Water Molecules In Binding Sites Research Articles

Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features.

Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it is difficult to identify the conserved water molecules (CWMs) from free water molecules (FWMs) directly as CWMs are normally deeply embedded in proteins and form strong hydrogen bonds with surrounding polar groups. To circumvent this difficulty, in this work, the abundance of spatial structure information and physicochemical properties of water molecules in proteins inspires us to adopt machine learning methods for identifying the CWMs. Therefore, in this study, a machine learning framework to identify the CWMs in the binding sites of the proteins was presented. First, by analyzing water molecules' physicochemical properties and spatial structure information, six features (i.e., atom density, hydrophilicity, hydrophobicity, solvent-accessible surface area, temperature B-factors, and mobility) were extracted. Those features were further analyzed and combined to reach a higher CWM identification rate. As a result, an optimal feature combination was determined. Based on this optimal combination, seven different machine learning models (including support vector machine (SVM), K-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), discriminant analysis (DA), naïve Bayes (NB), and ensemble learning (EL)) were evaluated for their abilities in identifying two categories of water molecules, i.e., CWMs and FWMs. It showed that the EL model was the desired prediction model due to its comprehensive advantages. Furthermore, the presented methodology was validated through a case study of crystal 3skh and extensively compared with Dowser++. The prediction performance showed that the optimal feature combination and the desired EL model in our method could achieve satisfactory prediction accuracy in identifying CWMs from FWMs in the proteins' binding sites.

Potency-Enhancing Mutations of Gating Modifier Toxins for the Voltage-Gated Sodium Channel NaV1.7 Can Be Predicted Using Accurate Free-Energy Calculations.

Gating modifier toxins (GMTs) isolated from venomous organisms such as Protoxin-II (ProTx-II) and Huwentoxin-IV (HwTx-IV) that inhibit the voltage-gated sodium channel NaV1.7 by binding to its voltage-sensing domain II (VSDII) have been extensively investigated as non-opioid analgesics. However, reliably predicting how a mutation to a GMT will affect its potency for NaV1.7 has been challenging. Here, we hypothesize that structure-based computational methods can be used to predict such changes. We employ free-energy perturbation (FEP), a physics-based simulation method for predicting the relative binding free energy (RBFE) between molecules, and the cryo electron microscopy (cryo-EM) structures of ProTx-II and HwTx-IV bound to VSDII of NaV1.7 to re-predict the relative potencies of forty-seven point mutants of these GMTs for NaV1.7. First, FEP predicted these relative potencies with an overall root mean square error (RMSE) of 1.0 ± 0.1 kcal/mol and an R2 value of 0.66, equivalent to experimental uncertainty and an improvement over the widely used molecular-mechanics/generalized born-surface area (MM-GB/SA) RBFE method that had an RMSE of 3.9 ± 0.8 kcal/mol. Second, inclusion of an explicit membrane model was needed for the GMTs to maintain stable binding poses during the FEP simulations. Third, MM-GB/SA and FEP were used to identify fifteen non-standard tryptophan mutants at ProTx-II[W24] predicted in silico to have a at least a 1 kcal/mol gain in potency. These predicted potency gains are likely due to the displacement of high-energy waters as identified by the WaterMap algorithm for calculating the positions and thermodynamic properties of water molecules in protein binding sites. Our results expand the domain of applicability of FEP and set the stage for its prospective use in biologics drug discovery programs involving GMTs and NaV1.7.

Water Thermodynamics of Peptide Toxin Binding Sites on Ion Channels.

Peptide toxins isolated from venomous creatures, long prized as research tools due to their innate potency for ion channels, are emerging as drugs as well. However, it remains challenging to understand why peptide toxins bind with high potency to ion channels, to identify residues that are key for activity, and to improve their affinities via mutagenesis. We use WaterMap, a molecular dynamics simulation-based method, to gain computational insight into these three questions by calculating the locations and thermodynamic properties of water molecules in the peptide toxin binding sites of five ion channels. These include an acid-sensing ion channel, voltage-gated potassium channel, sodium channel in activated and deactivated states, transient-receptor potential channel, and a nicotinic receptor whose structures were recently determined by crystallography and cryo-electron microscopy (cryo-EM). All channels had water sites in the peptide toxin binding site, and an average of 75% of these sites were stable (low-energy), and 25% were unstable (medium or high energy). For the sodium channel, more unstable water sites were present in the deactivated state structure than the activated. Additionally, for each channel, unstable water sites coincided with the positions of peptide toxin residues that previous mutagenesis experiments had shown were important for activity. Finally, for the sodium channel in the deactivated state, unstable water sites were present in the peptide toxin binding pocket but did not overlap with the peptide toxin, suggesting that future experimental efforts could focus on targeting these sites to optimize potency.

