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Slattery SA, Yon JC, Valeev EF. Revisiting Artifacts of Kohn-Sham Density Functionals for Biosimulation. J Chem Theory Comput 2024; 20:6652-6660. [PMID: 39083031 PMCID: PMC11325537 DOI: 10.1021/acs.jctc.4c00712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
We revisit the problem of unphysical charge density delocalization/fractionalization induced by the self-interaction error of common approximate Kohn-Sham (KS) density functional theory functionals on simulation of small to medium-sized proteins in a vacuum. Aside from producing unphysical electron densities and total energies, the vanishing of the HOMO-LUMO gap associated with the unphysical charge delocalization leads to an unphysical low-energy spectrum and catastrophic failure of most popular solvers for the KS self-consistent field (SCF) problem. We apply a robust quasi-Newton SCF solver [ Phys. Chem. Chem. Phys. 2024, 26, 6557] to obtain solutions for some of these difficult cases. The anatomy of the charge delocalization is revealed by the natural deformation orbitals obtained from the density matrix difference between the Hartree-Fock and KS solutions; the charge delocalization not only can occur between charged fragments (such as in zwitterionic polypeptides) but also involves neutral fragments. The vanishing-gap phenomenon and troublesome SCF convergence are both attributed to the unphysical KS Fock operator eigenspectra of molecular fragments (e.g., amino acids or their side chains). Analysis of amino acid pairs suggests that the unphysical charge delocalization can be partially ameliorated by the use of some range-separated hybrid functionals but not by semilocal or standard hybrid functionals. Last, we demonstrate that solutions without the unphysical charge delocalization can be located even for semilocal KS functionals highly prone to such defects, but such solutions have non-Aufbau character and are unstable with respect to mixing of the non-overlapping "frontier" orbitals. Caution should be exercised when unexpectedly small (or vanishing) HOMO-LUMO gaps and atypical SCF convergence patterns (e.g., oscillatory) are observed in KS DFT simulations in any context (bio or otherwise).
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Affiliation(s)
- Samuel A Slattery
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Jaden C Yon
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Edward F Valeev
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
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2
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Cao Y, Balduf T, Beachy MD, Bennett MC, Bochevarov AD, Chien A, Dub PA, Dyall KG, Furness JW, Halls MD, Hughes TF, Jacobson LD, Kwak HS, Levine DS, Mainz DT, Moore KB, Svensson M, Videla PE, Watson MA, Friesner RA. Quantum chemical package Jaguar: A survey of recent developments and unique features. J Chem Phys 2024; 161:052502. [PMID: 39092934 DOI: 10.1063/5.0213317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 07/12/2024] [Indexed: 08/04/2024] Open
Abstract
This paper is dedicated to the quantum chemical package Jaguar, which is commercial software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific features that are relevant to chemical research as well as describe those aspects of the program that are pertinent to the user interface, the organization of the computer code, and its maintenance and testing. Among the scientific topics that feature prominently in this paper are the quantum chemical methods grounded in the pseudospectral approach. A number of multistep workflows dependent on Jaguar are covered: prediction of protonation equilibria in aqueous solutions (particularly calculations of tautomeric stability and pKa), reactivity predictions based on automated transition state search, assembly of Boltzmann-averaged spectra such as vibrational and electronic circular dichroism, as well as nuclear magnetic resonance. Discussed also are quantum chemical calculations that are oriented toward materials science applications, in particular, prediction of properties of optoelectronic materials and organic semiconductors, and molecular catalyst design. The topic of treatment of conformations inevitably comes up in real world research projects and is considered as part of all the workflows mentioned above. In addition, we examine the role of machine learning methods in quantum chemical calculations performed by Jaguar, from auxiliary functions that return the approximate calculation runtime in a user interface, to prediction of actual molecular properties. The current work is second in a series of reviews of Jaguar, the first having been published more than ten years ago. Thus, this paper serves as a rare milestone on the path that is being traversed by Jaguar's development in more than thirty years of its existence.
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Affiliation(s)
- Yixiang Cao
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Ty Balduf
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Michael D Beachy
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - M Chandler Bennett
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Art D Bochevarov
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Alan Chien
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Pavel A Dub
- Schrödinger, Inc., 9868 Scranton Road, Suite 3200, San Diego, California 92121, USA
| | - Kenneth G Dyall
- Schrödinger, Inc., 101 SW Main St., Suite 1300, Portland, Oregon 97204, USA
| | - James W Furness
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Mathew D Halls
- Schrödinger, Inc., 9868 Scranton Road, Suite 3200, San Diego, California 92121, USA
| | - Thomas F Hughes
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Leif D Jacobson
- Schrödinger, Inc., 101 SW Main St., Suite 1300, Portland, Oregon 97204, USA
| | - H Shaun Kwak
- Schrödinger, Inc., 101 SW Main St., Suite 1300, Portland, Oregon 97204, USA
| | - Daniel S Levine
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Daniel T Mainz
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Kevin B Moore
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Mats Svensson
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Pablo E Videla
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Mark A Watson
- Schrödinger, Inc., 1540 Broadway, Floor 24, New York, New York 10036, USA
| | - Richard A Friesner
- Department of Chemistry, Columbia University, 3000 Broadway, New York, New York 10027, USA
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3
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Zubatyuk R, Biczysko M, Ranasinghe K, Moriarty NW, Gokcan H, Kruse H, Poon BK, Adams PD, Waller MP, Roitberg AE, Isayev O, Afonine PV. AQuaRef: Machine learning accelerated quantum refinement of protein structures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.21.604493. [PMID: 39071315 PMCID: PMC11275739 DOI: 10.1101/2024.07.21.604493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library- based stereochemical restraints, which, in addition to being limited to known chemical entities, do not include meaningful noncovalent interactions relying solely on nonbonded repulsions. Quantum mechanical (QM) calculations could alleviate these issues but are too expensive for large molecules. We present a novel AI-enabled Quantum Refinement (AQuaRef) based on AIMNet2 neural network potential mimicking QM at substantially lower computational costs. By refining 41 cryo-EM and 30 X-ray structures, we show that this approach yields atomic models with superior geometric quality compared to standard techniques, while maintaining an equal or better fit to experimental data.
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4
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Das D, Miller AF. A single hydrogen bond that tunes flavin redox reactivity and activates it for modification. Chem Sci 2024; 15:7610-7622. [PMID: 38784750 PMCID: PMC11110160 DOI: 10.1039/d4sc01642d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Accepted: 04/14/2024] [Indexed: 05/25/2024] Open
Abstract
Electron bifurcation produces high-energy products based on less energetic reagents. This feat enables biological systems to exploit abundant mediocre fuel to drive vital but demanding reactions, including nitrogen fixation and CO2 capture. Thus, there is great interest in understanding principles that can be portable to man-made devices. Bifurcating electron transfer flavoproteins (Bf ETFs) employ two flavins with contrasting reactivities to acquire pairs of electrons from a modest reductant, NADH. The bifurcating flavin then dispatches the electrons individually to a high and a low reduction midpoint potential (E°) acceptor, the latter of which captures most of the energy. Maximum efficiency requires that only one electron accesses the exergonic path that will 'pay for' the production of the low-E° product. It is therefore critical that one of the flavins, the 'electron transfer' (ET) flavin, is tuned to execute single-electron (1e-) chemistry only. To learn how, and extract fundamental principles, we systematically altered interactions with the ET-flavin O2 position. Removal of a single hydrogen bond (H-bond) disfavored the formation of the flavin anionic semiquinone (ASQ) relative to the oxidized (OX) state, lowering by 150 mV and retuning the flavin's tendency for 1e-vs. 2e- reactivity. This was achieved by replacing conserved His 290 with Phe, while also replacing the supporting Tyr 279 with Ile. Although this variant binds oxidized FADs at 90% the WT level, the ASQ state of the ET-flavin is not stable in the absence of H290's H-bond, and dissociates, in contrast to the WT. Removal of this H-bond also altered the ET-flavin's covalent chemistry. While the WT ETF accumulates modified flavins whose formation is believed to rely on an anionic paraquinone methide intermediate, the FADs of the H-bond lacking variant remain unchanged over weeks. Hence the variant that destabilizes the anionic semiquinone also suppresses the anionic intermediate in flavin modification, verifying electronic similarities between these two species. These correlations suggest that the H-bond that stabilizes the crucial flavin ASQ also promotes flavin modification. The two effects may indeed be inseparable, as a Jekyll and Hydrogen bond.
