Water molecules in protein–ligand interfaces. Evaluation of software tools and SAR comparison

The Three-Dimensional Reference Interaction Site Model Approach as a Promising Tool for Studying Hydrated Viruses and Their Complexes with Ligands

Viruses are the most numerous biological form living in any ecosystem. Viral diseases affect not only people but also representatives of fauna and flora. The latest pandemic has shown how important it is for the scientific community to respond quickly to the challenge, including critically assessing the viral threat and developing appropriate measures to counter this threat. Scientists around the world are making enormous efforts to solve these problems. In silico methods, which allow quite rapid obtention of, in many cases, accurate information in this field, are effective tools for the description of various aspects of virus activity, including virus-host cell interactions, and, thus, can provide a molecular insight into the mechanism of virus functioning. The three-dimensional reference interaction site model (3D-RISM) seems to be one of the most effective and inexpensive methods to compute hydrated viruses, since the method allows us to provide efficient calculations of hydrated viruses, remaining all molecular details of the liquid environment and virus structure. The pandemic challenge has resulted in a fast increase in the number of 3D-RISM calculations devoted to hydrated viruses. To provide readers with a summary of this literature, we present a systematic overview of the 3D-RISM calculations, covering the period since 2010. We discuss various biophysical aspects of the 3D-RISM results and demonstrate capabilities, limitations, achievements, and prospects of the method using examples of viruses such as influenza, hepatitis, and SARS-CoV-2 viruses.

De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO

By mediating interatomic interactions, water molecules play a major role in protein-protein, protein-DNA and protein-ligand interfaces, significantly affecting affinity and specificity. This notwithstanding, explicit water molecules are usually not considered in protein design software because of high computational costs. To challenge this situation, we analyzed the binding characteristics of 60,000 waters from high resolution crystal structures and used the observed parameters to implement the prediction of water molecules in the protein design and side chain-packing software MUMBO. To reduce the complexity of the problem, we incorporated water molecules through the solvation of rotamer pairs instead of relying on solvated rotamer libraries. Our validation demonstrates the potential of our algorithm by achieving recovery rates of 67% for bridging water molecules and up to 86% for fully coordinated waters. The efficacy of our algorithm is highlighted further by the prediction of 3 different proteinligand complexes. Here, 91% of water-mediated interactions between protein and ligand are correctly predicted. These results suggest that the new algorithm could prove highly beneficial for structure-based protein design, particularly for the optimization of ligand-binding pockets or protein-protein interfaces.

TWN-FS method: A novel fragment screening method for drug discovery

Fragment-based drug discovery (FBDD) is a well-established and effective method for generating diverse and novel hits in drug design. Kinases are suitable targets for FBDD due to their well-defined structure. Water molecules contribute to structure and function of proteins and also influence the environment within the binding pocket. Water molecules form a variety of hydrogen-bonded cyclic water-ring networks, collectively known as topological water networks (TWNs). Analyzing the TWNs in protein binding sites can provide valuable insights into potential locations and shapes for fragments within the binding site. Here, we introduce TWN-based fragment screening (TWN-FS) method, a novel screening method that suggests fragments through grouped TWN analysis within the protein binding site. We used this method to screen known CDK2, CHK1, IGF1R and ERBB4 inhibitors. Our findings suggest that TWN-FS method has the potential to effectively screen fragments. The TWN-FS method package is available on GitHub at https://github.com/pkj0421/TWN-FS.

BMaps: A Web Application for Fragment-Based Drug Design and Compound Binding Evaluation

Fragment-based drug design uses data about where, and how strongly, small chemical fragments bind to proteins, to assemble new drug molecules. Over the past decade, we have been successfully using fragment data, derived from thermodynamically rigorous Monte Carlo fragment-protein binding simulations, in dozens of preclinical drug programs. However, this approach has not been available to the broader research community because of the cost and complexity of doing simulations and using design tools. We have developed a web application, called BMaps, to make fragment-based drug design widely available with greatly simplified user interfaces. BMaps provides access to a large repository (>550) of proteins with 100s of precomputed fragment maps, druggable hot spots, and high-quality water maps. Users can also employ their own structures or those from the Protein Data Bank and AlphaFold DB. Multigigabyte data sets are searched to find fragments in bondable orientations, ranked by a binding-free energy metric. The designers use this to select modifications that improve affinity and other properties. BMaps is unique in combining conventional tools such as docking and energy minimization with fragment-based design, in a very easy to use and automated web application. The service is available at https://www.boltzmannmaps.com.

The Advances and Limitations of the Determination and Applications of Water Structure in Molecular Engineering

Water is a key actor of various processes of nature and, therefore, molecular engineering has to take the structural and energetic consequences of hydration into account. While the present review focuses on the target-ligand interactions in drug design, with a focus on biomolecules, these methods and applications can be easily adapted to other fields of the molecular engineering of molecular complexes, including solid hydrates. The review starts with the problems and solutions of the determination of water structures. The experimental approaches and theoretical calculations are summarized, including conceptual classifications. The implementations and applications of water models are featured for the calculation of the binding thermodynamics and computational ligand docking. It is concluded that theoretical approaches not only reproduce or complete experimental water structures, but also provide key information on the contribution of individual water molecules and are indispensable tools in molecular engineering.

WaterKit: Thermodynamic Profiling of Protein Hydration Sites

Water desolvation is one of the key components of the free energy of binding of small molecules to their receptors. Thus, understanding the energetic balance of solvation and desolvation resulting from individual water molecules can be crucial when estimating ligand binding, especially when evaluating different molecules and poses as done in High-Throughput Virtual Screening (HTVS). Over the most recent decades, several methods were developed to tackle this problem, ranging from fast approximate methods (usually empirical functions using either discrete atom-atom pairwise interactions or continuum solvent models) to more computationally expensive and accurate ones, mostly based on Molecular Dynamics (MD) simulations, such as Grid Inhomogeneous Solvation Theory (GIST) or Double Decoupling. On one hand, MD-based methods are prohibitive to use in HTVS to estimate the role of waters on the fly for each ligand. On the other hand, fast and approximate methods show an unsatisfactory level of accuracy, with low agreement with results obtained with the more expensive methods. Here we introduce WaterKit, a new grid-based sampling method with explicit water molecules to calculate thermodynamic properties using the GIST method. Our results show that the discrete placement of water molecules is successful in reproducing the position of crystallographic waters with very high accuracy, as well as providing thermodynamic estimates with accuracy comparable to more expensive MD simulations. Unlike these methods, WaterKit can be used to analyze specific regions on the protein surface, (such as the binding site of a receptor), without having to hydrate and simulate the whole receptor structure. The results show the feasibility of a general and fast method to compute thermodynamic properties of water molecules, making it well-suited to be integrated in high-throughput pipelines such as molecular docking.

In Silico Evaluation of the Thr58-Associated Conserved Water with KRAS Switch-II Pocket Binders

The KRAS switch-II pocket (SII-P) has proven to be one of the most successful tools for targeting KRAS with small molecules to date. This has been demonstrated with several KRAS(G12C)-targeting covalent inhibitors, already resulting in two FDA-approved drugs. Several earlier-stage compounds have also been reported to engage KRAS SII-P with other position 12 mutants, including G12D, G12S, and G12R. A highly conserved water molecule exists in the KRAS SII-P, linking Thr58 of switch-II and Gly10 of β1 sheet. This conserved water is also present in the cocrystal structures of most of the disclosed small-molecule inhibitors but is only displaced by a handful of SII-P binders. Here, we evaluated the conserved water molecule energetics by the WaterMap for the SII-P binders with publicly disclosed structures and studied the water behavior in the presence of selected inhibitors by microsecond timescale molecular dynamics (MD) simulations using two water models (total simulation time of 120 μs). Our data revealed the high-energy nature of this hydration site when coexisting with an SII-P binder and that there is a preference for a single isolated hydration site in this location within the most advanced compounds. Furthermore, water displacement was only achieved with a few disclosed compounds and was suboptimal, as for instance a cyanomethyl group as a water displacer appears to introduce repulsion with the native conformation of Thr58. These results suggested that this conserved water should be considered more central when designing new inhibitors, especially in the design of noncovalent inhibitors targeting the SII-P.

Recent PELE Developments and Applications in Drug Discovery Campaigns

Computer simulation techniques are gaining a central role in molecular pharmacology. Due to several factors, including the significant improvements of traditional molecular modelling, the irruption of machine learning methods, the massive data generation, or the unlimited computational resources through cloud computing, the future of pharmacology seems to go hand in hand with in silico predictions. In this review, we summarize our recent efforts in such a direction, centered on the unconventional Monte Carlo PELE software and on its coupling with machine learning techniques. We also provide new data on combining two recent new techniques, aquaPELE capable of exhaustive water sampling and fragPELE, for fragment growing.

