Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity.

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) molecules is essential to both novel immunotherapeutic development and human health at large. Current methods for predicting antigen peptide immunogenicity rely primarily on simple sequence representations, which allow for some understanding of immunogenic features but provide inadequate consideration of the full scale of molecular mechanisms tied to peptide recognition. We here characterize contributions that unsupervised and supervised artificial intelligence (AI) methods can make toward understanding and predicting MHC(HLA-A2)-peptide complex immunogenicity when applied to large ensembles of molecular dynamics simulations. We first show that an unsupervised AI method allows us to identify subtle features that drive immunogenicity differences between a cancer neoantigen and its wild-type peptide counterpart. Next, we demonstrate that a supervised AI method for class I MHC(HLA-A2)-peptide complex classification significantly outperforms a sequence model on small datasets corrected for trivial sequence correlations. Furthermore, we show that both unsupervised and supervised approaches reveal determinants of immunogenicity based on time-dependent molecular fluctuations and anchor position dynamics outside the MHC binding groove. We discuss implications of these structural and dynamic immunogenicity correlates for the induction of T cell responses and therapeutic T cell receptor design.

Metal-Organic Framework with Space-Partition Pores by Fluorinated Anions for Benchmark C2H2/CO2 Separation.

The efficient separation of C2H2 from C2H2/CO2 or C2H2/CO2/CH4 mixtures is crucial for achieving high-purity C2H2 (>99%), essential in producing contemporary commodity chemicals. In this report, we present ZNU-12, a metal-organic framework with space-partitioned pores formed by inorganic fluorinated anions, for highly efficient C2H2/CO2 and C2H2/CO2/CH4 separation. The framework, partitioned by fluorinated SiF62- anions into three distinct cages, enables both a high C2H2 capacity (176.5 cm3/g at 298 K and 1.0 bar) and outstanding C2H2 selectivity over CO2 (13.4) and CH4 (233.5) simultaneously. Notably, we achieve a record-high C2H2 productivity (132.7, 105.9, 98.8, and 80.0 L/kg with 99.5% purity) from C2H2/CO2 (v/v = 50/50) and C2H2/CO2/CH4 (v/v = 1/1/1, 1/1/2, or 1/1/8) mixtures through a cycle of adsorption-desorption breakthrough experiments with high recovery rates. Theoretical calculations suggest the presence of potent "2 + 2" collaborative hydrogen bonds between C2H2 and two hexafluorosilicate (SiF62-) anions in the confined cavities.

Developing semi-empirical water model for efficiently simulating temperature-dependent chemisorption of CO2 in amine solvents.

Classical molecular dynamics (MD) simulations without bond forming/breaking cannot be used to model chemical reactions (CRs) among small molecules. Although the first-principle MD simulation can adequately describe CRs with explicit water molecules, such simulation is normally too costly for most researchers to afford. Generally, water molecules in a solvent can exert hydrophobic forces on reacting molecules, which yields a so-called caging effect that cannot be ignored when constructing a free energy landscape for reacting molecules. Many recently developed semi-empirical methods (such as DFTB, PM6 and xTB) are highly efficient for modeling CRs, however none of them can be directly used to model bulk water properly. Here, we developed a modified xTB approach that enables the simulation of CRs in explicit water. Using the chemisorption of CO2 by amines in water as an example application, we demonstrate that our approach yielded results comparable with the first-principle ones, while only using a limited computing resource. Potentially, our proposed semi-empirical water model can be utilized for the computational study of any CR in water.

Stable Cell Clones Harboring Self-Replicating SARS-CoV-2 RNAs for Drug Screen.

