1 bound to PSK has been reported, however, the intrinsic dynamics of PSK binding and the architecture of the PSKR1 binding site remain to be understood. In this work, we used atomistic molecular dynamics (MD) simulations and free energy calculations to elucidate how the PSKR1 island domain (ID) loop forms and binds PSK. Moreover, we report a novel “druggable” binding site which could be exploited for the targeted modulation of the PSKR1-PSK binding by small molecules. We expect that our results will open new ways to modulate the PSK signalling cascade via small molecules, which can result in new crop control and agricultural applications.     

Molecular Simulation of Oxygen Sorption and Diffusion in the Poly (lactic acid)

Grand canonical Monte Carlo and molecular dynamics simulation methods are used to simulate oxygen sorption and diffusion in amorphous poly(lactic acid) (PLA). The simulated solubility coefficient of oxygen is close to experimental data obtained from the quartz crystal microbalance but much higher than those from the time-lag method. This discrepancy is explained by using the dual-mode sorption model. It is found that oxygen sorption in PLA is predominantly Langmuir type controlled, em.e., through the process of filling holes. The time-lag method only takes into account oxygen molecules that participate the diffusion process whereas a large proportion of oxygen molecules trapped in the void have little chance to execute hopping due to the glassy nature of PLA at room temperature. The simulated diffusion coefficient of oxygen is reasonably close to the data obtained from the time-lag method. The solubility coefficient of oxygen decreases linearly with increasing relative humidity while its diffusion coefficient firstly decreases and then increases as a function of relative humidity.     

MD-TSPC4: Computational Method for Predicting the Thermal Stability of I-Motif

I-Motif is a tetrameric cytosine-rich DNA structure with hemi-protonated cytosine: cytosine base pairs. Recent evidence showed that i-motif structures in human cells play regulatory roles in the genome. Therefore, characterization of novel i-motifs and investigation of their functional implication are urgently needed for comprehensive understanding of their roles in gene regulation. However, considering the complications of experimental investigation of i-motifs and the large number of putative i-motifs in the genome, development of an in silico tool for the characterization of i-motifs in the high throughput scale is necessary. We developed a novel computation method, MD-TSPC4, to predict the thermal stability of i-motifs based on molecular modeling and molecular dynamic simulation. By assuming that the flexibility of loops in i-motifs correlated with thermal stability within certain temperature ranges, we evaluated the correlation between the root mean square deviations (RMSDs) of model structures and the thermal stability as the experimentally obtained melting temperature (Tm). Based on this correlation, we propose an equation for Tm prediction from RMSD. We expect this method can be useful for estimating the overall structure and stability of putative i-motifs in the genome, which can be a starting point of further structural and functional studies of i-motifs.     

Combining Molecular Docking and Molecular Dynamics to Predict the Binding Modes of Flavonoid Derivatives with the Neuraminidase of the 2009 H1N1 Influenza A Virus

Control of flavonoid derivatives inhibitors release through the inhibition of neuraminidase has been identified as a potential target for the treatment of H1N1 influenza disease. We have employed molecular dynamics simulation techniques to optimize the 2009 H1N1 influenza neuraminidase X-ray crystal structure. Molecular docking of the compounds revealed the possible binding mode. Our molecular dynamics simulations combined with the solvated interaction energies technique was applied to predict the docking models of the inhibitors in the binding pocket of the H1N1 influenza neuraminidase. In the simulations, the correlation of the predicted and experimental binding free energies of all 20 flavonoid derivatives inhibitors is satisfactory, as indicated by R(2) = 0.75.     

Structural Consequence of Non-Synonymous Single-Nucleotide Variants in the N-Terminal Domain of LIS1

Disruptive neuronal migration during early brain development causes severe brain malformation. Characterized by mislocalization of cortical neurons, this condition is a result of the loss of function of migration regulating genes. One known neuronal migration disorder is lissencephaly (LIS), which is caused by deletions or mutations of the LIS1 (PAFAH1B1) gene that has been implicated in regulating the microtubule motor protein cytoplasmic dynein. Although this class of diseases has recently received considerable attention, the roles of non-synonymous polymorphisms (nsSNPs) in LIS1 on lissencephaly progression remain elusive. Therefore, the present study employed combined bioinformatics and molecular modeling approach to identify potential damaging nsSNPs in the LIS1 gene and provide atomic insight into their roles in LIS1 loss of function. Using this approach, we identified three high-risk nsSNPs, including rs121434486 (F31S), rs587784254 (W55R), and rs757993270 (W55L) in the LIS1 gene, which are located on the N-terminal domain of LIS1. Molecular dynamics simulation highlighted that all variants decreased helical conformation, increased the intermonomeric distance, and thus disrupted intermonomeric contacts in the LIS1 dimer. Furthermore, the presence of variants also caused a loss of positive electrostatic potential and reduced dimer binding potential. Since self-dimerization is an essential aspect of LIS1 to recruit interacting partners, thus these variants are associated with the loss of LIS1 functions. As a corollary, these findings may further provide critical insights on the roles of LIS1 variants in brain malformation.     

