Evaluating mAbs binding abilities to Omicron subvariant RBDs: implications for selecting effective mAb therapies.

The ongoing evolution of the Omicron lineage of SARS-CoV-2 has led to the emergence of subvariants that pose challenges to antibody neutralization. Understanding the binding dynamics between the receptor-binding domains (RBD) of these subvariants spike and monoclonal antibodies (mAbs) is pivotal for elucidating the mechanisms of immune escape and for advancing the development of therapeutic antibodies. This study focused on the RBD regions of Omicron subvariants BA.2, BA.5, BF.7, and XBB.1.5, employing molecular dynamics simulations to unravel their binding mechanisms with a panel of six mAbs, and subsequently analyzing the origins of immune escape from energetic and structural perspectives. Our results indicated that the antibody LY-COV1404 maintained binding affinities across all studied systems, suggesting the resilience of certain antibodies against variant-induced immune escape, as seen with the mAb 1D1-Fab. The newly identified mAb 002-S21F2 showed a similar efficacy profile to LY-COV1404, though with a slightly reduced binding to BF.7. In parallel, mAb REGN-10933 emerged as a potential therapeutic candidate against BF.7 and XBB.1.5, reflecting the importance of identifying variant-specific antibody interactions, akin to the binding optimization observed in BA.4/5 and XBB.1.5. And key residues that facilitate RBD-mAb binding were identified (T345, L441, K444, V445, and T500), alongside residues that hinder protein-protein interactions (D420, L455, K440, and S446). Particularly noteworthy was the inhibited binding of V445 and R509 with mAbs in the presence of mAb 002-S21F2, suggesting a mechanism for immune escape, especially through the reduction of V445 hydrophobicity. These findings enhance our comprehension of the binding interactions between mAbs and RBDs, contributing to the understanding of immune escape mechanisms. They also lay the groundwork for the design and optimization of antiviral drugs and have significant implications for the development of treatments against current and future coronaviruses.

Entropy driven cooperativity effect in multi-site drug optimization targeting SARS-CoV-2 papain-like protease.

Papain-like protease (PLpro), a non-structural protein encoded by SARS-CoV-2, is an important therapeutic target. Regions 1 and 5 of an existing drug, GRL0617, can be optimized to produce cooperativity with PLpro binding, resulting in stronger binding affinity. This work investigated the origin of the cooperativity using molecular dynamics simulations combined with the interaction entropy (IE) method. The regions' improvement exhibits cooperativity by calculating the binding free energies between the complex of PLpro-inhibitor. The thermodynamic integration method further verified the cooperativity generated in the drug improvement. To further determine the specific source of cooperativity, enthalpy and entropy in the complexes were calculated using molecular mechanics/generalized Born surface area and IE. The results show that the entropic change is an important contributor to the cooperativity. Our study also identified residues P248, Q269, and T301 that play a significant role in cooperativity. The optimization of the inhibitor stabilizes these residues and minimizes the entropic loss, and the cooperativity observed in the binding free energy can be attributed to the change in the entropic contribution of these residues. Based on our research, the application of cooperativity can facilitate drug optimization, and provide theoretical ideas for drug development that leverage cooperativity by reducing the contribution of entropy through multi-locus binding.

Comprehensive analysis unveils altered binding kinetics of 5-/6-methylCytosine/adenine modifications in R2R3-DNA system.

Recent studies have shown that DNA methylation is an important epigenetic marker. Two prominent forms are methylation of the C5 position of cytosine and methylation of the C6 position of adenine. Given the vital significance of DNA methylation, investigating the mechanisms that influence protein binding remains a compelling pursuit. This study used molecular dynamics simulations to investigate the binding patterns of R2R3 protein and four differentially methylated DNAs. The alanine scanning combined with interaction entropy method was used to identify key residues that respond to different methylation patterns. The order of protein binding ability to DNA is as follows: unmethylated DNA > A11 methylation (5'-A6mAC-3') (6m2A system) > A10 methylation (5'-6mAAC-3') (6m1A system) > both A10 and A11 methylation (5'-6mA6mAC-3') (6mAA system) > C12 methylation (5'-AA5mC-3') (5mC system). All methylation systems lead to the sixth α helix (H6) (residues D105 to L116) moving away from the binding interface, and in the 5mC and 6m1A systems, the third α helix (H3) (residues G54 to L65) exhibits a similar trend. When the positively charged amino acids in H3 and H6 move away from the binding interface, their electrostatic and van der Waals interactions with the negatively charged DNA are weakened. Structural changes induced by methylation contributed to the destabilization of the hydrogen bond network near the original binding site, except for the 6m2A system. Moreover, there is a positive correlation between the number of methylated sites and the probability of distorting the DNA structure. Our study explores how different methylation patterns affect binding and structural adaptability, and have implications for drug discovery and understanding diseases related to abnormal methylation.