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Affiliation(s)
- Debarati Das
- Department of Chemistry, University of Kentucky Lexington Kentucky USA
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5
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Agbaglo DA, Summers TJ, Cheng Q, DeYonker NJ. The influence of model building schemes and molecular dynamics sampling on QM-cluster models: the chorismate mutase case study. Phys Chem Chem Phys 2024; 26:12467-12482. [PMID: 38618904 PMCID: PMC11090134 DOI: 10.1039/d3cp06100k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Most QM-cluster models of enzymes are constructed based on X-ray crystal structures, which limits comparison to in vivo structure and mechanism. The active site of chorismate mutase from Bacillus subtilis and the enzymatic transformation of chorismate to prephenate is used as a case study to guide construction of QM-cluster models built first from the X-ray crystal structure, then from molecular dynamics (MD) simulation snapshots. The Residue Interaction Network ResidUe Selector (RINRUS) software toolkit, developed by our group to simplify and automate the construction of QM-cluster models, is expanded to handle MD to QM-cluster model workflows. Several options, some employing novel topological clustering from residue interaction network (RIN) information, are evaluated for generating conformational clustering from MD simulation. RINRUS then generates a statistical thermodynamic framework for QM-cluster modeling of the chorismate mutase mechanism via refining 250 MD frames with density functional theory (DFT). The 250 QM-cluster models sampled provide a mean ΔG‡ of 10.3 ± 2.6 kcal mol-1 compared to the experimental value of 15.4 kcal mol-1 at 25 °C. While the difference between theory and experiment is consequential, the level of theory used is modest and therefore "chemical" accuracy is unexpected. More important are the comparisons made between QM-cluster models designed from the X-ray crystal structure versus those from MD frames. The large variations in kinetic and thermodynamic properties arise from geometric changes in the ensemble of QM-cluster models, rather from the composition of the QM-cluster models or from the active site-solvent interface. The findings open the way for further quantitative and reproducible calibration in the field of computational enzymology using the model construction framework afforded with the RINRUS software toolkit.
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Affiliation(s)
- Donatus A Agbaglo
- Department of Chemistry, University of Memphis, Memphis, TN 38152, USA.
| | - Thomas J Summers
- Department of Chemistry, University of Memphis, Memphis, TN 38152, USA.
| | - Qianyi Cheng
- Department of Chemistry, University of Memphis, Memphis, TN 38152, USA.
| | - Nathan J DeYonker
- Department of Chemistry, University of Memphis, Memphis, TN 38152, USA.
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6
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Villot C, Huang T, Lao KU. Accurate prediction of global-density-dependent range-separation parameters based on machine learning. J Chem Phys 2023; 159:044103. [PMID: 37486048 DOI: 10.1063/5.0157340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 07/03/2023] [Indexed: 07/25/2023] Open
Abstract
In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0-1 and only five systems (0.07%) with an absolute error larger than 0.01 a0-1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.
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Affiliation(s)
- Corentin Villot
- Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, USA
| | - Tong Huang
- Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, USA
| | - Ka Un Lao
- Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, USA
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7
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González-Viegas M, Kar RK, Miller AF, Mroginski MA. Non-covalent interactions that tune the reactivities of the flavins in bifurcating electron transferring flavoprotein. J Biol Chem 2023:104762. [PMID: 37119850 DOI: 10.1016/j.jbc.2023.104762] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/20/2023] [Accepted: 04/25/2023] [Indexed: 05/01/2023] Open
Abstract
Bifurcating electron transferring flavoproteins (Bf-ETFs) tune chemically identical flavins to two contrasting roles. To understand how, we used hybrid quantum mechanical molecular mechanical calculations to characterize non-covalent interactions applied to each flavin by the protein. Our computations replicated the differences between the reactivities of the flavins: the electron transferring flavin (ETflavin) was calculated to stabilize anionic semiquinone (ASQ) as needed to execute its single-electron transfers, whereas the Bf flavin (Bfflavin) was found to disfavor the ASQ state more than does free flavin and to be less susceptible to reduction. The stability of ETflavin ASQ was attributed in part to H-bond donation to the flavin O2 from a nearby His side chain, via comparison of models employing different tautomers of His. This H-bond between O2 and the ET site was uniquely strong in the ASQ state, whereas reduction of ETflavin to the anionic hydroquinone (AHQ) was associated with side chain reorientation, backbone displacement and reorganization of its H-bond network including a Tyr from the other domain and subunit of the ETF. The Bf site was less responsive overall, but formation of the Bfflavin AHQ allowed a nearby Arg side chain to adopt an alternative rotamer that can H-bond to the Bfflavin O4. This would stabilize the anionic Bfflavin and rationalize effects of mutation at this position. Thus, our computations provide insights on states and conformations that have not been possible to characterize experimentally, offering explanations for observed residue conservation and raising possibilities that can now be tested.
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Affiliation(s)
- María González-Viegas
- Department of Chemistry, Technische Universität - Berlin, Berlin, Germany; Department of Physics, Freie Universität Berlin, Berlin, Germany
| | - Rajiv K Kar
- Department of Chemistry, Technische Universität - Berlin, Berlin, Germany
| | - Anne-Frances Miller
- Department of Chemistry, Technische Universität - Berlin, Berlin, Germany; Department of Chemistry, University of Kentucky, Lexington KY, U.S.A..
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8
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Kim CY, Mitchell AJ, Kastner DW, Albright CE, Gutierrez MA, Glinkerman CM, Kulik HJ, Weng JK. Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY. Nat Commun 2023; 14:597. [PMID: 36737607 PMCID: PMC9898226 DOI: 10.1038/s41467-023-36299-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 01/25/2023] [Indexed: 02/05/2023] Open
Abstract
Plants contain rapidly evolving specialized enzymes that support the biosynthesis of functionally diverse natural products. In coumarin biosynthesis, a BAHD acyltransferase-family enzyme COSY was recently discovered to accelerate coumarin formation as the only known BAHD enzyme to catalyze an intramolecular acyl transfer reaction. Here we investigate the structural and mechanistic basis for COSY's coumarin synthase activity. Our structural analyses reveal an unconventional active-site configuration adapted to COSY's specialized activity. Through mutagenesis studies and deuterium exchange experiments, we identify a unique proton exchange mechanism at the α-carbon of the o-hydroxylated trans-hydroxycinnamoyl-CoA substrates during the catalytic cycle of COSY. Quantum mechanical cluster modeling and molecular dynamics further support this key mechanism for lowering the activation energy of the rate-limiting trans-to-cis isomerization step in coumarin production. This study unveils an unconventional catalytic mechanism mediated by a BAHD-family enzyme, and sheds light on COSY's evolutionary origin and its recruitment to coumarin biosynthesis in eudicots.
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Affiliation(s)
- Colin Y Kim
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Andrew J Mitchell
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
| | - David W Kastner
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.,Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Claire E Albright
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
| | | | | | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Jing-Ke Weng
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA. .,Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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9
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Kastner DW, Nandy A, Mehmood R, Kulik HJ. Mechanistic Insights into Substrate Positioning That Distinguish Non-heme Fe(II)/α-Ketoglutarate-Dependent Halogenases and Hydroxylases. ACS Catal 2023. [DOI: 10.1021/acscatal.2c06241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- David W. Kastner
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Aditya Nandy
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Rimsha Mehmood
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Heather J. Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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10
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Yang Z, Hajlasz N, Kulik HJ. Computational Modeling of Conformer Stability in Benenodin-1, a Thermally Actuated Lasso Peptide Switch. J Phys Chem B 2022; 126:3398-3406. [PMID: 35481742 DOI: 10.1021/acs.jpcb.2c00762] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Benenodin-1 is a thermally actuated lasso peptide rotaxane switch with two primary translational isomers that differ in the relative position of the residue Gln15. The conversion from one conformer to the other involves substantial enthalpy-entropy compensation: one conformer is energetically favored and the other is entropically favored. Here, we take a multi-scale quantum mechanical (QM) and classical molecular dynamic (MD) approach to reveal residue-specific sources of these differences in stability. QM reveals that the two benenodin-1 conformers involve distinct hydrogen bonding networks, with the enthalpically favored conformer having more intra-peptide hydrogen bonds between the Gln15 side chain and nearby residues. The evaluation of configurational entropy over the MD-sampled geometries reveals that the entropically favored conformer has enhanced conformational flexibility. By computing the by-residue-sum entropies, we identify the role of Gln15 and neighboring Glu14 in mediating the entropic variation during the switching process. These computational insights help explain the effects of Glu14Ala and Gln15Ala mutations on the conformational population of benenodin-1 observed experimentally.
