title: Latest advances in molecular topology applications for drug discovery.
abstract: BACKGROUND
  Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. In the last decade, its application has become more and more popular among the leading research groups in the field of quantitative structure-activity relationships (QSAR) and drug design. This has, in turn, contributed to the rapid development of new techniques and applications of MT in QSAR studies, as well as the introduction of new topological indices.
  
  
  METHODS
  This review collates the main innovative techniques in the field of MT and provides a description of the novel topological indices recently introduced, through an exhaustive recompilation of the most significant works carried out by the leading research groups in the field of drug design and discovery. The objective is to show the importance of MT methods combined with the effectiveness of the descriptors.
  
  
  CONCLUSIONS
  Recent years have witnessed a remarkable rise in QSAR methods based on MT and its application to drug design. New methodologies have been introduced in the area such as QSAR multi-target, Markov networks or perturbation methods. Moreover, novel topological indices, such as Bourgas' descriptors and other new concepts as the derivative of a graph or cliques capable to distinguish between conformers, have also been introduced. New drugs have also been discovered, including anticonvulsants, anineoplastics, antimalarials or antiallergics, just to name a few. In the authors' opinion, MT and QSAR have moved from an attractive possibility to representing a foundation stone in the process of drug discovery.
authors.affiliation: University of Valencia Avd, Molecular Connectivity and Drug Design Research Unit, Faculty of Pharmacy, Department of Physical Chemistry , V.A. Estellés, s/n 46100-Burjassot, Valencia , Spain +34963544291 ; +34963544892 ; jorge.galvez@uv.es.
authors.forename: Riccardo
authors.initials: R
authors.lastname: Zanni
authors.forename: Maria
authors.initials: M
authors.lastname: Galvez-Llompart
authors.forename: Ramón
authors.initials: R
authors.lastname: García-Domenech
authors.forename: Jorge
authors.initials: J
authors.lastname: Galvez
mesh_terms: D003198:Computer Simulation; D017076:Computer-Aided Design; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008958:Models, Molecular; D021281:Quantitative Structure-Activity Relationship
keywords: drug discovery; molecular topology; quantitative structure–activity relationships; topological descriptors