A rational engineering strategy for designing protein a-binding camelid single-domain antibodies

Staphylococcal protein A (SpA) and streptococcal protein G (SpG) affinity chromatography are the gold standards for purifying monoclonal antibodies (mAbs) in therapeutic applications. However, camelid VHH single-domain Abs (sdAbs or VHHs) are not bound by SpG and only sporadically bound by SpA. Currently, VHHs require affinity tag-based purification, which limits their therapeutic potential and adds considerable complexity and cost to their production. Here we describe a simple and rapid mutagenesis-based approach designed to confer SpA binding upon a priori non-SpA-binding VHHs. We show that SpA binding of VHHs is determined primarily by the same set of residues as in human mAbs, albeit with an unexpected degree of tolerance to substitutions at certain core and non-core positions and some limited dependence on at least one residue outside the SpA interface, and that SpA binding could be successfully introduced into five VHHs against three different targets with no adverse effects on expression yield or antigen binding. Next-generation sequencing of llama, alpaca and dromedary VHH repertoires suggested that species differences in SpA binding may result from frequency variation in specific deleterious polymorphisms, especially Ile57. Thus, the SpA binding phenotype of camelid VHHs can be easily modulated to take advantage of tag-less purification techniques, although the frequency with which this is required may depend on the source species

Solvation models: Theory and validation

Water plays an active role in many fundamental phenomena in cellular systems such as molecular recognition, folding and conformational equilibria, reaction kinetics and phase partitioning. Hence, our ability to account for the energetics of these processes is highly dependent on the models we use for calculating solvation effects. For example, theoretical prediction of protein-ligand binding modes (i.e., docking) and binding affinities (i.e., scoring) requires an accurate description of the change in hydration that accompanies solute binding. In this review, we discuss the challenges of constructing solvation models that capture these effects, with an emphasis on continuum models and on more recent developments in the field. In our discussion of methods, relatively greater attention will be given to boundary element solutions to the Poisson equation and to nonpolar solvation models, two areas that have become increasingly important but are likely to be less familiar to many readers. The other focus will be upon the trending efforts for evaluating solvation models in order to uncover limitations, biases, and potentially attractive directions for their improvement and applicability. The prospective and retrospective performance of a variety of solvation models in the SAMPL blind challenges will be discussed in detail. After just a few years, these benchmarking exercises have already had a tangible effect in guiding the improvement of solvation models. \ua9 2014 Bentham Science Publishers.Peer reviewed: YesNRC publication: Ye

Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge

We continued prospective assessments of the Wilma-solvated interaction energy (SIE) platform for pose prediction, binding affinity prediction, and virtual screening on the challenging SAMPL4 data sets including the HIV-integrase inhibitor and two host-guest systems. New features of the docking algorithm and scoring function are tested here prospectively for the first time. Wilma-SIE provides good correlations with actual binding affinities over a wide range of binding affinities that includes strong binders as in the case of SAMPL4 host-guest systems. Absolute binding affinities are also reproduced with appropriate training of the scoring function on available data sets or from comparative estimation of the change in target's vibrational entropy. Even when binding modes are known, SIE predictions lack correlation with experimental affinities within dynamic ranges below 2\ua0kcal/mol as in the case of HIV-integrase ligands, but they correctly signaled the narrowness of the dynamic range. Using a common protein structure for all ligands can reduce the noise, while incorporating a more sophisticated solvation treatment improves absolute predictions. The HIV-integrase virtual screening data set consists of promiscuous weak binders with relatively high flexibility and thus it falls outside of the applicability domain of the Wilma-SIE docking platform. Despite these difficulties, unbiased docking around three known binding sites of the enzyme resulted in over a third of ligands being docked within 2\ua0\uc5 from their actual poses and over half of the ligands docked in the correct site, leading to better-than-random virtual screening results. \ua9 2014 Her Majesty the Queen in Right of Canada.Peer reviewed: YesNRC publication: Ye

Inhibition of a cathepsin L-like cysteine protease by a chimeric propeptide-derived inhibitor

International audienc

Local elevation: A method for improving the searching properties of molecular dynamics simulation

The concept of memory has been introduced into a molecular dynamics algorithm. This was done so as to persuade a molecular system to visit new areas of conformational space rather than be confined to a small number of low-energy regions. The method is demonstrated on a simple model system and the 11-residue cyclic peptide cyclosporin A. For comparison, calculations were also performed using simulated temperature annealing and a potential energy annealing scheme. Although the method can only be applied to systems with a small number of degrees of freedom, it offers the chance to generate a multitude of different low-energy structures, where other methods only give a single one or few. This is clearly important in problems such as drug design, where one is interested in the conformational spread of a system. © 1994 ESCOM Science Publishers B.V