Non-hydrogen Atom Research Articles

Nanomolar Inhibition of Type II Dehydroquinase Based on the Enolate Reaction Mechanism

We describe the rational design of a novel, highly potent inhibitor of type II dehydroquinase, the dicarboxylate 6. The incorporation of a carboxylate at the 3-position mimics the putative enolate intermediate in the reaction mechanism, and allows a potential electrostatic binding interaction with the arginine on the active site flap. This results in a 1000-fold increase in potency, making the dicarboxylate 6 the most potent inhibitor of type II dehydroquinase reported to date, with a high ligand efficiency of -0.68 kcal mol(-1) per nonhydrogen atom. The systematic dissection of 6 in compounds 7-12, all of which show a drop in potency, confirm the synergistic importance of the two carboxylates, the C3 and C4 hydroxyl groups, and the anhydroquinate ring structure for the potency of 6.

Screening-based Discovery and Structural Dissection of a Novel Family 18 Chitinase Inhibitor

Family 18 chitinases play key roles in the life cycles of a variety of organisms ranging from bacteria to man. Very recently it has been shown that one of the mammalian chitinases is highly overexpressed in the asthmatic lung and contributes to the pathogenic process through recruitment of inflammatory cells. Although several potent natural product chitinase inhibitors have been identified, their chemotherapeutic potential or their use as cell biological tools is limited due to their size, complex chemistry, and limited availability. We describe a virtual screening-based approach to identification of a novel, purine-based, chitinase inhibitor. This inhibitor acts in the low micromolar (Ki=2.8+/-0.2 microM) range in a competitive mode. Dissection of the binding mode by x-ray crystallography reveals that the compound, which consists of two linked caffeine moieties, binds in the active site through extensive and not previously observed stacking interactions with conserved, solvent exposed tryptophans. Such exposed aromatics are also present in the structures of many other carbohydrate processing enzymes. The compound exhibits favorable chemical properties and is likely to be useful as a general scaffold for development of pan-family 18 chitinase inhibitors.

A composite score for predicting errors in protein structure models

Reliable prediction of model accuracy is an important unsolved problem in protein structure modeling. To address this problem, we studied 24 individual assessment scores, including physics-based energy functions, statistical potentials, and machine learning-based scoring functions. Individual scores were also used to construct approximately 85,000 composite scoring functions using support vector machine (SVM) regression. The scores were tested for their abilities to identify the most native-like models from a set of 6000 comparative models of 20 representative protein structures. Each of the 20 targets was modeled using a template of <30% sequence identity, corresponding to challenging comparative modeling cases. The best SVM score outperformed all individual scores by decreasing the average RMSD difference between the model identified as the best of the set and the model with the lowest RMSD (DeltaRMSD) from 0.63 A to 0.45 A, while having a higher Pearson correlation coefficient to RMSD (r=0.87) than any other tested score. The most accurate score is based on a combination of the DOPE non-hydrogen atom statistical potential; surface, contact, and combined statistical potentials from MODPIPE; and two PSIPRED/DSSP scores. It was implemented in the SVMod program, which can now be applied to select the final model in various modeling problems, including fold assignment, target-template alignment, and loop modeling.

Correct Bond Order Assignment in a Molecular Framework Using Integer Linear Programming with Application to Molecules Where Only Non-Hydrogen Atom Coordinates Are Available

We describe a method based on linear programming, for deducing the correct bond orders in small molecules, which only needs the sigma bonds connectivity and atom symbols as input. The procedure checks whether the current structure can be written as a valid Lewis structure by assigning double and triple bonds by translating the octet equations into an integer linear program that is solved by an external solver. The procedure was intensively tested on some ligands from the protein data bank as well as some other exotic molecules, for which first the hydrogen topology is generated by a standard procedure from literature. The most stable Lewis structure is retained for which hydrogen coordinates are generated.

Knowledge-based prediction of DNA atomic structure from nucleic sequence.

A simple knowledge-based method for DNA atomic structure prediction from nucleic sequence is presented. We used free B-DNA crystal structures to estimate the distribution of trinucleotide base pairs and tetranucleotide base-pair steps conformational coordinates. We used these distributions as a basis to predict the 3D position of the non-hydrogen atoms of the nucleic bases of any arbitrary DNA sequence of any length. The only constraint imposed was that the structure is a B-DNA one with Watson-Crick complementary base pairs. The method was tested on not seen DNA structures with sequence lengths varying from 6bp to 12bp. The obtained predictions have RMSE around 0.5 A for the translational conformational coordinates, and around 5 degrees for the rotational. For the estimation of the nucleic base non-hydrogen atom coordinates the RMSE is around 1.1 A. The knowledge-based method outperformed a technique based on genetic algorithms in the prediction of B-DNA structures.

