Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III alpha Polymerase Activity

Revisiting the Roles of Catalytic Residues in Human Ornithine Transcarbamylase

Human ornithine transcarbamylase (hOTC) is a mitochondrial transferase protein involved in the urea cycle and is crucial for the conversion of toxic ammonia to urea. Structural analysis coupled with kinetic studies of Escherichia coli, rat, bovine, and other transferase proteins has identified residues that play key roles in substrate recognition and conformational changes but has not provided direct evidence for all of the active residues involved in OTC function. Here, computational methods were used to predict the likely active residues of hOTC; the function of these residues was then probed with site-directed mutagenesis and biochemical characterization. This process identified previously reported active residues, as well as distal residues that contribute to activity. Mutation of active site residue D263 resulted in a substantial loss of activity without a decrease in protein stability, suggesting a key catalytic role for this residue. Mutation of predicted second-layer residues H302, K307, and E310 resulted in significant decreases in enzymatic activity relative to that of wild-type (WT) hOTC with respect to l-ornithine. The mutation of fourth-layer residue H107 to produce the hOTC H107N variant resulted in a 66-fold decrease in catalytic efficiency relative to that of WT hOTC with respect to carbamoyl phosphate and a substantial loss of thermal stability. Further investigation identified H107 and to a lesser extent E98Q as key residues involved in maintaining the hOTC quaternary structure. This work biochemically demonstrates the importance of D263 in hOTC catalytic activity and shows that residues remote from the active site also play key roles in activity.

Escherichia coli DNA replication: the old model organism still holds many surprises

Research on Escherichia coli DNA replication paved the groundwork for many breakthrough discoveries with important implications for our understanding of human molecular biology, due to the high level of conservation of key molecular processes involved. To this day, it attracts a lot of attention, partially by virtue of being an important model organism, but also because the understanding of factors influencing replication fidelity might be important for studies on the emergence of antibiotic resistance. Importantly, the wide access to high-resolution single-molecule and live-cell imaging, whole genome sequencing, and cryo-electron microscopy techniques, which were greatly popularized in the last decade, allows us to revisit certain assumptions about the replisomes and offers very detailed insight into how they work. For many parts of the replisome, step-by-step mechanisms have been reconstituted, and some new players identified. This review summarizes the latest developments in the area, focusing on (a) the structure of the replisome and mechanisms of action of its components, (b) organization of replisome transactions and repair, (c) replisome dynamics, and (d) factors influencing the base and sugar fidelity of DNA synthesis.

Biochemical Activity of 17 Cancer-Associated Variants of DNA Polymerase Kappa Predicted by Electrostatic Properties

DNA damage and repair have been widely studied in relation to cancer and therapeutics. Y-family DNA polymerases can bypass DNA lesions, which may result from external or internal DNA damaging agents, including some chemotherapy agents. Overexpression of the Y-family polymerase human pol kappa can result in tumorigenesis and drug resistance in cancer. This report describes the use of computational tools to predict the effects of single nucleotide polymorphism variants on pol kappa activity. Partial Order Optimum Likelihood (POOL), a machine learning method that uses input features from Theoretical Microscopic Titration Curve Shapes (THEMATICS), was used to identify amino acid residues most likely involved in catalytic activity. The μ4 value, a metric obtained from POOL and THEMATICS that serves as a measure of the degree of coupling between one ionizable amino acid and its neighbors, was then used to identify which protein mutations are likely to impact the biochemical activity. Bioinformatic tools SIFT, PolyPhen-2, and FATHMM predicted most of these variants to be deleterious to function. Along with computational and bioinformatic predictions, we characterized the catalytic activity and stability of 17 cancer-associated DNA pol kappa variants. We identified pol kappa variants R48I, H105Y, G147D, G154E, V177L, R298C, E362V, and R470C as having lower activity relative to wild-type pol kappa; the pol kappa variants T102A, H142Y, R175Q, E210K, Y221C, N330D, N338S, K353T, and L383F were identified as being similar in catalytic efficiency to WT pol kappa. We observed that POOL predictions can be used to predict which variants have decreased activity. Predictions from bioinformatic tools like SIFT, PolyPhen-2, and FATHMM are based on sequence comparisons and therefore are complementary to POOL but are less capable of predicting biochemical activity. These bioinformatic and computational tools can be used to identify SNP variants with deleterious effects and altered biochemical activity from a large data set.

