The ClusPro AbEMap web server for the prediction of antibody epitopes.

Antibodies play an important role in the immune system by binding to molecules called antigens at their respective epitopes. These interfaces or epitopes are structural entities determined by the interactions between an antibody and an antigen, making them ideal systems to analyze by using docking programs. Since the advent of high-throughput antibody sequencing, the ability to perform epitope mapping using only the sequence of the antibody has become a high priority. ClusPro, a leading protein-protein docking server, together with its template-based modeling version, ClusPro-TBM, have been re-purposed to map epitopes for specific antibody-antigen interactions by using the Antibody Epitope Mapping server (AbEMap). ClusPro-AbEMap offers three different modes for users depending on the information available on the antibody as follows: (i) X-ray structure, (ii) computational/predicted model of the structure or (iii) only the amino acid sequence. The AbEMap server presents a likelihood score for each antigen residue of being part of the epitope. We provide detailed information on the server's capabilities for the three options and discuss how to obtain the best results. In light of the recent introduction of AlphaFold2 (AF2), we also show how one of the modes allows users to use their AF2-generated antibody models as input. The protocol describes the relative advantages of the server compared to other epitope-mapping tools, its limitations and potential areas of improvement. The server may take 45-90 min depending on the size of the proteins.

Neural network-derived Potts models for structure-based protein design using backbone atomic coordinates and tertiary motifs.

Designing novel proteins to perform desired functions, such as binding or catalysis, is a major goal in synthetic biology. A variety of computational approaches can aid in this task. An energy-based framework rooted in the sequence-structure statistics of tertiary motifs (TERMs) can be used for sequence design on predefined backbones. Neural network models that use backbone coordinate-derived features provide another way to design new proteins. In this work, we combine the two methods to make neural structure-based models more suitable for protein design. Specifically, we supplement backbone-coordinate features with TERM-derived data, as inputs, and we generate energy functions as outputs. We present two architectures that generate Potts models over the sequence space: TERMinator, which uses both TERM-based and coordinate-based information, and COORDinator, which uses only coordinate-based information. Using these two models, we demonstrate that TERMs can be utilized to improve native sequence recovery performance of neural models. Furthermore, we demonstrate that sequences designed by TERMinator are predicted to fold to their target structures by AlphaFold. Finally, we show that both TERMinator and COORDinator learn notions of energetics, and these methods can be fine-tuned on experimental data to improve predictions. Our results suggest that using TERM-based and coordinate-based features together may be beneficial for protein design and that structure-based neural models that produce Potts energy tables have utility for flexible applications in protein science.

Mapping of antibody epitopes based on docking and homology modeling.

Antibodies are key proteins produced by the immune system to target pathogen proteins termed antigens via specific binding to surface regions called epitopes. Given an antigen and the sequence of an antibody the knowledge of the epitope is critical for the discovery and development of antibody based therapeutics. In this work, we present a computational protocol that uses template-based modeling and docking to predict epitope residues. This protocol is implemented in three major steps. First, a template-based modeling approach is used to build the antibody structures. We tested several options, including generation of models using AlphaFold2. Second, each antibody model is docked to the antigen using the fast Fourier transform (FFT) based docking program PIPER. Attention is given to optimally selecting the docking energy parameters depending on the input data. In particular, the van der Waals energy terms are reduced for modeled antibodies relative to x-ray structures. Finally, ranking of antigen surface residues is produced. The ranking relies on the docking results, that is, how often the residue appears in the docking poses' interface, and also on the energy favorability of the docking pose in question. The method, called PIPER-Map, has been tested on a widely used antibody-antigen docking benchmark. The results show that PIPER-Map improves upon the existing epitope prediction methods. An interesting observation is that epitope prediction accuracy starting from antibody sequence alone does not significantly differ from that of starting from unbound (i.e., separately crystallized) antibody structure.

Assessing the binding properties of CASP14 targets and models.

