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Insecticide resistance jeopardizes the prevention of infectious diseases such as malaria and dengue fever by vector control of disease-transmitting mosquitoes. Effective new insecticidal compounds with minimal adverse effects on humans and the environment are therefore urgently needed. Here, we explore noncovalent inhibitors of the well-validated insecticidal target acetylcholinesterase (AChE) based on a 4-thiazolidinone scaffold. The 4-thiazolidinones inhibit AChE1 from the mosquitoes Anopheles gambiaeand Aedes aegyptiat low micromolar concentrations. Their selectivity depends primarily on the substitution pattern of the phenyl ring; halogen substituents have complex effects. The compounds also feature a pendant aliphatic amine that was important for activity; little variation of this group is tolerated. Molecular docking studies suggested that the tight selectivity profiles of these compounds are due to competition between two binding sites. Three 4-thiazolidinones tested for in vivo insecticidal activity had similar effects on disease-transmitting mosquitoes despite a 10-fold difference in their in vitro activity.

Arene–arene interactions play important roles in protein–ligand complex formation. Here, we investigate the characteristics of arene–arene interactions between small organic molecules and aromatic amino acids in protein interiors. The study is based on X-ray crystallographic data and quantum mechanical calculations using the enzyme acetylcholinesterase and selected inhibitory ligands as a model system. It is shown that the arene substituents of the inhibitors dictate the strength of the interaction and the geometry of the resulting complexes. Importantly, the calculated interaction energies correlate well with the measured inhibitor potency. Non-hydrogen substituents strengthened all interaction types in the protein milieu, in keeping with results for benzene dimer model systems. The interaction energies were dispersion-dominated, but substituents that induced local dipole moments increased the electrostatic contribution and thus yielded more strongly bound complexes. These findings provide fundamental insights into the physical mechanisms governing arene–arene interactions in the protein milieu and thus into molecular recognition between proteins and small molecules.

As a key molecule in biology, adenosine triphosphate (ATP) has numerous crucial functions in, for instance, energetics, post-translational modifications, nucleotide biosynthesis, and cofactor metabolism. Here, we have discovered an intricate interplay between the enzyme adenylate kinase and its substrate ATP. The side chain of an arginine residue was found to be an efficient sensor of the aromatic moiety of ATP through the formation of a strong cation−π interaction. In addition to recognition, the interaction was found to have dual functionality. First, it nucleates the activating conformational transition of the ATP binding domain and also affects the specificity in the distant AMP binding domain. In light of the functional consequences resulting from the cation−π interaction, it is possible that the mode of ATP recognition may be a useful tool in enzyme design.

Resistance development in insects significantly threatens the important benefits obtained by insecticide usage in vector control of disease-transmitting insects. Discovery of new chemical entities with insecticidal activity is highly desired in order to develop new insecticide candidates. Here, we present the design, synthesis, and biological evaluation of phenoxyacetamide-based inhibitors of the essential enzyme acetylcholinesterase 1 (AChE1). AChE1 is a validated insecticide target to control mosquito vectors of, e.g., malaria, dengue, and Zika virus infections. The inhibitors combine a mosquito versus human AChE selectivity with a high potency also for the resistance-conferring mutation G122S; two properties that have proven challenging to combine in a single compound. Structure–activity relationship analyses and molecular dynamics simulations of inhibitor–protein complexes have provided insights that elucidate the molecular basis for these properties. We also show that the inhibitors demonstrate in vivoinsecticidal activity on disease-transmitting mosquitoes. Our findings support the concept of noncovalent, selective, and resistance-breaking inhibitors of AChE1 as a promising approach for future insecticide development.

Iterative screening has emerged as a promising approach to increase the efficiency of high-throughput screening (HTS) campaigns in drug discovery. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models. One of the challenges of iterative screening is to decide how many iterations to perform. This is mainly related to difficulties in estimating the prospective hit rate in any given iteration. In this article, a novel method based on Venn–ABERS predictors is proposed. The method provides accurate estimates of the number of hits retrieved in any given iteration during an HTS campaign. The estimates provide the necessary information to support the decision on the number of iterations needed to maximize the screening outcome. Thus, this method offers a prospective screening strategy for early-stage drug discovery.

