Thermodynamics of protein–ligand interactions as a reference for computational analysis: how to assess accuracy, reliability and relevance of experimental data

Solid-phase extraction with the functionalization of calcium-sensing receptors onto magnetic microspheres as an affinity probe can capture ligands selectively from herbal extract

Magnetic solid phase extraction with the functionalization of protein onto micro- or nano-particles as a probe is favorable for the discovery of new drugs from complicated natural products. Herein, we aimed to develop a rapid method by immobilizing halogenated alkane dehalogenase (Halo)-tagged calcium-sensing receptor (CaSR) directly out of crude cell lysates onto the surface of magnetic microspheres (MM) with no need to purify protein. Thereby we achieved CaSR-functionalized MM for revealing adsorption characteristics of agonist neomycin and screening ligands from herbal medicine Radix Astragali (RA). About 43.87 mg CaSR could be immobilized per 1 g MM within 30 min, and the acquired CaSR-functionalized MM showed good stability and activity for 4 weeks. The maximum adsorption capacity of neomycin on CaSR-functionalized MM was determined as 4.70 × 10-4 ~ 3.96 × 10-4 mol/g within 277 ~ 310 K, and its adsorption isotherm characteristics described best by the Temkin model were further validated using isothermal titration calorimetry. It was inferred that CaSR's affinity for neomycin was driven by electrostatic forces in a spontaneous process when the system reached an equilibrium state. Moreover, the ligands from the RA extract were screened, three of which were assigned as astragaloside IV, ononin, and calycosin based on HPLC-MS. Our findings demonstrated that the functionalization of a receptor onto magnetic materials designed as an affinity probe has the capability to recognize its agonist and capture the ligands selectively from complex matrices like herbs.

Mutational Studies of Aldose Reductase to Trace a Transient Pocket Opening and to Explain Ligand Affinity Cliffs

Human aldose reductase, a target for the development of inhibitors for preventing diabetic complications, displays a transient specificity pocket which opens upon binding with specific, potent inhibitors. We investigated the opening mechanism of this pocket by mutating leucine residues involved in the gate keeping mechanism to alanine. Two isostructural inhibitors distinguished only by a single nitro to carboxy group replacement, have a 1000-fold difference in their binding affinity to the wild type. This difference is reduced to 10-fold in the mutated variants as the nitro derivative loses in affinity but conserves binding to the open transient pocket. The affinity of the carboxylate analog is minimally altered but the analog binding preference changes from the closed to open state of the transient pocket. Differences in the solvation properties of ligands and the transient pocket as well as changes from induced fit to conformational selections provide an explanation for the altered behavior of the ligands with respect to their binding to the different variants.

PLBD: protein-ligand binding database of thermodynamic and kinetic intrinsic parameters

We introduce a protein-ligand binding database (PLBD) that presents thermodynamic and kinetic data of reversible protein interactions with small molecule compounds. The manually curated binding data are linked to protein-ligand crystal structures, enabling structure-thermodynamics correlations to be determined. The database contains over 5500 binding datasets of 556 sulfonamide compound interactions with the 12 catalytically active human carbonic anhydrase isozymes defined by fluorescent thermal shift assay, isothermal titration calorimetry, inhibition of enzymatic activity and surface plasmon resonance. In the PLBD, the intrinsic thermodynamic parameters of interactions are provided, which account for the binding-linked protonation reactions. In addition to the protein-ligand binding affinities, the database provides calorimetrically measured binding enthalpies, providing additional mechanistic understanding. The PLBD can be applied to investigations of protein-ligand recognition and could be integrated into small molecule drug design. Database URL https://plbd.org/.

Fragtory: Pharmacophore-Focused Design, Synthesis, and Evaluation of an sp3-Enriched Fragment Library

Fragment-based drug discovery has played an important role in medicinal chemistry and pharmaceutical research. Despite numerous demonstrated successes, the limited diversity and overrepresentation of planar, sp²-rich structures in commercial libraries often hamper the full potential of this approach. Hence, the thorough design of screening libraries inevitably determines the probability for meaningful hits and subsequent structural elaboration. Against this background, we present the generation of an exclusive fragment library based on iterative entry nomination by a specifically designed computational workflow: "Fragtory". Following a pharmacophore diversity-driven approach, we used Fragtory in an interdisciplinary academic setting to guide both tailored synthesis efforts and the implementation of in-house compounds to build a curated 288-member library of sp³-enriched fragments. Subsequent NMR screens against a model protein and hit validation by protein crystallography led to the identification of structurally novel ligands that were further characterized by isothermal titration calorimetry, demonstrating the applicability of our experimental approach.