An important question is how well the models submitted to CASP retain the properties of target structures. We investigate several properties related to binding. First we explore the binding of small molecules as probes, and count the number of interactions between each residue and such probes, resulting in a binding fingerprint. The similarity between two fingerprints, one for the X-ray structure and the other for a model, is determined by calculating their correlation coefficient. The fingerprint similarity weakly correlates with global measures of accuracy, and GDT_TS higher than 80 is a necessary but not sufficient condition for the conservation of surface binding properties. The advantage of this approach is that it can be carried out without information on potential ligands and their binding sites. The latter information was available for a few targets, and we explored whether the CASP14 models can be used to predict binding sites and to dock small ligands. Finally, we tested the ability of models to reproduce protein-protein interactions by docking both the X-ray structures and the models to their interaction partners in complexes. The analysis showed that in CASP14 the quality of individual domain models is approaching that offered by X-ray crystallography, and hence such models can be successfully used for the identification of binding and regulatory sites, as well as for assembling obligatory protein-protein complexes. Success of ligand docking, however, often depends on fine details of the binding interface, and thus may require accounting for conformational changes by simulation methods.

Improved cluster ranking in protein-protein docking using a regression approach.

We develop a Regression-based Ranking by Pairwise Cluster Comparisons (RRPCC) method to rank clusters of similar protein complex conformations generated by an underlying docking program. The method leverages robust regression to predict the relative quality difference between any pair or clusters and combines these pairwise assessments to form a ranked list of clusters, from higher to lower quality. We apply RRPCC to clusters produced by the automated docking server ClusPro and, depending on the training/validation strategy, we show improvement by 24-100% in ranking acceptable or better quality clusters first, and by 15-100% in ranking medium or better quality clusters first. We compare the RRPCC-ClusPro combination to a number of alternatives, and show that very different machine learning approaches to scoring docked structures yield similar success rates. Finally, we discuss the current limitations on sampling and scoring, looking ahead to further improvements. Interestingly, some features important for improved scoring are internal energy terms that occur only due to the local energy minimization applied in the refinement stage following rigid body docking.

Performance and Its Limits in Rigid Body Protein-Protein Docking.

The development of fast Fourier transform (FFT) algorithms enabled the sampling of billions of complex conformations and thus revolutionized protein-protein docking. FFT-based methods are now widely available and have been used in hundreds of thousands of docking calculations. Although the methods perform "soft" docking, which allows for some overlap of component proteins, the rigid body assumption clearly introduces limitations on accuracy and reliability. In addition, the method can work only with energy expressions represented by sums of correlation functions. In this paper we use a well-established protein-protein docking benchmark set to evaluate the results of these limitations by focusing on the performance of the docking server ClusPro, which implements one of the best rigid body methods. Furthermore, we explore the theoretical limits of accuracy when using established energy terms for scoring, provide comparison with flexible docking algorithms, and review the historical performance of servers in the CAPRI docking experiment.

ClusPro in rounds 38 to 45 of CAPRI: Toward combining template-based methods with free docking.

Targets in the protein docking experiment CAPRI (Critical Assessment of Predicted Interactions) generally present new challenges and contribute to new developments in methodology. In rounds 38 to 45 of CAPRI, most targets could be effectively predicted using template-based methods. However, the server ClusPro required structures rather than sequences as input, and hence we had to generate and dock homology models. The available templates also provided distance restraints that were directly used as input to the server. We show here that such an approach has some advantages. Free docking with template-based restraints using ClusPro reproduced some interfaces suggested by weak or ambiguous templates while not reproducing others, resulting in correct server predicted models. More recently we developed the fully automated ClusPro TBM server that performs template-based modeling and thus can use sequences rather than structures of component proteins as input. The performance of the server, freely available for noncommercial use at https://tbm.cluspro.org, is demonstrated by predicting the protein-protein targets of rounds 38 to 45 of CAPRI.

Mechanically Responsive Crystals: Analysis of Macroscopic Strain Reveals "Hidden" Processes.