A Computational Simulation Study of Benzamidine Derivatives Binding to Arginine-Specific Gingipain (HRgpA) from Periodontopathogen Porphyromonas gingivalis

We have shown that the binding free energy calculation from molecular dynamics can be adapted successfully to cysteine proteinases, such as arginine-specific gingipain (HRgpA) from Porphyromonas gingivalis. The binding free energy obtained is in good agreement with the available experimental data for eight benzamidine derivatives including urea and ether linker. The calculations showed that the electrostatic energies between HRgpA and inhibitors were important in determining the relative affinities of the inhibitors to the HRgpA, with an average binding free energy of about -5 kcal/mol. The average structures of the eight complexes suggest that benzamidine inhibitors interact with Asp387, His435, and Cys468 by hydrogen bonding and with Trp508 by hydrophilic interactions that are essential for the activities of benzamidine inhibitors. It can therefore be expected that the method provides a reliable tool for the investigation of new HRgpA inhibitors. This finding could significantly benefit the future design of HRgpA inhibitors.     

A Deep Dive into VDAC1 Conformational Diversity Using All-Atom Simulations Provides New Insights into the Structural Origin of the Closed States

The voltage-dependent anion channel 1 (VDAC1) is a crucial mitochondrial transporter that controls the flow of ions and respiratory metabolites entering or exiting mitochondria. As a voltage-gated channel, VDAC1 can switch between a high-conducting “open” state and a low-conducting “closed” state emerging at high transmembrane (TM) potentials. Although cell homeostasis depends on channel gating to regulate the transport of ions and metabolites, structural hallmarks characterizing the closed states remain unknown. Here, we performed microsecond accelerated molecular dynamics to highlight a vast region of VDAC1 conformational landscape accessible at typical voltages known to promote closure. Conformers exhibiting durable subconducting properties inherent to closed states were identified. In all cases, the low conductance was due to the particular positioning of an unfolded part of the N-terminus, which obstructed the channel pore. While the N-terminal tail was found to be sensitive to voltage orientation, our models suggest that stable low-conducting states of VDAC1 predominantly take place from disordered events and do not result from the displacement of a voltage sensor or a significant change in the pore. In addition, our results were consistent with conductance jumps observed experimentally and corroborated a recent study describing entropy as a key factor for VDAC gating.     

Effects of Concentrations on the Transdermal Permeation Enhancing Mechanisms of Borneol: A Coarse-Grained Molecular Dynamics Simulation on Mixed-Bilayer Membranes

Borneol is a natural permeation enhancer that is effective in drugs used in traditional clinical practices as well as in modern scientific research. However, its molecular mechanism is not fully understood. In this study, a mixed coarse-grained model of stratum corneum (SC) lipid bilayer comprised of Ceramide-N-sphingosine (CER NS) 24:0, cholesterol (CHOL) and free fatty acids (FFA) 24:0 (2:2:1) was used to examine the permeation enhancing mechanism of borneol on the model drug osthole. We found two different mechanisms that were dependent on concentrations levels of borneol. At low concentrations, the lipid system maintained a bilayer structure. The addition of borneol made the lipid bilayer loosen and improved drug permeation. The “pull” effect of borneol also improved drug permeation. However, for a strongly hydrophobic drug like osthole, the permeation enhancement of borneol was limited. When most borneol molecules permeated into bilayers and were located at the hydrophobic tail region, the spatial competition effect inhibited drug molecules from permeating deeper into the bilayer. At high concentrations, borneol led to the formation of water pores and long-lived reversed micelles. This improved the permeation of osthole and possibly other hydrophobic or hydrophilic drugs through the SC. Our simulation results were supported by Franz diffusion tests and transmission electron microscope (TEM) experiments.     

Computational Insight on the Interaction of Common Blood Proteins with Gold Nanoparticles

Protein interactions with engineered gold nanoparticles (AuNPs) and the consequent formation of the protein corona are very relevant and poorly understood biological phenomena. The nanoparticle coverage affects protein binding modalities, and the adsorbed protein sites influence interactions with other macromolecules and cells. Here, we studied four common blood proteins, i.e., hemoglobin, serum albumin, α1-antiproteinase, and complement C3, interacting with AuNPs covered by hydrophobic 11-mercapto-1-undecanesulfonate (MUS). We use Molecular Dynamics and the Martini coarse−grained model to gain quantitative insight into the kinetics of the interaction, the physico-chemical characteristics of the binding site, and the nanoparticle adsorption capacity. Results show that proteins bind to MUS−capped AuNPs through strong hydrophobic interactions and that they adapt to the AuNP surfaces to maximize the contact surface, but no dramatic change in the secondary structure of the proteins is observed. We suggest a new method to calculate the maximum adsorption capacity of capped AuNPs based on the effective surface covered by each protein, which better represents the realistic behavior of these systems.