Induction of Antibodies in Rhesus Macaques That Recognize a Fusion-Intermediate Conformation of HIV-1 gp41

A component to the problem of inducing broad neutralizing HIV-1 gp41 membrane proximal external region (MPER) antibodies is the need to focus the antibody response to the transiently exposed MPER pre-hairpin intermediate neutralization epitope. Here we describe a HIV-1 envelope (Env) gp140 oligomer prime followed by MPER peptide-liposomes boost strategy for eliciting serum antibody responses in rhesus macaques that bind to a gp41 fusion intermediate protein. This Env-liposome immunization strategy induced antibodies to the 2F5 neutralizing epitope 664DKW residues, and these antibodies preferentially bound to a gp41 fusion intermediate construct as well as to MPER scaffolds stabilized in the 2F5-bound conformation. However, no serum lipid binding activity was observed nor was serum neutralizing activity for HIV-1 pseudoviruses present. Nonetheless, the Env-liposome prime-boost immunization strategy induced antibodies that recognized a gp41 fusion intermediate protein and was successful in focusing the antibody response to the desired epitope

Understanding covariate shift in model performance [version 3; referees: 2 approved]

Three (3) different methods (logistic regression, covariate shift and k-NN) were applied to five (5) internal datasets and one (1) external, publically available dataset where covariate shift existed. In all cases, k-NN’s performance was inferior to either logistic regression or covariate shift. Surprisingly, there was no obvious advantage for using covariate shift to reweight the training data in the examined datasets

Extensive 1D, 2D NMR spectra of some [7.0]metacyclophanes and X-ray analysis of (±)-myricanol

From the hexane extract of the bark of Myrica cerifera, the pentacyclic triterpenes taraxerol and myricadiol were isolated. The EtOH extract afforded the [7.0]metacyclophanes, (±)-myricanol (4), and myricanone (7). Accurate 1H- and 13C-NMR spectral assignments have been made for (±)-myricanol (4), 5,11,17-tri-O-acetyl-(±)-myricanol (5), 11-O-methyl-(±)-myricanol (6), and myricanone (7) by a study of the 1H-1H-COSY, 1H-13C-COSY (HETCOR), selective INEPT, and 1D NOE experiments. The structure of (±)-myricanol was established by a single crystal X-ray analysis. Molecular mechanics MM-3(94) calculations have been made for (R,Sa)- and (S,Sa)-myricanol, and the bond lengths, bond angles, and the torsion angles have been calculated for the energy-minimized conformation

Collaborating to improve the use of free-energy and other quantitative methods in drug discovery

In May and August, 2016, several pharmaceutical companies convened to discuss and compare experiences with Free Energy Perturbation (FEP). This unusual synchronization of interest was prompted by Schrödinger’s FEP+ implementation and offered the opportunity to share fresh studies with FEP and enable broader discussions on the topic. This article summarizes key conclusions of the meetings, including a path forward of actions for this group to aid the accelerated evaluation, application and development of free energy and related quantitative, structure-based design methods

Prediction of Protein Pairs Sharing Common Active Ligands Using Protein Sequence, Structure, and Ligand Similarity

We benchmarked the ability of comparative computational approaches to correctly discriminate protein pairs sharing a common active ligand (positive protein pairs) from protein pairs with no common active ligands (negative protein pairs). Since the target and the off-targets of a drug share at least a common ligand, i.e., the drug itself, the prediction of positive protein pairs may help identify off-targets. We evaluated representative protein-centric and ligand-centric approaches, including (1) 2D and 3D ligand similarity, (2) several measures of protein sequence similarity in conjunction with different sequence sources (e.g., full protein sequence versus binding site residues), and (3) a newly described pocket shape similarity and alignment program called SiteHopper. While the sequence-based alignment of pocket residues achieved the best overall performance, SiteHopper outperformed sequence-based approaches for unrelated proteins with only 20–30% pocket residue identity. Analogously, among ligand-centric approaches, path-based fingerprints achieved the best overall performance, but ROCS-based ligand shape similarity outperformed path-based fingerprints for structurally dissimilar ligands (Tanimoto 25%–40%). A significant drop in recognition performance was observed for ligand-centric approaches when PDB ligands were used instead of ChEMBL ligands. Finally, we analyzed the relationship between pocket shape and ligand shape in our data set and found that similar ligands tend to bind to similar pockets while similar pockets may accept a range of different-shaped ligands

D3R Grand Challenge 4: Blind Prediction of Protein-Ligand Poses, Affinity Rankings, and Relative Binding Free Energies

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods.</div

D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods