Mechanism of protein-RNA recognition: analysis based on the statistical mechanics of hydration

We investigate the RBD1-r(GUAGU) binding as a case study using all-atom models for the biomolecules, molecular models for water, and the currently most reliable statistical-mechanical method. RBD1 is one of the RNA-binding domains of mammalian Musashi1 (Msi1), and r(GUAGU) contains the minimum recognition sequence for Msi1, r(GUAG). We show that the binding is driven by a large gain of configurational entropy of water in the entire system. It is larger than the sum of conformational-entropy losses for RBD1 and r(GUAGU). The decrease in RBD1-r(GUAGU) interaction energy upon binding is largely cancelled out by the increase in the sum of RBD1-water, r(GUAGU)-water, and water-water interaction energies. We refer to this increase as "energetic dehydration". The decrease is larger than the increase for the van der Waals component, whereas the opposite is true for the electrostatic component. We give a novel reason for the empirically known fact that protein residues possessing side chains with positive charges and with flat moieties frequently appear within protein-RNA binding interfaces. A physical picture of the general protein-RNA binding mechanism is then presented. To achieve a sufficiently large water-entropy gain, shape complementarity at the atomic level needs to be constructed by utilizing the stacking and sandwiching of flat moieties (aromatic rings of the protein and nucleobases of RNA) as fundamental motifs. To compensate for electrostatic energetic dehydration, charge complementarity becomes crucial within the binding interface. We argue the reason why the RNA recognition motif (RRM) is the most ubiquitous RNA binding domain.

Statistical Thermodynamics for Actin-Myosin Binding: The Crucial Importance of Hydration Effects

Actomyosin is an important molecular motor, and the binding of actin and myosin is an essential research target in biophysics. Nevertheless, the physical factors driving or opposing the binding are still unclear. Here, we investigate the role of water in actin-myosin binding using the most reliable statistical-mechanical method currently available for assessing biomolecules immersed in water. This method is characterized as follows: water is treated not as a dielectric continuum but as an ensemble of molecules; the polyatomic structures of proteins are taken into consideration; and the binding free energy is decomposed into physically insightful entropic and energetic components by accounting for the hydration effect to its full extent. We find that the actin-myosin binding brings large gains of electrostatic and Lennard-Jones attractive interactions. However, these gains are accompanied by even larger losses of actin-water and myosin-water electrostatic and LJ attractive interactions. Although roughly half of the energy increase due to the losses is cancelled out by the energy decrease arising from structural reorganization of the water released upon binding, the remaining energy increase is still larger than the energy decrease brought by the gains mentioned above. Hence, the net change in system energy is positive, which opposes binding. Importantly, the binding is driven by a large gain of configurational entropy of water, which surpasses the positive change in system energy and the conformational entropy loss occurring for actin and myosin. The principal physical origin of the large water-entropy gain is as follows: the actin-myosin interface is closely packed with the achievement of high shape complementarity on the atomic level, leading to a large increase in the total volume available to the translational displacement of water molecules in the system and a resultant reduction of water crowding (i.e., entropic correlations among water molecules).

A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces

Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM), for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest) algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set.

Mechanism of One-to-Many Molecular Recognition Accompanying Target-Dependent Structure Formation: For the Tumor Suppressor p53 Protein as an Example

The new type of molecular recognition, in which an intrinsically disordered region (IDR) of a protein binds to many different target proteins with target-dependent structure formation, is indispensable to the expression of life phenomena and also implicated in a number of diseases. According to the prevailing view, the physicochemical factors responsible for the binding are also target dependent. Here we consider an IDR of the tumor suppressor p53 protein, p53CTD, as an important example related to carcinogenesis and analyze its binding to four targets accompanying the formation of target-dependent structures (i.e., helix, sheet, and two different coils) using our statistical-mechanical method combined with molecular models for water. We find that all of the seemingly different binding processes are driven by a large gain of the translational, configurational entropy of water in the system. The gain originates from sufficiently high shape complementarity on the atomic level within the p53CTD-target interface. It is also required that the electrostatic complementarity be ensured as much as possible to compensate for the dehydration. Such complementarities are achieved in harmony with the portion of the target to which p53CTD binds, leading to a large diversity of structures of p53CTD formed upon binding: If they are not achievable, the binding does not occur. This finding is made possible only by calculating the changes in thermodynamic quantities upon binding and decomposing them into physically insightful components.

