<Bioinformatics Center>Mathematical Bioinformatics

This Annual Report covers from 1 January to 31 December 201

定量的構造物性相関/定量的構造活性相関モデルの逆解析を利用した化学構造創出に関する研究

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 船津 公人, 東京大学教授 酒井 康行, 東京大学准教授 杉山 弘和, 東京大学准教授 伊藤 大知, 京都大学特任教授 奧野 恭史, スイス連邦工科大学教授 Gisbert SchneiderUniversity of Tokyo(東京大学

Development and Improvement of Tools and Algorithms for the Problem of Atom Type Perception and for the Assessment of Protein-Ligand-Complex Geometries

In context of the present work, a scoring function for protein-ligand complexes has been developed, not aimed at affinity prediction, but rather a good recognition rate of near native geometries. The developed program DSX makes use of the same formalism as the knowledge-based scoring function DrugScore, hence using the knowledge from crystallographic databases and atom-type specific distance-dependent distribution functions. It is based on newly defined atom-types. Additionally, the program is augmented by two novel potentials which evaluate the torsion angles and (de-)solvation effects. Validation of DSX is based on a literature-known, comprehensive data-set that allows for comparison with other popular scoring functions. DSX is intended for the recognition of near-native binding modes. In this important task, DSX outperforms the competitors, but is also among the best scoring functions regarding the ranking of different compounds. Another essential step in the development of DSX was the automatical assignment of the new atom types. A powerful programming framework was implemented to fulfill this task. Validation was done on a literature-known data-set and showed superior efficiency and quality compared to similar programs where this data was available. The front-end fconv was developed to share this functionality with the scientific community. Multiple features useful in computational drug-design workflows are also included and fconv was made freely available as Open Source Project. Based on the developed potentials for DSX, a number of further applications was created and impemented: The program HotspotsX calculates favorable interaction fields in protein binding pockets that can be used as a starting point for pharmacophoric models and that indicate possible directions for the optimization of lead structures. The program DSFP calculates scores based on fingerprints for given binding geometries. These fingerprints are compared with reference fingerprints that are derived from DSX interactions in known crystal structures of the particular target. Finally, the program DSX_wat was developed to predict stable water networks within a binding pocket. DSX interaction fields are used to calculate the putative water positions

The 21st Annual International Conference on Soils, Sediments and Water

Conference at a Glance Monday, October 17, 2005 Workshops (Workshops #1 and #2: 10:00am - 5:00pm; Workshop #3: 1:00 - 5:00pm; Workshop #4: 1:00 - 3:00pm, Workshop #5: 2:00 - 5:00pm) 1) Theory and Use of Field Portable X-ray Fluorescence for Soil Analysis 2) In-Situ Chemical Oxidation Workshop 3) The Role of Anaerobic Biodegradation Processes in Passive and Enhanced Monitored Natural Attenuation Programs 4) Application of Classic and Emerging Techniques in Environmental Forensics 5) Environmental Fate of Hydrocarbons in Soils and Groundwater Tuesday, October 18, 2005 Platform Presentations 8:30am – Noon Session 1: Environmental Biotechnology Session 2: Ecological Restoration and Natural Treatment Systems Session 3: Pesticides (10:30am – Noon) Session 4: Heavy Metals 1:30 – 5:30pm Session 1: Arsenic Session 2: Bioremediation Session 3: Bioremediation Strategies for Contaminated Soils and Sediments Session 4: Ozone Poster Session 4:00 – 6:00pm, Exhibit Area, First Floor, Campus Center Social 4:30-6:00pm, Exhibit Area, First Floor, Campus Center Workshops 7:00 - 10:00pm 6) Applied Environmental Forensics Workshop 7) Massachusetts Contingency Plan Method 2 Risk Characterizations Wednesday, October 19, 2005 Platform Presentations 8:30am – Noon Session 1: Perchlorate: Emerging Issues and Innovative Remedial Approaches Session 2: Soil Geochemical Background on a Continental Scale Session 3a: Environmental Fate Session 3b: Risk Assessment Session 4: Environmental Stewardship and Proactive Management at Small Arms Ranges 1:30 – 5:30pm Session 1: Ecoterrorism: Research Issues Session 2: Environmental Forensics Session 3a: Legal/Regulatory Session 3b: MTBE Session 4: Bioremediation of Acid Mine Drainage Wastes Poster Session 4:00 – 6:00pm Exhibit Area, First Floor, Campus Center Social 4:30-6:00pm, Exhibit Area, First Floor, Campus Center Workshops 7:00 - 10:00pm 8) In-Situ Thermal Remediation 9) Perchlorate: The Path to Regulatory Standards Setting and Future Assessment & Cleanup Implications 10) NIMS (National Incident Management System) and the Environment Thursday, October 20, 2005 Platform Presentations 8:30am – Noon Session 1: Evolving Strategies for Dealing with Contaminated Sediments Session 2: Pay-for-Performance Remediation Technologies - Methods & Case Studies of Science & Economics Session 3: Phytoremediation Session 4: Site Assessment 1:30 – 5:30pm Session 1: Remediation Session 2: Chemical Oxidation Session 3a: Analysis Session 3b: Indoor Ai