Evaluation of the anti-infective potential of the seed endophytic fungi of Corchorus olitorius through metabolomics and molecular docking approach

BACKGROUND

Endophytic fungi are very rich sources of natural antibacterial and antifungal compounds. The main aim of this study is to isolate the fungal endophytes from the medicinal plant Corchorus olitorius seeds (F. Malvaceae), followed by antimicrobial screening against various bacterial and fungal strains.

RESULTS

Seven endophytic fungal strains belonging to different three genera were isolated, including Penicillium, Fusarium, and Aspergillus. The seven isolated endophytic strains revealed selective noticeable activity against Escherichia coli (ATCC25922) with varied IC50s ranging from 1.19 to 10 µg /mL, in which Aspergillus sp. (Ar 6) exhibited the strongest potency against E. coli (ATCC 25,922) and candida albicans (ATCC 10,231) with IC50s 1.19 and 15 µg /mL, respectively. Therefore, the chemical profiling of Aspergillus sp. (Ar 6) crude extract was performed using LC-HR-ESI-MS and led to the dereplication of sixteen compounds of various classes (1-16). In-silico analysis of the dereplicated metabolites led to highlighting the compounds responsible for the antimicrobial activity of Aspergillus sp. extract. Moreover, molecular docking showed the potential targets of the metabolites; Astellatol (5), Aspergillipeptide A (10), and Emericellamide C (14) against E. coli and C. albicans.

CONCLUSION

These results will expand the knowledge of endophytes and provide us with new approaches to face the global antibiotic resistance problem and the future production of undiscovered compounds different from the antibiotics classes.

MAHOMES II: A webserver for predicting if a metal binding site is enzymatic

Recent advances have enabled high-quality computationally generated structures for proteins with no solved crystal structures. However, protein function data remains largely limited to experimental methods and homology mapping. Since structure determines function, it is natural that methods capable of using computationally generated structures for functional annotations need to be advanced. Our laboratory recently developed a method to distinguish between metalloenzyme and nonenzyme sites. Here we report improvements to this method by upgrading our physicochemical features to alleviate the need for structures with sub-angstrom precision and using machine learning to reduce training data labeling error. Our improved classifier identifies protein bound metal sites as enzymatic or nonenzymatic with 94% precision and 92% recall. We demonstrate that both adjustments increased predictive performance and reliability on sites with sub-angstrom variations. We constructed a set of predicted metalloprotein structures with no solved crystal structures and no detectable homology to our training data. Our model had an accuracy of 90%-97.5% depending on the quality of the predicted structures included in our test. Finally, we found the physicochemical trends that drove this model's successful performance were local protein density, second shell ionizable residue burial, and the pocket's accessibility to the site. We anticipate that our model's ability to correctly identify catalytic metal sites could enable identification of new enzymatic mechanisms and improve de novo metalloenzyme design success rates.

MAHOMES II: A webserver for predicting if a metal binding site is enzymatic

Recent advances have enabled high-quality computationally generated structures for proteins with no solved crystal structures. However, protein function data remains largely limited to experimental methods and homology mapping. Since structure determines function, it is natural that methods capable of using computationally generated structures for functional annotations need to be advanced. Our laboratory recently developed a method to distinguish between metalloenzyme and non-enzyme sites. Here we report improvements to this method by upgrading our physicochemical features to alleviate the need for structures with sub-angstrom precision and using machine learning to reduce training data labeling error. Our improved classifier identifies protein bound metal sites as enzymatic or non-enzymatic with 94% precision and 92% recall. We demonstrate that both adjustments increased predictive performance and reliability on sites with sub-angstrom variations. We constructed a set of predicted metalloprotein structures with no solved crystal structures and no detectable homology to our training data. Our model had an accuracy of 90 - 97.5% depending on the quality of the predicted structures included in our test. Finally, we found the physicochemical trends that drove this model's successful performance were local protein density, second shell ionizable residue burial, and the pocket's accessibility to the site. We anticipate that our model's ability to correctly identify catalytic metal sites could enable identification of new enzymatic mechanisms and improve de novo metalloenzyme design success rates.

