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In this paper, a method that allows to analyze the binding curves of ligand (EtBr) with single-stranded (ss) and double-stranded (ds) DNA, when there are at least two modes of ligand binding to DNA at small fillings has been proposed. The obtained experimental binding curves for EtBr–ssDNA and EtBr–dsDNA have two clearly expressed linear regions. These curves were analyzed by two modes: Experimental points on linear regions were described by two different lines and all experimental points were described by single curve. It was revealed that the description by single curve permits obtaining more precise data of binding parameters (i.e. binding constant and number of base pairs that bind one ligand molecule). Moreover, the proposed method permits determining the value of proportion of binding sites of each binding mode.

Measuring the accuracy of protein three-dimensional structures is one of the most important problems in protein structure prediction. For structure-based drug design, the accuracy of the binding site is far more important than the accuracy of any other region of the protein. We have developed an automated method for assessing the quality of a protein model by focusing on the set of residues in the small molecule binding site. Small molecule binding sites typically involve multiple regions of the protein coming together in space, and their accuracy has been observed to be sensitive to even small alignment errors. In addition, ligand binding sites contain the critical information required for drug design, making their accuracy particularly important. We analyzed the accuracy of the binding sites on two sets of protein models: the predictions submitted by the top-performing CASP7 groups, and the models generated by four widely used homology modeling packages. The results of our CASP7 analysis significantly differ from the previous findings, implying that the binding site measure does not correlate with the traditional model quality measures used in the structure prediction benchmarks. For the modeling programs, the resolution of binding sites is extremely sensitive to the degree of sequence homology between the query and the template, even when the most accurate alignments are used in the homology modeling process.

The acid-base interactions and solvoprotolytic dissociation of octaphenyltetraaza-porphyrin complexes with rare earth metals are discussed. The thermodynamic and kinetic stability of the acid forms of the complexes are compared.

Novel Zn(II) phthalocyanine and naphthalocyanine DBU complexes have been prepared in a one-pot synthesis reacting phthalonitrile precursors with an excess of DBU (1,8-diazabicyclo[5.4.0]undec-7-ene). For the first time, it has been well evidenced that DBU played the role of coordinating axial ligand together with the well known role of strong base. Also, DBU complexes showed better solubility in organic solvents due to the coordination of the bulky axial DBU ligand, compared to the Zn(II) phthalocyanines and naphthalocyanines without coordinated DBU. The coordinating properties of DBU toward ZnPcs (DBU free) complexes have also been investigated along with the ZnPc(pyridine) complex. Thermal analysis results reflecting the stability of the synthesized complexes under air are also presented.

We conducted a meta-analysis of (bacterio)chlorophyll [(B)Chl] molecules in photosynthetic pigment-protein complexes from the viewpoint of coordination chemistry. We surveyed the ligand species and site in the axial coordination of 146 Chl and 21 BChl molecules in 42 reported crystal structures of 12-type proteins. The imidazolyl moiety of histidine (His) is the most abundant ligand, and the second is water, a much weaker ligand. We focused on the positions, the circumstances, and the macrocycle sides for the coordination of the 31 hydrated (B)Chl molecules found in these proteins. A ligand water molecule of a hydrated (B)Chl is not necessarily hydrogen-bonded to the surrounding protein residues. A hydrated (B)Chl seems to occupy the redundant space where more strongly coupled His-Chl complexes cannot be formed. It is noted that 28 of 31 hydrated (B)Chl molecules (90) were coordinated from the α-side of the (bacterio)chlorin macrocycle, the opposite side from which the C17-propionic ester protrudes. Among them, all five hydrated Chl molecules at the edges of the proteins were coordinated from the α-side, suggesting that (B)Chl molecules prefer this side for the coordination bondings to the β-side. The analysis also revealed that each (B)Chl binding site was composed of both the protein residues and the neighboring pigment molecules contributing roughly equally. It can be safely said that the cofactor pigments aggregated even in the proteins. Penta-coordination is advantageous to flexible adjustment of intermolecular orientations of (B)Chl molecules in the aggregates.

A pyridyl side arm porphyrin incorporating C${}_{10}$ alkyl chains at the periphery of the porphyrin suitable for surface immobilisation on HOPG has been synthesised and tested for two state switching in solution. Temperature switching, involving reversible complexation of a covalently appended pyridyl side arm to the Zn(II) porphyrin, was comprehensively characterised by using variable temperature ¹H NMR (-30 to +100${}^{\circ }$C) and UV-vis (10 to 90${}^{\circ }$C) in toluene. Molecular modelling assisted in understanding strain within the complex.

Herein, we report the synthesis of cobalt-coordinated β-β’ bicyclo[2.2.2]octadiene-fused corrole 1-Co and benzo-fused 2-Co with axial PPh₃ ligands. The structures and properties of 1-Co and 2-Co are fully studied via single-crystal X-ray diffraction, UV-Vis spectroscopy, cyclic voltammograms, and density functional theory calculations. The benzo-fusion of 2-Co leads to a reduced energy gap and distinct coordination, photophysical, and redox properties. Compared to 1-Co, 2-Co exhibits increased bond-length alternation, red-shifted UV-vis absorption bands, and decreased aromaticity. For 2-Co, the axial PPh₃ dissociates during both oxidation and reduction processes, but for 1-Co, the dissociation occurs only during reduction. The theoretical calculations further predict a low-lying open-shell singlet state for 2-Co. This study advances the functionalization strategy of cobalt corroles for a broader range of potential applications.