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Affiliation(s)
- Zhongyue Yang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Natalia Hajlasz
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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11
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Prasad VK, Otero-de-la-Roza A, DiLabio GA. Fast and Accurate Quantum Mechanical Modeling of Large Molecular Systems Using Small Basis Set Hartree-Fock Methods Corrected with Atom-Centered Potentials. J Chem Theory Comput 2022; 18:2208-2232. [PMID: 35313106 DOI: 10.1021/acs.jctc.1c01128] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree-Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bioorganic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*) and the HF-3c method. The new ACPs are trained on a very large set (73 832 data points) of noncovalent properties (interaction and conformational energies) and validated additionally on a set of 32 048 data points. All reference data are of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for noncovalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set density functional theory (DFT) but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and noncovalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.
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Affiliation(s)
- Viki Kumar Prasad
- Department of Chemistry, University of British Columbia, Okanagan, 3247 University Way, Kelowna, British Columbia, Canada V1V 1V7
| | - Alberto Otero-de-la-Roza
- MALTA Consolider Team, Departamento de Química Física y Analítica, Facultad de Química, Universidad de Oviedo, E-33006 Oviedo, Spain
| | - Gino A DiLabio
- Department of Chemistry, University of British Columbia, Okanagan, 3247 University Way, Kelowna, British Columbia, Canada V1V 1V7
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12
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Aroeira GJR, Davis MM, Turney JM, Schaefer HF. Fermi.jl: A Modern Design for Quantum Chemistry. J Chem Theory Comput 2022; 18:677-686. [PMID: 34978451 DOI: 10.1021/acs.jctc.1c00719] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Approximating molecular wave functions involves heavy numerical effort; therefore, codes for such tasks are written completely or partially in efficient languages such as C, C++, and Fortran. While these tools are dominant throughout quantum chemistry packages, the efficient development of new methods is often hindered by the complexity associated with code development. In order to ameliorate this scenario, some software packages take a dual approach where a simpler, higher-level language, such as Python, substitutes the traditional ones wherever performance is not critical. Julia is a novel, dynamically typed, programming language that aims to solve this two-language problem. It gained attention because of its modern and intuitive design, while still being highly optimized to compete with "low-level" languages. Recently, some chemistry-related projects have emerged exploring the capabilities of Julia. Herein, we introduce the quantum chemistry package Fermi.jl, which contains the first implementations of post-Hartree-Fock methods written in Julia. Its design makes use of many Julia core features, including multiple dispatch, metaprogramming, and interactive usage. Fermi.jl is a modular package, where new methods and implementations can be easily added to the existing code. Furthermore, it is designed to maximize code reusability by relying on general functions with specialized methods for particular cases. The feasibility of the project is explored through evaluating the performance of popular ab initio methods. It is our hope that this project motivates the usage of Julia within the community and brings new contributions into Fermi.jl.
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Affiliation(s)
- Gustavo J R Aroeira
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Matthew M Davis
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Justin M Turney
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Henry F Schaefer
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
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13
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Mehmood R, Kulik HJ. Quantum-Mechanical/Molecular-Mechanical (QM/MM) Simulations for Understanding Enzyme Dynamics. Methods Mol Biol 2022; 2397:227-248. [PMID: 34813067 DOI: 10.1007/978-1-0716-1826-4_12] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Quantum mechanics/molecular mechanics (QM/MM) methods have become widely used for computational modeling of enzyme structure and mechanism. In these approaches, a portion of the enzyme of great interest (e.g., where a chemical reaction is occurring) is treated with QM, whereas the surrounding region is treated with MM. A critical challenge with these methods is the choice of the region to partition into QM and which to treat with MM along with numerous practical choices that must be made at each step of the modeling procedure. Here, we attempt to simplify this process by describing the steps involved in preparing protein structures, choosing the appropriate QM region size and electronic structure methods, preparing all necessary input files, and troubleshooting common errors for QM/MM simulations of enzymes.
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Affiliation(s)
- Rimsha Mehmood
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
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14
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Sheng M, Silvestrini F, Biczysko M, Puzzarini C. Structural and Vibrational Properties of Amino Acids from Composite Schemes and Double-Hybrid DFT: Hydrogen Bonding in Serine as a Test Case. J Phys Chem A 2021; 125:9099-9114. [PMID: 34623165 DOI: 10.1021/acs.jpca.1c06993] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The structures, relative stabilities, and vibrational wavenumbers of the two most stable conformers of serine, stabilized by the O-H···N, O-H···O═C and N-H···O-H intramolecular hydrogen bonds, have been evaluated by means of state-of-the-art composite schemes based on coupled-cluster (CC) theory. The so-called "cheap" composite approach (CCSD(T)/(CBS+CV)MP2) allowed determination of accurate equilibrium structures and harmonic vibrational wavenumbers, also pointing out significant corrections beyond the CCSD(T)/cc-pVTZ level. These accurate results stand as a reference for benchmarking selected hybrid and double-hybrid, dispersion-corrected DFT functionals. B2PLYP-D3 and DSDPBEP86 in conjunction with a triple-ζ basis set have been confirmed as effective methodologies for structural and spectroscopic studies of medium-sized flexible biomolecules, also showing intramolecular hydrogen bonding. These best performing double-hybrid functionals have been employed to simulate IR spectra by means of vibrational perturbation theory, also considering hybrid CC/DFT schemes. The best overall agreement with experiment, with mean absolute error of 8 cm-1, has been obtained by combining CCSD(T)/(CBS+CV)MP2 harmonic wavenumbers with B2PLYP-D3/maug-cc-pVTZ anharmonic corrections. Finally, a composite scheme entirely based on CCSD(T) calculations (CCSD(T)/CBS+CV) has been employed for energetics, further confirming that serine II is the most stable conformer, also when zero-point vibrational energy corrections are included.
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Affiliation(s)
- Mingzhu Sheng
- International Centre for Quantum and Molecular Structures, Physics Department, Shanghai University, 99 Shangda Road, Shanghai, 200444, China
| | - Filippo Silvestrini
- Department of Chemistry "Giacomo Ciamician", University of Bologna, Via F. Selmi 2, 40126 Bologna, Italy
| | - Malgorzata Biczysko
- International Centre for Quantum and Molecular Structures, Physics Department, Shanghai University, 99 Shangda Road, Shanghai, 200444, China
| | - Cristina Puzzarini
- Department of Chemistry "Giacomo Ciamician", University of Bologna, Via F. Selmi 2, 40126 Bologna, Italy
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15
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Harder, better, faster, stronger: Large-scale QM and QM/MM for predictive modeling in enzymes and proteins. Curr Opin Struct Biol 2021; 72:9-17. [PMID: 34388673 DOI: 10.1016/j.sbi.2021.07.004] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/25/2021] [Accepted: 07/05/2021] [Indexed: 11/23/2022]
Abstract
Computational prediction of enzyme mechanism and protein function requires accurate physics-based models and suitable sampling. We discuss recent advances in large-scale quantum mechanical (QM) modeling of biochemical systems that have reduced the cost of high-accuracy models. Tradeoffs between sampling and accuracy have motivated modeling with molecular mechanics (MM) in a multiscale QM/MM or iterative approach. Limitations to both conventional density-functional theory and classical MM force fields remain for describing noncovalent interactions in comparison to experiment or wavefunction theory. Because predictions of enzyme action (i.e. electrostatics), free energy barriers, and mechanisms are sensitive to the protocol and embedding method in QM/MM, convergence tests and systematic methods for quantifying QM-level interactions are a needed, active area of development.
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16
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Gray M, Herbert JM. Simplified tuning of long-range corrected density functionals for use in symmetry-adapted perturbation theory. J Chem Phys 2021; 155:034103. [PMID: 34293871 DOI: 10.1063/5.0059364] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Long considered a failure, second-order symmetry-adapted perturbation theory (SAPT) based on Kohn-Sham orbitals, or SAPT0(KS), can be resurrected for semiquantitative purposes using long-range corrected density functionals whose asymptotic behavior is adjusted separately for each monomer. As in other contexts, correct asymptotic behavior can be enforced via "optimal tuning" based on the ionization energy theorem of density functional theory, but the tuning procedure is tedious, expensive for large systems, and comes with a troubling dependence on system size. Here, we show that essentially identical results are obtained using a fast, convenient, and automated tuning procedure based on the size of the exchange hole. In conjunction with "extended" (X)SAPT methods that improve the description of dispersion, this procedure achieves benchmark-quality interaction energies, along with the usual SAPT energy decomposition, without the hassle of system-specific tuning.
