Combining Solvent Thermodynamic Profiles with Functionality Maps of the Hsp90 Binding Site to Predict the Displacement of Water Molecules

Haider, Kamran; Huggins, David J.

doi:10.1021/ci4003409

Cited by 43 publications

(74 citation statements)

References 89 publications

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“…34−37 Haider and Huggins have compared empirical displaceabilities (D) of water molecules in the binding site of Hsp90 with the IFST ΔG bind , finding a correlation of 0.57. 38 They also tried to predict D from interaction energies of probes used by MCSS (a method that, like GRID, does not consider solvation explicitly 39 ), and combining IFST with MCSS, but no significant correlation was found. ΔG bind derived from MDmix simulations (see Experimental Design section) provides a correlation of 0.61 with D and 0.70 with IFST (Table 6), indicating thatat least for this systemdirect measurement of water densities along the MD trajectory is as useful as the more convolute IFST.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Molecular Simulations with Solvent Competition Quantify Water Displaceability and Provide Accurate Interaction Maps of Protein Binding Sites

2014

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Binding sites present well-defined interaction patterns that putative ligands must meet. Knowing them is essential to guide structure-based drug discovery projects. However, complex aspects of molecular recognition-such as protein flexibility or the effect of aqueous solvation-hinder accurate predictions. This is particularly true for polar contacts, which are heavily influenced by the local environment and the behavior of discrete water molecules. Here we present and validate MDmix (Molecular Dynamics simulations with mixed solvents) as a method that provides much more accurate interaction maps than ordinary potentials (e.g., GRID). Additionally, MDmix also affords water displaceability predictions, with advantages over methods that use pure water as solvent (e.g., inhomogeneous fluid solvation theory). With current MD software and hardware solutions, predictions can be obtained in a matter of hours and visualized in a very intuitive manner. Thus, MDmix is an ideal complement in everyday structure-based drug discovery projects.

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Section: ■ Results and Discussionmentioning

confidence: 99%

Molecular Simulations with Solvent Competition Quantify Water Displaceability and Provide Accurate Interaction Maps of Protein Binding Sites

2014

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“…12,27,33−35 We used every 10th frame of this segment to identify the hydration sites. We first collected all instances, in these 1000 frames, of water molecules within 5 Å of any heavy atom of any bound ligand (see below).…”

Section: Methodsmentioning

confidence: 99%

“…Key early contributions include development of WaterMap 8,12 (Schrödinger LLC), STOW, 25 and other approaches, 26,27 which have provided new insight and shown promise as tools to help discover small molecules that will bind a targeted binding pocket. Such methods frequently define spherical sites, where water is present at high density, to represent the distribution of water in the binding site.…”

Section: Introductionmentioning

confidence: 99%

Thermodynamics of Water in an Enzyme Active Site: Grid-Based Hydration Analysis of Coagulation Factor Xa

Nguyen

Cruz

Gilson

et al. 2014

J. Chem. Theory Comput.

131

261

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Water molecules in the active site of an enzyme occupy a complex, heterogeneous environment, and the thermodynamic properties of active-site water are functions of position. As a consequence, it is thought that an enzyme inhibitor can gain affinity by extending into a region occupied by unfavorable water or lose affinity by displacing water from a region where it was relatively stable. Recent advances in the characterization of binding-site water, based on the analysis of molecular simulations with explicit water molecules, have focused largely on simplified representations of water as occupying well-defined hydration sites. Our grid-based treatment of hydration, GIST, offers a more complete picture of the complex distributions of water properties, but it has not yet been applied to proteins. This first application of GIST to protein–ligand modeling, for the case of Coagulation Factor Xa, shows that ligand scoring functions based on GIST perform at least as well as scoring functions based on a hydration-site approach (HSA), when applied to exactly the same simulation data. Interestingly, the displacement of energetically unfavorable water emerges as the dominant factor in the fitted scoring functions, for both GIST and HSA methods, while water entropy plays a secondary role, at least in the present context.

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“…The size and chemical diversity of the ligand data set makes it less practical to apply FEP methods to cover all the ligands. The ATP binding site in Hsp90 is known to be particularly difficult for binding free energy calculations [13] as ligand binding involves binding site conformational changes, burial of charged side chains inside the binding site and varying numbers of enclosed water molecules in the binding pocket [14]. Therefore, rather than aiming to predict the rank ordering of ligand binding affinities, our primary goal in this challenge is to test how well the different methods, such as BEDAM, MM-GB/SA and docking, can discriminate binders from nonbinders in this large scale blind prediction [15].…”

Section: Introductionmentioning

confidence: 99%

Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

Deng¹,

Flynn²,

Xia³

et al. 2016

J Comput Aided Mol Des

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We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein–ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

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Combining Solvent Thermodynamic Profiles with Functionality Maps of the Hsp90 Binding Site to Predict the Displacement of Water Molecules

Cited by 43 publications

References 89 publications

Molecular Simulations with Solvent Competition Quantify Water Displaceability and Provide Accurate Interaction Maps of Protein Binding Sites

Molecular Simulations with Solvent Competition Quantify Water Displaceability and Provide Accurate Interaction Maps of Protein Binding Sites

Thermodynamics of Water in an Enzyme Active Site: Grid-Based Hydration Analysis of Coagulation Factor Xa

Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

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