Solvated protein–DNA docking using HADDOCK

Interfacial water molecules play an important role in many aspects of protein–DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the docking of protein–DNA complexes and demonstrate its feasibility on a benchmark of 30 high-resolution protein–DNA complexes containing crystallographically-determined water molecules at their interfaces. Our protocol is capable of reproducing the solvation pattern at the interface and recovers hydrogen-bonded water-mediated contacts in many of the benchmark cases. Solvated docking leads to an overall improvement in the quality of the generated protein–DNA models for cases with limited conformational change of the partners upon complex formation. The applicability of this approach is demonstrated on real cases by docking a representative set of 6 complexes using unbound protein coordinates, model-built DNA and knowledge-based restraints. As HADDOCK supports the inclusion of a variety of NMR restraints, solvated docking is also applicable for NMR-based structure calculations of protein–DNA complexes.     

Incorporating replacement free energy of binding‐site waters in molecular docking

Binding‐site water molecules play a crucial role in protein‐ligand recognition, either being displaced upon ligand binding or forming water bridges to stabilize the complex. However, rigorously treating explicit binding‐site waters is challenging in molecular docking, which requires to fully sample ensembles of waters and to consider the free energy cost of replacing waters. Here, we describe a method to incorporate structural and energetic properties of binding‐site waters into molecular docking. We first developed a solvent property analysis (SPA) program to compute the replacement free energies of binding‐site water molecules by post‐processing molecular dynamics trajectories obtained from ligand‐free protein structure simulation in explicit water. Next, we implemented a distance‐dependent scoring term into DOCK scoring function to take account of the water replacement free energy cost upon ligand binding. We assessed this approach in protein targets containing important binding‐site waters, and we demonstrated that our approach is reliable in reproducing the crystal binding geometries of protein‐ligand‐water complexes, as well as moderately improving the ligand docking enrichment performance. In addition, SPA program (free available to academic users upon request) may be applied in identifying hot‐spot binding‐site residues and structure‐based lead optimization. Proteins 2014; 82:1765–1776. © 2014 Wiley Periodicals, Inc.     

Interfacial water as a "hydration fingerprint" in the noncognate complex of BamHI

The molecular code of specific DNA recognition by proteins as a paradigm in molecular biology remains an unsolved puzzle primarily because of the subtle interplay between direct protein-DNA interaction and the indirect contribution from water and ions. Transformation of the nonspecific, low affinity complex to a specific, high affinity complex is accompanied by the release of interfacial water molecules. To provide insight into the conversion from the loose to the tight form, we characterized the structure and energetics of water at the protein-DNA interface of the BamHI complex with a noncognate sequence and in the specific complex. The fully hydrated models were produced with Grand Canonical Monte Carlo simulations. Proximity analysis shows that water distributions exhibit sequence dependent variations in both complexes and, in particular, in the noncognate complex they discriminate between the correct and the star site. Variations in water distributions control the number of water molecules released from a given sequence upon transformation from the loose to the tight complex as well as the local entropy contribution to the binding free energy. We propose that interfacial waters can serve as a "hydration fingerprint" of a given DNA sequence.     

Interaction between bound water molecules and local protein structures: A statistical analysis of the hydrogen bond structures around bound water molecules

Water molecules play an important role in protein folding and protein interactions through their structural association with proteins. Examples of such structural association can be found in protein crystal structures, and can often explain protein functionality in the context of structure. We herein report the systematic analysis of the local structures of proteins interacting with water molecules, and the characterization of their geometric features. We first examined the interaction of water molecules with a large local interaction environment by comparing the preference of water molecules in three regions, namely, the protein–protein interaction (PPI) interfaces, the crystal contact (CC) interfaces, and the non‐interfacial regions. High preference of water molecules to the PPI and CC interfaces was found. In addition, the bound water on the PPI interface was more favorably associated with the complex interaction structure, implying that such water‐mediated structures may participate in the shaping of the PPI interface. The pairwise water‐mediated interaction was then investigated, and the water‐mediated residue–residue interaction potential was derived. Subsequently, the types of polar atoms surrounding the water molecules were analyzed, and the preference of the hydrogen bond acceptor was observed. Furthermore, the geometries of the structures interacting with water were analyzed, and it was found that the major structure on the protein surface exhibited planar geometry rather than tetrahedral geometry. Several previously undiscovered characteristics of water–protein interactions were unfolded in this study, and are expected to lead to a better understanding of protein structure and function. Proteins 2016; 84:43–51. © 2015 Wiley Periodicals, Inc.     