Escherichia coli CspA stimulates translation in the cold of its own mRNA by promoting ribosome progression

Escherichia coli CspA is an RNA binding protein that accumulates during cold-shock and stimulates translation of several mRNAs-including its own. Translation in the cold of cspA mRNA involves a cis-acting thermosensor element, which enhances ribosome binding, and the trans-acting action of CspA. Using reconstituted translation systems and probing experiments we show that, at low temperature, CspA specifically promotes the translation of the cspA mRNA folded in the conformation less accessible to the ribosome, which is formed at 37°C but is retained upon cold shock. CspA interacts with its mRNA without inducing large structural rearrangements, but allowing the progression of the ribosomes during the transition from translation initiation to translation elongation. A similar structure-dependent mechanism may be responsible for the CspA-dependent translation stimulation observed with other probed mRNAs, for which the transition to the elongation phase is progressively facilitated during cold acclimation with the accumulation of CspA.

The IQA Energy Partition in a Drug Design Setting: A Hepatitis C Virus RNA-Dependent RNA Polymerase (NS5B) Case Study

The interaction of the thumb site II of the NS5B protein of hepatitis C virus and a pair of drug candidates was studied using a topological energy decomposition method called interacting quantum atoms (IQA). The atomic energies were then processed by the relative energy gradient (REG) method, which extracts chemical insight by computation based on minimal assumptions. REG reveals the most important IQA energy contributions, by atom and energy type (electrostatics, sterics, and exchange–correlation), that are responsible for the behaviour of the whole system, systematically from a short-range ligand–pocket interaction until a distance of approximately 22 Å. The degree of covalency in various key interatomic interactions can be quantified. No exchange–correlation contribution is responsible for the changes in the energy profile of both pocket–ligand systems investigated in the ligand–pocket distances equal to or greater than that of the global minimum. Regarding the hydrogen bonds in the system, a “neighbour effect” was observed thanks to the REG method, which states that a carbon atom would rather not have its covalent neighbour oxygen form a hydrogen bond. The combination of IQA and REG enables the automatic identification of the pharmacophore in the ligands. The coarser Interacting Quantum Fragments (IQF) enables the determination of which amino acids of the pocket contribute most to the binding and the type of energy of said binding. This work is an example of the contribution topological energy decomposition methods can make to fragment-based drug design.

Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization

Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying “magic bullets” amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand–target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural–energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.

Sialic Acid Derivatives Inhibit SiaT Transporters and Delay Bacterial Growth

Antibiotic resistance is a major worldwide concern, and new drugs with mechanistically novel modes of action are urgently needed. Here, we report the structure-based drug design, synthesis, and evaluation in vitro and in cellular systems of sialic acid derivatives able to inhibit the bacterial sialic acid symporter SiaT. We designed and synthesized 21 sialic acid derivatives and screened their affinity for SiaT by a thermal shift assay and elucidated the inhibitory mechanism through binding thermodynamics, computational methods, and inhibitory kinetic studies. The most potent compounds, which have a 180-fold higher affinity compared to the natural substrate, were tested in bacterial growth assays and indicate bacterial growth delay in methicillin-resistant Staphylococcus aureus. This study represents the first example and a promising lead in developing sialic acid uptake inhibitors as novel antibacterial agents.

Which Properties Allow Ligands to Open and Bind to the Transient Binding Pocket of Human Aldose Reductase?

The transient specificity pocket of aldose reductase only opens in response to specific ligands. This pocket may offer an advantage for the development of novel, more selective ligands for proteins with similar topology that lack such an adaptive pocket. Our aim was to elucidate which properties allow an inhibitor to bind in the specificity pocket. A series of inhibitors that share the same parent scaffold but differ in their attached aromatic substituents were screened using ITC and X-ray crystallography for their ability to occupy the pocket. Additionally, we investigated the electrostatic potentials and charge distribution across the attached terminal aromatic groups with respect to their potential to bind to the transient pocket of the enzyme using ESP calculations. These methods allowed us to confirm the previously established hypothesis that an electron-deficient aromatic group is an important prerequisite for opening and occupying the specificity pocket. We also demonstrated from our crystal structures that a pH shift between 5 and 8 does not affect the binding position of the ligand in the specificity pocket. This allows for a comparison between thermodynamic and crystallographic data collected at different pH values.

Frag4Lead: growing crystallographic fragment hits by catalog using fragment-guided template docking

In recent years, crystallographic fragment screening has matured into an almost routine experiment at several modern synchrotron sites. The hits of the screening experiment, i.e. small molecules or fragments binding to the target protein, are revealed along with their 3D structural information. Therefore, they can serve as useful starting points for further structure-based hit-to-lead development. However, the progression of fragment hits to tool compounds or even leads is often hampered by a lack of chemical feasibility. As an attractive alternative, compound analogs that embed the fragment hit structurally may be obtained from commercial catalogs. Here, a workflow is reported based on filtering and assessing such potential follow-up compounds by template docking. This means that the crystallographic binding pose was integrated into the docking calculations as a central starting parameter. Subsequently, the candidates are scored on their interactions within the binding pocket. In an initial proof-of-concept study using five starting fragments known to bind to the aspartic protease endothiapepsin, 28 follow-up compounds were selected using the designed workflow and their binding was assessed by crystallography. Ten of these compounds bound to the active site and five of them showed significantly increased affinity in isothermal titration calorimetry of up to single-digit micromolar affinity. Taken together, this strategy is capable of efficiently evolving the initial fragment hits without major synthesis efforts and with full control by X-ray crystallography.

