A phenoxy-bridged trinuclear Ni(ii) complex: synthesis, structural elucidation and molecular docking with viral proteins

A novel phenoxy-bridged trinuclear nickel(ii) complex [Ni3(mu-L)2(bipy)3](1) (where H3L= (E)-2-hydroxy-N-(2-hydroxy-3,5-diiodophenyl)-3,5-diiodobenzohydrazonic acid, bipy = 2,2'-bipyridyl) has been designed and synthesized as a potential antivirus drug candidate. The trinuclear Ni(ii) complex [Ni3(mu-L)2(bipy)3](1) was fully characterized via single crystal X-ray crystallography. The unique structure of the trinuclear nickel(ii) complex crystallized in a trigonal crystal system with P3221 space group and revealed distorted octahedral coordination geometry around each Ni(ii) ion. The X-ray diffraction analysis established the existence of a new kind of trinuclear metal system containing nickel(ii)-nickel(ii) interactions with an overall octahedral-like geometry about the nickel(ii) atoms. The non-bonded Ni-Ni distance seems to be 3.067 and 4.455 A from the nearest nickel atoms. The detailed structural analysis and non-covalent supramolecular interactions are also investigated by single crystal structure analysis and computational approaches. Hirshfeld surfaces (HSs) and 2D fingerprint plots (FPs) have been explored in the crystal structure to investigate the intermolecular interactions. The preliminary analysis of redox and magnetic characterization was conducted using cyclic voltammetry measurements and a vibrating sample magnetometer (VSM), respectively. This unique structure shows good inhibition performance for SARS-CoV-2, Omicron and HIV viruses. For insight into the potential application of the Ni(ii) coordination complex as an effective antivirus drug, we have examined the molecular docking of the trinuclear Ni(ii) complex [Ni3(mu-L)2(bipy)3](1) with the receptor binding domain (RBD) from SARS-CoV-2 (PDB ID: 7MZF), Omicron BA.3 variant spike (PDB ID: 7XIZ), and HIV protease (PDB ID: 7WCQ) viruses. This structure shows good inhibition performance for SARS-CoV-2, Omicron S protein and HIV protease viruses;the binding energies (DELTAG) and the respective Ki/Kd (inhibition/dissociation constants) correlation values are -8.9 (2.373 muM or 2373 nM), -8.1 (1.218 muM or 1218 nM) and -7.9 (0.874 muM or 874 nM), respectively. The results could be used for rational drug design against SARS-CoV-2 Omicron variant and HIV protease viruses.Copyright © 2023 The Royal Society of Chemistry.

Copper(II) Schiff base complex derived from salen ligand: structural investigation, Hirshfeld surface analysis, anticancer and anti-SARS-CoV-2.

This work deals with the synthesis and characterization of copper(II) complex [Cu(salen)(H2O)](1) of salen-type Schiff base ligand derived from the condensation of 5-bromo-2-hydroxy-3-methoxybenzaldehyde and ethylenediamine in EtOH. This complex was characterized by different spectroscopic and physicochemical methods. Single crystal X-ray crystallography study revealed that Cu(II) in complex (1) is five-coordinate and adopts a distorted square pyramidal geometry. A DFT calculation was employed to evaluate the optimized electronic structure, HOMO-LUMO, energy gap, and global parameters. A detailed structural and non-covalent interaction on the complex is investigated by single crystal structure analysis and computational approaches. The strength of the interaction and 3D topology of the crystal packing are visualized through an energy framework. Hirshfeld surface and 2D fingerprint plots have been explored in the crystal structure of the complex. The anticancer properties of copper(II) complex was studied against the selected cancerous cell lines of breast cancer, cervical cancer, colon cancer and hepatocellular carcinoma. Additionally, molecular docking and MD simulations was performed on the complex to predict the binding mode and interactions between the ligand and the main protease of the SARS-CoV-2 (PDB ID: 7CBT and 7D1M). The molecular docking calculations of the complex (1) with SARS-CoV-2 virus revealed the binding energy of -8.1 kcal/mol and -7.5 kcal/mol with an inhibition constant of 3.245 µM and 2.318 µM at inhibition binding site of receptor towards 7CBT and 7D1M main protease (Mpro), respectively. Besides this, molecular docking results (-7.6 kcal/mol, 3.196 µM) towards Escherichia coli PBP2 targets (PDB ID: 6G9S) was also studied. Communicated by Ramaswamy H. Sarma.

