How Significant Are Unusual Protein-Ligand Interactions? Insights from Database Mining

User-centric design of a 3D search interface for protein-ligand complexes

In this work, we present the frontend of GeoMine and showcase its application, focusing on the new features of its latest version. GeoMine is a search engine for ligand-bound and predicted empty binding sites in the Protein Data Bank. In addition to its basic text-based search functionalities, GeoMine offers a geometric query type for searching binding sites with a specific relative spatial arrangement of chemical features such as heavy atoms and intermolecular interactions. In contrast to a text search that requires simple and easy-to-formulate user input, a 3D input is more complex, and its specification can be challenging for users. GeoMine's new version aims to address this issue from the graphical user interface perspective by introducing an additional visualization concept and a new query template type. In its latest version, GeoMine extends its query-building capabilities primarily through input formulation in 2D. The 2D editor is fully synchronized with GeoMine's 3D editor and provides the same functionality. It enables template-free query generation and template-based query selection directly in 2D pose diagrams. In addition, the query generation with the 3D editor now supports predicted empty binding sites for AlphaFold structures as query templates. GeoMine is freely accessible on the ProteinsPlus web server ( https://proteins.plus ).

Structure-based design of potent FABP4 inhibitors with high selectivity against FABP3

Fatty-acid binding protein 4 (FABP4) presents an attractive target for therapeutic intervention in metabolic and inflammatory diseases in recent years. However, highly similar three-dimensional structures and fatty acid binding ability of multiple FABP family members pose a significant challenge in design of FABP4-selective inhibitors. Particularly, inhibition of FABP3 raises safety concerns such as cardiac dysfunction and exercise intolerance. Here, we reported the discovery of new FABP4 inhibitors with high selectivity over FABP3 by exploiting the little structural difference in the ligand binding pockets of FABP4 and FABP3. On the basis of our previously reported FABP4 inhibitors with nanomolar potency, different substituents were further introduced to perfectly occupy two sub-pockets of FABP4 that are distinct from those of FABP3. Remarkably, a single methyl group introduction leads to the discovery of compound C3 that impressively exhibits a 601-fold selectivity over FABP3 when maintained nanomolar binding affinity for FABP4. Moreover, C3 also shows good metabolic stability and potent cellular anti-inflammatory activity, making it a promising inhibitor for further development. Therefore, the present study highlights the utility of the structure-based rational design strategy for seeking highly selective and potent inhibitors of FABP4 and the importance of identifying the appropriate subsite as well as substituent for gaining the desired selectivity.

Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets

This study introduces the PocketCFDM generative diffusion model, aimed at improving the prediction of small molecule poses in the protein binding pockets. The model utilizes a novel data augmentation technique, involving the creation of numerous artificial binding pockets that mimic the statistical patterns of non-bond interactions found in actual protein-ligand complexes. An algorithmic method was developed to assess and replicate these interaction patterns in the artificial binding pockets built around small molecule conformers. It is shown that the integration of artificial binding pockets into the training process significantly enhanced the model's performance. Notably, PocketCFDM surpassed DiffDock in terms of non-bond interaction and steric clash numbers, and the inference speed. Future developments and optimizations of the model are discussed. The inference code and final model weights of PocketCFDM are accessible publicly via the GitHub repository: https://github.com/vtarasv/pocket-cfdm.git.

Discovery of Orally Available and Brain Penetrant AEP Inhibitors

Alzheimer's Disease (AD) is the most widespread form of dementia, with one of the pathological hallmarks being the formation of neurofibrillary tangles (NFTs). These tangles consist of phosphorylated Tau fragments. Asparagine endopeptidase (AEP) is a key Tau cleaving enzyme that generates aggregation-prone Tau fragments. Inhibition of AEP to reduce the level of toxic Tau fragment formation could represent a promising therapeutic strategy. Here, we report the first orthosteric, selective, orally bioavailable, and brain penetrant inhibitors with an irreversible binding mode. We outline the development of the series starting from reversible molecules and demonstrate the link between inhibition of AEP and reduction of Tau N368 fragment both in vitro and in vivo.