Thermodynamics of Micellization of Ionized Surfactants: The Equivalence of Enthalpies of Micellization from Calorimetry and the Variation of Critical Micelle Points with Temperature as Exemplified for Aqueous Solutions of an Aliphatic Cationic Surfactant

There is considerable confusion on experimental and thermodynamic aspects of the formation of ionized surfactant micelles. Recent claims that the van't Hoff and calorimetric enthalpies of micellization of ionized surfactants represent different aspects of micellization are shown to be incorrect. New conductance and surface tension measurements on n-dodecyltrimethylammonium bromide (DTAB) in water and in cosolution with 0.1 M KBr over a range of temperatures are used to provide a set of critical micelle concentrations (cmc's). The molar enthalpies of micellization derived from these cmc's are compared with calorimetric enthalpies of micellization obtained from a critical survey of the literature and shown to be equivalent. This signifies that both enthalpies capture the contributions from all aspects of micellization of charged micelles. The apparent discrepancies arise from experimental problems, incorrect use of the van't Hoff equation, and failure to recognize the constraints of the Phase Rule and electroneutrality. Deficiencies in the application of the two major models of micellization, namely, the "mass-action" model and the "phase" model, are exposed. Neither model is generally valid. The van't Hoff enthalpies of micellization of DTAB in water are similar in the presence and absence of 0.1 M KBr, confirming a similar correspondence found with calorimetric enthalpies for DTAB in water and NaBr.

Machine learning approach to discovery of small molecules with potential inhibitory action against vasoactive metalloproteases

With the advancement of combinatorial chemistry and big data, drug repositioning has boomed. In this sense, machine learning and artificial intelligence techniques offer a priori information to identify the most promising candidates. In this study, we combine QSAR and docking methodologies to identify compounds with potential inhibitory activity of vasoactive metalloproteases for the treatment of cardiovascular diseases. To develop this study, we used a database of 191 thermolysin inhibitor compounds, which is the largest as far as we know. First, we use Dragon's molecular descriptors (0-3D) to develop classification models using Bayesian networks (Naive Bayes) and artificial neural networks (Multilayer Perceptron). The obtained models are used for virtual screening of small molecules in the international DrugBank database. Second, docking experiments are carried out for all three enzymes using the Autodock Vina program, to identify possible interactions with the active site of human metalloproteases. As a result, high-performance artificial intelligence QSAR models are obtained for training and prediction sets. These allowed the identification of 18 compounds with potential inhibitory activity and an adequate oral bioavailability profile, which were evaluated using docking. Four of them showed high binding energies for the three enzymes, and we propose them as potential dual ACE/NEP inhibitors for the control of blood pressure. In summary, the in silico strategies used here constitute an important tool for the early identification of new antihypertensive drug candidates, with substantial savings in time and money.

Ligand Strain and Its Conformational Complexity Is a Major Factor in the Binding of Cyclic Dinucleotides to STING Protein

STING (stimulator of interferon genes) is a key regulator of innate immunity that has recently been recognized as a promising drug target. STING is activated by cyclic dinucleotides (CDNs) which eventually leads to expression of type I interferons and other cytokines. Factors underlying the affinity of various CDN analogues are poorly understood. Herein, we correlate structural biology, isothermal calorimetry (ITC) and computational modeling to elucidate factors contributing to binding of six CDNs-three pairs of natural (ribo) and fluorinated (2'-fluororibo) 3',3'-CDNs. X-ray structural analyses of six {STING:CDN} complexes did not offer any explanation for the different affinities of the studied ligands. ITC showed entropy/enthalpy compensation up to 25 kcal mol-1 for this set of similar ligands. The higher affinities of fluorinated analogues are explained with help of computational methods by smaller loss of entropy upon binding and by smaller strain (free) energy.

Uncertainty in protein-ligand binding constants: asymmetric confidence intervals versus standard errors

Equilibrium binding constants (K_b) between chemical compounds and target proteins or between interacting proteins provide a quantitative understanding of biological interaction mechanisms. Reported uncertainties of measured experimental parameters are critical for decision-making in many scientific areas, e.g., in lead compound discovery processes and in comparing computational predictions with experimental results. Uncertainties in measured K_b values are commonly represented by a symmetric normal distribution, often quoted in terms of the experimental value plus-minus the standard deviation. However, in general, the distributions of measured K_b (and equivalent K_d) values and the corresponding free energy change ΔG_b are all asymmetric to varying degree. Here, using a simulation approach, we illustrate the effect of asymmetric K_b distributions within the realm of isothermal titration calorimetry (ITC) experiments. Further we illustrate the known, but perhaps not widely appreciated, fact that when distributions of any of K_b, K_d and ΔG_b are transformed into each other, their degree of asymmetry is changed. Consequently, we recommend that a more accurate way of expressing the uncertainties of K_b, K_d, and ΔG_b values is to consistently report 95% confidence intervals, in line with other authors' suggestions. The ways to obtain such error ranges are discussed in detail and exemplified for a binding reaction obtained by ITC.