The enzyme acetylcholinesterase (AChE) is essential in humans and animals because it catalyzes the breakdown of the nerve-signaling substance acetylcholine. Small molecules that inhibit the function of AChE are important for their use as drugs in the, for example, symptomatic treatment of Alzheimer’s disease. New and improved inhibitors are warranted, mainly because of severe side effects of current drugs. In the present study, we have investigated if and how two enantiomeric inhibitors of AChE influence the overall dynamics of noncovalent complexes, using elastic incoherent neutron scattering. A fruitful combination of univariate models, including a newly developed non-Gaussian model for atomic fluctuations, and multivariate methods (principal component analysis and discriminant analysis) was crucial to analyze the fine details of the data. The study revealed a small but clear increase in the dynamics of the inhibited enzyme compared to that of the noninhibited enzyme and contributed to the fundamental knowledge of the mechanisms of AChE–inhibitor binding valuable for the future development of inhibitors.

Inhibiting ADP-ribosyl transferases with PARP-inhibitors is considered a promising strategy for the treatment of many cancers and ischemia, but most of the cellular targets are poorly characterized. Here, we describe an inhibitor of ADP-ribosyltransferase-3/poly(ADP-ribose) polymerase-3 (ARTD3), a regulator of DNA repair and mitotic progression. In vitroprofiling against 12 members of the enzyme family suggests selectivity for ARTD3, and crystal structures illustrate the molecular basis for inhibitor selectivity. The compound is active in cells, where it elicits ARTD3-specific effects at submicromolar concentration. Our results show that by targeting the nicotinamide binding site, selective inhibition can be achieved among the closest relatives of the validated clinical target, ADP-ribosyltransferase-1/poly(ADP-ribose) polymerase-1.

Hamilton's method is a natural and common method to distribute seats proportionally between states (or parties) in a parliament. In the USA it has been abandoned due to some drawbacks, in particular the possibility of the Alabama paradox, but it is still in use in many other countries. In this paper we give, under certain assumptions, a closed formula for the asymptotic probability, as the number of seats tends to infinity, that the Alabama paradox occurs given the vector p1,…, pmof relative sizes of the states. From the formula we deduce a number of consequences. For example, the expected number of states that will suffer from the Alabama paradox is asymptotically bounded above by 1 / e and on average approximately 0.123.

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

Bioisosteric H/F or CH2OH/CF2H replacement was introduced in coumarin derivatives previously characterized as dual AChE-MAO B inhibitors to probe the effects on both inhibitory potency and drug-likeness. Along with in vitro screening, we investigated early-ADME parameters related to solubility and lipophilicity (Sol7.4, CHI7.4, log D7.4), oral bioavailability and central nervous system (CNS) penetration (PAMPA-HDM and PAMPA-blood–brain barrier (BBB) assays, Caco-2 bidirectional transport study), and metabolic liability (half-lives and clearance in microsomes, inhibition of CYP3A4). Both specific and nonspecific tissue toxicities were determined in SH-SY5Y and HepG2 lines, respectively. Compound 15bearing a −CF2H motif emerged as a water-soluble, orally bioavailable CNS-permeant potent inhibitor of both human AChE (IC50= 550 nM) and MAO B (IC50= 8.2 nM, B/A selectivity > 1200). Moreover, 15behaved as a safe and metabolically stable neuroprotective agent, devoid of cytochrome liability.