Significance statement

Identification of enzyme active sites on proteins with unsolved crystallographic structures can accelerate discovery of novel biochemical reactions, which can impact healthcare, industrial processes, and environmental remediation. Our lab has developed an ML tool for predicting sites on computationally generated protein structures as enzymatic and non-enzymatic. We have made our tool available on a webserver, allowing the scientific community to rapidly search previously unknown protein function space.

Role of distal sites in enzyme engineering

The limitations associated with natural enzyme catalysis have triggered the rise of the field of protein engineering. Traditional rational design was based on the analysis of protein structural information and catalytic mechanisms to identify key active sites or ligand binding sites to reshape the substrate pocket. The role and significance of functional sites in the active center have been studied extensively. With a deeper understanding of the structure-catalysis relationship map, the entire protein molecule can be filled with residues that play a substantial role in its structure and function. However, the catalytic mechanism underlying distal mutations remains unclear. The aim of this review was to highlight the criticality of the distal site in enzyme engineering based on the following three aspects: What can distal mutations exert on function from mutability landscape? How do distal sites influence enzyme function? How to predict and design distal mutations? This review provides insights into the catalytic mechanism of enzymes from the global interaction network, knowledge from sequence-structure-dynamics-function relationships, and strategies for distal mutation-based protein engineering.

Strand specificity of ribonucleotide excision repair in Escherichia coli

In Escherichia coli, replication of both strands of genomic DNA is carried out by a single replicase-DNA polymerase III holoenzyme (pol III HE). However, in certain genetic backgrounds, the low-fidelity TLS polymerase, DNA polymerase V (pol V) gains access to undamaged genomic DNA where it promotes elevated levels of spontaneous mutagenesis preferentially on the lagging strand. We employed active site mutants of pol III (pol IIIα_S759N) and pol V (pol V_Y11A) to analyze ribonucleotide incorporation and removal from the E. coli chromosome on a genome-wide scale under conditions of normal replication, as well as SOS induction. Using a variety of methods tuned to the specific properties of these polymerases (analysis of lacI mutational spectra, lacZ reversion assay, HydEn-seq, alkaline gel electrophoresis), we present evidence that repair of ribonucleotides from both DNA strands in E. coli is unequal. While RNase HII plays a primary role in leading-strand Ribonucleotide Excision Repair (RER), the lagging strand is subject to other repair systems (RNase HI and under conditions of SOS activation also Nucleotide Excision Repair). Importantly, we suggest that RNase HI activity can also influence the repair of single ribonucleotides incorporated by the replicase pol III HE into the lagging strand.

Novel Escherichia coli active site dnaE alleles with altered base and sugar selectivity

The Escherichia coli dnaE gene encodes the α‐catalytic subunit (pol IIIα) of DNA polymerase III, the cell’s main replicase. Like all high‐fidelity DNA polymerases, pol III possesses stringent base and sugar discrimination. The latter is mediated by a so‐called “steric gate” residue in the active site of the polymerase that physically clashes with the 2′‐OH of an incoming ribonucleotide. Our structural modeling data suggest that H760 is the steric gate residue in E.coli pol IIIα. To understand how H760 and the adjacent S759 residue help maintain genome stability, we generated DNA fragments in which the codons for H760 or S759 were systematically changed to the other nineteen naturally occurring amino acids and attempted to clone them into a plasmid expressing pol III core (α‐θ‐ε subunits). Of the possible 38 mutants, only nine were successfully sub‐cloned: three with substitutions at H760 and 6 with substitutions at S759. Three of the plasmid‐encoded alleles, S759C, S759N, and S759T, exhibited mild to moderate mutator activity and were moved onto the chromosome for further characterization. These studies revealed altered phenotypes regarding deoxyribonucleotide base selectivity and ribonucleotide discrimination. We believe that these are the first dnaE mutants with such phenotypes to be reported in the literature.

