Construction of genetic code from evolutionary stability

The construction of the genetic code is investigated based on a stability principle. The concept and formulation of mutational deterioration (MD) of the genetic code is proposed. It is proved that the degeneracies of codon multiplets obey the rule to best resist MD. The MD for each ideal multiplet of codons is expressed by four parameters and it takes on a minimum value for real distributions of codons in the multiplet. Then the global mutational deterioration (GMD) of code table is calculated and the minimal code is deduced. The domain-like distribution of hydrophobic and hydrophilic amino acids on the genetic code is explained from the minimization of GMD. It is demonstrated that the standard code is approximately GMD-minimal. By introducing some constraints that are related to the initial condition of the system, we have deduced the standard genetic code from the minimization of GMD. The minimization shows the general trend of evolutionary process to some stable state while the constraints reflect a 'frozen accident.' Many deviant codon assignments are also explained through MD minimization assuming the changeable degrees of degeneracies for some multiplets. So, a possible answer to the question of "Why are synonymous codons and amino acids distributed in the code table just as they are?" is given.     

Intragenic deletions at Atp7a in mouse models for Menkes disease

Mottled mice have mutations in the copper-transporting ATPase Atp7a. They are proven models for the human disorder Menkes disease (MD), which results from mutations in a homologous gene. Mottled mice can be divided into three classes: class 1, in which affected males die before birth; class 2, in which affected males die in the early postnatal period; and class 3, in which affected males survive to adulthood. In humans, it has been shown that mutations that lead to a complete absence of functional protein cause classical MD, which is characterized by death of boys in early childhood. We hypothesized that the most severely affected mottled alleles would be the most likely to carry mutations equivalent to those causing classical MD and therefore undertook mutational analysis of several class 1 mottled alleles to assess whether these were appropriate models for the disease at the molecular level. Two novel mutations, a deletion of exons 11-14 in mottled spot and an insertion in exon 10 leading to missplicing in mottled candy, were identified. However, these are both "in-frame" mutations, as are the other eight Atp7a mutations reported to date, and therefore no frameshift or nonsense mutations have yet been associated with the mottled phenotype. This contrasts with the mutation spectrum associated with MD, emphasizing the need for caution when mottled mice are used as models for the clinical disorder.     

TRPV4-associated skeletal dysplasias

Dominant mutations in the TRPV4 gene result in a bone dysplasia family and form a continuous phenotypic spectrum that includes, in decreasing severity, lethal, and nonlethal metatropic dysplasia (MD), spondylometaphyseal dysplasia Kozlowski type (SMDK), and autosomal dominant brachyolmia. Several rare variant phenotypes that have some overlap but deviate in some ways from the general pattern have also been described. The known variant phenotypes are spondyloepiphyseal dysplasia Maroteaux type (Pseudo-Morquio type 2), parastremmatic dysplasia, and familial digital arthropathy with brachydactyly. Interestingly, different TRPV4 mutations have been associated with dominantly inherited neurologic disorders such as congenital spinal muscular atrophy and hereditary motor and sensory neuropathy. Finally, a small number of patients have been identified in whom a TRPV4 mutation results in a phenotype combining skeletal dysplasia with peripheral neuropathy. The TRPV4 gene encodes a regulated calcium channel implicated in multiple and diverse cellular processes. Over 50 different TRPV4 mutations have been reported, with two codons appearing to be mutational hot spots: P799 in exon 15, mostly associated with MD, and R594 in exon 11, associated with SMDK. While most pathogenic mutations tested so far result in activation of the calcium channel in vitro, the mechanisms through which TRPV4 activation results in skeletal dysplasia and/or peripheral neuropathy remain unclear and the genotype-phenotype correlations in this group of disorders remains somewhat mysterious. Since the phenotypic expression of most mutations seems to be relatively constant, careful clinical and radiographic assessment is useful in directing molecular analysis.     

