De novo protein design by deep network hallucination.

There has been considerable recent progress in protein structure prediction using deep neural networks to predict inter-residue distances from amino acid sequences1-3. Here we investigate whether the information captured by such networks is sufficiently rich to generate new folded proteins with sequences unrelated to those of the naturally occurring proteins used in training the models. We generate random amino acid sequences, and input them into the trRosetta structure prediction network to predict starting residue-residue distance maps, which, as expected, are quite featureless. We then carry out Monte Carlo sampling in amino acid sequence space, optimizing the contrast (Kullback-Leibler divergence) between the inter-residue distance distributions predicted by the network and background distributions averaged over all proteins. Optimization from different random starting points resulted in novel proteins spanning a wide range of sequences and predicted structures. We obtained synthetic genes encoding 129 of the network-'hallucinated' sequences, and expressed and purified the proteins in Escherichia coli; 27 of the proteins yielded monodisperse species with circular dichroism spectra consistent with the hallucinated structures. We determined the three-dimensional structures of three of the hallucinated proteins, two by X-ray crystallography and one by NMR, and these closely matched the hallucinated models. Thus, deep networks trained to predict native protein structures from their sequences can be inverted to design new proteins, and such networks and methods should contribute alongside traditional physics-based models to the de novo design of proteins with new functions.

Insights into Structural and Dynamical Changes Experienced by Human RNase 6 upon Ligand Binding.

Ribonuclease 6 (RNase 6) is one of eight catalytically active human pancreatic-type RNases that belong to a superfamily of rapidly evolving enzymes. Like some of its human homologues, RNase 6 exhibits host defense properties such as antiviral and antibacterial activities. Recently solved crystal structures of this enzyme in its nucleotide-free form show the conservation of the prototypical kidney-shaped fold preserved among vertebrate RNases, in addition to revealing the presence of a unique secondary active site. In this study, we determine the structural and conformational properties experienced by RNase 6 upon binding to substrate and product analogues. We present the first crystal structures of RNase 6 bound to a nucleotide ligand (adenosine 5'-monophosphate), in addition to RNase 6 bound to phosphate ions. While the enzyme preserves B2 subsite ligand preferences, our results show a lack of typical B2 subsite interactions normally observed in homologous ligand-bound RNases. A comparison of the dynamical properties of RNase 6 in its apo-, substrate-, and product-bound states highlight the unique dynamical properties experienced on time scales ranging from nano- to milliseconds. Overall, our results confirm the specific evolutionary adaptation of RNase 6 relative to its unique catalytic and biological activities.

Differential Substrate Recognition by Maltose Binding Proteins Influenced by Structure and Dynamics.

The genome of the hyperthermophile Thermotoga maritima contains three isoforms of maltose binding protein (MBP) that are high-affinity receptors for di-, tri-, and tetrasaccharides. Two of these proteins (tmMBP1 and tmMBP2) share significant sequence identity, approximately 90%, while the third (tmMBP3) shares less than 40% identity. MBP from Escherichia coli (ecMBP) shares 35% sequence identity with the tmMBPs. This subset of MBP isoforms offers an interesting opportunity to investigate the mechanisms underlying the evolution of substrate specificity and affinity profiles in a genome where redundant MBP genes are present. In this study, the X-ray crystal structures of tmMBP1, tmMBP2, and tmMBP3 are reported in the absence and presence of oligosaccharides. tmMBP1 and tmMBP2 have binding pockets that are larger than that of tmMBP3, enabling them to bind to larger substrates, while tmMBP1 and tmMBP2 also undergo substrate-induced hinge bending motions (∼52°) that are larger than that of tmMBP3 (∼35°). Small-angle X-ray scattering was used to compare protein behavior in solution, and computer simulations provided insights into dynamics of these proteins. Comparing quantitative protein-substrate interactions and dynamical properties of tmMBPs with those of the promiscuous ecMBP and disaccharide selective Thermococcus litoralis MBP provides insights into the features that enable selective binding. Collectively, the results provide insights into how the structure and dynamics of tmMBP homologues enable them to differentiate between a myriad of chemical entities while maintaining their common fold.