A solvated ligand rotamer approach and its application in computational protein design

The structure-based design of protein–ligand interfaces with respect to different small molecules is of great significance in the discovery of functional proteins. By statistical analysis of a set of protein–ligand complex structures, it was determined that water-mediated hydrogen bonding at the protein–ligand interface plays a crucial role in governing the binding between the protein and the ligand. Based on the novel statistic results, a solvated ligand rotamer approach was developed to explicitly describe the key water molecules at the protein–ligand interface and a water-mediated hydrogen bonding model was applied in the computational protein design context to complement the continuum solvent model. The solvated ligand rotamer approach produces only one additional solvated rotamer for each rotamer in the ligand rotamer library and does not change the number of side-chain rotamers at each protein design site. This has greatly reduced the total combinatorial number in sequence selection for protein design, and the accuracy of the model was confirmed by two tests. For the water placement test, 61 % of the crystal water molecules were predicted correctly in five protein-ligand complex structures. For the sequence recapitulation test, 44.7 % of the amino acid identities were recovered using the solvated ligand rotamer approach and the water-mediated hydrogen bonding model, while only 30.4 % were recovered when the explicitly bound waters were removed. These results indicated that the developed solvated ligand rotamer approach is promising for functional protein design targeting novel protein–ligand interactions.     

Acidic groups docked to well defined wetted pockets at the core of the binding interface: a tale of scoring and missing protein interactions in CAPRI

Some challenging targets in CAPRI (T24/25 and T26) involve binding solvent accessible acidic residues at the core of the binding interface, where they are always found immersed in crystal waters. In fact, Asp and Glu residues are more likely to form part of the hydrogen bond network of their surrounding crystal water molecules than to form a buried salt bridge. Interestingly, many of the crystal waters mediating the intermolecular interactions of the acidic groups are already present in the unbound structure, reinforcing the notion that some water molecules behave as an extension of the protein structure. This is in contrast to acidic groups found in the periphery of the binding interface that form ubiquitous salt bridges that cement the high affinity complex, while at the same time they are exposed to rapidly exchanging water molecules. Because of this, dichotomy implicit solvent scoring functions fail to properly rank these complexes by prioritizing salt bridges rather than water mediated contacts. A detailed analysis of Target 24, for which our group predicted two out of the four successful homology model complex structures, and Target 26 reveal how crystal waters shape the binding cavities of acidic groups prior to binding, in agreement with the theory of anchor residues as mediators of protein recognition.     

Do water molecules mediate protein-DNA recognition?

A comprehensive analysis of interfacial water molecules in the structures of 109 unique protein-DNA complexes is presented together with a new view on their role in protein-DNA recognition. Location of interfacial water molecules as reported in the crystal structures and as emerging from a series of molecular dynamics studies on protein-DNA complexes with explicit solvent and counterions, was analyzed based on their acceptor, donor hydrogen bond relationships with the atoms and residues of the macromolecules, electrostatic field calculations and packing density considerations. Water molecules for the purpose of this study have been categorized into four classes: viz. (I) those that contact both the protein and the DNA simultaneously and thus mediate recognition directly; (II) those that contact either the protein or the DNA exclusively via hydrogen bonds solvating each solute separately; (III) those that contact the hydrophobic groups in either the protein or the DNA; and, lastly (IV) those that contact another water molecule. Of the 17,963 crystallographic water molecules under examination, about 6% belong to class I and 76% belong to class II. About three-fourths of class I and class II water molecules are exclusively associated with hydrogen bond acceptor atoms of both protein and DNA. Noting that DNA is polyanionic, it is significant that a majority of the crystallographically observed water molecules as well as those from molecular dynamics simulations should be involved in facilitating binding by screening unfavorable electrostatics. Less than 2% of the reported water molecules occur between hydrogen bond donor atoms of protein and acceptor atoms of DNA. These represent cases where protein atoms cannot reach out to DNA to make favorable hydrogen bond interactions due to packing/structural restrictions and interfacial water molecules provide an extension to side-chains to accomplish hydrogen bonding.     

