DREAMweb: An online tool for graph-based modeling of NMR protein structure

Das, NR and Chaudhury, KN and Pal, D (2024) DREAMweb: An online tool for graph-based modeling of NMR protein structure. In: Proteomics .

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Abstract

The value of accurate protein structural models closely conforming to the experimental data is indisputable. DREAMweb deploys an improved DREAM algorithm, DREAMv2, that incorporates a tighter bound in the constraint set of the underlying optimization approach. This reduces the artifacts while modeling the protein structure by solving the distance-geometry problem. DREAMv2 follows a bottom-up strategy of building smaller substructures for regions with a larger concentration of experimental bounds and consolidating them before modeling the rest of the protein structure. This improves secondary structure conformance in the final models consistent with experimental data. The proposed method efficiently models regions with sparse coverage of experimental data by reducing the possibility of artifacts compared to DREAM. To balance performance and accuracy, smaller substructures ((Formula presented.) atoms) are solved in this regime, allowing faster builds for the other parts under relaxed conditions. DREAMweb is accessible as an internet resource. The improvements in results are showcased through benchmarks on 10 structures. DREAMv2 can be used in tandem with any NMR-based protein structure determination workflow, including an iterative framework where the NMR assignment for the NOESY spectra is incomplete or ambiguous. DREAMweb is freely available for public use at http://pallab.cds.iisc.ac.in/DREAM/ and downloadable at https://github.com/niladriranjandas/DREAMv2.git. © 2024 Wiley-VCH GmbH.

Item Type:	Journal Article
Publication:	Proteomics
Publisher:	John Wiley and Sons Inc
Additional Information:	The copyright for this article belongs to John Wiley and Sons Inc.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering Division of Interdisciplinary Sciences > Computational and Data Sciences Division of Interdisciplinary Sciences > Interdisciplinary Mathematical Sciences
Date Deposited:	29 Aug 2024 06:28
Last Modified:	29 Aug 2024 06:28
URI:	http://eprints.iisc.ac.in/id/eprint/84862

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