Deciphering molecular basis of pesticide-induced recurrent pregnancy loss: insights from transcriptomics analysis.

Recent studies have revealed a notable connection between pesticide exposure and Recurrent Pregnancy Loss (RPL), yet the precise molecular underpinning of this toxicity remains elusive. Through the alignment of Differentially Expressed Genes (DEGs) of healthy and RPL patients with the target genes of 9 pesticide components, we identified a set of 12 genes responsible for RPL etiology. Interestingly, biological process showed that besides RPL, those 12 genes also associated with preeclampsia and cardiovascular disease. Enrichment analysis showed the engagement of these genes associated with essential roles in the molecular transport of small molecules, as well as the aldosterone-regulated sodium reabsorption, endocrine and other factor-regulated calcium reabsorption, mineral absorption, ion homeostasis, and ion transport by P-type ATPases. Notably, the crosstalk targets between pesticide components played crucial roles in influencing RPL results, suggesting a role in attenuating pesticide agents that contribute to RPL. It is important to note that non-significant concentration of the pesticide components observed in both control and RPL samples should not prematurely undermine the potential for pesticides to induce RPL in humans. This study emphasizes the complexity of pesticide induced RPL and highlights avenues for further research and precautionary measures.

Exploring polyamine interactions and binding pockets in SARS-CoV-2 ORF3a.

Ongoing global pandemic caused by coronavirus (COVID-19) requires urgent development of vaccines, treatments, and diagnostic tools. Open reading frame 3a (ORF3a) from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is considered to be a potential drug target for COVID-19 treatment. ORF3a is an accessory protein that plays a significant role in virus-host interactions and in facilitating host immune responses. Using putrescine, spermidine and spermine, an aliphatic polyamine for the activity suppression of ORF3a appears to be a promising approach in finding new targets for drug design. In this study, we explored the possible binding poses of polyamines to the ORF3a protein using a combination of various computational approaches i.e. pocket prediction, blind and site-specific molecular docking, molecular dynamics and ligand flooding simulations. The results showed that the tip of cytoplasmic domain and the upper tunnel of transmembrane domain of ORF3a provide a suitable binding site specific for the polyamines. MD simulations revealed the stability of spermidine binding in the upper tunnel pocket of ORF3a through salt bridge and hydrogen bond interactions between the amine groups of the ligand and negatively charged residues of ORF3a. These findings can be helpful in designing new therapeutic drugs.

Effect of pH on stability of dimer structure of the main protease of coronavirus-2.

The viral main protease (Mpro) from a novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a key enzyme essential for viral replication and has become an attractive target for antiviral drug development. The Mpro forms a functional dimer and exhibits a pH-dependent enzyme activity and dimerization. Here, we report a molecular dynamics (MD) investigation to gain insights into the structural stability of the enzyme dimer at neutral and acidic pH. Our data shows larger changes in structure of the protein with the acidic pH than that with the neutral pH. Structural analysis of MD trajectories reveals a substantial increase in intersubunit separation, the loss of domain contacts, binding free energy and interaction energy of the dimer which implies the protein instability and tendency of dimer dissociation at acidic pH. The loss in the interaction energy is mainly driven by electrostatic interactions. We have identified the intersubunit hydrogen-bonding residues involved in the decreased dimer stability. These findings may be helpful for rational drug design and target evaluation against COVID-19.

Interaction fingerprint of transmembrane segments in voltage sensor domains.