Introducing structure-based three-dimensional pharmacophore models for accelerating the discovery of selective BRD9 binders

A well-structured in silico workflow is here reported for disclosing structure-based pharmacophore models against bromodomain-containing protein 9 (BRD9), accelerating virtual screening campaigns and facilitating the identification of novel binders. Specifically, starting from 23 known ligands co-crystallized with BRD9, three-dimensional pharmacophore models, namely placed in a reference protein structure, were developed. Specifically, we here introduce a fragment-related pharmacophore model, useful for the identification of new promising small chemical probes targeting the protein region responsible of the acetyllysine recognition, and two further pharmacophore models useful for the selection of compounds featuring drug-like properties. A pharmacophore-driven virtual screening campaign was then performed to facilitate the selection of new selective BRD9 ligands, starting from a large library of commercially available molecules. The identification of a promising BRD9 binder (7) prompted us to re-iterate this computational workflow on a second focused in-house built library of synthesizable compounds and, eventually, three further novel BRD9 binders were disclosed (8-10). Moreover, all these compounds were tested among a panel comprising other nine bromodomains, showing a high selectivity for BRD9. Preclinical bioscreens for potential anticancer activity highlighted compound 7 as that showing the most promising biological effects, proving the reliability of this in silico pipeline and confirming the applicability of the here introduced structure-based three-dimensional (3D) pharmacophore models as straightforward tools for the selection of new BRD9 ligands.

Ligand binding: evaluating the contribution of the water molecules network using the Fragment Molecular Orbital method

Water molecules play a crucial role in protein-ligand binding, and many tools exist that aim to predict the position and relative energies of these important, but challenging participants of biomolecular recognition. The available tools are, in general, capable of predicting the location of water molecules. However, predicting the effects of their displacement is still very challenging. In this work, a linear-scaling quantum mechanics-based approach was used to assess water network energetics and the changes in network stability upon ligand structural modifications. This approach offers a valuable way to improve understanding of SAR data and help guide compound design.

Addressing a Trapped High-Energy Water: Design and Synthesis of Highly Potent Pyrimidoindole-Based Glycogen Synthase Kinase-3β Inhibitors

In small molecule binding, water is not a passive bystander but rather takes an active role in the binding site, which may be decisive for the potency of the inhibitor. Here, by addressing a high-energy water, we improved the IC₅₀ value of our co-crystallized glycogen synthase kinase-3β (GSK-3β) inhibitor by nearly two orders of magnitude. Surprisingly, our results demonstrate that this high-energy water was not displaced by our potent inhibitor (S)-3-(3-((7-ethynyl-9H-pyrimido[4,5-b]indol-4-yl)(methyl)amino)piperidin-1-yl)propanenitrile ((S)-15, IC₅₀ value of 6 nM). Instead, only a subtle shift in the location of this water molecule resulted in a dramatic decrease in the energy of this high-energy hydration site, as shown by the WaterMap analysis combined with microsecond timescale molecular dynamics simulations. (S)-15 demonstrated both a favorable kinome selectivity profile and target engagement in a cellular environment and reduced GSK-3 autophosphorylation in neuronal SH-SY5Y cells. Overall, our findings highlight that even a slight adjustment in the location of a high-energy water can be decisive for ligand binding.

Binding selectivity of inhibitors toward the first over the second bromodomain of BRD4: theoretical insights from free energy calculations and multiple short molecular dynamics simulations

Bromodomain-containing protein 4 (BRD4) plays an important role in mediating gene transcription involved in cancers and non-cancer diseases such as acute heart failure and inflammatory diseases. In this work, multiple short molecular dynamics (MSMD) simulations are integrated with a molecular mechanics generalized Born surface area (MM-GBSA) approach to decipher binding selectivity of three inhibitors 8NS, 82Y, and 837 toward two domains BD1 and BD2 of BRD4. The results demonstrate that the enthalpy effects play critical roles in selectivity identification of inhibitors toward BD1 and BD2, determining that 8NS has better selectivity toward BD2 than BD1, while 82Y and 837 more favorably bind to BD1 than BD2. A residue-based free-energy decomposition method was used to calculate an inhibitor-residue interaction spectrum and unveil contributions of separate residues to binding selectivity. The results identify six common residues, containing (P82, P375), (V87, V380), (L92, L385), (L94, L387), (N140, N433), and (I146, V439) individually belonging to (BD1, BD2) of BRD4, and yield a considerable binding difference of inhibitors to BD1 and BD2, suggesting that these residues play key roles in binding selectivity of inhibitors toward BD1 and BD2 of BRD4. Therefore, these results provide useful dynamics information and a structure affinity relationship for the development of highly selective inhibitors targeting BD1 and BD2 of BRD4.

