Masakazu Sekijima

Molecular Dynamics Simulation of Dimeric and Monomeric Forms of Human Prion Protein: Insight into Dynamics and Properties

A central theme in prion protein research is the detection of the process that underlies the conformational transition from the normal cellular prion form (PrP(C)) to its pathogenic isoform (PrP(Sc)). Although the three-dimensional structures of monomeric and dimeric human prion protein (HuPrP) have been revealed by NMR spectroscopy and x-ray crystallography, the process underlying the conformational change from PrP(C) to PrP(Sc) and the dynamics and functions of PrP(C) remain unknown. The dimeric form is thought to play an important role in the conformational transition. In this study, we performed molecular dynamics (MD) simulations on monomeric and dimeric HuPrP at 300 K and 500 K for 10 ns to investigate the differences in the properties of the monomer and the dimer from the perspective of dynamic and structural behaviors. Simulations were also undertaken with Asp178Asn and acidic pH, which is known as a disease-associated factor. Our results indicate that the dynamics of the dimer and monomer were similar (e.g., denaturation of helices and elongation of the beta-sheet). However, additional secondary structure elements formed in the dimer might result in showing the differences in dynamics and properties between the monomer and dimer (e.g., the greater retention of dimeric than monomeric tertiary structure).

Structural modeling of mutant α-glucosidases resulting in a processing/transport defect in Pompe disease

To elucidate the mechanism underlying transport and processing defects from the viewpoint of enzyme folding, we constructed three-dimensional models of human acid α-glucosidase encompassing 27 relevant amino acid substitutions by means of homology modeling. Then, we determined in each separate case the number of affected atoms, the root-mean-square distance value and the solvent-accessible surface area value. The analysis revealed that the amino acid substitutions causing a processing or transport defect responsible for Pompe disease were widely spread over all of the five domains comprising the acid α-glucosidase. They were distributed from the core to the surface of the enzyme molecule, and the predicted structural changes varied from large to very small. Among the structural changes, we paid particular attention to G377R and G483R. These two substitutions are predicted to cause electrostatic changes in neighboring small regions on the molecular surface. The quality control system of the endoplasmic reticulum apparently detects these very small structural changes and degrades the mutant enzyme precursor (G377R), but also the cellular sorting system might be misled by these minor changes whereby the precursor is secreted instead of being transported to lysosomes (G483R).

Molecular Mechanisms Underlying Oseltamivir Resistance Mediated by an I117V Substitution in the Neuraminidase of Subtype H5N1 Avian Influenza A Viruses

BACKGROUND The neuraminidase (NA) inhibitor oseltamivir is widely used to treat patients infected with influenza viruses. An Ile-to-Val change at position 117 in influenza A virus subtype H5N1 NA (NA-I117V) confers a reduction in susceptibility to oseltamivir carboxylate. However, the in vivo relevance and molecular basis of the decreased sensitivity mediated by this mutation are poorly understood. METHODS We created single-point-mutant viruses with 3 genetically different backgrounds (ie, 1 belonging to clade 1 and 2 belonging to clade 2.3.4) and evaluated the effects of the I117V mutation on oseltamivir susceptibility in vitro, in vivo, and in silico. RESULTS The NA-I117V mutation conferred a slight reduction in susceptibility to oseltamivir in vitro (1.3- to 6.3-fold changes), although it did not substantially compromise NA enzymatic activity. Mice infected with I117V virus exhibited reduced susceptibility to oseltamivir and decreased survival in 2 of 3 virus pairs tested. Molecular dynamics simulations revealed that I117V caused the loss of hydrogen bonds between an arginine at position 118 and the carboxyl group of oseltamivir, leading to a lower binding affinity for oseltamivir. CONCLUSIONS Our findings provide new insight into the mechanism of NA-I117V-mediated oseltamivir resistance in highly pathogenic H5N1 avian influenza viruses.

Pharmacophore Modeling for Anti-Chagas Drug Design Using the Fragment Molecular Orbital Method

Background Chagas disease, caused by the parasite Trypanosoma cruzi, is a neglected tropical disease that causes severe human health problems. To develop a new chemotherapeutic agent for the treatment of Chagas disease, we predicted a pharmacophore model for T. cruzi dihydroorotate dehydrogenase (TcDHODH) by fragment molecular orbital (FMO) calculation for orotate, oxonate, and 43 orotate derivatives. Methodology/Principal Findings Intermolecular interactions in the complexes of TcDHODH with orotate, oxonate, and 43 orotate derivatives were analyzed by FMO calculation at the MP2/6-31G level. The results indicated that the orotate moiety, which is the base fragment of these compounds, interacts with the Lys43, Asn67, and Asn194 residues of TcDHODH and the cofactor flavin mononucleotide (FMN), whereas functional groups introduced at the orotate 5-position strongly interact with the Lys214 residue. Conclusions/Significance FMO-based interaction energy analyses revealed a pharmacophore model for TcDHODH inhibitor. Hydrogen bond acceptor pharmacophores correspond to Lys43 and Lys214, hydrogen bond donor and acceptor pharmacophores correspond to Asn67 and Asn194, and the aromatic ring pharmacophore corresponds to FMN, which shows important characteristics of compounds that inhibit TcDHODH. In addition, the Lys214 residue is not conserved between TcDHODH and human DHODH. Our analysis suggests that these orotate derivatives should preferentially bind to TcDHODH, increasing their selectivity. Our results obtained by pharmacophore modeling provides insight into the structural requirements for the design of TcDHODH inhibitors and their development as new anti-Chagas drugs.

