Mutation-Induced Impacts on the Switch Transformations of the GDP- and GTP-Bound K-Ras: Insights from Multiple Replica Gaussian Accelerated Molecular Dynamics and Free Energy Analysis

In silico discovery of potential PPI inhibitors for anti-lung cancer activity by targeting the CCND1-CDK4 complex via the P21 inhibition mechanism

Non-Small Cell Lung Cancer (NSCLC) is a prevalent and deadly form of lung cancer worldwide with a low 5-year survival rate. Current treatments have limitations, particularly for advanced-stage patients. P21, a protein that inhibits the CCND1-CDK4 complex, plays a crucial role in cell proliferation. Computer-Aided Drug Design (CADD) based on pharmacophores can screen and design PPI inhibitors targeting the CCND1-CDK4 complex. By analyzing known inhibitors, key pharmacophores are identified, and computational methods are used to screen potential PPI inhibitors. Molecular docking, pharmacophore matching, and structure-activity relationship studies optimize the inhibitors. This approach accelerates the discovery of CCND1-CDK4 PPI inhibitors for NSCLC treatment. Molecular dynamics simulations of CCND1-CDK4-P21 and CCND1-CDK4 complexes showed stable behavior, comprehensive sampling, and P21's impact on complex stability and hydrogen bond formation. A pharmacophore model facilitated virtual screening, identifying compounds with favorable binding affinities. Further simulations confirmed the stability and interactions of selected compounds, including 513457. This study demonstrates the potential of CADD in optimizing PPI inhibitors targeting the CCND1-CDK4 complex for NSCLC treatment. Extended simulations and experimental validations are necessary to assess their efficacy and safety.

Unveiling therapeutic frontiers: DON/DRP-104 as innovative Plasma kallikrein inhibitors against carcinoma-associated hereditary angioedema shocks - a comprehensive molecular dynamics exploration

Human plasma kallikrein (PKa) is a member of the serine protease family and serves as a key mediator of the kallikrein-kinin system (KKS), which is known for its regulatory roles in inflammation, vasodilation, blood pressure, and coagulation. Genetic dysregulation of KKS leads to Hereditary Angioedema (HAE), which is characterized by spontaneous, painful swelling in various body regions. Importantly, HAE frequently coexists with various cancers. Despite substantial efforts towards the development of PKa inhibitors for HAE, there remains a need for bifunctional agents addressing both anti-cancer and anti-HAE aspects, especially against carcinoma-associated comorbid HAE conditions. Consequently, we investigated the therapeutic potential of the anti-glutamine prodrug, isopropyl(S)-2-((S)-2-acetamido-3-(1H-indol-3-yl)-propanamido)-6-diazo-5-oxo-hexanoate (DRP-104), and its active form, 6-Diazo-5-oxo-l-norleucine (DON), recognized for their anti-cancer properties, as novel PKa inhibitors. Utilizing structure-based in silico methods, we conducted a comparative analysis with berotralstat, a clinically approved HAE prophylactic, and sebetralstat, an investigational HAE therapeutic agent, in Phase 3 clinical trials. Inhibiting PKa with DON resulted in relatively heightened structural stability, rigidity, restricted protein folding, and solvent-accessible loop exposure, contributing to increased intra-atomic hydrogen bond formation. Conversely, PKa inhibition with DRP-104 induced restricted residue flexibility and significantly disrupted the critical SER195-HIS57 arrangement in the catalytic triad. Both DON and DRP-104, along with the reference drugs, induced strong cooperative intra-residue motion and bidirectional displacement in the PKa architecture. The results revealed favorable binding kinetics of DON/DRP-104, showing thermodynamic profiles that were either superior or comparable to those of the reference drugs. These findings support their consideration for clinical investigations into the management of carcinoma-associated HAE.

Molecular Insights into the Effects of F16L and F19L Substitutions on the Conformation and Aggregation Dynamics of Human Calcitonin

Human calcitonin (hCT) regulates calcium-phosphorus metabolism, but its amyloid aggregation disrupts physiological activity, increases thyroid carcinoma risk, and hampers its clinical use for bone-related diseases like osteoporosis and Paget's disease. Improving hCT with targeted modifications to mitigate amyloid formation while maintaining its function holds promise as a strategy. Understanding how each residue in hCT's amyloidogenic core affects its structure and aggregation dynamics is crucial for designing effective analogues. Mutants F16L-hCT and F19L-hCT, where Phe residues in the core are replaced with Leu as in nonamyloidogenic salmon calcitonin, showed different aggregation kinetics. However, the molecular effects of these substitutions in hCT are still unclear. Here, we systematically investigated the folding and self-assembly conformational dynamics of hCT, F16L-hCT, and F19L-hCT through multiple long-time scale independent atomistic discrete molecular dynamics (DMD) simulations. Our results indicated that the hCT monomer primarily assumed unstructured conformations with dynamic helices around residues 4-12 and 14-21. During self-assembly, the amyloidogenic core of hCT14-21 converted from dynamic helices to β-sheets. However, substituting F16L did not induce significant conformational changes, as F16L-hCT exhibited characteristics similar to those of wild-type hCT in both monomeric and oligomeric states. In contrast, F19L-hCT exhibited substantially more helices and fewer β-sheets than did hCT, irrespective of their monomers or oligomers. The substitution of F19L significantly enhanced the stability of the helical conformation for hCT14-21, thereby suppressing the helix-to-β-sheet conformational conversion. Overall, our findings elucidate the molecular mechanisms underlying hCT aggregation and the effects of F16L and F19L substitutions on the conformational dynamics of hCT, highlighting the critical role of F19 as an important target in the design of amyloid-resistant hCT analogs for future clinical applications.

Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning

CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy landscapes (FELs). DL finds that the binding pocket as well as the T-loop binding to the Vcyclin protein are involved in obvious differences of conformation contacts. This result suggests that the binding pocket of inhibitors (LQQ and AP9) and the binding interface of CDK6 to the Vcyclin protein play a key role in the function of CDK6. The analyses of FELs reveal that the binding pocket and the T-loop of CDK6 have disordered states. The results from principal component analysis (PCA) indicate that the binding of the Vcyclin protein affects the fluctuation behavior of the T-loop in CDK6. Our QM/MM-GBSA calculations suggest that the binding ability of LQQ to CDK6 is stronger than AP9 with or without the binding of the Vcyclin protein. Interaction networks of inhibitors with CDK6 were analyzed and the results reveal that LQQ contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. In addition, the binding pocket endures flexibility changes from opening to closing states and the Vcyclin protein plays an important role in the stabilizing conformation of the T-loop. We anticipate that this work could provide useful information for further understanding the function of CDK6 and developing new promising inhibitors targeting CDK6.

Molecular modeling and simulation approaches to characterize potential molecular targets for burdock inulin to instigate protection against autoimmune diseases

In the current study, we utilized molecular modeling and simulation approaches to define putative potential molecular targets for Burdock Inulin, including inflammatory proteins such as iNOS, COX-2, TNF-alpha, IL-6, and IL-1β. Molecular docking results revealed potential interactions and good binding affinity for these targets; however, IL-1β, COX-2, and iNOS were identified as the best targets for Inulin. Molecular simulation-based stability assessment demonstrated that inulin could primarily target iNOS and may also supplementarily target COX-2 and IL-1β during DSS-induced colitis to reduce the role of these inflammatory mechanisms. Furthermore, residual flexibility, hydrogen bonding, and structural packing were reported with uniform trajectories, showing no significant perturbation throughout the simulation. The protein motions within the simulation trajectories were clustered using principal component analysis (PCA). The IL-1β-Inulin complex, approximately 70% of the total motion was attributed to the first three eigenvectors, while the remaining motion was contributed by the remaining eigenvectors. In contrast, for the COX2-Inulin complex, 75% of the total motion was attributed to the eigenvectors. Furthermore, in the iNOS-Inulin complex, the first three eigenvectors contributed to 60% of the total motion. Furthermore, the iNOS-Inulin complex contributed 60% to the total motion through the first three eigenvectors. To explore thermodynamically favorable changes upon mutation, motion mode analysis was carried out. The Free Energy Landscape (FEL) results demonstrated that the IL-1β-Inulin achieved a single conformation with the lowest energy, while COX2-Inulin and iNOS-Inulin exhibited two lowest-energy conformations each. IL-1β-Inulin and COX2-Inulin displayed total binding free energies of - 27.76 kcal/mol and - 37.78 kcal/mol, respectively, while iNOS-Inulin demonstrated the best binding free energy results at - 45.89 kcal/mol. This indicates a stronger pharmacological potential of iNOS than the other two complexes. Thus, further experiments are needed to use inulin to target iNOS and reduce DSS-induced colitis and other autoimmune diseases.

Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning

The phosphorylation of different sites produces a significant effect on the conformational dynamics of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were combined with deep learning (DL) to explore the molecular mechanism of the phosphorylation-mediated effect on conformational dynamics of the GTP-bound KRAS. The DL finds that the switch domains are involved in obvious differences in conformation contacts and suggests that the switch domains play a key role in the function of KRAS. The analyses of free energy landscapes (FELs) reveal that the phosphorylation of pY32, pY64, and pY137 leads to more disordered states of the switch domains than the wild-type (WT) KRAS and induces conformational transformations between the closed and open states. The results from principal component analysis (PCA) indicate that principal motions PC1 and PC2 are responsible for the closed and open states of the phosphorylated KRAS. Interaction networks were analyzed and the results verify that the phosphorylation alters interactions of GTP and magnesium ion Mg2+ with the switch domains. It is concluded that the phosphorylation pY32, pY64, and pY137 tune the activity of KRAS through changing conformational dynamics and interactions of the switch domains. We anticipated that this work could provide theoretical aids for deeply understanding the function of KRAS.

In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches

Single-point mutations in the Kirsten rat sarcoma (KRAS) viral proto-oncogene are the most common cause of human cancer. In humans, oncogenic KRAS mutations are responsible for about 30% of lung, pancreatic, and colon cancers. One of the predominant mutant KRAS G12D variants is responsible for pancreatic cancer and is an attractive drug target. At the time of writing, no Food and Drug Administration (FDA) approved drugs are available for the KRAS G12D mutant. So, there is a need to develop an effective drug for KRAS G12D. The process of finding new drugs is expensive and time-consuming. On the other hand, in silico drug designing methodologies are cost-effective and less time-consuming. Herein, we employed machine learning algorithms such as K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF) for the identification of new inhibitors against the KRAS G12D mutant. A total of 82 hits were predicted as active against the KRAS G12D mutant. The active hits were docked into the active site of the KRAS G12D mutant. Furthermore, to evaluate the stability of the compounds with a good docking score, the top two complexes and the standard complex (MRTX-1133) were subjected to 200 ns MD simulation. The top two hits revealed high stability as compared to the standard compound. The binding energy of the top two hits was good as compared to the standard compound. Our identified hits have the potential to inhibit the KRAS G12D mutation and can help combat cancer. To the best of our knowledge, this is the first study in which machine-learning-based virtual screening, molecular docking, and molecular dynamics simulation were carried out for the identification of new promising inhibitors for the KRAS G12D mutant.

Gaussian accelerated molecular dynamics simulations facilitate prediction of the permeability of cyclic peptides

Despite their widespread use as therapeutics, clinical development of small molecule drugs remains challenging. Among the many parameters that undergo optimization during the drug development process, increasing passive cell permeability (i.e., log(P)) can have some of the largest impact on potency. Cyclic peptides (CPs) have emerged as a viable alternative to small molecules, as they retain many of the advantages of small molecules (oral availability, target specificity) while being highly effective at traversing the plasma membrane. However, the relationship between the dominant conformations that typify CPs in an aqueous versus a membrane environment and cell permeability remain poorly characterized. In this study, we have used Gaussian accelerated molecular dynamics (GaMD) simulations to characterize the effect of solvent on the free energy landscape of lariat peptides, a subset of CPs that have recently shown potential for drug development (Kelly et al., JACS 2021). Differences in the free energy of lariat peptides as a function of solvent can be used to predict permeability of these molecules, and our results show that permeability is most greatly influenced by N-methylation and exposure to solvent. Our approach lays the groundwork for using GaMD as a way to virtually screen large libraries of CPs and drive forward development of CP-based therapeutics.

Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning

Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop. The information from the post-processing analysis of MD simulations indicates that inhibitor binding highly influences the structural flexibility and dynamic behavior of BRD4 and BRD9. The results of the MM-GBSA calculations not only suggest that the binding ability of H1B, JQ1 and TVU to BRD9 are stronger than to BRD4, but they also verify that van der Walls interactions are the primary forces responsible for inhibitor binding. The hot spots of BRD4 and BRD9 revealed by residue-based free energy estimation provide target sites of drug design in regard to BRD4 and BRD9. This work is anticipated to provide useful theoretical aids for the development of selective inhibitors over BRD family members.

The switch states of the GDP-bound HRAS affected by point mutations: a study from Gaussian accelerated molecular dynamics simulations and free energy landscapes

Point mutations play a vital role in the conformational transformation of HRAS. In this work, Gaussian accelerated molecular dynamics (GaMD) simulations followed by constructions of free energy landscapes (FELs) were adopted to explore the effect of mutations D33K, A59T and L120A on conformation states of the GDP-bound HRAS. The results from the post-processing analyses on GaMD trajectories suggest that mutations alter the flexibility and motion modes of the switch domains from HRAS. The analyses from FELs show that mutations induce more disordered states of the switch domains and affect interactions of GDP with HRAS, implying that mutations yield a vital effect on the binding of HRAS to effectors. The GDP-residue interaction network revealed by our current work indicates that salt bridges and hydrogen bonding interactions (HBIs) play key roles in the binding of GDP to HRAS. Furthermore, instability in the interactions of magnesium ions and GDP with the switch SI leads to the extreme disorder of the switch domains. This study is expected to provide the energetic basis and molecular mechanism for further understanding the function of HRAS.Communicated by Ramaswamy H. Sarma.

A high-throughput molecular dynamics screening (HTMDS) approach to the design of novel cyclopeptide inhibitors of ATAD2B based on the non-canonical combinatorial library

Cyclic peptides (CPs) are a promising class of drugs because of their high biological activity and specificity. However, the design of CP remains challenging due to their conformational flexibility and difficulties in designing stable binding conformation. Herein, we present a high-throughput MD screening (HTMDS) process for the iterative design of stable CP binders with a combinatorial CP library composed of canonical and non-canonical amino acids. As a proof of concept, we apply our methods to design CP inhibitors for the bromodomain (BrD) of ATAD2B. 698,800 CP candidates with a total of 25,570 ns MD simulations were performed to study the protein-ligand binding interactions. The binding free energies (ΔGbind) estimated by MM/PBSA approach for eight lead CP designs were found to be low. CP-1st.43 was the best CP candidate with an estimated ΔGbind of -28.48 kcal/mol when compared to the standard inhibitor C-38 which has been experimentally validated and shown to exhibit ΔGbind of -17.11 kcal/mol. The major contribution of binding sites for BrD of ATAD2B involved the hydrogen-bonding anchor within the Aly-binding pocket, salt bridging, and hydrogen-bonding mediated stabilization of the ZA loop and BC loop, and the complementary Van der Waals attraction. Our methods demonstrate encouraging results by yielding conformationally stable and high-potential CP binders that should have potential applicability in future CP drug development.Communicated by Ramaswamy H. Sarma.

Mutations influence the conformational dynamics of the GDP/KRAS complex

Mutations near allosteric sites can have a significant impact on the function of KRAS. Three specific mutations, K104Q, G12D/K104Q, and G12D/G75A, which are located near allosteric positions, were selected to investigate the molecular mechanisms behind mutation-induced influences on the activity of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations followed by the principal component analysis (PCA) were performed to improve the sampling of conformational states. The results revealed that these mutations significantly alter the structural flexibility, correlated motions, and dynamic behavior of the switch regions that are essential for KRAS binding to effectors or regulators. Furthermore, the mutations have a significant impact on the hydrogen bonding interactions between GDP and the switch regions, as well as on the electrostatic interactions of magnesium ions (Mg2+) with these regions. Our results verified that these mutations strongly influence the binding of KRAS to its effectors or regulators and allosterically regulate the activity. We believe that this work can provide valuable theoretical insights into a deeper understanding of KRAS function.Communicated by Ramaswamy H. Sarma.

