MedusaScore: An Accurate Force Field-Based Scoring Function for Virtual Drug Screening

Yin, Shuangye; Biedermannová, Lada; Vondrášek, Jiřı́; Dokholyan, Nikolay V.

doi:10.1021/ci8001167

Cited by 177 publications

(227 citation statements)

References 49 publications

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“…Empirical Knowledge-Based DOCK [32] AutoDock [34] SMoG [82] AutoDock [34] GlideScore [37] DrugScore [62] GoldScore [35] ChemScore [60] PMF_Score [83] ICM [46] X_Score [66] MotifScore [84] LigandFit [47] F_Score [73] RF_Score [85] Molegro Virtual Docker [48] Fresno [75] PESD_SVM [86] SYBYL_G-Score [73] SCORE [76] PoseScore [87] SYBYL_D-Score [73] LUDI [77] MedusaScore [74] SFCscore [78] HYDE [79] LigScore [80] PLP [81] …”

Section: Force-field-basedmentioning

confidence: 99%

Molecular Docking and Structure-Based Drug Design Strategies

et al. 2015

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Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets. This approach also estimates the ligand-receptor binding free energy by evaluating critical phenomena involved in the intermolecular recognition process. Today, as a variety of docking algorithms are available, an understanding of the advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this review is to examine current molecular docking strategies used in drug discovery and medicinal chemistry, exploring the advances in the field and the role played by the integration of structure-and ligand-based methods.

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Section: Force-field-basedmentioning

confidence: 99%

Molecular Docking and Structure-Based Drug Design Strategies

et al. 2015

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“…The terms on the right side of Equation 2 were determined with Medusa using structural models of the closed and open states of WT and mutant RyR1. In the case of homology models, such calculations are good predictors of the net effect of mutation (stabilization or destabilization), but the magnitude of ⌬⌬G is not highly accurate (40). Thus, in this study, we used the ⌬⌬G values to predict if there will be an increase or decrease in P o of mutant channels, but not the extent of change in P o .…”

Section: Wtmentioning

confidence: 99%

Structural Determinants of Skeletal Muscle Ryanodine Receptor Gating*

Ramachandran

Chakraborty

et al. 2013

Journal of Biological Chemistry

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Background: The molecular basis of calcium release by ryanodine receptors (RyRs) is incompletely understood. Results: Mutations predicted by a computational model alter Ca 2ϩ -dependent single RyR channel activity. Conclusion: An interface between a pore-lining helix and a linker helix has a critical role in RyR channel gating. Significance: The results provide new insights into how RyR activity is regulated by Ca 2ϩ .

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“…Gohlke et al 61 and Velec et al 80 have also reported that DrugScore shows better ranking than the scoring functions within the docking programs. Furthermore, a recent study Dokholyan and colleagues 81 showed that the success rate of their docking results was improved to 85% by consensus scoring with DrugScore for a docking decoy set consisting of 100 complexes. Likewise, our binding affinities got improved by rescoring the lowest energy pose by DrugScore.…”

Section: Assessing the Scoring Accuracy With Drugscorementioning

confidence: 99%

A flexible docking scheme to explore the binding selectivity of PDZ domains

Gerek

Ozkan

2010

Protein Science

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Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å . We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

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MedusaScore: An Accurate Force Field-Based Scoring Function for Virtual Drug Screening

Cited by 177 publications

References 49 publications

Molecular Docking and Structure-Based Drug Design Strategies

Molecular Docking and Structure-Based Drug Design Strategies

Structural Determinants of Skeletal Muscle Ryanodine Receptor Gating*

A flexible docking scheme to explore the binding selectivity of PDZ domains

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