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John Z H Zhang - One of the best experts on this subject based on the ideXlab platform.
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Table_1_Automated Fragmentation QM/MM Calculation of NMR Chemical Shifts for Protein-Ligand Complexes.PDF
2018Co-Authors: Xinsheng Jin, Tong Zhu, John Z H ZhangAbstract:In this study, the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) method was applied for NMR chemical shift calculations of Protein-Ligand complexes. In the AF-QM/MM approach, the Protein binding pocket is automatically divided into capped fragments (within ~200 atoms) for density functional theory (DFT) calculations of NMR chemical shifts. Meanwhile, the solvent effect was also included using the Poission-Boltzmann (PB) model, which properly accounts for the electrostatic polarization effect from the solvent for Protein-Ligand complexes. The NMR chemical shifts of neocarzinostatin (NCS)-chromophore binding complex calculated by AF-QM/MM accurately reproduce the large-sized system results. The 1H chemical shift perturbations (CSP) between apo-NCS and holo-NCS predicted by AF-QM/MM are also in excellent agreement with experimental results. Furthermore, the DFT calculated chemical shifts of the chromophore and residues in the NCS binding pocket can be utilized as molecular probes to identify the correct Ligand binding conformation. By combining the CSP of the atoms in the binding pocket with the Glide scoring function, the new scoring function can accurately distinguish the native Ligand pose from decoy structures. Therefore, the AF-QM/MM approach provides an accurate and efficient platform for Protein-Ligand binding structure prediction based on NMR derived information.
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Automated Fragmentation QM/MM Calculation of NMR Chemical Shifts for Protein-Ligand Complexes
Frontiers Media S.A., 2018Co-Authors: Xinsheng Jin, John Z H Zhang, Tong ZhuAbstract:In this study, the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) method was applied for NMR chemical shift calculations of Protein-Ligand complexes. In the AF-QM/MM approach, the Protein binding pocket is automatically divided into capped fragments (within ~200 atoms) for density functional theory (DFT) calculations of NMR chemical shifts. Meanwhile, the solvent effect was also included using the Poission-Boltzmann (PB) model, which properly accounts for the electrostatic polarization effect from the solvent for Protein-Ligand complexes. The NMR chemical shifts of neocarzinostatin (NCS)-chromophore binding complex calculated by AF-QM/MM accurately reproduce the large-sized system results. The 1H chemical shift perturbations (CSP) between apo-NCS and holo-NCS predicted by AF-QM/MM are also in excellent agreement with experimental results. Furthermore, the DFT calculated chemical shifts of the chromophore and residues in the NCS binding pocket can be utilized as molecular probes to identify the correct Ligand binding conformation. By combining the CSP of the atoms in the binding pocket with the Glide scoring function, the new scoring function can accurately distinguish the native Ligand pose from decoy structures. Therefore, the AF-QM/MM approach provides an accurate and efficient platform for Protein-Ligand binding structure prediction based on NMR derived information
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interaction entropy a new paradigm for highly efficient and reliable computation of Protein Ligand binding free energy
Journal of the American Chemical Society, 2016Co-Authors: Xiao Liu, Lili Duan, John Z H ZhangAbstract:Efficient and reliable calculation of Protein–Ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to Protein–Ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in Protein–Ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in Protein–Ligand binding, the new method calculates the entropic component (interaction entropy or −TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected Protein–Ligand binding systems demonstrated that...
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quantum mechanical map for Protein Ligand binding with application to β trypsin benzamidine complex
Journal of Chemical Physics, 2004Co-Authors: Da W Zhang, Yun Xiang, Ai M Gao, John Z H ZhangAbstract:We report full ab initio Hartree–Fock calculation to compute quantum mechanical interaction energies for β-trypsin/benzamidine binding complex. In this study, the full quantum mechanical ab initio energy calculation for the entire Protein complex with 3238 atoms is made possible by using a recently developed MFCC (molecular fractionation with conjugate caps) approach in which the Protein molecule is decomposed into amino acid-based fragments that are properly capped. The present MFCC ab initio calculation enables us to obtain an “interaction spectrum” that provides detailed quantitative information on Protein-Ligand binding at the amino acid levels. These detailed information on individual residue-Ligand interaction gives a quantitative molecular insight into our understanding of Protein-Ligand binding and provides a guidance to rational design of potential inhibitors of Protein targets.
