Avoiding False Positive Conclusions in Molecular Simulation: The Importance of Replicas

Design, synthesis, computational study and cytotoxic evaluation of some new quinazoline derivatives containing pyrimidine moiety

Quinazoline derivatives, as an important category of heterocyclic compounds, have received much attention for the design and development of new drugs due to their various pharmacological properties. Besides, there is a great deal of evidence showing pyrimidine analogs as anticancer agents. Thus, in the present study, for the design of new target compounds with cytotoxic activity, we focused on various quinazolinone and pyrimidine hybrids. A new series of quinazoline-pyrimidine hybrid derivatives (6a-6n) have been designed and synthesized as novel antiproliferative agents. All the synthesized compounds characterized based on their IR, NMR and Mass spectroscopic data. Antiproliferative activities of the new compounds were evaluated against three human cancer cell lines (MCF-7, A549, SW-480). The compounds were found to have appropriate potential with IC50 values ranging from 2.3 ± 5.91 to 176.5 ± 0.7 μM against the tested cell lines. Compound 6n exerted the highest antiproliferative activity with IC50 values of 5.9 ± 1.69 μM, 2.3 ± 5.91 μM and 5.65 ± 2.33 μM against A549, SW-480 and MCF-7 respectively. The results indicated that 6n could induce apoptosis in A549 cell line in a dose dependent manner and arrest in the S phase of cell cycle. Docking studies were also done to investigate the detailed binding pattern of the synthesized compounds against EGFR. Furthermore, molecular dynamic simulation and binding free energy calculation have been done to rescore initial docking pose of the synthesized compounds using ensemble-based MMGB/PBSA free energy method. According to the results, free energy calculation confirmed biological activity of compounds and also, Arg 817 and Lys 721 residues had the pivotal role in the high potency of 6n. Finally, the drug likeness and in silico ADME study were also predicted.

3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors

Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features are computed to describe small molecules and proteins, which directly impact the quality of the predictive models. State-of-the-art protein descriptors, however, are calculated from the protein sequence and neglect the dynamic nature of proteins. This dynamic nature can be computationally simulated with molecular dynamics (MD). Here, novel 3D dynamic protein descriptors (3DDPDs) were designed to be applied in bioactivity prediction tasks with PCM models. As a test case, publicly available G protein-coupled receptor (GPCR) MD data from GPCRmd was used. GPCRs are membrane-bound proteins, which are activated by hormones and neurotransmitters, and constitute an important target family for drug discovery. GPCRs exist in different conformational states that allow the transmission of diverse signals and that can be modified by ligand interactions, among other factors. To translate the MD-encoded protein dynamics two types of 3DDPDs were considered: one-hot encoded residue-specific (rs) and embedding-like protein-specific (ps) 3DDPDs. The descriptors were developed by calculating distributions of trajectory coordinates and partial charges, applying dimensionality reduction, and subsequently condensing them into vectors per residue or protein, respectively. 3DDPDs were benchmarked on several PCM tasks against state-of-the-art non-dynamic protein descriptors. Our rs- and ps3DDPDs outperformed non-dynamic descriptors in regression tasks using a temporal split and showed comparable performance with a random split and in all classification tasks. Combinations of non-dynamic descriptors with 3DDPDs did not result in increased performance. Finally, the power of 3DDPDs to capture dynamic fluctuations in mutant GPCRs was explored. The results presented here show the potential of including protein dynamic information on machine learning tasks, specifically bioactivity prediction, and open opportunities for applications in drug discovery, including oncology.

Pentagalloyl Glucose-Targeted Inhibition of P-Glycoprotein and Re-Sensitization of Multidrug-Resistant Leukemic Cells (K562/ADR) to Doxorubicin: In Silico and Functional Studies

Combining phytochemicals with chemotherapeutic drugs has demonstrated the potential to surmount drug resistance. In this paper, we explore the efficacy of pentagalloyl glucose (PGG) in modulating P-gp and reversing multidrug resistance (MDR) in drug-resistant leukemic cells (K562/ADR). The cytotoxicity of PGG was evaluated using a CCK-8 assay, and cell apoptosis was assessed using flow cytometry. Western blotting was used to analyze protein expression levels. P-glycoprotein (P-gp) activity was evaluated by monitoring the kinetics of P-gp-mediated efflux of pirarubicin (THP). Finally, molecular docking, molecular dynamics simulation, and molecular mechanics with generalized Born and surface area solvation (MM-GBSA) calculation were conducted to investigate drug-protein interactions. We found that PGG selectively induced cytotoxicity in K562/ADR cells and enhanced sensitivity to doxorubicin (DOX), indicating its potential as a reversal agent. PGG reduced the expression of P-gp and its gene transcript levels. Additionally, PGG inhibited P-gp-mediated efflux and increased intracellular drug accumulation in drug-resistant cells. Molecular dynamics simulations and MM-GBSA calculation provided insights into the binding affinity of PGG to P-gp, suggesting that PGG binds tightly to both the substrate and the ATP binding sites of P-gp. These findings support the potential of PGG to target P-gp, reverse drug resistance, and enhance the efficacy of anticancer therapies.

Can Free Energy Perturbation Simulations Coupled with Replica-Exchange Molecular Dynamics Study Ligands with Distributed Binding Sites?

Free energy perturbation coupled with replica exchange with solute tempering (FEP/REST) offers a rigorous approach to compute relative free energy changes for ligands. To determine the applicability of FEP/REST for the ligands with distributed binding poses, we considered two alchemical transformations involving three putative inhibitors I0, I1, and I2 of the Venezuelan equine encephalitis virus nuclear localization signal sequence binding to the importin-α (impα) transporter protein. I0 → I1 and I0 → I2 transformations, respectively, increase or decrease the polarity of the parent molecule. Our objective was three-fold─(i) to verify FEP/REST technical performance and convergence, (ii) to estimate changes in binding free energy ΔΔG, and (iii) to determine the utility of FEP/REST simulations for conformational binding analysis. Our results are as follows. First, our FEP/REST implementation properly follows FEP/REST formalism and produces converged ΔΔG estimates. Due to ligand inherent unbinding, the better FEP/REST strategy lies in performing multiple independent trajectories rather than extending their length. Second, I0 → I1 and I0 → I2 transformations result in overall minor changes in inhibitor binding free energy, slightly strengthening the affinity of I1 and weakening that of I2. Electrostatic interactions dominate binding interactions, determining the enthalpic changes. The two transformations cause opposite entropic changes, which ultimately govern binding affinities. Importantly, we confirm the validity of FEP/REST free energy estimates by comparing them with our previous REST simulations, directly probing binding of three ligands to impα. Third, we established that FEP/REST simulations can sample binding ensembles of ligands. Thus, FEP/REST can be applied (i) to study the energetics of the ligand binding without defined poses and showing minor differences in affinities |ΔΔG| ≲ 0.5 kcal/mol and (ii) to collect ligand binding conformational ensembles.

