Nonbonded Force Field Parameters from MBIS Partitioning of the Molecular Electron Density Improve Binding Affinity Predictions of the T4-Lysozyme Double Mutant.

The use of computer simulation for binding affinity prediction is growing in drug discovery. However, its wider use is constrained by the accuracy of the free energy calculations. The key sources of error are the force fields used to depict molecular interactions and insufficient sampling of the configurational space. To improve the quality of the force field, we developed a Python-based computational workflow. The workflow described here uses the minimal basis iterative stockholder (MBIS) method to determine atomic charges and Lennard-Jones parameters from the polarized molecular density. This is done by performing electronic structure calculations on various configurations of the ligand when it is both bound and unbound. In addition, we validated a simulation procedure that accounts for the protein and ligand degrees of freedom to precisely calculate binding free energies. This was achieved by comparing the self-adjusted mixture sampling and nonequilibrium thermodynamic integration methods using various protein and ligand conformations. The accuracy of predicting binding affinity is improved by using MBIS-derived force field parameters and a validated simulation procedure. This improvement surpasses the chemical precision for the eight aromatic ligands, reaching a root-mean-square error of 0.7 kcal/mol.

Design and functional characterization of Salmo salar TLR5 agonist peptides derived from high mobility group B1 acidic tail.

Toll-like receptor 5 (TLR5) responds to the monomeric form of flagellin and induces the MyD88-depending signaling pathway, activating proinflammatory transcription factors such as NF-κB and the consequent induction of cytokines. On the other hand, HMGB1 is a highly conserved non-histone chromosomal protein shown to interact with and activate TLR5. The present work aimed to design and characterize TLR5 agonist peptides derived from the acidic tail of Salmo salar HMGB1 based on the structural knowledge of the TLR5 surface using global molecular docking platforms. Peptide binding poses complexed on TLR5 ectodomain model from each algorithm were filtrated based on docking scoring functions and predicted theoretical binding affinity of the complex. Circular dichroism spectra were recorded for each peptide selected for synthesis. Only intrinsically disordered peptides (6W, 11W, and SsOri) were selected for experimental functional assay. The functional characterization of the peptides was performed by NF-κB activation assays, RT-qPCR gene expression assays, and Piscirickettsia salmonis challenge in SHK-1 cells. The 6W and 11W peptides increased the nuclear translation of p65 and phosphorylation. In addition, the peptides induced the expression of genes related to the TLR5 pathway activation, pro- and anti-inflammatory response, and differentiation and activation of T lymphocytes towards phenotypes such as TH1, TH17, and TH2. Finally, it was shown that the 11W peptide protects immune cells against infection with P. salmonis bacteria. Overall, the results indicate the usefulness of novel peptides as potential immunostimulants in salmonids.

Nonbonded Force Field Parameters from Minimal Basis Iterative Stockholder Partitioning of the Molecular Electron Density Improve CB7 Host-Guest Affinity Predictions.

Binding affinity prediction by means of computer simulation has been increasingly incorporated in drug discovery projects. Its wide application, however, is limited by the prediction accuracy of the free energy calculations. The main error sources are force fields used to describe molecular interactions and incomplete sampling of the configurational space. Organic host-guest systems have been used to address force field quality because they share similar interactions found in ligands and receptors, and their rigidity facilitates configurational sampling. Here, we test the binding free energy prediction accuracy for 14 guests with an aromatic or adamantane core and the CB7 host using molecular electron density derived nonbonded force field parameters. We developed a computational workflow written in Python to derive atomic charges and Lennard-Jones parameters with the Minimal Basis Iterative Stockholder method using the polarized electron density of several configurations of each guest in the bound and unbound states. The resulting nonbonded force field parameters improve binding affinity prediction, especially for guests with an adamantane core in which repulsive exchange and dispersion interactions to the host dominate.

Molecular Environment-Specific Atomic Charges Improve Binding Affinity Predictions of SAMPL5 Host-Guest Systems.

