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Snake venoms are cocktails of biologically active molecules that have evolved to immobilize prey, but can also induce a severe pathology in humans that are bitten. While animal-derived polyclonal antivenoms are the primary treatment for snakebites, they often have limitations in efficacy and can cause severe adverse side effects. Building on recent efforts to develop improved antivenoms, notably through monoclonal antibodies, requires a comprehensive understanding of venom toxins. Among these toxins, snake venom metalloproteinases (SVMPs) play a pivotal role, particularly in viper envenomation, causing tissue damage, hemorrhage and coagulation disruption. One of the current challenges in the development of neutralizing monoclonal antibodies against SVMPs is the large size of the protein and the lack of existing knowledge of neutralizing epitopes. Here, we screened a synthetic human antibody library to isolate monoclonal antibodies against an SVMP from saw-scaled viper (genus Echis ) venom. Upon characterization, several antibodies were identified that effectively blocked SVMP-mediated prothrombin activation. Cryo-electron microscopy revealed the structural basis of antibody-mediated neutralization, pinpointing the non-catalytic cysteine-rich domain of SVMPs as a crucial target. These findings emphasize the importance of understanding the molecular mechanisms of SVMPs to counter their toxic effects, thus advancing the development of more effective antivenoms.

Snakebite envenoming is a major global public health concern for which improved therapies are urgently needed. The antigenic diversity present in snake venom toxins from various species presents a considerable challenge to the development of a universal antivenom. Here, we used a synthetic human antibody library to find and develop an antibody that neutralizes long-chain three-finger α-neurotoxins produced by numerous medically relevant snakes. Our antibody bound diverse toxin variants with high affinity, blocked toxin binding to the nicotinic acetylcholine receptor in vitro, and protected mice from lethal venom challenge. Structural analysis of the antibody-toxin complex revealed a binding mode that mimics the receptor-toxin interaction. The overall workflow presented is generalizable for the development of antibodies that target conserved epitopes among antigenically diverse targets, and it offers a promising framework for the creation of a monoclonal antibody-based universal antivenom to treat snakebite envenoming.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscores the need for strategies to rapidly develop neutralizing monoclonal antibodies that can function as prophylactic and therapeutic agents and to help guide vaccine design. Here, we demonstrate that engineering approaches can be used to refocus an existing antibody that neutralizes one virus but not a related virus. Through a rapid affinity maturation strategy, we engineered CR3022, a SARS-CoV-1-neutralizing antibody, to bind to the receptor binding domain of SARS-CoV-2 with >1000-fold increased affinity. The engineered CR3022 neutralized SARS-CoV-2 and provided prophylactic protection from viral challenge in a small animal model of SARS-CoV-2 infection. Deep sequencing throughout the engineering process paired with crystallographic analysis of engineered CR3022 elucidated the molecular mechanisms by which the antibody can accommodate sequence differences in the epitopes between SARS-CoV-1 and SARS-CoV-2. This workflow provides a blueprint for the rapid broadening of neutralization of an antibody from one virus to closely related but resistant viruses.

Nanobodies bind a target antigen with a kinetic profile similar to a conventional antibody, but exist as a single heavy chain domain that can be readily multimerized to engage antigen via multiple interactions. Presently, most nanobodies are produced by immunizing camelids; however, platforms for animal-free production are growing in popularity. Here, we describe the development of a fully synthetic nanobody library based on an engineered human V H 3-23 variable gene and a multispecific antibody-like format designed for biparatopic target engagement. To validate our library, we selected nanobodies against the SARS-CoV-2 receptor-binding domain and employed an on-yeast epitope binning strategy to rapidly map the specificities of the selected nanobodies. We then generated antibody-like molecules by replacing the V H and V L domains of a conventional antibody with two different nanobodies, designed as a molecular clamp to engage the receptor-binding domain biparatopically. The resulting bispecific tetra-nanobody immunoglobulins neutralized diverse SARS-CoV-2 variants with potencies similar to antibodies isolated from convalescent donors. Subsequent biochemical analyses confirmed the accuracy of the on-yeast epitope binning and structures of both individual nanobodies, and a tetra-nanobody immunoglobulin revealed that the intended mode of interaction had been achieved. This overall workflow is applicable to nearly any protein target and provides a blueprint for a modular workflow for the development of multispecific molecules.