Biotransformation: Impact and Application of Metabolism in Drug Discovery

Biotransformation has a huge impact on the efficacy and safety of drugs. Ultimately the effects of metabolism can be the lynchpin in the discovery and development cycle of a new drug. This article discusses the impact and application of biotransformation of drugs by mammalian systems, microorganisms, and recombinant enzymes, covering active and reactive metabolites, the impact of the gut microbiome on metabolism, and how insights gained from biotransformation studies can influence drug design from the combined perspectives of a CRO specializing in a range of biotransformation techniques and pharma biotransformation scientists. We include a commentary on how biology-driven approaches can complement medicinal chemistry strategies in drug optimization and the in vitro and surrogate systems available to explore and exploit biotransformation.

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.

Efficient consideration of coordinated water molecules improves computational protein-protein and protein-ligand docking discrimination

Highly coordinated water molecules are frequently an integral part of protein-protein and protein-ligand interfaces. We introduce an updated energy model that efficiently captures the energetic effects of these ordered water molecules on the surfaces of proteins. A two-stage method is developed in which polar groups arranged in geometries suitable for water placement are first identified, then a modified Monte Carlo simulation allows highly coordinated waters to be placed on the surface of a protein while simultaneously sampling amino acid side chain orientations. This “semi-explicit” water model is implemented in Rosetta and is suitable for both structure prediction and protein design. We show that our new approach and energy model yield significant improvements in native structure recovery of protein-protein and protein-ligand docking discrimination tests.

Well-coordinated water molecules—those forming multiple hydrogen bonds with nearby polar groups—play an important role in the structure of biomolecular systems, yet the effect of these waters is often not considered in molecular energy computations. In this paper, we describe a method to efficiently consider these water molecules both implicitly and explicitly at the interfaces formed by two polar molecules. In computations related to determining how a protein interacts with binding partners, we show that the use of this new method significantly improves results. Future application of this approach may improve the design of new protein and small molecule drugs.

Application of Atypical Acetyl-lysine Methyl Mimetics in the Development of Selective Inhibitors of the Bromodomain-Containing Protein 7 (BRD7)/Bromodomain-Containing Protein 9 (BRD9) Bromodomains

Non-BET bromodomain-containing proteins have become attractive targets for the development of novel therapeutics targeting epigenetic pathways. To help facilitate the target validation of this class of proteins, structurally diverse small-molecule ligands and methodologies to produce selective inhibitors in a predictable fashion are in high demand. Herein, we report the development and application of atypical acetyl-lysine (KAc) methyl mimetics to take advantage of the differential stability of conserved water molecules in the bromodomain binding site. Discovery of the n-butyl group as an atypical KAc methyl mimetic allowed generation of 31 (GSK6776) as a soluble, permeable, and selective BRD7/9 inhibitor from a pyridazinone template. The n-butyl group was then used to enhance the bromodomain selectivity of an existing BRD9 inhibitor and to transform pan-bromodomain inhibitors into BRD7/9 selective compounds. Finally, a solvent-exposed vector was defined from the pyridazinone template to enable bifunctional molecule synthesis, and affinity enrichment chemoproteomic experiments were used to confirm several of the endogenous protein partners of BRD7 and BRD9, which form part of the chromatin remodeling PBAF and BAF complexes, respectively.

Quantum Mechanical Investigation of Three-Dimensional Activity Cliffs Using the Molecules-in-Molecules Fragmentation-Based Method