Structural and Thermodynamic Analysis of the Resistance Development to Pimodivir (VX-787), the Clinical Inhibitor of Cap Binding to PB2 Subunit of Influenza A Polymerase

Influenza A virus (IAV) encodes a polymerase composed of three subunits: PA, with endonuclease activity, PB1 with polymerase activity and PB2 with host RNA five-prime cap binding site. Their cooperation and stepwise activation include a process called cap-snatching, which is a crucial step in the IAV life cycle. Reproduction of IAV can be blocked by disrupting the interaction between the PB2 domain and the five-prime cap. An inhibitor of this interaction called pimodivir (VX-787) recently entered the third phase of clinical trial; however, several mutations in PB2 that cause resistance to pimodivir were observed. First major mutation, F404Y, causing resistance was identified during preclinical testing, next the mutation M431I was identified in patients during the second phase of clinical trials. The mutation H357N was identified during testing of IAV strains at Centers for Disease Control and Prevention. We set out to provide a structural and thermodynamic analysis of the interactions between cap-binding domain of PB2 wild-type and PB2 variants bearing these mutations and pimodivir. Here we present four crystal structures of PB2-WT, PB2-F404Y, PB2-M431I and PB2-H357N in complex with pimodivir. We have thermodynamically analysed all PB2 variants and proposed the effect of these mutations on thermodynamic parameters of these interactions and pimodivir resistance development. These data will contribute to understanding the effect of these missense mutations to the resistance development and help to design next generation inhibitors.

Best practices for artificial intelligence in life sciences research

We describe 11 best practices for the successful use of artificial intelligence and machine learning in pharmaceutical and biotechnology research at the data, technology and organizational management levels.

Theoretical Evaluation of Novel Thermolysin Inhibitors from Bacillus thermoproteolyticus. Possible Antibacterial Agents

The search for new antibacterial agents that could decrease bacterial resistance is a subject in continuous development. Gram-negative and Gram-positive bacteria possess a group of metalloproteins belonging to the MEROPS peptidase (M4) family, which is the main virulence factor of these bacteria. In this work, we used the previous results of a computational biochemistry protocol of a series of ligands designed in silico using thermolysin as a model for the search of antihypertensive agents. Here, thermolysin from Bacillus thermoproteolyticus, a metalloprotein of the M4 family, was used to determine the most promising candidate as an antibacterial agent. Our results from docking, molecular dynamics simulation, molecular mechanics Poisson-Boltzmann (MM-PBSA) method, ligand efficiency, and ADME-Tox properties (Absorption, Distribution, Metabolism, Excretion, and Toxicity) indicate that the designed ligands were adequately oriented in the thermolysin active site. The Lig783, Lig2177, and Lig3444 compounds showed the best dynamic behavior; however, from the ADME-Tox calculated properties, Lig783 was selected as the unique antibacterial agent candidate amongst the designed ligands.

Estimation of non-constant variance in isothermal titration calorimetry using an ITC measurement model

Isothermal titration calorimetry (ITC) is the gold standard for accurate measurement of thermodynamic parameters in solution reactions. In the data processing of ITC, the non-constant variance of the heat requires special consideration. The variance function approach has been successfully applied in previous studies, but is found to fail under certain conditions in this work. Here, an explicit ITC measurement model consisting of main thermal effects and error components has been proposed to quantitatively evaluate and predict the non-constant variance of the heat data under various conditions. Monte Carlo simulation shows that the ITC measurement model provides higher accuracy and flexibility than variance function in high c-value reactions or with additional error components, for example, originated from the fluctuation of the concentrations or other properties of the solutions. The experimental design of basic error evaluation is optimized accordingly and verified by both Monte Carlo simulation and experiments. An easy-to-run Python source code is provided to illustrate the establishment of the ITC measurement model and the estimation of heat variances. The accurate and reliable non-constant variance of heat is helpful to the application of weighted least squares regression, the proper evaluation or selection of the reaction model.

Simultaneous determination of thermodynamic and kinetic data by isothermal titration calorimetry

BACKGROUND

Thermodynamic and binding kinetic data increasingly support and guide the drug optimization process.

METHODS

Because ITC thermograms contain binding thermodynamic and kinetic information, an efficient protocol for the simultaneous extraction of thermodynamic and kinetic data for 1:1 protein ligand reactions from AFFINImeter kinITC in one single experiment are presented.

RESULTS

The effort to apply this protocol requires the same time as for the standard protocol but increases the precision of both thermodynamic and kinetic data.

CONCLUSIONS

The protocol enables reliable extraction of both thermodynamic and kinetic data for 1:1 protein-ligand binding reactions with improved precision compared to the 'standard protocol'.

GENERAL SIGNIFICANCE

Thermodynamic and kinetic data are recorded under exactly the same conditions in solution without any labeling or immobilization from a protein sample that is not 100% active and would otherwise render the extraction of kinetic parameters impossible.

