Hybrid reduced graph for SAR studies

Carrasco-Velar, Ramón; Prieto-Entenza, Julio Omar; Antelo-Collado, Aurelio; Padrón-García, J.A.; García, Gonzalo Cerruela; Maceo-Pixa, Á.L.; Alcolea-Núñez, R.; Silva-Rojas, L.G.

doi:10.1080/1062936x.2013.764926

Cited by 4 publications

(4 citation statements)

References 28 publications

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“…If we observe the differences between the families of compounds 6, 7 and 8 (see Table 1), these differences were fundamentally due to the characteristics of the side chain. Moreover, the hybrid descriptors used in MCPhd have demonstrated [35,45] their capability to distinguish between the same DC at different positions in a molecule. That allows MCPhd to find relationships/groups of compounds that show a higher functional relationship, and find similarities between compounds of different families.…”

Section: Resultsmentioning

confidence: 99%

“…The reduction of the chemical graph is carried out by the method described by Carrasco et al [ 35 ], where the descriptor centers (DCs), rings of different orders (Rn), clusters of order 3 and 4 (C3 and C4, respectively), heteroatoms such as halogens, amino, etc. (X), and terminal groups such as methyl ( ), methylene ( ) and methyne (M) are defined.…”

Section: Methodsmentioning

confidence: 99%

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Maximum common property: a new approach for molecular similarity

et al. 2020

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The maximum common property similarity (MCPhd) method is presented using descriptors as a new approach to determine the similarity between two chemical compounds or molecular graphs. This method uses the concept of maximum common property arising from the concept of maximum common substructure and is based on the electrotopographic state index for atoms. A new algorithm to quantify the similarity values of chemical structures based on the presented maximum common property concept is also developed in this paper. To verify the validity of this approach, the similarity of a sample of compounds with antimalarial activity is calculated and compared with the results obtained by four different similarity methods: the small molecule subgraph detector (SMSD), molecular fingerprint based (OBabel_FP2), ISIDA descriptors and shape-feature similarity (SHAFTS). The results obtained by the MCPhd method differ significantly from those obtained by the compared methods, improving the quantification of the similarity. A major advantage of the proposed method is that it helps to understand the analogy or proximity between physicochemical properties of the molecular fragments or subgraphs compared with the biological response or biological activity. In this new approach, more than one property can be potentially used. The method can be considered a hybrid procedure because it combines descriptor and the fragment approaches.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Maximum common property: a new approach for molecular similarity

et al. 2020

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“…The reduction of the chemical graph is carried out by the method described by Carrasco et al [19], where the descriptor centers (CDs), rings of different orders (Rn), clusters of order 3 and 4 (C3 and C4, respectively), heteroatoms such as halogens, amino, etc. (X), and terminal groups such as methyl (M 3 ), methylene (M 2 ) and methyne (M) are defined.…”

Section: Graph Reductionmentioning

confidence: 99%

Maximum Common Property: A New Approach for Molecular Similarity

García

Collado

Carrasco-Velar

et al. 2020

Preprint

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The maximum common property similarity (MCPhd) method is presented using descriptors as a new approach to determine the similarity between two chemical compounds or molecular graphs. This method uses the concept of maximum common property arising from the concept of maximum common substructure and is based on the electrotopographic state index for atoms. A new algorithm to quantify the similarity values of chemical structures based on the presented maximum common property concept is also developed in this paper. To verify the validity of this approach, the similarity of a sample of compounds with antimalarial activity is calculated and compared with the results obtained by the small molecule subgraph detector (SMSD) method. The results obtained by the MCPhd method differ significantly from those obtained by the SMSD method, improving the quantification of the similarity. A major advantage of the proposed method is that it helps to understand the analogy or proximity between physicochemical properties of the molecular fragments or subgraphs compared with the biological response or biological activity. In this new approach, more than one property can be potentially used. The method can be considered a hybrid procedure because it combines descriptor and the fragment approaches.

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“…[25] In addition, reducedg raphr epresentations of ligandsh ave found use in QSAR,v irtual screening, and cheminformatics applications based on similarity searches. [26] Figure 1. Panels A) and B) show the original three-point attachmentmodel of protein-ligand stereoselectivity,where for al igand with one stereocenter,astereoisomer showni nA )n eeds threeattachment points to be selectively bound to the protein (shown by ac urve).…”

mentioning

confidence: 99%

Chiral Graphs: Reduced Representations of Ligand Scaffolds for Stereoselective Biomolecular Recognition, Drug Design, and Enhanced Exploration of Chemical Structure Space

Mikhael

Abrol

2019

ChemMedChem

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Rational structure‐based drug design relies on a detailed, atomic‐level understanding of protein–ligand interactions. The chiral nature of drug binding sites in proteins has led to the discovery of predominantly chiral drugs. A mechanistic understanding of stereoselectivity (which governs how one stereoisomer of a drug might bind stronger than the others to a protein) depends on the topology of stereocenters in the chiral molecule. Chiral graphs and reduced chiral graphs, introduced here, are new topological representations of chiral ligands using graph theory, to facilitate a detailed understanding of chiral recognition of ligands/drugs by proteins. These representations are demonstrated by application to all ≈14 000+ chiral ligands in the Protein Data Bank (PDB), which will facilitate an understanding of protein–ligand stereoselectivity mechanisms. Ligand modifications during drug development can be easily incorporated into these chiral graphs. In addition, these chiral graphs present an efficient tool for a deep dive into the enormous chemical structure space to enable sampling of unexplored structural scaffolds.

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Hybrid reduced graph for SAR studies

Cited by 4 publications

References 28 publications

Maximum common property: a new approach for molecular similarity

Maximum common property: a new approach for molecular similarity

Maximum Common Property: A New Approach for Molecular Similarity

Chiral Graphs: Reduced Representations of Ligand Scaffolds for Stereoselective Biomolecular Recognition, Drug Design, and Enhanced Exploration of Chemical Structure Space

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