QSAR Study, Molecular Docking and Molecular Dynamic Simulation of Aurora Kinase Inhibitors Derived from Imidazo[4,5-b]pyridine Derivatives

Cancer is a serious threat to human life and social development and the use of scientific methods for cancer prevention and control is necessary. In this study, HQSAR, CoMFA, CoMSIA and TopomerCoMFA methods are used to establish models of 65 imidazo[4,5-b]pyridine derivatives to explore the quantitative structure-activity relationship between their anticancer activities and molecular conformations. The results show that the cross-validation coefficients q2 of HQSAR, CoMFA, CoMSIA and TopomerCoMFA are 0.892, 0.866, 0.877 and 0.905, respectively. The non-cross-validation coefficients r2 are 0.948, 0.983, 0.995 and 0.971, respectively. The externally validated complex correlation coefficients r2pred of external validation are 0.814, 0.829, 0.758 and 0.855, respectively. The PLS analysis verifies that the QSAR models have the highest prediction ability and stability. Based on these statistics, virtual screening based on R group is performed using the ZINC database by the Topomer search technology. Finally, 10 new compounds with higher activity are designed with the screened new fragments. In order to explore the binding modes and targets between ligands and protein receptors, these newly designed compounds are conjugated with macromolecular protein (PDB ID: 1MQ4) by molecular docking technology. Furthermore, to study the nature of the newly designed compound in dynamic states and the stability of the protein-ligand complex, molecular dynamics simulation is carried out for N3, N4, N5 and N7 docked with 1MQ4 protease structure for 50 ns. A free energy landscape is computed to search for the most stable conformation. These results prove the efficient and stability of the newly designed compounds. Finally, ADMET is used to predict the pharmacology and toxicity of the 10 designed drug molecules.

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.

Computational insights into dynamics and conformational stability of N-acetylmannosamine kinase mutations

The activity of UDP-GlcNAc 2-epimerase/ManNAc kinase (GNE) is essential for the biosynthesis of sialic acid, which is involved in cellular processes in health and diseases. GNE contains an N-terminal epimerase domain and a C-terminal kinase domain (N-acetylmannosamine kinase, MNK). Mutations of the GNE protein led to hypoactivity of the enzyme and cause sialurea or autosomal recessive inclusion body myopathy/Nonaka myopathy. Here, we used all-atom molecular dynamics (MD) simulations to comprehend the folding, dynamics and conformational stability of MNK variants, including the wild type (WT) and three mutants (H677R, V696M and H677R/V696M). The deleterious and destabilizing nature of MNK mutants were predicted using different prediction tools. Results predicted that mutations modulate the stability, flexibility and function of MNK. The effect of mutations on the conformational stability and dynamics of MNK was next studied through the free-energy landscape (FEL), hydrogen-bonds and secondary structure changes. The FEL results show that the mutations interfere with various conformational transitions in both WT and mutants, exposing the structural underpinnings of protein destabilization and unfolding brought on by mutation. We discover that, when compared to the other two mutations, V696M and H677R/V696M, H677R has the most harmful effects. These findings have a strong correlation with published experimental studies that demonstrate how these mutations disrupt MNK activity. Hence, this computational study describes the structural details to unravel the mutant effects at the atomistic resolution and has implications for understanding the GNE's physiological and pathological role.Communicated by Ramaswamy H. Sarma.

Understanding the basis of thermostability for enzyme "Nanoluc" towards designing industry-competent engineered variants

As a leading contender in the study of luminescence, nanoluciferase has recently attracted attention and proven effective in a wide variety of research areas. Although numerous attempts have been made to improve activity, there has yet to be a thorough exploration of further possibilities to improve thermostability. In this study, protein engineering in tandem with molecular dynamics simulation at various temperatures (300 K, 400 K, 450 K and 500 K) was used to improve our understanding of nanoluciferase dynamics and identification of factors that could significantly enhance the thermostability. Based on these, three novel mutations have been narrowed down, which were hypothesised to improve thermostability. Root mean square deviation and root mean square fluctuation studies confirmed higher stability of mutant at high temperature. Solvent-accessible surface area and protein unfolding studies revealed a decreased tendency of mutant to unfold at higher temperatures. Further free energy landscape and principal component analysis was adapted to get deeper insights into the thermodynamic and structural behavior of these proteins at elevated temperature. Thus, this study provides a deeper insight into the dynamic factors for thermostability and introduces a novel, enhanced nanoluciferase candidate with potential use in industry.Communicated by Ramaswamy H. Sarma.

Structural dynamics of influenza A (H1N1) hemagglutinin protein: a comparative study of Indian (2018) isolate with its evolutionary neighbor, Californian (2009) strain

This work highlights the structure and dynamics of two trimeric HA proteins of the H1N1 virus from different origins, the pandemic Californian (HACal) and its closest Indian neighbor (HAInd), reported in 2009 and 2018, respectively. Because of mutation, HAInd acquires new N-glycosylation and epitope binding sites along with mutations at RBD, which might trigger an altered viral-host interaction mechanism. Molecular dynamics simulations performed on HA trimers for a period of 250 ns reveal the highly dynamic nature of HACal trimers inherited by the flexibility of HA monomers. In the trimer, the dynamics of one monomer are more pronounced compared to others, and the enhanced dynamics of RBD especially gain attention as they plays a key role during fusion. Conversely, the mutant HAInd trimer effectively establishes more H-bond interactions, and accordingly, the trimer undergoes more stabilized dynamics with a relatively lower amplitude of RBD dynamics, as endorsed by the reduced RMSD, Rg, and SASA variations. The cooperative and anti-cooperative motions dissected for the subdomains of both strains also reveal a prominent anticorrelative motion of RBD against other subdomains. In agreement, the free energy landscape of stable HAInd is also characterized by a single lowest wide energy basin instead of the two minimum energy basins of the HACal trimer. In essence, the mutant HAInd acquires a highly stable conformation with novel functional features, which calls for (i) further investigation on the emerging mutation-mediated variation in viral-host binding mechanism and (ii) the need for further design of site-specific potential inhibitors to face future challenges.Communicated by Ramaswamy H. Sarma.

Deciphering Campylobacter jejuni DsbA1 protein dynamics in the presence of anti-virulent compounds: a multi-pronged computer-aided approach

The current study aims to evaluate Asinex library compounds against Campylobacter jejuni DsbA1 protein, a thiol disulfide oxidoreductase enzyme that plays a major role in the oxidative folding of bacterial virulence proteins, making it a promising anti-viral drug target. By employing several techniques of computer-aided drug design, BDC25697459, BDD33601083, and BDC30129064 were identified with binding energy scores of -8.8 kcal/mol, -8.8 kcal/mol, and -8.3 kcal/mol, respectively. However, the control molecule, tetraethylene glycol, exhibited a binding energy score of -7.0 kcal/mol. The control, BDD33601083, and BDC30129064 were unveiled to bind the same co-crystallized binding site (pocket 1), while BDC25697459 interacted with a new binding pocket (pocket 2) adjacent to the control binding region. The molecular dynamics simulation showed that complexes exhibit stable dynamics without significant global or residue-level fluctuations. The average RMSD values were in the range of 2.07 Å-2.45 Å. Similarly, mean RMSF was recorded between 1.30 and 1.42 Å. The C. jejuni DsbA1 was also observed as compact in the presence of the compounds, showing a mean RoG value in the range of 16.42 Å-16.55 Å. In terms of MM/PBSA binding energy, the BDC30129064 complex was ranked top with -44.88 ± 4.14 kcal/mol, whereas the positive control molecule exhibited -22.22 ± 3.33 kcal/mol. From a pharmacokinetic perspective, the compounds are suitable candidates for clinical trial investigation. Preliminary computational analysis of these virtual hits indicates that these compounds have a low potential for ADME and toxicity-associated liabilities. In summary, the compounds displayed a high affinity for the C. jejuni DsbA1 protein, indicating potential efficacy that requires further investigation.Communicated by Ramaswamy H. Sarma.

In-silico evaluation of Bismurrayaquinone-A phytochemical as a potential multifunctional inhibitor targeting dihydrofolate reductase: implications for anticancer and antibacterial drug development

Dihydrofolate reductase (DHFR) has gained significant attention in drug development, primarily due to marked distinctions in its active site among different species. DHFR plays a crucial role in both DNA and amino acid metabolism by facilitating the transfer of monocarbon residues through tetrahydrofolate, which is vital for nucleotide and amino acid synthesis. This considers its potential as a promising target for therapeutic interventions. In this study, our focus was on conducting a virtual screening of phytoconstituents from the IMPPAT2.0 database to identify potential inhibitors of DHFR. The initial criterion involved assessing the binding energy of molecules against DHFR and we screened top 20 compounds ranging energy -13.5 to -11.4 (kcal/Mol) while Pemetrexed disodium bound with less energy -10.2 (kcal/Mol), followed by an analysis of their interactions to identify more effective hits. We prioritized IMPHY007679 (Bismurrayaquinone-A), which displayed a high binding affinity and crucial interaction with DHFR. We also evaluated the drug-like properties and biological activity of IMPHY007679. Furthermore, MD simulation was done, RMSD, RMSF, Rg, SASA, PCA and FEL explore the time-evolution impact of IMPHY007679 comparing it with a reference drug, Pemetrexed disodium. Collectively, our findings suggest that IMPHY007679 recommend further investigation in both in vitro and in vivo settings for its potential in developing anticancer and antibacterial therapies. This compound holds promise as a valuable candidate for advancing drug research and treatment strategies.Communicated by Ramaswamy H. Sarma.

Sequential virtual screening collaborated with machine-learning strategies for the discovery of precise medicine against non-small cell lung cancer

Dysregulation of MAPK pathway receptors are crucial in causing uncontrolled cell proliferation in many cancer types including non-small cell lung cancer. Due to the complications in targeting the upstream components, MEK is an appealing target to diminish this pathway activity. Hence, we have aimed to discover potent MEK inhibitors by integrating virtual screening and machine learning-based strategies. Preliminary screening was conducted on 11,808 compounds using the cavity-based pharmacophore model AADDRRR. Further, seven ML models were accessed to predict the MEK active compounds using six molecular representations. The LGB model with morgan2 fingerprints surpasses other models ensuing 0.92 accuracy and 0.83 MCC value versus test set and 0.85 accuracy and 0.70 MCC value with external set. Further, the binding ability of screened hits were examined using glide XP docking and prime-MM/GBSA calculations. Note that we have utilized three ML-based scoring functions to predict the various biological properties of the compounds. The two hit compounds such as DB06920 and DB08010 resulted excellent binding mechanism with acceptable toxicity properties against MEK. Further, 200 ns of MD simulation combined with MM-GBSA/PBSA calculations confirms that DB06920 may have stable binding conformations with MEK thus step forwarded to the experimental studies in the near future.Communicated by Ramaswamy H. Sarma.

Targeting CDK6 in hormone receptor-positive breast cancer: inhibitor discovery for precision oncology through dynamics study

CDK6 is a critical protein involved in the regulation of the cell cycle, playing an important role in the progression from the G1 to S phase. In breast cancer, dysregulation of this protein is involved in tumour development and progression, particularly in hormone receptor-positive (HR+) breast cancers. The upregulation of CDK6 have been observed in a subset of breast cancers, leading to uncontrolled progression of the cell cycle and increased proliferation of cells. The purpose of this abstract is to provide an outline of CDK6's role. In breast cancer and the therapeutic strategies targeting CDK6 using specific selected inhibitors. To discover viable therapeutic candidates after competitive inhibition of CDK6 with a small molecular drug complex, high throughput screening and docking studies were used. Further, we carried the compounds based on ADMET properties and prediction of activity spectra for substances analysis. Finally, two different compounds were selected to carry out MD simulations. CDK6-IMPHY002642 and CDK6-IMPHY005260 are the two compounds that were identified. Overall, our results suggest that the CDK6-IMPHY002642 and CDK6-IMPHY005260 complex was relatively stable during the simulation. The compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that CDK6, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.Communicated by Ramaswamy H. Sarma.

Phytochemicals as potential inhibitors of interleukin-8 for anticancer therapy: in silico evaluation and molecular dynamics analysis

Within the realm of soluble factors that have emerged as potential targets for therapeutic intervention, the chemokine interleukin-8 (IL-8) has garnered attention as a potential contributor to treatment responses in various cancer types. The utilization of naturally occurring anticancer compounds for treating cancer patients has shown substantial advancements in survival rates across early and advanced stages of the disease. In silico research findings provide support for the application of phytochemicals as potential inhibitors of IL-8, and phytochemicals exhibiting a high binding free energy and crucial interactions display promising anticancer properties, positioning them as candidates for future drug development. Noteworthy phytochemicals such as IMPHY006634 (Isohydnocarpin), IMPHY007957 (Chitranone) and IMPHY013015 (1-Hydroxyrutaecarpine) were predicted to possess inhibitory activity against IL-8, with calculated energies ranging from -9.9 to -9.1 kcal/mol, respectively. Several hydrogen bonds, including common amino acid residues Lys9 and CYS48, were identified. Molecular dynamics calculations conducted on these potent inhibitors demonstrated their stability throughout a 200 ns simulation, as indicated by metrics such as RMSD, RMSF, Rg, SASA, H-bonds, PCA and FEL analysis. Moreover, PASS analysis and adherence of these natural compounds to drug-likeness rules like Lipinski's further strengthen their candidacy. Considering these calculations and various parameters, these three prominent natural compounds emerge as promising candidates for anti-IL-8 therapy in the management of cancer.Communicated by Ramaswamy H. Sarma.

Exploring the conformational dynamics and thermodynamics of EGFR S768I and G719X + S768I mutations in non-small cell lung cancer: An in silico approaches

Non-small cell lung cancer (NSCLC) is often driven by mutations in the epidermal growth factor receptor (EGFR) gene. However, rare mutations such as G719X and S768I lack standard anti-EGFR targeted therapies. Understanding the structural differences between wild-type EGFR and these rare mutants is crucial for developing EGFR-targeted drugs. We performed a systematic analysis using molecular dynamics simulations, essential dynamics (ED), molecular mechanics Poisson-Boltzmann surface area, and free energy calculation methods to compare the kinetic properties, molecular motion, and free energy distribution between wild-type EGFR and the rare mutants' structures G719X-EGFR, S768I-EGFR, and G719X + S768I-EGFR. Our results showed that S768I-EGFR and G719X + S768I-EGFR have higher global and local conformational flexibility and lower thermal and global structural stability than WT-EGFR. ED analysis revealed different molecular motion patterns between S768I-EGFR, G719X + S768I-EGFR, and WT-EGFR. The A-loop and αC-helix, crucial structural elements related to the active state, showed a tendency toward active state development, providing a molecular mechanism explanation for NSCLC caused by EGFR S768I and EGFR G719C + S768I mutations. The present study may be helpful in the development of new EGFR-targeted drugs based on the structure of rare mutations. Our findings may aid in developing new targeted treatments for patients with EGFR S768I and EGFR G719X + S768I mutations.

Exploring conformation changes of Janus kinase 2 pseudokinase mediated by mutations through Gaussian accelerated molecular dynamics and principal component analysis

The pseudokinase domain (JH2) of the protein tyrosine kinase (Janus kinase 2, JAK2) regulates the activity of a tyrosine kinase domain (JH1) in JAK2, which is further affected by mutations in the JH2. In this work, Gaussian accelerated molecular dynamics (GaMD) simulations followed by construction of free energy landscapes (FELs) and principal component analysis (PCA) were performed to study effect of two mutations V617F and V617F/E596A on the conformations of the ATP-bound JH2. The dynamic analyses reveal that mutations affect the structural flexibility and correlated motions of the JH2, meanwhile also change the dynamics behavior of the P-loop and αC-helix of the JH2. The information from FELs unveils that mutations induce less energy states than the free JH2 and the WT one. The analyses of interaction networks uncover that mutations affect the salt bridge interactions of ATP with K581, K677 and R715 and alter hydrogen bonding interactions (HBIs) of ATP with the JH2. The changes in conformations of the JH2 and ATP-JH2 interaction networks caused by mutations in turn generate effect on the activity regulations of the JH2 on the JH1. This work is expected to provide significant theoretical helps for deeply understanding the function of the JH2 and drug design toward JAK2.Communicated by Ramaswamy H. Sarma.

