Structural insights into Nirmatrelvir (PF-07321332)-3C-like SARS-CoV-2 protease complexation: a ligand Gaussian accelerated molecular dynamics study.

Coronavirus 3C-like protease (3CLpro) is found in SARS-CoV-2 virus, which causes COVID-19. 3CLpro controls virus replication and is a major target for target-based antiviral discovery. As reported by Pfizer, Nirmatrelvir (PF-07321332) is a competitive protein inhibitor and a clinical candidate for orally delivered medication. However, the binding mechanisms between Nirmatrelvir and 3CLpro complex structures remain unknown. This study incorporated ligand Gaussian accelerated molecular dynamics, the one-dimensional and two-dimensional potential of mean force, normal molecular dynamics, and Kramers' rate theory to determine the binding and dissociation rate constants (koff and kon) associated with the binding of the 3CLpro protein to the Nirmatrelvir inhibitor. The proposed approach addresses the challenges in designing small-molecule antiviral drugs.

A universal in silico V(D)J recombination strategy for developing humanized monoclonal antibodies.

BACKGROUND: Humanization of mouse monoclonal antibodies (mAbs) is crucial for reducing their immunogenicity in humans. However, humanized mAbs often lose their binding affinities. Therefore, an in silico humanization method that can prevent the loss of the binding affinity of mAbs is needed. METHODS: We developed an in silico V(D)J recombination platform in which we used V(D)J human germline gene sequences to design five humanized candidates of anti-tumor necrosis factor (TNF)-α mAbs (C1-C5) by using different human germline templates. The candidates were subjected to molecular dynamics simulation. In addition, the structural similarities of their complementarity-determining regions (CDRs) to those of original mouse mAbs were estimated to derive the weighted interatomic root mean squared deviation (wRMSDi) value. Subsequently, the correlation of the derived wRMSDi value with the half maximal effective concentration (EC50) and the binding affinity (KD) of the humanized anti-TNF-α candidates was examined. To confirm whether our in silico estimation method can be used for other humanized mAbs, we tested our method using the anti-epidermal growth factor receptor (EGFR) a4.6.1, anti-glypican-3 (GPC3) YP9.1 and anti-α4ß1 integrin HP1/2L mAbs. RESULTS: The R2 value for the correlation between the wRMSDi and log(EC50) of the recombinant Remicade and those of the humanized anti-TNF-α candidates was 0.901, and the R2 value for the correlation between wRMSDi and log(KD) was 0.9921. The results indicated that our in silico V(D)J recombination platform could predict the binding affinity of humanized candidates and successfully identify the high-affinity humanized anti-TNF-α antibody (Ab) C1 with a binding affinity similar to that of the parental chimeric mAb (5.13 × 10-10). For the anti-EGFR a4.6.1, anti-GPC3 YP9.1, and anti-α4ß1 integrin HP1/2L mAbs, the wRMSDi and log(EC50) exhibited strong correlations (R2 = 0.9908, 0.9999, and 0.8907, respectively). CONCLUSIONS: Our in silico V(D)J recombination platform can facilitate the development of humanized mAbs with low immunogenicity and high binding affinities. This platform can directly transform numerous mAbs with therapeutic potential to humanized or even human therapeutic Abs for clinical use.

Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies.

The on-target toxicity of monoclonal antibodies (Abs) is mainly due to the fact that Abs cannot distinguish target antigens (Ags) expressed in disease regions from those in normal tissues during systemic administration. In order to overcome this issue, we "copied" an autologous Ab hinge as an "Ab lock" and "pasted" it on the binding site of the Ab by connecting a protease substrate and linker in between to generate a pro-Ab, which can be specifically activated in the disease region to enhance Ab selectivity and reduce side effects. Previously, we reported that 70% of pro-Abs can achieve more than 100-fold blocking ability compared to the parental Abs. However, 30% of pro-Abs do not have such efficient blocking ability. This is because the same Ab lock linker cannot be applied to every Ab due to the differences in the complementarity-determining region (CDR) loops. Here we designed a method which uses structure-based computational simulation (MSCS) to optimize the blocking ability of the Ab lock for all Ab drugs. MSCS can precisely adjust the amino acid composition of the linker between the Ab lock and Ab drug with the assistance of molecular simulation. We selected αPD-1, αIL-1ß, αCTLA-4 and αTNFα Ab as models and attached the Ab lock with various linkers (L1 to L7) to form pro-Abs by MSCS, respectively. The resulting cover rates of the Ab lock with various linkers compared to the Ab drug were in the range 28.33-42.33%. The recombinant pro-Abs were generated by MSCS prediction in order to verify the application of molecular simulation for pro-Ab development. The binding kinetics effective concentrations (EC-50) for αPD-1 (200-250-fold), αIL-1ß (152-186-fold), αCTLA-4 (68-150-fold) and αTNFα Ab (20-123-fold) were presented as the blocking ability of pro-Ab compared to the Ab drug. Further, there was a positive correlation between cover rate and blocking ability of all pro-Ab candidates. The results suggested that MSCS was able to predict the Ab lock linker most suitable for application to αPD-1, αIL-1ß, αCTLA-4 and αTNFα Ab to form pro-Abs efficiently. The success of MSCS in optimizing the pro-Ab can aid the development of next-generation pro-Ab drugs to significantly improve Ab-based therapies and thus patients' quality of life.

Correction: Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies.

