Thermodynamic analysis of the drug-receptor interaction

Thermodynamic analysis of pharmacologic data potentially offers an insight into the molecular events underlying drug-receptor interactions not obtainable by other techniques. Embodied in thermodynamics are the laws governing the interconvertibility of heat and work and, hence, it is a particularly apt framework for the analysis of the transduction of information from ligand to biological tissue during the initiation of a drug effect. Implicit in thermodynamic analysis of pharmacologic data is quantitative measurement of the driving forces involved in the drug-receptor interaction (in place of less precise terms such as "affinity"). In addition, the cautious interpretation of thermodynamic analysis can give clues to the underlying mechanisms of the drug-receptor interaction that is beyond the resolving power of other parameters, such as the dissociation constant. The present review is an attempt to identify representative reports that have overtly analyzed pharmacologic data with thermodynamic analysis, to summarize the findings within and across studies (particularly regarding enthalpy- versus entropy-driven binding of agonists and antagonists), to point out and address some apparent inconsistencies that can arise, and to consider the application of thermodynamic analysis to data obtained using isolated tissue preparations.     

A computergraphic determination of the chemotactic peptide preferred conformation

Replacement of leucine in the chemotactic peptide For-Met-Leu-Phe by the sterically constrained amino acids alpha-aminoisobutyric acid and aminocyclohexanecarboxylic acid affords compounds of equal or greater activity than the parent. NMR studies indicate that the parent compound is present as a beta-sheet in solution, whereas the analogues prefer a beta-turn. Application of molecular modelling would indicate that the beta-turn conformer is energetically preferable and thus suggests that it is the orientation adopted by the peptides.     

Molecular electrostatic potential as a factor of drug-receptor recognition

When a drug molecule approaches a non-specific acceptor both molecules are in electrostatic fields of equal sign which prevents drug-acceptor complex formation. At the same time, the drug-acceptor system does not achieve the thermodynamic global minimum. Otherwise, when a certain drug interacts with its specific receptor, mutual compensation of their molecular electrostatic potentials takes place. Then separate atoms and groups of the drug molecule can bind to the receptor. We show that the fundamental role of molecular electrostatic potential in the process of drug-receptor recognition consists in fast correction of errors.     

(Extra)thermodynamics of the drug-receptor interaction.

A core concept in pharmacology is drug-receptor affinity, i.e., the tendency of a drug molecule to bind to one or more receptors due to the collective influence of multiple molecular forces. The estimation of affinity as a dissociation constant (reciprocal of the equilibrium constant) is extraordinarily valuable. However, elucidation of the nature of the underlying concept--i.e., what accounts for affinity--is not achievable using such a static measure. Observing how the system responds to a perturbation (e.g., to a change in temperature) reveals more fundamental information. The present review summarizes the general concepts of thermodynamic analysis applied to drug-receptor interactions and discusses 'extrathermodynamic' phenomena, such as enthalpy-entropy 'compensation'. Together, these concepts may provide insight into the nature of drug-receptor interactions, begin to elucidate the forces that underlie such interactions--and begin to define and refine more nebulous terms such as affinity.     

A modified resonant recognition model to predict protein-protein interaction

Proteins are fundamental components of all living cells and the protein-protein interaction plays an important role in vital movement. This paper briefly introduced the original Resonant Recognition Model (RRM), and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM). The key characteristic of the new model is that it can predict directly the protein-protein interaction from the primary sequence, and the MRRM is more suitable than the RRM for this prediction. The results of numerical experiments show that the MRRM is effective for predicting the protein-protein interaction. Translated from Journal of Shanghai University (Natural Science), 2006, 12(1): 69–73 [译自: 上海大学学报(自然科学版)]     

A modified resonant recognition model to predict protein-protein interaction

Proteins are fundamental components of all living cells and the protein-protein interaction plays an important role in vital movement.This paper briefly introduced the original Resonant Recognition Model (RRM),and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM).The key characteristic of the new model is that it can predict directly the proteinprotein interaction from the primary sequence,and the MRRM is more suitable than the RRM for this prediction.The results of numerical experiments show that the MRRM is effective for predicting the protein-protein interaction.     