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Affiliation(s)
- Montgomery Gray
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - John M Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
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17
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Yang Z, Kulik HJ. Protein Dynamics and Substrate Protonation States Mediate the Catalytic Action of trans-4-Hydroxy-l-Proline Dehydratase. J Phys Chem B 2021; 125:7774-7784. [PMID: 34236200 DOI: 10.1021/acs.jpcb.1c05320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The enzyme trans-4-hydroxy-l-proline (Hyp) dehydratase (HypD) is among the most abundant glycyl radical enzymes (GREs) in the healthy human gut microbiome and is considered a promising antibiotic target for the prominent antibiotic-resistant pathogen Clostridium difficile. Although an enzymatic mechanism has been proposed, the role of the greater HypD protein environment in mediating radical reactivity is not well understood. To fill this gap in understanding, we investigate HypD across multiple time- and length-scales using electronic structure modeling and classical molecular dynamics. We observe that the Hyp substrate protonation state significantly alters both its enzyme-free reactivity and its dynamics within the enzyme active site. Accurate coupled-cluster modeling suggests the deprotonated form of Hyp to be the most reactive protonation state for C5-Hpro-S activation. In the protein environment, hydrophobic interactions modulate the positioning of the Cys434 radical to enhance the reactivity of C5-Hpro-S abstraction. Long-time dynamics reveal that changing Hyp protonation states triggers the switching of a Leu643-gated water tunnel, a functional feature that has not yet been observed for members of the GRE superfamily.
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Affiliation(s)
- Zhongyue Yang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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18
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Gale A, Hruska E, Liu F. Quantum chemistry for molecules at extreme pressure on graphical processing units: Implementation of extreme-pressure polarizable continuum model. J Chem Phys 2021; 154:244103. [PMID: 34241353 DOI: 10.1063/5.0056480] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Pressure plays essential roles in chemistry by altering structures and controlling chemical reactions. The extreme-pressure polarizable continuum model (XP-PCM) is an emerging method with an efficient quantum mechanical description of small- and medium-sized molecules at high pressure (on the order of GPa). However, its application to large molecular systems was previously hampered by a CPU computation bottleneck: the Pauli repulsion potential unique to XP-PCM requires the evaluation of a large number of electric field integrals, resulting in significant computational overhead compared to the gas-phase or standard-pressure polarizable continuum model calculations. Here, we exploit advances in graphical processing units (GPUs) to accelerate the XP-PCM-integral evaluations. This enables high-pressure quantum chemistry simulation of proteins that used to be computationally intractable. We benchmarked the performance using 18 small proteins in aqueous solutions. Using a single GPU, our method evaluates the XP-PCM free energy of a protein with over 500 atoms and 4000 basis functions within half an hour. The time taken by the XP-PCM-integral evaluation is typically 1% of the time taken for a gas-phase density functional theory (DFT) on the same system. The overall XP-PCM calculations require less computational effort than that for their gas-phase counterpart due to the improved convergence of self-consistent field iterations. Therefore, the description of the high-pressure effects with our GPU-accelerated XP-PCM is feasible for any molecule tractable for gas-phase DFT calculation. We have also validated the accuracy of our method on small molecules whose properties under high pressure are known from experiments or previous theoretical studies.
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Affiliation(s)
- Ariel Gale
- Department of Chemistry, Emory University, Atlanta, Georgia 30322, USA
| | - Eugen Hruska
- Department of Chemistry, Emory University, Atlanta, Georgia 30322, USA
| | - Fang Liu
- Department of Chemistry, Emory University, Atlanta, Georgia 30322, USA
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19
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Gaudreault R, Hervé V, van de Ven TGM, Mousseau N, Ramassamy C. Polyphenol-Peptide Interactions in Mitigation of Alzheimer's Disease: Role of Biosurface-Induced Aggregation. J Alzheimers Dis 2021; 81:33-55. [PMID: 33749653 DOI: 10.3233/jad-201549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder, responsible for nearly two-thirds of all dementia cases. In this review, we report the potential AD treatment strategies focusing on natural polyphenol molecules (green chemistry) and more specifically on the inhibition of polyphenol-induced amyloid aggregation/disaggregation pathways: in bulk and on biosurfaces. We discuss how these pathways can potentially alter the structure at the early stages of AD, hence delaying the aggregation of amyloid-β (Aβ) and tau. We also discuss multidisciplinary approaches, combining experimental and modelling methods, that can better characterize the biochemical and biophysical interactions between proteins and phenolic ligands. In addition to the surface-induced aggregation, which can occur on surfaces where protein can interact with other proteins and polyphenols, we suggest a new concept referred as "confinement stability". Here, on the contrary, the adsorption of Aβ and tau on biosurfaces other than Aβ- and tau-fibrils, e.g., red blood cells, can lead to confinement stability that minimizes the aggregation of Aβ and tau. Overall, these mechanisms may participate directly or indirectly in mitigating neurodegenerative diseases, by preventing protein self-association, slowing down the aggregation processes, and delaying the progression of AD.
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Affiliation(s)
- Roger Gaudreault
- Department of Physics, Université de Montréal, Montreal, QC, Canada
| | - Vincent Hervé
- INRS-Centre Armand-Frappier Santé Biotechnologie, Laval, QC, Canada
| | | | - Normand Mousseau
- Department of Physics, Université de Montréal, Montreal, QC, Canada
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20
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Vennelakanti V, Qi HW, Mehmood R, Kulik HJ. When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins. Chem Sci 2021; 12:1147-1162. [PMID: 35382134 PMCID: PMC8908278 DOI: 10.1039/d0sc05084a] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 11/18/2020] [Indexed: 01/02/2023] Open
Abstract
Hydrogen bonds (HBs) play an essential role in the structure and catalytic action of enzymes, but a complete understanding of HBs in proteins challenges the resolution of modern structural (i.e., X-ray diffraction) techniques and mandates computationally demanding electronic structure methods from correlated wavefunction theory for predictive accuracy. Numerous amino acid sidechains contain functional groups (e.g., hydroxyls in Ser/Thr or Tyr and amides in Asn/Gln) that can act as either HB acceptors or donors (HBA/HBD) and even form simultaneous, ambifunctional HB interactions. To understand the relative energetic benefit of each interaction, we characterize the potential energy surfaces of representative model systems with accurate coupled cluster theory calculations. To reveal the relationship of these energetics to the balance of these interactions in proteins, we curate a set of 4000 HBs, of which >500 are ambifunctional HBs, in high-resolution protein structures. We show that our model systems accurately predict the favored HB structural properties. Differences are apparent in HBA/HBD preference for aromatic Tyr versus aliphatic Ser/Thr hydroxyls because Tyr forms significantly stronger O–H⋯O HBs than N–H⋯O HBs in contrast to comparable strengths of the two for Ser/Thr. Despite this residue-specific distinction, all models of residue pairs indicate an energetic benefit for simultaneous HBA and HBD interactions in an ambifunctional HB. Although the stabilization is less than the additive maximum due both to geometric constraints and many-body electronic effects, a wide range of ambifunctional HB geometries are more favorable than any single HB interaction. Correlated wavefunction theory predicts and high-resolution crystal structure analysis confirms the important, stabilizing effect of simultaneous hydrogen bond donor and acceptor interactions in proteins.![]()
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Affiliation(s)
- Vyshnavi Vennelakanti
- Department of Chemical Engineering
- Massachusetts Institute of Technology
- Cambridge
- USA
- Department of Chemistry
| | - Helena W. Qi
- Department of Chemical Engineering
- Massachusetts Institute of Technology
- Cambridge
- USA
- Department of Chemistry
| | - Rimsha Mehmood
- Department of Chemical Engineering
- Massachusetts Institute of Technology
- Cambridge
- USA
- Department of Chemistry
| | - Heather J. Kulik
- Department of Chemical Engineering
- Massachusetts Institute of Technology
- Cambridge
- USA
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21
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Maia JDC, Dos Anjos Formiga Cabral L, Rocha GB. GPU algorithms for density matrix methods on MOPAC: linear scaling electronic structure calculations for large molecular systems. J Mol Model 2020; 26:313. [PMID: 33090341 DOI: 10.1007/s00894-020-04571-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 10/08/2020] [Indexed: 11/29/2022]
Abstract
Purification of the density matrix methods should be employed when dealing with complex chemical systems containing many atoms. The running times for these methods scale linearly with the number of atoms if we consider the sparsity from the density matrix. Since the efficiency expected from those methods is closely tied to the underlying parallel implementations of the linear algebra operations (e.g., P2 = P × P), we proposed a central processing unit (CPU) and graphics processing unit (GPU) parallel matrix-matrix multiplication in SVBR (symmetrical variable block row) format for energy calculations through the SP2 algorithm. This algorithm was inserted in MOPAC's MOZYME method, using the original LMO Fock matrix assembly, and the atomic integral calculation implemented on it. Correctness and performance tests show that the implemented SP2 is accurate and fast, as the GPU is able to achieve speedups up to 40 times for a water cluster system with 42,312 orbitals running in one NVIDIA K40 GPU card compared to the single-threaded version. The GPU-accelerated SP2 algorithm using the MOZYME LMO framework enables the calculations of semiempirical wavefunction with stricter SCF criteria for localized charged molecular systems, as well as the single-point energies of molecules with more than 100.000 LMO orbitals in less than 1 h. Graphical abstract Parallel CPU and GPU purification algorithms for electronic structure calculations were implemented in MOPAC's MOZYME method. Some matrices in these calculations, e.g., electron density P, are compressed, and the developed linear algebra operations deal with non-zero entries only. We employed the NVIDIA/CUDA platform to develop GPU algorithms, and accelerations up to 40 times for larger systems were achieved.