Voltage sensor domain (VSD) in channel and non-channel membrane proteins shares a common function in the detection of changes in the transmembrane electric potential. The VSD is made of four helical transmembrane segments (S1-S4) that form a structurally conserved scaffold through inter-transmembrane residue-residue interactions. Details about these interactions are yet to be fully understood in the context of the unique structural and physical characteristics of the voltage sensor unit. In this study, molecular dynamics simulations were carried out to investigate transmembrane helix-helix interactions via residue-based nonbonding energies using the activated and resting state conformations of VSD from Hv1, CiVSP, KvAP and NavAb. Inter-transmembrane interaction energies within the VSD were determined. Analysis of electrostatic and van der Waals components revealed the strengths and weaknesses of the interactions between each pair of transmembrane segments. In all cases the S4 helix had the highest electrostatic contribution to favor the key role as the voltage sensitive segment. Electrostatic interactions for the S1-S2 pair as well as the S1-S3 pair were relatively weak. Van der Waal interaction energies between adjacent segments were on average greater than that between diagonally opposite segments. Salt bridge interactions between S4-arginines and the negatively charged residues in other segments appear to contribute more to stabilizing the energy than the van der Waals interactions between nonpolar residues. The overall behavior of residue-residue contacts is similar among the transmembrane domains, reflecting the common inter- transmembrane interaction pattern in the VSD. In addition, analysis of the residue positions suggested that subtle differences in the orientation of the salt-bridges can be attributed to the difference in the inter-transmembrane interaction strengths inside the VSDs.

Self-Organized Morphology and Multiscale Structures of CoVE Proteins.

Self-organizing structures of CoVE proteins have been investigated using a coarse-grained model in Monte Carlo simulations as a function of temperature (T) in a range covering the native (low T) to denatured (high T) phases. The presence of even a few chains accelerates the very slow dynamics of an otherwise free protein chain in the native phase. The radius of gyration depends nonmonotonically on temperature and increases with the protein concentration in both the native and denatured phase. The density of organized morphology over residue-to-sample length scales (λ) is quantified by an effective dimension (D) that varies between ~ 2 at high to ~ 3 at low temperatures at λ ~ R g with an overall lower density (D ~ 2) on larger scales. The magnitude of D depends on temperature, length scale, and concentration of proteins, i.e., D ~ 3.2 at λ ~ Rg, D ~ 2.6 at λ > R g, and D ~ 2.0 at λ ≫ R g, at T = 0.024.

Preferential binding effects on protein structure and dynamics revealed by coarse-grained Monte Carlo simulation.

The effect of preferential binding of solute molecules within an aqueous solution on the structure and dynamics of the histone H3.1 protein is examined by a coarse-grained Monte Carlo simulation. The knowledge-based residue-residue and hydropathy-index-based residue-solvent interactions are used as input to analyze a number of local and global physical quantities as a function of the residue-solvent interaction strength (f). Results from simulations that treat the aqueous solution as a homogeneous effective solvent medium are compared to when positional fluctuations of the solute molecules are explicitly considered. While the radius of gyration (Rg) of the protein exhibits a non-monotonic dependence on solvent interaction over a wide range of f within an effective medium, an abrupt collapse in Rg occurs in a narrow range of f when solute molecules rapidly bind to a preferential set of sites on the protein. The structure factor S(q) of the protein with wave vector (q) becomes oscillatory in the collapsed state, which reflects segmental correlations caused by spatial fluctuations in solute-protein binding. Spatial fluctuations in solute binding also modify the effective dimension (D) of the protein in fibrous (D ∼ 1.3), random-coil (D ∼ 1.75), and globular (D ∼ 3) conformational ensembles as the interaction strength increases, which differ from an effective medium with respect to the magnitude of D and the length scale.

Asymmetry in structural response of inner and outer transmembrane segments of CorA protein by a coarse-grain model.

Structure of CorA protein and its inner (i.corA) and outer (o.corA) transmembrane (TM) components are investigated as a function of temperature by a coarse-grained Monte Carlo simulation. Thermal response of i.corA is found to differ considerably from that of the outer component, o.corA. Analysis of the radius of gyration reveals that the inner TM component undergoes a continuous transition from a globular conformation to a random coil structure on raising the temperature. In contrast, the outer transmembrane component exhibits an abrupt (nearly discontinuous) thermal response in a narrow range of temperature. Scaling of the structure factor shows a globular structure of i.corA at a low temperature with an effective dimension D ∼ 3 and a random coil at a high temperature with D ∼ 2. The residue distribution in o.corA is slightly sparser than that of i.corA in a narrow thermos-responsive regime. The difference in thermos-response characteristics of these components (i.corA and o.corA) may reflect their unique transmembrane functions.