Acquired Secondary HER2 Mutations Enhance HER2/MAPK Signaling and Promote Resistance to HER2 Kinase Inhibition in Breast Cancer

HER2 mutations drive the growth of a subset of breast cancers and are targeted with HER2 tyrosine kinase inhibitors (TKI) such as neratinib. However, acquired resistance is common and limits the durability of clinical responses. Most HER2-mutant breast cancers progressing on neratinib-based therapy acquire secondary mutations in HER2. It is unknown whether these secondary HER2 mutations, other than the HER2T798I gatekeeper mutation, are causal to neratinib resistance. Herein, we show that secondary acquired HER2T862A and HER2L755S mutations promote resistance to HER2 TKIs via enhanced HER2 activation and impaired neratinib binding. While cells expressing each acquired HER2 mutation alone were sensitive to neratinib, expression of acquired double mutations enhanced HER2 signaling and reduced neratinib sensitivity. Computational structural modeling suggested that secondary HER2 mutations stabilize the HER2 active state and reduce neratinib binding affinity. Cells expressing double HER2 mutations exhibited resistance to most HER2 TKIs but retained sensitivity to mobocertinib and poziotinib. Double-mutant cells showed enhanced MEK/ERK signaling, which was blocked by combined inhibition of HER2 and MEK. Together, these findings reveal the driver function of secondary HER2 mutations in resistance to HER2 inhibition and provide a potential treatment strategy to overcome acquired resistance to HER2 TKIs in HER2-mutant breast cancer.

SIGNIFICANCE

HER2-mutant breast cancers acquire secondary HER2 mutations that drive resistance to HER2 tyrosine kinase inhibitors, which can be overcome by combined inhibition of HER2 and MEK.

In silico prediction of mutation sites for anthranilate synthase from Serratia marcesens to deregulate tryptophan feedback inhibition

Allosteric feedback inhibition of the committed step in amino acid biosynthetic pathways is a major concern for production of amino acids at industrial scale. Anthranilate synthase (AS) catalyzes the first reaction of tryptophan biosynthetic pathway found in microorganisms and is feedback inhibited by its own product i.e. tryptophan. Here, we identified new mutant sites in AS using computational mutagenesis approach. MD simulations (20 ns) followed by MMPBSA and per residue decomposition energy analysis identified seven amino acid residues with best binding affinity for tryptophan. All 19 mutant structures were generated for each identified amino acid residue followed by simulation to evaluate effect of mutation on protein stability. Later, molecular docking studies were employed to generate mutant-tryptophan complex and structures with binding energies (kcal/mol) much higher than wild-type AS were selected. Finally, two mutants i.e., S37W and S37H were identified on the basis of positive binding scores and loss of tryptophan binding inside pocket. Further, MD simulations run for 200 ns were performed over these mutant-tryptophan complexes followed by RMSD, RMSF, radius of gyration , solvent accessible surface area , intra-protein hydrogen bond numbers, principal component analysis, free energy landscape (FEL) and secondary structure analysis to rationale effect of mutations on stability of protein. Cross correlation analysis of mutant site amino acids (S37W) with key residues of catalytic site (G325, T326, H395 and G482) was done to evaluate the effect of mutations on catalytic site conformation. Current computational mutagenesis approach predicted two mutants S37W and S37H with proposed deregulated feedback inhibition by tryptophan and retained catalytic activity.Communicated by Ramaswamy H. Sarma.

Structure and dynamics of whole-sequence homology model of ORF3a protein of SARS-CoV-2: An insight from microsecond molecular dynamics simulations

The ORF3a is a large accessory protein in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which plays an important role in virulence and viral replication; especially in inflammasome activation and apoptosis. However,, the existing cryo-EM structure of SARS-CoV-2 ORF3a is incomplete, . making it challenging to understand its structural and functional features. The aim of this study is to investigate the dynamic behaviors of the full-sequence homology model of ORF3a and compare it with the cryo-EM structure using microsecond molecular dynamics simulations. The previous studies indicated that the unresolved residues of the cryo-EM structure are not only involved in the pathogenesis of the SARS-CoV-2 but also exhibit a significant antigenicity. The dynamics scenario of homology model revealed higher RMSD, Rg, and SASA values with stable pattern when compared to the cryo-EM structure. Moreover, the RMSF analysis demonstrated higher fluctuations at specific positions (1-43, 97-110, 172-180, 219-243) in the model structure, whereas the cryo-EM structure displayed lower overall drift (except 1-43) in comparison to the model structure.Secondary structural features indicated that a significant unfolding in the transmembrane domains and β-strand at positions 166 to 172, affecting the stability and compactness of the cryo-EM structure , whereas the model exhibited noticeable unfolding in transmembrane domains and small-coiled regions in the N-terminal. , The results from molecular docking and steered molecular dynamics investigations showed the model structure had a greater number of non-bonding interactions, leading to enhanced stability when compared to the cryo-EM structure. Consequently, higher forces were necessary for unbinding of the baricitinib and ruxolitinib inhibitors from the model structure.. Our findings can help better understanding of the significance of unresolved residues at the molecular level. Additionally, this information can guide researchers for experimental endeavors aimed at completing the full-sequence structure of the ORF3a.Communicated by Ramaswamy H. Sarma.

Ordered-domain unfolding of thermophilic isolated β subunit ATP synthase

The flexibility of the ATP synthase's β subunit promotes its role in the ATP synthase rotational mechanism, but its domains stability remains unknown. A reversible thermal unfolding of the isolated β subunit (Tβ) of the ATP synthase from Bacillus thermophilus PS3, tracked through circular dichroism and molecular dynamics, indicated that Tβ shape transits from an ellipsoid to a molten globule through an ordered unfolding of its domains, preserving the β-sheet residual structure at high temperature. We determined that part of the stability origin of Tβ is due to a transversal hydrophobic array that crosses the β-barrel formed at the N-terminal domain and the Rossman fold of the nucleotide-binding domain (NBD), while the helix bundle of the C-terminal domain is the less stable due to the lack of hydrophobic residues, and thus the more flexible to trigger the rotational mechanism of the ATP synthase.

Steric Communication between Dynamic Components on DNA Nanodevices

Biomolecular nanotechnology has helped emulate basic robotic capabilities such as defined motion, sensing, and actuation in synthetic nanoscale systems. DNA origami is an attractive approach for nanorobotics, as it enables creation of devices with complex geometry, programmed motion, rapid actuation, force application, and various kinds of sensing modalities. Advanced robotic functions like feedback control, autonomy, or programmed routines also require the ability to transmit signals among subcomponents. Prior work in DNA nanotechnology has established approaches for signal transmission, for example through diffusing strands or structurally coupled motions. However, soluble communication is often slow and structural coupling of motions can limit the function of individual components, for example to respond to the environment. Here, we introduce an approach inspired by protein allostery to transmit signals between two distal dynamic components through steric interactions. These components undergo separate thermal fluctuations where certain conformations of one arm will sterically occlude conformations of the distal arm. We implement this approach in a DNA origami device consisting of two stiff arms each connected to a base platform via a flexible hinge joint. We demonstrate the ability for one arm to sterically regulate both the range of motion and the conformational state (latched or freely fluctuating) of the distal arm, results that are quantitatively captured by mesoscopic simulations using experimentally informed energy landscapes for hinge-angle fluctuations. We further demonstrate the ability to modulate signal transmission by mechanically tuning the range of thermal fluctuations and controlling the conformational states of the arms. Our results establish a communication mechanism well-suited to transmit signals between thermally fluctuating dynamic components and provide a path to transmitting signals where the input is a dynamic response to parameters like force or solution conditions.

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.

Waiting time dependence of aging

Aging phenomena have been observed in many non-equilibrium systems such as polymers and glasses, where physical properties depend on the waiting time between the starting time of observation and the time when the temperature is changed. The aging is classified into two types on the basis of the waiting time dependence of an instantaneous relaxation time: When the relaxation time is always an increasing function of the waiting time, the aging is called Type I and when it depends on the protocol of the temperature change, the aging is called Type II. Aging of a random walk in three dimensions is investigated when the free energy landscape controlling the jump rate responds to temperature change with a delay. It is shown that the intermediate scattering function of the random walk model exhibits Type II aging. It is also shown that the relaxation time of the free energy landscape can be deduced from the waiting time dependence of the instantaneous relaxation time.

