A graph-based multi-sample test for identifying pathways associated with cancer progression

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway being studied, followed by a graph-based multivariate test, which is very easy to implement in practice. The new test is applied to the rich Cancer Genome Atlas data to study the (epi)genetic alterations of 186 KEGG pathways in the development of serous ovarian cancer. To make use of the comprehensive data, we incorporate three data types in the analysis representing gene expression level, copy number and DNA methylation level. Our analysis suggests a list of nine pathways that are closely associated with serous ovarian cancer progression, including cell cycle, ERBB, JAK-STAT signaling and p53 signaling pathways. By pairwise tests, we found that most of the identified pathways contribute only to a particular transition step. For instance, the cell cycle and ERBB pathways play key roles in the early-stage transition, while the ECM receptor and apoptosis pathways contribute to the progression from stage III to stage IV. The proposed computational pipeline is powerful in detecting important pathways and gene sets that drive cancers at certain stage(s). It offers new insights into the understanding of molecular mechanism of cancer initiation and progression.     

Three-dimensional structure-activity relationship analysis between motilin and motilide using conformational analysis and a novel molecular superposing method

Motilide, an erythromycin derivative, has been shown to equal activity to that of motilin as an agonist at the motilin receptor. However, there is little information on the three-dimensional (3D) structure-activity relationship between these two molecules, largely because they have quite different structures. In this study, we applied a rational computational procedure consisting of conformational analysis and a novel superposing method to investigate the 3D structure-activity relationship between motilide and motilin. We propose common 3D structural features between these molecules, which may be important for their similar activity.     

Organic Chemistry as a Language and the Implications of Chemical Linguistics for Structural and Retrosynthetic Analyses

Methods of computational linguistics are used to demonstrate that a natural language such as English and organic chemistry have the same structure in terms of the frequency of, respectively, text fragments and molecular fragments. This quantitative correspondence suggests that it is possible to extend the methods of computational corpus linguistics to the analysis of organic molecules. It is shown that within organic molecules bonds that have highest information content are the ones that 1) define repeat/symmetry subunits and 2) in asymmetric molecules, define the loci of potential retrosynthetic disconnections. Linguistics‐based analysis appears well‐suited to the analysis of complex structural and reactivity patterns within organic molecules.     

Theoretical studies on the chemical decomposition of 5-aza-2′-deoxycytidine: DFT study and Monte Carlo simulation

The decomposition mechanism of 5-Aza-2??-deoxycytidine has been studied by the use of computational techniques. Optimized structures for all of the stationary points in the gas phase were investigated at B3LYP/6-31+G(d,p) level of theory. Single-point energies were determined employing the ab initio MP2 method in conjunction with the 6-311++G(d,p) basis set. Five possible pathways, paths 1?C5, were evaluated. In each pathway, the direct (A-paths 1?C5) and water-assisted (B-paths 1?C5) processes were considered. Meanwhile, the local microhydration model with the direct participation of three water molecules around the reaction centers was adopted to mimic the system for the water-assisted decomposition mechanisms above, where one water molecule is the nucleophilic reactant and the other two are the auxiliary molecules located on each side of the nucleophilic water. The results in the gas phase exhibit that the energy barriers of the water-assisted pathways based on the local microhydration model decrease dramatically by about 15?C20?kcal/mol as compared with those of the direct pathways because of the contribution of the auxiliary water molecules. In addition, bulk solvent effects of water were determined by means of the self-consistent reaction field based on the conductor-like polarized continuum model and Monte Carlo simulation with free energy perturbation (MC-FEP) technique, respectively. Our computational results indicate that B-path 3 in the decomposition reaction of 5-azadC is the most favorable, where the calculated rate constant (1.68?×?10^?3?min^?1) using the MC-FEP method is within the range of the experimentally determined values [(5.89?±?0.54)?×?10^?3?min^?1 by UV and (1.46?±?0.08)?×?10^?3?min^?1 by NMR].     

An exploration of a novel strategy for superposing several flexible molecules

Summary This paper describes a computational strategy for the superposition of a set of flexible molecules. The combinatorial problems of searching conformational space and molecular matching are reduced drastically by the combined use of simulated annealing methods and cluster analysis. For each molecule, the global minimum of the conformational energy is determined by annealing and the search trajectory is retained in a history file. All the significantly different low-energy conformations are extracted by cluster analysis of data in the history file. Each pair of molecules, in each of their significantly different conformations, is then matched by simulated annealing, using the difference-distance matrix as the objective function. A set of match statistics is then obtained, from which the best match taken from all different conformations can be found. The molecules are then superposed either by reference to a base molecule or by a consensus method. This strategy ensures that as wide a range of conformations as possible is considered, but at the same time that the smallest number of significantly different conformations is used. The method has been tested on a set of six angiotensin II antagonists with between 7–11 rotatable bonds.     

