Multicomponent reactions driving the discovery and optimization of agents targeting central nervous system pathologies

• Lucía Campos-Prieto,
• Aitor García-Rey,
• Eddy Sotelo and
• Ana Mallo-Abreu

Beilstein J. Org. Chem. 2024, 20, 3151–3173, doi:10.3762/bjoc.20.261

• EeAChE. On the other hand, the inhibitory activity on eqBuChE was more promising, with the best scoring compounds being 1a, 1b, and 1c (Figure 3). These compounds have mixed inhibitory activity (they can bind both the free enzyme and the enzyme–substrate complex, E–S complex). Additionally, compound 1a

Computational toolbox for the analysis of protein–glycan interactions

• Ferran Nieto-Fabregat,
• Maria Pia Lenza,
• Angela Marseglia,
• Cristina Di Carluccio,
• Antonio Molinaro,
• Alba Silipo and
• Roberta Marchetti

Beilstein J. Org. Chem. 2024, 20, 2084–2107, doi:10.3762/bjoc.20.180

• single model while modelling missing residues de novo. Advances in the scoring function, which is a mix of physics-based and knowledge-based potentials fitted against known structures and thermodynamic observables, have increased the accuracy of predictions. Incorporating experimental data into models

• /building the protein and the ligand in their optimal conformation (as discussed above), ii) predicting the protein binding site; iii) modelling the ligand into the protein binding site, iv) assessing binding affinity through sampling and scoring, as discussed in the following paragraphs [103]. Prediction

• potential ligand conformations. This is followed by the second phase, which focuses on scoring the binding poses obtained during the conformational search. In this phase, the generated ligand–receptor complexes are assessed and ranked based on their binding energy thanks to the use of scoring functions [111

On drug discovery against infectious diseases and academic medicinal chemistry contributions

• Yves L. Janin

Beilstein J. Org. Chem. 2022, 18, 1355–1378, doi:10.3762/bjoc.18.141

• least for the two following quotes: “Due to the inherent inaccuracies of molecular docking, visual inspection of binding modes is a crucial routine in the decision making process of computational medicinal chemists.” and “This suggests that the journey to reliable scoring functions is by far not over

• , as today’s scoring functions are often no match for the complex knowledge and vast experience of computational medicinal chemists.”. In other words, virtually screening millions of compounds appears to still require a completely unrealistic visual checking of each docking solutions. Another recent

Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification

• Steffen Lippold,
• Arnoud H. de Ru,
• Jan Nouta,
• Peter A. van Veelen,
• Magnus Palmblad,
• Manfred Wuhrer and
• Noortje de Haan

Beilstein J. Org. Chem. 2020, 16, 3038–3051, doi:10.3762/bjoc.16.253

• /MS-based scoring software tools such as Byonic [14] are frequently used for glycopeptide identification [12]. Recently, software tools were developed that are based on the retention time (RT) characteristics and accurate mass differences of glycopeptide MS1 signals in RPLC–MS [10][15]. These tools

• glycopeptide identification by GlycopeptideGraphMS. In MS/MS scoring approaches such as Byonic, the definition of a threshold for the automated assignment of glycopeptides is generally a challenge as the scores depend largely on the fragmentation method, the peptide characteristics (e.g., peptide length or

Computational tools for drawing, building and displaying carbohydrates: a visual guide

• Kanhaya Lal,
• Rafael Bermeo and
• Serge Perez

Beilstein J. Org. Chem. 2020, 16, 2448–2468, doi:10.3762/bjoc.16.199

• and the available utilities (codes) helps with the general problems in sampling, scoring, and nomenclature related to glycan modelling. It samples glycosidic bonds, ring forms, side-chain conformations, and utilises a glycan-specific term within its scoring function. The tool also consists of

A proposed sustainability index for synthesis plans based on input provenance and output fate: application to academic and industrial synthesis plans for vanillin as a case study

• John Andraos

Beilstein J. Org. Chem. 2020, 16, 2346–2362, doi:10.3762/bjoc.16.196

• index (SI) computed based on FVI, FVO, FVP, and FRE for the top eight scoring vanillin synthesis plans. Revised summary of overall solvent index (OSI) for various organic solvents used in the pharmaceutical industry. Summary of plan codes, starting materials, and process types for 22 synthesis plans of

Models of necessity

• Timothy Clark and
• Martin G. Hicks

Beilstein J. Org. Chem. 2020, 16, 1649–1661, doi:10.3762/bjoc.16.137

• molecular aggregation via weak interactions. Paradoxically, exactly such interactions between drug molecules and proteins form much of the basis of classical cheminformatics. These are, however, very specific in nature and have generally been defined in detail for, for instance, scoring functions. Current

Anthelmintic drug discovery: target identification, screening methods and the role of open science

• Frederick A. Partridge,
• Ruth Forman,
• Carole J. R. Bataille,
• Graham M. Wynne,
• Marina Nick,
• Angela J. Russell,
• Kathryn J. Else and
• David B. Sattelle

