Systematic identification and classification of three-dimensional activity cliffs

Activity cliffs were systematically extracted from public domain X-ray structures of targets for which complexes with multiple ligands were available, following the concept of three-dimensional (3D) cliffs. Binding modes of ligands with well-defined potency measurements were compared in a pairwise manner, and their 3D similarity was calculated using a previously reported property density function-based method taking conformational, positional, and chemical differences into account. Requiring the presence of at least 80% 3D similarity and a potency difference of at least 2 orders of magnitude as cliff criteria, a total of 216 well-defined 3D activity cliffs were detected in the Protein Data Bank (PDB). These 3D-cliffs involved a total of 269 ligands active against 38 different targets belonging to 17 protein families. For 255 of these compounds, binding modes were available at high crystallographic resolution. All 3D-cliffs were analyzed in detail and assigned to different categories on the basis of crystallographic interaction patterns. In many instances, differences in ligand-target interactions suggested plausible causes for origins of 3D-cliffs. In other cases, short-range interactions seen in X-ray structures were insufficient to deduce possible reasons for cliff formation. The 3D-cliffs described herein further advance the rationalization of activity cliffs at the level of ligand-target interactions and should also be useful for other applications such as the calibration of energy functions for structure-based design. The pool of identified activity cliffs is provided to enable subsequent structure-based analyses of cliffs.     

Molecular mechanism-based network-like similarity graphs reveal relationships between different types of receptor ligands and structural changes that determine agonistic, inverse-agonistic, and antagonistic effects

Receptor ligands might act as agonists, partial agonists, inverse agonists, or antagonists and it is often difficult to understand structural modifications that alter the mechanism of action. In order to compare ligands that are active against a given receptor but have different mechanisms of action, we have designed molecular networks that mirror similarity relationships and incorporate both mechanism of action information and mechanism-specific SAR features. These network representations make it possible to systematically evaluate relationships between different types of receptor ligands and identify communities of structurally very similar ligands with different mechanisms. From a series of such ligands, structural modifications can often be deduced that lead to "mechanism hops".     

cis-Nitenpyram Analogues Bearing Acyloxy Segments Anchored on the Tetrahydropyrimidine Ring: Synthesis,Insecticidal Activities and Molecular Docking Studies

A series of novel cis-nitenpyram analogues bearing acyloxy segments anchored on the tetrahydropyrimidine ring was designed and synthesized. Preliminary bioassays indicate that all the nitenpyram analogues 3a―3n exhibit good insecticidal activities against Nilaparvata lugens and Aphis medicaginis at 100 mg/L, while analogue 3k affords the best activity in vitro and the lethal concentration 50(LC₅₀) values(0.187, 0.214 mg/L) are close to that of nitenpyram. The structure activity relationships(SARs) suggest that their insecticidal potency is influenced by the species of acyloxy segments. The docking results reveal that analogue 3k forms stronger hydrogen-bonding with the nAChR, which explain the structure activity relationships(SARs) observed in vitro and imply that the strategies of our designed nitenpyram analogues are feasible.     

Extraction of discontinuous structure-activity relationships from compound data sets through particle swarm optimization

The characterization of structure-activity relationship (SAR) features of large compound data sets has been a hot topic in recent years, and different methods for large-scale SAR analysis have been introduced. The exploration of local SAR components and prioritization of compound subsets have thus far mostly relied on graphical analysis methods that capture similarity and potency relationships in a systematic manner. A currently unsolved problem in large-scale SAR analysis is how to automatically select those compound subsets from large data sets that carry most SAR information. For this purpose, we introduce a numerical optimization scheme that is based on particle swarm optimization guided by an SAR scoring function. The methodology is applied to four large compound sets. We demonstrate that compound subsets representing the most discontinuous local SARs are consistently selected through particle swarm optimization.     

An evaluation of selected global (Q)SARs/expert systems for the prediction of skin sensitisation potential

Skin sensitisation potential is an endpoint that needs to be assessed within the framework of existing and forthcoming legislation. At present, skin sensitisation hazard is normally identified using in vivo test methods, the favoured approach being the local lymph node assay (LLNA). This method can also provide a measure of relative skin sensitising potency which is essential for assessing and managing human health risks. One potential alternative approach to skin sensitisation hazard identification is the use of (Quantitative) structure activity relationships ((Q)SARs) coupled with appropriate documentation and performance characteristics. This represents a major challenge. Current thinking is that (Q)SARs might best be employed as part of a battery of approaches that collectively provide information on skin sensitisation hazard. A number of (Q)SARs and expert systems have been developed and are described in the literature. Here we focus on three models (TOPKAT, Derek for Windows and TOPS-MODE), and evaluate their performance against a recently published dataset of 211 chemicals. The current strengths and limitations of one of these models is highlighted, together with modifications that could be made to improve its performance. Of the models/expert systems evaluated, none performed sufficiently well to act as a standalone tool for hazard identification.     

