Structure prediction of loops with fixed and flexible stems

Deciphering the binding mode and structural perturbations in floxuridine-human serum albumin complexation with spectroscopic, microscopic, and computational techniques

The binding mode of antineoplastic antimetabolite, floxuridine (FUDR), with human serum albumin (HSA), the leading carrier in blood circulation, was ascertained using multi-spectroscopic, microscopic, and computational techniques. A static fluorescence quenching was established due to decreased Ksv values with rising temperatures, suggesting FUDR-HSA complexation. UV-vis absorption spectral results also supported this conclusion. The binding constant, Ka values, were found within 9.7-7.9 × 103 M-1 at 290, 300, and 310 K, demonstrating a moderate binding affinity for the FUDR-HSA system. Thermodynamic data (ΔS = +46.35 J.mol-1.K-1 and ΔH = -8.77 kJ.mol-1) predicted the nature of stabilizing forces (hydrogen-bonds, hydrophobic, and van der Waals interactions) for the FUDR-HSA complex. Circular dichroism spectra displayed a minor disruption in the protein's 2° and 3° structures. At the same time, atomic force microscopy images proved variations in the FUDR-HSA surface morphology, confirming its complex formation. The protein's microenvironment around Trp/Tyr residues was also modified, as judged by 3-D fluorescence spectra. FUDR-bound HSA showed better resistance against thermal stress. As disclosed from ligand displacement studies, the FUDR binding site was placed in subdomain IIA (Site I). Further, the molecular docking analysis corroborated the competing displacement studies. Molecular dynamics evaluations revealed that the complex achieved equilibrium during simulations, confirming the FUDR-HSA complex's stability.

Vanadium complex as a potential modulator of the autophagic mechanism through proteins PI3K and ULK1: development, validation and biological implications of a specific force field for [VO(bpy)2Cl]

The modulation of autophagy has been presented as a very useful strategy in anticancer treatments. In this sense, the vanadium complex (VC) bis(2,2'-bipyridine)chlorooxovanadium(IV), [VO(bpy)2Cl], is known for its ability to induce autophagy in triple-negative breast cancer cells (TNBC). An excellent resource to investigate the role of VC in the induction of autophagy is to make use of Molecular Dynamics (MD) simulations. However, until now, the scarcity of force field parameters for the VC prevented a reliable analysis. The autophagy signaling pathway starts with the PI3K protein and ends with ULK1. Therefore, in the first stage of this work, we developed a new AMBER force field for the VC (VCFF) from a quantum structure, obtained by DFT calculations. In the second stage, the VCFF was validated through structural analyses. From this, it was possible to investigate, through docking and MD (200 ns), the performance of the PI3K-VC and ULK1-VC systems (third stage). The analyses of this last stage involved RMSD, hydrogen bonds, RMSF and two pathways for the modulation of autophagy. In general, this work fills in the absence of force field parameters (FF) for VC by proposing an efficient and new FF, in addition to investigating, at the molecular level, how VC is able to induce autophagy in TNBC cells. This study encourages new parameterizations of metallic complexes and contributes to the understanding of the duality of autophagic processes.Communicated by Ramaswamy H. Sarma.

Molecular Dynamics-Assisted Interaction of Vanadium Complex-AMPK: From Force Field Development to Biological Application for Alzheimer's Treatment

A large part of the world's population is affected by Alzheimer's disease (AD) and diabetes mellitus type 2, which cause both social and economic impacts. These two conditions are associated with one protein, AMPK. Studies have shown that vanadium complexes, such as bis(N',N'-dimethylbiguanidato)-oxovanadium(IV), VO(metf)₂·H₂O, are potential agents against AD. A crucial step in drug design studies is obtaining information about the structure and interaction of these complexes with the biological targets involved in the process through molecular dynamics (MD) simulations. However, MD simulations depend on the choice of a good force field that could present reliable results. Moreover, general force fields are not efficient for describing the properties of metal complexes, and a VO(metf)₂·H₂O-specific force field does not yet exist; thus, the proper development of a parameter set is necessary. Furthermore, this investigation is essential and relevant given the importance for both the scientific community and the population that is affected by this neurodegenerative disease. Therefore, the present work aims to develop and validate the AMBER force field parameters for VO(metf)₂·H₂O since the literature lacks such information on metal complexes and investigate through classical molecular dynamics the interactions made by the complex with the protein. The proposed force field proved to be effective for describing the vanadium complex (VC), supported by different analyses and validations. Moreover, it had a great performance when compared to the general AMBER force field. Beyond that, MD findings provided an in-depth perspective of vanadium complex-protein interactions that should be taken into consideration in future studies.