Coronavirus Acute Respiratory Syndrome (SARS-CoV-2) is a very recent viral infection and has generated one of the world’s biggest problems of all time. There is no scientific evidence and clinical trials to indicate that possible therapies have shown results in suspected or confirmed patients other than the use of immunizations. Given the above, some substances are being studied to be applied to contain their spread and further damage. This work aims to perform an in silico study of amoxicillin, widely known as an antibiotic and used to prevent bacterial infections and a possible biomarker made from a complex with Europium (Eu). It was shown to have the ability to interact with the COVID-19 protein in M^pro protease as ligands. The study was conducted using the AutoDock Vina with Lamarckian genetic model algorithm (GA) combined with the estimation of grid-based energy in rigid and flexible conformation. Compared to affinity energy, amoxicillin presented $-7.7$kcal/mol, which was better than its co-crystallized ligand in the study. The Europium complex, where its synthesis was also demonstrated in this work, presented energy of $-6.3$kcal/mol with hydrogen bonds and possible color change when UV light was applied. For the choice of the best poses in the simulation, the neural network parameter, NNScore2, was used. It can be affirmed that this study is still introductory but promising both in the treatment and identification of the virus.

The notable ability of human liver cytochrome P450 3A4 (CYP3A4) to metabolize diverse xenobiotics encourages researchers to explore in-depth the mechanism of enzyme action. Numerous CYP3A4 protein crystal structures have been deposited in protein data bank (PDB) and are majorly used in molecular docking analysis. The quality of the molecular docking results depends on the three-dimensional CYP3A4 protein crystal structures from the PDB. Present review endeavors to provide a brief outline of some technical parameters of CYP3A4 PDB entries as valuable information for molecular docking research. PDB entries between 22 April 2004 and 2 June 2021 were compiled and the active sites were thoroughly observed. The present review identified 76 deposited PDB entries and described basic information that includes CYP3A4 from human genetic, Escherichia coli (E. coli) use for protein expression, crystal structure obtained from X-ray diffraction method, taxonomy ID 9606, Uniprot ID P08684, ligand–protein structure description, co-crystal ligand, protein site deposit and resolution ranges between 1.7Å and 2.95Å. The observation of protein–ligand interactions showed the various residues on the active site depending on the ligand. The residues Ala305, Ser119, Ala370, Phe304, Phe108, Phe213 and Phe215 have been found to frequently interact with ligands from CYP3A4 PDB. Literature surveys of 17 co-crystal ligands reveal multiple mechanisms that include competitive inhibition, noncompetitive inhibition, mixed-mode inhibition, mechanism-based inhibition, substrate with metabolite, inducer, or combination modes of action. This overview may help researchers choose a trustworthy CYP3A4 protein structure from the PDB database to apply the protein in molecular docking analysis for drug discovery.

The G-protein coupled receptor (GPCR) superfamily is the largest class of proteins with therapeutic value. More than 40% of present prescription drugs are GPCR ligands. The high therapeutic value of GPCR proteins and recent advancements in virtual screening methods gave rise to many virtual screening studies for GPCR ligands. However, in spite of vast amounts of research studying their functions and characteristics, 3D structures of most GPCRs are still unknown. This makes target-based virtual screenings of GPCR ligands extremely difficult, and successful virtual screening techniques rely heavily on ligand information. These virtual screening methods focus on specific features of ligands on GPCR protein level, and common features of ligands on higher levels of GPCR classification are yet to be studied. Here we extracted common substructures of GPCR ligands of GPCR protein subfamilies. We used the SIMCOMP, a graph-based chemical structure comparison program, and hierarchical clustering to reveal common substructures. We applied our method to 850 GPCR ligands and we found 53 common substructures covering 439 ligands. These substructures contribute to deeper understanding of structural features of GPCR ligands which can be used in new drug discovery methods.

Identification of small molecule ligands that bind to proteins is a critical step in drug discovery. Computational methods have been developed to accelerate the prediction of protein-ligand binding, but often depend on 3D protein structures. As only a limited number of protein 3D structures have been resolved, the ability to predict protein-ligand interactions without relying on a 3D representation would be highly valuable. We use an interpretable confidence-rated boosting algorithm to predict protein-ligand interactions with high accuracy from ligand chemical substructures and protein 1D sequence motifs, without relying on 3D protein structures. We compare several protein motif definitions, assess generalization of our model’s predictions to unseen proteins and ligands, demonstrate recovery of well established interactions and identify globally predictive protein-ligand motif pairs. By bridging biological and chemical perspectives, we demonstrate that it is possible to predict protein-ligand interactions using only motif-based features and that interpretation of these features can reveal new insights into the molecular mechanics underlying each interaction. Our work also lays a foundation to explore more predictive feature sets and sophisticated machine learning approaches as well as other applications, such as predicting unintended interactions or the effects of mutations.