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Affiliation(s)
- Julio Daniel Carvalho Maia
- Centro de Informática, Universidade Federal da Paraíba, João Pessoa, PB, CEP: 58055-000, Brazil.,Theoretical and Computational Biophysics Group - Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | | | - Gerd Bruno Rocha
- Departamento de Química - CCEN, Universidade Federal da Paraíba, Caixa Postal: 5093, João Pessoa, PB, CEP: 58051-970, Brazil.
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22
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Seritan S, Bannwarth C, Fales BS, Hohenstein EG, Isborn CM, Kokkila‐Schumacher SIL, Li X, Liu F, Luehr N, Snyder JW, Song C, Titov AV, Ufimtsev IS, Wang L, Martínez TJ. TeraChem
: A graphical processing unit
‐accelerated
electronic structure package for
large‐scale
ab initio molecular dynamics. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2020. [DOI: 10.1002/wcms.1494] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Stefan Seritan
- Department of Chemistry and the PULSE Institute Stanford University Stanford California USA
- SLAC National Accelerator Laboratory Menlo Park California USA
| | - Christoph Bannwarth
- Department of Chemistry and the PULSE Institute Stanford University Stanford California USA
- SLAC National Accelerator Laboratory Menlo Park California USA
| | - Bryan S. Fales
- Department of Chemistry and the PULSE Institute Stanford University Stanford California USA
- SLAC National Accelerator Laboratory Menlo Park California USA
| | - Edward G. Hohenstein
- Department of Chemistry and the PULSE Institute Stanford University Stanford California USA
- SLAC National Accelerator Laboratory Menlo Park California USA
| | - Christine M. Isborn
- Department of Chemistry University of California Merced Merced California USA
| | | | - Xin Li
- Division of Theoretical Chemistry and Biology, School of Engineering Sciences in Chemistry, Biotechnology and Health KTH Royal Institute of Technology Stockholm Sweden
| | - Fang Liu
- Department of Chemical Engineering Massachusetts Institute of Technology Cambridge Massachusetts USA
| | | | | | - Chenchen Song
- Department of Physics University of California Berkeley Berkeley California USA
- Molecular Foundry Lawrence Berkeley National Laboratory Berkeley California USA
| | | | - Ivan S. Ufimtsev
- Department of Structural Biology Stanford University School of Medicine Stanford California USA
| | - Lee‐Ping Wang
- Department of Chemistry University of California Davis Davis California USA
| | - Todd J. Martínez
- Department of Chemistry and the PULSE Institute Stanford University Stanford California USA
- SLAC National Accelerator Laboratory Menlo Park California USA
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23
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Seritan S, Bannwarth C, Fales BS, Hohenstein EG, Kokkila-Schumacher SIL, Luehr N, Snyder JW, Song C, Titov AV, Ufimtsev IS, Martínez TJ. TeraChem: Accelerating electronic structure and ab initio molecular dynamics with graphical processing units. J Chem Phys 2020; 152:224110. [PMID: 32534542 PMCID: PMC7928072 DOI: 10.1063/5.0007615] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 05/19/2020] [Indexed: 11/15/2022] Open
Abstract
Developed over the past decade, TeraChem is an electronic structure and ab initio molecular dynamics software package designed from the ground up to leverage graphics processing units (GPUs) to perform large-scale ground and excited state quantum chemistry calculations in the gas and the condensed phase. TeraChem's speed stems from the reformulation of conventional electronic structure theories in terms of a set of individually optimized high-performance electronic structure operations (e.g., Coulomb and exchange matrix builds, one- and two-particle density matrix builds) and rank-reduction techniques (e.g., tensor hypercontraction). Recent efforts have encapsulated these core operations and provided language-agnostic interfaces. This greatly increases the accessibility and flexibility of TeraChem as a platform to develop new electronic structure methods on GPUs and provides clear optimization targets for emerging parallel computing architectures.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Ivan S. Ufimtsev
- Department of Structural Biology, Stanford University School of Medicine, Stanford, California 94305, USA
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24
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Seritan S, Thompson K, Martínez TJ. TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations. J Chem Inf Model 2020; 60:2126-2137. [PMID: 32267693 DOI: 10.1021/acs.jcim.9b01152] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The encapsulation and commoditization of electronic structure arise naturally as interoperability, and the use of nontraditional compute resources (e.g., new hardware accelerators, cloud computing) remains important for the computational chemistry community. We present TeraChem Cloud, a high-performance computing service (HPCS) that offers on-demand electronic structure calculations on both traditional HPC clusters and cloud-based hardware. The framework is designed using off-the-shelf web technologies and containerization to be extremely scalable and portable. Within the HPCS model, users can quickly develop new methods and algorithms in an interactive environment on their laptop while allowing TeraChem Cloud to distribute ab initio calculations across all available resources. This approach greatly increases the accessibility of hardware accelerators such as graphics processing units (GPUs) and flexibility for the development of new methods as additional electronic structure packages are integrated into the framework as alternative backends. Cost-performance analysis indicates that traditional nodes are the most cost-effective long-term solution, but commercial cloud providers offer cutting-edge hardware with competitive rates for short-term large-scale calculations. We demonstrate the power of the TeraChem Cloud framework by carrying out several showcase calculations, including the generation of 300,000 density functional theory energy and gradient evaluations on medium-sized organic molecules and reproducing 300 fs of nonadiabatic dynamics on the B800-B850 antenna complex in LH2, with the latter demonstration using over 50 Tesla V100 GPUs in a commercial cloud environment in 8 h for approximately $1250.
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Affiliation(s)
- Stefan Seritan
- Department of Chemistry and the PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, Menlo Park, California 94305, United States
| | - Keiran Thompson
- Department of Chemistry and the PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, Menlo Park, California 94305, United States
| | - Todd J Martínez
- Department of Chemistry and the PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, Menlo Park, California 94305, United States
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25
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Schmitz S, Seibert J, Ostermeir K, Hansen A, Göller AH, Grimme S. Quantum Chemical Calculation of Molecular and Periodic Peptide and Protein Structures. J Phys Chem B 2020; 124:3636-3646. [PMID: 32275425 DOI: 10.1021/acs.jpcb.0c00549] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Special-purpose classical force fields (FFs) provide good accuracy at very low computational cost, but their application is limited to systems for which potential energy functions are available. This excludes most metal-containing proteins or those containing cofactors. In contrast, the GFN2-xTB semiempirical quantum chemical method is parametrized for almost the entire periodic table. The accuracy of GFN2-xTB is assessed for protein structures with respect to experimental X-ray data. Furthermore, the results are compared with those of two special-purpose FFs, HF-3c, PM6-D3H4X, and PM7. The test sets include proteins without any prosthetic groups as well as metalloproteins. Crystal packing effects are examined for a set of smaller proteins to validate the molecular approach. For the proteins without prosthetic groups, the special purpose FF OPLS-2005 yields the smallest overall RMSD to the X-ray data but GFN2-xTB provides similarly good structures with even better bond-length distributions. For the metalloproteins with up to 5000 atoms, a good overall structural agreement is obtained with GFN2-xTB. The full geometry optimizations of protein structures with on average 1000 atoms in wall-times below 1 day establishes the GFN2-xTB method as a versatile tool for the computational treatment of various biomolecules with a good accuracy/computational cost ratio.
