Enhanced Molecular Dynamics Method to Efficiently Increase the Discrimination Capability of Computational Protein-Protein Docking

Protein-protein docking typically consists of the generation of putative binding conformations, which are subsequently ranked by fast heuristic scoring functions. The simplicity of these functions allows for computational efficiency but has severe repercussions on their discrimination capabilities. In this work, we show the effectiveness of suitable descriptors calculated along short scaled molecular dynamics runs in recognizing the nearest-native bound conformation among a set of putative structures generated by the HADDOCK tool for eight protein-protein systems

Tuning Local Hydration Enables a Deeper Understanding of Protein-Ligand Binding: The PP1-Src Kinase Case

Water plays a key role in biomolecular recognition and binding. Despite the development of several computational and experimental approaches, it is still challenging to comprehensively characterize water-mediated effects on the binding process. Here, we investigate how water affects the binding of Src kinase to one of its inhibitors, PP1. Src kinase is a target for treating several diseases, including cancer. We use biased molecular dynamics simulations, where the hydration of predetermined regions is tuned at will. This computational technique efficiently accelerates the SRC-PP1 binding simulation and allows us to identify several key and yet unexplored aspects of the solvent's role. This study provides a further perspective on the binding phenomenon, which may advance the current drug design approaches for the development of new kinase inhibitors

Surface Enhanced Second Harmonic Generation from Macrocycle, Catenane, and Rotaxane Thin Films: Experiments and Theory

Surface enhanced second harmonic generation (SE SHG) experiments on molecular structures, macrocycles, catenanes, and rotaxanes, deposited as monolayers and multilayers by vacuum sublimation on silver, are reported. The measurements show that the molecules form ordered thin films, where the highest degree of order is observed in the case of macrocycle monolayers and the lowest in the case of rotaxane multilayers. The second harmonic generation activity is interpreted in terms of electric field induced second harmonic (EFISH) generation where the electric field is created by the substrate silver atoms. The measured second order nonlinear optical susceptibility for a rotaxane thin film is compared with that obtained by considering only EFISH contribution to SHG intensity. The electric field on the surface of a silver layer is calculated by using the Delphi4 program for structures obtained with TINKER molecular mechanics/dynamics simulations. An excellent agreement is observed between the calculated and the measured SHG susceptibilities.

A Serendipitous Galaxy Cluster Survey with XMM: Expected Catalogue Properties and Scientific Applications

This paper describes a serendipitous galaxy cluster survey that we plan to conduct with the XMM X-ray satellite. We have modeled the expected properties of such a survey for three different cosmological models, using an extended Press-Schechter (Press & Schechter 1974) formalism, combined with a detailed characterization of the expected capabilities of the EPIC camera on board XMM. We estimate that, over the ten year design lifetime of XMM, the EPIC camera will image a total of ~800 square degrees in fields suitable for the serendipitous detection of clusters of galaxies. For the presently-favored low-density model with a cosmological constant, our simulations predict that this survey area would yield a catalogue of more than 8000 clusters, ranging from poor to very rich systems, with around 750 detections above z=1. A low-density open Universe yields similar numbers, though with a different redshift distribution, while a critical-density Universe gives considerably fewer clusters. This dependence of catalogue properties on cosmology means that the proposed survey will place strong constraints on the values of Omega-Matter and Omega-Lambda. The survey would also facilitate a variety of follow-up projects, including the quantification of evolution in the cluster X-ray luminosity-temperature relation, the study of high-redshift galaxies via gravitational lensing, follow-up observations of the Sunyaev-Zel'dovich effect and foreground analyses of cosmic microwave background maps.Comment: Accepted to ApJ. Minor changes, e.g. presentation of temperature errors as a figure (rather than as a table). Latex (20 pages, 6 figures, uses emulateapj.sty

Identification of Key Residues for pH Dependent Activation of Violaxanthin De-Epoxidase from Arabidopsis thaliana

