New insights about the serine/threonine protein kinase substrates from Mycobacterium tuberculosis using molecular docking, quantum similarity analysis and DFT calculations

Background: The protein kinases present in the human body have received a lot of attention because of the interest in their use as therapeutic targets. However, little is known about the protein kinases associated with tuberculosis. For these reasons, this research investigates a new point of view regarding the crystallized serine/threonine protein kinases Pkn A, B and G of Mycobacterium tuberculosis. Methods: The conformational analysis shows a DFG-in motif in Pkn B and G and a DFG-out motif in Pkn A. For all the protein kinases that have been studied, the gatekeeper residue is methionine. A study of the protein kinases with their ligands was also conducted to find new insights on the binding site with a series of ligands associated to protein kinases Pkn A, B and G through molecular docking. The residues with hydrogen bonds on the hinge zone of Pkn A are GLU96 and VAL 98, of Pkn B are GLU 93 and VAL 95 and of Pkn G are GLU233 and VAL235. Results: The results show the H-bond acceptor and H-bond donor sites on the hinge zone to all ligands, establishing a structural model of the ligands on the active site with two or three interactions in this zone. This interaction model was validated using density functional theory calculations (by means of net charges and images of the electrostatic potential) and molecular quantum similarity analysis, showing a high correlation between the electronic and steric effects in each ATP complex studied. Conclusions: In this work we can see that the interactions of the hinge zone are characterized by the key factor of one or two H-bonds acceptors and one H-bond donor in the ligands of this zone. The quantum similarity analysis shows good correlation between the steric and electronic effects in each ATP complex. © 2021. Morales-Bayuelo A and Sánchez-Márquez

Computation of protein geometry and its applications: Packing and function prediction

This chapter discusses geometric models of biomolecules and geometric constructs, including the union of ball model, the weigthed Voronoi diagram, the weighted Delaunay triangulation, and the alpha shapes. These geometric constructs enable fast and analytical computaton of shapes of biomoleculres (including features such as voids and pockets) and metric properties (such as area and volume). The algorithms of Delaunay triangulation, computation of voids and pockets, as well volume/area computation are also described. In addition, applications in packing analysis of protein structures and protein function prediction are also discussed.Comment: 32 pages, 9 figure

An Antioxidant Potential, Quantum-Chemical and Molecular Docking Study of the Major Chemical Constituents Present in the Leaves of Curatella americana Linn

Reactive oxygen species (ROS) are continuously generated in the normal biological systems, primarily by enzymes as xanthine oxidase (XO). The inappropriate scavenging or inhibition of ROS has been considered to be linked with aging, inflammatory disorders, and chronic diseases. Therefore, many plants and their products have been investigated as natural antioxidants for their potential use in preventive medicine. The leaves and bark extracts of Curatella americana Linn. were described in scientific research as anti-inflammatory, vasodilator, anti-ulcerogenic, and hypolipidemic effects. So, the aim of this study was to evaluate the antioxidant potentials of leaf hydroalcoholic extract from C. americana (HECA) through the scavenging DPPH assay and their main chemical constituents, evaluated by the following quantum chemical approaches (DFT B3LYP/6-31G**): Maps of Molecular Electrostatic Potential (MEP), Frontier Orbital’s (HOMO and LUMO) followed by multivariate analysis and molecular docking simulations with the xanthine oxidase enzyme. The hydroalcoholic extract showed significant antioxidant activity by free radical scavenging probably due to the great presence of flavonoids, which were grouped in the PCA and HCA analysis with the standard gallic acid. In the molecular docking study, the compounds studied presented the binding free energy (ΔG) values close each other, due to the similar interactions with amino acids residues at the activity site. The descriptors Gap and softness were important to characterize the molecules with antioxidant potential by capturing oxygen radicals

Development of novel Classical and Quantum Information Theory Based Methods for the Detection of Compensatory Mutations in MSAs

