An integrated suite of fast docking algorithms

Molecular characterization of glutor-GLUT interaction and prediction of glutor's drug-likeness: implications for its utility as an antineoplastic agent

Recent experimental evidence from our and other laboratories has strongly indicated that glutor, a piperazine-2-one derivative, which is a pan-GLUT inhibitor, displays a promising antineoplastic action by hampering glucose uptake owing to its ability to inhibit GLUT1 and GLUT3, which are overexpressed in neoplastic cells. However, the molecular mechanism(s) of the inhibiting action of glutor has remained elusive. Thus, for optimal utilization of the antineoplastic potential of glutor, it is essential to decipher the precise mechanism(s) of its interaction with GLUTs. Therefore, the present investigation was carried out to understand the molecular mechanism(s) of the binding of glutor to GLUT1 and GLUT3 in silico. This study suggests that glutor can effectively bind to GLUTs at the reported binding site. Moreover, the docking of glutor to GLUT was stabilised by several contacts between these two partners as shown by the 200 ns long molecular dynamic simulation carried out using Gromacs, indicating the formation of a stable complex. Moreover, glutor was found to possess all characteristics conducive to its drug-likeness. Hence, these observations suggest that glutor has the potential to be used in antineoplastic therapeutic applications.Communicated by Ramaswamy H. Sarma.

Investigation of Peptidoglycan-Associated Lipoprotein of Acinetobacter baumannii and Its Interaction with Fibronectin To Find Its Therapeutic Potential

Acinetobacter baumannii causes hospital-acquired infections and is responsible for high mortality and morbidity. The interaction of this bacterium with the host is critical in bacterial pathogenesis and infection. Here, we report the interaction of peptidoglycan-associated lipoprotein (PAL) of A. baumannii with host fibronectin (FN) to find its therapeutic potential. The proteome of A. baumannii was explored in the host-pathogen interaction database to filter out the PAL of the bacterial outer membrane that interacts with the host's FN protein. This interaction was confirmed experimentally using purified recombinant PAL and pure FN protein. To investigate the pleiotropic role of PAL protein, different biochemical assays using wild-type PAL and PAL mutants were performed. The result showed that PAL mediates bacterial pathogenesis, adherence, and invasion in host pulmonary epithelial cells and has a role in the biofilm formation, bacterial motility, and membrane integrity of bacteria. All of the results suggest that PAL's interaction with FN plays a vital role in host-cell interaction. In addition, the PAL protein also interacts with Toll-like receptor 2 and MARCO receptor, which suggests the role of PAL protein in innate immune responses. We have also investigated the therapeutic potential of this protein for vaccine and therapeutic design. Using reverse vaccinology, PAL's potential epitopes were filtered out that exhibit binding potential with host major histocompatibility complex class I (MHC-I), MHC-II, and B cells, suggesting that PAL protein is a potential vaccine target. The immune simulation showed that PAL protein could elevate innate and adaptive immune response with the generation of memory cells and would have subsequent potential to eliminate bacterial infection. Therefore, the present study highlights the interaction ability of a novel host-pathogen interacting partner (PAL-FN) and uncovers its therapeutic potential to combat infection caused by A. baumannii.

Protein-protein interfaces in molecular glue-induced ternary complexes: classification, characterization, and prediction

Molecular glues are a class of small molecules that stabilize the interactions between proteins. Naturally occurring molecular glues are present in many areas of biology where they serve as central regulators of signaling pathways. Importantly, several clinical compounds act as molecular glue degraders that stabilize interactions between E3 ubiquitin ligases and target proteins, leading to their degradation. Molecular glues hold promise as a new generation of therapeutic agents, including those molecular glue degraders that can redirect the protein degradation machinery in a precise way. However, rational discovery of molecular glues is difficult in part due to the lack of understanding of the protein-protein interactions they stabilize. In this review, we summarize the structures of known molecular glue-induced ternary complexes and the interface properties. Detailed analysis shows different mechanisms of ternary structure formation. Additionally, we also review computational approaches for predicting protein-protein interfaces and highlight the promises and challenges. This information will ultimately help inform future approaches for rational molecular glue discovery.

Experimental and clinical data analysis for identification of COVID-19 resistant ACE2 mutations

The high magnitude zoonotic event has caused by Severe Acute Respitarory Syndrome CoronaVirus-2 (SARS-CoV-2) is Coronavirus Disease-2019 (COVID-19) epidemics. This disease has high rate of spreading than mortality in humans. The human receptor, Angiotensin-Converting Enzyme 2 (ACE2), is the leading target site for viral Spike-protein (S-protein) that function as binding ligands and are responsible for their entry in humans. The patients infected with COVID-19 with comorbidities, particularly cancer patients, have a severe effect or high mortality rate because of the suppressed immune system. Nevertheless, there might be a chance wherein cancer patients cannot be infected with SARS-CoV-2 because of mutations in the ACE2, which may be resistant to the spillover between species. This study aimed to determine the mutations in the sequence of the human ACE2 protein and its dissociation with SARS-CoV-2 that might be rejecting viral transmission. The in silico approaches were performed to identify the impact of SARS-CoV-2 S-protein with ACE2 mutations, validated experimentally, occurred in the patient, and reported in cell lines. The identified changes significantly affect SARS-CoV-2 S-protein interaction with ACE2, demonstrating the reduction in the binding affinity compared to SARS-CoV. The data presented in this study suggest ACE2 mutants have a higher and lower affinity with SARS-Cov-2 S-protein to the wild-type human ACE2 receptor. This study would likely be used to report SARS-CoV-2 resistant ACE2 mutations and can be used to design active peptide development to inactivate the viral spread of SARS-CoV-2 in humans.

Bioengineering and computational analysis of programmed cell death ligand-1 monoclonal antibody

The trans-membrane proteins of the B7 family programmed cell death ligand-1 (PD-L1) and programmed death-1 (PD-1) play important roles in inhibiting immune responses and enhancing self-tolerance via T-cell modulation. Several therapeutic antibodies are used to promote T-cell proliferation by preventing interactions between PD-1/PD-L1. Recombinant technology appears to be quite useful in the production of such potent antibodies. In this study, we constructed recombinant molecules by cloning variable regions of the PD-L1 molecule into pMH3 vectors and transferring them into mammalian cell lines for expression. G418 supplementation was used to screen the recombinant clones, which were then maintained on serum-free medium. The full-length antibody was isolated and purified from the medium supernatant at a concentration of 0.5-0.8 mg/ml. Antibody binding affinity was investigated using ELISA and immunofluorescence methods. The protein-protein interactions (PPI) were determined using a docking approach. The SWISS model was utilized for homology modeling, while ZDOCK, Chimera, and PyMOL were used to validate 3D models. The Ramachandran plots were constructed using the SWISS model, which revealed that high-quality structures had a value of more than 90%. Current technologies allow for the accurate determination of antigen-antibody interactions.

Development of multivalent vaccine targeting M segment of Crimean Congo Hemorrhagic Fever Virus (CCHFV) using immunoinformatic approaches

Crimean-Congo Hemorrhagic Fever (CCHF) is a tick-borne viral infection with no licensed vaccine or therapeutics available for its treatment. In the present study we have developed the first multi-epitope subunit vaccine effective against all the seven genotypes of CCHF virus (CCHFV). The vaccine contains five B-cell, two MHC-II (HTL), and three MHC-I (CTL) epitopes screened from two structural glycoproteins (Gc and Gn in M segment) of CCHFV with an N-terminus human β-defensin as an adjuvant, as well as an N-terminus EAAAK sequence. The epitopes were rigorously investigated for their antigenicity, allergenicity, IFN gamma induction, anti-inflammatory responses, stability, and toxicity. The three-dimensional structure of the vaccine was predicted and docked with TLR-3, TLR-8, and TLR-9 receptors to find the strength of the binding complexes via molecular dynamics simulation. After codon adaptation, the subunit vaccine construct was developed in a pDual-GC plasmid and has population coverage of 98.47% of the world's population (HLA-I & II combined). The immune simulation studies were carried out on the C-ImmSim in-silico interface showing a marked increase in the production of cellular and humoral response (B-cell and T-cell) as well as TGFβ, IL-2, IL-10, and IL-12 indicating that the proposed vaccine would be able to sufficiently provoke both humoral and cell-mediated immune responses. Thus, making it a new and promising vaccine candidate against CCHFV.

TN strain proteome mediated therapeutic target mapping and multi-epitopic peptide-based vaccine development for Mycobacterium leprae

Leprosy is a significant universal health problem that is remarkably still a concern in developing countries due to infection frequency. New therapeutic molecules and next-generation vaccines are urgently needed to accelerate the leprosy-free world. In this direction, the present study was performed using two routes: proteome-mediated therapeutic target identification and mapping as well as multi-epitopic peptide-based novel vaccine development using state of the art of computational biology for the TN strain of M. leprae. The TN strain was selected from 65 Mycobacterium strains, and TN strain proteome mediated 83 therapeutic protein targets were mapped and characterized according to subcellular localization. Also, drug molecules were mapped with respect to protein targets localization. The Druggability potential of proteins was also evaluated. For multi-epitope peptide-based vaccine development, the four common types of B and T cell epitopes were identified (SLFQSHNRK, VVGIGQHAA, MMHRSPRTR, LGVDQTQPV) and combined with the suitable peptide linker. The vaccine component had an acceptable protective antigenic score (0.9751). The molecular docking of vaccine components with TLR4/MD2 complex exhibited a low ACE value (-244.12) which signifies the proper binding between the two molecules. The estimated free Gibbs binding energy ensured accurate protein-protein interactions (-112.46 kcal/mol). The vaccine was evaluated through adaptive immunity stimulation as well as immune interactions. The molecular dynamic simulation was carried out by using CHARMM topology-based parameters to minimize the docked complex. Subsequently, the Normal Mode Analysis in the internal coordinates showed a low eigen-value (1.3982892e-05), which also signifies the stability of molecular docking. Finally, the vaccine components were adopted for reverse transcription and codon optimization in E. coli strain K12 for the pGEX-4T1 vector, which supports in silico cloning of the vaccine components against the pathogen. The study directs the experimental study for therapeutics molecules discovery and vaccine candidate development with higher reliability.

Synthesis, Spectroscopic and Biological Investigation of a New Ca(II) Complex of Meloxicam as Potential COX-2 Inhibitor

Drug development on basis of coordination compounds provides versatile structural and functional properties as compared to other organic compounds. In the present study, a new Ca(II) complex of meloxicam was synthesized and characterized by elemental analysis, FT-IR, UV–Vis, ¹³C NMR, SEM–EDX, powder XRD and thermal analysis (TGA). The Ca(II) complex was investigated for its in vitro, in vivo biological activities and in silico docking analysis against COX-1 and COX-2. The spectral analysis indicates that the meloxicam acts as a deprotonated bidentate ligand (coordinated to the metal atom through the amide oxygen and the nitrogen atom of the thiazolyl ring) in the complex. SEM–EDX and powder XRD analysis depicted crystalline morphology of Ca(II) complex with a crystalline size of 32.86 nm. The in vitro biological activities were evaluated by five different antioxidant methods and COX inhibition assay, while in vivo activities were evaluated by carrageenan-, histamine- and PGE₂-induced paw edema methods and acetic acid-induced writhing test. The Ca(II) complex showed prominent antioxidant activities and was found to be more selective toward COX-2 (43.77) than COX-1 as compared to meloxicam. It exhibited lower toxicity (LD₅₀ 1000 mg/Kg) and significantly inhibited carrageenan- and PGE₂-induced inflammation at 10 mg/Kg (P < 0.05), but no significant effect was observed on histamine-induced inflammation. Moreover, Ca(II) complex significantly reduced the number of writhes induced by acetic acid (P < 0.05). The in silico molecular docking data revealed that Ca(II) complex obstructed COX-2 (dock score 6438) more effectively than COX-1 (dock score 5732) as compared to meloxicam alone.

