Calculations of Absolute Free Energies, Enthalpies, and Entropies for Drug Binding.

Computer simulation methods can aid in the rational design of drugs aimed at a specific target, typically a protein. The affinity of a drug for its target is given by the free energy of binding. Binding can be further characterized by the enthalpy and entropy changes in the process. Methods exist to determine exact free energies, enthalpies, and entropies that are dependent only on the quality of the potential model and adequate sampling of conformational degrees of freedom. Entropy and enthalpy are roughly an order of magnitude more difficult to calculate than the free energy. This project combines a replica exchange method for enhanced sampling, designed to be efficient for protein-sized systems, with free energy calculations. This approach, replica exchange with dynamical scaling (REDS), uses two conventional simulations at different temperatures so that the entropy can be found from the temperature dependence of the free energy. A third replica is placed between them, with a modified Hamiltonian that allows it to span the temperature range of the conventional replicas. REDS provides temperature-dependent data and aids in sampling. It is applied to the bromodomain-containing protein 4 (BRD4) system. We find that for the force fields used, the free energies are accurate but the entropies and enthalpies are not, with the entropic contribution being too positive. Reproducing the entropy and enthalpy of binding appears to be a more stringent test of the force fields than reproducing the free energy.

Genomic analysis of hypoxia inducible factor alpha in ray-finned fishes reveals missing Ohnologs and evidence of widespread positive selection.

As aquatic hypoxia worsens on a global scale, fishes will become increasingly challenged by low oxygen, and understanding the molecular basis of their response to hypoxia may help to better define the capacity of fishes to cope with this challenge. The hypoxia inducible factor (HIF) plays a critical role in the molecular response to hypoxia by activating the transcription of genes that serve to improve oxygen delivery to the tissues or enhance the capacity of tissues to function at low oxygen. The current study examines the molecular evolution of genes encoding the oxygen-dependent HIFα subunit (HIFA) in the ray-finned fishes (Actinopterygii). Genomic analyses demonstrate that several lineages retain four paralogs of HIFA predicted from two rounds of genome duplication at the base of vertebrate evolution, broaden the known distribution of teleost-specific HIFA paralogs, and provide evidence for salmonid-specific HIFA duplicates. Evolution of the HIFA gene family is characterized by widespread episodic positive selection at amino acid sites that potentially mediate protein stability, protein-protein interactions, and transcriptional regulation. HIFA transcript abundance depends upon paralog, tissue, and fish lineage. A phylogenetically-informed gene nomenclature is proposed along with avenues for future research on this critical family of transcription factors.

An Implementation of Replica Exchange with Dynamical Scaling for Efficient Large-Scale Simulations.

An implementation of the replica exchange with dynamical scaling (REDS) method in the commonly used molecular dynamics program GROMACS is presented. REDS is a replica exchange method that requires fewer replicas than conventional replica exchange while still providing data over a range of temperatures and can be used in either constant volume or constant pressure ensembles. Details for running REDS simulations are given, and an application to the human islet amyloid polypeptide (hIAPP) 11-25 fragment shows that the model efficiently samples conformational space.

In silico modeling of the cryptic E2∼ubiquitin-binding site of E6-associated protein (E6AP)/UBE3A reveals the mechanism of polyubiquitin chain assembly.

