Thermodynamics of interactions between amino acid side chains: experimental differentiation of aromatic-aromatic, aromatic-aliphatic, and aliphatic-aliphatic side-chain interactions in water

Developing a Programmable, Self-Assembling Squash Leaf Curl China Virus (SLCCNV) Capsid Proteins into "Nanocargo"-like Architecture

A new era has begun in which pathogens have become useful scaffolds for nanotechnology applications. In this research/study, an attempt has been made to generate an empty cargo-like architecture from a plant pathogenic virus named Squash leaf curl China virus (SLCCNV). In this approach, SLCCNV coat protein monomers are obtained efficiently by using a yeast Pichia pastoris expression system. Further, dialysis of purified SLCCNV-CP monomers against various pH modified (5-10) disassembly and assembly buffers produced a self-assembled "Nanocargo"-like architecture, which also exhibited an ability to encapsulate magnetic nanoparticles in vitro. Bioinformatics tools were also utilized to predict the possible self-assembly kinetics and bioconjugation sites of coat protein monomers. Significantly, an in vitro biocompatibility study using SLCCNV-Nanocargo particles showed low toxicity to the cells, which eventually proved as a potential nanobiomaterial for biomedical applications.

Pattern to Knowledge: Deep Knowledge-Directed Machine Learning for Residue-Residue Interaction Prediction

Residue-residue close contact (R2R-C) data procured from three-dimensional protein-protein interaction (PPI) experiments is currently used for predicting residue-residue interaction (R2R-I) in PPI. However, due to complex physiochemical environments, R2R-I incidences, facilitated by multiple factors, are usually entangled in the source environment and masked in the acquired data. Here we present a novel method, P2K (Pattern to Knowledge), to disentangle R2R-I patterns and render much succinct discriminative information expressed in different specific R2R-I statistical/functional spaces. Since such knowledge is not visible in the data acquired, we refer to it as deep knowledge. Leveraging the deep knowledge discovered to construct machine learning models for sequence-based R2R-I prediction, without trial-and-error combination of the features over external knowledge of sequences, our R2R-I predictor was validated for its effectiveness under stringent leave-one-complex-out-alone cross-validation in a benchmark dataset, and was surprisingly demonstrated to perform better than an existing sequence-based R2R-I predictor by 28% (p: 1.9E-08). P2K is accessible via our web server on https://p2k.uwaterloo.ca .

Elucidating a chemical defense mechanism of Antarctic sponges: A computational study

In 2000, a novel secondary metabolite (erebusinone, Ereb) was isolated from the Antarctic sea sponge, Isodictya erinacea. The bioactivity of Ereb was investigated, and it was found to inhibit molting when fed to the arthropod species Orchomene plebs. Xanthurenic acid (XA) is a known endogenous molt regulator present in arthropods. Experimental studies have confirmed that XA inhibits molting by binding to either (or both) of two P450 enzymes (CYP315a1 or CYP314a1) that are responsible for the final two hydroxylations in the production of the molt-inducing hormone, 20-hydroxyecdysone (20E). The lack of crystal structures and biochemical assays for CYP315a1 or CYP314a1, has prevented further experimental exploration of XA and Ereb's molt inhibition mechanisms. Herein, a wide array of computational techniques - homology modeling, molecular dynamics simulations, binding site bioinformatics, flexible receptor-flexible ligand docking, and molecular mechanics-generalized Born surface area calculations - have been employed to elucidate the structure-function relationships between the aforementioned P450s and the two described small molecule inhibitors (Ereb and XA). Results indicate that Ereb likely targets CYP315a1 by interacting with a network of aromatic residues in the binding site, while XA may inhibit both CYP315a1 and CYP314a1 because of its aromatic, as well as charged nature.

Influence of side-chain interactions on the self-assembly of discotic tricarboxyamides: a crystallographic insight

Side chains interactions promote the self-assembly of discotic tricarboxyamides to form an entangled fiber network and thermo responsive gel.

