3D Molecular Similarity Research Articles

Modeling of the anticancer action for radical derivatives of nitroazoles: quantitative structure-activity relationship (QSAR) study.

A QSAR analysis of the anti-tumor, anti-metastasis and anti-colony formation (for metastatic colonies) activities of eighteen nitroazoles (including metronidazole and hypoxic radiosensitizers RP-170, KU-2285 and sanazole (drug AK-2123)) and their nitro and nitroso anion radical derivatives against melanoma B16 in mice has been performed. The QSAR models were built with the use of the frontal polygon method. This approach has features of different 3D QSAR methodologies and belongs to the group of "indirect" methods. The procedure allows to build robust models with high predictive ability even in series of diverse and conformationally flexible compounds. Key atomic characteristics accompany the geometrical requirements in the analysis of local 3D molecular similarity. By variation of weight coefficients for hydrophobicity, refraction increments, and partial charge it is possible to achieve better quality of QSAR and evaluate the importance of each characteristic for biological activity under consideration. It was found that hydrophobicity, molar refraction and charge characteristics of nitro anion radical derivatives are more significant for interaction with molecular targets than those of the parent compounds and of the nitroso anion radical derivatives. Size and hydrophobic properties of substituents in nitro anion radicals play significant role for ligand-target interaction in the processes of inhibition of metastatic spreading and growth of metastatic colonies by nitroazoles. A scheme of competitive interaction of parent nitroazoles and their anion radicals with a target in organism is suggested. It can be concluded that the step of one-electron reduction of nitroazoles can be important for anticancer activity of these drugs.

Morphological similarity: a 3D molecular similarity method correlated with protein-ligand recognition.

Recognition of small molecules by proteins depends on three-dimensional molecular surface complementarity. However, the dominant techniques for analyzing the similarity of small molecules are based on two-dimensional chemical structure, with such techniques often outperforming three-dimensional techniques in side-by-side comparisons of correlation to biological activity. This paper introduces a new molecular similarity method, termed morphological similarity (MS), that addresses the apparent paradox. Two sets of molecule pairs are identified from a set of ligands whose protein-bound states are known crystallographically. Pairs that bind the same protein sites form the first set, and pairs that bind different sites from the second. MS is shown to separate the two sets significantly better than a benchmark 2D similarity technique. Further, MS agrees with crystallographic observation of bound ligand states, independent of information about bound states. MS is efficient to compute and can be practically applied to large libraries of compounds.