A new approach is presented for predicting ligand binding to proteins using hierarchical partial-least-squares regression to latent structures (Hi-PLS). Models were based on information from the 2002 release of the PDBbind database containing (after in-house refinement) high-resolution X-ray crystallography and binding affinity (Kd or Ki) data for 612 protein−ligand complexes. The complexes were characterized by four different descriptor blocks:  three-dimensional (3D) structural descriptors of the proteins, protein−ligand interactions according to the Validate scoring function, binding site surface areas, and ligand 2D and 3D descriptors. These descriptor blocks were used in Hi-PLS models, generated using both linear and nonlinear terms, to relate the characterizations to pKd/i. The results show that each of the four descriptor blocks contributed to the model, and the predictions of pKd/i of the internal test set gave a root-mean-square error of prediction (RMSEP) of 1.65. The data were further divided according to the structural classification of the proteins, and Hi-PLS models were constructed for the resulting subclasses. The models for the four subclasses differed considerably in terms of both their ability to predict pKd/i (with RMSEPs ranging from 0.8 to 1.56) and the descriptor block that had the strongest influence. The models were validated with an external test set of 174 complexes from the 2003 release of the PDBbind database. The overall results show that the presented Hi-PLS methodology could facilitate the difficult task of predicting binding affinity.

A peptide library targeting protein−protein interactions crucial for pilus assembly in Gram negative bacteria has been designed using statistical molecular design. A nonamer peptide scaffold was used, with seven positions being varied. The selection was performed in the building block space, and previously known structure−activity data were included in the design procedure. This resulted in a heavily reduced library consisting of 32 peptides which was prepared by solid-phase synthesis. The ability of the peptides to inhibit the protein−protein interaction between the periplasmic chaperone FimC and the pilus adhesin FimH was then determined in an ELISA. Novel peptides with the capability to inhibit the FimC/FimH protein−protein interaction to the same extent as the native FimC peptides were discovered. Multivariate QSAR studies of the response in the ELISA gave valuable information on the properties of amino acids which were preferred at the seven positions in the nonamer scaffold. This information can be used in attempts to develop optimized peptides and peptidomimetics that inhibit pilus assembly in pathogenic bacteria.

A library of thrombin inhibitors has been designed using statistical molecular design. An aromatic scaffold was used, with three varied positions corresponding to three pockets at the active site of thrombin (the S-, P-, and D-pockets). The selection was performed in the building block space, and previously acquired data were included in the design procedure. The design resulted in six, four, and six building blocks for the first (S), second (P), and third (D) pockets, respectively. A second round of selection applied to the combined selected building blocks resulted in a subset of 18 compounds. The selected library was synthesized in parallel and biologically evaluated. The compounds were analyzed with respect to their inhibition (pIC50) of thrombin; membrane permeability, estimated by migration behavior in micellar media (CE log k‘) and pKa; and specificity with respect to inhibition (Ki) of trypsin. Multivariate QSAR studies of the responses yielded valuable results and information that could only be found using statistical molecular design in combination with multivariate analysis.

By a sleeping bagfor a baby snake in ddimensions we mean a subset of Rdwhich can cover, by rotation and translation, every curve of unit length. We construct sleeping bags which are smaller than any previously known in dimensions 3 and higher. In particular, we construct a three-dimensional sleeping bag of volume approximately 0.075803. For large dwe construct d-dimensional sleeping bags with volume less than $$\left( {c\sqrt {\log d} } \right)^d /d^{3d/2}$$for some constant c. To obtain the last result, we show that every curve of unit length in Rdlies between two parallel hyperplanes at distance at most $$c_1 d^{ - 3/2} \sqrt {\log d}$$, for some constant c1.

We study a decomposition of Fl(n)d−1, where Fl(n) denotes the flag manifold over Cn. The strata are defined by the dimensions of intersections of one space from each flag, so for dequal to 2 this is the usual Bruhat cell decomposition. The strata are indexed by “permutation arrays,” which are d-dimensional analogs of permutation matrices. We present a partial order on these permutation arrays, specializing to the Bruhat order on Snwhen dequals 2 and to the lattice of partitions of a d-set when nequals 2.

We define a class of hypercubic (shape [n]d) arrays that in a certain sense are d-dimensional analogs of permutation matrices with our motivation from algebraic geometry. Various characterizations of permutation arrays are proved, an efficient generation algorithm is given, and enumerative questions are discussed although not settled. There is a partial order on the permutation arrays, specializing to the Bruhat order on Snwhen dequals 2, and specializing to the lattice of partitions of a d-set when nequals 2.

