High-Throughput parallel blind Virtual Screening using BINDSURF

Irene Sanchez-Linares, Horacio Perez-Sanchez, Jose M Cecilia, Jose M Garcia
Computer Engineering Department, School of Computer Science, University of Murcia, Spain
BMC Bioinformatics, 13(Suppl 14):S13, 2012


   title={High-Throughput parallel blind Virtual Screening using BINDSURF},

   author={S{‘a}nchez-Linares, I. and P{‘e}rez-S{‘a}nchez, H. and Cecilia, J.M. and Garc{‘i}a, J.M.},

   journal={BMC Bioinformatics},


   number={Suppl 14},



   publisher={BioMed Central Ltd}


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BACKGROUND: Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, usually derived from the interpretation of the protein crystal structure. However, it has been demonstrated that in many cases, diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. RESULTS: We present BINDSURF, a novel VS methodology that scans the whole protein surface in order to find new hotspots, where ligands might potentially interact with, and which is implemented in last generation massively parallel GPU hardware, allowing fast processing of large ligand databases. CONCLUSIONS: BINDSURF is an efficient and fast blind methodology for the determination of protein binding sites depending on the ligand, that uses the massively parallel architecture of GPUs for fast pre-screening of large ligand databases. Its results can also guide posterior application of more detailed VS methods in concrete binding sites of proteins, and its utilization can aid in drug discovery, design, repurposing and therefore help considerably in clinical research.
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