1,721,016 research outputs found
Influence of linker flexibility on the binding affinity of bidentate binders
No full textThe design of responsive nanosensors typically relies on the availability of probes capable of capturing their target with high affinity and specificity. This can be achieved by coupling two or more binding units through a linker. In this work, we study the dependence on the binder architecture of the binding affinity between a target molecule and a semirigid bidentate binder. Using two different binder architectures, central-rigid and extreme-rigid, and modifying the length and the flexibility degree of the linker we generated 153 different architectures. We computed their dissociation free energies by means of Monte Carlo simulations and thermodynamic integration. We found that central-rigid bidentate binders are a poor choice, as they dissociate more easily than analogous fully flexible bidentate binders. On the other hand, molecular architectures presenting extreme-rigid units were shown effective for a wide range of set-ups
Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies
Full text linkNanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular
recognition. Their small size represents a precious advantage for rational mutagenesis based on
modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate
mutations by developing a simulation protocol based on all-atom molecular dynamics and wholemolecule
docking. The method was tested on two sets of nanobodies characterized experimentally
for their biophysical features. One set contained point mutations introduced to humanize a wild type
sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae
and human hallmarks. The method resulted in accurate scoring approaches to predict experimental
yields and enabled to identify the structural modifications induced by mutations. This work is a
promising tool for the in silico development of single-domain antibodies and opens the opportunity to
customize single functional domains of larger macromolecule
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Enhanced Molecular Dynamics Method to Efficiently Increase the Discrimination Capability of Computational Protein-Protein Docking
Full text linkProtein-protein docking typically consists of the generation of putative binding conformations, which are subsequently ranked by fast heuristic scoring functions. The simplicity of these functions allows for computational efficiency but has severe repercussions on their discrimination capabilities. In this work, we show the effectiveness of suitable descriptors calculated along short scaled molecular dynamics runs in recognizing the nearest-native bound conformation among a set of putative structures generated by the HADDOCK tool for eight protein-protein systems
Binding affinity prediction of nanobody-protein complexes by scoring of molecular dynamics trajectories
No full textNanobodies offer a viable alternative to antibodies for engineering high affinity binders. Their small size has an additional advantage: it allows exploiting computational protocols for optimizing their biophysical features, such as the binding affinity. The efficient prediction of this quantity is still considered a daunting task especially for modelled complexes. We show how molecular dynamics can successfully assist in the binding affinity prediction of modelled nanobody-protein complexes. The approximate initial configurations obtained by in silico design must undergo large rearrangements before achieving a stable conformation, in which the binding affinity can be meaningfully estimated. The scoring functions developed for the affinity evaluation of crystal structures will provide accurate estimates for modelled binding complexes if the scores are averaged over long finite temperature molecular dynamics simulations
Effects of knot type in the folding of topologically complex lattice proteins
No full textThe folding properties of a protein whose native structure contains a 52 knot are investigated by means of extensive Monte Carlo simulations of a simple lattice model and compared with those of a 31 knot. A 52 knot embedded in the native structure enhances the kinetic stability of the carrier lattice protein in a way that is clearly more pronounced than in the case of the 31 knot. However, this happens at the expense of a severe loss in folding efficiency, an observation that is consistent with the relative abundance of 31 and 52 knots in the Protein Data Bank. The folding mechanism of the 52 knot shares with that of the 31 knot the occurrence of a threading movement of the chain terminus that lays closer to the knotted core. However, co-concomitant knotting and folding in the 52 knot occurs with negligible probability, in sharp contrast to what is observed for the 31 knot. The study of several single point mutations highlights the importance in the folding of knotted proteins of the so-called structural mutations (i.e., energetic perturbations of native interactions between residues that are critical for knotting but not for folding). On the other hand, the present study predicts that mutations that perturb the folding transition state may significantly enhance the kinetic stability of knotted proteins provided they involve residues located within the knotted core. © 2014 AIP Publishing LLC
Statistical accuracy of molecular dynamics-based methods for sampling conformational ensembles of disordered proteins
Full text linkThe characterization of the statistical ensemble of conformations of intrinsically disordered regions (IDRs) is a great challenge both from experimental and computational points of view. In this respect, a number of protocols have been developed using molecular dynamics (MD) simulations to sample the huge conformational space of the molecule. In this work, we consider one of the best methods available, replica exchange solute tempering (REST), as a reference to compare the results obtained using this method with the results obtained using other methods, in terms of experimentally measurable quantities. Along with the methods assessed, we propose here a novel protocol called probabilistic MD chain growth (PMD-CG), which combines the flexible-meccano and hierarchical chain growth methods with the statistical data obtained from tripeptide MD trajectories as the starting point. The system chosen for testing is a 20-residue region from the C-terminal domain of the p53 tumor suppressor protein (p53-CTD). Our results show that PMD-CG provides an ensemble of conformations extremely quickly, after suitable computation of the conformational pool for all peptide triplets of the IDR sequence. The measurable quantities computed on the ensemble of conformations agree well with those based on the REST conformational ensemble
Antibody Affinity Maturation Using Computational Methods: From an Initial Hit to Small-Scale Expression of Optimized Binders
No full textNanobodies (VHHs) are engineered fragments of the camelid single-chain immunoglobulins. The VHH domain contains the highly variable segments responsible for antigen recognition. VHHs can be easily produced as recombinant proteins. Their small size is a good advantage for in silico approaches. Computer methods represent a valuable strategy for the optimization and improvement of their binding affinity. They also allow for epitope selection offering the possibility to design new VHHs for regions of a target protein that are not naturally immunogenic. Here we present an in silico mutagenic protocol developed to improve the binding affinity of nanobodies together with the first step of their in vitro production. The method, already proven successful in improving the low Kd of a nanobody hit obtained by panning, can be employed for the ex novo design of antibody fragments against selected protein target epitopes
Replica-exchange optimization of antibody fragments
No full textIn the framework of the rational design of macromolecules capable of binding to a specific target for biosensing applications, we here further develop an evolutionary protocol designed to optimize the binding affinity of protein binders. In particular we focus on the optimization of the binding portion of small antibody fragments known as nanobodies (or VHH) and choose the hen egg white lysozyme (HEWL) as our target. By implementing a replica exchange scheme for this optimization, we show that an initial hit is not needed and similar solutions can be found by either optimizing an already known anti-HEWL VHH or a randomly selected binder (here a VHH selective towards another macromolecule). While we believe that exhaustive searches of the mutation space are most appropriate when only few key residues have to be optimized, in case a lead binder is not available the proposed evolutionary algorithm should be instead the method of choice
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