To understand the mechanism for assembly of Lys48-linked polyubiquitin degradation signals, we previously demonstrated that the E6AP/UBE3A ligase harbors two functionally distinct E2∼ubiquitin-binding sites: a high-affinity Site 1 required for E6AP Cys820∼ubiquitin thioester formation and a canonical Site 2 responsible for subsequent chain elongation. Ordered binding to Sites 1 and 2 is here revealed by observation of UbcH7∼ubiquitin-dependent substrate inhibition of chain formation at micromolar concentrations. To understand substrate inhibition, we exploited the PatchDock algorithm to model in silico UbcH7∼ubiquitin bound to Site 1, validated by chain assembly kinetics of selected point mutants. The predicted structure buries an extensive solvent-excluded surface bringing the UbcH7∼ubiquitin thioester bond within 6 Šof the Cys820 nucleophile. Modeling onto the active E6AP trimer suggests that substrate inhibition arises from steric hindrance between Sites 1 and 2 of adjacent subunits. Confirmation that Sites 1 and 2 function in trans was demonstrated by examining the effect of E6APC820A on wild-type activity and single-turnover pulse-chase kinetics. A cyclic proximal indexation model proposes that Sites 1 and 2 function in tandem to assemble thioester-linked polyubiquitin chains from the proximal end attached to Cys820 before stochastic en bloc transfer to the target protein. Non-reducing SDS-PAGE confirms assembly of the predicted Cys820-linked 125I-polyubiquitin thioester intermediate. Other studies suggest that Glu550 serves as a general base to generate the Cys820 thiolate within the low dielectric binding interface and Arg506 functions to orient Glu550 and to stabilize the incipient anionic transition state during thioester exchange.

Lead optimization mapper: automating free energy calculations for lead optimization.

Alchemical free energy calculations hold increasing promise as an aid to drug discovery efforts. However, applications of these techniques in discovery projects have been relatively few, partly because of the difficulty of planning and setting up calculations. Here, we introduce lead optimization mapper, LOMAP, an automated algorithm to plan efficient relative free energy calculations between potential ligands within a substantial library of perhaps hundreds of compounds. In this approach, ligands are first grouped by structural similarity primarily based on the size of a (loosely defined) maximal common substructure, and then calculations are planned within and between sets of structurally related compounds. An emphasis is placed on ensuring that relative free energies can be obtained between any pair of compounds without combining the results of too many different relative free energy calculations (to avoid accumulation of error) and by providing some redundancy to allow for the possibility of error and consistency checking and provide some insight into when results can be expected to be unreliable. The algorithm is discussed in detail and a Python implementation, based on both Schrödinger's and OpenEye's APIs, has been made available freely under the BSD license.

Anti-HIV double variable domain immunoglobulins binding both gp41 and gp120 for targeted delivery of immunoconjugates.

BACKGROUND: Anti-HIV immunoconjugates targeted to the HIV envelope protein may be used to eradicate the latent reservoir of HIV infection using activate-and-purge protocols. Previous studies have identified the two target epitopes most effective for the delivery of cytotoxic immunoconjugates the CD4-binding site of gp120, and the hairpin loop of gp41. Here we construct and test tetravalent double variable domain immunoglobulin molecules (DVD-Igs) that bind to both epitopes. METHODS: Synthetic genes that encode DVD-Igs utilizing V-domains derived from human anti-gp120 and anti-gp41 Abs were designed and expressed in 293F cells. A series of constructs tested different inter-V-linker domains and orientations of the two V domains. Antibodies were tested for binding to recombinant Ag and native Env expressed on infected cells, for neutralization of infectious HIV, and for their ability to deliver cytotoxic immunoconjugates to infected cells. FINDINGS: The outer V-domain was the major determinant of binding and functional activity of the DVD-Ig. Function of the inner V-domain and bifunctional binding required at least 15 AA in the inter-V-domain linker. A molecular model showing the spatial orientation of the two epitopes is consistent with this observation. Linkers that incorporated helical domains (A[EAAAK](n)A) resulted in more effective DVD-Igs than those based solely on flexible domains ([GGGGS](n)). In general, the DVD-Igs outperformed the less effective parental antibody and equaled the activity of the more effective. The ability of the DVD-Igs to deliver cytotoxic immunoconjugates in the absence of soluble CD4 was improved over that of either parent. CONCLUSIONS: DVD-Igs can be designed that bind to both gp120 and gp41 on the HIV envelope. DVD-Igs are effective in delivering cytotoxic immunoconjugates. The optimal design of these DVD-Igs, in which both domains are fully functional, has not yet been achieved.