In silico study of cox protein from P2 type enteric bacteriophages based on sequence, structure and dynamics to understand its functional integrity

Cox protein plays a critical role in deciding the lytic-lysogenic switch of P2 enteric phages. This phenomenon makes Cox protein one of the most important candidates in developing novel phage-based therapeutics against antibacterial resistant pathogens. The principle focus concerning protein and its decision making is a DNA binding event, which helps to regulate differential promoter expression. In the current study, we have attempted to understand the sequence, structural and dynamic features associated with Cox protein and its DNA binding. Unavailability of information was a big burden in further proceedings. We have done an extensive literature search to develop a database of Cox with relevant information. That information coupled with the methods of Sequence-based phylogenetic and conservation studies, Homology Modelling, Atomic-level Docking and Molecular Dynamics (MD) Simulation (50 ns each for 10 systems, i.e. total of 500 ns) were performed in the current study. Analysis of those extensive studies has provided us the required sequence to structure to dynamics to functional understanding. Our present study would indeed be very helpful in understanding the biochemical mechanism of Cox activation as well as designing potential phage therapeutics.

Large scale peptide screening against main protease of SARS CoV-2

The COVID-19 pandemic has been a public health emergency, with deadly forms constantly emerging around the world, highlighting the dire need for highly effective antiviral therapeutics. Peptide therapeutics show significant potential for this viral disease due to their efficiency, safety, and specificity. Here, two thousand seven hundred eight antibacterial peptides were screened computationally targeting the Main protease (Mpro) of SARS CoV-2. Six top-ranked peptides according to their binding scores, binding pose were investigated by molecular dynamics to explore the interaction and binding behavior of peptide-Mpro complexes. The structural and energetic characteristics of Mpro-DRAMP01760 and Mpro-DRAMP01808 complexes fluctuated less during a 250 ns MD simulation. In addition, three peptides (DRAMP01760, DRAMP01808, and DRAMP01342) bind strongly to Mpro protein, according to the free energy landscape and principal component analysis. Peptide helicity and secondary structure analysis are in agreement with our findings. Interaction analysis of protein-peptide complexes demonstrated that Mpro's residue CYS145, HIS41, PRO168, GLU166, GLN189, ASN142, MET49, and THR26 play significant contributions in peptide-protein attachment. Binding free energy analysis (MM-PBSA) demonstrated the energy profile of interacting residues of Mpro in peptide-Mpro complexes. To summarize, the peptides DRAMP01808 and DRAMP01760 may be highly Mpro specific, resulting disruption in a viral replication and transcription. The results of this research are expected to assist future research toward the development of antiviral peptide-based therapeutics for Covid-19 treatment.

Development of a deep learning-based quantitative structure-activity relationship model to identify potential inhibitors against the 3C-like protease of SARS-CoV-2

Background: In the recent COVID-19 pandemic, SARS-CoV-2 infection spread worldwide. The 3C-like protease (3CLpro) is a promising drug target for SARS-CoV-2. Results: We constructed a deep learning-based convolutional neural network-quantitative structure-activity relationship (CNN-QSAR) model and deployed it on various databases to predict the biological activity of 3CLpro inhibitors. Subsequently, molecular docking analysis, molecular dynamics simulations and binding free energy calculations were performed to validate the predicted inhibitory activity against 3CLpro of SARS-CoV-2. The model showed mean squared error = 0.114, mean absolute error = 0.24 and predicted R² = 0.84 for the test dataset. Diosmin showed good binding affinity and stability over the course of the simulations. Conclusion: The results suggest that the proposed CNN-QSAR model can be an efficient method for hit prediction and a new way to identify hit compounds against 3CLpro of SARS-CoV-2.

Characterizing (un)binding mechanism of USP7 inhibitors to unravel the cause of enhanced binding potencies at allosteric checkpoint

The ability to predict the intricate mechanistic behavior of ligands and associated structural determinants during protein-ligand (un)binding is of great practical importance in drug discovery. Ubiquitin specific protease-7 (USP7) is a newly emerging attractive cancer therapeutic target with bound allosteric inhibitors. However, none of the inhibitors have reached clinical trials, allowing opportunities to examine every aspect of allosteric modulation. The crystallographic insights reveal that these inhibitors have common properties such as chemical scaffolds, binding site and interaction fingerprinting. However, they still possess a broader range of binding potencies, ranging from 22 nM to 1,300 nM. Hence, it becomes more critical to decipher the structural determinants guiding the enhanced binding potency of the inhibitors. In this regard, we elucidated the atomic-level insights from both interacting partners, that is, protein-ligand perspective, and established the structure-activity link between USP7 inhibitors by using classical and advanced molecular dynamics simulations combined with linear interaction energy and molecular mechanics-Poisson Boltzmann surface area. We revealed the inhibitor potency differences by examining the contributions of chemical moieties and USP7 residues, the involvement of water-mediated interactions, and the thermodynamic landscape alterations. Additionally, the dissociation profiles aided in the establishment of a correlation between experimental potencies and structural determinants. Our study demonstrates the critical role of blocking loop 1 in allosteric inhibition and enhanced binding affinity. Comprehensively, our findings provide a constructive expansion of experimental outcomes and show the basis for varying binding potency using in-silico approaches. We expect this atomistic approach to be useful for effective drug design.

Interdisciplinary in silico studies to understand in-depth molecular level mechanism of drug resistance involving NS3-4A protease of HCV

Hepatitis C virus (HCV) causes hepatitis, a life-threatening disease responsible for liver cirrhosis. Urgent measures have been taken to develop therapeutics against this deadly pathogen. NS3/4A protease is an extremely important target. A series of inhibitors have been developed against this viral protease including Faldaprevir. Unfortunately, the error-prone viral RNA polymerase causes the emergence of resistance, thereby causing reduced effectiveness of those peptidomimetic inhibitors. Among the drug resistant variants, three single amino acid residues (R155, A156 and D168) are notable for their presence in clinical isolates and also their effectivity against most of the known inhibitors in clinical development. Therefore, it is crucial to understand the mechanistic role of those drug resistant variants while designing potent novel inhibitors. In this communication, we have deeply analyzed through using in silico studies to understand the molecular mechanism of alteration of inhibitor binding between wild type and its R155K, A156V and D168V variants. Principal component analysis was carried to identify the backbone fluctuations of important residues in HCV NS3/4A responsible for the inhibitor binding and maintaining drug resistance. Free energy landscape as a function of the principal components has been used to identify the stability and conformation of the key residues that regulate inhibitor binding and their impact in developing drug resistance. Our findings are consistent with the trend of experimental results. The observations are also true in case of other Faldaprevir-like peptidomimetic inhibitors. Understanding this binding mechanism would be significant for the development of novel inhibitors with less susceptibility towards drug resistance.

Counteractive Effects of Choline Geranate (CAGE) ILs and Ethanol on Insulin's Stability-A Leap Forward towards Oral Insulin Formulation

Choline geranate (CAGE) ionic liquids (ILs) stabilize insulin, thereby aiding its oral delivery, whereas ethanol (EtOH) affects its stability by disrupting the hydrophobic interactions. In this study, cognizance of the stabilization mechanism of insulin dimer in the presence of both CAGE ILs and EtOH mixtures is achieved through biased and unbiased molecular dynamics (MD) simulations. Here, two order parameters are employed to study the insulin dimer dissociation using well-tempered metadynamics (WT-MetaD). The stability of insulin is found to be strongly maintained until a 0.20 mole fraction of EtOH. Besides, higher concentrations of EtOH marginally affect the insulin stability. Moreover, geranate anions form a higher number of H-bonding interactions with water molecules, which aids insulin stabilization. Conversely, the addition of EtOH minimizes the water-mediated H-bonding interactions of geranate. Additionally, geranate traps the EtOH molecules, thereby preventing the interactions between insulin and EtOH. Furthermore, the free energy landscape (FEL) reveals the absence of dimer dissociation along with noticeable deviations in the distances R and the number of contacts Q. The dimerization free energy of insulin was calculated to be −16.1 kcal/mol at a 0.20 mole fraction of EtOH. Moreover, increments in mole fractions of EtOH effectuate a decrease in the insulin stability. Thus, the present study represents CAGE ILs as efficient insulin dimer stabilizes at low concentrations of EtOH.

