SDOVS: A solvent dipole ordering‐based method for virtual screening

We previously reported that solvent dipole ordering (SDO) at the ligand binding site of a protein indicates an outline of the preferred shape and binding pose of the ligands. We suggested that SDO‐mimetic pseudo‐molecules that mimic the 3D shape of the SDO region could be used as molecular queries with a shape similarity matching method in virtual screening. In this work, a virtual screening method based on SDO, named SDOVS, was proposed. This method was applied to virtual screening of ligands for four typical drug target proteins and the performance compared with that of FRED (well‐known rigid docking method); the efficiency of SDOVS was demonstrated to be better than FRED. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

PhAST: pharmacophore alignment search tool

We present a ligand-based virtual screening technique (PhAST) for rapid hit and lead structure searching in large compound databases. Molecules are represented as strings encoding the distribution of pharmacophoric features on the molecular graph. In contrast to other text-based methods using SMILES strings, we introduce a new form of text representation that describes the pharmacophore of molecules. This string representation opens the opportunity for revealing functional similarity between molecules by sequence alignment techniques in analogy to homology searching in protein or nucleic acid sequence databases. We favorably compared PhAST with other current ligand-based virtual screening methods in a retrospective analysis using the BEDROC metric. In a prospective application, PhAST identified two novel inhibitors of 5-lipoxygenase product formation with minimal experimental effort. This outcome demonstrates the applicability of PhAST to drug discovery projects and provides an innovative concept of sequence-based compound screening with substantial scaffold hopping potential.     

Quantum fidelity for analyzing atoms and fragments in molecule: Application to similarity,chirality, and aromaticity

Quantum information theory is applied to formulate a new technique for dealing with molecular similarity problems. In this technique, the so‐called quantum fidelity appears to be a counterpart of the conventional similarity measure due to Carbo (Carbo, R.; Leyda, L.; Arnau, M. Int J Quantum Chem 1980, 17, 1185). We define many‐body spin‐free density matrices for atoms and fragments in molecule, and compute corresponding fidelity measures for molecular subsystems. It allows us to treat the problem from the beginning within a many‐electron setting. The approach is employed for analyzing similarity between free atoms and atoms in molecule. A new chirality index, as based on the fidelity between molecule and its mirror image, is suggested to be an approximately additive nonnegative quantity. We also examine a local aromaticity by computing the fidelity measures for benzenoid fragments in polyaromatic hydrocarbons. A detailed study of the proposed indices is reported at the ab initio or semiempirical levels. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011     

Conductor‐like screening model for relaxed excited states: Implementation in the semiempirical method MSINDO

Two approaches to treat solvent polarization and reorientation effects for excited states of molecules and surfaces have been implemented in the recently developed MSINDO‐sCIS method (Gadaczek, Krause, Hintze, Bredow, J. Chem. Theory Comput. 2011, 7, 3675). They allow for an efficient calculation of analytical energy gradients and hence open the opportunity to investigate fluorescence effects or photochemical reactions in solution for large molecules that are difficult to treat with high‐level methods. Both approaches are based on the conductor‐like screening model (COSMO) (Klamt and Schüürmann, J. Chem. Soc., Perkin Trans. 1993, 2, 799) in combination with the configuration interaction singles (CIS) method (Foresman, Head‐Gordon, Pople, and Frisch, J. Phys. Chem. 1992, 96, 135). The paper gives a brief outline of the theoretical background. As a first application, solvent shifts of three well‐studied, environment‐sensitive fluorescent dyes (Kucherak, Didier, Mély, and Klymchenko, J. Phys. Chem. Lett. 2010, 1, 616) have been calculated and compared with experimental results and standard time‐dependent density functional theory. A statistical evaluation of MSINDO‐COSMO‐sCIS is provided for a set of 39 molecules suggested recently by Jacquemin et al. (Jacquemin, Planchat, Adamo, and Mennucci, J. Chem. Theory Comput. 2012, 8, 2359). Calculated vertical and adiabatic excitation energies and fluorescence energies are compared to experimental data. © 2014 Wiley Periodicals, Inc.     