Small Angle Neutron Scattering Studies of R67 Dihydrofolate Reductase, a Tetrameric Protein with Intrinsically Disordered N-Termini.

R67 dihydrofolate reductase (DHFR) is a homotetramer with a single active site pore and no sequence or structural homology with chromosomal DHFRs. The R67 enzyme provides resistance to trimethoprim, an active site-directed inhibitor of Escherichia coli DHFR. Sixteen to twenty N-terminal amino acids are intrinsically disordered in the R67 dimer crystal structure. Chymotrypsin cleavage of 16 N-terminal residues results in an active enzyme with a decreased stability. The space sampled by the disordered N-termini of R67 DHFR was investigated using small angle neutron scattering. From a combined analysis using molecular dynamics and the program SASSIE ( http://www.smallangles.net/sassie/SASSIE_HOME.html ), the apoenzyme displays a radius of gyration (Rg) of 21.46 ± 0.50 Å. Addition of glycine betaine, an osmolyte, does not result in folding of the termini as the Rg increases slightly to 22.78 ± 0.87 Å. SASSIE fits of the latter SANS data indicate that the disordered N-termini sample larger regions of space and remain disordered, suggesting they might function as entropic bristles. Pressure perturbation calorimetry also indicated that the volume of R67 DHFR increases upon addition of 10% betaine and decreased at 20% betaine because of the dehydration of the protein. Studies of the hydration of full-length R67 DHFR in the presence of the osmolytes betaine and dimethyl sulfoxide find around 1250 water molecules hydrating the protein. Similar studies with truncated R67 DHFR yield around 400 water molecules hydrating the protein in the presence of betaine. The difference of ∼900 waters indicates the N-termini are well-hydrated.

Applications of NMR and computational methodologies to study protein dynamics.

Overwhelming evidence now illustrates the defining role of atomic-scale protein flexibility in biological events such as allostery, cell signaling, and enzyme catalysis. Over the years, spin relaxation nuclear magnetic resonance (NMR) has provided significant insights on the structural motions occurring on multiple time frames over the course of a protein life span. The present review article aims to illustrate to the broader community how this technique continues to shape many areas of protein science and engineering, in addition to being an indispensable tool for studying atomic-scale motions and functional characterization. Continuing developments in underlying NMR technology alongside software and hardware developments for complementary computational approaches now enable methodologies to routinely provide spatial directionality and structural representations traditionally harder to achieve solely using NMR spectroscopy. In addition to its well-established role in structural elucidation, we present recent examples that illustrate the combined power of selective isotope labeling, relaxation dispersion experiments, chemical shift analyses, and computational approaches for the characterization of conformational sub-states in proteins and enzymes.

Aspects of Weak Interactions between Folate and Glycine Betaine.

Folate, or vitamin B9, is an important compound in one-carbon metabolism. Previous studies have found weaker binding of dihydrofolate to dihydrofolate reductase in the presence of osmolytes. In other words, osmolytes are more difficult to remove from the dihydrofolate solvation shell than water; this shifts the equilibrium toward the free ligand and protein species. This study uses vapor-pressure osmometry to explore the interaction of folate with the model osmolyte, glycine betaine. This method yields a preferential interaction potential (µ23/RT value). This value is concentration-dependent as folate dimerizes. The µ23/RT value also tracks the deprotonation of folate's N3-O4 keto-enol group, yielding a pKa of 8.1. To determine which folate atoms interact most strongly with betaine, the interaction of heterocyclic aromatic compounds (as well as other small molecules) with betaine was monitored. Using an accessible surface area approach coupled with osmometry measurements, deconvolution of the µ23/RT values into α values for atom types was achieved. This allows prediction of µ23/RT values for larger molecules such as folate. Molecular dynamics simulations of folate show a variety of structures from extended to L-shaped. These conformers possess µ23/RT values from -0.18 to 0.09 m-1, where a negative value indicates a preference for solvation by betaine and a positive value indicates a preference for water. This range of values is consistent with values observed in osmometry and solubility experiments. As the average predicted folate µ23/RT value is near zero, this indicates folate interacts almost equally well with betaine and water. Specifically, the glutamate tail prefers to interact with water, while the aromatic rings prefer betaine. In general, the more protonated species in our small molecule survey interact better with betaine as they provide a source of hydrogens (betaine is not a hydrogen bond donor). Upon deprotonation of the small molecule, the preference swings toward water interaction because of its hydrogen bond donating capacities.