Mechanistic and structural insight into R2R3-MYB transcription factor in plants: molecular dynamics based binding free energy analysis

The MYB transcription factor (TF) family is essential for various plant growth and development processes, including responses to biotic and abiotic stresses. This study investigated the R2R3-MYB protein structure from five plants, including cereal crops. The R2R3-MYB protein structure was docked with the DNA structure, and the best complexes were selected for two runs of molecular dynamics (MD) simulations to investigate the key interacting residues and conformational changes in the R2R3-MYB proteins caused by DNA binding. The MM/PBSA method calculated the binding free energy for each R2R3-MYB protein-DNA complex, showing strong interaction. Hydrophobic and hydrogen bonds significantly stabilized the R2R3-MYB protein-DNA complexes. The principal component analysis showed high restrictions on the movement of protein atoms in the phase space. A similar MD simulation analysis was performed using the crystal structure of the R2R3-MYB protein-DNA complex from Arabidopsis thaliana, and the generated complexes resembled the X-ray crystal structure. This is the first detailed study on the R2R3-MYB protein-DNA complex in cereal crops, providing a cost-effective solution to identify the key interacting residues and analyze the conformational changes in the MYB domain before and after DNA binding.Communicated by Ramaswamy H. Sarma.

In silico design of multipoint mutants for enhanced performance of Thermomyces lanuginosus lipase for efficient biodiesel production

BACKGROUND

Biodiesel, an emerging sustainable and renewable clean energy, has garnered considerable attention as an alternative to fossil fuels. Although lipases are promising catalysts for biodiesel production, their efficiency in industrial-scale application still requires improvement.

RESULTS

In this study, a novel strategy for multi-site mutagenesis in the binding pocket was developed via FuncLib (for mutant enzyme design) and Rosetta Cartesian_ddg (for free energy calculation) to improve the reaction rate and yield of lipase-catalyzed biodiesel production. Thermomyces lanuginosus lipase (TLL) with high activity and thermostability was obtained using the Pichia pastoris expression system. The specific activities of the mutants M11 and M21 (each with 5 and 4 mutations) were 1.50- and 3.10-fold higher, respectively, than those of the wild-type (wt-TLL). Their corresponding melting temperature profiles increased by 10.53 and 6.01 °C, [Formula: see text] (the temperature at which the activity is reduced to 50% after 15 min incubation) increased from 60.88 to 68.46 °C and 66.30 °C, and the optimum temperatures shifted from 45 to 50 °C. After incubation in 60% methanol for 1 h, the mutants M11 and M21 retained more than 60% activity, and 45% higher activity than that of wt-TLL. Molecular dynamics simulations indicated that the increase in thermostability could be explained by reduced atomic fluctuation, and the improved catalytic properties were attributed to a reduced binding free energy and newly formed hydrophobic interaction. Yields of biodiesel production catalyzed by mutants M11 and M21 for 48 h at an elevated temperature (50 °C) were 94.03% and 98.56%, respectively, markedly higher than that of the wt-TLL (88.56%) at its optimal temperature (45 °C) by transesterification of soybean oil.

CONCLUSIONS

An integrating strategy was first adopted to realize the co-evolution of catalytic efficiency and thermostability of lipase. Two promising mutants M11 and M21 with excellent properties exhibited great potential for practical applications for in biodiesel production.

Unveiling the State Transition Mechanisms of Ras Proteins through Enhanced Sampling and QM/MM Simulations

In cells, wild-type RasGTP complexes exist in two distinct states: active State 2 and inactive State 1. These complexes regulate their functions by transitioning between the two states. However, the mechanisms underlying this state transition have not been clearly elucidated. To address this, we conducted a detailed simulation study to characterize the energetics of the stable states involved in the state transitions of the HRasGTP complex, specifically from State 2 to State 1. This was achieved by employing multiscale quantum mechanics/molecular mechanics and enhanced sampling molecular dynamics methods. Based on the simulation results, we constructed the two-dimensional free energy landscapes that provide crucial information about the conformational changes of the HRasGTP complex from State 2 to State 1. Furthermore, we also explored the conformational changes from the intermediate state to the product state during guanosine triphosphate hydrolysis. This study on the conformational changes involved in the HRas state transitions serves as a valuable reference for understanding the corresponding events of both KRas and NRas as well.

Decoupling the dynamic mechanism revealed by FGFR2 mutation-induced population shift

The fibroblast growth factor receptor 2 (FGFR2) is a key component in cellular signaling networks, and its dysfunctional activation has been implicated in various diseases including cancer and developmental disorders. Mutations at the activation loop (A-loop) have been suggested to trigger an increased basal kinase activity. However, the molecular mechanism underlying this highly dynamic process has not been fully understood due to the limitation of static structural information. Here, we conducted multiple, large-scale Gaussian accelerated molecular dynamics simulations of five (K659E, K659N, K659M, K659Q, and K659T) FGFR2 mutants at the A-loop, and comprehensively analyzed the dynamic molecular basis of FGFR2 activation. The results quantified the population shift of each system, revealing that all mutants had a higher proportion of active-like states. Using Markov state models, we extracted the representative structure of different conformational states and identified key residues related to the increased kinase activity. Furthermore, community network analysis showed enhanced information connections in the mutants, highlighting the long-range allosteric communication between the A-loop and the hinge region. Our findings may provide insights into the dynamic mechanism for FGFR2 dysfunctional activation and allosteric drug discovery.Communicated by Ramaswamy H. Sarma.

Identification and mechanistic exploration of structural and conformational dynamics of NF-kB inhibitors: rationale insights from in silico and in vitro studies

Increased expression of target genes that code for proinflammatory chemical mediators results from a series of intracellular cascades triggered by activation of dysregulated NF-κB signaling pathway. Dysfunctional NF-kB signaling amplifies and perpetuates autoimmune responses in inflammatory diseases, including psoriasis. This study aimed to identify therapeutically relevant NF-kB inhibitors and elucidate the mechanistic aspects behind NF-kB inhibition. After virtual screening and molecular docking, five hit NF-kB inhibitors opted, and their therapeutic efficacy was examined using cell-based assays in TNF-α stimulated human keratinocyte cells. To investigate the conformational changes of target protein and inhibitor-protein interaction mechanisms, molecular dynamics (MD) simulations, binding free energy calculations together with principal component (PC) analysis, dynamics cross-correlation matrix analysis (DCCM), free energy landscape (FEL) analysis and quantum mechanical calculations were carried out. Among identified NF-kB inhibitors, myricetin and hesperidin significantly scavenged intracellular ROS and inhibited NF-kB activation. Analysis of the MD simulation trajectories of ligand-protein complexes revealed that myricetin and hesperidin formed energetically stabilized complexes with the target protein and were able to lock NF-kB in a closed conformation. Myricetin and hesperidin binding to the target protein significantly impacted conformational changes and internal dynamics of amino acid residues in protein domains. Tyr57, Glu60, Lys144 and Asp239 residues majorly contributed to locking the NF-kB in a closed conformation. The combinatorial approach employing in silico tools integrated with cell-based approaches substantiated the binding mechanism and NF-kB active site inhibition by the lead molecule myricetin, which can be explored as a viable antipsoriatic drug candidate associated with dysregulated NF-kB.Communicated by Ramaswamy H. Sarma.

Conformational States of the GDP- and GTP-Bound HRAS Affected by A59E and K117R: An Exploration from Gaussian Accelerated Molecular Dynamics

The HRAS protein is considered a critical target for drug development in cancers. It is vital for effective drug development to understand the effects of mutations on the binding of GTP and GDP to HRAS. We conducted Gaussian accelerated molecular dynamics (GaMD) simulations and free energy landscape (FEL) calculations to investigate the impacts of two mutations (A59E and K117R) on GTP and GDP binding and the conformational states of the switch domain. Our findings demonstrate that these mutations not only modify the flexibility of the switch domains, but also affect the correlated motions of these domains. Furthermore, the mutations significantly disrupt the dynamic behavior of the switch domains, leading to a conformational change in HRAS. Additionally, these mutations significantly impact the switch domain's interactions, including their hydrogen bonding with ligands and electrostatic interactions with magnesium ions. Since the switch domains are crucial for the binding of HRAS to effectors, any alterations in their interactions or conformational states will undoubtedly disrupt the activity of HRAS. This research provides valuable information for the design of drugs targeting HRAS.

DON/DRP-104 as potent serine protease inhibitors implicated in SARS-CoV-2 infection: Comparative binding modes with human TMPRSS2 and novel therapeutic approach

Human transmembrane serine protease 2 (TMPRSS2) is an important member of the type 2 transmembrane serine protease (TTSP) family with significant therapeutic markings. The search for potent TMPRSS2 inhibitors against severe acute respiratory syndrome coronavirus 2 infection with favorable tissue specificity and off-site toxicity profiles remains limited. Therefore, probing the anti-TMPRSS2 potential of enhanced drug delivery systems, such as nanotechnology and prodrug systems, has become compelling. We report the first in silico study of TMPRSS2 against a prodrug, [isopropyl(S)-2-((S)-2-acetamido-3-(1H-indol-3-yl)-propanamido)-6-diazo-5-oxo-hexanoate] also known as DRP-104 synthesized from 6-Diazo-5-oxo-l-norleucine (DON). We performed comparative studies on DON and DRP-104 against a clinically potent TMPRSS2 inhibitor, nafamostat, and a standard serine protease inhibitor, 4-(2-Aminoethyl) benzenesulfonyl fluoride (AEBSF) against TMPRSS2 and found improved TMPRSS2 inhibition through synergistic binding of the S1/S1' subdomains. Both DON and DRP-104 had better thermodynamic profiles than AEBSF and nafamostat. DON was found to confer structural stability with strong positive correlated inter-residue motions, whereas DRP-104 was found to confer kinetic stability with restricted residue displacements and reduced loop flexibility. Interestingly, the Scavenger Receptor Cysteine-Rich (SRCR) domain of TMPRSS2 may be involved in its inhibition mechanics. Two previously unidentified loops, designated X (270-275) and Y (293-296) underwent minimal and major structural transitions, respectively. In addition, residues 273-277 consistently transitioned to a turn conformation in all ligated systems, whereas unique transitions were identified for other transitioning residue groups in each TMPRSS2-inhibitor complex. Intriguingly, while both DON and DRP-104 showed similar loop transition patterns, DRP-104 preserved loop structural integrity. As evident from our systematic comparative study using experimentally/clinically validated inhibitors, DRP-104 may serve as a potent and novel TMPRSS2 inhibitor and warrants further clinical investigation.

Identification of potential inhibitor against CTX-M-3 and CTX-M-15 proteins: an in silico and in vitro study

Extended-spectrum beta-lactamase (ESBL) producing Enterobacteriaceae infection is a serious global threat. ESBLs target 3rd generation cephalosporin antibiotics, the most commonly prescribed medicine for gram-negative bacterial infections. As bacteria are prone to develop resistance against market-available ESBL inhibitors, finding a novel and effective inhibitor has become mandatory. Among ESBL, the worldwide reported two enzymes, CTX-M-15 and CTX-M-3, are selected for the present study. CTX-M-3 protein was modeled, and two thousand phyto-compounds were virtually screened against both proteins. After filtering through docking and pharmacokinetic properties, four phyto-compounds (catechin gallate, silibinin, luteolin, uvaol) were further selected for intermolecular contact analysis and molecular dynamics (MD) simulation. MD trajectory analysis results were compared, revealing that both catechin gallate and silibinin had a stabilizing effect against both proteins. Silibinin having the lowest docking score, also displayed the lowest MIC (128 µg/mL) against the bacterial strains. Silibinin was also reported to have synergistic activity with cefotaxime and proved to have bactericidal effect. Nitrocefin assay confirmed that silibinin could inhibit beta-lactamase enzyme only in living cells, unlike clavulanic acid. Thus the present study validated the CTX-M inhibitory activity of silibinin both in silico and in vitro and suggested its promotion for further studies as a potential lead. The present study adopted a protocol through the culmination of bioinformatics and microbiological analyses, which will help future researchers identify more potential leads and design new effective drugs.Communicated by Ramaswamy H. Sarma.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

Computational analysis of potential drug-like compounds from Solanum torvum - A promising phytotherapeutics approach for the treatment of diabetes

Diabetes mellitus (DM) is a global pandemic that is characterized by high blood glucose levels. Conventional treatments have limitations, leading to the search for natural alternatives. This study focused on Solanum torvum (STV), a medicinal plant, to identify potential anti-diabetic compounds using molecular docking and molecular dynamics simulations. We focused on identifying natural inhibitors of two key enzymes involved in glucose metabolism: α-amylase (1HNY) and α-glucosidase (4J5T). In our preliminary docking study, rutin showed the highest binding affinity (-11.58 kcal/mol) to α-amylase, followed by chlorogenin (-7.58 kcal/mol) and myricetin (-5.82 kcal/mol). For α-glucosidase, rutin had the highest binding affinity (-11.78 kcal/mol), followed by chlorogenin (-7.11 kcal/mol) and fisetin (-6.44 kcal/mol). Hence, chlorogenin and rutin were selected for further analysis and compared with acarbose, an FDA-approved antidiabetic drug. Comparative docking revealed that chlorogenin had the highest binding affinity of (-9.9 kcal/mol) > rutin (-8.7 kcal/mol) and > acarbose (-7.7 kcal/mol) for α-amylase. While docking with α-glucosidase, chlorogenin again had the highest binding affinity of (-9.8 kcal/mol) > compared to rutin (-9.5 kcal/mol) and acarbose (-7.9 kcal/mol). Molecular dynamics (MD) simulations were conducted to assess their stability. We simulated 100 nanoseconds (ns) trajectories to analyze their stability on various parameters, including RMSD, RMSF, RG, SASA, H-bond analysis, PCA, FEL, and MM-PBSA on the six docked proteins. In conclusion, our study suggests that chlorogenin and rutin derived from STV may be effective natural therapeutic agents for diabetes management because of their strong binding affinities for the α-amylase and α-glucosidase enzymes.Communicated by Ramaswamy H. Sarma.

Lipase A from Bacillus subtilis: Substrate Binding, Conformational Dynamics, and Signatures of a Lid

Protein-ligand binding studies are crucial for understanding the molecular basis of biological processes and for further advancing industrial biocatalysis and drug discovery. Using computational modeling and molecular dynamics simulations, we investigated the binding of a butyrate ester substrate to the lipase A (LipA) enzyme of Bacillus subtilis. Besides obtaining a close agreement of the binding free energy with the experimental value, the study reveals a remarkable reorganization of the catalytic triad upon substrate binding, leading to increased essential hydrogen bond populations. The investigation shows the distortion of the oxyanion hole in both the substrate-bound and unbound states of LipA and highlights the strengthening of the same in the tetrahedral intermediate complex. Principal component analysis of the unbound ensemble reveals the dominant motion in LipA to be the movement of Loop-1 (Tyr129-Arg142) between two states that cover and uncover the active site, mirroring that of a lid prevalent in several lipases. This lid-like motion of Loop-1 is also supported by its tendency to spontaneously open up at an oil-water interface. Overall, this study provides valuable insights into the impact of substrate binding on the structure, flexibility, and conformational dynamics of the LipA enzyme.

In silico design of a lipid-like compound targeting KRAS4B-G12D through non-covalent bonds

One of the most common drivers in human cancer is the peripheral membrane protein KRAS4B, able to promote oncogenic signalling. To signal, oncogenic KRAS4B not only requires a sufficient nucleotide exchange, but also needs to recruit effectors by exposing its effector-binding sites while anchoring to the phospholipid bilayer where KRAS4B-mediated signalling events occur. The enzyme phosphodiesterase-δ plays an important role in sequestering KRAS4B from the cytoplasm and targeting it to cellular membranes of different cell species. In this work, we present an in silico design of a lipid-like compound that has the remarkable feature of being able to target both an oncogenic KRAS4B-G12D mutant and the phosphodiesterase-δ enzyme. This double action is accomplished by adding a lipid tail (analogous to the farnesyl group of the KRAS4B protein) to an previously known active compound (2H-1,2,4-benzothiadiazine, 3,4-dihydro-,1,1-dioxide). The proposed lipid-like molecule was found to lock KRAS4B-G12D in its GDP-bound state by adjusting the effector-binding domain to be blocked by the interface of the lipid bilayer. Meanwhile, it can tune GTP-bound KRAS4B-G12D to shift from the active orientation state to the inactive state. The proposed compound is also observed to stably accommodate itself in the prenyl-binding pocket of phosphodiesterase-δ, which impairs KRAS4B enrichment at the lipid bilayer, potentially reducing the proliferation of KRAS4B inside the cytoplasm and its anchoring at the bilayer. In conclusion, we report a potential inhibitor of KRAS4B-G12D with a lipid tail attached to a specific warhead, a compound which has not yet been considered for drugs targeting RAS mutants. Our work provides new ways to target KRAS4B-G12D and can also foster drug discovery efforts for the targeting of oncogenes of the RAS family and beyond.

