Noriaki Okimoto

High-performance drug discovery: computational screening by combining docking and molecular dynamics simulations.

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins.

FGF9 monomer-dimer equilibrium regulates extracellular matrix affinity and tissue diffusion

The spontaneous dominant mouse mutant, Elbow knee synostosis (Eks), shows elbow and knee joint synosotsis, and premature fusion of cranial sutures. Here we identify a missense mutation in the Fgf9 gene that is responsible for the Eks mutation. Through investigation of the pathogenic mechanisms of joint and suture synostosis in Eks mice, we identify a key molecular mechanism that regulates FGF9 signaling in developing tissues. We show that the Eks mutation prevents homodimerization of the FGF9 protein and that monomeric FGF9 binds to heparin with a lower affinity than dimeric FGF9. These biochemical defects result in increased diffusion of the altered FGF9 protein (FGF9Eks) through developing tissues, leading to ectopic FGF9 signaling and repression of joint and suture development. We propose a mechanism in which the range of FGF9 signaling in developing tissues is limited by its ability to homodimerize and its affinity for extracellular matrix heparan sulfate proteoglycans.

Theoretical Studies of the ATP Hydrolysis Mechanism of Myosin

The ATP hydrolysis mechanism of myosin was studied using quantum chemical (QM) and molecular dynamics calculations. The initial model compound for QM calculations was constructed on the basis of the energy-minimized structure of the myosin(S1dc)-ATP complex, which was determined by molecular mechanics calculations. The result of QM calculations suggested that the ATP hydrolysis mechanism of myosin consists of a single elementary reaction in which a water molecule nucleophilically attacked gamma-phosphorus of ATP. In addition, we performed molecular dynamics simulations of the initial and final states of the ATP hydrolysis reaction, that is, the myosin-ATP and myosin-ADP.Pi complexes. These calculations revealed roles of several amino acid residues (Lys185, Thr186, Ser237, Arg238, and Glu459) in the ATPase pocket. Lys185 maintains the conformation of beta- and gamma-phosphate groups of ATP by forming the hydrogen bonds. Thr186 and Ser237 are coordinated to a Mg(2+) ion, which interacts with the phosphates of ATP and therefore contributes to the stabilization of the ATP structure. Arg238 and Glu459, which consisted of the gate of the ATPase pocket, retain the water molecule acting on the hydrolysis at the appropriate position for initiating the hydrolysis.

Molecular Mechanisms of How Mercury Inhibits Water Permeation through Aquaporin-1: Understanding by Molecular Dynamics Simulation

Aquaporin (AQP) functions as a water-conducting pore. Mercury inhibits the water permeation through AQP. Although site-directed mutagenesis has shown that mercury binds to Cys189 during the inhibition process, it is not fully understood how this inhibits the water permeation through AQP1. We carried out 40 ns molecular dynamics simulations of bovine AQP1 tetramer with mercury (Hg-AQP1) or without mercury (Free AQP1). In Hg-AQP1, Cys191 (Cys189 in human AQP1) is converted to Cys-SHg+ in each monomer. During each last 10 ns, we observed water permeation events occurred 23 times in Free AQP1 and never in Hg-AQP1. Mercury binding did not influence the whole structure, but did induce a collapse in the orientation of several residues at the ar/R region. In Free AQP1, backbone oxygen atoms of Gly190, Cys191, and Gly192 lined, and were oriented to, the surface of the water pore channel. In Hg-AQP1, however, the SHg+ of Cys191-SHg+ was oriented toward the outside of the water pore. As a result, the backbone oxygen atoms of Gly190, Cys191, and Gly192 became disorganized and the ar/R region collapsed, thereby obstructing the permeation of water. We suggest that mercury disrupts the water pore of AQP1 through local conformational changes in the ar/R region.