Protocol for production and purification of SARS-CoV-2 3CLpro.

3CLpro protease from SARS-CoV-2 is a primary target for COVID-19 antiviral drug development. Here, we present a protocol for 3CLpro production in Escherichia coli. We describe steps to purify 3CLpro, expressed as a fusion with the Saccharomyces cerevisiae SUMO protein, with yields up to 120 mg L-1 following cleavage. The protocol also provides isotope-enriched samples suitable for nuclear magnetic resonance (NMR) studies. We also present methods to characterize 3CLpro by mass spectrometry, X-ray crystallography, heteronuclear NMR, and a Förster-resonance-energy-transfer-based enzyme assay. For complete details on the use and execution of this protocol, please refer to Bafna et al.1.

Conformational exchange divergence along the evolutionary pathway of eosinophil-associated ribonucleases.

The evolutionary role of conformational exchange in the emergence and preservation of function within structural homologs remains elusive. While protein engineering has revealed the importance of flexibility in function, productive modulation of atomic-scale dynamics has only been achieved on a finite number of distinct folds. Allosteric control of unique members within dynamically diverse structural families requires a better appreciation of exchange phenomena. Here, we examined the functional and structural role of conformational exchange within eosinophil-associated ribonucleases. Biological and catalytic activity of various EARs was performed in parallel to mapping their conformational behavior on multiple timescales using NMR and computational analyses. Despite functional conservation and conformational seclusion to a specific domain, we show that EARs can display similar or distinct motional profiles, implying divergence rather than conservation of flexibility. Comparing progressively more distant enzymes should unravel how this subfamily has evolved new functions and/or altered their behavior at the molecular level.

Structural similarities between SARS-CoV2 3CLpro and other viral proteases suggest potential lead molecules for developing broad spectrum antivirals.

Considering the significant impact of the recent COVID-19 outbreak, development of broad-spectrum antivirals is a high priority goal to prevent future global pandemics. Antiviral development processes generally emphasize targeting a specific protein from a particular virus. However, some antiviral agents developed for specific viral protein targets may exhibit broad spectrum antiviral activity, or at least provide useful lead molecules for broad spectrum drug development. There is significant potential for repurposing a wide range of existing viral protease inhibitors to inhibit the SARS-CoV2 3C-like protease (3CLpro). If effective even as relatively weak inhibitors of 3CLpro, these molecules can provide a diverse and novel set of scaffolds for new drug discovery campaigns. In this study, we compared the sequence- and structure-based similarity of SARS-CoV2 3CLpro with proteases from other viruses, and identified 22 proteases with similar active-site structures. This structural similarity, characterized by secondary-structure topology diagrams, is evolutionarily divergent within taxonomically related viruses, but appears to result from evolutionary convergence of protease enzymes between virus families. Inhibitors of these proteases that are structurally similar to the SARS-CoV2 3CLpro protease were identified and assessed as potential inhibitors of SARS-CoV2 3CLpro protease by virtual docking. Several of these molecules have docking scores that are significantly better than known SARS-CoV2 3CLpro inhibitors, suggesting that these molecules are also potential inhibitors of the SARS-CoV2 3CLpro protease. Some have been previously reported to inhibit SARS-CoV2 3CLpro. The results also suggest that established inhibitors of SARS-CoV2 3CLpro may be considered as potential inhibitors of other viral 3C-like proteases.

Hepatitis C virus drugs that inhibit SARS-CoV-2 papain-like protease synergize with remdesivir to suppress viral replication in cell culture.

