Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first 6 months of the COVID-19 pandemic.

Understanding the molecular evolution of the SARS-CoV-2 virus as it continues to spread in communities around the globe is important for mitigation and future pandemic preparedness. Three-dimensional structures of SARS-CoV-2 proteins and those of other coronavirusess archived in the Protein Data Bank were used to analyze viral proteome evolution during the first 6 months of the COVID-19 pandemic. Analyses of spatial locations, chemical properties, and structural and energetic impacts of the observed amino acid changes in >48 000 viral isolates revealed how each one of 29 viral proteins have undergone amino acid changes. Catalytic residues in active sites and binding residues in protein-protein interfaces showed modest, but significant, numbers of substitutions, highlighting the mutational robustness of the viral proteome. Energetics calculations showed that the impact of substitutions on the thermodynamic stability of the proteome follows a universal bi-Gaussian distribution. Detailed results are presented for potential drug discovery targets and the four structural proteins that comprise the virion, highlighting substitutions with the potential to impact protein structure, enzyme activity, and protein-protein and protein-nucleic acid interfaces. Characterizing the evolution of the virus in three dimensions provides testable insights into viral protein function and should aid in structure-based drug discovery efforts as well as the prospective identification of amino acid substitutions with potential for drug resistance.

Biomolecular Condensates: Sequence Determinants of Phase Separation, Microstructural Organization, Enzymatic Activity, and Material Properties.

This perspective article highlights recent progress and emerging challenges in understanding the formation and function of membraneless organelles (MLOs). A long-term goal in the MLO field is to identify the sequence-encoded rules that dictate the formation of compositionally controlled biomolecular condensates, which cells utilize to perform a wide variety of functions. The molecular organization of the different components within a condensate can vary significantly, ranging from a homogeneous mixture to core-shell droplet structures. We provide many examples to highlight the richness of the observed behavior and potential research directions for improving our mechanistic understanding. The tunable environment within condensates can, in principle, alter enzymatic activity significantly. We examine recent examples where this was demonstrated, including applications in synthetic biology. An important question about MLOs is the role of liquid-like material properties in biological function. We discuss the need for improved quantitative characterization tools and the development of sequence-structure-dynamics relationships.

Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first six months of the COVID-19 pandemic.

Three-dimensional structures of SARS-CoV-2 and other coronaviral proteins archived in the Protein Data Bank were used to analyze viral proteome evolution during the first six months of the COVID-19 pandemic. Analyses of spatial locations, chemical properties, and structural and energetic impacts of the observed amino acid changes in >48,000 viral proteome sequences showed how each one of the 29 viral study proteins have undergone amino acid changes. Structural models computed for every unique sequence variant revealed that most substitutions map to protein surfaces and boundary layers with a minority affecting hydrophobic cores. Conservative changes were observed more frequently in cores versus boundary layers/surfaces. Active sites and protein-protein interfaces showed modest numbers of substitutions. Energetics calculations showed that the impact of substitutions on the thermodynamic stability of the proteome follows a universal bi-Gaussian distribution. Detailed results are presented for six drug discovery targets and four structural proteins comprising the virion, highlighting substitutions with the potential to impact protein structure, enzyme activity, and functional interfaces. Characterizing the evolution of the virus in three dimensions provides testable insights into viral protein function and should aid in structure-based drug discovery efforts as well as the prospective identification of amino acid substitutions with potential for drug resistance.

Protease-Catalyzed l-Aspartate Oligomerization: Substrate Selectivity and Computational Modeling.

Poly(aspartic acid) (PAA) is a biodegradable water-soluble anionic polymer that can potentially replace poly(acrylic acid) for industrial applications and has shown promise for regenerative medicine and drug delivery. This paper describes an efficient and sustainable route that uses protease catalysis to convert l-aspartate diethyl ester (Et2-Asp) to oligo(ß-ethyl-α-aspartate), oligo(ß-Et-α-Asp). Comparative studies of protease activity for oligo(ß-Et-α-Asp) synthesis revealed α-chymotrypsin to be the most efficient. Papain, which is highly active for l-glutamic acid diethyl ester (Et2-Glu) oligomerization, is inactive for Et2-Asp oligomerization. The assignment of α-linkages between aspartate repeat units formed by α-chymotrypsin catalysis is based on nuclear magnetic resonance (NMR) trifluoacetic acid titration, circular dichroism, and NMR structural analysis. The influence of reaction conditions (pH, temperature, reaction time, and buffer/monomer/α-chymotrypsin concentrations) on oligopeptide yield and average degree of polymerization (DPavg) was determined. Under preferred reaction conditions (pH 8.5, 40 °C, 0.5 M Et2-Asp, 3 mg/mL α-chymotrypsin), Et2-Asp oligomerizations reached maximum oligo(ß-Et-α-Asp) yields of ∼60% with a DPavg of ∼12 (M n 1762) in just 5 min. Computational modeling using Rosetta software gave relative energies of substrate docking to papain and α-chymotrypsin active sites. The substrate preference calculated by Rosetta modeling of α-chymotrypsin and papain for Et2-Asp and Et2-Glu oligomerizations, respectively, is consistent with experimental results.

Mathematical Models of Protease-Based Enzymatic Biosensors.

An important goal of synthetic biology is to build biosensors and circuits with well-defined input-output relationships that operate at speeds found in natural biological systems. However, for molecular computation, most commonly used genetic circuit elements typically involve several steps from input detection to output signal production: transcription, translation, and post-translational modifications. These multiple steps together require up to several hours to respond to a single stimulus, and this limits the overall speed and complexity of genetic circuits. To address this gap, molecular frameworks that rely exclusively on post-translational steps to realize reaction networks that can process inputs at a time scale of seconds to minutes have been proposed. Here, we build mathematical models of fast biosensors capable of producing Boolean logic functionality. We employ protease-based chemical and light-induced switches, investigate their operation, and provide selection guidelines for their use as on-off switches. As a proof of concept, we implement a rapamycin-induced switch in vitro and demonstrate that its response qualitatively agrees with the predictions from our models. We then use these switches as elementary blocks, developing models for biosensors that can perform OR and XOR Boolean logic computation while using reaction conditions as tuning parameters. We use sensitivity analysis to determine the time-dependent sensitivity of the output to proteolytic and protein-protein binding reaction parameters. These fast protease-based biosensors can be used to implement complex molecular circuits with a capability of processing multiple inputs controllably and algorithmically. Our framework for evaluating and optimizing circuit performance can be applied to other molecular logic circuits.

Computation-Guided Design of a Stimulus-Responsive Multienzyme Supramolecular Assembly.

The construction of stimulus-responsive supramolecular complexes of metabolic pathway enzymes, inspired by natural multienzyme assemblies (metabolons), provides an attractive avenue for efficient and spatiotemporally controllable one-pot biotransformations. We have constructed a phosphorylation- and optically responsive metabolon for the biodegradation of the environmental pollutant 1,2,3-trichloropropane.