53,748 research outputs found
A bibliometric analysis of the Journal of Molecular Graphics and Modelling
This paper reviews the articles published in Volumes 2-24 of the Journal of Molecular Graphics and Modelling (formerly the Journal of Molecular Graphics), focusing on the changes that have occurred in the subject over the years, and on the most productive and most cited authors and institutions. The most cited papers are those describing systems or algorithms, but the proportion of these types of article is decreasing as more applications of molecular graphics and molecular modelling are reported
The Journal of Computer-Aided Molecular Design: a bibliometric note
Summarizes the articles in, and the citations to, volumes 2-24 of the Journal of Computer-Aided Molecular Design. The citations to the journal come from almost 2000 different sources that span a very wide range of academic subjects, with the most heavily cited articles being descriptions of software systems and of computational methods
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Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose.
We introduce the QuanSA method for inducing physically meaningful field-based models of ligand binding pockets based on structure-activity data alone. The method is closely related to the QMOD approach, substituting a learned scoring field for a pocket constructed of molecular fragments. The problem of mutual ligand alignment is addressed in a general way, and optimal model parameters and ligand poses are identified through multiple-instance machine learning. We provide algorithmic details along with performance results on sixteen structure-activity data sets covering many pharmaceutically relevant targets. In particular, we show how models initially induced from small data sets can extrapolatively identify potent new ligands with novel underlying scaffolds with very high specificity. Further, we show that combining predictions from QuanSA models with those from physics-based simulation approaches is synergistic. QuanSA predictions yield binding affinities, explicit estimates of ligand strain, associated ligand pose families, and estimates of structural novelty and confidence. The method is applicable for fine-grained lead optimization as well as potent new lead identification
Repurposing designed mutants: a valuable strategy for computer-aided laccase engineering – the case of POXA1b
The broad specificity of laccases, a direct consequence of their shallow binding site, makes this class of enzymes a suitable template to build specificity toward putative substrates. In this work, a computational methodology that accumulates beneficial interactions between the enzyme and the substrate in productive conformations is applied to oxidize 2,4-diamino-benzenesulfonic acid with POXA1b laccase. Although the experimental validation of two designed variants yielded negative results, most likely due to the hard oxidizability of the target substrate, molecular simulations suggest that a novel polar binding scaffold was designed to anchor negatively charged groups. Consequently, the oxidation of three such molecules, selected as representative of different classes of substances with different industrial applications, significantly improved. According to molecular simulations, the reason behind such an improvement lies in the more productive enzyme–substrate binding achieved thanks to the designed polar scaffold. In the future, mutant repurposing toward other substrates could be first carried out computationally, as done here, testing molecules that share some similarity with the initial target. In this way, repurposing would not be a mere safety net (as it is in the laboratory and as it was here) but rather a powerful approach to transform laccases into more efficient multitasking enzymes.This work was funded by INDOX (KBBE-2013-7-613549) European project and CTQ2013-48287-R Spanish National Project.
V. G. and E. M. acknowledge UniversitĂ degli Studi di Napoli and Generalitat de Catalunya for their respective predoctoral fellowships.Peer ReviewedPostprint (author's final draft
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