scholarly journals Modeling Organic Chemistry and Planning Organic Synthesis

10.29007/493z ◽  
2018 ◽  
Author(s):  
Arman Masoumi ◽  
Megan Antoniazzi ◽  
Mikhail Soutchanski
Keyword(s):  
Organic Chemistry ◽  
Organic Synthesis ◽  
Chemical Reactions ◽  
Practical Problem ◽  
State Of The Art ◽  
Benchmark Problems ◽  
Planning Problem ◽  
Input Language ◽  
Domain Definition ◽  
Domain Independent

Organic Synthesis is a computationally challenging practical problem concerned with constructing a target molecule from a set of initially available molecules via chemical reactions. This paper demonstrates how organic synthesis can be formulated as a planning problem in Artificial Intelligence, and how it can be explored using the state-of-the-art domain independent planners.To this end, we develop a methodology to represent chemical molecules and generic reactions in PDDL 2.2, a version of the standardized Planning Domain Definition Language popular in AI. In our model, derived predicates define common functional groups and chemical classes in chemistry, and actionscorrespond to generic chemical reactions. We develop a set of benchmark problems. Since PDDL is supported as an input language by many modern planners, our benchmark can be subsequently useful forempirical assessment of the performance of various state-of-the-art planners.

scholarly journals Organic chemistry synthesis problem as artificial intelligence planning.

2021 ◽  
Author(s):  
Arman Masoumi
Keyword(s):  
Organic Chemistry ◽  
Artificial Intelligence ◽  
Functional Groups ◽  
Organic Synthesis ◽  
Chemical Reactions ◽  
Benchmark Problems ◽  
Logical Language ◽  
Artificial Intelligence Planning ◽  
Planning Problems ◽  
Novel Algorithm

This thesis formulates organic chemistry synthesis problems as Artificial Intelligence planning problems and uses a combination of techniques developed in the field of planning to solve organic synthesis problems. To this end, a methodology for axiomatizing organic chemistry is developed, which includes axiomatizing molecules and functional groups, as well as two approaches for representing chemical reactions in a logical language amenable to reasoning. A novel algorithm for planning specific to organic chemistry is further developed, based on which a planner capable of identifying 75 functional groups and chemical classes is implemented with a knowledge base of 55 generic chemical reactions. The performance of the planner is empirically evaluated on two sets of benchmark problems and analytically compared with a number of competing algorithms. v

scholarly journals Organic chemistry synthesis problem as artificial intelligence planning.

2021 ◽  
Author(s):  
Arman Masoumi
Keyword(s):  
Organic Chemistry ◽  
Artificial Intelligence ◽  
Functional Groups ◽  
Organic Synthesis ◽  
Chemical Reactions ◽  
Benchmark Problems ◽  
Logical Language ◽  
Artificial Intelligence Planning ◽  
Planning Problems ◽  
Novel Algorithm

This thesis formulates organic chemistry synthesis problems as Artificial Intelligence planning problems and uses a combination of techniques developed in the field of planning to solve organic synthesis problems. To this end, a methodology for axiomatizing organic chemistry is developed, which includes axiomatizing molecules and functional groups, as well as two approaches for representing chemical reactions in a logical language amenable to reasoning. A novel algorithm for planning specific to organic chemistry is further developed, based on which a planner capable of identifying 75 functional groups and chemical classes is implemented with a knowledge base of 55 generic chemical reactions. The performance of the planner is empirically evaluated on two sets of benchmark problems and analytically compared with a number of competing algorithms. v

scholarly journals Efficient Lifted Planning with Regression-Based Heuristics

2021 ◽  
Author(s):  
Hadi Qovaizi
Keyword(s):  
Organic Synthesis ◽  
State Of The Art ◽  
Transition System ◽  
Modern State ◽  
Synthetic Approach ◽  
Best First Search ◽  
Planning Task ◽  
International Planning ◽  
Domain Independent ◽  
Novel Algorithm

Modern state-of-the-art planners operate by generating a grounded transition system prior to performing search for a solution to a given planning task. Some tasks involve a significant number of objects or entail managing predicates and action schemas with a significant number of arguments. Hence, this instantiation procedure can exhaust all available memory and therefore prevent a planner from performing search to find a solution. This thesis explores this limitation by presenting a benchmark set of problems based on Organic Chemistry Synthesis that was submitted to the latest International Planning Competition (IPC-2018). This benchmark was constructed to gauge the performance of the competing planners given that instantiation is an issue. Furthermore, a novel algorithm, the Regression-Based Heuristic Planner (RBHP), is developed with the aim of averting this issue. RBHP was inspired by the retro-synthetic approach commonly used to solve organic synthesis problems efficiently. RBHP solves planning tasks by applying domain independent heuristics, computed by regression, and performing best-first search. In contrast to most modern planners, RBHP computes heuristics backwards by applying the goal-directed regression operator. However, the best-first search proceeds forward similar to other planners. The proposed planner is evaluated on a set of planning tasks included in previous International Planning Competitions (IPC) against a subset of the top scoring state-of-the-art planners submitted to the IPC-2018.