Mechanical response of single crystals to light, temperature, and/or force-an emerging platform for the development of new organic actuating materials for soft robotics-has recently been quantitatively described by a general and robust mathematical model ( Chem. Rev . 2015 , 115 , 12440 - 12490 ). The model can be used to extract accurate activation energies and kinetics of solid-state chemical reactions simply by tracking the time-dependent bending of the crystal. Here we illustrate that deviations of the macroscopic strain in the crystal from that predicted by the model reveal the existence of additional, "hidden" chemical or physical processes, such as sustained structural relaxation between the chemical transformation and the resulting macroscopic deformation of the crystal. This is illustrated with photobendable single crystals of 4-hydroxy-2-(2-pyridinylmethylene)hydrazide, a photochemical switch that undergoes E-to-Z isomerization. The irreversible isomerization in these crystals results in amorphization and plastic deformation that are observed as poor correlation between the transformation extent and the induced strains. The occurrence of these processes was independently confirmed by X-ray diffraction and differential scanning calorimetry. An extended mathematical model is proposed to account for this complex mechanical response.

Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment.

We present the results for CAPRI Round 46, the third joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo-oligomers and 6 heterocomplexes. Eight of the homo-oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher-order assemblies. These were more difficult to model, as their prediction mainly involved "ab-initio" docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance "gap" was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template-based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

Template-based modeling by ClusPro in CASP13 and the potential for using co-evolutionary information in docking.

As a participant in the joint CASP13-CAPRI46 assessment, the ClusPro server debuted its new template-based modeling functionality. The addition of this feature, called ClusPro TBM, was motivated by the previous CASP-CAPRI assessments and by the proven ability of template-based methods to produce higher-quality models, provided templates are available. In prior assessments, ClusPro submissions consisted of models that were produced via free docking of pre-generated homology models. This method was successful in terms of the number of acceptable predictions across targets; however, analysis of results showed that purely template-based methods produced a substantially higher number of medium-quality models for targets for which there were good templates available. The addition of template-based modeling has expanded ClusPro's ability to produce higher accuracy predictions, primarily for homomeric but also for some heteromeric targets. Here we review the newest additions to the ClusPro web server and discuss examples of CASP-CAPRI targets that continue to drive further development. We also describe ongoing work not yet implemented in the server. This includes the development of methods to improve template-based models and the use of co-evolutionary information for data-assisted free docking.

What method to use for protein-protein docking?

A number of well-established servers perform 'free' docking of proteins of known structures. In contrast, template-based docking can start from sequences if structures are available for complexes that are homologous to the target. On the basis of the results of the CAPRI-CASP structure prediction experiments, template-based methods yield more accurate predictions if good templates can be found, but generally fail without such templates. However, free global docking, or focused docking around even poor quality template-based models, can still generate acceptable docked structures in these cases. In accordance with the analysis of a benchmark set, free docking of heterodimers yields acceptable or better predictions in the top 10 models for around 40% of structures. However, it is likely that a combination of template-based and free docking methods can perform better for targets that have template structures available. Another way of improving the reliability of predictions is adding experimental information as restraints, an option built into several docking servers.

Detecting and Trapping of a Single C. elegans Worm in a Microfluidic Chip for Automated Microplate Dispensing.

Microfluidic devices offer new technical possibilities for a precise manipulation of Caenorhabditis elegans due to the comparable length scale. C. elegans is a small, free-living nematode worm that is a popular model system for genetic, genomic, and high-throughput experimental studies of animal development and neurobiology. In this paper, we demonstrate a microfluidic system in polydimethylsiloxane (PDMS) for dispensing of a single C. elegans worm into a 96-well plate. It consists of two PDMS layers, a flow and a control layer. Using five microfluidic pneumatic valves in the control layer, a single worm is trapped upon optical detection with a pair of optical fibers integrated perpendicular to the constriction channel and then dispensed into a microplate well with a dispensing tip attached to a robotic handling system. Due to its simple design and facile fabrication, we expect that our microfluidic chip can be expanded to a multiplexed dispensation system of C. elegans worms for high-throughput drug screening.