Crosstalk between PKA and Epac regulates the phenotypic maturation and function of human dendritic cells.

The cAMP-dependent signaling pathways that orchestrate dendritic cell (DC) maturation remain to be defined in detail. Although cAMP was previously thought to signal exclusively through protein kinase A (PKA), it is now clear that cAMP also activates exchange protein activated by cAMP (Epac), a second major cAMP effector. Whether cAMP signaling via PKA is sufficient to drive DC maturation or whether Epac plays a role has not been examined. In this study, we used cAMP analogs to selectively activate PKA or Epac in human monocyte-derived DCs and examined the effect of these signaling pathways on several hallmarks of DC maturation. We show that PKA activation induces DC maturation as evidenced by the increased cell-surface expression of MHC class II, costimulatory molecules, and the maturation marker CD83. PKA activation also reduces DC endocytosis and stimulates chemotaxis to the lymph node-associated chemokines CXCL12 and CCL21. Although PKA signaling largely suppresses cytokine production, the net effect of PKA activation translates to enhanced DC activation of allogeneic T cells. In contrast to the stimulatory effects of PKA, Epac signaling has no effect on DC maturation or function. Rather, Epac suppresses the effects of PKA when both pathways are activated simultaneously. These data reveal a previously unrecognized crosstalk between the PKA and Epac signaling pathways in DCs and raise the possibility that therapeutics targeting PKA may generate immunogenic DCs, whereas those that activate Epac may produce tolerogenic DCs capable of attenuating allergic or autoimmune disease.

Solvent dramatically affects protein structure refinement.

One of the most challenging problems in protein structure prediction is improvement of homology models (structures within 1-3 A C(alpha) rmsd of the native structure), also known as the protein structure refinement problem. It has been shown that improvement could be achieved using in vacuo energy minimization with molecular mechanics and statistically derived continuously differentiable hybrid knowledge-based (KB) potential functions. Globular proteins, however, fold and function in aqueous solution in vivo and in vitro. In this work, we study the role of solvent in protein structure refinement. Molecular dynamics in explicit solvent and energy minimization in both explicit and implicit solvent were performed on a set of 75 native proteins to test the various energy potentials. A more stringent test for refinement was performed on 729 near-native decoys for each native protein. We use a powerfully convergent energy minimization method to show that implicit solvent (GBSA) provides greater improvement for some proteins than the KB potential: 24 of 75 proteins showing an average improvement of >20% in C(alpha) rmsd from the native structure with GBSA, compared to just 7 proteins with KB. Molecular dynamics in explicit solvent moved the structures further away from their native conformation than the initial, unrefined decoys. Implicit solvent gives rise to a deep, smooth potential energy attractor basin that pulls toward the native structure.

Feedback algorithm and web-server for protein structure alignment.

We have developed a feedback algorithm for protein structure alignment that uses a series of phases to improve the global alignment between two protein backbones. The method implements a self-improving learning strategy by sending the output of one phase, the global alignment, to the next phase as an input. A web portal implementing this method has been constructed and is freely available for use at http://fpsa.cs.uno.edu/. Based on hundreds of test cases, we compare our algorithm with three other, commonly used methods: CE, Dali, and SSM. Our results show that, in most cases, our algorithm outputs a larger number of aligned positions when the (C(alpha)) RMSD is comparable. Also, in many cases where the number of aligned positions is larger or comparable to the other methods, our learning method is able to achieve a smaller (C(alpha)) RMSD than the other methods tested.

Feedback algorithm and web-server for protein structure alignment.

We have developed a feedback algorithm for protein structure alignment between two protein backbones. A web portal implementing this method has been constructed and is freely available for use at http://fpsa.cs.uno.edu/ with a mirror site at http://fpsa.cs.panam.edu/FPSA/. We compare our algorithm with three other, commonly used methods: CE, DaliLite and SSM. The results show that in most cases our algorithm outputs a larger number of aligned positions when the (Calpha) RMSD is comparable. Also, in many cases where the number of aligned positions is larger or comparable, our learning method is able to achieve a smaller (Calpha) RMSD than the other methods tested. This trend of larger number of aligned positions and smaller (Calpha) RMSD is observed more frequently in cases where the similarity between protein structures is weak.