The role of residue 50 and hydration water molecules in homeodomain DNA recognition

We conducted molecular dynamics simulations on several wild-type and mutant homeodomain-DNA complexes to investigate the role of residue 50 in homeodomain-DNA interaction and the behavior of interfacial hydration water. Our results suggest that this residue interacts more favorably with its consensus sequence and thus plays a considerable role in DNA recognition. However, residue 50 was not responsible for DNA recognition alone. Other residues in the vicinity could interact with residue 50 in cooperation upon DNA binding. We also found the lifetime for some water in the protein-DNA interface can be as high as nanoseconds and that a few well-conserved sites for water-mediated hydrogen bonds from protein to DNA are occupied by high-mobility hydrating waters.     

Intuitive,but not simple: Including explicit water molecules in protein–protein docking simulations improves model quality

Characterizing the nature of interaction between proteins that have not been experimentally cocrystallized requires a computational docking approach that can successfully predict the spatial conformation adopted in the complex. In this work, the Hydropathic INTeractions (HINT) force field model was used for scoring docked models in a data set of 30 high‐resolution crystallographically characterized “dry” protein–protein complexes and was shown to reliably identify native‐like models. However, most current protein–protein docking algorithms fail to explicitly account for water molecules involved in bridging interactions that mediate and stabilize the association of the protein partners, so we used HINT to illuminate the physical and chemical properties of bridging waters and account for their energetic stabilizing contributions. The HINT water Relevance metric identified the “truly” bridging waters at the 30 protein–protein interfaces and we utilized them in “solvated” docking by manually inserting them into the input files for the rigid body ZDOCK program. By accounting for these interfacial waters, a statistically significant improvement of ～24% in the average hit‐count within the top‐10 predictions the protein–protein dataset was seen, compared to standard “dry” docking. The results also show scoring improvement, with medium and high accuracy models ranking much better than incorrect ones. These improvements can be attributed to the physical presence of water molecules that alter surface properties and better represent native shape and hydropathic complementarity between interacting partners, with concomitantly more accurate native‐like structure predictions. Proteins 2014; 82:916–932. © 2013 Wiley Periodicals, Inc.     

Structural Determinants of Yeast Protein-Protein Interaction Interface Evolution at the Residue Level

Interfaces of contact between proteins play important roles in determining the proper structure and function of protein–protein interactions (PPIs). Therefore, to fully understand PPIs, we need to better understand the evolutionary design principles of PPI interfaces. Previous studies have uncovered that interfacial sites are more evolutionarily conserved than other surface protein sites. Yet, little is known about the nature and relative importance of evolutionary constraints in PPI interfaces. Here, we explore constraints imposed by the structure of the microenvironment surrounding interfacial residues on residue evolutionary rate using a large dataset of over 700 structural models of baker’s yeast PPIs. We find that interfacial residues are, on average, systematically more conserved than all other residues with a similar degree of total burial as measured by relative solvent accessibility (RSA). Besides, we find that RSA of the residue when the PPI is formed is a better predictor of interfacial residue evolutionary rate than RSA in the monomer state. Furthermore, we investigate four structure-based measures of residue interfacial involvement, including change in RSA upon binding (ΔRSA), number of residue-residue contacts across the interface, and distance from the center or the periphery of the interface. Integrated modeling for evolutionary rate prediction in interfaces shows that ΔRSA plays a dominant role among the four measures of interfacial involvement, with minor, but independent contributions from other measures. These results yield insight into the evolutionary design of interfaces, improving our understanding of the role that structure plays in the molecular evolution of PPIs at the residue level.     