Hydration of methemoglobin studied by in silico modeling and dielectric spectroscopy

The hemoglobin concentration of 35 g/dl of human red blood cells is close to the solubility threshold. Using microwave dielectric spectroscopy, we have assessed the amount of water associated with hydration shells of methemoglobin as a function of its concentration in the presence or absence of ions. We estimated water-hemoglobin interactions to interpret the obtained data. Within the concentration range of 5-10 g/dl of methemoglobin, ions play an important role in defining the free-to-bound water ratio competing with hemoglobin to recruit water molecules for the hydration shell. At higher concentrations, hemoglobin is a major contributor to the recruitment of water to its hydration shell. Furthermore, the amount of bound water does not change as the hemoglobin concentration is increased from 15 to 30 g/dl, remaining at the level of ∼20% of the total intracellular water pool. The theoretical evaluation of the ratio of free and bound water for the hemoglobin concentration in the absence of ions corresponds with the experimental results and shows that the methemoglobin molecule binds about 1400 water molecules. These observations suggest that within the concentration range close to the physiological one, hemoglobin molecules are so close to each other that their hydration shells interact. In this case, the orientation of the hemoglobin molecules is most likely not stochastic, but rather supports partial neutralization of positive and negative charges at the protein surface. Furthermore, deformation of the red blood cell shape results in the rearrangement of these structures.

Characterization of an A3G-VifHIV-1-CRL5-CBFβ Structure Using a Cross-linking Mass Spectrometry Pipeline for Integrative Modeling of Host-Pathogen Complexes

Structural analysis of host-pathogen protein complexes remains challenging, largely due to their structural heterogeneity. Here, we describe a pipeline for the structural characterization of these complexes using integrative structure modeling based on chemical cross-links and residue-protein contacts inferred from mutagenesis studies. We used this approach on the HIV-1 Vif protein bound to restriction factor APOBEC3G (A3G), the Cullin-5 E3 ring ligase (CRL5), and the cellular transcription factor Core Binding Factor Beta (CBFβ) to determine the structure of the (A3G-Vif-CRL5-CBFβ) complex. Using the MS-cleavable DSSO cross-linker to obtain a set of 132 cross-links within this reconstituted complex along with the atomic structures of the subunits and mutagenesis data, we computed an integrative structure model of the heptameric A3G-Vif-CRL5-CBFβ complex. The structure, which was validated using a series of tests, reveals that A3G is bound to Vif mostly through its N-terminal domain. Moreover, the model ensemble quantifies the dynamic heterogeneity of the A3G C-terminal domain and Cul5 positions. Finally, the model was used to rationalize previous structural, mutagenesis and functional data not used for modeling, including information related to the A3G-bound and unbound structures as well as mapping functional mutations to the A3G-Vif interface. The experimental and computational approach described here is generally applicable to other challenging host-pathogen protein complexes.

Subtractive proteomic analysis of antigenic extracellular proteins and design a multi-epitope vaccine against Staphylococcus aureus

Staphylococcus aureus is a versatile Gram's positive bacterium that can reside as an asymptomatic colonizer, which can cause a wide range of skin, soft-tissue, and nosocomial infections. A vaccine against multi-drug resistant S. aureus, therefore, is urgently needed. Subtractive proteomics and reverse vaccinology are newly emerging techniques to design multiepitope-based vaccines. The analysis of 7290 proteomes (sensitive and resistant strains), five potent nonhuman homologous vaccine targets [(UNIPORT ID Q2FZL3 (Staphopain B), Q2G2R8 (Staphopain A), Q2FWP0 (uncharacterized leukocidin-like protein 1), Q2G1S6 (uncharacterized protein), and Q2FWV3 (Staphylokinase, putative)] were selected. These proteins were absent in the gut microbiome, which further enhances the significance of these proteins in vaccine design. These five virulence-associated proteins mainly have a role in the invasion mechanism in the host phagocyte cells. MHC I, MHC II, and B cell epitopes were identified in these five proteins. Finalized epitopes were examined by different online servers to screen suitable epitopes for multi-epitope based vaccine design. Shortlisted antigenic and nonallergenic associated epitopes were joined with linkers to design 30 variants (VSA1-VSA30) of multi-epitope vaccine conjugates. The antigenicity and allergenicity of all the 30 vaccine constructs were identified, and VSA30 was found to have the highest antigenicity and lowest allergenicity, and hence was selected for further study. Accordingly, VSA30 was docked with different HLA allelic variants, and the best-docked complex (VSA30-1SYS) was further analyzed by molecular dynamics simulation (MDS). The MDS result confirms the interaction of VSA30 with MHC (HLA-allelic variant). Thus, the final vaccine construct was in silico cloned in the pET28a vector for suitable expression in a heterologous system. Therefore, the designed vaccine construct VSA-30 can be developed as an appropriate vaccine to target S. aureus infection. VSA-30 still needs experimental validation to assure the antigenic and immunogenic properties.

Targeting SARS-CoV-2 Receptor Binding Domain with Stapled Peptides: An In Silico Study

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into a pandemic of unprecedented scale. This coronavirus enters cells by the interaction of the receptor binding domain (RBD) with the human angiotensin-converting enzyme 2 receptor (hACE2). In this study, we employed a rational structure-based design to propose 22-mer stapled peptides using the structure of the hACE2 α1 helix as a template. These peptides were designed to retain the α-helical character of the natural structure, to enhance binding affinity, and to display a better solubility profile compared to other designed peptides available in the literature. We employed different docking strategies (PATCHDOCK and ZDOCK) followed by a double-step refinement process (FIBERDOCK) to rank our peptides, followed by stability analysis/evaluation of the interaction profile of the best docking predictions using a 500 ns molecular dynamics (MD) simulation, and a further binding affinity analysis by molecular mechanics with generalized Born and surface area (MM/GBSA) method. Our most promising stapled peptides presented a stable profile and could retain important interactions with the RBD in the presence of the E484K RBD mutation. We predict that these peptides can bind to the viral RBD with similar potency to the control NYBSP-4 (a 30-mer experimentally proven peptide inhibitor). Furthermore, our study provides valuable information for the rational design of double-stapled peptide as inhibitors of SARS-CoV-2 infection.