Plants are often exposed to saturating light conditions, which can lead to oxidative stress. The carotenoid zeaxanthin, synthesized from violaxanthin by Violaxanthin De-Epoxidase (VDE) plays a major role in the protection from excess illumination. VDE activation is triggered by a pH reduction in the thylakoids lumen occurring under saturating light. In this work the mechanism of the VDE activation was investigated on a molecular level using multi conformer continuum electrostatic calculations, site directed mutagenesis and molecular dynamics. The pKa values of residues of the inactive VDE were determined to identify target residues that could be implicated in the activation. Five such target residues were investigated closer by site directed mutagenesis, whereas variants in four residues (D98, D117, H168 and D206) caused a reduction in enzymatic activity indicating a role in the activation of VDE while D86 mutants did not show any alteration. The analysis of the VDE sequence showed that the four putative activation residues are all conserved in plants but not in diatoms, explaining why VDE in these algae is already activated at higher pH. Molecular dynamics showed that the VDE structure was coherent at pH 7 with a low amount of water penetrating the hydrophobic barrel. Simulations carried out with the candidate residues locked into their protonated state showed instead an increased amount of water penetrating the barrel and the rupture of the H121–Y214 hydrogen bond at the end of the barrel, which is essential for VDE activation. These results suggest that VDE activation relies on a robust and redundant network, in which the four residues identified in this study play a major role

SECRET domain of variola virus CrmB protein can be a member of poxviral type II chemokine-binding proteins family

<p>Abstract</p> <p>Background</p> <p>Variola virus (VARV) the causative agent of smallpox, eradicated in 1980, have wide spectrum of immunomodulatory proteins to evade host immunity. Recently additional biological activity was discovered for VARV CrmB protein, known to bind and inhibit tumour necrosis factor (TNF) through its N-terminal domain homologous to cellular TNF receptors. Besides binding TNF, this protein was also shown to bind with high affinity several chemokines which recruit B- and T-lymphocytes and dendritic cells to sites of viral entry and replication. Ability to bind chemokines was shown to be associated with unique C-terminal domain of CrmB protein. This domain named SECRET (Smallpox virus-Encoded Chemokine Receptor) is unrelated to the host proteins and lacks significant homology with other known viral chemokine-binding proteins or any other known protein.</p> <p>Findings</p> <p><it>De novo </it>modelling of VARV-CrmB SECRET domain spatial structure revealed its apparent structural homology with cowpox virus CC-chemokine binding protein (vCCI) and vaccinia virus A41 protein, despite low sequence identity between these three proteins. Potential ligand-binding surface of modelled VARV-CrmB SECRET domain was also predicted to bear prominent electronegative charge which is characteristic to known orthopoxviral chemokine-binding proteins.</p> <p>Conclusions</p> <p>Our results suggest that SECRET should be included into the family of poxviral type II chemokine-binding proteins and that it might have been evolved from the vCCI-like predecessor protein.</p

Pandemic Drugs at Pandemic Speed: Infrastructure for Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers

Molecular Recognition of H3/H4 Histone Tails by the Tudor Domains of JMJD2A: A Comparative Molecular Dynamics Simulations Study