A dynamic biomimetic model of the membrane-bound CD4-CD3-TCR complex during pMHC disengagement

The coordinated (dis)engagement of the membrane-bound T cell receptor (TCR)-CD3-CD4 complex from the peptide-major histocompatibility complex (pMHC) is fundamental to TCR signal transduction and T cell effector function. As such, an atomic-scale understanding would not only enhance our basic understanding of the adaptive immune response but would also accelerate the rational design of TCRs for immunotherapy. In this study, we explore the impact of the CD4 coreceptor on the TCR-pMHC (dis)engagement by constructing a molecular-level biomimetic model of the CD3-TCR-pMHC and CD4-CD3-TCR-pMHC complexes within a lipid bilayer. After allowing the system complexes to equilibrate (engage), we use steered molecular dynamics to dissociate (disengage) the pMHC. We find that 1) the CD4 confines the pMHC closer to the T cell by 1.8 nm at equilibrium; 2) CD4 confinement shifts the TCR along the MHC binding groove engaging a different set of amino acids and enhancing the TCR-pMHC bond lifetime; 3) the CD4 translocates under load increasing the interaction strength between the CD4-pMHC, CD4-TCR, and CD4-CD3; and 4) upon dissociation, the CD3-TCR complex undergoes structural oscillation and increased energetic fluctuation between the CD3-TCR and CD3-lipids. These atomic-level simulations provide mechanistic insight on how the CD4 coreceptor impacts TCR-pMHC (dis)engagement. More specifically, our results provide further support (enhanced bond lifetime) for a force-dependent kinetic proofreading model and identify an alternate set of amino acids in the TCR that dominate the TCR-pMHC interaction and could thus impact the design of TCRs for immunotherapy.

Analysis of the Distribution and Influencing Factors of Diffusion Coefficient Model Parameters Based on Molecular Dynamics Simulations

The establishment of mathematical models to predict the diffusion coefficients of gas and liquid systems have important theoretical significance and practical value. In this work, based on the previously proposed diffusion coefficient model D_LV, the distribution and influencing factors of the model parameters characteristic length (L) and diffusion velocity (V) were further investigated using molecular dynamics simulations. The statistical analysis of L and V for 10 gas systems and 10 liquid systems was presented in the paper. New distribution functions were established to describe the probability distributions of molecular motion L and V. The mean values of the correlation coefficients were 0.98 and 0.99, respectively. Meanwhile, the effects of molecular molar mass and system temperature on the molecular diffusion coefficients were discussed. The results show that the effect of molecular molar mass on the diffusion coefficient mainly affects the molecular motion L, and the effect of system temperature on the diffusion coefficient mainly affects V. For the gas system, the average relative deviation of D_LV and D_MSD is 10.73% and that of D_LV and experimental value is 12.63%; for the solution system, the average relative deviation of D_LV and D_MSD is 12.93% and that of D_LV and experimental value is 18.86%, which indicates the accuracy of the new model results. The new model reveals the potential mechanism of molecular motion and provides a theoretical basis for further study of the diffusion process.

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.

Multiscale models of integrins and cellular adhesions

Computational models of integrin-based adhesion complexes have revealed important insights into the mechanisms by which cells establish connections with their external environment. However, how changes in conformation and function of individual adhesion proteins regulate the dynamics of whole adhesion complexes remains largely elusive. This is because of the large separation in time and length scales between the dynamics of individual adhesion proteins (nanoseconds and nanometers) and the emergent dynamics of the whole adhesion complex (seconds and micrometers), and the limitations of molecular simulation approaches in extracting accurate free energies, conformational transitions, reaction mechanisms, and kinetic rates, that can inform mechanisms at the larger scales. In this review, we discuss models of integrin-based adhesion complexes and highlight their main findings regarding: (i) the conformational transitions of integrins at the molecular and macromolecular scales and (ii) the molecular clutch mechanism at the mesoscale. Lastly, we present unanswered questions in the field of modeling adhesions and propose new ideas for future exciting modeling opportunities.

All-Atom Simulations Reveal the Intricacies of Signal Transduction upon Binding of the HLA-E Ligand to the Transmembrane Inhibitory CD94/NKG2A Receptor

Natural killer (NK) cells play an important role in the innate immune response against tumors and various pathogens such as viruses and bacteria. Their function is controlled by a wide array of activating and inhibitory receptors, which are expressed on their cell surface. Among them is a dimeric NKG2A/CD94 inhibitory transmembrane (TM) receptor which specifically binds to the non-classical MHC I molecule HLA-E, which is often overexpressed on the surface of senescent and tumor cells. Using the Alphafold 2 artificial intelligence system, we constructed the missing segments of the NKG2A/CD94 receptor and generated its complete 3D structure comprising extracellular (EC), TM, and intracellular regions, which served as a starting point for the multi-microsecond all-atom molecular dynamics simulations of the receptor with and without the bound HLA-E ligand and its nonameric peptide. The simulated models revealed that an intricate interplay of events is taking place between the EC and TM regions ultimately affecting the intracellular immunoreceptor tyrosine-based inhibition motif (ITIM) regions that host the point at which the signal is transmitted further down the inhibitory signaling cascade. Signal transduction through the lipid bilayer was also coupled with the changes in the relative orientation of the NKG2A/CD94 TM helices in response to linker reorganization, mediated by fine-tuned interactions in the EC region of the receptor, taking place after HLA-E binding. This research provides atomistic details of the cells' protection mechanism against NK cells and broadens the knowledge regarding the TM signaling of ITIM-bearing receptors.

Deciphering the intrinsic dynamics of unphosphorylated IRAK4 kinase bound to type I and type II inhibitors

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a vital protein involved in Toll-like and interleukin-1 receptor signal transduction. Several studies have reported regarding the crystal structure, dynamic properties, and interactions with inhibitors of the phosphorylated form of IRAK4. However, no dynamic properties of inhibitor-bound unphosphorylated IRAK4 have been previously studied. Herein, we report the intrinsic dynamics of unphosphorylated IRAK4 (uIRAK4) bound to type I and type II inhibitors. The corresponding apo and inhibitor-bound forms of uIRAK4 were subjected to three independent simulations of 500 ns (total 1.5 μs) each, and their trajectories were analyzed. The results indicated that all three systems were relatively stable, except for the type II inhibitor-bound form of uIRAK4, which exhibited less compact folding and higher solvent surface area. The intra-hydrogen bonds corroborated the structural deformation of the type-II inhibitor-bound complex, which could be attributed to the long molecular structure of the type-II inhibitor. Moreover, the type II inhibitor bound to uIRAK4 showed higher binding free energy with uIRAK4 than the type I inhibitor. The free energy landscape analysis showed a reorientation of Phe330 side chain from the DFG motif at different metastable states for all the systems. The intra-residual distance between residues Lys213, Glu233, Tyr262, and Phe330 suggests a functional interplay when the inhibitors are bound to uIRAK4, thereby hinting at their crucial role in the inhibition mechanism. Ultimately, the intrinsic dynamics study observed between type I/II inhibitor-bound forms of uIRAK4 may assist in better understanding the enzyme and designing therapeutic compounds.

The nucleotide excision repair proteins through the lens of molecular dynamics simulations

Mutations that affect the proteins responsible for the nucleotide excision repair (NER) pathway can lead to diseases such as xeroderma pigmentosum, trichothiodystrophy, Cockayne syndrome, and Cerebro-oculo-facio-skeletal syndrome. Hence, understanding their molecular behavior is needed to elucidate these diseases' phenotypes and how the NER pathway is organized and coordinated. Molecular dynamics techniques enable the study of different protein conformations, adaptable to any research question, shedding light on the dynamics of biomolecules. However, as important as they are, molecular dynamics studies focused on DNA repair pathways are still becoming more widespread. Currently, there are no review articles compiling the advancements made in molecular dynamics approaches applied to NER and discussing: (i) how this technique is currently employed in the field of DNA repair, focusing on NER proteins; (ii) which technical setups are being employed, their strengths and limitations; (iii) which insights or information are they providing to understand the NER pathway or NER-associated proteins; (iv) which open questions would be suited for this technique to answer; and (v) where can we go from here. These questions become even more crucial considering the numerous 3D structures published regarding the NER pathway's proteins in recent years. In this work, we tackle each one of these questions, revising and critically discussing the results published in the context of the NER pathway.

