Protein Amyloid Cofactors: Charged Side-Chain Arrays Meet Their Match?

Recent advances in high-resolution structural studies of protein amyloids have revealed parallel in-register cross-ß-sheets with periodic arrays of closely spaced identical residues. What do these structures tell us about the mechanisms of action of common amyloid-promoting factors, such as heparan sulfate (HS), nucleic acids, polyphosphates, anionic phospholipids, and acidic pH?

Molecular Periphery Design Allows Control of the New Nitrofurans Antimicrobial Selectivity.

A series of 13 new 3-substituted 5-(5-nitro-2-furyl)-1,2,4-oxadiazoles was synthesized from different aminonitriles. All compounds were screened in the disc diffusion test at a 100 µg/mL concentration to determine the bacterial growth inhibition zone presence and diameter, and then the minimum inhibitory concentrations (MICs) were determined for the most active compounds by serial dilution. The compounds showed antibacterial activity against ESKAPE bacteria, predominantly suppressing the growth of 5 species out of the panel. Some compounds had similar or lower MICs against ESKAPE pathogens compared to ciprofloxacin, nitrofurantoin, and furazidin. In particular, 3-azetidin-3-yl-5-(5-nitro-2-furyl)-1,2,4-oxadiazole (2h) inhibited S. aureus at a concentration lower than all comparators. Compound 2e (5-(5-nitro-2-furyl)-3-[4-(pyrrolidin-3-yloxy)phenyl]-1,2,4-oxadiazole) was active against Gram-positive ESKAPE pathogens as well as M. tuberculosis. Differences in the molecular periphery led to high selectivity for the compounds. The induced-fit docking (IFD) modeling technique was applied to in silico research. Molecular docking results indicated the targeting of compounds against various nitrofuran-associated biological targets.

QUBO Problem Formulation of Fragment-Based Protein-Ligand Flexible Docking.

Protein-ligand docking plays a significant role in structure-based drug discovery. This methodology aims to estimate the binding mode and binding free energy between the drug-targeted protein and candidate chemical compounds, utilizing protein tertiary structure information. Reformulation of this docking as a quadratic unconstrained binary optimization (QUBO) problem to obtain solutions via quantum annealing has been attempted. However, previous studies did not consider the internal degrees of freedom of the compound that is mandatory and essential. In this study, we formulated fragment-based protein-ligand flexible docking, considering the internal degrees of freedom of the compound by focusing on fragments (rigid chemical substructures of compounds) as a QUBO problem. We introduced four factors essential for fragment-based docking in the Hamiltonian: (1) interaction energy between the target protein and each fragment, (2) clashes between fragments, (3) covalent bonds between fragments, and (4) the constraint that each fragment of the compound is selected for a single placement. We also implemented a proof-of-concept system and conducted redocking for the protein-compound complex structure of Aldose reductase (a drug target protein) using SQBM+, which is a simulated quantum annealer. The predicted binding pose reconstructed from the best solution was near-native (RMSD = 1.26 Å), which can be further improved (RMSD = 0.27 Å) using conventional energy minimization. The results indicate the validity of our QUBO problem formulation.

Modeling protein-nucleic acid complexes with extremely large conformational changes using Flex-LZerD.

Proteins and nucleic acids are key components in many processes in living cells, and interactions between proteins and nucleic acids are often crucial pathway components. In many cases, large flexibility of proteins as they interact with nucleic acids is key to their function. To understand the mechanisms of these processes, it is necessary to consider the 3D atomic structures of such protein-nucleic acid complexes. When such structures are not yet experimentally determined, protein docking can be used to computationally generate useful structure models. However, such docking has long had the limitation that the consideration of flexibility is usually limited to small movements or to small structures. We previously developed a method of flexible protein docking which could model ordered proteins which undergo large-scale conformational changes, which we also showed was compatible with nucleic acids. Here, we elaborate on the ability of that pipeline, Flex-LZerD, to model specifically interactions between proteins and nucleic acids, and demonstrate that Flex-LZerD can model more interactions and types of conformational change than previously shown.

Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement.

The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein-peptide complex structures and model scoring. We evaluated the proposed protocol on the set of seven different GPCR-peptide complexes (including one containing a cyclic peptide), for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimization, leading in most of the cases to sub-Angstrom accuracy in terms of interface root-mean-square-deviation measure.

RLDOCK method for predicting RNA-small molecule binding modes.