Novel Mechanism of Interaction of p85 Subunit of Phosphatidylinositol 3-Kinase and ErbB3 Receptor-derived Phosphotyrosyl Peptides

Ligand-activated and tyrosine-phosphorylated ErbB3 receptor binds to the SH2 domain of the p85 subunit of phosphatidylinositol 3-kinase and initiates intracellular signaling. Here, we studied the interactions between the N- (N-SH2) and C- (C-SH2) terminal SH2 domains of the p85 subunit of the phosphatidylinositol 3-kinase and eight ErbB3 receptor-derived phosphotyrosyl peptides (P-peptides) by using molecular dynamics, free energy, and surface plasmon resonance (SPR) analyses. In SPR analysis, these P-peptides showed no binding to the C-SH2 domain, but P-peptides containing a phospho-YXXM or a non-phospho-YXXM motif did bind to the N-SH2 domain. The N-SH2 domain has two phosphotyrosine binding sites in its N- (N1) and C- (N2) terminal regions. Interestingly, we found that P-peptides of pY1180 and pY1241 favored to bind to the N2 site, although all other P-peptides showed favorable binding to the N1 site. Remarkably, two phosphotyrosines, pY1178 and pY1243, which are just 63 amino acids apart from the pY1241 and pY1180, respectively, showed favorable binding to the N1 site. These findings indicate a possibility that the pair of phosphotyrosines, pY1178-pY1241 or pY1243-pY1180, will fold into an appropriate configuration for binding to the N1 and N2 sites simultaneously. Our model structures of the cytoplasmic C-terminal domain of ErbB3 receptor also strongly supported the speculation. The calculated binding free energies between the N-SH2 domain and P-peptides showed excellent qualitative agreement with SPR data with a correlation coefficient of 0.91. The total electrostatic solvation energy between the N-SH2 domain and P-peptide was the dominant factor for its binding affinity.

Free-energy landscapes of protein domain movements upon ligand binding.

The conformation and functions of proteins are closely linked, and many proteins undergo conformational changes upon ligand binding. The X-ray crystallographic studies have revealed conformational differences in proteins between the liganded and unliganded states. Currently, the conformational transitions that originate in the ligand binding are explained on the basis of two representative models, the induced-fit and preexisting equilibrium dynamics models. However, the actual dynamics of the proteins remain ambiguous. Though these two models are the extreme ones, it is important to understand the difference between these two, particularly in structural biology and medicinal chemistry studies. Here, we clarified the difference in the mechanisms responsible for the conformational changes induced in two proteins upon ligand binding by examining computationally determined free-energy profiles of the apo- and holoproteins. The lysine/arginine/ornithine-binding protein and maltose/maltodextrin-binding protein were chosen as the target proteins, and the energy profiles were generated by a molecular simulation approach. Our results revealed that fluctuations in the apo state and protein-ligand interactions both play important roles in conformational transition, and the mechanism is highly influenced by the fluctuations in the apo state, which are unique to a particular structure.

Computational Studies on Prion Proteins: Effect of Ala117→Val Mutation

Molecular dynamics calculations demonstrated the conformational change in the prion protein due to Ala(117)-->Val mutation, which is related to Gerstmann-Sträussler-Sheinker disease, one of the familial prion diseases. Three kinds of model structures of human and mouse prion proteins were examined: (model 1) nuclear magnetic resonance structures of human prion protein HuPrP (125-228) and mouse prion protein MoPrP (124-224), each having a globular domain consisting of three alpha-helices and an antiparallel beta-sheet; (model 2) extra peptides including Ala(117) (109-124 in HuPrP and 109-123 in MoPrP) plus the nuclear magnetic resonance structures of model 1; and (model 3) extra peptides including Val(117) (109-124 in HuPrP and 109-123 in MoPrP) plus the nuclear magnetic resonance structures of model 1. The results of molecular dynamics calculations indicated that the globular domains of models 1 and 2 were stable and that the extra peptide in model 2 tended to form a new alpha-helix. On the other hand, the globular domain of model 3 was unstable, and the beta-sheet region increased especially in HuPrP.