Experimental Quantification of Halogen⋅⋅⋅Arene van der Waals Contacts

Crystallographic and computational studies suggest the occurrence of favourable interactions between polarizable arenes and halogen atoms. However, the systematic experimental quantification of halogen⋅⋅⋅arene interactions in solution has been hindered by the large variance in the steric demands of the halogens. Here we have synthesized molecular balances to quantify halogen⋅⋅⋅arene contacts in 17 solvents and solvent mixtures using 1 H NMR spectroscopy. Calculations indicate that favourable halogen⋅⋅⋅arene interactions arise from London dispersion in the gas phase. In contrast, comparison of our experimental measurements with partitioned SAPT0 energies indicate that dispersion is sufficiently attenuated by the solvent that the halogen⋅⋅⋅arene interaction trend was instead aligned with increasing exchange repulsion as the halogen increased in size (ΔGX ⋅⋅⋅Ph =0 to +1.5 kJ mol-1 ). Halogen⋅⋅⋅arene contacts were slightly less disfavoured in solvents with higher solvophobicities and lower polarizabilities, but strikingly, were always less favoured than CH3 ⋅⋅⋅arene contacts (ΔGMe ⋅⋅⋅Ph =0 to -1.4 kJ mol-1 ).

Exploring isofunctional molecules: Design of a benchmark and evaluation of prediction performance

Identification of novel chemotypes with biological activity similar to a known active molecule is an important challenge in drug discovery called 'scaffold hopping'. Small-, medium-, and large-step scaffold hopping efforts may lead to increasing degrees of chemical structure novelty with respect to the parent compound. In the present paper, we focus on the problem of large-step scaffold hopping. We assembled a high quality and well characterized dataset of scaffold hopping examples comprising pairs of active molecules and including a variety of protein targets. This dataset was used to build a benchmark corresponding to the setting of real-life applications: one active molecule is known, and the second active is searched among a set of decoys chosen in a way to avoid statistical bias. This allowed us to evaluate the performance of computational methods for solving large-step scaffold hopping problems. In particular, we assessed how difficult these problems are, particularly for classical 2D and 3D ligand-based methods. We also showed that a machine-learning chemogenomic algorithm outperforms classical methods and we provided some useful hints for future improvements.

Competition between electrostatic interactions and halogen bonding in the protein-ligand system: structural and thermodynamic studies of 5,6-dibromobenzotriazole-hCK2α complexes

CK2 is a member of the CMGC group of eukaryotic protein kinases and a cancer drug target. It can be efficiently inhibited by halogenated benzotriazoles and benzimidazoles. Depending on the scaffold, substitution pattern, and pH, these compounds are either neutral or anionic. Their binding poses are dictated by a hydrophobic effect (desolvation) and a tug of war between a salt bridge/hydrogen bond (to K68) and halogen bonding (to E114 and V116 backbone oxygens). Here, we test the idea that binding poses might be controllable by pH for ligands with near-neutral pK_a, using the conditionally anionic 5,6-DBBt and constitutively anionic TBBt as our models. We characterize the binding by low-volume Differential Scanning Fluorimetry (nanoDSF), Isothermal Calorimetry (ITC), Hydrogen/Deuterium eXchange (HDX), and X-ray crystallography (MX). The data indicate that the ligand pose away from the hinge dominates for the entire tested pH range (5.5-8.5). The insensitivity of the binding mode to pH is attributed to the perturbation of ligand pK_a upon binding that keeps it anionic in the ligand binding pocket at all tested pH values. However, a minor population of the ligand, detectable only by HDX, shifts towards the hinge in acidic conditions. Our findings demonstrate that electrostatic (ionic) interactions predominate over halogen bonding.