Screening Power of End-Point Free-Energy Calculations in Cucurbituril Host-Guest Systems

End-point free-energy methods as an indispensable component in virtual screening are commonly recognized as a tool with a certain level of screening power in pharmaceutical research. While a huge number of records could be found for end-point applications in protein-ligand, protein-protein, and protein-DNA complexes from academic and industrial reports, up to now, there is no large-scale benchmark in host-guest complexes supporting the screening power of end-point free-energy techniques. A good benchmark requires a data set of sufficient coverage of pharmaceutically relevant chemical space, a long-time sampling length supporting the trajectory approximation of the ensemble average, and a sufficient sample size of receptor-acceptor pairs to stabilize the performance statistics. In this work, selecting a popular family of macrocyclic hosts named cucurbiturils, we construct a large data set containing 154 host-guest pairs, perform extensive end-point sampling of several hundred nanosecond lengths for each system, and extract the free-energy estimates with a variety of end-point free-energy techniques, including the advanced three-trajectory dielectric-constant-variable regime proposed in our recent work. The best-performing end-point protocol employs GAFF2 for solute descriptions, the three-trajectory end-point sampling regime, and the MM/GBSA Hamiltonian in free-energy extraction, achieving a high ranking metrics of Kendall τ > 0.6, a Pearlman predictive index of ∼0.8, and a high scoring power of Pearson r > 0.8. The current project as the first large-scale systematic benchmark of end-point methods in host-guest complexes in academic publications provides solid evidence of the applicability of end-point techniques and direct guidance of computational setups in practical host-guest systems.

Beyond structural bioinformatics for genomics with dynamics characterization of an expanded KRAS mutational landscape

Current capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions. Because KRAS-altered tumors frequently harbor one of three classic hotspot mutations, nearly all studies have focused on these mutations, leaving significant functional ambiguity across the broader KRAS genomic landscape observed in cancer and non-cancer diseases. Herein, we extend structural bioinformatics with molecular simulations to study an expanded landscape of 86 KRAS mutations. We identify multiple coordinated changes strongly associated with experimentally established KRAS biophysical and biochemical properties. The patterns we observe span hotspot and non-hotspot alterations, which can all dysregulate Switch regions, producing mutation-restricted conformations with different effector binding propensities. We experimentally measured mutation thermostability and identified shared and distinct patterns with simulations. Our results indicate mutation-specific conformations, which show potential for future research into how these alterations reverberate into different molecular and cellular functions. The data we present is not predictable using current genomic tools, demonstrating the added functional information derived from molecular simulations for interpreting human genetic variation.

Molecular Dynamics Simulations of the Human Ecto-5'-Nucleotidase (h-ecto-5'-NT, CD73): Insights into Protein Flexibility and Binding Site Dynamics

Human ecto-5'-nucleotidase (h-ecto-5'-NT, CD73) is a homodimeric Zn2+-binding metallophosphoesterase that hydrolyzes adenosine 5'-monophosphate (5'-AMP) to adenosine and phosphate. h-Ecto-5'-NT is a key enzyme in purinergic signaling pathways and has been recognized as a promising biological target for several diseases, including cancer and inflammatory, infectious, and autoimmune diseases. Despite its importance as a biological target, little is known about h-ecto-5'-NT dynamics, which poses a considerable challenge to the design of inhibitors of this target enzyme. Here, to explore h-ecto-5'-NT flexibility, all-atom unbiased molecular dynamics (MD) simulations were performed. Remarkable differences in the dynamics of the open (catalytically inactive) and closed (catalytically active) conformations of the apo-h-ecto-5'-NT were observed during the simulations, and the nucleotide analogue inhibitor AMPCP was shown to stabilize the protein structure in the closed conformation. Our results suggest that the large and complex domain motion that enables the h-ecto-5'-NT open/closed conformational switch is slow, and therefore, it could not be completely captured within the time scale of our simulations. Nonetheless, we were able to explore the faster dynamics of the h-ecto-5'-NT substrate binding site, which is mainly located at the C-terminal domain and well conserved among the protein's open and closed conformations. Using the TRAPP ("Transient Pockets in Proteins") approach, we identified transient subpockets close to the substrate binding site. Finally, conformational states of the substrate binding site with higher druggability scores than the crystal structure were identified. In summary, our study provides valuable insights into h-ecto-5'-NT structural flexibility, which can guide the structure-based design of novel h-ecto-5'-NT inhibitors.

Binding Mechanism of Inhibitors to Heat Shock Protein 90 Investigated by Multiple Independent Molecular Dynamics Simulations and Prediction of Binding Free Energy

The heat shock protein (HSP90) has been an import target of drug design in the treatment of human disease. An exploration of the conformational changes in HSP90 can provide useful information for the development of efficient inhibitors targeting HSP90. In this work, multiple independent all-atom molecular dynamics (AAMD) simulations followed by calculations of the molecular mechanics generalized Born surface area (MM-GBSA) were performed to explore the binding mechanism of three inhibitors (W8Y, W8V, and W8S) to HSP90. The dynamics analyses verified that the presence of inhibitors impacts the structural flexibility, correlated movements, and dynamics behavior of HSP90. The results of the MM-GBSA calculations suggest that the selection of GB models and empirical parameters has important influences on the predicted results and verify that van der Waals interactions are the main forces that determine inhibitor-HSP90 binding. The contributions of separate residues to the inhibitor-HSP90 binding process indicate that hydrogen-bonding interactions (HBIs) and hydrophobic interactions play important roles in HSP90-inhibitor identifications. Moreover, residues L34, N37, D40, A41, D79, I82, G83, M84, F124, and T171 are recognized as hot spots of inhibitor-HSP90 binding and provide significant target sites of for the design of drugs related to HSP90. This study aims to contribute to the development of efficient inhibitors that target HSP90 by providing an energy-based and theoretical foundation.

Identification Mechanism of BACE1 on Inhibitors Probed by Using Multiple Separate Molecular Dynamics Simulations and Comparative Calculations of Binding Free Energies

β-amyloid cleaving enzyme 1 (BACE1) is regarded as an important target of drug design toward the treatment of Alzheimer's disease (AD). In this study, three separate molecular dynamics (MD) simulations and calculations of binding free energies were carried out to comparatively determine the identification mechanism of BACE1 for three inhibitors, 60W, 954 and 60X. The analyses of MD trajectories indicated that the presence of three inhibitors influences the structural stability, flexibility and internal dynamics of BACE1. Binding free energies calculated by using solvated interaction energy (SIE) and molecular mechanics generalized Born surface area (MM-GBSA) methods reveal that the hydrophobic interactions provide decisive forces for inhibitor-BACE1 binding. The calculations of residue-based free energy decomposition suggest that the sidechains of residues L91, D93, S96, V130, Q134, W137, F169 and I179 play key roles in inhibitor-BACE1 binding, which provides a direction for future drug design toward the treatment of AD.

Accelerating therapeutic protein design with computational approaches toward the clinical stage

Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.