ProteinsPlus: interactive analysis of protein-ligand binding interfaces.

Due to the increasing amount of publicly available protein structures searching, enriching and investigating these data still poses a challenging task. The ProteinsPlus web service (https://proteins.plus) offers a broad range of tools addressing these challenges. The web interface to the tool collection focusing on protein–ligand interactions has been geared towards easy and intuitive access to a large variety of functionality for life scientists. Since our last publication, the ProteinsPlus web service has been extended by additional services as well as it has undergone substantial infrastructural improvements. A keyword search functionality was added on the start page of ProteinsPlus enabling users to work on structures without knowing their PDB code. The tool collection has been augmented by three tools: StructureProfiler validates ligands and active sites using selection criteria of well-established protein–ligand benchmark data sets, WarPP places water molecules in the ligand binding sites of a protein, and METALizer calculates, predicts and scores coordination geometries of metal ions based on surrounding complex atoms. Additionally, all tools provided by ProteinsPlus are available through a REST service enabling the automated integration in structure processing and modeling pipelines.

Insights from molecular dynamics simulation of human ceruloplasmin (ferroxidase enzyme) binding with biogenic monoamines.

Human ceruloplasmin (hCP) is a multi-copper oxidase with ferroxidase and amine oxidase activities. Molecular dynamics simulation (MDS) and docking analysis of biogenic monoamines with ceruloplasmin explain the role of Asp1025, Glu935, Glu272, Glu232 and Glu230 together with the binding site water molecules (referred as conserved water molecules) in the stabilization of neurotransmitter (Serotonin, Norepinephrine and Epinephrine) molecules within the binding cavity of hCP. Conserved water molecules are found at specific positions interacting with the protein structures that have sequence similarity. The ethylamine side chain nitrogen atom (N1) of neurotransmitter molecules interacts with water molecules in the binding cavity formed by Asp1025, Glu935 and Glu232 residues. These residues form an acidic triad mimicking a substrate binding cavity. The hydroxyl groups attached to the catechol ring of epinephrine and norepinephrine have been stabilized by Asp230 and Asp232 residues. Data suggests that the recognition of biogenic amines mediates through the N+(amine) ...Asp1025-His1026-CuCis-His path. The potential recognition path of biogenic monoamines to trinuclear copper cluster supported by active site water molecules (referred as conserved water molecules) is described in this report.

Effect of set up protocols on the accuracy of alchemical free energy calculation over a set of ACK1 inhibitors.

Hit-to-lead virtual screening frequently relies on a cascade of computational methods that starts with rapid calculations applied to a large number of compounds and ends with more expensive computations restricted to a subset of compounds that passed initial filters. This work focuses on set up protocols for alchemical free energy (AFE) scoring in the context of a Docking–MM/PBSA–AFE cascade. A dataset of 15 congeneric inhibitors of the ACK1 protein was used to evaluate the performance of AFE set up protocols that varied in the steps taken to prepare input files (using previously docked and best scored poses, manual selection of poses, manual placement of binding site water molecules). The main finding is that use of knowledge derived from X-ray structures to model binding modes, together with the manual placement of a bridging water molecule, improves the R2 from 0.45 ± 0.06 to 0.76 ± 0.02 and decreases the mean unsigned error from 2.11 ± 0.08 to 1.24 ± 0.04 kcal mol-1. By contrast a brute force automated protocol that increased the sampling time ten-fold lead to little improvements in accuracy. Besides, it is shown that for the present dataset hysteresis can be used to flag poses that need further attention even without prior knowledge of experimental binding affinities.

Assessing the Predictive Power of Relative Binding Free Energy Calculations for Test Cases Involving Displacement of Binding Site Water Molecules.

Improved sampling methodologies, more accurate force fields, and access to longer simulation time scales have led to an increased application of Relative Binding Free Energy (RBFE) calculations in drug discovery projects. In order to assess the strengths and limitations of such tools, adequate benchmark sets are required that challenge the methodology in certain well-defined aspects. We applied Free Energy Perturbation (FEP) calculations to six congeneric ligand pairs taken from the literature, in which addition of a functional group resulted in the displacement of buried binding site water molecules and compared the calculated relative binding free energies with the experimental ones. We started the perturbations from different initial solvation states and registered large inconsistencies (large hysteresis) between the calculated values. We furthermore applied a Grand Canonical Monte Carlo (GCMC) solvent sampling step prior to the FEP calculation that led to a smaller hysteresis for the simulations. By applying a hydration site analysis to the trajectories of the end-states of the perturbation, we could point out that the low accuracy of the predictions as well as the high dependence of the prediction on the chosen initial state is likely caused by the trapping of binding site water molecules and/or insufficient solvation of buried cavities that are formed upon completion of the perturbation. This work highlights that RBFE calculations can suffer from slow solvent exchange of buried parts of the binding sites with the bulk.

