Katrina W. Lexa

CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes

A major goal in drug design is the improvement of computational methods for docking and scoring. The Community Structure Activity Resource (CSAR) aims to collect available data from industry and academia which may be used for this purpose (www.csardock.org). Also, CSAR is charged with organizing community-wide exercises based on the collected data. The first of these exercises was aimed to gauge the overall state of docking and scoring, using a large and diverse data set of protein–ligand complexes. Participants were asked to calculate the affinity of the complexes as provided and then recalculate with changes which may improve their specific method. This first data set was selected from existing PDB entries which had binding data (Kd or Ki) in Binding MOAD, augmented with entries from PDBbind. The final data set contains 343 diverse protein–ligand complexes and spans 14 pKd. Sixteen proteins have three or more complexes in the data set, from which a user could start an inspection of congeneric series. Inherent experimental error limits the possible correlation between scores and measured affinity; R2 is limited to ∼0.9 when fitting to the data set without over parametrizing. R2 is limited to ∼0.8 when scoring the data set with a method trained on outside data. The details of how the data set was initially selected, and the process by which it matured to better fit the needs of the community are presented. Many groups generously participated in improving the data set, and this underscores the value of a supportive, collaborative effort in moving our field forward.

Structure of a peptidoglycan amidase effector targeted to Gram-negative bacteria by the type VI secretion system

The target range of a bacterial secretion system can be defined by effector substrate specificity or by the efficacy of effector delivery. Here, we report the crystal structure of Tse1, a type VI secretion (T6S) bacteriolytic amidase effector from Pseudomonas aeruginosa. Consistent with its role as a toxin, Tse1 has a more accessible active site than related housekeeping enzymes. The activity of Tse1 against isolated peptidoglycan shows its capacity to act broadly against Gram-negative bacteria and even certain Gram-positive species. Studies with intact cells indicate that Gram-positive bacteria can remain vulnerable to Tse1 despite cell wall modifications. However, interbacterial competition studies demonstrate that Tse1-dependent lysis is restricted to Gram-negative targets. We propose that the previously observed specificity for T6S against Gram-negative bacteria is a consequence of high local effector concentration achieved by T6S-dependent targeting to its site of action rather than inherent effector substrate specificity.

Protein Flexibility in Docking and Surface Mapping

Structure-based drug design has become an essential tool for rapid lead discovery and optimization. As available structural information has increased, researchers have become increasingly aware of the importance of protein flexibility for accurate description of the native state. Typical protein-ligand docking efforts still rely on a single rigid receptor, which is an incomplete representation of potential binding conformations of the protein. These rigid docking efforts typically show the best performance rates between 50 and 75%, while fully flexible docking methods can enhance pose prediction up to 80-95%. This review examines the current toolbox for flexible protein-ligand docking and receptor surface mapping. Present limitations and possibilities for future development are discussed.

Probing the Physicochemical Boundaries of Cell Permeability and Oral Bioavailability in Lipophilic Macrocycles Inspired by Natural Products

Cyclic peptide natural products contain a variety of conserved, nonproteinogenic structural elements such as d-amino acids and amide N-methylation. In addition, many cyclic peptides incorporate γ-amino acids and other elements derived from polyketide synthases. We hypothesized that the position and orientation of these extended backbone elements impact the ADME properties of these hybrid molecules, especially their ability to cross cell membranes and avoid metabolic degradation. Here we report the synthesis of cyclic hexapeptide diastereomers containing γ-amino acids (e.g., statines) and systematically investigate their structure-permeability relationships. These compounds were much more water-soluble and, in many cases, were both more membrane permeable and more stable to liver microsomes than a similar non-statine-containing derivative. Permeability correlated well with the extent of intramolecular hydrogen bonding observed in the solution structures determined in the low-dielectric solvent CDCl3, and one compound showed an oral bioavailability of 21% in rat. Thus, the incorporation of γ-amino acids offers a route to increase backbone diversity and improve ADME properties in cyclic peptide scaffolds.

Beyond cyclosporine A: conformation-dependent passive membrane permeabilities of cyclic peptide natural products

Many cyclic peptide natural products are larger and structurally more complex than conventional small molecule drugs. Although some molecules in this class are known to possess favorable pharmacokinetic properties, there have been few reports on the membrane permeabilities of cyclic peptide natural products. Here, we present the passive membrane permeabilities of 39 cyclic peptide natural products, and interpret the results using a computational permeability prediction algorithm based on their known or calculated 3D conformations. We found that the permeabilities of these compounds, measured in a parallel artificial membrane permeability assay, spanned a wide range and demonstrated the important influence of conformation on membrane permeability. These results will aid in the development of these compounds as a viable drug paradigm.

De novo mutations in KIF1A cause progressive encephalopathy and brain atrophy

To determine the cause and course of a novel syndrome with progressive encephalopathy and brain atrophy in children.