The Glu143 Residue Might Play a Significant Role in T20 Peptide Binding to HIV-1 Receptor gp41: An In Silico Study

Despite the enormous efforts made to develop other fusion inhibitors for HIV, the enfuvirtide (known as T20) peptide is the only approved HIV-1 inhibitory drug so far. Investigating the role of potential residues of the T20 peptide’s conformational dynamics could help us to understand the role of potential residues of the T20 peptide. We investigated T20 peptide conformation and binding interactions with the HIV-1 receptor (i.e., gp41) using MD simulations and docking techniques, respectively. Although the mutation of E143 into alanine decreased the flexibility of the E143A mutant, the conformational compactness of the mutant was increased. This suggests a potential role of E143 in the T20 peptide’s conformation. Interestingly, the free energy landscape showed a significant change in the wild-type T20 minimum, as the E143A mutant produced two observed minima. Finally, the docking results of T20 to the gp41 receptor showed a different binding interaction in comparison to the E143A mutant. This suggests that E143 residue can influence the binding interaction with the gp41 receptor. Overall, the E143 residue showed a significant role in conformation and binding to the HIV-1 receptor. These findings can be helpful in optimizing and developing HIV-1 inhibitor peptides.

Bioactive Phytoconstituents as Potent Inhibitors of Tyrosine-Protein Kinase Yes (YES1): Implications in Anticancer Therapeutics

Tyrosine-protein kinase Yes (YES1) belongs to the Tyrosine-protein kinase family and is involved in several biological activities, including cell survival, cell–cell adhesion, cell differentiation, and cytoskeleton remodeling. It is highly expressed in esophageal, lung, and bladder cancers, and thus considered as an attractive drug target for cancer therapy. In this study, we performed a virtual screening of phytoconstituents from the IMPPAT database to identify potential inhibitors of YES1. Initially, the molecules were retrieved on their physicochemical properties following the Lipinski rule of five. Then binding affinities calculation, PAINS filter, ADMET, and PASS analyses followed by an interaction analysis to select safe and clinically better hits. Finally, two compounds, Glabrene and Lupinisoflavone C (LIC), with appreciable affinities and a specific interaction towards the AlphaFold predicted structure of YES1, were identified. Their time-evolution analyses were carried out using an all-atom molecular dynamics (MD) simulation, principal component analysis, and free energy landscapes. Altogether, we propose that Glabrene and LIC can be further explored in clinical settings to develop anticancer therapeutics targeting YES1 kinase.

A lesson for the maestro of the replication fork: Targeting the protein-binding interface of proliferating cell nuclear antigen for anticancer therapy

The proliferating cell nuclear antigen (PCNA) has emerged as a promising candidate for the development of novel cancer therapeutics. PCNA is a nononcogenic mediator of DNA replication that regulates a diverse range of cellular functions and pathways through a comprehensive list of protein-protein interactions. The hydrophobic binding pocket on PCNA offers an opportunity for the development of inhibitors to target various types of cancers and modulate protein-protein interactions. In the present study, we explored the binding modes and affinity of molecule I1 (standard molecule) with the previously suggested dimer interface pocket and the hydrophobic pocket present on the frontal side of the PCNA monomer. We also identified potential lead molecules from the library of in-house synthesized 3-methylenisoindolin-1-one based molecules to inhibit the protein-protein interactions of PCNA. Our results were based on robust computational methods, including molecular docking, conventional, steered, and umbrella sampling molecular dynamics simulations. Our results suggested that the standard inhibitor I1 interacts with the hydrophobic pocket of PCNA with a higher affinity than the previously suggested binding site. Also, the proposed molecules showed better or comparable binding free energies as calculated by the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach and further validated by enhanced umbrella sampling simulations. In vitro and in vivo methods could test the computationally suggested molecules for advancement in the drug discovery pipeline.

Human Vitamin K Epoxide Reductase as a Target of Its Redox Protein

Human vitamin K epoxide reductase (hVKORC1) enzymatic activity requires an initial activation by a specific redox protein, a less studied step in the hVKORC1 vital cycle. Significant steric conditions must be met by enzymes, being that to adapt their configurations is mandatory for hVKORC1 activation. We studied, by molecular dynamics (MD) simulations, the folding and conformational plasticity of hVKORC1 in its inactive (fully oxidised) state using available structures, crystallographic and from de novo modelling. According to the obtained results, hVKORC1 is a modular protein composed of the stable transmembrane domain (TMD) and intrinsically disordered luminal (L) loop, possessing the great plasticity/adaptability required to perform various steps of the activation process. The docking (HADDOCK) of Protein Disulfide Isomerase (PDI) onto different hVKORC1 conformations clearly indicated that the most interpretable solutions were found on the target closed L-loop form, a prevalent conformation of hVKORC1’s oxidised state. We also suggest that the cleaved L-loop is an appropriate entity to study hVKORC1 recognition/activation by its redox protein. Additionally, the application of hVKORC1 (membrane protein) in aqueous solution is likely to prove to be very useful in practice in either in silico studies or in vitro experiments.

Discovery of multi-target mur enzymes inhibitors with anti-mycobacterial activity through a Scaffold approach

In the present study, we generated a ligand-based scaffold model from a known bioactive datasets of mur enzymes of other species to identify multi-targeting inhibitors as antitubercular agents. Compounds in the ChEMBL database were first filtered to screen for substructure molecules ofMtb's multi-target enzymes. 5'-O-(5-Amino-5-deoxy-β-D-ribofuranosyl)uridine has been identified as scaffold to develop compounds targeting Mtb's mur enzymes. A library of Murcko scaffolds was extracted and evaluated for their in-silico antitubercular activity against Mtb's mur enzymes. The screened compounds were subjected to molecular docking, molecular dynamics simulations, MM/PBSA calculation with Mtb's mur enzymes to evaluate the mechanism of interaction to assess inhibitory activity against the target protein. The results revealed that 15 compounds have higher docking scores and good interactions with multiple mur enzymes of Mtb. From the docking analysis, compound HPT had the best score and binding affinity with the all mur enzymes. Further, protein-ligand interactions were evaluated by molecular dynamics simulations to assess their stability throughout 100 ns period. From the MD trajectory, we calculated RMSD, RMSF, Rg, PCA, DCCM, FEL, hydrogen bonding, and vector motion. Furthermore, the binding free energies of the all nine mur enzymes with compound HPT exhibited good binding affinity might show the anti-mycobacterial activity. The compound HPT revealed from this computational study could act as potent anti-mycobacterial inhibitors and further serve as lead scaffolds to develop more potent pharmaceutical molecules targeting multiple mur enzymes of Mtb based on 5'-O-(5-Amino-5-deoxy-β-D-ribofuranosyl)uridine in the future. Communicated by Ramaswamy H. Sarma.

Is Protein Folding a Thermodynamically Unfavorable, Active, Energy-Dependent Process?

The prevailing current view of protein folding is the thermodynamic hypothesis, under which the native folded conformation of a protein corresponds to the global minimum of Gibbs free energy G. We question this concept and show that the empirical evidence behind the thermodynamic hypothesis of folding is far from strong. Furthermore, physical theory-based approaches to the prediction of protein folds and their folding pathways so far have invariably failed except for some very small proteins, despite decades of intensive theory development and the enormous increase of computer power. The recent spectacular successes in protein structure prediction owe to evolutionary modeling of amino acid sequence substitutions enhanced by deep learning methods, but even these breakthroughs provide no information on the protein folding mechanisms and pathways. We discuss an alternative view of protein folding, under which the native state of most proteins does not occupy the global free energy minimum, but rather, a local minimum on a fluctuating free energy landscape. We further argue that ΔG of folding is likely to be positive for the majority of proteins, which therefore fold into their native conformations only through interactions with the energy-dependent molecular machinery of living cells, in particular, the translation system and chaperones. Accordingly, protein folding should be modeled as it occurs in vivo, that is, as a non-equilibrium, active, energy-dependent process.