Contribution of the catalytic dyad of SARS-CoV-2 main protease to binding covalent and noncovalent inhibitors.

The effect of mutations of the catalytic dyad residues of SARS-CoV-2 main protease (MProWT) on the thermodynamics of binding of covalent inhibitors comprising nitrile [nirmatrelvir (NMV), NBH2], aldehyde (GC373), and ketone (BBH1) warheads to MPro is examined together with room temperature X-ray crystallography. When lacking the nucleophilic C145, NMV binding is ∼400-fold weaker corresponding to 3.5 kcal/mol and 13.3 °C decrease in free energy (ΔG) and thermal stability (Tm), respectively, relative to MProWT. The H41A mutation results in a 20-fold increase in the dissociation constant (Kd), and 1.7 kcal/mol and 1.4 °C decreases in ΔG and Tm, respectively. Increasing the pH from 7.2 to 8.2 enhances NMV binding to MProH41A, whereas no significant change is observed in binding to MProWT. Structures of the four inhibitor complexes with MPro1-304/C145A show that the active site geometries of the complexes are nearly identical to that of MProWT with the nucleophilic sulfur of C145 positioned to react with the nitrile or the carbonyl carbon. These results support a two-step mechanism for the formation of the covalent complex involving an initial non-covalent binding followed by a nucleophilic attack by the thiolate anion of C145 on the warhead carbon. Noncovalent inhibitor ensitrelvir (ESV) exhibits a binding affinity to MProWT that is similar to NMV but differs in its thermodynamic signature from NMV. The binding of ESV to MProC145A also results in a significant, but smaller, increase in Kd and decrease in ΔG and Tm, relative to NMV.

Ultrasound assisted regioselective synthesis of novel adamantyl-pyrazolo[1,5-a]pyrimidines in aqueous media and molecular docking and drug likeness studies

Multi-step synthesis of adamantyl-pyrazolo[1,5-a]pyrimidine derivatives under ultrasound irradiation has been described adopting the technique of molecular hybridization, whereby two core bioactive units- adamantanamine and pyrazolo[1,5-a]pyrimidine templates have been brought together into a new chemical entity. Ultrasound irradiation of N-(adamantan-1-yl)-3-amino-1H-pyrazole-4-carboxamide with formylated active proton compounds yields the desired hybrids in good to excellent yields. The N-(adamantan-1-yl)-3-amino pyrazolo[1,5-a]pyrimidine carboxamide derivatives were successfully identified with the help of spectral and analytical data. X-ray crystallography of ethyl 3-(adamantan-1-ylcarbamoyl)-7-methylpyrazolo[1,5-a]pyrimidine-6-carboxylate (14c) unambiguously confirmed the formation of the desired hybrid. The results and the findings of the docking scores indicate that the active ligands 7a and 11b exhibited highest binding energies with a score of –7.33 Kcal/mol and – 8.73 Kcal/mol, respectively. The inhibition constant (KI) for ligands 7a and 11b were found to be 4.24 µM and 396.32 µM, respectively which are comparatively lower than the control favipiravir thereby conforming to the drug-likeness prediction. These compounds as such become favorable for screening as drug candidates compared to the control favipiravir with lower binding energy, lower lipophilicity range and very high KI constant. The active ligands have promising functions to inhibit and interfere with the replication and maturation of Chymotrypsin-like protease (3CLpro) of SARS-Coronavirus 2. The lower KI, high binding energy and drug-likeness efficiency of the compounds can be further developed into a potent drug molecule against the uncontrollable SARS-COV-2.

Computer-aided comprehensive explorations of RNA structural polymorphism through complementary simulation methods

While RNA folding was originally seen as a simple problem to solve, it has been shown that the promiscuous interactions of the nucleobases result in structural polymorphism, with several competing structures generally observed for non-coding RNA. This inherent complexity limits our understanding of these molecules from experiments alone, and computational methods are commonly used to study RNA. Here, we discuss three advanced sampling schemes, namely Hamiltonian-replica exchange molecular dynamics (MD), ratchet-and-pawl MD and discrete path sampling, as well as the HiRE-RNA coarse-graining scheme, and highlight how these approaches are complementary with reference to recent case studies. While all computational methods have their shortcomings, the plurality of simulation methods leads to a better understanding of experimental findings and can inform and guide experimental work on RNA polymorphism.Copyright ©