Pan-betacoronavirus neutralizing antibodies may hold the key to developing broadly protective vaccines against novel pandemic coronaviruses and to more effectively respond to SARS-CoV-2 variants. The emergence of Omicron and subvariants of SARS-CoV-2 illustrates the limitations of solely targeting the receptor-binding domain (RBD) of the spike (S) protein. Here, we isolated a large panel of broadly neutralizing antibodies (bnAbs) from SARS-CoV-2 recovered-vaccinated donors, which targets a conserved S2 region in the betacoronavirus spike fusion machinery. Select bnAbs showed broad in vivo protection against all three deadly betacoronaviruses, SARS-CoV-1, SARS-CoV-2, and MERS-CoV, which have spilled over into humans in the past two decades. Structural studies of these bnAbs delineated the molecular basis for their broad reactivity and revealed common antibody features targetable by broad vaccination strategies. These bnAbs provide new insights and opportunities for antibody-based interventions and for developing pan-betacoronavirus vaccines., Competing Interests: Declaration of interests P.Z., G.S., W.-t.H., D.R.B., and R.A. are listed as inventors on pending patent applications describing the betacoronavirus bnAbs isolated in this study. D.R.B. is a consultant for IAVI and for Invivyd. R.S.B. and L.E.G. have ongoing collaborations with Invivyd., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

The rapid spread of SARS-CoV-2 variants poses a constant threat of escape from monoclonal antibody and vaccine countermeasures. Mutations in the ACE2 receptor binding site on the surface S protein have been shown to disrupt antibody binding and prevent viral neutralization. Here, we used a directed evolution-based approach to engineer three neutralizing antibodies for enhanced binding to S protein. The engineered antibodies showed increased in vitro functional activity in terms of neutralization potency and/or breadth of neutralization against viral variants. Deep mutational scanning revealed that higher binding affinity reduces the total number of viral escape mutations. Studies in the Syrian hamster model showed two examples where the affinity-matured antibody provided superior protection compared to the parental antibody. These data suggest that monoclonal antibodies for antiviral indications would benefit from affinity maturation to reduce viral escape pathways and appropriate affinity maturation in vaccine immunization could help resist viral variation., Competing Interests: J.G.J., D.R.B., and F.Z. are listed as inventors on pending patent applications describing the engineered SARS-CoV-2 neutralizing antibodies., (© 2022 The Authors.)

Therapeutic proteins, including monoclonal antibodies, are typically manufactured using clonally derived, stable host cell lines, since consistent and predictable cell culture performance is highly desirable. However, selecting and preparing banks of stable clones takes considerable time, which inevitably extends overall development timelines for new therapeutics by delaying the start of subsequent activities, such as the scale-up of manufacturing processes. In the context of the coronavirus disease 2019 (COVID-19) pandemic, with its intense pressure for accelerated development strategies, we used a novel transposon-based Leap-In Transposase® system to rapidly generate high-titer stable pools and then used them directly for large scale-manufacturing of an anti-severe acute respiratory syndrome coronavirus 2 monoclonal antibody under cGMP. We performed the safety testing of our non-clonal cell bank, then used it to produce material at a 200L-scale for preclinical safety studies and formulation development work, and thereafter at 2000L scale for supply of material for a Phase 1 clinical trial. Testing demonstrated the comparability of critical product qualities between the two scales and, more importantly, that our final clinical trial product met all pre-set product quality specifications. The above expediated approach provided clinical trial material within 4.5 months, in comparison to 12-14 months for production of clinical trial material via the conventional approach., (© 2021 Wiley Periodicals LLC.)