A discrete time stochastic model of a two prey, one predator species interaction

A stochastic discrete time model of a two prey, one predator interaction, an extension of one and two species models proposed by Leslie (1958) and Leslie and Gower, 1958, Leslie and Gower, 1960, is studied. Monte Carlo simulations and the stability properties of the analogous continuous time deterministic model suggest the following hypotheses. (1) The two prey, one predator interaction is in general unstable. The range of parameters allowing coexistence of all three species is small. (2) Deterministically the predator always survives. (3) If the parameters defining the effects of density on the rates of population growth are large, the simulations lead to the rapid extinction of all three species or all but one of the prey species even if the interaction is deterministically stable. (4) The outcome of this three species interaction is largely probabilistic over a wide range of parameters. (5) A prey species with a competitive advantage over a second prey species may still find it difficult to invade and displace the second prey species if the density of the second prey species is high. Increasing the density of the predator offsets this numerical advantage somewhat. (6) The introduction of a predator common to two noncompeting species of prey usually leads to the extinction of one of the prey species. (7) In a stable two prey, one predator interaction the fluctuations of the two prey species are nonperiodic and erratic. The fluctuations of the rarer prey species are damped relative to the commoner species and the fluctuations of the rarer prey species behave as if the series has no fixed mean abundance. The predator population fluctuates with a remarkably constant period. The relevance of these hypotheses to the problem of relating population stability and persistence with the number of species in a community is discussed.     

A Bayesian network model for protein fold and remote homologue recognition

MOTIVATION: The Bayesian network approach is a framework which combines graphical representation and probability theory, which includes, as a special case, hidden Markov models. Hidden Markov models trained on amino acid sequence or secondary structure data alone have been shown to have potential for addressing the problem of protein fold and superfamily classification. RESULTS: This paper describes a novel implementation of a Bayesian network which simultaneously learns amino acid sequence, secondary structure and residue accessibility for proteins of known three-dimensional structure. An awareness of the errors inherent in predicted secondary structure may be incorporated into the model by means of a confusion matrix. Training and validation data have been derived for a number of protein superfamilies from the Structural Classification of Proteins (SCOP) database. Cross validation results using posterior probability classification demonstrate that the Bayesian network performs better in classifying proteins of known structural superfamily than a hidden Markov model trained on amino acid sequences alone.     

On the stability properties of a stochastic model for phage-bacteria interaction in open marine environment

In this paper we extend the deterministic model for the epidemics induced by virulent phages on bacteria in marine environment introduced by Beretta and Kuang [Math. Biosci. 149 (1998) 57], allowing random fluctuations around the positive equilibrium. The stochastic stability properties of the model are investigated both analytically and numerically suggesting that the deterministic model is robust with respect to stochastic perturbations.     

A stochastic model for the development of Bateson-Dobzhansky-Muller incompatibilities that incorporates protein interaction networks

Speciation is characterized by the development of reproductive isolating barriers between diverging groups. Intrinsic post-zygotic barriers of the type envisioned by Bateson, Dobzhansky, and Muller are deleterious epistatic interactions among loci that reduce hybrid fitness, leading to reproductive isolation. The first formal population genetic model of the development of these barriers was published by Orr in 1995, and here we develop a more general model of this process by incorporating finite protein-protein interaction networks, which reduce the probability of deleterious interactions in vivo. Our model shows that the development of deleterious interactions is limited by the density of the protein-protein interaction network. We have confirmed our analytical predictions of the number of possible interactions given the number of allele substitutions by using simulations on the Saccharomyces cerevisiae protein-protein interaction network. These results allow us to define the rate at which deleterious interactions are expected to form, and hence the speciation rate, for any protein-protein interaction network.     

A stochastic model of a temperature-dependent population

The theoretical basis is developed for a population model which allows the use of constant temperature experimental data in predicting the size of an insect population for any variable temperature environment. The model is based on a stochastic analysis of an insect's mortality, development, and reproduction response to temperature. The key concept in the model is the utilization of a physiological time scale. Different temperatures affect the population by increasing an individual's physiological age by differing rates. Conditions for the temperature response properties are given which establish the validity of the model for variable temperature regimes. These conditions refer to the relationship between chronological and physiological age. Reasonable agreement between the model and field populations demonstrates the practicality of this approach.     

A preferred conformation in the vasoactive intestinal peptide (VIP). Molecular architecture of gastrointestinal hormones

The ORD spectrum of the vasoactive intestinal peptide (VIP) in water indicates a preferred conformation with low helix content. Addition of organic solvents, especially of trifluoroethanol, results, even at low solvent concentration, in spectra with pronounced helical character. The readiness of shorter chains, with C-terminal sequences of VIP, to take up helical conformation under the effect of organic solvents parallels their biological activity. This suggests that an “active architecture” may be required for the interaction between hormone and receptor.     

Polyproline II helix is the preferred conformation for unfolded polyalanine in water

Does aqueous solvent discriminate among peptide conformers? To address this question, we computed the solvation free energy of a blocked, 12‐residue polyalanyl‐peptide in explicit water and analyzed its solvent structure. The peptide was modeled in each of 4 conformers: α‐helix, antiparallel β‐strand, parallel β‐strand, and polyproline II helix (P_II). Monte Carlo simulations in the canonical ensemble were performed at 300 K using the CHARMM 22 forcefield with TIP3P water. The simulations indicate that the solvation free energy of P_II is favored over that of other conformers for reasons that defy conventional explanation. Specifically, in these 4 conformers, an almost perfect correlation is found between a residue's solvent‐accessible surface area and the volume of its first solvent shell, but neither quantity is correlated with the observed differences in solvation free energy. Instead, solvation free energy tracks with the interaction energy between the peptide and its first‐shell water. An additional, previously unrecognized contribution involves the conformation‐dependent perturbation of first‐shell solvent organization. Unlike P_II, β‐strands induce formation of entropically disfavored peptide:water bridges that order vicinal water in a manner reminiscent of the hydrophobic effect. The use of explicit water allows us to capture and characterize these dynamic water bridges that form and dissolve during our simulations. Proteins 2004. © 2004 Wiley‐Liss, Inc.     