Improving Protocols for Protein Mapping through Proper Comparison to Crystallography Data

Computational approaches to fragment-based drug design (FBDD) can complement experiments and facilitate the identification of potential hot spots along the protein surface. However, the evaluation of computational methods for mapping binding sites frequently focuses upon the ability to reproduce crystallographic coordinates to within a low RMSD threshold. This dependency on the deposited coordinate data overlooks the original electron density from the experiment, thus techniques may be developed based upon subjective-or even erroneous-atomic coordinates. This can become a significant drawback in applications to systems where the location of hot spots is unknown. On the basis of comparison to crystallographic density, we previously showed that mixed-solvent molecular dynamics (MixMD) accurately identifies the active site for HEWL, with acetonitrile as an organic solvent. Here, we concentrated on the influence of protic solvent on simulation and refined the optimal MixMD approach for extrapolation of the method to systems without established sites. Our results establish an accurate approach for comparing simulations to experiment. We have outlined the most efficient strategy for MixMD, based on simulation length and number of runs. The development outlined here makes MixMD a robust method which should prove useful across a broad range of target structures. Lastly, our results with MixMD match experimental data so well that consistency between simulations and density may be a useful way to aid the identification of probes vs waters during the refinement of future multiple solvent crystallographic structures.

A structure-based model for predicting serum albumin binding.

One of the many factors involved in determining the distribution and metabolism of a compound is the strength of its binding to human serum albumin. While experimental and QSAR approaches for determining binding to albumin exist, various factors limit their ability to provide accurate binding affinity for novel compounds. Thus, to complement the existing tools, we have developed a structure-based model of serum albumin binding. Our approach for predicting binding incorporated the inherent flexibility and promiscuity known to exist for albumin. We found that a weighted combination of the predicted logP and docking score most accurately distinguished between binders and nonbinders. This model was successfully used to predict serum albumin binding in a large test set of therapeutics that had experimental binding data.

Identifying binding hot spots on protein surfaces by mixed‐solvent molecular dynamics: HIV‐1 protease as a test case

Mixed‐solvent molecular dynamics (MixMD) simulations use full protein flexibility and competition between water and small organic probes to achieve accurate hot‐spot mapping on protein surfaces. In this study, we improved MixMD using human immunodeficiency virus type‐1 protease (HIVp) as the test case. We used three probe–water solutions (acetonitrile–water, isopropanol–water, and pyrimidine–water), first at 50% w/w concentration and later at 5% v/v. Paradoxically, better mapping was achieved by using fewer probes; 5% simulations gave a superior signal‐to‐noise ratio and far fewer spurious hot spots than 50% MixMD. Furthermore, very intense and well‐defined probe occupancies were observed in the catalytic site and potential allosteric sites that have been confirmed experimentally. The Eye site, an allosteric site underneath the flap of HIVp, has been confirmed by the presence of a 5‐nitroindole fragment in a crystal structure. MixMD also mapped two additional hot spots: the Exo site (between the Gly16‐Gly17 and Cys67‐Gly68 loops) and the Face site (between Glu21‐Ala22 and Val84‐Ile85 loops). The Exo site was observed to overlap with crystallographic additives such as acetate and dimethyl sulfoxide that are present in different crystal forms of the protein. Analysis of crystal structures of HIVp in different symmetry groups has shown that some surface sites are common interfaces for crystal contacts, which means that they are surfaces that are relatively easy to desolvate and complement with organic molecules. MixMD should identify these sites; in fact, their occupancy values help establish a solid cut‐off where “druggable” sites are required to have higher occupancies than the crystal‐packing faces.

Binding to the open conformation of HIV‐1 protease

A recent crystal structure of HIV‐1 protease (HIVp) was the first to experimentally observe a ligand targeting an open‐flap conformation. Researchers studying a symmetric pyrrolidine inhibitor found that two ligands cocrystallized with the protease, forcing an unusual configuration and unique crystallographic contacts. One molecule is centered in the traditional binding site (α pose) and the other binds between the flaps (β pose). The ligands stack against each other in a region termed the “eye” site. Ligands bound to the eye site should prevent flap closure, but it is unclear if the pyrrolidine inhibitors or the crystal packing are causing the open state. Molecular dynamics simulations were used to examine the solution‐state behavior of three possible binding modes: the ternary complex of HIVp+αβ and the binary complexes, HIVp+α and HIVp+β. We show that HIVp+α is the most stable of the three states. During conformational sampling, α takes an asymmetric binding pose, with one naphthyl ring occupying the eye site and the other reoriented down to occupy positions seen with traditional inhibitors. This finding supports previous studies that reveal a requirement for asymmetric binding at the eye site. In fact, if the α pose is modified to splay both naphthyl rings across the binding site like traditional inhibitors, one ring consistently flips to occupy the eye site. Our simulations reveal that interactions to the eye site encourage a conformationally restrained state, and understanding those contacts may aid the design of ligands to specifically target alternate conformations of the protease. Proteins 2011;