Robustification of RosettaAntibody and Rosetta SnugDock

In recent years, the observed antibody sequence space has grown exponentially due to advances in high-throughput sequencing of immune receptors. The rise in sequences has not been mirrored by a rise in structures, as experimental structure determination techniques have remained low-throughput. Computational modeling, however, has the potential to close the sequence–structure gap. To achieve this goal, computational methods must be robust, fast, easy to use, and accurate. Here we report on the latest advances made in RosettaAntibody and Rosetta SnugDock—methods for antibody structure prediction and antibody–antigen docking. We simplified the user interface, expanded and automated the template database, generalized the kinematics of antibody–antigen docking (which enabled modeling of single-domain antibodies) and incorporated new loop modeling techniques. To evaluate the effects of our updates on modeling accuracy, we developed rigorous tests under a new scientific benchmarking framework within Rosetta. Benchmarking revealed that more structurally similar templates could be identified in the updated database and that SnugDock broadened its applicability without losing accuracy. However, there are further advances to be made, including increasing the accuracy and speed of CDR-H3 loop modeling, before computational approaches can accurately model any antibody.

Structural investigations, quantum mechanical studies on proton and metal affinity and biological activity predictions of selpercatinib

Cancer of the lungs and thyroid is particularly difficult to manage and treat. Notably, selpercatinib has recently been suggested as an effective drug to combat these diseases. The entire world is currently tackling the pandemic caused by the SARS-CoV-19 virus. Numerous pharmaceuticals have been evaluated for the management of the disease caused by SARS-CoV-19 (i.e., COVID-19). In this study, selpercatinib was proposed as a potential inhibitor of different SARS-CoV-19 proteins. Several intriguing effects of the molecule were found during the conducted computational investigations. Selpercatinib could effectively act as a proton sponge and exhibited high proton affinity in solution. Moreover, it was able to form complexes with metal ions in aqueous solutions. Specifically, the compound displayed high affinity towards zinc ions, which are important for the prevention of virus multiplication inside human cells. However, due to their charge, zinc ions are not able to pass the lipid bilayer and enter the cell. Thus, it was determined that selpercatinib could act as an ionophore, effectively transporting active zinc ions into cells. Furthermore, various quantum mechanical analyses, including energy studies, evaluation of the reactivity parameters, examination of the electron localisation and delocalisation properties, as well as assessment of the nonlinear optical (NLO) properties and information entropy, were conducted herein. The performed docking studies (docking scores -9.3169, -9.1002, -8.1853 and -8.1222 kcal mol^-1) demonstrated that selpercatinib strongly bound with four isolated SARS-CoV-2 proteins.

Application of docking methodologies to modeled proteins

Protein docking is essential for structural characterization of protein interactions. Besides providing the structure of protein complexes, modeling of proteins and their complexes is important for understanding the fundamental principles and specific aspects of protein interactions. The accuracy of protein modeling, in general, is still less than that of the experimental approaches. Thus, it is important to investigate the applicability of docking techniques to modeled proteins. We present new comprehensive benchmark sets of protein models for the development and validation of protein docking, as well as a systematic assessment of free and template-based docking techniques on these sets. As opposed to previous studies, the benchmark sets reflect the real case modeling/docking scenario where the accuracy of the models is assessed by the modeling procedure, without reference to the native structure (which would be unknown in practical applications). We also expanded the analysis to include docking of protein pairs where proteins have different structural accuracy. The results show that, in general, the template-based docking is less sensitive to the structural inaccuracies of the models than the free docking. The near-native docking poses generated by the template-based approach, typically, also have higher ranks than those produces by the free docking (although the free docking is indispensable in modeling the multiplicity of protein interactions in a crowded cellular environment). The results show that docking techniques are applicable to protein models in a broad range of modeling accuracy. The study provides clear guidelines for practical applications of docking to protein models.

Structural and functional alterations of nitric oxide synthase 3 due to missense variants associate with high-altitude pulmonary edema through dynamic study

The human endothelial nitric oxide synthase (NOS3) is 28 Kbp at 7q36.1 and encodes protein comprising of 1280 amino acids. Being a major source of nitric oxide, the enzyme is crucial to the vascular homeostasis and thereby to be an important pharmaceutical target. We hence have been investigating this molecule in a high-altitude disorder namely, high-altitude pulmonary edema (HAPE). We performed a genome-wide association study (GWAS) in a case-control design of sojourners that included healthy controls and HAPE patients (n = 200) each. Four NOS3 missense SNPs i.e. rs1799983 (E298D), rs3918232 (V827M), rs3918201 (R885M) and rs3918234 (Q982L), were associated significantly with HAPE (P-value < 0.05). Furthermore, extensive in silico analyses were performed to predict the detrimental effect of the four variant types and their three most relevant co-factors namely, heme, flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN) that are accountable for amendment of protein stability leading to structural de-construction. Subsequently, we validated the findings in a larger sample size of the two study groups. HAPE patients had a higher frequency of the four variants and significantly decreased levels of circulating nitric oxide (NO) (P-value < 0.001). The in silico and human subjects findings complement each other. This study explored the impact of HAPE-associated NOS3 variants with its protein structure stability and holds promise to be current and future drug targets.Communicated by Ramaswamy H. Sarma.

A Guide for Protein-Protein Docking Using SwarmDock

Many of the biological functions of the cell are driven by protein-protein interactions. However, determining which proteins interact and exactly how they do so to enable their functions, remain major research questions. Functional interactions are dependent on a number of complicated factors; therefore, modeling the three-dimensional structure of protein-protein complexes is still considered a complex endeavor. Nevertheless, the rewards for modeling protein interactions to atomic level detail are substantial, and there are numerous examples of how models can provide useful information for drug design, protein engineering, systems biology, and understanding of the immune system. Here, we provide practical guidelines for docking proteins using the web-server, SwarmDock, a flexible protein-protein docking method. Moreover, we provide an overview of the factors that need to be considered when deciding whether docking is likely to be successful.

Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment

We present the results for CAPRI Round 46, the third joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo-oligomers and 6 heterocomplexes. Eight of the homo-oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher-order assemblies. These were more difficult to model, as their prediction mainly involved "ab-initio" docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance "gap" was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template-based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

A phenotype-directed chemical screen identifies ponalrestat as an inhibitor of the plant flavin monooxygenase YUCCA in auxin biosynthesis

Plant development is regulated by both synergistic and antagonistic interactions of different phytohormones, including a complex crosstalk between ethylene and auxin. For instance, auxin and ethylene synergistically control primary root elongation and root hair formation. However, a lack of chemical agents that specifically modulate ethylene or auxin production has precluded precise delineation of the contribution of each hormone to root development. Here, we performed a chemical genetic screen based on the recovery of root growth in ethylene-related Arabidopsis mutants with constitutive "short root" phenotypes (eto1-2 and ctr1-1). We found that ponalrestat exposure recovers root elongation in these mutants in an ethylene signal-independent manner. Genetic and pharmacological investigations revealed that ponalrestat inhibits the enzymatic activity of the flavin-containing monooxygenase YUCCA, which catalyzes the rate-limiting step of the indole-3-pyruvic acid branch of the auxin biosynthesis pathway. In summary, our findings have identified a YUCCA inhibitor that may be useful as a chemical tool to dissect the distinct steps in auxin biosynthesis and in the regulation of root development.