Aromatic-aromatic interactions in proteins: beyond the dimer

Aromatic residues are key widespread elements of protein structures and have been shown to be important for structure stability, folding, protein-protein recognition, and ligand binding. The interactions of pairs of aromatic residues (aromatic dimers) have been extensively studied in protein structures. Isolated aromatic molecules tend to form higher order clusters, like trimers, tetramers, and pentamers, that adopt particular well-defined structures. Taking this into account, we have surveyed protein structures deposited in the Protein Data Bank in order to find clusters of aromatic residues in proteins larger than dimers and characterized them. Our results show that larger clusters are found in one of every two unique proteins crystallized so far, that the clusters are built adopting the same trimer motifs found for benzene clusters in vacuum, and that they are clearly nonlocal brining primary structure distant sites together. We extensively analyze the trimers and tetramers conformations and found two main cluster types: a symmetric cluster and an extended ladder. Finally, using calmodulin as a test case, we show aromatic clsuters possible role in folding and protein-protein interactions. All together, our study highlights the relevance of aromatic clusters beyond the dimer in protein function, stability, and ligand recognition.

Redox control of GTPases: from molecular mechanisms to functional significance in health and disease

Small GTPases, including the proto-oncoprotein Ras and Rho GTPases, are involved in various cellular signaling events. Some of these small GTPases are redox sensitive, including Ras, Rho, Ran, Dexras1, and Rhes GTPases. Thus, the redox-mediated regulation of these GTPases often determines the course of their cellular signaling cascades. This article takes into consideration the application of Marcus theory to potential redox-based molecular mechanisms in the regulation of these redox-sensitive GTPases and the relevance of such mechanisms to a specific redox-sensitive motif. The discussion also takes into account various diseases, including cancers, heart, and neuronal disorders, that are often linked with the dysregulation of the redox signaling cascades associated with these redox-sensitive GTPases.

Revisiting the carboxylic acid dimers in aqueous solution: interplay of hydrogen bonding, hydrophobic interactions, and entropy

Carboxylic acid dimers are useful model systems for understanding the interplay of hydrogen bonding, hydrophobic effects, and entropy in self-association and assembly. Through extensive sampling with a classical force field and careful free energy analysis, it is demonstrated that both hydrogen bonding and hydrophobic interactions are indeed important for dimerization of carboxylic acids (except formic acid). The dimers are only weakly ordered, and the degree of ordering increases with stronger hydrophobic interactions between longer alkyl chains. Comparison of calculated and experimental dimerization constants reveals a systematic tendency for excessive self-aggregation in current classical force fields. Qualitative and quantitative information on the thermodynamics of hydrogen bonding and hydrophobic interactions derived from these simulations is in excellent agreement with existing results from experiment and theory. These results provide a verification from first principles of previous estimations based on two statistical mechanical hydrophobic theories. We also revisit and clarify the fundamental statistical thermodynamics formalism for calculating absolute binding constants, external entropy, and solvation entropy changes upon association from detailed free energy simulations. This analysis is believed to be useful for a wide range of applications including computational studies of protein-ligand and protein-protein binding.

Protein adsorption isotherm behavior in hydrophobic interaction chromatography

The adsorption behavior of proteins in hydrophobic interaction chromatography (HIC) was evaluated by determining the isotherms of a wide range of proteins on various HIC resin systems. Parallel batch experiments were carried out with eleven proteins on three hydrophobic resins with different ligand chemistries and densities. The effects of salt concentration, resin chemistry and protein properties on the isotherms were also examined. The resulting isotherms exhibited unique patterns of adsorption behaviors. For certain protein-resin combinations, a "critical salt behavior" was observed where the amount of protein bound to the resin increased significantly above this salt concentration. Proteins that exhibited this behavior tended to be relatively large with more solvent accessible hydrophobic surface area. Further, calculations indicated that under these conditions the occupied surface area of the adsorbed protein layer could exceed the accessible surface area. The establishment of unique classes of adsorption behavior may shed light on our understanding of the behavior of proteins in HIC systems.

Description of atomic burials in compact globular proteins by Fermi-Dirac probability distributions

