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1. Mutational analysis confirms the presence of distal inhibitor-selectivity determining residues in B. stearothermophilus dihydrofolate reductase

   Eck, Tyler; Patel, Seema; Candela, Thomas; Leon H, Katherine; Little, Michael; Reis, Natalia E.; Liyanagunawardana, Uththara; Gubler, Ueli; Janson, Cheryl A.; Catalano, Jaclyn; et al (January 2020, Archives of biochemistry and biophysics)

   null (Ed.)

   Many antibacterial and antiparasitic drugs work by competitively inhibiting dihydrofolate reductase (DHFR), a vital enzyme in folate metabolism. The interactions between inhibitors and DHFR active site residues are known in many homologs but the contributions from distal residues are less understood. Identifying distal residues that aid in inhibitor binding can improve targeted drug development programs by accounting for distant influences that may be less conserved and subject to frequent resistance causing mutations. Previously, a novel, homologybased, computational approach that mines ligand inhibition data was used to predict residues involved in inhibitor selectivity in the DHFR family. Expectedly, some inhibitor selectivity determining residue positions were predicted to lie in the active site and coincide with experimentally known inhibitor selectivity determining positions. However, other residues that group spatially in clusters distal to the active site have not been previously investigated. In this study, the effect of introducing amino acid substitutions at one of these predicted clusters (His38-Ala39-Ile40) on the inhibitor selectivity profile in Bacillus stearothermophilus dihydrofolate reductase (Bs DHFR) was investigated. Mutations were introduced into these cluster positions to change sidechain chemistry and size. We determined kcat and KM values and measured KD values at equilibrium for two competitive DHFR inhibitors, trimethoprim (TMP) and pyrimethamine (PYR). Mutations in the His38-Ala39-Ile40 cluster significantly impacted inhibitor binding and TMP/PYR selectivity - seven out of nine mutations resulted in tighter binding to PYR when compared to TMP. These data suggest that the His38-Ala39-Ile40 cluster is a distal inhibitor selectivity determining region that favors PYR binding in Bs DHFR and, possibly, throughout the DHFR family. 

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2. Allostery and Epistasis: Emergent Properties of Anisotropic Networks

   https://doi.org/10.3390/e22060667  

   Campitelli, Paul; Ozkan, S. Banu (June 2020, Entropy)

   Understanding the underlying mechanisms behind protein allostery and non-additivity of substitution outcomes (i.e., epistasis) is critical when attempting to predict the functional impact of mutations, particularly at non-conserved sites. In an effort to model these two biological properties, we extend the framework of our metric to calculate dynamic coupling between residues, the Dynamic Coupling Index (DCI) to two new metrics: (i) EpiScore, which quantifies the difference between the residue fluctuation response of a functional site when two other positions are perturbed with random Brownian kicks simultaneously versus individually to capture the degree of cooperativity of these two other positions in modulating the dynamics of the functional site and (ii) DCIasym, which measures the degree of asymmetry between the residue fluctuation response of two sites when one or the other is perturbed with a random force. Applied to four independent systems, we successfully show that EpiScore and DCIasym can capture important biophysical properties in dual mutant substitution outcomes. We propose that allosteric regulation and the mechanisms underlying non-additive amino acid substitution outcomes (i.e., epistasis) can be understood as emergent properties of an anisotropic network of interactions where the inclusion of the full network of interactions is critical for accurate modeling. Consequently, mutations which drive towards a new function may require a fine balance between functional site asymmetry and strength of dynamic coupling with the functional sites. These two tools will provide mechanistic insight into both understanding and predicting the outcome of dual mutations. 

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3. The Role of Conformational Dynamics and Allostery in Modulating Protein Evolution

   https://doi.org/10.1146/annurev-biophys-052118-115517  

   Campitelli, Paul; Modi, Tushar; Kumar, Sudhir; Ozkan, S. Banu (May 2020, Annual Review of Biophysics)

   Advances in sequencing techniques and statistical methods have made it possible not only to predict sequences of ancestral proteins but also to identify thousands of mutations in the human exome, some of which are disease associated. These developments have motivated numerous theories and raised many questions regarding the fundamental principles behind protein evolution, which have been traditionally investigated horizontally using the tip of the phylogenetic tree through comparative studies of extant proteins within a family. In this article, we review a vertical comparison of the modern and resurrected ancestral proteins. We focus mainly on the dynamical properties responsible for a protein's ability to adapt new functions in response to environmental changes. Using the Dynamic Flexibility Index and the Dynamic Coupling Index to quantify the relative flexibility and dynamic coupling at a site-specific, single-amino-acid level, we provide evidence that the migration of hinges, which are often functionally critical rigid sites, is a mechanism through which proteins can rapidly evolve. Additionally, we show that disease-associated mutations in proteins often result in flexibility changes even at positions distal from mutational sites, particularly in the modulation of active site dynamics. 

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4. Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations

   https://doi.org/10.7554/eLife.67474  

   Kazan, I Can; Sharma, Prerna; Rahman, Mohammad Imtiazur; Bobkov, Andrey; Fromme, Raimund; Ghirlanda, Giovanna; Ozkan, S Banu (December 2022, eLife)

   We develop integrated co-evolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 β-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function. 

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5. Energy landscape reshaped by strain-specific mutations underlies epistasis in NS1 evolution of influenza A virus

   https://doi.org/10.1038/s41467-022-33554-9  

   Kim, Iktae; Dubrow, Alyssa; Zuniga, Bryan; Zhao, Baoyu; Sherer, Noah; Bastiray, Abhishek; Li, Pingwei; Cho, Jae-Hyun (December 2022, Nature Communications)

   Abstract Elucidating how individual mutations affect the protein energy landscape is crucial for understanding how proteins evolve. However, predicting mutational effects remains challenging because of epistasis—the nonadditive interactions between mutations. Here, we investigate the biophysical mechanism of strain-specific epistasis in the nonstructural protein 1 (NS1) of influenza A viruses (IAVs). We integrate structural, kinetic, thermodynamic, and conformational dynamics analyses of four NS1s of influenza strains that emerged between 1918 and 2004. Although functionally near-neutral, strain-specific NS1 mutations exhibit long-range epistatic interactions with residues at the p85β-binding interface. We reveal that strain-specific mutations reshaped the NS1 energy landscape during evolution. Using NMR spin dynamics, we find that the strain-specific mutations altered the conformational dynamics of the hidden network of tightly packed residues, underlying the evolution of long-range epistasis. This work shows how near-neutral mutations silently alter the biophysical energy landscapes, resulting in diverse background effects during molecular evolution. 

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