RNA molecules play critical roles in cellular functions at the level of gene expression and regulation. The intricate 3D structures and the functional roles of RNAs make RNA molecules ideal targets for therapeutic drugs. The rational design of RNA-targeted drug requires accurate modeling of RNA-ligand interactions. Recently a new computational tool, RLDOCK, was developed to predict ligand binding sites and binding poses. Using an iterative multiscale sampling and search algorithm and a energy-based evaluation of ligand poses, the method enables efficient and accurate predictions for RNA-ligand interactions. Here we present a detailed illustration of the computational procedure for the practical implementation of the RLDOCK method. Using Flavin mononucleotide (FMN) docking to F. nucleatum FMN riboswitch as an example, we illustrate the computational protocol for RLDOCK-based prediction of RNA- ligand interactions. The RLDOCK software is freely accessible at http://https://github.com/Vfold-RNA/RLDOCK.

5-Nitrofuran-Tagged Oxazolyl Pyrazolopiperidines: Synthesis and Activity against ESKAPE Pathogens.

A series of eight 5-nitrofuran-tagged oxazolyl tetrahydropyrazolopyridines (THPPs) has been prepared in six stages with excellent regioselectivity. The testing of these compounds against pathogens of the ESKAPE panel showed a good activity of lead compound 1-(2-methoxyethyl)-5-(5-nitro-2-furoyl)-3-(1,3-oxazol-5-yl)-4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c] pyridine (13g), which is superior to nitrofurantoin. These results confirmed the benefit of combining a THPP scaffold with a nitrofuran warhead. Certain structure-activity relationships were established in the course of this study which were rationalized by the induced-fit docking experiments in silico.

Molecular characterization of lipase from a psychrotrophic bacterium Pseudomonas sp. CRBC14.

Lipases from Pseudomonas species are particularly useful due to their broader biocatalytic applications and temperature activity. In this study, we amplified the gene encoding wild-type cold-active lipase from the genome of psychrotrophic bacterium isolated from the Himalayan glacier. The isolated CRBC14 strain was identified as Pseudomonas sp. based on the 16S rRNA gene sequence. Lipase activity was determined by observing the hydrolysis zone on nutrient agar containing tributyrin (1%, v/v). The sequence analysis of cold-active lipase revealed a protein of 611 amino acids with a calculated molecular mass of 63.71 kDa. The three-dimensional structure of this lipase was generated through template-supported modeling. Distinct techniques stamped the model quality, following which the binding free energies of tributyrin and oleic acid in the complex state with this enzymatic protein were predicted through molecular mechanics generalized born surface area (MMGBSA). A relative comparison of binding free energy values of these substrates indicated tributyrin's comparatively higher binding propensity towards the lipase. Using molecular docking, we evaluated the binding activity of cold-active lipase against tributyrin and oleic acid. Our docking analysis revealed that the lipase had a higher affinity for tributyrin than oleic acid, as evidenced by our measurement of the hydrolysis zone on two media plates. This study will help to understand the bacterial diversity of unexplored Himalayan glaciers and the possible application of their cold-adapted enzymes.

A computational study of structural differences of binding of NADP+ and G6P substrates to G6PD Mediterraneanc.563T, G6PD A-c.202A/c.376G, G6PD Cairoc.404C and G6PD Gazac.536A mutations.

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is a common X-linked inherited enzymopathic disorder that may lead to transfusion-requiring acute hemolytic anemia (AHA) triggered by fava beans ingestion, infection or some drugs. The gene encoding for G6PD carries a large number of genetic variants that have varying pathogenicity. We reported on three G6PD variants in the Gaza Strip Palestinian population with differing clinical impacts and frequencies: G6PD Mediterraneanc.563T, African G6PD A-c.202A/c.376G, and G6PD Cairoc.404C. We also identified a novel G6PD missense (Ser179Asn) mutation c.536G > A "G6PD Gaza". In this work we explore the effect of these four genetic variants on the structural and substrate (NADP+ and G6P) binding characteristics of the G6PD enzyme using the Monte Carlo (MC) flexible docking and molecular dynamics (MD) simulation approaches. We report that G6PD A-c.202A/c.376G, G6PD Mediterraneanc.563T, G6PD Cairoc.404C and G6PD Gazac.536A mutations cause significant structural changes in G6PD enzyme to induce conformational instability leading to the loss of binding of one or both substrates and are causative of G6PD deficiency.