Beilstein J. Org. Chem. 2020, 16, 1203–1224, doi:10.3762/bjoc.16.105

Design and synthesis of diazine-based panobinostat analogues for HDAC8 inhibition

• Sivaraman Balasubramaniam,
• Sajith Vijayan,
• Liam V. Goldman,
• Xavier A. May,
• Kyra Dodson,
• Sweta Adhikari,
• Fatima Rivas,
• Davita L. Watkins and
• Shana V. Stoddard

Beilstein J. Org. Chem. 2020, 16, 628–637, doi:10.3762/bjoc.16.59

• the receptor using the Surflex-Dock Geom (SFXC) protocol [41][42][43] to evaluate the binding affinity of the ligand for the HDAC8 receptor. The C-scoring method was used to calculate these binding affinities and binding scores are given in −log10(Kd) values [45]. Docking simulations where ran

Palladium-catalyzed synthesis and nucleotide pyrophosphatase inhibition of benzo[4,5]furo[3,2-b]indoles

• Hoang Huy Do,
• Saif Ullah,
• Alexander Villinger,
• Joanna Lecka,
• Jean Sévigny,
• Peter Ehlers,
• Jamshed Iqbal and
• Peter Langer

Beilstein J. Org. Chem. 2019, 15, 2830–2839, doi:10.3762/bjoc.15.276

• find docking calculations and scoring functions. Out of 40 conformations for each compound, the conformations with lowest free binding energies and S score were selected for visualization by using Discovery studio visualizer DS [47][48]. X-ray structure determination An X-ray quality crystal of 5d was

Diazirine-functionalized mannosides for photoaffinity labeling: trouble with FimH

• Femke Beiroth,
• Tomas Koudelka,
• Thorsten Overath,
• Stefan D. Knight,
• Andreas Tholey and
• Thisbe K. Lindhorst

Beilstein J. Org. Chem. 2018, 14, 1890–1900, doi:10.3762/bjoc.14.163

• carbohydrate binding site. They are flexible and can be more distant to one another (“open gate”) or closer together (“closed gate”) [20]. Both conformations were considered for the docking studies. For each docked conformation, a scoring value is obtained that correlates with the affinity of the ligand to the

• diazirine 3, with scoring values of −34.7 (open gate) and −36.2 (closed gate), is predicted as suitable FimH ligand with high affinity. Additionally, docking suggests that the diazirine function of 3 is positioned in close proximity to the protein surface, making a specific insertion reaction of the carbene

• formed after irradiation very likely (involving for example Y48 or T51, Figure 4). Docking of mannoside 4 also delivered good scoring values and therefore both photolabile ligands 3 and 4 were synthesized. Synthesis of photolabile mannosides The synthesis of the photolabile mannosides 3 and 4 started

A permutation approach to the assignment of the configuration to diastereomeric tetrads by comparison of experimental and ab initio calculated differences in NMR data

• Przemysław J. Boratyński

Beilstein J. Org. Chem. 2017, 13, 2478–2485, doi:10.3762/bjoc.13.245

• Przemyslaw J. Boratynski Department of Organic Chemistry, Wrocław University of Technology, Wyspiańskiego 27, 50-370 Wrocław, Poland 10.3762/bjoc.13.245 Abstract Scoring permutations of experimental chemical shift deviations and DFT/GIAO calculated deviations of isotropic shieldings for sets of

• atom i in conformer j. An example of scoring of all permutations based on 13C NMR data for tetrad 1 is shown in Table 2 (for all data, see Supporting Information File 1). For all the compounds comparison of the 13C NMR data identified the permutations corresponding to proper configuration assignment

Computational methods in drug discovery

• Sumudu P. Leelananda and
• Steffen Lindert

Beilstein J. Org. Chem. 2016, 12, 2694–2718, doi:10.3762/bjoc.12.267

• ; machine learning; pharmacophore; QSAR; SBDD; scoring; target flexibility; Introduction Bringing a pharmaceutical drug to the market is a long term process that costs billions of dollars. In 2014, the Tufts Center for the Study of Drug Development estimated that the cost associated with developing and

• structure prediction tools that are routinely used in structure-based drug discovery, widely used docking algorithms, scoring functions, virtual high-throughput screening, lead optimization and methods of assessment of ADME properties of drugs. Review Structure-based drug discovery (SBDD) If the three

• stage. Once the models are verified to be acceptable in terms of their stereochemistry, they are then evaluated using 3D profiles or scoring functions that were not used in their generation. It is generally possible to use homology modeling to predict the structure of a protein sequence that has over 40

Discovery of an inhibitor of the production of the Pseudomonas aeruginosa virulence factor pyocyanin in wild-type cells

• Bernardas Morkunas,
• Balint Gal,
• Warren R. J. D. Galloway,
• James T. Hodgkinson,
• Brett M. Ibbeson,
• Yaw Sing Tan,
• Martin Welch and
• David R. Spring

Beilstein J. Org. Chem. 2016, 12, 1428–1433, doi:10.3762/bjoc.12.137

• . Binding poses of OdDHL and compound 4 in OdDHL binding site. Hydrogen bonds are shown in black dotted lines. a) Crystal structure of OdDHL bound to LasR LBD (PDB 2UV0 [31]). b) Top-scoring pose of compound 4 obtained by docking into LasR LBD. Unexpected synthesis of compound 4. The synthesis of 2 was