The development of antivirals against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been hampered by the lack of efficient cell-based replication systems that are amenable to high-throughput screens in biosafety level 2 laboratories. Here we report that stable cell clones harboring autonomously replicating SARS-CoV-2 RNAs without spike (S), membrane (M), and envelope (E) genes can be efficiently derived from the baby hamster kidney (BHK-21) cell line when a pair of mutations were introduced into the non-structural protein 1 (Nsp1) of SARS-CoV-2 to ameliorate cellular toxicity associated with virus replication. In a proof-of-concept experiment we screened a 273-compound library using replicon cells and identified three compounds as novel inhibitors of SARS-CoV-2 replication. Altogether, this work establishes a robust, cell-based system for genetic and functional analyses of SARS-CoV-2 replication and for the development of antiviral drugs. IMPORTANCE SARS-CoV-2 replicon systems that have been reported up to date were unsuccessful in deriving stable cell lines harboring non-cytopathic replicons. The transient expression of viral sgmRNA or a reporter gene makes it impractical for industry-scale screening of large compound libraries using these systems. Here, for the first time, we derived stable cell clones harboring the SARS-CoV-2 replicon. These clones may now be conveniently cultured in a standard BSL-2 laboratory for high throughput screen of compound libraries. Additionally, our stable replicon cells represent a new model system to study SARS-CoV-2 replication.

Highly Efficient CO2/C2H2 Separation by Porous Graphene via Quadrupole Gating Mechanism.

Acetylene (C2H2) is an important and widely used raw material in various industries (such as petrochemical). Generally, a product yield is proportional to the purity of C2H2; however, C2H2 from a typical industrial gas-production process is commonly contaminated by CO2. So far, the achievement of high-purity C2H2 separated from a CO2/C2H2 mixture is still challenging due to their very close molecular dimensions and boiling temperatures. Taking advantage of their quadrupoles with opposite signs, here, we show that the graphene membrane embedded with crown ether nanopores can achieve an unprecedented separation efficiency of CO2/C2H2. Combining the molecular dynamics simulation and the density functional theory (DFT) approaches, we discovered that the electrostatic gas-pore interaction favorably allows the fast transport of CO2 through crown ether nanopores while completely prohibiting C2H2 transport, which yields a remarkable permeation selectivity. In particular, the utilized crown ether pore is capable of allowing the individual transport of CO2 while completely rejecting the passage of C2H2, independent of the applied pressures, fed gases ratios, and exerted temperatures, featuring the superiority and robustness of the crown pore in CO2/C2H2 separation. Further, DFT and PMF calculations demonstrate that the transport of CO2 through the crown pore is energetically more favorable than the transport of C2H2. Our findings reveal the potential application of graphene crown pore for CO2 separation with outstanding performance.

Topological Design of Unprecedented Metal-Organic Frameworks Featuring Multiple Anion Functionalities and Hierarchical Porosity for Benchmark Acetylene Separation.

Separation of acetylene (C2 H2 ) from carbon dioxide (CO2 ) or ethylene (C2 H4 ) is industrially important but still challenging so far. Herein, we developed two novel robust metal organic frameworks AlFSIX-Cu-TPBDA (ZNU-8) with znv topology and SIFSIX-Cu-TPBDA (ZNU-9) with wly topology for efficient capture of C2 H2 from CO2 and C2 H4 . Both ZNU-8 and ZNU-9 feature multiple anion functionalities and hierarchical porosity. Notably, ZNU-9 with more anionic binding sites and three distinct cages displays both an extremely large C2 H2 capacity (7.94 mmol/g) and a high C2 H2 /CO2 (10.3) or C2 H2 /C2 H4 (11.6) selectivity. The calculated capacity of C2 H2 per anion (4.94 mol/mol at 1 bar) is the highest among all the anion pillared metal organic frameworks. Theoretical calculation indicated that the strong cooperative hydrogen bonds exist between acetylene and the pillared SiF6 2- anions in the confined cavity, which is further confirmed by in situ IR spectra. The practical separation performance was explicitly demonstrated by dynamic breakthrough experiments with equimolar C2 H2 /CO2 mixtures and 1/99 C2 H2 /C2 H4 mixtures under various conditions with excellent recyclability and benchmark productivity of pure C2 H2 (5.13 mmol/g) or C2 H4 (48.57 mmol/g).