Discovery of Potent and Orally Bioavailable Pyridine N-Oxide-Based Factor XIa Inhibitors through Exploiting Nonclassical Interactions

Activated factor XI (FXIa) inhibitors are promising novel anticoagulants with low bleeding risk compared with current anticoagulants. The discovery of potent FXIa inhibitors with good oral bioavailability has been challenging. Herein, we describe our discovery effort, utilizing nonclassical interactions to improve potency, cellular permeability, and oral bioavailability by enhancing the binding while reducing polar atoms. Beginning with literature-inspired pyridine N-oxide-based FXIa inhibitor 1, the imidazole linker was first replaced with a pyrazole moiety to establish a polar C-H···water hydrogen-bonding interaction. Then, structure-based drug design was employed to modify lead molecule 2d in the P1' and P2' regions, with substituents interacting with key residues through various nonclassical interactions. As a result, a potent FXIa inhibitor 3f (K_i = 0.17 nM) was discovered. This compound demonstrated oral bioavailability in preclinical species (rat 36.4%, dog 80.5%, and monkey 43.0%) and displayed a dose-dependent antithrombotic effect in a rabbit arteriovenous shunt model of thrombosis.

Discovery of potent dual ligands for dopamine D4 and σ1 receptors

During our work on exploration of molecules with some piperidine-triazole scaffolds, we realized that our compounds display chemical similarity with some σ, as well as dopaminergic receptor ligands. Here we show that this series of molecules has indeed strong affinity both for σ1 and dopamine D4 receptors. Moreover, they appear selective towards σ2, dopamine paralogues D1, D2, D3 and D5 receptors and hERG channel. Extensive molecular dynamics with our lead compound AVRM-13 were carried out on σ1, supporting agonist activity of the ligand. Unexpectedly, several observations suggested the existence of a cation binding domain, a probable regulatory site for calcium.

fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions

Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt—a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt)—a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.

Intramolecular N-H⋅⋅⋅F Hydrogen Bonding Interaction in a Series of 4-Anilino-5-Fluoroquinazolines: Experimental and Theoretical Characterization of Electronic and Conformational Effects

The 4-anilino-6,7-ethylenedioxy-5-fluoroquinazoline scaffold is presented as a novel model system for the characterization of the weak NH⋅⋅⋅F hydrogen bonding (HB) interaction. In this scaffold, the aniline NH proton is forced into close proximity with the nearby fluorine (d_H,F ∼2.0 Å, ∠∼138°), and a through-space interaction is observed by NMR spectroscopy with couplings (^1h J_NH,F ) of 19±1 Hz. A combination of experimental (NMR spectroscopy and X-ray crystallography) and theoretical methods (DFT calculations) were used for the characterization of this weak interaction. In particular, the effects of conformational rigidity and steric compression on coupling were investigated. This scaffold was used for the direct comparison of fluoride with methoxy as HB acceptors, and the susceptibility of the NH⋅⋅⋅F interaction to changes in electron distribution and resonance was probed by preparing a series of molecules with different electron-donating or -withdrawing groups in the positions para to the NH and F. The results support the idea that fluorine can act as a weak HB acceptor, and the HB strength can be modulated through additive and linear electronic substituent effects.

Structural Biology-Guided Design, Synthesis, and Biological Evaluation of Novel Insect Nicotinic Acetylcholine Receptor Orthosteric Modulators

The development of novel and safe insecticides remains an important need for a growing world population to protect crops and animal and human health. New chemotypes modulating the insect nicotinic acetylcholine receptors have been recently brought to the agricultural market, yet with limited understanding of their molecular interactions at their target receptor. Herein, we disclose the first crystal structures of these insecticides, namely, sulfoxaflor, flupyradifurone, triflumezopyrim, flupyrimin, and the experimental compound, dicloromezotiaz, in a double-mutated acetylcholine-binding protein which mimics the insect-ion-channel orthosteric site. Enabled by these findings, we discovered novel pharmacophores with a related mode of action, and we describe herein their design, synthesis, and biological evaluation.

5-Fluoro-1,2,3-triazole motif in peptides and its electronic properties

The 5-fluoro triazole amino acid has been prepared by halogen exchange between the 5-iodo triazole and fluoride salts and incorporated in peptides. X-ray crystallography reveals a cylindrical shape in its deformation electron density.

