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bioRxiv · 10.1101/2025.02.18.638856

BENDER DB: a database of protein binding sites across neglected disease proteomes

Paiva, V.·Pires, D. E. V.·Bressan, G.·Izidoro, S.·Silveira, S.
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Abstract

Identifying binding sites is crucial for expanding our knowledge of various biological processes, supporting drug discovery, and repositioning strategies, particularly in the early research phases of target hopping. This is especially important for neglected diseases, which predominantly impact vulnerable populations in developing regions. To address this, we created BENDER DB, a database designed to map predicted protein binding sites within the proteomes of pathogens associated with neglected diseases. Utilizing AlphaFold-predicted structures, BENDER DB integrates results from five leading binding site prediction tools, resulting in over one million binding sites across over 100,000 proteins from 10 different proteomes. BENDER DB offers unique features, such as integrating multiple predictors, interactive visualization tools, and comprehensive graphical representations, allowing for a detailed visual comparative analysis of different prediction methods and the predicted binding sites. We combined the computational approaches to offer a consensus of binding site predictions, leveraging the strengths of multiple techniques. Additionally, we introduce BENDER AI, a meta-predictor that combines the outputs of the predictors to provide a unified binding site classification. BENDER AI outperformed all individual methods in 4 out of 5 evaluated metrics. Specifically, it achieved an MCC of 0.64 and an AUC of 0.89, surpassing the highest MCC of 0.63 and the highest AUC of 0.84 obtained by individual predictors, demonstrating strong performance and effectiveness in supporting binding site prediction. By consolidating these results, BENDER DB enables detailed comparative analyses of prediction methods and integrates interactive visualization tools to provide users with an intuitive platform for binding site exploration. The database aims to accelerate drug discovery efforts, particularly in underdeveloped regions, by providing a robust and detailed resource for studying protein binding sites. BENDER DB is available at https://benderdb.ufv.br.

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Paiva, V., Pires, D. E. V., Bressan, G., Izidoro, S., Silveira, S.. 2025-02-23. BENDER DB: a database of protein binding sites across neglected disease proteomes. https://doi.org/10.1101/2025.02.18.638856

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