Organic Synthesis

2011 ◽  
Author(s):  
Douglass Taber
Keyword(s):  
Organic Chemistry ◽  
Organic Synthesis ◽  
State Of The Art ◽  
Synthetic Method ◽  
Total Syntheses ◽  
New Methods ◽  
Recent Developments ◽  
Asymmetric Organocatalysis

Organic synthesis is a vibrant and rapidly evolving field; we can now cyclize amines directly onto alkenes. Like the first two books in this series, Organic Synthesis: State of the Art 2003-2005 and Organic Synthesis: State of the Art 2005-2007, this reference leads readers quickly to the most important recent developments. Two years of Taber's popular weekly online column, "Organic Chemistry Highlights", as featured on the organic-chemistry.org website, are consolidated here, with cumulative indices of all three volumes in this series. Important topics that are covered range from powerful new methods for C-C bond construction to asymmetric organocatalysis and direct C-H functionalization. This go-to reference focuses on the most important recent developments in organic synthesis, and includes a succinct analysis of the significance and applicability of each new synthetic method. It details and analyzes more than twenty complex total syntheses, including the Sammakia synthesis of the Macrolide RK-397, the Ley synthesis of Rapamycin, and the Kobayashi synthesis of (-)-Norzoanthamine.

scholarly journals Class Map: Improving Students’ Skills of Organic Synthesis in Learning Organic Chemistry for Pre-University Students

2022 ◽  
Vol 7 (1) ◽  
pp. 270-284
Author(s):  
Nik Mawar Hanifah Nik Hassan ◽  
Othman Talib ◽  
Hairul Faiezi Lokman
Keyword(s):  
Organic Chemistry ◽  
University Students ◽  
Organic Synthesis ◽  
Chemical Reactions ◽  
Functional Group ◽  
Document Analysis ◽  
Test Results ◽  
Chemistry Students ◽  
The Subject ◽  
Answering Questions

This action research uses the Kemmis & Mc Taggart Model (1988) to improve the skills for science stream of pre-university students in organic synthesis topic to convert one functional group to another by using Class Map in learning Organic Chemistry. The objectives of this study were to improve memory skills in conversion of functional groups in an Organic Chemistry reaction and to cultivate students' interest in the subject of Organic Chemistry. A total of six students of 6 Delta 2, SMK Sultan Abu Bakar were involved in this study. Preliminary surveys were conducted through observations, document analysis and interviews. The results of the survey showed that students could not remember the conversion of functional group well because in the Semester Three chemistry syllabus, there are too many chemical reactions, causing students less interested in learning Organic Chemistry. Students were exposed to the Class Map within two months. The test results displayed that (i) students can recall the functional group conversion reaction in an Organic Chemistry and (ii) students can apply the organic reactions learned in answering questions. The findings of the interviews showed that students can cultivate an interest in Organic Chemistry subject.

scholarly journals Efficient Lifted Planning with Regression-Based Heuristics

2021 ◽  
Author(s):  
Hadi Qovaizi
Keyword(s):  
Organic Synthesis ◽  
State Of The Art ◽  
Transition System ◽  
Modern State ◽  
Synthetic Approach ◽  
Best First Search ◽  
Planning Task ◽  
International Planning ◽  
Domain Independent ◽  
Novel Algorithm

Modern state-of-the-art planners operate by generating a grounded transition system prior to performing search for a solution to a given planning task. Some tasks involve a significant number of objects or entail managing predicates and action schemas with a significant number of arguments. Hence, this instantiation procedure can exhaust all available memory and therefore prevent a planner from performing search to find a solution. This thesis explores this limitation by presenting a benchmark set of problems based on Organic Chemistry Synthesis that was submitted to the latest International Planning Competition (IPC-2018). This benchmark was constructed to gauge the performance of the competing planners given that instantiation is an issue. Furthermore, a novel algorithm, the Regression-Based Heuristic Planner (RBHP), is developed with the aim of averting this issue. RBHP was inspired by the retro-synthetic approach commonly used to solve organic synthesis problems efficiently. RBHP solves planning tasks by applying domain independent heuristics, computed by regression, and performing best-first search. In contrast to most modern planners, RBHP computes heuristics backwards by applying the goal-directed regression operator. However, the best-first search proceeds forward similar to other planners. The proposed planner is evaluated on a set of planning tasks included in previous International Planning Competitions (IPC) against a subset of the top scoring state-of-the-art planners submitted to the IPC-2018.