Computational diagnosis of protein conformational diseases: short molecular dynamics simulations reveal a fast unfolding of r-LDL mutants that cause familial hypercholesterolemia

The molecular basis of conformational diseases frequently resides in mutant proteins constituting a subset of the vast mutational space. While the subtleties of protein structure point to molecular dynamics (MD) techniques as promising tools for an efficient exploration of such a space, the average size of proteins and the time scale of unfolding events make this goal difficult with present computational capabilities. We show here, nevertheless, that an efficient approach is already feasible for modular proteins. Familial hypercholesterolemia (FH) is a conformational disease linked to mutations in the gene encoding the low density lipoprotein receptor. A high percentage of these mutations has been found in the seven small modular binding repeats of the receptor. Taking advantage of its small size, we have performed an in depth MD study of the fifth binding repeat. Fast unfolding dynamics have been observed in the absence of a structural bound calcium ion, which agrees with its reported essential role in the stability of the module. In addition, several mutations detected in FH patients have been analyzed, starting from the native conformation. Our results indicate that in contrast with the wild type protein and an innocuous control mutant, disease-related mutants experience, in short simulation times (2-8 ns), gross departures from the native state that lead to unfolded conformations and, in some cases, to binding site desorganization deriving in calcium release. Computational diagnosis of mutations leading to conformational diseases seems thus feasible, at least for small or modular pathogenic proteins.     

Computational modeling of human coreceptor CCR5 antagonist as a HIV-1 entry inhibitor: using an integrated homology modeling,docking, and membrane molecular dynamics simulation analysis approach

Chemokine receptor 5 (CCR5) is an integral membrane protein that is utilized during human immunodeficiency virus type-1 entry into host cells. CCR5 is a G-protein coupled receptor that contains seven transmembrane (TM) helices. However, the crystal structure of CCR5 has not been reported. A homology model of CCR5 was developed based on the recently reported CXCR4 structure as template. Automated docking of the most potent (14), medium potent (37), and least potent (25) CCR5 antagonists was performed using the CCR5 model. To characterize the mechanism responsible for the interactions between ligands (14, 25, and 37) and CCR5, membrane molecular dynamic (MD) simulations were performed. The position and orientation of ligands (14, 25, and 37) were found to be changed after MD simulations, which demonstrated the ability of this technique to identify binding modes. Furthermore, at the end of simulation, it was found that residues identified by docking were changed and some new residues were introduced in the proximity of ligands. Our results are in line with the majority of previous mutational reports. These results show that hydrophobicity is the determining factor of CCR5 antagonism. In addition, salt bridging and hydrogen bond contacts between ligands (14, 25, and 37) and CCR5 are also crucial for inhibitory activity. The residues newly identified by MD simulation are Ser160, Phe166, Ser180, His181, and Trp190, and so far no site-directed mutagenesis studies have been reported. To determine the contributions made by these residues, additional mutational studies are suggested. We propose a general binding mode for these derivatives based on the MD simulation results of higher (14), medium (37), and lower (25) potent inhibitors. Interestingly, we found some trend for these inhibitors such as, salt bridge interaction between basic nitrogen of ligand and acidic Glu283 seemed necessary for inhibitory activity. Also, two aromatic pockets (pocket I – TM1-3 and pocket II – TM3-6) were linked by the central polar region in TM7, and the simulated inhibitors show important interactions with the Trp86, Tyr89, Tyr108, Phe112, Ile198, Tyr251, Leu255, and Gln280 and Glu283 residues. These results shed light on the usage of MD simulation to identify more stable, optimal binding modes of the inhibitors.     