Anomalously Rapid Hydration Water Diffusion Dynamics Near DNA Surfaces

The emerging Overhauser effect dynamic nuclear polarization (ODNP) technique measures the translational mobility of water within the vicinity (5-15 Å) of preselected sites. The work presented here expands the capabilities of the ODNP technique and illuminates an important, previously unseen, property of the translational diffusion dynamics of water at the surface of DNA duplexes. We attach nitroxide radicals (i.e., spin labels) to multiple phosphate backbone positions of DNA duplexes, allowing ODNP to measure the hydration dynamics at select positions along the DNA surface. With a novel approach to ODNP analysis, we isolate the contributions of water molecules at these sites that undergo free translational diffusion from water molecules that either loosely bind to or exchange protons with the DNA. The results reveal that a significant population of water in a localized volume adjacent to the DNA surface exhibits fast, bulk-like characteristics and moves unusually rapidly compared to water found in similar probe volumes near protein and membrane surfaces. Control studies show that the observation of these characteristics are upheld even when the DNA duplex is tethered to streptavidin or the mobility of the nitroxides is altered. This implies that, as compared to protein or lipid surfaces, it is an intrinsic feature of the DNA duplex surface that it interacts only weakly with a significant fraction of the surface hydration water network. The displacement of this translationally mobile water is energetically less costly than that of more strongly bound water by up to several kBT and thus can lower the activation barrier for interactions involving the DNA surface.

ATP-induced conformational changes of nucleotide-binding domains in an ABC transporter. Importance of the water-mediated entropic force

ATP binding cassette (ABC) proteins belong to a superfamily of active transporters. Recent experimental and computational studies have shown that binding of ATP to the nucleotide binding domains (NBDs) of ABC proteins drives the dimerization of NBDs, which, in turn, causes large conformational changes within the transmembrane domains (TMDs). To elucidate the active substrate transport mechanism of ABC proteins, it is first necessary to understand how the NBD dimerization is driven by ATP binding. In this study, we selected MalKs (NBDs of a maltose transporter) as a representative NBD and calculated the free-energy change upon dimerization using molecular mechanics calculations combined with a statistical thermodynamic theory of liquids, as well as a method to calculate the translational, rotational, and vibrational entropy change. This combined method is applied to a large number of snapshot structures obtained from molecular dynamics simulations containing explicit water molecules. The results suggest that the NBD dimerization proceeds with a large gain of water entropy when ATP molecules bind to the NBDs. The energetic gain arising from direct NBD-NBD interactions is canceled by the dehydration penalty and the configurational-entropy loss. ATP hydrolysis induces a loss of the shape complementarity between the NBDs, which leads to the dissociation of the dimer, due to a decrease in the water-entropy gain and an increase in the configurational-entropy loss. This interpretation of the NBD dimerization mechanism in concert with ATP, especially focused on the water-mediated entropy force, is potentially applicable to a wide variety of the ABC transporters.

Binding of an RNA aptamer and a partial peptide of a prion protein: crucial importance of water entropy in molecular recognition

It is a central issue to elucidate the new type of molecular recognition accompanied by a global structural change of a molecule upon binding to its targets. Here we investigate the driving force for the binding of R12 (a ribonucleic acid aptamer) and P16 (a partial peptide of a prion protein) during which P16 exhibits the global structural change. We calculate changes in thermodynamic quantities upon the R12–P16 binding using a statistical-mechanical approach combined with molecular models for water which is currently best suited to studies on hydration of biomolecules. The binding is driven by a water-entropy gain originating primarily from an increase in the total volume available to the translational displacement of water molecules in the system. The energy decrease due to the gain of R12–P16 attractive (van der Waals and electrostatic) interactions is almost canceled out by the energy increase related to the loss of R12–water and P16–water attractive interactions. We can explain the general experimental result that stacking of flat moieties, hydrogen bonding and molecular-shape and electrostatic complementarities are frequently observed in the complexes. It is argued that the water-entropy gain is largely influenced by the geometric characteristics (overall shapes, sizes and detailed polyatomic structures) of the biomolecules.

Coarse-grained versus atomistic simulations: realistic interaction free energies for real proteins

MOTIVATION

To assess whether two proteins will interact under physiological conditions, information on the interaction free energy is needed. Statistical learning techniques and docking methods for predicting protein-protein interactions cannot quantitatively estimate binding free energies. Full atomistic molecular simulation methods do have this potential, but are completely unfeasible for large-scale applications in terms of computational cost required. Here we investigate whether applying coarse-grained (CG) molecular dynamics simulations is a viable alternative for complexes of known structure.

RESULTS

We calculate the free energy barrier with respect to the bound state based on molecular dynamics simulations using both a full atomistic and a CG force field for the TCR-pMHC complex and the MP1-p14 scaffolding complex. We find that the free energy barriers from the CG simulations are of similar accuracy as those from the full atomistic ones, while achieving a speedup of >500-fold. We also observe that extensive sampling is extremely important to obtain accurate free energy barriers, which is only within reach for the CG models. Finally, we show that the CG model preserves biological relevance of the interactions: (i) we observe a strong correlation between evolutionary likelihood of mutations and the impact on the free energy barrier with respect to the bound state; and (ii) we confirm the dominant role of the interface core in these interactions. Therefore, our results suggest that CG molecular simulations can realistically be used for the accurate prediction of protein-protein interaction strength.

AVAILABILITY AND IMPLEMENTATION

The python analysis framework and data files are available for download at http://www.ibi.vu.nl/downloads/bioinformatics-2013-btt675.tgz.

