Role of Water Molecules in Protein–Ligand Dissociation and Selectivity Discrimination: Analysis of the Mechanisms and Kinetics of Biomolecular Solvation Using Molecular Dynamics

Absolute Binding Free Energies with OneOPES

The calculation of absolute binding free energies (ABFEs) for protein-ligand systems has long been a challenge. Recently, refined force fields and algorithms have improved the quality of the ABFE calculations. However, achieving the level of accuracy required to inform drug discovery efforts remains difficult. Here, we present a transferable enhanced sampling strategy to accurately calculate absolute binding free energies using OneOPES with simple geometric collective variables. We tested the strategy on two protein targets, BRD4 and Hsp90, complexed with a total of 17 chemically diverse ligands, including both molecular fragments and drug-like molecules. Our results show that OneOPES accurately predicts protein-ligand binding affinities with a mean unsigned error within 1 kcal mol-1 of experimentally determined free energies, without the need to tailor the collective variables to each system. Furthermore, our strategy effectively samples different ligand binding modes and consistently matches the experimentally determined structures regardless of the initial protein-ligand configuration. Our results suggest that the proposed OneOPES strategy can be used to inform lead optimization campaigns in drug discovery and to study protein-ligand binding and unbinding mechanisms.

OneOPES, a Combined Enhanced Sampling Method to Rule Them All

Enhanced sampling techniques have revolutionized molecular dynamics (MD) simulations, enabling the study of rare events and the calculation of free energy differences in complex systems. One of the main families of enhanced sampling techniques uses physical degrees of freedom called collective variables (CVs) to accelerate a system's dynamics and recover the original system's statistics. However, encoding all the relevant degrees of freedom in a limited number of CVs is challenging, particularly in large biophysical systems. Another category of techniques, such as parallel tempering, simulates multiple replicas of the system in parallel, without requiring CVs. However, these methods may explore less relevant high-energy portions of the phase space and become computationally expensive for large systems. To overcome the limitations of both approaches, we propose a replica exchange method called OneOPES that combines the power of multireplica simulations and CV-based enhanced sampling. This method efficiently accelerates the phase space sampling without the need for ideal CVs, extensive parameters fine tuning nor the use of a large number of replicas, as demonstrated by its successful applications to protein-ligand binding and protein folding benchmark systems. Our approach shows promise as a new direction in the development of enhanced sampling techniques for molecular dynamics simulations, providing an efficient and robust framework for the study of complex and unexplored problems.

Temperature Accelerated Sliced Sampling to Probe Ligand Dissociation from Protein

Modeling ligand unbinding in proteins to estimate the free energy of binding and probing the mechanism presents several challenges. They primarily pertain to the entropic bottlenecks resulting from protein and solvent conformations. While exploring the unbinding processes using enhanced sampling techniques, very long simulations are required to sample all of the conformational states as the system gets trapped in local free energy minima along transverse coordinates. Here, we demonstrate that temperature accelerated sliced sampling (TASS) is an ideal approach to overcome some of the difficulties faced by conventional sampling methods in studying ligand unbinding. Using TASS, we study the unbinding of avibactam inhibitor molecules from the Class C β-lactamase (CBL) active site. Extracting CBL-avibactam unbinding free energetics, unbinding pathways, and identifying critical interactions from the TASS simulations are demonstrated.

Total free energy analysis of fully hydrated proteins

The total free energy of a hydrated biomolecule and its corresponding decomposition of energy and entropy provides detailed information about regions of thermodynamic stability or instability. The free energies of four hydrated globular proteins with different net charges are calculated from a molecular dynamics simulation, with the energy coming from the system Hamiltonian and entropy using multiscale cell correlation. Water is found to be most stable around anionic residues, intermediate around cationic and polar residues, and least stable near hydrophobic residues, especially when more buried, with stability displaying moderate entropy-enthalpy compensation. Conversely, anionic residues in the proteins are energetically destabilized relative to singly solvated amino acids, while trends for other residues are less clear-cut. Almost all residues lose intraresidue entropy when in the protein, enthalpy changes are negative on average but may be positive or negative, and the resulting overall stability is moderate for some proteins and negligible for others. The free energy of water around single amino acids is found to closely match existing hydrophobicity scales. Regarding the effect of secondary structure, water is slightly more stable around loops, of intermediate stability around β strands and turns, and least stable around helices. An interesting asymmetry observed is that cationic residues stabilize a residue when bonded to its N-terminal side but destabilize it when on the C-terminal side, with a weaker reversed trend for anionic residues.