Conformational Trapping of a β-Glucosides-Binding Protein Unveils the Selective Two-Step Ligand-Binding Mechanism of ABC Importers

Substrate-binding proteins (SBPs), selectively capture ligand(s) and ensure their translocation via its cognate ATP-binding cassette (ABC) import system. SBPs bind their cognate ligand(s) via an induced-fit mechanism known as the "Venus Fly-trap"; however, this mechanism lacks the atomic details of all conformational landscape as the confirmatory evidence(s) in its support. In this study, we delineate the atomic details of an SBP, β-glucosides-binding protein (βGlyBP) from Thermus thermophilus HB8. The protein βGlyBP is multi-specific and binds to different types of β-glucosides varying in their glycosidic linkages viz. β-1,2; β-1,3; β-1,4 and β-1,6 with a degree of polymerization of 2-5 glucosyl units. Structurally, the protein βGlyBP possesses four subdomains (N1, N2, C1 and C2). The unliganded protein βGlyBP remains in an open state, which closes upon binding to sophorose (SOP2), laminari-oligosaccharides (LAMn), cello-oligosaccharides (CELn), and gentiobiose (GEN2). This study reports, for the first time, four different structural states (open-unliganded, partial-open-unliganded, open-liganded and closed-liganded) of the protein βGlyBP, revealing its conformational changes upon ligand binding and suggesting a two-step induced-fit mechanism. Further, results suggest that the conformational changes of N1 and C1 subdomains drive the ligand binding, unlike that of the whole N- and C-terminal domains (NTD and CTD) as known in the "Venus Fly-trap" mechanism. Additionally, profiling of stereo-selection mechanism for α- and β-glucosides reveals that in the ligand-binding site four secondary structural elements (L1, H1, H2 and H3) drive the ligand selection. In summary, results demonstrate that the details of conformational changes and ligand selection are pre-encoded in the SBPs.

Determination of acidity constants for weak acids and bases by isothermal titration calorimetry

The advantage of isothermal titration calorimetry (ITC) to determine the acid dissociation constant (pK_a value) is the simultaneous determination of the binding constant and binding enthalpy, as well as being precise and easy to use. The pK_a can be calculated from the binding constant, and the temperature dependency of the pK_a can be calculated from the binding enthalpy. The use of ITC to study protonation reactions is less common compared to its more conventional use of studying macromolecules and ligands. Water will influence the equilibrium due to autoionization, meaning that both the conjugate base and acid will exist in the sample cell at the beginning of the experiment. These differences are accounted for by optimizing the theoretical model used to estimate the binding constant and binding enthalpy. Through simulations and experimental measurements, we show that ITC can be used to determine the pK_a for ibuprofen, ascorbic acid, 2-morpholin-4-ylethanesulfonic acid and paracetamol. The pK_a values were consistent with potentiometric or spectrophotometric determinations as well as literature values. Optimizing the theoretical model does not lead to an improved determination, so the "one set of sites" model is adequate for the determination of pK_a values.

Evaluation of new antihypertensive drugs designed in silico using Thermolysin as a target

The search for new therapies for the treatment of Arterial hypertension is a major concern in the scientific community. Here, we employ a computational biochemistry protocol to evaluate the performance of six compounds (Lig783, Lig1022, Lig1392, Lig2177, Lig3444 and Lig6199) to act as antihypertensive agents. This protocol consists of Docking experiments, efficiency calculations of ligands, molecular dynamics simulations, free energy, pharmacological and toxicological properties predictions (ADME-Tox) of the six ligands against Thermolysin. Our results show that the docked structures had an adequate orientation in the pocket of the Thermolysin enzymes, reproducing the X-ray crystal structure of Inhibitor-Thermolysin complexes in an acceptable way. The most promising candidates to act as antihypertensive agents among the series are Lig2177 and Lig3444. These compounds form the most stable ligand-Thermolysin complexes according to their binding free energy values obtained in the docking experiments as well as MM-GBSA decomposition analysis calculations. They present the lowest values of Ki, indicating that these ligands bind strongly to Thermolysin. Lig2177 was oriented in the pocket of Thermolysin in such a way that both OH of the dihydroxyl-amino groups to establish hydrogen bond interactions with Glu146 and Glu166. In the same way, Lig3444 interacts with Asp150, Glu143 and Tyr157. Additionally, Lig2177 and Lig3444 fulfill all the requirements established by Lipinski Veber and Pfizer 3/75 rules, indicating that these compounds could be safe compounds to be used as antihypertensive agents. We are confident that our computational biochemistry protocol can be used to evaluate and predict the behavior of a broad range of compounds designed in silicoagainst a protein target.

The Influence of Varying Fluorination Patterns on the Thermodynamics and Kinetics of Benzenesulfonamide Binding to Human Carbonic Anhydrase II

The fluorination of lead-like compounds is a common tool in medicinal chemistry to alter molecular properties in various ways and with different goals. We herein present a detailed study of the binding of fluorinated benzenesulfonamides to human Carbonic Anhydrase II by complementing macromolecular X-ray crystallographic observations with thermodynamic and kinetic data collected with the novel method of kinITC. Our findings comprise so far unknown alternative binding modes in the crystalline state for some of the investigated compounds as well as complex thermodynamic and kinetic structure-activity relationships. They suggest that fluorination of the benzenesulfonamide core is especially advantageous in one position with respect to the kinetic signatures of binding and that a higher degree of fluorination does not necessarily provide for a higher affinity or more favorable kinetic binding profiles. Lastly, we propose a relationship between the kinetics of binding and ligand acidity based on a small set of compounds with similar substitution patterns.

