Search

A novel computational method is applied to study molecular recognition for three sets of synthetic hosts that are molecular clips , molecular tweezers, and a synthetic barbiturate receptor. The observation shows a strong correlation between the changes in configurational energy and configurational entropy upon binding, resulting in near-linear compensation analogous to classical entropy-enthalpy compensation.

A method is presented for calculating the conformational free energy of a molecule in all degrees of freedom. The study reveals that the method using harmonic approximation with finite integration ranges along with Mode scanning gives excellent accuracy.

Recently, we presented a strategy for packaging peptides as side‐chains in high‐density brush polymers. For this globular protein‐like polymer (PLP) formulation, therapeutic peptides were shown to resist proteolytic degradation, enter cells efficiently and maintain biological function. In this paper, we establish the role charge plays in dictating the cellular uptake of these peptide formulations, finding that peptides with a net positive charge will enter cells when polymerized, while those formed from anionic or neutral peptides remain outside of cells. Given these findings, we explored whether cellular uptake could be selectively induced by a stimulus. In our design, a cationic peptide is appended to a sequence of charge‐neutralizing anionic amino acids through stimuli‐responsive cleavable linkers. As a proof‐of‐concept study, we tested this strategy with two different classes of stimuli, exogenous UV light and an enzyme (a matrix metalloproteinase) associated with the inflammatory response. The key finding is that these materials enter cells only when acted upon by the stimulus. This approach makes it possible to achieve delivery of the polymers, therapeutic peptides or an appended cargo into cells in response to an appropriate stimulus. [ABSTRACT FROM AUTHOR]

Issues concerning a new method to calculate binding free energies and use of the predominant states method, 'Mining Minima', with a series of water-soluble adenine receptors are discussed. A comparison of the changes in translational and rotational entropy which occur upon binding is made between this model and others.

Generalized Born (GB) approximation model coupled with a torsion-space sampling method were used to estimate pKa shifts for a series of dicarboxylic acids and amino acids and for the active-site aspartyl dyad in HIV-1 protease (HIVP). Results showed significant occupancy of salt-bridged conformations for the zwitterionic forms of the amino acids. Although the GB technique's validity was confirmed in the calculations for the HIVP test, adjustments in the model were needed to improve its reliability in smaller molecules.

The pKa values of seven basic residues in turkey ovomucoid third domain were determined and compared to previously predicted values. The pKa values of these basic groups were expected to be raised by the effect of Lys 13, 29 and 34 on the acidity of several acidic residues. Findings show, however, that the pKa values of Lys 13 and 34 are lower than the values of the model compound. Those of the other basic groups are higher than the model compound values and are all insensitive to salt, in contrast with the acidic residues.

Limitations and other issues regarding theoretical models for predicting the pKaS of ionizable groups of proteins are examined. Findings indicate that computed pKaS averaged over NMR structure sets are more accurate than those based upon single crystal structures. Also, the use of atomic parameters optimized to produce hydration energies of small molecules improves agreement with experiment when a low protein dielectric constant is assumed. Despite the use of NMR structures and optimized atomic parameters, pKaS calculated with a protein dielectric constant of 20 are more accurate.

The catalytic rate of acetylcholinesterase is influenced by the electrostatic steering as explained from the mutation experiments. The rate constants are enhanced by an order of magnitude in the wild type and mutants on elevating the electrostatic field of the enzyme. The degree of diffusion limitation is increased with rise of ionic strength. By decreasing electrostatic steering the ionic strength increases resulting in reduced rate constants for diffusional encounter.

Water molecules can be found interacting with the surface and within cavities in proteins. However, water exchange between bulk and buried hydration sites can be slow compared to simulation timescales, thus leading to the inefficient sampling of the locations of water. This can pose problems for free energy calculations for computer-aided drug design. Here, we apply a hybrid method that combines nonequilibrium candidate Monte Carlo (NCMC) simulations and molecular dynamics (MD) to enhance sampling of water in specific areas of a system, such as the binding site of a protein. Our approach uses NCMC to gradually remove interactions between a selected water molecule and its environment, then translates the water to a new region, before turning the interactions back on. This approach of gradual removal of interactions, followed by a move and then reintroduction of interactions, allows the environment to relax in response to the proposed water translation, improving acceptance of moves and thereby accelerating water exchange and sampling. We validate this approach on several test systems including the ligand-bound MUP-1 and HSP90 proteins with buried crystallographic waters removed. We show that our BLUES (NCMC/MD) method enhances water sampling relative to normal MD when applied to these systems. Thus, this approach provides a strategy to improve water sampling in molecular simulations which may be useful in practical applications in drug discovery and biomolecular design. [ABSTRACT FROM AUTHOR]

Force fields used in molecular simulations contain numerical parameters, such as Lennard–Jones (LJ) parameters, which are assigned to the atoms in a molecule based on a classification of their chemical environments. The number of classes, or types, should be no more than needed to maximize agreement with experiment, as parsimony avoids overfitting and simplifies parameter optimization. However, types have historically been crafted based largely on chemical intuition, so current force fields may contain more types than needed. In this study, we seek the minimum number of LJ parameter types needed to represent the key properties of organic liquids. We find that highly competitive force field accuracy is obtained with minimalist sets of LJ types; e.g., two H types and one type apiece for C, O, and N atoms. We also find that the fitness surface has multiple minima, which can lead to local trapping of the optimizer. The force fields used in molecular simulations typically assign varied Lennard-Jones parameters to the atoms of a given element, depending on the neighborhood of each atom in the chemical graph of a compound, but optimizing so many parameters without overfitting is challenging. Here, the authors provide evidence that far fewer LJ parameters may be needed. [ABSTRACT FROM AUTHOR]

Continuum solvation models are widely used to estimate the hydration free energies of small molecules and proteins, in applications ranging from drug design to protein engineering, and most such models are based on the approximation of a linear dielectric response by the solvent. We used explicit-water molecular dynamics simulations with the TIP3P water model to probe this linear response approximation in the case of neutral polar molecules, using miniature cucurbituril and cyclodextrin receptors and protein side-chain analogs as model systems. We observe supralinear electrostatic solvent responses, and this nonlinearity is found to result primarily from waters' being drawn closer and closer to the solutes with increased solute-solvent electrostatic interactions; i.e., from solute electrostriction. Dielectric saturation and changes in the water-water hydrogen bonding network, on the other hand, play little role. Thus, accounting for solute electrostriction may be a productive approach to improving the accuracy of continuum solvation models. [ABSTRACT FROM AUTHOR]

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host–guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange—while displaying very small variance—can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations. [ABSTRACT FROM AUTHOR]