Background: Histone demethylase, JMJD2A, specifically recognizes and binds to methylated lysine residues at histone H3 and H4 tails (especially trimethylated H3K4 (H3K4me3), trimethylated H3K9 (H3K9me3) and di, trimethylated H4K20 (H4K20me2, H4K20me3)) via its tandem tudor domains. Crystal structures of JMJD2A-tudor binding to H3K4me3 and H4K20me3 peptides are available whereas the others are not. Complete picture of the recognition of the four histone peptides by the tandem tudor domains yet remains to be clarified. Methodology/Principal Findings: We report a detailed molecular dynamics simulation and binding energy analysis of the recognition of JMJD2A-tudor with four different histone tails. 25 ns fully unrestrained molecular dynamics simulations are carried out for each of the bound and free structures. We investigate the important hydrogen bonds and electrostatic interactions between the tudor domains and the peptide molecules and identify the critical residues that stabilize the complexes. Our binding free energy calculations show that H4K20me2 and H3K9me3 peptides have the highest and lowest affinity to JMJD2A-tudor, respectively. We also show that H4K20me2 peptide adopts the same binding mode with H4K20me3 peptide, and H3K9me3 peptide adopts the same binding mode with H3K4me3 peptide. Decomposition of the enthalpic and the entropic contributions to the binding free energies indicate that the recognition of the histone peptides is mainly driven by favourable van der Waals interactions. Residue decomposition of the binding free energies with backbone and side chain contributions as well as their energetic constituents identify the hotspots in the binding interface of the structures. Conclusion: Energetic investigations of the four complexes suggest that many of the residues involved in the interactions are common. However, we found two receptor residues that were related to selective binding of the H3 and H4 ligands. Modifications or mutations on one of these residues can selectively alter the recognition of the H3 tails or the H4 tails

The Hexamer Structure of the Rift Valley Fever Virus Nucleoprotein Suggests a Mechanism for its Assembly into Ribonucleoprotein Complexes

Rift Valley fever virus (RVFV), a Phlebovirus with a genome consisting of three single-stranded RNA segments, is spread by infected mosquitoes and causes large viral outbreaks in Africa. RVFV encodes a nucleoprotein (N) that encapsidates the viral RNA. The N protein is the major component of the ribonucleoprotein complex and is also required for genomic RNA replication and transcription by the viral polymerase. Here we present the 1.6 Å crystal structure of the RVFV N protein in hexameric form. The ring-shaped hexamers form a functional RNA binding site, as assessed by mutagenesis experiments. Electron microscopy (EM) demonstrates that N in complex with RNA also forms rings in solution, and a single-particle EM reconstruction of a hexameric N-RNA complex is consistent with the crystallographic N hexamers. The ring-like organization of the hexamers in the crystal is stabilized by circular interactions of the N terminus of RVFV N, which forms an extended arm that binds to a hydrophobic pocket in the core domain of an adjacent subunit. The conformation of the N-terminal arm differs from that seen in a previous crystal structure of RVFV, in which it was bound to the hydrophobic pocket in its own core domain. The switch from an intra- to an inter-molecular interaction mode of the N-terminal arm may be a general principle that underlies multimerization and RNA encapsidation by N proteins from Bunyaviridae. Furthermore, slight structural adjustments of the N-terminal arm would allow RVFV N to form smaller or larger ring-shaped oligomers and potentially even a multimer with a super-helical subunit arrangement. Thus, the interaction mode between subunits seen in the crystal structure would allow the formation of filamentous ribonucleocapsids in vivo. Both the RNA binding cleft and the multimerization site of the N protein are promising targets for the development of antiviral drugs

Predicting Peptide Binding Affinities to MHC Molecules Using a Modified Semi-Empirical Scoring Function

The Major Histocompatibility Complex (MHC) plays an important role in the human immune system. The MHC is involved in the antigen presentation system assisting T cells to identify foreign or pathogenic proteins. However, an MHC molecule binding a self-peptide may incorrectly trigger an immune response and cause an autoimmune disease, such as multiple sclerosis. Understanding the molecular mechanism of this process will greatly assist in determining the aetiology of various diseases and in the design of effective drugs. In the present study, we have used the Fresno semi-empirical scoring function and modify the approach to the prediction of peptide-MHC binding by using open-source and public domain software. We apply the method to HLA class II alleles DR15, DR1, and DR4, and the HLA class I allele HLA A2. Our analysis shows that using a large set of binding data and multiple crystal structures improves the predictive capability of the method. The performance of the method is also shown to be correlated to the structural similarity of the crystal structures used. We have exposed some of the obstacles faced by structure-based prediction methods and proposed possible solutions to those obstacles. It is envisaged that these obstacles need to be addressed before the performance of structure-based methods can be on par with the sequence-based methods