Conformational and Thermodynamic Differences Underlying Wild-Type and Mutant Eleven-Nineteen-Leukemia YEATS Domain Specificity for Epigenetic Marks

Histone post-translational modifications (PTMs) are interpreted by multiple reader domains and proteins to regulate gene expression. The eleven-nineteen-leukemia (ENL) YEATS domain is a prototypical PTM reader that recognizes multiple lysine acetylation marks on the histone H3 tails as a way of recruiting chromatin remodellers. Two ENL YEATS mutations have been identified which have been linked with leukemia, Wilms tumor, and other forms of cancer and result in either an insertion or deletion of residues in the loop connecting beta sheets distant from the protein active site. In vitro experiments have shown that these mutations modulate the selectivities of YEATS domains for various lysine acetylation marks, although different experiments have provided contrasting views on the abilities of the insertion and deletion mutants to discern specific PTMs. Here, we have performed multiple molecular dynamics simulations of wild-type and insertion and deletion mutant YEATS domains free from and in complex with two PTM peptides: one that is acetylated at K9 of H3 and the other that is acetylated at residue K27 of H3. Results show that these two peptides have distinct flexibilities and binding energetics when bound to YEATS domains and that these properties are affected by interactions with residues within and outside of the peptide consensus motif. Furthermore, these properties are modulated by the YEATS insertion and deletion mutants, which results in disparate binding effects in these systems. Together, these results suggest that only the partial exposure of histone tails is sufficient in the context of nucleosomes for YEATS-mediated recognition of acetylation marks on histone tails. They also caution against the overinterpretation of results obtained from experiments on reader domain-histone peptide binding in isolation and not in the full-length nucleosome context.

Structural and energetic basis of interaction between human estrogen-related receptor γ and environmental endocrine disruptors from multiple molecular dynamics simulations and free energy predictions

Environmental endocrine disruptors (EEDs), a class of molecules that are widespread in our environment, may adversely affect the endocrine system. Exploring the interactions between these compounds and their potential targets is important for assessing their role in the organism. Focused on the human estrogen-related receptor γ (hERRγ) with BPA, BPB, HPTE, BPE, BP(2,2)(Et), and BP(2,2)(MeO) complexes, respectively, we groped for the mechanisms of conformational changes and interactions of hERRγ when binding to these six EEDs by combining multiple molecular dynamics (MD) simulations with energy prediction (MM-PBSA and solvated interaction energy (SIE)). Dynamics analysis results revealed these six EEDs have different effects on the internal dynamics of hERRγ, resulting in significant changes in the interaction of key residues around Leu268, Val313, Leu345, and Phe435 with EEDs, and thus affected its binding energy with these EEDs. The energy calculations further demonstrated that van der Waals interactions are critical for these EEDs binding to hERRγ. These results present detailed molecular insight into the interaction features between EEDs and hERRγ and help guide the search for safer alternatives to BPA.

In silico study of potential immunonutrient-based sports supplements against COVID-19 via targeting ACE2 inhibition using molecular docking and molecular dynamics simulations

Use of some sports supplements can inhibit angiotensin-converting enzyme II (ACE2), a receptor for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as reviewed through molecular docking and sequent molecular dynamics (MD) simulations against this condition. The crystal structures of ACE2 receptors of SARS-CoV-2 and SARS-CoV, applied in docking analysis, were taken from the Protein Data Bank (PDB). The receptors were then prepared using the Molecular Operating Environment (MOE), as a drug-discovery software platform for docking. Supplements such as quercetin and beta glucan (β-glucan) were the top docked compounds to ACE2 receptor though they strongly interacted with CoV target protein. The study data showed that immune responses to immunonutrient-based sports compounds (viz. quercetin and β-glucan) in Coronavirus disease 2019 (COVID-19) were essential in mounting successful immune responses by athletes. While awaiting the development of an effective vaccine, there is a need to focus on immunonutrient-based sports supplements as preventive and therapeutic options that can be implemented in a safe and quick manner to bolster immune responses in athletes.Communicated by Ramaswamy H. Sarma.

The nuclear receptor LRH-1 discriminates between ligands using distinct allosteric signaling circuits

Nuclear receptors (NRs) are transcription factors that regulate essential biological processes in response to cognate ligands. An important part of NR function involves ligand-induced conformational changes that recruit coregulator proteins to the activation function surface (AFS), ~15 Å away from the ligand binding pocket. Ligands must communicate with the AFS to recruit appropriate coregulators and elicit different transcriptional outcomes, but this communication is poorly understood. These studies illuminate allosteric communication networks underlying activation of liver receptor homolog-1 (LRH-1), a NR that regulates development, metabolism, cancer progression and intestinal inflammation. Using >100 microseconds of all-atom molecular dynamics simulations involving 69 LRH-1 complexes, we identify distinct signaling circuits used by active and inactive ligands for AFS communication. Inactive ligands communicate via strong, coordinated motions along paths through the receptor to the AFS. Activating ligands disrupt the "inactive" circuit by inducing connectivity elsewhere. Ligand-contacting residues in helix 7 help mediate the switch between circuits, suggesting new avenues for developing LRH-1-targeted therapeutics. We also elucidate aspects of coregulator signaling, showing that localized, destabilizing fluctuations are induced by inappropriate ligand-coregulator pairings. These studies have uncovered novel features of LRH-1 allostery, and the quantitative approach used to analyze many simulations provides a framework to study allosteric signaling in other receptors.

How do salt and lipids affect conformational dynamics of Aβ42 monomers in water?

It is well established that amyloid β-protein (Aβ) self-assembly is involved in triggering of Alzheimer's disease. On the other hand, evidence of physiological function of Aβ interacting with lipids has only begun to emerge. Details of Aβ-lipid interactions, which may underlie physiological and pathological activities of Aβ, are not well understood. Here, the effects of salt and 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipids on conformational dynamics of Aβ42 monomer in water are examined by all-atom molecular dynamics (MD). We acquired six sets of 250 ns long MD trajectories for each of the three lipid concentrations (0, 27, and 109 mM) in the absence and presence of 150 mM salt. Ten replica trajectories per set are used to enhance sampling of Aβ42 conformational space. We show that salt facilitates long-range tertiary contacts in Aβ42, resulting in more compact Aβ42 conformations. By contrast, addition of lipids results in lipid-concentration dependent Aβ42 unfolding concomitant with enhanced stability of the turn in the A21-A30 region. At the high lipid concentration, salt enables the N-terminal region of Aβ42 to form long-range tertiary contacts and interact with lipids, which results in formation of a parallel β-strand. Aβ42 forms stable lipid-protein complexes whereby the protein is adhered to the lipid cluster rather than embedded into it. We propose that the inability of Aβ42 monomer to get embedded into the lipid cluster may be important for facilitating repair of leaks in the blood-brain barrier without penetrating and damaging cellular membranes.