The potential emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) escape mutants is a threat to the efficacy of existing vaccines and neutralizing antibody (nAb) therapies. An understanding of the antibody/S escape mutation landscape is urgently needed to preemptively address this threat. Here we describe a rapid method to identify escape mutants for nAbs targeting the S receptor binding site. We identified escape mutants for five nAbs, including three from the public germline class VH3-53 elicited by natural coronavirus disease 2019 (COVID-19) infection. Escape mutations predominantly mapped to the periphery of the angiotensin-converting enzyme 2 (ACE2) recognition site on the RBD with K417, D420, Y421, F486, and Q493 as notable hotspots. We provide libraries, methods, and software as an openly available community resource to accelerate new therapeutic strategies against SARS-CoV-2., Competing Interests: Declaration of interests I.M.F.-U., P.J.S., M.B.K., C.M.H., J.G.J., and T.A.W. have a US provisional patent application “IDENTIFICATION OF SARS-COV-2 S RBD ESCAPE MUTANTS” covering some of the mutants identified in the present study., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Tools to monitor SARS-CoV-2 transmission and immune responses are needed. We present a neutralization ELISA to determine the levels of Ab-mediated virus neutralization and a preclinical model of focused immunization strategy. The ELISA is strongly correlated with the elaborate plaque reduction neutralization test (ρ = 0.9231, p < 0.0001). The neutralization potency of convalescent sera strongly correlates to IgG titers against SARS-CoV-2 receptor-binding domain (RBD) and spike (ρ = 0.8291 and 0.8297, respectively; p < 0.0001) and to a lesser extent with the IgG titers against protein N (ρ = 0.6471, p < 0.0001). The preclinical vaccine NMRI mice models using RBD and full-length spike Ag as immunogens show a profound Ab neutralization capacity (IC 50 = 1.9 × 10 4 to 2.6 × 10 4 and 3.9 × 10 3 to 5.2 × 10 3 , respectively). Using a panel of novel high-affinity murine mAbs, we also show that a majority of the RBD-raised mAbs have inhibitory properties, whereas only a few of the spike-raised mAbs do. The ELISA-based viral neutralization test offers a time- and cost-effective alternative to the plaque reduction neutralization test. The immunization results indicate that vaccine strategies focused only on the RBD region may have advantages compared with the full spike., (Copyright © 2021 by The American Association of Immunologists, Inc.)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike pseudotyped virus (PSV) assays are widely used to measure neutralization titers of sera and of isolated neutralizing Abs (nAbs). PSV neutralization assays are safer than live virus neutralization assays and do not require access to biosafety level 3 laboratories. However, many PSV assays are nevertheless somewhat challenging and require at least 2 d to carry out. In this study, we report a rapid (<30 min), sensitive, cell-free, off-the-shelf, and accurate assay for receptor binding domain nAb detection. Our proximity-based luciferase assay takes advantage of the fact that the most potent SARS-CoV-2 nAbs function by blocking the binding between SARS-CoV-2 and angiotensin-converting enzyme 2. The method was validated using isolated nAbs and sera from spike-immunized animals and patients with coronavirus disease 2019. The method was particularly useful in patients with HIV taking antiretroviral therapies that interfere with the conventional PSV assay. The method provides a cost-effective and point-of-care alternative to evaluate the potency and breadth of the predominant SARS-CoV-2 nAbs elicited by infection or vaccines., (Copyright © 2021 by The American Association of Immunologists, Inc.)

Globally, the COVID-19 pandemic has had extreme consequences for the healthcare system and has led to calls for diagnostic tools to monitor and understand the transmission, pathogenesis, and epidemiology, as well as to evaluate future vaccination strategies. In this study, we have developed novel, to our knowledge, flexible ELISA-based assays for specific detection of human SARS-CoV-2 Abs against the receptor-binding domain, including an Ag sandwich ELISA relevant for large population screening and three isotype-specific assays for in-depth diagnostics. Their performance was evaluated in a cohort of 350 convalescent participants with previous COVID-19 infection, ranging from asymptomatic to critical cases. We mapped the Ab responses to different areas on protein N and S and showed that the IgM, A, and G Ab responses against receptor-binding domain are significantly correlated to the disease severity. These assays and the data generated from them are highly relevant for diagnostics and prognostics and contribute to the understanding of long-term COVID-19 immunity., (Copyright © 2020 by The American Association of Immunologists, Inc.)