1,4,9-Triazaspiro[5.5]undecan-2-one Derivatives as Potent and Selective METTL3 Inhibitors

N⁶-methyladenosine (m⁶A) is the most frequent of the 160 RNA modifications reported so far. Accumulating evidence suggests that the METTL3/METTL14 protein complex, part of the m⁶A regulation machinery, is a key player in a variety of diseases including several types of cancer, type 2 diabetes, and viral infections. Here we report on a protein crystallography-based medicinal chemistry optimization of a METTL3 hit compound that has resulted in a 1400-fold potency improvement (IC₅₀ of 5 nM for the lead compound 22 (UZH2) in a time-resolved Förster resonance energy transfer (TR-FRET) assay). The series has favorable ADME properties as physicochemical characteristics were taken into account during hit optimization. UZH2 shows target engagement in cells and is able to reduce the m⁶A/A level of polyadenylated RNA in MOLM-13 (acute myeloid leukemia) and PC-3 (prostate cancer) cell lines.

Searching Geometric Patterns in Protein Binding Sites and Their Application to Data Mining in Protein Kinase Structures

The ever-growing number of protein-ligand complex structures can give fundamental insights into protein functions and protein-ligand interactions, especially in the field of protein kinase research. The number of tools to mine this data for individually defined structural motifs is restricted due to the challenging task of developing efficient index structures for 3D data in relational databases. Herein we present GeoMine, a database system with web front-end mining of more than 900 000 binding sites. It enables database searches for geometric (interaction) patterns in protein-ligand interfaces by, for example, textual, numerical, substructure, similarity, and 3D searches. GeoMine processes reasonably selective user-defined queries within minutes. We demonstrate its usability for advancing protein kinase research with a special emphasis on unusual interactions, their use in designing selective kinase inhibitors, and the analysis of reactive cysteine residues that are amenable to covalent kinase inhibitors. GeoMine is freely available as part of our modeling support server at https://proteins.plus.

Biological halogen bonds in protein-ligand complexes: a combined QTAIM and NCIPlot study in four representative cases

In this study, the PDB has been manually scrutinized by using a subset of all PDB entries containing organic iodinated ligands. Four structures exhibiting short IA halogen bonding (HaB) contacts (A stands for the σ-hole acceptor) have been selected and further analysed. In most hits, the sigma-hole acceptor corresponds to an O-atom of the amido group belonging to the protein backbone. In a minority of hits, the electron donors are O, S, Se or π-systems of the amino-acid side chains. A judicious selection of four PDB structures presenting all four types of HaB interactions (C-IA, A = O, S, Se, π) has been performed. For these selected structures, a comprehensive RI-MP2/def2-TZVP study has been carried out to evaluate the HaB energetically. Moreover, the interactions have been characterized by combining the quantum theory of "atoms-in-molecules" (QTAIM) and the noncovalent interaction plot (NCIPlot) and rationalized using the molecular electrostatic potential (MEP) surface.

Augmenting Structure-Based Design with Experimental Protein-Ligand Interaction Data: Molecular Recognition, Interactive Visualization, and Rescoring

The previously introduced ratio of frequencies (R_F ) framework provides statistically sound information on the relative interaction preferences of atoms in crystal structures. By applying the methodology to protein-ligand complexes, we can investigate the significance of interactions that are employed in structure-based drug design. Here, we revisit three aspects of molecular recognition in the light of the R_F framework, namely stacking interactions of heteroaromatic rings with protein amide groups, interactions of acidified C-H groups, and interaction differences between syn and anti lone pairs of carboxylate groups. In addition, we introduce a highly interactive visualization tool that facilitates design idea generation in structure-enabled drug discovery projects. Finally, we show that applying the R_F analysis as a simple rescoring tool after docking improves enrichment factors for the DUD-E diverse targets subset supporting the relevance of our approach.