Docking-based approach for identification of mutations that disrupt binding between Bcl-2 and Bax proteins: Inducing apoptosis in cancer cells

BACKGROUND

Inducing apoptosis in cancer cells is an important step for the successful treatment of cancer patients. Bcl-2 is an antiapoptotic protein which determines apoptosis by interacting with proapoptotic members of the Bcl-2 family. Exome sequencing has identified Bcl-2 and Bax missense mutations in more than 40 cancer types. However, a little information is available about the functional impact of each Bcl-2 and Bax mutation on the pathogenesis of cancer.

METHODS

The mutational data from cancer tissues and cell lines were retrieved from the cBioPortal web resource. The 13 mutated Bcl-2 and wild-type Bax complexes with experimentally verified binding were identified from previous studies wherein, binding for all complexes was reportedly disrupted except one. Several protein-protein docking methods such as ClusPro, HDOCK, PatchDock, FireDock, InterEVDock2 and several mutation prediction methods such as PolyPhen-2, SIFT, and OncoKB have been used to predict the effect of mutation to disrupt the binding between Bcl-2 and Bax. The result obtained was compared with the known experimental data.

RESULTS

The protein-protein docking method, ClusPro, employed in the present study confirmed that the binding affinity of 11 out of 13 complexes decreases. Similarly, binding affinity computed for all the 10 wild-type Bcl-2 and mutated Bax complexes agreed with experimentally verified results.

CONCLUSION

Several methods like PolyPhen-2, SIFT, and OncoKB have been developed to predict cancer-associated or deleterious mutations, but no method is available to predict apoptosis-inducing mutations. Thus, in this study, we have examined the mutations in Bcl-2 and Bax proteins that disrupt their binding, which is crucial for inducing apoptosis to eradicate cancer. This study suggests that protein-protein docking methods can play a significant role in the identification of hotspot mutations in Bcl-2 or Bax that can disrupt their binding with wild-type partner to induce apoptosis in cancer cells.

Molecular simulation studies on B-cell lymphoma/leukaemia 11A (BCL11A)

B-cell lymphoma/leukaemia 11A (BCL11A) is a modulator of foetal-to-adult globin switching and is involved in brain development and normal lymphopoiesis. The three-dimensional structure of BCL11A and its structural domains had not yet been completely determined; hence, this study aimed to elucidate the structural domains of BCL11A. Molecular modelling and dynamics simulation studies were conducted using in silico tools with the templates selected based on Basic Local Alignment Search Tool (BLAST) searches of the Protein Data Bank (PDB). Ten protein models were generated using the MODELLER software, and the best model was selected according to the Discrete Optimised Protein Energy (DOPE) score and validated using the RAMPAGE server by evaluation of the Ramachandran plot. More than 93% of the amino acid residues of the best model of BCL11A were found to be in the favoured and allowed regions. The best model was validated using a 100-ns time span molecular dynamics simulation. The root-mean-square deviation, root-mean-square fluctuation, and radius of gyration values were found to explain the stability of the best BCL11A protein molecular model generated in the study. The validated best model of the BCL11A protein may be useful for effective modulator studies on foetal-to-adult globin switching and related research.

B1.12: a novel peptide interacting with the extracellular loop of the EBV oncoprotein LMP1

Latent membrane protein 1 (LMP1) encoded by the Epstein-Barr virus (EBV) plays an important role in EBV-induced cell transformation. Down-regulation of the LMP1 expression had shown promising results on cancer cell therapy. In this study, we identified by Phage display a novel peptide called B1.12 (ACPLDLRSPCG) which selectively binds to the extracellular loop (B1) of the LMP1 oncoprotein as demonstrated by molecular docking, NMR and ITC. Using an LMP1 expressing cell line, we showed that B1.12 decreased cell viability, and induced G0/G1 cell cycle arrest. In addition, the expression of A20, pAkt, and pNFkb (pRelA536) in C666-1 cells treated with B1.12 decreased compared to the untreated cells. In conclusion, we selected a novel peptide able to bind specifically to the extracellular loop of LMP1 and thus modulate its oncogenic properties.

The mechanism of PI3Kα activation at the atomic level

PI3K lipid kinases phosphorylate PIP₂ to PIP₃ in the PI3K/Akt/mTOR pathway to regulate cellular processes. They are frequently mutated in cancer. Here we determine the PI3Kα activation mechanism at the atomic level. Unlike protein kinases where the substrate abuts the ATP, crystal structures indicate that in PI3Kα, the distance between the γ phosphate of the ATP and the PIP₂ lipid substrate is over 6 Å, much too far for the phosphoryl transfer, raising the question of how catalysis is executed. PI3Kα has two subunits, the catalytic p110α and the regulatory p85α. Our simulations show that release of the autoinhibition exerted by the nSH2 domain of the p85α triggers significant conformational change in p110α, leading to the exposure of the kinase domain for membrane interaction. Structural rearrangement in the C-lobe of the kinase domain reduces the distance between the ATP γ-phosphate and the substrate, offering an explanation as to how phosphoryl transfer is executed. An alternative mechanism may involve ATP relocation. This mechanism not only explains how oncogenic mutations promote PI3Kα activation by facilitating nSH2 release, or nSH2-release-induced, allosteric motions; it also offers an innovative, PI3K isoform-specific drug discovery principle. Rather than competing with nanomolar range ATP in the ATP-binding pocket and contending with ATP pocket conservation and massive binding targets, this mechanism suggests blocking the PI3Kα sequence-specific cavity between the ATP-binding pocket and the substrate binding site. Targeting isoform-specific residues in the cavity may prevent PIP₂ phosphorylation.

Microcin J25 inhibits ubiquinol oxidase activity of purified cytochrome bd-I from Escherichia coli

Microcin J25 (MccJ25), an antimicrobial peptide, targets the respiratory chain but the exact mechanism by which it does so remains unclear. Here, we reveal that MccJ25 is able to inhibit the enzymatic activity of the isolated cytochrome bd-I from E. coli and induces at the same time production of reactive oxygen species. MccJ25 behaves as a dose-dependent weak inhibitor. Intriguingly, MccJ25 is capable of producing a change in the oxidation state of cytochrome bd-I causing its partial reduction in the presence of cyanide. These effects are specific for cytochrome bd-I, since the peptide is not able to act on purified cytochrome bo₃.

Benchmarking of different molecular docking methods for protein-peptide docking

Background

Molecular docking studies on protein-peptide interactions are a challenging and time-consuming task because peptides are generally more flexible than proteins and tend to adopt numerous conformations. There are several benchmarking studies on protein-protein, protein-ligand and nucleic acid-ligand docking interactions. However, a series of docking methods is not rigorously validated for protein-peptide complexes in the literature. Considering the importance and wide application of peptide docking, we describe benchmarking of 6 docking methods on 133 protein-peptide complexes having peptide length between 9 to 15 residues. The performance of docking methods was evaluated using CAPRI parameters like FNAT, I-RMSD, L-RMSD.

Result

Firstly, we performed blind docking and evaluate the performance of the top docking pose of each method. It was observed that FRODOCK performed better than other methods with average L-RMSD of 12.46 Å. The performance of all methods improved significantly for their best docking pose and achieved highest average L-RMSD of 3.72 Å in case of FRODOCK. Similarly, we performed re-docking and evaluated the performance of the top and best docking pose of each method. We achieved the best performance in case of ZDOCK with average L-RMSD 8.60 Å and 2.88 Å for the top and best docking pose respectively. Methods were also evaluated on 40 protein-peptide complexes used in the previous benchmarking study, where peptide have length up to 5 residues. In case of best docking pose, we achieved the highest average L-RMSD of 4.45 Å and 2.09 Å for the blind docking using FRODOCK and re-docking using AutoDock Vina respectively.

Conclusion

The study shows that FRODOCK performed best in case of blind docking and ZDOCK in case of re-docking. There is a need to improve the ranking of docking pose generated by different methods, as the present ranking scheme is not satisfactory. To facilitate the scientific community for calculating CAPRI parameters between native and docked complexes, we developed a web-based service named PPDbench (http://webs.iiitd.edu.in/raghava/ppdbench/).

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2449-y) contains supplementary material, which is available to authorized users.

In silico-prediction of protein-protein interactions network about MAPKs and PP2Cs reveals a novel docking site variants in Brachypodium distachyon

Protein-protein interactions (PPIs) underlie the molecular mechanisms of most biological processes. Mitogen-activated protein kinases (MAPKs) can be dephosphorylated by MAPK-specific phosphatases such as PP2C, which are critical to transduce extracellular signals into adaptive and programmed responses. However, the experimental approaches for identifying PPIs are expensive, time-consuming, laborious and challenging. In response, many computational methods have been developed to predict PPIs. Yet, these methods have inherent disadvantages such as high false positive and negative results. Thus, it is crucial to develop in silico approaches for predicting PPIs efficiently and accurately. In this study, we identified PPIs among 16 BdMAPKs and 86 BdPP2Cs in B. distachyon using a novel docking approach. Further, we systematically investigated the docking site (D-site) of BdPP2C which plays a vital role for recognition and docking of BdMAPKs. D-site analysis revealed that there were 96 pairs of PPIs including all BdMAPKs and most BdPP2Cs, which indicated that BdPP2C may play roles in other signaling networks. Moreover, most BdPP2Cs have a D-site for BdMAPKs in our prediction results, which suggested that our method can effectively predict PPIs, as confirmed by their 3D structure. In addition, we validated this methodology with known Arabidopsis and yeast phosphatase-MAPK interactions from the STRING database. The results obtained provide a vital research resource for exploring an accurate network of PPIs between BdMAPKs and BdPP2Cs.

Optimum Number of Anchored Clathrate Water and Its Instantaneous Fluctuations Dictate Ice Plane Recognition Specificities of Insect Antifreeze Protein

Ice recognition by antifreeze proteins (AFPs) is a subject of topical interest. Among several classes of AFPs, insect AFPs are hyperactive presumably due to their ability to adsorb on basal plane. However, the origin of the basal plane binding specificity is not clearly known. Present work aims to provide atomistic insight into the origin of basal plane recognition by an insect antifreeze protein. Free energy calculations reveal that the order of binding affinity of the AFP toward different ice planes is basal plane > prism plane > pyramidal plane. Critical insight reveals that the observed plane specificity is strongly correlated with the number and their instantaneous fluctuations of clathrate water forming hydrogen bonds with both ice binding surface (IBS) of AFP and ice surface, thus anchoring AFP to the ice surface. On basal plane, anchored clathrate water array is highly stable due to exact match in the periodicity of oxygen atom repeat distances of the ice surface and the threonine repeat distances at the IBS. The stability of anchored clathrate water array progressively decreases upon prism and pyramidal plane adsorption due to mismatch between the threonine ladder and oxygen atom repeat distance. Further analysis reveals that hydration around the methyl side-chains of threonine residues becomes highly significant at low temperature which stabilizes the anchored clathrate water array and dual hydrogen-bonding is a consequence of this stability. Structural insight gained from this study paves the way for rational designing of highly potent antifreeze-mimetic with potential industrial applications.