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Affiliation(s)
- Sarah Schmitz
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstraße 4, D-53115 Bonn, Germany
| | - Jakob Seibert
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstraße 4, D-53115 Bonn, Germany
| | - Katja Ostermeir
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstraße 4, D-53115 Bonn, Germany
| | - Andreas Hansen
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstraße 4, D-53115 Bonn, Germany
| | - Andreas H Göller
- Computational Molecular Design, Pharmaceuticals, R&D, Bayer AG, D-42096 Wuppertal, Germany
| | - Stefan Grimme
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstraße 4, D-53115 Bonn, Germany
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26
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Mehmood R, Kulik HJ. Both Configuration and QM Region Size Matter: Zinc Stability in QM/MM Models of DNA Methyltransferase. J Chem Theory Comput 2020; 16:3121-3134. [PMID: 32243149 DOI: 10.1021/acs.jctc.0c00153] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Quantum-mechanical/molecular-mechanical (QM/MM) methods are essential to the study of metalloproteins, but the relative importance of sampling and degree of QM treatment in achieving quantitative predictions is poorly understood. We study the relative magnitude of configurational and QM-region sensitivity of energetic and electronic properties in a representative Zn2+ metal binding site of a DNA methyltransferase. To quantify property variations, we analyze snapshots extracted from 250 ns of molecular dynamics simulation. To understand the degree of QM-region sensitivity, we perform analysis using QM regions ranging from a minimal 49-atom region consisting only of the Zn2+ metal and its four coordinating Cys residues up to a 628-atom QM region that includes residues within 12 Å of the metal center. Over the configurations sampled, we observe that illustrative properties (e.g., rigid Zn2+ removal energy) exhibit large fluctuations that are well captured with even minimal QM regions. Nevertheless, for both energetic and electronic properties, we observe a slow approach to asymptotic limits with similarly large changes in absolute values that converge only with larger (ca. 300-atom) QM region sizes. For the smaller QM regions, the electronic description of Zn2+ binding is incomplete: the metal binds too tightly and is too stabilized by the strong electrostatic potential of MM point charges, and the Zn-S bond covalency is overestimated. Overall, this work suggests that efficient sampling with QM/MM in small QM regions is an effective method to explore the influence of enzyme structure on target properties. At the same time, accurate descriptions of electronic and energetic properties require a larger QM region than the minimal metal-coordinating residues in order to converge treatment of both metal-local bonding and the overall electrostatic environment.
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Affiliation(s)
- Rimsha Mehmood
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.,Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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27
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Dasgupta S, Herbert JM. Using Atomic Confining Potentials for Geometry Optimization and Vibrational Frequency Calculations in Quantum-Chemical Models of Enzyme Active Sites. J Phys Chem B 2020; 124:1137-1147. [PMID: 31986049 DOI: 10.1021/acs.jpcb.9b11060] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Quantum-chemical studies of enzymatic reaction mechanisms sometimes use truncated active-site models as simplified alternatives to mixed quantum mechanics molecular mechanics (QM/MM) procedures. Eliminating the MM degrees of freedom reduces the complexity of the sampling problem, but the trade-off is the need to introduce geometric constraints in order to prevent structural collapse of the model system during geometry optimizations that do not contain a full protein backbone. These constraints may impair the efficiency of the optimization, and care must be taken to avoid artifacts such as imaginary vibrational frequencies. We introduce a simple alternative in which terminal atoms of the model system are placed in soft harmonic confining potentials rather than being rigidly constrained. This modification is simple to implement and straightforward to use in vibrational frequency calculations, unlike iterative constraint-satisfaction algorithms, and allows the optimization to proceed without constraint even though the practical result is to fix the anchor atoms in space. The new approach is more efficient for optimizing minima and transition states, as compared to the use of fixed-atom constraints, and also more robust against unwanted imaginary frequencies. We illustrate the method by application to several enzymatic reaction pathways where entropy makes a significant contribution to the relevant reaction barriers. The use of confining potentials correctly describes reaction paths and facilitates calculation of both vibrational zero-point and finite-temperature entropic corrections to barrier heights.
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Affiliation(s)
- Saswata Dasgupta
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
| | - John M Herbert
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
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28
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Reinholdt P, Kjellgren ER, Steinmann C, Olsen JMH. Cost-Effective Potential for Accurate Polarizable Embedding Calculations in Protein Environments. J Chem Theory Comput 2020; 16:1162-1174. [PMID: 31855427 DOI: 10.1021/acs.jctc.9b00616] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The fragment-based polarizable embedding (PE) model combined with an appropriate electronic structure method constitutes a highly efficient and accurate multiscale approach for computing spectroscopic properties of a central moiety including effects from its molecular environment through an embedding potential. There is, however, a comparatively high computational overhead associated with the computation of the embedding potential, which is derived from first-principles calculations on individual fragments of the environment. To reduce the computational cost associated with the calculation of embedding potential parameters, we developed a set of amino acid-specific transferable parameters tailored for large-scale PE-based calculations that include proteins. The amino acid-based parameters are obtained by simultaneously fitting to a set of reference electric potentials based on structures derived from a backbone-dependent rotamer library. The developed cost-effective polarizable protein potential (CP3) consists of atom-centered charges and isotropic dipole-dipole polarizabilities of the standard amino acids. In terms of reproduction of electric potentials, the CP3 is shown to perform consistently and with acceptable accuracy across both small tripeptide test systems and larger proteins. We show, through applications on realistic protein systems, that acceptable accuracy can be obtained by using a pure CP3 representation of the protein environment, thus altogether omitting the cost associated with the calculation of embedding potential parameters. High accuracy comparable to that of the full fragment-based approach can be achieved through a mixed description where the CP3 is used only to describe amino acids beyond a threshold distance from the central quantum part.
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Affiliation(s)
- Peter Reinholdt
- Department of Physics, Chemistry and Pharmacy , University of Southern Denmark , Campusvej 55 , DK-5230 Odense M , Denmark
| | - Erik Rosendahl Kjellgren
- Department of Physics, Chemistry and Pharmacy , University of Southern Denmark , Campusvej 55 , DK-5230 Odense M , Denmark
| | - Casper Steinmann
- Department of Chemistry and Bioscience , Aalborg University , Fredrik Bajers Vej 7H , DK-9220 Aalborg , Denmark
| | - Jógvan Magnus Haugaard Olsen
- Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry , UiT The Arctic University of Norway , Tromsø N-9037 , Norway
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29
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Valleau S, Martínez TJ. Reaction Dynamics of Cyanohydrins with Hydrosulfide in Water. J Phys Chem A 2019; 123:7210-7217. [DOI: 10.1021/acs.jpca.9b05735] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Stéphanie Valleau
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Todd J. Martínez
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
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30
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Yang Z, Liu F, Steeves AH, Kulik HJ. Quantum Mechanical Description of Electrostatics Provides a Unified Picture of Catalytic Action Across Methyltransferases. J Phys Chem Lett 2019; 10:3779-3787. [PMID: 31244268 DOI: 10.1021/acs.jpclett.9b01555] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Methyl transferases (MTases) are a well-studied class of enzymes for which competing enzymatic enhancement mechanisms have been suggested, ranging from structural methyl group CH···X hydrogen bonds (HBs) to electrostatic- and charge-transfer-driven stabilization of the transition state (TS). We identified all Class I MTases for which reasonable resolution (<2.0 Å) crystal structures could be used to form catalytically competent ternary complexes for multiscale (i.e., quantum-mechanical/molecular-mechanical or QM/MM) simulation of the SN2 methyl transfer reaction coordinate. The four Class I MTases studied have both distinct functions (e.g., protein repair or biosynthesis) and substrate nucleophiles (i.e., C, N, or O). While CH···X HBs stabilize all reactant complexes, no universal TS stabilization role is found for these interactions in MTases. A consistent picture is instead obtained through analysis of charge transfer and electrostatics, wherein much of cofactor-substrate charge separation is maintained in the TS region, and electrostatic potential is correlated with substrate nucleophilicity (i.e., intrinsic reactivity).
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Affiliation(s)
- Zhongyue Yang
- Department of Chemical Engineering , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Fang Liu
- Department of Chemical Engineering , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Adam H Steeves
- Department of Chemical Engineering , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Heather J Kulik
- Department of Chemical Engineering , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
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31
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Mehmood R, Qi HW, Steeves AH, Kulik HJ. The Protein’s Role in Substrate Positioning and Reactivity for Biosynthetic Enzyme Complexes: The Case of SyrB2/SyrB1. ACS Catal 2019. [DOI: 10.1021/acscatal.9b00865] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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32
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Northey T, Kirrander A. Ab Initio Fragment Method for Calculating Molecular X-ray Diffraction. J Phys Chem A 2019; 123:3395-3406. [PMID: 30892904 DOI: 10.1021/acs.jpca.9b00621] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A fragment-based approach for the prediction of elastic X-ray scattering is presented. The total diffraction pattern is assembled from anisotropic form factors calculated for individual molecular fragments, optionally including corrections for pairwise interactions between fragments. The approach is evaluated against full ab initio scattering calculations in the peptide diphenylalanine, and the optimal selection of fragments is examined in the ethanol molecule. The approach is found to improve significantly on the independent atom model while remaining conceptually simple and computationally efficient. It is expected to be particularly useful for macromolecules with repeated subunits, such as peptides, proteins, DNA, or RNA and other polymers, where it is straightforward to define appropriate fragments.
