Amide isomerization pathways: Electronic and structural background of protonation- and deprotonation-mediated cis-trans interconversions.

The cis-trans isomerization of amide bonds leads to wide range of structural and functional changes in proteins and can easily be the rate-limiting step in folding. The trans isomer is thermodynamically more stable than the cis, nevertheless the cis form can play a role in biopolymers' function. The molecular system of N-methylacetamide · 2H2O is complex enough to reveal energetics of the cis-trans isomerization at coupled cluster single-double and coupled cluster single-double and perturbative triple [CCSD(T)] levels of theory. The cis-trans isomerization cannot be oversimplified by a rotation along ω, since this rotation is coupled with the N-atom pyramidal inversion, requesting the introduction of a second dihedral angle "α." Full f(ω,α) potential energy surfaces of the different amide protonation states, critical points and isomerization reaction paths were determined, and the barriers of the neutral, O-protonated and N-deprotonated amides were found too high to allow cis-trans interconversion at room temperature: ∼85, ∼140, and ∼110 kJ mol-1, respectively. For the N-protonated amide bond, the cis form (ω = 0°) is a maximum rather than a minimum, and each ω state is accessible for less than ∼10 kJ mol-1. Here we outline a cis-trans isomerization pathway with a previously undescribed low energy transition state, which suggests that the proton is transferred from the more favorable O- to the N-protonation site with the aid of nearby water molecules, allowing the trans → cis transition to occur at an energy cost of ≤11.6 kJ mol-1. Our results help to explain why isomerase enzymes operate via protonated amide bonds and how N-protonation of the peptide bond occurs via O-protonation.

Fragment evolution for GPCRs: the role of secondary binding sites in optimization.

We developed a docking-based fragment evolution approach that extends orthosteric fragments towards a less conserved secondary binding pocket of GPCRs. Evaluating 13 000 extensions for the ß1- and ß2-adrenergic receptors we synthesized and tested 112 bitopic molecules. Our results confirmed the positive contribution of the secondary binding pocket to both potency and selectivity optimizations.

Controlling the selectivity of aminergic GPCR ligands from the extracellular vestibule.

In addition to the orthosteric binding pocket (OBP) of GPCRs, recent structural studies have revealed that there are several allosteric sites available for pharmacological intervention. The secondary binding pocket (SBP) of aminergic GPCRs is located in the extracellular vestibule of these receptors, and it has been suggested to be a potential selectivity pocket for bitopic ligands. Here, we applied a virtual screening protocol based on fragment docking to the SBP of the orthosteric ligand-receptor complex. This strategy was employed for a number of aminergic receptors. First, we designed dopamine D3 preferring bitopic compounds from a D2 selective orthosteric ligand. Next, we designed 5-HT2B selective bitopic compounds starting from the 5-HT1B preferring ergoline core of LSD. Comparing the serotonergic profiles of the new derivatives to that of LSD, we found that these derivatives became significantly biased towards the desired 5-HT2B receptor target. Finally, addressing the known limitations of H1 antihistamines, our protocol was successfully used to eliminate the well-known side effects related to the muscarinic M1 activity of amitriptyline while preserving H1 potency in some of the designed bitopic compounds. These applications highlight the usefulness of our new virtual screening protocol and offer a powerful strategy towards bitopic GPCR ligands with designed receptor profiles.

Cysteine specific bioconjugation with benzyl isothiocyanates.

Protein labelling has a wide variety of applications in medicinal chemistry and chemical biology. In addition to covalent inhibition, specific labelling of biomolecules with fluorescent dyes is important in both target discovery, validation and diagnostics. Our research was conducted through the fragment-based development of a new benzyl-isothiocyanate-activated fluorescent dye based on the fluorescein scaffold. This molecule was evaluated against fluorescein isothiocyanate, a prevalent labelling agent. The reactivity and selectivity of phenyl- and benzyl isothiocyanate were compared at different pHs, and their activity was tested on several protein targets. Finally, the clinically approved antibody trastuzumab (and it's Fab fragment) were specifically labelled through reaction with free cysteines reductively liberated from their interchain disulfide bonds. The newly developed benzyl-fluorescein isothiocyanate and its optimized labelling protocol stands to be a valuable addition to the tool kit of chemical biology.

Reproducibility of biomarker identifications from mass spectrometry proteomic data in cancer studies.

Reproducibility of disease signatures and clinical biomarkers in multi-omics disease analysis has been a key challenge due to a multitude of factors. The heterogeneity of the limited sample, various biological factors such as environmental confounders, and the inherent experimental and technical noises, compounded with the inadequacy of statistical tools, can lead to the misinterpretation of results, and subsequently very different biology. In this paper, we investigate the biomarker reproducibility issues, potentially caused by differences of statistical methods with varied distribution assumptions or marker selection criteria using Mass Spectrometry proteomic ovarian tumor data. We examine the relationship between effect sizes, p values, Cauchy p values, False Discovery Rate p values, and the rank fractions of identified proteins out of thousands in the limited heterogeneous sample. We compared the markers identified from statistical single features selection approaches with machine learning wrapper methods. The results reveal marked differences when selecting the protein markers from varied methods with potential selection biases and false discoveries, which may be due to the small effects, different distribution assumptions, and p value type criteria versus prediction accuracies. The alternative solutions and other related issues are discussed in supporting the reproducibility of findings for clinical actionable outcomes.

Synthesis and Biochemical Evaluation of Lid-Open D-Amino Acid Oxidase Inhibitors.