Design of multitarget activity landscapes that capture hierarchical activity cliff distributions

An activity landscape model of a compound data set can be rationalized as a graphical representation that integrates molecular similarity and potency relationships. Activity landscape representations of different design are utilized to aid in the analysis of structure-activity relationships and the selection of informative compounds. Activity landscape models reported thus far focus on a single target (i.e., a single biological activity) or at most two targets, giving rise to selectivity landscapes. For compounds active against more than two targets, landscapes representing multitarget activities are difficult to conceptualize and have not yet been reported. Herein, we present a first activity landscape design that integrates compound potency relationships across multiple targets in a formally consistent manner. These multitarget activity landscapes are based on a general activity cliff classification scheme and are visualized in graph representations, where activity cliffs are represented as edges. Furthermore, the contributions of individual compounds to structure-activity relationship discontinuity across multiple targets are monitored. The methodology has been applied to derive multitarget activity landscapes for compound data sets active against different target families. The resulting landscapes identify single-, dual-, and triple-target activity cliffs and reveal the presence of hierarchical cliff distributions. From these multitarget activity landscapes, compounds forming complex activity cliffs can be readily selected.     

Combining 4D pharmacophore generation and multidimensional QSAR: modeling ligand binding to the bradykinin B2 receptor

We recently reported the development of two receptor-modeling concepts (software Quasar and Raptor) based on multidimensional quantitative structure-activity relationships (QSAR) and allowing for the explicit simulation of induced fit. As the identification of the bioactive configuration of ligand molecules in such studies is all but unambiguous, each compound may be represented by an ensemble of different conformations, orientations, stereoisomers, and protonation states, leading to a 4D data set. In this account, we present a novel technology (software Symposar) allowed to automatically generate a 4D pharmacophore as input for multidimensional QSAR. Symposar aligns ligands utilizing fuzzylike 2D-subfeature mapping and, subsequently, a Monte Carlo search on a 3D similarity grid. The two-step concept (4D pharmacophore generation and quantification of ligand binding by multidimensional QSAR) was applied to 186 compounds binding to the bradykinin B2 receptor. The prediction of their binding affinity by means of the Quasar and Raptor technologies allowed for consensus scoring and generated topologically and quantitatively consistent receptor models. These converged at a cross-validated r2 of 0.752 and 0.815 and yielded a predictive r2 of 0.784 and 0.853 for a test set (for Quasar and Raptor, respectively).     

An evaluation of selected global (Q)SARs/expert systems for the prediction of skin sensitisation potential

Skin sensitisation potential is an endpoint that needs to be assessed within the framework of existing and forthcoming legislation. At present, skin sensitisation hazard is normally identified using in vivo test methods, the favoured approach being the local lymph node assay (LLNA). This method can also provide a measure of relative skin sensitising potency which is essential for assessing and managing human health risks. One potential alternative approach to skin sensitisation hazard identification is the use of (Quantitative) structure activity relationships ((Q)SARs) coupled with appropriate documentation and performance characteristics. This represents a major challenge. Current thinking is that (Q)SARs might best be employed as part of a battery of approaches that collectively provide information on skin sensitisation hazard. A number of (Q)SARs and expert systems have been developed and are described in the literature. Here we focus on three models (TOPKAT, Derek for Windows and TOPS-MODE), and evaluate their performance against a recently published dataset of 211 chemicals. The current strengths and limitations of one of these models is highlighted, together with modifications that could be made to improve its performance. Of the models/expert systems evaluated, none performed sufficiently well to act as a standalone tool for hazard identification.     

Morphological similarity: A 3D molecular similarity method correlated with protein-ligand recognition

Recognition of small molecules by proteins depends on three-dimensional molecular surface complementarity. However, the dominant techniques for analyzing the similarity of small molecules are based on two-dimensional chemical structure, with such techniques often outperforming three-dimensional techniques in side-by-side comparisons of correlation to biological activity. This paper introduces a new molecular similarity method, termed morphological similarity (MS), that addresses the apparent paradox. Two sets of molecule pairs are identified from a set of ligands whose protein-bound states are known crystallographically. Pairs that bind the same protein sites form the first set, and pairs that bind different sites form the second. MS is shown to separate the two sets significantly better than a benchmark 2D similarity technique. Further, MS agrees with crystallographic observation of bound ligand states, independent of information about bound states. MS is efficient to compute and can be practically applied to large libraries of compounds.     