Protein-peptide docking using CABS-dock and contact information.

CABS-dock is a computational method for protein-peptide molecular docking that does not require predefinition of the binding site. The peptide is treated as fully flexible, while the protein backbone undergoes small fluctuations and, optionally, large-scale rearrangements. Here, we present a specific CABS-dock protocol that enhances the docking procedure using fragmentary information about protein-peptide contacts. The contact information is used to narrow down the search for the binding peptide pose to the proximity of the binding site. We used information on a single-chosen and randomly chosen native protein-peptide contact to validate the protocol on the peptiDB benchmark. The contact information significantly improved CABS-dock performance. The protocol has been made available as a new feature of the CABS-dock web server (at http://biocomp.chem.uw.edu.pl/CABSdock/). SHORT ABSTRACT: CABS-dock is a tool for flexible docking of peptides to proteins. In this article, we present a protocol for CABS-dock docking driven by information about protein-peptide contact(s). Using information on individual protein-peptide contacts allows to improve the accuracy of CABS-dock docking.

Multiscale Modeling of Amyloid Fibrils Formed by Aggregating Peptides Derived from the Amyloidogenic Fragment of the A-Chain of Insulin.

Computational prediction of molecular structures of amyloid fibrils remains an exceedingly challenging task. In this work, we propose a multi-scale modeling procedure for the structure prediction of amyloid fibrils formed by the association of ACC1-13 aggregation-prone peptides derived from the N-terminal region of insulin's A-chain. First, a large number of protofilament models composed of five copies of interacting ACC1-13 peptides were predicted by application of CABS-dock coarse-grained (CG) docking simulations. Next, the models were reconstructed to all-atom (AA) representations and refined during molecular dynamics (MD) simulations in explicit solvent. The top-scored protofilament models, selected using symmetry criteria, were used for the assembly of long fibril structures. Finally, the amyloid fibril models resulting from the AA MD simulations were compared with atomic force microscopy (AFM) imaging experimental data. The obtained results indicate that the proposed multi-scale modeling procedure is capable of predicting protofilaments with high accuracy and may be applied for structure prediction and analysis of other amyloid fibrils.

(2R)- and (2S)- 2-hydroxy- hexanoyl and octanoyl-l-homoserine lactones: New highly potent Quorum Sensing modulators with opposite activities.

The synthesis and the QS modulation activity of diastereoisomerically pure 2-hydroxy-N-acyl-l-homoserine lactones (2-OH-AHLs) are unveiled. (2R)- and (2S)- 2-hydroxy-N-hexanoyl-l-homoserine lactone and 2-hydroxy-N-octanoyl-l-homoserine lactone have been identified as very potent QS agonists and antagonists on the Vibrio fischeri-quorum sensing system with opposite activities depending on the configuration of the carbon atom with the hydroxyl group. Flexible molecular docking showed that the (2R)-OH configuration in the antagonist isomer induces new hydrogen bonds with Tyr70 and Asp79, two importantly conserved residues in the LuxR protein family, while the (2S)-OH agonist configuration exhibits a binding mode comparable to the natural ligand 3-oxo-hexanoyl-l-homoserine lactone (OHHL). For the analogs with long alkyl chain 3a and 3b and aromatic analogs, all are antagonists with no effect of the configuration at C-2.

Integrative biology of native cell extracts: a new era for structural characterization of life processes.

Advances in electron microscopy have provided unprecedented access to the structural characterization of large, flexible and heterogeneous complexes. Until recently, cryo-electron microscopy (cryo-EM) has been applied to understand molecular organization in either highly purified, isolated biomolecules or in situ. An emerging field is developing, bridging the gap between the two approaches, and focuses on studying molecular organization in native cell extracts. This field has demonstrated its potential by resolving the structure of fungal fatty acid synthase (FAS) at 4.7 Å [Fourier shell correlation (FSC) = 0.143]; FAS was not only less than 50% enriched, but also retained higher-order binders, previously unknown. Although controversial in the sense that the lysis step might introduce artifacts, cell extracts preserve aspects of cellular function. In addition, cell extracts are accessible, besides cryo-EM, to modern proteomic methods, chemical cross-linking, network biology and biophysical modeling. We expect that automation in imaging cell extracts, along with the integration of molecular/cell biology approaches, will provide remarkable achievements in the study of closer-to-life biomolecular states of pronounced biotechnological and medical importance. Such steps will, eventually, bring us a step closer to the biophysical description of cellular processes in an integrative, holistic approach.