Most of the known inhibitors of D-amino acid oxidase (DAAO) are small polar molecules recognized by the active site of the enzyme. More recently a new class of DAAO inhibitors has been disclosed that interacts with loop 218-224 at the top of the binding pocket. These compounds have a significantly larger size and more beneficial physicochemical properties than most reported DAAO inhibitors, however, their structure-activity relationship is poorly explored. Here we report the synthesis and evaluation of this type of DAAO inhibitors that open the lid over the active site of DAAO. In order to collect relevant SAR data we varied two distinct parts of the inhibitors. A systematic variation of the pendant aromatic substituents according to the Topliss scheme resulted in DAAO inhibitors with low nanomolar activity. The activity showed low sensitivity to the substituents investigated. The variation of the linker connecting the pendant aromatic moiety and the acidic headgroup revealed that the interactions of the linker with the enzyme were crucial for achieving significant inhibitory activity. Structures and activities were analyzed based on available X-ray structures of the complexes. Our findings might support the design of drug-like DAAO inhibitors with advantageous physicochemical properties and ADME profile.

Spiro[pyrrolidine-3,3'-oxindoles] as 5-HT7 receptor ligands.

Here we report the design and synthesis of spiro[pyrrolidine-3,3'-oxindole] derivatives representing a novel scaffold of 5-HT7 receptor ligands. The synthesized analogues were validated as low nanomolar ligands showing selectivity in a panel of related serotonin receptor subtypes including 5-HT1AR, 5-HT2AR and 5-HT6R.

Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands.

The identification of subtype-selective GPCR (G-protein coupled receptor) ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HT2BR versus 5-HT1BR selectivity. Our approach employs the hierarchical combination of machine learning methods, docking, and multiple scoring methods. First, we applied machine learning tools to filter a large database of druglike compounds by the new Neighbouring Substructures Fingerprint (NSFP). This two-dimensional fingerprint contains information on the connectivity of the substructural features of a compound. Preselected subsets of the database were then subjected to docking calculations. The main indicators of compounds' selectivity were their different interactions with the secondary binding pockets of both target proteins, while binding modes within the orthosteric binding pocket were preserved. The combined methodology of ligand-based and structure-based methods was validated prospectively, resulting in the identification of hits with nanomolar affinity and ten-fold to ten thousand-fold selectivities.

Spiro[pyrrolidine-3,3'-oxindoles] and Their Indoline Analogues as New 5-HT6 Receptor Chemotypes.

Synthetic derivatives of spiro[pyrrolidinyl-3,3'-oxindole] alkaloids (coerulescine analogues) were investigated as new ligands for aminergic G-protein coupled receptors (GPCRs). The chemical starting point 2'-phenylspiro[indoline-3,3'-pyrrolidin]-2-one scaffold was identified by virtual fragment screening utilizing ligand- and structure based methods. As a part of the hit-to-lead optimization a structure-activity relationship analysis was performed to explore the differently substituted 2'-phenyl-derivatives, introducing the phenylsulphonyl pharmacophore and examining the corresponding reduced spiro[pyrrolidine-3,3'-indoline] scaffold. The optimization process led to ligands with submicromolar affinities towards the 5-HT6 receptor that might serve as viable leads for further optimization.

Structure-Based Consensus Scoring Scheme for Selecting Class A Aminergic GPCR Fragments.

Aminergic G-protein coupled receptors (GPRCs) represent well-known targets of central nervous-system related diseases. In this study a structure-based consensus virtual screening scheme was developed for designing targeted fragment libraries against class A aminergic GPCRs. Nine representative aminergic GPCR structures were selected by first clustering available X-ray structures and then choosing the one in each cluster that performs best in self-docking calculations. A consensus scoring protocol was developed using known promiscuous aminergic ligands and decoys as a training set. The consensus score (FrACS-fragment aminergic consensus score) calculated for the optimized protein ensemble showed improved enrichments in most cases as compared to stand-alone structures. Retrospective validation was carried out on public screening data for aminergic targets (5-HT1 serotonin receptor, TA1 trace-amine receptor) showing 8-17-fold enrichments using an ensemble of aminergic receptor structures. The performance of the structure based FrACS in combination with our ligand-based prefilter (FrAGS) was investigated both in a retrospective validation on the ChEMBL database and in a prospective validation on an in-house fragment library. In prospective validation virtual fragment hits were tested on 5-HT6 serotonin receptors not involved in the development of FrACS. Six out of the 36 experimentally tested fragments exhibited remarkable antagonist efficacies, and 4 showed IC50 values in the low micromolar or submicromolar range in a cell-based assay. Both retrospective and prospective validations revealed that the methodology is suitable for designing focused class A GPCR fragment libraries from large screening decks, commercial compound collections, or virtual databases.

A desirability function-based scoring scheme for selecting fragment-like class A aminergic GPCR ligands.

A physicochemical property-based desirability scoring scheme for fragment-based drug discovery was developed for class A aminergic GPCR targeted fragment libraries. Physicochemical property distributions of known aminergic GPCR-active fragments from the ChEMBL database were examined and used for a desirability function-based score. Property-distributions such as log D (at pH 7.4), PSA, pKa (strongest basic center), number of nitrogen atoms, number of oxygen atoms, and the number of rotatable bonds were combined into a desirability score (FrAGS). The validation of the scoring scheme was carried out using both public and proprietary experimental screening data. The scoring scheme is suitable for the design of aminergic GPCR targeted fragment libraries and might be useful for preprocessing fragments before structure based virtual or wet screening.