Use of restrained molecular dynamics in water to determine three-dimensional protein structure: prediction of the three-dimensional structure of Ecballium elaterium trypsin inhibitor II

Refinement of distance geometry (DG) structures of EETI-II (Heitz et al.: Biochemistry 28:2392-2398, 1989), a member of the squash family trypsin inhibitor, have been carried out by restrained molecular dynamics (RMD) in water. The resulting models show better side chain apolar/polar surface ratio and estimated solvation free energy than structures refined "in vacuo." The consistent lower values of residual NMR constraint violations, apolar/polar surface ratio, and solvation free energy for one of these refined structures allowed prediction of the 3D folding and disulfide connectivity of EETI-II. Except for the few first residues for which no NMR constraints were available, this computer model fully agreed with X-ray structures of CMTI-I (Bode et al.: FEBS Lett. 242:285-292, 1989) and EETI-II complexed with trypsin that appeared after the RMD simulation was completed. Restrained molecular dynamics in water is thus proved to be highly valuable for refinement of DG structures. Also, the successful use of apolar/polar surface ratio and of solvation free energy reinforce the analysis of Novotny et al. (Proteins 4:19-30, 1988) and shows that these criteria are useful indicators of correct versus misfolded models.     

Monte carlo simulations of protein folding. II. Application to protein A,ROP, and crambin

The hierarchy of lattice Monte Carlo models described in the accompanying paper (Kolinski, A., Skolnick, J. Monte Carlo simulations of protein folding. I. Lattice model and interaction scheme. Proteins 18:338–352, 1994) is applied to the simulation of protein folding and the prediction of 3-dimensional structure. Using sequence information alone, three proteins have been successfully folded: the B domain of staphylococcal protein A, a 120 residue, monomeric version of ROP dimer, and crambin. Starting from a random expanded conformation, the model proteins fold along relatively well-defined folding pathways. These involve a collection of early intermediates, which are followed by the final (and rate-determining) transition from compact intermediates closely resembling the molten globule state to the native-like state. The predicted structures are rather unique, with native-like packing of the side chains. The accuracy of the predicted native conformations is better than those obtained in previous folding simulations. The best (but by no means atypical) folds of protein A have a coordinate rms of 2.25 Å from the native Cα trace, and the best coordinate rms from crambin is 3.18 Å. For ROP monomer, the lowest coordinate rms from equivalent Cαs of ROP dimer is 3.65 Å. Thus, for two simple helical proteins and a small α/β protein, the ability to predict protein structure from sequence has been demonstrated. © 1994 John Wiley & Sons, Inc.     

Discrimination of folding types of globular proteins based on average distance maps constructed from their sequences

It has been shown that probable portions which form contacts in a protein can be predicted by means of an average distance map (ADM) as well as regular structures (-helices and -turns) defined as short-range compact regions (Kikuchiet al., 1988a,c). In this paper, we analyze the occurrence of those portions and short-range compact regions on ADMs for various proteins regarding their folding types. We have found out that each folding type of proteins shows characteristic distribution of such parts on ADMS. We also discuss the possibility of the prediction of folding types of proteins by ADMs.     

Chemical induction of β-carotene biosynthesis

Marsh white seedless grapefruit were treated with the 2-diethylaminoethanol esters of the following acids: benzoic, phenylacetic, hydrocinnamic, 4-phenylbutyric, 5-phenylvaleric, valeric, hexanoic, heptanoic, octanoic, nonanoic, 5-chlorovaleric, cyclohexanecarboxylic, phenoxyacetic, p-chlorophenoxyacetic, 3-phenoxypropionic, cinnamic and p-chlorocinnamic. Several of these esters, in particular the hexanoate, 4-phenylbutyrate and cinnamate, caused the accumulation of large amounts of β-carotene. The effects of the hexanoate and of 2-phenoxytriethylamine, which causes only lycopene accumulation, were studied as functions of time. The hexanoate caused the rapid accumulation of lycopene during the first day. The amount of lycopene then began to decrease and that of β-carotene increased until, after 14 days, β-carotene was the major pigment. 2-Phenoxytriethylamine caused rapid lycopene accumulation during the first day and a slow steady increase afterwards. Thus, the mode of action of the β-carotene inducers may be similar to that of the lycopene inducers except that the former are probably rapidly hydrolysed by the esterase(s) in the flavedo, so that they no longer inhibit the cyclase(s), and β-carotene is accumulated at the expanse of lycopene.     