Crystal-structures-guided design of fragment-based drugs for inhibiting the main protease of SARS-CoV-2.

Since the beginning of the COVID-19 pandemic, scientists across the globe are racing to find a cure for the highly contagious infectious disease caused by the SARS-CoV-2 virus. Despite many promising ongoing progress, there are currently no FDA approved drug to treat infected patients. Recently, the crowdsourcing of drug discovery for inhibiting the main protease (Mpro) of SARS-CoV-2 have yielded a plenty of drug fragments resolved inside the active site of Mpro via the crystallography method. Following the principle of fragment-based drug design (FBDD), we are motivated to design a potent drug candidate (named B19) by merging three fragments JFM, U0P, and HWH. Through extensive all-atom molecular dynamics simulation and molecular docking, we found that B19 among all designed ones is most stable inside the Mpro's active site and the binding free energy of B19 is comparable to or even a little better than that of a native protein ligand processed by Mpro. Our promising results suggest that B19 and its derivatives can potentially be efficacious drug candidates for COVID-19.

Nanopores in Atomically Thin 2D Nanosheets Limit Aqueous Single-Stranded DNA Transport.

Nanopores in 2D materials are highly desirable for DNA sequencing, yet achieving single-stranded DNA (ssDNA) transport through them is challenging. Using density functional theory calculations and molecular dynamics simulations we show that ssDNA transport through a pore in monolayer hexagonal boron nitride (h-BN) is marked by a basic nanomechanical conflict. It arises from the notably inhomogeneous flexural rigidity of ssDNA and causes high friction via transient DNA desorption costs exacerbated by solvation effects. For a similarly sized pore in bilayer h-BN, its self-passivated atomically smooth edge enables continuous ssDNA transport. Our findings shed light on the fundamental physics of biopolymer transport through pores in 2D materials.

Structure-Function Analysis of Resistance to Bamlanivimab by SARS-CoV-2 Variants Kappa, Delta, and Lambda.

The newly emerging Kappa, Delta, and Lambda SARS-CoV-2 variants are worrisome, characterized with the double mutations E484Q/L452R, T478K/L452R, and F490S/L452Q, respectively, in their receptor binding domains (RBDs) of the spike proteins. As revealed in crystal structures, most of these residues (e.g., 452 and 484 in RBDs) are not in direct contact with interfacial residues in the angiotensin-converting enzyme 2 (ACE2). This suggests that albeit there are some possibly nonlocal effects, these mutations might not significantly affect RBD's binding with ACE2, which is an important step for viral entry into host cells. Thus, without knowing the molecular mechanism, these successful mutations (from the point of view of SARS-CoV-2) may be hypothesized to evade human antibodies. Using all-atom molecular dynamics (MD) simulation, here, we show that the E484Q/L452R mutations significantly reduce the binding affinity between the RBD of the Kappa variant and the antibody LY-CoV555 (also named as Bamlanivimab), which was efficacious for neutralizing the wild-type SARS-CoV-2. To verify simulation results, we further carried out experiments with both pseudovirions- and live virus-based neutralization assays and demonstrated that LY-CoV555 completely lost neutralizing activity against the L452R/E484Q mutant. Similarly, we show that mutations in the Delta and Lambda variants can also destabilize the RBD's binding with LY-CoV555. With the revealed molecular mechanism on how these variants evade LY-CoV555, we expect that more specific therapeutic antibodies can be accordingly designed and/or a precise mixing of antibodies can be achieved as a cocktail treatment for patients infected with these variants.

Targeting Proteases for Treating COVID-19.

The unprecedented pandemic of coronavirus disease 2019 (COVID-19) demands effective treatment for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The infection of SARS-CoV-2 critically depends on diverse viral or host proteases, which mediate viral entry, viral protein maturation, as well as the pathogenesis of the viral infection. Endogenous and exogenous agents targeting for proteases have been proved to be effective toward a variety of viral infections ranging from HIV to influenza virus, suggesting protease inhibitors as a promising antiviral treatment for COVID-19. In this Review, we discuss how host and viral proteases participated in the pathogenesis of COVID-19 as well as the prospects and ongoing clinical trials of protease inhibitors as treatments.

