Tower 1978

1978 yearbook of Westbrook College in Portland, Maine.https://dune.une.edu/wchc_yearbooks/1007/thumbnail.jp

Integrated Covalent Drug Design Workflow Using Site Identification by Ligand Competitive Saturation

Covalent drug design is an important component in drug discovery. Traditional drugs interact with their target in a reversible equilibrium, while irreversible covalent drugs increase the drug–target interaction duration by forming a covalent bond with targeted residues and thus may offer a more effective therapeutic approach. To facilitate the design of this class of ligands, computational methods can be used to help identify reactive nucleophilic residues, frequently cysteines, on a target protein for covalent binding, to test various warhead groups for their potential reactivities, and to predict noncovalent contributions to binding that can facilitate drug–target interactions that are important for binding specificity. To further aid covalent drug design, we extended a functional group mapping approach based on explicit solvent all-atom molecular simulations (SILCS: site identification by ligand competitive saturation) that intrinsically considers protein flexibility, functional group, and protein desolvation along with functional group–protein interactions. Through docking of a library of representative warhead fragments using SILCS-Monte Carlo (SILCS-MC), reactive cysteines can be correctly identified for proteins being tested. Furthermore, a machine learning model was trained to quantify the effectiveness of various warhead groups for proteins using metrics from SILCS-MC as well as experimental model compound warhead reactivity data. The ability to rank covalent molecular binders with similar warheads using SILCS ligand grid free energy (LGFE) ranking was also tested for several proteins. Based on these tools, an integrated SILCS-based workflow was developed, named SILCS-Covalent, which can both qualitatively and quantitatively inform covalent drug discovery

Sampling of Organic Solutes in Aqueous and Heterogeneous Environments Using Oscillating Excess Chemical Potentials in Grand Canonical-like Monte Carlo-Molecular Dynamics Simulations

Solute sampling of explicit bulk-phase aqueous environments in grand canonical (GC) ensemble simulations suffer from poor convergence due to low insertion probabilities of the solutes. To address this, we developed an iterative procedure involving Grand Canonical-like Monte Carlo (GCMC) and molecular dynamics (MD) simulations. Each iteration involves GCMC of both the solutes and water followed by MD, with the excess chemical potential (μ_ex) of both the solute and the water oscillated to attain their target concentrations in the simulation system. By periodically varying the μ_ex of the water and solutes over the GCMC-MD iterations, solute exchange probabilities and the spatial distributions of the solutes improved. The utility of the oscillating-μ_ex GCMC-MD method is indicated by its ability to approximate the hydration free energy (HFE) of the individual solutes in aqueous solution as well as in dilute aqueous mixtures of multiple solutes. For seven organic solutes: benzene, propane, acetaldehyde, methanol, formamide, acetate, and methylammonium, the average μ_ex of the solutes and the water converged close to their respective HFEs in both 1 M standard state and dilute aqueous mixture systems. The oscillating-μ_ex GCMC methodology is also able to drive solute sampling in proteins in aqueous environments as shown using the occluded binding pocket of the T4 lysozyme L99A mutant as a model system. The approach was shown to satisfactorily reproduce the free energy of binding of benzene as well as sample the functional group requirements of the occluded pocket consistent with the crystal structures of known ligands bound to the L99A mutant as well as their relative binding affinities

Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules

Receptor-based pharmacophore modeling is an efficient computer-aided drug design technique that uses the structure of the target protein to identify novel leads. However, most methods consider protein flexibility and desolvation effects in a very approximate way, which may limit their use in practice. The Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling protocol (SILCS-Pharm) was introduced recently to address these issues, as SILCS naturally takes both protein flexibility and desolvation effects into account by using full molecular dynamics simulations to determine 3D maps of the functional group-affinity patterns on a target receptor. In the present work, the SILCS-Pharm protocol is extended to use a wider range of probe molecules including benzene, propane, methanol, formamide, acetaldehyde, methylammonium, acetate and water. This approach removes the previous ambiguity brought by using water as both the hydrogen-bond donor and acceptor probe molecule. The new SILCS-Pharm protocol is shown to yield improved screening results, as compared to the previous approach based on three target proteins. Further validation of the new protocol using five additional protein targets showed improved screening compared to those using common docking methods, further indicating improvements brought by the explicit inclusion of additional feature types associated with the wider collection of probe molecules in the SILCS simulations. The advantage of using complementary features and volume constraints, based on exclusion maps of the protein defined from the SILCS simulations, is presented. In addition, reranking using SILCS-based ligand grid free energies is shown to enhance the diversity of identified ligands for the majority of targets. These results suggest that the SILCS-Pharm protocol will be of utility in rational drug design

Comprehensive Conformational Studies of Five Tripeptides and a Deduced Method for Efficient Determinations of Peptide Structures

