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SMILES alignment: a dynamic programming approach for the alignment of metabolites and other small organic molecules
by
Tang, Alexis L.
, Liberles, David A.
in
Algorithms
/ Alignment
/ Applications software
/ Biochemical pathways
/ Biochemistry
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomolecules
/ Chemical alignment
/ Chemical fingerprinting
/ Chemical properties
/ Chemical research
/ Chemoinformatics
/ Citric Acid Cycle
/ Comparative analysis
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Datasets
/ Dynamic Programming
/ Electric properties
/ Electronegativity
/ Global alignment
/ Glycolysis
/ Krebs cycle
/ Life Sciences
/ Machine learning
/ Metabolic pathways
/ Metabolites
/ Methods
/ Microarrays
/ Molecular structure
/ Neural networks
/ Nucleotide sequence
/ Organic Chemicals - chemistry
/ Organic Chemicals - metabolism
/ Organic chemistry
/ Organic molecule similarity search
/ Pentose
/ Pentose phosphate pathway
/ Principal components analysis
/ Software
/ Transformations (mathematics)
/ Tricarboxylic acid cycle
2025
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SMILES alignment: a dynamic programming approach for the alignment of metabolites and other small organic molecules
by
Tang, Alexis L.
, Liberles, David A.
in
Algorithms
/ Alignment
/ Applications software
/ Biochemical pathways
/ Biochemistry
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomolecules
/ Chemical alignment
/ Chemical fingerprinting
/ Chemical properties
/ Chemical research
/ Chemoinformatics
/ Citric Acid Cycle
/ Comparative analysis
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Datasets
/ Dynamic Programming
/ Electric properties
/ Electronegativity
/ Global alignment
/ Glycolysis
/ Krebs cycle
/ Life Sciences
/ Machine learning
/ Metabolic pathways
/ Metabolites
/ Methods
/ Microarrays
/ Molecular structure
/ Neural networks
/ Nucleotide sequence
/ Organic Chemicals - chemistry
/ Organic Chemicals - metabolism
/ Organic chemistry
/ Organic molecule similarity search
/ Pentose
/ Pentose phosphate pathway
/ Principal components analysis
/ Software
/ Transformations (mathematics)
/ Tricarboxylic acid cycle
2025
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Do you wish to request the book?
SMILES alignment: a dynamic programming approach for the alignment of metabolites and other small organic molecules
by
Tang, Alexis L.
, Liberles, David A.
in
Algorithms
/ Alignment
/ Applications software
/ Biochemical pathways
/ Biochemistry
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomolecules
/ Chemical alignment
/ Chemical fingerprinting
/ Chemical properties
/ Chemical research
/ Chemoinformatics
/ Citric Acid Cycle
/ Comparative analysis
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Datasets
/ Dynamic Programming
/ Electric properties
/ Electronegativity
/ Global alignment
/ Glycolysis
/ Krebs cycle
/ Life Sciences
/ Machine learning
/ Metabolic pathways
/ Metabolites
/ Methods
/ Microarrays
/ Molecular structure
/ Neural networks
/ Nucleotide sequence
/ Organic Chemicals - chemistry
/ Organic Chemicals - metabolism
/ Organic chemistry
/ Organic molecule similarity search
/ Pentose
/ Pentose phosphate pathway
/ Principal components analysis
/ Software
/ Transformations (mathematics)
/ Tricarboxylic acid cycle
2025
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SMILES alignment: a dynamic programming approach for the alignment of metabolites and other small organic molecules
Journal Article
SMILES alignment: a dynamic programming approach for the alignment of metabolites and other small organic molecules
2025
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Overview
Background
There is a need for computational approaches to compare small organic molecules based on chemical similarity or for evaluating biochemical transformations. No tool currently exists to generate global molecular alignments for small organic molecules. The study introduces a new approach to molecular alignment in the Simplified Molecular Input Line Entry System (SMILES) format. This method leverages programming and scoring alignments to minimize differences in electronegativity, here using a measure of atomic partial charges to address the challenge of understanding structural transformations in reaction pathways. This can be applied to study transitions from linear to cyclical pathways.
Results
The proposed method is based on the Needleman-Wunsch algorithm for sequence alignment, but it uses a modified scoring function for different input data. Validation against a benchmarked dataset from the Krebs cycle, based on the known chemical transformations in the pathway, confirmed the efficacy of the approach in aligning atoms that are known to be the same across the transformation. The algorithm also quantified each transformation of metabolites in the Pentose Phosphate Pathway and in Glycolysis. The method was used to study the difference in chemical similarity over transformations between linear and cyclical pathways. The study found a midpoint dissimilarity peak in cyclical pathways (particularly the Krebs Cycle) and a progressive decrease in molecular similarity in linear pathways, consistent with expectations.
Conclusions
The study introduces an algorithm that quantifies molecular transformations in metabolic pathways. The algorithm effectively highlights structural changes and was applied to a hypothesis about the transition from linear to cyclical structures. The software, which provides valuable insights into molecular transformations, is available at:
https://github.com/24atang/SMILES-Alignment.git
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Biomedical and Life Sciences
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Datasets
/ Methods
/ Organic Chemicals - chemistry
/ Organic Chemicals - metabolism
/ Organic molecule similarity search
/ Pentose
/ Principal components analysis
/ Software
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