Biology subjects

Bolon, D. N. A.

Publications and source records attributed to Bolon, D. N. A..

9 recordsLinked to original sources

bioRxiv2025

Cooperativity and Communication between the Active Sites of the Dimeric SARS-CoV-2 Main Protease

The coronaviral main protease (Mpro) is essential for the replication of the virus, and has been the subject of various biochemical, structural and enzymatic studies, as well as a drug target against SARS-CoV-2 infections. SARS-CoV-2 Mpro is known to be active as a dimer, with the N terminus of one protomer completing a key active site pocket of the other protomer. Despite apparent cooperativity in catalytic activity, how the two distal active sites in the dimer communicate and might be modulating binding and/or catalysis at the other remain to be clarified. Here, we have investigated the interplay between cooperativity, dimerization, and substrate cleavage in SARS-CoV-2 Mpro through a combination of enzymatic assays, crystal structures, and protein characterization. To disentangle the contribution of each active site to the observed enzymatic activity, we developed a cleavage assay involving heterodimers of active and inactive (C145A or inhibitor-bound) monomers. Strikingly, we found that heterodimerization increased cleavage efficiency per active monomer. Additionally, we mapped a network of critical residues bridging the two active sites and probed this network through engineered mutations. By dissecting the cooperativity and communication between the active sites, we provide new insights into the Mpro reaction cycle and functional significance of its dimeric architecture.

biochemistry↗

bioRxiv2023

Systematic analyses of the resistance potential of drugs targeting SARS-CoV-2 main protease

Drugs that target the main protease (Mpro) of SARS-CoV-2 are effective therapeutics that have entered clinical use. Wide-scale use of these drugs will apply selection pressure for the evolution of resistance mutations. To understand resistance potential in Mpro, we performed comprehensive surveys of amino acid changes that can cause resistance in a yeast screen to nirmatrelvir (contained in the drug Paxlovid), and ensitrelvir (Xocova) that is currently in phase III trials. The most impactful resistance mutation (E166V) recently reported in multiple viral passaging studies with nirmatrelvir showed the strongest drug resistance score for nirmatrelvir, while P168R had the strongest resistance score for ensitrelvir. Using a systematic approach to assess potential drug resistance, we identified 142 resistance mutations for nirmatrelvir and 177 for ensitrelvir. Among these mutations, 99 caused apparent resistance to both inhibitors, suggesting a strong likelihood for the evolution of cross-resistance. Many mutations that exhibited inhibitor-specific resistance were consistent with distinct ways that each inhibitor protrudes beyond the substrate envelope. In addition, mutations with strong drug resistance scores tended to have reduced function. Our results indicate that strong pressure from nirmatrelvir or ensitrelvir will select for multiple distinct resistant lineages that will include both primary resistance mutations that weaken interactions with drug while decreasing enzyme function and secondary mutations that increase enzyme activity. The comprehensive identification of resistance mutations enables the design of inhibitors with reduced potential of developing resistance and aids in the surveillance of drug resistance in circulating viral populations.

molecular biology↗

bioRxiv2022

Complete mutational mapping of a GTPase switch in vivo reveals novel allosteric regulation

Allosteric regulation is central to protein function in cellular networks1. However, despite technological advances2,3 most studies of allosteric effects on function are conducted in heterologous environments2,4,5, limiting the discovery of allosteric mechanisms that rely on endogenous binding partners or posttranslational modifications to modulate activity. Here we report an approach that enables probing of new sites of allosteric regulation at residue-level resolution in essential eukaryotic proteins in their native biological context by comprehensive mutational scanning. We apply our approach to the central GTPase Gsp1/Ran. GTPases are highly regulated molecular switches that control signaling, with switching occurring via catalyzed GTP hydrolysis and nucleotide exchange. We find that 28% of 4,315 assayed mutations in Gsp1/Ran are highly deleterious, showing a toxic response identified by our assay as gain-of-function (GOF). Remarkably, a third of all positions enriched for GOF mutations (20/60) are outside the GTPase active site. Kinetic analysis shows that these distal sites are allosterically coupled to the active site, including a novel cluster of sites that alter the nucleotide preference of Gsp1 from GDP to GTP. We describe multiple distinct mechanisms by which allosteric mutations alter Gsp1/Ran cellular function by modulating GTPase switching. Our systematic discovery of new regulatory sites provides a functional map relevant to other GTPases such as Ras that could be exploited for targeting and reprogramming critical biological processes.

biophysics↗

bioRxiv2022

Comprehensive fitness landscape of SARS-CoV-2 Mpro reveals insights into viral resistance mechanisms

With the continual evolution of new strains of SARS-CoV-2 that are more virulent, transmissible, and able to evade current vaccines, there is an urgent need for effective anti-viral drugs. SARS-CoV-2 main protease (Mpro) is a leading target for drug design due to its conserved and indispensable role in the viral life cycle. Drugs targeting Mpro appear promising but will elicit selection pressure for resistance. To understand resistance potential in Mpro, we performed a comprehensive mutational scan of the protease that analyzed the function of all possible single amino acid changes. We developed three separate high-throughput assays of Mpro function in yeast, based on either the ability of Mpro variants to cleave at a defined cut-site or on the toxicity of their expression to yeast. We used deep sequencing to quantify the functional effects of each variant in each screen. The protein fitness landscapes from all three screens were strongly correlated, indicating that they captured the biophysical properties critical to Mpro function. The fitness landscapes revealed a non-active site location on the surface that is extremely sensitive to mutation making it a favorable location to target with inhibitors. In addition, we found a network of critical amino acids that physically bridge the two active sites of the Mpro dimer. The clinical variants of Mpro were predominantly functional in our screens, indicating that Mpro is under strong selection pressure in the human population. Our results provide predictions of mutations that will be readily accessible to Mpro evolution and that are likely to contribute to drug resistance. This complete mutational guide of Mpro can be used in the design of inhibitors with reduced potential of evolving viral resistance.