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Affiliation(s)
- Thomas Northey
- EaStCHEM, School of Chemistry , University of Edinburgh , David Brewster Road , Edinburgh EH9 3FJ , United Kingdom
| | - Adam Kirrander
- EaStCHEM, School of Chemistry , University of Edinburgh , David Brewster Road , Edinburgh EH9 3FJ , United Kingdom
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33
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Qi HW, Kulik HJ. Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis. J Chem Inf Model 2019; 59:2199-2211. [DOI: 10.1021/acs.jcim.9b00144] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Helena W. Qi
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Heather J. Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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34
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Murphy BA. Circadian and Circannual Regulation in the Horse: Internal Timing in an Elite Athlete. J Equine Vet Sci 2019; 76:14-24. [PMID: 31084748 DOI: 10.1016/j.jevs.2019.02.026] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 02/25/2019] [Indexed: 12/20/2022]
Abstract
Biological rhythms evolved to provide temporal coordination across all tissues and organs and allow synchronization of physiology with predictable environmental cycles. Most important of these are circadian and circannual rhythms, primarily regulated via photoperiod signals from the retina. Understanding the nature of physiological rhythms in horses is crucially important for equine management. Predominantly, they have been removed from exposure to their natural environmental stimuli; the seasonally changing photoperiod, continuous foraging and feeding activity, social herd interactions, and the continuous low-intensity exercise of a grassland dweller. These have been replaced in many cases with confined indoor housing, regimental feeding and exercise times, social isolation, and exposure to lighting that is often erratic and does not come close to mimicking the spectral composition of sunlight. Man has further altered seasonal timing cues through the use of artificial lighting programs that impact reproductive behavior, breeding efficiency, and the development of youngstock. Understanding how these new environmental cues (some stronger and some weaker) impact the internal physiology of the horse in the context of the natural endogenous rhythms that evolved over millennia is key to helping to improve equine health, welfare, and performance, now and into the future. This review provides an overview of the field, highlights the recent discoveries related to biological timing in horses, and discusses the implications that these findings may have for the production and management of the elite equine athlete.
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Affiliation(s)
- Barbara A Murphy
- School of Agriculture and Food Science, University College Dublin, Dublin, Ireland.
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35
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Kapranov SV, Kouzaev GA. Nonlinear dynamics of dipoles in microwave electric field of a nanocoaxial tubular reactor. Mol Phys 2019. [DOI: 10.1080/00268976.2018.1524526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- Sergey V. Kapranov
- Department of Electronic Systems, Norwegian University of Science and Technology – NTNU, Gløshaugen, Trondheim, Norway
| | - Guennadi A. Kouzaev
- Department of Electronic Systems, Norwegian University of Science and Technology – NTNU, Gløshaugen, Trondheim, Norway
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36
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Yang Z, Mehmood R, Wang M, Qi HW, Steeves AH, Kulik HJ. Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation. REACT CHEM ENG 2019; 4:298-315. [PMID: 31572618 PMCID: PMC6768422 DOI: 10.1039/c8re00213d] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Enzymes have evolved to facilitate challenging reactions at ambient conditions with specificity seldom matched by other catalysts. Computational modeling provides valuable insight into catalytic mechanism, and the large size of enzymes mandates multi-scale, quantum mechanical-molecular mechanical (QM/MM) simulations. Although QM/MM plays an essential role in balancing simulation cost to enable sampling with full QM treatment needed to understand electronic structure in enzyme active sites, the relative importance of these two strategies for understanding enzyme mechanism is not well known. We explore challenges in QM/MM for studying the reactivity and stability of three diverse enzymes: i) Mg2+-dependent catechol O-methyltransferase (COMT), ii) radical enzyme choline trimethylamine lyase (CutC), and iii) DNA methyltransferase (DNMT1), which has structural Zn2+ binding sites. In COMT, strong non-covalent interactions lead to long range coupling of electronic structure properties across the active site, but the more isolated nature of the metallocofactor in DNMT1 leads to faster convergence of some properties. We quantify these effects in COMT by computing covariance matrices of by-residue electronic structure properties during dynamics and along the reaction coordinate. In CutC, we observe spontaneous bond cleavage following initiation events, highlighting the importance of sampling and dynamics. We use electronic structure analysis to quantify the relative importance of CHO and OHO non-covalent interactions in imparting reactivity. These three diverse cases enable us to provide some general recommendations regarding QM/MM simulation of enzymes.
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Affiliation(s)
- Zhongyue Yang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Rimsha Mehmood
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Mengyi Wang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Helena W. Qi
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Adam H. Steeves
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Heather J. Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
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37
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Kulik HJ. MODELING MECHANOCHEMISTRY FROM FIRST PRINCIPLES. REVIEWS IN COMPUTATIONAL CHEMISTRY 2018. [DOI: 10.1002/9781119518068.ch6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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38
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Ricard TC, Iyengar SS. Efficiently Capturing Weak Interactions in ab Initio Molecular Dynamics with on-the-Fly Basis Set Extrapolation. J Chem Theory Comput 2018; 14:5535-5552. [DOI: 10.1021/acs.jctc.8b00803] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Timothy C. Ricard
- Department of Chemistry and Department of Physics, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, United States
| | - Srinivasan S. Iyengar
- Department of Chemistry and Department of Physics, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, United States
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39
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Morrison AF, Epifanovsky E, Herbert JM. Double-buffered, heterogeneous CPU + GPU integral digestion algorithm for single-excitation calculations involving a large number of excited states. J Comput Chem 2018; 39:2173-2182. [PMID: 30368836 DOI: 10.1002/jcc.25531] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Revised: 05/12/2018] [Accepted: 06/14/2018] [Indexed: 01/29/2023]
Abstract
The most widely used quantum-chemical models for excited states are single-excitation theories, a category that includes configuration interaction with single substitutions, time-dependent density functional theory, and also a recently developed ab initio exciton model. When a large number of excited states are desired, these calculations incur a significant bottleneck in the "digestion" step in which two-electron integrals are contracted with density or density-like matrices. We present an implementation that moves this step onto graphical processing units (GPUs), and introduce a double-buffer scheme that minimizes latency by computing integrals on the central processing units (CPUs) concurrently with their digestion on the GPUs. An automatic code generation scheme simplifies the implementation of high-performance GPU kernels. For the exciton model, which requires separate excited-state calculations on each electronically coupled chromophore, the heterogeneous implementation described here results in speedups of 2-6× versus a CPU-only implementation. For traditional time-dependent density functional theory calculations, we obtain speedups of up to 5× when a large number of excited states is computed. © 2018 Wiley Periodicals, Inc.
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Affiliation(s)
- Adrian F Morrison
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio.,Q-Chem Inc., Pleasanton, California
| | | | - John M Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio
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40
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Kulik HJ. Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer. Phys Chem Chem Phys 2018; 20:20650-20660. [PMID: 30059109 PMCID: PMC6085747 DOI: 10.1039/c8cp03871f] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Hybrid quantum mechanical-molecular mechanical (QM/MM) simulations provide key insights into enzyme structure-function relationships. Numerous studies have demonstrated that large QM regions are needed to systematically converge ground state, zero temperature properties with electrostatic embedding QM/MM. However, it is not well known if ab initio QM/MM free energy simulations have this same dependence, in part due to the hundreds of thousands of energy evaluations required for free energy estimations that in turn limit QM region size. Here, we leverage recent advances in electronic structure efficiency and accuracy to carry out range-separated hybrid density functional theory free energy simulations in a representative methyltransferase. By studying 200 ps of ab initio QM/MM dynamics for each of five QM regions from minimal (64 atoms) to one-sixth of the protein (544 atoms), we identify critical differences between large and small QM region QM/MM in charge transfer between substrates and active site residues as well as in geometric structure and dynamics that coincide with differences in predicted free energy barriers. Distinct geometric and electronic structure features in the largest QM region indicate that important aspects of enzymatic rate enhancement in methyltransferases are identified with large-scale electronic structure.