Lipid biosynthesis in cultures of oilseed rape

Summary This review focuses on how microspore-derived (MD) embros and cell suspension cultures of oilseed rape have been used to advance our understanding of the biochemistry and molecular biology of lipid biosynthesis in plants. Both types of cultures are easily maintained and circumvent the difficulties associated with using developing seeds for investigations of lipid biosynthesis. Developing MD embryos exhibit a similar storage lipid accumulation profile and fatty acid composition to developing seed. The use of dihaploids derived from plantlets of MD embryos have accelerated breeding programs and have proven useful in the detection of recessive mutations. MD embryos and MD cell suspension cultures have been particularly useful in investigating the properties of key enzymes involved in triacylglycerol (TG) bioassembly. MD cell suspension cultures, however, offer the advantage of being able to study lipid metabolism in the absence of cellular differentiation. TG accumulation can be induced in MD cell suspension cultures by increasing the sucrose concentration of the growth medium thereby providing a useful system to investigate gene expression and the proteomics of lipid biosynthesis.     

Computational investigation of the HIV-1 Rev multimerization using molecular dynamics simulations and binding free energy calculations

The HIV Rev protein mediates the nuclear export of viral mRNA, and is thereby essential for the production of late viral proteins in the replication cycle. Rev forms a large organized multimeric protein-protein complex for proper functioning. Recently, the three-dimensional structures of a Rev dimer and tetramer have been resolved and provide the basis for a thorough structural analysis of the binding interaction. Here, molecular dynamics (MD) and binding free energy calculations were performed to elucidate the forces thriving dimerization and higher order multimerization of the Rev protein. It is found that despite the structural differences between each crystal structure, both display a similar behavior according to our calculations. Our analysis based on a molecular mechanics-generalized Born surface area (MM/GBSA) and a configurational entropy approach demonstrates that the higher order multimerization site is much weaker than the dimerization site. In addition, a quantitative hot spot analysis combined with a mutational analysis reveals the most contributing amino acid residues for protein interactions in agreement with experimental results. Additional residues were found in each interface, which are important for the protein interaction. The investigation of the thermodynamics of the Rev multimerization interactions performed here could be a further step in the development of novel antiretrovirals using structure based drug design. Moreover, the variability of the angle between each Rev monomer as measured during the MD simulations suggests a role of the Rev protein in allowing flexibility of the arginine rich domain (ARM) to accommodate RNA binding.     

Headgroup Conformations of Phospholipids from Molecular Dynamics Simulation: Sampling Challenges and Comparison to Experiment

The preferred conformations of the glycerol region of a phospholipid have been explored using replica exchange molecular dynamics (MD) simulations and compared with the results of standard MD approaches and with experiment. We found that due to isomerization rates in key torsions that are slow on the timescale of atomistic MD simulations, standard MD is not able to produce accurate equilibrium conformer distributions from reasonable trajectory lengths (e.g., on the 100 ns) timescale. Replica exchange MD, however, results in quite efficient sampling due to the rapid increase in isomerization rate with temperature. The equilibrium distributions obtained from replica exchange MD have been compared with the results of experimental nuclear magnetic resonance observations. This comparison suggests that the sampling approach demonstrated here is a valuable tool that can be used in evaluating force fields for molecular simulation of lipids.     

Probing structural features of Alzheimer's amyloid-β pores in bilayers using site-specific amino acid substitutions

A current hypothesis for the pathology of Alzheimer's disease (AD) proposes that amyloid-β (Aβ) peptides induce uncontrolled, neurotoxic ion flux across cellular membranes. The mechanism of ion flux is not fully understood because no experiment-based Aβ channel structures at atomic resolution are currently available (only a few polymorphic states have been predicted by computational models). Structural models and experimental evidence lend support to the view that the Aβ channel is an assembly of loosely associated mobile β-sheet subunits. Here, using planar lipid bilayers and molecular dynamics (MD) simulations, we show that amino acid substitutions can be used to infer which residues are essential for channel structure. We created two Aβ(1-42) peptides with point mutations: F19P and F20C. The substitution of Phe19 with Pro inhibited channel conductance. MD simulation suggests a collapsed pore of F19P channels at the lower bilayer leaflet. The kinks at the Pro residues in the pore-lining β-strands induce blockage of the solvated pore by the N-termini of the chains. The cysteine mutant is capable of forming channels, and the conductance behavior of F20C channels is similar to that of the wild type. Overall, the mutational analysis of the channel activity performed in this work tests the proposition that the channels consist of a β-sheet rich organization, with the charged/polar central strand containing the mutation sites lining the pore, and the C-terminal strands facing the hydrophobic lipid tails. A detailed understanding of channel formation and its structure should aid studies of drug design aiming to control unregulated Aβ-dependent ion fluxes.     