Structure-based lead optimization of herbal medicine rutin for inhibiting SARS-CoV-2's main protease.

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic with very limited specific treatments. To fight COVID-19, various traditional antiviral medicines have been prescribed in China to infected patients with mild to moderate symptoms and received unexpected success in controlling the disease. However, the molecular mechanisms of how these herbal medicines interact with the SARS-CoV-2 virus that causes COVID-19 have remained elusive. It is well known that the main protease (Mpro) of SARS-CoV-2 plays an important role in maturation of many viral proteins such as the RNA-dependent RNA polymerase. Here, we explore the underlying molecular mechanisms of the computationally determined top candidate, namely, rutin which is a key component in many traditional antiviral medicines such as Lianhuaqinwen and Shuanghuanlian, for inhibiting the viral target-Mpro. Using in silico methods (docking and molecular dynamics simulations), we revealed the dynamics and energetics of rutin when interacting with the Mpro of SARS-CoV-2, suggesting that the highly hydrophilic rutin molecule can be bound inside the Mpro's pocket (active site) and possibly inhibit its biological functions. In addition, we optimized the structure of rutin and designed two more hydrophobic analogs, M1 and M2, which satisfy the rule of five for western medicines and demonstrated that they (M2 in particular) possess much stronger binding affinities to the SARS-COV-2s Mpro than rutin, due to the enhanced hydrophobic interaction as well as more hydrogen bonds. Therefore, our results provide invaluable insights into the mechanism of a ligand's binding inside the Mpro and shed light on future structure-based designs of high-potent inhibitors for SARS-CoV-2 Mpro.

Atomic-Scale Fluidic Diodes Based on Triangular Nanopores in Bilayer Hexagonal Boron Nitride.

Nanofluidic diodes based on nanochannels have been studied theoretically and experimentally for applications such as biosensors and logic gates. However, when analyzing attoliter-scale samples or enabling high-density integration of lab-on-a-chip devices, it is beneficial to miniaturize the size of a nanofluidic channel. Using molecular dynamics simulations, we investigate conductance of nanopores in bilayer hexagonal boron nitride (h-BN). Remarkably, we found that triangular nanopores possess excellent rectifications of ionic currents while hexagonal ones do not. It is worth highlighting that the pore length is only about 0.7 nm, which is about the atomic limit for a bipolar diode. We determined scaling relations between ionic currents I and pore sizes L for small nanopores, that are I ∼ L1 in a forward biasing voltage and I ∼ L2 in a reverse biasing voltage. Simulation results qualitatively agree with analytical ones derived from the one-dimensional Poisson-Nerst-Planck equations.

Combined Computational-Experimental Approach to Explore the Molecular Mechanism of SaCas9 with a Broadened DNA Targeting Range.

Despite accelerating development of CRISPR technology, there remains high demand for further interrogation of its fundamental biology. This is particularly fascinating as new improved CRISPR tools were artificially engineered to harbor beneficial features but often lack mechanistic explanation. SaCas9, a minimal Cas9 ideal for in vivo applications, suffers from long protospacer adjacent motif (PAM), which prompted effort on mutant KKH SaCas9 with relaxed PAM requirement. Leveraging structure-based molecular dynamics simulation, free-energy perturbation, and targeted experimentation, we developed a workflow for probing SaCas9 and a series of its variants, revealing intriguing dynamics of PAM recognition and the molecular mechanism of KKH mutations. Furthermore, we deployed this approach to design and validate new mutant SaCas9, SaCas9-NR and SaCas9-RL, with enhanced targeting range distinctive from the KKH mutant and improved activity in mammalian cells. Overall, our approach provides a dynamic understanding of SaCas9 PAM recognition and a new gateway to enlighten rationally designed Cas9 variants harboring novel properties.