Accelerating antiviral discovery by combining machine learning with structural biology

COVID Moonshot is an international open science consortium aiming to discover oral antiviral against SARS-CoV-2, targeting the main protease. Launched in Feb 2020, Moonshot went from fragment hits to development candidates which are now under preclinical evaluation. In my talk, I will discuss Moonshot's journey, specifically how the combination of machine learning and structural biology has accelerated our design-make-test cycle. I will also discuss our vision for pandemic preparedness, and early results from AI-driven Structure Enabled Antiviral Platform (ASAP). ASAP is a NIH-funded antiviral drug discovery center which builds on COVID Moonshot's approach to target flaviviruses, enteroviruses, and coronaviruses. We are applying machine learning to generate potent chemical matter from crystallographic fragment hits, and leveraging high throughput library synthesis guided by models to rapidly expand on promising hits. Aiming to achieve pandemic preparedness, I will also discuss our approaches to preempting resistance, and how these strategic considerations impact drug-hunting.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Fight against COVID-19: Functional and structural study of the T cell response

T cells, and especially cytotoxic T cells are at the forefront of the fight against viral infection. The killer cells are able not only to distinguish between self and foreign peptides, but also to engage in the fight to clear the viral infection by eliminating the infected cells. Our lab is focused on understanding how T cells engage with viral peptide antigens, that are presented by highly polymorphic HLA molecules. T cells have receptors on their surface called T cell receptors (TCRs) that allow them to recognize the composite surface of the peptide- HLA complex. Using x-ray crystallography we can understand at the atomic level both peptide antigens presentation and TCR recognition, both important to determine the quality of the subsequent immune response. We can then link that structural information with our cellular assay that determines the strength and magnitude of the anti-viral response, providing the basis for peptide modification to reach stronger response or an understanding of viral mutation that led to viral escape. Our current work compared the T cell response, at the antigen level against 32 single epitope derived from spike, between COVID-19 recovered and vaccinated donors. We have shown that the booster shot (3rd dose) increases the antigen-specific T cell response, increases the level of T cell cross-reactivity against variant of SARS-CoV-2, but also alters the phenotype of the T cell. Those results are important to future guide vaccination advise and better understand the immune response to SARS-CoV-2 infection. POSTER PRESENTATIONS Autoimmunity, Infection, Reproduction and Cancer.

Technologies for Direct Detection of Covalent Protein-Drug Adducts.

In the past two decades, drug candidates with a covalent binding mode have gained the interest of medicinal chemists, as several covalent anticancer drugs have successfully reached the clinic. As a covalent binding mode changes the relevant parameters to rank inhibitor potency and investigate structure-activity relationship (SAR), it is important to gather experimental evidence on the existence of a covalent protein-drug adduct. In this work, we review established methods and technologies for the direct detection of a covalent protein-drug adduct, illustrated with examples from (recent) drug development endeavors. These technologies include subjecting covalent drug candidates to mass spectrometric (MS) analysis, protein crystallography, or monitoring intrinsic spectroscopic properties of the ligand upon covalent adduct formation. Alternatively, chemical modification of the covalent ligand is required to detect covalent adducts by NMR analysis or activity-based protein profiling (ABPP). Some techniques are more informative than others and can also elucidate the modified amino acid residue or bond layout. We will discuss the compatibility of these techniques with reversible covalent binding modes and the possibilities to evaluate reversibility or obtain kinetic parameters. Finally, we expand upon current challenges and future applications. Overall, these analytical techniques present an integral part of covalent drug development in this exciting new era of drug discovery.