Novel Dual AChE and ROCK2 Inhibitor Induces Neurogenesis via PTEN/AKT Pathway in Alzheimer's Disease Model

Alzheimer's disease (AD) is a progressive and complex neurodegenerative disease. Acetylcholinesterase inhibitors (AChEIs) are a major class of drugs used in AD therapy. ROCK2, another promising target for AD, has been associated with the induction of neurogenesis via PTEN/AKT. This study aimed to characterize the therapeutic potential of a novel donepezil-tacrine hybrid compound (TA8Amino) to inhibit AChE and ROCK2 protein, leading to the induction of neurogenesis in SH-SY5Y cells. Experiments were carried out with undifferentiated and neuron-differentiated SH-SY5Y cells submitted to treatments with AChEIs (TA8Amino, donepezil, and tacrine) for 24 h or 7 days. TA8Amino was capable of inhibiting AChE at non-cytotoxic concentrations after 24 h. Following neuronal differentiation for 7 days, TA8Amino and donepezil increased the percentage of neurodifferentiated cells and the length of neurites, as confirmed by β-III-tubulin and MAP2 protein expression. TA8Amino was found to participate in the activation of PTEN/AKT signaling. In silico analysis showed that TA8Amino can stably bind to the active site of ROCK2, and in vitro experiments in SH-SY5Y cells demonstrate that TA8Amino significantly reduced the expression of ROCK2 protein, contrasting with donepezil and tacrine. Therefore, these results provide important information on the mechanism underlying the action of TA8Amino with regard to multi-target activities.

Molecular insights into the interaction of 5-fluorouracil and Fe3O4 nanoparticles with beta-casein: An experimental and theoretical study

We investigated the potential carrier of milk beta-casein (β-CN) and its interactions with 5-fluorouracil (5-FU) and iron oxide nanoparticles (Fe₃O₄ NPs). We used different spectroscopic methods of fluorescence, UV-Visble, circular dichroism (CD), synchronous fluorescence, zeta potential assay, and computational studies to clarify the protein interaction with 5-FU and Fe₃O₄ NPs. The fluorescence data indicated both Fe₃O₄ NPs and 5-FU could quench the intrinsic fluorescence of β-CN. Fluorescence measurements showed that the single interaction of β-CN with 5-FU or Fe₃O₄ NPs was static, while reacted β-CN with both 5-FU and Fe₃O₄ NPs simultaneously showed a dynamic quenching. Synchronous fluorescence data in both tests revealed that the tryptophan (Trp) residue of β-CN had a dominant role in quenching and the polarity of its microenvironment more than tyrosine (Tyr) increased in interaction with 5-FU. All the binding sites and thermodynamic parameters were obtained at 25, 37, and 42 °C. The analysis of thermodynamic parameters and Job's plot techniques pointed to that both of these complexes with the 1:1 M ratio were exothermic (ΔH°<0) driven with the van der Waals and H-bonding interactions (in agreement with the docking results). The CD spectra in the region of far-UV and thermal denaturation study indicated minor changes in the secondary structure of β-CN in the presence of various concentrations of Fe₃O₄ NPs and 5-FU. Also, from the molecular dynamics (MD) analysis, as a result, the protein structure was stable during 100 ns. The outcomes highlighted that β-CN protein could form a great bind with 5-FU and Fe₃O₄ NPs ligands (supporting the zeta potential assay results) by independent binding sites. These results would be helpful insight to construct a potential magnetic nanocarrier β-CN base for 5-FU drug delivery.