Structure--activity relationships of chemical inducers of carotenoid biosynthesis

Fifteen amines having a profound effect on carotenogenesis in Marsh seedless grapefruit are reported. The compounds fall into three series: Et₂N(CH₂)_nMe (n = 4–8), Et₂N(CH₂)_nPh (n = 1–5), and Et₂NCH₂CH₂OC₆H₄R (R=H, p-Me, p-Et, p-iso-Pr, p-tert-Bu), There was up to an 11-fold increase in the total carotene content. Lycopene, not normally accumulated, became a major pigment. The inducing ability of the amines on carotenoid biosynthesis is correlated with the octanol-water partition coefficient. The mode of action appears to be similar to that of 2-(4-chlorophenylthio)triethylamine hydrochloride.     

Structural analysis based on state-space modeling.

A new method has been developed to compute the probability that each amino acid in a protein sequence is in a particular secondary structural element. Each of these probabilities is computed using the entire sequence and a set of predefined structural class models. This set of structural classes is patterned after Jane Richardson''s taxonomy for the domains of globular proteins. For each structural class considered, a mathematical model is constructed to represent constraints on the pattern of secondary structural elements characteristic of that class. These are stochastic models having discrete state spaces (referred to as hidden Markov models by researchers in signal processing and automatic speech recognition). Each model is a mathematical generator of amino acid sequences; the sequence under consideration is modeled as having been generated by one model in the set of candidates. The probability that each model generated the given sequence is computed using a filtering algorithm. The protein is then classified as belonging to the structural class having the most probable model. The secondary structure of the sequence is then analyzed using a "smoothing" algorithm that is optimal for that structural class model. For each residue position in the sequence, the smoother computes the probability that the residue is contained within each of the defined secondary structural elements of the model. This method has two important advantages: (1) the probability of each residue being in each of the modeled secondary structural elements is computed using the totality of the amino acid sequence, and (2) these probabilities are consistent with prior knowledge of realizable domain folds as encoded in each model. As an example of the method''s utility, we present its application to flavodoxin, a prototypical alpha/beta protein having a central beta-sheet, and to thioredoxin, which belongs to a similar structural class but shares no significant sequence similarity.     

Tertiary motifs as building blocks for the design of protein‐binding peptides

Despite advances in protein engineering, the de novo design of small proteins or peptides that bind to a desired target remains a difficult task. Most computational methods search for binder structures in a library of candidate scaffolds, which can lead to designs with poor target complementarity and low success rates. Instead of choosing from pre‐defined scaffolds, we propose that custom peptide structures can be constructed to complement a target surface. Our method mines tertiary motifs (TERMs) from known structures to identify surface‐complementing fragments or “seeds.” We combine seeds that satisfy geometric overlap criteria to generate peptide backbones and score the backbones to identify the most likely binding structures. We found that TERM‐based seeds can describe known binding structures with high resolution: the vast majority of peptide binders from 486 peptide‐protein complexes can be covered by seeds generated from single‐chain structures. Furthermore, we demonstrate that known peptide structures can be reconstructed with high accuracy from peptide‐covering seeds. As a proof of concept, we used our method to design 100 peptide binders of TRAF6, seven of which were predicted by Rosetta to form higher‐quality interfaces than a native binder. The designed peptides interact with distinct sites on TRAF6, including the native peptide‐binding site. These results demonstrate that known peptide‐binding structures can be constructed from TERMs in single‐chain structures and suggest that TERM information can be applied to efficiently design novel target‐complementing binders.     

