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Wu Y, Zhang S, York DM, Wang L. Adsorption of Flavonoids in a Transcriptional Regulator TtgR: Relative Binding Free Energies and Intermolecular Interactions. J Phys Chem B 2024. [PMID: 38935925 DOI: 10.1021/acs.jpcb.4c02303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Abstract
Antimicrobial resistance in bacteria often arises from their ability to actively identify and expel toxic compounds. The bacterium strain Pseudomonas putida DOT-T1E utilizes its TtgABC efflux pump to confer robust resistance against antibiotics, flavonoids, and organic solvents. This resistance mechanism is intricately regulated at the transcriptional level by the TtgR protein. Through molecular dynamics and alchemical free energy simulations, we systematically examine the binding of seven flavonoids and their derivatives with the TtgR transcriptional regulator. Our simulations reveal distinct binding geometries and free energies for the flavonoids in the active site of the protein, which are driven by a range of noncovalent forces encompassing van der Waals, electrostatic, and hydrogen bonding interactions. The interplay of molecular structures, substituent patterns, and intermolecular interactions effectively stabilizes the bound flavonoids, confining their movements within the TtgR binding pocket. These findings yield valuable insights into the molecular determinants that govern ligand recognition in TtgR and shed light on the mechanism of antimicrobial resistance in P. putida DOT-T1E.
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Affiliation(s)
- Yuxuan Wu
- Department of Chemistry and Chemical Biology, Institute for Quantitative Biomedicine, Laboratory for Biomolecular Simulation Research, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Shi Zhang
- Department of Chemistry and Chemical Biology, Institute for Quantitative Biomedicine, Laboratory for Biomolecular Simulation Research, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Darrin M York
- Department of Chemistry and Chemical Biology, Institute for Quantitative Biomedicine, Laboratory for Biomolecular Simulation Research, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Lu Wang
- Department of Chemistry and Chemical Biology, Institute for Quantitative Biomedicine, Laboratory for Biomolecular Simulation Research, Rutgers University, Piscataway, New Jersey 08854, United States
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2
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de Carvalho Matias EG, Bezerra KS, Costa AHL, Clemente Junior WS, Oliveira JIN, Ribeiro Junior LA, Galvão DS, Fulco UL. Quantum biochemical analysis of the TtgR regulator and effectors. Sci Rep 2024; 14:8519. [PMID: 38609407 PMCID: PMC11015042 DOI: 10.1038/s41598-024-58441-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
The recent expansion of multidrug-resistant (MDR) pathogens poses significant challenges in treating healthcare-associated infections. Although antibacterial resistance occurs by numerous mechanisms, active efflux of the drugs is a critical concern. A single species of efflux pump can produce a simultaneous resistance to several drugs. One of the best-studied efflux pumps is the TtgABC: a tripartite resistance-nodulation-division (RND) efflux pump implicated in the intrinsic antibiotic resistance in Pseudomonas putida DOT-T1E. The expression of the TtgABC gene is down-regulated by the HTH-type transcriptional repressor TtgR. In this context, by employing quantum chemistry methods based on the Density Functional Theory (DFT) within the Molecular Fragmentation with Conjugate Caps (MFCC) approach, we investigate the coupling profiles of the transcriptional regulator TtgR in complex with quercetin (QUE), a natural polyphenolic flavonoid, tetracycline (TAC), and chloramphenicol (CLM), two broad-spectrum antimicrobial agents. Our quantum biochemical computational results show the: [i] convergence radius, [ii] total binding energy, [iii] relevance (energetically) of the ligands regions, and [iv] most relevant amino acids residues of the TtgR-QUE/TAC/CLM complexes, pointing out distinctions and similarities among them. These findings improve the understanding of the binding mechanism of effectors and facilitate the development of new chemicals targeting TtgR, helping in the battle against the rise of resistance to antimicrobial drugs. These advances are crucial in the ongoing fight against rising antimicrobial drug resistance, providing hope for a future where healthcare-associated infections can be more beneficially treated.
