Molecular dynamics-solvated interaction energy studies of protein-protein interactions: the MP1-p14 scaffolding complex

Molecular dynamics of transferrin receptor binder peptides: unlocking blood-brain barrier for enhanced CNS drug delivery

A cystine-dense peptide (CDP) named TfRB1 was identified for its ability to bind to the transferrin receptor (TfR). CDPs are stabilized by their disulfide bonds, and variants of TfRB1 - specifically TfRB1G1, TfRB1G2, and TfRB1G3 - are explored for their potential to transport molecules across the blood-brain barrier (BBB) into the central nervous system (CNS). This study employed molecular modeling and dynamics simulations to characterize the interactions between these TfRB1 variants and TfR. Binding free energy calculations showed a strong correlation with experimental binding affinities of -10.99 kcal/mol for TfRB1G2 and -13.18 kcal/mol for TfRB1G3, with a relative error of 1.98%. The key forces driving these interactions include electrostatic and van der Waals forces, with mutations in TfRB1G3 (T9M and A13D) enhancing its binding affinity through improved interactions with residues such as Arg633. The free energy landscape analysis revealed that TfRB1G3 maintains the N-terminal residues of TfR in an α-helical conformation, unlike TfRB1G2. Per-residue free energy decomposition identified key residues - Leu619, Arg629, Tyr643, and Phe650 - as crucial for TfR binding, underscoring their competitive nature with transferrin. Additionally, Glu612, which is favorable for binding in TfRB1G2, becomes unfavorable in TfRB1G3. Conversely, Arg633 shifts from unfavorable in TfRB1G2 to favorable in TfRB1G3, compensating for the loss of favorable interaction with Glu612. These findings provide valuable molecular insights into the TfRB1 peptides' potential as drug carriers, highlighting their capability to deliver molecules to the CNS and compete with transferrin for BBB transport.

Novel Quinoline- and Naphthalene-Incorporated Hydrazineylidene-Propenamide Analogues as Antidiabetic Agents: Design, Synthesis, and Computational Studies

Background: Type 2 diabetes has become a significant global health challenge. Numerous drugs have been developed to treat the condition, either as standalone therapies or in combination when glycemic control cannot be achieved with a single medication. As existing treatments often come with limitations, there is an increasing focus on creating novel therapeutic agents that offer greater efficacy and fewer side effects to better address this widespread issue. Methods: The methylene derivatives 3a,b were coupled with phenyl/ethyl isothiocyanate in the basic medium, and dimethyl sulfate was subsequently added. Further, 5a-d were reacted with the quinoline/naphthalene hydrazides 6a,b. The target compounds 7a-g were subjected to the in vitro enzyme inhibition studies on α-glucosidase, α-amylase, and aldose reductase. Results: 7g exerted remarkable inhibitory effects on α-glycosidase [Inhibitory Concentration (IC50): 20.23 ± 1.10 µg/mL] and α-amylase (17.15 ± 0.30 µg/mL), outperforming acarbose (28.12 ± 0.20 µg/mL for α-glycosidase and 25.42 ± 0.10 µg/mL for α-amylase), and exhibited a strong inhibition action on aldose reductase (12.15 ± 0.24 µg/mL), surpassing quercetin (15.45 ± 0.32 µg/mL) and the other tested compounds. In a computational study, 7g demonstrated promising binding affinities (-8.80, -8.91 kcal/mol) with α-glycosidase and α-amylase, compared to acarbose (-10.87, -10.38 kcal/mol) for α-glycosidase and α-amylase. Additionally, 7g had strong binding with aldose reductase (-9.20 kcal/mol) in comparison to quercetin (-9.95 kcal/mol). Molecular dynamics (MDs) simulations demonstrated that 7g remained stable over a 100 ns simulation period, and the binding free energy estimates remained consistent throughout this time. Conclusions: We reported the modification of quinoline and naphthalene rings to hydrazineylidene-propenamides 7a-g using various synthetic approaches. 7g emerged as a leading candidate, exhibiting greater inhibition of α-glycosidase, α-amylase, and aldose reductase. These findings underscore their potential as essential molecules for the development of innovative antidiabetic treatments.

Selective inhibition mechanism of three inhibitors to BRD4 uncovered by molecular docking and molecular dynamics simulations

Bromodomain-containing protein 4 (BRD4) plays an important role in gene transcription in a variety of diseases, including inflammation and cancer. However, the mechanism by which the BRD4 inhibitors bind selectively to its bromodomain 1 (BRD4-BD1) and bromodomain 2 (BRD4-BD2) remains unclear. Studying the interaction mechanism between bromodomain of BRD4 and inhibitors will provide new ideas for drug development and disease treatment. To explore the molecular mechanism of selective binding of three novel phenoxypyridone Cpd11, Cpd14, and Cpd23 to BRD4-BD1 and BRD4-BD2, respectively, molecular docking, molecular dynamics (MD) simulation, and free energy calculation containing molecular mechanics generalized born surface area (MM-GBSA) and solvation interaction energy (SIE) were achieved. The results show that these three inhibitors have different effects on the internal dynamics of BRD4-BD1 and BRD4-BD2, but the key interactions are similar. Key residues of BRD4-BD1 and BRD4-BD2, Ile146/Val439, Trp81/Trp374, Phe83/Phe375, Val87/Val380, Leu92/Leu385, Leu94/Leu387, Tyr97/Tyr390, and Asn140/Asn433, play a key role in selective binding of BRD4-BD1 and BRD4-BD2 to these three inhibitors. At the same time, non-polar interactions, especially van der Waals interactions, are the main drivers of the interactions of these three inhibitors with BRD4-BD1 and BRD4-BD2. These results provide useful dynamic and energy information for the development of novel highly selective phenoxypyridone inhibitors targeting BRD4-BD2.

Computational Prediction of 3,5-Diaryl-1H-Pyrazole and spiropyrazolines derivatives as potential acetylcholinesterase inhibitors for alzheimer disease treatment by 3D-QSAR, molecular docking, molecular dynamics simulation, and ADME-Tox

The efficacy of 40 synthesized variants of 3,5-diaryl-1H-pyrazole and spiropyrazoline' derivatives as acetylcholinesterase inhibitors is verified using a quantitative three-dimensional structure-activity relationship (3D-QSAR) by comparative molecular field analysis (CoMFA) and molecular similarity index analysis (CoMSIA) models. In this research, different field models proved that CoMSIA/SE model is the best model with high predictive power compared to several models (Qved2 = O.65; R2 = 0.980; R2test = 0.727). Also, contour maps produced by CoMSIA/SE model have been employed to prove the key structural needs of the activity. Consequently, six new compounds have been generated. Among these compounds, M4 and M5 were the most active but remained toxic and had poor absorption capacities. While the M1, M2, M3 and M6 remained highly active while respecting ADMET's characteristics. Molecular docking results showed compound M2 better with acetylcholinesterase than compound 22. The interactions are classical hydrogen bonding with residues TYR:124, TYR:72, and SER:293, which play a critical role in the biological activity as AChE inhibitors. MD results confirmed the docking results and showed that compound M2 had satisfactory stability with (ΔGbinding = -151.225 KJ/mol) in the active site of AChE receptor compared with compound 22 (ΔGbinding = -133.375 KJ/mol). In addition, both compounds had good stability regarding RMSD, Rg, and RMSF. The previous results show that the newly designed compound M2 is more active in the active site of AChE receptor than compound 22.Communicated by Ramaswamy H. Sarma.