Lipase-Catalyzed Chemoselective Ester Hydrolysis of Biomimetically Coupled Aryls for the Synthesis of Unsymmetric Biphenyl Esters

Lipases are among the most frequently used biocatalysts in organic synthesis, allowing numerous environmentally friendly and inexpensive chemical transformations. Here, we present a biomimetic strategy based on iron(III)-catalyzed oxidative coupling and selective ester monohydrolysis using lipases for the synthesis of unsymmetric biphenyl-based esters under mild conditions. The diverse class of biphenyl esters is of pharmaceutical and technical relevance. We explored the potency of a series of nine different lipases of bacterial, fungal, and mammalian origin on their catalytic activities to cleave biphenyl esters, and optimized the reaction conditions, in terms of reaction time, temperature, pH, organic solvent, and water–organic solvent ratios, to improve the chemoselectivity, and hence control the ratio of unsymmetric versus symmetric products. Elevated temperature and increased DMSO content led to an almost exclusive monohydrolysis by the four lipases Candida rugosa lipase (CRL), Mucor miehei lipase (MML), Rhizopus niveus lipase (RNL), and Pseudomonas fluorescens lipase (PFL). The study was complemented by in silico binding predictions to rationalize the observed differences in efficacies of the lipases to convert biphenyl esters. The optimized reaction conditions were transferred to the preparative scale with high yields, underlining the potential of the presented biomimetic approach as an alternative strategy to the commonly used transition metal-based strategies for the synthesis of diverse biphenyl esters.

Strategies for Late-Stage Optimization: Profiling Thermodynamics by Preorganization and Salt Bridge Shielding

Structural fixation of a ligand in its bioactive conformation may, due to entropic reasons, improve affinity. We present a congeneric series of thrombin ligands with a variety of functional groups triggering preorganization prior to binding. Fixation in solution and complex formation have been characterized by crystallography, isothermal titration calorimetry (ITC), and molecular dynamics (MD) simulations. First, we show why these preorganizing modifications do not affect the overall binding mode and how key interactions are preserved. Next, we demonstrate how preorganization thermodynamics can be largely dominated by enthalpy rather than entropy because of the significant population of low-energy conformations. Furthermore, a salt bridge is shielded by actively reducing its surface exposure, thus leading to an enhanced enthalpic binding profile. Our results suggest that the consideration of the ligand solution ensemble by MD simulation is necessary to predict preorganizing modifications that enhance the binding behavior of already promising binders.

Thermodynamic, kinetic, and structural parameterization of human carbonic anhydrase interactions toward enhanced inhibitor design

The aim of rational drug design is to develop small molecules using a quantitative approach to optimize affinity. This should enhance the development of chemical compounds that would specifically, selectively, reversibly, and with high affinity interact with a target protein. It is not yet possible to develop such compounds using computational (i.e., in silico) approach and instead the lead molecules are discovered in high-throughput screening searches of large compound libraries. The main reason why in silico methods are not capable to deliver is our poor understanding of the compound structure-thermodynamics and structure-kinetics correlations. There is a need for databases of intrinsic binding parameters (e.g., the change upon binding in standard Gibbs energy (ΔGint), enthalpy (ΔHint), entropy (ΔSint), volume (ΔVintr), heat capacity (ΔCp,int), association rate (ka,int), and dissociation rate (kd,int)) between a series of closely related proteins and a chemically diverse, but pharmacophoric group-guided library of compounds together with the co-crystal structures that could help explain the structure-energetics correlations and rationally design novel compounds. Assembly of these data will facilitate attempts to provide correlations and train data for modeling of compound binding. Here, we report large datasets of the intrinsic thermodynamic and kinetic data including over 400 primary sulfonamide compound binding to a family of 12 catalytically active human carbonic anhydrases (CA). Thermodynamic parameters have been determined by the fluorescent thermal shift assay, isothermal titration calorimetry, and by the stopped-flow assay of the inhibition of enzymatic activity. Kinetic measurements were performed using surface plasmon resonance. Intrinsic thermodynamic and kinetic parameters of binding were determined by dissecting the binding-linked protonation reactions of the protein and sulfonamide. The compound structure-thermodynamics and kinetics correlations reported here helped to discover compounds that exhibited picomolar affinities, hour-long residence times, and million-fold selectivities over non-target CA isoforms. Drug-lead compounds are suggested for anticancer target CA IX and CA XII, antiglaucoma CA IV, antiobesity CA VA and CA VB, and other isoforms. Together with 85 X-ray crystallographic structures of 60 compounds bound to six CA isoforms, the database should be of help to continue developing the principles of rational target-based drug design.