The concept of activity cliff (AC) (i.e., a small structural modification resulting in a substantial bioactivity change) is widely encountered in medicinal chemistry during compound design. Whereas the study of ACs is of high interest as it provides a wealth of opportunities for effective drug design, its practical application in the actual drug development process has been difficult because of significant computational challenges. To provide some understanding of the ACs, we have carried out a rigorous quantum-mechanical investigation of the electronic interactions of a wide range of ACs (205 cliffs formed by 261 protein-ligand complexes covering 37 different receptor types) using multilayer molecules-in-molecules (MIM) fragmentation-based methodology. The MIM methodology enables performing accurate high-level quantum mechanical (QM) calculations at a substantially lower computational cost, while allowing for a quantitative decomposition of the protein-ligand binding energy into the contributions from individual residues, solvation, and entropy. Our investigation in this study is mainly focused on whether the QM binding energy calculation can correctly identify the higher potency cliff partner for a given ligand pair having a sufficiently high activity difference. We have also analyzed the effect of including crystal water molecules as a part of the receptor as well as the impact of ligand desolvation energy on the correct identification of the more potent ligand in a cliff pair. Our analysis reveals that, in the majority of the cases, the AC prediction could be significantly improved by carefully identifying the critical crystal water molecules, whereas the contribution from the ligand desolvation also remains essential. Additionally, we have exploited the residue-specific interaction energies provided by MIM to identify the key residues and interaction hot-spots that are responsible for the experimentally observed drastic activity changes. The results show that our MIM fragmentation-based protocol provides comprehensive interaction energy profiles that can be employed to understand the distinctiveness of ligand modifications, for potential applications in structure-based drug design.

Revealing binding selectivity of inhibitors toward bromodomain-containing proteins 2 and 4 using multiple short molecular dynamics simulations and free energy analyses

Emerging evidences indicate bromodomain-containing proteins 2 and 4 (BRD2 and BRD4) play critical roles in cancers, inflammations, cardiovascular diseases and other pathologies. Multiple short molecular dynamics (MSMD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were applied to investigate the binding selectivity of three inhibitors 87D, 88M and 89G towards BRD2 over BRD4. The root-mean-square fluctuation (RMSF) analysis indicates that the structural flexibility of BRD4 is stronger than that of BRD2. Moreover the calculated distances between the C_α atoms in the centres of the ZA_loop and BC_loop of BRD4 are also bigger than that of BRD2. The rank of binding free energies calculated using MM-GBSA method agrees well with that determined by experimental data. The results show that 87D can bind more favourably to BRD2 than BRD4, while 88M has better selectivity on BRD4 over BRD2. Residue-based free-energy decomposition method was utilized to estimate the inhibitor-residue interaction spectrum and the results not only identify the hot interaction spots of inhibitors with BRD2 and BRD4, but also demonstrate that several common residues, including (W370, W374), (P371, P375), (V376, V380) and (L381, L385) belonging to (BRD2, BRD4), generate significant binding difference of inhibitors to BRD2 and BRD4.

Utilizing Grand Canonical Monte Carlo Methods in Drug Discovery

The concepts behind targeting waters for potency and selectivity gains have been well documented and explored, although maximizing such potential gains can prove to be challenging. This problem is exacerbated in cases where there are multiple interacting waters, wherein perturbation of one water can affect the free energy landscape of the remaining waters. Knowing the right modification a priori is challenging, and computational approaches are ideally suited to help answer the key question of which substitution is best to try. Here, we use Grand Canonical Monte Carlo and the recent Grand Canonical Alchemical Perturbation methods to both understand and predict the effect of ligand-mediated water displacement when more than one water molecule is involved, as well as to understand how exploiting water networks can help govern selectivity.

A Molecular Dynamics Study of Vasoactive Intestinal Peptide Receptor 1 and the Basis of Its Therapeutic Antagonism

Vasoactive intestinal peptide receptor 1 (VPAC1) is a member of a secretin-like subfamily of G protein-coupled receptors. Its endogenous neuropeptide (VIP), secreted by neurons and immune cells, modulates various physiological functions such as exocrine and endocrine secretions, immune response, smooth muscles relaxation, vasodilation, and fetal development. As a drug target, VPAC1 has been selected for therapy of inflammatory diseases but drug discovery is still hampered by lack of its crystal structure. In this study we presented the homology model of this receptor constructed with the well-known web service GPCRM. The VPAC1 model is composed of extracellular and transmembrane domains that form a complex with an endogenous hormone VIP. Using the homology model of VPAC1 the mechanism of action of potential drug candidates for VPAC1 was described. Only two series of small-molecule antagonists of confirmed biological activity for VPAC1 have been described thus far. Molecular docking and a series of molecular dynamics simulations were performed to elucidate their binding to VPAC1 and resulting antagonist effect. The presented work provides the basis for the possible binding mode of VPAC1 antagonists and determinants of their molecular recognition in the context of other class B GPCRs. Until the crystal structure of VPAC1 will be released, the presented homology model of VPAC1 can serve as a scaffold for drug discovery studies and is available from the author upon request.