Aggregation and network formation in self-assembly of protein (H3.1) by a coarse-grained Monte Carlo simulation.

Multi-scale aggregation to network formation of interacting proteins (H3.1) are examined by a knowledge-based coarse-grained Monte Carlo simulation as a function of temperature and the number of protein chains, i.e., the concentration of the protein. Self-assembly of corresponding homo-polymers of constitutive residues (Cys, Thr, and Glu) with extreme residue-residue interactions, i.e., attractive (Cys-Cys), neutral (Thr-Thr), and repulsive (Glu-Glu), are also studied for comparison with the native protein. Visual inspections show contrast and similarity in morphological evolutions of protein assembly, aggregation of small aggregates to a ramified network from low to high temperature with the aggregation of a Cys-polymer, and an entangled network of Glu and Thr polymers. Variations in mobility profiles of residues with the concentration of the protein suggest that the segmental characteristic of proteins is altered considerably by the self-assembly from that in its isolated state. The global motion of proteins and Cys polymer chains is enhanced by their interacting network at the low temperature where isolated chains remain quasi-static. Transition from globular to random coil transition, evidenced by the sharp variation in the radius of gyration, of an isolated protein is smeared due to self-assembly of interacting networks of many proteins. Scaling of the structure factor S(q) with the wave vector q provides estimates of effective dimension D of the mass distribution at multiple length scales in self-assembly. Crossover from solid aggregates (D ∼ 3) at low temperature to a ramified fibrous network (D ∼ 2) at high temperature is observed for the protein H3.1 and Cys polymers in contrast to little changes in mass distribution (D ∼ 1.6) of fibrous Glu- and Thr-chain configurations.

Binding of solvated peptide (EPLQLKM) with a graphene sheet via simulated coarse-grained approach.

Binding of a solvated peptide A1 ((1)E (2)P (3)L (4)Q (5)L (6)K (7)M) with a graphene sheet is studied by a coarse-grained computer simulation involving input from three independent simulated interaction potentials in hierarchy. A number of local and global physical quantities such as energy, mobility, and binding profiles and radius of gyration of peptides are examined as a function of temperature (T). Quantitative differences (e.g., the extent of binding within a temperature range) and qualitative similarities are observed in results from three simulated potentials. Differences in variations of both local and global physical quantities suggest a need for such analysis with multiple inputs in assessing the reliability of both quantitative and qualitative observations. While all three potentials indicate binding at low T and unbinding at high T, the extent of binding of peptide with the temperature differs. Unlike un-solvated peptides (with little variation in binding among residues), solvation accentuates the differences in residue binding. As a result the binding of solvated peptide at low temperatures is found to be anchored by three residues, (1)E, (4)Q, and (6)K (different from that with the un-solvated peptide). Binding to unbinding transition can be described by the variation of the transverse (with respect to graphene sheet) component of the radius of gyration of the peptide (a potential order parameter) as a function of temperature.

Distinction in binding of peptides (P2E) and its mutations (P2G, P2Q) to a graphene sheet via a hierarchical coarse-grained Monte Carlo simulation.