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Affiliation(s)
- Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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41
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Pinney MM, Natarajan A, Yabukarski F, Sanchez DM, Liu F, Liang R, Doukov T, Schwans JP, Martinez TJ, Herschlag D. Structural Coupling Throughout the Active Site Hydrogen Bond Networks of Ketosteroid Isomerase and Photoactive Yellow Protein. J Am Chem Soc 2018; 140:9827-9843. [DOI: 10.1021/jacs.8b01596] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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42
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Amaro RE, Mulholland AJ. Multiscale Methods in Drug Design Bridge Chemical and Biological Complexity in the Search for Cures. Nat Rev Chem 2018; 2:0148. [PMID: 30949587 PMCID: PMC6445369 DOI: 10.1038/s41570-018-0148] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Drug action is inherently multiscale: it connects molecular interactions to emergent properties at cellular and larger scales. Simulation techniques at each of these different scales are already central to drug design and development, but methods capable of connecting across these scales will extend understanding of complex mechanisms and the ability to predict biological effects. Improved algorithms, ever-more-powerful computing architectures and the accelerating growth of rich datasets are driving advances in multiscale modeling methods capable of bridging chemical and biological complexity from the atom to the cell. Particularly exciting is the development of highly detailed, structure-based, physical simulations of biochemical systems, which are now able to access experimentally relevant timescales for large systems and, at the same time, achieve unprecedented accuracy. In this Perspective, we discuss how emerging data-rich, physics-based multiscale approaches are of the cusp of realizing long-promised impact in the discovery, design and development of novel therapeutics. We highlight emerging methods and applications in this growing field, and outline how different scales can be combined in practical modelling and simulation strategies.
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Affiliation(s)
- Rommie E Amaro
- Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0304
| | - Adrian J Mulholland
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
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43
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Mittal S, Shukla D. Recruiting machine learning methods for molecular simulations of proteins. MOLECULAR SIMULATION 2018. [DOI: 10.1080/08927022.2018.1448976] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Shriyaa Mittal
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign , Urbana, IL, USA
| | - Diwakar Shukla
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign , Urbana, IL, USA
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign , Urbana, IL, USA
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44
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Affiliation(s)
- Rahul Kaushik
- Kusuma
School of Biological Sciences, Indian Institute of Technology, Delhi, India
- Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology, Delhi, India
| | - Ankita Singh
- Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology, Delhi, India
- Department
of Bioinformatics, Banasthali Vidyapith, Banasthali, India
| | - B. Jayaram
- Kusuma
School of Biological Sciences, Indian Institute of Technology, Delhi, India
- Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology, Delhi, India
- Department
of Chemistry, Indian Institute of Technology, Delhi, India
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45
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Liu KY, Herbert JM. Understanding the many-body expansion for large systems. III. Critical role of four-body terms, counterpoise corrections, and cutoffs. J Chem Phys 2017; 147:161729. [DOI: 10.1063/1.4986110] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Kuan-Yu Liu
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
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46
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Fedorov DG, Kitaura K. Many-body expansion of the Fock matrix in the fragment molecular orbital method. J Chem Phys 2017; 147:104106. [DOI: 10.1063/1.5001018] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
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47
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Heshmat M, Privalov T. Testing the nature of reaction coordinate describing interaction of H2 with carbonyl carbon, activated by Lewis acid complexation, and the Lewis basic solvent: A Born-Oppenheimer molecular dynamics study with explicit solvent. J Chem Phys 2017; 147:094302. [DOI: 10.1063/1.4999708] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Mojgan Heshmat
- Department of Organic Chemistry, Stockholm University, Stockholm 10691, Sweden
| | - Timofei Privalov
- Department of Organic Chemistry, Stockholm University, Stockholm 10691, Sweden
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48
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Culka M, Gisdon FJ, Ullmann GM. Computational Biochemistry-Enzyme Mechanisms Explored. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2017; 109:77-112. [PMID: 28683923 DOI: 10.1016/bs.apcsb.2017.04.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Understanding enzyme mechanisms is a major task to achieve in order to comprehend how living cells work. Recent advances in biomolecular research provide huge amount of data on enzyme kinetics and structure. The analysis of diverse experimental results and their combination into an overall picture is, however, often challenging. Microscopic details of the enzymatic processes are often anticipated based on several hints from macroscopic experimental data. Computational biochemistry aims at creation of a computational model of an enzyme in order to explain microscopic details of the catalytic process and reproduce or predict macroscopic experimental findings. Results of such computations are in part complementary to experimental data and provide an explanation of a biochemical process at the microscopic level. In order to evaluate the mechanism of an enzyme, a structural model is constructed which can be analyzed by several theoretical approaches. Several simulation methods can and should be combined to get a reliable picture of the process of interest. Furthermore, abstract models of biological systems can be constructed combining computational and experimental data. In this review, we discuss structural computational models of enzymatic systems. We first discuss various models to simulate enzyme catalysis. Furthermore, we review various approaches how to characterize the enzyme mechanism both qualitatively and quantitatively using different modeling approaches.
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Affiliation(s)
- Martin Culka
- Computational Biochemistry, University of Bayreuth, Bayreuth, Germany
| | - Florian J Gisdon
- Computational Biochemistry, University of Bayreuth, Bayreuth, Germany
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49
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Hayashi S, Uchida Y, Hasegawa T, Higashi M, Kosugi T, Kamiya M. QM/MM Geometry Optimization on Extensive Free-Energy Surfaces for Examination of Enzymatic Reactions and Design of Novel Functional Properties of Proteins. Annu Rev Phys Chem 2017; 68:135-154. [DOI: 10.1146/annurev-physchem-052516-050827] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Shigehiko Hayashi
- Department of Chemistry, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan;, , ,
| | - Yoshihiro Uchida
- Department of Chemistry, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan;, , ,
| | - Taisuke Hasegawa
- Department of Chemistry, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan;, , ,
| | - Masahiro Higashi
- Department of Chemistry, Biology and Marine Science, University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan
| | - Takahiro Kosugi
- Research Center of Integrative Molecular Systems, Institute for Molecular Science, and Department of Structural Molecular Science, School of Physical Science, The Graduate University for Advanced Studies (SOKENDAI), Okazaki 444-8585, Japan
| | - Motoshi Kamiya
- Department of Chemistry, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan;, , ,
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50
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Wang LP, McKiernan KA, Gomes J, Beauchamp KA, Head-Gordon T, Rice JE, Swope WC, Martínez TJ, Pande VS. Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15. J Phys Chem B 2017; 121:4023-4039. [PMID: 28306259 DOI: 10.1021/acs.jpcb.7b02320] [Citation(s) in RCA: 166] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical force fields for simulation of proteins. We developed the AMBER-FB15 protein force field by building a high-quality quantum chemical data set consisting of comprehensive potential energy scans and employing the ForceBalance software package for parameter optimization. The optimized potential surface allows for more significant thermodynamic fluctuations away from local minima. In validation studies where simulation results are compared to experimental measurements, AMBER-FB15 in combination with the updated TIP3P-FB water model predicts equilibrium properties with equivalent accuracy, and temperature dependent properties with significantly improved accuracy, in comparison with published models. We also discuss the effect of changing the protein force field and water model on the simulation results.
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Affiliation(s)
- Lee-Ping Wang
- Department of Chemistry, University of California, Davis , Davis, California 95616, United States
| | - Keri A McKiernan
- Department of Chemistry, Stanford University , Stanford, California 94305, United States
| | - Joseph Gomes
- Department of Chemistry, Stanford University , Stanford, California 94305, United States
| | - Kyle A Beauchamp
- Counsyl, Inc. , South San Francisco, California 94080, United States
| | - Teresa Head-Gordon
- Departments of Chemistry, Bioengineering, Chemical and Biomolecular Engineering, and Kenneth S. Pitzer Center for Theoretical Chemistry, University of California, Berkeley , Berkeley, California 94720, United States.,Chemical Sciences Division, Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States
| | - Julia E Rice
- IBM Almaden Research Center, IBM Research , San Jose, California 95120, United States
| | - William C Swope
- IBM Almaden Research Center, IBM Research , San Jose, California 95120, United States
| | - Todd J Martínez
- Department of Chemistry, Stanford University , Stanford, California 94305, United States.,PULSE Institute, Stanford University , Stanford, California 94305, United States.,SLAC National Accelerator Laboratory , Menlo Park, California 94025, United States
| | - Vijay S Pande
- Department of Chemistry, Stanford University , Stanford, California 94305, United States.,Departments of Computer Science, Structural Biology, and Program in Biophysics, Stanford University , Stanford, California 94305, United States
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