The challenge of modeling macular degeneration in mice

Macular degenerations (MD), age-related or inherited, interfere with the ability to read, drive and recognize faces. Understanding this class of diseases has been challenging because the mouse, the mammal most amenable to genetic manipulation, lacks a macula. Here we discuss whether we can model MD in the mouse, present criteria for an 'ideal' mouse model of MD and discuss how mouse models have contributed to our knowledge of MD by contrasting how well they meet the 'ideal' criteria with how informative they have actually been. By modeling MD in mice, we can learn about aspects of MD that an animal with a macula would be unable to teach us.     

Comparing analysis methods for mutation-accumulation data: a simulation study

We simulated single-generation data for a fitness trait in mutation-accumulation (MA) experiments, and we compared three methods of analysis. Bateman-Mukai (BM) and maximum likelihood (ML) need information on both the MA lines and control lines, while minimum distance (MD) can be applied with or without the control. Both MD and ML assume gamma-distributed mutational effects. ML estimates of the rate of deleterious mutation had larger mean square error (MSE) than MD or BM had due to large outliers. MD estimates obtained by ignoring the mean decline observed from comparison to a control are often better than those obtained using that information. When effects are simulated using the gamma distribution, reducing the precision with which the trait is assayed increases the probability of obtaining no ML or MD estimates but causes no appreciable increase of the MSE. When the residual errors for the means of the simulated lines are sampled from the empirical distribution in a MA experiment, instead of from a normal one, the MSEs of BM, ML, and MD are practically unaffected. When the simulated gamma distribution accounts for a high rate of mild deleterious mutation, BM detects only approximately 30% of the true deleterious mutation rate, while MD or ML detects substantially larger fractions. To test the robustness of the methods, we also added a high rate of common contaminant mutations with constant mild deleterious effect to a low rate of mutations with gamma-distributed deleterious effects and moderate average. In that case, BM detects roughly the same fraction as before, regardless of the precision of the assay, while ML fails to provide estimates. However, MD estimates are obtained by ignoring the control information, detecting approximately 70% of the total mutation rate when the mean of the lines is assayed with good precision, but only 15% for low-precision assays. Contaminant mutations with only tiny deleterious effects could not be detected with acceptable accuracy by any of the above methods.     

Oxygen affinity controlled by dynamical distal conformations: the soybean leghemoglobin and the Paramecium caudatum hemoglobin cases

The binding of diatomic ligands, such as O(2), NO, and CO, to heme proteins is a process intimately related with their function. In this work, we analyzed by means of a combination of classical Molecular Dynamics (MD) and Hybrid Quantum-Classical (QM/MM) techniques the existence of multiple conformations in the distal site of heme proteins and their influence on oxygen affinity regulation. We considered two representative examples: soybean leghemoglobin (Lba) and Paramecium caudatum truncated hemoglobin (PcHb). The results presented in this work provide a molecular interpretation for the kinetic, structural, and mutational data that cannot be obtained by assuming a single distal conformation.     

Assessment of the molecular dynamics structure of DNA in solution based on calculated and observed NMR NOESY volumes and dihedral angles from scalar coupling constants