Thorough searches on the potential energy surfaces of five tripeptides, GGG, GYG, GWG, TGG, and MGG, were performed by considering all possible combinations of the bond rotational degrees of freedom with a semiempirical and ab initio combined computational approach. Structural characteristics of the obtained stable tripeptide conformers were carefully analyzed. Conformers of the five tripeptides were found to be closely connected with conformers of their constituting dipeptides and amino acids. A method for finding all important tripeptide conformers by optimizing a small number of trial structures generated by suitable superposition of the parent amino acid and dipeptide conformers is thus proposed. Applying the method to another five tripeptides, YGG, FGG, WGG, GFA, and GGF, studied before shows that the new approach is both efficient and reliable by providing the most complete ensembles of tripeptide conformers. The method is further generalized for application to larger peptides by introducing the breeding and mutation concepts in a genetic algorithm way. The generalized method is verified to be capable of finding tetrapeptide conformers with secondary structures of strands, helices, and turns, which are highly populated in larger peptides. This show some promise for the proposed method to be applied for the structural determination of larger peptides

Mapping Functional Group Free Energy Patterns at Protein Occluded Sites: Nuclear Receptors and G‑Protein Coupled Receptors

Occluded ligand-binding pockets (LBP) such as those found in nuclear receptors (NR) and G-protein coupled receptors (GPCR) represent a significant opportunity and challenge for computer-aided drug design. To determine free energies maps of functional groups of these LBPs, a Grand-Canonical Monte Carlo/Molecular Dynamics (GCMC/MD) strategy is combined with the Site Identification by Ligand Competitive Saturation (SILCS) methodology. SILCS-GCMC/MD is shown to map functional group affinity patterns that recapitulate locations of functional groups across diverse classes of ligands in the LBPs of the androgen (AR) and peroxisome proliferator-activated-γ (PPARγ) NRs and the metabotropic glutamate (mGluR) and β₂-adreneric (β₂AR) GPCRs. Inclusion of protein flexibility identifies regions of the binding pockets not accessible in crystal conformations and allows for better quantitative estimates of relative ligand binding affinities in all the proteins tested. Differences in functional group requirements of the active and inactive states of the β₂AR LBP were used in virtual screening to identify high efficacy agonists targeting β₂AR in Airway Smooth Muscle (ASM) cells. Seven of the 15 selected ligands were found to effect ASM relaxation representing a 46% hit rate. Hence, the method will be of use for the rational design of ligands in the context of chemical biology and the development of therapeutic agents

Pathological changes in mice subjected to chronic i.n. LPS administration.

<p>a) Loss of dopaminergic neurons in the SN of mice challenged with right intranasal LPS administration of 10 µg/ every other day for 5 months; b) DA neurons in the VTA region on both sides; c) Representative photomicrographs illustrating TH immunoreactivity in the striatum; d) Neurons in the hippocampus and cortex were immunostained with anti-NeuN antibodies. Bars indicate SD for 7-10 mice. **<i>P</i><0.01 compared with contralateral side and saline control, respectively; scale bar is 2 mm. </p

The influence of peripheral immune on mice with chronic i.n. LPS.

<p>At the 5th month after LPS inoculation, mice were sacrificed and splenic mononuclear cells and the serum were isolated. The viability of T cells, oxidation products and inflammatory cytokines from spleens were detected in the presence and/or absence of α-synuclein stimulation by MTT, Nitrite and ELISA assays, respectively. Inflammatory cytokines from the serum were detected by ELISA assays. a) The viability of T cells; b) NO production, c) The secretion of inflammatory cytokines IL-1β, IL-6 and TNF-α; d) the secretion of Th1 IFN-γ, Th2 IL-10 and Th17 IL-17 and e) The secretion of inflammatory cytokines IL-1β, IL-6, IL-10 and TNF-α from the serum of the mice. There was no statistical significance between and within two groups. Determinations were performed in duplicate and results were expressed as mean±S.E.M. from at least six mice.</p

Behavioral alteration in mice with chronic i.n. LPS administration.

<p>a) The ambulatory motility (VM=voluntary movement), Motor behavior was analyzed in an open-field test at the 1st, 3rd and 5th months after LPS instillation. b) Adhesive removal test, the asymmetry of left and right movement was detected by the adhesive removal test at the 5th month after LPS instillation. c) Latency to find platforms (from day 1 to day 5), the cognition was measured by Morris water maze at the 5th month after LPS instillation. Left=time to remove adhesive dots from left forelimb; Right= time to remove adhesive dots from right forelimb. Bars indicate SD for 7-10 mice at each point. *<i>P</i><0.05 compared with the contralateral side and/or saline control, respectively. </p

The changes of the striatal biogenic amines following chronic i.n.

<div><p><b>LPS in mice</b>. </p> <p>The levels of DA and its major metabolites DOPAC and HVA, as well as NE, Iso, 5-HT and 5-HIAA in SN were determined by specific HPLC assay at the 5th month after LPS inoculation. a) DA; b) DOPAC; c) HVA and d) the ration of HVA/DA; e) NE; f) Iso; g) 5-HT; h) 5-HIAA. Quantitative results were obtained from among at least six mice. *<i>P</i><0.05 and **<i>P</i><0.01 compared with the contralateral striatum and saline control, respectively.</p></div