Antipsychotic haloperidol binding to the human dopamine D3 receptor: beyond docking through QM/MM refinement toward the design of improved schizophrenia medicines

Chronic treatment with D2-antagonist haloperidol leads to inhibitory/excitatory imbalance in striatal D1-neurons

Striatal dysfunction has been implicated in the pathophysiology of schizophrenia, a disorder characterized by positive symptoms such as hallucinations and delusions. Haloperidol is a typical antipsychotic medication used in the treatment of schizophrenia that is known to antagonize dopamine D2 receptors, which are abundantly expressed in the striatum. However, haloperidol's delayed therapeutic effect also suggests a mechanism of action that may go beyond the acute blocking of D2 receptors. Here, we performed proteomic analysis of striatum brain tissue and found more than 400 proteins significantly altered after 30 days of chronic haloperidol treatment in mice, namely proteins involved in glutamatergic and GABAergic synaptic transmission. Cell-type specific electrophysiological recordings further revealed that haloperidol not only reduces the excitability of striatal medium spiny neurons expressing dopamine D2 receptors (D2-MSNs) but also affects D1-MSNs by increasing the ratio of inhibitory/excitatory synaptic transmission (I/E ratio) specifically onto D1-MSNs but not D2-MSNs. Therefore, we propose the slow remodeling of D1-MSNs as a mechanism mediating the delayed therapeutic effect of haloperidol over striatum circuits. Understanding how haloperidol exactly contributes to treating schizophrenia symptoms may help to improve therapeutic outcomes and elucidate the molecular underpinnings of this disorder.

Quantum biochemistry description of PI3Kα enzyme bound to selective inhibitors

The PI3K class I is composed of four PI3K isoforms that serve as regulatory enzymes governing cellular metabolism, proliferation, and survival. The hyperactivation of PI3Kα is observed in various types of cancer and is linked to poor prognosis. Unfortunately, the development inhibitors selectively targeting one of the isoforms remains challenging, with only few agents in clinical use. The main difficulty arises from the high conservation among residues at the ATP-binding pocket across isoforms, which also serves as target pocket for inhibitors. In this work, molecular dynamics and quantum calculations were performed to investigate the molecular features guiding the binding of selective inhibitors, alpelisib and GDC-0326, into the ATP-binding pocket of PI3Kα. While molecular dynamics allowed crystallographic coordinates to relax, the interaction eergy between each amino acid residues and inhibitors was obtained by combining the Molecular Fractionation with Conjugated Caps scheme with Density Functional Theory calculations. In addition, the atomic charge of ligands in the bound and unbound (free) was calculated. Results indicated that the most relevant residues for the binding of alpelisib are Ile932, Glu859, Val851, Val850, Tyr836, Met922, Ile800, and Ile848, while the most important residues for the binding of GDC-0326 are Ile848, Ile800, Ile932, Gln859, Glu849, and Met922. In addition, residues Trp780, Ile800, Tyr836, Ile848, Gln859 Val850, Val851, Ile932 and Met922 are common hotspots for both inhibitors. Overall, the results from this work contribute to improving the understanding of the molecular mechanisms controlling selectivity and highlight important interactions to be considered during the rational design of new agents.Communicated by Ramaswamy H. Sarma.

Approach to the specificity and selectivity between D2 and D3 receptors by mutagenesis and binding experiments part I: Expression and characterization of D2 and D3 receptor mutants

D3/D2 sub-specificity is a complex problem to solve. Indeed, in the absence of easy structural biology of the G-protein coupled receptors, and despite key progresses in this area, the systematic knowledge of the ligand/receptor relationship is difficult to obtain. Due to these structural biology limitations concerning membrane proteins, we favored the use of directed mutagenesis to document a rational towards the discovery of markedly specific D3 ligands over D2 ligands together with basic binding experiments. Using our methodology of stable expression of receptors in HEK cells, we constructed the gene encoding for 24 mutants and 4 chimeras of either D2 or D3 receptors and expressed them stably. Those cell lines, expressing a single copy of one receptor mutant each, were stably constructed, selected, amplified and the membranes from them were prepared. Binding data at those receptors were obtained using standard binding conditions for D2 and D3 dopamine receptors. We generated 26 new molecules derived from D2 or D3 ligands. Using 8 reference compounds and those 26 molecules, we characterized their binding at those mutants and chimeras, exemplifying an approach to better understand the difference at the molecular level of the D2 and D3 receptors. Although all the individual results are presented and could be used for minute analyses, the present report does not discuss the differences between D2 and D3 data. It simply shows the feasibility of the approach and its potential.

Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.

Losartan as an ACE inhibitor: a description of the mechanism of action through quantum biochemistry

Losartan (LST) is a potent and selective angiotensin II (Ang II) type 1 (AT1) receptor antagonist widely used in the treatment of hypertension. The formation of Ang II is catalyzed by the angiotensin I-converting enzyme (ACE) through proteolytic cleavage of angiotensin I (Ang I), which is involved in the control of blood pressure. Despite the vast literature on the relationship of losartan with the renin-angiotensin system (RAS), the actions of losartan on the sACE enzyme are so far poorly understood. In view of this, we investigated how losartan can interact with the sACE enzyme to block its activity and intracellular signaling. After performing docking assays following quantum biochemistry calculations using losartan and sACE crystallographic data, we report that their interaction results reveal a new mechanism of action with important implications for understanding its effects on hypertension.

Computational methods for calculation of protein-ligand binding affinities in structure-based drug design

Drug design is an expensive and time-consuming process. Any method that allows reducing the time the costs of the drug development project can have great practical value for the pharmaceutical industry. In structure-based drug design, affinity prediction methods are of great importance. The majority of methods used to predict binding free energy in protein-ligand complexes use molecular mechanics methods. However, many limitations of these methods in describing interactions exist. An attempt to go beyond these limits is the application of quantum-mechanical description for all or only part of the analyzed system. However, the extensive use of quantum mechanical (QM) approaches in drug discovery is still a demanding challenge. This chapter briefly reviews selected methods used to calculate protein-ligand binding affinity applied in virtual screening (VS), rescoring of docked poses, and lead optimization stage, including QM methods based on molecular simulations.

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.

Quantum Biochemical Investigation of Lys49-PLA2 from Bothrops moojeni

Envenomation via snakebites occurs largely in areas where it is harder to access the hospital. Its mortality rate and sequelae acquired by the survivors symbolize a big challenge for antivenom therapy. In particular, the homologous phospholipase A₂ (Lys49-PLA₂) proteins can induce myonecrosis and are not effectively neutralized by current treatments. Thus, by taking advantage of crystallographic structures of Bothrops moojeni Lys49-PLA₂ complexed with VRD (varespladib) and AIN (aspirin), a quantum biochemistry study based on the molecular fractionation with conjugate cap scheme within the density functional theory formalism is performed to unveil these complexes' detailed interaction energies. The calculations revealed that important interactions between ligands and the Lys49-PLA₂ pocket could occur up to a pocket radius of r = 6.5 (5.0 Å) for VRD (AIN), with the total interaction energy of the VRD ligand being higher than that of the AIN ligand, which is well-correlated with the experimental binding affinity. Furthermore, we have identified the role played by the amino acids LYS0069, LYS0049, LEU0005, ILE0009, CYS0029, GLY0030, HIS0048, PRO0018, ALA0019, CYS0045, TYR0052, TYR0022, PRO0125*, and PHE0126* (LYS0069, LYS0049, GLY0032, LEU0002, and LEU0005) in the VRD↔Lys49-PLA₂ (AIN↔Lys49-PLA₂) complex. Our simulations are a valuable tool to support the big challenge for neutralizing the damages in victims of snakebites.

Antioxidant Potential of Psychotropic Drugs: From Clinical Evidence to In Vitro and In Vivo Assessment and toward a New Challenge for in Silico Molecular Design

Due to high oxygen consumption, the brain is particularly vulnerable to oxidative stress, which is considered an important element in the etiopathogenesis of several mental disorders, including schizophrenia, depression and dependencies. Despite the fact that it is not established yet whether oxidative stress is a cause or a consequence of clinic manifestations, the intake of antioxidant supplements in combination with the psychotropic therapy constitutes a valuable solution in patients' treatment. Anyway, some drugs possess antioxidant capacity themselves and this aspect is discussed in this review, focusing on antipsychotics and antidepressants. In the context of a collection of clinical observations, in vitro and in vivo results are critically reported, often highlighting controversial aspects. Finally, a new challenge is discussed, i.e., the possibility of assessing in silico the antioxidant potential of these drugs, exploiting computational chemistry methodologies and machine learning. Despite the physiological environment being incredibly complex and the detection of meaningful oxidative stress biomarkers being all but an easy task, a rigorous and systematic analysis of the structural and reactivity properties of antioxidant drugs seems to be a promising route to better interpret therapeutic outcomes and provide elements for the rational design of novel drugs.