To assess the accuracy of the molecular dynamics (MD) models of nucleic acids, a detailed comparison between MD-calculated and NMR-observed indices of the dynamical structure of DNA in solution has been carried out. The specific focus of our comparison is the oligonucleotide duplex, d(CGCGAATTCGCG)(2), for which considerable structural data have been obtained from crystallography and NMR spectroscopy. An MD model for the structure of d(CGCGAATTCGCG)(2) in solution, based on the AMBER force field, has been extended with a 14 ns trajectory. New NMR data for this sequence have been obtained in order to allow a detailed and critical comparison between the calculated and observed parameters. Observable two-dimensional (2D) nuclear Overhauser effect spectroscopy (NOESY) volumes and scalar coupling constants were back-calculated from the MD trajectory and compared with the corresponding NMR data. The comparison of these results indicate that the MD model is in generally good agreement with the NMR data, and shows closer accord with experiment than back-calculations based on the crystal structure of d(CGCGAATTCGCG)(2) or the canonical A or B forms of the sequence. The NMR parameters are not particularly sensitive to the known deficiency in the AMBER MD model, which is a tendency toward undertwisting of the double helix when the parm.94 force field is used. The MD results are also compared with a new determination of the solution structure of d(CGCGAATTCGCG)(2) using NMR dipolar coupling data.     

Promotion of Crystal Phase Transitions by Mass-of-cell Control in Molecular Dynamics Simulations: Phase Transitions in Benzene Crystals

Abstract

The promotion of crystal phase transitions in molecular dynamics (MD) simulations was realized by controlling the momentum of the MD cell. It was implemented by increasing the mass or velocity of the MD cell instantaneously during simulations within the framework of the constant-pressure method by Parrinello and Rahman. This method induced phase transitions in benzene crystals which have not been obtained in conventional MD simulations. This method is useful for the global search of stable (and metastable) crystal structures.     

The isolation of Yersinia intermedia strains with a plasmid of 82-megadalton molecular weight in natural populations of Yersinia

For the first time Y. intermedia strains containing plasmids with a molecular weight of 82 MD have been detected in natural populations of urease-positive Yersinia. Such populations have been isolated from two species of birds and from the soil in the area where they have been killed (the Maritime Territory), as well as from washings from the surface of onions in a vegetable store (Chita Province). The strains, administered orally to white mice, proved to be nonpathogenic. Plasmids with a molecular weight of 82 MD are supposed to occur in natural populations of other Yersinia species.     

Structure and axis curvature in two dA6 x dT6 DNA oligonucleotides: comparison of molecular dynamics simulations with results from crystallography and NMR spectroscopy

Molecular dynamics (MD) simulations have been performed on the A6 containing DNA dodecamers d(GGCAAAAAACGG) solved by NMR and d(CGCAAAAAAGCG) solved by crystallography. The experimental structures differ in the direction of axis bending and in other small but important aspects relevant to the DNA curvature problem. Five nanosecond MD simulations of each sequence have been performed, beginning with both the NMR and crystal forms as well as canonical B-form DNA. The results show that all simulations converge to a common form in close proximity to the observed NMR structure, indicating that the structure obtained in the crystal is likely a strained form due to packing effects. A-tracts in the MD model are essentially straight. The origin of axis curvature is found at pyrimidine-purine steps in the flanking sequences.     

Mutation network-based understanding of pleiotropic and epistatic mutational behavior of Enterococcus faecalis FMN-dependent azoreductase

We previously identified a highly active homodimeric FMN-dependent NADH-preferred azoreductase (AzoA) from Enterococcus faecalis, which cleaves the azo bonds (R-N?N-R) of diverse azo dyes, and determined its crystal structure. The preliminary network-based mutational analysis suggested that the two residues, Arg-21 and Asn-121, have an apparent mutational potential for fine-tuning of AzoA, based on their beneficial pleiotropic feedbacks. However, epistasis between the two promising mutational spots in AzoA has not been obtained in terms of substrate binding and azoreductase activity. In this study, we further quantified, visualized, and described the pleiotropic and/or epistatic behavior of six single or double mutations at the positions, Arg-21 and Asn-121, as a further research endeavor for beneficial fine-tuning of AzoA. Based on this network-based mutational analysis, we showed that pleiotropy and epistasis are common, sensitive, and complex mutational behaviors, depending mainly on the structural and functional responsibility and the physicochemical properties of the residue(s) in AzoA.     

