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Virtual Combinatorial Synthesis and Drug Design
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Virtual Combinatorial Synthesis and Drug Design

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Physical Chemistry, Theoretical and Computational Chemistry".

Deadline for manuscript submissions: closed (31 August 2006) | Viewed by 36616

Special Issue Editors

Dr. Jesus Vicente De Julián Ortiz

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Guest Editor
Department of Physical Chemistry, Faculty of Pharmacy, University of Valencia, Av. Vicent Andrés Estellés, 0, 46100 Burjassot, Valencia, Spain
Interests: molecular topology; topological indices; drug design; virtual combinatorial synthesis; virtual screening; linear models; QSAR; statistical validation; antituberculosis; antimalarial; antialzheimer; antineoplastic; telomerase inhibitors; insecticides; 5-HT receptors ligands; interaction SDA-zeolite; microporous oxides modeling; templating
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hongjun Liang

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Assistant Guest Editor
Department of Cell Physiology & Molecular Biophysics, Center for Membrane Protein Research, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
Interests: antimicrobial; membrane proteins; cancer therapy; drug delivery

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Published Papers (3 papers)

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Article
Understanding the Selectivity Mechanism of the Human Asialoglycoprotein Receptor (ASGP-R) toward Gal- and Man- type Ligands for Predicting Interactions with Exogenous Sugars
by Ilaria Massarelli, Laura Murgia, Anna Maria Bianucci, Federica Chiellini and Emo Chiellini
Int. J. Mol. Sci. 2007, 8(1), 13-28; https://doi.org/10.3390/i8010013 - 29 Jan 2007
Cited by 8 | Viewed by 11380
Abstract
A practical approach for addressing the computer simulation of protein-carbohydrate interactions is described here. An articulated computational protocol was setup and validated by checking its ability to predict experimental data, available in theliterature, and concerning the selectivity shown by the Carbohydrate Recognition Domain(CRD) [...] Read more.
A practical approach for addressing the computer simulation of protein-carbohydrate interactions is described here. An articulated computational protocol was setup and validated by checking its ability to predict experimental data, available in theliterature, and concerning the selectivity shown by the Carbohydrate Recognition Domain(CRD) of the human asialoglycoprotein receptor (ASGP-R) toward Gal-type ligands. Somerequired features responsible for the interactions were identified. Subsequently the sameprotocol was applied to monomer sugar molecules that constitute the building blocks foralginates and ulvans. Such sugar polymers may supply a low-cost source of rare sugars witha potential impact on several industrial applications, from pharmaceutical to fine chemicalindustry. An example of their applicative exploitation could be given by their use indeveloping biomaterial with adhesion properties toward hepatocytes, through interactionwith the ASGP-R. Such a receptor has been already proposed as a target for exogenousmolecules, specifically in the case of hepatocytes, for diagnostic and therapeutic purposes.The DOCK5.2 program was used to search optimal locations of the above ligands of interestinto CRD binding site and to roughly estimate interaction energies. Finally, the binding ∆G oftheoretical protein-ligand complexes was estimated by using the DelPhi program in which thesolvation free energy is accounted for with a continuum solvent model, by solving the Poisson-Boltzmann equation. The structure analysis of the obtained complexes and their ∆G values suggest that one of the sugar monomers of interest shows the desired characteristics. Full article
(This article belongs to the Special Issue Virtual Combinatorial Synthesis and Drug Design)
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Article
Internal Test Sets Studies in a Group of Antimalarials
by J. V. De Julián-Ortiz and E. Besalú
Int. J. Mol. Sci. 2006, 7(10), 456-468; https://doi.org/10.3390/i8200456 - 31 Oct 2006
Cited by 5 | Viewed by 9986
Abstract
Topological indices have been applied to build QSAR models for a set of 20 an-timalarial cyclic peroxy cetals. In order to evaluate the reliability of the proposed linearmodels leave-n-out and Internal Test Sets (ITS) approaches have been considered. The pro-posed procedure resulted in [...] Read more.
Topological indices have been applied to build QSAR models for a set of 20 an-timalarial cyclic peroxy cetals. In order to evaluate the reliability of the proposed linearmodels leave-n-out and Internal Test Sets (ITS) approaches have been considered. The pro-posed procedure resulted in a robust and consensued prediction equation and here it isshown why it is superior to the employed standard cross-validation algorithms involvingmultilinear regression models. Full article
(This article belongs to the Special Issue Virtual Combinatorial Synthesis and Drug Design)
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Review

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Review
In Silico Design in Homogeneous Catalysis Using Descriptor Modelling
by Enrico Burello and Gadi Rothenberg
Int. J. Mol. Sci. 2006, 7(9), 375-404; https://doi.org/10.3390/i7090375 - 28 Sep 2006
Cited by 73 | Viewed by 14728
Abstract
This review summarises the state-of-the-art methodologies used for designing homogeneous catalysts and optimising reaction conditions (e.g. choosing the right solvent). We focus on computational techniques that can complement the current advances in high-throughput experimentation, covering the literature in the period 1996-2006. The review [...] Read more.
This review summarises the state-of-the-art methodologies used for designing homogeneous catalysts and optimising reaction conditions (e.g. choosing the right solvent). We focus on computational techniques that can complement the current advances in high-throughput experimentation, covering the literature in the period 1996-2006. The review assesses the use of molecular modelling tools, from descriptor models based on semiempirical and molecular mechanics calculations, to 2D topological descriptors and graph theory methods. Different techniques are compared based on their computational and time cost, output level, problem relevance and viability. We also review the application of various data mining tools, including artificial neural networks, linear regression, and classification trees. The future of homogeneous catalysis discovery and optimisation is discussed in the light of these developments. Full article
(This article belongs to the Special Issue Virtual Combinatorial Synthesis and Drug Design)
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