Rational Design of a Cocktail of Inhibitors against Aβ Aggregation

It has been reported that many molecules could inhibit the aggregation of Aβ (amyloid-β) through suppressing either primary nucleation, secondary nucleation, or elongation processes. In order to suppress multiple pathways of Aβ aggregation, we screened 23 small molecules and found two types of inhibitors with different inhibiting mechanisms based on chemical kinetics analysis. Trp-glucose conjugates ( AS2 ) could bind with fibril ends while natural products ( D3 and D4 ) could associate with monomers. A cocktail of these two kinds of molecules achieved co-inhibition of various fibrillar species and avoid unwanted interference.     

A theory of molecules in molecules

The theory of molecules in molecules introduced in previous articles is applied to study the hydrogen bonding interaction in the linear configuration of the dimer of FH. The transfer of localized molecular orbitals as well as the majority of the additional approximations introduced to save computational time can be justified and shown to lead to results in good agreement with those of ab initio calculations. An energy analysis of the effect of the hydrogen bond formation on the localized orbitals is given. It is seen that the effect is small, the major contribution to the binding energy is given by a first order perturbation treatment.     

Partial optimization of large molecules and clusters

By examining the displacement coordinate metric three modes of constrained optimization for large molecules and clusters are suggested. The first method corresponds to a conventional optimization using internal coordinates. The second mode has applications with respect to both internal and cartesian coordinates. The final mode is particularly interesting because it can result in computational savings. A mixture of both internal and cartesian coordinates is specified where these coordinates are usually a subset of the molecules or clusters total coordinate set. In the optimization only a subset of the energy derivatives need be evaluated reducing the computational effort associated with the gradient calculation.     

Advances in the analysis of dynamic protein complexes by proteomics and data processing

Signal transduction governs virtually every cellular function of multicellular organisms, and its deregulation leads to a variety of diseases. This intricate network of molecular interactions is mediated by proteins that are assembled into complexes within individual signaling pathways, and their composition and function is often regulated by different post-translational modifications. Proteomic approaches are commonly used to analyze biological complexes and networks, but often lack the specificity to address the dynamic and hence transient nature of the interactions and the influence of the multiple post-translational modifications that govern these processes. Here we review recent developments in proteomic research to address these limitations, and discuss several technologies that have been developed for this purpose. The synergy between these proteomic and computational tools, when applied together with global methods to the analysis of individual proteins, complexes and pathways, may allow researchers to unravel the underlying mechanisms of signaling networks in greater detail than previously possible.     

Improved efficiency of focal point conformational analysis with truncated correlation consistent basis sets

It has been suggested that the computational cost of correlated ab initio calculations could be reduced efficiently by using truncated basis sets on hydrogen atoms (Mintz et al., J Chem Phys 2004, 121, 5629). We now explore this proposal in the context of conformational analysis of small molecules, such as hydrogen peroxide, dimethyl ether, ethyl methyl ether, formic acid, methyl formate, and several small alcohols. It is found that truncated correlation consistent basis sets that lack certain higher angular momentum functions on hydrogen atoms offer accuracy similar to traditional Dunning's basis sets for conformational analysis. Combination of such basis sets with the basis set extrapolation technique to estimate Hartree-Fock and M?ller-Plesset second order energies provides composite extrapolation model chemistries that are significantly more accurate and faster than analogous single point calculations with traditional correlation consistent basis sets. Root mean square errors of best composite extrapolation model chemistries on the used set of molecules are within 0.03 kcal/mol of traditional focal point conformational energies. The applicability of composite extrapolation methods is illustrated by performing conformational analysis of tert-butanol and cyclohexanol. For comparison, conformational energies calculated with popular molecular mechanics force fields are also given.     

Nitro group as a means of attaching organic molecules to silicon: nitrobenzene on Si(100)-2 x 1

This paper will present the computational and experimental infrared studies of the reactions of nitrobenzene on a Si(100) surface, a prototypical model reaction for understanding the behavior of bifunctional molecules on semiconductor surfaces. The initial reaction of nitrobenzene with the Si(100)-2 x 1 occurs via 1,3-dipolar cycloaddition of the nitro group to the silicon surface dimer. Computational exploration of the initial adsorption configurations suggests that two stable structures can be formed: one with the phenyl ring essentially perpendicular to the surface; the other one with the tilt angle of approximately 113 degrees with respect to the surface normal. The barrier for converting the latter into the former, more stable by approximately 13 kJ/mol, is 19.1 kJ/mol. Further thermal reactions are analyzed, and the reaction pathways are compared for the computational models with fixed vs relaxed subsurface silicon atoms. While all the surface species resulting from nitrobenzene transformations on the Si(100)-2 x 1 surface studied here are thermodynamically stable, most of the reaction pathways can be ruled out on the basis of the analysis of the transition states leading to these species and on the comparison of predicted and measured vibrational spectra. As a result, the exact adsorption configurations can be pinpointed.     