Identifying Systematic Force Field Errors Using a 3D-RISM Element Counting Correction

Hydration free energies of small molecules are commonly used as benchmarks for solvation models. However, errors in predicting hydration free energies are partially due to the force fields used and not just the solvation model. To address this, we have used the 3D reference interaction site model (3D-RISM) of molecular solvation and existing benchmark explicit solvent calculations with a simple element count correction (ECC) to identify problems with the non-bond parameters in the general AMBER force field (GAFF). 3D-RISM was used to calculate hydration free energies of all 642 molecules in the FreeSolv database, and a partial molar volume correction (PMVC), ECC, and their combination (PMVECC) were applied to the results. The PMVECC produced a mean unsigned error of 1.01±0.04kcal/mol and root mean squared error of 1.44±0.07kcal/mol, better than the benchmark explicit solvent calculations from FreeSolv, and required less than 15 s of computing time per molecule on a single CPU core. Importantly, parameters for PMVECC showed systematic errors for molecules containing Cl, Br, I, and P. Applying ECC to the explicit solvent hydration free energies found the same systematic errors. The results strongly suggest that some small adjustments to the Lennard-Jones parameters for GAFF will lead to improved hydration free energy calculations for all solvent models.

Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies

T-cell receptor-mimetic antibodies (TCRms) targeting disease-associated peptides presented by Major Histocompatibility Complexes (pMHCs) are set to become a major new drug modality. However, we lack a general understanding of how TCRms engage pMHC targets, which is crucial for predicting their specificity and safety. Several new structures of TCRm:pMHC complexes have become available in the past year, providing sufficient initial data for a holistic analysis of TCRms as a class of pMHC binding agents. Here, we profile the complete set of TCRm:pMHC complexes against representative TCR:pMHC complexes to quantify the TCR-likeness of their pMHC engagement. We find that intrinsic molecular differences between antibodies and TCRs lead to fundamentally different roles for their heavy/light chains and Complementarity-Determining Region loops during antigen recognition. The idiotypic properties of antibodies may increase the likelihood of TCRms engaging pMHCs with less peptide selectivity than TCRs. However, the pMHC recognition features of some TCRms, including the two TCRms currently in clinical trials, can be remarkably TCR-like. The insights gained from this study will aid in the rational design and optimisation of next-generation TCRms.

Molecular Insights into the Calcium Binding in Troponin C through a Molecular Dynamics Study

Calcium-binding proteins play critical roles in various biological processes such as signal transduction, cell growth, and transcription factor regulation. Ion binding and target binding of Ca²⁺-binding proteins are highly related. Therefore, understanding the ion binding mechanism will benefit the relevant inhibitor design toward the Ca²⁺-binding proteins. The EF-hand is the typical ion binding motif in Ca²⁺-binding proteins. Previous studies indicate that the ion binding affinity of the EF-hand increases with the peptide length, but this mechanism has not been fully understood. Herein, using molecular dynamics simulations, thermodynamic integration calculations, and molecular mechanics Poisson-Boltzmann surface area analysis, we systematically investigated four Ca²⁺-binding peptides containing the EF-hand loop in site III of rabbit skeletal troponin C. These four peptides have 13, 21, 26, and 34 residues. Our simulations reproduced the observed trend that the ion binding affinity increases with the peptide length. Our results implied that the E-helix motif preceding the EF-hand loop, likely the Phe99 residue in particular, plays a significant role in this regulation. The E-helix has a significant impact on the backbone and side-chain conformations of the Asp103 residue, rigidifying important hydrogen bonds in the EF-hand and decreasing the solvent exposure of the Ca²⁺ ion, hence leading to more favorable Ca²⁺ binding in longer peptides. The present study provides molecular insights into the ion binding in the EF-hand and establishes an important step toward elucidating the responses of Ca²⁺-binding proteins toward the ion and target availability.

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.

Computational identification of potential inhibitory compounds in Indian medicinal and aromatic plant species against major pathogenicity determinants of SARS-CoV-2

SARS-CoV-2 (COVID-19) viral pandemic has been reported across 223 countries and territories. Globalized vaccination programs alongside administration of repurposed drugs will assumingly confer a stronger and longer individual specific immune protection. However, considering possible recurrence of the disease via new variants, a conveniently deliverable phytopharmaceutical drug might be the best option for COVID-19 treatment. In the current study, the efforts have been made to identify potential leads for inhalation therapy as nasal swabs have been reported to transfer viral load prominently. In that direction, 2363 Essential oil (EOs) compounds from Indian medicinal and aromatic plants were screened through docking analysis and potential candidates were shortlisted that can interfere with viral pathogenicity. The main protease (M^pro) of SARS-CoV-2 interacted closely with jatamansin (JM), 6,7-dehydroferruginol (FG) and beta-sitosterol (BS), while Papain-like Protease (PL^pro) with friedelane-3-one (F3O) and lantadene D (LD) independently. Reduced Lantadene A (LAR) exhibited preferable interaction with RNA-dependent-RNA-polymerase (RdRp) whereas Lantadene A (LA) with RdRp and spike-glycoprotein (SG-pro) both target proteins. When compared against highest binding affinity conformations of well-known inhibitors of targets, these prioritized compounds conferred superior or comparable SARS-CoV-2 protein inhibition. Additionally, promising results were noted from pharmacokinetics prediction for all shortlisted compounds. Besides, molecular dynamics simulation for 100 ns in two replicates and binding free energy analysis revealed the stability of complexes with optimum compactness. To the best of our knowledge, the current investigation is a unique initial attempt whereby EO compounds have been computationally screened, irrespective of their known medicinal properties to fight COVID-19 infection.Communicated by Ramaswamy H. Sarma.

Maturation of siRNA by strand separation: Steered molecular dynamics study

RNA interference, particularly siRNA induced gene silencing is becoming an important avenue of modern therapeutics. The siRNA is delivered to the cells as short double helical RNA which becomes single stranded for forming the RISC complex. Significant experimental evidence is available for most of the steps except the process of the separation of the two strands. We have attempted to understand the pathway for double stranded siRNA (dsRNA) to single stranded (ssRNA) molecules using steered molecular dynamics simulations. As the process is completely unexplored we have applied force from all possible directions restraining all possible residues to convert dsRNA to ssRNA. We found pulling one strand along the helical axis direction restraining the far end of the other strand demands excessive force for ssRNA formation. Pulling a central residue of one strand, in a direction perpendicular to the helix axis, while keeping the base paired residue fixed requires intermediate force for strand separation. Moreover, we found that in this process the force requirement is quite high for the first bubble formation (nucleation energy) and the bubble propagation energies are quite small. We believe the success rate of the design of siRNA sequences for gene silencing may increase if this mechanistic knowledge is utilized for such a design process.Communicated by Ramaswamy H. Sarma.

On the Possibility That Bond Strain Is the Mechanism of RING E3 Activation in the E2-Catalyzed Ubiquitination Reaction

Ubiquitination is a type of post-translational modification wherein the small protein ubiquitin (Ub) is covalently bound to a lysine on a target protein. Ubiquitination can signal for several regulatory pathways including protein degradation. Ubiquitination occurs by a series of reactions catalyzed by three types of enzymes: ubiquitin activating enzymes, E1; ubiquitin conjugating enzymes, E2; and ubiquitin ligases, E3. E2 enzymes directly catalyze the transfer of Ub to the target protein─the RING E3 improves the efficiency. Prior to its transfer, Ub is covalently linked to the E2 via a thioester bond and the Ub∼E2 conjugate forms a quaternary complex with the RING E3. It is hypothesized that the RING E3 improves the catalytic efficiency of ubiquitination by placing the E2∼Ub conjugate in a "closed" position, which tensions and weakens the thioester bond. We interrogate this hypothesis by analyzing the strain on the thioester during molecular dynamics simulations of both open and closed E2∼Ub/E3 complexes. Our data indicate that the thioester is strained when the E2∼Ub conjugate is in the closed position. We also show that the amount of strain is consistent with the experimental rate enhancement caused by the RING E3. Finally, our simulations show that the closed configuration increases the populations of key hydrogen bonds in the E2∼Ub active site. This is consistent with another hypothesis stating that the RING E3 enhances reaction rates by preorganizing the substrates.

