
Full text loading...
Nowadays, it is well known that Quantitative studies on Structure-Activity and Structure-Property relationships (QSAR/QSPR) may become powerful tools to help Medicinal Chemistry scientist in directed drug research. In past years, various strategies have been developed to characterize and classify structural patterns of low weighted drugs by means of molecular descriptors. It has become possible not only to assess diversities or similarities of structure databases, but molecular descriptors also facilitate the identification of potential bioactive molecules from the rapidly increasing number of compound libraries. They even allow for a controlled de-novo design of new lead structures. The number and apparent diversity of molecular descriptors develop in this sense is wide covering from constitutional, and physicochemical properties to 3D descriptors. For instance, the Handbook of Molecular Descriptors (HMD) published by Todeschini and Consoni describe more than 1 500 molecular descriptors grouped on more than 15 different families. This is the most comprehensive collection of molecular descriptors and presents a detailed review from the origins of this research field up to present day. This practically oriented reference book gives a thorough overview of the different molecular descriptors representations and their corresponding molecular descriptors. Anyhow, the research in this field is far from ended and more recently, in the post-HMD times, are being investigated new trends in the development of molecular descriptors and computational techniques to seek QSAR models as well. Specifically, the class of Topological Indices (TIs), previously collected in HMD, has called the attention of many researchers due to their important capacity to capture biologically relevant information but being very simple and fast to calculate. New descriptors appeared that come to reinforce the tool of indices published in HMD but also go beyond these frontiers opening new possibilities such as the study of proteins, RNAs, Complex Networks, which is a more broad view for TIs that have been developed in parallel to small-sized drug indices. Specifically, the application of TIs or modified variants of them was used in the past to study social and technological Complex Networks and are being now “rediscovered” for molecular sciences. That is way, the present collection of papers pretend to humbly call the attention of experimental and theoretical authors (of different and somehow parallel areas) on the new scenarios that may be considered when we put in the same bag all together Medicinal Chemistry, Drug Design, Proteomics, QSAR, Complex Systems theory, and Bioinformatics. At the same time, we pretend to give some introductory but useful details on the particularities of legal issues that appear in Medicinal Chemistry research when we involve QSAR and Bioinformatics such as: copyright protection, patents registry, trademarks, and taxes. As a guest editor I would like to express my sincere appreciation to the contributing authors for their prompt submission of their manuscripts for this issue. All co-authors of the present collection and several QSAR scientists worldwide would like also to devote the present collection to remember the Cuban Prof. Maykel Perez Gonzalez, who was one of the most prolific Cuban authors on QSAR applications to Medicinal Chemistry and promoted the interest of new students in the field. Then, we hope that this issue will not only offer useful and interesting information to scientists who are involved in the field, but, perhaps more importantly, will also serve as an inspiration for new researchers. Finally, on behalf of all co-authors, I extend many thanks to Dr. Allen Reitz, Editor-in-Chief of Current Topics in Medicinal Chemistry for kind attention and help.