The Excellent Chemical Interaction Properties of Poloxamer and Pullulan with Alpha Mangostin on Amorphous Solid Dispersion System: Molecular Dynamics Simulation

BACKGROUND

Alpha mangostin (AM) has demonstrated significant potential as an anticancer agent, owing to its potent bioactivity. However, its clinical application is limited by poor solubility, which hampers its bioavailability and effectiveness. Amorphous solid dispersion (ASD) presents a promising technique to enhance the solubility and stability of AM. Molecular dynamics simulation offers a rapid, efficient, and precise method to evaluate and optimize ASD formulations before production.

AIM OF STUDY

In this study, we conducted molecular dynamics simulations to explore the ASD development of AM with poloxamer and pullulan.

RESULT

Our results revealed that AM-poloxamer complexes exhibit superior interaction characteristics compared to AM-pullulan, with a 1:5 ratio of AM to poloxamer and a cooling rate of 1 °C/ns demonstrating the most favorable outcomes. This combination showed enhanced hydrogen bonding, a more compact molecular structure, and higher stability, making it the optimal choice for ASD formulation.

CONCLUSION

The integration of molecular dynamics simulation into ASD development significantly accelerates the formulation process and provides critical insights into achieving a stable and effective AM dispersion. The AM-poloxamer complex, particularly at a 1:5 ratio with a 1 °C/ns cooling rate, offers the best potential for improving AM solubility and therapeutic efficacy.

Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning

BACE1 has been regarded as an essential drug design target for treating Alzheimer's disease (AD). Multiple independent Gaussian accelerated molecular dynamics simulations (GaMD), deep learning (DL), and molecular mechanics general Born surface area (MM-GBSA) method are integrated to elucidate the molecular mechanism underlying the effect of D93 and D289 protonation on binding of inhibitors OV6 and 4B2 to BACE1. The GaMD trajectory-based DL successfully identifies significant function domains. Dynamic analysis shows that the protonation of D93 and D289 strongly affects the structural flexibility and dynamic behaviour of BACE1. Free energy landscapes indicate that inhibitor-bound BACE1s have more conformational states in the protonated states than the wild-type (WT) BACE1, and show more binding poses of inhibitors. Binding affinities calculated using the MM-GBSA method indicate that the protonation of D93 and D289 highly disturbs the binding ability of inhibitors to BACE1. In addition, the protonation of two residues significantly affects the hydrogen bonding interactions (HBIs) of OV6 and 4B2 with BACE1, altering their binding activity to BACE1. The binding hot spots of BACE1 recognized by residue-based free energy estimations provide rational targeting sites for drug design towards BACE1. This study is anticipated to provide theoretical aids for drug development towards treatment of AD.

Molecular recognition between volatile molecules and odorant binding proteins 7 by homology modeling, molecular docking and molecular dynamics simulation

BACKGROUND

Odorant-binding proteins (OBPs) in insects are key to detection and recognition of external chemical signals associated with survival. OBP7 in Spodoptera frugiperda's larval stage (SfruOBP7) may search for host plants by sensing plant volatiles, which are important sources of pest attractants and repellents. However, the atomic-level basis of binding modes remains elusive.

RESULTS

SfruOBP7 structure was constructed through homology modeling, and complex models of six plant volatiles ((E)-2-hexenol, α-pinene, (Z)-3-hexenyl acetate, lauric acid, O-cymene and 1-octanol) and SfruOBP7 were obtained through molecular docking. To study the detailed interactions between the six plant volatile molecules and SfruOBP7, we conducted three 300 ns molecular dynamics simulations for each study object. The correlation coefficients between binding free energy obtained by molecular mechanics/generalized Born surface area together with solvated interaction energy methods and experimental values are 0.90 and 0.88, respectively, showing a good correlation. By comparing binding free energy along with interaction patterns between SfruOBP7 and the six volatile molecules, hotspot residues of SfruOBP7 when binding with different volatile molecules were determined. Hydrophobic interactions stemming from van der Waals interactions play a significant role in SfruOBP7 and these plant volatile systems.

CONCLUSION

The optimized three-dimensional structure of SfruOBP7 and its binding modes with six plant volatiles revealed their interactions, thus providing a means for estimating the binding energies of other plant volatiles. Our study will help to guide the rational design of effective and selective insect attractants. © 2024 Society of Chemical Industry.

Insight into the molecular recognition of human and polar bear pregnane X receptor by three organic pollutants using molecular docking and molecular dynamics simulations

Pregnane X receptor (PXR) is a heterologous biosensor that is involved in the metabolic pathway of environmental pollutants, regulating the transcription of genes involved in biotransformation. There are significant differences in the selectivity and specificity of organic pollutants (OPs) toward polar bear PXR (pbPXR) and human PXR (hPXR), but the detailed dynamical characteristics of their interactions are unclear. Homology Modeling, molecular docking, molecular dynamics simulation, and free energy calculation were used to analyze the recognition of pbPXR and hPXR by three OPs: BPA, chlordane and toxaphene. Comparing interaction patterns along with binding free energy of pbPXR and hPXR with these three OPs revealed that although pbPXR and hPXR interact similar with these three OPs, these OPs have different effects on the internal dynamics of pbPXR and hPXR. This results in significant alterations in the interaction of key residues near Leu209, Met243, Phe288, Met323, and His407 with OPs, thereby influencing their binding energy. Non-polar interactions, especially van der Waals interactions, were found to be the dominating factors in interacting of these OPs with PXRs. The region surrounding these key residues facilitates hydrophobic contacts with PXR, which are crucial for the selective activation of PXRs in different species by these three OPs. These findings are of significant guidance in understanding the impacts of environmental endocrine disruptors on different organisms.

Unveiling Allosteric Regulation and Binding Mechanism of BRD9 through Molecular Dynamics Simulations and Markov Modeling

Bromodomain-containing protein 9 (BRD9) is a key player in chromatin remodeling and gene expression regulation, and it is closely associated with the development of various diseases, including cancers. Recent studies have indicated that inhibition of BRD9 may have potential value in the treatment of certain cancers. Molecular dynamics (MD) simulations, Markov modeling and principal component analysis were performed to investigate the binding mechanisms of allosteric inhibitor POJ and orthosteric inhibitor 82I to BRD9 and its allosteric regulation. Our results indicate that binding of these two types of inhibitors induces significant structural changes in the protein, particularly in the formation and dissolution of α-helical regions. Markov flux analysis reveals notable changes occurring in the α-helicity near the ZA loop during the inhibitor binding process. Calculations of binding free energies reveal that the cooperation of orthosteric and allosteric inhibitors affects binding ability of inhibitors to BRD9 and modifies the active sites of orthosteric and allosteric positions. This research is expected to provide new insights into the inhibitory mechanism of 82I and POJ on BRD9 and offers a theoretical foundation for development of cancer treatment strategies targeting BRD9.

Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning

Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the β-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics-generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor-MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members.

Insight into the Binding Interaction between PEDCs and hERRγ Utilizing Molecular Docking and Molecular Dynamics Simulations

Phenolic environmental endocrine-disrupting chemicals (PEDCs) are persistent EDCs that are widely found in food packaging materials and environmental media and seriously threaten human health and ecological security. Human estrogen-related receptor γ (hERRγ) has been proposed as a mediator for the low-dose effects of many environmental PEDCs; however, the atomic-level descriptions of dynamical structural features and interactions of hERRγ and PEDCs are still unclarified. Herein, how three PEDCs, 4-(1-methylpropyl)phenol (4-sec-butylphenol), 5,6,7,8-tetrahydro-2-naphthol (tetrahydro-2-napthol), and 2,2-bis(4-hydroxy-3,5-dimethoxyphenyl)propane (BP(2,2)(Me)), interact with hERRγ to produce its estrogenic disruption effects was studied. Molecular docking and multiple molecular dynamics (MD) simulations were first conducted to distinguish the detailed interaction pattern of hERRγ with PEDCs. These binding structures revealed that residues around Leu271, Leu309, Leu345, and Phe435 are important when binding with PEDCs. Furthermore, the binding energies of PEDCs with hERRγ were also characterized using the molecular mechanics/Poisson Boltzmann surface area (MM-PBSA) and solvated interaction energy (SIE) methods, and the results showed that the interactions of CH-π, π-π, and hydrogen bonds are the major contributors for hERRγ binding to these three PEDCs. What is striking is that the methoxide groups of BP(2,2)(Me), as hydrophobic groups, can help to reduce the binding energy of PEDCs binding with hERRγ. These results provide important guidance for further understanding the influence of PEDCs on human health problems.

Molecular docking and molecular dynamics simulation decoding molecular mechanism of EDCs binding to hERRγ

CONTEXT

Human estrogen-related receptor γ (hERRγ) is a key protein involved in various endocrines and metabolic signaling. Numerous environmental endocrine-disrupting chemicals (EDCs) can impact related physiological activities through receptor signaling pathways. Focused on hERRγ with 4-isopropylphenol, bisphenol-F (BPF), and BP(2,2)(Un) complexes, we executed molecular docking and multiple molecular dynamics (MD) simulations along with molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) and solvation interaction energy (SIE) calculation to study the detailed dynamical structural characteristics and interactions between them. Molecular docking showed that hydrogen bonds and hydrophobic interactions were the prime interactions to keep the stability of BPF-hERRγ and hERRγ-BP(2,2)(Un) complexes. Through MD simulations, we observed that all complexes reach equilibrium during the initial 50 ns of simulation, but these three EDCs lead to local structure changes in hERRγ. Energy results further identified key residues L268, V313, L345, and F435 around the binding pockets through CH-π, π-π, and hydrogen bonds interactions play an important stabilizing role in the recognition with EDCs. And most noticeable of all, hydrophobic methoxide groups in BP(2,2)(Un) is useful for decreasing the binding ability between EDCs and hERRγ. These results may contribute to evaluate latent diseases associated with EDCs exposure at the micro level and find potential substitutes.

METHOD

Autodock4.2 was used to conduct the molecular docking, sietraj program was performed to calculate the energy, and VMD software was used to visualize the structure. Amber18 was conducted to perform the MD simulation and other analyses.

Enhancing bezlotoxumab binding to C. difficile toxin B2: insights from computational simulations and mutational analyses for antibody design

Clostridioides difficile infection (CDI) is a significant concern caused by widespread antibiotic use, resulting in diarrhea and inflammation from the gram-positive anaerobic bacterium C. difficile. Although bezlotoxumab (Bez), a monoclonal antibody (mAb), was developed to address CDI recurrences, the recurrence rate remains high, partly due to reduced neutralization efficiency against toxin B2. In this study, we aimed to enhance the binding of Bez to C. difficile toxin B2 by combining computational simulations and mutational analyses. We identified specific mutations in Bez, including S28R, S31W/K, Y32R, S56W and G103D/S in the heavy chain (Hc), and S32F/H/R/W/Y in the light chain (Lc), which significantly improved binding to toxin B2 and formed critical protein-protein interactions. Through molecular dynamics simulations, several single mutations, such as HcS28R, LcS32H, LcS32R, LcS32W and LcS32Y, exhibited superior binding affinities to toxin B2 compared to Bez wild-type (WT), primarily attributed to Coulombic interactions. Combining the HcS28R mutation with four different mutations at residue LcS32 led to even greater binding affinities in double mutants (MTs), particularly HcS28R/LcS32H, HcS28R/LcS32R and HcS28R/LcS32Y, reinforcing protein-protein binding. Analysis of per-residue decomposition free energy highlighted key residues contributing significantly to enhanced binding interactions, emphasizing the role of electrostatic interactions. These findings offer insights into rational Bez MT design for improved toxin B2 binding, providing a foundation for developing more effective antibodies to neutralize toxin B2 and combat-related infections.

In Silico and In Vitro Potential of FDA-Approved Drugs for Antimalarial Drug Repurposing against Plasmodium Serine Hydroxymethyltransferases

Malaria has spread in many countries, with a 12% increase in deaths after the coronavirus disease 2019 pandemic. Malaria is one of the most concerning diseases in the Greater Mekong subregion, showing increased drug-resistant rates. Serine hydroxymethyltransferase (SHMT), a key enzyme in the deoxythymidylate synthesis pathway, has been identified as a promising antimalarial drug target due to its conserved folate binding pocket. This study used a molecular docking approach to screen 2509 US Food and Drug Administration (FDA)-approved drugs against seven Plasmodium SHMT structures. Eight compounds had significantly lower binding energies than the known SHMT inhibitors pyrazolopyran(+)-86, tetrahydrofolate, and antimalarial drugs, ranging from 4 to 10 kcal/mol. Inhibition assays testing the eight compounds against Plasmodium falciparum SHMT (PfSHMT) showed that amphotericin B was a competitive inhibitor of PfSHMT with a half-maximal inhibitory concentration (IC50) of 106 ± 1 μM. Therefore, a 500 ns molecular dynamics simulation of PfSHMT/PLS/amphotericin B was performed. The backbone root-mean-square deviation of the protein-ligand complex indicated the high complex stability during simulations, supported by its radius of gyration, hydrogen-bond interactions, and number of atom contacts. The appreciable binding affinity of amphotericin B for PfSHMT was indicated by their solvated interaction energy (-11.15 ± 0.09 kcal/mol) and supported by strong ligand-protein interactions (≥80% occurrences) with its essential residues (i.e., Y78, K151, N262, F266, and V365) predicted by pharmacophore modeling and per-residue decomposition free energy methods. Therefore, our findings identify a promising new PfSHMT inhibitor, albeit with less inhibitory activity, and suggest a core structure that differs from that of previous SHMT inhibitors, thus being a rational approach for novel antimalarial drug design.