[This corrects the article DOI: 10.1039/D1SC01748A.].

In silico studies of conformational dynamics of Mu opioid receptor performed using gaussian accelerated molecular dynamics.

G-protein-coupled receptors play a crucial role in various signaling pathways and function as targets for treating a wide spectrum of diseases. Since the twentieth century, extensive research has been conducted on the Mu opioid receptor (MOR) as a drug target. We examined the MOR inactivation and activation processes using an enhanced sampling method (Gaussian accelerated molecular dynamics), the binding pocket site area method, the root mean square deviation method, and the free energy (potential of mean force) method. This study revealed two important intermediate MOR structures (intermediate and intermediate inactive), and the results suggest that the intermediate MOR structure is responsible for the selectivity of opioids.

A fragment-based docking simulation for investigating peptide-protein bindings.

A fragment-based method was developed to investigate the binding conformations of peptide ligands. This method efficiently avoids the high degree of freedom (DOF) of peptide dockings by dividing a peptide into two half fragments. The fragments are separately docked on receptors and the results are used to rebuild a profile of massive possible docking conformations of the whole peptide. Through rapid scoring for filtering, the remaining peptide docking conformations are rigorously optimized by molecular dynamics (MD) and scored by molecular mechanics/generalized born surface area (MM/GBSA) method to predict the near-native binding conformations. This method has been tested on 17 cases of long peptide-protein interaction with known crystal structures, and also on 7 unbound protein receptors for which both the bound and unbound conformations are known. The resultant binding predictions fit very closely to the crystal structures.

Theoretical investigation on reaction of sulbactam with wild-type SHV-1 ß-lactamase: acylation, tautomerization, and deacylation.

Molecular dynamics (MD) simulation and quantum mechanical (QM) calculations were used to investigate the reaction mechanism of sulbactam with class A wild-type SHV-1 ß-lactamase including acylation, tautomerization, and deacylation. Five different sulbactam-enzyme configurations were investigated by MD simulations. In the acylation step, we found that Glu166 cannot activate Ser70 directly for attacking on the carbonyl carbon, and Lys73 would participate in the reaction acting as a relay. Additionally, we found that sulbactam carboxyl can also act as a general base. QM calculations were performed on the formation mechanism of linear intermediates. We suggest that both imine and trans-enamine intermediates can be obtained in the opening of a five-membered thiazolidine ring. By MD simulation, we found that imine intermediate can exist in two conformations, which can generate subsequent trans- and cis-enamine intermediates, respectively. The QM calculations revealed that trans-enamine intermediate is much more stable than other intermediates. The deacylation mechanism of three linear intermediates (imine, trans-enamine, cis-enamine) was investigated separately. It is remarkably noted that, in cis-enamine intermediate, Glu166 cannot activate water for attacking on the carbonyl carbon directly. This leads to a decreasing of the deacylation rate of cis-enamine. These findings will be potentially useful in the development of new inhibitors.

Computer simulation to investigate the FRET application in DNA hybridization systems.

Molecular dynamics (MD) and quantum mechanics (QM) were used to investigate fluorescence resonance energy transfer (FRET) between coumarin and ethidium in two Mergny's DNA hybridization systems. By combining the transition dipoles calculated by the quantum semi-empirical method and the conformations of the FRET probes collected by MD, FRET efficiencies were derived from the Förster equation at five temperatures from 273 K to 313 K. The plotted efficiencies were compared with Mergny's experiments, and showed good agreement. The simulated orientation factor and isotropically averaged orientation factor were compared, and the results demonstrated that the assumption of isotropic orientations is invalid when FRET probes are close to each other. The first order kinetic assumptions were also used to calculate the transfer efficiencies, and the results show that this D-A FRET process approximates the first order kinetic reactions.

Enhanced recognition of single-base mismatch using locked nucleic acid-integrated hairpin DNA probes revealed by atomic force microscopy nanolithography.

Probe design is a critical parameter in successful DNA and RNA target detection. In this proof-of-concept study, we evaluated the single-base mismatch recognition power of surface immobilized and self-assembled stem-loop hairpin DNA oligonucleotide probes modified to contain locked nucleic acid residues (LNA-HP). The stiffness change in conjunction with the stem opening of the interfacial molecules before and after hybridization led to clear variations of the overall film thickness or miniaturized nanospot height, which could be directly measured using an atomic force microscopy (AFM) nanolithography technique. Particularly, LNA-HP achieved highly differentiable readouts between perfectly complementary and singly mismatched targets (discrimination ratio as high as 2 to 3), outperforming the selectivity of its linear and hairpin counterparts with no LNA modification.

Potential of mean force for Syrian hamster prion epitope protein--monoclonal fab 3f4 antibody interaction studies.

Simulating antigen-antibody interactions are crucial for understanding antigen-antibody associations in immunology. To shed further light on this question, we study a dissociation of the Syrian hamster prion epitope protein-fab 3f4 antibody complex structure. The stretching, that is, the distance between the center of mass of the prion epitope protein and the fab 3f4 antibody, has been studied using potential of mean force (PMF) calculations based on molecular dynamics (MD) and the implicit water model. For the complex structure, there are four important intermediates, U-shaped groove on the antibodies, and two inter-protein molecular hydrogen bonds in the stretching process. Use of our simulations may help in understanding the binding mechanics of the complex structure, and thus of significance in the design of antibodies against prion disease.