A hierarchical coarse-grained approach is used to study the binding of peptides (P2E: (1)E(2)P(3)L(4)Q(5)L(6)K(7)M) and variants (P2G: (1)G(2)P(3)L(4)Q(5)L(6)K(7)M and P2Q: (1)Q(2)L(3)P(4)M(5)E(6)K(7)L) with a graphene sheet. Simulation-based residue-substrate and hydropathy index-based residue-residue interaction is used as input to a phenomenological interaction potential for peptide chains to execute the stochastic motion with a graphene sheet at the center of a box. Large-scale Monte Carlo simulations are performed at a range (low to high) of temperatures to identify peptides binding with the graphene sheet with a constant peptide concentration (Cp = 0.01). A number of local (energy, mobility, and substrate contact profiles) and global (density profiles, mean square displacement of the center of mass of a peptide and its radius of gyration) physical quantities are examined to monitor the patterns. We find that each peptide can bind to a graphene sheet at low temperatures but the residues that can anchor their binding vary among these three peptides. For example, P2E is anchored by (1)E, (4)Q, and (6)K, P2Q by (1)Q, (5)E, and (6)K, and P2G by nearly all its residues with about the same strength except (1)G and (2)P. The site-specific binding is reflected in the thermal response of the radius of gyration of the peptides. Despite the lack of a large difference in binding patterns, a systematic variation in radius of gyration and surface binding profile with the temperature reveals the distinction in their binding: the probability of P2E binding is the highest and that of P2G is the lowest.

Scaffolding of an antimicrobial peptide (KSL) by a scale-down coarse-grained approach.

A coarse-grained approach with enhanced representation of amino acid (involving four components, i.e. a central alpha carbon and its side group along with C and N terminals) is used to study the multi-scale assembly of an antimicrobial peptide (KSL) in an explicit solvent (in a scale-down hierarchy of Eby et al. [Phys. Chem. Chem. Phys., 2011, 13, 1123-1130]). Both local (mobility, solvent-surrounding, energy profiles) and global (variation of the root mean square displacement of peptides and its gyration radius with time steps, radial distribution function, and structure factors) physical quantities are analyzed as a function of the solvent quality (i.e. the solvent-residue interaction strength). We find that the mobility of the interacting side group (lysine) decays as the number of its surrounding solvent constituents grows systematically on increasing the interaction strength. Pinning of lysine directs the underlying segmental conformation that propagates to larger scale scaffolding. The radial distribution function (a measure of the correlated peptide assembly) decays with the distance (faster with stronger solvent interaction). Scaling of the structure factor (S(q)) of peptide assembly with the wave vector q = 2π/λ (λ is the wavelength), S(q) ∝q(-1/ν) provides an insight into its multi-scale mass (N) distribution. The effective dimension D(e) = 1/ν of the peptide assembly over the spatial distribution (R) can be estimated using N∝R(D(e)). On scales larger than the size (i.e. the radius of gyration R(g)) of the peptide, D(e) ≈ 1.303 ± 0.070 to D(e) ≈ 1.430 ± 0.096, a rather fibrous morphology appears perhaps due to directed pinning while the morphology appears like an ideal chain, D(e) ≈ 1.809 ± 0.017 to D(e) ≈ 1.978 ± 0.017, at a smaller scale R≤R(g).

Biofunctionalization and immobilization of a membrane via peptide binding (CR3-1, S2) by a Monte Carlo simulation.

A coarse-grained computer simulation model is used to study the immobilization of a dynamic tethered membrane (representation of a clay platelet) in a matrix of mobile peptide chains CR3-1: 1Trp-2Pro-3Ser-4Ser-5Tyr-6Leu-7Ser-8Pro-9Ile-10Pro-11Tyr-12Ser and S2: 1His-2Gly-3Ile-4Asn-5Thr-6Thr-7Lys-8Pro-9Phe-10Lys-11Ser-12Val on a cubic lattice. Each residue interacts with the membrane nodes with appropriate interaction and executes their stochastic motion with the Metropolis algorithm. Density profiles, binding energy of each residue, mobility, and targeted structural profile are analyzed as a function of peptide concentration. We find that the binding of peptides S2 is anchored by lysine residues (7Lys, 10Lys) while peptides CR3-1 do not bind to membrane. The membrane slows down as peptides S2 continues to bind leading to its eventual pinning. How fast the immobilization of the membrane occurs depends on peptide concentration. Binding of peptide S2 modulates the morphology of the membrane. The immobilization of membrane occurs faster if peptides S2 are replaced by the homopolymer of lysine ([Lys]12 of the same molecular weight), the strongest binding residue. The surface of membrane can be patterned with somewhat reduced roughness with the homopolymer of lysine than that with peptide S2

Globular structure of a human immunodeficiency virus-1 protease (1DIFA dimer) in an effective solvent medium by a Monte Carlo simulation.