Quantitative investigation of the effects of DNA modifications and protein mutations on MeCP2-MBD-DNA interactions.

DNA methylation as an important epigenetic marker, has gained attention for the significance of three oxidative modifications (hydroxymethyl-C (hmC), formyl-C (fC), and carboxyl-C (caC)). Mutations occurring in the methyl-CpG-binding domain (MBD) of MeCP2 result in Rett. However, uncertainties persist regarding DNA modification and MBD mutation-induced interaction changes. Here, molecular dynamics simulations were used to investigate the underlying mechanisms behind changes due to different modifications of DNA and MBD mutations. Alanine scanning combined with the interaction entropy method was employed to accurately evaluate the binding free energy. The results show that MBD has the strongest binding ability for mCDNA, followed by caC, hmC, and fCDNA, with the weakest binding ability observed for CDNA. Further analysis revealed that mC modification induces DNA bending, causing residues R91 and R162 closer to the DNA. This proximity enhances van der Waals and electrostatic interactions. Conversely, the caC/hmC and fC modifications lead to two loop regions (near K112 and K130) closer to DNA, respectively. Furthermore, DNA modifications promote the formation of stable hydrogen bond networks, however mutations in the MBD significantly reduce the binding free energy. This study provides detailed insight into the effects of DNA modifications and MBD mutations on binding ability. It emphasizes the necessity for research and development of targeted Rett compounds that induce conformational compatibility between MBD and DNA, enhancing the stability and strength of their interactions.

An Attempt of Seeking Favorable Binding Free Energy Prediction Schemes Considering the Entropic Effect on Fis-DNA Binding.

Protein-DNA binding mechanisms in a complex manner are essential for understanding many biological processes. Over the past decades, numerous experiments and calculations have analyzed the specificity of protein-DNA binding. However, the accuracy of binding free energy prediction for multi-base DNA systems still needs to be improved. Fis is a DNA-binding protein that regulates various transcription and recombination reactions. In the present work, we tested several methods of predict binding free energy based on this system to find a favorable prediction scheme and explore the binding mechanism of Fis protein and DNA. Two solvent models (explicit and implicit solvent models) were chosen for the dynamics process, and the predicted binding free energy was more accurate under the explicit solvent model. When different Poisson-Boltzmann/Generalized Born (PB/GB) models were tested for DNA force fields (BSC1 and OL15), it was found that the binding free energy predicted by the selected OL15 force field performed better and the correlation between predicted and experimental values was improved with the increasing interior dielectric constant (Dk). Finally, using Dk = 8, the GBOBC1 model combined with interaction entropy (IE), which was calculated for entropic contribution (GBOBC1_IE_8), was screened out for the binding free energy prediction and analysis of the Fis-DNA system, and the validity of the method was further verified by testing the Cren7-DNA system. By performing conformational analysis of the minor groove, it was found that mutation of the DNA central sequence A/T to C/G and deletion of the guanine 2-amino group would change the minor groove width and thus affect the formation of the major groove, altering the interaction and atomic contact between the protein and the major groove, thus changing the binding affinity of Fis and DNA. Hopefully, the series of tests in this work can shed some light on the related studies of protein and DNA systems.

Molecular Mechanism of the Non-Covalent Orally Targeted SARS-CoV-2 Mpro Inhibitor S-217622 and Computational Assessment of Its Effectiveness against Mainstream Variants.

Convenient and efficient therapeutic agents are urgently needed to block the continued spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, the mechanism for the novel orally targeted SARS-CoV-2 main protease (Mpro) inhibitor S-217622 is revealed through a molecular dynamics simulation. The difference in the movement modes of the S-217622-Mpro complex and apo-Mpro suggested S-217622 could inhibit the motility intensity of Mpro, thus maintaining their stable binding. Subsequent energy calculations showed that the P2 pharmacophore possessed the highest energy contribution among the three pharmacophores of S-217622. Additionally, hot-spot residues H41, M165, C145, E166, and H163 have strong interactions with S-217622. To further investigate the resistance of S-217622 to six mainstream variants, the binding modes of S-217622 with these variants were elucidated. The subtle differences in energy compared to that of the wild type implied that the binding patterns of these systems were similar, and S-217622 still inhibited these variants. We hope this work will provide theoretical insights for optimizing novel targeted Mpro drugs.

Molecular investigation of the dual inhibition mechanism for targeted P53 regulator MDM2/MDMX inhibitors.