Amino acid interactions that facilitate enzyme catalysis

Interactions in enzymes between catalytic and neighboring amino acids and how these interactions facilitate catalysis are examined. In examples from both natural and designed enzymes, it is shown that increases in catalytic rates may be achieved through elongation of the buffer range of the catalytic residues; such perturbations in the protonation equilibria are, in turn, achieved through enhanced coupling of the protonation equilibria of the active ionizable residues with those of other ionizable residues. The strongest coupling between protonation states for a pair of residues that deprotonate to form an anion (or a pair that accept a proton to form a cation) is achieved when the difference in the intrinsic pK_as of the two residues is approximately within 1 pH unit. Thus, catalytic aspartates and glutamates are often coupled to nearby acidic residues. For an anion-forming residue coupled to a cation-forming residue, the elongated buffer range is achieved when the intrinsic pK_a of the anion-forming residue is higher than the intrinsic pK_a of the (conjugate acid of the) cation-forming residue. Therefore, the high pK_a, anion-forming residues tyrosine and cysteine make good coupling partners for catalytic lysine residues. For the anion-cation pairs, the optimum difference in intrinsic pK_as is a function of the energy of interaction between the residues. For the energy of interaction ε expressed in units of (ln 10)RT, the optimum difference in intrinsic pK_as is within ∼1 pH unit of ε.

Analysis of electrostatic coupling throughout the laboratory evolution of a designed retroaldolase

The roles of local interactions in the laboratory evolution of a highly active, computationally designed retroaldolase (RA) are examined. Partial Order Optimum Likelihood (POOL) is used to identify catalytically important amino acid interactions in several RA95 enzyme variants. The series RA95.5, RA95.5–5, RA95.5–8, and RA95.5–8F, representing progress along an evolutionary trajectory with increasing activity, is examined. Computed measures of coupling between charged states of residues show that, as evolution proceeds and higher activities are achieved, electrostatic coupling between the biochemically active amino acids and other residues is increased. In silico residue scanning suggests multiple coupling partners for the catalytic lysine K83. The effects of two predicted partners, Y51 and E85, are tested using site‐directed mutagenesis and kinetic analysis of the variants Y51F and E85Q. The Y51F variants show decreases in k_cat relative to wild type, with the greatest losses observed for the more evolved constructs; they also exhibit significant decreases in k_cat/K_M across the series. Only modest decreases in k_cat/K_M are observed for the E85Q variants with little effect on k_cat. Computed metrics of the degree of coupling between protonation states rise significantly as evolution proceeds and catalytic turnover rate increases. Specifically, the charge state of the catalytic lysine K83 becomes more strongly coupled to those of other amino acids as the enzyme evolves to a better catalyst.

Novel ribonucleotide discrimination in the RNA polymerase-like two-barrel catalytic core of Family D DNA polymerases

Family D DNA polymerase (PolD) is the essential replicative DNA polymerase for duplication of most archaeal genomes. PolD contains a unique two-barrel catalytic core absent from all other DNA polymerase families but found in RNA polymerases (RNAPs). While PolD has an ancestral RNA polymerase catalytic core, its active site has evolved the ability to discriminate against ribonucleotides. Until now, the mechanism evolved by PolD to prevent ribonucleotide incorporation was unknown. In all other DNA polymerase families, an active site steric gate residue prevents ribonucleotide incorporation. In this work, we identify two consensus active site acidic (a) and basic (b) motifs shared across the entire two-barrel nucleotide polymerase superfamily, and a nucleotide selectivity (s) motif specific to PolD versus RNAPs. A novel steric gate histidine residue (H931 in Thermococcus sp. 9°N PolD) in the PolD s-motif both prevents ribonucleotide incorporation and promotes efficient dNTP incorporation. Further, a PolD H931A steric gate mutant abolishes ribonucleotide discrimination and readily incorporates a variety of 2' modified nucleotides. Taken together, we construct the first putative nucleotide bound PolD active site model and provide structural and functional evidence for the emergence of DNA replication through the evolution of an ancestral RNAP two-barrel catalytic core.

