iBioProVis: interactive visualization and analysis of compound bioactivity space

Date

2020-08-15

Author

Dönmez, Ataberk
Rifaioğlu, Ahmet Süreyya
Atalay, Rengül
Atalay, Mehmet Volkan

Metadata

Show full item record

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

Item Usage Stats

254
views

0
downloads

SUMMARY: iBioProVis is an interactive tool for visual analysis of the compound bioactivity space in the context of target proteins, drugs and drug candidate compounds. iBioProVis tool takes target protein identifiers and, optionally, compound SMILES as input, and uses the state-of-the-art non-linear dimensionality reduction method t-Distributed Stochastic Neighbor Embedding (t-SNE) to plot the distribution of compounds embedded in a 2D map, based on the similarity of structural properties of compounds and in the context of compounds' cognate targets. Similar compounds, which are embedded to proximate points on the 2D map, may bind the same or similar target proteins. Thus, iBioProVis can be used to easily observe the structural distribution of one or two target proteins' known ligands on the 2D compound space, and to infer new binders to the same protein, or to infer new potential target(s) for a compound of interest, based on this distribution. Principal component analysis (PCA) projection of the input compounds is also provided, Hence the user can interactively observe the same compound or a group of selected compounds which is projected by both PCA and embedded by t-SNE. iBioProVis also provides detailed information about drugs and drug candidate compounds through cross-references to widely used and well-known databases, in the form of linked table views. Two use-case studies were demonstrated, one being on angiotensin-converting enzyme 2 (ACE2) protein which is Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Spike protein receptor. ACE2 binding compounds and seven antiviral drugs were closely embedded in which two of them have been under clinical trial for Coronavirus disease 19 (COVID-19). AVAILABILITY AND IMPLEMENTATION: iBioProVis and its carefully filtered dataset are available at https://ibpv.kansil.org/ for public use. CONTACT: vatalay@metu.edu.tr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Subject Keywords

Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications

URI

https://hdl.handle.net/11511/57127

Journal

Bioinformatics (Oxford, England)

DOI

https://doi.org/10.1093/bioinformatics/btaa496

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

GLANET: genomic loci annotation and enrichment tool Otlu, Burcak; Firtina, Can; Keles, Sunduz; Tastan, Oznur (Oxford University Press (OUP), 2017-09-15) Motivation: Genomic studies identify genomic loci representing genetic variations, transcription factor (TF) occupancy, or histone modification through next generation sequencing (NGS) technologies. Interpreting these loci requires evaluating them with known genomic and epigenomic annotations.
Integrated search and alignment of protein structures Sacan, Ahmet; Toroslu, İsmail Hakkı; Ferhatosmanoglu, Hakan (Oxford University Press (OUP), 2008-12-15) Motivation: Identification and comparison of similar three-dimensional (3D) protein structures has become an even greater challenge in the face of the rapidly growing structure databases. Here, we introduce Vorometric, a new method that provides efficient search and alignment of a query protein against a database of protein structures. Voronoi contacts of the protein residues are enriched with the secondary structure information and a metric substitution matrix is developed to allow efficient indexing. The ...
Implicit motif distribution based hybrid computational kernel for sequence classification Atalay, Mehmet Volkan (Oxford University Press (OUP), 2005-04-15) Motivation: We designed a general computational kernel for classification problems that require specific motif extraction and search from sequences. Instead of searching for explicit motifs, our approach finds the distribution of implicit motifs and uses as a feature for classification. Implicit motif distribution approach may be used as modus operandi for bioinformatics problems that require specific motif extraction and search, which is otherwise computationally prohibitive.
RBPSponge: genome-wide identification of lncRNAs that sponge RBPs HafezQorani, Saber; Houdjedj, Aissa; Arici, Mehmet; Said, Abdesselam; KAZAN, HİLAL (Oxford University Press (OUP), 2019-11-15) The Summary: Long non-coding RNAs (lncRNAs) can act as molecular sponge or decoys for an RNA-binding protein (RBP) through their RBP-binding sites, thereby modulating the expression of all target genes of the corresponding RBP of interest. Here, we present a web tool named RBPSponge to explore lncRNAs based on their potential to act as a sponge for an RBP of interest. RBPSponge identifies the occurrences of RBP-binding sites and CLIP peaks on lncRNAs, and enables users to run statistical analyses to investi...
iBioProVis: Interactive Visualization and Analysis of Compound Bioactivity Space Dönmez, Ataberk; Rifaioğlu, Ahmet Süreyya; Acar, Aybar Can; Doğan, Tunca; Martin, Maria Jesus; Atalay, Rengül; Atalay, Mehmet Volkan (2019-07-21) Visualization and interpretation of high-dimensional chemical compound and target space is critical for better understanding of the mechanisms of bioactivity space and drug discovery process. Here, we describe iBioProVis, which projects and visualizes compounds on 2D space based on their structural features in the context of their cognate targets. The inputs are pairs of ChEMBL target identifiers and the output is the 2D projection plot of the active compounds of the input targets. By looking ...

Citation Formats

A. Dönmez, A. S. Rifaioğlu, R. Atalay, and M. V. Atalay, “iBioProVis: interactive visualization and analysis of compound bioactivity space,” Bioinformatics (Oxford, England), pp. 4227–4230, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57127.