Computational Approach for Rational Design of Fusion Uricase with PAS Sequences.
Ontology highlight
ABSTRACT:
SUBMITTER: Najjari A
PROVIDER: S-EPMC7422847 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ASCT2 (SLC1A5) is a sodium-dependent neutral amino acid transporter that controls amino acid homeostasis in peripheral tissues. In cancer, ASCT2 is up-regulated where it modulates intracellular glutamine levels, fueling cell proliferation. Nutrient deprivation via ASCT2 inhibition provides a potential strategy for cancer therapy. Here, we rationally designed stereospecific inhibitors exploiting specific subpockets in the substrate binding site using computational modeling and cryo-electron microscopy (cryo-EM). The final structures combined with molecular dynamics simulations reveal multiple pharmacologically relevant conformations in the ASCT2 binding site as well as a previously unknown mechanism of stereospecific inhibition. Furthermore, this integrated analysis guided the design of a series of unique ASCT2 inhibitors. Our results provide a framework for future development of cancer therapeutics targeting nutrient transport via ASCT2, as well as demonstrate the utility of combining computational modeling and cryo-EM for solute carrier ligand discovery.
| S-EPMC8449414 | biostudies-literature
Project description:Due to the synergic relationship between medical chemistry, bioinformatics and molecular simulation, the development of new accurate computational tools for small molecules drug design has been rising over the last years. The main result is the increased number of publications where computational techniques such as molecular docking, de novo design as well as virtual screening have been used to estimate the binding mode, site and energy of novel small molecules. In this work I review some tools, which enable the study of biological systems at the atomistic level, providing relevant information and thereby, enhancing the process of rational drug design.
| S-EPMC5039900 | biostudies-literature
Project description:Temperature-sensitive (ts) mutations are mutations that exhibit a mutant phenotype at high or low temperatures and a wild-type phenotype at normal temperature. Temperature-sensitive mutants are valuable tools for geneticists, particularly in the study of essential genes. However, finding ts mutations typically relies on generating and screening many thousands of mutations, which is an expensive and labor-intensive process. Here we describe an in silico method that uses Rosetta and machine learning techniques to predict a highly accurate "top 5" list of ts mutations given the structure of a protein of interest. Rosetta is a protein structure prediction and design code, used here to model and score how proteins accommodate point mutations with side-chain and backbone movements. We show that integrating Rosetta relax-derived features with sequence-based features results in accurate temperature-sensitive mutation predictions.
| S-EPMC3166291 | biostudies-literature
Project description:Proteins are the most multifaceted macromolecules in living systems and have various important functions, including structural, catalytic, sensory, and regulatory functions. Rational design of enzymes is a great challenge to our understanding of protein structure and physical chemistry and has numerous potential applications. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. The field of de novo protein design, although only a few decades old, is beginning to produce exciting results. Developments in this field are already having a significant impact on biotechnology and chemical biology. The application of powerful computational methods for functional protein designing has recently succeeded at engineering target activities. Here, we review recently reported de novo functional proteins that were developed using various protein design approaches, including rational design, computational optimization, and selection from combinatorial libraries, highlighting recent advances and successes.
| S-EPMC3962203 | biostudies-literature
Project description:Hyperuricemia is a prevalent disease worldwide that is characterized by elevated urate levels in the blood owing to purine metabolic disorders, which can result in gout and comorbidities. To facilitate the treatment of hyperuricemia through the uricolysis, we engineered a probiotic Escherichia coli Nissle 1917 (EcN) named EcN C6 by inserting an FtsP-uricase cassette into an "insulated site" located between the uspG and ahpF genes. Expression of FtsP-uricase in this insulated region did not influence the probiotic properties or global gene transcription of EcN but strongly increased the enzymatic activity for urate degeneration, suggesting that the genome-based insulated system is an ideal strategy for EcN modification. Oral administration of EcN C6 successfully alleviated hyperuricemia, related symptoms and gut microbiota in a purine-rich food-induced hyperuricemia rat model and a uox-knockout mouse model. Together, our study provides an insulated site for heterologous gene expression in EcN strain and a recombinant EcN C6 strain as a safe and effective therapeutic candidate for hyperuricemia treatment.