We perform a statistical analysis of atomic distributions as a function of the distance R from the molecular geometrical center in a nonredundant set of compact globular proteins. The number of atoms increases quadratically for small R, indicating a constant average density inside the core, reaches a maximum at a size-dependent distance R(max), and falls rapidly for larger R. The empirical curves turn out to be consistent with the volume increase of spherical concentric solid shells and a Fermi-Dirac distribution in which the distance R plays the role of an effective atomic energy epsilon(R) = R. The effective chemical potential mu governing the distribution increases with the number of residues, reflecting the size of the protein globule, while the temperature parameter beta decreases. Interestingly, betamu is not as strongly dependent on protein size and appears to be tuned to maintain approximately half of the atoms in the high density interior and the other half in the exterior region of rapidly decreasing density. A normalized size-independent distribution was obtained for the atomic probability as a function of the reduced distance, r = R/R(g), where R(g) is the radius of gyration. The global normalized Fermi distribution, F(r), can be reasonably decomposed in Fermi-like subdistributions for different atomic types tau, F(tau)(r), with Sigma(tau)F(tau)(r) = F(r), which depend on two additional parameters mu(tau) and h(tau). The chemical potential mu(tau) affects a scaling prefactor and depends on the overall frequency of the corresponding atomic type, while the maximum position of the subdistribution is determined by h(tau), which appears in a type-dependent atomic effective energy, epsilon(tau)(r) = h(tau)r, and is strongly correlated to available hydrophobicity scales. Better adjustments are obtained when the effective energy is not assumed to be necessarily linear, or epsilon(tau)*(r) = h(tau)*r(alpha,), in which case a correlation with hydrophobicity scales is found for the product alpha(tau)h(tau)*. These results indicate that compact globular proteins are consistent with a thermodynamic system governed by hydrophobic-like energy functions, with reduced distances from the geometrical center, reflecting atomic burials, and provide a conceptual framework for the eventual prediction from sequence of a few parameters from which whole atomic probability distributions and potentials of mean force can be reconstructed.

Classification of protein adsorption and recovery at low salt conditions in hydrophobic interaction chromatographic systems

There is significant interest in establishing appropriate bioprocessing conditions for protein adsorption in hydrophobic interaction chromatographic (HIC) systems without the need for high salt concentrations. In this paper, the adsorption and recovery of proteins under low salt conditions in HIC systems was investigated using a variety of experimental and computational techniques. Parallel batch screening was employed to determine protein adsorption and recovery. Experiments were carried out with twenty six proteins using five resins with different ligand chemistry, ligand density and backbone chemistry. Proteins were classified based on various combinations of adsorption and recovery behavior. In order to gain insight into the effect of protein properties on this behavior, molecular descriptors were computed based on protein crystal structure and primary sequence information as well as a set of hydrophobicity descriptors based on the solvent accessible surface area of the proteins. Finally, classification software CART was employed to determine the key molecular descriptors associated with various types of adsorption behavior.

Chromatographic and fluorometric study of interactions between thiophilic and hydrophobic ligands and tryptophan peptide homologues

The interactions of tryptophan and its peptide homologues with thiophilic ligands were studied in terms of their chromatographic retention and steady-state fluorescence under various conditions, and compared with non-polar structures typically regarded as pure hydrophobic ligands. The experimental results show that both non-polar and polar interactions are involved in what has been termed "thiophilic adsorption chromatography".

Evaluation of methods for measuring amino acid hydrophobicities and interactions

The concept of hydrophobicity has been addressed by researchers in all aspects of science, particularly in the fields of biology and chemistry. Over the past several decades, the study of the hydrophobicity of biomolecules, particularly amino acids has resulted in the development of a variety of hydrophobicity scales. In this review, we discuss the various methods of measuring amino acid hydrophobicity and provide explanations for the wide range of rankings that exist among these published scales. A discussion of the literature on amino acid interactions is also presented. Only a surprisingly small number of papers exist in this rather important area of research; measuring pairwise amino acid interactions will aid in understanding structural aspects of proteins.

Microcalorimetric studies on the interaction mechanism between proteins and hydrophobic solid surfaces in hydrophobic interaction chromatography: effects of salts, hydrophobicity of the sorbent, and structure of the protein

