Computational approaches to studying methylated H4K20 recognition by DNA repair factor 53BP1

An Efficient Approach to the Accurate Prediction of Mutational Effects in Antigen Binding to the MHC1

The major histocompatibility complex (MHC) can recognize and bind to external peptides to generate effective immune responses by presenting the peptides to T cells. Therefore, understanding the binding modes of peptide-MHC complexes (pMHC) and predicting the binding affinity of pMHCs play a crucial role in the rational design of peptide vaccines. In this study, we employed molecular dynamics (MD) simulations and free energy calculations with an Alanine Scanning with Generalized Born and Interaction Entropy (ASGBIE) method to investigate the protein-peptide interaction between HLA-A*02:01 and the G9209 peptide derived from the melanoma antigen gp100. The energy contribution of individual residue was calculated using alanine scanning, and hotspots on both the MHC and the peptides were identified. Our study shows that the pMHC binding is dominated by the van der Waals interactions. Furthermore, we optimized the ASGBIE method, achieving a Pearson correlation coefficient of 0.91 between predicted and experimental binding affinity for mutated antigens. This represents a significant improvement over the conventional MM/GBSA method, which yields a Pearson correlation coefficient of 0.22. The computational protocol developed in this study can be applied to the computational screening of antigens for the MHC1 as well as other protein-peptide binding systems.

Combined Antibodies Evusheld against the SARS-CoV-2 Omicron Variants BA.1.1 and BA.5: Immune Escape Mechanism from Molecular Simulation

The Omicron lineage of SARS-CoV-2, which was first reported in November 2021, has spread globally and become dominant, splitting into several sublineages. Experiments have shown that Omicron lineage has escaped or reduced the activity of existing monoclonal antibodies, but the origin of escape mechanism caused by mutation is still unknown. This work uses molecular dynamics and umbrella sampling methods to reveal the escape mechanism of BA.1.1 to monoclonal antibody (mAb) Tixagevimab (AZD1061) and BA.5 to mAb Cilgavimab (AZD8895), both mAbs were combined to form antibody cocktail, Evusheld (AZD7442). The binding free energy of BA.1.1-AZD1061 and BA.5-AZD8895 has been severely reduced due to multiple-site mutated Omicron variants. Our results show that the two Omicron variants, which introduce a substantial number of positively charged residues, can weaken the electrostatic attraction between the receptor binding domain (RBD) and AZD7442, thus leading to a decrease in affinity. Additionally, using umbrella sampling along dissociation pathway, we found that the two Omicron variants severely impaired the interaction between the RBD of SARS-CoV-2's spike glycoprotein (S protein) and complementary determining regions (CDRs) of mAbs, especially in CDR3H. Although mAbs AZD8895 and AZD1061 are knocked out by BA.5 and BA.1.1, respectively, our results confirm that the antibody cocktail AZD7442 retains activity against BA.1.1 and BA.5 because another antibody is still on guard. The study provides theoretical insights for mAbs interacting with BA.1.1 and BA.5 from both energetic and dynamic perspectives, and we hope this will help in developing new monoclonals and combinations to protect those unable to mount adequate vaccine responses.

Mutational Effect of Some Major COVID-19 Variants on Binding of the S Protein to ACE2

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has many variants that accelerated the spread of the virus. In this study, we investigated the quantitative effect of some major mutants of the spike protein of SARS-CoV-2 binding to the human angiotensin-converting enzyme 2 (ACE2). These mutations are directly related to the Variant of Concern (VOC) including Alpha, Beta, Gamma, Delta and Omicron. Our calculations show that five major mutations (N501Y, E484K, L452R, T478K and K417N), first reported in Alpha, Beta, Gamma and Delta variants, all increase the binding of the S protein to ACE2 (except K417N), consistent with the experimental findings. We also studied an additional eight mutations of the Omicron variant that are located on the interface of the receptor binding domain (RDB) and have not been reported in other VOCs. Our study showed that most of these mutations (except Y505H and G446S) enhance the binding of the S protein to ACE2. The computational predictions helped explain why the Omicron variant quickly became dominant worldwide. Finally, comparison of several different computational methods for binding free energy calculation of these mutants was made. The alanine scanning method used in the current calculation helped to elucidate the residue-specific interactions responsible for the enhanced binding affinities of the mutants. The results show that the ASGB (alanine scanning with generalized Born) method is an efficient and reliable method for these binding free energy calculations due to mutations.

Lysine Methyltransferase Inhibitors Impair H4K20me2 and 53BP1 Foci in Response to DNA Damage in Sarcomas, a Synthetic Lethality Strategy

Background

Chromatin is dynamically remodeled to adapt to all DNA-related processes, including DNA damage responses (DDR). This adaptation requires DNA and histone epigenetic modifications, which are mediated by several types of enzymes; among them are lysine methyltransferases (KMTs).

Methods

KMT inhibitors, chaetocin and tazemetostat (TZM), were used to study their role in the DDR induced by ionizing radiation or doxorubicin in two human sarcoma cells lines. The effect of these KMT inhibitors was tested by the analysis of chromatin epigenetic modifications, H4K16ac and H4K20me2. DDR was monitored by the formation of γH2AX, MDC1, NBS1 and 53BP1 foci, and the induction of apoptosis.

