Looking for Missing Proteins

Jabeen, Amara; Mohamedali, Abidali; Ranganathan, Shoba

doi:10.1016/b978-0-12-809633-8.20167-2

Cited by 4 publications

(10 citation statements)

References 117 publications

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“…For OR1A1, molecular docking of ligands was performed with ICM software ( Abagyan et al, 1994 ). The binding pocket was predicted though ICMPocketFinder ( An et al, 2005 ) and selected based on the available mutagenesis data for all ORs ( Jabeen et al, 2019a ).…”

Section: Methodsmentioning

confidence: 99%

“…SBVS has also been used to find novel ligands for GPCRs ( Congreve et al, 2020 ) but unfortunately, only 91 GPCRs have experimentally resolved structures to date, according to GPCRdb statistics ( Munk et al, 2019 ) (as of 05.01.2021) with over 500 structures deposited in the Protein Data Bank (PDB) ( Berman et al, 2000 ). This sequence to structure gap is mainly because of the challenges associated with structure determination of GPCRs ( Baker et al, 2017 ; Jabeen et al, 2019a ). Among the challenges are difficulties in heterologous expression, lower stability, maintaining the structural integrity by embedding into the membrane-like environment, and the existence of multiple conformations ( Miyagi et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“…ORs are the largest superfamily of GPCRs and have no known experimental structure. Only 30 of 405 human ORs are currently known as proteins, with the rest regarded as “missing” proteins on account of insubstantial proteomic evidence ( Jabeen et al, 2019a ). ORs share low sequence identity with available GPCR structures.…”

Section: Introductionmentioning

confidence: 99%

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BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling

Jabeen

Vijayram

Ranganathan

2021

Front. Mol. Biosci.

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G protein-coupled receptors (GPCRs) are the largest family of membrane proteins with more than 800 members. GPCRs are involved in numerous physiological functions within the human body and are the target of more than 30% of the United States Food and Drug Administration (FDA) approved drugs. At present, over 400 experimental GPCR structures are available in the Protein Data Bank (PDB) representing 76 unique receptors. The absence of an experimental structure for the majority of GPCRs demand homology models for structure-based drug discovery workflows. The generation of good homology models requires appropriate templates. The commonly used methods for template selection are based on sequence identity. However, there exists low sequence identity among the GPCRs. Sequences with similar patterns of hydrophobic residues are often structural homologs, even with low sequence identity. Extending this, we propose a biophysical approach for template selection based principally on hydrophobicity correspondence between the target and the template. Our approach takes into consideration other relevant parameters, including resolution, similarity within the orthosteric binding pocket of GPCRs, and structure completeness, for template selection. The proposed method was implemented in the form of a free tool called Bio-GATS, to provide the user with easy selection of the appropriate template for a query GPCR sequence. Bio-GATS was successfully validated with recent published benchmarking datasets. An application to an olfactory receptor to select an appropriate template has also been provided as a case study.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling

Jabeen

Vijayram

Ranganathan

2021

Front. Mol. Biosci.

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“…Many reasons lie behind this limit. When looking for molecular proofs of the translation of known coding genes, roughly 11% of the expected proteome is still missing [17]. In addition to this, as discussed above, the number of individual proteoforms exceed by orders of magnitude of the number of expected proteins.…”

Section: Proteomicsmentioning

confidence: 99%

Proteomics and Metabolomics for Cystic Fibrosis Research

Liessi

Pedemonte

Armirotti

et al. 2020

IJMS

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The aim of this review article is to introduce the reader to the state-of-the-art of the contribution that proteomics and metabolomics sciences are currently providing for cystic fibrosis (CF) research: from the understanding of cystic fibrosis transmembrane conductance regulator (CFTR) biology to biomarker discovery for CF diagnosis. Our work particularly focuses on CFTR post-translational modifications and their role in cellular trafficking as well as on studies that allowed the identification of CFTR molecular interactors. We also show how metabolomics is currently helping biomarker discovery in CF. The most recent advances in these fields are covered by this review, as well as some considerations on possible future scenarios for new applications.

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“…However, they are not fully functionally characterized as yet in the majority of tissues, owing to difficulties associated with their heterologous functional expression ( Tsai et al., 2017 ). Also, the evidence for their ectopic expression is at the mRNA level and not at the protein level in several tissues ( Jabeen et al., 2019a ). Among their diversified functions in the human body are mediation of rennin secretion and blood pressure, negative chronotropic effect on fetal and adult heart, serotonin release within gut enterochromaffin cells, inducing melanocyte pigmentation and differentiation, and sperm migration ( Dalesio et al., 2018 ).…”

Section: Introductionmentioning

confidence: 99%

A two-stage computational approach to predict novel ligands for a chemosensory receptor

Jabeen

Vijayram

Ranganathan

2020

Current Research in Structural Biology

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Olfactory receptor (OR) 1A2 is the member of largest superfamily of G protein-coupled receptors (GPCRs). OR1A2 is an ectopically expressed receptor with only 13 known ligands, implicated in reducing hepatocellular carcinoma progression, with enormous therapeutic potential. We have developed a two-stage screening approach to identify novel putative ligands of OR1A2. We first used a pharmacophore model based on atomic property field (APF) to virtually screen a library of 5942 human metabolites. We then carried out structure-based virtual screening (SBVS) for predicting the potential agonists, based on a 3D homology model of OR1A2. This model was developed using a biophysical approach for template selection, based on multiple parameters including hydrophobicity correspondence, applied to the complete set of available GPCR structures to pick the most appropriate template. Finally, the membrane-embedded 3D model was refined by molecular dynamics (MD) simulations in both the apo and holo forms. The refined model in the apo form was selected for SBVS. Four novel small molecules were identified as strong binders to this olfactory receptor on the basis of computed binding energies.

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Looking for Missing Proteins

Cited by 4 publications

References 117 publications

BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling

BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling

Proteomics and Metabolomics for Cystic Fibrosis Research

A two-stage computational approach to predict novel ligands for a chemosensory receptor

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