An Efficient Computational Method for Calculating Ligand Binding Affinities

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, the docking scores are not sufficiently precise to represent the protein-ligand binding affinity. Here, we developed an efficient computational method for calculating protein-ligand binding affinity, which is based on molecular mechanics generalized Born/surface area (MM-GBSA) calculations and Jarzynski identity. Jarzynski identity is an exact relation between free energy differences and the work done through non-equilibrium process, and MM-GBSA is a semimacroscopic approach to calculate the potential energy. To calculate the work distribution when a ligand is pulled out of its binding site, multiple protein-ligand conformations are randomly generated as an alternative to performing an explicit single-molecule pulling simulation. We assessed the new method, multiple random conformation/MM-GBSA (MRC-MMGBSA), by evaluating ligand-binding affinities (scores) for four target proteins, and comparing these scores with experimental data. The calculated scores were qualitatively in good agreement with the experimental binding affinities, and the optimal docking structure could be determined by ranking the scores of the multiple docking poses obtained by the molecular docking process. Furthermore, the scores showed a strong linear response to experimental binding free energies, so that the free energy difference of the ligand binding (ΔΔG) could be calculated by linear scaling of the scores. The error of calculated ΔΔG was within ≈±1.5 kcal•mol−1 of the experimental values. Particularly, in the case of flexible target proteins, the MRC-MMGBSA scores were more effective in ranking ligands than those generated by the MM-GBSA method using a single protein-ligand conformation. The results suggest that, owing to its lower computational costs and greater accuracy, the MRC-MMGBSA offers efficient means to rank the ligands, in the post-docking process, according to their binding affinities, and to compare these directly with the experimental values.

A leukotriene C4 synthase inhibitor with the backbone of 5-(5-methylene-4-oxo-4,5-dihydrothiazol-2-ylamino) isophthalic acid

The cysteinyl leukotrienes (cys-LTs), leukotriene C4 (LTC4) and its metabolites, LTD4 and LTE4, are proinflammatory lipid mediators in asthma and other inflammatory diseases. They are generated through the 5-lipoxygenase/LTC4 synthase (LTC4S) pathway and act via at least two distinct G protein-coupled receptors. The inhibition of human LTC4S will make a simple way to treat the cys-LT relevant inflammatory diseases. Here, we show that compounds having 5-(5-methylene-4-oxo-4,5-dihydrothiazol-2-ylamino) isophthalic acid moiety suppress LTC4 synthesis, glutathione conjugation to the precursor LTA4, in both an enzyme assay and a whole-cell assay. Hierarchical in silico screenings of 6 million compounds provided 300,000 dataset for docking, and after energy minimization based on the crystal structure of LTC4S, 111 compounds were selected as candidates for a competitive inhibitor to glutathione. One of those compounds showed significant inhibitory activity, and subsequently, its derivative 5-((Z)-5-((E)-2-methyl-3-phenylallylidene)-4-oxo-4,5-dihydrothiazol-2-ylamino) isophthalic acid (compound 1) was found to be the most potent inhibitor. The enzyme assay showed the IC50 was 1.9 µM and the corresponding 95% confidence interval was from 1.7 to 2.2 µM. The whole-cell assay showed that compound 1 was cell permeable and inhibited LTC4 synthesis in a concentration dependent manner.

Prediction of the Structure of Complexes Comprised of Proteins and Glycosaminoglycans Using Docking Simulation and Cluster Analysis.

A typical docking simulation provides information on the structure of ligand-receptor complexes and their binding affinity in terms of a docking energy. We have developed a potent method combining a docking simulation with cluster analysis to extract adequate docking structures from the many possible output structures of the simulation. First, we tried to predict the structure of basic fibroblast growth factor (bFGF) bound to heparin, using the docking simulation program AutoDock 3.0. Two X-ray crystal structures had already been obtained for bFGF. One was a complex of the protein and heparin, a kind of glycosaminoglycan, and the other, only the protein itself, hereafter called a simplex. We docked a heparin molecule onto the protein simplex and generated many trial structures for the bFGF-heparin complex. The structures of those docked complexes were optimized through energy minimization by AMBER8. Although neither the docking energy calculated by AMBER8 nor that calculated by AutoDock 3.0 could be used satisfactorily by themselves to select a proper heparin-binding complex from the output structures, the majority of the structures generated by AutoDock 3.0 were fairly close to each other in atom geometry, and the averaged geometry over these structures was also close to that of the crystal. Hence, we utilized only the atom geometry for evaluation and carried out cluster analysis with the collection of geometries. This procedure enabled selection of a structure considerably close to the crystals. We applied this approach to two other heparin-binding proteins:  antithrombin and annexin V. Two crystal structures, a complex and a simplex, had been elucidated for these proteins as well as for bFGF. Our trials gave an exact prediction of the heparin-binding structures of these proteins, showing the approach in this study is effective in studying the docking of ligands that have a variety of docking conformations due to the presence of multiple rotatable bonds and charged chemical groups.