Enhanced sampling simulations to construct free-energy landscape of protein–partner substrate interaction

Molecular dynamics (MD) simulations using all-atom and explicit solvent models provide valuable information on the detailed behavior of protein–partner substrate binding at the atomic level. As the power of computational resources increase, MD simulations are being used more widely and easily. However, it is still difficult to investigate the thermodynamic properties of protein–partner substrate binding and protein folding with conventional MD simulations. Enhanced sampling methods have been developed to sample conformations that reflect equilibrium conditions in a more efficient manner than conventional MD simulations, thereby allowing the construction of accurate free-energy landscapes. In this review, we discuss these enhanced sampling methods using a series of case-by-case examples. In particular, we review enhanced sampling methods conforming to trivial trajectory parallelization, virtual-system coupled multicanonical MD, and adaptive lambda square dynamics. These methods have been recently developed based on the existing method of multicanonical MD simulation. Their applications are reviewed with an emphasis on describing their practical implementation. In our concluding remarks we explore extensions of the enhanced sampling methods that may allow for even more efficient sampling.     

Local Diffusion Homogeneity (LDH): An Inter-Voxel Diffusion MRI Metric for Assessing Inter-Subject White Matter Variability

Many diffusion parameters and indices (e.g., fractional anisotropy [FA] and mean diffusivity [MD]) have been derived from diffusion magnetic resonance imaging (MRI) data. These parameters have been extensively applied as imaging markers for localizing white matter (WM) changes under various conditions (e.g., development, degeneration and disease). However, the vast majority of the existing parameters is derived from intra-voxel analyses and represents the diffusion properties solely within the voxel unit. Other types of parameters that characterize inter-voxel relationships have been largely overlooked. In the present study, we propose a novel inter-voxel metric referred to as the local diffusion homogeneity (LDH). This metric quantifies the local coherence of water molecule diffusion in a model-free manner. It can serve as an additional marker for evaluating the WM microstructural properties of the brain. To assess the distinguishing features between LDH and FA/MD, the metrics were systematically compared across space and subjects. As an example, both the LDH and FA/MD metrics were applied to measure age-related WM changes. The results indicate that LDH reveals unique inter-subject variability in specific WM regions (e.g., cerebral peduncle, internal capsule and splenium). Furthermore, there are regions in which measurements of age-related WM alterations with the LDH and FA/MD metrics yield discrepant results. These findings suggest that LDH and FA/MD have different sensitivities to specific WM microstructural properties. Taken together, the present study shows that LDH is complementary to the conventional diffusion-MRI markers and may provide additional insights into inter-subject WM variability. Further studies, however, are needed to uncover the neuronal mechanisms underlying the LDH.     

Benzo[a]pyrene, aflatoxine B₁ and acetaldehyde mutational patterns in TP53 gene using a functional assay: relevance to human cancer aetiology

Mutations in the TP53 gene are the most common alterations in human tumours. TP53 mutational patterns have sometimes been linked to carcinogen exposure. In hepatocellular carcinoma, a specific G>T transversion on codon 249 is classically described as a fingerprint of aflatoxin B(1) exposure. Likewise G>T transversions in codons 157 and 158 have been related to tobacco exposure in human lung cancers. However, controversies remain about the interpretation of TP53 mutational pattern in tumours as the fingerprint of genotoxin exposure. By using a functional assay, the Functional Analysis of Separated Alleles in Yeast (FASAY), the present study depicts the mutational pattern of TP53 in normal human fibroblasts after in vitro exposure to well-known carcinogens: benzo[a]pyrene, aflatoxin B(1) and acetaldehyde. These in vitro patterns of mutations were then compared to those found in human tumours by using the IARC database of TP53 mutations. The results show that the TP53 mutational patterns found in human tumours can be only partly ascribed to genotoxin exposure. A complex interplay between the functional impact of the mutations on p53 phenotype and the cancer natural history may affect these patterns. However, our results strongly support that genotoxins exposure plays a major role in the aetiology of the considered cancers.