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function,efficient optimization,and multithreading

AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed‐up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed‐up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

RNA secondary structure alignment based on an extended binary coding method

Recently, we proposed a three‐dimensional cube representation of RNA secondary structure. An efficient method for mutation analysis has been proposed based on the introduced representation. According to the proposed three‐dimensional cube representations, we will introduce an extended binary coding method for RNA secondary structure alignment by converting the structure alignment to sequence alignment. Using our method, the result of structure alignment can be obtained quickly. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011     

Acceleration of the GAMESS‐UK electronic structure package on graphical processing units

The approach used to calculate the two‐electron integral by many electronic structure packages including generalized atomic and molecular electronic structure system‐UK has been designed for CPU‐based compute units. We redesigned the two‐electron compute algorithm for acceleration on a graphical processing unit (GPU). We report the acceleration strategy and illustrate it on the (ss|ss) type integrals. This strategy is general for Fortran‐based codes and uses the Accelerator compiler from Portland Group International and GPU‐based accelerators from Nvidia. The evaluation of (ss|ss) type integrals within calculations using Hartree Fock ab initio methods and density functional theory are accelerated by single and quad GPU hardware systems by factors of 43 and 153, respectively. The overall speedup for a single self consistent field cycle is at least a factor of eight times faster on a single GPU compared with that of a single CPU. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

Efficiency of tabu‐search‐based conformational search algorithms

Efficient conformational search or sampling approaches play an integral role in molecular modeling, leading to a strong demand for even faster and more reliable conformer search algorithms. This article compares the efficiency of a molecular dynamics method, a simulated annealing method, and the basin hopping (BH) approach (which are widely used in this field) with a previously suggested tabu‐search‐based approach called gradient only tabu search (GOTS). The study emphasizes the success of the GOTS procedure and, more importantly, shows that an approach which combines BH and GOTS outperforms the single methods in efficiency and speed. We also show that ring structures built by a hydrogen bond are useful as starting points for conformational search investigations of peptides and organic ligands with biological activities, especially in structures that contain multiple rings. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

Communications on quantum similarity,part 3: A geometric‐quantum similarity molecular superposition algorithm

This work describes a new procedure to obtain optimal molecular superposition based on quantum similarity (QS): the geometric‐quantum similarity molecular superposition (GQSMS) algorithm. It has been inspired by the QS Aufbau principle, already described in a previous work, to build up coherently quantum similarity matrices (QSMs). The cornerstone of the present superposition technique relies upon the fact that quantum similarity integrals (QSIs), defined using a GTO basis set, depend on the squared intermolecular atomic distances. The resulting QSM structure, constructed under the GQSMS algorithm, becomes not only optimal in terms of its QSI elements but can also be arranged to produce a positive definite matrix global structure. Kruskal minimum spanning trees are also discussed as a device to order molecular sets described in turn by means of QSM. Besides the main subject of this work, focused on MS and QS, other practical considerations are also included in this study: essentially the use of elementary Jacobi rotations as QSM refinement tools and inward functions as QSM scaling methods. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011     

Comment on “A stationary‐wave model of enzyme catalysis” by Carlo Canepa

Energy barriers for enzyme‐catalyzed reactions calculated with quantum mechanics/molecular mechanics (QM/MM) and empirical valence bond (EVB) methods can be in excellent agreement with activation energies derived from experiments, supporting the applicability of transition state theory for enzymic reactions. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011     

Molecular dynamics simulations and free energy calculations on the enzyme 4‐hydroxyphenylpyruvate dioxygenase