Host-guest systems are widely used in benchmarks as model systems to improve computational methods for absolute binding free energy predictions. Recent advances in sampling algorithms for alchemical free energy calculations and the increase in computational power have made their binding affinity prediction primarily dependent on the quality of the force field. Here, we propose a new methodology to derive the atomic charges of host-guest systems based on quantum mechanics/molecular mechanics calculations and minimal basis iterative stockholder (MBIS) partitioning of the polarized electron density. A newly developed interface between the OpenMM and ORCA software packages provides D-MBIS charges that represent the guest's average electrostatic interactions in the hosts or the solvent. The simulation workflow also calculates the average energy required to polarize the guest in the bound and unbound state. Alchemical free energy calculations using the general Amber force field parameters with D-MBIS charges improve the binding affinity prediction of six guests bound to two octa acid hosts compared to the AM1-BCC charge set after correction with the average energetic polarization cost. This correction originates from the difference in potential energy that is required to polarize the guest in the bound and unbound state and contributes significantly to the binding affinity of anionic guests.

A trivalent TNF-R2 as a new tumor necrosis factor alpha-blocking molecule.

The neutralization of tumor necrosis factor alpha (TNFα) with biopharmaceuticals is a successful therapy for inflammatory diseases. Currently, one of the main TNFα-antagonists is Etanercept, a dimeric TNF-R2 ectodomain. Considering that TNFα and its receptors are homotrimers, we proposed that a trimeric TNF-R2 ectodomain could be an innovative TNFα-antagonist. Here, the 3cTNFR2 protein was designed by the fusion of the TNF-R2 ectodomain with the collagen XV trimerization domain. 3cTNFR2 was produced in HEK293 cells and purified by immobilized metal affinity chromatography. Monomers, dimers, and trimers of 3cTNFR2 were detected. The interaction 3cTNFR2-TNFα was assessed. By microscale thermophoresis, the KD value for the interaction was 4.17 ± 0.88 nM, and complexes with different molecular weights were detected by size exclusion chromatography-high performance liquid chromatography. Moreover, 3cTNFR2 neutralized the TNFα-induced cytotoxicity totally in vitro. Although more studies are required to evaluate the anti-inflammatory effect, the results suggest that 3cTNFR2 could be a TNFα-antagonist agent.

Expression and characterization of a novel single-chain anti-vascular endothelial growth factor antibody in the goat milk.

Vascular endothelial growth factor (VEGF) has essential functions in angiogenesis, endothelial cell proliferation, migration, and tumor invasion. Different approaches have been developed to suppress tumor angiogenesis, which is considered a hallmark of cancer. Anti-VEGF monoclonal antibodies constitute an important strategy for cancer immunotherapy, which has been produced on several platforms. In this study, a novel single-chain anti-VEGF monoclonal antibody (scVEGFmAb) was produced in the goat mammary gland by adenoviral transduction. scVEGFmAb was purified by affinity chromatography. N-glycans were analyzed by exoglycosidase digestion and hydrophilic interaction ultra-performance liquid chromatography coupled to electrospray ionization mass spectrometry. The biological activity of scVEGFmAb was assessed by scratch and mouse aortic ring assays. scVEGFmAb was produced at 0.61 g/L in the goat milk, and its purification rendered 95 % purity. N-glycans attached to scVEGFmAb backbone were mainly neutral biantennary core fucosylated with Galß1,4GlcNAc motif, and charged structures were capped with Neu5Ac and Neu5Gc. The chimeric molecule significantly prevented cell migration and suppressed microvessel sprouting. These results demonstrated for the first time the feasibility of producing an anti-VEGF therapeutic antibody in the milk of non-transgenic goats with the potential to counteract tumor angiogenesis.

Design and characterization of a novel dimeric blood-brain barrier penetrating TNFα inhibitor.