Hydration of protein–RNA recognition sites

We investigate the role of water molecules in 89 protein–RNA complexes taken from the Protein Data Bank. Those with tRNA and single-stranded RNA are less hydrated than with duplex or ribosomal proteins. Protein–RNA interfaces are hydrated less than protein–DNA interfaces, but more than protein–protein interfaces. Majority of the waters at protein–RNA interfaces makes multiple H-bonds; however, a fraction do not make any. Those making H-bonds have preferences for the polar groups of RNA than its partner protein. The spatial distribution of waters makes interfaces with ribosomal proteins and single-stranded RNA relatively ‘dry’ than interfaces with tRNA and duplex RNA. In contrast to protein–DNA interfaces, mainly due to the presence of the 2′OH, the ribose in protein–RNA interfaces is hydrated more than the phosphate or the bases. The minor groove in protein–RNA interfaces is hydrated more than the major groove, while in protein–DNA interfaces it is reverse. The strands make the highest number of water-mediated H-bonds per unit interface area followed by the helices and the non-regular structures. The preserved waters at protein–RNA interfaces make higher number of H-bonds than the other waters. Preserved waters contribute toward the affinity in protein–RNA recognition and should be carefully treated while engineering protein–RNA interfaces.     

Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism

pH is a ubiquitous regulator of biological activity, including protein‐folding, protein‐protein interactions, and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH‐dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi‐site λ‐dynamics (CPHMD^MSλD). In the CPHMD^MSλD framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi‐site λ‐dynamics, and designed novel biasing potentials to ensure that the physical end‐states are predominantly sampled. We show that explicit solvent CPHMD^MSλD simulations model realistic pH‐dependent properties of proteins such as the Hen‐Egg White Lysozyme (HEWL), binding domain of 2‐oxoglutarate dehydrogenase (BBL) and N‐terminal domain of ribosomal protein L9 (NTL9), and the pK_a predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 pK_a units. With the recent development of the explicit solvent CPHMD^MSλD framework for nucleic acids, accurate modeling of pH‐dependent properties of both major class of biomolecules—proteins and nucleic acids is now possible. Proteins 2014; 82:1319–1331. © 2013 Wiley Periodicals, Inc.     

Analysis of solvent structure in proteins using neutron D2O-H2O solvent maps: pattern of primary and secondary hydration of trypsin.

A method of determining the water structure in protein crystals is described using neutron solvent difference maps. These maps are obtained by comparing the changes in diffracted intensities between two data sets, one in which H2O is the major solvent constituent, and a second in which D2O is the solvent medium. To a good first approximation, the protein atom contributions to the scattering intensities in both data sets are equal and cancel, but since H2O and D2O have very different neutron-scattering properties, their differences are accentuated to reveal an accurate representation of the solvent structure. The method also employs a series of density modification steps that impose known physical constraints on the density distribution function in the unit cell by making real space modifications directly to the density maps. Important attributes of the method are that (1) it is less subjective in the assignment of water positions than X-ray analysis; (2) there is threefold improvement in the signal-to-noise ratio for the solvent density; and (3) the iterative density modification produces a low-biased representation of the solvent density. Tests showed that water molecules with as low as 10% occupancy could be confidently assigned. About 300 water sites were assigned for trypsin from the refined solvent density; 140 of these sites were defined in the maps as discrete peaks, while the remaining were found within less-ordered channels of density. There is a very good correspondence between the sites in the primary hydration layer and waters found in the X-ray structure. Most water sites are clustered into H-bonding networks, many of which are found along intermolecular contact zones. The bound water is equally distributed between contacting apolar and polar atoms at the protein interface. A common occurrence at hydrophobic surfaces is that apolar atoms are circumvented by one or more waters that are part of a larger water network. When the effects on surface accessibility by neighboring molecules in the crystal lattice are taken into consideration, only about 29% of the surface does not interface ordered water. About 25% of the ordered water is found in the second hydration sphere. In many instances these waters bridge larger clusters of primary layer waters. It is apparent that, in certain regions of the crystal, the organization of ordered water reflects the characteristics of the crystal environment more than those of trypsin's surface alone.     