Molecular electronegativity-distance vector (MEDV-4): a two-dimensional QSAR method for the estimation and prediction of biological activities of estradiol derivatives

By using molecular electronegativity-distance vector (MEDV-4) approach, a two-dimensional quantitative structure–activity relationship (2D-QSAR) model has been developed to estimate and predict the binding activities of a series of 11β-, 16α-, 17α-substituted estradiols for estrogen receptor. Considering the contribution of each non-hydrogen atom, the MEDV-4 exhibits high relevance to the structural properties. The 10-parameter model yields a R 2=0.870 and a leave-one-out procedure cross-validation R CV 2=0.616. The parameters were screened by the stepwise multiple regression approach and the newly formed optimal models had R 2=0.852 and R CV 2=0.747 when the number of parameters are taken as m=6. The performance of the models is better than that reported in literature, and had high correlation with the typical parameters (hydrophobic parameter π 11, molecular refraction MR 11 and indicator variable I) used in literature. The MEDV-4 model can provide a simple and rapid way to investigate the binding activities of estradiols.

Ab Initio Study on the Effects of the Substituent and the Functional Group on the Isomerization of H3CC(X)Y and H2C(X)CHY (Y = SiH2, PH, S; X = H, CH3, NH2, OH, F)

We report the effects of the substituent and functional group on the tautomerizations of H3CC(X)Y and H2C(X)CHY (Y = SiH2, PH, S; X = H, CH3, NH2, OH, F) at the G2 level of theory. In the Y = SiH2 series, the enol forms (H2CCXSiH3) are thermodynamically more stable than their counterparts, by ca. 20−30 kcal/mol, regardless of their site of substitution. In the Y = PH and S cases, the keto forms (H3CC(X)PH, H3CC(X)S) are thermodynamically more stable than their counterparts by ca. 2−12 kcal/mol for the 1-substituted series, while for the 2-substituted series the enolization processes are either endothermic or exothermic, with their relative energies near 0. Combining these results with those from the previous study, the enolization is endothermic when the non-hydrogen atom in Y is more electronegative than a carbon atom and is exothermic if the former is more electropositive than the latter. Substituents with π-donating ability in the 1-substituted series increase the relative energy when Y = PH and S, but they decrease it when Y = SiH2. On the other hand, in the 2-substituted series, the relative energies decrease in the sequence H > CH3 > F > OH > NH2, which is the opposite order of the increasing π-donating abilities of these substituents. The barriers to enolization in this study range from 36 to 61 kcal/mol at the G2 level of theory. The effects of the functional groups and substituents on the energy barriers are explained by interpreting Hammond's postulate in terms of the position of the transition structure along the reaction coordinate, nT, defined by Agmon, Pearson's principle of hard and soft acids and bases, and Hammett's electron push/pull effect. By Mulliken population analysis, the electronic charge of the migrating hydrogen atom becomes gradually negative, which indicates the tautomeric interconversion is as an Hδ- transfer (or a hydride transfer). This is in contrast with that of the analogous process that occurs for compounds of the second period (Y = O, NH, and CH2).

Modified connectivity indices and their application to QSPR study.

A modified adjacency matrix was developed to delineate the chemical graph of a compound, in which the element a(ii) along the diagonal of the matrix reflects the numbers of the lone-pair electrons and pi bonds of the ith atom, and the off-diagonal element a(ij) of the matrix characterizes whether the jth non-hydrogen atom is bonded to the ith non-hydrogen atom as well as the number of hydrogen atoms bonded to the jth non-hydrogen atom. The corresponding vertex-degree matrix can distinguish the non-hydrogen atoms in the compound better than that from the original adjacency matrix. Based on the newly proposed adjacency matrix, modified molecular connectivity indices (mMCIs) were proposed as structural descriptors for organic compounds, which were applied to the QSPR studies on the boiling point temperature, molar volume and molar refraction of alkanes, alkenes and alcohols. The results show that, in most cases, the mMCIs give improved correlations than the original molecular connectivity indices (MCIs), which are particularly suitable to distinguish isomers.

