Docking Simulation of the Binding Interactions of Saxitoxin Analogs Produced by the Marine Dinoflagellate Gymnodinium catenatum to the Voltage-Gated Sodium Channel Nav1.4

Saxitoxin (STX) and its analogs are paralytic alkaloid neurotoxins that block the voltage-gated sodium channel pore (Nav), impeding passage of Na+ ions into the intracellular space, and thereby preventing the action potential in the peripheral nervous system and skeletal muscle. The marine dinoflagellate Gymnodinium catenatum produces an array of such toxins, including the recently discovered benzoyl analogs, for which the mammalian toxicities are essentially unknown. We subjected STX and its analogs to a theoretical docking simulation based upon two alternative tri-dimensional models of the Nav1.4 to find a relationship between the binding properties and the known mammalian toxicity of selected STX analogs. We inferred hypothetical toxicities for the benzoyl analogs from the modeled values. We demonstrate that these toxins exhibit different binding modes with similar free binding energies and that these alternative binding modes are equally probable. We propose that the principal binding that governs ligand recognition is mediated by electrostatic interactions. Our simulation constitutes the first in silico modeling study on benzoyl-type paralytic toxins and provides an approach towards a better understanding of the mode of action of STX and its analogs

Conformational changes associated with L16P and T118M mutations in the membrane-embedded PMP22 protein, consequential in CMT-1A

<p>Peripheral myelin protein 22 (PMP22) resides in the plasma membrane and is required for myelin formation in the peripheral nervous system. Excess PMP22 mutants accumulate in the endoplasmic reticulum (ER) resulting in the inherited neuropathies of Charcot–Marie–Tooth disease. However, there was no evidence of the structure of PMP22 or how mutations affect its folding. Therefore, in this study, we combined bioinformatics and homology modeling approaches to obtain three-dimensional native and mutated PMP22 models and its anchoring to a POPC membrane, submitted to .5-μs MD simulations, to determine how the L16P and T118M mutations affect the conformational behavior of PMP22. In addition, we investigated the ability of the native and mutated species to accumulate in the ER, via interaction with RER1, by combining protein–protein docking and MD simulations, taking the conformations that were most representative of the native and mutated PMP22 systems and RER1 conformations. Principal component analysis over MD simulations revealed that L16P and T118M mutations resulted in increased structural instability compared to the native form, which is consistent with previous experimental findings of increased structural fluctuations along a loop connecting transmembrane α-helix1 and α-helix2. Docking and MD simulations coupled with the MMGBSA approach allowed the identification that the binding interface for the PMP22-RER1 complex takes place through transmembrane α-helix1 and α-helix2, with higher effective binding free energy values between the mutated PMP22 systems and RER1 than for the native PMP22, mainly through van der Waals interactions.</p

A complex view of GPCR signal transduction: Molecular dynamics of the histamine H3 membrane receptor

In this work, we study the mechanisms of classical activation and inactivation of signal transduction by the histamine H3 receptor, a 7-helix transmembrane bundle G-Protein Coupled Receptor through long-time-scale molecular dynamics simulations of the receptor embedded in a hydrated double layer of dipalmitoyl phosphatidyl choline, a zwitterionic poly-saturated ordered lipid. Three systems were prepared: the apo receptor, representing the constitutively active receptor; and two holo-receptors -the receptor coupled to the antagonist/inverse agonist ciproxifan and representing the inactive state of the receptor, and the receptor coupled to the endogenous agonist histamine and representing the active state of the receptor.An extensive analysis of the simulation shows that the three states of H3R present significant structural and dynamical differences, as well as a complex behavior given that the measured properties interact in multiple and inter-dependent ways. In addition, the simulations describe an unexpected escape of histamine from the orthosteric binding site, in agreement with the experimental modest affinities and rapid off-rates of agonists

QSAR, DFT and molecular modeling studies of peptides from HIV-1 to describe their recognition properties by MHC-I