Mangiferin is a new potential antimalarial and anticancer drug for targeting serine hydroxymethyltransferase

Mangiferin, a polyphenolic xanthone glycoside found in various botanical sources, including mango (Mangifera indica L.) leaves, can exhibit a variety of bioactivities. Although mangiferin has been reported to inhibit many targets, none of the studies have investigated the inhibition of serine hydroxymethyltransferase (SHMT), an attractive target for antimalarial and anticancer drugs. SHMT, one of the key enzymes in the deoxythymidylate synthesis cycle, catalyzes the reversible conversion of l-serine and (6S)-tetrahydrofolate (THF) into glycine and 5,10-methylene THF. Here, in vitro and in silico studies were used to probe how mangiferin isolated from mango leaves inhibits Plasmodium falciparum and human cytosolic SHMTs. The inhibition kinetics at pH 7.5 revealed that mangiferin is a competitive inhibitor against THF for enzymes from both organisms. Molecular docking and molecular dynamic (MD) simulations demonstrated the inhibitory effects of the deprotonated forms of mangiferin, specifically the C6-O- species and its resonance C9-O- species appearing at pH 7.5, combined with two docked poses, either a xanthone or glucose moiety, placed inside the THF-binding pocket. The MD analysis revealed that both C6-O- and its resonance-stabilized C9-O- species can favorably bind to SHMT in a similar fashion to THF, supporting the THF competitive inhibition of mangiferin. In addition, characterization of the proton dissociation equilibria of isolated mangiferin revealed that only three hydroxy groups of the xanthone moiety, C6-OH, C3-OH, and C7-OH, underwent varying degrees of deprotonation with pKa values of 6.38 ± 0.11, 8.21 ± 0.35, and 12.37 ± 0.30, respectively, while C1-OH remained protonated. Altogether, our findings demonstrate a new bioactivity of mangiferin and provide the basis for the future development of mangiferin as a potent antimalarial and anticancer drug.

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.

Solvated interaction energy: from small-molecule to antibody drug design

Scoring functions are ubiquitous in structure-based drug design as an aid to predicting binding modes and estimating binding affinities. Ideally, a scoring function should be broadly applicable, obviating the need to recalibrate and refit its parameters for every new target and class of ligands. Traditionally, drugs have been small molecules, but in recent years biologics, particularly antibodies, have become an increasingly important if not dominant class of therapeutics. This makes the goal of having a transferable scoring function, i.e., one that spans the range of small-molecule to protein ligands, even more challenging. One such broadly applicable scoring function is the Solvated Interaction Energy (SIE), which has been developed and applied in our lab for the last 15 years, leading to several important applications. This physics-based method arose from efforts to understand the physics governing binding events, with particular care given to the role played by solvation. SIE has been used by us and many independent labs worldwide for virtual screening and discovery of novel small-molecule binders or optimization of known drugs. Moreover, without any retraining, it is found to be transferrable to predictions of antibody-antigen relative binding affinities and as accurate as functions trained on protein-protein binding affinities. SIE has been incorporated in conjunction with other scoring functions into ADAPT (Assisted Design of Antibody and Protein Therapeutics), our platform for affinity modulation of antibodies. Application of ADAPT resulted in the optimization of several antibodies with 10-to-100-fold improvements in binding affinity. Further applications included broadening the specificity of a single-domain antibody to be cross-reactive with virus variants of both SARS-CoV-1 and SARS-CoV-2, and the design of safer antibodies by engineering of a pH switch to make them more selective towards acidic tumors while sparing normal tissues at physiological pH.

DeepWEST: Deep Learning of Kinetic Models with the Weighted Ensemble Simulation Toolkit for Enhanced Sampling

Recent advances in computational power and algorithms have enabled molecular dynamics (MD) simulations to reach greater time scales. However, for observing conformational transitions associated with biomolecular processes, MD simulations still have limitations. Several enhanced sampling techniques seek to address this challenge, including the weighted ensemble (WE) method, which samples transitions between metastable states using many weighted trajectories to estimate kinetic rate constants. However, initial sampling of the potential energy surface has a significant impact on the performance of WE, i.e., convergence and efficiency. We therefore introduce deep-learned kinetic modeling approaches that extract statistically relevant information from short MD trajectories to provide a well-sampled initial state distribution for WE simulations. This hybrid approach overcomes any statistical bias to the system, as it runs short unbiased MD trajectories and identifies meaningful metastable states of the system. It is shown to provide a more refined free energy landscape closer to the steady state that could efficiently sample kinetic properties such as rate constants.

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.

Recognition and release of uridine and hCNT3: From multivariate interactions to molecular design

As a vital target for the development of novel anti-cancer drugs, human concentrative nucleoside transporter 3 (hCNT3) has been widely concerned. Nevertheless, the lack of a comprehensive understanding of molecular interactions and motion mechanism has greatly hindered the development of novel inhibitors against hCNT3. In this paper, molecular recognition of hCNT3 with uridine was investigated with molecular docking, conventional molecular dynamics (CMD) simulations and adaptive steered molecular dynamics (ASMD) simulations; and then, the uridine derivatives with possibly highly inhibitory activity were designed. The result of CMD showed that more water-mediated H-bonds and lower binding free energy both explained higher recognition ability and transported efficiency of hCNT3. While during the ASMD simulation, nucleoside transport process involved the significant side-chain flip of residues F321 and Q142, a typical substrate-induced conformational change. By considering electronegativity, atomic radius, functional group and key H-bonds factors, 25 novel uridine derivatives were constructed. Subsequently, the receptor-ligand binding free energy was predicted by solvated interaction energy (SIE) method to determine the inhibitor c8 with the best potential performance. This work not only revealed molecular recognition and release mechanism of uridine with hCNT3, but also designed a series of uridine derivatives to obtain lead compounds with potential high activity.

Theoretical studies on RNA recognition by Musashi 1 RNA-binding protein

The Musashi (MSI) family of RNA-binding proteins, comprising the two homologs Musashi-1 (MSI1) and Musashi-2 (MSI2), typically regulates translation and is involved in cell proliferation and tumorigenesis. MSI proteins contain two ribonucleoprotein-like RNA-binding domains, RBD1 and RBD2, that bind single-stranded RNA motifs with a central UAG trinucleotide with high affinity and specificity. The finding that MSI also promotes the replication of Zika virus, a neurotropic Flavivirus, has triggered further investigations of the biochemical principles behind MSI–RNA interactions. However, a detailed molecular understanding of the specificity of MSI RBD1/2 interaction with RNA is still missing. Here, we performed computational studies of MSI1–RNA association complexes, investigating different RNA pentamer motifs using molecular dynamics simulations with binding free energy calculations based on the solvated interaction energy method. Simulations with Alphafold2 suggest that predicted MSI protein structures are highly similar to experimentally determined structures. The binding free energies show that two out of four RNA pentamers exhibit a considerably higher binding affinity to MSI1 RBD1 and RBD2, respectively. The obtained structural information on MSI1 RBD1 and RBD2 will be useful for a detailed functional and mechanistic understanding of this type of RNA–protein interactions.