Atom Depth as a Descriptor of the Protein Interior

Atom depth, defined as the distance (dpx, Å) of a nonhydrogen atom from its closest solvent-accessible protein neighbor, provides a simple but precise description of the protein interior. Mean residue depths can be easily computed and are very sensitive to structural features. From the analysis of the average and maximum atom depths of a set of 136 protein structures, we derive a limit of ∼200 residues for protein and protein domain size. The average and maximum atom depths in a protein are related to its size but not to the fold type. From the same set of structures, we calculated the mean residue depths for the 20 amino acid types, and show that they correlate well with hydrophobicity scales. We show that dpx values can be used to partition atoms in discrete layers according to their depth and to identify atoms that, although buried, are potential targets for posttranslational modifications like phosphorylation. Finally, we find a correlation between highly conserved residues in structural neighbors of the same fold type, and their mean residue depth in the reference structure.

Use of a novel electrotopological descriptor for the prediction of biological activity of peptide analogues

A new set of electrotopological descriptors called Molecular Electronegativity Topological Distance Vector (METDV) which are used to describe the molecular structure of peptide analogues is proposed based on the Pauling electronegativity and topological distance between each non-hydrogen atom. A quantitative structure activity relationship model, based on biological activity of 58 angiotensin converting enzyme (ACE) inhibitors, was constructed by multiple linear regression method. In order to explain the ability of theMETDV to characterize the molecular structure of peptides, a further investigation was performed by modeling quantitative structure activity relationship of bradykinin-potentiating pentapeptides. The results show that the novelMETDV has both excellent structural characterization ability and good activity estimation ability, and reinforce the key role of the joint use of electronic and topological descriptors.

Stability of macromolecular complexes.

Macromolecular interactions are crucial in numerous biologic processes, yet few general principles are available that establish firm expectations for the strength of these interactions or the expected contribution of specific forces. The simplest principle would be a monotonic increase in interactions as the size of the interface grows. The exact relationship might be linear or nonlinear depending on the nature of the forces involved. Simple "linear-free energy" relationships based on atomic properties have been well documented, for example, additivity for the interaction of small molecules with solvent, and, recently, have been explored for ligand-receptor interactions. Horton and Lewis propose such additivity based on buried surface area for protein-protein complexes. We investigated macromolecular interactions and found that the highest-affinity complexes do not fulfill this simple expectation. Instead, binding free energies of the tightest macromolecular complexes are roughly constant, independent of interface size, with the notable exception of DNA duplexes. By comparing these results to an earlier study of protein-ligand interactions we find that: (1) The maximum affinity is approximately 1.5 kcal/mol per nonhydrogen atom or 120 cal/mol A(2) of buried surface area, comparable to results of our earlier work; (2) the lack of an increase in affinity with interface size is likely due to nonthermodynamic factors, such as functional and evolutionary constraints rather than some fundamental physical limitation. The implication of these results have some importance for molecular design because they suggest that: (1) The stability of any given complex can be increased significantly if desired; (2) small molecule inhibitors of macromolecular interactions are feasible; and (3) different functional classes of protein-protein complexes exhibit differences in maximal stability, perhaps in response to differing evolutionary pressures. These results are consistent with the widespread observation that proteins have not evolved to maximize thermodynamic stability, but are only marginally stable.

Calculation of hydrodynamic properties of small nucleic acids from their atomic structure.

Hydrodynamic properties (translational diffusion, sedimentation coefficients and correlation times) of short B-DNA oligonucleotides are calculated from the atomic-level structure using a bead modeling procedure in which each non-hydrogen atom is represented by a bead. Using available experimental data of hydrodynamic properties for several oligonucleotides, the best fit for the hydrodynamic radius of the atoms is found to be approximately 2.8 A. Using this value, the predictions for the properties corresponding to translational motion and end-over-end rotation are accurate to within a few percent error. Analysis of NMR correlation times requires accounting for the internal flexibility of the double helix, and allows an estimation of approximately 0.85 for the Lipari-Szabo generalized order parameter. Also, the degree of hydration can be determined from hydrodynamics, with a result of approximately 0.3 g (water)/g (DNA). These numerical results are quite similar to those found for globular proteins. If the hydrodynamic model for the short DNA is simply a cylindrical rod, the predictions for overall translation and rotation are slightly worse, but the NMR correlation times and the degree of hydration, which depend more on the cross-sectional structure, are more severely affected.