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Affiliation(s)
- E G de Carvalho Matias
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil
| | - K S Bezerra
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil
| | - A H Lima Costa
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil
| | - W S Clemente Junior
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil
| | - J I N Oliveira
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil
| | - L A Ribeiro Junior
- Institute of Physics, University of Brasília, Brasília, 70919-970, Brazil.
| | - D S Galvão
- Applied Physics Department, University of Campinas, Campinas, São Paulo, Brazil
| | - U L Fulco
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59072-970, Brazil
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3
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Liu X, Zheng L, Qin C, Cong Y, Zhang JZH, Sun Z. Comprehensive Evaluation of End-Point Free Energy Techniques in Carboxylated-Pillar[6]arene Host–Guest Binding: III. Force-Field Comparison, Three-Trajectory Realization and Further Dielectric Augmentation. Molecules 2023; 28:molecules28062767. [PMID: 36985739 PMCID: PMC10059726 DOI: 10.3390/molecules28062767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 03/13/2023] [Accepted: 03/17/2023] [Indexed: 03/22/2023] Open
Abstract
Host–guest binding, despite the relatively simple structural and chemical features of individual components, still poses a challenge in computational modelling. The extreme underperformance of standard end-point methods in host–guest binding makes them practically useless. In the current work, we explore a potentially promising modification of the three-trajectory realization. The alteration couples the binding-induced structural reorganization into free energy estimation and suffers from dramatic fluctuations in internal energies in protein–ligand situations. Fortunately, the relatively small size of host–guest systems minimizes the magnitude of internal fluctuations and makes the three-trajectory realization practically suitable. Due to the incorporation of intra-molecular interactions in free energy estimation, a strong dependence on the force field parameters could be incurred. Thus, a term-specific investigation of transferable GAFF derivatives is presented, and noticeable differences in many aspects are identified between commonly applied GAFF and GAFF2. These force-field differences lead to different dynamic behaviors of the macrocyclic host, which ultimately would influence the end-point sampling and binding thermodynamics. Therefore, the three-trajectory end-point free energy calculations are performed with both GAFF versions. Additionally, due to the noticeable differences between host dynamics under GAFF and GAFF2, we add additional benchmarks of the single-trajectory end-point calculations. When only the ranks of binding affinities are pursued, the three-trajectory realization performs very well, comparable to and even better than the regressed PBSA_E scoring function and the dielectric constant-variable regime. With the GAFF parameter set, the TIP3P water in explicit solvent sampling and either PB or GB implicit solvent model in free energy estimation, the predictive power of the three-trajectory realization in ranking calculations surpasses all existing end-point methods on this dataset. We further combine the three-trajectory realization with another promising modified end-point regime of varying the interior dielectric constant. The combined regime does not incur sizable improvements for ranks and deviations from experiment exhibit non-monotonic variations.
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Affiliation(s)
- Xiao Liu
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China
- Correspondence: (X.L.); (Y.C.); (Z.S.)
| | - Lei Zheng
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Department of Chemistry, New York University, New York, NY 10003, USA
| | - Chu Qin
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Yalong Cong
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
- Correspondence: (X.L.); (Y.C.); (Z.S.)
| | - John Z. H. Zhang
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Department of Chemistry, New York University, New York, NY 10003, USA
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhaoxi Sun
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
- Correspondence: (X.L.); (Y.C.); (Z.S.)
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4
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Liu X, Zheng L, Qin C, Zhang JZH, Sun Z. Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure. J Comput Aided Mol Des 2022; 36:735-752. [PMID: 36136209 DOI: 10.1007/s10822-022-00475-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/06/2022] [Indexed: 10/14/2022]
Abstract
Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein-ligand binding, the standard end-point calculations cannot produce useful outcomes in host-guest binding and thus are not recommended unless alterations are performed.
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Affiliation(s)
- Xiao Liu
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China.