Effective control of COVID-19 requires antivirals directed against SARS-CoV-2. We assessed 10 hepatitis C virus (HCV) protease-inhibitor drugs as potential SARS-CoV-2 antivirals. There is a striking structural similarity of the substrate binding clefts of SARS-CoV-2 main protease (Mpro) and HCV NS3/4A protease. Virtual docking experiments show that these HCV drugs can potentially bind into the Mpro substrate-binding cleft. We show that seven HCV drugs inhibit both SARS-CoV-2 Mpro protease activity and SARS-CoV-2 virus replication in Vero and/or human cells. However, their Mpro inhibiting activities did not correlate with their antiviral activities. This conundrum is resolved by demonstrating that four HCV protease inhibitor drugs, simeprevir, vaniprevir, paritaprevir, and grazoprevir inhibit the SARS CoV-2 papain-like protease (PLpro). HCV drugs that inhibit PLpro synergize with the viral polymerase inhibitor remdesivir to inhibit virus replication, increasing remdesivir's antiviral activity as much as 10-fold, while those that only inhibit Mpro do not synergize with remdesivir.

Structural Similarity of SARS-CoV2 Mpro and HCV NS3/4A Proteases Suggests New Approaches for Identifying Existing Drugs Useful as COVID-19 Therapeutics.

During the current COVID-19 pandemic more than 160,000 people have died worldwide as of mid-April 2020, and the global economy has been crippled. Effective control of the SARS-CoV2 virus that causes the COVID-19 pandemic requires both vaccines and antivirals. Antivirals are particularly crucial to treat infected people during the period of time that an effective vaccine is being developed and deployed. Because the development of specific antiviral drugs can take a considerable length of time, an important approach is to identify existing drugs already approved for use in humans which could be repurposed as COVID-19 therapeutics. Here we focus on antivirals directed against the SARS-CoV2 Mpro protease, which is required for virus replication. A structural similarity search showed that the Hepatitis C virus (HCV) NS3/4A protease has a striking three-dimensional structural similarity to the SARS-CoV2 Mpro protease, particularly in the arrangement of key active site residues. We used virtual docking predictions to assess the hypothesis that existing drugs already approved for human use or clinical testing that are directed at the HCV NS3/4A protease might fit well into the active-site cleft of the SARS-CoV2 protease (Mpro). AutoDock docking scores for 12 HCV protease inhibitors and 9 HIV-1 protease inhibitors were determined and compared to the docking scores for an α-ketoamide inhibitor of Mpro, which has recently been shown to inhibit SARS-CoV2 virus replication in cell culture. We identified eight HCV protease inhibitors that bound to the Mpro active site with higher docking scores than the α-ketoamide inhibitor, suggesting that these protease inhibitors may effectively bind to the Mpro active site. These results provide the rationale for us to test the identified HCV protease inhibitors as inhibitors of the SARS-CoV2 protease, and as inhibitors of SARS-CoV2 virus replication. Subsequently these repurposed drugs could be evaluated as COVID-19 therapeutics.

Enzyme dynamics: Looking beyond a single structure.

Conventional understanding of how enzymes function strongly emphasizes the role of structure. However, increasing evidence clearly indicates that enzymes do not remain fixed or operate exclusively in or close to their native structure. Different parts of the enzyme (from individual residues to full domains) undergo concerted motions on a wide range of time-scales, including that of the catalyzed reaction. Information obtained on these internal motions and conformational fluctuations has so far uncovered and explained many aspects of enzyme mechanisms, which could not have been understood from a single structure alone. Although there is wide interest in understanding enzyme dynamics and its role in catalysis, several challenges remain. In addition to technical difficulties, the vast majority of investigations are performed in dilute aqueous solutions, where conditions are significantly different than the cellular milieu where a large number of enzymes operate. In this review, we discuss recent developments, several challenges as well as opportunities related to this topic. The benefits of considering dynamics as an integral part of the enzyme function can also enable new means of biocatalysis, engineering enzymes for industrial and medicinal applications.

Nucleotide substrate binding characterization in human pancreatic-type ribonucleases.