Charge density in Cu(glygly)(OH2)2·H2O at 10 K and the reproducibility of atomic orbital populations

An extensive accurate X-ray data set for diaqua(glycylglycinato)copper(II) hydrate, Cu(glygly)(OH2)2·H2O, at 10 K is reported. The molecular structure is very accurately defined. The Cu(glygly)(OH2)2 unit approximates to a square pyramid with the apical water molecule only loosely bound. The data have been analysed by multipole and valence orbital population models and the topology of the electron density has been examined for chemical bonding features. There are two independent molecules of the complex in the unit cell, and the agreement between their bonding features is used as a measure of the validity of obtaining quantitative valence-related parameters from X-ray data. The agreement is quite reasonable. Atomic charges evaluated by the Stockholder and monopole population methods do not conform with chemical expectations. Those from the sum of valence orbital populations and the atom-in-molecules approach are more reasonable but contain anomalies. The ‘hole’ in the 3d10 shell corresponding to the 3d9 configuration, predicted on the grounds of ligand field theory, is seen as a much lowered (1.16 e) population of 3dz2 relative to the other 3d orbitals (av. 1.65 e). Populations of valence hybrid orbitals conform with chemical expectations and, for the (sp2)σ hybridised carbon atoms of CO groups, relocation of electrons from a pπ orbital to those σ hybrids is seen. Bond critical points have been located between all the appropriate non-hydrogen atom pairs. The electron densities at these points show values typical for mixed ionic/covalent character in the Cu–O and Cu–N interactions and of covalent character in the C–C, O–C and N–C bonds. The Laplacian of the density at the bond critical points also behaves in a fashion which conforms with those bond types, although the scatter in the results is greater. There is little evidence of the copper atom having influenced the electron densities of the bonds between light atoms within the glycylglycinato moiety.

Design of novel pharmaceutical products via combinatorial optimization

This paper describes a new methodology for the application of computer-aided molecular design to the design of pharmaceutical products with prespecified physical properties. For a pharmaceutical product to be effective, it must not only cause a desirable therapeutic effect, but it must also have proper values of physical properties such as solubility and density. In order to apply computer-aided molecular design to the discovery of new pharmaceuticals, it is therefore necessary to be able to first predict the physical and biological properties of a given molecule, and then optimize over an entire set of molecules to find one which matches target values on those properties. This work employs topological descriptors to predict the physical properties of pharmaceutical molecules. The descriptors used here, called connectivity indices, are easy to compute, yet contain valuable information about the internal molecular structure of a molecule. Property prediction, via connectivity indices, can be viewed as an improvement over group contribution methods, since these indices take into account molecular connectivity and internal electronic structure in addition to the identity of each group in the molecule. Thus these indices correlate well with physical properties which are important in pharmaceutical design. Furthermore, these indices are fairly simple to compute, and a proper choice of variables to describe the molecule allows the equations for these indices to be written in a linear form. The optimization problem used here combines a set of basic groups, which are defined as a non-hydrogen atom at a given valency state bonded to a given number of hydrogens, to form a candidate molecule. Each candidate molecule can then be tested by computing estimated property values and comparing those to prespecified target values. Structural constraints are also added to the problem to ensure a connected, stable molecule is generated. The set of constraints and the correlation equations for property prediction are then combined and reformulated, resulting in a mixed integer linear program (MILP). If a certain functional group is known to be required in the molecule, this requirement can also be added to the constraint set. For problems consisting of a smaller number of basic groups or property targets, commercial solvers can be employed to solve the resulting MILP. The effectiveness of this method is presented through the solution of a small example problem.

In- and out-Cyclophanes Bearing Non-Hydrogen Bridgehead Substituents.

The syntheses of several cyclophanes containing a triaryl(element) "top" poised above a trisubstituted benzene "base" were carried out to install a non-hydrogen atom as a substituent on a bridgehead with an inwardly directed geometry. Most significantly, the tribenzo 6-fluoro-6-sila-2,10,19-trithia[5(6,14)][11]metacyclophane 2 was prepared by condensation of tris[2-(bromomethyl)phenyl]fluorosilane and 1,3,5-tris(mercaptomethyl)benzene in 0.4% yield. The X-ray structure of 2 shows that the cyclophane adopts an in-configuration; i.e., the fluorine atom is on the interior of the macrocycle and only 2.8 Å from the center of the basal aromatic ring. Compound 2 is one of only a very few molecules to contain a non-hydrogen in-atom, and the in-fluorosilane of 2 is the largest in-functional group to have been installed in any molecule. Similar attempts to prepare an in-phosphine oxide were unsuccessful, although the corresponding in-phosphines were prepared, and an attempt to prepare an in-methylsilane led instead to the corresponding out-isomer.