<p>Human immunodeficiency virus type-1 (HIV-1) has infected more than 40 million people around the world. HIV-1 treatment still has several side effects, and the development of a vaccine, which is another potential option for decreasing human infections, has faced challenges. This work presents a computational study that includes a quantitative structure activity relationship(QSAR) using density functional theory(DFT) for reported peptides to identify the principal quantum mechanics descriptors related to peptide activity. In addition, the molecular recognition properties of these peptides are explored on major histocompatibility complex I (MHC-I) through docking and molecular dynamics (MD) simulations accompanied by the Molecular Mechanics Generalized Born Surface Area (MMGBSA) approach for correlating peptide activity reported elsewhere vs. theoretical peptide affinity. The results show that the carboxylic acid and hydroxyl groups are chemical moieties that have an inverse relationship with biological activity. The number of sulfides, pyrroles and imidazoles from the peptide structure are directly related to biological activity. In addition, the HOMO orbital energy values of the total absolute charge and the Ghose–Crippen molar refractivity of peptides are descriptors directly related to the activity and affinity on MHC-I. Docking and MD simulation studies accompanied by an MMGBSA analysis show that the binding free energy without considering the entropic contribution is energetically favorable for all the complexes. Furthermore, good peptide interaction with the most affinity is evaluated experimentally for three proteins. Overall, this study shows that the combination of quantum mechanics descriptors and molecular modeling studies could help describe the immunogenic properties of peptides from HIV-1.</p

Deciphering the GPER/GPR30-agonist and antagonists interactions using molecular modeling studies, molecular dynamics, and docking simulations

International audienc

In vitro and in silico studies of terpenes, terpenoids and related compounds with larvicidal and pupaecidal activity against Culex quinquefasciatus Say (Diptera: Culicidae)

Abstract Background In order to develop new larvicidal agents derived from phytochemicals, the larvicidal activity of fifty molecules that are constituent of essential oils was evaluated against Culex quinquefasciatus Say. Terpenes, terpenoids and phenylpropanoids molecules were included in the in vitro evaluation, and QSAR models using genetic algorithms were built to identify molecular and structural properties of biological interest. Further, to obtain structural details on the possible mechanism of action, selected compounds were submitted to docking studies on sterol carrier protein-2 (SCP-2) as possible target. Results Results showed high larvicidal activity of carvacrol and thymol on the third and fourth larval stage with a median lethal concentration (LC50) of 5.5 and 11.1 µg/mL respectively. Myrcene and carvacrol were highly toxic for pupae, with LC50 values of 31.8 and 53.2 µg/mL. Structure–activity models showed that the structural property π-bonds is the largest contributor of larvicidal activity while ketone groups should be avoided. Similarly, property–activity models attributed to the molecular descriptor LogP the most contribution to larvicidal activity, followed by the absolute total charge (Qtot) and molar refractivity (AMR). The models were statistically significant; thus the information contributes to the design of new larvicidal agents. Docking studies show that all molecules tested have the ability to interact with the SCP-2 protein, wherein α-humulene and β-caryophyllene were the compounds with higher binding energy. Conclusions The description of the molecular properties and the structural characteristics responsible for larvicidal activity of the tested compounds were used for the development of mathematical models of structure–activity relationship. The identification of molecular and structural descriptors, as well as studies of molecular docking on the SCP-2 protein, provide insight on the mechanism of action of the active molecules, and the information can be used for the design of new structures for synthesis as potential new larvicidal agents

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Additional file 1. Additional tables and figures

Molecular dynamics simulations to explore the active/inactive conformers of guinea pig β₂ adrenoceptor for the selective design of agonists or antagonists

<div><p>It is well known that guinea pig β₂ adrenoceptors (Gβ₂ARs) and human β₂ adrenoceptors (Hβ₂ARs) have structural similarity. However, only one conformational state of Gβ₂ARs has been studied – the putative inactive state. As adrenoceptors have a repertoire of conformations, and there is evidence that a certain conformation is stabilised as a ligand approaches, the aim of this study was to build four models of Gβ₂ARs by using putative active/inactive Hβ₂AR conformers as a template. We evaluated the accuracy of these models in regard to the binding mode and affinity values of a set of known β₂AR ligands through docking and molecular dynamics simulations. During docking simulations, ligands reached Gβ₂AR sites similar to those reported for Hβ₂ARs. The greatest differences between conformational states were found in the domains (TM5 and TM6) previously suggested as being key to ligand recognition. The coefficients of determination between experimental and calculated affinity values were near to but less than 0.66 in all cases. The highest values were for agonists on the active models and antagonists on the inactive model. The four Gβ₂AR models proved useful for analysing agonist/antagonist activity. The results suggest that the selection of an adequate model is dependent on the intrinsic activity of a given ligand.</p></div