Multiple Sequenzalignments (MSAs) von homologen Proteinen sind nützliche Werkzeuge, um kompensatorische Mutationen zwischen nicht-konservierten Residuen zu charakterisieren. Die Identifizierung dieser Residuen in MSAs ist eine wichtige Aufgabe um die strukturellen Grundlagen und molekularen Mechanismen von Proteinfunktionen besser zu verstehen. Trotz der vielen Anzahl an Literatur über kompensatorische Mutationen sowie über die Sequenzkonservierungsanalyse für die Erkennung von wichtigen Residuen, haben vorherige Methoden meistens die biochemischen Eigenschaften von Aminosäuren nicht mit in Betracht gezogen, welche allerdings entscheidend für die Erkennung von kompensatorischen Mutationssignalen sein können. Jedoch werden kompensatorische Mutationssignale in MSAs oft durch das Rauschen verfälscht. Aus diesem Grund besteht ein weiteres Problem der Bioinformatik in der Trennung signifikanter Signale vom phylogenetischen Rauschen und beziehungslosen Paarsignalen. Das Ziel dieser Arbeit besteht darin Methoden zu entwickeln, welche biochemische Eigenschaften wie Ähnlichkeiten und Unähnlichkeiten von Aminosäuren in der Identifizierung von kompensatorischen Mutationen integriert und sich mit dem Rauschen auseinandersetzt. Deshalb entwickeln wir unterschiedliche Methoden basierend auf klassischer- und quantum Informationstheorie sowie multiple Testverfahren. Unsere erste Methode basiert auf der klassischen Informationstheorie. Diese Methode betrachtet hauptsächlich BLOSUM62-unähnliche Paare von Aminosäuren als ein Modell von kompensatorischen Mutationen und integriert sie in die Identifizierung von wichtigen Residuen. Um diese Methode zu ergänzen, entwickeln wir unsere zweite Methode unter Verwendung der Grundlagen von quantum Informationstheorie. Diese neue Methode unterscheidet sich von der ersten Methode durch gleichzeitige Modellierung ähnlicher und unähnlicher Signale in der kompensatorischen Mutationsanalyse. Des Weiteren, um signifikante Signale vom Rauschen zu trennen, entwickeln wir ein MSA-spezifisch statistisches Modell in Bezug auf multiple Testverfahren. Wir wenden unsere Methode für zwei menschliche Proteine an, nämlich epidermal growth factor receptor (EGFR) und glucokinase (GCK). Die Ergebnisse zeigen, dass das MSA-spezifisch statistische Modell die signifikanten Signale vom phylogenetischen Rauschen und von beziehungslosen Paarsignalen trennen kann. Nur unter Berücksichtigung BLOSUM62-unähnlicher Paare von Aminosäuren identifiziert die erste Methode erfolgreich die krankheits-assoziierten wichtigen Residuen der beiden Proteine. Im Gegensatz dazu, durch die gleichzeitige Modellierung ähnlicher und unähnlicher Signale von Aminosäurepaare ist die zweite Methode sensibler für die Identifizierung von katalytischen und allosterischen Residuen

Defining binding efficiency and specificity of auxins for SCF(TIR1/AFB)-Aux/IAA co-receptor complex formation.

Structure-activity profiles for the phytohormone auxin have been collected for over 70 years, and a number of synthetic auxins are used in agriculture. Auxin classification schemes and binding models followed from understanding auxin structures. However, all of the data came from whole plant bioassays, meaning the output was the integral of many different processes. The discovery of Transport Inhibitor-Response 1 (TIR1) and the Auxin F-Box (AFB) proteins as sites of auxin perception and the role of auxin as molecular glue in the assembly of co-receptor complexes has allowed the development of a definitive quantitative structure-activity relationship for TIR1 and AFB5. Factorial analysis of binding activities offered two uncorrelated factors associated with binding efficiency and binding selectivity. The six maximum-likelihood estimators of Efficiency are changes in the overlap matrixes, inferring that Efficiency is related to the volume of the electronic system. Using the subset of compounds that bound strongly, chemometric analyses based on quantum chemical calculations and similarity and self-similarity indices yielded three classes of Specificity that relate to differential binding. Specificity may not be defined by any one specific atom or position and is influenced by coulomb matrixes, suggesting that it is driven by electrostatic forces. These analyses give the first receptor-specific classification of auxins and indicate that AFB5 is the preferred site for a number of auxinic herbicides by allowing interactions with analogues having van der Waals surfaces larger than that of indole-3-acetic acid. The quality factors are also examined in terms of long-standing models for the mechanism of auxin binding