Domain-Based Protein Docking with Extremely Large Conformational Changes

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

CG-COA: a coarse-grained cubic orientation approach for systematic protein-protein docking validation.

Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to the limited computational resources, the protein docking approach has been originated and developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations. The rigid docking has successfully predicted structures of various protein complexes, but often failed if the proteins acquire conformational changes or are driven by influences of other factors (e.g. solvent) while interacting. Formulation of the initial rigid docking contains two main stages: (1) searching for all possible surface matches on a rotational and translational sampling space and (2) ranking those possible solutions to distinguish the correct predictions by locating them on the top high ranks. To obtain better results of the protein rigid docking, one can improve it by optimizing the solutions in the search space or by developing more effective ranking methodology to discriminate the correct predictions from the incorrect or false positive ones. However, while development and improvement are reported in the searching stage, it seems to-date that most initial docking algorithms find it difficult or even fail to locate successfully the correct predictions apart from the others in the ranking stage, especially for Antigen/Antibody complexes. To tackle this issue, a new energy-based scoring function is proposed in this research, namely IFACEwat, to re-rank the results of an initial rigid docking algorithm and therefore further improve the discrimination of the near-native structures from the other false positives. Unlike other re-ranking techniques, in which the solvent effect is ignored or implicitly presented, the IFACEwat implements interfacial water into the protein interfaces and explicitly reflects the water influences on the protein interactions. The IFACEwat was implemented based on the interface Atomic Contact Energy (IFACE) of the initial rigid docking algorithm ZDOCK3.0.2 and the derived energies of water-involved interactions at the protein interfaces. The IFACEwat therefore not only takes advantages of shape complementarity from the initial rigid docking algorithm for protein recognitions but also accounts for the water-mediated contacts during the protein associations. Evaluated for various types of protein complexes, the IFACEwat both increases the numbers of the near-native structures and improves their ranks (i.e. most of them ranked at the top-1) as compared to the original rigid docking. In fact, it achieves a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method in F2Dock, it performs equivalently well or better for several Antigen/Antibody complexes. In conclusion, with the inclusion of interfacial water, the IFACEwat improves significantly the results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly accounting the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains the sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near-native structures found.

Many large protein complexes undergo extensive conformational changes as part of their functionality. Tracing these changes is important for understanding the way these proteins function. It is not always possible to obtain a high resolution structure for very large complexes. Electron cryo-microscopy (Cryo-EM) enables the representation of large macromolecular structures at a medium resolution level (4–8A). Traditional conformational search methods cannot be applied to medium resolution data where structural information may be partial or missing. Additionally, simulating large scale conformational changes in proteins require a massive amount of computational efforts. We apply a search method from robotics to structural information obtained from medium resolution Cryo-EM maps, modeled to approximate backbone trace level. The pathways obtained by this method can be useful in understanding protein motions, providing reliable results for the medium resolution data. To provide a baseline validation for our method, we tested it on Adenylate Kinase and Cyanovirin. To test the data on actual cryo-EM determined structures, we simulated the conformational opening of the GroEL single ring complex. We show that we can produce low energy conformational pathways which correspond to known structural data. The method presented here is a promising step towards exploring the conformational motion of even larger complexes.

The motor enzymes that belong to the family of RNA helicases catalyze the strand separation of duplex RNA via ATP hydrolysis. Among these enzymes, Escherichia coli DbpA is a unique RNA helicase because it possesses ATPase-specific activity toward the peptidyl transferase center in 23 S ribosomal RNA. For this reason, it has been the subject of numerous biochemical and structure-function studies. The ATP-stimulated unwinding activity of DbpA toward specific and nonspecific RNA duplexes has been demonstrated. However, the underlying molecular and structural basis, which facilitates its helicase activities, is presently not known. We combined time-dependent limited proteolysis digestion, fluorescence spectroscopy, and three-dimensional structural homology modeling techniques to study the structural conformations of DbpA with respect to its binding to stoichiometric ratios of RNA and cofactors. We show that the conformational state of DbpA is markedly different in the ADP-bound state than in any other state (ATP- or RNA-bound). These results, together with structural homology studies, suggest that a hinge region located in the core domain of DbpA mediates such conformational changes.

