Biomedical subjects

Yoshifumi Fukunishi

Publications and source records attributed to Yoshifumi Fukunishi.

16 recordsLinked to original sources

PubMed2006

A virtual active compound produced from the negative image of a ligand-binding pocket, and its application to in-silico drug screening.

We developed a new structure-based in-silico screening method using a negative image of a ligand-binding pocket and a multi-protein-compound interaction matrix. Based on the structure of the ligand pocket of the target protein, we designed a negative image, which consists of virtual atoms whose radii are close to those of carbon atoms. The virtual atoms fit the pocket ideally and achieve an optimal Coulomb interaction. A protein-compound docking program calculates the protein-compound interaction matrix for many proteins and many compounds including the negative image, which can be treated as a virtual compound. With specific attention to a vector of docking scores for a single compound with many proteins, we selected a compound whose score vector was similar to that of the negative image as a candidate hit compound. This method was applied to representative target proteins and showed high database enrichment with a relatively quick procedure.

Binding Sites↗

PubMed2006

Finding ligands for G protein-coupled receptors based on the protein-compound affinity matrix.

We developed a novel method of identifying new active ligands based on information related to known active compounds using protein-compound docking simulations, even when the tertiary structure of the actual target receptor protein is unknown. This method was used to find ligands of G protein-coupled receptors (GPCRs), i.e., agonists and antagonists of histamine, adrenaline, serotonin and dopamine receptors. The principal component analysis (PCA) method was applied to the protein-compound affinity matrix, which was given by thorough docking calculations between sets of many protein pockets and chemical compounds. The set of protein pockets did not necessary include the target protein. Each compound was depicted as a point in the PCA space. Compounds in a sphere, whose center was set to the known active compound in the multi-dimensional PCA space or to the average position of several known active compounds, were selected as candidate-hit compounds. Our method was found to be effective for finding the ligands of GPCRs based on known native ligands, even when only the soluble protein structures were used in the docking simulations.

Binding Sites↗

PubMed2006

Classification of chemical compounds by protein-compound docking for use in designing a focused library.

We developed a new method for the classification of chemical compounds and protein pockets and applied it to a random screening experiment for macrophage migration inhibitory factor (MIF). The principal component analysis (PCA) method was applied to the protein-compound interaction matrix, which was given by thorough docking calculations between a set of many protein pockets and chemical compounds. Each compound and protein pocket was depicted as a point in the PCA spaces of compounds and proteins, respectively. This method was applied to distinguish active compounds from negative compounds of MIF. A random screening experiment for MIF was performed, and our method revealed that the active compounds were localized in the PCA space of compounds, while the negative compounds showed a wide distribution. Furthermore, protein pockets, which bind similar compounds, were classified and were found to form a cluster in the PCA space.

Binding Sites↗

PubMed2006

Utilization of methyl proton resonances in cross-saturation measurement for determining the interfaces of large protein-protein complexes.

Cross-saturation experiments allow the identification of the contact residues of large protein complexes (MW>50 K) more rigorously than conventional NMR approaches which involve chemical shift perturbations and hydrogen-deuterium exchange experiments [Takahashi et al. (2000) Nat. Struct. Biol., 7, 220-223]. In the amide proton-based cross-saturation experiment, the combined use of high deuteration levels for non-exchangeable protons of the ligand protein and a solvent with a low concentration of (1)H(2)O greatly enhanced the selectivity of the intermolecular cross-saturation phenomenon. Unfortunately, experimental limitations caused losses in sensitivity. Furthermore, since main chain amide protons are not generally exposed to solvent, the efficiency of the saturation transfer directed to the main chain amide protons is not very high. Here we propose an alternative cross-saturation experiment which utilizes the methyl protons of the side chains of the ligand protein. Owing to the fast internal rotation along the methyl axis, we theoretically and experimentally demonstrated the enhanced efficiency of this approach. The methyl-utilizing cross-saturation experiment has clear advantages in sensitivity and saturation transfer efficiency over the amide proton-based approach.

Computer Simulation↗

PubMed2005

Multiple target screening method for robust and accurate in silico ligand screening.