Tumor necrosis factor-alpha (TNFα) inhibitors could prevent neurological disorders systemically, but their design generally relies on molecules unable to cross the blood-brain barrier (BBB). This research was aimed to design and characterize a novel TNFα inhibitor based on the angiopeptide-2 as a BBB shuttle molecule fused to the extracellular domain of human TNFα receptor 2 and a mutated vascular endothelial growth factor (VEGF) dimerization domain. This new chimeric protein (MTV) would be able to trigger receptor-mediated transcytosis across the BBB via low-density lipoprotein receptor-related protein-1 (LRP-1) and inhibit the cytotoxic effect of TNFα more efficiently because of its dimeric structure. Stably transformed CHO cells successfully expressed MTV, and its purification by Immobilized-Metal Affinity Chromatography (IMAC) rendered high purity degree. Mutated VEGF domain included in MTV did not show cell proliferation or angiogenic activities measured by scratch and aortic ring assays, which corroborate that the function of this domain is restricted to dimerization. The pairs MTV-TNFα (Kd 279 ± 40.9 nM) and MTV-LRP1 (Kd 399 ± 50.5 nM) showed high affinity by microscale thermophoresis, and a significant increase in cell survival was observed after blocking TNFα with MTV in a cell cytotoxicity assay. Also, the antibody staining in CHOK1 and bEnd3 cells demonstrated the adhesion of MTV to the LRP1 receptor located in the cell membrane. These results provide compelling evidence for the proper functioning of the three main domains of MTV individually, which encourage us to continue the research with this new molecule as a potential candidate for the systemic treatment of neurological disorders.

IOData: A python library for reading, writing, and converting computational chemistry file formats and generating input files.

IOData is a free and open-source Python library for parsing, storing, and converting various file formats commonly used by quantum chemistry, molecular dynamics, and plane-wave density-functional-theory software programs. In addition, IOData supports a flexible framework for generating input files for various software packages. While designed and released for stand-alone use, its original purpose was to facilitate the interoperability of various modules in the HORTON and ChemTools software packages with external (third-party) molecular quantum chemistry and solid-state density-functional-theory packages. IOData is designed to be easy to use, maintain, and extend; this is why we wrote IOData in Python and adopted many principles of modern software development, including comprehensive documentation, extensive testing, continuous integration/delivery protocols, and package management. This article is the official release note of the IOData library.

New insights on the interaction mechanism of rhTNFα with its antagonists Adalimumab and Etanercept.

TNFα is a pro-inflammatory cytokine that is a therapeutic target for inflammatory autoimmune disorders. Thus, TNFα antagonists are successfully used for the treatment of these disorders. Here, new association patterns of rhTNFα and its antagonists Adalimumab and Etanercept are disclosed. Active rhTNFα was purified by IMAC from the soluble fraction of transformed Escherichia coli. Protein detection was assessed by SDS-PAGE and Western blot. The KD values for rhTNFα interactions with their antagonists were obtained by non-competitive ELISA and by microscale thermophoresis (MST). Molecular sizes of the complexes were evaluated by size-exclusion chromatography-high performance liquid chromatography (SEC-HPLC). Surprisingly, both antagonists recognized the monomeric form of rhTNFα under reducing and non-reducing conditions, indicating unexpected bindings of the antagonists to linear epitopes and to rhTNFα monomers. For the first time, the interactions of rhTNFα with Adalimumab and Etanercept were assessed by MST, which allows evaluating molecular interactions in solution with a wide range of concentrations. Biphasic binding curves with low and high KD values (<10-9 M and >10-8 M) were observed during thermophoresis experiments, suggesting the generation of complexes with different stoichiometry, which were confirmed by SEC-HPLC. Our results demonstrated the binding of TNFα-antagonists with rhTNFα monomers and linear epitopes. Also, complexes of high molecular mass were observed. This pioneer investigation constitutes valuable data for future approaches into the study of the interaction mechanism of TNFα and its antagonists.