Assessment of mutations on RBD in the Spike protein of SARS-CoV-2 Alpha, Delta and Omicron variants

The severe acute respiratory syndrome (SARS) coronavirus 2 (CoV-2) variant Omicron spread more rapid than the other variants of SARS-CoV-2 virus. Mutations on the Spike (S) protein receptor-binding domain (RBD) are critical for the antibody resistance and infectivity of the SARS-CoV-2 variants. In this study, we have used accelerated molecular dynamics (aMD) simulations and free energy calculations to present a systematic analysis of the affinity and conformational dynamics along with the interactions that drive the binding between Spike protein RBD and human angiotensin-converting enzyme 2 (ACE2) receptor. We evaluate the impacts of the key mutation that occur in the RBDs Omicron and other variants in the binding with the human ACE2 receptor. The results show that S protein Omicron has stronger binding to the ACE2 than other variants. The evaluation of the decomposition energy per residue shows the mutations N440K, T478K, Q493R and Q498R observed in Spike protein of SARS-CoV-2 provided a stabilization effect for the interaction between the SARS-CoV-2 RBD and ACE2. Overall, the results demonstrate that faster spreading of SARS-CoV-2 Omicron may be correlated with binding affinity of S protein RBD to ACE2 and mutations of uncharged residues to positively charged residues such as Lys and Arg in key positions in the RBD.

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.

Mutations in the receptor-binding domain of human SARS CoV-2 spike protein increases its affinity to bind human ACE-2 receptor

The severe acute respiratory syndrome virus-2 (SARS CoV-2) infection has resulted in the current global pandemic. The binding of SARS CoV-2 spike protein receptor-binding domain (RBD) to the human angiotensin converting enzyme-2 (ACE-2) receptor causes the host infection. The spike protein has undergone several mutations with reference to the initial strain isolated during December 2019 from Wuhan, China. A number of these mutant strains have been reported as variants of concern and as variants being monitored. Some of these mutants are known to be responsible for increased transmissibility of the virus. The reason for the increased transmissibility caused by the point mutations can be understood by studying the structural implications and inter-molecular interactions in the binding of viral spike protein RBD and human ACE-2. Here, we use the crystal structure of the RBD in complex with ACE-2 available in the public domain and analyse the 250 ns molecular dynamics (MD) simulations of wild-type and mutants; K417N, K417T, N440K, N501Y, L452R, T478K, E484K and S494P. The ionic, hydrophobic and hydrogen bond interactions, amino acid residue flexibility, binding energies and structural variations are characterized. The MD simulations provide clues to the molecular mechanisms of ACE-2 receptor binding in wild-type and mutant complexes. The mutant spike proteins RBD were associated with greater binding affinity with ACE-2 receptor. Communicated by Ramaswamy H. Sarma.

Multiple Molecular Dynamics Simulations and Free-Energy Predictions Uncover the Susceptibility of Variants of HIV-1 Protease against Inhibitors Darunavir and KNI-1657

HIV-1 protease (PR) is considered to be the main targets of anti-AIDS drug design because of its role in the proteolytic processing of viral polyproteins. However, the emergence of drug-resistant HIV has become a major problem in the therapy of HIV-1-infected patients. Focused on the complexes of wild type (WT) PR and two mutant PRs (V32I/L33F/I54M/V82I and V32I/L33F/I54M/I84 V) with inhibitors Darunavir (DRV) and KNI-1657 (KNI), respectively, we have conducted research on the conformational dynamics and the resistance mechanism caused by residue mutations through multiple molecular dynamics (MD) simulations combined with an energy (MM-PBSA and solvated interaction energy (SIE)) prediction. The results indicate that mutated residues of PR alter the distance between flap regions and catalytic sites, the volume of the inner catalytic site, and the curling degree of the flap tips, thereby affecting DRV and KNI inhibitor binding to PR. These mutated residues reduced the binding affinity of the two mutant PRs to DRV, resulting in drug resistance, whereas the two mutant PRs increase the binding affinity with KNI, indicating they enhance the sensitivity to KNI. Compared with the WT PR, the changes in van der Waals interaction and electrostatic interaction in the two variant PRs play a vital part in the binding of PR with DRV and KNI. These results may supply valuable guidance for the design of anti-AIDS drugs targeting PR.

Structural, energetic and lipophilic analysis of SARS-CoV-2 non-structural protein 9 (NSP9)

In SARS-CoV-2 replication complex, the Non-structural protein 9 (Nsp9) is an important RNA binding subunit in the RNA-synthesizing machinery. The dimeric forms of coronavirus Nsp9 increase their nucleic acid binding affinity and the N-finger motif appears to play a critical role in dimerization. Here, we present a structural, lipophilic and energetic study about the Nsp9 dimer of SARS-CoV-2 through computational methods that complement hydrophobicity scales of amino acids with molecular dynamics simulations. Additionally, we presented a virtual N-finger mutation to investigate whether this motif contributes to dimer stability. The results reveal for the native dimer that the N-finger contributes favorably through hydrogen bond interactions and two amino acids bellowing to the hydrophobic region, Leu45 and Leu106, are crucial in the formation of the cavity for potential drug binding. On the other hand, Gly100 and Gly104, are responsible for stabilizing the α-helices and making the dimer interface remain stable in both, native and mutant (without N-finger motif) systems. Besides, clustering results for the native dimer showed accessible cavities to drugs. In addition, the energetic and lipophilic analysis reveal that the higher binding energy in the native dimer can be deduced since it is more lipophilic than the mutant one, increasing non-polar interactions, which is in line with the result of MM-GBSA and SIE approaches where the van der Waals energy term has the greatest weight in the stability of the native dimer. Overall, we provide a detailed study on the Nsp9 dimer of SARS-CoV-2 that may aid in the development of new strategies for the treatment and prevention of COVID-19.

Feruloyl Sucrose Esters: Potent and Selective Inhibitors of α-glucosidase and α-amylase

INTRODUCTION

Feruloyl Sucrose Esters (FSEs) are a class of Phenylpropanoid Sucrose Esters (PSEs) widely distributed in plants. They were investigated as potential selective Alpha Glucosidase Inhibitors (AGIs) to eliminate the side effects associated with the current commercial AGIs. The latter effectively lowers blood glucose levels in diabetic patients but causes severe gastrointestinal side effects.

METHODS

Systematic structure-activity relationship (SAR) studies using in silico, in vitro and in vivo experiments were used to accomplish this aim. FSEs were evaluated for their in vitro inhibition of starch and oligosaccharide digesting enzymes α-glucosidase and α-amylase followed by in silico docking studies to identify the binding modes. A lead candidate, FSE 12 was investigated in an STZ mouse model.