A Structural Model of a P450-Ferredoxin Complex from Orientation-Selective Double Electron-Electron Resonance Spectroscopy

Cytochrome P450 (CYP) monooxygenases catalyze the oxidation of chemically inert carbon-hydrogen bonds in diverse endogenous and exogenous organic compounds by atmospheric oxygen. This C-H bond oxy-functionalization activity has huge potential in biotechnological applications. Class I CYPs receive the two electrons required for oxygen activation from NAD(P)H via a ferredoxin reductase and ferredoxin. The interaction of Class I CYPs with their cognate ferredoxin is specific. In order to reconstitute the activity of diverse CYPs, structural characterization of CYP-ferredoxin complexes is necessary, but little structural information is available. Here we report a structural model of such a complex (CYP199A2-HaPux) in frozen solution derived from distance and orientation restraints gathered by the EPR technique of orientation-selective double electron-electron resonance (os-DEER). The long-lived oscillations in the os-DEER spectra were well modeled by a single orientation of the CYP199A2-HaPux complex. The structure is different from the two known Class I CYP-Fdx structures: CYP11A1-Adx and CYP101A1-Pdx. At the protein interface, HaPux residues in the [Fe₂S₂] cluster-binding loop and the α3 helix and the C-terminus residue interact with CYP199A2 residues in the proximal loop and the C helix. These residue contacts are consistent with biochemical data on CYP199A2-ferredoxin binding and electron transfer. Electron-tunneling calculations indicate an efficient electron-transfer pathway from the [Fe₂S₂] cluster to the heme. This new structural model of a CYP-Fdx complex provides the basis for tailoring CYP enzymes for which the cognate ferredoxin is not known, to accept electrons from HaPux and display monooxygenase activity.

Flexible Protein-Protein Docking with SwarmDock

The atomic structures of protein complexes can provide useful information for drug design, protein engineering, systems biology, and understanding pathology. Obtaining this information experimentally can be challenging. However, if the structures of the subunits are known, then it is often possible to model the complex computationally. This chapter provide practical guidelines for docking proteins using the SwarmDock flexible protein-protein docking method, providing an overview of the factors that need to be considered when deciding whether docking is likely to be successful, the preparation of structural input, generation of docked poses, analysis and ranking of docked poses, and the validation of models using external data.

The computational prediction of protein assemblies

The function of proteins in the cell is almost always mediated by their interaction with different partners, including other proteins, nucleic acids or small organic molecules. The ability of identifying all of them is an essential step in our quest for understanding life at the molecular level. The inference of the protein complex composition and of its molecular details can also provide relevant clues for the development and the design of drugs. In this short review, I will discuss the computational aspects of the analysis and prediction of protein-protein assemblies and discuss some of the most recent developments as seen in the last Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment.

Suppressing allostery in epitope mapping experiments using millisecond hydrogen / deuterium exchange mass spectrometry

Localization of the interface between the candidate antibody and its antigen target, commonly known as epitope mapping, is a critical component of the development of therapeutic monoclonal antibodies. With the recent availability of commercial automated systems, hydrogen / deuterium eXchange (HDX) is rapidly becoming the tool for mapping epitopes preferred by researchers in both industry and academia. However, this approach has a significant drawback in that it can be confounded by ‘allosteric’ structural and dynamic changes that result from the interaction, but occur far from the point(s) of contact. Here, we introduce a ‘kinetic’ millisecond HDX workflow that suppresses allosteric effects in epitope mapping experiments. The approach employs a previously introduced microfluidic apparatus that enables millisecond HDX labeling times with on-chip pepsin digestion and electrospray ionization. The ‘kinetic’ workflow also differs from conventional HDX-based epitope mapping in that the antibody is introduced to the antigen at the onset of HDX labeling. Using myoglobin / anti-myoglobin as a model system, we demonstrate that at short ‘kinetic’ workflow labeling times (i.e., 200 ms), the HDX signal is already fully developed at the ‘true’ epitope, but is still largely below the significance threshold at allosteric sites. Identification of the ‘true’ epitope is supported by computational docking predictions and allostery modeling using the rigidity transmission allostery algorithm.

The antigen-binding fragment of human gamma immunoglobulin prevents amyloid β-peptide folding into β-sheet to form oligomers

The amyloid beta-peptide (Aβ) plays a leading role in Alzheimer's disease (AD) physiopathology. Even though monomeric forms of Aβ are harmless to cells, Aβ can aggregate into β-sheet oligomers and fibrils, which are both neurotoxic. Therefore, one of the main therapeutic approaches to cure or delay AD onset and progression is targeting Aβ aggregation. In the present study, we show that a pool of human gamma immunoglobulins (IgG) protected cortical neurons from the challenge with Aβ oligomers, as assayed by MTT reduction, caspase-3 activation and cytoskeleton integrity. In addition, we report the inhibitory effect of IgG on Aβ aggregation, as shown by Thioflavin T assay, size exclusion chromatography and atomic force microscopy. Similar results were obtained with Palivizumab, a human anti-sincitial virus antibody. In order to dissect the important domains, we cleaved the pool of human IgG with papain to obtain Fab and Fc fragments. Using these cleaved fragments, we functionally identified Fab as the immunoglobulin fragment inhibiting Aβ aggregation, a result that was further confirmed by an in silico structural model. Interestingly, bioinformatic tools show a highly conserved structure able to bind amyloid in the Fab region. Overall, our data strongly support the inhibitory effect of human IgG on Aβ aggregation and its neuroprotective role.

Addressing recent docking challenges: A hybrid strategy to integrate template-based and free protein-protein docking

Protein-protein docking is an important computational tool for predicting protein-protein interactions. With the rapid development of proteomics projects, more and more experimental binding information ranging from mutagenesis data to three-dimensional structures of protein complexes are becoming available. Therefore, how to appropriately incorporate the biological information into traditional ab initio docking has been an important issue and challenge in the field of protein-protein docking. To address these challenges, we have developed a Hybrid DOCKing protocol of template-based and template-free approaches, referred to as HDOCK. The basic procedure of HDOCK is to model the structures of individual components based on the template complex by a template-based method if a template is available; otherwise, the component structures will be modeled based on monomer proteins by regular homology modeling. Then, the complex structure of the component models is predicted by traditional protein-protein docking. With the HDOCK protocol, we have participated in the CPARI experiment for rounds 28-35. Out of the 25 CASP-CAPRI targets for oligomer modeling, our HDOCK protocol predicted correct models for 16 targets, ranking one of the top algorithms in this challenge. Our docking method also made correct predictions on other CAPRI challenges such as protein-peptide binding for 6 out of 8 targets and water predictions for 2 out of 2 targets. The advantage of our hybrid docking approach over pure template-based docking was further confirmed by a comparative evaluation on 20 CASP-CAPRI targets. Proteins 2017; 85:497-512. © 2016 Wiley Periodicals, Inc.

