Ligand binding site superposition and comparison based on Atomic Property Fields: identification of distant homologues, convergent evolution and PDB-wide clustering of binding sites

A new binding site comparison algorithm using optimal superposition of the continuous pharmacophoric property distributions is reported. The method demonstrates high sensitivity in discovering both, distantly homologous and convergent binding sites. Good quality of superposition is also observed on multiple examples. Using the new approach, a measure of site similarity is derived and applied to clustering of ligand binding pockets in PDB

In silico Drug Repurposing for COVID-19: Targeting SARS-CoV-2 Proteins through Docking and Consensus Ranking

In December 2019, an infectious disease caused by the coronavirus SARS-CoV-2 appeared in Wuhan, China. This disease (COVID-19) spread rapidly worldwide, and on March 2020 was declared a pandemic by the World Health Organization (WHO). Today, over 21 million people have been infected, with more than 750.000 casualties. Today, no vaccine or antiviral drug is available. While the development of a vaccine might take at least a year, and for a novel drug, even longer; finding a new use to an old drug (drug repurposing) could be the most effective strategy. We present a docking-based screening using a quantum mechanical scoring of a library built from approved drugs and compounds undergoing clinical trials, against three SARS-CoV-2 target proteins: the spike or S-protein, and two proteases, the main protease and the papain-like protease. The S-protein binds directly to the Angiotensin Converting Enzyme 2 receptor of the human host cell surface, while the two proteases process viral polyproteins. Following the analysis of our structure-based compound screening, we propose several structurally diverse compounds (either FDA-approved or in clinical trials) that could display antiviral activity against SARS-CoV-2. Clearly, these compounds should be further evaluated in experimental assays and clinical trials to confirm their actual activity against the disease. We hope that these findings may contribute to the rational drug design against COVID-19.Fil: Cavasotto, Claudio Norberto. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; ArgentinaFil: Di Filippo, Juan Ignacio. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentin

Rationally Designed Immunogens Targeting HIV-1 gp120 V1V2 Induce Distinct Conformation-Specific Antibody Responses in Rabbits

The V1V2 region of HIV-1 gp120 harbors a major vulnerable site targeted by a group of broadly neutralizing monoclonal antibodies (MAbs) such as PG9 through strand-strand recognition. However, this epitope region is structurally polymorphic as it can also form a helical conformation recognized by RV144 vaccine-induced MAb CH58. This structural polymorphism is a potential mechanism for masking the V1V2 vulnerable site. Designing immunogens that can induce conformation-specific antibody (Ab) responses may lead to vaccines targeting this vulnerable site. We designed a panel of immunogens engrafting the V1V2 domain into trimeric and pentameric scaffolds in structurally constrained conformations. We also fused V1V2 to an Fc fragment to mimic the unconstrained V1V2 conformation. We tested these V1V2-scaffold proteins for immunogenicity in rabbits and assessed the responses by enzyme-linked immunosorbent assay (ELISA) and competition assays. Our V1V2 immunogens induced distinct conformation-specific Ab responses. Abs induced by structurally unconstrained immunogens reacted preferentially with unconstrained V1V2 antigens, suggesting recognition of the helical configuration, while Abs induced by the structurally constrained immunogens reacted preferentially with constrained V1V2 antigens, suggesting recognition of the beta-strand conformation. The Ab responses induced by the structurally constrained immunogens were more broadly reactive and had higher titers than those induced by the structurally unconstrained immunogens. Our results demonstrate that immunogens presenting the different structural conformations of the gp120 V1V2 vulnerable site can be designed and that these immunogens induce distinct Ab responses with epitope conformation specificity. Therefore, these structurally constrained V1V2 immunogens are vaccine prototypes targeting the V1V2 domain of the HIV-1 envelope. IMPORTANCE: The correlates analysis of the RV144 HIV-1 vaccine trial suggested that the presence of antibodies to the V1V2 region of HIV-1 gp120 was responsible for the modest protection observed in the trial. In addition, V1V2 harbors one of the key vulnerable sites of HIV-1 Env recognized by a family of broadly neutralizing MAbs such as PG9. Thus, V1V2 is a key target for vaccine development. However, this vulnerable site is structurally polymorphic, and designing immunogens that present different conformations is crucial for targeting this site. We show here that such immunogens can be designed and that they induced conformation-specific antibody responses in rabbits. Our immunogens are therefore prototypes of vaccine candidates targeting the V1V2 region of HIV-1 Env

Continuous dielectric permittivity II: An Iterative Method for Calculating the Polar Component of the Molecular Solvation Gibbs Energy Under a Smooth Change in the Dielectric Permittivity of a Solution

An iterative method for calculating the polar component of the solvation Gibbs energy under a smooth change in dielectric permittivity, both between a substrate and a solvent and in a solvent is formulated on the basis of a previously developed model. The method is developed in the approximation of the local relationship D = \eps (r) E between the displacement vectors D and the electric field intensity E.Comment: 36 pages,3 Figures, in English and in Russia

Spatial chemical distance based on atomic property fields

Similarity of compound chemical structures often leads to close pharmacological profiles, including binding to the same protein targets. The opposite, however, is not always true, as distinct chemical scaffolds can exhibit similar pharmacology as well. Therefore, relying on chemical similarity to known binders in search for novel chemicals targeting the same protein artificially narrows down the results and makes lead hopping impossible. In this study we attempt to design a compound similarity/distance measure that better captures structural aspects of their pharmacology and molecular interactions. The measure is based on our recently published method for compound spatial alignment with atomic property fields as a generalized 3D pharmacophoric potential. We optimized contributions of different atomic properties for better discrimination of compound pairs with the same pharmacology from those with different pharmacology using Partial Least Squares regression. Our proposed similarity measure was then tested for its ability to discriminate pharmacologically similar pairs from decoys on a large diverse dataset of 115 protein–ligand complexes. Compared to 2D Tanimoto and Shape Tanimoto approaches, our new approach led to improvement in the area under the receiver operating characteristic curve values in 66 and 58% of domains respectively. The improvement was particularly high for the previously problematic cases (weak performance of the 2D Tanimoto and Shape Tanimoto measures) with original AUC values below 0.8. In fact for these cases we obtained improvement in 86% of domains compare to 2D Tanimoto measure and 85% compare to Shape Tanimoto measure. The proposed spatial chemical distance measure can be used in virtual ligand screening

T-Analyst: a program for efficient analysis of protein conformational changes by torsion angles

T-Analyst is a user-friendly computer program for analyzing trajectories from molecular modeling. Instead of using Cartesian coordinates for protein conformational analysis, T-Analyst is based on internal bond-angle-torsion coordinates in which internal torsion angle movements, such as side-chain rotations, can be easily detected. The program computes entropy and automatically detects and corrects angle periodicity to produce accurate rotameric states of dihedrals. It also clusters multiple conformations and detects dihedral rotations that contribute hinge-like motions. Correlated motions between selected dihedrals can also be observed from the correlation map. T-Analyst focuses on showing changes in protein flexibility between different states and selecting representative protein conformations for molecular docking studies. The program is provided with instructions and full source code in Perl