| | - Lei Zheng
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China
| | - Chu Qin
- School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai, 201620, China
| | - John Z H Zhang
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China.,School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China.,Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.,Department of Chemistry, New York University, New York, NY, 10003, USA
| | - Zhaoxi Sun
- College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
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5
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Wang H, Liu H, Ning S, Zeng C, Zhao Y. DLSSAffinity: protein-ligand binding affinity prediction via a deep learning model. Phys Chem Chem Phys 2022; 24:10124-10133. [PMID: 35416807 DOI: 10.1039/d1cp05558e] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Evaluating the protein-ligand binding affinity is a substantial part of the computer-aided drug discovery process. Most of the proposed computational methods predict protein-ligand binding affinity using either limited full-length protein 3D structures or simple full-length protein sequences as the input features. Thus, protein-ligand binding affinity prediction remains a fundamental challenge in drug discovery. In this study, we proposed a novel deep learning-based approach, DLSSAffinity, to accurately predict the protein-ligand binding affinity. Unlike the existing methods, DLSSAffinity uses the pocket-ligand structural pairs as the local information to predict short-range direct interactions. Besides, DLSSAffinity also uses the full-length protein sequence and ligand SMILES as the global information to predict long-range indirect interactions. We tested DLSSAffinity on the PDBbind benchmark. The results showed that DLSSAffinity achieves Pearson's R = 0.79, RMSE = 1.40, and SD = 1.35 on the test set. Comparing DLSSAffinity with the existing state-of-the-art deep learning-based binding affinity prediction methods, the DLSSAffinity model outperforms other models. These results demonstrate that combining global sequence and local structure information as the input features of a deep learning model can improve the accuracy of protein-ligand binding affinity prediction.
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Affiliation(s)
- Huiwen Wang
- School of Physics and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
| | - Haoquan Liu
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan 430079, China.
| | - Shangbo Ning
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan 430079, China.
| | - Chengwei Zeng
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan 430079, China.
| | - Yunjie Zhao
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan 430079, China.
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6
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Sun Z, He Q. Seeding the multi-dimensional nonequilibrium pulling for Hamiltonian variation: indirect nonequilibrium free energy simulations at QM levels. Phys Chem Chem Phys 2022; 24:8800-8819. [PMID: 35352744 DOI: 10.1039/d2cp00355d] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The combination of free energy simulations in the alchemical and configurational spaces provides a feasible route to access the thermodynamic profiles under a computationally demanding target Hamiltonian. Normally, due to the significant differences between the computational cost of ab initio quantum mechanics (QM) calculations and those of semi-empirical quantum mechanics (SQM) and molecular mechanics (MM), this indirect method could be used to obtain the QM thermodynamics by combining the SQM or MM results and the SQM-to-QM or MM-to-QM corrections. In our previous work, a multi-dimensional nonequilibrium pulling framework for Hamiltonian variations was introduced based on bidirectional pulling and bidirectional reweighting. The method performs nonequilibrium free energy simulations in the configurational space to obtain the thermodynamic profile along the conformational change pathway under a selected computationally efficient Hamiltonian, and uses the nonequilibrium alchemical method to correct or perturb the thermodynamic profile to that under the target Hamiltonian. The BAR-based method is designed to achieve the best generality and transferability and thus leads to modest (∼20 fold) speedup. In this work, we explore the possibility of further accelerating the nonequilibrium free energy simulation by employing unidirectional pulling and using the selection criterion to obtain the initial configurations used to initiate nonequilibrium trajectories following the idea of adaptive steered molecular dynamics (ASMD). A single initial condition is used to seed the whole multi-dimensional nonequilibrium free energy simulation and the sampling is performed fully in the nonequilibrium ensemble. Introducing very short ps-length equilibrium sampling to grab more initial seeds could also be helpful. The ASMD scheme estimates the free energy difference with the unidirectional exponential average (EXP), but it does not follow exactly the requirements of the EXP estimator. Another deficiency of the seeding simulation is the inherently sequential or serial pulling due to the inter-segment dependency, which triggers some problems in the parallelizability of the simulation. Numerical tests are performed to grasp some insights and guidelines for using this selection-criterion-based ASMD scheme. The presented selection-criterion-based multi-dimensional ASMD scheme follows the same perturbation network of the BAR-based method, and thus could be used in various Hamiltonian-variation cases.
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Affiliation(s)
- Zhaoxi Sun
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Institute of Theoretical and Computational Chemistry, Peking University, Beijing 100871, China.