Efficient and Accurate Hydration Site Profiling for Enclosed Binding Sites.

Molecular dynamics (MD) simulations allow for accurate prediction of the thermodynamic profile of binding-site water molecules critical for protein-ligand association. Whereas this hydration-site profiling converges rapidly for solvent-exposed sites independent of the initial water placement, an accurate and reliable placement is required for water molecules in occluded binding sites. Here, we present an accurate and efficient hydration-site prediction method for occluded binding sites combining water placement based on 3D-RISM and MD simulations using WATsite.

Multi-Body Interactions in Molecular Docking Program Devised with Key Water Molecules in Protein Binding Sites.

Water molecules play an important role in modeling protein-ligand interactions. However, traditional molecular docking methods often ignore the impact of the water molecules by removing them without any analysis or keeping them as a static part of the proteins or the ligands. Hence, the accuracy of the docking simulations will inevitably be damaged. Here, we introduce a multi-body docking program which incorporates the fixed or the variable number of the key water molecules in protein-ligand docking simulations. The program employed NSGA II, a multi-objective optimization algorithm, to identify the binding poses of the ligand and the key water molecules for a protein. To this end, a force-field-based hydration-specific scoring function was designed to favor estimate the binding affinity considering the key water molecules. The program was evaluated in aspects of the docking accuracy, cross-docking accuracy, and screening efficiency. When the numbers of the key water molecules were treated as fixed-length optimization variables, the docking accuracy of the multi-body docking program achieved a success rate of 80.58% for the best RMSD values for the recruit of the ligands smaller than 2.0 Å. The cross-docking accuracy was investigated on the presence and absence of the key water molecules by four protein targets. The screening efficiency was assessed against those protein targets. Results indicated that the proposed multi-body docking program was with good performance compared with the other programs. On the other side, when the numbers of the key water molecules were treated as variable-length optimization variables, the program obtained comparative performance under the same three evaluation criterions. These results indicated that the multi-body docking with the variable numbers of the water molecules was also efficient. Above all, the multi-body docking program developed in this study was capable of dealing with the problem of the water molecules that explicitly participating in protein-ligand binding.

Thermodynamic Insight into the Effects of Water Displacement and Rearrangement upon Ligand Modifications using Molecular Dynamics Simulations.

Computational methods, namely molecular dynamics (MD) simulations in combination with inhomogeneous fluid solvation theory (IFST) were used to retrospectively investigate various cases of ligand structure modifications that led to the displacement of binding site water molecules. Our findings are that water displacement per se is energetically unfavorable in the discussed examples, and that it is merely the fine balance between change in protein-ligand interaction energy, ligand solvation free energies, and binding site solvation free energies that determine if water displacement is favorable or not. We furthermore evaluated if we can reproduce experimental binding affinities by a computational approach combining changes in solvation free energies with changes in protein-ligand interaction energies and entropies. In two of the seven cases, this estimation led to large errors, implying that accurate predictions of relative binding free energies based on solvent thermodynamics is challenging. Nevertheless, MD simulations can provide insight regarding which water molecules can be targeted for displacement.

Multispecific Substrate Recognition in a Proton-Dependent Oligopeptide Transporter

SummaryProton-dependent oligopeptide transporters (POTs) are important for uptake of dietary di- and tripeptides in many organisms, and in humans are also involved in drug absorption. These transporters accept a wide range of substrates, but the structural basis for how different peptide side chains are accommodated has so far remained obscure. Twenty-eight peptides were screened for binding to PepTSt from Streptococcus thermophilus, and structures were determined of PepTSt in complex with four physicochemically diverse dipeptides, which bind with millimolar affinity: Ala-Leu, Phe-Ala, Ala-Gln, and Asp-Glu. The structures show that PepTSt can adapt to different peptide side chains through movement of binding site residues and water molecules, and that a good fit can be further aided by adjustment of the position of the peptide itself. Finally, structures were also determined in complex with adventitiously bound HEPES, polyethylene glycol, and phosphate molecules, which further underline the adaptability of the binding site.

Prediction of Ordered Water Molecules in Protein Binding Sites from Molecular Dynamics Simulations: The Impact of Ligand Binding on Hydration Networks.

