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

• , water network prediction, and 3D-QSAR. GRID 2021 introduced a new interface aimed at structure-based design. It enables users to explore binding sites using classic GRID MIFs, encompassing 74 different chemical types. Additionally, it offers a new molecular probe for generating MIFs specific to

2-Heteroarylethylamines in medicinal chemistry: a review of 2-phenethylamine satellite chemical space

• Carlos Nieto,
• Alejandro Manchado,
• Ángel García-González,
• David Díez and
• Narciso M. Garrido

Beilstein J. Org. Chem. 2024, 20, 1880–1893, doi:10.3762/bjoc.20.163

• rings Furans: Racemic heteroarylisopropylamines were described as MAO inhibitors (monoamine oxidase) by Vallejos et al. [14] as a natural extension of their previous QSAR studies using phenylisopropylamines [15]. The authors supported their aryl-to-heteroaryl group hopping due to the success of similar

• )-[3H]-baclofen displacement. QSAR studies have been developed in order to examine the pivotal role of the aromatic moiety of baclofen-like compounds [25]. In this sense, the QSAR equation revealed HOMO/LUMO orbital energies are critical for a high correlation with binding strength. An in vivo

• docking or QSAR calculations to describe the bioisostere, impact and rationalize the observed experimental binding or efficacy measurements. As it was stated in the introduction, only the rings described in this review, are the ones with reported activity, but there exists a plethora of other analogues

Rhodium-catalyzed homo-coupling reaction of aryl Grignard reagents and its application for the synthesis of an integrin inhibitor

• Kazuyuki Sato,
• Satoki Teranishi,
• Atsushi Sakaue,
• Yukiko Karuo,
• Atsushi Tarui,
• Kentaro Kawai,
• Hiroyuki Takeda,
• Tatsuo Kinashi and
• Masaaki Omote

Beilstein J. Org. Chem. 2024, 20, 1341–1347, doi:10.3762/bjoc.20.118

• IC50 of 190 μM in an AlphaScreen system, and we believe that further QSAR studies of analogs of the inhibitor will lead to the discovery of novel potential therapeutics for the treatment of several intractable diseases. Scope and limitations for the Rh-catalyzed one-pot Ullmann-type reaction

Photochromic derivatives of indigo: historical overview of development, challenges and applications

• Gökhan Kaplan,
• Zeynel Seferoğlu and
• Daria V. Berdnikova

Beilstein J. Org. Chem. 2024, 20, 228–242, doi:10.3762/bjoc.20.23

• lifetimes, radiative and non-radiative relaxation pathways of the indigo chromophore [26][27][30][31][32][33][34][35] as well as to estimate ionization potentials and electronic structures [28][29], singlet oxygen generation capacity [31], QSAR properties [25], and others. In both solution and solid state

Synthesis of ether lipids: natural compounds and analogues

• Marco Antônio G. B. Gomes,
• Alicia Bauduin,
• Chloé Le Roux,
• Romain Fouinneteau,
• Wilfried Berthe,
• Mathieu Berchel,
• Hélène Couthon and
• Paul-Alain Jaffrès

Beilstein J. Org. Chem. 2023, 19, 1299–1369, doi:10.3762/bjoc.19.96

• ). The review of Lemaire et al., dedicated to the synthesis of glycerol ether, is complemental to this review article [57]. Of note, the review of Godfroid and Braquet attempted to decipher the binding site of PAF via a QSAR study [58]. 1.1 Synthesis of PAF and some building blocks The platelet

Biomimetic molecular design tools that learn, evolve, and adapt

• David A Winkler

Beilstein J. Org. Chem. 2017, 13, 1288–1302, doi:10.3762/bjoc.13.125

• Adam and Eve that automate drug development via cycles of quantitative structure–activity relationship (QSAR) learning and biological testing (Figure 3) [16][17][18]. Eve’s selection of compounds was more cost efficient than standard drug screening, and the robotic scientist has identified several new

G-Protein coupled receptors: answers from simulations

• Timothy Clark

Beilstein J. Org. Chem. 2017, 13, 1071–1078, doi:10.3762/bjoc.13.106

• have often observed that in quantitative structure–activity relationships (QSAR) for GPCRs, agonists give far better results than antagonists [40]. Metadynamics simulations on the vasopressin receptor [41] revealed the reason for this behavior. As also found previously in unbiased simulations of the β2

• . Significantly, antagonists bind to one of the alternative sites more strongly than to the orthosteric one. Of pharmacological importance is the fact that antagonists bind to different sites in the two subtypes of the vasopressin receptor investigated, so that a general QSAR that encompasses agonists and

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

• methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed. Keywords: ADME; computer-aided drug design; docking; free energy; high-throughput screening; LBDD; lead optimization

• ; 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

Is conformation a fundamental descriptor in QSAR? A case for halogenated anesthetics

• Maria C. Guimarães,
• Mariene H. Duarte,
• Josué M. Silla and
• Matheus P. Freitas

Beilstein J. Org. Chem. 2016, 12, 760–768, doi:10.3762/bjoc.12.76

• Maria C. Guimaraes Mariene H. Duarte Josue M. Silla Matheus P. Freitas Department of Chemistry, Federal University of Lavras, P. O. Box 3037, 37200-000, Lavras, MG, Brazil 10.3762/bjoc.12.76 Abstract An intriguing question in 3D-QSAR lies on which conformation(s) to use when generating molecular

• can cause misinterpretation of the QSAR model. The present computational work reports the conformational analysis of the volatile anesthetic isoflurane (2-chloro-2-(difluoromethoxy)-1,1,1-trifluoroethane) in the gas phase and also in polar and nonpolar implicit and explicit solvents to show that

• stable minima (ruled by intramolecular interactions) do not necessarily coincide with the bioconformation (ruled by enzyme induced fit). Consequently, a QSAR model based on two-dimensional chemical structures was built and exhibited satisfactory modeling/prediction capability and interpretability, then

De novo macrolide–glycolipid macrolactone hybrids: Synthesis, structure and antibiotic activity of carbohydrate-fused macrocycles

• Richard T. Desmond,
• Anniefer N. Magpusao,
• Chris Lorenc,
• Jeremy B. Alverson,
• Nigel Priestley and
• Mark W. Peczuh

Beilstein J. Org. Chem. 2014, 10, 2215–2221, doi:10.3762/bjoc.10.229

• -membered ring macrocycles with a C4’-O-tert-butyldimethylsilyl group. MICs as low as 52 μg/mL against S. aureus, E. faecalis, and B. subtillis were observed. The small data set and low activity of the compounds prevent a QSAR analysis but the influence of a log P effect seems most likely [31][32][33

Utilizing the σ-complex stability for quantifying reactivity in nucleophilic substitution of aromatic fluorides

• Magnus Liljenberg,
• Tore Brinck,
• Tobias Rein and
• Mats Svensson

Beilstein J. Org. Chem. 2013, 9, 791–799, doi:10.3762/bjoc.9.90

• assessment of reactivity: property- or descriptor-based and direct modeling of the PES, especially of the rate-determining TS. The first type is generally termed QSAR (quantitative structure–activity relationships), where experimentally known or calculated properties are fitted to observed reactivities