The discovery of novel auxin transport inhibitors by molecular modeling and three-dimensional pattern analysis

Summary Molecular modeling techniques and three-dimensional (3D) pattern analysis have been used to investigate the chemical and steric properties of compounds that inhibit transport of the plant hormone auxin. These compounds bind to a specific site on the plant plasma membrane characterized by its affinity for the herbicide N-1-naphthylphthalamic acid (NPA). A 3D model was derived from critical features of a set of ligands for the NPA receptor, a suggested binding conformation is proposed, and implications for the topographical features of the NPA receptor are discussed. This model, along with 3D structural analysis techniques, was then used to search the Abbott corporate database of chemical structures. Of the 467 compounds that satisfied the criteria of the model, 77 representative molecules were evaluated for their ability to compete for the binding of [³H]NPA to corn microsomal membranes. Nineteen showed activity that ranged from 16 to 85% of the maximum NPA binding. Four of the most active of these, representing chemical classes not included in the original compound set, were also found to inhibit polar auxin transport through corn coleoptile sections. Thus, this study demonstrates that 3D analysis techniques can identify active, novel ligands for biochemical target sites with concomitant physiological activity.     

Exploration of 3D activity cliffs on the basis of compound binding modes and comparison of 2D and 3D cliffs

Activity cliffs are formed by pairs or groups of structurally similar compounds having large differences in potency and are focal points of structure-activity relationship (SAR) analysis. The choice of molecular representations is a critically important aspect of activity cliffs analysis. Thus far, activity cliffs have predominantly been defined on the basis of molecular graph or fingerprint representations. Herein we introduce 3D activity cliffs derived from comparisons of experimentally determined compound binding modes. The analysis of 3D activity cliffs is generally applicable to target proteins for which structures of multiple ligand complexes are available. For two popular targets, β-secretase 1 (BACE1) and factor Xa (FXa), public domain X-ray structures with bound inhibitors were collected. Crystallographic binding modes of inhibitors were systematically compared using a 3D similarity method taking conformational, positional, and atomic property differences into account. In addition, standard 2D similarity relationships were also determined. SAR information associated with individual compounds substantially changed when either bioactive conformations or 2D molecular graphs were used for similarity evaluation. 3D activity cliffs were identified for BACE1 and FXa inhibitor sets and systematically compared to 2D cliffs. It was found that less than 40% of 3D activity cliffs were conserved when 2D similarity was applied. The limited conservation of 3D and 2D cliffs provides further evidence for the strong molecule representation dependence of activity cliffs. Moreover, 3D cliffs represent a new class of activity cliffs that convey SAR information in ways that differ from graph-based similarity measures. In cases where sufficient structural information is available, the comparison of 3D and 2D cliffs is expected to aid in SAR analysis and mapping of critical binding determinants.     

缺陷位工程在二维材料电催化析氢反应中的研究进展

面对不可再生资源的快速消耗和环境污染的日益加重,寻找清洁可再生能源势在必行.氢能是一种清洁可再生的能源,是目前最有希望替代化石燃料的一种能源.电化学水分解可用来产生高纯氢气,其中析氢催化剂起着至关重要的作用.尽管贵金属铂基催化剂表现出优异的析氢性能,然而稀缺性和高成本限制了其大规模应用.因此,开发高效和地球存量丰富的电...     

Transforming 3D CAU-10-H into 2D Materials with High Base Stability for Membrane Separation

Two-dimensional (2D) nanomaterials have received a significant research attention owing to their unique chemical and physical properties. These materials not only provide the chemically active sites and exposed surface atoms, but also display the porous nature suitable for their use as membranes for gas separation. In this study, 3D CAU-10-H has been transformed into a novel alkali stabilized 2D CACl-10 (180). Though CACl-10 (180) is similar to AlOOH, it is a novel 2D nanomaterial synthesized by using 4-chloroisophthalic acid and aluminum nitrate nonahydrate, with thermal decomposition at 300 °C. Further, CACl-10 (180) is noted to retain its framework structure in strong alkali solutions, attributed to the alkali-resistant aluminum hydroxide. At the same time, it has been demonstrated that 3D CAU-10-H can also transform into 3D CACl-10 (140) and 3D CACl-10 (130), and the halogen atoms of the ligands (−Cl) affect the alkali stability of the materials. Subsequently, the PVAm-CACl-10 (180)/MPSf mixed matrix membranes were prepared and applied for CH₄/N₂ separation. The developed membrane exhibits the CH₄ permeance of 1647.99 GPU with a CH₄/N₂ selectivity of 3.1. As a result, 2D CACl-10 (180), with a strong alkali stability and an acceptable CH₄/N₂ membrane separation performance, represents a high potential of application in the membrane separation process.     