G protein betagamma subunits as targets for small molecule therapeutic development

G proteins mediate the action of G protein coupled receptors (GPCRs), a major target of current pharmaceuticals and a major target of interest in future drug development. Most pharmaceutical interest has been in the development of selective GPCR agonists and antagonists that activate or inhibit specific GPCRs. Some recent thinking has focused on the idea that some pathologies are the result of the actions of an array of GPCRs suggesting that targeting single receptors may have limited efficacy. Thus, targeting pathways common to multiple GPCRs that control critical pathways involved in disease has potential therapeutic relevance. G protein betagamma subunits released from some GPCRs upon receptor activation regulate a variety of downstream pathways to control various aspects of mammalian physiology. There is evidence from cell- based and animal models that excess Gbetagamma signaling can be detrimental and blocking Gbetagamma signaling has salutary effects in a number of pathological models. Gbetagamma regulates downstream pathways through modulation of enzymes that produce cellular second messengers or through regulation of ion channels by direct protein-protein interactions. Thus, blocking Gbetagamma functions requires development of small molecule agents that disrupt Gbetagamma protein interactions with downstream partners. Here we discuss evidence that small molecule targeting Gbetagamma could be of therapeutic value. The concept of disruption of protein-protein interactions by targeting a "hot spot" on Gbetagamma is delineated and the biochemical and virtual screening strategies for identification of small molecules that selectively target Gbetagamma functions are outlined. Evaluation of the effectiveness of virtual screening indicates that computational screening enhanced identification of true Gbetagamma binding molecules. However, further refinement of the approach could significantly improve the yield of Gbetagamma binding molecules from this screen that could result in multiple candidate leads for future drug development.     

Special Collection: Computational Chemistry

Chemists know well the value of an experimental or a theoretical result, but what is the value of a computational result? Simulation is neither theory nor experience, nor a mere calculation tool, but a genuine way of approaching reality that is transforming the scientific method. In some cases, it offers explanations to observations or experiments that seem incomprehensible because they are too complex. In this case, the computation serves as a relief. An experiment that converges with a certain computation has more scientific value than an experiment that does not converge with anything at all. In other cases, contribution of computational chemistry is essential because there is no experimental manner to determine what happens during a chemical process; for instance, in the path from reactants to products in (fast) reactions. Now, computational chemistry provides additional information that is not possible to obtain from experiments, so it is a valuable complement to them. Indeed, fruitful synergy between computation and experiment has led to the approach of theory-driven experimentation. Finally, computational chemistry helps to legitimize models or theories that have little opportunity to be contrasted with reality. In this situation, computational chemistry is not experience, but it does substitute it in relation to theory. In the present special collection, we have examples of the different ways computational chemistry helps chemists to interpret the electronic and molecular structure of molecules and their reactivity.     

Photochemical dynamics of E-iPr-furylfulgide

As an important theoretical step towards unraveling the mechanistic details of the photochemical switching processes in molecules of the fulgide type, we carried out a large-scale, full-dimensional computational study of the ring closure reaction of E-iPr-furylfulgide. Simulated static UV spectra and femtosecond transient spectra are in good agreement with their experimental counterparts. Using surface-hopping photodynamics simulations, we identify three major de-excitation pathways and their interplay. The dominant photochemical pathway (70% of the trajectories) allows for ring closure, while the two minor pathways involve E-Z double bond isomerization rather than cyclization. The relative abundance of the pathways is rationalized by arguments linking structure with dynamics. It should be emphasized, however, that the distinction into three pathways is only a simplified interpretational model, since the actual dynamical trajectories do not strictly follow these idealized pathways but often show mixed behaviour, evolving along two or three of them during the course of the simulation.     

Stepwise and concerted electron-transfer/bond breaking reactions. solvent control of the existence of unstable pi ion radicals and of the activation barriers of their heterolytic cleavage

Available data from various sources seem to indicate an important role of solvation in the cleavage rates of intermediate pi ion radicals, in the passage from concerted to stepwise electron-transfer/bond breaking reaction pathways and even in the very existence of pi ion radicals. After preliminary computations treating the solvent as dielectric continuum, these expectations are examined with the help of a simple model system involving the anion radical of ONCH(2)Cl and two molecules of water, which allows the application of advanced computational techniques and a treatment of these solvent effects that emphasizes the role of solvent molecules that sit close to the charge centers of the molecule. A pi ion radical minimum indeed appears upon introduction of the two water molecules, and cleavage is accompanied by their displacement toward the leaving anion, thus offering a qualitative mimicry of the experimental observations.     