4‐Hydroxyphenylpyruvate dioxygenase is a relevant target in both pharmaceutical and agricultural research. We report on molecular dynamics simulations and free energy calculations on this enzyme, in complex with 12 inhibitors for which experimental affinities were determined. We applied the thermodynamic integration approach and the more efficient one‐step perturbation. Even though simulations seem well converged and both methods show excellent agreement between them, the correlation with the experimental values remains poor. We investigate the effect of slight modifications on the charge distribution of these highly conjugated systems and find that accurate models can be obtained when using improved force field parameters. This study gives insight into the applicability of free energy methods and current limitations in force field parameterization. © 2011 Wiley Periodicals, Inc. J Comput Chem 2011     

Using Gaussian model to improve biological sequence comparison

One of the major tasks in biological sequence analysis is to compare biological sequences, which could serve as evidence of structural and functional conservation, as well as of evolutionary relations among the sequences. Numerous efficient methods have been developed for sequence comparison, but challenges remain. In this article, we proposed a novel method to compare biological sequences based on Gaussian model. Instead of comparing the frequencies of k‐words in biological sequences directly, we considered the k‐word frequency distribution under Gaussian model which gives the different expression levels of k‐words. The proposed method was tested by similarity search, evaluation on functionally related genes, and phylogenetic analysis. The performance of our method was further compared with alignment‐based and alignment‐free methods. The results demonstrate that Gaussian model provides more information about k‐word frequencies and improves the efficiency of sequence comparison. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Identification of small molecule aggregators from large compound libraries by support vector machines

Small molecule aggregators non‐specifically inhibit multiple unrelated proteins, rendering them therapeutically useless. They frequently appear as false hits and thus need to be eliminated in high‐throughput screening campaigns. Computational methods have been explored for identifying aggregators, which have not been tested in screening large compound libraries. We used 1319 aggregators and 128,325 non‐aggregators to develop a support vector machines (SVM) aggregator identification model, which was tested by four methods. The first is five fold cross‐validation, which showed comparable aggregator and significantly improved non‐aggregator identification rates against earlier studies. The second is the independent test of 17 aggregators discovered independently from the training aggregators, 71% of which were correctly identified. The third is retrospective screening of 13M PUBCHEM and 168K MDDR compounds, which predicted 97.9% and 98.7% of the PUBCHEM and MDDR compounds as non‐aggregators. The fourth is retrospective screening of 5527 MDDR compounds similar to the known aggregators, 1.14% of which were predicted as aggregators. SVM showed slightly better overall performance against two other machine learning methods based on five fold cross‐validation studies of the same settings. Molecular features of aggregation, extracted by a feature selection method, are consistent with published profiles. SVM showed substantial capability in identifying aggregators from large libraries at low false‐hit rates. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2010     

Fast and accurate predictions of binding free energies using MM‐PBSA and MM‐GBSA

In the drug discovery process, accurate methods of computing the affinity of small molecules with a biological target are strongly needed. This is particularly true for molecular docking and virtual screening methods, which use approximated scoring functions and struggle in estimating binding energies in correlation with experimental values. Among the various methods, MM‐PBSA and MM‐GBSA are emerging as useful and effective approaches. Although these methods are typically applied to large collections of equilibrated structures of protein‐ligand complexes sampled during molecular dynamics in water, the possibility to reliably estimate ligand affinity using a single energy‐minimized structure and implicit solvation models has not been explored in sufficient detail. Herein, we thoroughly investigate this hypothesis by comparing different methods for the generation of protein‐ligand complexes and diverse methods for free energy prediction for their ability to correlate with experimental values. The methods were tested on a series of structurally diverse inhibitors of Plasmodium falciparum DHFR with known binding mode and measured affinities. The results showed that correlations between MM‐PBSA or MM‐GBSA binding free energies with experimental affinities were in most cases excellent. Importantly, we found that correlations obtained with the use of a single protein‐ligand minimized structure and with implicit solvation models were similar to those obtained after averaging over multiple MD snapshots with explicit water molecules, with consequent save of computing time without loss of accuracy. When applied to a virtual screening experiment, such an approach proved to discriminate between true binders and decoy molecules and yielded significantly better enrichment curves. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

