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Samuel Genheden

Bio: Samuel Genheden is an academic researcher from AstraZeneca. The author has contributed to research in topics: Solvation & Molecular dynamics. The author has an hindex of 27, co-authored 57 publications receiving 3632 citations. Previous affiliations of Samuel Genheden include University of Southampton & Lund University.


Papers
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Journal ArticleDOI
TL;DR: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications.
Abstract: Introduction: The molecular mechanics energies combined with the Poisson–Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor–ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success.Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications.Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used success...

2,480 citations

Journal ArticleDOI
TL;DR: This work probed the conformational entropy and its relative contribution to the free energy of ligand binding to the carbohydrate recognition domain of galectin-3 and revealed an intricate interplay between structure and conformational fluctuations in the different complexes that fine-tunes the affinity.
Abstract: Rational drug design is predicated on knowledge of the three-dimensional structure of the protein-ligand complex and the thermodynamics of ligand binding. Despite the fundamental importance of both enthalpy and entropy in driving ligand binding, the role of conformational entropy is rarely addressed in drug design. In this work, we have probed the conformational entropy and its relative contribution to the free energy of ligand binding to the carbohydrate recognition domain of galectin-3. Using a combination of NMR spectroscopy, isothermal titration calorimetry, and X-ray crystallography, we characterized the binding of three ligands with dissociation constants ranging over 2 orders of magnitude. (15)N and (2)H spin relaxation measurements showed that the protein backbone and side chains respond to ligand binding by increased conformational fluctuations, on average, that differ among the three ligand-bound states. Variability in the response to ligand binding is prominent in the hydrophobic core, where a distal cluster of methyl groups becomes more rigid, whereas methyl groups closer to the binding site become more flexible. The results reveal an intricate interplay between structure and conformational fluctuations in the different complexes that fine-tunes the affinity. The estimated change in conformational entropy is comparable in magnitude to the binding enthalpy, demonstrating that it contributes favorably and significantly to ligand binding. We speculate that the relatively weak inherent protein-carbohydrate interactions and limited hydrophobic effect associated with oligosaccharide binding might have exerted evolutionary pressure on carbohydrate-binding proteins to increase the affinity by means of conformational entropy.

207 citations

Journal ArticleDOI
TL;DR: The binding of seven biotin analogues to avidin is studied, taking advantage of the fact that the protein is a tetramer with four independent binding sites, which should give the same estimated binding affinities.
Abstract: The molecular mechanics/generalized Born surface area (MM/GBSA) method has been investigated with the aim of achieving a statistical precision of 1 kJ/mol for the results. We studied the binding of seven biotin analogues to avidin, taking advantage of the fact that the protein is a tetramer with four independent binding sites, which should give the same estimated binding affinities. We show that it is not enough to use a single long simulation (10 ns), because the standard error of such a calculation underestimates the difference between the four binding sites. Instead, it is better to run several independent simulations and average the results. With such an approach, we obtain the same results for the four binding sites, and any desired precision can be obtained by running a proper number of simulations. We discuss how the simulations should be performed to optimize the use of computer time. The correlation time between the MM/GBSA energies is approximately 5 ps and an equilibration time of 100 ps is needed. For MM/GBSA, we recommend a sampling time of 20-200 ps for each separate simulation, depending on the protein. With 200 ps production time, 5-50 separate simulations are required to reach a statistical precision of 1 kJ/mol (800-8000 energy calculations or 1.5-15 ns total simulation time per ligand) for the seven avidin ligands. This is an order of magnitude more than what is normally used, but such a number of simulations is needed to obtain statistically valid results for the MM/GBSA method. (c) 2009 Wiley Periodicals, Inc. J Comput Chem 2009.

