Fecha
Inicio: 01/05/2020, Fin: 30/04/2022.
Objetivos
Objetivos del proyecto
Peptides have been acclaimed as the drugs of the future, thanks to their high specificity and activity, as well as their easy degradation. This implies that they generally possess reduced toxicity, few secondary effects, and are thus administered in small doses. Peptides possess multiple therapeutic applications, which include: antivirals, antifungals, antibiotics, modulators of the immune, cardiovascular and nervous systems, etc. However, it has...
Peptides have been acclaimed as the drugs of the future, thanks to their high specificity and activity, as well as their easy degradation. This implies that they generally possess reduced toxicity, few secondary effects, and are thus administered in small doses. Peptides possess multiple therapeutic applications, which include: antivirals, antifungals, antibiotics, modulators of the immune, cardiovascular and nervous systems, etc. However, it has been demonstrated that therapeutically relevant peptides generally exhibit limited capacity to diffuse across biomembranes such as the human gastrointestinal epithelium, in addition to their low stability. Moreover, due the short plasmatic half-life and low stability of these peptides, they are administered through injections, often several times a day. It is essential to develop methods for modeling the bioactivity of peptides, predict their pharmacokinetic profiles and ultimately allow for the design of novel peptide chains adapted to predetermined bioactivity profiles. Such modeling systems will allow for the design of peptides with favorable therapeutic efficacy, and above all, ensure their adequate bioavailability and (preferably oral) administration.Based on this background, the objectives of PeptiMOL are:•Define parameters (numerical molecular descriptors) for characterizing the structural, compositional and physicochemical properties of peptides and develop a user-friendly Java-based tool for their computation. •Construct mathematical models to predict the PK properties of peptides using the state of the art statistical and machine learning techniques. •Implement the developed models in a Java-based chemoinformatic platform which will enable potential end-users to virtually screen peptide libraries or design novel peptide structures with desirable physicochemical and PK profiles.
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Ambito
Comunidad autónoma: Se buscaba un proyecto en cooperación con un partner de CCAA especificas.
Este proyecto fue tramitado con éxito!.