Human genome contains a group of more than a dozen similar genes with diverse biological functions including antiviral, antibacterial and angiogenesis activities. The characterized gene products of this group show significant sequence similarity and a common structural fold associated with binding and cleavage of ribonucleic acid (RNA) substrates. Therefore, these proteins have been categorized as members of human pancreatic-type ribonucleases (hRNases). hRNases differ in cell/tissue localization and display distinct substrate binding preferences and a wide range of ribonucleolytic catalytic efficiencies. Limited information is available about structural and dynamical properties that influence this diversity among these homologous RNases. Here, we use computer simulations to characterize substrate interactions, electrostatics and dynamical properties of hRNases 1-7 associated with binding to two nucleotide substrates (ACAC and AUAU). Results indicate that even with complete conservation of active-site catalytic triad associated with ribonucleolytic activity, these enzymes show significant differences in substrate interactions. Detailed characterization suggests that in addition to binding site electrostatic and van der Waals interactions, dynamics of distal regions may also play a role in binding. Another key insight is that a small difference in temperature of 300 K (used in experimental studies) and 310 K (physiological temperature) shows significant changes in enzyme-substrate interactions.

Ligand-Induced Variations in Structural and Dynamical Properties Within an Enzyme Superfamily.

Enzyme catalysis is a complex process involving several steps along the reaction coordinates, including substrate recognition and binding, chemical transformation, and product release. Evidence continues to emerge linking the functional and evolutionary role of conformational exchange processes in optimal catalytic activity. Ligand binding changes the conformational landscape of enzymes, inducing long-range conformational rearrangements. Using functionally distinct members of the pancreatic ribonuclease superfamily as a model system, we characterized the structural and conformational changes associated with the binding of two mononucleotide ligands. By combining NMR chemical shift titration experiments with the chemical shift projection analysis (CHESPA) and relaxation dispersion experiments, we show that biologically distinct members of the RNase superfamily display discrete chemical shift perturbations upon ligand binding that are not conserved even in structurally related members. Amino acid networks exhibiting coordinated chemical shift displacements upon binding of the two ligands are unique to each of the RNases analyzed. Our results reveal the contribution of conformational rearrangements to the observed chemical shift perturbations. These observations provide important insights into the contribution of the different ligand binding specificities and effects of conformational exchange on the observed perturbations associated with ligand binding for functionally diverse members of the pancreatic RNase superfamily.

Conservation of Dynamics Associated with Biological Function in an Enzyme Superfamily.

Enzyme superfamily members that share common chemical and/or biological functions also share common features. While the role of structure is well characterized, the link between enzyme function and dynamics is not well understood. We present a systematic characterization of intrinsic dynamics of over 20 members of the pancreatic-type RNase superfamily, which share a common structural fold. This study is motivated by the fact that the range of chemical activity as well as molecular motions of RNase homologs spans over 105 folds. Dynamics was characterized using a combination of nuclear magnetic resonance experiments and computer simulations. Phylogenetic clustering led to the grouping of sequences into functionally distinct subfamilies. Detailed characterization of the diverse RNases showed conserved dynamical traits for enzymes within subfamilies. These results suggest that selective pressure for the conservation of dynamical behavior, among other factors, may be linked to the distinct chemical and biological functions in an enzyme superfamily.

Correction to: Sequence-specific backbone resonance assignments and microsecond timescale molecular dynamics simulation of human eosinophil-derived neurotoxin.

After publication of this article, the authors noticed that a 15N-13C dimension error was unwillingly coded in the 3D NMR spectrum "fid.com" processing script used to perform backbone assignments for this enzyme. The authors noticed that some OBS, CAR and LAB values in the "fid.com" had been switched in the y and z dimensions, probably resulting from a wrong NMRPipe selection when reading the Varian NMR experimental parameters. They have carefully re-processed, re-analyzed, re-assigned, in addition to checking all scripts to evaluate the extent of this processing error on the published assignments. Authors determined that the "fid.com" error resulted in a significant number of incorrect backbone resonance assignments, requiring us to issue corrections in Figs. 2, 3 and 4 of this published manuscript, in addition to Table S1. New versions of these figures and table are provided below. The corresponding BMRB entry has also been revised. The authors note that these modifications do not change the global message, conclusions, and molecular dynamics simulations presented in this article. The authors are grateful to David N. Bernard (INRS) for help with finding and correcting these errors.

Sequence-specific backbone resonance assignments and microsecond timescale molecular dynamics simulation of human eosinophil-derived neurotoxin.