Molecular understanding of neutralizing antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could accelerate vaccine design and drug discovery. We analyzed 294 anti-SARS-CoV-2 antibodies and found that immunoglobulin G heavy-chain variable region 3-53 (IGHV3-53) is the most frequently used IGHV gene for targeting the receptor-binding domain (RBD) of the spike protein. Co-crystal structures of two IGHV3-53-neutralizing antibodies with RBD, with or without Fab CR3022, at 2.33- to 3.20-angstrom resolution revealed that the germline-encoded residues dominate recognition of the angiotensin I converting enzyme 2 (ACE2)-binding site. This binding mode limits the IGHV3-53 antibodies to short complementarity-determining region H3 loops but accommodates light-chain diversity. These IGHV3-53 antibodies show minimal affinity maturation and high potency, which is promising for vaccine design. Knowledge of these structural motifs and binding mode should facilitate the design of antigens that elicit this type of neutralizing response., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Countermeasures to prevent and treat coronavirus disease 2019 (COVID-19) are a global health priority. We enrolled a cohort of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-recovered participants, developed neutralization assays to investigate antibody responses, adapted our high-throughput antibody generation pipeline to rapidly screen more than 1800 antibodies, and established an animal model to test protection. We isolated potent neutralizing antibodies (nAbs) to two epitopes on the receptor binding domain (RBD) and to distinct non-RBD epitopes on the spike (S) protein. As indicated by maintained weight and low lung viral titers in treated animals, the passive transfer of a nAb provides protection against disease in high-dose SARS-CoV-2 challenge in Syrian hamsters. The study suggests a role for nAbs in prophylaxis, and potentially therapy, of COVID-19. The nAbs also define protective epitopes to guide vaccine design., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Protein secondary structure elements (PSSEs) such as α-helices, β-strands, and turns are the primary building blocks of the tertiary protein structure. Our primary interest here is to reveal the characteristics of the nanoenvironment formed by both PSSEs and their surrounding amino acid residues (AARs), which might contribute to the general understanding of how proteins fold. The characteristics of such nanoenvironments must be specific to each secondary structure element, and we have set our goal here to gather the fullest possible description of the α-helical nanoenvironment. In general, this postulate (the existence of specific nanoenvironments for specific protein substructures/neighbourhoods/regions with distinct functionality) was already successfully explored and confirmed for some protein regions, such as protein-protein interfaces and enzyme catalytic sites. Consequently, PSSEs were the obvious next choice for additional work for further evidence showing that specific nanoenvironments (having characteristics fully describable by means of structural and physical chemical descriptors) do exist for the corresponding and determined intraprotein regions. The nanoenvironment of α-helices (nEoαH) is defined as any region of the protein where this secondary structure element type is detected. The nEoαH, therefore, includes not only the α-helix amino acid residues but also the residues immediately around the α-helix. The hypothesis that motivated this work is that it might in fact be possible to detect a postulated "signal" or "signature" that distinguishes the specific location of α-helices. This "signal" must be discernible by tracking differences in the values of physical, chemical, physicochemical, structural and geometric descriptors immediately before (or after) the PSSE from those in the region along the α-helices. The search for this specific nanoenvironment "signal" was made possible by aligning previously selected α-helices of equal length. Afterward, we calculated the average value, standard deviation and mean square error at each aligned residue position for each selected descriptor. We applied Student's t-test, the Kolmogorov-Smirnov test and MANOVA statistical tests to the dataset constructed as described above, and the results confirmed that the hypothesized "signal"/"signature" is both existing/identifiable and capable of distinguishing the presence of an α-helix inside the specific nanoenvironment, contextualized as a specific region within the whole protein. However, such conclusion might rarely be reached if only one descriptor is considered at a time. A more accurate signal with broader coverage is achieved only if one applies multivariate analysis, which means that several descriptors (usually approximately 10 descriptors) should be considered at the same time. To a limited extent (up to a maximum of 15% of cases), such conclusion is also possible with only a single descriptor, and the conclusion is also possible in general for up to 50-80% of cases when no less than 5 nonlinear descriptors are selected and considered. Using all the descriptors considered in this work, provided all assumptions about data characteristics for this analysis are met, multivariate analysis regularly reached a coverage and accuracy above 90%. Understanding how secondary structure elements are formed and maintained within a protein structure could enable a more detailed understanding of how proteins reach their final 3D structure and consequently, their function. Likewise, this knowledge may also improve the tools used to determine how good a structure is by means of comparing the "signal" around a selected PSSE with the one obtained from the best (resolution and quality wise) protein structures available., Competing Interests: The authors have declared that no competing interests exist.