Role of Thylakoid Lipids in Protochlorophyllide Oxidoreductase Activation: Allosteric Mechanism Elucidated by a Computational Study

Light-dependent protochlorophyllide oxidoreductase (LPOR) is a chlorophyll synthetase that catalyzes the reduction of protochlorophyllide (Pchlide) to chlorophyllide (Chlide) with indispensable roles in regulating photosynthesis processes. A recent study confirmed that thylakoid lipids (TL) were able to allosterically enhance modulator-induced LPOR activation. However, the allosteric modulation mechanism of LPOR by these compounds remains unclear. Herein, we integrated multiple computational approaches to explore the potential cavities in the Arabidopsis thaliana LPOR and an allosteric site around the helix-G region where high affinity for phosphatidyl glycerol (PG) was identified. Adopting accelerated molecular dynamics simulation for different LPOR states, we rigorously analyzed binary LPOR/PG and ternary LPOR/NADPH/PG complexes in terms of their dynamics, energetics, and attainable allosteric regulation. Our findings clarify the experimental observation of increased NADPH binding affinity for LPOR with PGs. Moreover, the simulations indicated that allosteric regulators targeting LPOR favor a mechanism involving lid opening upon binding to an allosteric hinge pocket mechanism. This understanding paves the way for designing novel LPOR activators and expanding the applications of LPOR.

Exploration of natural product database for the identification of potent inhibitor against IDH2 mutational variants for glioma therapy

Mutation in isocitrate dehydrogenase 2 (mIDH2) is an oncogenic driver prevalently reported in various cancer types including gliomas. To date, enasidenib is the only FDA-approved drug widely used as a mIDH2 (R140Q) inhibitor. However, dose-limiting toxicity and modest brain penetrating capability restrict its use as a plausible mIDH2 inhibitor. Furthermore, secondary site mutations (Q316E and I319M) were identified in patients with enasidenib treatments resulting in acquired therapeutic resistance. Hence, in the present investigation, we aimed to identify novel and potent drug-like compounds to overcome the existing drawbacks using an integrated in-silico strategy. A sum of 1574 natural compounds from the naturally occurring plant-based anti-cancerous compound activity target (NPACT) database was proclaimed and subjected to molecular docking. The binding affinities of the resultant natural compounds were rescored using MM-GBSA scoring functions. The resultant lead molecules were subjected to anticancer activity prediction using the machine-learning model. Furthermore, the toxicity and drug-likeliness of the lead compounds were investigated using ADMET properties. Eventually, the integrated in silico approach resulted in a lead molecule, namely squalene (NPACT00954) against mIDH2 protein. The screened compound was subjected to mutational analysis accomplishing second-site mutations. Interestingly, squalene exhibited appreciable binding affinity alongside good brain penetrating potential than enasidenib. Indeed, the reproducibility and significance of our results are examined by running 3 replicas of 100-ns simulations per system using the random initial velocities of the atoms generated by Maxwell distribution at a given temperature. Thus, we hypothesize from our results that further optimization of squalene could be beneficial for the treatment and management of glioma in the near future.

Copper coordination states affect the flexibility of copper Metallochaperone Atox1: Insights from molecular dynamics simulations

Copper is an essential element in nature but in excess, it is toxic to the living cell. The human metallochaperone Atox1 participates in copper homeostasis and is responsible for copper transmission. In a previous multiscale simulation study, we noticed a change in the coordination state of the Cu(I) ion, from 4 bound cysteine residues to 3, in agreement with earlier studies. Here, we perform and analyze classical molecular dynamic simulations of various coordination states: 2, 3, and 4. The main observation is an increase in protein flexibility as a result of a decrease in the coordination state. In addition, we identified several populated conformations that correlate well with double electron-electron resonance distance distributions or an X-ray structure of Cu(I)-bound Atox1. We suggest that the increased flexibility might benefit the process of ion transmission between interacting proteins. Further experiments can scrutinize this hypothesis and shed additional light on the mechanism of action of Atox1.

Molecular dynamics insights on temperature and pressure effects on electroporation

Electroporation is a cell-level phenomenon caused by an ionic imbalance in the membrane, being of great relevance in various fields of knowledge. A dependence of the pore formation kinetics on the environmental conditions (temperature and pressure) of the cell membrane has already been reported, but further clarification regarding how these variables affect the pore formation/resealing dynamics and the transport of molecules through the membrane is still lacking. The objective of the present study was to investigate the temperature (288-348 K) and pressure (1-5000 atm) effects on the electroporation kinetics using coarse-grained molecular dynamics simulations. Results shown that the time for pore formation and resealing increased with pressure and decreased with temperature, whereas the maximum pore radius increased with temperature and decreased with pressure. This behavior influenced the ion migration through the bilayer, and the higher ionic mobility was obtained in the 288 K/1000 atm simulations, i.e., a combination of low temperature and (not excessively) high pressure. These results were used to discuss some experimental observations regarding the extraction of intracellular compounds applying this technique. This study contributes to a better understanding of electroporation under different thermodynamic conditions and to an optimal selection of processing parameters in practical applications which exploit this phenomenon.

Electrostatic Interactions Are the Primary Determinant of the Binding Affinity of SARS-CoV-2 Spike RBD to ACE2: A Computational Case Study of Omicron Variants

To explore the mechanistic origin that determines the binding affinity of SARS-CoV-2 spike receptor binding domain (RBD) to human angiotensin converting enzyme 2 (ACE2), we constructed the homology models of RBD-ACE2 complexes of four Omicron subvariants (BA.1, BA.2, BA.3 and BA.4/5), and compared them with wild type complex (RBD_WT-ACE2) in terms of various structural dynamic properties by molecular dynamics (MD) simulations and binding free energy (BFE) calculations. The results of MD simulations suggest that the RBDs of all the Omicron subvariants (RBD_OMIs) feature increased global structural fluctuations when compared with RBD_WT. Detailed comparison of BFE components reveals that the enhanced electrostatic attractive interactions are the main determinant of the higher ACE2-binding affinity of RBD_OMIs than RBD_WT, while the weakened electrostatic attractive interactions determine RBD of BA.4/5 subvariant (RBD_BA.4/5) lowest ACE2-binding affinity among all Omicron subvariants. The per-residue BFE decompositions and the hydrogen bond (HB) networks analyses indicate that the enhanced electrostatic attractive interactions are mainly through gain/loss of the positively/negatively charged residues, and the formation or destruction of the interfacial HBs and salt bridges can also largely affect the ACE2-binding affinity of RBD. It is worth pointing out that since Q493R plays the most important positive contribution in enhancing binding affinity, the absence of this mutation in RBD_BA.4/5 results in a significantly weaker binding affinity to ACE2 than other Omicron subvariants. Our results provide insight into the role of electrostatic interactions in determining of the binding affinity of SARS-CoV-2 RBD to human ACE2.

