2019
DOI: 10.1038/s41598-019-41594-3
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Exponential consensus ranking improves the outcome in docking and receptor ensemble docking

Abstract: Consensus-scoring methods are commonly used with molecular docking in virtual screening campaigns to filter potential ligands for a protein target. Traditional consensus methods combine results from different docking programs by averaging the score or rank of each molecule obtained from individual programs. Unfortunately, these methods fail if one of the docking programs has poor performance, which is likely to occur due to training-set dependencies and scoring-function parameterization. In this work, we intro… Show more

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Cited by 121 publications
(144 citation statements)
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“…In the subsequent calculations, we used the relevant program of molecular dynamics, which can more accurately reflect the state of receptor-ligand complexes than molecular docking. It has proven to be able to study a wide range of phenomena related to simple and complex molecules [49]. In this study, the protein ligand complexes obtained from the molecular docking procedure were calculated by molecular dynamics.…”
Section: Discussionmentioning
confidence: 99%
“…In the subsequent calculations, we used the relevant program of molecular dynamics, which can more accurately reflect the state of receptor-ligand complexes than molecular docking. It has proven to be able to study a wide range of phenomena related to simple and complex molecules [49]. In this study, the protein ligand complexes obtained from the molecular docking procedure were calculated by molecular dynamics.…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, with molecular docking, it is 285 possible to screen and rank molecules from compound libraries. However, it has been 286 shown that the docking results might be system or structure dependent [43,70], possibly 287 due to algorithm-parameterization biases, which are trained over particular benchmark 288 systems. To overcome this limitation, we use a consensus strategy that combines the 289 results from different docking programs to obtain a consensus rank using a sum of 290 exponential functions (ECR method) [43].…”
Section: Ecr-docking: Exponential Consensus Ranking Of Docking Vs 280mentioning
confidence: 99%
“…However, it has been 286 shown that the docking results might be system or structure dependent [43,70], possibly 287 due to algorithm-parameterization biases, which are trained over particular benchmark 288 systems. To overcome this limitation, we use a consensus strategy that combines the 289 results from different docking programs to obtain a consensus rank using a sum of 290 exponential functions (ECR method) [43]. Below and in the Supplementary 291 Information, we explain different docking-scoring alternatives that we used to find the 292 optimal enrichment for the FMNAT-FADS ligand screening.…”
Section: Ecr-docking: Exponential Consensus Ranking Of Docking Vs 280mentioning
confidence: 99%
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