J Chem Inf Model - Noncontiguous atom matching structural similarity function.


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Measuring similarity between molecules is a fundamental problem in cheminformatics. Given that similar molecules tend to have similar physical, chemical, and biological properties, the notion of molecular similarity plays an important role in the exploration of molecular data sets, query-retrieval in molecular databases, and in structure-property/activity modeling. Various methods to define structural similarity between molecules are available in the literature, but so far none has been used with consistent and reliable results for all situations. We propose a new similarity method based on atom alignment for the analysis of structural similarity between molecules. This method is based on the comparison of the bonding profiles of atoms on comparable molecules, including features that are seldom found in other structural or graph matching approaches like chirality or double bond stereoisomerism. The similarity measure is then defined on the annotated molecular graph, based on an iterative directed graph similarity procedure and optimal atom alignment between atoms using a pairwise matching algorithm. With the proposed approach the similarities detected are more intuitively understood because similar atoms in the molecules are explicitly shown. This noncontiguous atom matching structural similarity method (NAMS) was tested and compared with one of the most widely used similarity methods (fingerprint-based similarity) using three difficult data sets with different characteristics. Despite having a higher computational cost, the method performed well being able to distinguish either different or very similar hydrocarbons that were indistinguishable using a fingerprint-based approach. NAMS also verified the similarity principle using a data set of structurally similar steroids with differences in the binding affinity to the corticosteroid binding globulin receptor by showing that pairs of steroids with a high degree of similarity (>80%) tend to have smaller differences in the absolute value of binding activity. Using a highly diverse set of compounds with information about the monoamine oxidase inhibition level, the method was also able to recover a significantly higher average fraction of active compounds when the seed is active for different cutoff threshold values of similarity. Particularly, for the cutoff threshold values of 86%, 93%, and 96.5%, NAMS was able to recover a fraction of actives of 0.57, 0.63, and 0.83, respectively, while the fingerprint-based approach was able to recover a fraction of actives of 0.41, 0.40, and 0.39, respectively. NAMS is made available freely for the whole community in a simple Web based tool as well as the Python source code at http://nams.lasige.di.fc.ul.pt/.

Resumo Limpo

measur similar molecul fundament problem cheminformat given similar molecul tend similar physic chemic biolog properti notion molecular similar play import role explor molecular data set queryretriev molecular databas structurepropertyact model various method defin structur similar molecul avail literatur far none use consist reliabl result situat propos new similar method base atom align analysi structur similar molecul method base comparison bond profil atom compar molecul includ featur seldom found structur graph match approach like chiral doubl bond stereoisomer similar measur defin annot molecular graph base iter direct graph similar procedur optim atom align atom use pairwis match algorithm propos approach similar detect intuit understood similar atom molecul explicit shown noncontigu atom match structur similar method nam test compar one wide use similar method fingerprintbas similar use three difficult data set differ characterist despit higher comput cost method perform well abl distinguish either differ similar hydrocarbon indistinguish use fingerprintbas approach nam also verifi similar principl use data set structur similar steroid differ bind affin corticosteroid bind globulin receptor show pair steroid high degre similar tend smaller differ absolut valu bind activ use high divers set compound inform monoamin oxidas inhibit level method also abl recov signific higher averag fraction activ compound seed activ differ cutoff threshold valu similar particular cutoff threshold valu nam abl recov fraction activ respect fingerprintbas approach abl recov fraction activ respect nam made avail freeli whole communiti simpl web base tool well python sourc code httpnamslasigedifculpt

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