Markov State Model Analysis of Haloperidol Binding to the D3 Dopamine Receptor

We have developed Markov state models (MSMs) and hidden Markov models (HMMs) that describe the binding of haloperidol to the D₃ dopamine receptor. Haloperidol is an antipsychotic drug that binds with nanomolar affinity to the D₃ dopamine receptor, where it functions as an inverse agonist. The models were constructed using an adaptive sampling approach from 519 individual molecular dynamics simulations totaling 122 μs of simulated time and encompass the entire drug binding process. They reveal short-lived metastable bound states and two distinct long-lived bound conformations that cannot be separated in affinity using our current methodology. This work extends the use of MSMs and HMMs to study ligand binding, which thus far has been limited to simpler systems.

Multiscale Molecular Modeling in G Protein-Coupled Receptor (GPCR)-Ligand Studies

G protein-coupled receptors (GPCRs) are major drug targets due to their ability to facilitate signal transduction across cell membranes, a process that is vital for many physiological functions to occur. The development of computational technology provides modern tools that permit accurate studies of the structures and properties of large chemical systems, such as enzymes and GPCRs, at the molecular level. The advent of multiscale molecular modeling permits the implementation of multiple levels of theories on a system of interest, for instance, assigning chemically relevant regions to high quantum mechanics (QM) level of theory while treating the rest of the system using classical force field (molecular mechanics (MM) potential). Multiscale QM/MM molecular modeling have far-reaching applications in the rational design of GPCR drugs/ligands by affording precise ligand binding configurations through the consideration of conformational plasticity. This enables the identification of key binding site residues that could be targeted to manipulate GPCR function. This review will focus on recent applications of multiscale QM/MM molecular simulations in GPCR studies that could boost the efficiency of future structure-based drug design (SBDD) strategies.

User-Friendly Quantum Mechanics: Applications for Drug Discovery

Quantum mechanics (QM) methods provide a fine description of receptor-ligand interactions and of chemical reactions. Their use in drug design and drug discovery is increasing, especially for complex systems including metal ions in the binding sites, for the design of highly selective inhibitors, for the optimization of bi-specific compounds, to understand enzymatic reactions, and for the study of covalent ligands and prodrugs. They are also used for generating molecular descriptors for predictive QSAR/QSPR models and for the parameterization of force fields. Thanks to the continuous increase of computational power offered by GPUs and to the development of sophisticated algorithms, QM methods are becoming part of the standard tools used in computer-aided drug design (CADD). We present the most used QM methods and software packages, and we discuss recent representative applications in drug design and drug discovery.

The urokinase plasminogen activator binding to its receptor: a quantum biochemistry description within an in/homogeneous dielectric function framework with application to uPA–uPAR peptide inhibitors

DFT calculations using the MFCC fragment-based model considering a spatial-dependent dielectric function based on the Poisson–Boltzmann approximation were performed to describe the uPA–uPAR interactions.

mTOR–mLST8 interaction: hot spot identification through quantum biochemistry calculations

Quantum calculation of mTOR–mLST8 interaction.

3D-QSAR studies of D3R antagonists and 5-HT1AR agonists

Combination of dopamine D₃ antagonism and serotonin 5-HT_1A agonism leads to an effective way to atypical antipsychotics. In this work, two predictive 3D-QSAR models were bulit for D₃R antagonists and 5-HT_1AR agonists, respectively. Based on the steric and electrostatic information of contour maps, four compounds with improved predicted activities were newly designed. In addition, molecular docking and ADMET properties suggested that designed molecules had strong interactions with receptors and low hepatotoxicity. This work sheds light on the design of bifunctional novel antipsychotic drugs for D₃R antagonists and 5HT_1AR agonists.

Vitamin B₆ and Its Role in Cell Metabolism and Physiology

Vitamin B₆ is one of the most central molecules in cells of living organisms. It is a critical co-factor for a diverse range of biochemical reactions that regulate basic cellular metabolism, which impact overall physiology. In the last several years, major progress has been accomplished on various aspects of vitamin B₆ biology. Consequently, this review goes beyond the classical role of vitamin B₆ as a cofactor to highlight new structural and regulatory information that further defines how the vitamin is synthesized and controlled in the cell. We also discuss broader applications of the vitamin related to human health, pathogen resistance, and abiotic stress tolerance. Overall, the information assembled shall provide helpful insight on top of what is currently known about the vitamin, along with addressing currently open questions in the field to highlight possible approaches vitamin B₆ research may take in the future.