Probing remote residues important for catalysis in Escherichia coli ornithine transcarbamoylase

Understanding how enzymes achieve their tremendous catalytic power is a major question in biochemistry. Greater understanding is also needed for enzyme engineering applications. In many cases, enzyme efficiency and specificity depend on residues not in direct contact with the substrate, termed remote residues. This work focuses on Escherichia coli ornithine transcarbamoylase (OTC), which plays a central role in amino acid metabolism. OTC has been reported to undergo an induced-fit conformational change upon binding its first substrate, carbamoyl phosphate (CP), and several residues important for activity have been identified. Using computational methods based on the computed chemical properties from theoretical titration curves, sequence-based scores derived from evolutionary history, and protein surface topology, residues important for catalytic activity were predicted. The roles of these residues in OTC activity were tested by constructing mutations at predicted positions, followed by steady-state kinetics assays and substrate binding studies with the variants. First-layer mutations R57A and D231A, second-layer mutation H272L, and third-layer mutation E299Q, result in 57- to 450-fold reductions in k_cat/K_M with respect to CP and 44- to 580-fold reductions with respect to ornithine. Second-layer mutations D140N and Y160S also reduce activity with respect to ornithine. Most variants had decreased stability relative to wild-type OTC, with variants H272L, H272N, and E299Q having the greatest decreases. Variants H272L, E299Q, and R57A also show compromised CP binding. In addition to direct effects on catalytic activity, effects on overall protein stability and substrate binding were observed that reveal the intricacies of how these residues contribute to catalysis.

Dynamics of the E. coli β-Clamp Dimer Interface and Its Influence on DNA Loading

The ring-shaped sliding clamp proteins have crucial roles in the regulation of DNA replication, recombination, and repair in all organisms. We previously showed that the Escherichia coli β-clamp is dynamic in solution, transiently visiting conformational states in which Domain 1 at the dimer interface is more flexible and prone to unfolding. This work aims to understand how the stability of the dimer interface influences clamp-opening dynamics and clamp loading by designing and characterizing stabilizing and destabilizing mutations in the clamp. The variants with stabilizing mutations conferred similar or increased thermostability and had similar quaternary structure as compared to the wild type. These variants stimulated the ATPase function of the clamp loader, complemented cell growth of a temperature-sensitive strain, and were successfully loaded onto a DNA substrate. The L82D and L82E I272A variants with purported destabilizing mutations had decreased thermostability, did not complement the growth of a temperature-sensitive strain, and had weakened dimerization as determined by native trapped ion mobility spectrometry-mass spectrometry. The β L82E variant had a reduced melting temperature but dimerized and complemented growth of a temperature-sensitive strain. All three clamps with destabilizing mutations had perturbed loading on DNA. Molecular dynamics simulations indicate altered hydrogen-bonding patterns at the dimer interface, and cross-correlation analysis showed the largest perturbations in the destabilized variants, consistent with the observed change in the conformations and functions of these clamps.

Tri-arginine exosite patch of caspase-6 recruits substrates for hydrolysis

Caspases are cysteine-aspartic proteases involved in the regulation of programmed cell death (apoptosis) and a number of other biological processes. Despite overall similarities in structure and active-site composition, caspases show striking selectivity for particular protein substrates. Exosites are emerging as one of the mechanisms by which caspases can recruit, engage, and orient these substrates for proper hydrolysis. Following computational analyses and database searches for candidate exosites, we utilized site-directed mutagenesis to identify a new exosite in caspase-6 at the hinge between the disordered N-terminal domain (NTD), residues 23-45, and core of the caspase-6 structure. We observed that substitutions of the tri-arginine patch Arg-42-Arg-44 or the R44K cancer-associated mutation in caspase-6 markedly alter its rates of protein substrate hydrolysis. Notably, turnover of protein substrates but not of short peptide substrates was affected by these exosite alterations, underscoring the importance of this region for protein substrate recruitment. Hydrogen-deuterium exchange MS-mediated interrogation of the intrinsic dynamics of these enzymes suggested the presence of a substrate-binding platform encompassed by the NTD and the 240's region (containing residues 236-246), which serves as a general exosite for caspase-6-specific substrate recruitment. In summary, we have identified an exosite on caspase-6 that is critical for protein substrate recognition and turnover and therefore highly relevant for diseases such as cancer in which caspase-6-mediated apoptosis is often disrupted, and in neurodegeneration in which caspase-6 plays a central role.