Michael C Fitzgerald - One of the best experts on this subject based on the ideXlab platform.
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mass spectrometry based thermal shift assay for Protein Ligand binding analysis
Analytical Chemistry, 2010Co-Authors: Graham M West, Will J Thompson, Erik J Soderblom, Laura G Dubois, Patrick D Dearmond, Arthur M Moseley, Michael C FitzgeraldAbstract:Described here is a mass spectrometry-based screening assay for the detection of Protein-Ligand binding interactions in multicomponent Protein mixtures. The assay utilizes an oxidation labeling protocol that involves using hydrogen peroxide to selectively oxidize methionine residues in Proteins in order to probe the solvent accessibility of these residues as a function of temperature. The extent to which methionine residues in a Protein are oxidized after specified reaction times at a range of temperatures is determined in a MALDI analysis of the intact Proteins and/or an LC-MS analysis of tryptic peptide fragments generated after the oxidation reaction is quenched. Ultimately, the mass spectral data is used to construct thermal denaturation curves for the detected Proteins. In this proof-of-principle work, the protocol is applied to a four-Protein model mixture comprised of ubiquitin, ribonuclease A (RNaseA), cyclophilin A (CypA), and bovine carbonic anhydrase II (BCAII). The new protocol's ability to detect Protein-Ligand binding interactions by comparing thermal denaturation data obtained in the absence and in the presence of Ligand is demonstrated using cyclosporin A (CsA) as a test Ligand. The known binding interaction between CsA and CypA was detected using both the MALDI- and LC-MS-based readouts described here.
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hydrogen deuterium exchange and protease digestion based screening assay for Protein Ligand binding detection
Analytical Chemistry, 2009Co-Authors: Erin D Hopper, Adrianne M C Pittman, Chandra L Tucker, Michael J Campa, Edward F Patz, Michael C FitzgeraldAbstract:A protease digestion strategy was incorporated into single-point stability of unpurified Proteins from rates of H/D exchange (SUPREX), which is a hydrogen/deuterium (H/D) exchange- and mass spectrometry-based assay for the detection of Protein−Ligand binding. Single-point SUPREX is an abbreviated form of SUPREX in which Protein−Ligand binding interactions are detected by measuring the increase in a Protein’s thermodynamic stability upon Ligand binding. The new protease digestion protocol provides a noteworthy increase in the efficiency of single-point SUPREX because peptide masses can be determined with greater precision than intact Protein masses in the matrix-assisted laser desorption ionization (MALDI) readout of single-point SUPREX. The protocol was evaluated in test screens on two model Protein systems, including cyclophilin A (CypA) and the minor allele variant of human alanine:glyoxylate aminotransferase (AGTmi). The test screening results obtained on both Proteins revealed that the peptide readout...
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a general mass spectrometry based assay for the quantitation of Protein Ligand binding interactions in solution
Journal of the American Chemical Society, 2002Co-Authors: Kendall D Powell, Sina Ghaemmaghami, Michael Zhuo Wang, Terrance G Oas, Michael C FitzgeraldAbstract:A new method that utilizes matrix-assisted laser desorption/ionization (MALDI) mass spectrometry and exploits the hydrogen/deuterium (H/D) exchange properties of Proteins was developed for measuring the thermodynamic properties of Protein-Ligand complexes in solution. Dissociation constants (Kd values) determined by the method for five model Protein-Ligand complexes that included those with small molecules, nucleic acids, peptides, and other Proteins were generally in good agreement with Kd values measured by conventional methods. Important experimental advantages of the described method over existing methods include: the ability to make measurements in a high-throughput and automated fashion, the ability to make measurements using only picomole quantitities of Protein, and the ability to analyze either purified or unpurified Protein-Ligand complexes.