Schizophrenia: synthetic strategies and recent advances in drug design

Schizophrenia is a complex and unpredictable mental disorder which affects several domains of cognition and behaviour. It is a heterogeneous illness characterised by positive, negative, and cognitive symptoms, often accompanied by signs of depression. In this tutorial review, we discuss recent progress in understanding the target sites and mechanisms of action of second-generation antipsychotic drugs. Progress in identifying and defining target sites has been accelerated recently by advances in neuroscience, and newly developed agents that regulate signalling by the main excitatory neurotransmitters in the brain are surveyed. Examples of novel molecules for the treatment of schizophrenia in preclinical and clinical development and their industrial sponsors are highlighted.

Dopamine D3 receptor antagonist reveals a cryptic pocket in aminergic GPCRs

The recent increase in the number of X-ray crystal structures of G-protein coupled receptors (GPCRs) has been enabling for structure-based drug design (SBDD) efforts. These structures have revealed that GPCRs are highly dynamic macromolecules whose function is dependent on their intrinsic flexibility. Unfortunately, the use of static structures to understand ligand binding can potentially be misleading, especially in systems with an inherently high degree of conformational flexibility. Here, we show that docking a set of dopamine D3 receptor compounds into the existing eticlopride-bound dopamine D3 receptor (D3R) X-ray crystal structure resulted in poses that were not consistent with results obtained from site-directed mutagenesis experiments. We overcame the limitations of static docking by using large-scale high-throughput molecular dynamics (MD) simulations and Markov state models (MSMs) to determine an alternative pose consistent with the mutation data. The new pose maintains critical interactions observed in the D3R/eticlopride X-ray crystal structure and suggests that a cryptic pocket forms due to the shift of a highly conserved residue, F^6.52. Our study highlights the importance of GPCR dynamics to understand ligand binding and provides new opportunities for drug discovery.

da Silva JJ, dos Santos RCR, Sales FAM, Gottfried C, S. Caetano EW, Freire VN. First-generation antipsychotic haloperidol: optical absorption measurement and structural, electronic, and optical properties of its anhydrous monoclinic crystal by first-principle approaches

Application of the Density Functional Theory for the structural, electronic and optical properties of haloperidol crystal.

Computational investigation of the α2β1 integrin–collagen triple helix complex interaction

In this paper, quantum biochemistry methods have been used to describe important protein–protein interactions for the complex integrin–collagen.

Outlining migrainous through dihydroergotamine–serotonin receptor interactions using quantum biochemistry

We present the electronic structure of the complex dihydroergotamine–serotonin receptor to unveil new medications to treat migraine and related diseases.

An improved quantum biochemistry description of the glutamate–GluA2 receptor binding within an inhomogeneous dielectric function framework

A new methodology to define the inhomogeneous dielectric constant of protein residues, to apply to the calculation of protein–ligand properties such as the electrostatic interaction.

Two Binding Geometries for Risperidone in Dopamine D3 Receptors: Insights on the Fast-Off Mechanism through Docking, Quantum Biochemistry, and Molecular Dynamics Simulations

Risperidone is an atypical antipsychotic used in the treatment of schizophrenia and of symptoms of irritability associated with autism spectrum disorder (ASD). Its main action mechanism is the blockade of D2-like receptors acting over positive and negative symptoms of schizophrenia with small risk of extrapyramidal symptoms (EPS) at doses corresponding to low/moderate D2 occupancy. Such a decrease in the side effect incidence can be associated with its fast unbinding from D2 receptors in the nigrostriatal region allowing the recovery of dopamine signaling pathways. We performed docking essays using risperidone and the D3 receptor crystallographic data and results suggested two possible distinct orientations for risperidone at the binding pocket. Orientation 1 is more close to the opening of the binding site and has the 6-fluoro-1,2 benzoxazole fragment toward the bottom of the D3 receptor cleft, while orientation 2 is deeper inside the binding pocket with the same fragment toward to the receptor surface. In order to unveil the implications of these two binding orientations, classical molecular dynamics and quantum biochemistry computations within the density functional theory formalism and the molecular fractionation with conjugate caps framework were performed. Quantum mechanics/molecular mechanics suggests that orientation 2 (considering the contribution of Glu90) is slightly more energetically stable than orientation 1 with the main contribution coming from residue Asp110. The residue Glu90, positioned at the opening of the binding site, is closer to orientation 1 than 2, suggesting that it may have a key role in stability through attractive interaction with risperidone. Therefore, although orientations 1 and 2 are both likely to occur, we suggest that the occurrence of the first may contribute to the reduction of side effects in patients taking risperidone due to the reduction of dopamine receptor occupancy in the nigrostriatal region through a mechanism of fast dissociation. The atypical effect may be obtained simply by either delaying D3R full blockage by spatial hindrance of orientation 1 at the binding site or through an effective blockade followed by orientation 1 fast dissociation. While the molecular interpretation suggested in this work shed some light on the potential molecular mechanisms accounting for the reduced extrapyramidal symptoms observed during risperidone treatment, further studies are necessary in order to evaluate the implications of both orientations during the receptor activation/inhibition. Altogether these data highlight important hot spots in the dopamine receptor binding site bringing relevant information for the development of novel/derivative agents with atypical profile.

