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1.
2.
Computational design of customised nanobodies for biotechnological applications
Sara Fortuna, Ario de Marco, Miguel Soler, 2016, unpublished conference contribution

Abstract: In silico modeling to improve the biophysical characteristics of recombinant single-domain antibodies
Found in: ključnih besedah
Summary of found: ...In silico modeling to improve the biophysical characteristics of recombinant...
Keywords: nanobodies, modeling, protein stability, antibody humanization, molecular dynamics
Published: 26.04.2016; Views: 1532; Downloads: 0
.pdf Fulltext (2,42 MB)

3.
From Trajectory Modeling to Social Habits and Behaviors Analysis
Donatella 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.
Found in: ključnih besedah
Keywords: Trajectory modeling, Social habits and behaviors, Spatio-temporal data, Data mining
Published: 18.11.2016; Views: 1864; Downloads: 0
.pdf Fulltext (652,73 KB)

4.
Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies
Ario de Marco, Miguel Soler, 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
Found in: ključnih besedah
Summary of found: ...nanobodies, molecular dynamics, modeling, antibody solubility...
Keywords: nanobodies, molecular dynamics, modeling, antibody solubility
Published: 11.10.2016; Views: 1613; Downloads: 149
.pdf Fulltext (1,95 MB)

5.
Is there an approach for optimizing the specific binding of antibodies to target cells?
Ario De Marco, invited lecture at foreign university

Found in: ključnih besedah
Summary of found: ...Nanobodies, avidity, modeling, off-target accumulation...
Keywords: Nanobodies, avidity, modeling, off-target accumulation
Published: 31.01.2017; Views: 1350; Downloads: 0
.pdf Fulltext (81,48 KB)

6.
Nanobodies: towards rational design of immune-reagents
Ario 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.
Found in: ključnih besedah
Keywords: recombinant antibody modeling, nanobody engineering, molecular dynamics and docking
Published: 21.03.2018; Views: 1305; Downloads: 0
.pdf Fulltext (638,20 KB)

7.
Binding affinity prediction of nanobody–protein complexes by scoring of molecular dynamics trajectories
Miguel Soler, Sara Fortuna, Ario de Marco, Alessandro Laio, 2018, original scientific article

Found in: ključnih besedah
Summary of found: ...in silico modeling, nanobodies, binding affinity prediction...
Keywords: in silico modeling, nanobodies, binding affinity prediction
Published: 15.01.2018; Views: 1019; Downloads: 0
.pdf Fulltext (2,45 MB)

8.
9.
Nanobodies isolated from pre-immune libraries as tunable biotechnological tools
Ario de Marco, invited lecture at foreign university

Found in: ključnih besedah
Keywords: nanobodies, panning, modeling
Published: 27.02.2020; Views: 113; Downloads: 0
.pdf Fulltext (61,23 KB)

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