A Reliable and Accurate Solution to the Induced Fit Docking Problem for Protein-Ligand Binding

Miller, Edward B.; Murphy, Robert C.; Sindhikara, Daniel J.; Borrelli, Ken; Grisewood, Matthew J.; Ranalli, F.; Dixon, S.; Jerome, Steven V.; Boyles, Nicholas A.; Day, Tyler; Ghanakota, Phani; Mondal, Sayan; Rafi, Salma B.; Troast, Dawn M.; Abel, Robert; Friesner, Richard A.

doi:10.26434/chemrxiv.11983845

Cited by 22 publications

(39 citation statements)

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“…Free G4 structures often do not resemble the bound G4 structures because flexible flanking and loop regions adopt different arrangements upon ligand binding, as shown for the binding of epiberberine to a non-parallel telomeric G4 structure [ 47 ]. Docking against such a ligand-induced bound conformation needs to consider receptor rearrangement, which is a major challenge and an active area of research [ 48 ].…”

Section: Resultsmentioning

confidence: 99%

Evaluating Molecular Docking Software for Small Molecule Binding to G-Quadruplex DNA

Dickerhoff

Warnecke

Wang

et al. 2021

IJMS

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G-quadruplexes are four-stranded nucleic acid secondary structures of biological significance and have emerged as an attractive drug target. The G4 formed in the MYC promoter (MycG4) is one of the most studied small-molecule targets, and a model system for parallel structures that are prevalent in promoter DNA G4s and RNA G4s. Molecular docking has become an essential tool in structure-based drug discovery for protein targets, and is also increasingly applied to G4 DNA. However, DNA, and in particular G4, binding sites differ significantly from protein targets. Here we perform the first systematic evaluation of four commonly used docking programs (AutoDock Vina, DOCK 6, Glide, and RxDock) for G4 DNA-ligand binding pose prediction using four small molecules whose complex structures with the MycG4 have been experimentally determined in solution. The results indicate that there are considerable differences in the performance of the docking programs and that DOCK 6 with GB/SA rescoring performs better than the other programs. We found that docking accuracy is mainly limited by the scoring functions. The study shows that current docking programs should be used with caution to predict G4 DNA-small molecule binding modes.

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Section: Resultsmentioning

confidence: 99%

Evaluating Molecular Docking Software for Small Molecule Binding to G-Quadruplex DNA

Dickerhoff

Warnecke

Wang

et al. 2021

IJMS

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“…They are more than 60 docking programs [36] and some of them like AutoDock [37], DOCK [38], AutoDock Vina [39], GalaxyDock [40], and FITTED [41] can incorporate protein flexibility into docking, although this is typically is limited to sidechain motions in the binding pocket. In addition, there are approaches that incorporate protein flexibility using a larger set of protein conformations that are generated either beforehand ("ensemble docking") [42,43,34] or on-the-fly ("induced fit docking") [33,44,45]. Boltzmann docking [46] and Implicit Ligand Theory [47] are also used to dock ligands to an ensemble of protein conformations, however these ensembles are generated in the apo structure and would not easily capture pocket conformations that are induced by the presence of a ligand.…”

Section: Introductionmentioning

confidence: 99%

Flexible Topology: A New Method for Dynamic Drug Design

Donyapour

Roussey

Bose

et al. 2022

Preprint

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Ligand-induced conformational changes form the underpinnings of most essential biomolecular processes, however they are often neglected in screening and design applications, due to the high computational cost. We propose a method called “Flexible Topology”, where a ligand is comprised of a set of shapeshifting “ghost” atoms, whose atomic identities and connectivity can dynamically change over the course of a simulation. Ghost atoms are guided toward their target positions using a translation-, rotation-, and index-invariant restraint potential. When implemented with a large set possible targets, this can simulate trajectories in a coupled chemical-conformational space that allows solutions to molecular design problems to simply emerge over the course of a trajectory. It also provides a mechanism for observing ligand-induced conformational change, by allowing for the surrounding environment and the ghost atoms to respond to each other during the design process. This builds on a substantial history of alchemy in the field of molecular dynamics simulation, including the Lambda dynamics method developed by Brooks and coworkers [X. Kong and C.L. Brooks III, J. Chem. Phys. 105, 2414 (1996)], but takes it to an extreme by associating a set of four dynamical variables with each shapeshifting atom that control not only its presence but its atomic identity. Here we outline the theoretical details of this method, its implementation using the OpenMM simulation package, and some preliminary studies of ghost particle assembly simulations. We show that while Flexible Topology is able to consistently assemble molecules up to 50 atoms in size, modifications are needed before it can reliably predict bound poses in heterogeneous environments.

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“…As seen in Table 1, native Glide SP delivers considerably higher enrichment over the DUD-E dataset using holo structures as compared to the enrichments reported in the study of Im and coworkers 25 , where AutoDock 21 was used to generate the docked poses. Next, we use our recently released induced-fit docking program (IFD-MD) 26,27 to induce a more holo-like structure suitable for docking using the holo ligand provided in the DUD-E dataset and repeat the docking calculations on this structure. IFD-MD is a rigorous, template-free physics-based protocol that combines traditional docking calculations, pharmacophore-based analysis of the active site, detailed analysis of the active site water network using WScore, side chain sampling, and MD-based refinement, to capture induced fit effects upon ligand binding 27 .…”

Section: Introductionmentioning

confidence: 99%

Benchmarking Refined and Unrefined AlphaFold2 Structures for Hit Discovery

Zhang

Vass

Shi

et al. 2022

Preprint

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The recently developed AlphaFold2 (AF2) algorithm predicts proteins’ 3D structures from amino acid sequences. The open AlphaFold Protein Structure Database covers the complete human proteome. It shows great potential to provide structural information to enable and enhance existing and new drug discovery projects. Using an industry-leading molecular docking method (Glide), we benchmarked the virtual screening performance of 28 common drug targets each with an AF2 structure and known holo and apo structures from the DUD-E dataset. The AF2 structures show comparable early enrichment of known active compounds (avg. EF 1%: 13.16) to apo structures (avg. EF 1%: 11.56), while falling behind early enrichment of the holo structures (avg. EF 1%: 24.81). We also demonstrated that with the IFD-MD induced-fit docking approach, we can refine the AF2 structures using a known binding ligand to improve the performance in structure-based virtual screening (avg. EF 1%: 19.25). Thus, with proper preparation and refinement, AF2 structures show considerable promise for in silico hit identification.

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A Reliable and Accurate Solution to the Induced Fit Docking Problem for Protein-Ligand Binding

Cited by 22 publications

References 0 publications

Evaluating Molecular Docking Software for Small Molecule Binding to G-Quadruplex DNA

Evaluating Molecular Docking Software for Small Molecule Binding to G-Quadruplex DNA

Flexible Topology: A New Method for Dynamic Drug Design

Benchmarking Refined and Unrefined AlphaFold2 Structures for Hit Discovery

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