11. Nanobodies: towards rational design of immune-reagentsArio De Marco, 2017, published scientific conference contribution abstract (invited lecture) Abstract: Antibodies are irreplaceable reagents in both research and clinical practice. Despite their relevance, the structural complexity of conventional mono- and polyclonal antibodies (IgG) has always been a limit for their engineering towards reagents optimized for specific applications, such as in vivo diagnostics and therapy. Furthermore, their isolation is time consuming, their production expensive, and their functionalization results often in heterogeneous macromolecule populations. These drawbacks promoted the search for both innovative antibody isolation strategies and alternative scaffolds. In vitro panning of pre-immune collections of recombinant antibody fragments allows for the simple and fast recovery of binders. Since they did not undergo somatic maturation, their affinity for targets can be insufficient but on the other hand they can be rapidly mutated by standard molecular biology techniques to generate second-generation antibodies among which to identify clones with improved characteristics. Both stochastic and rational methods have been proposed for the optimization process. Random mutagenesis followed by panning at stringent conditions has been successful used to select binders with improved physical characteristics. Rational methods try to identify in silico key residues involved in the regulation of specific antibody features, such as stability or binding affinity. The accuracy of these methods usually depends on the calculation resources. In this perspective, smaller molecules can be analyzed “better” than larger because of their restricted number of residues. Nanobodies small dimensions have been long appreciated since enable better tissue penetration, shorter clearance time, higher yields. Now it becomes evident that this characteristic makes them also optimal objects for modeling.
Keywords: recombinant antibody modeling, nanobody engineering, molecular dynamics and docking
Published in RUNG: 21.03.2018; Views: 4874; Downloads: 0
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14. From Trajectory Modeling to Social Habits and Behaviors AnalysisDonatella Gubiani, Marco Pavan, 2016, independent scientific component part or a chapter in a monograph Abstract: In recent years, the widespread of mobile devices has made easier and popular the activities of recording locations visited by users and of inferring their trajectories. The availability of such large amount of spatio-temporal data opens new challenges to automatically extract information and get valuable knowledge. The many aspects of this issue have aroused the interest of researchers in several areas, such as information retrieval, data mining, context-aware computing, security and privacy issues, urban planning, and transport management. Recently, there has been a strong interest in understanding how people move during their common daily activities in order to get information about their behaviors and habits. In this paper we describe considerable recent research works related to the analysis of mobile spatio-temporal data, focusing on the study of social habits and behaviors. We provide a general perspective on studies on human mobility by depicting and comparing methods and algorithms, highlighting some critical issues related to information extraction from spatio-temporal data, and future research directions.
Keywords: Trajectory modeling, Social habits and behaviors, Spatio-temporal data, Data mining
Published in RUNG: 18.11.2016; Views: 4997; Downloads: 0
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15. Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodiesMiguel Soler, Ario De Marco, Sara Fortuna, 2016, original scientific article Abstract: Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular
recognition. Their small size represents a precious advantage for rational mutagenesis based on
modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate
mutations by developing a simulation protocol based on all-atom molecular dynamics and wholemolecule
docking. The method was tested on two sets of nanobodies characterized experimentally
for their biophysical features. One set contained point mutations introduced to humanize a wild type
sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae
and human hallmarks. The method resulted in accurate scoring approaches to predict experimental
yields and enabled to identify the structural modifications induced by mutations. This work is a
promising tool for the in silico development of single-domain antibodies and opens the opportunity to
customize single functional domains of larger macromolecules
Keywords: nanobodies, molecular dynamics, modeling, antibody solubility
Published in RUNG: 11.10.2016; Views: 5005; Downloads: 245
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