Biomolecular interaction mechanism of an anticancer drug, pazopanib with human serum albumin: a multi-spectroscopic and computational approach

Pazopanib (PZP) is a multi-targeting tyrosine kinase inhibitor and is currently approved by FDA for the treatment of soft tissue sarcoma and renal cancer. Molecular interaction mechanism of PZP with human serum albumin (HSA) was explored under simulated physiological conditions (pH = 7.4), using fluorescence and UV absorption spectroscopy along with computational methods. Based on the inverse correlation between the Stern-Volmer constant (K_sv) and temperature, it was concluded that PZP quenched the protein fluorescence through static quenching mechanism. This was also confirmed from the UV-vis absorption spectral results. Moderate binding affinity between PZP and HSA was evident from the K_a values (5.51 - 1.05 × 10⁵ M^-1) while PZP-HSA complex formation was driven by hydrophobic and van der Waals interactions as well as hydrogen bonds, as revealed by positive entropy change (ΔS = +98.37 J mol^-1 K^-1) and negative enthalpy change (ΔH = -60.31 kJ mol^-1). Three-dimensional fluorescence spectral results disclosed microenvironmental perturbations around Trp and Tyr residues of the protein upon PZP binding. Interestingly, the addition of PZP to HSA significantly protected the protein against thermal stress. Competitive drug displacement results obtained with warfarin, phenylbutazone and diazepam elucidated Sudlow's Site I, positioned in subdomain IIA of HSA, as the preferred binding site of PZP which was well supported by molecular docking analysis, while molecular dynamics simulation results suggested the stability of the PZP-HSA complex.Communicated by Vsevolod Makeev.

Structuraland antigenic analysis of a new Rhoptry Pseudokinase Gene (ROP54) in Toxoplasma gondii

Toxoplasma gondii is defined as an obligate intracellular apicomplexan parasite and influences approximatelyone-third of the human all over the world. ROP54 protein is expressed in the rhoptry of Toxoplasma gondii. In the present study, we used SMART software to analyzethe secondary structure of ROP54. The 3D model of ROP54 protein was constructed and analyzed using SWISS-MODEL server and VMD software. The structure results fully showed that ROP54 proteinis an importantmember from the ROP family. Moreover, DNAMAN software and Epitope Database online service were used to analyze liner-B cell epitopes and Th-cell epitopes of the protein. The bioinformatics prediction of ROP54 protein could provide positive information on treatment and vaccine for toxoplasmosis. Furthermore, ROP54 gene was obtained from PCR, and a recombinant eukaryotic expression vector (pEGFP-ROP54) was constructed in the following study. After identification of enzyme digestion, the constructed plasmid was transfected into HEK 293-T cells. The RT-PCR result suggested that the recombinant plasmid could transcribe successfully in HEK 293-T cell.

Algorithms for protein design

Computational structure-based protein design programs are becoming an increasingly important tool in molecular biology. These programs compute protein sequences that are predicted to fold to a target structure and perform a desired function. The success of a program's predictions largely relies on two components: first, the input biophysical model, and second, the algorithm that computes the best sequence(s) and structure(s) according to the biophysical model. Improving both the model and the algorithm in tandem is essential to improving the success rate of current programs, and here we review recent developments in algorithms for protein design, emphasizing how novel algorithms enable the use of more accurate biophysical models. We conclude with a list of algorithmic challenges in computational protein design that we believe will be especially important for the design of therapeutic proteins and protein assemblies.

Conformational sampling and structure prediction of multiple interacting loops in soluble and β-barrel membrane proteins using multi-loop distance-guided chain-growth Monte Carlo method

MOTIVATION

Loops in proteins are often involved in biochemical functions. Their irregularity and flexibility make experimental structure determination and computational modeling challenging. Most current loop modeling methods focus on modeling single loops. In protein structure prediction, multiple loops often need to be modeled simultaneously. As interactions among loops in spatial proximity can be rather complex, sampling the conformations of multiple interacting loops is a challenging task.

RESULTS

In this study, we report a new method called multi-loop Distance-guided Sequential chain-Growth Monte Carlo (M-DiSGro) for prediction of the conformations of multiple interacting loops in proteins. Our method achieves an average RMSD of 1.93 Å for lowest energy conformations of 36 pairs of interacting protein loops with the total length ranging from 12 to 24 residues. We further constructed a data set containing proteins with 2, 3 and 4 interacting loops. For the most challenging target proteins with four loops, the average RMSD of the lowest energy conformations is 2.35 Å. Our method is also tested for predicting multiple loops in β-barrel membrane proteins. For outer-membrane protein G, the lowest energy conformation has a RMSD of 2.62 Å for the three extracellular interacting loops with a total length of 34 residues (12, 12 and 10 residues in each loop).

AVAILABILITY AND IMPLEMENTATION

The software is freely available at: tanto.bioe.uic.edu/m-DiSGro.

CONTACT

jinfeng@stat.fsu.edu or jliang@uic.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exploring the structure of the 100 amino-acid residue long N-terminus of the plant antenna protein CP29

The structure of the unusually long (∼100 amino-acid residues) N-terminal domain of the light-harvesting protein CP29 of plants is not defined in the crystal structure of this membrane protein. We studied the N-terminus using two electron paramagnetic resonance (EPR) approaches: the rotational diffusion of spin labels at 55 residues with continuous-wave EPR, and three sets of distances with a pulsed EPR method. The N-terminus is relatively structured. Five regions that differ considerably in their dynamics are identified. Two regions have low rotational diffusion, one of which shows α-helical character suggesting contact with the protein surface. This immobile part is flanked by two highly dynamic, unstructured regions (loops) that cover residues 10-22 and 82-91. These loops may be important for the interaction with other light-harvesting proteins. The region around residue 4 also has low rotational diffusion, presumably because it attaches noncovalently to the protein. This section is close to a phosphorylation site (Thr-6) in related proteins, such as those encoded by the Lhcb4.2 gene. Phosphorylation might influence the interaction with other antenna complexes, thereby regulating the supramolecular organization in the thylakoid membrane.

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Fast protein loop sampling and structure prediction using distance-guided sequential chain-growth Monte Carlo method

Loops in proteins are flexible regions connecting regular secondary structures. They are often involved in protein functions through interacting with other molecules. The irregularity and flexibility of loops make their structures difficult to determine experimentally and challenging to model computationally. Conformation sampling and energy evaluation are the two key components in loop modeling. We have developed a new method for loop conformation sampling and prediction based on a chain growth sequential Monte Carlo sampling strategy, called Distance-guided Sequential chain-Growth Monte Carlo (DISGRO). With an energy function designed specifically for loops, our method can efficiently generate high quality loop conformations with low energy that are enriched with near-native loop structures. The average minimum global backbone RMSD for 1,000 conformations of 12-residue loops is 1:53 A° , with a lowest energy RMSD of 2:99 A° , and an average ensembleRMSD of 5:23 A° . A novel geometric criterion is applied to speed up calculations. The computational cost of generating 1,000 conformations for each of the x loops in a benchmark dataset is only about 10 cpu minutes for 12-residue loops, compared to ca 180 cpu minutes using the FALCm method. Test results on benchmark datasets show that DISGRO performs comparably or better than previous successful methods, while requiring far less computing time. DISGRO is especially effective in modeling longer loops (10-17 residues).

LEAP: highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chains

Prediction of protein loop conformations without any prior knowledge (ab initio prediction) is an unsolved problem. Its solution will significantly impact protein homology and template-based modeling as well as ab initio protein-structure prediction. Here, we developed a coarse-grained, optimized scoring function for initial sampling and ranking of loop decoys. The resulting decoys are then further optimized in backbone and side-chain conformations and ranked by all-atom energy scoring functions. The final integrated technique called loop prediction by energy-assisted protocol achieved a median value of 2.1 Å root mean square deviation (RMSD) for 325 12-residue test loops and 2.0 Å RMSD for 45 12-residue loops from critical assessment of structure-prediction techniques (CASP) 10 target proteins with native core structures (backbone and side chains). If all side-chain conformations in protein cores were predicted in the absence of the target loop, loop-prediction accuracy only reduces slightly (0.2 Å difference in RMSD for 12-residue loops in the CASP target proteins). The accuracy obtained is about 1 Å RMSD or more improvement over other methods we tested. The executable file for a Linux system is freely available for academic users at http://sparks-lab.org.

Identification of Functional Regulatory Residues of the β -Lactam Inducible Penicillin Binding Protein in Methicillin-Resistant Staphylococcus aureus

Resistance to methicillin by Staphylococcus aureus is a persistent clinical problem worldwide. A mechanism for resistance has been proposed in which methicillin resistant Staphylococcus aureus (MRSA) isolates acquired a new protein called β-lactam inducible penicillin binding protein (PBP-2′). The PBP-2′ functions by substituting other penicillin binding proteins which have been inhibited by β-lactam antibiotics. Presently, there is no structural and regulatory information on PBP-2′ protein. We conducted a complete structural and functional regulatory analysis of PBP-2′ protein. Our analysis revealed that the PBP-2′ is very stable with more hydrophilic amino acids expressing antigenic sites. PBP-2′ has three striking regulatory points constituted by first penicillin binding site at Ser25, second penicillin binding site at Ser405, and finally a single metallic ligand binding site at Glu657 which binds to Zn²⁺ ions. This report highlights structural features of PBP-2′ that can serve as targets for developing new chemotherapeutic agents and conducting site direct mutagenesis experiments.

Protein WISDOM: a workbench for in silico de novo design of biomolecules

The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.

Toxoplasma gondii cathepsin proteases are undeveloped prominent vaccine antigens against toxoplasmosis

Background

Toxoplasma gondii, an obligate intracellular apicomplexan parasite, infects a wide range of warm-blooded animals including humans. T. gondii expresses five members of the C1 family of cysteine proteases, including cathepsin B-like (TgCPB) and cathepsin L-like (TgCPL) proteins. TgCPB is involved in ROP protein maturation and parasite invasion, whereas TgCPL contributes to proteolytic maturation of proTgM2AP and proTgMIC3. TgCPL is also associated with the residual body in the parasitophorous vacuole after cell division has occurred. Both of these proteases are potential therapeutic targets in T. gondii. The aim of this study was to investigate TgCPB and TgCPL for their potential as DNA vaccines against T. gondii.

Methods

Using bioinformatics approaches, we analyzed TgCPB and TgCPL proteins and identified several linear-B cell epitopes and potential Th-cell epitopes in them. Based on these results, we assembled two single-gene constructs (TgCPB and TgCPL) and a multi-gene construct (pTgCPB/TgCPL) with which to immunize BALB/c mice and test their effectiveness as DNA vaccines.

Results

TgCPB and TgCPL vaccines elicited strong humoral and cellular immune responses in mice, both of which were Th-1 cell mediated. In addition, all of the vaccines protected the mice against infection with virulent T. gondii RH tachyzoites, with the multi-gene vaccine (pTgCPB/TgCPL) providing the highest level of protection.

Conclusions

T. gondii CPB and CPL proteases are strong candidates for development as novel DNA vaccines.

What's in a loop?

DNAs and proteins are major classes of biomolecules that differ in many aspects. However, a considerable number of their members also share a common architectural feature that enables the assembly of multi-protein complexes and thereby permits the effective processing of signals: loop structures of substantial sizes. Here we briefly review a few representative examples and suggest a functional classification of different types of loop structures. In proteins, these loops occur in protein regions classified as intrinsically disordered. Studying such loops, their binders and their interactions with other loops should reveal much about cellular information computation and signaling network architectures. It is also expected to provide critical information for synthetic biologists and bioengineers.