Engineering enzyme specificity using computational design of a defined-sequence library

Engineered biosynthetic pathways have the potential to produce high-value molecules from inexpensive feedstocks, but a key limitation is engineering enzymes with high activity and specificity for new reactions. Here, we developed a method for combining structure-based computational protein design with library-based enzyme screening, in which inter-residue correlations favored by the design are encoded into a defined-sequence library. We validated this approach by engineering a glucose 6-oxidase enzyme for use in a proposed pathway to convert D-glucose into D-glucaric acid. The most active variant, identified after only one round of diversification and screening of only 10,000 wells, is approximately 400-fold more active on glucose than is the wild-type enzyme. We anticipate that this strategy will be broadly applicable to the discovery of new enzymes for engineered biological pathways.     

Vibrational projection analysis: New tool for quantitatively comparing vibrational normal modes of similar molecules

A new method for quantitatively comparing calculated vibrational modes is described that relies on projecting the vectors describing the normal modes of one molecule onto those of a basis molecule. The procedure virtually automates the assignment of vibrational modes from one molecule to a second, structurally similar one. We illustrate the concept by using the classical Wilson modes of benzene as a basis for describing normal modes of the monosubstituted benzene derivatives phenol, phenol-d5, and phenol radical cation. These examples demonstrate the method's power for accurately assigning and comparing the normal modes of molecules perturbed by chemical substitution, isotopic substitution, or oxidation state. The vibrational projection analysis method—a special case of vector projection analysis—is compared and contrasted with total energy distribution analysis, perhaps the most commonly used technique for quantitatively comparing vibrational modes, and is found superior in each case when comparing normal modes. Vibrational projection analysis need not be limited to single molecules and quantum calculations, because normal modes may be obtained for much larger systems using molecular mechanics or molecular dynamics techniques. The method should therefore prove useful for interpreting the normal modes of ordered periodic solids and structures perturbed by noncovalent contacts, including proteins and polymers. The method may also prove useful in evaluating new computational methods by allowing direct, quantitative comparison of the vibrational modes obtained from different techniques. The power of this technique will make vibrational projection analysis a valuable tool for computational chemists as well as those using calculations to complement vibrational spectroscopic measurements. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1663–1674, 1998     

Theoretical studies on the chemical decomposition of 5-aza-2′-deoxycytidine: DFT study and Monte Carlo simulation

The decomposition mechanism of 5-Aza-2′-deoxycytidine has been studied by the use of computational techniques. Optimized structures for all of the stationary points in the gas phase were investigated at B3LYP/6-31+G(d,p) level of theory. Single-point energies were determined employing the ab initio MP2 method in conjunction with the 6-311++G(d,p) basis set. Five possible pathways, paths 1–5, were evaluated. In each pathway, the direct (A-paths 1–5) and water-assisted (B-paths 1–5) processes were considered. Meanwhile, the local microhydration model with the direct participation of three water molecules around the reaction centers was adopted to mimic the system for the water-assisted decomposition mechanisms above, where one water molecule is the nucleophilic reactant and the other two are the auxiliary molecules located on each side of the nucleophilic water. The results in the gas phase exhibit that the energy barriers of the water-assisted pathways based on the local microhydration model decrease dramatically by about 15–20 kcal/mol as compared with those of the direct pathways because of the contribution of the auxiliary water molecules. In addition, bulk solvent effects of water were determined by means of the self-consistent reaction field based on the conductor-like polarized continuum model and Monte Carlo simulation with free energy perturbation (MC-FEP) technique, respectively. Our computational results indicate that B-path 3 in the decomposition reaction of 5-azadC is the most favorable, where the calculated rate constant (1.68 × 10⁻³ min⁻¹) using the MC-FEP method is within the range of the experimentally determined values [(5.89 ± 0.54) × 10⁻³ min⁻¹ by UV and (1.46 ± 0.08) × 10⁻³ min⁻¹ by NMR].     

Predicting Trigger Bonds in Explosive Materials through Wiberg Bond Index Analysis

Understanding the explosive decomposition pathways of high‐energy‐density materials (HEDMs) is important for developing compounds with improved properties. Rapid reaction rates make the detonation mechanisms of HEDMs difficult to understand, so computational tools are used to predict trigger bonds—weak bonds that break, leading to detonation. Wiberg bond indices (WBIs) have been used to compare bond densities in HEDMs to reference molecules to provide a relative scale for the bond strength to predict the activated bonds most likely to break to trigger an explosion. This analysis confirms that X?NO₂ (X=N,C,O) bonds are trigger linkages in common HEDMs such as TNT, RDX and PETN, consistent with previous experimental and theoretical studies. Calculations on a small test set of substituted tetrazoles show that the assignment of the trigger bond depends upon the functionality of the material and that the relative weakening of the bond correlates with experimental impact sensitivities.