| S-EPMC10013758 | biostudies-literature
Project description:A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.
| S-EPMC3309769 | biostudies-literature
Project description:Alzheimer's disease (AD) is a neurodegenerative disorder that lacks effective treatment options. Anti-amyloid beta (A?) antibodies are the leading drug candidates to treat AD, but the results of clinical trials have been disappointing. Introducing rational mutations into anti-A? antibodies to increase their effectiveness is a way forward, but the path to take is unclear. In this study, we demonstrate the use of computational fragment-based docking and MMPBSA binding free energy calculations in the analysis of anti-A? antibodies for rational drug design efforts. Our fragment-based docking method successfully predicts the emergence of the common EFRH epitope. MD simulations coupled with MMPBSA binding free energy calculations are used to analyze scenarios described in prior studies, and we computationally introduce rational mutations into PFA1 to predict mutations that can improve its binding affinity toward the pE3-A?3-8 form of A?. Two out of our four proposed mutations are predicted to stabilize binding. Our study demonstrates that a computational approach may lead to an improved drug candidate for AD in the future.
| S-EPMC5927393 | biostudies-literature
Project description:Hybridization probes have become an indispensable tool for nucleic acid analysis. Systematic efforts in probe optimization resulted in their improved binding affinity, turn-on ratios, and ability to discriminate single nucleotide substitutions (SNSs). The use of split (or multicomponent) probes is a promising strategy to improve probe selectivity and enable an analysis of folded analytes. Here, we developed criteria for the rational design of a split G-quadruplex (G4) peroxidase-like deoxyribozyme (sPDz) probe that provides a visual output signal. The sPDz probe consists of two DNA strands that hybridize to the abutting positions of a DNA/RNA target and form a G4 structure catalyzing, in the presence of a hemin cofactor, H2O2-mediated oxidation of organic compounds into their colored oxidation products. We have demonstrated that probe design becomes complicated in the case of target sequences containing clusters (two or more) of cytosine residues and developed strategies to overcome the challenges to achieving high signal-to-noise and excellent SNS discrimination. Specifically, to improve selectivity, a conformational constraint that stabilizes the probe's dissociated state is beneficial. If the signal intensity is compromised, introduction of flexible non-nucleotide linkers between the G4-forming and target-recognizing elements of the probe helps to decrease the steric hindrance for G4 PDz formation observed as a signal increase. Varying the modes of G4 core splitting is another instrument for the optimal sPDz design. The suggested algorithm was successfully utilized for the design of the sPDz probe interrogating a fragment of the Influenza A virus genome (subtype H1N1), which can be of practical use for flu diagnostics and surveillance.
| S-EPMC7179085 | biostudies-literature
Project description:Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules. In the past, such representations were utilized to compare protein structures on global and local scales and have shed light on functional properties of proteins. Here we describe RosettaSurf, a surface-centric computational design protocol, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering, offering a unique approach for the design of proteins and their functions. The RosettaSurf protocol combines the explicit optimization of molecular surface features with a global scoring function during the sequence design process, diverging from the typical design approaches that rely solely on an energy scoring function. With this computational approach, we attempt to address a fundamental problem in protein design related to the design of functional sites in proteins, even when structurally similar templates are absent in the characterized structural repertoire. Surface-centric design exploits the premise that molecular surfaces are, to a certain extent, independent of the underlying sequence and backbone configuration, meaning that different sequences in different proteins may present similar surfaces. We benchmarked RosettaSurf on various sequence recovery datasets and showcased its design capabilities by generating epitope mimics that were biochemically validated. Overall, our results indicate that the explicit optimization of surface features may lead to new routes for the design of functional proteins.
| S-EPMC9015148 | biostudies-literature
Project description:Analysis of whole mouse muscle and inguinal lymph node gene expression signature induced after 24h by in-vivo intramuscularly administration of R848, SMIP-7.7, SMIP-7.8 and 4%DMSO controls. Analysis of whole mouse muscle and inguinal lymph node gene expression signature induced after 6h by in-vivo intramuscularly administration of R848 and SMIP-7.2 in 1% DMSO, and SMIP-7.10 and SMIP-7.10+alum in Buffer.
2015-11-02 | E-MTAB-2948 | biostudies-arrayexpress