No abstract

Proteins are an important class of biochemical molecules, as the structural components of animal and human tissue are based on them. Antibodies are proteins that play a crucial role in the preservation of life since they are produced by the body's immune system as a response to harmful substances. The modelling of proteins and antibodies in particular is a vibrant research field which facilitates the design of drugs, a process otherwise demanding in terms of time and resources. A variety of computational methods and tools are being developed towards that goal, among which are hybrid quantum chemical/molecular mechanical methods and three-dimensional antibody modelling. In this review the authors discuss the knowledge concerning proteins and antibodies, as well as the use of quantum mechanics in the simulation of molecular systems and the three-dimensional antibody modelling.

Antibody–drug conjugates (ADCs) constitute a category of anticancer targeted therapy that has gathered great interest during the last few years because of their potential to kill cancer cells while causing significantly fewer side effects than traditional chemotherapy. In this paper, a process of computational construction of ADCs is described, using the surface lysines of an antibody and a non-covalent linker molecule, as well as a cytotoxic substance, as files in Protein Data Bank format. Also, aspects related to the function, properties, and development of ADCs are discussed.

Artificial neural networks (ANNs) are a well-established computational method inspired by the structure and function of biological central nervous systems. Since their conception, ANNs have been utilized in a vast variety of applications due to their impressive information processing abilities. A vibrant field, ANNs have been utilized in bioinformatics, a general term for describing the combination of informatics, biology and medicine. This article is an effort to investigate recent advances in the area of bioinformatical applications of ANNs, with emphasis in disease diagnosis, genetics, proteomics, and chemoinformatics. The combination of neural networks and game theory in some of these application is also discussed.