Computational Study and Modified Design of Selective Dopamine D3 Receptor Agonists

Dopamine D3 receptor (D3 R) is considered as a potential target for the treatment of nervous system disorders, such as Parkinson's disease. Current research interests primarily focus on the discovery and design of potent D3 agonists. In this work, we selected 40 D3 R agonists as the research system. Comparative molecular field analysis (CoMFA) of three-dimensional quantitative structure-activity relationship (3D-QSAR), structure-selectivity relationship (3D-QSSR), and molecular docking was performed on D3 receptor agonists to obtain the details at atomic level. The results indicated that both the CoMFA model (r(2) = 0.982, q(2) = 0.503, rpred2 = 0.893, SEE  = 0.057, F = 166.308) for structure-activity and (r(2) = 0.876, q(2) = 0.436, rpred2 = 0.828, F = 52.645) for structure-selectivity have good predictive capabilities. Furthermore, docking studies on three compounds binding to D3 receptor were performed to analyze the binding modes and interactions. The results elucidate that agonists formed hydrogen bond and hydrophobic interactions with key residues. Finally, we designed six molecules under the guidance of 3D-QSAR/QSSR models. The activity and selectivity of designed molecules have been improved, and ADMET properties demonstrate they have low probability of hepatotoxicity (<0.5). These results from 3D-QSAR/QSSR and docking studies have great significance for designing novel dopamine D3 selective agonists in the future.

Ligand Binding Pathways of Clozapine and Haloperidol in the Dopamine D2 and D3 Receptors

The binding of a small molecule ligand to its protein target is most often characterized by binding affinity and is typically viewed as an on/off switch. The more complex reality is that binding involves the ligand passing through a series of intermediate states between the solution phase and the fully bound pose. We have performed a set of 29 unbiased molecular dynamics simulations to model the binding pathways of the dopamine receptor antagonists clozapine and haloperidol binding to the D2 and D3 dopamine receptors. Through these simulations we have captured the binding pathways of clozapine and haloperidol from the extracellular vestibule to the orthosteric binding site and thereby, we also predict the bound pose of each ligand. These are the first long time scale simulations of haloperidol or clozapine binding to dopamine receptors. From these simulations, we have identified several important stages in the binding pathway, including the involvement of Tyr7.35 in a "handover" mechanism that transfers the ligand between the extracellular vestibule and Asp3.32. We have also performed interaction and cluster analyses to determine differences in binding pathways between the D2 and D3 receptors and identified metastable states that may be of use in drug design.

Explaining RANKL inhibition by OPG through quantum biochemistry computations and insights into peptide-design for the treatment of osteoporosis

Quantum biochemistry computations are applied to precisely describe important protein–protein interactions, providing a basis for the design of inhibitory peptides against osteoporosis.

Multicomponent Synthesis and Biological Evaluation of a Piperazine-Based Dopamine Receptor Ligand Library

A series of 1,4-disubstituted piperazine-based compounds were designed, synthesized, and evaluated as dopamine D2/D3 receptor ligands. The synthesis relies on the key multicomponent split-Ugi reaction, assessing its great potential in generating chemical diversity around the piperazine core. With the aim of evaluating the effect of such diversity on the dopamine receptor affinity, a small library of compounds was prepared, applying post-Ugi transformations. Ligand stimulated binding assays indicated that some compounds show a significant affinity, with K i values up to 53 nM for the D2 receptor. Molecular docking studies with the D2 and D3 receptor homology models were also performed on selected compounds. They highlighted key interactions at the indole head and at the piperazine moiety, which resulted in good agreement with the known pharmacophore models, thus helping to explain the observed structure-activity relationship data. Molecular insights from this study could enable a rational improvement of the split-Ugi primary scaffold, toward more selective ligands.

Quantum molecular modelling of ibuprofen bound to human serum albumin

The total interaction energies of the ibuprofen complexed with FA3/FA4 and FA6 binding sites of human serum albumin are in agreement with the hypothesis that the Sudlow's site II is the main binding pocket for ibuprofen.