Targeting a Cryptic Pocket in a Protein-Protein Contact by Disulfide-Induced Rupture of a Homodimeric Interface

Interference with protein-protein interfaces represents an attractive as well as challenging option for therapeutic intervention and drug design. The enzyme tRNA-guanine transglycosylase, a target to fight Shigellosis, is only functional as a homodimer. Although we previously produced monomeric variants by site-directed mutagenesis, we only crystallized the functional dimer, simply because upon crystallization the local protein concentration increases and favors formation of the dimer interface, which represents an optimal and highly stable packing of the protein in the solid state. Unfortunately, this prevents access to structural information about the interface geometry in its monomeric state and complicates the development of modulators that can interfere with and prevent dimer formation. Here, we report on a cysteine-containing protein variant in which, under oxidizing conditions, a disulfide linkage is formed. This reinforces a novel packing geometry of the enzyme. In this captured quasi-monomeric state, the monomer units arrange in a completely different way and, thus, expose a loop-helix motif, originally embedded into the old interface, now to the surface. The motif adopts a geometry incompatible with the original dimer formation. Via the soaking of fragments into the crystals, we identified several hits accommodating a cryptic binding site next to the loop-helix motif and modulated its structural features. Our study demonstrates the druggability of the interface by breaking up the homodimeric protein using an introduced disulfide cross-link. By rational concepts, we increased the potency of these fragments to a level where we confirmed their binding by NMR to a nondisulfide-linked TGT variant. The idea of intermediately introducing a disulfide linkage may serve as a general concept of how to transform a homodimer interface into a quasi-monomeric state and give access to essential structural and design information.

Data-Driven Ensemble Docking to Map Molecular Interactions of Steroid Analogs with Hepatic Organic Anion Transporting Polypeptides

Hepatic organic anion transporting polypeptides—OATP1B1, OATP1B3, and OATP2B1—are expressed at the basolateral membrane of hepatocytes, being responsible for the uptake of a wide range of natural substrates and structurally unrelated pharmaceuticals. Impaired function of hepatic OATPs has been linked to clinically relevant drug–drug interactions leading to altered pharmacokinetics of administered drugs. Therefore, understanding the commonalities and differences across the three transporters represents useful knowledge to guide the drug discovery process at an early stage. Unfortunately, such efforts remain challenging because of the lack of experimentally resolved protein structures for any member of the OATP family. In this study, we established a rigorous computational protocol to generate and validate structural models for hepatic OATPs. The multistep procedure is based on the systematic exploration of available protein structures with shared protein folding using normal-mode analysis, the calculation of multiple template backbones from elastic network models, the utilization of multiple template conformations to generate OATP structural models with various degrees of conformational flexibility, and the prioritization of models on the basis of enrichment docking. We employed the resulting OATP models of OATP1B1, OATP1B3, and OATP2B1 to elucidate binding modes of steroid analogs in the three transporters. Steroid conjugates have been recognized as endogenous substrates of these transporters. Thus, investigating this data set delivers insights into mechanisms of substrate recognition. In silico predictions were complemented with in vitro studies measuring the bioactivity of a compound set on OATP expressing cell lines. Important structural determinants conferring shared and distinct binding patterns of steroid analogs in the three transporters have been identified. Overall, this comparative study provides novel insights into hepatic OATP-ligand interactions and selectivity. Furthermore, the integrative computational workflow for structure-based modeling can be leveraged for other pharmaceutical targets of interest.

Into the Fray! A Beginner's Guide to Medicinal Chemistry

Modern medicinal chemistry is a complex, multidimensional discipline that operates at the interface of the chemical and biological sciences. The medicinal chemistry contribution to drug discovery is typically described in the context of the well-recited linear progression of the drug discovery pipeline. However, compound optimization is idiosyncratic to each project, and clear definitions of hit and lead molecules and the subsequent progress along the pipeline becomes easily blurred. In addition, this description lacks insight into the entangled relationship between chemical and pharmacological properties, and thus provides limited guidance on how innovative medicinal chemistry strategies can be applied to solve optimization problems, regardless of the stage in the pipeline. Through discussion and illustrative examples, this article seeks to provide insights into the finesse of medicinal chemistry and the subtlety of balancing chemical properties pharmacology. In so doing, it aims to serve as an accessible and simple-to-digest guide for anyone who wishes to learn about the underlying principles of medicinal chemistry, in a context that has been decoupled from the pipeline description.