Exploring the strength of a hydrogen bond as a function of steric environment using 1,2-azaborine ligands and engineered T4 lysozyme receptors

A congeneric series of 1,2-azaborine ligands was used to study the relationship between the steric demand of the ligand and hydrogen bonding strength in the context of ligand-protein binding using engineered T4 lysozymes as the model biomacromolecules. The hydrogen bonding strength values were extracted from experimentally accessible binding free energies using the Double Mutant Cycle analysis. With the increasing steric demand, the NH…102Q hydrogen bonding interaction is weakened; however, this weakening of the hydrogen bonding interaction occurs in discrete steps rather than in an incremental fashion.

Broad-scale analysis of thermodynamic signatures in medicinal chemistry: are enthalpy-favored binders the better development option?

Thermodynamic profiles of ligand binding, particularly enthalpically favored binding signatures, have been suggested as a criterion to support the decision-making process around which compounds to select for further optimization in drug development. The concept was enthusiastically taken up, but turned out to be too superficial, either because many aspects determining thermodynamic profiles are insufficiently appreciated or because it is difficult to compare such data on a global scale. The impact of water, changes in protonation states, along with buffer dependencies and incompatible measurement conditions that are far from standard conditions hamper such broad-scale comparisons. However, thermodynamic signatures can make us aware of the impact of these aspects and provide important hints for improving our understanding of the binding process and defining criteria for drug optimization.

Application of ITC-Based Characterization of Thermodynamic and Kinetic Association of Ligands With Proteins in Drug Design

A comprehensive characterization of the thermodynamic and kinetic profiling of ligands binding to a given target protein is crucial for the hit selection as well as the hit-to-lead-to-drug evolution. Isothermal titration calorimetry (ITC), widely known as an invaluable tool to measure the thermodynamic data, has recently found its way to determine the binding kinetics too. The extensive application of ITC in measurement of both thermodynamic and kinetic data manifests unique roles of ITC in drug discovery and development. This mini-review concentrates on elaborating how to gain the thermodynamic and kinetic data using ITC, highlighting the importance of these data in lead discovery and optimization, and intends to provide an overview of the technical and conceptual advances that offer unprecedented access to protein–ligand recognition by ITC measurement.

Biophysical, Biochemical, and Cell Based Approaches Used to Decipher the Role of Carbonic Anhydrases in Cancer and to Evaluate the Potency of Targeted Inhibitors

Carbonic anhydrases (CAs) are thought to be important for regulating pH in the tumor microenvironment. A few of the CA isoforms are upregulated in cancer cells, with only limited expression in normal cells. For these reasons, there is interest in developing inhibitors that target these tumor-associated CA isoforms, with increased efficacy but limited nonspecific cytotoxicity. Here we present some of the biophysical, biochemical, and cell based techniques and approaches that can be used to evaluate the potency of CA targeted inhibitors and decipher the role of CAs in tumorigenesis, cancer progression, and metastatic processes. These techniques include esterase activity assays, stop flow kinetics, and mass inlet mass spectroscopy (MIMS), all of which measure enzymatic activity of purified protein, in the presence or absence of inhibitors. Also discussed is the application of X-ray crystallography and Cryo-EM as well as other structure-based techniques and thermal shift assays to the studies of CA structure and function. Further, large-scale genomic and proteomic analytical methods, as well as cell based techniques like those that measure cell growth, apoptosis, clonogenicity, and cell migration and invasion, are discussed. We conclude by reviewing approaches that test the metastatic potential of CAs and how the aforementioned techniques have contributed to the field of CA cancer research.

An update on anticancer drug development and delivery targeting carbonic anhydrase IX

The expression of carbonic anhydrase (CA) IX is up-regulated in many types of solid tumors in humans under hypoxic and acidic microenvironment. Inhibition of CA IX enzymatic activity with selective inhibitors, antibodies or labeled probes has been shown to reverse the acidic environment of solid tumors and reduce the tumor growth establishing the significant role of CA IX in tumorigenesis. Thus, the development of potent antitumor drugs targeting CA IX with minimal toxic effects is important for the target-specific tumor therapy. Recently, several promising antitumor agents against CA IX have been developed to treat certain types of cancers in combination with radiation and chemotherapy. Here we review the inhibition of CA IX by small molecule compounds and monoclonal antibodies. The methods of enzymatic assays, biophysical methods, animal models including zebrafish and Xenopus oocytes, and techniques of diagnostic imaging to detect hypoxic tumors using CA IX-targeted conjugates are discussed with the aim to overview the recent progress related to novel therapeutic agents that target CA IX in hypoxic tumors.