Flexible docking-based molecular dynamics simulation of natural product compounds and Ebola virus Nucleocapsid (EBOV NP): a computational approach to discover new drug for combating Ebola.

BACKGROUND: Ebola still remains as one of the most problematic infectious diseases in Africa with a high rate of mortality. Although this disease has been known for an almost half-century, there are no vaccines and drugs available in the market to treat Ebola. Zaire ebolavirus (EBOV), a single-stranded RNA virus which belongs to Filoviridae family and Mononegavirales order, is one of the virus causing Ebola. As one of seven proteins that EBOV encodes, Ebola virus nucleoprotein (EBOV NP) plays an imperative role in EBOV proliferation cycle. Therefore, the development of a new Ebola treatment can be targeted towards EBOV NP. RESULTS: In this work, we screened about 190,084 natural product compounds from ZINC15 database through in silico virtual screening and flexible docking simulation. Furthermore, the bioavailability and toxicity prediction have been conducted as well. Two best ligands according to the simulation and prediction tests were progressed into the molecular dynamics simulation. CONCLUSION: In the end, we found that our proposed ligands, namely α-lipomycin (ZINC56874155) and 3-(((S)-1-amino-1,2,3,4-tetrahydroisoquinolin-5-yl)methyl)-5-((5-((5R,7S)-5,7-dihydroxy-3-oxodecyl)-2-hydroxyphenoxy) methyl)pyrrolo[3,4-b]pyrrol-5-ium (ZINC85628951), showed the promising results to be developed as a lead compounds for treating Ebola. Therefore, an experimental study is required to validate their inhibition activities against EBOV NP.

Computational Feasibility of an Exhaustive Search of Side-Chain Conformations in Protein-Protein Docking.

Protein-protein docking procedures typically perform the global scan of the proteins relative positions, followed by the local refinement of the putative matches. Because of the size of the search space, the global scan is usually implemented as rigid-body search, using computationally inexpensive intermolecular energy approximations. An adequate refinement has to take into account structural flexibility. Since the refinement performs conformational search of the interacting proteins, it is extremely computationally challenging, given the enormous amount of the internal degrees of freedom. Different approaches limit the search space by restricting the search to the side chains, rotameric states, coarse-grained structure representation, principal normal modes, and so on. Still, even with the approximations, the refinement presents an extreme computational challenge due to the very large number of the remaining degrees of freedom. Given the complexity of the search space, the advantage of the exhaustive search is obvious. The obstacle to such search is computational feasibility. However, the growing computational power of modern computers, especially due to the increasing utilization of Graphics Processing Unit (GPU) with large amount of specialized computing cores, extends the ranges of applicability of the brute-force search methods. This proof-of-concept study demonstrates computational feasibility of an exhaustive search of side-chain conformations in protein pocking. The procedure, implemented on the GPU architecture, was used to generate the optimal conformations in a large representative set of protein-protein complexes. © 2018 Wiley Periodicals, Inc.

Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2.

The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein-ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many available experimental structures. We participated in the Stage 1 of the Challenge devoted to the docking pose predictions, with the mean RMSD value of our submission poses of 2.9 Å. Here we present a thorough analysis of our docking predictions made with AutoDock Vina and the Convex-PL rescoring potential by reproducing our submission protocol and running a series of additional molecular docking experiments. We conclude that a correct receptor structure, or more precisely, the structure of the binding pocket, plays the crucial role in the success of our docking studies. We have also noticed the important role of a local ligand geometry, which seems to be not well discussed in literature. We succeed to improve our results up to the mean RMSD value of 2.15-2.33 Å  dependent on the models of the ligands, if docking these to all available homologous receptors. Overall, for docking of ligands of diverse chemical series we suggest to perform docking of each of the ligands to a set of multiple receptors that are homologous to the target.

Modeling of protein-peptide interactions using the CABS-dock web server for binding site search and flexible docking.

