Assessing the Quality of in Silico Produced Biomolecules: The Discovery of a New Conformer

Insights into co-amorphous systems in therapeutic drug delivery

Co-amorphous (CAM) systems are promising drug-delivery systems in the arena of therapeutic drug delivery, addressing the poor aqueous solubility of drugs by enhancing solubility and thereby improving the oral bioavailability and therapeutic effect of the drug. A CAM system is a single-phase homogeneous blend of two or more low molecular weight molecules that can be drug–drug or drug–co-former, stabilized via intermolecular interactions, adding the benefit of thermodynamic stability. This review covers the fundamentals of CAM systems and recent advances in formulation development. In particular, we strive to address the theoretical, molecular, technical and biopharmaceutical aspects, advantages over polymeric amorphous solid dispersions, mechanisms of stabilization of amorphous forms, insights into unexplored in silico tools in excipient selection and regulatory viewpoints.

Aptamers Which Target Proteins: What Proteotronics Suggests to Pharmaceutics

Aptamers represent a challenging field of research, relevant for diagnosis in macular degeneration, cancer, thrombosis and many inflammatory diseases, and promising in drug discovery and development. Their selection is currently performed by a stable in vitro technology, namely, SELEX. Furthermore, computationalstatistical tools have been developed to complement the SELEX selection; they work both in the preliminary stage of selection, by designing high affinity aptamers for the assigned target, and also in the final stage, analyzing the features of the best performers to implement the selection technique further. A massive use of the in silico approach is, at present, only restricted by the limited knowledge of the specific aptamer-target topology. Actually, only about fifty X-ray structures of aptamer-protein complexes have been experimentally resolved, highlighting how this knowledge has to be improved. The structure of biomolecules like aptamer-protein complexes can be represented by networks, from which several parameters can be extracted. This work briefly reviews the literature, discussing if and how general network parameters in the framework of Proteotronics and graph theory (such as electrical features, link number, free energy change, and assortativity), are important in characterizing the complexes, anticipating some features of the biomolecules. To better explain this topic, a case-study is proposed, constituted by a set of anti-angiopoietin (Ang2) aptamers, whose performances are known from the experiments, and for which two different types of conformers were predicted. A topological indicator is proposed, named Möbius (M), which combines local and global information, and seems able to discriminate between the two possible types of conformers, so that it can be considered as a useful complement to the in vitro screening for pharmaceutical aims.

Biosensing Cytokine IL-6: A Comparative Analysis of Natural and Synthetic Receptors

Cytokines are a family of proteins which play a major role in the regulation of the immune system and the development of several diseases, from rheumatoid arthritis to cancer and, more recently, COVID-19. Therefore, many efforts are currently being developed to improve therapy and diagnosis, as well as to produce inhibitory drugs and biosensors for a rapid, minimally invasive, and effective detection. In this regard, even more efficient cytokine receptors are under investigation. In this paper we analyze a set of IL-6 cytokine receptors, investigating their topological features by means of a theoretical approach. Our results suggest a topological indicator that may help in the identification of those receptors having the highest complementarity with the protein, a feature expected to ensure a stable binding. Furthermore, we propose and discuss the use of these receptors in an idealized experimental setup.

Computational predictive approaches for interaction and structure of aptamers

Aptamers are short single-strand sequences that can bind to their specific targets with high affinity and specificity. Usually, aptamers are selected experimentally via systematic evolution of ligands by exponential enrichment (SELEX), an evolutionary process that consists of multiple cycles of selection and amplification. The SELEX process is expensive, time-consuming, and its success rates are relatively low. To overcome these difficulties, in recent years, several computational techniques have been developed in aptamer sciences that bring together different disciplines and branches of technologies. In this paper, a complementary review on computational predictive approaches of the aptamer has been organized. Generally, the computational prediction approaches of aptamer have been proposed to carry out in two main categories: interaction-based prediction and structure-based predictions. Furthermore, the available software packages and toolkits in this scope were reviewed. The aim of describing computational methods and tools in aptamer science is that aptamer scientists might take advantage of these computational techniques to develop more accurate and more sensitive aptamers.