No immunogen to date has reliably elicited broadly neutralizing antibodies to HIV in humans or animal models. Advances in the design of immunogens that antigenically mimic the HIV envelope glycoprotein (Env), such as the soluble cleaved trimer BG505 SOSIP, have improved the elicitation of potent isolate-specific antibody responses in rabbits and macaques, but so far failed to induce broadly neutralizing antibodies. One possible reason for this failure is that the relevant antibody repertoires are poorly suited to target the conserved epitope regions on Env, which are somewhat occluded relative to the exposed variable epitopes. Here, to test this hypothesis, we immunized four cows with BG505 SOSIP. The antibody repertoire of cows contains long third heavy chain complementary determining regions (HCDR3) with an ultralong subset that can reach more than 70 amino acids in length. Remarkably, BG505 SOSIP immunization resulted in rapid elicitation of broad and potent serum antibody responses in all four cows. Longitudinal serum analysis for one cow showed the development of neutralization breadth (20%, n = 117 cross-clade isolates) in 42 days and 96% breadth (n = 117) at 381 days. A monoclonal antibody isolated from this cow harboured an ultralong HCDR3 of 60 amino acids and neutralized 72% of cross-clade isolates (n = 117) with a potent median IC 50 of 0.028 μg ml -1 . Breadth was elicited with a single trimer immunogen and did not require additional envelope diversity. Immunization of cows may provide an avenue to rapidly generate antibody prophylactics and therapeutics to address disease agents that have evolved to avoid human antibody responses.

A major obstacle to a broadly neutralizing antibody (bnAb)-based HIV vaccine is the activation of appropriate B cell precursors. Germline-targeting immunogens must be capable of priming rare bnAb precursors in the physiological setting. We tested the ability of the VRC01-class bnAb germline-targeting immunogen eOD-GT8 60mer (60-subunit self-assembling nanoparticle) to activate appropriate precursors in mice transgenic for human immunoglobulin (Ig) loci. Despite an average frequency of, at most, about one VRC01-class precursor per mouse, we found that at least 29% of singly immunized mice produced a VRC01-class memory response, suggesting that priming generally succeeded when at least one precursor was present. The results demonstrate the feasibility of using germline targeting to prime specific and exceedingly rare bnAb-precursor B cells within a humanlike repertoire., (Copyright © 2016, American Association for the Advancement of Science.)

Induction of broadly neutralizing antibodies (bnAbs) is a primary goal of HIV vaccine development. VRC01-class bnAbs are important vaccine leads because their precursor B cells targeted by an engineered priming immunogen are relatively common among humans. This priming immunogen has demonstrated the ability to initiate a bnAb response in animal models, but recall and maturation toward bnAb development has not been shown. Here, we report the development of boosting immunogens designed to guide the genetic and functional maturation of previously primed VRC01-class precursors. Boosting a transgenic mouse model expressing germline VRC01 heavy chains produced broad neutralization of near-native isolates (N276A) and weak neutralization of fully native HIV. Functional and genetic characteristics indicate that the boosted mAbs are consistent with partially mature VRC01-class antibodies and place them on a maturation trajectory that leads toward mature VRC01-class bnAbs. The results show how reductionist sequential immunization can guide maturation of HIV bnAb responses., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