Vittorio Limongelli - One of the best experts on this subject based on the ideXlab platform.
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Protein Ligand binding with the coarse grained martini model
Nature Communications, 2020Co-Authors: Paulo C T Souza, Sebastian Thallmair, Paolo Conflitti, Carlos Ramirezpalacios, Riccardo Alessandri, Stefano Raniolo, Vittorio Limongelli, Siewert J MarrinkAbstract:The detailed understanding of the binding of small molecules to Proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of Protein–Ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of Protein–Ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of Ligand libraries or Protein mutations using the coarse-grained Martini model. Computer-aided design of Protein-Ligand binding is important for the development of novel drugs. Here authors present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of Protein-Ligand binding interactions of small drug-like molecules.
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Protein Ligand binding with the coarse grained martini model
Nature Communications, 2020Co-Authors: Paulo C T Souza, Sebastian Thallmair, Paolo Conflitti, Carlos Ramirezpalacios, Riccardo Alessandri, Stefano Raniolo, Vittorio Limongelli, Siewert J MarrinkAbstract:The detailed understanding of the binding of small molecules to Proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of Protein-Ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of Protein-Ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of Ligand libraries or Protein mutations using the coarse-grained Martini model.
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kinetics of Protein Ligand unbinding predicting pathways rates and rate limiting steps
Proceedings of the National Academy of Sciences of the United States of America, 2015Co-Authors: Pratyush Tiwary, Vittorio Limongelli, Matteo Salvalaglio, Michele ParrinelloAbstract:The ability to predict the mechanisms and the associated rate constants of Protein–Ligand unbinding is of great practical importance in drug design. In this work we demonstrate how a recently introduced metadynamics-based approach allows exploration of the unbinding pathways, estimation of the rates, and determination of the rate-limiting steps in the paradigmatic case of the trypsin–benzamidine system. Protein, Ligand, and solvent are described with full atomic resolution. Using metadynamics, multiple unbinding trajectories that start with the Ligand in the crystallographic binding pose and end with the Ligand in the fully solvated state are generated. The unbinding rate k o f f is computed from the mean residence time of the Ligand. Using our previously computed binding affinity we also obtain the binding rate k o n . Both rates are in agreement with reported experimental values. We uncover the complex pathways of unbinding trajectories and describe the critical rate-limiting steps with unprecedented detail. Our findings illuminate the role played by the coupling between subtle Protein backbone fluctuations and the solvation by water molecules that enter the binding pocket and assist in the breaking of the shielded hydrogen bonds. We expect our approach to be useful in calculating rates for general Protein–Ligand systems and a valid support for drug design.
Siewert J Marrink - One of the best experts on this subject based on the ideXlab platform.
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Protein Ligand binding with the coarse grained martini model
Nature Communications, 2020Co-Authors: Paulo C T Souza, Sebastian Thallmair, Paolo Conflitti, Carlos Ramirezpalacios, Riccardo Alessandri, Stefano Raniolo, Vittorio Limongelli, Siewert J MarrinkAbstract:The detailed understanding of the binding of small molecules to Proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of Protein–Ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of Protein–Ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of Ligand libraries or Protein mutations using the coarse-grained Martini model. Computer-aided design of Protein-Ligand binding is important for the development of novel drugs. Here authors present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of Protein-Ligand binding interactions of small drug-like molecules.
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Protein Ligand binding with the coarse grained martini model
Nature Communications, 2020Co-Authors: Paulo C T Souza, Sebastian Thallmair, Paolo Conflitti, Carlos Ramirezpalacios, Riccardo Alessandri, Stefano Raniolo, Vittorio Limongelli, Siewert J MarrinkAbstract:The detailed understanding of the binding of small molecules to Proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of Protein-Ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of Protein-Ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of Ligand libraries or Protein mutations using the coarse-grained Martini model.