In-silico Discovery of Fungal Metabolites Bergenin, Quercitrin and Dihy-droartemisinin as Potential Inhibitors against Main Protease of SARS-CoV-2

Background: Emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has given rise to COVID-19 pandemic, which has become a wreaking havoc worldwide. Therefore, there is an urgent need to find out novel drugs to combat SARS-CoV-2 in-fection. In this backdrop, the present study aimed to assess potent bioactive compounds from different fungi as potential inhibitors of SARS-CoV-2 main protease (Mpro) using an in-silico analysis. Method(s): High-Resolution Liquid Chromatography Mass Spectrometry analysis (HR-LCMS) was used for the bioactive profiling of ethanolic crude extract of Dictyophora indusiata, Geastrum tri-plex and Cyathus stercoreus. Of which, only bergenin (D. indusiata), quercitrin (G. triplex) and di-hydroartemisinin (C. stercoreus) were selected based on their medicinal uses, binding score and the active site covered. The 6LU7, a protein crystallographic structure of SARS-CoV-2 Mpro, was docked with bergenin, quercitrin and dihydroartemisinin using Autodock 4.2. Result(s): A total of 118 bioactive compounds were analyzed from the crude extract of used fungi and identified using HR LC/MS analysis. The binding energies obtained were-7.86,-10.29 and-7.20 kcal/mol, respectively, after docking analysis. Bergenin, quercitrin and dihydroartemisinin formed hydrogen bond, electrostatic interactions and hydrophobic interactions with foremost active site amino acids THR190, GLU166, GLN189, GLY143, HIS163, HIS164, CYS145 and PHE140. Conclusion(s): Present investigation suggests that these three compounds may be used as alternative inhibitors against SARS-CoV-2 Mpro. However, further research is necessary to assess in vitro potential of these compounds. To the best of our knowledge, the present investigation reported these three bioactive compounds of fungal origin for the first time.Copyright © 2021 Bentham Science Publishers.

Studying the Effect of Glycosylation towards SARS-CoV-2 Spike RBD and ACE2 Interaction by Native Mass Spectrometry

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has serious consequences on global public health and social development. The binding of receptor binding domain (RBD) of spike protein to angiotensin converting enzyme 2 (ACE2) on the surface of SARS-CoV-2 host cell initiates the infection progress. Spike and ACE2 are both glycoproteins, the impact of glycosylation on protein structures and protein-protein interactions remains largely elusive. Characterizing the structural and dynamics of protein-protein binding progress will improve mechanism understanding of viral infection and facilitate targeted drug design. Structural mass spectrometry (MS) method is widely used in protein structural studies, providing complementary information to conventional biophysical methods, such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and cryo-electron microscopy (cryo-EM). Native mass spectrometry (native MS) is an emerging technology that enables the study of intact protein, non-covalent protein-protein, and protein-ligand complexes in their biological state, which can provide structural stability, binding stoichiometry, and spatial arrangement information. Here, native MS was used to examine the interaction between RBD and ACE2 as well as the impact of deglycosylation on the interaction stability of the RBD-ACE2 complex. The results revealed that both RBD and ACE2 are highly glycosylated, ACE2 presents as a dimer while RBD as a monomer, and they form a (RBD-ACE2)2 complex. The conditions of using PNGasc F to remove the N-glycan were optimized. At least two Oglycans including NcuAc(2) and GalNAcC 1) Gal( 1) NcuAc(2) or GlcNAcd ) Gal(l) NeuAc(2) were observed for the N-glycan removed RBD. Furthermore, the stability of the complexes formed by glycosylated and deglycosylated RBD with ACE2 was compared, and the results showed that the removal of N-glycan significantly drops the interaction stability of the RBD-ACE2 complex. Therefore, we recommend that glycosyla-tion should not be removed for structural and functional studies. Additional glycosyla-tion, structural and dynamics studies on Spike (including separated RBD) and ACE2 complexes would help us to understand the process of viral infection, advance drug design and vaccine developments. Nowadays, a comprehensive MS-based toolbox has been developed for the analysis of protein structure, function, and dynamics, including hydrogen-deuterium exchange MS (HDX-MS), native top-down (nTD) MS, cross-linking MS (XL-MS), and covalent labelling MS (CL-MS), etc. Through integrating structural MS methods, more detailed and comprehensive structural information about glycoproteins and their complexes will be uncovered. © 2022 Chinese Society for Mass Spectrometry. All rights reserved.