Conservation of water molecules in an antibody–antigen interaction

The solvation of the antibody–antigen Fv D1.3–lysozyme complex is investigated through a study of the conservation of water molecules in crystal structures of the wild-type Fv fragment of antibody D1.3, 5 free lysozyme, the wild-type Fv D1.3–lysozyme complex, 5 Fv D1.3 mutants complexed with lysozyme and the crystal structure of an idiotope (Fv D1.3)-abti-idiotope (Fv E5.2) complex. In all, there are 99 water molecules common to the wild-type and mutant antibody–lysozyme complexes. The antibody–lysozyme interface includes 25 well-ordered solvent molecules, conserved among the wild-type and mutant Fv D1.3–lysozyme complexes, which are bound directly or through other water molecules to both antibody and antigen. In addition to contributing hydrogen bonds to the antibody–antigen interaction the solvent molecules fill many interface cavities. Comparison with x-ray crystal structures of free Fv D1.3 and free lysozyme shows that 20 of these conserved interface waters in the complex were bound to one of the free proteins. Uo to 23 additional water molecules are also found in the antibody–antigen interface, however these waters do no bridge antibody and antigen and their temperature factors are much higher than those of the 25 well-ordered waters. Fifteen water molecules are displaced to form the complex, some of which are substituted by hydrophilic protein atoms, and 5 water molecules are added at the antibody–antigen interface with the formation of the complex. While the current crystal models of the D1.3–lysozyme complex do not demonstrate the increase in bound waters found in a physico-chemical study of the interaction at decreased water activities, the 25 well-ordered interface water contribute a net gain of 10 hydrogen bonds to complex stability.     

Modeling implicit reorganization in continuum descriptions of protein-protein interactions

The determination of free energies that govern protein-protein recognition is essential for a detailed molecular understanding of biological specificity. Continuum models of macromolecular interactions, in which the solvent is treated by an implicit representation and the proteins are treated semi-microscopically, are computationally tractable for estimating free energies, yet many questions remain concerning their accuracy. This article reports a continuum analysis of the free-energy changes underlying the binding of 31 interfacial alanine substitutions of two complexes of the antihen egg white lysozyme (HEL) antibody D1.3 bound with HEL or the antibody E5.2. Two implicit schemes for modeling the effects of protein and solvent relaxation were examined, in which the protein environment was treated as either homogeneous with a "protein dielectric constant" of epsilon(p) = 4 or inhomogeneous, with epsilon(p) = 4 for neutral residues and epsilon(p) = 25 for ionized residues. The results showed that the nonuniform dielectric model reproduced the experimental differences better, with an average absolute error of +/-1.1 kcal/mol, compared with +/-1.4 kcal/mol for the uniform model. More importantly, the error for charged residues in the nonuniform model is +/-0.8 kcal/mol and is nearly half of that corresponding to the uniform model. Several substitutions were clearly problematic in determining qualitative trends and probably required explicit structural reorganization at the protein-protein interface.     

Weak conservation of structural features in the interfaces of homologous transient protein–protein complexes

Residue types at the interface of protein–protein complexes (PPCs) are known to be reasonably well conserved. However, we show, using a dataset of known 3‐D structures of homologous transient PPCs, that the 3‐D location of interfacial residues and their interaction patterns are only moderately and poorly conserved, respectively. Another surprising observation is that a residue at the interface that is conserved is not necessarily in the interface in the homolog. Such differences in homologous complexes are manifested by substitution of the residues that are spatially proximal to the conserved residue and structural differences at the interfaces as well as differences in spatial orientations of the interacting proteins. Conservation of interface location and the interaction pattern at the core of the interfaces is higher than at the periphery of the interface patch. Extents of variability of various structural features reported here for homologous transient PPCs are higher than the variation in homologous permanent homomers. Our findings suggest that straightforward extrapolation of interfacial nature and inter‐residue interaction patterns from template to target could lead to serious errors in the modeled complex structure. Understanding the evolution of interfaces provides insights to improve comparative modeling of PPC structures.