Scalable Indirect Free Energy Method Applied to Divalent Cation-Metalloprotein Binding

Litman, Jacob M.; Thiel, Andrew; Schnieders, Michael

doi:10.1021/acs.jctc.9b00147

Cited by 5 publications

(9 citation statements)

References 76 publications

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“…While DFF was originally demonstrated on ∆ a^+_(>,f(]-for a set of small organic molecules 41 , both the DFF and SB algorithms will be explained in the context of metalloprotein-divalent cation binding for simplicity. Additionally, while the original DFF manuscript utilized untempered orthogonal space random walk (OSRW), the SB work 153 utilized transition-tempered orthogonal space random walk (TT-OSRW). [29][30].…”

Section: Dual Force Field: Our Prior Indirect Free Energy Methodsmentioning

confidence: 99%

“…While unavailable for the dual force field publication 41 , the trigonometric switch was used for most simulations in the SB manuscript 153 . The primary exception was the AMOEBA direct mutational path, which used a linear switch.…”

Section: Target Potential Regionmentioning

confidence: 99%

“…developing the simultaneous bookending (SB) indirect free energy (IFE) method 153 . These IFE methods utilize a fast simulation in a "reference" potential to obtain an initial, well-converged but inaccurate estimate, then add two additional thermodynamic legs to correct results to values consistent with a more accurate "target" potential.…”

Section: The Work Of Chapter 3 Directly Addresses the Tradeoff Betweementioning

confidence: 99%

“…This could pose a significant issue for SB, as it assumes that the background conformational ensemble is largely independent of the alchemical change. Based on a literature review (Table 14), it seems that none of the six metalloproteins studied by us 153 and the Ren group 70 are subject to radical conformational changes on ion binding. For 4ICB, while it had significant changes distal from the ion binding site, it is not a totally different fold.…”

Section: Potential Flexibility In Calcium-binding Proteinsmentioning

confidence: 99%

“…By introducing this tunable sampling approximation, SB represents a fundamentally different approach to tackling the inherent challenge of IFE methods by improving convergence of the sum ∆ e],Za\-+ ∆ Z\Ÿ(-\ , while transforming large systems in their entirety to the target potential. I demonstrated this method153 on a series of six divalent cation-binding metalloproteins70,134,[158][159][160][161][162] of up to 2972 atoms (Figure 22,…”

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Advanced optimization and sampling techniques for biomolecules using a polarizable force field

Litman¹

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with science and the Ph.D. process. Prof. Schnieders and the rest of the Schnieders lab provided endless support and guidance. Without his assistance, this work would not have been possible. Mallory Tollefson in particular is co-first-author on the material presented in Chapter 2, having performed most of the data collection and determined appropriate cutoff schemes. Andrew Thiel assisted in preparing the manuscript referenced in Chapter 3. Hernan Bernabe is leading the Monte Carlo Orthogonal Space Random Walk project discussed in Section 4D. Guowei Qi produced an automated script for the work described by Chapter 2, vastly reducing the human effort required and speeding up that project by months. Maya Benowitz assisted with deriving the total number of energy evaluations needed for the many-body expansion (Chapter 2). I would also like to thank the labs of Prof. Pengyu Ren, Prof. Richard Smith, Prof. Ernesto Fuentes, and Prof. Simonson. Professor Pengyu Ren and his student, Zhifeng Jing, provided data used in Chapter 3 prior to their publication, which helped us perform our study on simultaneous bookending. Prof. Richard Smith and the other members of Audiogene provided data, motivation, and critical analysis for the work in Chapter 2, which is our most directly clinically motivated work. The labs of Prof. Fuentes and Simonson assisted in the simultaneous bookending project; while we were unable to produce high-quality results on the PDZ domains iii they study, their advice and assistance was key to developing the algorithm. In addition, the Simonson lab described the native environment approximation used by the optimization work.