Renxiao Wang - One of the best experts on this subject based on the ideXlab platform.
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test mm pb sa on true conformational ensembles of Protein Ligand complexes
Journal of Chemical Information and Modeling, 2010Co-Authors: Zhihai Liu, Renxiao WangAbstract:The molecular mechanics Poisson−Boltzmann surface area (MM-PB/SA) method has been popular for computing Protein−Ligand binding free energies in recent years. All previous evaluations of the MM-PB/SA method are based upon computer-generated conformational ensembles, which may be affected by the defective computational methods used for preparing these conformational ensembles. In an attempt to reach more convincing conclusions, we have evaluated the MM-PB/SA method on a set of 24 diverse Protein−Ligand complexes, each of which has a set of conformations derived from NMR spectroscopy. Our results indicate that both MM-PB/SA and molecular mechanics generalized Born surface area (MM-GB/SA) are able to produce a modest correlation between their results and the experimentally measured binding free energies on our test set. In particular, both MM-PB/SA and MM-GB/SA produced better results by using a representative structure (R = 0.72−0.79) rather than averaging over the conformational ensemble of each given compl...
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geometrical preferences of the hydrogen bonds on Protein Ligand binding interface derived from statistical surveys and quantum mechanics calculations
Journal of Chemical Theory and Computation, 2008Co-Authors: Zhiguo Liu, Guitao Wang, Renxiao WangAbstract:We have conducted potential of mean force (PMF) analyses to derive the geometrical parameters of various types of hydrogen bonds on Protein-Ligand binding interface. Our PMF analyses are based on a set of 4535 high-quality Protein-Ligand complex structures, which are compiled through a systematic mining of the entire Protein Data Bank. Hydrogen bond donor and acceptor atoms are classified into several basic types. Both distance- and angle-dependent statistical potentials are derived for each donor-acceptor pair, from which distance and angle cutoffs are obtained in an objective, unambiguous manner. These donor-acceptor pairs are also studied by quantum mechanics (QM) calculations at the MP2/6-311++G** level on model molecules. Comparison of the outcomes of PMF analyses and QM calculations suggests that QM calculation may serve as an alternative approach for characterizing hydrogen bond geometry. Both of our PMF analyses and QM calculations indicate that C-H···O hydrogen bonds are relatively weak as compared to common hydrogen bonds formed between nitrogen and oxygen atoms. A survey on the Protein-Ligand complex structures in our data set has revealed that Cα-H···O hydrogen bonds observed in Protein-Ligand binding are frequently accompanied by bifurcate N-H···O hydrogen bonds. Thus, the Cα-H···O hydrogen bonds in such cases would better be interpreted as secondary interactions.
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score a new empirical method for estimating the binding affinity of a Protein Ligand complex
Journal of Molecular Modeling, 1998Co-Authors: Renxiao Wang, Liang Liu, Luhua Lai, Youqi TangAbstract:A new method is presented to estimate the binding affinity of a Protein-Ligand complex with known three-dimensional structure. The method, SCORE, uses an empirical scoring function to describe the binding free energy, which includes terms to account for van der Waals contact, metal-Ligand bonding, hydrogen bonding, desolvation effect, and deformation penalty upon the binding process. The coefficients of each term are obtained by multivariate regressional analysis of a diverse training set of 170 Protein-Ligand complexes. The final scoring function reproduces the binding free energies of the whole training set with a cross-validated deviation of 6.3 kJ/mol. The predictive ability of the function is further tested by a set of 11 endothiapepsin complexes and the internal consistency of the function is demonstrated in a stepwise procedure named Evolutionary Test. A major innovation of this method is the introduction of an atomic binding score which allows the researcher to inspect and optimize the lead compound rationally in a structure-based drug design scheme.