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target.

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

Structure based approach for understanding organism specific recognition of protein-RNA complexes

BackgroundProtein-RNA interactions perform diverse functions within the cell. Understanding the recognition mechanism of protein-RNA complexes has been a challenging task in molecular and computational biology. In earlier works, the recognition mechanisms have been studied for a specific complex or using a set of non–redundant complexes. In this work, we have constructed 18 sets of same protein-RNA complexes belonging to different organisms from Protein Data Bank (PDB). The similarities and differences in each set of complexes have been revealed in terms of various sequence and structure based features such as root mean square deviation, sequence homology, propensity of binding site residues, variance, conservation at binding sites, binding segments, binding motifs of amino acid residues and nucleotides, preferred amino acid-nucleotide pairs and influence of neighboring residues for binding.ResultsWe found that the proteins of mesophilic organisms have more number of binding sites than thermophiles and the binding propensities of amino acid residues are distinct in E. coli, H. sapiens, S. cerevisiae, thermophiles and archaea. Proteins prefer to bind with RNA using a single residue segment in all the organisms while RNA prefers to use a stretch of up to six nucleotides for binding with proteins. We have developed amino acid residue-nucleotide pair potentials for different organisms, which could be used for predicting the binding specificity. Further, molecular dynamics simulation studies on aspartyl tRNA synthetase complexed with aspartyl tRNA showed specific modes of recognition in E. coli, T. thermophilus and S. cerevisiae.ConclusionBased on structural analysis and molecular dynamics simulations we suggest that the mode of recognition depends on the type of the organism in a protein-RNA complex.ReviewersThis article was reviewed by Sandor Pongor, Gajendra Raghava and Narayanaswamy Srinivasan.

Database of the clinical phenotypes, genotypes and mutant arylsulfatase B structures in mucopolysaccharidosis type VI

Mucopolysaccharidosis type VI (MPS VI) is a genetic disorder caused by a deficiency of arylsulfatase B (ARSB). In our previous study, we investigated the structural changes in ARSB caused by amino acid substitutions associated with MPS VI, and revealed that such structural changes in ARSB were correlated with the clinical phenotypes. To the best of our knowledge, there is no database containing the structures of mutant ARSBs. Here, we built a database of clinical phenotypes, genotypes and structures of mutant ARSBs (http://mps6-database.org). This database can be accessed via the Internet, and is user friendly being equipped with powerful computational tools. This database will be useful for a better understanding of MPS VI.

An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes

We propose a new iterative screening contest method to identify target protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-protein kinase Yes as an example target protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.

Identification of type I and type II inhibitors of c-Yes kinase using in silico and experimental techniques

c-Yes kinase is considered as one of the attractive targets for anti-cancer drug design. The DFG (Asp-Phe-Gly) motif present in most of the kinases will adopt active and inactive conformations, known as DFG-in and DFG-out and their inhibitors are classified into type I and type II, respectively. In the present study, two screening protocols were followed for identification of c-Yes kinase inhibitors. (i) Structure-based virtual screening (SBVS) and (ii) Structure-based (SB) and Pharmacophore-based (PB) tandem screening. In SBVS, the c-Yes kinase structure was obtained from homology modeling and seven ensembles with different active site scaffolds through molecular dynamics (MD) simulations. For SB-PB tandem screening, we modeled ligand bound active and inactive conformations. Physicochemical properties of inhibitors of Src kinase family and c-Yes kinase were used to prepare target focused libraries for screenings. Our screening procedure along with docking showed 520 probable hits in SBVS and tandem screening (120 and 400, respectively). Out of 5000 compounds identified from different computational methods, 2410 were examined using kinase inhibition assays. It includes 266 compounds (5.32%) identified from our method. We observed that 14 compounds (12%) are identified by the present method out of 168 that showed > 30% inhibition. Among them, three compounds are novel, unique, and showed good inhibition. Further, we have studied the binding of these compounds at the DFG-in and DFG-out conformations and reported the probable class (type I or type II). Hence, we suggest that these compounds could be novel drug leads for regulation of colorectal cancer.

The Power Efficiency of GPUs in Multi Nodes Environment with Molecular Dynamics

Energy efficient systems are highly demanded as the power consumption in HPC region increase. The use of GPUs has attracted attention as a possible solution to these problems because of their parallel performance and power efficiency. However, it is uncertain how much improvement can be obtained by applying GPUs to applications. In this study, we developed a molecular dynamics simulation program for CPU parallel and GPU parallel, and executed it on our computer cluster. Then we compared the performance of CPUs and GPUs. We obtained the result that the GPUs were about 10 times faster and 5 times more power efficient than the CPUs.