An optimal HIV vaccine should induce broadly neutralizing antibodies (bnAbs) that neutralize diverse viral strains and subtypes. However, potent bnAbs develop in only a small fraction of HIV-infected individuals, all contain rare features such as extensive mutation, insertions, deletions, and/or long complementarity-determining regions, and some are polyreactive, casting doubt on whether bnAbs to HIV can be reliably induced by vaccination. We engineered two potent VRC01-class bnAbs that minimized rare features. According to a quantitative features frequency analysis, the set of features for one of these minimally mutated bnAbs compared favorably with all 68 HIV bnAbs analyzed and was similar to antibodies elicited by common vaccines. This same minimally mutated bnAb lacked polyreactivity in four different assays. We then divided the minimal mutations into spatial clusters and dissected the epitope components interacting with those clusters, by mutational and crystallographic analyses coupled with neutralization assays. Finally, by synthesizing available data, we developed a working-concept boosting strategy to select the mutation clusters in a logical order following a germline-targeting prime. We have thus developed potent HIV bnAbs that may be more tractable vaccine goals compared to existing bnAbs, and we have proposed a strategy to elicit them. This reductionist approach to vaccine design, guided by antibody and antigen structure, could be applied to design candidate vaccines for other HIV bnAbs or protective Abs against other pathogens., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: WRS is a co-founder and stock holder in Compuvax, Inc. which has programs in non-HIV vaccine design that might benefit indirectly from this research.

The dense patch of high-mannose-type glycans surrounding the N332 glycan on the HIV envelope glycoprotein (Env) is targeted by multiple broadly neutralizing antibodies (bnAbs). This region is relatively conserved, implying functional importance, the origins of which are not well understood. Here we describe the isolation of new bnAbs targeting this region. Examination of these and previously described antibodies to Env revealed that four different bnAb families targeted the (324)GDIR(327) peptide stretch at the base of the gp120 V3 loop and its nearby glycans. We found that this peptide stretch constitutes part of the CCR5 co-receptor binding site, with the high-mannose patch glycans serving to camouflage it from most antibodies. GDIR-glycan bnAbs, in contrast, bound both (324)GDIR(327) peptide residues and high-mannose patch glycans, which enabled broad reactivity against diverse HIV isolates. Thus, as for the CD4 binding site, bnAb effectiveness relies on circumventing the defenses of a critical functional region on Env., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Motivation: A graphical representation of physicochemical and structural descriptors attributed to amino acid residues occupying the same topological position in different, structurally aligned proteins can provide a more intuitive way to associate possible functional implications to identified variations in structural characteristics. This could be achieved by observing selected characteristics of amino acids and of their corresponding nano environments, described by the numerical value of matching descriptor. For this purpose, a web-based tool called multiple structure single parameter (MSSP) was developed and here presented., Results: MSSP produces a two-dimensional plot of a single protein descriptor for a number of structurally aligned protein chains. From a total of 150 protein descriptors available in MSSP, selected of >1500 parameters stored in the STING database, it is possible to create easily readable and highly informative XY-plots, where X-axis contains the amino acid position in the multiple structural alignment, and Y-axis contains the descriptor's numerical values for each aligned structure. To illustrate one of possible MSSP contributions to the investigation of changes in physicochemical and structural properties of mutants, comparing them with the cognate wild-type structure, the oncogenic mutation of M918T in RET kinase is presented. The comparative analysis of wild-type and mutant structures shows great changes in their electrostatic potential. These variations are easily depicted at the MSSP-generated XY-plot., Availability and Implementation: The web server is freely available at http://www.cbi.cnptia.embrapa.br/SMS/STINGm/MPA/index.html Web server implemented in Perl, Java and JavaScript and JMol or Protein Viewer as structure visualizers., Contact: goran.neshich@embrapa.br or gneshich@gmail.com, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Induction of broadly neutralizing antibodies (bnAbs) is a major HIV vaccine goal. Germline-targeting immunogens aim to initiate bnAb induction by activating bnAb germline precursor B cells. Critical unmet challenges are to determine whether bnAb precursor naïve B cells bind germline-targeting immunogens and occur at sufficient frequency in humans for reliable vaccine responses. Using deep mutational scanning and multitarget optimization, we developed a germline-targeting immunogen (eOD-GT8) for diverse VRC01-class bnAbs. We then used the immunogen to isolate VRC01-class precursor naïve B cells from HIV-uninfected donors. Frequencies of true VRC01-class precursors, their structures, and their eOD-GT8 affinities support this immunogen as a candidate human vaccine prime. These methods could be applied to germline targeting for other classes of HIV bnAbs and for Abs to other pathogens., (Copyright © 2016, American Association for the Advancement of Science.)

