Fast calculation of thermodynamic and structural parameters of solutions using the 3DRISM model and the multi-grid method

In the paper a new method to solve the tree-dimensional reference interaction site model (3DRISM) integral equations is proposed. The algorithm uses the multi-grid technique which allows to decrease the computational expanses. 3DRISM calculations for aqueous solutions of four compounds (argon, water, methane, methanol) on the different grids are performed in order to determine a dependence of the computational error on the parameters of the grid. It is shown that calculations on the grid with the step 0.05\Angstr and buffer 8\Angstr give the error of solvation free energy calculations less than 0.3 kcal/mol which is comparable to the accuracy of the experimental measurements. The performance of the algorithm is tested. It is shown that the proposed algorithm is in average more than 12 times faster than the standard Picard direct iteration method.Comment: the information in this preprint is not up to date. Since the first publication of the preprint (9 Nov 2011) the algorithm was modified which allowed to achieve better results. For the new algorithm see the JCTC paper: DOI: 10.1021/ct200815v, http://pubs.acs.org/doi/abs/10.1021/ct200815

The Impact of Small Molecule Binding on the Energy Landscape of the Intrinsically Disordered Protein C-Myc

Intrinsically disordered proteins are attractive therapeutic targets owing to their prevalence in several diseases. Yet their lack of well-defined structure renders ligand discovery a challenging task. An intriguing example is provided by the oncoprotein c-Myc, a transcription factor that is over expressed in a broad range of cancers. Transcriptional activity of c-Myc is dependent on heterodimerization with partner protein Max. This protein-protein interaction is disrupted by the small molecule 10058-F4 (1), that binds to monomeric and disordered c-Myc. To rationalize the mechanism of inhibition, structural ensembles for the segment of the c-Myc domain that binds to 1 were computed in the absence and presence of the ligand using classical force fields and explicit solvent metadynamics molecular simulations. The accuracy of the computed structural ensembles was assessed by comparison of predicted and measured NMR chemical shifts. The small molecule 1 was found to perturb the composition of the apo equilibrium ensemble and to bind weakly to multiple distinct c-Myc conformations. Comparison of the apo and holo equilibrium ensembles reveals that the c-Myc conformations binding 1 are already partially formed in the apo ensemble, suggesting that 1 binds to c-Myc through an extended conformational selection mechanism. The present results have important implications for rational ligand design efforts targeting intrinsically disordered proteins

Актуальність впровадження систем газового обліку в сучасних умовах

Free energy calculation has long been an important goal for molecular dynamics simulation and force field development, but historically it has been challenged by limited performance, accuracy, and creation of topologies for arbitrary small molecules. This has made it difficult to systematically compare different sets of parameters to improve existing force fields, but in the past few years several authors have developed increasingly automated procedures to generate parameters for force fields such as Amber, CHARMM, and OPLS. Here, we present a new framework that enables fully automated generation of GROMACS topologies for any of these force fields and an automated setup for parallel adaptive optimization of high-throughput free energy calculation by adjusting lambda point placement on the fly. As a small example of this automated pipeline, we have calculated solvation free energies of 50 different small molecules using the GAFF, OPLS-AA, and CGenFF force fields and four different water models, and by including the often neglected polarization costs, we show that the common charge models are somewhat underpolarized.QC 20150505</p

Identification of a novel polyfluorinated compound as a lead to inhibit human enzymes aldose reductase and AKR1B10 : structure determination of both ternary complexes and implications for drug design