Multiple Strategies to Develop Small Molecular KRAS Directly Bound Inhibitors

KRAS gene mutation is widespread in tumors and plays an important role in various malignancies. Targeting KRAS mutations is regarded as the "holy grail" of targeted cancer therapies. Recently, multiple strategies, including covalent binding strategy, targeted protein degradation strategy, targeting protein and protein interaction strategy, salt bridge strategy, and multivalent strategy, have been adopted to develop KRAS direct inhibitors for anti-cancer therapy. Various KRAS-directed inhibitors have been developed, including the FDA-approved drugs sotorasib and adagrasib, KRAS-G12D inhibitor MRTX1133, and KRAS-G12V inhibitor JAB-23000, etc. The different strategies greatly promote the development of KRAS inhibitors. Herein, the strategies are summarized, which would shed light on the drug discovery for both KRAS and other "undruggable" targets.

Identification of novel peptide inhibitors for oncogenic KRAS G12D as therapeutic options using mutagenesis-based remodeling and MD simulations

The Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) serves as a molecular switch, cycling between guanosine triphosphate (GTP)-bound and inactive guanosine diphosphate (GDP)-bound states. KRAS modulates numerous signal transduction pathways including the conventional RAF-MEK-ERK pathway. Mutations in the RAS genes have been linked to the formation of malignant tumors. Human malignancies typically show mutations in the Ras gene including HRAS, KRAS, and NRAS. Among all the mutations in exon 12 and exon 13 of the KRAS gene, the G12D mutation is more prevalent in pancreatic and lung cancer and accounts for around 41% of all G12 mutations, making them potential anticancer therapeutic targets. The present study is aimed at repurposing the peptide inhibitor KD2 of the KRAS G12D mutant. We employed an in-silico mutagenesis approach to design novel peptide inhibitors from the experimentally reported peptide inhibitor, and it was found that substitutions (N8W, N8I, and N8Y) might enhance the peptide's binding affinity toward the KRAS. Molecular dynamics simulations and binding energy calculations confirmed that the newly designed peptide inhibitors are stable and that their binding affinities are stronger as compared to the wild-type peptide. The detailed analysis revealed that newly designed peptides have the potential to inhibit KRAS/Raf interaction and the oncogenic signal of the KRAS G12D mutant. Our findings strongly suggest that these peptides should be tested and clinically validated to combat the oncogenic activity of KRAS.Communicated by Ramaswamy H. Sarma.

Impacts of Mutations in the P-Loop on Conformational Alterations of KRAS Investigated with Gaussian Accelerated Molecular Dynamics Simulations

G12 mutations heavily affect conformational transformation and activity of KRAS. In this study, Gaussian accelerated molecular dynamics (GaMD) simulations were performed on the GDP-bound wild-type (WT), G12A, G12D, and G12R KRAS to probe mutation-mediated impacts on conformational alterations of KRAS. The results indicate that three G12 mutations obviously affect the structural flexibility and internal dynamics of the switch domains. The analyses of the free energy landscapes (FELs) suggest that three G12 mutations induce more conformational states of KRAS and lead to more disordered switch domains. The principal component analysis shows that three G12 mutations change concerted motions and dynamics behavior of the switch domains. The switch domains mostly overlap with the binding region of KRAS to its effectors. Thus, the high disorder states and concerted motion changes of the switch domains induced by G12 mutations affect the activity of KRAS. The analysis of interaction network of GDP with KRAS signifies that the instability in the interactions of GDP and magnesium ion with the switch domain SW1 drives the high disordered state of the switch domains. This work is expected to provide theoretical aids for understanding the function of KRAS.

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

BRD9 and TAF1(2) have been regarded as significant targets of drug design for clinically treating acute myeloid leukemia, malignancies, and inflammatory diseases. In this study, multiple short molecular dynamics simulations combined with the molecular mechanics generalized Born surface area method were employed to investigate the binding selectivity of three ligands, 67B, 67C, and 69G, to BRD9/TAF1(2) with IC50 values of 230/59 nM, 1400/46 nM, and 160/410 nM, respectively. The computed binding free energies from the MM-GBSA method displayed good correlations with that provided by the experimental data. The results indicate that the enthalpic contributions played a critical factor in the selectivity recognition of inhibitors toward BRD9 and TAF1(2), indicating that 67B and 67C could more favorably bind to TAF1(2) than BRD9, while 69G had better selectivity toward BRD9 over TAF1(2). In addition, the residue-based free energy decomposition approach was adopted to calculate the inhibitor–residue interaction spectrum, and the results determined the gatekeeper (Y106 in BRD9 and Y1589 in TAF1(2)) and lipophilic shelf (G43, F44, and F45 in BRD9 and W1526, P1527, and F1528 in TAF1(2)), which could be identified as hotspots for designing efficient selective inhibitors toward BRD9 and TAF1(2). This work is also expected to provide significant theoretical guidance and insightful molecular mechanisms for the rational designs of efficient selective inhibitors targeting BRD9 and TAF1(2).

Classification of GTP-dependent K-Ras4B active and inactive conformational states

Classifying reliably active and inactive molecular conformations of wildtype (WT) and mutated oncogenic proteins is a key, ongoing challenge in molecular cancer studies. Here, we probe the GTP-bound K-Ras4B conformational dynamics using long-time atomistic molecular dynamics (MD) simulations. We extract and analyze the detailed underlying free energy landscape of WT K-Ras4B. We use two key reaction coordinates, labeled d₁ and d₂ (i.e., distances coordinating the P_β atom of the GTP ligand with two key residues, T35 and G60), shown to correlate closely with activities of WT and mutated K-Ras4B. However, our new K-Ras4B conformational kinetics study reveals a more complex network of equilibrium Markovian states. We show that a new reaction coordinate is required to account for the orientation of acidic K-Ras4B sidechains such as D38 with respect to the interface with binding effector RAF1 and rationalize the activation/inactivation propensities and the corresponding molecular binding mechanisms. We use this understanding to unveil how a relatively conservative mutation (i.e., D33E, in the switch I region) can lead to significantly different activation propensities compared with WT K-Ras4B. Our study sheds new light on the ability of residues near the K-Ras4B-RAF1 interface to modulate the network of salt bridges at the binding interface with the RAF1 downstream effector and, thus, to influence the underlying GTP-dependent activation/inactivation mechanism. Altogether, our hybrid MD-docking modeling approach enables the development of new in silico methods for quantitative assessment of activation propensity changes (e.g., due to mutations or local binding environment). It also unveils the underlying molecular mechanisms and facilitates the rational design of new cancer drugs.

Probing the E1o-E2o and E1a-E2o Interactions in Binary Subcomplexes of the Human 2-Oxoglutarate Dehydrogenase and 2-Oxoadipate Dehydrogenase Complexes by Chemical Cross-Linking Mass Spectrometry and Molecular Dynamics Simulation

The human 2-oxoglutarate dehydrogenase complex (hOGDHc) is a key enzyme in the tricarboxylic acid cycle and is one of the main regulators of mitochondrial metabolism through NADH and reactive oxygen species levels. Evidence was obtained for formation of a hybrid complex between the hOGDHc and its homologue the 2-oxoadipate dehydrogenase complex (hOADHc) in the L-lysine metabolic pathway, suggesting a crosstalk between the two distinct pathways. Findings raised fundamental questions about the assembly of hE1a (2-oxoadipate-dependent E1 component) and hE1o (2-oxoglutarate-dependent E1) to the common hE2o core component. Here we report chemical cross-linking mass spectrometry (CL-MS) and molecular dynamics (MD) simulation analyses to understand assembly in binary subcomplexes. The CL-MS studies revealed the most prominent loci for hE1o-hE2o and hE1a-hE2o interactions and suggested different binding modes. The MD simulation studies led to the following conclusions: (i) The N-terminal regions in E1s are shielded by, but do not interact directly with hE2o. (ii) The hE2o linker region exhibits the highest number of H-bonds with the N-terminus and α/β1 helix of hE1o, yet with the interdomain linker and α/β1 helix of hE1a. (iii) The C-termini are involved in dynamic interactions in complexes, suggesting the presence of at least two conformations in solution.