We developed a new in silico multiple target screening (MTS) method, based on a multi-receptor versus multi-ligand docking affinity matrixes, and examined its robustness against changes in the scoring system. According to this method, compounds in a database are docked to multiple proteins. The compounds among these proteins that are likely bind to the target protein are selected as the members of the candidate-hit compound group. Then, the compounds in the group are sorted into descending order using the docking score: the first (n-th) compound is expected to be the most (n-th) probable hit compound. This method was applied to the analysis of a set of 142 receptors and 142 compounds using a receptor-ligand docking program, Sievgene [Y. Fukunishi, Y. Mikami, H. Nakamura, Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening, J. Mol. Graphics Modelling, 24 (2005) 34-45], and the results demonstrated that this method achieves a high hit ratio compared to uniform sampling. We prepared two new scores: the DeltaG score, designed to reproduce the protein-ligand binding free energy, and the hit-optimized score, designed to maximize the hit ratio of in silico screening. Using the Sievgene docking score, DeltaG score and hit-optimized score, the MTS method is more robust than the multiple active-site correction scoring method [G.P.A. Vigers, J.P. Rizzi, Multiple active site corrections for docking and virtual screening, J. Med. Chem., 47 (2004) 80-89].

Databases, Factual↗

PubMed2005

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

Bacterial Proteins↗

PubMed2004

Multicanonical molecular dynamics algorithm employing an adaptive force-biased iteration scheme.

We present one effective multicanonical molecular dynamics (MCMD) algorithm accelerating the convergence of rough energy landscapes simulations via an adaptive force-biased iteration scheme. Our method utilizes several short MCMD simulations with dynamically updated weights and combines them to estimate the density of states via multiple histogram technique. The key step of our algorithm is the adaptive refinement for the derivative of multicanonical weight, which allows the system to enlarge the sampling energy range maintaining the statistical accuracy. The performance of our method has been validated for atomic Lennard-Jones clusters.

Journal Article↗

PubMed2004

Generalized simulated tempering realized on expanded ensembles of non-Boltzmann weights.

A generalized version of the simulated tempering operated in the expanded ensembles of non-Boltzmann weights has been proposed to mitigate a quasiergodicity problem occurring in simulations of rough energy landscapes. In contrast to conventional simulated tempering employing the Boltzmann weight, our method utilizes a parametrized, generalized distribution as a workhorse for stochastic exchanges of configurations and subensembles transitions, which allows a considerable enhancement for the rate of convergence of Monte Carlo and molecular dynamics simulations using delocalized weights. A feature of our method is that the exploration of the parameter space encouraging subensembles transitions is greatly accelerated using the dynamic update scheme for the weight via the average guide specific to the energy distribution. The performance and characteristic feature of our method have been validated in the liquid-solid transition of Lennard-Jones clusters and the conformational sampling of alanine dipeptide by taking two types of Tsallis [C. Tsallis, J. Stat. Phys. 52, 479 (1988)] expanded ensembles associated with different parametrization schemes.

Computer Simulation↗

PubMed2004

Dynamical origin of enhanced conformational searches of Tsallis statistics sampling.

The characteristic sampling dynamics of importance samplings driven by the Tsallis weight [C. Tsallis, J. Stat. Phys. 52, 479 (1988)] has been analyzed in terms of recently developed Langevin stochastic model by considering the effects of the density of states and the potential smoothing of the Tsallis transformation. Our study reveals that the fixed points, which are determined by the crossing points of the statistical temperature and the Tsallis effective temperature, play a critical role in overall dynamics of the Tsallis statistics sampling. The dynamical origin of enhanced conformational searches of the Tsallis weight has been investigated by unveiling the intimate relationship between the sampling dynamics and the stability change of corresponding fixed points. Based on this stochastic analysis, we propose one effective method to realize a broad energy distribution in the Tsallis statistics sampling by determining optimal Tsallis parameters systematically based on preliminary canonical samplings. The effectiveness of our method has been validated in the folding simulation of Met-Enkephalin and liquid-solid transition simulation of Lennard-Jones cluster systems.

Algorithms↗

PubMed2004

Stochastic formulation of sampling dynamics in generalized ensemble methods.

The fundamental relations of the sampling process in the multicanonical ensemble and simulated tempering have been studied in the expanded ensembles formalism. The simulated tempering is identified as the multicanonical sampling with the generalized weight determined by a Laplace transform of the temperature weight. The characteristic dynamics of both sampling methods has been verified in the stochastic formulation of the sampling process. Our study gives a necessary and sufficient condition for the weights to realize a uniform sampling in the energy and temperature spaces. Based on the stochastic model, robust force biased iteration schemes have been proposed to allow automatic determinations of uniform sampling weights.