199 citations

Journal ArticleDOI
TL;DR: A systematic study of the entropy term in the MM/GBSA (molecular mechanics combined with generalized Born and surface-area solvation) approach to calculate ligand-binding affinities shows that removing protein residues with distances larger than 8-16 Å to the ligand changes the absolute entropies by 1-5 kJ/mol on average.
Abstract: We have performed a systematic study of the entropy term in the MM/GBSA (molecular Mechanics combined with generalized Born and surface area solvation) approach to calculate ligand-binding affinities The entropies are calculated by a normal mode analysis of harmonic frequencies from minimized snapshots of molecular dynamics simulations. For computational reasons, these calculations have normally been performed on truncated systems. We have studied the binding of eight inhibitors of blood clotting factor Xa, nine ligands of ferritin, and two ligands of HIV-1 protease and show that removing protein residues with. distances. larger than 8-16 angstrom to the ligand, including a 4 angstrom shell of fixed protein residues and water molecules, change the absolute entropies by 1-5 kJ/mol on average. However, the change is systematic, so relative entropies for different ligands change by only 0.7-1.6 kJ/mol on average. Consequently, entropies from truncated systems give relative binding affinities that are identical to those obtained for the Whole protein within statistical uncertainty (172 kJ/mol). We have also tested to use a distance dependent dielectric constant in the minimization and. frequency calculation (epsilon = 4r), but it typically gives slightly different entropies and poorer binding, affinities. Therefore, we recommend entropies calculated with the smallest truncation radius (8 angstrom) and epsilon =1 Such an approach also gives an improved precision for the calculated binding free energies. (Less)

146 citations

Journal ArticleDOI
TL;DR: The 3D-RISM-KH theory yields a full molecular picture of the solvation structure and thermodynamics from the first principles, with proper account of chemical specificities of both solvent and biomolecules, such as hydrogen bonding, hydrophobic interactions, salt bridges, etc.
Abstract: We have modified the popular MM/PBSA or MM/GBSA approaches (molecular mechanics for a biomolecule, combined with a Poisson-Boltzmann or generalized Born electrostatic and surface area nonelectrostatic solvation energy) by employing instead the statistical-mechanical, three-dimensional molecular theory of solvation (also known as 3D reference interaction site model, or 3D-RISM-KH) coupled with molecular mechanics or molecular dynamics ( Blinov , N. ; et al. Biophys. J. 2010 ; Luchko , T. ; et al. J. Chem. Theory Comput. 2010 ). Unlike the PBSA or GBSA semiempirical approaches, the 3D-RISM-KH theory yields a full molecular picture of the solvation structure and thermodynamics from the first principles, with proper account of chemical specificities of both solvent and biomolecules, such as hydrogen bonding, hydrophobic interactions, salt bridges, etc. We test the method on the binding of seven biotin analogues to avidin in aqueous solution and show it to work well in predicting the ligand-binding affinities. We have compared the results of 3D-RISM-KH with four different generalized Born and two Poisson-Boltzmann methods. They give absolute binding energies that differ by up to 208 kJ/mol and mean absolute deviations in the relative affinities of 10-43 kJ/mol.

134 citations


Cited by
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01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 citations

Journal ArticleDOI
TL;DR: MMPBSA.py is a program written in Python for streamlining end-state free energy calculations using ensembles derived from molecular dynamics or Monte Carlo simulations, including the Poisson-Boltzmann Model and several implicit solvation models.
Abstract: MM-PBSA is a post-processing end-state method to calculate free energies of molecules in solution. MMPBSA.py is a program written in Python for streamlining end-state free energy calculations using ensembles derived from molecular dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson–Boltzmann Model, the Generalized Born Model, and the Reference Interaction Site Model. Vibrational frequencies may be calculated using normal mode or quasi-harmonic analysis to approximate the solute entropy. Specific interactions can also be dissected using free energy decomposition or alanine scanning. A parallel implementation significantly speeds up the calculation by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calculations. The source code can be downloaded at http://ambermd.org/ with AmberTools, rele...

2,528 citations

Journal ArticleDOI
TL;DR: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications.
Abstract: Introduction: The molecular mechanics energies combined with the Poisson–Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor–ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success.Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications.Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used success...

2,480 citations

Journal ArticleDOI
TL;DR: In this review, methods to adjust the polar solvation energy and to improve the performance of MM/PBSA and MM/GBSA calculations are reviewed and discussed and guidance is provided for practically applying these methods in drug design and related research fields.
Abstract: Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) are arguably very popular methods for binding free energy prediction since they are more accurate than most scoring functions of molecular docking and less computationally demanding than alchemical free energy methods. MM/PBSA and MM/GBSA have been widely used in biomolecular studies such as protein folding, protein-ligand binding, protein-protein interaction, etc. In this review, methods to adjust the polar solvation energy and to improve the performance of MM/PBSA and MM/GBSA calculations are reviewed and discussed. The latest applications of MM/GBSA and MM/PBSA in drug design are also presented. This review intends to provide readers with guidance for practically applying MM/PBSA and MM/GBSA in drug design and related research fields.

822 citations

Journal ArticleDOI
TL;DR: The physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized.
Abstract: Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein–ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models—the “lock-and-key”, “induced fit”, and “conformational selection”—are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein–ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed.

793 citations