Johan Ulander

Permeation Across Hydrated DPPC Lipid Bilayers: Simulation of the Titrable Amphiphilic Drug Valproic Acid

Valproic acid is a short branched fatty acid used as an anticonvulsant drug whose therapeutic action has been proposed to arise from membrane-disordering properties. Static and kinetic properties of valproic acid interacting with fully hydrated dipalmitoyl phosphatidylcholine lipid bilayers are studied using molecular-dynamics simulations. We calculate spatially resolved free energy profiles and local diffusion coefficients using the distance between the bilayer and valproic acid respective centers-of-mass along the bilayer normal as reaction coordinate. To investigate the pH dependence, we calculate profiles for the neutral valproic acid as well as its water-soluble anionic conjugate base valproate. The local diffusion constants for valproate/valproic acid along the bilayer normal are found to be approximately 10(-6) to 10(-5) cm2 s(-1). Assuming protonation of valproic acid upon association with--or insertion into--the lipid bilayer, we calculate the permeation coefficient to be approximately 2.0 10(-3) cm s(-1), consistent with recent experimental estimates of fast fatty acid transport. The ability of the lipid bilayer to sustain local defects such as water intrusions stresses the importance of going beyond mean field and taking into account correlation effects in theoretical descriptions of bilayer translocation processes.

High-throughput pKa screening and prediction amenable for ADME profiling

Recent technological advances have made it possible for several new pKa assays to be used in drug screening. In this review, a critical overview is provided of current new methodologies for high-throughput screening and prediction of pKa. Typical applications of using pKa constants and charge state for absorption, distribution, metabolism and excretion (ADME) profiling and quantitative structureactivity relationship modelling complements the methodological comparisons and discussions. The experimental methods discussed include high-throughput screening of pKa by multiplexed capillary with ultraviolet absorbance detection on a 96-capillary format instrument, capillary electrophoresis and mass spectrometry (CEMS) based on sample pooling, determination of pKa by pH gradient high-performance liquid chromatography, and measurement of pKa by a mixed-buffer liner pH gradient system. Comparisons of the different experimental assays are made with emphasis on the newly developed CEMS method. The current status and recent progress in computational approaches to pKa prediction are also discussed. In particular, the accuracy limits of simple fragment-based approaches as well as quantum mechanical methods are addressed. Examples of pKa prediction from in-house drug candidates as well as commercially available drug molecules are shown and an outline is provided for how drug discovery companies can integrate experiments with computational approaches for increased applications for ADME profiling.

Screening and asymptotic decay of pair distributions in asymmetric electrolytes

An accurate description of the screening behavior of asymmetric binary electrolyte solutions is obtained by applying the dressed ion theory to acquire the three leading terms in the asymptotic decay of the radial pair distribution function gij(r) at large distances r. These terms give a surprisingly good representation of the distribution function for quite small r values. A minimum of two asymptotic terms are needed for representing gij(r) at moderately large r in a quite wide concentration range. The relationships between the large r asymptotic behavior of charge–charge, density–density, and charge–density correlations are investigated by means of the dressed ion distribution functions. The role that the dielectric response function of the electrolyte plays for the asymptotic behavior is illuminated and the relationship between this function and the dressed ion charge distributions is given. Ionic effective charges, effective permittivities, and decay lengths and their higher order analogues are calcula...

Pharmacodynamic-Pharmacokinetic Integration as a Guide to Medicinal Chemistry

A primary objective of pharmacokinetic-pharmacodynamic (PKPD) reasoning is to identify key in vivo drug and system proper¬ties, enabling prediction of the magnitude and time course of drug responses under physiological and pathological conditions in animals and man. Since the pharmacological response generated by a drug is highly dependent on the actual system used to study its action, knowledge about its potency and efficacy at a given concentration or dose is insufficient to obtain a proper understanding of its pharmacodynamic profile. Hence, the output of PKPD activities extends beyond the provision of quantitative measures (models) of results, to the design of future protocols. Furthermore, because PKPD integrates DMPK (e.g. clearance) and pharmacology (e.g. potency),it provides an anchor point for compound selection, and, as such, should be viewed as an important weapon in medicinal chemistry. Here we outline key PK concepts relevant to PD, and then consider real-life experiments to illustrate the importance to the medicinal chemist of data obtained by PKPD. Useful assumptions and potential pitfalls are described, providing a holistic view of the plethora of determinants behind in vitro-in vivo correlations. By condensing complexity to simplicity, there are not only consequences for experimental design, and for the ranking and design of compounds, but it is also possible to make important predictions such as the impact of changes in drug potency and kinetics. In short, by using quantitative methods to tease apart pharmacodynamic complexities such as temporal differences and changes in plasma protein binding, it is possible to target the changes necessary for improving a compounds profile.

