Protein-Ligand Interaction Energy-Based Entropy Calculations: Fundamental Challenges For Flexible Systems

Probing Dual Covalent Irreversible Inhibition of EGFR/FGFR4 by Electrophilic-Based Natural Compounds to Overcome Resistance and Enhance Combination Therapeutic Potentials and Management of Hepatocellular Carcinoma (HCC)

Hepatocellular carcinoma (HCC) is one of the most prevalent cancer types in the world and accounts for the majority of cases of primary liver cancer. A crucial part of the carcinogenesis of HCC involves aberrant stimulation of the FGF19-FGFR4 signaling pathway. Therefore, FGFR4 inhibition has become a strategic therapeutic approach for the treatment of HCC. However, the clinical treatment procedure is significantly hampered by the prevalence of kinase inhibitors resistance. It was recently established that the activation of EGFR signaling was found to be one of the primary mechanisms mediating the acquired resistance to FGFR4 inhibitors, moreover, sensitivity to FGFR4 inhibitors was effectively restored by inhibiting EGFR. These results provide compelling evidence that dual inhibition of EGFR and FGFR4 could represent a viable therapeutic approach to overcome resistance, hence enhanced management of HCC. To this end, we proposed a dual irreversible inhibition strategy through covalent binding by naturally occurring electrophilic warhead-bearing compounds (curcumin, deoxyelephantopin, eupalmerin acetate, syringolin A and andrographolide) to covalently target both EGFR and FGFR4 through cysteine residues, Cys797 and Cys552, respectively. Covalent docking and covalent molecular dynamics (MM/MDcov) simulations combined with thermodynamic binding free energy calculations were performed, and the results were compared against known potent and selective covalent EGFR and FGFR4 inhibitors with available X-ray crystal structures, Afatinib and BLU9931, respectively. Curcumin, deoxyelephantopin, eupalmerin acetate, syringolin A, and andrographolide showed relative binding free energies of -22.85, -17.14, -12.98, -21.81, and - 19.00 kcal/mol against EGFR and - 41.06, -29.45, -24.76, -40.11, and - 37.55 kcal/mol against FGFR4, respectively. The mechanisms of binding were emphasized by hydrogen bonding and binding forces analysis as well as active site physicochemical profiling. The findings of this study identified that curcumin, syringolin A and andrographolide-but not eupalmerin acetate or deoxyelephantopin -could be viable dual EGFR and FGFR4 covalent irreversible inhibitors and could be implemented in HCC combination therapy protocols alone or in conjunction with other chemotherapeutic agents. Investigations of this study conclusively indicate dual blockade of EGFR and FGFR4 may be a promising future therapeutic strategy for enhanced management of HCC.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure

Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein-ligand binding, the standard end-point calculations cannot produce useful outcomes in host-guest binding and thus are not recommended unless alterations are performed.

BRD4: quantum mechanical protein–ligand binding free energies using the full-protein DFT-based QM-PBSA method

Fully quantum mechanical approaches to calculating protein–ligand free energies of binding have the potential to reduce empiricism and explicitly account for all physical interactions responsible for protein–ligand binding.

TNFSF14-Derived Molecules as a Novel Treatment for Obesity and Type 2 Diabetes

Obesity is one of the most prevalent metabolic diseases in the Western world and correlates directly with glucose intolerance and insulin resistance, often culminating in Type 2 Diabetes (T2D). Importantly, our team has recently shown that the TNF superfamily (TNFSF) member protein, TNFSF14, has been reported to protect against high fat diet induced obesity and pre-diabetes. We hypothesized that mimics of TNFSF14 may therefore be valuable as anti-diabetic agents. In this study, we use in silico approaches to identify key regions of TNFSF14 responsible for binding to the Herpes virus entry mediator and Lymphotoxin β receptor. In vitro evaluation of a selection of optimised peptides identified six potentially therapeutic TNFSF14 peptides. We report that these peptides increased insulin and fatty acid oxidation signalling in skeletal muscle cells. We then selected one of these promising peptides to determine the efficacy to promote metabolic benefits in vivo. Importantly, the TNFSF14 peptide 7 reduced high fat diet-induced glucose intolerance, insulin resistance and hyperinsulinemia in a mouse model of obesity. In addition, we highlight that the TNFSF14 peptide 7 resulted in a marked reduction in liver steatosis and a concomitant increase in phospho-AMPK signalling. We conclude that TNFSF14-derived molecules positively regulate glucose homeostasis and lipid metabolism and may therefore open a completely novel therapeutic pathway for treating obesity and T2D.

Binding thermodynamics and interaction patterns of human purine nucleoside phosphorylase-inhibitor complexes from extensive free energy calculations

Human purine nucleoside phosphorylase (hPNP) plays a significant role in the catabolism of deoxyguanosine. The trimeric protein is an important target in the treatment of T-cell cancers and autoimmune disorders. Experimental studies on the inhibition of the hPNP observe that the first ligand bound to one of three subunits effectively inhibits the protein, while the binding of more ligands to the subsequent sites shows negative cooperativities. In this work, we performed extensive end-point and alchemical free energy calculations to determine the binding thermodynamics of the trimeric protein-ligand system. 13 Immucillin inhibitors with experimental results are under calculation. Two widely accepted charge schemes for small molecules including AM1-BCC and RESP are adopted for ligands. The results of RESP are in better agreement with the experimental reference. Further investigations of the interaction networks in the protein-ligand complexes reveal that several residues play significant roles in stabilizing the complex structure. The most commonly observed ones include PHE200, GLU201, MET219, and ASN243. The conformations of the protein in different protein-ligand complexes are observed to be similar. We expect these insights to aid the development of potent drugs targeting hPNP.