Water regulates the residence time of Benzamidine in Trypsin

The process of ligand-protein unbinding is crucial in biophysics. Water is an essential part of any biological system and yet, many aspects of its role remain elusive. Here, we simulate with state-of-the-art enhanced sampling techniques the binding of Benzamidine to Trypsin which is a much studied and paradigmatic ligand-protein system. We use machine learning methods to determine efficient collective coordinates for the complex non-local network of water. These coordinates are used to perform On-the-fly Probability Enhanced Sampling simulations, which we adapt to calculate also the ligand residence time. Our results, both static and dynamic, are in good agreement with experiments. We find that the presence of a water molecule located at the bottom of the binding pocket allows via a network of hydrogen bonds the ligand to be released into the solution. On a finer scale, even when unbinding is allowed, another water molecule further modulates the exit time.

Grid inhomogeneous solvation theory for cross-solvation in rigid solvents

Grid Inhomogeneous Solvation Theory (GIST) has proven useful to calculate localized thermodynamic properties of water around a solute. Numerous studies have leveraged this information to enhance structure-based binding predictions. We have recently extended GIST toward chloroform as a solvent to allow the prediction of passive membrane permeability. Here, we further generalize the GIST algorithm toward all solvents that can be modeled as rigid molecules. This restriction is inherent to the method and is already present in the inhomogeneous solvation theory. Here, we show that our approach can be applied to various solvent molecules by comparing the results of GIST simulations with thermodynamic integration (TI) calculations and experimental results. Additionally, we analyze and compare a matrix consisting of 100 entries of ten different solvent molecules solvated within each other. We find that the GIST results are highly correlated with TI calculations as well as experiments. For some solvents, we find Pearson correlations of up to 0.99 to the true entropy, while others are affected by the first-order approximation more strongly. The enthalpy-entropy splitting provided by GIST allows us to extend a recently published approach, which estimates higher order entropies by a linear scaling of the first-order entropy, to solvents other than water. Furthermore, we investigate the convergence of GIST in different solvents. We conclude that our extension to GIST reliably calculates localized thermodynamic properties for different solvents and thereby significantly extends the applicability of this widely used method.

Spatially Resolved Hydration Thermodynamics in Biomolecular Systems

Water is essential for the structure, dynamics, energetics, and thus the function of biomolecules. It is a formidable challenge to elicit, in microscopic detail, the role of the solvation-related driving forces of biomolecular processes, such as the enthalpy and entropy contributions to the underlying free-energy landscape. In this Perspective, we discuss recent developments and applications of computational methods that provide a spatially resolved map of hydration thermodynamics in biomolecular systems and thus yield atomic-level insights to guide the interpretation of experimental observations. An emphasis is on the challenge of quantifying the hydration entropy, which requires characterization of both the motions of the biomolecules and of the water molecules in their surrounding.

In the footsteps of an inhibitor unbinding from the active site of human carbonic anhydrase II

The crystal structure of human carbonic anhydrase (HCA) II bound to an inhibitor molecule, 6-hydroxy-2-thioxocoumarin (FC5), shows FC5 to be located in a hydrophobic pocket at the active site. The present work employs classical molecular dynamics (MD) simulation to follow the FC5 molecule for 1 μs as it unbinds from its binding location, adopts the path of substrate/product diffusion (path 1) to leave the active site at around 75 ns. It is then found to undergo repeated binding and unbinding at different locations on the surface of the enzyme in water. Several transient excursions through different regions of the enzyme are also observed prior to its exit from the active site. These transient paths are combined with functionally relevant cavities/channels to enlist five additional pathways (path 2-6). Pathways 1-6 are subsequently explored using steered MD and umbrella sampling simulations. A free energy barrier of 0.969 kcal mol^-1 is encountered along path 1, while barriers in the range of 0.57-2.84 kcal mol^-1 are obtained along paths 2, 4 and 5. We also analyze in detail the interaction between FC5 and the enzyme along each path as the former leaves the active site of HCA II. Our results indicate path 1 to be the major exit pathway for FC5, although competing contributions may also come from the paths 2, 4 and 5.Communicated by Ramaswamy H. Sarma.