Influence of systems biology response and environmental exposure level on between-subject variability in breath and blood biomarkers

To explain the underlying causes of apparently stochastic disease, current research is focusing on systems biology approaches wherein individual genetic makeup and specific ‘gene–environment’ interactions are considered. This is an extraordinarily complex task because both the environmental exposure profiles and the specific genetic susceptibilities presumably have large variance components. In this article, the focus is on the initial steps along the path to disease outcome namely environmental uptake, biologically available dose, and preclinical effect. The general approach is to articulate a conceptual model and identify biomarker measurements that could populate the model with hard data. Between-subject variance components from different exposure studies are used to estimate the source and magnitude of the variability of biomarker measurements. The intent is to determine the relative effects of different biological media (breath or blood), environmental compounds and their metabolites, different concentration levels, and levels of environmental exposure control. Examples are drawn from three distinct exposure biomarker studies performed by the US Environmental Protection Agency that studied aliphatic and aromatic hydrocarbons, trichloroethylene and methyl tertiary butyl ether. All results are based on empirical biomarker measurements of breath and blood from human subjects; biological specimens were collected under appropriate Institutional Review Board protocols with informed consent of the subjects. The ultimate goal of this work is to develop a framework for eventually assessing the total susceptibility ranges along the toxicological pathway from exposure to effect. The investigation showed that exposures are a greater contributor to biomarker variance than are internal biological parameters.     

Population density analysis for determining the protonation state of the catalytic dyad in BACE1-tertiary carbinamine-based inhibitor complex

BACE1 is an aspartyl protease with a very relevant role in medicinal chemistry related to Alzheimer Disease since it has demonstrated to be a promising therapeutic target for inhibition and possible control for the progress of the peptide accumulation characteristic of this pathology. The enzymatic activity of this protein is given by the aspartic dyad, Asp93 and Asp289, which can adopt several protonation states depending on the chemical nature of its inhibitors, this is, monoprotonated, diprotonated and di-deprotonated states. In the present study, the analysis of the population density, for a series of protein-inhibitor molecular dynamics simulations, was carried out to identify the most feasible protonation state adopted by the catalytic dyad in the presence of tertiary carbinamine (TC) transition state analog inhibitors. The results revealed that the monoprotonated Asp289i state, in which the Asp93 and Asp289 residue side chains are deprotonated and protonated on the inner oxygen, respectively, is the most preferred in the presence of TC family inhibitors. This result was obtained after evaluating, for all 9 possible protonation state configurations, the individual and combined population densities of a set of parameters sensitive to protonation state of the Aspartic dyad, using an X-ray experimental BACE1/TC crystallographic structure as reference. This case study demonstrates again the usefulness of the concept of population density as a quantitative tool to establish the most stable system settings, among all possible, by measuring the level of occurrence of simultaneous events obtained from a sampling over time. These results will help to clear the phenomena related to the TCs inhibitory pathway, as well as assist in the design of better TC inhibitors against Alzheimer’s protease.     

Molecular characterization influencing metal resistance in the Cupriavidus/Ralstonia genomes

Our environment is stressed with a load of heavy and toxic metals. Microbes, abundant in our environment, are found to adapt well to this metal-stressed condition. A comparative study among five Cupriavidus/Ralstonia genomes can offer a better perception of their evolutionary mechanisms to adapt to these conditions. We have studied codon usage among 1051 genes common to all these organisms and identified 15 optimal codons frequently used in highly expressed genes present within 1051 genes. We found the core genes of Cupriavidus metallidurans CH34 have a different optimal codon choice for arginine, glycine and alanine in comparison with the other four bacteria. We also found that the synonymous codon usage bias within these 1051 core genes is highly correlated with their gene expression. This supports that translational selection drives synonymous codon usage in the core genes of these genomes. Synonymous codon usage is highly conserved in the core genes of these five genomes. The only exception among them is C. metallidurans CH34. This genomewide shift in synonymous codon choice in C. metallidurans CH34 may have taken place due to the insertion of new genes in its genomes facilitating them to survive in heavy metal containing environment and the co-evolution of the other genes in its genome to achieve a balance in gene expression. Structural studies indicated the presence of a longer N-terminal region containing a copper-binding domain in the cupC proteins of C. metallidurans CH3 that helps it to attain higher binding efficacy with copper in comparison with its orthologs.