Exploring the binding mechanism between human profilin (PFN1) and polyproline-10 through binding mode screening.

The large magnitude of protein-protein interaction (PPI) pairs within the human interactome necessitates the development of predictive models and screening tools to better understand this fundamental molecular communication. However, despite enormous efforts from various groups to develop predictive techniques in the last decade, PPI complex structures are in general still very challenging to predict due to the large number of degrees of freedom. In this study, we use the binding complex of human profilin (PFN1) and polyproline-10 (P10) as a model system to examine various approaches, with the aim of going beyond normal protein docking for PPI prediction and evaluation. The potential of mean force (PMF) was first obtained from the time-consuming umbrella sampling, which confirmed that the most stable binding structure identified by the maximal PMF difference is indeed the crystallographic binding structure. Moreover, crucial residues previously identified in experimental studies, W3, H133, and S137 of PFN1, were found to form favorable hydrogen bonds with P10, suggesting a zipping process during the binding between PFN1 and P10. We then explored both regular molecular dynamics (MD) and steered molecular dynamics (SMD) simulations, seeking for better criteria of ranking the PPI prediction. Despite valuable information obtained from conventional MD simulations, neither the commonly used interaction energy between the two binding parties nor the long-term root mean square displacement correlates well with the PMF results. On the other hand, with a sizable collection of trajectories, we demonstrated that the average and minimal rupture works calculated from SMD simulations correlate fairly well with the PMFs (R 2 = 0.67), making this a promising PPI screening method.

Glassy dynamics in mutant huntingtin proteins.

Causative to the neurodegenerative Huntington's disease (HD), a mutational huntingtin (HTT) protein consists of an unusual expansion on the poly-glutamine (polyQ) region in the first exon (exon-1) domain. Despite its significance on HD progression, the structural role of the exon-1 with the polyQ region is still elusive. As HTT is an intrinsically disordered protein (IDP), a large ensemble of various conformations (instead of a mostly single native conformation) is required to characterize its structural properties and to infer biological functions, which is challenging even for the most state-of-the-art experimental techniques. For this reason, molecular dynamics (MD) simulations with enhanced sampling techniques are ideal to compliment experiment on collecting such a large ensemble of thermodynamically accessible structures. Here, we performed large-scale temperature replica-exchange MD (T-REMD) simulations on the exon-1 with an illustration on the necessity of using T-REMD instead of unbiased regular MD. By comparing T-REMD data and unbiased MD data, we discovered that (1) the dynamics of polyQ regions are extremely sluggish and glassy at the room temperature and the relaxation of the system cannot be achieved within a reasonable amount of time without utilizing an enhanced sampling method and (2) an ensemble of protein structures containing the surprising cis-peptide bonds in the proline-rich domain can be obtained at much elevated temperatures. Our results may provide valuable insights for future studies on the HTT as well as other IDPs using the T-REMD method.

High-Curvature Nanostructuring Enhances Probe Display for Biomolecular Detection.

High-curvature electrodes facilitate rapid and sensitive detection of a broad class of molecular analytes. These sensors have reached detection limits not attained using bulk macroscale materials. It has been proposed that immobilized DNA probes are displayed at a high deflection angle on the sensor surface, which allows greater accessibility and more efficient hybridization. Here we report the first use of all-atom molecular dynamics simulations coupled with electrochemical experiments to explore the dynamics of single-stranded DNA immobilized on high-curvature versus flat surfaces. We find that high-curvature structures suppress DNA probe aggregation among adjacent probes. This results in conformations that are more freely accessed by target molecules. The effect observed is amplified in the presence of highly charged cations commonly used in electrochemical biosensing. The results of the simulations agree with experiments that measure the degree of hybridization in the presence of mono-, di-, and trivalent cations. On high-curvature structures, hybridization current density increases as positive charge increases, whereas on flat electrodes, the trivalent cations cause aggregation due to electrostatic overscreening, which leads to decreased current density and less sensitive detection.

Emerging ß-Sheet Rich Conformations in Supercompact Huntingtin Exon-1 Mutant Structures.