Water plays a major role in ligand binding and is attracting increasing attention in structure-based drug design. Water molecules can make large contributions to binding affinity by bridging protein–ligand interactions or by being displaced upon complex formation, but these phenomena are challenging to model at the molecular level. Herein, networks of ordered water molecules in protein binding sites were analyzed by clustering of molecular dynamics (MD) simulation trajectories. Locations of ordered waters (hydration sites) were first identified from simulations of high resolution crystal structures of 13 protein–ligand complexes. The MD-derived hydration sites reproduced 73% of the binding site water molecules observed in the crystal structures. If the simulations were repeated without the cocrystallized ligands, a majority (58%) of the crystal waters in the binding sites were still predicted. In addition, comparison of the hydration sites obtained from simulations carried out in the absence of ligands to those identified for the complexes revealed that the networks of ordered water molecules were preserved to a large extent, suggesting that the locations of waters in a protein–ligand interface are mainly dictated by the protein. Analysis of >1000 crystal structures showed that hydration sites bridged protein–ligand interactions in complexes with different ligands, and those with high MD-derived occupancies were more likely to correspond to experimentally observed ordered water molecules. The results demonstrate that ordered water molecules relevant for modeling of protein–ligand complexes can be identified from MD simulations. Our findings could contribute to development of improved methods for structure-based virtual screening and lead optimization.

WATsite2.0 with PyMOL Plugin: Hydration Site Prediction and Visualization.

Water molecules in the binding site of a protein significantly influence protein structure and function, for example, by mediating protein-ligand interactions or due to water displacement as driving force for ligand binding. The knowledge about location and thermodynamic contributions of binding site water molecules is crucial for understanding protein function. WATsite is a hydration site analysis program that was developed together with an easy-to-use graphical user interface (GUI) based on PyMOL. WATsite identifies hydration sites from a molecular dynamics (MD) simulation trajectory with four different types of explicit water molecules. Hydration sites can be identified with or without the presence of a bound ligand dependent on the scientific problem. The protein desolvation free energy can be estimated for any ligand by summation of the hydration site free energies of the displaced hydration sites. The location and thermodynamic profile of hydration sites mediating the protein-ligand interactions is important for understanding protein-ligand binding. The WATsite program and GUI are available free of charge from http://people.pharmacy.purdue.edu/~mlill/software/watsite/version2.shtml .

Theoretical analysis of the binding of potential inhibitors to protein kinases MK2 and MK3.

MK2 (or MAPKAPK2) was already known for its role in the inflammatory response, however recent studies indicate the involvement of this protein kinase in the DNA damage response mechanism. Within its kinase family the enzyme MK3 shows the highest identity with MK2. Here we report a theoretical study on the binding of two molecules, 05B and P4O, to the proteins MK2 and MK3. The data here obtained may shed light on the contribution of individual residues and binding site water molecules for the binding of potential inhibitors to these two kinases.

The importance of hydration thermodynamics in fragment-to-lead optimization.

Using a computational approach to assess changes in solvation thermodynamics upon ligand binding, we investigated the effects of water molecules on the binding energetics of over 20 fragment hits and their corresponding optimized lead compounds. Binding activity and X-ray crystallographic data of published fragment-to-lead optimization studies from various therapeutically relevant targets were studied. The analysis reveals a distinct difference between the thermodynamic profile of water molecules displaced by fragment hits and those displaced by the corresponding optimized lead compounds. Specifically, fragment hits tend to displace water molecules with notably unfavorable excess entropies-configurationally constrained water molecules-relative to those displaced by the newly added moieties of the lead compound during the course of fragment-to-lead optimization. Herein we describe the details of this analysis with the goal of providing practical guidelines for exploiting thermodynamic signatures of binding site water molecules in the context of fragment-to-lead optimization.

Effect of explicit water molecules on ligand-binding affinities calculated with the MM/GBSA approach.

We tested different approaches to including the effect of binding-site water molecules for ligand-binding affinities within the MM/GBSA approach (molecular mechanics combined with generalised Born and surface-area solvation). As a test case, we studied the binding of nine phenol analogues to ferritin. The effect of water molecules mediating the interaction between the receptor and the ligand can be studied by considering a few water molecules as a part of the receptor. We extended previous methods by allowing for a variable number of water molecules in the binding site. The effect of displaced water molecules can also be considered within the MM/GBSA philosophy by calculating the affinities of binding-site water molecules, both before and after binding of the ligand. To obtain proper energies, both the water molecules and the ligand need then to be converted to non-interacting ghost molecules and a single-average approach (i.e., the same structures are used for bound and unbound states) based on the simulations of both the complex and the free receptor can be used to improve the precision. The only problem is to estimate the free energy of an unbound water molecule. With an experimental estimate of this parameter, promising results were obtained for our test case.

