Similitud molecular empleando Índices Híbridos / Molecular similarity using Hybrid Indices

Se presenta un método para la detección de semejanza entre moléculas basado en macheo inexacto de grafos. Se parte del grafo molecular completo ponderado en sus vértices por propiedades químico-físicas particionadas sobre los mismos, se reduce el grafo por el procedimiento CALEDE que define Centros Descriptores o fragmentos de primer orden, los cuales son subgrafos ponderados por la suma de los valores de los vértices ponderados individualmente a su vez, y se construyen fragmentos denominados de segundo orden que incluyen la distancia entre los centros de masas de ambos centros descriptores. Se presenta el método de búsqueda aplicado a una base de datos de más de 300 moléculas con sus respectivas estructuras en tres dimensiones. Esos compuestos se encuentran evaluados como anticancerígenos en la base de datos de compuestos del NCBI-USA. En el experimento computacional se encuentra que, en dependencia de la función de similitud empleada, es posible detectar compuestos que a pesar de poseer diferente topología, poseen valores de las propiedades empleadas para el macheo lo cual sugiere la presencia de potenciales farmacóforos como hallazgo relevante, lo cual constituiría un novedoso enfoque para el diseño computacional de fármacos(AU)

A method for detecting similarity between molecules based on inexact matching graph is presented. We start from a complete molecular graph vertices weighted by several hybrid indices. The molecular graph is reduced by CALEDE procedure, which define descriptors centers or first order fragments. These fragments are subgraphs weighted with the sum of values of the vertices weighted with the hybrid indices. It also define second order fragments by including the distance between the centers of mass of both descriptors centers. The search method applied to a database of over 300 molecules with their respective threedimensional structures is presented. These compounds are reported in the NCBI-USA database of compounds whish were evaluated in anticancer tests. In the computational experiment, depending on the similarity function used, is possible to detect compounds that despite having different topology have property values suggesting the presence of potential pharmacophore. It suggest the possibility to use this approach as a novel approach for computational drug design(AU)

Analyzing resistance pattern of non-small cell lung cancer to crizotinib using molecular dynamic approaches.

Crizotinib is the potential anticancer drug used for the treatment of non-small cell lung cancer (NSCLC) approved by FDA in 2011. The main target for the crizotinib is anaplastic lymphoma kinase (ALK). Evidences available indicate that double mutant ALK (L1196M and G1269A) confers resistance to crizotinib. However, how mutation confers drug resistance is not well-understood. Hence, in the present study, molecular dynamic (MD) simulation approach was employed to study the impact of crizotinib binding efficacy with ALK structures at a molecular level. Docking results indicated that ALK double mutant (L1196M and G1269A) significantly affected the binding affinity for crizotinib. Furthermore, MD studies revealed that mutant ALK-crizotinib complex showed higher deviation, higher fluctuation and decreased number of intermolecular H-bonds, when compared to the native ALK-crizotinib complex. These results may be immense importance for the molecular level understanding of the crizotinib resistance pattern and also for designing potential drug molecule for the treatment of lung cancer.