Learning Probabilistic Protein-DNA Recognition Codes from DNA-Binding Specificities Using Structural Mappings

Wetzel, Joshua; Zhang, Kaiqian; Singh, Mona

doi:10.1007/978-3-031-04749-7_29

Cited by 1 publication

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“…Computationally identifying which DNA sequence, a given protein will bind to remains a challenging question. Although proteins from certain DNA binding families, such as HDs 15,20,[54][55][56] and C2H2 ZFs [14][15][16]18,34,57 , have been studied extensively in this regard, a generalized model of binding specificity remains elusive. This complexity emanates, in part, from the pivotal role that the protein and DNA conformation or shape play in the context of binding specificity.…”

Section: Discussionmentioning

confidence: 99%

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DeepPBS: Geometric deep learning for interpretable prediction of protein–DNA binding specificity

Mitra,

Li,

Sagendorf

et al. 2023

Preprint

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Predicting specificity in protein-DNA interactions is a challenging yet essential task for understanding gene regulation. Here, we present Deep Predictor of Binding Specificity (DeepPBS), a geometric deep-learning model designed to predict binding specificity across protein families based on protein-DNA structures. The DeepPBS architecture allows investigation of different family-specific recognition patterns. DeepPBS can be applied to predicted structures, and can aid in the modeling of protein-DNA complexes. DeepPBS is interpretable and can be used to calculate protein heavy atom-level importance scores, demonstrated as a case-study on p53-DNA interface. When aggregated at the protein residue level, these scores conform well with alanine scanning mutagenesis experimental data. The inference time for DeepPBS is sufficiently fast for analyzing simulation trajectories, as demonstrated on a molecular-dynamics simulation of aDrosophilaHox-DNA tertiary complex with its cofactor. DeepPBS and its corresponding data resources offer a foundation for machine-aided protein-DNA interaction studies, guiding experimental choices and complex design, as well as advancing our understanding of molecular interactions.

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Section: Discussionmentioning

confidence: 99%

“…Predicting binding specificity for a given protein sequence, across protein families, remains a challenging and unsolved problem, despite progress for specific protein families [14][15][16][17][18][19][20][21] . Structural changes in the context of binding, along with large mechanistic diversity, contribute to the difficulty 22 .…”

Section: Introductionmentioning

confidence: 99%