Oligomeric cadmium-phthalocyanine complexes: novel supramolecular free radical structures

Certain cadmium-metallated phthalocyanines give rise to EPR active triple-decker sandwich complexes containing two Cd ions and three phthalocyanine (Pc) ligands. These have been shown to form when the ligands bear either eight non- peripheral alkyl or alkenyl substituents or eight peripheral 2-ethylhexyl groups. They can be derived either from three equivalents of a cadmium phthalocyanine precursor or from a 2:1 mixture of a cadmium phthalocyanine (CdPc) and a metal-free phthalocyanine (H(2)Pc). The mode of their formation has been investigated by a series of "cross" experiments. The results indicate that the triple-decker structures are formed by a self-assembly process. This is deduced from results that show that they can disassemble and reassemble with incorporation of differently substituted ligands derived from either an H(2)Pc or CdPc. The reassembled structures in these cross experiments can contain more than one ligand that originated from either the added CdPc or, and more surprisingly, the H(2)Pc compound. Mass spectrometry has also established that higher order oligomers can be formed when steric requirements between the alkyl substituents on adjacent rings in the stack are reduced. Thus an isotopic cluster for a Cd(5)Pc(6) complex has been observed when the eight peripheral substituents are hexyl chains and tetrameric complexes are formed when two different ligands are incorporated within a stack, with one carrying substituents at the peripheral sites and the other bearing substituents at the non-peripheral sites.     

Electrostatic Interactions in Docking a 3D Model of Bovine Testicular Hyaluronidase with a Chondroitin Sulfate Trimer and a Heparin Tetramer

The molecular docking of a 3D-model of bovine testicular hyaluronidase with glycosaminoglycan ligands is performed. A chondroitin sulfate trimer and a heparin tetramer were used as ligands. Methods of computational chemistry are applied to elucidate the regulation of hyaluronidase functioning in an organism when the heparin ligand inactivates the biocatalyst, and the chondroitin sulfate ligand protects the enzyme structure. Eight ligand binding sites are identified on the molecular surface of the enzyme, each of which is equally capable of interacting with chondroitin sulfate trimers and heparin tetramers via electrostatic interactions. It is found that reversible and irreversible conformational changes in the enzyme 3D structure can occur depending on the positioning of negatively charged ligands on its globule (under different conditions, they can either stabilize or inactivate the biocatalyst). Binding sites whose occupancy is sufficient for preventing irreversible deformations of the enzyme conformation upon introducing the heparin ligand into the active site are identified on the molecular surface of hyaluronidase. The interaction of glycosaminoglycan ligands with hyaluronidase is mainly determined by electrostatic forces.     

Do active site conformations of small ligands correspond to low free-energy solution structures?

We compare the low free energy structures of ten small, polar ligands in solution to their conformations in their respective receptor active sites. The solution conformations are generated by a systematic search and the free energies of representative structures are computed with a continuum solvation model. Based on the values of torsion angles, we find little similarity between low energy solution structures of small ligands and their active site conformations. However, in nine out of ten cases, the positions of 'anchor points' (key atoms responsible for tight binding) in the lowest energy solution structures are very similar to the positions of these atoms in the active site conformations. A metric that more closely captures the essentials of binding supports the basic premise underlying pharmacophore mapping, namely that active site conformations of small flexible ligands correspond to their low energy structures in solution. This work supports the efforts of building pharmacophore models based on the information present in solution structures of small isolated ligands.     

Sophisticated Design of Covalent Organic Frameworks with Controllable Bimetallic Docking for a Cascade Reaction

Precise control of the number and position of the catalytic metal ions in heterogeneous catalysts remains a big challenge. Here we synthesized a series of two‐dimensional (2D) covalent organic frameworks (COFs) containing two different types of nitrogen ligands, namely imine and bipyridine, with controllable contents. For the first time, the selective coordination of the two nitrogen ligands of the 2D COFs to two different metal complexes, chloro(1,5‐cyclooctadiene)rhodium(I) (Rh(COD)Cl) and palladium(II) acetate (Pd(OAc)₂), has been realized using a programmed synthetic procedure. The bimetallically docked COFs showed excellent catalytic activity in a one‐pot addition–oxidation cascade reaction. The high surface area, controllable metal‐loading content, and predesigned active sites make them ideal candidates for their use as heterogeneous catalysts in a wide range of chemical reactions.     

Pattern similarity study of functional sites in protein sequences: lysozymes and cystatins

Background  

Although it is generally agreed that topography is more conserved than sequences, proteins sharing the same fold can have different functions, while there are protein families with low sequence similarity. An alternative method for profile analysis of characteristic conserved positions of the motifs within the 3D structures may be needed for functional annotation of protein sequences. Using the approach of quantitative structure-activity relationships (QSAR), we have proposed a new algorithm for postulating functional mechanisms on the basis of pattern similarity and average of property values of side-chains in segments within sequences. This approach was used to search for functional sites of proteins belonging to the lysozyme and cystatin families.