Primary and secondary effective charges for electrical double layer systems with asymmetric electrolytes

We show that the screening of the electrostatic potential in electrolytes can in exact theory be expressed in terms of a generalized screened Colomb potential, analogous to the Yukawa potential from the Debye–Huckel approximation, provided the source charge of the potential is renormalized. The renormalized charge distribution is identical to that of a “dressed particle” in dressed ion theory, DIT, of Kjellander and Mitchell. Using DIT we analyze the leading terms of the decay of density profiles and electrostatic potential outside a charged planar wall in contact with 1:2 electrolytes. The formalism leads in a natural manner to the definition of a primary and a secondary effective charge of an object immersed in an electrolyte. These charges are associated with the leading and second leading decay modes of the potential, which have different decay lengths. It is found that both leading terms in the decay are important; together, they give in many cases a very good representation of the density profiles a...

The decay of pair correlation functions in ionic fluids: A dressed ion theory analysis of Monte Carlo simulations

We analyze the decay of structural correlation functions for 1:1, 1:2, and 2:2 electrolyte solutions obtained from Monte Carlo simulations. It is found that by the use of dressed ion theory and a simple Picard iteration scheme one can extract the leading decay parameters with high accuracy, even from simulations with a rather limited number of ions in the simulation cell. The extraction scheme consists of replacing in a self-consistent manner the tails of the simulated pair distribution functions by analytical expressions evaluated by residue analysis of short-ranged parts of the correlation functions. Numerical results in this work are restricted to primitive model electrolytes where the solvent only enters as a dielectric continuum. The leading decay parameters of the simulated correlation functions are compared to results obtained from the hypernetted chain (HNC) approximation. For 1:1 and 1:2 electrolytes in aqueous solution the simulation results confirm predictions from the HNC approximation. For 2:...

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design

Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting. The current study presents a systematic and exhaustive investigation of predicting binding modes for a range of systems using PELE (Protein Energy Landscape Exploration), an efficient and fast protein-ligand sampling algorithm. The systems analyzed (cytochrome P, kinase, protease, and nuclear hormone receptor) exhibit different complexities of ligand induced fit mechanisms and protein dynamics. The results are compared with results from classical molecular dynamics simulations and (induced fit) docking. This study shows that ligand induced side chain rearrangements and smaller to medium backbone movements are captured well in PELE. Large secondary structure rearrangements, however, remain challenging for all employed techniques. Relevant binding modes (ligand heavy atom RMSD < 1.0 Å) can be obtained by the PELE method within a few hours of simulation, positioning PELE as a tool applicable for rapid drug design cycles.

Dressed ion theory of size-asymmetric electrolytes: Effective ionic charges and the decay length of screened Coulomb potential and pair correlations

The effects of ionic size asymmetry on long-range electrostatic interactions in electrolyte solutions are investigated within the primitive model. Using the formalism of dressed ion theory we analyze correlation functions from Monte Carlo simulations and the hypernetted chain approximation for size asymmetric 1:1 electrolytes. We obtain decay lengths of the screened Coulomb potential, effective charges of ions, and effective permittivity of the solution. It is found that the variation of these quantities with the degree of size asymmetry depends in a quite intricate manner on the interplay between the electrostatic coupling and excluded volume effects. In most cases the magnitude of the effective charge of the small ion species is larger than that of the large species; the difference increases with increasing size asymmetry. The effective charges of both species are larger (in absolute value) than the bare ionic charge, except for high asymmetry where the effective charge of the large ions can become smaller than the bare charge.

Intramolecular Hydrogen Bond Expectations in Medicinal Chemistry

Design strategies centered on intramolecular hydrogen bonds are sometime used in drug discovery, but their general applicability has not been addressed beyond scattered examples or circumstantial evidence. A total of 1053 matched molecular pairs where only one of the two molecules is able to form an intramolecular hydrogen bond via monatomic transformations have been identified across the ChEMBL database. These pairs were used to investigate the effect of intramolecular hydrogen bonds on biological activity. While cases of extreme, conflicting variation of effect emerge, the mean biological activity difference for a pair is close to zero and does not exceed ±0.5 log biological activity for over 50% of the analyzed sample.

A comprehensive company database analysis of biological assay variability

Analysis of data from various compounds measured in diverse biological assays is a central part of drug discovery research projects. However, no systematic overview of the variability in biological assays has been published and judgments on assay quality and robustness of data are often based on personal belief and experience within the drug discovery community. To address this we performed a reproducibility analysis of all biological assays at AstraZeneca between 2005 and 2014. We found an average experimental uncertainty of less than a twofold difference and no technologies or assay types had higher variability than others. This work suggests that robust data can be obtained from the most commonly applied biological assays.