Quantitative aspects of drug-receptor interactions. I. Ca2+ and cholinergic receptor activation in smooth muscle: a basic model for drug-receptor interactions

An attempt has been made to devise a general model of drug-receptor interactions as it relates to the initiation of mechanical responses. A key feature of this model is the regulatory role played by membrane-bound Ca²⁺ (Ca_mem²⁺).The effects on the mechanical responsiveness of guinea pig ileal longitudinal muscle of four muscarinic agonists derived from and including the highly active cis-2-methyl-4-dimethylaminomethyl-1, 3-dioxolane methiodide have been studied. The concentration-response (isotonic contraction) curves of these four agonists at normal Ca_ext²⁺-levels show evidence of cooperativity (n_H > 1) and this was found to increase dramatically with decreasing [Ca_ext²⁺]. A three step model has been proposed, based on that previously advanced by Hurwitz &; Suria (1971), in which activation of the acetylcholine receptor initiates a Ca²⁺ translocation mechanism supplying the contractile machinery with Ca²⁺. Arguments are advanced to suggest that two sources of Ca²⁺ are thus utilized: membrane-bound (Ca_mem²⁺) and free extracellular (Ca_ext²⁺), the former being responsible for the initial phasic contraction and the latter for the slower phase of contractile development.Analysis of the theoretical model shows that the cooperativity of the concentration-response relationships derives not from the initial agonist-receptor interaction but from the subsequently initiated Ca²⁺ translocation step so that [Ca_int²⁺] ∝ [Ca_ext²⁺]ⁿ. The limiting value of n is found to be 6 and to be the same for agonists and partial agonists. According to this model intrinsic activity is determined by the linkage between the agonist-receptor complex and the Ca²⁺ translocation process.The general findings of this work are discussed in terms of an equilibrium between Ca²⁺-associated and Ca²⁺-dissociated membrane states. The similarities to other Ca²⁺ dependent processes are emphasized.     

A model for the delta-receptor-bound conformation of enkephalin

Sets of low-energy structures were determined by energy calculations for two cyclic analogues of enkephalin (Ek), [D-Pen2, D-Pen5]-Ek and [D-Pen2, L-Pen5]-Ek, possessing the highest specificity towards delta-opioid receptors. Comparison of mutual spatial orientations of the alpha-amino group and aromatic moieties of the Tyr and Phe residues permitted one to suggest a model for the delta-receptor-bound conformation of enkephalin-related peptides. The model involves a pronounced gamma-like turn of the peptide backbone centred on the Gly3 residue.     

Electrostatic components of drug-receptor recognition. II. The DNA-binding antibiotic actinomycin

The semiempirical molecular orbital method PCILO has been used to study the electronic charge distribution and conformation of the antibiotic actinomycin. Molecular electrostatic potential fields have been constructed in three-dimensional space round the molecule and displayed stereoscopically together with contour maps in the orthogonal planes relative to that of the chromophore. It was found that the drug has a considerable dipole moment and that the electrostatic fields can be separated into two large regions; an area of positive potential surrounds the chromophore and one of negative potential is directed away from the peptide rings. In this and the preceding paper these observations are discussed with respect to drug-receptor recognition phenomena. Pattern-matching of complementary electrostatic fields between the drug and polynucleotide receptor can be discerned.     

DNA interaction with RNase A alters protein conformation

DNA-RNase H adducts were used for site specific cleavage of RNA and DNA-RNA duplexes, whereas nonspecific DNA interaction with ribonuclease A (RNase A) has been observed. The aim of this study was to examine the complexation of calf-thymus DNA with RNase A at physiological condition, using constant DNA concentration (12.5 mM) and various protein contents (1 microM to 270 microM). FTIR, UV-visible, and CD spectroscopic methods were used to analyse protein binding mode, the binding constant and the effects of nucleic acid-enzyme interaction on both DNA and protein conformations. Our structural analysis showed a strong RNase-PO2 binding and minor interaction with G-C bases with overall binding constant of K = 6.1 x 10(4) M(-1). The RNase-DNA interaction alters the protein secondary structure with a major reduction of the alpha-helix and increase of the beta-sheet and random structure, while DNA remains in the B-family structure.