A Method for Substructure Search by Atom-Centered Multilayer Code

Atom-Centered Multilayer Code (ACMC) is a novel coding algorithm by characterizing the sphere environment of a non-hydrogen atom, called center atom. This algorithm starts from the center atom and then develops to its environment layer by layer automatically without predefining specific fragments, and the number of layers is determined on the structure of the coded compound without limit. Fast searching strategy at the atomic level is obtained by using this code. The coding process and the global structure and substructure searching are discussed with examples.

Routineab initiostructure determination of chlorothiazide by X-ray powder diffraction using optimised data collection and analysis strategies

The likelihood of solving crystal structures from powder diffraction data is greatly enhanced if data collection and analysis strategies can be designed to effectively remove Bragg peak overlap. In this way, accurate normalised structure factors of essentially single-crystal quality are obtained. Such strategies are illustrated here with theab initio solution, from powder diffraction data using traditional direct methods, of the clinically used diuretic compound chlorothiazide. The structure solution is outstanding in that, despite the non-centrosymmetric, triclinic symmetry, all 17 non-hydrogen atom positions are clearly visible in the E-map generated from the top direct methods solution.

X-ray structure of tricyclohexylmethyl chloride

The X-ray crystallographic structure of tricyclohexylmethyl chloride, a precursor of the tricyclohexylmethyl radical, has been determined. Colourless tablets of C19H33Cl crystallized from hexane/chloroform in the orthorhombic space group Pnma, with cell dimensions a=10.725(3),b=15.670(3),c=10.168(3) A;V=1708.8(1.3) A3;Z=4. 1586 reflections withI>3 σ(I), and 302 with zero intensity, on refinement gaveR=0.046,Rw=0.076. The three cyclohexyl rings are arranged to give the molecule a plane of symmetry containing the central C−H axis. The large volume per nonhydrogen atom, of about 21.3 A3, is close to values found in the crystal structures of analogous tricyclohexyl compounds.

Linear Solvation Energy Relationship of the Limiting Partition Coefficient of Organic Solutes between Water and Activated Carbon

A linear solvation energy relationship has been found for 353 values of the limiting adsorption coefficients of diverse chemicals: log K = −0.37 + 0.0341Vi − 1.07β + D + 0.65P with R = 0.951, s = 0.51, n = 353, and F = 818.0, where Vi is the intrinsic molar volume; β is a measure of the hydrogen bond acceptor strength of the solute; D is an index parameter for the research group which includes the effects of the different types of carbon used, the temperature, and the length of time allowed for the adsorption equilibrium to be established; and P is an index parameter for the flatness of the molecule. P is defined to be unity if there is an aromatic system in the molecule or if there is a double bond or series of conjugated double bonds with no more that one non-hydrogen atom beyond the double bond and zero otherwise. A slightly better fit is obtained if the two-thirds power of Vi is used as a measure of the surface area in place of the volume term: log K = −1.75 + 0.227V2/3 − 1.10β + D + 0.60P with R = 0.954, s = 0.49, n = 353, and F = 895.39. This is the first quantitative measure of the effect of the shape of the molecule on its tendency to be adsorbed on activated carbon.

Rapid approximation to molecular surface area via the use of Boolean logic and look‐up tables

AbstractWe report the development of a new approximate method of calculating molecular surface areas. Our technique is based upon the method of Sharake and Rupley but incorporates several major advances. First, we represent the state of surface points as bits in a bit string so we can utilize Boolean operations to simultaneously turn off multiple test points in one Boolean AND operation. Second, we use a series of Boolean mask look‐up tables to reduce the time complexity of the calculation of molecular surface area down to the same magnitude as doing a potential energy evaluation. When we use a 256 surface point sphere for all of the atoms in BPTI, a 454 nonhydrogen atom protein, and a 1.4‐Å solvent probe, we in general underestimate the total solvent‐accessible surface area (SASA) by approximately 1.25% with a correlation coefficient of 0.9990 over a wide range of conformations. The average CPU time required to calculate the SASA of a BPTI conformer is 0.58 s on an SGI 4D/220 workstation. We also describe a method by which we can calculate an approximate finite difference SASA gradient for BPTI in 0.79 of CPU time. © 1993 John Wiley &amp; Sons, Inc.