RESULTS

All active FSEs showed desired higher % inhibition of α-glucosidase and desired lower inhibition of α-amylase in comparison to AGI gold standard acarbose. This suggests a greater selectivity of the FSEs towards α-glucosidase than α-amylase, which is proposed to eliminate the gastrointestinal side effects. From the in vitro studies, the position and number of the feruloyl substituents on the sucrose core, the aromatic 'OH' group, and the diisopropylidene bridges were key determinants of the % inhibition of α-glucosidase and α-amylase. In particular, the diisopropylidene bridges are critical for achieving inhibition selectivity. Molecular docking studies of the FSEs corroborates the in vitro results. The molecular docking studies further reveal that the presence of free aromatic 'OH' groups and the substitution at position 3 on the sucrose core are critical for the inhibition of both the enzymes. From the in vitro and molecular docking studies, FSE 12 was selected as a lead candidate for validation in vivo. The oral co-administration of FSE 12 with starch abrogated the increase in post-prandial glucose and significantly reduced blood glucose excursion in STZ-treated mice compared to control (starch only) mice.

CONCLUSION

Our studies reveal the potential of FSEs as selective AGIs for the treatment of diabetes, with a hypothetical reduction of side effects associated with commercial AGIs.

Targeting Peptidyl-prolyl Cis-trans Isomerase NIMA-interacting 1: A Structure-based Virtual Screening Approach to Find Novel Inhibitors

BACKGROUND

Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (Pin1) is an enzyme that isomerizes phosphorylated serine or threonine motifs adjacent to proline residues. Pin1 has important roles in several cellular signaling pathways, consequently impacting the development of multiple types of cancers.

METHODS

Based on the previously reported inhibitory activity of pentacyclic triterpenoids isolated from the gum resin of Boswellia genus against Pin1, we designed a computational experiment using molecular docking, pharmacophore filtering, and structural clustering allied to molecular dynamics (MD) simulations and binding free energy calculations to explore the inhibitory activity of new triterpenoids against Pin1 structure.

RESULTS

Here, we report different computational evidence that triterpenoids from neem (Azadirachta indica A. Juss), such as 6-deacetylnimbinene, 6-Oacetylnimbandiol, and nimbolide, replicate the binding mode of the Pin1 substrate peptide, interacting with high affinity with the binding site and thus destabilizing the Pin1 structure.

CONCLUSIONS

Our results are supported by experimental data, and provide interesting structural insights into their molecular mechanism of action, indicating that their structural scaffolds could be used as a start point to develop new inhibitors against Pin1.

A molecular model to study FosA enzyme inhibition

Fosfomycin resistance protein (FosA) is a metalloenzyme known for catalyzing a nucleophilic addition reaction of glutathione to the epoxide ring of Fosfomycin, a broad-spectrum antibiotic used to combat Gram-positive pathogens. The reaction leads fosfomycin to lose its pharmacological effect, thus promotes antibiotic resistance. A small-molecule FosA inhibitor has been discovered. ANY1 (3-bromo-6-[3-(3-bromo-2-oxo-1H-pyrazolo[1,5-a]pyrimidin-6-yl)-4-nitro-1H-pyrazol-5-yl]-1H-pyrazolo[1,5-a]pyrimidin-2-one) is competitive with the antibiotic for binding the active site of the enzyme. Through Molecular Mechanics methods, using the AMBER force field, we carry out molecular dynamics simulations and binding free energy calculations to investigate the most important interactions between the enzyme and inhibitor. Our results were able to reproduce the trend of experimental data with R² of 77.51%. Furthermore, we have shown that electrostatic and van der Waals interactions, as well as cavitation energies, are favorable for maintaining the enzyme-inhibitor complex, while reactive field energies and non-polar interactions act in an unfavorable way for interactions between FosA and ANY1.

Binding mechanism of a de novo coiled coil complex elucidated from surface forces measurements

We used the Surface Forces Apparatus to elucidate the interaction mechanism between grafted 5 heptad-long peptides engineered to spontaneously form a heterodimeric coiled-coil complex. The results demonstrated that when intimate contact between peptides is reached, binding occurs first via weakly interacting but more mobile distal heptads, suggesting an induced-fit association process. Precise control of the distance between peptide-coated surfaces allowed to quantitatively monitor the evolution of their biding energy. The binding energy of the coiled-coil complex increased in a stepwise fashion rather than monotonically with the overlapping distance, each step corresponding to the interaction between a quantized number of heptads. Surface forces data were corroborated to surface plasmon resonance measurements and molecular dynamics simulations and allowed the calculation of the energetic contribution of each heptad within the coiled-coil complex.

Multiple Molecular Dynamics Simulations of the Inhibitor GRL-02031 Complex with Wild Type and Mutant HIV-1 Protease Reveal the Binding and Drug-Resistance Mechanism

Human immunodeficiency virus type 1 (HIV-1) protease is regarded as a fascinating target for drug development against HIV infection. However, mutations causing drug resistance severely limit the efficiency of the recently marketed drugs in the treatment of HIV replication. To elucidate the binding mechanism of HIV-1 protease with promising inhibitor GRL-02031 and further to probe the resistance mechanism associated with mutations (I47V, L76V, V82A, and N88D) to the inhibitor, we applied multiple molecular dynamics (MMD) simulations along with energy analysis by the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and solvated interaction energy (SIE) methodology on specific HIV-1 protease with GRL-0231 complexes. On the basis of detail analysis of the simulations, we revealed key characteristics that constitute the drug resistance of four mutation HIV-1 proteases toward GRL-02031: substitution of the side chain in these four mutation residues leads to a change in the distances between the flaps and catalytic sites, thereby reducing the affinity for GRL-02031 with these four mutation proteases, even though the L76V and N88D residues cannot directly contact GRL-02031. The results of energy analysis according to the MM-PBSA and SIE methods further indicated that hydrophobic interaction was considered to be the prime driving force for inhibitor GRL-02031 binding to protease and the decrease in van der Waals interactions between inhibitor GRL-02031 and mutant proteases as the primary cause of the drug resistance. Analyses of the hydrogen bonds and atomic interactions further provided detailed explanations for the resistance of these four mutation proteases toward inhibitor GRL-02031. The present study provides potential guidance on the structure-based inhibitors' design targeting HIV-1 protease.

Predicting antibody affinity changes upon mutations by combining multiple predictors

Antibodies are proteins working in our immune system with high affinity and specificity for target antigens, making them excellent tools for both biotherapeutic and bioengineering applications. The prediction of antibody affinity changes upon mutations (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Delta \Delta {\mathrm{G}}}}_{\mathrm{binding}}$$\end{document}ΔΔGbinding) is important for antibody engineering. Numerous computational methods have been proposed based on different approaches including molecular mechanics and machine learning. However, the accuracy by each individual predictor is not enough for efficient antibody development. In this study, we develop a new prediction method by combining multiple predictors based on machine learning. Our method was tested on the SiPMAB database, evaluating the Pearson’s correlation coefficient between predicted and experimental \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Delta \Delta {\mathrm{G}}}}_{\mathrm{binding}}$$\end{document}ΔΔGbinding. Our method achieved higher accuracy (R = 0.69) than previous molecular mechanics or machine-learning based methods (R = 0.59) and the previous method using the average of multiple predictors (R = 0.64). Feature importance analysis indicated that the improved accuracy was obtained by combining predictors with different importance, which have different protocols for calculating energies and for generating mutant and unbound state structures. This study demonstrates that machine learning is a powerful framework for combining different approaches to predict antibody affinity changes.