Inhibitors that competitively bind MDM2/MDMX can block the inhibition of P53 by MDM2/MDMX and restart its tumor-suppressive effect. Molecular studies targeting MDM2/MDMX inhibitors have always been a hot topic in anticancer drug design. Although numerous inhibitors have been designed previously against MDM2/MDMX, their dual inhibition efficacy has not been demonstrated, and few studies assessed the general causes affecting the dual inhibition of MDM2/MDMX by these inhibitors. Here, molecular dynamics simulations and alanine scanning combined with the interaction entropy method were employed to precisely investigate whether 16 inhibitors could dually inhibit MDM2/MDMX and the similarities and differences in the interaction modes. Thereby addressing the key residue sites affecting dual inhibition. Residues L54/M53, I61/60, M62/61, Y67/66, and V93/92 of MDM2/MDMX, which are in corresponding positions in both protein structures, provide significant conditions for these inhibitors to bind to MDM2/MDMX tightly. In addition, most of these inhibitors prefer to bind MDM2 than MDMX, and residues H96 and I99 in MDM2 are attractive targets for inhibitors, resulting in inhibitors binding to MDM2/MDMX with different affinity. These key residues should be considered in the development of dual inhibitors. For these 16 inhibitors, most have dual inhibitory potential for MDM2/MDMX based on the binding affinity of the complexes. Still, it is questionable whether they can exert excellent dual inhibition considering the assessment of the hot-spots. At least their binding affinity for MDMX is not superior to that for MDM2 due to the difference in energy of the van der Waals interactions at the key sites. Furthermore, based on the analysis of three representative inhibitors (TUZ/HRH and HRQ with different binding preferences for MDM2/MDMX), 3-chloropyridine in TUZ leads to the differential binding affinity between the inhibitor and MDM2/MDMX. It readily forms hydrophobic interactions with the surrounding residues H96 and I99. But this phenomenon does not occur in the TUZ-MDMX system, implying the critical role of residues H96/P95 and I99/L98. And the completely different binding mechanism of HRQ binding to MDM2/MDMX explains its inability to inhibit MDM2 well. Thus, we are cautious about its dual inhibitory ability. Besides, HRH is more prone to strong van der Waals interactions with MDM2 than MDMX whereas its 2-chlorofluorobenzene is detrimental to this. We hope that these findings will provide reliable molecular insights for the screening and optimization of targeting MDM2/MDMX dual inhibitors.

Immune Escape Mechanisms of SARS-CoV-2 Delta and Omicron Variants against Two Monoclonal Antibodies That Received Emergency Use Authorization.

Multiple-site mutated SARS-CoV-2 Delta and Omicron variants may trigger immune escape against existing monoclonal antibodies. Here, molecular dynamics simulations combined with the interaction entropy method reveal the escape mechanism of Delta/Omicron variants to Bamlanivimab/Etesevimab. The result shows the significantly reduced binding affinity of the Omicron variant for both antibodies, due to the introduction of positively charged residues that greatly weaken their electrostatic interactions. Meanwhile, significant structural deflection induces fewer atomic contacts and an unstable binding mode. As for the Delta variant, the reduced binding affinity for Bamlanivimab is owing to the alienation of the receptor-binding domain to the main part of this antibody, and the binding mode of the Delta variant to Etesevimab is similar to that of the wild type, suggesting that Etesevimab could still be effective against the Delta variant. We hope this work will provide timely theoretical insights into developing antibodies to prevalent and possible future variants of SARS-CoV-2.

Origin of the tight binding mode to ACE2 triggered by multi-point mutations in the omicron variant: a dynamic insight.

The continuous spread of the newly emerged SARS-CoV-2 Omicron variant (B.1.1.529) has become an important reason for the surge in COVID-19 infections. Its numerous mutated residues containing key sites on the receptor-binding domain (RBD) undoubtedly pose new challenges for epidemic control. Although the preventive measures are becoming more sophisticated, the effects of mutations on the binding of the virus to the receptor protein remain to be elucidated. Here, we used molecular dynamics (MD) simulations to investigate the differences in the binding mode between the Omicron variant and the angiotensin-converting enzyme 2 (ACE2) compared to the wild-type strain (WT). Multi-point mutations in the Omicron variant RBD could cause the conformation shift in the large Loop (where T478K and E484A are located), which makes it easier to wrap the N-terminal helix of ACE2 and form tighter contacts. The stronger electrostatic interaction was the main reason for its enhanced binding affinity as compared to WT. This was due to the large number of positively charged patches (N440K, T478K, Q493R, Q498R, and Y505H) formed by the substitution of neutral amino acids at multiple sites. The appearance of these highly polar hydrophilic amino acids may cause local perturbations and affect the electrostatic complementarity of RBD with the ACE2, and further mediate conformational changes. Thus, a more extensive interaction network was found in the mutation system and the complex interaction cluster was formed near E37@ACE2, which was essential for the stable binding of the two. In addition, we speculated that these mutations may affect the electrostatic complementarity with the four potential antibodies to reduce the sensitivity of the virus to antibodies. This study reveals the key details of the Omicron variant binding to ACE2 and provides important theoretical views for the enhanced infectivity of this variant. We hope that these observations can provide timely molecular insights for responding to the Omicron variant pandemic.