Binding Thermodynamics and Interaction Patterns of Inhibitor-Major Urinary Protein-I Binding from Extensive Free-Energy Calculations: Benchmarking AMBER Force Fields

Mouse major urinary protein (MUP) plays a key role in the pheromone communication system. The one-end-closed β-barrel of MUP-I forms a small, deep, and hydrophobic central cavity, which could accommodate structurally diverse ligands. Previous computational studies employed old protein force fields and short simulation times to determine the binding thermodynamics or investigated only a small number of structurally similar ligands, which resulted in sampled regions far from the experimental structure, nonconverged sampling outcomes, and limited understanding of the possible interaction patterns that the cavity could produce. In this work, extensive end-point and alchemical free-energy calculations with advanced protein force fields were performed to determine the binding thermodynamics of a series of MUP-inhibitor systems and investigate the inter- and intramolecular interaction patterns. Three series of inhibitors with a total of 14 ligands were simulated. We independently simulated the MUP-inhibitor complexes under two advanced AMBER force fields. Our benchmark test showed that the advanced AMBER force fields including AMBER19SB and AMBER14SB provided better descriptions of the system, and the backbone root-mean-square deviation (RMSD) was significantly lowered compared with previous computational studies with old protein force fields. Surprisingly, although the latest AMBER force field AMBER19SB provided better descriptions of various observables, it neither improved the binding thermodynamics nor lowered the backbone RMSD compared with the previously proposed and widely used AMBER14SB. The older but widely used AMBER14SB actually achieved better performance in the prediction of binding affinities from the alchemical and end-point free-energy calculations. We further analyzed the protein-ligand interaction networks to identify important residues stabilizing the bound structure. Six residues including PHE38, LEU40, PHE90, ALA103, LEU105, and TYR120 were found to contribute the most significant part of protein-ligand interactions, and 10 residues were found to provide favorable interactions stabilizing the bound state. The two AMBER force fields gave extremely similar interaction networks, and the secondary structures also showed similar behavior. Thus, the intra- and intermolecular interaction networks described with the two AMBER force fields are similar. Therefore, AMBER14SB could still be the default option in free-energy calculations to achieve highly accurate binding thermodynamics and interaction patterns.

Solvation Free Energy Calculation Using a Fixed-Charge Model: Implicit and Explicit Treatments of the Polarization Effect

In this work, IPolQ-Mod charges and the reference potential scheme are used to calculate the solvation free energies of a set of organic molecules. Both methods could capture the phase transfer of a solute with accompanying polarization cost utilizing a fixed-charge model. The IPolQ-Mod charges, which are the average of two charge sets fitted in a vacuum state and a condensed phase, take account of the polarization effect implicitly. For the reference potential method, the quantum mechanics polarization corrections are calculated explicitly by thermodynamic perturbation. The polarization effect captured by the IPolQ-Mod charges is an approximation to that of the reference potential method theoretically. In the present study, the reference potential method shows a slight improvement over the classical restrained electrostatic potential (RESP) charges, which perform pretty well in predicting the solvation free energy. However, IPolQ-Mod(MP2) shows a poor agreement with the experimental data. Compared with IPolQ-Mod(MP2), IPolQ-Mod(M06-2X) or IPolQ-Mod(ωB97X) is found to give more appropriate prediction of the molecule's dipole and the solvation free energies calculated by IPolQ-Mod(M06-2X) or IPolQ-Mod(ωB97X) are more compatible with those of the RESP charges. If the other force field parameters remain unchanged, M06-2X or ωB97X is recommended to derive the IPolQ-Mod charges.

Affinity Calculations of Cyclodextrin Host-Guest Complexes: Assessment of Strengths and Weaknesses of End-Point Free Energy Methods

The end-point methods like MM/PBSA or MM/GBSA estimate the free energy of a biomolecule by combining its molecular mechanics energy with solvation free energy and entropy terms. On the one hand, their performance largely depends on the particular system of interest, and despite numerous attempts to improve their reliability that have resulted in many variants, there is still no clear alternative to improve their accuracy. On the other hand, the relatively small cyclodextrin host-guest complexes, for which high-quality binding calorimetric data are usually available, are becoming reference models for testing the accuracy of free energy methods. In this work, we further assess the performance of various MM/PBSA-like approaches as applied to cyclodextrin complexes. To this end, we select a set of complexes between β-cyclodextrin and 57 small organic molecules that has been previously studied with the binding energy distribution analysis method in combination with an implicit solvent model ( Wickstrom, L.; He, P.; Gallicchio, E.; Levy, R. M. J. Chem. Theory Comput. 2013 , 9 , 3136 - 3150 ). For each complex, a conventional 1.0 μs molecular dynamics simulation in explicit solvent is performed. Then we employ semiempirical quantum chemical calculations, several variants of the MM-PB(GB)SA methods, entropy estimations, etc., to assess the reliability of the end-point affinity calculations. The best end-point protocol in this study, which combines DFTB3 energies with entropy corrections, yields estimations of the binding free energies that still have substantial errors (RMSE = 2.2 kcal/mol), but it exhibits a good prediction capacity in terms of ligand ranking ( R² = 0.66) that is close to or even better than that of rigorous free energy methodologies. Our results can be helpful to discriminate between the intrinsic limitations of the end-point methods and other sources of error, such as the underlying energy and continuum solvation methods.

The molecular mechanism of structural changes in the antimicrobial peptide CM15 upon complex formation with drug molecule suramin: a computational analysis

Stabilization of helical conformations of CM15 upon interactions with suramin.