Modeling Epac1 interactions with the allosteric inhibitor AM-001 by co-solvent molecular dynamics

The exchange proteins activated by cAMP (EPAC) are implicated in a large variety of physiological processes and they are considered as promising targets for a wide range of therapeutic applications. Several recent reports provided evidence for the therapeutic effectiveness of the inhibiting EPAC1 activity cardiac diseases. In that context, we recently characterized a selective EPAC1 antagonist named AM-001. This compound was featured by a non-competitive mechanism of action but the localization of its allosteric site to EPAC1 structure has yet to be investigated. Therefore, we performed cosolvent molecular dynamics with the aim to identify a suitable allosteric binding site. Then, the docking and molecular dynamics were used to determine the binding of the AM-001 to the regions highlighted by cosolvent molecular dynamics for EPAC1. These analyses led us to the identification of a suitable allosteric AM-001 binding pocket at EPAC1. As a model validation, we also evaluated the binding poses of the available AM-001 analogues, with a different biological potency. Finally, the complex EPAC1 with AM-001 bound at the putative allosteric site was further refined by molecular dynamics. The principal component analysis led us to identify the protein motion that resulted in an inactive like conformation upon the allosteric inhibitor binding.

Unraveling the conformational dynamics of glycerol 3-phosphate dehydrogenase, a nicotinamide adenine dinucleotide-dependent enzyme of Leishmania mexicana

Allosteric changes modulate the enzymatic activity, leading to activation or inhibition of the molecular target. Understanding the induced fit accommodation mechanism of a ligand in its lowest-free energy state and the subsequent conformational changes induced in the protein are important questions for drug design. In the present study, molecular dynamics (MD) simulations, binding free energy calculations, and principal component analysis (PCA) were applied to analyze the glycerol-3-phosphate dehydrogenase of Leishmania mexicana (LmGPDH) conformational changes induced by its cofactor and substrate binding. GPDH is a nicotinamide adenine dinucleotide (NAD)-dependent enzyme, which has been reported as an interesting target for drug discovery and development against leishmaniasis. Despite its relevance for glycolysis and pentose phosphate pathways, the structural flexibility and conformational motions of LmGPDH in complex with NADH and dihydroxyacetone phosphate (DHAP) remain unexplored. Here, we analyzed the conformational dynamics of the enzyme-NADH complex (cofactor), and the enzyme-NADH-DHAP complex (adduct), mapped the hydrogen-bond interactions for the complexes and pointed some structural determinants of the enzyme that emerge from these contacts to NADH and DHAP. Finally, we proposed a consistent mechanism for the conformational changes on the first step of the reversible redox conversion of dihydroxyacetone phosphate to glycerol 3-phosphate, indicating key residues and interactions that could be further explored in drug discovery.

In vivo crystals reveal critical features of the interaction between cystic fibrosis transmembrane conductance regulator (CFTR) and the PDZ2 domain of Na+/H+ exchange cofactor NHERF1

Crystallization of recombinant proteins has been fundamental to our understanding of protein function, dysfunction, and molecular recognition. However, this information has often been gleaned under extremely nonphysiological protein, salt, and H⁺ concentrations. Here, we describe the development of a robust Inka1-Box (iBox)-PAK4cat system that spontaneously crystallizes in several mammalian cell types. The semi-quantitative assay described here allows the measurement of in vivo protein-protein interactions using a novel GFP-linked reporter system that produces fluorescent readouts from protein crystals. We combined this assay with in vitro X-ray crystallography and molecular dynamics studies to characterize the molecular determinants of the interaction between the PDZ2 domain of Na⁺/H⁺ exchange regulatory cofactor NHE-RF1 (NHERF1) and cystic fibrosis transmembrane conductance regulator (CFTR), a protein complex pertinent to the genetic disease cystic fibrosis. These experiments revealed the crystal structure of the extended PDZ domain of NHERF1 and indicated, contrary to what has been previously reported, that residue selection at positions -1 and -3 of the PDZ-binding motif influences the affinity and specificity of the NHERF1 PDZ2-CFTR interaction. Our results suggest that this system could be utilized to screen additional protein-protein interactions, provided they can be accommodated within the spacious iBox-PAK4cat lattice.

Revealing the binding and drug resistance mechanism of amprenavir, indinavir, ritonavir, and nelfinavir complexed with HIV-1 protease due to double mutations G48T/L89M by molecular dynamics simulations and free energy analyses

MD simulations, MM-PBSA, and SIE analyses were used to investigate the drug resistance mechanisms of two mutations G48T and L89M in HIV-1 protease toward four inhibitors.

Exploring the Potentiality of Natural Products from Essential Oils as Inhibitors of Odorant-Binding Proteins: A Structure- and Ligand-Based Virtual Screening Approach To Find Novel Mosquito Repellents

Odorant-binding proteins (OBPs) are the main olfactory proteins of mosquitoes, and their structures have been widely explored to develop new repellents. In the present study, we combined ligand- and structure-based virtual screening approaches using as a starting point 1633 compounds from 71 botanical families obtained from the Essential Oil Database (EssOilDB). Using as reference the crystallographic structure of N,N-diethyl-meta-toluamide interacting with the OBP1 homodimer of Anopheles gambiae (AgamOBP1), we performed a structural and pharmacophoric similarity search to select potential natural products from the library. Thymol acetate, 4-(4-methyl phenyl)-pentanal, thymyl isovalerate, and p-cymen-8-yl demonstrated a favorable chemical correlation with DEET and also had high-affinity interactions with the OBP binding pocket that molecular dynamics simulations showed to be stable. To the best of our knowledge, this is the first study to evaluate on a large scale the potentiality of NPs from essential oils as inhibitors of the mosquito OBP1 using in silico approaches. Our results could facilitate the design of novel repellents with improved selectivity and affinity to the protein binding pocket and can shed light on the mechanism of action of these compounds against insect olfactory recognition.

Improving the accuracy of predicting protein-ligand binding-free energy with semiempirical quantum chemistry charge

Aim: It is a challenge to predict binding-free energy (ΔG) accurately. Methodology/results: For accurate ΔG prediction, a new strategy combining solvated interaction energy (SIE) or molecular mechanics/generalized Born surface area (MM/GBSA) approach with the Coulson charge of both protein and ligand calculated by semiempirical quantum mechanics (SQM), named SIE-SQMPC or MM/GBSA-SQMPC approach, was developed and tested on 50 protein-ligand complexes. Both approaches achieved higher correlation (R ²) between experimental and predicted ΔG than that with Amber-ff03 charge, even for ligands with highly different scaffolds. But, SIE-SQMPC is computationally much faster than MM/GBSA-SQMPC. Conclusion: SIE-SQMPC provided an effective alternative to predict ΔG of protein-ligand binding (R ² = 0.66-0.94 for SIE-AM1; R ² = 0.59-0.98 for SIE-PM7), which has the potential of high-throughput processing for molecular docking and drug design.