A bioinorganic study of some cobalt(II) Schiff base complexes of variously substituted hydroxybenzaldimines

Syntheses of Schiff bases were carried out by reacting salicylaldyhde, ortho-vanillin, para-vanillin or vanillin with aniline, 1-aminonaphthalene, 4- and 3-aminopyridine, and also with 2- and 3-aminomethylpyridine. The various Schiff bases obtained from the condensation reaction were reacted with CoCl₂.6H₂0, triethylamine stripped CoCl₂.6H₂0 or Co(CH₃COO)₂ to form cobalt(Il) complexes of ratio 2:1. The complexes obtained from cobalt chloride designated as the "A series" are of the general formulae ML₂X₂.nH₂0 , (L = Schiff base, X = chlorine) while those obtained from cobalt acetate or triethylamine stripped cobalt chloride denoted as "B" and C" are of the general formulae ML₂. nH₂0. The few complexes that do not follow the general formulae highlighted above are: IA [M(HL)₃.Cl₂], (L = N-phenylsalicylaldimine), 4A = (MLCl₂), (L = N-phenylvanaldiminato), 7 A and 21 A (ML₂), (L = N-naphthyl-o-vanaldiminato, and N-methy-2-pyridylsalicylaldiminato respectively), 8A = MLCI, (L = N-naphthylvanaldiminato), 12A = M₂L₃Cl₂, (L = N-4-pyridylvanaldiminato), 15A (MLCI), (L = N-3-pyridyl-o-vanaldiminato). The ligands and their complexes were characterized using elemental analyses and cobalt analysis using ICP, FT-IR spectroscopy (mid and far-IR), NIR-UV/vis (diffuse reflectance), UV/vis in an aprotic and a protic solvents, while mass spectrometry, ¹HNMR and ¹³CNMR, was used to further characterized the ligands. The tautomeric nature of the Schiff bases were determined by examining the behaviour of Schiff bases and their complexes in a protic (e.g. MeOH) and non-protic (e.g. DMF) polar solvents. The effects of solvents on the electronic behaviour of the compounds were also examined. Using CDCl₃, the NMR technique was further used to confirm the structures of the Schiff bases. The tentative geometry of the complexes was determined using the spectra information obtained from the far infrared and the diffuse reflectance spectroscopy. With few exceptions, most of the "A" series are tetrahedral or distorted tetrahedral, while the "B + C" are octahedral or pseudooctahedral. A small number of complexes are assigned square-planar geometry owing to the characteristic spectral behaviour shown. In order to determine their biological activity, two biological assay methods (antimicrobial testing and brine shrimp lethality assay) were used. Using disc method, the bacteriostatic and fungicidal activities of the various Schiff bases and their respective complexes to Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa as well as Aspergillus niger, were measured and the average inhibition zones are tabulated and analysed. Both the Schiff bases and their complexes showed varying bacteriostatic and fungicidal activity against the bacteria and fungus tested. The inhibition activity is concentration dependent and potential antibiotic and fungicides are identified. To determine the toxicity of the ligands and their corresponding cobalt(II) complexes, brine shrimp lethality assay was used. The LD₅₀ of the tested compounds were calculated and the results obtained were tabulated for comparison