molecular biology↗

bioRxiv2019

Mapping the growth effect of previously hidden ubiquitin alleles using an overexpression based mutational scan

Deep mutational scanning has emerged as a powerful, high throughput approach to determine the growth effect of thousands of alleles at once in bulk competition. However, to date only the growth effect of mutant alleles in isolation has been determined. Building off previous work, we have created a library of all possible single point mutations in ubiquitin and determined the growth effect of mutants overexpressed in the presence of a wild type allele. Using this scan, we explained over half of the previously missing mutants in the single allele scan by showing that they exhibit deleterious effects when co-expressed with wild type ubiquitin. Additionally, unlike the single allele growth effect, these overexpression growth effects were distributed across the entire protein. This overexpression scan methodology can identify likely dominant mutant effects in any essential gene and is highly complementary with traditional deep mutational scanning approaches.

genetics↗

bioRxiv2019

The adaptive potential of the M-domain of yeast Hsp90

The distribution of fitness effects (DFE) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the DFEs of the same {approx}2300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat-shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase-chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client binding interfaces, or residues that are involved in ATPase chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

evolutionary biology↗

bioRxiv2019

Investigating the influence of environment on the evolution of Hsp90 using comprehensive fitness maps

Gene-environment interactions have long been theorized to influence molecular evolution. However, the environmental dependence of most mutations remains unknown. Using deep mutational scanning, we engineered yeast with all 44,604 single codon changes encoding 14,160 amino acid variants in Hsp90 and quantified growth effects under standard conditions and under five stress conditions. To our knowledge these are the largest determined comprehensive fitness maps of point mutants. The growth of many variants differed between conditions, indicating that environment can have a large impact on Hsp90 evolution. Multiple variants provided growth advantages under individual conditions, however these variants tended to exhibit growth defects in other environments. The diversity of Hsp90 sequences observed in extant eukaryotes preferentially contains variants that supported robust growth under all tested conditions. Rather than favoring substitutions in individual conditions, the long-term selective pressure on Hsp90 may have been that of fluctuating environments, leading to robustness under a variety of conditions.

evolutionary biology↗

bioRxiv2018

Constrained mutational sampling of amino acids in HIV-1 protease evolution

The evolution of HIV-1 protein sequences should be governed by a combination of factors including nucleotide mutational probabilities, the genetic code, and fitness. The impact of these factors on protein sequence evolution are interdependent, making it challenging to infer the individual contribution of each factor from phylogenetic analyses alone. We investigated the protein sequence evolution of HIV-1 by determining an experimental fitness landscape of all individual amino acid changes in protease. We compared our experimental results to the frequency of protease variants in a publicly available dataset of 32,163 sequenced isolates from drug-naive individuals. The most common amino acids in sequenced isolates supported robust experimental fitness, indicating that the experimental fitness landscape captured key features of selection acting on protease during viral infections of hosts. Amino acid changes requiring multiple mutations from the likely ancestor were slightly less likely to support robust experimental fitness than single mutations, consistent with the genetic code favoring chemically conservative amino acid changes. Amino acids that were common in sequenced isolates were predominantly accessible by single mutations from the likely protease ancestor. Multiple mutations commonly observed in isolates were accessible by mutational walks with highly fit single mutation intermediates. Our results indicate that the prevalence of multiple base mutations in HIV-1 protease is strongly influenced by mutational sampling.

evolutionary biology↗

bioRxiv2017

Pervasive contingency and entrenchment in a billion years of Hsp90 evolution

Although many potential mutations within proteins modulate each others effects1-4, the extent to which these epistatic interactions influenced the fitness effects of the sequence changes that actually occurred during historical evolution - and thus made molecular evolution contingent and irreversible - is controversial5-16. We addressed this question directly by precisely measuring the fitness effects in both extant and reconstructed ancestral sequence contexts of all historical amino acid substitutions that occurred during the billion-year evolutionary history of the heat shock protein 90 (Hsp90) ATPase domain beginning from a deep eukaryotic ancestor to modern Saccharomyces cerevisiae. We find a pervasive influence of epistasis on historical sequence evolution: the majority of the 98 derived states that evolved during history were deleterious at times before they happened, and the vast majority also became subsequently entrenched6, with the ancestral state becoming deleterious after its substitution. A few of these epistatic interactions were of massive fitness consequence, but the majority were of small but evolutionarily relevant effect size. We find that both the large- and small-effect epistasis were largely caused by specific interactions among sites rather than a general permissive or restrictive effect17. Our results highlight how epistasis continually opens and closes windows of mutational opportunity over evolutionary timescales, producing histories and biological states that reflect, in significant part, the transient internal constraints imposed by a proteins fleeting sequence states.

evolutionary biology↗