Organic Synthesis

2015 ◽  
Author(s):  
Douglass F. Taber ◽  
Tristan Lambert
Keyword(s):  
Organic Chemistry ◽  
Organic Synthesis ◽  
Functional Group ◽  
State Of The Art ◽  
Bond Formation ◽  
Natural Product Synthesis ◽  
Total Syntheses ◽  
Carbon Carbon Bond ◽  
Ideal Tool ◽  
Source Of Information

Organic Synthesis: State of the Art 2011-2013 is a convenient, concise reference that summarizes the most important current developments in organic synthesis, from functional group transformations to complex natural product synthesis. The fifth volume in the esteemed State of the Art series, the book compiles two years' worth of Douglass Taber's popular weekly column Organic Chemistry Highlights. The series is an invaluable resource, leading chemists quickly and easily to the most significant developments in the field. The book is logically divided into two sections: the first section focuses on specific topics in organic synthesis, such as C-N Ring Construction and Carbon-Carbon Bond Formation. Each topic is presented using the most significant publications within those areas of research. The journal references are included in the text. The second section focuses on benchmark total syntheses, with an analysis of the strategy for each, and discussions of pivotal transformations. Synthetic organic chemistry is a complex and rapidly growing field, with additional new journals appearing almost every year. Staying abreast of recent research is a daunting undertaking. This book is an ideal tool for both practicing chemists and students, offering a rich source of information and suggesting fruitful pathways for future investigation.

The molecular diversity of 1,8-diaminonaphthalene in organic chemistry

2020 ◽  
Vol 23 ◽  
Author(s):  
Ghodsi Mohammadi Ziarani ◽  
Fatemeh Mohajer ◽  
Suraj N. Mali
Keyword(s):  
Organic Chemistry ◽  
Organic Synthesis ◽  
Molecular Diversity ◽  
Organic Reactions ◽  
Recent Application ◽  
Organic Structure

: 1,8-diaminonaphthalene (1,8-DAN) with special organic structure was applied in organic synthesis to provide efficient complex scaffolds, through the two or four-component fashion. This review highlights its recent application in organic reactions under different conditions and heterogynous catalysts to produce various molecules, which were used as medicines, sensors, and dyes.

Modern Organic Synthesis in the Laboratory

2008 ◽  
Author(s):  
Jie Jack Li ◽  
Chris Limberakis ◽  
Derek A. Pflum
Keyword(s):  
Organic Chemistry ◽  
Graduate Students ◽  
Organic Synthesis ◽  
Functional Group ◽  
Bond Formation ◽  
Reaction Conditions ◽  
Carbon Bond ◽  
Oxidation Reduction ◽  
Carbon Carbon Bond ◽  
Daunting Task

Searching for reaction in organic synthesis has been made much easier in the current age of computer databases. However, the dilemma now is which procedure one selects among the ocean of choices. Especially for novices in the laboratory, it becomes a daunting task to decide what reaction conditions to experiment with first in order to have the best chance of success. This collection intends to serve as an "older and wiser lab-mate" one could have by compiling many of the most commonly used experimental procedures in organic synthesis. With chapters that cover such topics as functional group manipulations, oxidation, reduction, and carbon-carbon bond formation, Modern Organic Synthesis in the Laboratory will be useful for both graduate students and professors in organic chemistry and medicinal chemists in the pharmaceutical and agrochemical industries.

scholarly journals Extraction of organic chemistry grammar from unsupervised learning of chemical reactions

2021 ◽  
Vol 7 (15) ◽  
pp. eabe4166
Author(s):  
Philippe Schwaller ◽  
Benjamin Hoover ◽  
Jean-Louis Reymond ◽  
Hendrik Strobelt ◽  
Teodoro Laino
Keyword(s):  
Organic Chemistry ◽  
Neural Networks ◽  
Chemical Synthesis ◽  
Unsupervised Learning ◽  
Chemical Reactions ◽  
Data Driven ◽  
Experimental Task ◽  
Rule Based ◽  
Atom Mapping ◽  
Mapping Information

Humans use different domain languages to represent, explore, and communicate scientific concepts. During the last few hundred years, chemists compiled the language of chemical synthesis inferring a series of “reaction rules” from knowing how atoms rearrange during a chemical transformation, a process called atom-mapping. Atom-mapping is a laborious experimental task and, when tackled with computational methods, requires continuous annotation of chemical reactions and the extension of logically consistent directives. Here, we demonstrate that Transformer Neural Networks learn atom-mapping information between products and reactants without supervision or human labeling. Using the Transformer attention weights, we build a chemically agnostic, attention-guided reaction mapper and extract coherent chemical grammar from unannotated sets of reactions. Our method shows remarkable performance in terms of accuracy and speed, even for strongly imbalanced and chemically complex reactions with nontrivial atom-mapping. It provides the missing link between data-driven and rule-based approaches for numerous chemical reaction tasks.

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