Spectrally Resolved Estimation of Water Entropy in the Active Site of Human Carbonic Anhydrase II

A major challenge in understanding ligand binding to biomacromolecules lies in dissecting the underlying thermodynamic driving forces at the atomic level. Quantifying the contributions of water molecules is often especially demanding, although they can play important roles in biomolecular recognition and binding processes. One example is human carbonic anhydrase II, whose active site harbors a conserved network of structural water molecules that are essential for enzymatic catalysis. Inhibitor binding disrupts this water network and changes the hydrogen-bonding patterns in the active site. Here, we use atomistic molecular dynamics simulations to compute the absolute entropy of the individual water molecules confined in the active site of hCAII using a spectrally resolved estimation (SRE) approach. The entropy decrease of water molecules that remain in the active site upon binding of a dorzolamide inhibitor is caused by changes in hydrogen bonding and stiffening of the hydrogen-bonding network. Overall, this entropy decrease is overcompensated by the gain due to the release of three water molecules from the active site upon inhibitor binding. The spectral density calculations enable the assignment of the changes to certain vibrational modes. In addition, the range of applicability of the SRE approximation is systematically explored by exploiting the gradually changing degree of immobilization of water molecules as a function of the distance to a phospholipid bilayer surface, which defines an "entropy ruler". These results demonstrate the applicability of SRE to biomolecular solvation, and we expect it to become a useful method for entropy calculations in biomolecular systems.

Effect of Water Molecules on the Activating S810L Mutation of the Mineralocorticoid Receptor

The mineralocorticoid receptor (MR) is a nuclear receptor whose endogenous ligands are mineralocorticoids, a type of steroid hormone. The activating S810L mutation is known to cause severe early-onset and pregnancy-related hypertension. Progesterone binds to the wild-type (WT) MR as a passive antagonist with fast dissociation; however, it binds to the S810L mutant as a full agonist with slow dissociation. The switch in the biological activity of progesterone is considered to be one of the causes of the disease. First, we used steered molecular dynamics simulations to analyze the dissociation process of progesterone for the WT and the S810L mutant. Progesterone in the WT dissociated from the ligand-binding pocket with a weak force in comparison with progesterone in the S810L mutant due to the large inflow of water molecules into the pocket. Therefore, we used conventional molecular dynamics simulations for the ligand-free structures of the WT and the S810L mutant to investigate the effect of the mutation on the inflow of water. In the WT, water molecules enter the ligand-binding pocket in two ways: in the vicinity of (i) Arg817 and (ii) Ser810. In contrast, few water molecules enter the pocket in the S810L mutant because of the large size and hydrophobic nature of the Leu810 side chain. Fast dissociation is a common feature among passive antagonists of MR; therefore, we inferred that the water inflow could be responsible for the dissociation kinetics of progesterone in the WT and the S810L mutant.

How a Fragment Draws Attention to Selectivity Discriminating Features between the Related Proteases Trypsin and Thrombin

In the S₁ pocket, the serine proteases thrombin and trypsin commonly feature Asp189 and a Ala190Ser and Glu192Gln exchange. Nevertheless, thrombin cleaves peptide chains solely after Arg, and trypsin after Lys and Arg. Thrombin exhibits a Na+-binding site next to Asp189, which is missing in trypsin. The fragment benzylamine shows direct H-bonding to Asp189 in trypsin, while in thrombin, it forms an H-bond to Glu192. A series of fragments and expanded ligands were studied against both enzymes and mutated variants by crystallography and ITC. The selectivity-determining features of both S₁ pockets are difficult to assign to one dominating factor. The Ala190Ser and Glu192Gln replacements may be regarded as highly conserved as no structural and affinity changes are observed between both proteases. With respect to charge distribution, Glu192, together with the thrombin-specific sodium ion, helps in creating an electrostatic gradient across the S₁ pocket. This feature is definitely absent in trypsin but important for selectivity along with solvation-pattern differences in the S₁ pocket.