| | - Qiaole He
- AI Department of Enzymaster (Ningbo) Bio-Engineering Co., Ltd, North Century Avenue 333, 315100 Ningbo, China
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7
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Sun Z, Liu Z. BAR‐Based Multi‐Dimensional Nonequilibrium Pulling for Indirect Construction of QM/MM Free Energy Landscapes: Varying the QM Region. ADVANCED THEORY AND SIMULATIONS 2021. [DOI: 10.1002/adts.202100185] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Zhaoxi Sun
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering Peking University Beijing 100871 China
| | - Zhirong Liu
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering Peking University Beijing 100871 China
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9
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Huai Z, Yang H, Sun Z. Binding thermodynamics and interaction patterns of human purine nucleoside phosphorylase-inhibitor complexes from extensive free energy calculations. J Comput Aided Mol Des 2021; 35:643-656. [PMID: 33759016 DOI: 10.1007/s10822-021-00382-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 03/13/2021] [Indexed: 11/29/2022]
Abstract
Human purine nucleoside phosphorylase (hPNP) plays a significant role in the catabolism of deoxyguanosine. The trimeric protein is an important target in the treatment of T-cell cancers and autoimmune disorders. Experimental studies on the inhibition of the hPNP observe that the first ligand bound to one of three subunits effectively inhibits the protein, while the binding of more ligands to the subsequent sites shows negative cooperativities. In this work, we performed extensive end-point and alchemical free energy calculations to determine the binding thermodynamics of the trimeric protein-ligand system. 13 Immucillin inhibitors with experimental results are under calculation. Two widely accepted charge schemes for small molecules including AM1-BCC and RESP are adopted for ligands. The results of RESP are in better agreement with the experimental reference. Further investigations of the interaction networks in the protein-ligand complexes reveal that several residues play significant roles in stabilizing the complex structure. The most commonly observed ones include PHE200, GLU201, MET219, and ASN243. The conformations of the protein in different protein-ligand complexes are observed to be similar. We expect these insights to aid the development of potent drugs targeting hPNP.
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Affiliation(s)
- Zhe Huai
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai, 200062, China
| | - Huaiyu Yang
- College of Engineering, Hebei Normal University, Shijiazhuang, 050024, China
| | - Zhaoxi Sun
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai, 200062, China.
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Huai Z, Shen Z, Sun Z. Binding Thermodynamics and Interaction Patterns of Inhibitor-Major Urinary Protein-I Binding from Extensive Free-Energy Calculations: Benchmarking AMBER Force Fields. J Chem Inf Model 2020; 61:284-297. [PMID: 33307679 DOI: 10.1021/acs.jcim.0c01217] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Mouse major urinary protein (MUP) plays a key role in the pheromone communication system. The one-end-closed β-barrel of MUP-I forms a small, deep, and hydrophobic central cavity, which could accommodate structurally diverse ligands. Previous computational studies employed old protein force fields and short simulation times to determine the binding thermodynamics or investigated only a small number of structurally similar ligands, which resulted in sampled regions far from the experimental structure, nonconverged sampling outcomes, and limited understanding of the possible interaction patterns that the cavity could produce. In this work, extensive end-point and alchemical free-energy calculations with advanced protein force fields were performed to determine the binding thermodynamics of a series of MUP-inhibitor systems and investigate the inter- and intramolecular interaction patterns. Three series of inhibitors with a total of 14 ligands were simulated. We independently simulated the MUP-inhibitor complexes under two advanced AMBER force fields. Our benchmark test showed that the advanced AMBER force fields including AMBER19SB and AMBER14SB provided better descriptions of the system, and the backbone root-mean-square deviation (RMSD) was significantly lowered compared with previous computational studies with old protein force fields. Surprisingly, although the latest AMBER force field AMBER19SB provided better descriptions of various observables, it neither improved the binding thermodynamics nor lowered the backbone RMSD compared with the previously proposed and widely used AMBER14SB. The older but widely used AMBER14SB actually achieved better performance in the prediction of binding affinities from the alchemical and end-point free-energy calculations. We further analyzed the protein-ligand interaction networks to identify important residues stabilizing the bound structure. Six residues including PHE38, LEU40, PHE90, ALA103, LEU105, and TYR120 were found to contribute the most significant part of protein-ligand interactions, and 10 residues were found to provide favorable interactions stabilizing the bound state. The two AMBER force fields gave extremely similar interaction networks, and the secondary structures also showed similar behavior. Thus, the intra- and intermolecular interaction networks described with the two AMBER force fields are similar. Therefore, AMBER14SB could still be the default option in free-energy calculations to achieve highly accurate binding thermodynamics and interaction patterns.