This study examines the effects of different salts as well as the influence of the relative hydrophobicities of different sorbents on the adsorption processes of proteins in hydrophobic interaction chromatography (HIC). Comparative data acquired by the equilibrium binding analysis and by isothermal titration microcalorimetry (ITC) are presented. In particular, thermodynamic parameters, including the enthalpy changes, related to the interactions between several globular proteins and various Toyopearl 650 M sorbents under solvent conditions containing either 2.0 M ammonium sulfate or 2.0 M sodium sulfate at pH 7.0 and 298.15 K have been evaluated in terms of the molecular properties of these systems. The results reveal that the dependence of the free energy change, deltaGads, for protein adsorption to HIC sorbents on the salt composition can be mainly attributed to the enthalpy changes associated with protein and sorbent dehydration and hydrophobic interactions. Differences in binding mechanisms between the n-butyl- and phenyl-HIC sorbents were evident. In the latter case, the participation of pi-pi hydrophobic interactions leads to significant differences in the associated enthalpy and entropy changes. Furthermore, an increase in the hydrophobicity of either the sorbent or the protein resulted in more negative values for the free energy change, which arose mostly from dehydration processes. Entropic effects favoring HIC adsorption increased with an increase in the exposed nonpolar surface area of the protein. Consequently, an increased contribution from the entropy change to the respective change in free energy occurs when HIC sorbents or proteins of higher hydrophobicity are employed, with these larger entropy changes consistent with a change in the interaction mechanism from a binding event dominated by adsorption to a partitioning-like process. Data extracted from the ITC measurements also provided insight into the interaction mechanisms that occur between proteins and hydrophobic solid surfaces, yielding information that can be applied to the HIC purification of proteins according to the concept of critical hydrophobicity of the system and its thermodynamic consequences.

Folding protein models with a simple hydrophobic energy function: the fundamental importance of monomer inside/outside segregation

The present study explores a "hydrophobic" energy function for folding simulations of the protein lattice model. The contribution of each monomer to conformational energy is the product of its "hydrophobicity" and the number of contacts it makes, i.e., E(h,c) = -Sigma N/i=1 c(i)h(i) = -(h.c) is the negative scalar product between two vectors in N-dimensional cartesian space: h = (h1,., hN), which represents monomer hydrophobicities and is sequence-dependent; and c = (c(1),., c(N)), which represents the number of contacts made by each monomer and is conformation-dependent. A simple theoretical analysis shows that restrictions are imposed concomitantly on both sequences and native structures if the stability criterion for protein-like behavior is to be satisfied. Given a conformation with vector c, the best sequence is a vector h on the direction upon which the projection of c - c is maximal, where c is the diagonal vector with components equal to c, the average number of contacts per monomer in the unfolded state. Best native conformations are suggested to be not maximally compact, as assumed in many studies, but the ones with largest variance of contacts among its monomers, i.e., with monomers tending to occupy completely buried or completely exposed positions. This inside/outside segregation is reflected on an apolar/polar distribution on the corresponding sequence. Monte Carlo simulations in two dimensions corroborate this general scheme. Sequences targeted to conformations with large contact variances folded cooperatively with thermodynamics of a two-state transition. Sequences targeted to maximally compact conformations, which have lower contact variance, were either found to have degenerate ground state or to fold with much lower cooperativity.

Analysis of the binding of hydroxamic acid and carboxylic acid inhibitors to the stromelysin-1 (matrix metalloproteinase-3) catalytic domain by isothermal titration calorimetry

Matrix metalloproteinases (MMPs) are implicated in diseases such as arthritis and cancer. Among these enzymes, stromelysin-1 can also activate the proenzymes of other MMPs, making it an attractive target for pharmaceutical design. Isothermal titration calorimetry (ITC) was used to analyze the binding of three inhibitors to the stromelysin catalytic domain (SCD). One inhibitor (Galardin) uses a hydroxamic acid group (pK(a) congruent with 8.7) to bind the active site zinc; the others (PD180557 and PD166793) use a carboxylic acid group (pK(a) congruent with 4.7). Binding affinity increased dramatically as the pH was decreased over the range 5.5-7.5. Experiments carried out at pH 6.7 in several different buffers revealed that approximately one and two protons are transferred to the enzyme-inhibitor complexes for the hydroxamic and carboxylic acid inhibitors, respectively. This suggests that both classes of inhibitors bind in the protonated state, and that one amino acid residue of the enzyme also becomes protonated upon binding. Similar experiments carried out with the H224N mutant gave strong evidence that this residue is histidine 224. DeltaG, DeltaH, DeltaS, and DeltaC(p) were determined for the three inhibitors at pH 6.7, and DeltaC(p) was used to obtain estimates of the solvational, translational, and conformational components of the entropy term. The results suggest that: (1) a polar group at the P1 position can contribute a large favorable enthalpy, (2) a hydrophobic group at P2' can contribute a favorable entropy of desolvation, and (3) P1' substituents of certain sizes may trigger an entropically unfavorable conformational change in the enzyme upon binding. These findings illustrate the value of complete thermodynamic profiles generated by ITC in discovering binding interactions that might go undetected when relying on binding affinities alone.