Molecular Modeling Program Research Articles

Physicochemical properties as a function of lomefloxacin biological activity.

Aim: The goal is to discover QSAR of Lomefloxacin as antibacterial activity. Materials and Methods: A number of lomefloxacins analogs activities were studied by program Windows Chem SW. The analogues were obtained and energy minimization was carried out through Molecular Modeling Program, the calculations were performed using General Atomic and Molecular Electronic Structure System (GAMESS) software. Results: There were six descriptions (N-quinoline more (-) ev charge, Kinetic Energy, Potential Energy, Log p, Log S, F6 charge) results have highly compatible of physicochemical properties with lomefloxacin analogs activities. It can be used to estimate the activities depending on QSAR equation of lomefloxacin analogs. Conclusions: The parameters used for calculation were depending on the quantum chemical was employed in deriving from computational study of properties and can used to predict the activities of certain analogs of Lomefloxacins as antibacterial compounds.

Tetrasiklin Antibiyotikleri ve Bromelain Enzimi Arasındaki Etkileşimlerin Kenetleme Araçları Kullanılarak İncelenmesi

Bromelain, extracted from the stem of the pineapple, is a complex enzyme used for different purposes. Bromelain supplements are often used to facilitate digestion, improve the circulatory system and relieve arthritis symptoms due to its pain relief. However, in some cases where there is a risk of antibiotic use or bleeding, the use of bromelain or direct consumption of pineapple should be limited. For this purpose, this study was carried out to show the mechanism by which the antibiotic bromelain interaction occurs. Firstly, the bromelain molecule and demeclocycline, minocycline, and tetracycline antibiotics were prepared in the UCSF Chimera visualizing program. The interactions were monitored in the Auto Dock Molecular Modelling Toolkit molecular modeling program. The free binding energies of these interactions were also calculated in Auto Dock. According the molecular modelling results, bromelain and demeclocycline, minocycline, tetracycline antibiotics were interact with hydrogen bonds and hydrophobic interactions. These interactions between bromelain and antibiotics were energetically favorable based on free binding energy calculations.

Prediction of antimicrobial activity of a food peptide and evaluation of its effectiveness in vitro

Food antimicrobial peptides are increasingly relevant in the treatment of bacterial infections and have a number of advantages in comparison with drugs: slower emergence of resistance in bacterial strains, high activity against antibiotic films and immunomodulatory properties. The physico-chemical properties causing antimicrobial properties include: cationic charge, hydrophobicity, molecular weight and amino acid sequence. Promising sources of antimicrobial peptides are milk proteins, in particular, cow colostrum proteins. The aim of the work is to extract a peptide from the pepsin hydrolysate of cow colostrum, predict its antimicrobial activity using a bioinformatic approach and confirm its effectiveness in vitro. The molecular mass distribution of the peptide was evaluated by mass spectrometric method. The analysis of mass spectra was carried out using the Mascot program, the Peptide Fingerprint option – using the Protein NCBI database. Microsequencing was performed using a MiSeq sequencer. Modeling of the spatial structure of the isolated peptide was carried out using the Schrodinger Maestro molecular modeling program. The antimicrobial activity of the peptide was studied by the disco-diffusion method on gram-positive and gram-negative bacteria. The peptide has been isolated from the pepsin hydrolysate of cow colostrum, which is absent in the known proteomic bases Protein NCBI and AVPdb and, accordingly, its biological activity and functions have not been studied. The resulting peptide belongs to linear alpha-helical peptides consists of 11 amino acid sequences ANRKLRANKSR with a molecular weight of 8.2 kDa, an isoelectric point at 12.79, a charge of +5 (cationic), hydrophilicity (hydrophobicity) +20.84 Kcal*mol-1. As a result of in vitro studies, it was found that the isolated peptide has antimicrobial activity against E. coli ATCC 25922 and B. subtilis and antimicrobial action against C. albicans.

De novo design of stable proteins that efficaciously inhibit oncogenic G proteins.

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an "inside-out" approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gαq and its effector PLC-β isozymes. Several of the designed proteins remain folded above 90°C and bind to Gαq with equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gαq , the designed proteins inhibit activation of PLC-β isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection.

Inside-Out Design of Zinc-Binding Proteins with Non-Native Backbones.

The de novo design of functional proteins requires specification of tertiary structure and incorporation of molecular binding sites. Here, we develop an inside-out design strategy in the molecular modeling program Rosetta that begins with amino acid side chains from one or two α-helices making well-defined contacts with a ligand. A full-sized protein is then built around the ligand by adding additional helices that promote the formation of a protein core and allow additional contacts with the ligand. The protocol was tested by designing 12 zinc-binding proteins, each with 4-5 helices. Four of the designs were folded and bound to zinc with equilibrium dissociation constants varying between 95 nM and 1.1 μM. The design with the tightest affinity for zinc, N12, adopts a unique conformation in the folded state as assessed with nuclear magnetic resonance (NMR) and the design model closely matches (backbone root-mean-square deviation (RMSD) < 1 Å) an AlphaFold model of the sequence. Retrospective analysis with AlphaFold suggests that the sequences of many of the failed designs did not encode the desired tertiary packing.

MYOGLOBIN vs. HEMOGLOBIN BLOCKADE MODEL RELATED SMOKE GAS INHALATION - A COMPUTATIONAL ANALYSIS

To identify the pattern of myoglobin compared to hemoglobin blockade by the combustion products contained in the fire smoke using computational chemistry tools. The myoglobin unavailability can be a determining factor of the severity and consequences of smoke poisoning, generating the inability of patients to attempt evacuate themselves, compromising myocardial function, leading to crush syndrome-like effects and increasing of multi-organ failure to the victims of mass burn casualties event. In this study, it was used quantum chemical calculations performed with the Gaussian program suite using DFT/B3LYP/6-311G level of theory to optimize molecular geometries, calculate the molecular electrostatic potential, and obtain the vibrational spectrum. These calculations were applied to the myoglobin and hemoglobin model, thus studying their binding to the essential components of toxic fire smoke. Comparing the structural descriptors – frontier molecular orbitals, energy difference, electric dipole moment (μ), was obtained the highest values as belonging to hydrogen cyanide (2.9), which may explain its increased reactivity, meaning strong interaction with both myoglobin and hemoglobin, followed by hydrochloric acid (1.03) and carbon monoxide (0.122). Within the framework of complex intoxication generated by the inhalation of fire smoke, myoglobin is blocked in a temporal manner and according to a very similar pattern to hemoglobin. It follows that the significant rhabdomyolysis found in these patients is due not only to hypoxemia but also to the primary unavailability of myoglobin, and myocardial damage is also multifactorial. Although slightly discussed, the calculation of different structural and geometric descriptors for hydrochloric acid reveals for hydrochloric acid high values, suggesting binding affinities comparable to those of carbon monoxide. Molecular modeling programs allow for new approaches and can identify parameters or areas of their reference that influence the management of patients intoxicated with fire smoke components.

Stabilizing proteins, simplified: A Rosetta-based webtool for predicting favorable mutations.

Many proteins have low thermodynamic stability, which can lead to low expression yields and limit functionality in research, industrial and clinical settings. This article introduces two, web-based tools that use the high-resolution structure of a protein along with the Rosetta molecular modeling program to predict stabilizing mutations. The protocols were recently applied to three genetically and structurally distinct proteins and successfully predicted mutations that improved thermal stability and/or protein yield. In all three cases, combining the stabilizing mutations raised the protein unfolding temperatures by more than 20°C. The first protocol evaluates point mutations and can generate a site saturation mutagenesis heatmap. The second identifies mutation clusters around user-defined positions. Both applications only require a protein structure and are particularly valuable when a deep multiple sequence alignment is not available. These tools were created to simplify protein engineering and enable research that would otherwise be infeasible due to poor expression and stability of the native molecule.

AlphaFold accurately predicts distinct conformations based on the oligomeric state of a de novo designed protein.

Using the molecular modeling program Rosetta, we designed a de novo protein, called SEWN0.1, which binds the heterotrimeric G protein Gαq. The design is helical, well-folded, and primarily monomeric in solution at a concentration of 10μM. However, when we solved the crystal structure of SEWN0.1 at 1.9Å, we observed a dimer in a conformation incompatible with binding Gαq . Unintentionally, we had designed a protein that adopts alternate conformations depending on its oligomeric state. Recently, there has been tremendous progress in the field of protein structure prediction as new methods in artificial intelligence have been used to predict structures with high accuracy. We were curious if the structure prediction method AlphaFold could predict the structure of SEWN0.1 and if the prediction depended on oligomeric state. When AlphaFold was used to predict the structure of monomeric SEWN0.1, it produced a model that resembles the Rosetta design model and is compatible with binding Gαq , but when used to predict the structure of a dimer, it predicted a conformation that closely resembles the SEWN0.1 crystal structure. AlphaFold's ability to predict multiple conformations for a single protein sequence should be useful for engineering protein switches.

Characterization, theoretical computation, DNA‐binding, molecular docking, antibacterial, and antioxidant activities of new metal complexes of (E)‐1‐([1H‐1,2,4‐triazol‐3‐yl]diazenyl)naphthalen‐2‐ol

AbstractComplexes of (E)‐1‐([1H‐1,2,4‐triazol‐3‐yl]diazenyl)naphthalen‐2‐ol with manganese (II), cobalt (II), nickel (II), and zinc (II) have been constructed. Elemental analyses, molar conductance, magnetic moment measurements, spectral (IR, 1H, 13C NMR, EI‐mass, and UV–Vis), XRD, and thermal studies have all been used to determine the structure of complexes. Except for Ni (II), which has a tetrahedral geometry, the results demonstrated that all complexes have octahedral geometry. The molecular mechanic calculations used in the hyper chem. 8.03 molecular modeling program were used to determine the potential structures of metal complexes. To confirm the geometrical geometries of the investigated metal complexes, the bond lengths, bond angles, LUMO, HOMO, and dipole moments of the listed complexes were determined. At varied heating rates, the thermal analysis (TG) measurements are also investigated. Different integral equations were used to compute the kinetic and thermodynamic characteristics of the thermal degradation processes. UV–Vis absorption titration was used to study the complexes' DNA binding mechanisms. The results revealed that the complexes attach to DNA in either intercalative or non‐intercalative manner. Azodye and its metal complexes were tested in vitro against Gram positive bacteria (Staphylococcus aureus), Gram negative bacteria (Escherichia coli and Pseudomonas aeruginosa), fungi (Aspergillus flavus, Candida albicans, and Mucor), and yeast (Malassezia furfur). The azodye and its metal chelates have shown potent antioxidant activities. The molecular docking analysis has been tested with Topoisomerase II protein code: 4CHT model.

Insulin Complexation with Cyclodextrins-A Molecular Modeling Approach.

Around 5% of the population of the world is affected with the disease called diabetes mellitus. The main medication of the diabetes is the insulin; the active form is the insulin monomer, which is an instable molecule, because the long storage time, or the high temperature, can cause the monomer insulin to adapt an alternative fold, rich in β-sheets, which is pharmaceutically inactive. The aim of this study is to form different insulin complexes with all the cyclodextrin used for pharmaceutical excipients (native cyclodextrin, methyl, hydroxyethyl, hydroxypropyl and sulfobutylether substituted β-cyclodextrin), in silico condition, with the AutoDock molecular modeling program, to determine the best type of cyclodextrin or cyclodextrin derivate to form a complex with an insulin monomer, to predict the molar ratio, the conformation of the complex, and the intermolecular hydrogen bonds formed between the cyclodextrin and the insulin. From the results calculated by the AutoDock program it can be predicted that insulin can make a stable complex with 5–7 molecules of hydroxypropyl-β-cyclodextrin or sulfobutylether-β-cyclodextrin, and by forming a complex potentially can prevent or delay the amyloid fibrillation of the insulin and increase the stability of the molecule.

Optimization of covalent docking for organophosphates interaction with Anopheles acetylcholinesterase

Organophosphates (OPs) used as potent insecticides for malaria vector control, covalently phosphorylate the catalytic serine residue of Anopheles gambiae AChE (AgAChE) in a reaction that liberates their leaving groups. In the recent 10-year insecticide use assessment, OPs were the most frequently used World Health Organization prequalified insecticides. Molecular modelling programs are best suited to display molecular interactions between ligands and the target proteins. The docking modes that generate ligand poses closer to the binding site show high accuracy in predicting the ligand binding mode. The implicit solvation approach such as molecular mechanics-generalized born surface area (MM-GBSA) is a more reliable method to predict ligand onformations and binding affinities. Apart from covalent docking studies being scarce, current molecular docking programs do not adequately possess the covalent docking reaction algorithm to display the molecular mechanism of OPs at the AgAChE catalytic site. This results into OP docking studies commonly being conducted through noncovalent pannels. The aim of this study was to establish the optimim covalent docking system for OPs through manual customization of Schrödinger's Glide covalent docking reaction algorithm. To achieve this, a newly customized covalent reaction algorithm was assessed on a set of ligands covering aromatic, non-aromatic and hydrophobic OPs and compared to the noncovalent docking results in terms of reliability based on the reported X-ray diffraction molecular interactions and crystal poses. The study established that by virtue of omitting the well-known OP hydrolysis, noncovalent mode suggested molecular interactions that were further from the catalytic triad and could not otherwise occur when the molecule is hydrolyzed as in the customized covalent docking mode. Moreover, the MM-GBSA concurred with the optimized covalent docking in eliminating such inaccurate molecular interactions. Additionally, the covalent docking mode confined the interactions and ligand poses to the catalytic site indicating relatively high accuracy and reliability. This study reports the optimized covalent docking panel that effectively confirmed the molecular mechanisms of OPs, as well as indentifying the corresponding amino acid residues required to stabilize the aromatic, non-aromatic and hydrophobic OPs at the AgAChE catalytic site in line with the reported X-ray diffraction studies. As such, the proposed manual customization of the Schrödinger's Glide covalent docking platform can be used to reliably predict molecular interactions between OPs and AgAChE target.

Assembly of Biomolecular Gigastructures and Visualization with the Vulkan Graphics API.

Building and displaying all-atom models of biomolecular structures with millions or billions of atoms, like virus particles or cells, remain a challenge due to the sheer size of the data, the required levels of automated building, and the visualization limits of today’s graphics hardware. Based on concepts introduced with the CellPack program, we report new algorithms to create such large-scale models using an intermediate coarse-grained “pet representation” of biomolecules with 1/10th the normal size. Pet atoms are placed such that they optimally trace the surface of the original molecule with just ∼1/50th the original atom number and are joined with covalent bonds. Molecular dynamics simulations of pet molecules allow for efficient packing optimization, as well as the generation of realistic DNA/RNA conformations. This pet world can be expanded back to the all-atom representation to be explored and visualized with full details. Essential for the efficient interactive visualization of gigastructures is the use of multiple levels of detail (LODs), where distant molecules are drawn with a heavily reduced polygon count. We present a grid-based algorithm to create such LODs for all common molecular graphics styles (including ball-and-sticks, ribbons, and cartoons) that do not require monochrome molecules to hide LOD transitions. As a practical application, we built all-atom models of SARS-CoV-2, HIV, and an entire presynaptic bouton with 1 μm diameter and 3.6 billion atoms, using modular building blocks to significantly reduce GPU memory requirements through instancing. We employ the Vulkan graphics API to maximize performance on consumer grade hardware and describe how to use the mmCIF format to efficiently store such giant models. An implementation is available as part of the YASARA molecular modeling and simulation program from www.YASARA.org. The free YASARA View program can be used to explore the presented models, which can be downloaded from www.YASARA.org/petworld, a Creative Commons platform for sharing giant biomolecular structures.

From Proteomic Mapping to Invasion-Metastasis-Cascade Systemic Biomarkering and Targeted Drugging of Mutant BRAF-Dependent Human Cutaneous Melanomagenesis.

Simple SummaryDespite the recent advances in human malignancy therapy, metastasis and chemoresistance remain the principal causes of cancer-derived deaths. Given the fatal forms of cutaneous metastatic melanoma, we herein employed primary (WM115) and metastatic (WM266-4) melanoma cells, both obtained from the same patient, to identify novel biomarkers and therapeutic agents. Through state-of-the-art technologies including deep proteome landscaping, immunofluorescence phenotyping, and drug toxicity screening, we were able to describe new molecular programs, oncogenic drivers, and drug regimens, controlling the invasion-metastasis cascade during BRAFV600D-dependent melanomagenesis. It proved that proteomic navigation could foster the development of systemic biomarkering and targeted drugging for successful treatment of advanced disease.Melanoma is classified among the most notoriously aggressive human cancers. Despite the recent progress, due to its propensity for metastasis and resistance to therapy, novel biomarkers and oncogenic molecular drivers need to be promptly identified for metastatic melanoma. Hence, by employing nano liquid chromatography-tandem mass spectrometry deep proteomics technology, advanced bioinformatics algorithms, immunofluorescence, western blotting, wound healing protocols, molecular modeling programs, and MTT assays, we comparatively examined the respective proteomic contents of WM115 primary (n = 3955 proteins) and WM266-4 metastatic (n = 6681 proteins) melanoma cells. It proved that WM115 and WM266-4 cells have engaged hybrid epithelial-to-mesenchymal transition/mesenchymal-to-epithelial transition states, with TGF-β controlling their motility in vitro. They are characterized by different signatures of SOX-dependent neural crest-like stemness and distinct architectures of the cytoskeleton network. Multiple signaling pathways have already been activated from the primary melanoma stage, whereas HIF1α, the major hypoxia-inducible factor, can be exclusively observed in metastatic melanoma cells. Invasion-metastasis cascade-specific sub-routines of activated Caspase-3-triggered apoptosis and LC3B-II-dependent constitutive autophagy were also unveiled. Importantly, WM115 and WM266-4 cells exhibited diverse drug response profiles, with epirubicin holding considerable promise as a beneficial drug for metastatic melanoma clinical management. It is the proteome navigation that enables systemic biomarkering and targeted drugging to open new therapeutic windows for advanced disease.

Could Peganum harmala be effective in the treatment of COVID-19?

Predominant molecules in Peganum harmala leaves were detected using gas chromatography-mass spectrometry (GC-MS). Based on the results of this analysis, most alkaloids, flavonoids and triterpenoids in found P. harmala was compiled from the literature in order to develop and lead the production of effective inhibitor drugs for ACE2, main protease, and RNA dependent RNA polymerase (RdRp) proteins of SARS-CoV-2 virus, which is today's most contagious and deadly disease. By comparing FDA-approved drugs used in the treatment of COVID-19, we aimed to determine whether the molecules in P. harmala are effective against SARS CoV-2 in silico. P. harmala molecules were selected as drug candidates from the PubChem web tool. Afterwards, molecular docking calculations of these inhibitor molecules were made with Maestro Molecular modeling program by Schrödinger. The comparison of molecules with high inhibitory activities with FDA-approved drugs was made. With molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations, docking calculations of molecules that have high inhibitory activity, were tried to be verified by calculations in the range of 0-100 nanoseconds (Tab. 4, Fig. 6, Ref. 53).

Perturbing the energy landscape for improved packing during computational protein design.

The FastDesign protocol in the molecular modeling program Rosetta iterates between sequence optimization and structure refinement to stabilize de novo designed protein structures and complexes. FastDesign has been used previously to design novel protein folds and assemblies with important applications in research and medicine. To promote sampling of alternative conformations and sequences, FastDesign includes stages where the energy landscape is smoothened by reducing repulsive forces. Here, we discover that this process disfavors larger amino acids in the protein core because the protein compresses in the early stages of refinement. By testing alternative ramping strategies for the repulsive weight, we arrive at a scheme that produces lower energy designs with more native-like sequence composition in the protein core. We further validate the protocol by designing and experimentally characterizing over 4000 proteins and show that the new protocol produces higher stability proteins.

The interaction of metallic ions onto activated carbon surface using computational chemistry software

Activated carbon was prepared from the seeds of aguaje palm ( Mauritia flexuosa L.f.) by a chemical activation with phosphoric acid. This activated carbon was used for adsorbing metal ions: Pb(II), Cd(II), and Cr(III). To understand the mechanism of adsorption of these heavy metals (Cr, Cd, and Pb), the activated carbon surface was oxidized with nitric acid (1 M) increasing the oxygenated surface groups showing an increasing in their adsorption capacities of these metals. The oxidized activated carbon slightly increased the maximum adsorption capacity to 5–7%. The order of adsorption for unoxidized and oxidized activated carbons was Pb&gt; Cd&gt; Cr. This experimental information was corroborated by molecular modeling program Hyperchem 8 based adsorption mainly on two factors: the electron density and orbitals—highest occupied molecular orbital and lowest unoccupied molecular orbital.Activated carbons were characterized by adsorption/desorption of N2, obtaining an increase of microporous surface area for oxidized activated carbon. An increase of surface acidity and a reduction of isoelectric points were observed in oxidized activated carbon. According to these results, the adsorption of metal ions is favored in contact with an oxidized activated carbon, which has more amount of phenolic and carboxylic functional groups. Similarly, decreasing the isoelectric point indicates that the surface has a higher negative charge. The surface information was corroborated by Hyperchem, which indicates that the surface of the oxidized activated carbon has a higher electron density, indicating a larger amount of electrons on its surface, which means the surface of oxidized activated carbon charges negatively and thereby attracts metal ions.

Molecular interactions in liquid mixtures containing o-cresol and 1-alkanols: Thermodynamics, FT-IR and computational studies

Abstract To investigate the nature and class of association forces between the pure liquids and their liquid mixtures, we have been analyzed with excess thermodynamic properties, spectroscopic and computational techniques. Although, the thermodynamic parameters such as excess volume (VE), isentropic compressibility (ks) and excess isentropic compressibility (ksE) have been calculated using the experimental data of density (ρ) and speeds of sound (u) of o-cresol with 1-alkanols (C3–C8) namely, 1-propanol, 1-butanol, 1-pentanol, 1-hexanol, 1-heptanol and 1-octanol at different temperatures from 25 to 40 °C with interval of 5 °C and at 0.1 MPa. The calculated excess and deviation functions have been fitted to the Redlich-Kister polynomial equation and the results have been analyzed in terms of molecular interactions and structural effects. However, the FT-IR data strongly supports the presence of intra- and inter molecular interactions between component molecules in the liquid mixtures through changing the stretching vibrational frequency of various functional groups of pure liquids. In addition, the hydrogen bonding features between o-cresol with different 1-alkanols were examined by using a molecular modeling program with the help of density functional theory (DFT - B3LYP), the optimized geometries, bond characteristics, natural bond orbital (NBO) and interaction energies of pure components and their complexes have been analyzed theoretically to recognize the nature and strength of interactions between o-cresol and 1-alkanols.

Preparation, characterization of some transition metal complexes of hydrazone derivatives and their antibacterial and antioxidant activities

A new series of metal complexes of Pd(II), Cd(II) and Cu(II, I) of polydentate Schiff base ligand (H2L), namely ((Z)-2-(phenylamino)-N'-(thiophen-2-ylmethylene) acetohydrazide) have been prepared. The ligand and its metal complexes have been characterized based on various physicochemical studies as elemental analyses, molar conductance, spectral (UV–Vis, MS, IR, 1H NMR, 13C NMR and XRD), magnetic moment measurements and thermal studies (TG, DTG). In the view of previous studies, the ligand (H2L) acts as polydentate one and coordinates with metal ions to form all metal complexes. The kinetic and thermodynamic parameters of decomposition process (ΔG, ΔH, ΔS) were calculated. The possible structures of the metal complexes have been computed using the molecular mechanic calculations using the hyper chem. 8.03 molecular modeling program. The calculations are performed to obtain the optimized molecular geometry. The antibacterial study of the selected compounds was assayed against two pathogenic bacteria. Moreover, the complexes (Cu II, I), Cd(II), Pd(II)) and the ligand revealed excellent antioxidant properties and could be useful in fighting the free radicals which occur in close connection with cancerous cells. It was remarkable that the two complexes (Cu II, I) demonstrated stronger antioxidant effects than their parent compounds. It is clear that the new complexes are good active compounds for use in a variety of applications.

A Computational Protocol for Regulating Protein Binding Reactions with a Light-Sensitive Protein Dimer

Light-sensitive proteins can be used to perturb signaling networks in living cells and animals with high spatiotemporal resolution. We recently engineered a protein heterodimer that dissociates when irradiated with blue light and demonstrated that by fusing each half of the dimer to termini of a protein that it is possible to selectively block binding surfaces on the protein when in the dark. On activation with light, the dimer dissociates and exposes the binding surface, allowing the protein to bind its partner. Critical to the success of this system, called Z-lock, is that the linkers connecting the dimer components to the termini are engineered so that the dimer forms over the appropriate binding surface. Here, we develop and test a protocol in the Rosetta molecular modeling program for designing linkers for Z-lock. We show that the protocol can predict the most effective linker sets for three different light-sensitive switches, including a newly designed switch that binds the Rho-family GTPase Cdc42 on stimulation with blue light. This protocol represents a generalized computational approach to placing a wide variety of proteins under optogenetic control with Z-lock.

Computer-based Engineering of Thermostabilized Antibody Fragments.

We used the molecular modeling program Rosetta to identify clusters of amino acid substitutions in antibody fragments (scFvs and scAbs) that improve global protein stability and resistance to thermal deactivation. Using this methodology, we increased the melting temperature (Tm) and resistance to heat treatment of an antibody fragment that binds to the Clostridium botulinum hemagglutinin protein (anti-HA33). Two designed antibody fragment variants with two amino acid replacement clusters, designed to stabilize local regions, were shown to have both higher Tm compared to the parental scFv and importantly, to retain full antigen binding activity after 2 hours of incubation at 70 °C. The crystal structure of one thermostabilized scFv variants was solved at 1.6 Å and shown to be in close agreement with the RosettaAntibody model prediction.