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Affiliation(s)
- Zhe Huai
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
| | - Zhaoxi Shen
- Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Zhaoxi Sun
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
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SAMPL7 TrimerTrip host-guest binding affinities from extensive alchemical and end-point free energy calculations. J Comput Aided Mol Des 2020; 35:117-129. [PMID: 33037549 DOI: 10.1007/s10822-020-00351-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 09/30/2020] [Indexed: 12/12/2022]
Abstract
The prediction of host-guest binding affinities with computational modelling is still a challenging task. In the 7th statistical assessment of the modeling of proteins and ligands (SAMPL) challenge, a new host named TrimerTrip was synthesized and the thermodynamic parameters of 16 structurally diverse guests binding to the host were characterized. In the TrimerTrip-guest challenge, only structures of the host and the guests are provided, which indicates that the predictions of both the binding poses and the binding affinities are under assessment. In this work, starting from the binding poses obtained from our previous enhanced sampling simulations in the configurational space, we perform extensive alchemical and end-point free energy calculations to calculate the host-guest binding affinities retrospectively. The alchemical predictions with two widely accepted charge schemes (i.e. AM1-BCC and RESP) are in good agreement with the experimental reference, while the end-point estimates perform poorly in reproducing the experimental binding affinities. Aside from the absolute value of the binding affinity, the rank of binding free energies is also crucial in drug design. Surprisingly, the end-point MM/PBSA method seems very powerful in reproducing the experimental rank of binding affinities. Although the length of our simulations is long and the intermediate spacing is dense, the convergence behavior is not very good, which may arise from the flexibility of the host molecule. Enhanced sampling techniques in the configurational space may be required to obtain fully converged sampling. Further, as the length of sampling in alchemical free energy calculations already achieves several hundred ns, performing direct simulations of the binding/unbinding event in the physical space could be more useful and insightful. More details about the binding pathway and mechanism could be obtained in this way. The nonequilibrium method could also be a nice choice if one insists to use the alchemical method, as the intermediate sampling is avoided to some extent.
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12
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Sun Z. SAMPL7 TrimerTrip host-guest binding poses and binding affinities from spherical-coordinates-biased simulations. J Comput Aided Mol Des 2020; 35:105-115. [PMID: 32776199 DOI: 10.1007/s10822-020-00335-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 08/04/2020] [Indexed: 12/21/2022]
Abstract
Host-guest binding remains a major challenge in modern computational modelling. The newest 7th statistical assessment of the modeling of proteins and ligands (SAMPL) challenge contains a new series of host-guest systems. The TrimerTrip host binds to 16 structurally diverse guests. Previously, we have successfully employed the spherical coordinates as the collective variables coupled with the enhanced sampling technique metadynamics to enhance the sampling of the binding/unbinding event, search for possible binding poses and calculate the binding affinities in all three host-guest binding cases of the 6th SAMPL challenge. In this work, we report a retrospective study on the TrimerTrip host-guest systems by employing the same protocol to investigate the TrimerTrip host in the SAMPL7 challenge. As no binding pose is provided by the SAMPL7 host, our simulations initiate from randomly selected configurations and are proceeded long enough to obtain converged free energy estimates and search for possible binding poses. The calculated binding affinities are in good agreement with the experimental reference, and the obtained binding poses serve as a nice starting point for end-point or alchemical free energy calculations. Note that as the work is performed after the close of the SAMPL7 challenge, we do not participate in the challenge and the results are not formally submitted to the SAMPL7 challenge.
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Affiliation(s)
- Zhaoxi Sun
- State Key Laboratory of Precision Spectroscopy, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China.
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13
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SAMPL6 host-guest binding affinities and binding poses from spherical-coordinates-biased simulations. J Comput Aided Mol Des 2020; 34:589-600. [PMID: 31974852 DOI: 10.1007/s10822-020-00294-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 01/17/2020] [Indexed: 10/25/2022]
Abstract
Host-guest binding is a challenging problem in computer simulation. The prediction of binding affinities between hosts and guests is an important part of the statistical assessment of the modeling of proteins and ligands (SAMPL) challenges. In this work, the volume-based variant of well-tempered metadynamics is employed to calculate the binding affinities of the host-guest systems in the SAMPL6 challenge. By biasing the spherical coordinates describing the relative position of the host and the guest, the initial-configuration-induced bias vanishes and all possible binding poses are explored. The agreement between the predictions and the experimental results and the observation of new binding poses indicate that the volume-based technique serves as a nice candidate for the calculation of binding free energies and the search of the binding poses.
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