Structural stability of proteins in aqueous and nonpolar environments

A protein folds into its native structure with the α-helix and∕or β-sheet in aqueous solution under the physiological condition. The relative content of these secondary structures largely varies from protein to protein. However, such structural variability is not exhibited in nonaqueous environment. For example, there is a strong trend that alcohol induces a protein to form α-helices, and many of the membrane proteins within the lipid bilayer consists of α-helices. Here we investigate the structural stability of proteins in aqueous and nonpolar environments using our recently developed free-energy function F = (Λ - TS)∕(k(B)T(0)) = Λ∕(k(B)T(0)) - S∕k(B) (T(0) = 298 K and the absolute temperature T is set at T(0)) which is based on statistical thermodynamics. Λ∕(k(B)T(0)) and S∕k(B) are the energetic and entropic components, respectively, and k(B) is Boltzmann's constant. A smaller value of the positive quantity, -S, represents higher efficiency of the backbone and side-chain packing promoted by the entropic effect arising from the translational displacement of solvent molecules or the CH(2), CH(3), and CH groups which constitute nonpolar chains of lipid molecules. As for Λ, in aqueous solution, a transition to a more compact structure of a protein accompanies the break of protein-solvent hydrogen bonds: As the number of donors and acceptors buried without protein intramolecular hydrogen bonding increases, Λ becomes higher. In nonpolar solvent, lower Λ simply implies more intramolecular hydrogen bonds formed. We find the following. The α-helix and β-sheet are advantageous with respect to -S as well as Λ and to be formed as much as possible. In aqueous solution, the solvent-entropy effect on the structural stability is so strong that the close packing of side chains is dominantly important, and the α-helix and β-sheet contents are judiciously adjusted to accomplish it. In nonpolar solvent, the solvent-entropy effect is substantially weaker than in aqueous solution. Λ is crucial and the α-helix is more stable than the β-sheet in terms of Λ, which develops a tendency that α-helices are exclusively chosen. For a membrane protein, α-helices are stabilized as fundamental structural units for the same reason, but their arrangement is performed through the entropic effect mentioned above.

A new theoretical approach to biological self-assembly

Upon biological self-assembly, the number of accessible translational configurations of water in the system increases considerably, leading to a large gain in water entropy. It is important to calculate the solvation entropy of a biomolecule with a prescribed structure by accounting for the change in water-water correlations caused by solute insertion. Modeling water as a dielectric continuum is not capable of capturing the physical essence of the water entropy effect. As a reliable tool, we propose a hybrid of the angle-dependent integral equation theory combined with a multipolar water model and a morphometric approach. Using our methods wherein the water entropy effect is treated as the key factor, we can elucidate a variety of processes such as protein folding, cold, pressure, and heat denaturating of a protein, molecular recognition, ordered association of proteins such as amyloid fibril formation, and functioning of ATP-driven proteins.

Energetics of oligomeric protein folding and association

In nature, proteins most often exist as complexes, with many of these consisting of identical subunits. Understanding of the energetics governing the folding and misfolding of such homooligomeric proteins is central to understanding their function and misfunction, in disease or biotechnology. Much progress has been made in defining the mechanisms and thermodynamics of homooligomeric protein folding. In this review, we outline models as well as calorimetric and spectroscopic methods for characterizing oligomer folding, and describe extensive results obtained for diverse proteins, ranging from dimers to octamers and higher order aggregates. To our knowledge, this area has not been reviewed comprehensively in years, and the collective progress is impressive. The results provide evolutionary insights into the development of subunit interfaces, mechanisms of oligomer folding, and contributions of oligomerization to protein stability, function and regulation. Thermodynamic analyses have also proven valuable for understanding protein misfolding and aggregation mechanisms, suggesting new therapeutic avenues. Successful recent designs of novel, functional proteins demonstrate increased understanding of oligomer folding. Further rigorous analyses using multiple experimental and computational approaches are still required, however, to achieve consistent and accurate prediction of oligomer folding energetics. Modeling the energetics remains challenging but is a promising avenue for future advances.

Structure of the ultra-high-affinity colicin E2 DNase--Im2 complex

How proteins achieve high-affinity binding to a specific protein partner while simultaneously excluding all others is a major biological problem that has important implications for protein design. We report the crystal structure of the ultra-high-affinity protein-protein complex between the endonuclease domain of colicin E2 and its cognate immunity (Im) protein, Im2 (K(d)∼10(-)(15) M), which, by comparison to previous structural and biophysical data, provides unprecedented insight into how high affinity and selectivity are achieved in this model family of protein complexes. Our study pinpoints the role of structured water molecules in conjoining hotspot residues that govern stability with residues that control selectivity. A key finding is that a single residue, which in a noncognate context massively destabilizes the complex through frustration, does not participate in specificity directly but rather acts as an organizing center for a multitude of specificity interactions across the interface, many of which are water mediated.