Identification of potent EGFR-TKD inhibitors from NPACT database through combined computational approaches

Cancer is the world's second leading cause of death, and there are no approved herbal therapies. The epidermal growth factor receptor tyrosine kinase (EGFR-TK) receptor is a transmembrane protein with eight domains that is found in almost every cancer type and plays an important role in abnormal cell cellular function and causes malignant outcomes. The current study aimed to virtually screen phytochemicals from the NPACT database against EGFR-TKD and also to identify potential inhibitors of this transmembrane protein among plant candidates for anticancer drug development. The docking scores of the chosen phytochemicals were compared with the control (erlotinib). Kurarinone, (2S)-2-methoxykurarnione, and Sophoraflavanone-G exhibited a stronger binding affinity of -18.102 kcal/mol, -14.243 kcal/mol, and -13.759 kcal/mol than erlotinib -12.783 kcal/mol. Moreover, several online search engines were used to predict ADME and toxicity. The drug-likeness of selected phytochemicals was higher than the reference (erlotinib). A 100 ns molecular dynamic (MD) simulation was also applied to the docked conformations to examine the stability and molecular mechanics of protein-ligand interactions. Furthermore, the calculated molecular mechanics Poisson Boltzmann surface area energy of (2S)-2-methoxykurarnione was found to be -129.555 ± 0.512 kJ/mol, which approximately corresponds to the free energy of the reference molecule -130.595 ± 0.908 kJ/mol. We identify phytoconstituents present in Sophora flavescens from the NPACT database, providing key insights into tyrosine kinase inhibition and may serve as better chemotherapeutic agents. Experimental validation is required to determine the anti-EGFR potency of the potent lead molecules discussed in this study.Communicated by Ramaswamy H. Sarma.

Dynamic regulation of RAS and RAS signaling

RAS proteins regulate most aspects of cellular physiology. They are mutated in 30% of human cancers and 4% of developmental disorders termed Rasopathies. They cycle between active GTP-bound and inactive GDP-bound states. When active, they can interact with a wide range of effectors that control fundamental biochemical and biological processes. Emerging evidence suggests that RAS proteins are not simple on/off switches but sophisticated information processing devices that compute cell fate decisions by integrating external and internal cues. A critical component of this compute function is the dynamic regulation of RAS activation and downstream signaling that allows RAS to produce a rich and nuanced spectrum of biological outputs. We discuss recent findings how the dynamics of RAS and its downstream signaling is regulated. Starting from the structural and biochemical properties of wild-type and mutant RAS proteins and their activation cycle, we examine higher molecular assemblies, effector interactions and downstream signaling outputs, all under the aspect of dynamic regulation. We also consider how computational and mathematical modeling approaches contribute to analyze and understand the pleiotropic functions of RAS in health and disease.

Molecular Modelling of Ionic Liquids: Situations When Charge Scaling Seems Insufficient

Charge scaling as an effective solution to the experiment-computation disagreement in molecular modelling of ionic liquids (ILs) could bring the computational results close to the experimental reference for various thermodynamic properties. According to the large-scale benchmark calculations of mass density, solvation, and water-ILs transfer-free energies in our series of papers, the charge-scaling factor of 0.8 serves as a near-optimal option generally applicable to most ILs, although a system-dependent parameter adjustment could be attempted for further improved performance. However, there are situations in which such a charge-scaling treatment would fail. Namely, charge scaling cannot really affect the simulation outcome, or minimally perturbs the results that are still far from the experimental value. In such situations, the vdW radius as an additional adjustable parameter is commonly tuned to minimize the experiment-calculation deviation. In the current work, considering two ILs from the quinuclidinium family, we investigate the impacts of this vdW-scaling treatment on the mass density and the solvation/partition thermodynamics in a fashion similar to our previous charge-scaling works, i.e., scanning the vdW-scaling factor and computing physical properties under these parameter sets. It is observed that the mass density exhibits a linear response to the vdW-scaling factor with slopes close to -1.8 g/mL. By further investigating a set of physiochemically relevant temperatures between 288 K and 348 K, we confirm the robustness of the vdW-scaling treatment in the estimation of bulk properties. The best vdW-scaling parameter for mass density would worsen the computation of solvation/partition thermodynamics, and a marginal decrease in the vdW-scaling factor is considered as an intermediate option balancing the reproductions of bulk properties and solvation thermodynamics. These observations could be understood in a way similar to the charge-scaling situation. i.e., overfitting some properties (e.g., mass density) would degrade the accuracy of the other properties (e.g., solvation free energies). Following this principle, the general guideline for applying this vdW-tuning protocol is by using values between the density-derived choice and the solvation/partition-derived solution. The charge and current vdW scaling treatments cover commonly encountered ILs, completing the protocol for accurate modelling of ILs with fixed-charge force fields.

Exploring the state- and allele-specific conformational landscapes of Ras: understanding their respective druggabilities

Recent advances in direct inhibition of Ras benefit from the protein's intrinsic dynamic nature that derives therapeutically vulnerable conformers bearing transiently formed cryptic pockets. Hotspot mutants of Ras are major tumor drivers and are hyperactivated in cells at variable levels, which may require allele-specific strategies for effective targeting. However, it remains unclear how the prevalent oncogenic mutations and activation states perturb the free energy landscape governing the protein dynamics and druggability. Here we characterized the nucleotide state- and allele-dependent alterations of Ras conformational dynamics using a combined NMR experimental and computational approach and constructed quantitative ensembles revealing the conservation of the cryptic SI/II-P and SII-P pockets in different states and alleles. Highly local but critical conformational reorganizations that undermine the SII-P accessibility to residue 12 have been identified as a common mechanism resulting in the low reactivities of Ras·GTP as well as Ras(G12D)·GDP with covalent SII-P inhibitors. Our results strongly support the conformational selection scenario for interactions between Ras and the previously reported binders and offer insights for the future development of state- and allele-specific, as well as pan-Ras, inhibitors.

Molecular basis of ssDNA recognition by RBM45 protein of neurodegenerative disease from multiple molecular dynamics simulations and energy predictions

Neurodegenerative diseases (NDD) are a group of cognitive and behavioral disorders characterized by progressive loss of neuronal structure and function. As the population ages, the incidence is getting higher and higher, but there is currently no effective treatment. The details of RNA/DNA recognition by the RNA-binding protein RBM45 closely related to neurodegenerative diseases through its two tandem RNA-recognition domains at its N-terminus have important implications for structure-based drug discovery against degenerative diseases. To explore the key characteristics of interaction between ssDNA and RBM45, we performed multiple molecular dynamics (MD) simulations along with MM-PBSA energy prediction on the complexes of wild type (WT) and three mutant RBM45s (K100A, F124A/Y165A, and F29A/F70A/F124A/Y165A) with ssDNA, respectively. The findings suggest that these mutated residues of RBM45 modify the interaction of their surrounding residues with ssDNA, thereby affecting RBM45 protein binding to ssDNA. In contrast with WT RBM45 protein, variations in van der Waals and electrostatic interactions with ssDNA caused by these three RBM45 mutants are critical to affect binding between them. In addition, energy analysis showed that RBM45 is a specific ssDNA-binding protein. The results of our work provide valuable theoretical guidance for the design effective drugs of NDD.

Binding modes of GDP, GTP and GNP to NRAS deciphered by using Gaussian accelerated molecular dynamics simulations

Probing binding modes of GDP, GTP and GNP to NRAS are of significance for understanding the regulation mechanism on the activity of RAS proteins. Four separate Gaussian accelerated molecular dynamics (GaMD) simulations were performed on the apo, GDP-, GTP- and GNP-bound NRAS. Dynamics analyses suggest that binding of three ligands highly affects conformational states of the switch domains from NRAS, which disturbs binding of NRAS to its effectors. The analyses of free energy landscapes (FELs) indicate that binding of GDP, GTP and GNP induces more energetic states of NRAS compared to the apo NRAS but the presence of GNP makes the switch domains more ordered than binding of GDP and GNP. The information of interaction networks of ligands with NRAS reveals that the π-π interaction of residue F28 and the salt bridge interactions of K16 and D119 with ligands stabilize binding of GDP, GTP and GNP to NRAS. Meanwhile magnesium ion plays a bridge role in interactions of ligands with NRAS, which is favourable for associations of GDP, GTP and GNP with NRAS. This work is expected to provide useful information for deeply understanding the function and activity of NRAS.

