On the fly estimation of host–guest binding free energies using the movable type method: participation in the SAMPL5 blind challenge

We review our performance in the SAMPL5 challenge for predicting host–guest binding affinities using the movable type (MT) method. The challenge included three hosts, acyclic Cucurbit[2]uril and two octa-acids with and without methylation at the entrance to their binding cavities. Each host was associated with 6–10 guest molecules. The MT method extrapolates local energy landscapes around particular molecular states and estimates the free energy by Monte Carlo integration over these landscapes. Two blind submissions pairing MT with variants of the KECSA potential function yielded mean unsigned errors of 1.26 and 1.53 kcal/mol for the non-methylated octa-acid, 2.83 and 3.06 kcal/mol for the methylated octa-acid, and 2.77 and 3.36 kcal/mol for Cucurbit[2]uril host. While our results are in reasonable agreement with experiment, we focused on particular cases in which our estimates gave incorrect results, particularly with regard to association between the octa-acids and an adamantane derivative. Working on the hypothesis that differential solvation effects play a role in effecting computed binding affinities for the parent octa-acid and the methylated octa-acid and that the ligands bind inside the pockets (rather than on the surface) we devised a new solvent accessible surface area term to better quantify solvation energy contributions in MT based studies. To further explore this issue a, molecular dynamics potential of mean force (PMF) study indicates that, as found by our docking calculations, the stable binding mode for this ligand is inside (rather than surface bound) the octa-acid cavity whether the entrance is methylated or not. The PMF studies also obtained the correct order for the methylation-induced change in binding affinities and associated the difference, to a large extent to differential solvation effects. Overall, the SAMPL5 challenge yielded in improvements our solvation modeling and also demonstrated the need for thorough validation of input data integrity prior to any computational analysis.     

Empowering pharmacoinformatics by linked life science data

With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models.     

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

The growing number of protein–ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein–ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein–ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein–ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein–ligand complex structures available to improve predictions on binding.     

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

\(\alpha\)-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577–585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM. Website is implemented in PHP, MySQL and Apache, with all major browsers supported.     

Co-operative intra-protein structural response due to protein–protein complexation revealed through thermodynamic quantification: study of MDM2-p53 binding

The p53 protein activation protects the organism from propagation of cells with damaged DNA having oncogenic mutations. In normal cells, activity of p53 is controlled by interaction with MDM2. The well understood p53-MDM2 interaction facilitates design of ligands that could potentially disrupt or prevent the complexation owing to its emergence as an important objective for cancer therapy. However, thermodynamic quantification of the p53-peptide induced structural changes of the MDM2-protein remains an area to be explored. This study attempts to understand the conformational free energy and entropy costs due to this complex formation from the histograms of dihedral angles generated from molecular dynamics simulations. Residue-specific quantification illustrates that, hydrophobic residues of the protein contribute maximum to the conformational thermodynamic changes. Thermodynamic quantification of structural changes of the protein unfold the fact that, p53 binding provides a source of inter-element cooperativity among the protein secondary structural elements, where the highest affected structural elements (α2 and α4) found at the binding site of the protein affects faraway structural elements (β1 and Loop1) of the protein. The communication perhaps involves water mediated hydrogen bonded network formation. Further, we infer that in inhibitory F19A mutation of P53, though Phe19 is important in the recognition process, it has less prominent contribution in the stability of the complex. Collectively, this study provides vivid microscopic understanding of the interaction within the protein complex along with exploring mutation sites, which will contribute further to engineer the protein function and binding affinity.     

Computational design of bio-inspired carnosine-based HOBr antioxidants

During a respiratory burst the enzyme myeloperoxidase generates significant amounts of hypohalous acids (HOX, X?=?Cl and Br) in order to inflict oxidative damage upon invading pathogens. However, excessive production of these potent oxidants is associated with numerous inflammatory diseases. It has been suggested that the endogenous antioxidant carnosine is an effective HOCl scavenger. Recent computational and experimental studies suggested that an intramolecular Cl⁺ transfer from the imidazole ring to the terminal amine might play an important role in the antioxidant activity of carnosine. Based on high-level ab initio calculations, we propose a similar reaction mechanism for the intramolecular Br⁺ transfer in carnosine. These results suggest that carnosine may be an effective HOBr scavenger. On the basis of the proposed reaction mechanism, we proceed to design systems that share similar structural features to carnosine but with enhanced HOX scavenging capabilities for X?=?Cl and Br. We find that (i) elongating the β-alanyl-glycyl side chain by one carbon reduces the reaction barriers by up to 44%, and (ii) substituting the imidazole ring with strong electron-donating groups reduces the reaction barriers by similar amounts. We also show that the above structural and electronic effects are largely additive. In an antioxidant candidate that involves both of these effects the reaction barriers are reduced by 71%.     

An investigation of the complexation of host <Emphasis Type="Italic">N,N′</Emphasis>-bis(9-phenyl-9-thioxanthenyl)ethylenediamine with dihaloalkane guests

In this study, the formation of supramolecular inclusion complex of doxorubicin (DOX), a high loading and pH-dependent delivery of DOX on β-CD dendrimer was studied. β-cyclodextrin (β-CD) dendrimer having β-CD in both periphery and core was prepared with entrapment efficiency using click reaction. The encapsulation property of the β-CD-dendrimer was investigated by DOX as model drug. The chemical construction of β-CD-dendrimer was described by ¹H NMR, ¹³C NMR and FTIR and its inclusion complex construction was studied by FTIR, DSC, SEM, and DLS techniques. It was confirmed that β-CD dendrimer able to encapsulate DOX in solution; as a result, the designed complex revealed pH-dependent sustained release of DOX, in vitro. Also, the in vitro outcomes on T47D cells displayed that complexation of DOX with β-CD dendrimer involved an improvement of in vitro cytotoxicity and anticancer activity and this data appeared to be as a result of the developed solubility of the DOX.     

Cucurbit[<Emphasis Type="Italic">n</Emphasis>]uril-based host–guest-metal ion chemistry: an emerging branch in cucurbit[<Emphasis Type="Italic">n</Emphasis>]uril chemistry

The unique pumpkin-shape macrocyclic structure with inherent cavities renders cucurbituril (CB) a type of versatile supramolecular container. On account of their good biocompatibility and low toxicity, the applications of CB to encapsulate drug molecules provide promising candidates and the pharmacological activities have been investigated currently. How to control over the uptake and release of the guest at will is significant for practical applications of drug delivery. The noncovalent nature of supramolecular interactions offers variety of options to control the release of guest molecules from CB under external stimuli, including pH, temperature, metal cations, competing guests, light, redox and so on. Moreover, CB containers are capable of assembling into higher ordered supramolecular structures such as polymers, nanoparticles, hydrogels, and colloids, which greatly enrich the scope of CB-type inclusion materials. Those results provide useful principles and guidelines for controlled release from supramolecular containers.