Repurposing fusion inhibitor peptide against SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving. Although several vaccines were approved, this pandemic is still a major threat to public life. Till date, no established therapies are available against SARS-CoV-2. Peptide inhibitors hold great promise for this viral pathogen due to their efficacy, safety, and specificity. In this study, seventeen antiviral peptides which were known to inhibit SARS-CoV-1 are collected and computationally screened against heptad repeat 1 (HR1) of the SARS-CoV-2 spike protein (S2). Out of 17 peptides, Fp13 and Fp14 showed better binding affinity toward HR1 compared to a control peptide EK1 (a modified pan-coronavirus fusion inhibitor) in molecular docking. To explore the time-dependent interactions of the fusion peptide with HR1, molecular dynamics simulation was performed incorporating lipid membrane. During 100 ns MD simulation, structural and energy parameters of Fp13-HR1 and Fp14-HR1 complexes demonstrated lower fluctuations compared to the control EK1-HR1 complex. Furthermore, principal component analysis and free energy landscape study revealed that these two peptides (Fp13 and Fp14) strongly bind to the HR1 with higher affinity than that of control EK1. Tyr917, Asn919, Gln926, lys933, and Gln949 residues in HR1 protein were found to be crucial residues for peptide interaction. Notably, Fp13, Fp14 showed reasonably better binding free energy and hydrogen bond contribution than that of EK1. Taken together, Fp13 and Fp14 peptides may be highly specific for HR1 which can potentially prevent the formation of the fusion core and could be further developed as therapeutics for treatment or prophylaxis of SARS-CoV-2 infection.

Localization, Disorder, and Entropy in a Coarse-Grained Model of the Amorphous Solid

We study the role of disorder in producing the metastable states in which the extent of mass localization is intermediate between that of a liquid and a crystal with long-range order. We estimate the corresponding entropy with the coarse-grained description of a many-particle system used in the classical density functional model. We demonstrate that intermediate localization of the particles results in a change of the entropy from what is obtained from a microscopic approach using for sharply localized vibrational modes following a Debye distribution. An additional contribution is included in the density of vibrational states g(ω) to account for this excess entropy. A corresponding peak in g(ω)/ω2 vs. frequency ω matches the characteristic boson peak seen in amorphous solids. In the present work, we also compare the shear modulus for the inhomogeneous solid having localized density profiles with the corresponding elastic response for the uniform liquid in the limit of high frequencies.

Mutations of SARS-CoV-2 RBD May Alter Its Molecular Structure to Improve Its Infection Efficiency

The receptor-binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates the viral-host interaction and is a target for most neutralizing antibodies. Nevertheless, SARS-CoV-2 RBD mutations pose a threat due to their role in host cell entry via the human angiotensin-converting enzyme 2 receptor that might strengthen SARS-CoV-2 infectivity, viral load, or resistance against neutralizing antibodies. To understand the molecular structural link between RBD mutations and infectivity, the top five mutant RBDs (i.e., N501Y, E484K L452R, S477N, and N439K) were selected based on their recorded case numbers. These mutants along with wild-type (WT) RBD were studied through all-atom molecular dynamics (MD) simulations of 100 ns. The principal component analysis and the free energy landscape were used too. Interestingly, N501Y, N439K, and E484K mutations were observed to increase the rigidity in some RBD regions while increasing the flexibility of the receptor-binding motif (RBM) region, suggesting a compensation of the entropy penalty. However, S477N and L452R RBDs were observed to increase the flexibility of the RBM region while maintaining similar flexibility in other RBD regions in comparison to WT RBD. Therefore, both mutations (especially S477N) might destabilize the RBD structure, as loose conformation compactness was observed. The destabilizing effect of S477N RBD was consistent with previous work on S477N mutation. Finally, the free energy landscape results showed that mutations changed WT RBD conformation while local minima were maintained for all mutant RBDs. In conclusion, RBD mutations definitely impact the WT RBD structure and conformation as well as increase the binding affinity to angiotensin-converting enzyme receptor.

Folding and Intrinsic Disorder of the Receptor Tyrosine Kinase KIT Insert Domain Seen by Conventional Molecular Dynamics Simulations

The kinase insert domain (KID) of RTK KIT is the key recruitment region for downstream signalling proteins. KID, studied by molecular dynamics simulations as a cleaved polypeptide and as a native domain fused to KIT, showed intrinsic disorder represented by a set of heterogeneous conformations. The accurate atomistic models showed that the helical fold of KID is mainly sequence dependent. However, the reduced fold of the native KID suggests that its folding is allosterically controlled by the kinase domain. The tertiary structure of KID represents a compact array of highly variable α- and 3₁₀-helices linked by flexible loops playing a principal role in the conformational diversity. The helically folded KID retains a collapsed globule-like shape due to non-covalent interactions associated in a ternary hydrophobic core. The free energy landscapes constructed from first principles-the size, the measure of the average distance between the conformations, the amount of helices and the solvent-accessible surface area-describe the KID disorder through a collection of minima (wells), providing a direct evaluation of conformational ensembles. We found that the cleaved KID simulated with restricted N- and C-ends better reproduces the native KID than the isolated polypeptide. We suggest that a cyclic, generic KID would be best suited for future studies of KID f post-transduction effects.

Structure and Sequence-based Computational Approaches to Allosteric Signal Transduction: Application to Electromechanical Coupling in Voltage-gated Ion Channels

Allosteric signaling underlies the function of many biomolecules, including membrane proteins such as ion channels. Experimental methods have enabled specific quantitative insights into the coupling between the voltage sensing domain (VSD) and the pore gate of voltage-gated ion channels, located tens of Ångström apart from one another, as well as pinpointed specific residues and domains that participate in electromechanical signal transmission. Nevertheless, an overall atomic-level resolution picture is difficult to obtain from these methods alone. Today, thanks to the cryo-EM resolution revolution, we have access to high resolution structures of many different voltage-gated ion channels in various conformational states, putting a quantitative description of the processes at the basis of these changes within our close reach. Here, we review computational methods that build on structures to detect and characterize allosteric signaling and pathways. We then examine what has been learned so far about electromechanical coupling between VSD and pore using such methods. While no general theory of electromechanical coupling in voltage-gated ion channels integrating results from all these methods is available yet, we outline the types of insights that could be achieved in the near future using the methods that have not yet been put to use in this field of application.

Quantify the combined effects of temperature and force on the stability of DNA hairpin

OxDNA, as a successful coarse-grain model, has been applied to reproduce the thermodynamic and mechanical properties of both single- and double-stranded DNA. In current simulation, oxDNA is extended to explore the combined effects of temperature and force on the stability of DNA hairpin and its free energy landscape. Simulations were carried out at different forces and temperatures, at each temperature, a 18-base-pair DNA hairpin dynamically transited between folded state and unfolded state, and the separation between two states is consistent with the full contour length of single-stranded DNA in the unfolded state. Two methods were used to identify the critical force of DNA hairpin at each temperature and the critical forces obtained from two methods were consistent with each other and gradually decreased with the increasing temperature from 300 K to 326 K. The critical force at 300 K is reasonably consistent with the single molecule result of DNA hairpin with the same stem length. The two-state free energy landscape can be elucidated from the probability distribution of DNA hairpin extension and its dependence on the force and temperature is totally different. The increasing temperature not only reduces the free energy barrier, but also alters the position of transition point along the extension coordinate, resulting in the reduction of folding distance and the extension of unfolding distance, but their sum is not obviously dependent on the temperature. Generally, an assumption that the location of transition state in two-state energy landscape is independent of the stretching force is used to analyze the data of the single molecule experiment, but current simulation results indicate that effects of stretching forces on the location of transition state in two-state energy landscape are dependent on temperature. At relatively high temperature, stretching force can also change the location of transition state in the free energy landscape.

Identifying the natural polyphenol catechin as a multi-targeted agent against SARS-CoV-2 for the plausible therapy of COVID-19: an integrated computational approach

The global pandemic crisis, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed the lives of millions of people across the world. Development and testing of anti-SARS-CoV-2 drugs or vaccines have not turned to be realistic within the timeframe needed to combat this pandemic. Here, we report a comprehensive computational approach to identify the multi-targeted drug molecules against the SARS-CoV-2 proteins, whichare crucially involved in the viral-host interaction, replication of the virus inside the host, disease progression and transmission of coronavirus infection. Virtual screening of 75 FDA-approved potential antiviral drugs against the target proteins, spike (S) glycoprotein, human angiotensin-converting enzyme 2 (hACE2), 3-chymotrypsin-like cysteine protease (3CLpro), cathepsin L (CTSL), nucleocapsid protein, RNA-dependent RNA polymerase (RdRp) and non-structural protein 6 (NSP6), resulted in the selection of seven drugs which preferentially bind to the target proteins. Further, the molecular interactions determined by molecular dynamics simulation revealed that among the 75 drug molecules, catechin can effectively bind to 3CLpro, CTSL, RBD of S protein, NSP6 and nucleocapsid protein. It is more conveniently involved in key molecular interactions, showing binding free energy (ΔGbind) in the range of -5.09 kcal/mol (CTSL) to -26.09 kcal/mol (NSP6). At the binding pocket, catechin is majorly stabilized by the hydrophobic interactions, displays ΔEvdW values: -7.59 to -37.39 kcal/mol. Thus, the structural insights of better binding affinity and favorable molecular interaction of catechin toward multiple target proteins signify that catechin can be potentially explored as a multi-targeted agent against COVID-19.