Signal integration in the (m)TORC1 growth pathway

Background

The protein kinase Target Of Rapamycin (TOR) is a nexus for the regulation of eukaryotic cell growth. TOR assembles into one of two distinct signalling complexes, TOR complex 1 (TORC1) and TORC2 (mTORC1/2 in mammals), with a set of largely non-overlapping protein partners. (m)TORC1 activation occurs in response to a series of stimuli relevant to cell growth, including nutrient availability, growth factor signals and stress, and regulates much of the cell's biosynthetic activity, from proteins to lipids, and recycling through autophagy. mTORC1 regulation is of great therapeutic significance, since in humans many of these signalling complexes, alongside subunits of mTORC1 itself, are implicated in a wide variety of pathophysiologies, including multiple types of cancer, neurological disorders, neurodegenerative diseases and metabolic disorders including diabetes.

Methodology

Recent years have seen numerous structures determined of (m)TOR, which have provided mechanistic insight into (m)TORC1 activation in particular, however the integration of cellular signals occurs upstream of the kinase and remains incompletely understood. Here we have collected and analysed in detail as many as possible of the molecular and structural studies which have shed light on (m)TORC1 repression, activation and signal integration.

Conclusions

A molecular understanding of this signal integration pathway is required to understand how (m)TORC1 activation is reconciled with the many diverse and contradictory stimuli affecting cell growth. We discuss the current level of molecular understanding of the upstream components of the (m)TORC1 signalling pathway, recent progress on this key biochemical frontier, and the future studies necessary to establish a mechanistic understanding of this master-switch for eukaryotic cell growth.

Identification of new inhibitors against human Great wall kinase using in silico approaches

Microtubule associated serine/threonine kinase (MASTL) is an important Ser/Thr kinase belonging to the family of AGC kinases. It is the human orthologue of Greatwall kinase (Gwl) that plays a significant role in mitotic progression and cell cycle regulation. Upregulation of MASTL in various cancers and its association with poor patient survival establishes it as an important drug target in cancer therapy. Nevertheless, the target remains unexplored with the paucity of studies focused on identification of inhibitors against MASTL, which emphasizes the relevance of our present study. We explored various drug databases and performed virtual screening of compounds from both natural and synthetic sources. A list of promising compounds displaying high binding characteristics towards MASTL protein is reported. Among the natural compounds, we found a 6-hydroxynaphthalene derivative ZINC85597499 to display best binding energy value of −9.32 kcal/mol. While among synthetic compounds, a thieno-pyrimidinone based tricyclic derivative ZINC53845290 compound exhibited best binding affinity of value −7.85 kcal/mol. MASTL interactions with these two compounds were further explored using molecular dynamics simulations. Altogether, this study identifies potential inhibitors of human Gwl kinase from both natural and synthetic origin and calls for studying these compounds as potential drugs for cancer therapy.

Chaperone-like effect of ceftriaxone on HEWL aggregation: A spectroscopic and computational study

BACKGROUND

Lysozyme is a widely distributed enzyme present in a variety of tissue and body fluids. Human and hen egg white lysozyme are used as validated model to study protein folding and stability and to understand protein misfolding and aggregation. We recently found that ceftriaxone, a β-lactam antibiotic able to overcome the blood-brain barrier, successfully eliminated the cellular toxic effects of misfolded proteins as Glial Fibrillary Acidic Protein (GFAP) and α-synuclein. To further understand the anti-amyloidogenic properties of ceftriaxone, we studied its activity towards lysozyme aggregation with the aim to investigate a possible chaperone-like activity of this molecule.

METHODS

Here we present the results obtained from fluorescence and synchrotron radiation circular dichroism spectroscopies and from molecular docking and molecular dynamics about the lysozyme-ceftriaxone interaction at neutral and acidic pH values.

RESULTS

We found that ceftriaxone exhibits comparable affinity constants to lysozyme in both experimental pH conditions and that its addition enhanced lysozyme stability reducing its aggregation propensity in acidic conditions. Computational methods allowed the identification of the putative binding site of ceftriaxone, thus rationalizing the spectroscopic results.

CONCLUSIONS

Spectroscopy data and molecular dynamics indicated a protective effect of ceftriaxone on pathological aggregation phenomena suggesting a chaperone-like effect of this molecule on protein folding. General significance These results, in addition to our previous studies on α-synuclein and GFAP, confirm the property of ceftriaxone to inhibit the pathological protein aggregation of lysozyme also by a chaperone-like mechanism, extending the potential therapeutic application of this molecule to some forms of human hereditary systemic amyloidosis.

Investigating energy-based pool structure selection in the structure ensemble modeling with experimental distance constraints: The example from a multidomain protein Pub1

The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure-based and physics-based atomistic force field with an efficient sampling strategy is adopted to simulate a model di-domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low-energy structures and the minimum-size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small-angle X-ray scattering data. It is illustrated that the regularizations of energy and ensemble-size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high-energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure-ensemble optimizations with a topology-based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates.

Structure-activity relationships of fraxamoside as an unusual xanthine oxidase inhibitor

Fraxamoside, a macrocyclic secoiridoid glucoside featuring a hydroxytyrosol group, was recently identified as a xanthine oxidase inhibitor (XOI) comparable in potency in vitro to the standard antigout drug allopurinol. However, this activity and its considerably higher value than its derivatives oleuropein, oleoside 11-methyl ester, and hydroxytyrosol are not explained by structure-activity relationships (SARs) of known XOIs. To exclude allosteric mechanisms, we first determined the inhibition kinetic of fraxamoside. The resulting competitive mechanism prompted a computational SAR characterization, combining molecular docking and dynamics, which fully explained the behavior of fraxamoside and its derivatives, attributed the higher activity of the former to conformational properties of its macrocycle, and showed a substantial contribution of the glycosidic moiety to binding, in striking contrast with glycoside derivatives of most other XOIs. Overall, fraxamoside emerged as a lead compound for a new class of XOIs potentially characterized by reduced interference with purine metabolism.

Computational analyses of interactions between ALK-5 and bioactive ligands: insights for the design of potential anticancer agents

Activin Receptor-Like Kinase 5 (ALK-5) is related to some types of cancer, such as breast, lung, and pancreas. In this study, we have used molecular docking, molecular dynamics simulations, and free energy calculations in order to explore key interactions between ALK-5 and six bioactive ligands with different ranges of biological activity. The motivation of this work is the lack of crystal structure for inhibitor-protein complexes for this set of ligands. The understanding of the molecular structure and the protein-ligand interaction could give support for the development of new drugs against cancer. The results show that the calculated binding free energy using MM-GBSA, MM-PBSA, and SIE is correlated with experimental data with r² = 0.88, 0.80, and 0.94, respectively, which indicates that the calculated binding free energy is in excellent agreement with experimental data. In addition, the results demonstrate that H bonds with Lys232, Glu245, Tyr249, His283, Asp351, and one structural water molecule play an important role for the inhibition of ALK-5. Overall, we discussed the main interactions between ALK-5 and six inhibitors that may be used as starting points for designing new molecules to the treatment of cancer.