The reduction of the size of a combinatorial library can be made in two ways, either base the selection on the building blocks (BB's) or base it on the full set of virtually constructed products. In this paper we have investigated the effects of applying statistical designs to BB sets compared to selections based on the final products. The two sets of BB's and the virtually constructed library were described by structural parameters, and the correlation between the two characterizations was investigated. Three different selection approaches were used both for the BB sets and for the products. In the first two the selection algorithms were applied directly to the data sets (D-optimal design and space-filling design), while for the third a cluster analysis preceded the selection (cluster-based design). The selections were compared using visual inspection, the Tanimoto coefficient, the Euclidean distance, the condition number, and the determinant of the resulting data matrix. No difference in efficiency was found between selections made in the BB space and in the product space. However, it is of critical importance to investigate the BB space carefully and to select an appropriate number of BB's to result in an adequate diversity. An example from the pharmaceutical industry is then presented, where selection via BB's was made using a cluster-based design.

We study a class of lattices called weak*complemented lattices which are shown to have the property that the order complex of any interval of the lattice is either contractible or homotopy equivalent to a sphere. The two main examples are lattices generated by intervals in a total order and the lattices of partitions of integers under dominance order. The proofs are done mainly using homotopy complementation formulas for lattices and with a method called B-labeling. We also show that a class of lattices called Greene lattices are either contractible or spherical. Lattices generated by multisets are also discussed.

M: -sequences (a.k.a. f-vectors for multicomplexes or O-sequences) in terms of the number of variables and a maximum degree. In particular, it is shown that the number of M-sequences for at most 2 variables are powers of two and for at most 3 variables are Bell numbers. We give an asymptotic estimate of the number of M-sequences when the number of variables is fixed. This leads to a new lower bound for the number of polytopes with few vertices. We also prove a similar recursive formula for the number of f-vectors for simplicial complexes. Keeping the maximum degree fixed we get the number of M-sequences and the number of f-vectors for simplicial complexes as polynomials in the number of variables and it is shown that these numbers are asymptotically equal.

Consider the question: Given integers 0 \lek N(d,k)the answer is yes if and only if {G(d,k)}divides n. Furthermore, a formula for G(d,k)is given, showing that, e.g., G(d,k)=1if $ k \ge \left\lfloor (d+1)/{2}\right\rfloor $ or if both dand kare even, and also in some other cases (meaning that all numbers beyond N(d,k)occur as the number of k-faces of some simple d-polytope). This question has previously been studied only for the case of vertices (k=0), where Lee [Le] proved the existence of N(d,0)(with G(d,0)=1or 2depending on whether dis even or odd), and Prabhu [P1] showed that $ N(d,0) \le cd\sqrt {d} $ . We show here that asymptotically the true value of Prabhu's constant is $ c=\sqrt2 $ if dis even, and c=1if dis odd.

Two data sets, one from the 1960s and one from 1990, from continuously managed semi-natural meadows (semi-natural grasslands used for hay-cutting) in Småland, southern Sweden, were analysed to describe the vegetation and in an attempt to characterise changes that have occurred in the vegetation. Based on a classification of the data set, nine plant communities were recognised. The main vegetational differences, as revealed by an ordination, were due to variation in soil moisture, which ranged from wet to dry. During the investigation period, the amount of hay meadow area decreased, particularly the area of wet-moist meadows. In addition, the total variation in the vegetation diminished, and three plant communities more or less disappeared. The turnover index of species in the data set was 36%, and most of the species that were lost had initially been uncommon. Lost species included rare taxa, such as Gentianella campestris and Linum catharticum, while the new species tended to be common in the region. Annual and biennial species accounted for a greater proportion of the lost taxa than did perennial species. The mean cover of species per plot and the relative abundance of graminoids per plot increased. The recorded changes in the vegetation may be related to the increased loads of nitrogen pollutants as well as to a decrease in management intensity. The diminished area is related to changes in land-use. The meadow sites in Småland have been part of a landscape rich in grasslands, but today they have a more or less relict status. They differ from grasslands found elsewhere in Sweden and Scandinavia. In Sweden, the majority (68%) of endangered vascular plants belong to the agricultural landscape. To ensure the survival of individual species it is important to preserve all types of meadows, not only a few selected ones, since no two meadows are alike.

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