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      Nanoinformatics: an emerging area of information technology at the intersection of bioinformatics, computational chemistry and nanobiotechnology

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          Abstract

          After the progress made during the genomics era, bioinformatics was tasked with supporting the flow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fields. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent field. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientific fields, such as bioinformatics and computational chemistry.

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          Comparative protein modelling by satisfaction of spatial restraints.

          We describe a comparative protein modelling method designed to find the most probable structure for a sequence given its alignment with related structures. The three-dimensional (3D) model is obtained by optimally satisfying spatial restraints derived from the alignment and expressed as probability density functions (pdfs) for the features restrained. For example, the probabilities for main-chain conformations of a modelled residue may be restrained by its residue type, main-chain conformation of an equivalent residue in a related protein, and the local similarity between the two sequences. Several such pdfs are obtained from the correlations between structural features in 17 families of homologous proteins which have been aligned on the basis of their 3D structures. The pdfs restrain C alpha-C alpha distances, main-chain N-O distances, main-chain and side-chain dihedral angles. A smoothing procedure is used in the derivation of these relationships to minimize the problem of a sparse database. The 3D model of a protein is obtained by optimization of the molecular pdf such that the model violates the input restraints as little as possible. The molecular pdf is derived as a combination of pdfs restraining individual spatial features of the whole molecule. The optimization procedure is a variable target function method that applies the conjugate gradients algorithm to positions of all non-hydrogen atoms. The method is automated and is illustrated by the modelling of trypsin from two other serine proteinases.
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            The Amber biomolecular simulation programs.

            We describe the development, current features, and some directions for future development of the Amber package of computer programs. This package evolved from a program that was constructed in the late 1970s to do Assisted Model Building with Energy Refinement, and now contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates. (c) 2005 Wiley Periodicals, Inc.
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              Evaluation of comparative protein modeling by MODELLER.

              We evaluate 3D models of human nucleoside diphosphate kinase, mouse cellular retinoic acid binding protein I, and human eosinophil neurotoxin that were calculated by MODELLER, a program for comparative protein modeling by satisfaction of spatial restraints. The models have good stereochemistry and are at least as similar to the crystallographic structures as the closest template structures. The largest errors occur in the regions that were not aligned correctly or where the template structures are not similar to the correct structure. These regions correspond predominantly to exposed loops, insertions of any length, and non-conserved side chains. When a template structure with more than 40% sequence identity to the target protein is available, the model is likely to have about 90% of the mainchain atoms modeled with an rms deviation from the X-ray structure of approximately 1 A, in large part because the templates are likely to be that similar to the X-ray structure of the target. This rms deviation is comparable to the overall differences between refined NMR and X-ray crystallography structures of the same protein.
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                Author and article information

                Journal
                bres
                Biological Research
                Biol. Res.
                Sociedad de Biología de Chile (Santiago, , Chile )
                0716-9760
                2011
                : 44
                : 1
                : 43-51
                Affiliations
                [02] orgnameUniversidad de Chile orgdiv1Facultad de Ciencias Físicas y Matemáticas orgdiv2Centro de Modelamiento Matemático Chile
                [03] Frederick Maryland orgnameNational Cancer Institute orgdiv1Science Applications International Corporation orgdiv2Advanced Structure Analysis Collaboratory USA
                [01] Talca orgnameUniversidad de Talca Chile
                Article
                S0716-97602011000100006 S0716-9760(11)04400106
                10.4067/S0716-97602011000100006
                fe2c4c0f-bf16-490f-83a8-ca39ace7a7eb

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 09 April 2010
                : 05 October 2010
                : 16 December 2010
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 97, Pages: 9
                Product

                SciELO Chile

                Categories
                Articles

                nanobiotechnology,Bioinformatics,molecular simulation,nanoinformatics,nanomedicine

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