Mapping the druggable allosteric space of G-protein coupled receptors: a fragment-based molecular dynamics approach.

To address the problem of specificity in G-protein coupled receptor (GPCR) drug discovery, there has been tremendous recent interest in allosteric drugs that bind at sites topographically distinct from the orthosteric site. Unfortunately, structure-based drug design of allosteric GPCR ligands has been frustrated by the paucity of structural data for allosteric binding sites, making a strong case for predictive computational methods. In this work, we map the surfaces of the beta1 (beta1AR) and beta2 (beta2AR) adrenergic receptor structures to detect a series of five potentially druggable allosteric sites. We employ the FTMAP algorithm to identify 'hot spots' with affinity for a variety of organic probe molecules corresponding to drug fragments. Our work is distinguished by an ensemble-based approach, whereby we map diverse receptor conformations taken from molecular dynamics (MD) simulations totaling approximately 0.5 micros. Our results reveal distinct pockets formed at both solvent-exposed and lipid-exposed cavities, which we interpret in light of experimental data and which may constitute novel targets for GPCR drug discovery. This mapping data can now serve to drive a combination of fragment-based and virtual screening approaches for the discovery of small molecules that bind at these sites and which may offer highly selective therapies

Pyrone-based inhibitors of metalloproteinase types 2 and 3 may work as conformation-selective inhibitors.

Matrix metalloproteinases are zinc-containing enzymes capable of degrading all components of the extracellular matrix. Owing to their role in human disease, matrix metalloproteinase have been the subject of extensive study. A bioinorganic approach was recently used to identify novel inhibitors based on a maltol zinc-binding group, but accompanying molecular-docking studies failed to explain why one of these inhibitors, AM-6, had approximately 2500-fold selectivity for MMP-3 over MMP-2. A number of studies have suggested that the matrix-metalloproteinase active site is highly flexible, leading some to speculate that differences in active-site flexibility may explain inhibitor selectivity. To extend the bioinorganic approach in a way that accounts for MMP-2 and MMP-3 dynamics, we here investigate the predicted binding modes and energies of AM-6 docked into multiple structures extracted from matrix-metalloproteinase molecular dynamics simulations. Our findings suggest that accounting for protein dynamics is essential for the accurate prediction of binding affinity and selectivity. Additionally, AM-6 and other similar inhibitors likely select for and stabilize only a subpopulation of all matrix-metalloproteinase conformations sampled by the apo protein. Consequently, when attempting to predict ligand affinity and selectivity using an ensemble of protein structures, it may be wise to disregard protein conformations that cannot accommodate the ligand

Hierarchical Orthogonal Matrix Generation and Matrix-Vector Multiplications in Rigid Body Simulations

In this paper, we apply the hierarchical modeling technique and study some numerical linear algebra problems arising from the Brownian dynamics simulations of biomolecular systems where molecules are modeled as ensembles of rigid bodies. Given a rigid body $p$ consisting of $n$ beads, the $6 \times 3n$ transformation matrix $Z$ that maps the force on each bead to $p$'s translational and rotational forces (a $6\times 1$ vector), and $V$ the row space of $Z$, we show how to explicitly construct the $(3n-6) \times 3n$ matrix $\tilde{Q}$ consisting of $(3n-6)$ orthonormal basis vectors of $V^{\perp}$ (orthogonal complement of $V$) using only $\mathcal{O}(n \log n)$ operations and storage. For applications where only the matrix-vector multiplications $\tilde{Q}{\bf v}$ and $\tilde{Q}^T {\bf v}$ are needed, we introduce asymptotically optimal $\mathcal{O}(n)$ hierarchical algorithms without explicitly forming $\tilde{Q}$. Preliminary numerical results are presented to demonstrate the performance and accuracy of the numerical algorithms

From Zn to Mn: the study of novel manganese-binding groups in the search for new drugs against tuberculosis.

In most eubacteria, apicomplexans, and most plants, including the causal agents for diseases such as malaria, leprosy, and tuberculosis, the methylerythritol phosphate pathway is the route for the biosynthesis of the C(5) precursors to the essential isoprenoid class of compounds. Owing to their absence in humans, the enzymes of the methylerythritol phosphate pathway have become attractive targets for drug discovery. This work investigates a new class of inhibitors against the second enzyme of the pathway, 1-deoxy-D-xylulose 5-phosphate reductoisomerase. Inhibition of this enzyme may involve the chelation of a crucial active site Mn ion, and the metal-chelating moieties studied here have previously been shown to be successful in application to the zinc-dependent metalloproteinases. Quantum mechanics and docking calculations presented in this work suggest the transferability of these metal-chelating compounds to Mn-containing 1-deoxy-D-xylulose 5-phosphate reductoisomerase enzyme, as a promising starting point to the development of potent inhibitors

Dynamics and calcium association to the N-terminal regulatory domain of human cardiac troponin C: a multiscale computational study.

Troponin C (TnC) is an important regulatory molecule in cardiomyocytes. Calcium binding to site II in TnC initiates a series of molecular events that result in muscle contraction. The most direct change upon Ca(2+) binding is an opening motion of the molecule that exposes a hydrophobic patch on the surface allowing for Troponin I to bind. Molecular dynamics simulations were used to elucidate the dynamics of this crucial protein in three different states: apo, Ca(2+)-bound, and Ca(2+)-TnI-bound. Dynamics between the states are compared, and the Ca(2+)-bound system is investigated for opening motions. On the basis of the simulations, NMR chemical shifts and order parameters are calculated and compared with experimental observables. Agreement indicates that the simulations sample the relevant dynamics of the system. Brownian dynamics simulations are used to investigate the calcium association of TnC. We find that calcium binding gives rise to correlative motions involving the EF hand and collective motions conducive of formation of the TnI-binding interface. We furthermore indicate the essential role of electrostatic steering in facilitating diffusion-limited binding of Ca(2+)

Replica-Exchange Accelerated Molecular Dynamics (REXAMD) Applied to Thermodynamic Integration

Accelerated molecular dynamics (AMD) is an efficient strategy for accelerating the sampling of molecular dynamics simulations, and observable quantities such as free energies derived on the biased AMD potential can be reweighted to yield results consistent with the original, unmodified potential. In conventional AMD the reweighting procedure has an inherent statistical problem in systems with large acceleration, where the points with the largest biases will dominate the reweighted result and reduce the effective number of data points. We propose a replica exchange of various degrees of acceleration (REXAMD) to retain good statistics while achieving enhanced sampling. The REXAMD method is validated and benchmarked on two simple gas-phase model systems, and two different strategies for computing reweighted averages over a simulation are compared

Dependency Map of Proteins in the Small Ribosomal Subunit

The assembly of the ribosome has recently become an interesting target for antibiotics in several bacteria. In this work, we extended an analytical procedure to determine native state fluctuations and contact breaking to investigate the protein stability dependence in the 30S small ribosomal subunit of Thermus thermophilus. We determined the causal influence of the presence and absence of proteins in the 30S complex on the binding free energies of other proteins. The predicted dependencies are in overall agreement with the experimentally determined assembly map for another organism, Escherichia coli. We found that the causal influences result from two distinct mechanisms: one is pure internal energy change, the other originates from the entropy change. We discuss the implications on how to target the ribosomal assembly most effectively by suggesting six proteins as targets for mutations or other hindering of their binding. Our results show that by blocking one out of this set of proteins, the association of other proteins is eventually reduced, thus reducing the translation efficiency even more. We could additionally determine the binding dependency of THX—a peptide not present in the ribosome of E. coli—and suggest its assembly path