A coarse-grained model is used to study the structure and dynamics of a human immunodeficiency virus-1 protease (1DIFA dimer) consisting of 198 residues in an effective solvent medium on a cubic lattice by Monte Carlo simulations for a range of interaction strengths. Energy and mobility profiles of residues are found to depend on the interaction strength and exhibit remarkable segmental symmetries in two monomers. Lowest energy residues such as Arg(41) and Arg(140) (most electrostatic and polar) are not the least mobile; despite the higher energy, the hydrophobic residues (Ile, Leu, and Val) are least mobile and form the core by pinning down the local segments for the globular structure. Variations in the gyration radius (R(g)) and energy (E(c)) of the protein show nonmonotonic dependence on the interaction strength with the smallest R(g) around the largest value of E(c). Pinning of the conformations by the hydrophobic residues at high interaction strength seems to provide seed for the protein chain to collapse.

Correlated response in a driven flow of self-organizing particles around a slit in porous media by interacting lattice gas.

The flow of immiscible particles (A, B) through a porous medium with a vertical slit is studied by an interacting lattice-gas computer simulation on a discrete lattice. The source of the particles is connected to the bottom and particles are driven upward by concentration gradient and a pressure bias against gravity. Distribution of flowing particles around the slit is examined as a function of the slit width and bias at high and low porosity at a steady state. At the low bias, a sharp change in the densities (high in slit to low in adjacent porous media) of both constituents occurs as expected. Onset of an undershooting in the density and mobility of particle profiles appears at the interface of slit and the porous medium on increasing the bias, an unexpected correlated response. The competition between the faster flow in the slit and slower motion of the particles in the surrounding porous medium induces stronger correlations at higher bias; as a result, a well-defined density profile emerges with higher density in the porous matrix away from the slit interface. The range of correlation and therefore the response increases on increasing the bias. Lowering the porosity to near the percolation threshold leads to the onset of oscillation in the density profile and broadening of the mobility profile, a distinct difference from the response at high porosity.

Adsorption of peptides (A3, Flg, Pd2, Pd4) on gold and palladium surfaces by a coarse-grained Monte Carlo simulation.

Monte Carlo simulations are performed to study adsorption and desorption of coarse-grained peptide chains on generic gold and palladium surfaces in the presence of solvent. The atomistic structural details are ignored within the amino acid residues; however, their specificity and hydrophobicity are incorporated via an interaction matrix guided by atomistic simulation. Adsorption probabilities of the peptides A3, Flg, Pd2, Pd4, Gly10, Pro10 on gold and palladium surfaces are studied via analysis of the mobility of each residue, the interaction energy with the surface, profiles of the proximity to the surface, the radius of gyration, and comparisons to homopolymers. In contrast to the desorption of Gly10 and Pro10 (with faster global dynamics), peptides Pd2, Pd4, Flg, and A3 exhibit various degrees of adsorption on gold and palladium surfaces (with relatively slower dynamics). Adsorption on both gold and palladium occurs through aromatic anchoring residues Tyr2 and Phe12 in A3, Tyr2 in Flg, Phe2, His10 and His12 in Pd2, and His6 and His11 in Pd4. A lower (more negative) surface-interaction energy of these residues and lower mobility on palladium lead us to conclude that they are slightly more likely to be adsorbed on palladium surfaces than on gold.

Residue energy and mobility in sequence to global structure and dynamics of a HIV-1 protease (1DIFA) by a coarse-grained Monte Carlo simulation.