Enhancing Reaction-based de novo Design using Machine Learning

De novo design is a branch of chemoinformatics that is concerned with the rational design of molecular structures with desired properties, which specifically aims at achieving suitable pharmacological and safety profiles when applied to drug design. Scoring, construction, and search methods are the main components that are exploited by de novo design programs to explore the chemical space to encourage the cost-effective design of new chemical entities. In particular, construction methods are concerned with providing strategies for compound generation to address issues such as drug-likeness and synthetic accessibility. Reaction-based de novo design consists of combining building blocks according to transformation rules that are extracted from collections of known reactions, intending to restrict the enumerated chemical space into a manageable number of synthetically accessible structures. The reaction vector is an example of a representation that encodes topological changes occurring in reactions, which has been integrated within a structure generation algorithm to increase the chances of generating molecules that are synthesisable. The general aim of this study was to enhance reaction-based de novo design by developing machine learning approaches that exploit publicly available data on reactions. A series of algorithms for reaction standardisation, fingerprinting, and reaction vector database validation were introduced and applied to generate new data on which the entirety of this work relies. First, these collections were applied to the validation of a new ligand-based design tool. The tool was then used in a case study to design compounds which were eventually synthesised using very similar procedures to those suggested by the structure generator. A reaction classification model and a novel hierarchical labelling system were then developed to introduce the possibility of applying transformations by class. The model was augmented with an algorithm for confidence estimation, and was used to classify two datasets from industry and the literature. Results from the classification suggest that the model can be used effectively to gain insights on the nature of reaction collections. Classified reactions were further processed to build a reaction class recommendation model capable of suggesting appropriate reaction classes to apply to molecules according to their fingerprints. The model was validated, then integrated within the reaction vector-based design framework, which was assessed on its performance against the baseline algorithm. Results from the de novo design experiments indicate that the use of the recommendation model leads to a higher synthetic accessibility and a more efficient management of computational resources

Enumeration method for tree-like chemical compounds with benzene rings and naphthalene rings by breadth-first search order

Background: Drug discovery and design are important research fields in bioinformatics. Enumeration of chemical compounds is essential not only for the purpose, but also for analysis of chemical space and structure elucidation. In our previous study, we developed enumeration methods BfsSimEnum and BfsMulEnum for tree-like chemical compounds using a tree-structure to represent a chemical compound, which is limited to acyclic chemical compounds only. Results: In this paper, we extend the methods, and develop BfsBenNaphEnum that can enumerate tree-like chemical compounds containing benzene rings and naphthalene rings, which include benzene isomers and naphthalene isomers such as ortho, meta, and para, by treating a benzene ring as an atom with valence six, instead of a ring of six carbon atoms, and treating a naphthalene ring as two benzene rings having a special bond. We compare our method with MOLGEN 5.0, which is a well-known general purpose structure generator, to enumerate chemical structures from a set of chemical formulas in terms of the number of enumerated structures and the computational time. The result suggests that our proposed method can reduce the computational time efficiently. Conclusions: We propose the enumeration method BfsBenNaphEnum for tree-like chemical compounds containing benzene rings and naphthalene rings as cyclic structures. BfsBenNaphEnum was from 50 times to 5, 000, 000 times faster than MOLGEN 5.0 for instances with 8 to 14 carbon atoms in our experiments

Building robust chemical reaction mechanisms : next generation of automatic model construction software

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2004.Includes bibliographical references (p. 308-319).Building proper reaction mechanisms is crucial to model the system dynamic properties for many industrial processes with complex chemical reaction phenomena. Because of the complexity of a reaction mechanism, computer-aided reaction mechanism generation software appeared in recent years to help people efficiently build large reaction mechanisms. However, the limitations of those programs, such as not being able to model different types of reaction systems and to provide sufficiently precise thermodynamic and kinetic parameters impede their broad usage in real reaction system modeling. Targeting the drawbacks in current first-generation reaction modeling software, this thesis presents the second-generation of reaction mechanism construction software, Reaction Mechanism Generator, (RMG). In RMG, a new reaction template method is proposed to help quickly and flexibly define different types of reaction families, so that users can easily characterize any reaction system of interest without modifying the software. Furthermore, this work also presents new functional group tree approaches to construct hierarchical structured thermodynamics and kinetics databases for managing a large number of parameters, so that people are able to quickly and precisely identify better kinetics for different reactions in the same reaction family and to easily extend and update the databases with the latest research results. This new data-model dramatically improves the interface between the chemistry and computer science, removing many of the ambiguities that have plagued the field of chemical kinetics for many years, and greatly facilitating the maintenance and documentation of both the software and the databases that provide the key inputs to any chemical kinetic model.(cont.) The author applied object-oriented technology and unified modeling language in system analysis, architecture design, and implementation of RMG. Therefore it is designed and developed into a robust software with good architecture and detailed documentation, so that this software can be easily maintained, reused, and extended. RMG is successfully applied to generate a reaction mechanism for n-butane low temperature oxidation, which includes a complex autoignition process. The model generated by RMG caught the fundamental phenomena of autoignition, and the predicted ignition delay time and many major products' yields are in very good agreement with experimental data. This is the first time that model generation software automatically generated such a complicated reaction mechanism without human interference, and provided precise predictions on ignition delay and major products yields consistent with experimental data.by Jing Song.Ph.D