Eight active canonical members of the pancreatic-like ribonuclease A (RNase A) superfamily have been identified in human. All structural homologs share similar RNA-degrading functions, while also cumulating other various biological activities in different tissues. The functional homologs eosinophil-derived neurotoxin (EDN, or RNase 2) and eosinophil cationic protein (ECP, or RNase 3) are known to be expressed and secreted by eosinophils in response to infection, and have thus been postulated to play an important role in host defense and inflammatory response. We recently initiated the biophysical and dynamical investigation of several vertebrate RNase homologs and observed that clustering residue dynamics appear to be linked with the phylogeny and biological specificity of several members. Here we report the 1H, 13C and 15N backbone resonance assignments of human EDN (RNase 2) and its molecular dynamics simulation on the microsecond timescale, providing means to pursue this comparative atomic-scale functional and dynamical analysis by NMR and computation over multiple time frames.

Computational Structure-Based De Novo Design of Hypothetical Inhibitors against the Anti- Inflammatory Target COX-2.

Cyclooxygenase-2 (COX-2) produces prostaglandins in inflamed tissues and hence has been considered as an important target for the development of anti-inflammatory drugs since long. Administration of traditional non-steroidal anti-inflammatory drugs (NSAIDs) and other COX-2 selective inhibitors (COXIBS) for the treat of inflammation has been found to be associated with side effects, which mainly includes gastro-intestinal (GI) toxicity. The present study involves developing a virtual library of novel molecules with high druglikeliness using structure-based de novo drug designing and 2D fingerprinting approach. A library of 2657 drug like molecules was generated. 2D fingerprinting based screening of the designed library gave a unique set of compounds. Molecular docking approach was then used to identify two compounds highly specific for COX-2 isoform. Molecular dynamics simulations of protein-ligand complexes revealed that the candidate ligands were dynamically stable within the cyclooxygenase binding site of COX-2. The ligands were further analyzed for their druglikeliness, ADMET properties and synthetic accessibility using knowledge based set of rules. The results revealed that the molecules are predicted to selectively bind to COX-2 enzyme thereby potentially overcoming the limitations posed by the drugs in clinical use.

The bitter barricading of prostaglandin biosynthesis pathway: understanding the molecular mechanism of selective cyclooxygenase-2 inhibition by amarogentin, a secoiridoid glycoside from Swertia chirayita.

Swertia chirayita, a medicinal herb inhabiting the challenging terrains and high altitudes of the Himalayas, is a rich source of essential phytochemical isolates. Amarogentin, a bitter secoiridoid glycoside from S. chirayita, shows varied activity in several patho-physiological conditions, predominantly in leishmaniasis and carcinogenesis. Experimental analysis has revealed that amarogentin downregulates the cyclooxygenase-2 (COX-2) activity and helps to curtail skin carcinogenesis in mouse models; however, there exists no account on selective inhibition of the inducible cyclooxygenase (COX) isoform by amarogentin. Hence the computer-aided drug discovery methods were used to unravel the COX-2 inhibitory mechanism of amarogentin and to check its selectivity for the inducible isoform over the constitutive one. The generated theoretical models of both isoforms were subjected to molecular docking analysis with amarogentin and twenty-one other Food and Drug Authority (FDA) approved lead molecules. The post-docking binding energy profile of amarogentin was comparable to the binding energy profiles of the FDA approved selective COX-2 inhibitors. Subsequent molecular dynamics simulation analysis delineated the difference in the stability of both complexes, with amarogentin-COX-2 complex being more stable after 40ns simulation. The total binding free energy calculated by MMGBSA for the amarogentin-COX-2 complex was -52.35 KCal/mol against a binding free energy of -8.57 KCal/mol for amarogentin-COX-1 complex, suggesting a possible selective inhibition of the COX-2 protein by the natural inhibitor. Amarogentin achieves this potential selectivity by small, yet significant, structural differences inherent to the binding cavities of the two isoforms. Hypothetically, it might block the entry of the natural substrates in the hydrophobic binding channel of the COX-2, inhibiting the cyclooxygenation step. To sum up briefly, this work highlights the mechanism of the possible selective COX-2 inhibition by amarogentin and endorses the possibility of obtaining efficient, futuristic and targeted therapeutic agents for relieving inflammation and malignancy from this phytochemical source.