Insights from computational analysis: how does the SARS-CoV-2 Delta (B.1.617.2) variant hijack ACE2 more effectively?

The SARS-CoV-2 Delta (B.1.617.2) variant was identified in India in October 2020, and it has quickly become the mainstream strain with strong toxicity and spread, posing great challenges to epidemic control. However, the molecular mechanism of its powerful infectivity remains unclear. It is meaningful to investigate the process of Delta variant's receptor-binding domain (RBD) binding to angiotensin-converting enzyme 2 (ACE2). Here, we performed three repeated molecular dynamics simulations for each system to avoid accidents, and the alanine scanning combined with the interaction entropy (ASIE) method was utilized to evaluate the binding free energy. Through the detailed energy and conformational analysis, the binding mechanism of the Delta variant was illustrated. The results showed that the existence of L452R and T478K mutations can trigger the effective hijacking of ACE2 by the Delta variant through the following three ways: (i) these two mutations can significantly enhance the electrostatic energy of the system by the introduction of two positively charged amino acids (Arg and Lys), thereby increasing the binding affinity of RBD and ACE2, (ii) the Loops 1, 3, and 4 in the receptor-binding motif (RBM) of RBD form a tighter conformation under the dominance of the T478K mutation, allowing ACE2 to be captured more effectively than the wild-type system, and (iii) these conformational changes lead to a more stable hydrogen bond in the Delta variant, which further ensures the stability of the binding. In addition, to explore the effect of mutations on the antibody, the key residues contributing to the changes in the binding ability of RBD in the Delta variant with the existing 42 neutralizing monoclonal antibodies (mAbs) have been preliminarily evaluated. The present study reveals the molecular mechanism for the increased infectivity of SARS-CoV-2 caused by mutations, and the key sites that cause antigenic changes were screened. It provides important theoretical insights for the development of novel targeted RBD drugs and antibodies.

Targeting mechanism for SARS-CoV-2 in silico: interaction and key groups of TMPRSS2 toward four potential drugs.

The global dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seriously endangered human health. The number of confirmed cases is still increasing; however, treatment options are limited. Transmembrane protease serine 2 (TMPRSS2), as a key protease that primes the binding of SARS-CoV-2 spike protein and angiotensin-converting enzyme 2 (ACE2), has become an attractive target and received widespread attention. Thus, four potential drugs (bromhexine, camostat, gabexate, and nafamostat) were used to explore the mechanism of binding with TMPRSS2 in this work. A 65 ns molecular dynamics simulation was performed three times for each drug-TMPRSS2 system for reliable energy calculation and conformational analysis, of which the simulations of nafamostat-TMPRSS2 systems were further extended to 150 ns three times due to the discovery of two binding modes. Through the results of calculating binding free energy by nine methods, the binding affinity of camostat, gabexate, and nafamostat to TMPRSS2 showed great advantages compared with bromhexine, where the nafamostat was surprisingly found to present two reasonable binding conformations (forward and reverse directions). Two negatively charged amino acids (Asp435 and Glu299) can clamp the two positively charged groups (guanidinium group and amidinium group) in either forward or reverse fashion, and the forward one is more stable than the reverse. In addition, compared with gabexate, the dimethylamino group in camostat forms more van der Waals interactions with surrounding hot-spots His296 and Val280, resulting in a stronger affinity to TMPRSS2. For bromhexine, multiple binding sites are displayed in the binding pocket due to its small molecular structure, and van der Waals interactions play the dominant role in the binding process. In particular, six typical hot-spots were identified in the last three serine protease inhibitor systems, i.e., Asp435, Ser436, Gln438, Trp461, Ser463, and Gly464. The guanidinium groups of the drugs have powerful interactions with adjacent residues due to the formation of more hydrogen bonds, suggesting that this may be the critical site for drug design against TMPRSS2. This work provides valuable molecular insight into these four drug-TMPRSS2 binding mechanisms and is helpful for designing and screening drugs targeting TMPRSS2.