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Section: Dual Force Field: Our Prior Indirect Free Energy Methodsmentioning

confidence: 99%

Section: Target Potential Regionmentioning

confidence: 99%

Section: The Work Of Chapter 3 Directly Addresses the Tradeoff Betweementioning

confidence: 99%

Section: Potential Flexibility In Calcium-binding Proteinsmentioning

confidence: 99%

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confidence: 99%

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Advanced optimization and sampling techniques for biomolecules using a polarizable force field

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A Comparison of Methods for Computing Relative Anhydrous–Hydrate Stability with Molecular Simulation

Dybeck

Thiel

Schnieders

et al. 2022

Crystal Growth & Design

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The transformation of a pharmaceutical solid from an anhydrous crystal into a hydrated form during drug development represents a risk to a product’s safety and efficacy due to the potential impact on stability, bioavailability, and manufacturability. In this work, we examine 10 classical free energy simulation protocols to evaluate the thermodynamic stability of hydrated crystals relative to their anhydrous forms. Molecular dynamics simulations are used to compute the Gibbs free energies of the crystals of three pharmaceutically relevant systems using two fixed-charge potentials, GAFF and OPLS, as well as the polarizable AMOEBA model. In addition, we explore a variety of water models, including TIP3P, TIP4P, and AMOEBA, for both the interstitial water and the effects of ambient humidity. The AMOEBA model predicts free energy values most consistent with experimental measurements among the models examined. The benefits of a fully polarizable water model relative to fixed-charged models appear to derive predominantly from a better treatment of water’s dipole moment in the crystalline phase. Despite this improved physical treatment, we find that no single model produces reliable predictions of the phase boundary between hydrated and anhydrous crystals from theory alone. However, we show that accurate phase diagrams can be constructed from the simulations by introducing a single experimentally determined coexistence point. With this single experimental data point as input, the phase boundary is correctly predicted within 10% relative humidity on the temperature range of 15 to 75 °C for all three systems examined. Furthermore, we demonstrate that with this known coexistence point as an input, the differences between the various potentials and the water models become insignificant, as all models yield accurate phase boundaries regardless of whether polarization is included due to significant temperature-dependent error cancellation between models.

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Crystal Polymorph Search in the NPT Ensemble via a Deposition/Sublimation Alchemical Path

Nessler,

Okada,

Kinoshita

et al. 2024

Crystal Growth & Design

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The formulation of active pharmaceutical ingredients involves discovering stable crystal packing arrangements or polymorphs, each of which has distinct pharmaceutically relevant properties. Traditional experimental screening techniques utilizing various conditions are commonly supplemented with in silico crystal structure prediction (CSP) to inform the crystallization process and mitigate risk. Predictions are often based on advanced classical force fields or quantum mechanical calculations that model the crystal potential energy landscape but do not fully incorporate temperature, pressure, or solution conditions during the search procedure. This study proposes an innovative alchemical path that utilizes an advanced polarizable atomic multipole force field to predict crystal structures based on direct sampling of the NPT ensemble. The use of alchemical (i.e., nonphysical) intermediates, a novel Monte Carlo barostat, and an orthogonal space tempering bias combine to enhance the sampling efficiency of the deposition/sublimation phase transition. The proposed algorithm was applied to 2-((4-(2-(3,4-dichlorophenyl)ethyl)phenyl)amino)benzoic acid (Cambridge Crystallography Database Centre ID: XAFPAY) as a case study to showcase the algorithm. Each experimentally determined polymorph with one molecule in the asymmetric unit was successfully reproduced via approximately 1000 short 1 ns simulations per space group where each simulation was initiated from random rigid body coordinates and unit cell parameters. Utilizing two threads of a recent Intel CPU (a Xeon Gold 6330 CPU at 2.00 GHz), 1 ns of sampling using the polarizable AMOEBA force field can be acquired in 4 h (equating to more than 300 ns/day using all 112 threads/56 cores of a dual CPU node) within the Force Field X software (https://ffx.biochem.uiowa.edu). These results demonstrate a step forward in the rigorous use of the NPT ensemble during the CSP search process and open the door to future algorithms that incorporate solution conditions using continuum solvation methods.

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Scalable Indirect Free Energy Method Applied to Divalent Cation-Metalloprotein Binding

Cited by 5 publications

References 76 publications

Advanced optimization and sampling techniques for biomolecules using a polarizable force field

Advanced optimization and sampling techniques for biomolecules using a polarizable force field

A Comparison of Methods for Computing Relative Anhydrous–Hydrate Stability with Molecular Simulation

Crystal Polymorph Search in the NPT Ensemble via a Deposition/Sublimation Alchemical Path

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