Structural quality of unrefined models in protein docking

Structural characterization of protein-protein interactions is essential for understanding life processes at the molecular level. However, only a fraction of protein interactions have experimentally resolved structures. Thus, reliable computational methods for structural modeling of protein interactions (protein docking) are important for generating such structures and understanding the principles of protein recognition. Template-based docking techniques that utilize structural similarity between target protein-protein interaction and cocrystallized protein-protein complexes (templates) are gaining popularity due to generally higher reliability than that of the template-free docking. However, the template-based approach lacks explicit penalties for intermolecular penetration, as opposed to the typical free docking where such penalty is inherent due to the shape complementarity paradigm. Thus, template-based docking models are commonly assumed to require special treatment to remove large structural penetrations. In this study, we compared clashes in the template-based and free docking of the same proteins, with crystallographically determined and modeled structures. The results show that for the less accurate protein models, free docking produces fewer clashes than the template-based approach. However, contrary to the common expectation, in acceptable and better quality docking models of unbound crystallographically determined proteins, the clashes in the template-based docking are comparable to those in the free docking, due to the overall higher quality of the template-based docking predictions. This suggests that the free docking refinement protocols can in principle be applied to the template-based docking predictions as well. Proteins 2016; 85:39-45. © 2016 Wiley Periodicals, Inc.

Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches

MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.

Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility

Predicting protein conformational changes from unbound structures or even homology models to bound structures remains a critical challenge for protein docking. Here we present a study directly addressing the challenge by reducing the dimensionality and narrowing the range of the corresponding conformational space. The study builds on cNMA-our new framework of partner- and contact-specific normal mode analysis that exploits encounter complexes and considers both intrinsic and induced flexibility. First, we established over a CAPRI (Critical Assessment of PRedicted Interactions) target set that the direction of conformational changes from unbound structures and homology models can be reproduced to a great extent by a small set of cNMA modes. In particular, homology-to-bound interface root-mean-square deviation (iRMSD) can be reduced by 40% on average with the slowest 30 modes. Second, we developed novel and interpretable features from cNMA and used various machine learning approaches to predict the extent of conformational changes. The models learned from a set of unbound-to-bound conformational changes could predict the actual extent of iRMSD with errors around 0.6 Å for unbound proteins in a held-out benchmark subset, around 0.8 Å for unbound proteins in the CAPRI set, and around 1 Å even for homology models in the CAPRI set. Our results shed new insights into origins of conformational differences between homology models and bound structures and provide new support for the low-dimensionality of conformational adjustment during protein associations. The results also provide new tools for ensemble generation and conformational sampling in unbound and homology docking. Proteins 2017; 85:544-556. © 2016 Wiley Periodicals, Inc.

PB2 substitutions V598T/I increase the virulence of H7N9 influenza A virus in mammals

PB2 is one of the subunits of the influenza A virus (IAV) polymerase complex. By bioinformatics analysis we identified PB2 substitutions at positions 389 and 598 among IAV isolates from humans, which might associate with viral pathogenicity. To evaluate the biological significance of these substitutions, PB2-K389R and -V598T/I mutant viruses of avian H7N9 IAVs were generated by reverse genetics. Compared to the wild type, the mutant viruses displayed an enhanced growth capacity in human and mammalian cells. Meanwhile, they presented increased transcription and replication by producing higher levels of viral mRNA, cRNA and vRNA. Minireplicon assays indicated that the polymerase activity was elevated by these substitutions. Notably, the PB2-V598T/I substitutions substantially increased virus replication and virulence in mice. Together, we demonstrated that the substitutions PB2-V598T/I contributed to higher IAV replication and virulence in mammals, which added to the knowledge of IAV virulence determinants and benefited the surveillance of IAVs.

PRISM-EM: template interface-based modelling of multi-protein complexes guided by cryo-electron microscopy density maps

The structures of protein assemblies are important for elucidating cellular processes at the molecular level. Three-dimensional electron microscopy (3DEM) is a powerful method to identify the structures of assemblies, especially those that are challenging to study by crystallography. Here, a new approach, PRISM-EM, is reported to computationally generate plausible structural models using a procedure that combines crystallographic structures and density maps obtained from 3DEM. The predictions are validated against seven available structurally different crystallographic complexes. The models display mean deviations in the backbone of <5 Å. PRISM-EM was further tested on different benchmark sets; the accuracy was evaluated with respect to the structure of the complex, and the correlation with EM density maps and interface predictions were evaluated and compared with those obtained using other methods. PRISM-EM was then used to predict the structure of the ternary complex of the HIV-1 envelope glycoprotein trimer, the ligand CD4 and the neutralizing protein m36.

GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking

Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex.

Challenges of docking in large, flexible and promiscuous binding sites

After decades of work, the correct determination of the binding mode of a small molecule into a target protein is still a challenging problem, whose difficulty depends on: (i) the sizes of the binding site and the ligand; (ii) the flexibility of both interacting partners, and (iii) the differential solvation of bound and unbound partners. We have evaluated the performance of standard rigid(receptor)/flexible(ligand) docking approaches with respect to last-generation fully flexible docking methods to obtain reasonable poses in a very challenging case: soluble Epoxide Hydrolase (sEH), a flexible protein showing different binding sites. We found that full description of the flexibility of both protein and ligand and accurate description of solvation leads to significant improvement in the ability of docking to reproduce well known binding modes, and at the same time capture the intrinsic binding promiscuity of the protein.

Atomic-Level Characterization of the Chain-Flipping Mechanism in Fatty-Acids Biosynthesis

During fatty acids biosynthesis the elongating acyl chain is sequestered within the core of the highly conserved acyl carrier protein (ACP). At each catalytic step, the acyl intermediates are transiently delivered from ACP to the active site of the enzymatic counterparts and, at the same time, are protected from the solvent to prevent nonselective reactivity. Yet, the molecular determinants of such a universal transition-termed chain flipping-remain poorly understood. Here we capture the atomic-level details of the chain-flipping mechanism by using metadynamics simulations. We observe the fatty-acid chain gliding through the protein-protein interface with barely 30% of its surface exposed to water molecules. The small ACP's helix III acts as gatekeeper of the process, and we find its conformational plasticity critical for a successful substrate transfer. The results are in agreement with a wide range of experimental observations and provide unprecedented insight on the molecular determinants and driving forces of the chain-flipping process.