Rational Discovery of Microtubule-Stabilizing Peptides

Microtubule (MT) stabilization is an attractive pharmacological strategy to hamper the progress of neurodegenerative diseases. In this regard, seeking peptides with MT-stabilizing properties has awoken great interest. This work reports the rational discovery of two structurally related MT-stabilizing octapeptides using a combination of protein-peptide docking, conventional molecular dynamics, Gaussian accelerated molecular dynamics (GaMD), and tubulin polymerization assays. FASTA sequences for ∼1000 peptides were crafted from single and double mutants of davunetide (NAP) and docked against the Taxol (TX) site on an octameric MT model representing a portion of the MT wall. Docked peptides were rescored after MM minimization and binding free energy refinement through single-point MM/GBSA calculations. The 60 best-ranked peptides were subjected to 50 ns MD simulations on peptide-MT complexes at the terminal TX site in the octameric Tau-MT model resulting in 11 complexes with occupancies greater than 99% and peptide-protein binding free energies less than -40 kcal/mol. Selected peptides were then examined through 300 ns GaMD simulations in complexes containing two identical ligands at the terminal and intermediate TX sites in the Tau-MT model to account for the differential association of MT-binding peptides to different regions of the MT structure. Six candidates showed a favorable MT-binding potential based on the analysis of interaction frequencies and relative mobilities of the complex components, suggesting a pivotal role of Arg278, Gln281, and Arg369 residues for peptides recognition. Four candidates were predicted to preserve an adequate balance of longitudinal and lateral interactions between tubulin dimers in peptide-MT complexes such that MT-stabilizing effects could be expected. MT polymerization experiments confirmed that four peptides (HAPVSIHQ, NYPVSIHQ, NWPVSIWQ, HAPVSIIQ) exhibit MT-stabilizing activity in vitro with NWPVSIWQ (P43) and HAPVSIIQ (P52) being the most active. Tryptophan quenching assays verified that P43 and P52 bind to nonpolymeric tubulin, whereas viability experiments on HEK cells confirmed their safety to pursue future pharmacological studies. The results herein presented are valuable to making progress in the rational design of MT-stabilizing peptides.

Decoding the Identification Mechanism of an SAM-III Riboswitch on Ligands through Multiple Independent Gaussian-Accelerated Molecular Dynamics Simulations

S-Adenosyl-l-methionine (SAM)-responsive riboswitches play a central role in the regulation of bacterial gene expression at the level of transcription attenuation or translation inhibition. In this study, multiple independent Gaussian-accelerated molecular dynamics simulations were performed to decipher the identification mechanisms of SAM-III (S_MK) on ligands SAM, SAH, and EEM. The results reveal that ligand binding highly affects the structural flexibility, internal dynamics, and conformational changes of SAM-III. The dynamic analysis shows that helices P3 and P4 as well as two junctions J23 and J24 of SAM-III are highly susceptible to ligand binding. Analyses of free energy landscapes suggest that ligand binding induces different free energy profiles of SAM-III, which leads to the difference in identification sites of SAM-III on ligands. The information on ligand-nucleotide interactions not only uncovers that the π-π, cation-π, and hydrogen bonding interactions drive identification of SAM-III on the three ligands but also reveals that different electrostatic properties of SAM, SAH, and EEM alter the active sites of SAM-III. Meanwhile, the results also verify that the adenine group of SAM, SAH, and EEM is well recognized by conserved nucleotides G7, A29, U37, A38, and G48. We expect that this study can provide useful information for understanding the applications of SAM-III in chemical, synthetic RNA biology, and biomedical fields.

Investigating the Dynamic Binding Behavior of PMX53 Cooperating with Allosteric Antagonist NDT9513727 to C5a Anaphylatoxin Chemotactic Receptor 1 through Gaussian Accelerated Molecular Dynamics and Free-Energy Perturbation Simulations

C5a anaphylatoxin chemotactic receptor 1 (C5aR1) is an important target in anti-inflammatory therapeutics. The cyclic peptide antagonist PMX53 binds to the orthosteric site located in the extracellular vestibule of C5aR1, and the non-peptide antagonist NDT9513727 binds to the allosteric site formed by the middle region of TM3 (trans-membrane helix), TM4, and TM5. We catch a sight of the variational binding mode of PMX53 during the Gaussian accelerated molecular dynamic (GaMD) simulations. In the binary complex of C5aR1 and PMX53, the PMX53 takes a dynamic binding mechanism during the simulation. Namely, the side chain of Arg⁶ of PMX53 extends to TM6-TM7 (pose 1) or swings to TM5 (pose 2), forming a salt bridge with Glu199. Meanwhile, in the ternary complex of C5aR1 with PMX53 and NDT9513727, the side chain of Arg⁶ of PMX53 swings to TM5 (pose 2) from extending to TM6-TM7 (pose 1) at the beginning of the GaMD simulation. In subsequent simulation, PMX53 stabilizes in the pose 2 binding mode by forming a stable salt bridge with Glu199. The free-energy perturbation (FEP) calculations demonstrate that pose 1 (ΔG_binding = -10.94 kcal/mol) is more stable in the binary complex and pose 2 (ΔG_binding = -7.91 kcal/mol) is unstable because of highly dynamic TM5. NDT9513727 interacts directly with TM4 and TM5 and stabilizes the hydrophobic stack between the extracellular sides of the two helices. Therefore, pose 2 (ΔG_binding = -16.27 kcal/mol) is notably stable than pose 1 (ΔG_binding = -9.78 kcal/mol) in the ternary complex. The identification of a novel binding mode of PMX53 and the detailed structural information of PMX53 interacting with a receptor obtained by GaMD simulations will be helpful in designing potent antagonists of C5aR1.

Discovering and Targeting Dynamic Drugging Pockets of Oncogenic Proteins: The Role of Magnesium in Conformational Changes of the G12D Mutated Kirsten Rat Sarcoma-Guanosine Diphosphate Complex

KRAS-G12D mutations are the one of most frequent oncogenic drivers in human cancers. Unfortunately, no therapeutic agent directly targeting KRAS-G12D has been clinically approved yet, with such mutated species remaining undrugged. Notably, cofactor Mg2+ is closely related to the function of small GTPases, but no investigation has been conducted yet on Mg2+ when associated with KRAS. Herein, through microsecond scale molecular dynamics simulations, we found that Mg2+ plays a crucial role in the conformational changes of the KRAS-GDP complex. We located two brand new druggable dynamic pockets exclusive to KRAS-G12D. Using the structural characteristics of these two dynamic pockets, we designed in silico the inhibitor DBD15-21-22, which can specifically and tightly target the KRAS-G12D-GDP-Mg2+ ternary complex. Overall, we provide two brand new druggable pockets located on KRAS-G12D and suitable strategies for its inhibition.

IL-2 Flexible Loops Might Play a Role in IL-2 Interaction with the High-Affinity IL-2 Receptor: A Molecular Dynamics (MD) Study

The clinical use of high-dose IL-2 in cancer immunotherapy faces several drawbacks such as toxicity and unfavorable pharmacokinetic profile. These drawbacks can be avoided by inhibiting IL-2 interaction with the CD25 subunit, which is a component of the high-affinity IL-2 receptor (IL-2Rαβγ). Several studies showed mutations of potential IL-2 residues such as R38, F42, Y45, and Y72 would produce IL-2 that is CD25-independent. In essence, structural comparison between wild-type (WT) IL-2 and CD25-independent IL-2 can be very insightful to assess the role of IL-2 flexibility and conformation in the IL-2 receptor interactions. Here, we investigated the flexibility loops and conformation of IL-2m (F24A, Y45A, and L72G), which is known to be CD25-independent, and IL-2m2 (F42Y and L72R) mutants along with WT IL-2 using MD simulations. Despite residue mutations, both IL-2m and IL-2m2 showed comparable conformational compactness and better stability than WT IL-2. Interestingly, IL-2m and IL-2m2 mutants showed rigid BC and CD loops in comparison to WT IL-2 . Also, the AB loop conformation of IL-2m was a bent structure compared to the WT IL-2 and IL-2m2. Principal component analysis (PCA) and free-energy landscape results suggested IL-2m and IL-2m2 have stable conformations compared to the WT IL-2. Therefore, these mutation sites of IL-2 produced stable and rigid loops that might prevent IL-2 from binding to the CD25 subunit. Our results can help to assess IL-2 flexibility loops to design new CD25-independent IL-2 mutants without compromising the IL-2 structure.