A major goal of HIV-1 vaccine research is the design of immunogens capable of inducing broadly neutralizing antibodies (bnAbs) that bind to the viral envelope glycoprotein (Env). Poor binding of Env to unmutated precursors of bnAbs, including those of the VRC01 class, appears to be a major problem for bnAb induction. We engineered an immunogen that binds to VRC01-class bnAb precursors and immunized knock-in mice expressing germline-reverted VRC01 heavy chains. Induced antibodies showed characteristics of VRC01-class bnAbs, including a short CDRL3 (light-chain complementarity-determining region 3) and mutations that favored binding to near-native HIV-1 gp120 constructs. In contrast, native-like immunogens failed to activate VRC01-class precursors. The results suggest that rational epitope design can prime rare B cell precursors for affinity maturation to desired targets., (Copyright © 2015, American Association for the Advancement of Science.)

The term "agrochemicals" is used in its generic form to represent a spectrum of pesticides, such as insecticides, fungicides or bactericides. They contain active components designed for optimized pest management and control, therefore allowing for economically sound and labor efficient agricultural production. A "drug" on the other side is a term that is used for compounds designed for controlling human diseases. Although drugs are subjected to much more severe testing and regulation procedures before reaching the market, they might contain exactly the same active ingredient as certain agrochemicals, what is the case described in present work, showing how a small chemical compound might be used to control pathogenicity of Gram negative bacteria Xylella fastidiosa which devastates citrus plantations, as well as for control of, for example, meningitis in humans. It is also clear that so far the production of new agrochemicals is not benefiting as much from the in silico new chemical compound identification/discovery as pharmaceutical production. Rational drug design crucially depends on detailed knowledge of structural information about the receptor (target protein) and the ligand (drug/agrochemical). The interaction between the two molecules is the subject of analysis that aims to understand relationship between structure and function, mainly deciphering some fundamental elements of the nanoenvironment where the interaction occurs. In this work we will emphasize the role of understanding nanoenvironmental factors that guide recognition and interaction of target protein and its function modifier, an agrochemical or a drug. The repertoire of nanoenvironment descriptors is used for two selected and specific cases we have approached in order to offer a technological solution for some very important problems that needs special attention in agriculture: elimination of pathogenicity of a bacterium which is attacking citrus plants and formulation of a new fungicide. Finally, we also briefly describe a workflow which might be useful when research requires that model structures of target proteins are firstly generated (starting from genome sequences), followed by identification of ligand-target sites at the surface of those modeled structures, then application of procedures that adequately prepare both protein and ligand structures (the latter also involving filtration that satisfies acceptable adsorption/desorption/metabolism/excretion/toxicity [ADMET] parameters) for virtual high throughput screening (involving docking of ligands to indicated sites) and terminating by ranking of best pairs: target protein with selected ligand.