Point Mutations in TbpA Abrogate Human Transferrin Binding in Neisseria gonorrhoeae

TonB-dependent transporters (TDTs) are essential proteins for metal acquisition, an important step in the growth and pathogenesis of many pathogens, including Neisseria gonorrhoeae, the causative agent of gonorrhea. There is currently no available vaccine for gonorrhea; TDTs are being investigated as vaccine candidates because they are highly conserved and expressed in vivo. Transferrin binding protein A (TbpA) is an essential virulence factor in the initiation of experimental infection in human males and functions by acquiring iron upon binding to host transferrin (human transferrin [hTf]). The loop 3 helix (L3H) is a helix finger that inserts into the hTf C-lobe and is required for hTf binding and subsequent iron acquisition. This study identified and characterized the first TbpA single-point substitutions resulting in significantly decreased hTf binding and iron acquisition, suggesting that the helix structure is more important than charge for hTf binding and utilization. The tbpA D355P ΔtbpB and tbpA A356P ΔtbpB mutants demonstrated significantly reduced hTf binding and impaired iron uptake from Fe-loaded hTf; however, only the tbpA A356P ΔtbpB mutant was able to grow when hTf was the sole source of iron. The expression of tbpB was able to restore function in all tbpA mutants. These results implicate both D355 and A356 in the key binding, extraction, and uptake functions of gonococcal TbpA.

Computational molecular interaction between SARS-CoV-2 main protease and theaflavin digallate using free energy perturbation and molecular dynamics

Our objective was to identify the molecule which can inhibit SARS-CoV-2 main protease and can be easily procured. Natural products may provide such molecules and can supplement the current custom chemical synthesis-based drug discovery for this objective. A combination of docking approaches, scoring functions, classical molecular dynamic simulation, binding pose metadynamics, and free energy perturbation calculations have been employed in this study. Theaflavin digallate has been observed in top-scoring compounds after the three independent virtual screening simulations of 598435 compounds (unique 27256 chemical entities). The main protease-theaflavin digallate complex interacts with critical active site residues of the main protease in molecular dynamics simulation independent of the explored computational framework, simulation time, initial structure, and force field used. Theaflavin digallate forms approximately three hydrogen bonds with Glutamate166 of main protease, primarily through hydroxyl groups in the benzene ring of benzo(7)annulen-6-one, along with other critical residues. Glu166 is the most critical amino acid for main protease dimerization, which is necessary for catalytic activity. The estimated binding free energy, calculated by Amber and Schrodinger MMGBSA module, reflects a high binding free energy between theaflavin digallate and main protease. Binding pose metadynamics simulation shows the highly persistent H-bond and a stable pose for the theaflavin digallate-main protease complex. Using method control, experimental controls, and test set, alchemical transformation studies confirm high relative binding free energy of theaflavin digallate with the main protease. Computational molecular interaction suggests that theaflavin digallate can inhibit the main protease of SARS-CoV-2.

Identification of Graphene Dispersion Agents through Molecular Fingerprints

The scalable production and dispersion of 2D materials, like graphene, is critical to enable their use in commercial applications. While liquid exfoliation is commonly used, solvents such as N-methyl-pyrrolidone (NMP) are toxic and difficult to scale up. However, the search for alternative solvents is hindered by the intimidating size of the chemical space. Here, we present a computational pipeline informing the identification of effective exfoliation agents. Classical molecular dynamics simulations provide statistical sampling of interactions, enabling the identification of key molecular descriptors for a successful solvent. The statistically representative configurations from these simulations, studied with quantum mechanical calculations, allow us to gain insights onto the chemophysical interactions at the surface-solvent interface. As an exemplar, through this pipeline we identify a potential graphene exfoliation agent 2-pyrrolidone and experimentally demonstrate it to be as effective as NMP. Our workflow can be generalized to any 2D material and solvent system, enabling the screening of a wide range of compounds and solvents to identify safer and cheaper means of producing dispersions.

Mechanisms of isoform-specific residue influence on GTP-bound HRas, KRas, and NRas

HRas, KRas, and NRas are GTPases with a common set of effectors that control many cell-signaling pathways, including proliferation through Raf kinase. Their G-domains are nearly identical in sequence, with a few isoform-specific residues that have an effect on dynamics and biochemical properties. Here, we use accelerated molecular dynamics (aMD) simulations consistent with solution x-ray scattering experiments to elucidate mechanisms through which isoform-specific residues associated with each Ras isoform affects functionally important regions connected to the active site. HRas-specific residues cluster in loop 8 to stabilize the nucleotide-binding pocket, while NRas-specific residues on helix 3 directly affect the conformations of switch I and switch II. KRas, the most globally flexible of the isoforms, shows greatest fluctuations in the switch regions enhanced by a KRas-specific residue in loop 7 and a highly dynamic loop 8 region. The analysis of isoform-specific residue effects on Ras proteins is supported by NMR experiments and is consistent with previously published biochemical data.

Linker-Dependent Folding Rationalizes PROTAC Cell Permeability

Proteolysis-targeting chimeras (PROTACs) must be cell permeable to reach their target proteins. This is challenging as the bivalent structure of PROTACs puts them in chemical space at, or beyond, the outer limits of oral druggable space. We used NMR spectroscopy and molecular dynamics (MD) simulations independently to gain insights into the origin of the differences in cell permeability displayed by three flexible cereblon PROTACs having closely related structures. Both methods revealed that the propensity of the PROTACs to adopt folded conformations with a low solvent-accessible 3D polar surface area in an apolar environment is correlated to high cell permeability. The chemical nature and the flexibility of the linker were essential for the PROTACs to populate folded conformations stabilized by intramolecular hydrogen bonds, π-π interactions, and van der Waals interactions. We conclude that MD simulations may be used for the prospective ranking of cell permeability in the design of cereblon PROTACs.

All-Atom Simulations Uncover Structural and Dynamical Properties of STING Proteins in the Membrane System

Recent studies have shown that the stimulator of interferon gene (STING) protein plays a central role in the immune system by facilitating the production of type I interferons in cells. The STING signaling pathway is also a prominent activator of cancer-killing T cells that initiate a powerful adaptive immune response. Since biomolecular signaling pathways are complicated and not easily identified through traditional experiments, molecular dynamics (MD) has often been used to study structural and dynamical responses of biological pathways. Here, we carried out MD simulations for full-length chicken and human STING (chSTING and hSTING) proteins. Specifically, we investigated ligand-bound closed (holo) and ligand-unbound open (apo) forms of STING in the membrane system by comparing their conformational and dynamical differences. Our research provides clues for understanding the mechanism of the STING signaling pathway by uncovering detailed insights for the examined systems: the residues from each chain in the binding pocket are strongly correlated to one another in the open STING structure compared with those in the closed STING structure. Ligand-bound closed STING displays ∼174° rotation of the ligand-binding domain (LBD) relative to the open STING structure. The dynamical analysis of residue Cys148 located in the linker region of hSTING does not support the earlier hypothesis that Cys148 can form disulfide bonds between adjacent STING dimers. We also demonstrate that using the full-length proteins is critical, since the MD simulations of the LBD portion alone cannot properly describe the global conformational properties of STING.

Catalytic Mechanism of ATP Hydrolysis in the ATPase Domain of Human DNA Topoisomerase IIα

Human DNA topoisomerase IIα is a biological nanomachine that regulates the topological changes of the DNA molecule and is considered a prime target for anticancer drugs. Despite intensive research, many atomic details about its mechanism of action remain unknown. We investigated the ATPase domain, a segment of the human DNA topoisomerase IIα, using all-atom molecular simulations, multiscale quantum mechanics/molecular mechanics (QM/MM) calculations, and a point mutation study. The results suggested that the binding of ATP affects the overall dynamics of the ATPase dimer. Reaction modeling revealed that ATP hydrolysis favors the dissociative substrate-assisted reaction mechanism with the catalytic Glu87 serving to properly position and polarize the lytic water molecule. The point mutation study complemented our computational results, demonstrating that Lys378, part of the important QTK loop, acts as a stabilizing residue. The work aims to pave the way to a deeper understanding of these important molecular motors and to advance the development of new therapeutics.