Results

Chaetocin and tazemetostat treatments caused a significant increase of H4K16 acetylation, associated with chromatin relaxation, and increased DNA damage, detected by the labeling of free DNA-ends. These inhibitors significantly reduced H4K20 dimethylation levels in response to DNA damage and impaired the recruitment of 53BP1, but not of MDC1 and NBS1, at DNA damaged sites. This modification of epigenetic marks prevents DNA repair by the NHEJ pathway and leads to cell death.

Conclusion

KMT inhibitors could function as sensitizers to DNA damage-based therapies and be used in novel synthetic lethality strategies for sarcoma treatment.

Anchor-Locker Binding Mechanism of the Coronavirus Spike Protein to Human ACE2: Insights from Computational Analysis

COVID-19 has emerged as the most serious international pandemic in early 2020 and the lack of comprehensive knowledge in the recognition and transmission mechanisms of this virus hinders the development of suitable therapeutic strategies. The specific recognition during the binding of the spike glycoprotein (S protein) of coronavirus to the angiotensin-converting enzyme 2 (ACE2) in the host cell is widely considered the first step of infection. However, detailed insights on the underlying mechanism of dynamic recognition and binding of these two proteins remain unknown. In this work, molecular dynamics simulation and binding free energy calculation were carried out to systematically compare and analyze the receptor-binding domain (RBD) of six coronavirus' S proteins. We found that affinity and stability of the RBD from SARS-CoV-2 under the binding state with ACE2 are stronger than those of other coronaviruses. The solvent-accessible surface area (SASA) and binding free energy of different RBD subunits indicate an "anchor-locker" recognition mechanism involved in the binding of the S protein to ACE2. Loop 2 (Y473-F490) acts as an anchor for ACE2 recognition, and Loop 3 (G496-V503) locks ACE2 at the other nonanchoring end. Then, the charged or long-chain residues in the β-sheet 1 (N450-F456) region reinforce this binding. The proposed binding mechanism was supported by umbrella sampling simulation of the dissociation process. The current computational study provides important theoretical insights for the development of new vaccines against SARS-CoV-2.

Quantitative analysis of ACE2 binding to coronavirus spike proteins: SARS-CoV-2 vs. SARS-CoV and RaTG13

The global outbreak of the COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Bat virus RaTG13 and SARS-CoV are also members of the coronavirus family and SARS-CoV caused a world-wide pandemic in 2003. SARS-CoV-2, SARS-CoV and RaTG13 bind to angiotensin-converting enzyme 2 (ACE2) through their receptor-binding domain (RBD) of the spike protein. SARS-CoV-2 binds ACE2 with a higher binding affinity than SARS-CoV and RaTG13. Here we performed molecular dynamics simulation of these binding complexes and calculated their binding free energies using a computational alanine scanning method. Our MD simulation and hotspot residue analysis showed that the lower binding affinity of SARS-CoV to ACE2 vs. SARS-CoV-2 to ACE2 can be explained by different hotspot interactions in these two systems. We also found that the lower binding affinity of RaTG13 to ACE2 is mainly due to a mutated residue (D501) which resulted in a less favorable complex formation for binding. We also calculated an important mutation of N501Y in SARS-CoV-2 using both alanine scanning calculation and a thermodynamic integration (TI) method. Both calculations confirmed a significant increase of the binding affinity of the N501Y mutant to ACE2 and explained its molecular mechanism. The present work provides an important theoretical basis for understanding the molecular mechanism in coronavirus spike protein binding to human ACE2.

Binding thermodynamics and interaction patterns of human purine nucleoside phosphorylase-inhibitor complexes from extensive free energy calculations

Human purine nucleoside phosphorylase (hPNP) plays a significant role in the catabolism of deoxyguanosine. The trimeric protein is an important target in the treatment of T-cell cancers and autoimmune disorders. Experimental studies on the inhibition of the hPNP observe that the first ligand bound to one of three subunits effectively inhibits the protein, while the binding of more ligands to the subsequent sites shows negative cooperativities. In this work, we performed extensive end-point and alchemical free energy calculations to determine the binding thermodynamics of the trimeric protein-ligand system. 13 Immucillin inhibitors with experimental results are under calculation. Two widely accepted charge schemes for small molecules including AM1-BCC and RESP are adopted for ligands. The results of RESP are in better agreement with the experimental reference. Further investigations of the interaction networks in the protein-ligand complexes reveal that several residues play significant roles in stabilizing the complex structure. The most commonly observed ones include PHE200, GLU201, MET219, and ASN243. The conformations of the protein in different protein-ligand complexes are observed to be similar. We expect these insights to aid the development of potent drugs targeting hPNP.