Impact of binding site waters on inhibitor design: contemplating a novel inverse binding mode of indirubin derivatives in DYRK kinases

DYRK kinases are involved in alternative pre-mRNA splicing as well as in neuropathological states such as Alzheimer's disease and Down syndrome. In this study, we present the design, synthesis, and biological evaluation of indirubins as DYRK inhibitors with enhanced selectivity. Modifications of the bis-indole included polar or acidic functionalities at positions 5′ and 6′ and a bromine or a trifluoromethyl group at position 7, affording analogues that possess high activity and pronounced specificity. Compound 6i carrying a 5′- carboxylate moiety demonstrated the best inhibitory profile. A novel inverse binding mode, which forms the basis for the improved selectivity, was suggested by molecular modeling and confirmed by determining the crystal structure of DYRK2 in complex with 6i. Structure–activity relationships were further established, including a thermodynamic analysis of binding site water molecules, offering a structural explanation for the selective DYRK inhibition [1].

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.

PLIC: protein–ligand interaction clusters

Most of the biological processes are governed through specific protein–ligand interactions. Discerning different components that contribute toward a favorable protein– ligand interaction could contribute significantly toward better understanding protein function, rationalizing drug design and obtaining design principles for protein engineering. The Protein Data Bank (PDB) currently hosts the structure of ∼68 000 protein–ligand complexes. Although several databases exist that classify proteins according to sequence and structure, a mere handful of them annotate and classify protein–ligand interactions and provide information on different attributes of molecular recognition. In this study, an exhaustive comparison of all the biologically relevant ligand-binding sites (84 846 sites) has been conducted using PocketMatch: a rapid, parallel, in-house algorithm. PocketMatch quantifies the similarity between binding sites based on structural descriptors and residue attributes. A similarity network was constructed using binding sites whose PocketMatch scores exceeded a high similarity threshold (0.80). The binding site similarity network was clustered into discrete sets of similar sites using the Markov clustering (MCL) algorithm. Furthermore, various computational tools have been used to study different attributes of interactions within the individual clusters. The attributes can be roughly divided into (i) binding site characteristics including pocket shape, nature of residues and interaction profiles with different kinds of atomic probes, (ii) atomic contacts consisting of various types of polar, hydrophobic and aromatic contacts along with binding site water molecules that could play crucial roles in protein–ligand interactions and (iii) binding energetics involved in interactions derived from scoring functions developed for docking. For each ligand-binding site in each protein in the PDB, site similarity information, clusters they belong to and description of site attributes are provided as a relational database—protein–ligand interaction clusters (PLIC).Database URL: http://proline.biochem.iisc.ernet.in/PLIC

Analysis and Assay of Oseltamivir-Resistant Mutants of Influenza Neuraminidase via Direct Observation of Drug Unbinding and Rebinding in Simulation

The emergence of influenza drug resistance is a major public health concern. The molecular basis of resistance to oseltamivir (Tamiflu) is investigated using a computational assay involving multiple 500 ns unrestrained molecular dynamics (MD) simulations of oseltamivir complexed with mutants of H1N1-2009 influenza neuraminidase. The simulations, accelerated using graphics processors (GPUs), and using a fully explicit model of water, are of sufficient length to observe multiple drug unbinding and rebinding events. Drug unbinding occurs during simulations of known oseltamivir-resistant mutants of neuraminidase. Molecular-level rationalizations of drug resistance are revealed by analysis of these unbinding trajectories, with particular emphasis on the dynamics of the mutant residues. The results indicate that MD simulations can predict weakening of binding associated with drug resistance. In addition, visualization and analysis of binding site water molecules reveal their importance in stabilizing the binding mode of the drug. Drug unbinding is accompanied by conformational changes, driven by the mutant residues, which results in flooding of a key pocket containing tightly bound water molecules. This displaces oseltamivir, allowing the tightly bound water molecules to be released into bulk. In addition to the role of water, analysis of the trajectories reveals novel behavior of the structurally important 150-loop. Motion of the loop, which can move between an open and closed conformation, is intimately associated with drug unbinding and rebinding. Opening of the loop occurs coincidentally with drug unbinding, and interactions between oseltamivir and the loop seem to aid in the repositioning of the drug back into an approximation of its original binding mode on rebinding. The similarity of oseltamivir to a transition state analogue for neuraminidase suggests that the dynamics of the loop could play an important functional role in the enzyme, with loop closing aiding in binding of the substrate and loop opening aiding the release of the product.