Engineered P450 Atom-Transfer Radical Cyclases are Bifunctional Biocatalysts: Reaction Mechanism and Origin of Enantioselectivity

New-to-nature radical biocatalysis has recently emerged as a powerful strategy to tame fleeting open-shell intermediates for stereoselective transformations. In 2021, we introduced a novel metalloredox biocatalysis strategy that leverages the innate redox properties of the heme cofactor of P450 enzymes, furnishing new-to-nature atom-transfer radical cyclases (ATRCases) with excellent activity and stereoselectivity. Herein, we report a combined computational and experimental study to shed light on the mechanism and origins of enantioselectivity for this system. Molecular dynamics and quantum mechanics/molecular mechanics (QM/MM) calculations revealed an unexpected role of the key beneficial mutation I263Q. The glutamine residue serves as an essential hydrogen bond donor that engages with the carbonyl moiety of the substrate to promote bromine atom abstraction and enhance the enantioselectivity of radical cyclization. Therefore, the evolved ATRCase is a bifunctional biocatalyst, wherein the heme cofactor enables atom-transfer radical biocatalysis, while the hydrogen bond donor residue further enhances the activity and enantioselectivity. Unlike many enzymatic stereocontrol rationales based on a rigid substrate binding model, our computations demonstrate a high degree of rotational flexibility of the allyl moiety in an enzyme-substrate complex and succeeding intermediates. Therefore, the enantioselectivity is controlled by the radical cyclization transition states rather than the substrate orientation in ground-state complexes in the preceding steps. During radical cyclization, anchoring effects of the Q263 residue and steric interactions with the heme cofactor concurrently control the π-facial selectivity, allowing for highly enantioselective C-C bond formation. Our computational findings are corroborated by experiments with ATRCase mutants generated from site-directed mutagenesis.

Implementation of Telescoping Boxes in Adaptive Steered Molecular Dynamics

Long-time dynamical processes, such as those involving protein unfolding and ligand interactions, can be accelerated and realized through steered molecular dynamics (SMD). The challenge has been the extraction of information from such simulations that generalize for complex nonequilibrium processes. The use of Jarzynski's equality opened the possibility of determining the free energy along the steered coordinate, but sampling over the nonequilibrium trajectories is slow to converge. Adaptive steered molecular dynamics (ASMD) and other related techniques have been introduced to overcome this challenge through the use of stages. Here, we take advantage of these stages to address the numerical cost that arises from the required use of very large solvent boxes. We introduce telescoping box schemes within adaptive steered molecular dynamics (ASMD) in which we adjust the solvent box between stages and thereby vary (and optimize) the required number of solvent molecules. We have benchmarked the method on a relatively long α-helical peptide, Ala₃₀, with respect to the potential of mean force and hydrogen bonds. We show that the use of telescoping boxes introduces little numerical error while significantly reducing the computational cost.

Molecular Mechanism of Protein Arginine Deiminase 2: A Study Involving Multiple Microsecond Long Molecular Dynamics Simulations

Peptidylarginine deiminase 2 (PAD2) is a Ca²⁺-dependent enzyme that catalyzes the conversion of protein arginine residues to citrulline. This kind of structural modification in histone molecules may affect gene regulation, leading to effects that may trigger several diseases, including breast cancer, which makes PAD2 an attractive target for anticancer drug development. To design new effective inhibitors to control activation of PAD2, improving our understanding of the molecular mechanisms of PAD2 using up-to-date computational techniques is essential. We have designed five different PAD2-substrate complex systems based on varying protonation states of the active site residues. To search the conformational space broadly, multiple independent molecular dynamics simulations of the complexes have been performed. In total, 50 replica simulations have been performed, each of 1 μs, yielding a total simulation time of 50 μs. Our findings identify that the protonation states of Cys647, Asp473, and His471 are critical for the binding and localization of the N-α-benzoyl-l-arginine ethyl ester substrate within the active site. A novel mechanism for enzyme activation is proposed according to near attack conformers. This represents an important step in understanding the mechanism of citrullination and developing PAD2-inhibiting drugs for the treatment of breast cancer.

Insighting isatin derivatives as potential antiviral agents against NSP3 of COVID-19

The world is now facing intolerable damage in all sectors of life because of the deadly COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2. The discovery and development of anti-SARS-CoV-2 drugs have become pragmatic in the time needed to fight against this pandemic. The non-structural protein 3 is essential for the replication of transcriptase complex (RTC) and may be regarded as a possible target against SARS-CoV-2. Here, we have used a comprehensive in silico technique to find potent drug molecules against the NSP3 receptor of SARS-CoV-2. Virtual screening of 150 Isatin derivatives taken from PubChem was performed based on their binding affinity estimated by docking simulations, resulting in the selection of 46 ligands having binding energy greater than -7.1 kcal/mol. Moreover, the molecular interactions of the nine best-docked ligands having a binding energy of ≥ -8.5 kcal/mol were analyzed. The molecular interactions showed that the three ligands (S5, S16, and S42) were stabilized by forming hydrogen bonds and other significant interactions. Molecular dynamic simulations were performed to mimic an in vitro protein-like aqueous environment and to check the stability of the best three ligands and NSP3 complexes in an aqueous environment. The binding energy of the S5, S16, and S42 systems obtained from the molecular mechanics Poisson-Boltzmann surface area also favor the system's stability. The MD and MM/PBSA results explore that S5, S16, and S42 are more stable and can be considered more potent drug candidates against COVID-19 disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11696-022-02298-7.

The performance of ensemble-based free energy protocols in computing binding affinities to ROS1 kinase

Optimization of binding affinities for compounds to their target protein is a primary objective in drug discovery. Herein we report on a collaborative study that evaluates a set of compounds binding to ROS1 kinase. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to rank the binding free energies. The predicted binding free energies from ESMACS simulations show good correlations with experimental data for subsets of the compounds. Consistent binding free energy differences are generated for TIES and ESMACS. Although an unexplained overestimation exists, we obtain excellent statistical rankings across the set of compounds from the TIES protocol, with a Pearson correlation coefficient of 0.90 between calculated and experimental activities.

Uncovering the Molecular Basis for the Better Gefitinib Sensitivity of EGFR with Complex Mutations over Single Rare Mutation: Insights from Molecular Simulations

Epidermal growth factor receptor (EGFR) is an intensively focused target for anti-tumor compounds used in non-small cell lung cancer (NSCLC) therapy. Compared to the classical activating mutations, there are still many uncommon EGFR mutations associated with poorer responses to EGFR inhibitors. A detailed understanding of the molecular basis for multiple EGFR mutants exhibiting diverse responses to inhibitors is of critical importance for related drug development. Herein, we explored the molecular determinants contributing to the distinct responses of EGFR with a single rare mutation (G719S) or combined mutations (G719S/L858R and G719S/l861Q) to Gefitinib (IRE). Our results indicated that interactions, formed within the tetrad of residues S768 (in the αC-helix), D770 (in the αC-β4 loop), Y827 (in the αE-helix), and R831 (in the catalytic loop), play an important role in the stability of αC-helix and the maintenance of K745–E762 salt bridge in the absence of IRE, which are weakened in the EGFR^G719S system and enhanced in the EGFR^G719S/L858R system upon IRE binding. Besides, the introduced hydrogen bonds by the co-occurring mutation partner also contribute to the stability of αC-helix. The work done for inhibitor dissociation suggests that IRE exhibits a stronger binding affinity to EGFR^G719S/L858R mutant. Together, these findings provide a deeper understanding of minor mutations, which is essential for drug development targeting EGFR with less common mutations.

Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.

Multiscale computational investigations of the translesion synthesis bypass of tobacco-derived DNA adducts: critical insights that complement experimental biochemical studies

Among the numerous agents that damage DNA, tobacco products remain one of the most lethal and result in the most diverse set of DNA lesions. This perspective aims to provide an overview of computational work conducted to complement experimental biochemical studies on the mutagenicity of adducts derived from the most potent tobacco carcinogen, namely 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (nicotine-derived nitrosaminoketone or NNK). Lesions ranging from the smallest methylated thymine derivatives to the larger, flexible pyridyloxobutyl (POB) guanine adducts are considered. Insights are obtained from density functional theory (DFT) calculations and molecular dynamics (MD) simulations into the damaged nucleobase and nucleoside structures, the accommodation of the lesions in the active site of key human polymerases, the intrinsic base pairing potentials of the adducts, and dNTP incorporation opposite the lesions. Overall, the computational data provide atomic level information that can rationalize the differential mutagenic properties of tobacco-derived lesions and uncover important insights into the impact of adduct size, nucleobase, position, and chemical composition of the bulky moiety.

Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcriptional regulation in cell proliferation, cell cycle, and human carcinogenesis. Experimental measurements using the scintillation proximity assay show that the distributions of binding free energies from a large number of independent measurements exhibit non-normal properties. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to predict the binding free energies and to provide a detailed chemical insight into the nature of ligand-protein binding. Our results show that the 1-trajectory ESMACS protocol works well for the set of ligands studied here. Although one unexplained outlier exists, we obtain excellent statistical ranking across the set of compounds from the ESMACS protocol and good agreement between calculations and experiments for the relative binding free energies from the TIES protocol. ESMACS and TIES are again found to be powerful protocols for the accurate comparison of the binding free energies.

Multiple Molecular Dynamics Simulations and Energy Analysis Unravel the Dynamic Properties and Binding Mechanism of Mutants HIV-1 Protease with DRV and CA-p2

PRS17, a variant of human immunodeficiency virus type I protease (HIV-1 PR), has 17 mutated residues showing high levels of multidrug resistance. To describe the effects of these mutated residues on the dynamic properties and the binding mechanism of PR with substrate and inhibitor, focused on six systems (two complexes of WT PR and PRS17 with inhibitor Darunavir (DRV), two complexes of WT PR and PRS17 with substrate analogue CA-p2, two unligand WT PR and PRS17), we performed multiple molecular dynamics (MD) simulations combined with MM-PBSA and solvated interaction energy (SIE) methods. For both the unligand PRs and ligand-PR complexes, the results from simulations revealed 17 mutated residues alter the flap-flap distance, the distance from flap regions to catalytic sites, and the curling degree of the flap tips. These mutated residues changed the flexibility of the flap region in PR, and thus affected its binding energy with DRV and CA-p2, resulting in differences in sensitivity. Hydrophobic cavity makes an important contribution to the binding of PR and ligands. And most noticeable of all, the binding of the guanidine group in CA-p2 and Arg8' of PRS17 is useful for increasing their binding ability. These results have important guidance for the further design of drugs against multidrug resistant PR. IMPORTANCE Developing effective anti-HIV inhibitors is the current requirement to cope with the emergence of the resistance of mutants. Compared with the experiments, MD simulations along with energy calculations help reduce the time and cost of designing new inhibitors. Based on our simulation results, we propose two factors that may help design effective inhibitors against HIV-1 PR: (i) importance of hydrophobic cavity, and (ii) introduction of polar groups similar to the guanidine group.

Phosphorylation-Induced Conformational Dynamics and Inhibition of Janus Kinase 1 by Suppressors of Cytokine Signaling 1

The dysfunction of the JAK/STAT (Janus kinase/signal transducers and activators of transcription) pathway results in several pathophysiological conditions, including autoimmune disorders. The negative feedback regulators of the JAK/STAT signaling pathway, suppressors of cytokine signaling (SOCS), act as a natural inhibitor of JAK and inhibit aberrant activity. SOCS1 is the most potent member of the SOCS family, whose kinase inhibitory region targets the substrate-binding groove of JAK with high affinity and blocks the phosphorylation of JAK kinases. Overall, we performed an aggregate of 13 μs molecular dynamics simulations on the activation loop's three different phosphorylation (double and single) states. Results from our simulations show that the single Tyr¹⁰³⁴ phosphorylation could stabilize the JAK1/SOCS1 complex as well as the flexible activation segment. The phosphate-binding loop (P-loop) shows conformational variability at dual and single phosphorylated states. Principal component analysis and protein structure network (PSN) analysis reveal that the different phosphorylation states and SOCS1 binding induce intermediate inactive conformations of JAK1, which could be a better target for future JAK1 selective drug design. PSN analysis suggests that the com-pY1034 system is stabilized due to higher values of network hubs than the other two complex systems. Moreover, the binding free energy calculations suggest that pTyr¹⁰³⁴ states show a higher affinity toward SOCS1 than the dual and pTyr¹⁰³⁵ states. We believe that the mechanistic understanding of JAK1/SOCS1 complexation will aid future studies related to peptide inhibitors based on SOCS1.

In Silico Modeling and Scoring of PROTAC-Mediated Ternary Complex Poses

Proteolysis targeting chimeras (PROTACs) are molecules that induce protein degradation via formation of ternary complexes between an E3 ubiquitin ligase and a target protein. The rational design of PROTACs requires accurate knowledge of the native configuration of the PROTAC-induced ternary complex. This study demonstrates that native and non-native ternary complex poses can be distinguished based on the pose occupancy time in MD, where native poses exhibit longer occupancy times at both room and higher temperatures. Candidate poses are generated by MD sampling and pre-ranked by classic MM/GBSA. A specific heating scheme is then applied to accelerate ternary pose departure, with the pose occupancy time and fraction being measured. This scoring identifies the native pose in all systems tested. Its success is partially attributed to the dynamic nature of pose departure analyses, which accounts for entropic effects typically neglected in the faster static scoring methods, while entropy plays a greater role in protein-protein than in protein-ligand systems.

GROMACS in the Cloud: A Global Supercomputer to Speed Up Alchemical Drug Design

We assess costs and efficiency of state-of-the-art high-performance cloud computing and compare the results to traditional on-premises compute clusters. Our use case is atomistic simulations carried out with the GROMACS molecular dynamics (MD) toolkit with a particular focus on alchemical protein-ligand binding free energy calculations. We set up a compute cluster in the Amazon Web Services (AWS) cloud that incorporates various different instances with Intel, AMD, and ARM CPUs, some with GPU acceleration. Using representative biomolecular simulation systems, we benchmark how GROMACS performs on individual instances and across multiple instances. Thereby we assess which instances deliver the highest performance and which are the most cost-efficient ones for our use case. We find that, in terms of total costs, including hardware, personnel, room, energy, and cooling, producing MD trajectories in the cloud can be about as cost-efficient as an on-premises cluster given that optimal cloud instances are chosen. Further, we find that high-throughput ligand-screening can be accelerated dramatically by using global cloud resources. For a ligand screening study consisting of 19 872 independent simulations or ∼200 μs of combined simulation trajectory, we made use of diverse hardware available in the cloud at the time of the study. The computations scaled-up to reach peak performance using more than 4 000 instances, 140 000 cores, and 3 000 GPUs simultaneously. Our simulation ensemble finished in about 2 days in the cloud, while weeks would be required to complete the task on a typical on-premises cluster consisting of several hundred nodes.