Studying the Effect of Glycosylation towards SARS-CoV-2 Spike RBD and ACE2 Interaction by Native Mass Spectrometry

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has serious consequences on global public health and social development. The binding of receptor binding domain (RBD) of spike protein to angiotensin converting enzyme 2 (ACE2) on the surface of SARS-CoV-2 host cell initiates the infection progress. Spike and ACE2 are both glycoproteins, the impact of glycosylation on protein structures and protein-protein interactions remains largely elusive. Characterizing the structural and dynamics of protein-protein binding progress will improve mechanism understanding of viral infection and facilitate targeted drug design. Structural mass spectrometry (MS) method is widely used in protein structural studies, providing complementary information to conventional biophysical methods, such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and cryo-electron microscopy (cryo-EM). Native mass spectrometry (native MS) is an emerging technology that enables the study of intact protein, non-covalent protein-protein, and protein-ligand complexes in their biological state, which can provide structural stability, binding stoichiometry, and spatial arrangement information. Here, native MS was used to examine the interaction between RBD and ACE2 as well as the impact of deglycosylation on the interaction stability of the RBD-ACE2 complex. The results revealed that both RBD and ACE2 are highly glycosylated, ACE2 presents as a dimer while RBD as a monomer, and they form a (RBD-ACE2)2 complex. The conditions of using PNGasc F to remove the N-glycan were optimized. At least two Oglycans including NcuAc(2) and GalNAcC 1) Gal( 1) NcuAc(2) or GlcNAcd ) Gal(l) NeuAc(2) were observed for the N-glycan removed RBD. Furthermore, the stability of the complexes formed by glycosylated and deglycosylated RBD with ACE2 was compared, and the results showed that the removal of N-glycan significantly drops the interaction stability of the RBD-ACE2 complex. Therefore, we recommend that glycosyla-tion should not be removed for structural and functional studies. Additional glycosyla-tion, structural and dynamics studies on Spike (including separated RBD) and ACE2 complexes would help us to understand the process of viral infection, advance drug design and vaccine developments. Nowadays, a comprehensive MS-based toolbox has been developed for the analysis of protein structure, function, and dynamics, including hydrogen-deuterium exchange MS (HDX-MS), native top-down (nTD) MS, cross-linking MS (XL-MS), and covalent labelling MS (CL-MS), etc. Through integrating structural MS methods, more detailed and comprehensive structural information about glycoproteins and their complexes will be uncovered. © 2022 Chinese Society for Mass Spectrometry. All rights reserved.

In Silico Identification of Potential Inhibitors of SARS-CoV-2 Papain-like Protease From Natural Sources: A Natural Weapon to Fight COVID-19

Background: The rapid spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) globally has created unprecedented health care and economic crisis. The ever-in-creasing death toll highlights an urgent need for the development of specific antiviral to combat Novel Coronavirus Disease 2019 (COVID-19). Objective(s): In the present study, we aimed to identify potential SARS-CoV-2 papain-like protease inhibitors from regularly used spices. Method(s): A structure-based virtual screening (VS) of our in-house databank of 1152 compounds was employed to identify small molecule inhibitors of SARS-CoV-2 papain-like protease (PLpro), which are important protease for virus replication. The databank was built of the compounds from ten spices and two medicinal plants. Result(s): The top three potential hits that resulted from VS were myricetin (1) available in Alium cepa and Mentha piperita;alpha-hydroxyhydrocaffeic acid (2) available in M. Piperita;and luteolin (3) available in M. Piperita, Curcuma longa, A. cepa, and Trigonella foenum-graecum, which showed fair binding affinity to PLpro of SARS-CoV-2 compared to known SARS-CoV PLpro in-hibitors. The predicted Absorption, Distribution, Metabolism, and Excretion (ADME) properties of the selected hits showed that all are drug-like. The compounds bind to biologically critical regions of the target protein, indicating their potential to inhibit the functionality of this component. Conclusion(s): There are only a few reports available in the literature on the in-silico identification of PLpro inhibitors and most of them used homology modeling of protein. Here, we used the recently uploaded X-ray crystal structure of PLpro (PDB ID: 6WX4) with a well-defined active site. Our computational approach has resulted in the identification of effective inhibitors of SARS-CoV-2PL-pro. The reported edible spices may be useful against COVID-19 as a home remedy after an in--vitro study.Copyright © 2021 Bentham Science Publishers.

Crystal structure of the membrane (M) protein from a bat betacoronavirus.