The Nucleotide Dependent Mechanism of Get3 as Revealed by Molecular Dynamics Simulations

The motor protein myosin uses energy derived from ATP hydrolysis to produce force and motion. Important conserved components (P-loop, switch I, and switch II) help propagate small conformational changes at the active site into large scale conformational changes in distal regions of the protein. Structural and biochemical studies have indicated that switch I may be directly responsible for the reciprocal opening and closing of the actin and nucleotide-binding pockets during the ATPase cycle, thereby aiding in the coordination of these important substrate-binding sites. Smooth muscle myosin has displayed the ability to simultaneously bind tightly to both actin and ADP, although it is unclear how both substrate-binding clefts could be closed if they are rigidly coupled to switch I. Here we use single tryptophan mutants of smooth muscle myosin to determine how conformational changes in switch I are correlated with structural changes in the nucleotide and actin-binding clefts in the presence of actin and ADP. Our results suggest that a closed switch I conformation in the strongly bound actomyosin-ADP complex is responsible for maintaining tight nucleotide binding despite an open nucleotide-binding pocket. This unique state is likely to be crucial for prolonged tension maintenance in smooth muscle.

SAXS Ensemble Refinement of ESCRT-III CHMP3 Conformational Transitions

Native top-down mass spectrometry (nTDMS) has emerged as a powerful structural biology tool that can localize post-translational modifications (PTMs), explore ligand-binding interactions, and elucidate the three-dimensional structure of proteins and protein complexes in the gas-phase. Fourier-transform ion cyclotron resonance (FTICR) MS offers distinct capabilities for nTDMS, owing to its ultrahigh resolving power, mass accuracy, and robust fragmentation techniques. Previous nTDMS studies using FTICR have mainly been applied to overexpressed recombinant proteins and protein complexes. Here, we report the first nTDMS study that directly analyzes human heart tissue lysate by direct infusion FTICR MS without prior chromatographic separation strategies. We have achieved comprehensive nTDMS characterization of cardiac contractile proteins that play critical roles in heart contraction and relaxation. Specifically, our results reveal structural insights into ventricular myosin light chain 2 (MLC-2v), ventricular myosin light chain 1 (MLC-1v), and alpha-tropomyosin (α-Tpm) in the sarcomere, the basic contractile unit of cardiac muscle. Furthermore, we verified the calcium (Ca2+) binding domain in MLC-2v. In summary, our nTDMS platform extends the application of FTICR MS to directly characterize the structure, PTMs, and metal-binding of endogenous proteins from heart tissue lysate without prior separation methods.

A Riemannian Framework for Tackling Large-Scale Conformational Changes of Proteins using All-ATOM Molecular Dynamics Simulations

Re-Docking Scheme to Explore Docking Search Space by using Interaction Profiles

Nucleic acid–protein interfaces studied by MAS solid-state NMR spectroscopy

Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BPSS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BPSS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BPSS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BPSS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R0) and fluorophore orientation factor (κ2) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET.

Signal recognition particle (SRP) is an RNA and protein complex that exists in all domains of life. It consists of one protein and one noncoding RNA in some bacteria. It is more complex in eukaryotes and consists of six proteins and one noncoding RNA in mammals. In the eukaryotic cytoplasm, SRP co-translationally targets proteins to the endoplasmic reticulum and prevents misfolding and aggregation of the secretory proteins in the cytoplasm. It was demonstrated recently that SRP also possesses an earlier unknown function, the protection of mRNAs of secretory proteins from degradation. In this review, we analyze the progress in studies of SRPs from different organisms, SRP biogenesis, its structure, and function in protein targeting and mRNA protection.

Monoclonal antibodies have recently started to deliver on their promise as highly specific and active drugs; however, a more effective, knowledge-based approach to the selection, design, and optimization of potential therapeutic antibodies is currently limited by the surprising lack of detailed structural information for complexes formed with target proteins. Here we show that complexes formed with minimal antigen binding single chain variable fragments (scFv) reliably reflect all the features of the binding interface present in larger Fab fragments, which are commonly used as therapeutics, and report the development of a robust, reliable, and relatively rapid approach to the determination of high resolution models for scFv-target protein complexes. This NMR spectroscopy-based approach combines experimental determination of the interaction surfaces and relative orientations of the scFv and target protein, with NMR restraint-driven, semiflexible docking of the proteins to produce a reliable and highly informative model of the complex. Experience with scFvs and Fabs targeted at a number of secreted regulatory proteins suggests that the approach will be applicable to many therapeutic antibodies targeted at proteins, and its application is illustrated for a potential therapeutic antibody targeted at the cytokine IL-1beta. The detailed structural information that can be obtained by this approach has the potential to have a major impact on the rational design and development of an increasingly important class of biological pharmaceuticals.