In silico prediction and screening of γ‐secretase inhibitors by molecular descriptors and machine learning methods

γ‐Secretase inhibitors have been explored for the prevention and treatment of Alzheimer's disease (AD). Methods for prediction and screening of γ‐secretase inhibitors are highly desired for facilitating the design of novel therapeutic agents against AD, especially when incomplete knowledge about the mechanism and three‐dimensional structure of γ‐secretase. We explored two machine learning methods, support vector machine (SVM) and random forest (RF), to develop models for predicting γ‐secretase inhibitors of diverse structures. Quantitative analysis of the receiver operating characteristic (ROC) curve was performed to further examine and optimize the models. Especially, the Youden index (YI) was initially introduced into the ROC curve of RF so as to obtain an optimal threshold of probability for prediction. The developed models were validated by an external testing set with the prediction accuracies of SVM and RF 96.48 and 98.83% for γ‐secretase inhibitors and 98.18 and 99.27% for noninhibitors, respectively. The different feature selection methods were used to extract the physicochemical features most relevant to γ‐secretase inhibition. To the best of our knowledge, the RF model developed in this work is the first model with a broad applicability domain, based on which the virtual screening of γ‐secretase inhibitors against the ZINC database was performed, resulting in 368 potential hit candidates. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Using fractal to solve the multiple minima problem in molecular mechanics calculation

This article presents an approach using fractal to solve the multiple minima problem. We use the Newton–Raphson method of the MM3 molecular mechanics program to scan the conformational spaces of a model molecule and a real molecule. The results show each energy minimum, maximum point, and saddle point has a basin of initial points converging to it in conformational spaces. Points converging to different extrema are mixed, and form fractal structures around basin boundaries. Singular points seem to involve in the formation of fractal. When searching within a small region of fractal basin boundaries, the self‐similarity of fractal makes it possible to find all energy minima, maxima, and saddle points from which global minimum may be extracted. Compared with other methods, this approach is efficient, accurate, conceptually simple, and easy to implement. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 1101–1108, 2000     

GridMAT‐MD: A grid‐based membrane analysis tool for use with molecular dynamics

GridMAT‐MD is a new program developed to aid in the analysis of lipid bilayers from molecular dynamics simulations. It reads a GROMACS coordinate file and generates two types of data: a two‐dimensional contour plot depicting membrane thickness, and a polygon‐based tessellation of the individual lipid headgroups. GridMAT‐MD can also account for proteins or small molecules within the headgroups of the lipids, closely approximating their occupied lateral area. The program requires no installation, is fast, and is freely available. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009     

A generalized higher order kernel energy approximation method

We present a general mathematical model that can be used to improve almost all fragment‐based methods for ab initio calculation of total molecular energy. Fragment‐based methods of computing total molecular energy mathematically decompose a molecule into smaller fragments, quantum‐mechanically compute the energies of single and multiple fragments, and then combine the computed fragment energies in some particular way to compute the total molecular energy. Because the kernel energy method (KEM) is a fragment‐based method that has been used with much success on many biological molecules, our model is presented in the context of the KEM in particular. In this generalized model, the total energy is not based on sums of all possible double‐, triple‐, and quadruple‐kernel interactions, but on the interactions of precisely those combinations of kernels that are connected in the mathematical graph that represents the fragmented molecule. This makes it possible to estimate total molecular energy with high accuracy and no superfluous computation and greatly extends the utility of the KEM and other fragment‐based methods. We demonstrate the practicality and effectiveness of our model by presenting how it has been used on the yeast initiator tRNA molecule, ytRN (1YFG in the Protein Data Bank), with kernel computations using the Hartree‐Fock equations with a limited basis of Gaussian STO‐3G type. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010