Quantitative Characterization of the Binding and Unbinding of Millimolar Drug Fragments with Molecular Dynamics Simulations

A quantitative characterization of the binding properties of drug fragments to a target protein is an important component of a fragment-based drug discovery program. Fragments typically have a weak binding affinity, however, making it challenging to experimentally characterize key binding properties, including binding sites, poses, and affinities. Direct simulation of the binding equilibrium by molecular dynamics (MD) simulations can provide a computational route to characterize fragment binding, but this approach is so computationally intensive that it has thus far remained relatively unexplored. Here, we perform MD simulations of sufficient length to observe several different fragments spontaneously and repeatedly bind to and unbind from the protein FKBP, allowing the binding affinities, on- and off-rates, and relative occupancies of alternative binding sites and alternative poses within each binding site to be estimated, thereby illustrating the potential of long time scale MD as a quantitative tool for fragment-based drug discovery. The data from the long time scale fragment binding simulations reported here also provide a useful benchmark for testing alternative computational methods aimed at characterizing fragment binding properties. As an example, we calculated binding affinities for the same fragments using a standard free energy perturbation approach and found that the values agreed with those obtained from the fragment binding simulations within statistical error.

Physicochemical Evidence on Sublethal Neonicotinoid Imidacloprid Interacting with an Odorant-Binding Protein from the Tea Geometrid Moth, Ectropis obliqua

Nowadays the excessive usage of neonicotinoid insecticides always results in residues in Chinese tea fields. It is not clear whether the insecticide residue at the sublethal level influences the physiological processes of tea pests. Here, we provide evidence of interaction between the neonicotinoid imidacloprid and a general odorant-binding protein, EoblGOBP2, from the tea geometrid moth, Ectropis obliqua. The interacting process was demonstrated through multiple fluorescence spectra, UV absorption spectra, circular dichroism (CD) spectra, molecular docking, etc. The binding mode was determined to be static (from 300 to 310 K) and dynamic quenching (from 290 to 300 K). The binding distance was calculated to be 6.9 nm on the basis of FRET theory. According to the thermodynamic analysis, the process was mainly driven by enthalpy (ΔH < 0), and hydrogen bond and van der Waals interactions were the main driving forces in the static and dynamic binding cases, respectively. Moreover, synchronous fluorescence spectra and CD spectra analysis showed stretching of the EoblGOBP2 peptide chains with a decreasing α-helix when imidacloprid was added. Molecular docking was applied and predicted that two hydrogen bonds were formed between imidacloprid and Arg110 in the mature peptide of EoblGOBP2. Moreover, when the absolute amounts of EoblGOBP2 in the moth antennae were measured and calculated by using real-time PCR, it was estimated that imidacloprid at sublethal level (about 0.233 and 0.175 ng/male and female moth antennae, respectively) inhibited the binding of a tea volatile, E-2-hexenal, to EoblGOBP2 at about half. This study indicates that neonicotinoid insecticide at sublethal level may still affect the olfactory cognition of the tea geometrid moth to volatile compounds from tea leaves.

Interaction of human serum albumin with uremic toxins: a thermodynamic study

Interaction of uremic toxins with HSA is studied by ITC and understood in terms of thermodynamic driving forces.

Binding thermodynamics discriminates fragments from druglike compounds: a thermodynamic description of fragment-based drug discovery

Small is beautiful - reducing the size and complexity of chemical starting points for drug design allows better sampling of chemical space, reveals the most energetically important interactions within protein-binding sites and can lead to improvements in the physicochemical properties of the final drug. The impact of fragment-based drug discovery (FBDD) on recent drug discovery projects and our improved knowledge of the structural and thermodynamic details of ligand binding has prompted us to explore the relationships between ligand-binding thermodynamics and FBDD. Information on binding thermodynamics can give insights into the contributions to protein-ligand interactions and could therefore be used to prioritise compounds with a high degree of specificity in forming key interactions.

Analysis of multitemperature isothermal titration calorimetry data at very low c: Global beats van't Hoff

Isothermal titration calorimetry data for very low c (≡K[M]0) must normally be analyzed with the stoichiometry parameter n fixed - at its known value or at any reasonable value if the system is not well characterized. In the latter case, ΔH° (and hence n) can be estimated from the T-dependence of the binding constant K, using the van't Hoff (vH) relation. An alternative is global or simultaneous fitting of data at multiple temperatures. In this Note, global analysis of low-c data at two temperatures is shown to estimate ΔH° and n with double the precision of the vH method.

Applications of isothermal titration calorimetry - the research and technical developments from 2011 to 2015

Isothermal titration calorimetry is a widely used biophysical technique for studying the formation or dissociation of molecular complexes. Over the last 5 years, much work has been published on the interpretation of isothermal titration calorimetry (ITC) data for single binding and multiple binding sites. As over 80% of ITC papers are on macromolecules of biological origin, this interpretation is challenging. Some researchers have attempted to link the thermodynamics constants to events at the molecular level. This review highlights work carried out using binding sites characterized using x-ray crystallography techniques that allow speculation about individual bond formation and the displacement of individual water molecules during ligand binding and link these events to the thermodynamic constants for binding. The review also considers research conducted with synthetic binding partners where specific binding events like anion-π and π-π interactions were studied. The revival of assays that enable both thermodynamic and kinetic information to be collected from ITC data is highlighted. Lastly, published criticism of ITC research from a physical chemistry perspective is appraised and practical advice provided for researchers unfamiliar with thermodynamics and its interpretation. Copyright © 2016 John Wiley & Sons, Ltd.