Crystals on the move: mechanical effects in dynamic solids.

When exposed to external stimuli such as heat or light, certain single crystals can acquire momentum and undergo motion. On a molecular scale, the motility of such dynamic single crystals is triggered by a phase transition or chemical reaction without gaseous products, and macroscopically manifests as either slow (reversible or irreversible) deformation, or as rapid, almost instantaneous propulsion of the crystals that is oftentimes accompanied by disintegration. While the elastic energy of the slow reconfiguration processes such as bending, twisting and coiling can be utilized for actuation of other objects, the fast disintegrative processes could be exploited to initiate pressure-sensitive applications. This short review intends to summarize recent developments in the growing research on dynamic crystals, especially aspects of the mechanism of rapid motion of thermosalient and photosalient (leaping) crystals. The collective evidence indicates that these solids are organic-based analogues of the inorganic martensitic materials. While qualitative explanation of the molecular processes that lead to the related dynamic phenomena can be provided, quantification of their kinematics, estimation of the useful work that can be extracted, and prediction of their occurrence are yet to be established. Harnessing the potential of these materials to rapidly and efficiently perform the fundamentally important process of transduction of heat or light into kinetic energy appears as a prospective basis for their application in motion gears and devices.

Shape-Memory and Self-Healing Effects in Mechanosalient Molecular Crystals.

The thermosalient crystals of terephthalic acid are extraordinarily mechanically compliant and reversibly shape-shift between two forms with different crystal habits. While the transition of form II to form I is spontaneous, the transition of form I to form II is latent and can be triggered by applying local mechanical stress, whereby crystals leap several centimeters in air. This mechanosalient effect (mechanically stimulated motility) is due to sudden release of strain that has accrued in the crystal of form I, which is a metastable structure at ambient conditions. High-speed optical analysis and serial scanning electron microscopy reveal that the mechanical effect is due to rapid reshaping of crystal domains on a millisecond time scale triggered by mechanical stimulation. Mechanically pre-deformed crystals taken over the thermal phase transition exhibit memory effects and partially regain their shape, while cracked, sliced, or otherwise damaged crystals tend to recover their macroscopic integrity by restorative action of intermolecular π-π interactions in a manner which resembles the behavior of shape-memory and self-healing polymers. These observations provide additional evidence that the thermo-/photo-/mechanosalient effects are macroscopic manifestations of martensitic-type transitions in molecular solids.

Synergistic action of thermoresponsive and hygroresponsive elements elicits rapid and directional response of a bilayer actuator.

A bilayer actuator composed of thermoresponsive and thermo/hygroresponsive elements is developed, which undergoes fast, directional and autonomous curling with a speed of up to 0.7 m s(-1) and recovers its shape by hydration. In situ tensile testing of the thermal response of individual layers provided insights into the mechanism of actuation of thermo/hygromorphic bilayers.

Redox Polypharmacology as an Emerging Strategy to Combat Malarial Parasites.

3-Benzylmenadiones are potent antimalarial agents that are thought to act through their 3-benzoylmenadione metabolites as redox cyclers of two essential targets: the NADPH-dependent glutathione reductases (GRs) of Plasmodium-parasitized erythrocytes and methemoglobin. Their physicochemical properties were characterized in a coupled assay using both targets and modeled with QSPR predictive tools built in house. The substitution pattern of the west/east aromatic parts that controls the oxidant character of the electrophore was highlighted and accurately predicted by QSPR models. The effects centered on the benz(o)yl chain, induced by drug bioactivation, markedly influenced the oxidant character of the reduced species through a large anodic shift of the redox potentials that correlated with the redox cycling of both targets in the coupled assay. Our approach demonstrates that the antimalarial activity of 3-benz(o)ylmenadiones results from a subtle interplay between bioactivation, fine-tuned redox properties, and interactions with crucial targets of P. falciparum. Plasmodione and its analogues give emphasis to redox polypharmacology, which constitutes an innovative approach to antimalarial therapy.