There exists strong correlation between the extended polyglutamines (polyQ) within exon-1 of Huntingtin protein (Htt) and age onset of Huntington's disease (HD); however, the underlying molecular mechanism is still poorly understood. Here we apply extensive molecular dynamics simulations to study the folding of Htt-exon-1 across five different polyQ-lengths. We find an increase in secondary structure motifs at longer Q-lengths, including ß-sheet content that seems to contribute to the formation of increasingly compact structures. More strikingly, these longer Q-lengths adopt supercompact structures as evidenced by a surprisingly small power-law scaling exponent (0.22) between the radius-of-gyration and Q-length that is substantially below expected values for compact globule structures (∼0.33) and unstructured proteins (∼0.50). Hydrogen bond analyses further revealed that the supercompact behavior of polyQ is mainly due to the "glue-like" behavior of glutamine's side chains with significantly more side chain-side chain H-bonds than regular proteins in the Protein Data Bank (PDB). The orientation of the glutamine side chains also tend to be "buried" inside, explaining why polyQ domains are insoluble on their own.

Structural perturbations on huntingtin N17 domain during its folding on 2D-nanomaterials.

A globular protein's folded structure in its physiological environment is largely determined by its amino acid sequence. Recently, newly discovered transformer proteins as well as intrinsically disordered proteins may adopt the folding-upon-binding mechanism where their secondary structures are highly dependent on their binding partners. Due to the various applications of nanomaterials in biological sensors and potential wearable devices, it is important to discover possible conformational changes of proteins on nanomaterials. Here, through molecular dynamics simulations, we show that the first 17 residues of the huntingtin protein (HTT-N17) exhibit appreciable differences during its folding on 2D-nanomaterials, such as graphene and MoS2 nanosheets. Namely, the protein is disordered on the graphene surface but is helical on the MoS2 surface. Despite that the amphiphilic environment at the nanosheet-water interface promotes the folding of the amphipathic proteins (such as HTT-N17), competitions between protein-nanosheet and intra-protein interactions yield very different protein conformations. Therefore, as engineered binding partners, nanomaterials might significantly affect the structures of adsorbed proteins.

A novel self-activation mechanism of Candida antarctica lipase B.

Candida antarctica lipase B (CalB), resembling many other lipases structure-wise, contains a flexible lid that undergoes a surprisingly large conformational change when catalyzing hydrophobic substrates (e.g. triglycerides). Despite extensive and important applications in industry, it is so far still elusive whether CalB can be activated on a hydrophobic surface, like other lipases. From large-scale all-atom molecular dynamics simulations, we discovered an open state that strikingly shows a much wider and more stable entrance to the catalytic site than the one suggested by previous crystal structures. Simulations demonstrate that in the newly found open state CalB possesses a "lid-holder" structure that intimately harbors the lid of CalB, i.e. a remarkable self-activation mechanism. To account for the unusual interfacial activation of CALB revealed in a recent experiment, we further introduce a simple model: the activation occurs only when the binding free energy between the lid and a hydrophobic surface is larger than a critical value, 4.0 kcal mol-1 that is the one between the lid and the "lid-holder". Our findings shed light on possible protein engineering of lipases to permit either self-activation with broadened catalytic targets (including water soluble ones) or surface activation with elevated activities.

Bio-nano interactions detected by nanochannel electrophoresis.

Engineered nanoparticles have been widely used in industry and are present in many consumer products. However, their bio-safeties especially in a long term are largely unknown. Here, a nanochannel-electrophoresis-based method is proposed for detecting the potential bio-nano interactions that may further lead to damages to human health and/or biological environment. Through proof-of-concept molecular dynamics simulations, it was demonstrated that the transport of a protein-nanoparticle complex is very different from that of a protein along. By monitoring the change of ionic currents induced by a transported analyte as well as the transport velocities of the analyte, the complex (with bio-nano interaction) can be clearly distinguished from the protein alone (with no interaction with tested nanoparticles).