Near-native structure refinement using in vacuo energy minimization.

One of the greatest shortcomings of macromolecular energy minimization and molecular dynamics techniques is that they generally do not preserve the native structure of proteins as observed by x-ray crystallography. This deformation of the native structure means that these methods are not generally used to refine structures produced by homology-modeling techniques. Here, we use a database of 75 proteins to test the ability of a variety of popular molecular mechanics force fields to maintain the native structure. Minimization from the native structure is a weak test of potential energy functions: It is complemented by a much stronger test in which the same methods are compared for their ability to attract a near-native decoy protein structure toward the native structure. We use a powerfully convergent energy-minimization method and show that, of the traditional molecular mechanics potentials tested, only one showed a modest net improvement over a large data set of structurally diverse proteins. A smooth, differentiable knowledge-based pairwise atomic potential performs better on this test than traditional potential functions. This work is expected to have important implications for protein structure refinement, homology modeling, and structure prediction.

An atomic environment potential for use in protein structure prediction.

We describe the derivation and testing of a knowledge-based atomic environment potential for the modeling of protein structural energetics. An analysis of the probabilities of atomic interactions in a dataset of high-resolution protein structures shows that the probabilities of non-bonded inter-atomic contacts are not statistically independent events, and that the multi-body contact frequencies are poorly predicted from pairwise contact potentials. A pseudo-energy function is defined that measures the preferences for protein atoms to be in a given microenvironment defined by the number of contacting atoms in the environment and its atomic composition. This functional form is tested for its ability to recognize native protein structures amongst an ensemble of decoy structures and a detailed relative performance comparison is made with a number of common functions used in protein structure prediction.

Computational design of a water-soluble analog of phospholamban.

Membrane proteins and water-soluble proteins share a similar core. This similarity suggests that it should be possible to water-solubilize membrane proteins by mutating only their lipid-exposed residues. We have developed computational tools to design water-soluble variants of helical membrane proteins, using the pentameric phospholamban (PLB) as our test case. To water-solublize PLB, the membrane-exposed positions were changed to polar or charged amino acids, while the putative core was left unaltered. We generated water-soluble phospholamban (WSPLB), and compared its properties to its predecessor PLB. In aqueous solution, WSPLB mimics all of the reported properties of PLB including oligomerization state, helical structure, and stabilization upon phosphorylation. We also characterized the truncated mutant WSPLB (21-52) comprising only the former transmembrane segment of PLB. This peptide shows a decreased specificity for forming a pentameric oligomerization state.

Computational de novo design, and characterization of an A(2)B(2) diiron protein.

Diiron proteins are found throughout nature and have a diverse range of functions; proteins in this class include methane monooxygenase, ribonucleotide reductase, Delta(9)-acyl carrier protein desaturase, rubrerythrin, hemerythrin, and the ferritins. Although each of these proteins has a very different overall fold, in every case the diiron active site is situated within a four-helix bundle. Additionally, nearly all of these proteins have a conserved Glu-Xxx-Xxx-His motif on two of the four helices with the Glu and His residues ligating the iron atoms. Intriguingly, subtle differences in the active site can result in a wide variety of functions. To probe the structural basis for this diversity, we designed an A(2)B(2) heterotetrameric four-helix bundle with an active site similar to those found in the naturally occurring diiron proteins. A novel computational approach was developed for the design, which considers the energy of not only the desired fold but also alternatively folded structures. Circular dichroism spectroscopy, analytical ultracentrifugation, and thermal unfolding studies indicate that the A and B peptides specifically associate to form an A(2)B(2) heterotetramer. Further, the protein binds Zn(II) and Co(II) in the expected manner and shows ferroxidase activity under single turnover conditions.