Vaccines prevent infectious disease largely by inducing protective neutralizing antibodies against vulnerable epitopes. Several major pathogens have resisted traditional vaccine development, although vulnerable epitopes targeted by neutralizing antibodies have been identified for several such cases. Hence, new vaccine design methods to induce epitope-specific neutralizing antibodies are needed. Here we show, with a neutralization epitope from respiratory syncytial virus, that computational protein design can generate small, thermally and conformationally stable protein scaffolds that accurately mimic the viral epitope structure and induce potent neutralizing antibodies. These scaffolds represent promising leads for the research and development of a human respiratory syncytial virus vaccine needed to protect infants, young children and the elderly. More generally, the results provide proof of principle for epitope-focused and scaffold-based vaccine design, and encourage the evaluation and further development of these strategies for a variety of other vaccine targets, including antigenically highly variable pathogens such as human immunodeficiency virus and influenza.

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING&#95;interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html).

Background: Enzymes belonging to the same super family of proteins in general operate on variety of substrates and are inhibited by wide selection of inhibitors. In this work our main objective was to expand the scope of studies that consider only the catalytic and binding pocket amino acids while analyzing enzyme specificity and instead, include a wider category which we have named the Interface Forming Residues (IFR). We were motivated to identify those amino acids with decreased accessibility to solvent after docking of different types of inhibitors to sub classes of serine proteases and then create a table (matrix) of all amino acid positions at the interface as well as their respective occupancies. Our goal is to establish a platform for analysis of the relationship between IFR characteristics and binding properties/specificity for bi-molecular complexes., Results: We propose a novel method for describing binding properties and delineating serine proteases specificity by compiling an exhaustive table of interface forming residues (IFR) for serine proteases and their inhibitors. Currently, the Protein Data Bank (PDB) does not contain all the data that our analysis would require. Therefore, an in silico approach was designed for building corresponding complexes. The IFRs are obtained by "rigid body docking" among 70 structurally aligned, sequence wise non-redundant, serine protease structures with 3 inhibitors: bovine pancreatic trypsin inhibitor (BPTI), ecotine and ovomucoid third domain inhibitor. The table (matrix) of all amino acid positions at the interface and their respective occupancy is created. We also developed a new computational protocol for predicting IFRs for those complexes which were not deciphered experimentally so far, achieving accuracy of at least 0.97., Conclusions: The serine proteases interfaces prefer polar (including glycine) residues (with some exceptions). Charged residues were found to be uniquely prevalent at the interfaces between the "miscellaneous-virus" subfamily and the three inhibitors. This prompts speculation about how important this difference in IFR characteristics is for maintaining virulence of those organisms.Our work here provides a unique tool for both structure/function relationship analysis as well as a compilation of indicators detailing how the specificity of various serine proteases may have been achieved and/or could be altered. It also indicates that the interface forming residues which also determine specificity of serine protease subfamily can not be presented in a canonical way but rather as a matrix of alternative populations of amino acids occupying variety of IFR positions.

An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one's ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting&#95;RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting&#95;RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting&#95;RDB toward data quality assessment. To the best of our knowledge, Sting&#95;RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting&#95;RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting&#95;rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented. Further details are accessible at the Sting&#95;RDB demo web page: http://www.cbi.cnptia.embrapa.br/StingRDB.

Star STING is the latest version of the STING suite of programs and corresponding database. We report on five important aspects of this package that have acquired some new characteristics, designed to add key advantages to the whole suite: 1) availability for most popular platforms and browsers, 2) introduction of the STING&#95;DB quality assessment, 3) improvement in algorithms for calculation of three STING parameters, 4) introduction of five new STING modules, and 5) expansion of the existing modules. Star STING is freely accessible at: http://sms.cbi.cnptia.embrapa.br/SMS/, http://trantor.bioc.columbia.edu/SMS, http://www.es.embnet.org/SMS/, http://gibk26.bse.kyutech.ac.jp/SMS/ and http://www.ar.embnet.org/SMS.

Predicting enzyme class from protein structure parameters is a challenging problem in protein analysis. We developed a method to predict enzyme class that combines the strengths of statistical and data-mining methods. This method has a strong mathematical foundation and is simple to implement, achieving an accuracy of 45%. A comparison with the methods found in the literature designed to predict enzyme class showed that our method outperforms the existing methods.