Journal Article↗

PubMed2004

A hybrid method of molecular dynamics and harmonic dynamics for docking of flexible ligand to flexible receptor.

We have developed a new docking method to consider receptor flexibility, a hybrid method of molecular dynamics and harmonic dynamics. The global motions of the whole receptor were approximately introduced into those of the receptor in the docking simulation as harmonic dynamics. On the other hand, the local flexibility of the side chains was also considered by conventional molecular dynamics. We confirmed that this new method can reproduce the fluctuations of the whole receptor by making a comparison of the directions and amplitudes of the global fluctuations. Then this method was applied to the docking of HIV-1 protease and its ligand. As a result, we observed a docking process where the ligand enters into the binding pocket well, which implies that this method is effective enough to reproduce a molecular complex formation.

Algorithms↗

PubMed2004

Modelling of third cytoplasmic loop of bovine rhodopsin by multicanonical molecular dynamics.

The third cytoplasmic loop (C3) of bovine rhodopsin (Rh) is an important site for its interaction with G-protein transducin. The tertiary structure of Rh was determined by X-ray crystallography, although the local conformation around the C3 loop (residues: 236-240) was not visible in electron density maps. We constructed a canonical conformation ensemble at 310 K for the C3 loop (residues: 227-244) using a multicanonical molecular dynamics simulation, and predicted several putative conformations. The conformation ensemble was classified by principal component analysis into several distinct structural clusters, some of which could provide the putative structural models of Rh and the activated state of Rh.

Amino Acid Sequence↗

PubMed2003

Determination of multicanonical weight based on a stochastic model of sampling dynamics.

Based on the stochastic interpretation of the sampling process modeled by a Langevin equation, we present an effective iteration scheme to determine the weight in multicanonical molecular dynamics. Our method enables an automatic determination of the weight producing a uniform energy sampling via an iterative cancellation of the deterministic force in a Langevin equation. The deterministic force has been calculated from the energy trajectory by identifying the moments of the transition probability of a Fokker-Planck equation associated with a Langevin equation. The intimate relationship between the sampling process and the stochastic dynamics has been verified by applying the iteration scheme to a helix-coil transition of the 8-polyalanine system in a gas phase.

Journal Article↗

PubMed2003

Dynamical origin of uniform sampling in multicanonical ensemble.

The stochastic model describing the sampling process in multicanonical ensemble has been derived by considering the sampling process as an overdamped Brownian motion on the free energy surface. The essential dynamics of the multicanonical sampling has been characterized by a Langevin equation in a piecewise multivalleyed free energy landscape, modulated by a temperature-dependent curvature. Based on the stochastic model we showed that the multicanonical weight can be determined by interpolating maximum probability energy points of the canonical samplings at different temperatures.

Journal Article↗

PubMedDate not supplied

Noise reduction method for molecular interaction energy: application to in silico drug screening and in silico target protein screening.

We developed a new method to improve the accuracy of molecular interaction data using a molecular interaction matrix. This method was applied to enhance the database enrichment of in silico drug screening and in silico target protein screening using a protein-compound affinity matrix calculated by a protein-compound docking software. Our assumption was that the protein-compound binding free energy of a compound could be improved by a linear combination of its docking scores with many different proteins. We proposed two approaches to determine the coefficients of the linear combination. The first approach is based on similarity among the proteins, and the second is a machine-learning approach based on the known active compounds. These methods were applied to in silico screening of the active compounds of several target proteins and in silico target protein screening.

Pharmaceutical Preparations↗

PubMedDate not supplied

An efficient in silico screening method based on the protein-compound affinity matrix and its application to the design of a focused library for cytochrome P450 (CYP) ligands.

A new method has been developed to design a focused library based on available active compounds using protein-compound docking simulations. This method was applied to the design of a focused library for cytochrome P450 (CYP) ligands, not only to distinguish CYP ligands from other compounds but also to identify the putative ligands for a particular CYP. Principal component analysis (PCA) was applied to the protein-compound affinity matrix, which was obtained by thorough docking calculations between a large set of protein pockets and chemical compounds. Each compound was depicted as a point in the PCA space. Compounds that were close to the known active compounds were selected as candidate hit compounds. A machine-learning technique optimized the docking scores of the protein-compound affinity matrix to maximize the database enrichment of the known active compounds, providing an optimized focused library.

Artificial Intelligence↗