DIRseq as a method for predicting drug-interacting residues of intrinsically disordered proteins from sequences

Intrinsically disordered proteins (IDPs) are now well-recognized as drug targets. Identifying drug-interacting residues is valuable for both optimizing compounds and elucidating the mechanism of action. Currently, NMR chemical shift perturbation and all-atom molecular dynamics (MD) simulations are the primary tools for this purpose. Here, we present DIRseq, a fast method for predicting drug-interacting residues from the amino-acid sequence. All residues contribute to the propensity of a particular residue to be drug-interacting; the contributing factor of each residue has an amplitude that is determined by its amino-acid type and attenuates with increasing sequence distance from the particular residue. DIRseq predictions match well with drug-interacting residues identified by NMR chemical shift perturbation and other methods, including residues L 22 WK 24 and Q 52 WFT 55 in the tumor suppressor protein p53. These successes augur well for deciphering the sequence code for IDP-drug binding. DIRseq is available as a web server at https://zhougroup-uic.github.io/DIRseq/ and has many applications, such as virtual screening against IDPs and designing IDP fragments for in-depth NMR and MD studies.

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Publication Details

Journal
eLife
Published
2025-10-07
DOI
https://doi.org/10.7554/elife.107470.3
Primary Topic
Protein Structure and Dynamics
Type
article
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article

DIRseq as a method for predicting drug-interacting residues of intrinsically disordered proteins from sequences

Huan‐Xiang Zhou, Sanbo Qin, Matt MacAinsh
eLife
Protein Structure and Dynamics
article

DIRseq as a method for predicting drug-interacting residues of intrinsically disordered proteins from sequences

Huan‐Xiang Zhou, Sanbo Qin, Matt MacAinsh
article en

Abstract

Intrinsically disordered proteins (IDPs) are now well-recognized as drug targets. Identifying drug-interacting residues is valuable for both optimizing compounds and elucidating the mechanism of action. Currently, NMR chemical shift perturbation and all-atom molecular dynamics (MD) simulations are the primary tools for this purpose. Here, we present DIRseq, a fast method for predicting drug-interacting residues from the amino-acid sequence. All residues contribute to the propensity of a particular residue to be drug-interacting; the contributing factor of each residue has an amplitude that is determined by its amino-acid type and attenuates with increasing sequence distance from the particular residue. DIRseq predictions match well with drug-interacting residues identified by NMR chemical shift perturbation and other methods, including residues L 22 WK 24 and Q 52 WFT 55 in the tumor suppressor protein p53. These successes augur well for deciphering the sequence code for IDP-drug binding. DIRseq is available as a web server at https://zhougroup-uic.github.io/DIRseq/ and has many applications, such as virtual screening against IDPs and designing IDP fragments for in-depth NMR and MD studies.

eLifeVol. 14
University of Illinois Chicago (US)
Openalex Percentile: Top 75%
Protein Structure and Dynamics
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DIRseq as a method for predicting drug-interacting residues of intrinsically disordered proteins from sequences — Huan‐Xiang Zhou, Sanbo Qin, et al. · eLife (2025) | TGRS Research Map | TGRS