The membrane (M) protein is the most abundant structural protein of coronaviruses including MERS-CoV, SARS-CoV, and SARS-CoV-2, and plays a central role in virus assembly through its interaction with various partner proteins. However, mechanistic details about how M protein interacts with others remain elusive due to lack of high-resolution structures. Here, we present the first crystal structure of a betacoronavirus M protein from Pipistrellus bat coronavirus HKU5 (batCOV5-M), which is closely related to MERS-CoV, SARS-CoV, and SARS-CoV-2 M proteins. Furthermore, an interaction analysis indicates that the carboxy-terminus of the batCOV5 nucleocapsid (N) protein mediates its interaction with batCOV5-M. Combined with a computational docking analysis an M-N interaction model is proposed, providing insight into the mechanism of M protein-mediated protein interactions.

Turning high-throughput structural biology into predictive inhibitor design.

A common challenge in drug design pertains to finding chemical modifications to a ligand that increases its affinity to the target protein. An underutilized advance is the increase in structural biology throughput, which has progressed from an artisanal endeavor to a monthly throughput of hundreds of different ligands against a protein in modern synchrotrons. However, the missing piece is a framework that turns high-throughput crystallography data into predictive models for ligand design. Here, we designed a simple machine learning approach that predicts protein-ligand affinity from experimental structures of diverse ligands against a single protein paired with biochemical measurements. Our key insight is using physics-based energy descriptors to represent protein-ligand complexes and a learning-to-rank approach that infers the relevant differences between binding modes. We ran a high-throughput crystallography campaign against the SARS-CoV-2 main protease (MPro), obtaining parallel measurements of over 200 protein-ligand complexes and their binding activities. This allows us to design one-step library syntheses which improved the potency of two distinct micromolar hits by over 10-fold, arriving at a noncovalent and nonpeptidomimetic inhibitor with 120 nM antiviral efficacy. Crucially, our approach successfully extends ligands to unexplored regions of the binding pocket, executing large and fruitful moves in chemical space with simple chemistry.

Teaching Single Crystal X-ray Crystallography in the Undergraduate Classroom with Sugar and Epsom Salt

We developed a single crystal X-ray crystallography experiment based on the crystal structure of sucrose (table sugar), and a more challenging experiment using Epsom salt. Both crystals are readily available in X-ray quality crystalline form. In these experiments, students mounted a crystal on a MiTeGen loop and analyzed it using a Rigaku XtaLAB Mini diffractometer (built 2011). Students generated models of both compounds using CrysAlisPro, Olex2, SHELXT, and SHELXL. All aspects of this experiment use free software programs which have user-friendly interfaces. A step-by-step laboratory protocol for determining the structure of both compounds is included in the Supporting Information. These experiments were used in the Fall of 2019 at the Junior and the Senior level. In the Summer of 2020, a take-home version of the lab was created in response to the Novel 2019 Coronavirus (COVID-19) pandemic and implemented in the General Chemistry laboratory curriculum;this experiment was used for the duration of the 2020-2021 academic year. These experiments are suitable for all undergraduate experience levels. © 2022 American Chemical Society and Division of Chemical Education, Inc.

Structural insights into protection against a SARS-CoV-2 spike variant by T cell receptor diversity.

T cells play a crucial role in combatting SARS-CoV-2 and forming long-term memory responses to this coronavirus. The emergence of SARS-CoV-2 variants that can evade T cell immunity has raised concerns about vaccine efficacy and the risk of reinfection. Some SARS-CoV-2 T cell epitopes elicit clonally restricted CD8+ T cell responses characterized by T cell receptors (TCRs) that lack structural diversity. Mutations in such epitopes can lead to loss of recognition by most T cells specific for that epitope, facilitating viral escape. Here, we studied an HLA-A2-restricted spike protein epitope (RLQ) that elicits CD8+ T cell responses in COVID-19 convalescent patients characterized by highly diverse TCRs. We previously reported the structure of an RLQ-specific TCR (RLQ3) with greatly reduced recognition of the most common natural variant of the RLQ epitope (T1006I). Opposite to RLQ3, TCR RLQ7 recognizes T1006I with even higher functional avidity than the WT epitope. To explain the ability of RLQ7, but not RLQ3, to tolerate the T1006I mutation, we determined structures of RLQ7 bound to RLQ-HLA-A2 and T1006I-HLA-A2. These complexes show that there are multiple structural solutions to recognizing RLQ and thereby generating a clonally diverse T cell response to this epitope that assures protection against viral escape and T cell clonal loss.

Computational tools for aptamer identification and optimization

Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively. Copyright © 2022 Elsevier B.V.

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future.

As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.