Epistructural tension promotes protein associations

Epistructural tension is the reversible work per unit area required to span the aqueous interface of a soluble protein structure. The parameter accounts for the free-energy cost of imperfect hydration, involving water molecules with a shortage of hydrogen bonding partnerships relative to bulk levels. The binding hot spots along protein-protein interfaces are identified with residues that contribute significantly to the epistructural tension in the free subunits. Upon association, such residues either displace or become deprived of low-coordination vicinal water molecules.Fil: Fernandez, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderon; Argentina. University of Wisconsin; Estados Unidos. University of Chicago; Estados Unido

Structural Impact of Mutation D614G in SARS-CoV-2 Spike Protein: Enhanced Infectivity and Therapeutic Opportunity

With the COVID-19 pandemic, the evolutionary fate of SARS-CoV-2 becomes a matter of utmost concern. Mutation D614G in the spike (S) protein has become dominant, and recent evidence suggests it yields a more stable phenotype with higher transmission efficacy. We carry out a structural analysis that provides mechanistic clues on the enhanced infectivity. The D614G substitution creates a sticky packing defect in subunit S1, promoting its association with subunit S2 as a means to stabilize the structure of S1 within the S1/S2 complex. The results raise the therapeutic possibility of immunologically targeting the epitope involved in stabilizing the G614 phenotype as a means of reducing the infection efficacy of SARS-CoV-2. This therapeutic modality would not a-priori interfere directly with current efforts toward the immunological targeting of the RBD epitope; hence, it could be exploited as a complementary treatment.Fil: Fernandez, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentin

A multilayer network approach for guiding drug repositioning in neglected diseases

Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent experimental validations as found post-facto in the literature.Fil: Berenstein, Ariel José. Fundación Instituto Leloir; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Física; ArgentinaFil: Magariños, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); ArgentinaFil: Chernomoretz, Ariel. Fundación Instituto Leloir; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Física; ArgentinaFil: Fernandez Aguero, Maria Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); Argentin

Drug-based cancer therapy to overcome immune resistance by steering tumor evolution

We argue that therapy must lead rather than follow vis-à-vis cancer evolution. Clinical experience suggests that the evading phenotype resulting from treatment can never be fully anticipated or eliminated when a single source of selection pressure is applied during treatment. Thus, therapy must steer cancer evolution and LIC may well become the underlying paradigm to overcome resistance in a therapeutic context where immune surveillance is maintained.Fil: Fernandez, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentin

Targeted therapy to annihilate the immune-evading phenotype in cancer evolution

Cancer is a moving target, and targeted therapy must ultimatelydeal with the evolution of the disease. This is becauseevolution is the substrate for development of resistance totargeted therapy. A successful therapeutic strategy is onethat can tackle and ultimately eliminate the evading phenotype.Thus, to steer cancer evolution for therapeutic purposes,one must first note that targeted therapy imposes selectionpressure and resistant phenotypes prevail in a context ofclonal heterogeneity. The quest for complete cure makes itimperative to control the evolutionary fate of the tumor.We focus on the problem of cornering the evolving phenotypepromoted by T cell checkpoint blockade. Theseantibodies unleash the anti-tumor adaptive immune responseby blocking an off-switch T-cell receptor whose natural ligandis secreted by the tumor. In this way, checkpoint blockers turnoff the negative signal in tumor-induced immunosuppression.This immunotherapy constitutes possibly the most auspiciousanticancer treatment to date. In this context, cancer evolutionresults in immunoediting, and the evolving phenotype may besteered by targeting signaling pathways that control the modulationof the adaptive immune response, as shown in thiseditorial.Fil: Fernandez, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentin

Manfred Eigen

Manfred Eigen, Nobel laureate, 1928-2019.Fil: Fernandez, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentin

Quasilinear eigenvalues

In this work, we review and extend some well known results for the eigenvalues of the Dirichlet $p-$Laplace operator to a more general class of monotone quasilinear elliptic operators. As an application we obtain some homogenization results for nonlinear eigenvalues.Comment: 23 pages, Rev. UMA, to appea