Protein-peptide interactions play essential functional roles in living organisms and their structural characterization is a hot subject of current experimental and theoretical research. Computational modeling of the structure of protein-peptide interactions is usually divided into two stages: prediction of the binding site at a protein receptor surface, and then docking (and modeling) the peptide structure into the known binding site. This paper presents a comprehensive CABS-dock method for the simultaneous search of binding sites and flexible protein-peptide docking, available as a user's friendly web server. We present example CABS-dock results obtained in the default CABS-dock mode and using its advanced options that enable the user to increase the range of flexibility for chosen receptor fragments or to exclude user-selected binding modes from docking search. Furthermore, we demonstrate a strategy to improve CABS-dock performance by assessing the quality of models with classical molecular dynamics. Finally, we discuss the promising extensions and applications of the CABS-dock method and provide a tutorial appendix for the convenient analysis and visualization of CABS-dock results. The CABS-dock web server is freely available at http://biocomp.chem.uw.edu.pl/CABSdock/.

Modeling EphB4-EphrinB2 protein-protein interaction using flexible docking of a short linear motif.

BACKGROUND: Many protein-protein interactions are mediated by a short linear motif. Usually, amino acid sequences of those motifs are known or can be predicted. It is much harder to experimentally characterize or predict their structure in the bound form. In this work, we test a possibility of using flexible docking of a short linear motif to predict the interaction interface of the EphB4-EphrinB2 complex (a system extensively studied for its significance in tumor progression). METHODS: In the modeling, we only use knowledge about the motif sequence and experimental structures of EphB4-EphrinB2 complex partners. The proposed protocol enables efficient modeling of significant conformational changes in the short linear motif fragment during molecular docking simulation. For the docking simulations, we use the CABS-dock method for docking fully flexible peptides to flexible protein receptors (available as a server at http://biocomp.chem.uw.edu.pl/CABSdock/ ). Based on the docking result, the protein-protein complex is reconstructed and refined. RESULTS: Using this novel protocol, we obtained an accurate EphB4-EphrinB2 interaction model. CONCLUSIONS: The results show that the CABS-dock method may be useful as the primary docking tool in specific protein-protein docking cases similar to EphB4-EphrinB2 complex-that is, where a short linear motif fragment can be identified.

A protocol for CABS-dock protein-peptide docking driven by side-chain contact information.

BACKGROUND: The characterization of protein-peptide interactions is a challenge for computational molecular docking. Protein-peptide docking tools face at least two major difficulties: (1) efficient sampling of large-scale conformational changes induced by binding and (2) selection of the best models from a large set of predicted structures. In this paper, we merge an efficient sampling technique with external information about side-chain contacts to sample and select the best possible models. METHODS: In this paper we test a new protocol that uses information about side-chain contacts in CABS-dock protein-peptide docking. As shown in our recent studies, CABS-dock enables efficient modeling of large-scale conformational changes without knowledge about the binding site. However, the resulting set of binding sites and poses is in many cases highly diverse and difficult to score. RESULTS: As we demonstrate here, information about a single side-chain contact can significantly improve the prediction accuracy. Importantly, the imposed constraints for side-chain contacts are quite soft. Therefore, the developed protocol does not require precise contact information and ensures large-scale peptide flexibility in the broad contact area. CONCLUSIONS: The demonstrated protocol provides the extension of the CABS-dock method that can be practically used in the structure prediction of protein-peptide complexes guided by the knowledge of the binding interface.

N-(2-hydroxyphenyl)-2-propylpentanamide, a valproic acid aryl derivative designed in silico with improved anti-proliferative activity in HeLa, rhabdomyosarcoma and breast cancer cells.

Epigenetic alterations are associated with cancer and their targeting is a promising approach for treatment of this disease. Among current epigenetic drugs, histone deacetylase (HDAC) inhibitors induce changes in gene expression that can lead to cell death in tumors. Valproic acid (VPA) is a HDAC inhibitor that has antitumor activity at mM range. However, it is known that VPA is a hepatotoxic drug. Therefore, the aim of this study was to design a set of VPA derivatives adding the arylamine core of the suberoylanilide hydroxamic acid (SAHA) with different substituents at its carboxyl group. These derivatives were submitted to docking simulations to select the most promising compound. The compound 2 (N-(2-hydroxyphenyl)-2-propylpentanamide) was the best candidate to be synthesized and evaluated in vitro as an anti-cancer agent against HeLa, rhabdomyosarcoma and breast cancer cell lines. Compound 2 showed a better IC50 (µM range) than VPA (mM range) on these cancer cells. And also, 2 was particularly effective on triple negative breast cancer cells. In conclusion, 2 is an example of drugs designed in silico that show biological properties against human cancer difficult to treat as triple negative breast cancer.