Red-Edge Excitation Shift Spectroscopy (REES): Application to Hidden Bound States of Ligands in Protein-Ligand Complexes

Ligand-protein binding is responsible for the vast majority of bio-molecular functions. Most experimental techniques examine the most populated ligand-bound state. The determination of less populated, intermediate, and transient bound states is experimentally challenging. However, hidden bound states are also important because these can strongly influence ligand binding and unbinding processes. Here, we explored the use of a classical optical spectroscopic technique, red-edge excitation shift spectroscopy (REES) to determine the number, population, and energetics associated with ligand-bound states in protein–ligand complexes. We describe a statistical mechanical model of a two-level fluorescent ligand located amongst a finite number of discrete protein microstates. We relate the progressive emission red shift with red-edge excitation to thermodynamic parameters underlying the protein–ligand free energy landscape and to photo-physical parameters relating to the fluorescent ligand. We applied the theoretical model to published red-edge excitation shift data from small molecule inhibitor–kinase complexes. The derived thermodynamic parameters allowed dissection of the energetic contribution of intermediate bound states to inhibitor–kinase interactions.

Exploring the Cold-Adaptation Mechanism of Serine Hydroxymethyltransferase by Comparative Molecular Dynamics Simulations

Cold-adapted enzymes feature a lower thermostability and higher catalytic activity compared to their warm-active homologues, which are considered as a consequence of increased flexibility of their molecular structures. The complexity of the (thermo)stability-flexibility-activity relationship makes it difficult to define the strategies and formulate a general theory for enzyme cold adaptation. Here, the psychrophilic serine hydroxymethyltransferase (pSHMT) from Psychromonas ingrahamii and its mesophilic counterpart, mSHMT from Escherichia coli, were subjected to μs-scale multiple-replica molecular dynamics (MD) simulations to explore the cold-adaptation mechanism of the dimeric SHMT. The comparative analyses of MD trajectories reveal that pSHMT exhibits larger structural fluctuations and inter-monomer positional movements, a higher global flexibility, and considerably enhanced local flexibility involving the surface loops and active sites. The largest-amplitude motion mode of pSHMT describes the trends of inter-monomer dissociation and enlargement of the active-site cavity, whereas that of mSHMT characterizes the opposite trends. Based on the comparison of the calculated structural parameters and constructed free energy landscapes (FELs) between the two enzymes, we discuss in-depth the physicochemical principles underlying the stability-flexibility-activity relationships and conclude that (i) pSHMT adopts the global-flexibility mechanism to adapt to the cold environment and, (ii) optimizing the protein-solvent interactions and loosening the inter-monomer association are the main strategies for pSHMT to enhance its flexibility.

Identification of ligand-specific G protein-coupled receptor states and prediction of downstream efficacy via data-driven modeling

Ligand binding stabilizes different G protein-coupled receptor states via a complex allosteric process that is not completely understood. Here, we have derived free energy landscapes describing activation of the β₂ adrenergic receptor bound to ligands with different efficacy profiles using enhanced sampling molecular dynamics simulations. These reveal shifts toward active-like states at the Gprotein-binding site for receptors bound to partial and full agonists, and that the ligands modulate the conformational ensemble of the receptor by tuning protein microswitches. We indeed find an excellent correlation between the conformation of the microswitches close to the ligand binding site and in the transmembrane region and experimentally reported cyclic adenosine monophosphate signaling responses. Dimensionality reduction further reveals the similarity between the unique conformational states induced by different ligands, and examining the output of classifiers highlights two distant hotspots governing agonism on transmembrane helices 5 and 7.

A QM/MM simulation study of transamination reaction at the active site of aspartate aminotransferase: Free energy landscape and proton transfer pathways

Transaminase is a key enzyme for amino acid metabolism, which reversibly catalyzes the transamination reaction with the help of PLP (pyridoxal 5^' -phosphate) as its cofactor. Here we have investigated the mechanism and free energy landscape of the transamination reaction involving the aspartate transaminase (AspTase) enzyme and aspartate-PLP (Asp-PLP) complex using QM/MM simulation and metadynamics methods. The reaction is found to follow a stepwise mechanism where the active site residue Lys258 acts as a base to shuttle a proton from α-carbon (CA) to imine carbon (C4A) of the PLP-Asp Schiff base. In the first step, the Lys258 abstracts the CA proton of the substrate leading to the formation of a carbanionic intermediate which is followed by the reprotonation of the Asp-PLP Schiff base at C4A atom by Lys258. It is found that the free energy barrier for the proton abstraction by Lys258 and that for the reprotonation are 17.85 and 3.57 kcal/mol, respectively. The carbanionic intermediate is 7.14 kcal/mol higher in energy than the reactant. Hence, the first step acts as the rate limiting step. The present calculations also show that the Lys258 residue undergoes a conformational change after the first step of transamination reaction and becomes proximal to C4A atom of the Asp-PLP Schiff base to favor the second step. The active site residues Tyr70* and Gly38 anchor the Lys258 in proper position and orientation during the first step of the reaction and stabilize the positive charge over Lys258 generated at the intermediate step.

Persistent homology and application on residues 1 to 28 of amyloid beta peptide

This article combines the principal component analysis (PCA) with persistent homology for applications in biomolecular data analysis. We extend the technique of persistent homology to localized weighted persistent homology to fit the properties of molecules. We introduce this novel PCA in the study of the folding process of residues 1 to 28 of amyloid beta peptide in solution. We are able to determine seven metastable states of amyloid beta 1 to 28 using homology of dimension 2, corresponding to seven local minimums in the free energy landscape. We also give the transition information between the seven types and the disconnectivity graph. Our result is very robust under change of parameters. Furthermore persistent homology of dimension 1 also give consistent results. This method can be applied to different peptides and molecules.

Exhaustive search of the configurational space of heat-shock protein 90 with its inhibitor by multicanonical molecular dynamics based dynamic docking

Multicanonical molecular dynamics based dynamic docking was used to exhaustively search the configurational space of an inhibitor binding to the N-terminal domain of heat-shock protein 90 (Hsp90). The obtained structures at 300 K cover a wide structural ensemble, with the top two clusters ranked by their free energy coinciding with the native binding site. The representative structure of the most stable cluster reproduced the experimental binding configuration, but an interesting conformational change in Hsp90 could be observed. The combined effects of solvation and ligand binding shift the equilibrium from a preferred loop-in conformation in the unbound state to an α-helical one in the bound state for the flexible lid region of Hsp90. Thus, our dynamic docking method is effective at predicting the native binding site while exhaustively sampling a wide configurational space, modulating the protein structure upon binding.