Energy, mobility, and structural profiles of residues in a specific sequence of human immunodeficiency virus (HIV)-1 protease chain and its global conformation and dynamics are studied by a coarse-grained computer simulation model on a cubic lattice. HIV-1 protease is described by a chain of 99 residues (nodes) in a specific sequence (1DIFA) with N- and C-terminals on the lattice, where empty lattice sites represent an effective solvent medium. Internal structures of the residues are ignored but their specificities are captured via an interaction (epsilon(ij)) matrix (residue-residue, residue-solvent) of the coefficient (fepsilon(ij)) of the Lennard-Jones potential. Simulations are performed for a range of interaction strength (f) with the solvent-residue interaction describing the quality of the solvent. Snapshots of the protein show considerable changes in the conformation of the protein on varying the interaction. From the mobility and energy profiles of the residues, it is possible to identify the active (and not so active) segments of the protein and consequently their role in proteolysis. Contrary to interaction thermodynamics, the hydrophobic residues possess higher configurational energy and lower mobility while the electrostatic and polar residues are more mobile despite their lower interaction energy. Segments of hydrophobic core residues, crucial for the structural evolution of the protein are identified-some of which are consistent with recent molecular dynamics simulation in context to possible clinical observations. Global energy and radius of gyration of the protein exhibit nonmonotonic dependence on the interaction strength (f) with opposite trends, e.g., rapid transition into globular structure with higher energy. Variations of the rms displacement of the protein and that of a tracer residue, Gly(49), with the time steps show how they slow down on increasing the interaction strength.

Conformation of a coarse-grained protein chain (an aspartic acid protease) model in effective solvent by a bond-fluctuating Monte Carlo simulation.

In a coarse-grained description of a protein chain, all of the 20 amino acid residues can be broadly divided into three groups: Hydrophobic (H) , polar (P) , and electrostatic (E) . A protein can be described by nodes tethered in a chain with a node representing an amino acid group. Aspartic acid protease consists of 99 residues in a well-defined sequence of H , P , and E nodes tethered together by fluctuating bonds. The protein chain is placed on a cubic lattice where empty lattice sites constitute an effective solvent medium. The amino groups (nodes) interact with the solvent (S) sites with appropriate attractive (PS) and repulsive (HS) interactions with the solvent and execute their stochastic movement with the Metropolis algorithm. Variations of the root mean square displacements of the center of mass and that of its center node of the protease chain and its gyration radius with the time steps are examined for different solvent strength. The structure of the protease swells on increasing the solvent interaction strength which tends to enhance the relaxation time to reach the diffusive behavior of the chain. Equilibrium radius of gyration increases linearly on increasing the solvent strength: A slow rate of increase in weak solvent regime is followed by a faster swelling in stronger solvent. Variation of the gyration radius with the time steps suggests that the protein chain moves via contraction and expansion in a somewhat quasiperiodic pattern particularly in strong solvent.

Multiscale mode dynamics of a tethered membrane.

Stochastic dynamics of a tethered membrane with a bond-fluctuating coarse-grained Monte Carlo simulation shows, in addition to diffusion, nondiffusive behavior sensitive to the type of membrane, its size, and quality of the solvent. Motion of the membrane's center node is described by the variation of the mean-square displacement (R{n}{2}) with time step (t) , i.e., R{n}{2} proportional, variantt{2nu} with the exponent nu approximately 18-16 in the short time followed by subdiffusive power laws (i.e., nu approximately 15,110 ) in the intermediate time regimes before reaching diffusion nu=1. The crossover between in-plane wrinkle modes is identified from the segmental (node) motion of the membrane.

Relaxation to native conformation of a bond-fluctuating protein chain with hydrophobic and polar nodes.

The conformation and dynamics of a protein chain with hydrophobic and polar nodes are examined by the bond-fluctuation model using Monte Carlo simulations on a cubic lattice. The minimal (nearest neighbor) interaction leads to standard (self-avoiding walk) conformation, i.e., the scaling of the radius of gyration R(g) with the molecular weight N R(g) proportional, variant Ngamma with gamma approximately 3/5 . Specific interactions with longer range and higher strength are needed to approach the native globular conformations with gamma<3/5 . Relaxation into the globular ground state shows a weak power-law decay, i.e., R(g) proportional, variant t(-alpha) , alpha approximately 0.06-0.12 .