Effective in silico prediction of new oxazolidinone antibiotics: force field simulations of the antibiotic–ribosome complex supervised by experiment and electronic structure methods

• Jörg Grunenberg and
• Giuseppe Licari

Beilstein J. Org. Chem. 2016, 12, 415–428, doi:10.3762/bjoc.12.45

• , based on scoring functions, are able to tread hundred thousands of candidates in a highly approximate (and sometimes erratic) fashion, alchemical-free energy perturbation (FEP) calculations are also error prone. The predictive power of those FEPs depends on many adjustable parameters, even if the

Are D-manno-configured Amadori products ligands of the bacterial lectin FimH?

• Tobias-Elias Gloe,
• Insa Stamer,
• Cornelia Hojnik,
• Tanja M. Wrodnigg and
• Thisbe K. Lindhorst

Beilstein J. Org. Chem. 2015, 11, 1096–1104, doi:10.3762/bjoc.11.123

• ) scoring function and correlated with the binding affinity of the ligand for the FimH CRD. More negative scores indicate higher binding affinity than less negative values (Table 1). According to this docking procedure, Amadori products 9 and 10 have similar scores, which lie in the range of that for MeMan

• . We took a closer look at the docking results by comparing top scoring conformations of the different ligands (Figure 3). No difference between complexation of the Amadori products 9 and 10 and MeMan (1) can be seen when inspected from above the CRD. However, the side view clearly shows that the

• aniline to yield C-glycosyl-type D-mannoside derivatives 9 and 10, respectively. Docking scoring values of the most stable conformers complexed by FimH (open gate structure PDB 1KLF) of MeMan (1) in comparison with Amadori rearrangement products. Inhibition of bacterial adhesion (E. coli) to a mannan

Synthesis and testing of the first azobenzene mannobioside as photoswitchable ligand for the bacterial lectin FimH

• Vijayanand Chandrasekaran,
• Katharina Kolbe,
• Femke Beiroth and
• Thisbe K. Lindhorst

Beilstein J. Org. Chem. 2013, 9, 223–233, doi:10.3762/bjoc.9.26

• of FimH FlexX [24][25][26], flexible docking and consensus scoring [27][28], as implemented in Sybyl 6.9 [29], was employed. Docking was based on two different X-ray structures of FimH. They differ in the conformation of the so-called tyrosine gate at the entrance of the CRD, formed by the side

• to change their conformations under the influence of the force field. A FlexX scoring value has been attributed to each of the 30 obtained conformations (Table 3). This value correlates with the binding affinity of the ligand for the FimH CRD, more negative values suggesting higher binding affinity

• than less negative ones. Docking gave very similar results for both isomers of mannobioside 2, (E)-2 and (Z)-2. Scoring values based on the open-gate structure of FimH are almost equal (−28.8 and −28.7), and also the scoring values obtained with the closed-gate structure do not differ significantly

Synthesis and in silico screening of a library of β-carboline-containing compounds

• Kay M. Brummond,
• John R. Goodell,
• Matthew G. LaPorte,
• Lirong Wang and
• Xiang-Qun Xie

Beilstein J. Org. Chem. 2012, 8, 1048–1058, doi:10.3762/bjoc.8.117

• site of each protein was defined by the corresponding residues around the cocrystallized ligands. In-house algorithms were used to evaluate ligand-docking efficiency, and docking scores were used to assess and rank the protein targets. A portion of the protein-scoring matrix is illustrated in Figure 3

En route to photoaffinity labeling of the bacterial lectin FimH

• Thisbe K. Lindhorst,
• Michaela Märten,
• Andreas Fuchs and
• Stefan D. Knight

Beilstein J. Org. Chem. 2010, 6, 810–822, doi:10.3762/bjoc.6.91

• photoactive mannosides 1, 2, 3, and 5, we have performed computer-aided docking studies using FlexX [17][18][19] to get an idea about their binding to the bacterial lectin FimH, as reported earlier [20]. FlexX produces so-called scoring values for each docked ligand, which can be regarded as a rough estimate

• modeling to predict binding of the various FimH ligands was carried out using FlexX flexible docking and consensus scoring as implemented in Sybyl 6.8 as described earlier [20]. Docking was based on published X-ray structures of the FimH CRD. This CRD was held fixed during the minimization, whereas the

A bivalent glycopeptide to target two putative carbohydrate binding sites on FimH

• Thisbe K. Lindhorst,
• Kathrin Bruegge,
• Andreas Fuchs and
• Oliver Sperling

Beilstein J. Org. Chem. 2010, 6, 801–809, doi:10.3762/bjoc.6.90

• regulation of the ligand-receptor interaction. Experimental Docking studies Computer-aided modeling to estimate the spacer lengths of a bivalent glycopeptide ligand to allow bridging of two putative binding sites on FimH was carried out using FlexX flexible docking and consensus scoring, implemented in Sybyl