Computational and Experimental Approaches to Decipher the Binding Mechanism of General Odorant-Binding Protein 2 from Athetis lepigone to Chlorpyrifos and Phoxim

Insect resistance to insecticides is an increasingly serious problem, and the resistant mechanisms are complicated. The resistance research based on the chemosensory pathway is one of the hot problems at present, but the specific binding mechanism of chemosensory genes and insecticides remains elusive. The binding mechanism of AlepGOBP2 (belong to insect chemosensory gene) with two insecticides was investigated by computational and experimental approaches. Our calculation results indicated that four key residues (Phe12, Ile52, Ile94, and Phe118) could steadily interact with these two insecticides and be assigned as hotspot sites responsible for their binding affinities. The significant alkyl-π and hydrophobic interactions involved by these four hotspot residues were found to be the driving forces for their binding affinities, especially for two residues (Phe12 and Ile94) that significantly contribute to the binding of chlorpyrifos, which were also validated by our binding assay results. Furthermore, we also found that the AlepGOBP2-chlorpyrifos/phoxim complexes can be more efficiently converged in the residue-specific force field-(RSFF2C) and its higher accuracy and repeatability in protein dynamics simulation, per-residue free energy decomposition, and computational alanine scanning calculations have also been achieved in this paper. These findings provided useful insights for efficient and reliable calculation of the binding mechanism of relevant AlepGOBPs with other insecticides, facilitating to develop new and efficient insecticides targeting the key sites of AlepGOBP2.

Binding Thermodynamics and Interaction Patterns of Inhibitor-Major Urinary Protein-I Binding from Extensive Free-Energy Calculations: Benchmarking AMBER Force Fields

Mouse major urinary protein (MUP) plays a key role in the pheromone communication system. The one-end-closed β-barrel of MUP-I forms a small, deep, and hydrophobic central cavity, which could accommodate structurally diverse ligands. Previous computational studies employed old protein force fields and short simulation times to determine the binding thermodynamics or investigated only a small number of structurally similar ligands, which resulted in sampled regions far from the experimental structure, nonconverged sampling outcomes, and limited understanding of the possible interaction patterns that the cavity could produce. In this work, extensive end-point and alchemical free-energy calculations with advanced protein force fields were performed to determine the binding thermodynamics of a series of MUP-inhibitor systems and investigate the inter- and intramolecular interaction patterns. Three series of inhibitors with a total of 14 ligands were simulated. We independently simulated the MUP-inhibitor complexes under two advanced AMBER force fields. Our benchmark test showed that the advanced AMBER force fields including AMBER19SB and AMBER14SB provided better descriptions of the system, and the backbone root-mean-square deviation (RMSD) was significantly lowered compared with previous computational studies with old protein force fields. Surprisingly, although the latest AMBER force field AMBER19SB provided better descriptions of various observables, it neither improved the binding thermodynamics nor lowered the backbone RMSD compared with the previously proposed and widely used AMBER14SB. The older but widely used AMBER14SB actually achieved better performance in the prediction of binding affinities from the alchemical and end-point free-energy calculations. We further analyzed the protein-ligand interaction networks to identify important residues stabilizing the bound structure. Six residues including PHE38, LEU40, PHE90, ALA103, LEU105, and TYR120 were found to contribute the most significant part of protein-ligand interactions, and 10 residues were found to provide favorable interactions stabilizing the bound state. The two AMBER force fields gave extremely similar interaction networks, and the secondary structures also showed similar behavior. Thus, the intra- and intermolecular interaction networks described with the two AMBER force fields are similar. Therefore, AMBER14SB could still be the default option in free-energy calculations to achieve highly accurate binding thermodynamics and interaction patterns.

Molecular Mechanism of Selective Binding of NMS-P118 to PARP-1 and PARP-2: A Computational Perspective

The nuclear protein poly (ADP-ribose) polymerase-1 (PARP-1) inhibitors have been proven effective to potentiate both chemotherapeutic agents and radiotherapy. However, a major problem of most current PARP inhibitors is their lack of selectivity for PARP-1 and its closest isoform PARP-2. NMS-P118 is a highly selective PARP inhibitor that binds PARP-1 stronger than PARP-2 and has many advantages such as excellent pharmacokinetic profiles. In this study, molecular dynamics (MD) simulations of NMS-P118 in complex with PARP-1 and PARP-2 were performed to understand the molecular mechanism of its selectivity. Alanine scanning together with free energy calculation using MM/GBSA and interaction entropy reveal key residues that are responsible for the selectivity. Although the conformation of the binding pockets and NMS-P118 are very similar in PARP-1 and PARP-2, most of the hot-spot residues in PARP-1 have stronger binding free energy than the corresponding residues in PARP-2. Detailed analysis of the binding energy shows that the 4′4-difluorocyclohexyl ring on NMS-P118 form favorable hydrophobic interaction with Y889 in PARP-1. In addition, the H862 residue in PARP-1 has stronger binding free energy than H428 in PARP-2, which is due to shorter distance and stronger hydrogen bonds. Moreover, the negatively charged E763 residue in PARP-1 forms stronger electrostatic interaction energy with the positively charged NMS-P118 than the Q332 residue in PARP-2. These results rationalize the selectivity of NMS-P118 and may be useful for designing novel selective PARP inhibitors.