Conformational Analysis of Acyclic α-Fluoro Sulfur Motifs

Bioactive small molecules containing α-fluoro sulfur motifs [RS(O)n CH2 F] are appearing with increasing frequency in the pharmaceutical and agrochemical sectors. Prominent examples include the anti-asthma drug Flovent® and the phenylpyrazole insecticide pyrafluprole. Given the popularity of these structural units in bioactive small molecule design, together with the varying oxidation states of sulfur, a conformational analysis of α-fluoro sulfides, sulfoxides, and sulfones, would be instructive in order to delineate the non-covalent interactions that manifest themselves in structure. A combined crystallographic and computational analysis demonstrates the importance of hyperconjugative donor-acceptor interactions in achieving acyclic conformational control. The conformational disparity in the syn- and anti-diastereoisomers of α-fluorosulfoxides is particularly noteworthy.

Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease

COVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments were progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease.

N-Sulfonyl dipeptide nitriles as inhibitors of human cathepsin S: In silico design, synthesis and biochemical characterization

A library of cathepsin S inhibitors of the dipeptide nitrile chemotype, bearing a bioisosteric sulfonamide moiety, was synthesized. Kinetic investigations were performed at four human cysteine proteases, i.e. cathepsins S, B, K and L. Compound 12 with a terminal 3-biphenyl sulfonamide substituent was the most potent (K_i = 4.02 nM; selectivity ratio cathepsin S/K = 5.8; S/L = 67) and 24 with a 4'-fluoro-4-biphenyl sulfonamide substituent the most selective cathepsin S inhibitor (K_i = 35.5 nM; selectivity ratio cathepsin S/K = 57; S/L = 31). In silico design and biochemical evaluation emphasized the impact of the sulfonamide linkage on selectivity and a possible switch of P2 and P3 substituents with respect to the occupation of the corresponding binding sites of cathepsin S.

A Focus on Unusual ECL2 Interactions Yields β2 -Adrenergic Receptor Antagonists with Unprecedented Scaffolds

The binding pockets of aminergic G protein-coupled receptors are often targeted by drugs and virtual screening campaigns. In order to find ligands with unprecedented scaffolds for one of the best-investigated receptors of this subfamily, the β2 -adrenergic receptor, we conducted a docking-based screen insisting that molecules would address previously untargeted residues in extracellular loop 2. We here report the discovery of ligands with a previously undescribed coumaran-based scaffold. Furthermore, we provide an analysis of the added value that X-ray structures in different conformations deliver for such docking screens.

STACKED - Solvation Theory of Aromatic Complexes as Key for Estimating Drug Binding

The use of fragments to biophysically characterize a protein binding pocket and determine the strengths of certain interactions is a computationally and experimentally commonly applied approach. Almost all drug like molecules contain at least one aromatic moiety forming stacking interactions in the binding pocket. In computational drug design, the strength of stacking and the resulting optimization of the aromatic core or moiety is usually calculated using high level quantum mechanical approaches. However, as these calculations are performed in a vacuum, solvation properties are neglected. We close this gap by using Grid Inhomogeneous Solvation Theory (GIST) to describe the properties of individual heteroaromatics and complexes and thereby estimate the desolvation penalty. In our study, we investigated the solvation free energies of heteroaromatics frequently occurring in drug design projects in complex with truncated side chains of phenylalanine, tyrosine, and tryptophan. Furthermore, we investigated the properties of drug-fragments crystallized in a fragment-based lead optimization approach investigating PDE-10-A. We do not only find good correlation for the estimated desolvation penalty and the experimental binding free energy, but our calculations also allow us to predict prominent interaction sites. We highlight the importance of including the desolvation penalty of the respective heteroaromatics in stacked complexes to explain the gain or loss in affinity of potential lead compounds.

Identifying intermolecular atom⋯atom interactions that are not just bonding but also competitive

This highlight criticises the QTAIM method and discusses algorithms for identifying intermolecular interactions that are both bonding and competitive.