Aldo-keto reductases (AKRs) are mostly monomeric enzymes which fold into a highly conserved ([alpha]/[beta])8 barrel, while their substrate specificity and inhibitor selectivity are determined by interaction with residues located in three highly variable external loops. The closely related human enzymes aldose reductase (AR or AKR1B1) and AKR1B10 are of biomedical interest because of their involvement in secondary diabetic complications (AR) and in cancer, e.g. hepatocellular carcinoma and smoking-related lung cancer (AKR1B10). After characterization of the IC50 values of both AKRs with a series of polyhalogenated compounds, 2,2',3,3',5,5',6,6'-octafluoro-4,4'-biphenyldiol (JF0064) was identified as a lead inhibitor of both enzymes with a new scaffold (a 1,1'-biphenyl-4,4'-diol). An ultrahigh-resolution X-ray structure of the AR-­NADP+-JF0064 complex has been determined at 0.85 Å resolution, allowing it to be observed that JF0064 interacts with the catalytic residue Tyr48 through a negatively charged hydroxyl group (i.e. the acidic phenol). The non-competitive inhibition pattern observed for JF0064 with both enzymes suggests that this acidic hydroxyl group is also present in the case of AKR1B10. Moreover, the combination of surface lysine methylation and the introduction of K125R and V301L mutations enabled the determination of the X-ray crystallo­graphic structure of the corresponding AKR1B10-NADP+-JF0064 complex. Comparison of the two structures has unveiled some important hints for subsequent structure-based drug-design efforts

Rational design and validation of a Tip60 histone acetyltransferase inhibitor

Histone acetylation is required for many aspects of gene regulation, genome maintenance and metabolism and dysfunctional acetylation is implicated in numerous diseases, including cancer. Acetylation is regulated by histone acetyltransferases (HATs) and histone deacetylases and currently, few general HAT inhibitors have been described. We identified the HAT Tip60 as an excellent candidate for targeted drug development, as Tip60 is a key mediator of the DNA damage response and transcriptional co-activator. Our modeling of Tip60 indicated that the active binding pocket possesses opposite charges at each end, with the positive charges attributed to two specific side chains. We used structure based drug design to develop a novel Tip60 inhibitor, TH1834, to fit this specific pocket. We demonstrate that TH1834 significantly inhibits Tip60 activity in vitro and treating cells with TH1834 results in apoptosis and increased unrepaired DNA damage (following ionizing radiation treatment) in breast cancer but not control cell lines. Furthermore, TH1834 did not affect the activity of related HAT MOF, as indicated by H4K16Ac, demonstrating specificity. The modeling and validation of the small molecule inhibitor TH1834 represents a first step towards developing additional specific, targeted inhibitors of Tip60 that may lead to further improvements in the treatment of breast cancer

The Role of Phe82 and Phe351 in Auxin-Induced Substrate Perception by TIR1 Ubiquitin Ligase: A Novel Insight from Molecular Dynamics Simulations

It is well known that Auxin plays a key role in controlling many aspects of plant growth and development. Crystal structures of Transport inhibitor response 1 (TIR1), a true receptor of auxin, were very recently determined for TIR1 alone and in complexes with auxin and different synthetic analogues and an Auxin/Indole-3-Acetic Acid (Aux/IAA) substrate peptide. However, the dynamic conformational changes of the key residues of TIR1 that take place during the auxin and substrate perception by TIR1 and the detailed mechanism of these changes are still unclear. In the present study, various computational techniques were integrated to uncover the detailed molecular mechanism of the auxin and Aux/IAA perception process; these simulations included molecular dynamics (MD) simulations on complexes and the free enzyme, the molecular mechanics Poisson Boltzmann surface area (MM-PBSA) calculations, normal mode analysis, and hydrogen bond energy (HBE) calculations. The computational simulation results provided a reasonable explanation for the structure-activity relationships of auxin and its synthetic analogues in view of energy. In addition, a more detailed model for auxin and Aux/IAA perception was also proposed, indicating that Phe82 and Phe351 played a pivotal role in Aux/IAA perception. Upon auxin binding, Phe82 underwent conformational changes to accommodate the subsequent binding of Aux/IAA. As a result, auxin enhances the TIR1-Aux/IAA interactions by acting as a “molecular glue”. Besides, Phe351 acts as a “fastener” to further improve the substrate binding. The structural and mechanistic insights obtained from the present study will provide valuable clues for the future design of promising auxin analogues

Distinguishing Binders from False Positives by Free Energy Calculations: Fragment Screening Against the Flap Site of HIV Protease

Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand–receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein–ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets