ZDOCK Server Research Articles

Prediction of superantigen active sites and clonal expression of staphylococcal enterotoxin-like W

Objective: The docking and superantigen activity sites of staphylococcal enterotoxin-like W (SElW) and T cell receptor (TCR) were predicted, and its SElW was cloned, expressed and purified. Methods: AlphaFold was used to predict the 3D structure of SElW protein monomers, and the protein models were evaluated with the help of the SAVES online server from ERRAT, Ramachandran plot, and Verify_3D. The ZDOCK server simulates the docking conformation of SElW and TCR, and the amino acid sequences of SElW and other serotype enterotoxins were aligned. The primers were designed to amplify selw, and the fragment was recombined into the pMD18-T vector and sequenced. Then recombinant plasmid pMD18-T was digested with BamHⅠand Hind Ⅲ. The target fragment was recombined into the expression plasmid pET-28a(+). After identification of the recombinant plasmid, the protein expression was induced by isopropyl-beta-D- thiogalactopyranoside. The SElW expressed in the supernatant was purified by affinity chromatography and quantified by the BCA method. Results: The predicted three-dimensional structure showed that the SElW protein was composed of two domains, the amino-terminal and the carboxy-terminal. The amino-terminal domain was composed of 3 α-helices and 6 β-sheets, and the carboxy-terminal domain included 2 α-helices and 7 antiparallel β-sheets composition. The overall quality factor score of the SElW protein model was 98.08, with 93.24% of the amino acids having a Verify_3D score ≥0.2 and no amino acids located in disallowed regions. The docking conformation with the highest score (1 521.328) was selected as the analysis object, and the 19 hydrogen bonds between the corresponding amino acid residues of SElW and TCR were analyzed by PyMOL. Combined with sequence alignment and the published data, this study predicted and found five important superantigen active sites, namely Y18, N19, W55, C88, and C98. The highly purified soluble recombinant protein SElW was obtained with cloning, expression, and protein purification. Conclusions: The study found five superantigen active sites in SElW protein that need special attention and successfully constructed and expressed the SElW protein, which laid the foundation for further exploration of the immune recognition mechanism of SElW.

In silico analysis of the predicted protein-protein interaction of syntaxin-18, a putative receptor of Peregrinus maidis Ashmead (Hemiptera: Delphacidae) with Maize mosaic virus glycoprotein

The corn planthopper, Peregrinus maidis Ashmead (Hemiptera:Delphacidae), is a widely distributed insect pest which serves as a vector of two phytopathogenic viruses, Maize mosaic virus (MMV) and Maize stripe virus (MStV). It transmits the viruses in a persistent and propagative manner. MMV is an alphanucleorhabdovirus with a negative-sense, single-stranded RNA unsegmented genome. One identified insect vector protein that may serve as receptor to MMV is Syntaxin-18 (PmStx18) which belongs to the SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) proteins. SNAREs play major roles in the final stage of docking and subsequent fusion of diverse vesicle-mediated transport events. In this work, in silico analysis of the interaction of MMV glycoprotein (MMV G) and PmStx18 was performed. Various freely available protein-protein docking web servers were used to predict the 3 D complex of MMV G and PmStx18. Analysis and protein-protein interaction (PPI) count showed that the complex predicted by the ZDOCK server has the highest number of interaction and highest affinity, as suggested by the calculated solvation free energy gain upon formation of the interface (ΔiG = −31 kcal/mol). Molecular dynamics simulation of the complex revealed important interactions at the interface over the course of 25 ns. This is the first in silico analysis performed for the interaction on a putative receptor of P. maidis and MMV G. The results of the PPI prediction provide novel information for studying the role of Stx18 in the transport, docking and fusion events involved in virus particle transport in the insect vector cells and its release. Communicated by Ramaswamy H. Sarma

Computational structural assessment of BReast CAncer type 1 susceptibility protein (BRCA1) and BRCA1-Associated Ring Domain protein 1 (BARD1) mutations on the protein-protein interface.

Breast cancer type 1 susceptibility protein (BRCA1) is closely related to the BRCA2 (breast cancer type 2 susceptibility protein) and BARD1 (BRCA1-associated RING domain-1) proteins. The homodimers were formed through their RING fingers; however they form more compact heterodimers preferentially, influencing BRCA1 residues 1-109 and BARD1 residues 26-119. We implemented an integrative computational pipeline to screen all the mutations in BRCA1 and identify the most significant mutations influencing the Protein-Protein Interactions (PPI) in the BRCA1-BARD1 protein complex. The amino acids involved in the PPI regions were identified from the PDBsum database with the PDB ID: 1JM7. We screened 2118 missense mutations in BRCA1 and none in BARD1 for pathogenicity and stability and analyzed the amino acid sequences for conserved residues. We identified the most significant mutations from these screenings as V11G, M18K, L22S, and T97R positioned in the PPI regions of the BRCA1-BARD1 protein complex. We further performed protein-protein docking using the ZDOCK server. The native protein-protein complex showed the highest binding score of 2118.613, and the V11G mutant protein complex showed the least binding score of 1992.949. The other three mutation protein complexes had binding scores between the native and V11G protein complexes. Finally, a molecular dynamics simulation study using GROMACS was performed to comprehend changes in the BRCA1-BARD1 complex's binding pattern due to the mutation. From the analysis, we observed the highest deviation with lowest compactness and a decrease in the intramolecular h-bonds in the BRCA1-BARD1 protein complex with the V11G mutation compared to the native complex or the complexes with other mutations.

Factual insights of the allosteric inhibition mechanism of SARS-CoV-2 main protease by quercetin: an in silico analysis.

SARS-CoV-2 main protease (Mpro) cleaves the viral polypeptide 1a and 1ab in a site-specific ((L-Q|(S, A, G)) manner and produce functional enzymes for mediating viral replication. Numerous studies have reported synthetic competitive inhibitors against this target enzyme but increase in substrate concentration often reduces the effectiveness of such inhibitors. Allosteric inhibition by natural compound can provide safe and effective treatment by alleviating this limitation. Present study deals with in silico allosteric inhibition analysis of quercetin, against SARS-CoV-2-Mpro. Molecular docking of quercetin with Mpro revealed consistent binding of quercetin at a site other than active site in multiple runs, with the highest binding energy of − 8.31 kcal/mol, forming 6 H-bonds with residues Gln127, Cys128, Lys137, Asp289 and Glu290. Molecular dynamic simulation of 50 ns revealed high stability of Mpro-quercetin complex with RMSD values ranging from 0.1 to 0.25 nm. Moreover, native-Mpro and Mpro-quercetin complex conformations extracted at different time points from simulation trajectories were subjected to active site-specific docking with modelled substrate peptide (AVLQSGFR) by ZDOCK server. Results displayed site-specific cleavage of peptide when docked with native-Mpro. While substrate peptide remained intact when docked with Mpro-quercetin complex, also the binding energy of peptide reduced from 785 to 86 from 1 to 50 ns as quercetin induced alterations in the active site cavity reducing its affinity for the substrate. Further, no interactions were noticed between peptide and active site residues of Mpro-quercetin complex conformations at 40 and 50 ns. Hence, quercetin displayed effective allosteric inhibition potential against SARS-CoV-2 Mpro, and can be developed into an efficient treatment for COVID-19.

A phytochemical-based medication search for the SARS-CoV-2 infection by molecular docking models towards spike glycoproteins and main proteases.

Identifying best bioactive phytochemicals from different medicinal plants using molecular docking techniques demonstrates a potential pre-clinical compound discovery against SARS-CoV-2 viral infection. The in silico screening of bioactive phytochemicals with the two druggable targets of SARS-CoV-2 by simple precision/extra precision molecular docking methods was used to compute binding affinity at its active sites. phyllaemblicin and cinnamtannin class of phytocompounds showed a better binding affinity range (−9.0 to −8.0 kcal mol−1) towards both these SARS-CoV-2 targets; the corresponding active site residues in the spike protein were predicted as: Y453, Q496, Q498, N501, Y449, Q493, G496, T500, Y505, L455, Q493, and K417; and Mpro: Q189, H164, H163, P168, H41, L167, Q192, M165, C145, Y54, M49, and Q189. Molecular dynamics simulation further established the structural and energetic stability of protein–phytocompound complexes and their interactions with their key residues supporting the molecular docking analysis. Protein–protein docking using ZDOCK and Prodigy server predicted the binding pose and affinity (−13.8 kcal mol−1) of the spike glycoprotein towards the human ACE2 enzyme and also showed significant structural variations in the ACE2 recognition site upon the binding of phyllaemblicin C compound at their binding interface. The phyllaemblicin and cinnamtannin class of phytochemicals can be potential inhibitors of both the spike and Mpro proteins of SARS-CoV-2; furthermore, its pharmacology and clinical optimization would lead towards novel COVID-19 small-molecule therapy.

Energetics and IC50 based epitope screening in SARS CoV-2 (COVID 19) spike protein by immunoinformatic analysis implicating for a suitable vaccine development

BackgroundThe recent outbreak by SARS-CoV-2 has generated a chaos in global health and economy and claimed/infected a large number of lives. Closely resembling with SARS CoV, the present strain has manifested exceptionally higher degree of spreadability, virulence and stability possibly due to some unidentified mutations. The viral spike glycoprotein is very likely to interact with host Angiotensin-Converting Enzyme 2 (ACE2) and transmits its genetic materials and hijacks host machinery with extreme fidelity for self propagation. Few attempts have been made to develop a suitable vaccine or ACE2 blocker or virus-receptor inhibitor within this short period of time.MethodsHere, attempt was taken to develop some therapeutic and vaccination strategies with a comparison of spike glycoproteins among SARS-CoV, MERS-CoV and the SARS-CoV-2. We verified their structure quality (SWISS-MODEL, Phyre2, and Pymol) topology (ProFunc), motifs (MEME Suite, GLAM2Scan), gene ontology based conserved domain (InterPro database) and screened several epitopes (SVMTrip) of SARS CoV-2 based on their energetics, IC50 and antigenicity with regard to their possible glycosylation and MHC/paratope binding (Vaxigen v2.0, HawkDock, ZDOCK Server) effects.ResultsWe screened here few pairs of spike protein epitopic regions and selected their energetic, Inhibitory Concentration50 (IC50), MHC II reactivity and found some of those to be very good target for vaccination. A possible role of glycosylation on epitopic region showed profound effects on epitopic recognition.ConclusionThe present work might be helpful for the urgent development of a suitable vaccination regimen against SARS CoV-2.

Immunoglobulin interface redesigning to enhance lebrikizumab mediated immunomodulation of IL-13 hyper-response

The overexpression of interleukin-13 (IL-13) leads to autoimmune and inflammatory diseases. These adverse responses can be neutralized by using lebrikizumab as a therapeutic monoclonal antibody (mAb). Herein, we have attempted to modulate the lebrikizumab mAb to enhance its binding affinity towards IL-13. The interface residues of the lebrikizumab-IL-13 complex were determined by the PyMOL and verified by the artificial neural network-based B-cell epitope prediction server (ABCpred server) and the Paratome web server. The Cologne University Protein Stability Analysis Tool (CUPSAT) web server based mutational approach was used to identify the stable and favorable interface mutations in the lebrikizumab. Only 40 mutations were selected to generate a single mutant library, and their binding affinity for IL-13 was analyzed by using the Z-Dock server. Based on high Z-score, mutants having a better affinity with IL-13 were selected to create a multi-mutant library. The multi-mutant library was again subjected to the Z-Dock server, and their binding affinity was determined. The highest-scoring ten mAb mutants were validated by using PatchDock and ClusPro servers. The best two potential mAb mutants were identified and subjected to molecular dynamics (MD) simulations to ensure its structural stability at the microscopic level. The changes in the different bonds as the effect of mutation were assessed by LigPlot + v2.1. The AllerTOP and ToxinPred web servers were used to analyze the non-allergic and nontoxic nature of the selected mutants. Therefore, these redesigned mAb could be used for potential treatment against IL-13 associated diseased conditions. Communicated by Ramaswamy H. Sarma

Molecular characterization of a Trichinella spiralis enolase and its interaction with the host\u2019s plasminogen

The binding and activation of host plasminogen (PLG) by worm surface enolases has been verified to participate in parasite invasion, but the role of this processes during Trichinella spiralis infection has not been clarified. Therefore, the expression and immunolocalization of a T. spiralis enolase (TsENO) and its binding activity with PLG were evaluated in this study. Based on the three-dimensional (3D) molecular model of TsENO, the protein interaction between TsENO and human PLG was analysed by the ZDOCK server. The interacting residues were identified after analysis of the protein–protein interface by bioinformatics techniques. The key interacting residues were confirmed by a series of experiments. The qPCR analysis results demonstrated that Ts-eno was transcribed throughout the whole life cycle of T. spiralis. The immunofluorescence assay (IFA) results confirmed that TsENO was distributed on the T. spiralis surface. The binding assays showed that recombinant TsENO (rTsENO) and native TsENO were able to bind PLG. Four lysine residues (90, 289, 291 and 300) of TsENO were considered to be active residues for PLG interaction. The quadruple mutant (Lys90Ala + Lys289Ala + Lys291Ala + Lys300Ala) TsENO, in which the key lysine residues were substituted with alanine (Ala) residues, exhibited a reduction in PLG binding of nearly 50% (45.37%). These results revealed that TsENO has strong binding activity with human PLG. The four lysine residues (90, 289, 291 and 300) of TsENO play an important role in PLG binding and could accelerate PLG activation and invasion of the host’s intestinal wall by T. spiralis.

A novel protease-activated receptor 1 inhibitor from the leech Whitmania pigra

Whitmania pigra has been used as a traditional Chinese medicine (TCM) for promoting blood circulation, alleviating blood coagulation, activating meridians and relieving stasis for several hundred years. However, the therapeutic components of this species, especially proteins and peptides were poorly exploited. Until now only a few of them were obtained by using chromatographic isolation and purification. In recent decade, transcriptome techniques were rapidly developed, and have been used to fully reveal the functional components of many animal venoms. In the present study, the cDNA of the salivary gland of Whitmania pigra was sequenced by illumina and the transcriptome was assembled by using Trinity. The proteome were analysed by LC-MS/MS. Based on the data of the transcriptome and the proteome, a potential antiplatelet protein named pigrin was found. Pigrin was cloned and expressed using P. pastoris GS115. The antiplatelet andantithrombotic bioactivities of pigrin were tested by using aggregometer and the rat arterio-venous shunt thrombosis model, respectively. Thebleeding time of pigrin was measured by a mice tail cutting method. The docking of pigrin and protease-activated receptor 1 (PAR1) or collagen were conducted using the ZDOCK Server. Pigrin was able to selectively inhibit platelet aggregation stimulated by PAR1 agonist and collagen. Pigrin attenuated thrombotic formation in vivo in rat, while did not prolong bleeding time at its effective dosage. There are significant differences in the key residues participating in binding of Pigrin-Collagen complex from Pigrin-PAR1 complex. In conclusion,a novel PAR1 inhibitor pigrin was found from the leech Whitmania pigra. This study helped to elucidate the mechanism of the leech for the treatment of cardiovascular disorder.

Computational analysis and optimization of carcinoembryonic antigen aptamers and experimental evaluation

Carcinoembryonic antigen (CEA), a highly glycosylated protein, overexpresses in many cancers. In this study, computational methods were used to optimize CEA aptamers. Experimental evaluvation of selected aptamers were conducted through electrochemical impedance spectroscopy. After two and three-dimensional structure modeling, the complexes of twelve reported aptamers against CEA were simulated using the ZDOCK server. Based on docking scores, two aptamer sequences (CSR59 and CSR57.1) were selected and used to create a new library. This ssDNA aptamer library consisting of 91 sequences was created using diverse in silico mutational methods. We obtained seventeen sequences having higher binding scores than reported sequences. Based on ZDOCK scores, the interaction domain of CEA, and steric hindrance due to glycosylation, two aptamer sequences (G3S1.5 and G2S2.2) were selected. An impedimetric aptasensor was designed, and selected aptamers were used as biorecognition elements. Resistance to charge transfer (Rct) quantities confirmed the bioinformatic approach and molecular docking scores. The result showed that the interaction ability of selected aptamers was about 13.5 fold higher than the control. It can be concluded that the selected aptamers have good potential for detection of carcinoembryonic antigen biomarker.

Neuropilin-1 is a glial cell line-derived neurotrophic factor receptor in glioblastoma.

The aim of this study was to identify the receptor for glial cell line-derived neurotrophic factor (GDNF) in glioblastoma multiforme (GBM). After GST pull-down assays, membrane proteins purified from C6 rat glioma cells were subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The differentially expressed proteins were annotated using Gene Ontology, and neuropilin-1 (NRP1) was identified as the putative GDNF receptor in glioma. NRP1 was more highly expressed in human GBM brains and C6 rat glioma cells than in normal human brains or primary rat astrocytes. Immunofluorescence staining showed that NRP1 was recruited to the membrane by GDNF, and NRP1 co-immunoprecipitated with GDNF. Using the NRP1 and GDNF protein structures to assess molecular docking in the ZDOCK server and visualization with the PyMOL Molecular Graphics System revealed 8 H-bonds and stable positive and negative electrostatic interactions between NRP1 and GDNF. RNAi knockdown of NRP1 reduced proliferation of C6 glioma cells when stimulated with GDNF. NRP1 was an independent risk factor for both survival and recurrence in GBM patients. High NRP1 mRNA expression correlated with shorter OS and DFS (OS: χ2=4.6720, P=0.0307; DFS: χ2=11.013, P=0.0009). NRP1 is thus a GDNF receptor in glioma cells and a potential therapeutic target.

IRaPPA: information retrieval based integration of biophysical models for protein assembly selection.

MotivationIn order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction.ResultsAtomic modeling of protein–protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100.Availability and ImplementationIRaPPA has been implemented in the SwarmDock server (http://bmm.crick.ac.uk/∼SwarmDock/), pyDock server (http://life.bsc.es/pid/pydockrescoring/) and ZDOCK server (http://zdock.umassmed.edu/), with code available on request.Supplementary information Supplementary data are available at Bioinformatics online.

Mutations in Human Interferon α2b Gene and Potential as Risk Factor Associated with Female Breast Cancer.

The current study explored the potential links between breast cancer and human interferon α-2b (hIFNα-2b) gene mutations. The hIFNα-2b gene was amplified from breast cancer tumor tissue samples (N = 60) by polymerase chain reaction (PCR) and the products were subjected to gene sequencing. A total of 38 (63.3%) samples showed positive PCR amplification results. Several of these also exhibited frequent alterations (mutations) after 400 bp and, in particular, adenine was replaced by other bases. A total of 19 selected mutated amino acids were analyzed for local/general fold pattern changes. Human IFNα-2b receptor (IFNAR): ligand (hIFNα-2b protein) interactions through a Z-DOCK (3.0.2) server were also evaluated to assess the binding patterns of each ligand to receptor to induce Janus-Kinase-signal transducer and activator of transcription antiproliferative signal transduction pathway inside the cancer cells. Certain local structural and conformational changes were predicted to be induced by mutations in the ligand. The variant models of the hIFNα-2b displayed structural and conformational changes that signified that changes to hIFNα-2b may be a risk factor in addition to other known factors associated with onset/progression of female breast carcinoma. It was hoped that others might build upon the research in this study evaluating protein structural models with mutations and their consequent interactions with receptors in the development of potent immune therapeutic drugs for breast cancer that are based on recombinant hIFNα-2b.

A novel homozygous mutation disrupting the initiation codon in the SLURP1 gene underlies mal de Meleda in a consanguineous family.

Mal de Meleda (MDM) is a palmoplantar keratoderma (PPK), characterized by hyperkeratosis of the palms and soles, and keratotic skin lesions. Patients with MDM can develop perioral erythema, keratotic and lichenoid plaques over the joints (including the elbows and knees), nail abnormalities, joint contractures and stiffness, brachydactyly, sclerodactyly, pseudoainhum, and malodorous maceration. MDM is associated with mutations in the SLURP1 gene. We report a consanguineous family in which MDM was inherited in an autosomal recessive manner. Genotyping using microsatellite markers established linkage in the family to the SLURP1 gene, which has been mapped previously to chromosome 8q24.3. Sequence analysis revealed a homozygous missense mutation (c.2T>C, p.Met1Thr) in affected family members. Molecular docking studies using a ZDOCK server predicted disruption of binding of the mutant variant to its target α7-nAChR. This study further supports the previously reported findings that homozygous mutations in the SLURP1 gene cause MDM.

Computational approach to analyze isolated ssDNA aptamers against angiotensin II

Aptamers are oligonucleotides with highly structured molecules that can bind to their targets through specific 3-D conformation. Commonly, not all the nucleotides such as primer binding fixed region and some other sequences are vital for aptamers folding and interaction. Elimination of unnecessary regions needs trustworthy prediction tools to reduce experimental efforts and errors. Here we introduced a manipulated in-silico approach to predict the 3-D structure of aptamers and their target interactions. To design an approach for computational analysis of isolated ssDNA aptamers (FLC112, FLC125 and their truncated core region including CRC112 and CRC125), their secondary and tertiary structures were modeled by Mfold and RNA composer respectively. Output PDB files were modified from RNA to DNA in the discovery studio visualizer software. Using ZDOCK server, the aptamer-target interactions were predicted. Finally, the interaction scores were compared with the experimental results. In-silico interaction scores and the experimental outcomes were in the same descending arrangement of FLC112>CRC125>CRC112>FLC125 with similar intensity. The consistent results of innovative in-silico method with experimental outputs, affirmed that the present method may be a reliable approach. Also, it showed that the exact in-silico predictions can be utilized as a credible reference to find aptameric fragments binding potency.

Diabetes mellitus caused by mutations in human insulin: analysis of impaired receptor binding of insulins Wakayama, Los Angeles and Chicago using pharmacoinformatics

Several naturally occuring mutations in the human insulin gene are associated with diabetes mellitus. The three known mutant molecules, Wakayama, Los Angeles and Chicago were evaluated using molecular docking and molecular dynamics (MD) to analyse mechanisms of deprived binding affinity for insulin receptor (IR). Insulin Wakayama, is a variant in which valine at position A3 is substituted by leucine, while in insulin Los Angeles and Chicago, phenylalanine at positions B24 and B25 is replaced by serine and leucine, respectively. These mutations show radical changes in binding affinity for IR. The ZDOCK server was used for molecular docking, while AMBER 14 was used for the MD study. The published crystal structure of IR bound to natural insulin was also used for MD. The binding interactions and MD trajectories clearly explained the critical factors for deprived binding to the IR. The surface area around position A3 was increased when valine was substituted by leucine, while at positions B24 and B25 aromatic amino acid phenylalanine replaced by non-aromatic serine and leucine might be responsible for fewer binding interactions at the binding site of IR that leads to instability of the complex. In the MD simulation, the normal mode analysis, rmsd trajectories and prediction of fluctuation indicated instability of complexes with mutant insulin in order of insulin native insulin < insulin Chicago < insulin Los Angeles < insulin Wakayama molecules which corresponds to the biological evidence of the differing affinities of the mutant insulins for the IR.

Probing binding mechanism of interleukin-6 and olokizumab: in silico design of potential lead antibodies for autoimmune and inflammatory diseases

Computer-aided antibody engineering has been successful in the design of new biologics for disease diagnosis and therapeutic interventions. Interleukin-6 (IL-6), a well-recognized drug target for various autoimmune and inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, and psoriasis, was investigated in silico to design potential lead antibodies. Here, crystal structure of IL-6 along with monoclonal antibody olokizumab was explored to predict antigen–antibody (Ag − Ab)-interacting residues using DiscoTope, Paratome, and PyMOL. Tyr56, Tyr103 in heavy chain and Gly30, Ile31 in light chain of olokizumab were mutated with residues Ser, Thr, Tyr, Trp, and Phe. A set of 899 mutant macromolecules were designed, and binding affinity of these macromolecules to IL-6 was evaluated through Ag − Ab docking (ZDOCK, ClusPro, and Rosetta server), binding free-energy calculations using Molecular Mechanics/Poisson Boltzman Surface Area (MM/PBSA) method, and interaction energy estimation. In comparison to olokizumab, eight newly designed theoretical antibodies demonstrated better result in all assessments. Therefore, these newly designed macromolecules were proposed as potential lead antibodies to serve as a therapeutics option for IL-6-mediated diseases.

Molecular modeling of the binding modes of the iron-sulfur protein to the Jac1 co-chaperone from Saccharomyces cerevisiae by all-atom and coarse-grained approaches.

The iron-sulfur protein 1 (Isu1) and the J-type co-chaperone Jac1 from yeast are part of a huge ATP-dependent system, and both interact with Hsp70 chaperones. Interaction of Isu1 and Jac1 is a part of the iron-sulfur cluster biogenesis system in mitochondria. In this study, the structure and dynamics of the yeast Isu1-Jac1 complex has been modeled. First, the complete structure of Isu1 was obtained by homology modeling using the I-TASSER server and YASARA software and thereafter tested for stability in the all-atom force field AMBER. Then, the known experimental structure of Jac1 was adopted to obtain initial models of the Isu1-Jac1 complex by using the ZDOCK server for global and local docking and the AutoDock software for local docking. Three most probable models were subsequently subjected to the coarse-grained molecular dynamics simulations with the UNRES force field to obtain the final structures of the complex. In the most probable model, Isu1 binds to the left face of the Γ-shaped Jac1 molecule by the β-sheet section of Isu1. Residues L105 , L109 , and Y163 of Jac1 have been assessed by mutation studies to be essential for binding (Ciesielski et al., J Mol Biol 2012; 417:1-12). These residues were also found, by UNRES/molecular dynamics simulations, to be involved in strong interactions between Isu1 and Jac1 in the complex. Moreover, N(95), T(98), P(102), H(112), V(159), L(167), and A(170) of Jac1, not yet tested experimentally, were also found to be important in binding.

Molecular modeling and molecular dynamics simulation study of the human Rab9 and RhoBTB3 C-terminus complex.

Rab9 is required for the transport of mannose 6-phosphate receptors to the trans-Golgi network from late endosomes through the interaction with its effector: RhoBTB3. Earlier research indicates the C-terminus of RhoBTB3 (Rho_Cterm) is used for the interaction with Rab9. We used the homology modeling along with the molecular dynamics (MD) simulation to study the binding pattern of Rho_Cterm and Rab9 at atomic level. Both modeled structures, Rab9 and Rho_Cterm, are of high quality as suggested by the Ramachandran plot and ProCheck. The complex of Rab9-Rho_Cterm was generated by unrestrained pairwise docking using ZDOCK server. The interface of complex is consistent with the previous experimental data. The results of MD simulation indicate that the binding interface is stable along the simulation process.

ZDOCK server: interactive docking prediction of protein–protein complexes and symmetric multimers

Protein-protein interactions are essential to cellular and immune function, and in many cases, because of the absence of an experimentally determined structure of the complex, these interactions must be modeled to obtain an understanding of their molecular basis. We present a user-friendly protein docking server, based on the rigid-body docking programs ZDOCK and M-ZDOCK, to predict structures of protein-protein complexes and symmetric multimers. With a goal of providing an accessible and intuitive interface, we provide options for users to guide the scoring and the selection of output models, in addition to dynamic visualization of input structures and output docking models. This server enables the research community to easily and quickly produce structural models of protein-protein complexes and symmetric multimers for their own analysis. The ZDOCK server is freely available to all academic and non-profit users at: http://zdock.umassmed.edu. No registration is required.