Identification of Selective Novel Hits against Plasmodium falciparum Prolyl tRNA Synthetase Active Site and a Predicted Allosteric Site Using in silico Approaches

Recently, there has been increased interest in aminoacyl tRNA synthetases (aaRSs) as potential malarial drug targets. These enzymes play a key role in protein translation by the addition of amino acids to their cognate tRNA. The aaRSs are present in all Plasmodium life cycle stages, and thus present an attractive malarial drug target. Prolyl tRNA synthetase is a class II aaRS that functions in charging tRNA with proline. Various inhibitors against Plasmodium falciparum ProRS (PfProRS) active site have been designed. However, none have gone through clinical trials as they have been found to be highly toxic to human cells. Recently, a possible allosteric site was reported in PfProRS with two possible allosteric modulators: glyburide and TCMDC-124506. In this study, we sought to identify novel selective inhibitors targeting PfProRS active site and possible novel allosteric modulators of this enzyme. To achieve this, virtual screening of South African natural compounds against PfProRS and the human homologue was carried out using AutoDock Vina. The modulation of protein motions by ligand binding was studied by molecular dynamics (MD) using the GROningen MAchine for Chemical Simulations (GROMACS) tool. To further analyse the protein global motions and energetic changes upon ligand binding, principal component analysis (PCA), and free energy landscape (FEL) calculations were performed. Further, to understand the effect of ligand binding on the protein communication, dynamic residue network (DRN) analysis of the MD trajectories was carried out using the MD-TASK tool. A total of ten potential natural hit compounds were identified with strong binding energy scores. Binding of ligands to the protein caused observable global and residue level changes. Dynamic residue network calculations showed increase in betweenness centrality (BC) metric of residues at the allosteric site implying these residues are important in protein communication. A loop region at the catalytic domain between residues 300 and 350 and the anticodon binding domain showed significant contributions to both PC1 and PC2. Large motions were observed at a loop in the Z-domain between residues 697 and 710 which was also in agreement with RMSF calculations that showed increase in flexibility of residues in this region. Residues in this loop region are implicated in ATP binding and thus a change in dynamics may affect ATP binding affinity. Free energy landscape (FEL) calculations showed that the holo protein (protein-ADN complex) and PfProRS-SANC184 complexes were stable, as shown by the low energy with very few intermediates and hardly distinguishable low energy barriers. In addition, FEL results agreed with backbone RMSD distribution plots where stable complexes showed a normal RMSD distribution while unstable complexes had multimodal RMSD distribution. The betweenness centrality metric showed a loss of functional importance of key ATP binding site residues upon allosteric ligand binding. The deep basins in average L observed at the allosteric region imply that there is high accessibility of residues at this region. To further analyse BC and average L metrics data, we calculated the ΔBC and ΔL values by taking each value in the holo protein BC or L matrix less the corresponding value in the ligand-bound complex BC or L matrix. Interestingly, in allosteric complexes, residues located in a loop region implicated in ATP binding had negative ΔL values while in orthosteric complexes these residues had positive ΔL values. An increase in contact frequency between residues Ser263, Thr267, Tyr285, and Leu707 at the allosteric site and residues Thr397, Pro398, Thr402, and Gln395 at the ATP binding TXE loop was observed. In summary, this study identified five potential orthosteric inhibitors and five allosteric modulators against PfProRS. Allosteric modulators changed ATP binding site dynamics, as shown by RMSF, PCA, and DRN calculations. Changes in dynamics of the ATP binding site and increased contact frequency between residues at the proposed allosteric site and the ATP binding site may explain how allosteric modulators distort the ATP binding site and thus might inhibit PfProRS. The scaffolds of the identified hits in the study can be used as a starting point for antimalarial inhibitor development with low human cytotoxicity.

New Insight into Mechanisms of Protein Adaptation to High Temperatures: A Comparative Molecular Dynamics Simulation Study of Thermophilic and Mesophilic Subtilisin-Like Serine Proteases

In high-temperature environments, thermophilic proteins must possess enhanced thermal stability in order to maintain their normal biological functions. However, the physicochemical basis of the structural stability of thermophilic proteins at high temperatures remains elusive. In this study, we performed comparative molecular dynamics simulations on thermophilic serine protease (THM) and its homologous mesophilic counterpart (PRK). The comparative analyses of dynamic structural and geometrical properties suggested that THM adopted a more compact conformation and exhibited more intramolecular interactions and lower global flexibility than PRK, which could be in favor of its thermal stability in high-temperature environments. Comparison between protein solvent interactions and the hydrophobicity of these two forms of serine proteases showed that THM had more burial of nonpolar areas, and less protein solvent hydrogen bonds (HBs), indicating that solvent entropy maximization and mobility may play a significant role in THM's adaption to high temperature environments. The constructed funnel-like free energy landscape (FEL) revealed that, in comparison to PRK, THM had a relatively flat and narrow free energy surface, and a lower minimum free energy level, suggesting that the thermophilic form had lower conformational diversity and flexibility. Combining the FEL theory and our simulation results, we conclude that the solvent (entropy force) plays a significant role in protein adaption at high temperatures.

Are Parallel Proliferation Pathways Redundant?

Are the receptor tyrosine kinase (RTK) and JAK-STAT-driven proliferation pathways 'parallel' or 'redundant'? And what about those of K-Ras4B versus N-Ras? 'Parallel' proliferation pathways accomplish a similar drug resistance outcome. Thus, are they 'redundant'? In this paper, it is argued that there is a fundamental distinction between 'parallel' and 'redundant'. Cellular proliferation pathways are influenced by the genome sequence, 3D organization and chromatin accessibility, and determined by protein availability prior to cancer emergence. In the opinion presented, if they operate the same downstream protein families, they are redundant; if evolutionary-independent, they are parallel. Thus, RTK and JAK-STAT-driven proliferation pathways are parallel; those of Ras isoforms are redundant. Our Precision Medicine Call to map cancer proliferation pathways is vastly important since it can expedite effective therapeutics.

Understanding the mechanism of amygdalin's multifunctional anti-cancer action using computational approach

Amygdalin possesses anticancer properties and induces apoptosis. Based on experimental studies the presence of amygdalin with cancer cells led to activate the caspase-3 and BAX and inhibits Bcl-2 and Poly (ADP-ribose) polymerase-1 (PARP-1) but without deep information on action mode of these activities. Herein, we leaped forward to examine the molecular dynamics of the bound amygdalin and free ligand proteins, to identify precise action (conformation changes in targeted proteins) of amygdalin through using double docking and molecular dynamics (MD) simulations for 50 ns time scale. The MD simulations revealed that the binding of amygdalin led to disrupting the interaction between the Bcl-2/BAX complex. We furthermore conducted MD simulation for Bcl-2/amygdalin to investigate the stability of the complex which is responsible for inhibition of Bcl-2. It has been obtained a stable Bcl-2/amygdalin complex during the 50 ns. The results give a detail explanation of how amygdalin activates BAX and inhibits Bcl-2. For caspase-3, the matter is different, we found that amygdalin led to disrupting the interaction of caspase-3's two chains for intervals during 50 ns and then bind together repeatedly. The mechanism of caspase-3's activation through switching by disrupt the interacts for periodic intervals manner. For PARP-1, the dynamics simulations results indicated amygdalin interacts with PARP-1's binding site and forms stable interaction during simulation to render it inactive. Hence, amygdalin revealed a supernatural behavior through the MD simulations: it revealed a further clarification of the mystery amygdalin's experimental action which can act as a multifunctional drug in the cancer therapeutics.Communicated by Ramaswamy H. Sarma.

Conformational flexibility correlates with glucose tolerance for point mutations in β-glucosidases - a computational study

β-glucosidases (EC 3.2.1.21) have been described as essential to second-generation biofuel production. They act in the last step of the lignocellulosic saccharification, cleaving the β - 1,4 glycosidic bonds in cellobiose to produce two molecules of glucose. However, β-glucosidases have been described as strongly inhibited by glucose, causing an increment of cellobiose concentration. Also, cellobiose is an inhibitor of other enzymes used in this process, such as exoglucanases and endoglucanases. Hence, the engineering of thermostable and glucose-tolerant β-glucosidases has been targeted by many studies. In this study, we performed high sampling accelerated molecular dynamics for a wild glucose-tolerant GH1 β-glucosidase (Bgl1A), a wild non-tolerant (Bgl1B), and a set of glucose-tolerant Bgl1B's mutants: V302F, N301Q/V302F, F172I, V227M, G246S, T299S, and H228T. Our results suggest that point mutations promissory to induce glucose tolerance trend to enhance the mobility of the flexible loops around the active site. Mutations affected B and C loops regions, and an αβ-hairpin motif between them. Conformational clusters and free energy landscape profiles suggest that the mobility acquired by mutants allows a higher closure of the substrate channel. This closure is compatible with a higher impedance for glucose entrance and stimulus of its withdrawal. Based on mutants' structural analyses, we inferred that both the direct stereochemical effect on the glucose path and the changes in the mobility affect glucose tolerance. We hope these results be useful for the rational design of glucose-tolerant and industrially promising enzymes.Communicated by Ramaswamy H. Sarma.