Molecular Fractionation With Conjugate Caps Research Articles

Unveiling fructose and glucose binding to human serum albumin: fluorescence measurements and docking, molecular dynamics and quantum biochemistry computations

This research examines the interaction between human serum albumin (HSA) and various sugar forms (β-D-fructofuranose (FRC), α-D-glucopyranose (GLC), Keto-D-fructose (FRO), Aldehydo-D-glucose (GLO), and modified Aldehydo-D-glucose (GLOm)) using fluorescent spectroscopy, molecular docking simulations, molecular dynamics, protein conformational clusters (EnGens), molecular fractionation with conjugate caps (MFCC) and quantum biochemistry analysis. We analyze molecular and quantum aspects, uncovering interaction energies between sugar atoms and amino acids. Total interaction energy considers protein fragmentation, energetic decomposition, and interaction energy from a bottom-up perspective. Molecular dynamics reveal that unmodified Aldehydo-D-glucose (GLO) escapes HSA binding sites, explaining gradual glycation. We pioneer studying HSA’s binding mechanism with glucose and fructose in a 1:1 ratio using long molecular dynamics simulations. Results suggest the transitional GLOm form has a higher Sudlow I site propensity than unmodified glucose, crucial for K195 glycation. FRO and GLOm interaction tendencies move toward a deeper FA7 cavity, near its center. This approach effectively elucidates small molecule binding mechanisms, consistent with previous experimental results. Communicated by Ramaswamy H. Sarma

Deciphering Interactions between Potential Inhibitors and the Plasmodium falciparum DHODH Enzyme: A Computational Perspective.

Malaria is a parasitic disease that, in its most severe form, can even lead to death. Insect-resistant vectors, insufficiently effective vaccines, and drugs that cannot stop parasitic infestations are making the fight against the disease increasingly difficult. It is known that the enzyme dihydroorotate dehydrogenase (DHODH) is of paramount importance for the synthesis of pyrimidine from the Plasmodium precursor, that is, for its growth and reproduction. Therefore, its blockade can lead to disruption of the parasite's life cycle in the vertebrate host. In this scenario, PfDHODH inhibitors have been considered candidates for a new therapy to stop the parasitic energy source. Given what is known, in this work, we applied molecular fractionation with conjugated caps (MFCC) in the framework of the quantum formalism of density functional theory (DFT) to evaluate the energies of the interactions between the enzyme and the different triazolopyrimidines (DSM483, DMS557, and DSM1), including a complex carrying the mutation C276F. From these results, it was possible to identify the main features of each system, focusing on the wild-type and mutant PfDHODH and examining the major amino acid residues that are part of the four complexes. Our analysis provides new information that can be used to develop new drugs that could prove to be more effective alternatives to present antimalarial drugs.

Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps Including Hydrogen Bonds.

Polarizable embedding (PE) refers to classical embedding approaches, such as those used in quantum mechanics/molecular mechanics (QM/MM), that allow mutual polarization between the quantum and classical regions. The quality of the embedding potential is critical to provide accurate results, e.g., for spectroscopic properties and dynamical processes. High-quality embedding-potential parameters can be obtained by dividing the classical region into smaller fragments and deriving the parameters from ab initio calculations on the fragments. For solvents and other systems composed of small molecules, the fragments can be individual molecules, while a more complicated fragmentation procedure is needed for larger molecules, such as proteins and nucleic acids. One such fragmentation strategy is the molecular fractionation with conjugate caps (MFCC) approach. As is widely known, hydrogen bonds play a key role in many biomolecular systems, e.g., in proteins, where they are responsible for the secondary structure. In this work, we assess the effects of including hydrogen-bond fragmentation in the MFCC procedure [MFCC(HB)] for deriving the embedding-potential parameters. The MFCC(HB) extension is evaluated on several molecular systems, ranging from small model systems to proteins, directly in terms of molecular electrostatic potentials and embedding potentials and indirectly in terms of selected properties of chromophores embedded in water and complex protein environments.

In Silico Evaluation of the Binding Energies of Androgen Receptor Agonists in Wild-Type and Mutational Models.

Anabolic androgenic steroids (AAS) are substances with androgenic and anabolic characteristics. Among the many side effects of hormone therapy with AAS, the following stand out: heart problems, adrenal gland disorders, aggressive behavior, increased risk of prostate cancer, problems related to lack of libido and impotence. Such substances vary in the relationship between androgenic activity, and the activation of the androgen receptor (AR) is of fundamental importance for the singularity of the action of each AAS. In this sense, our study evaluates the aspects that comprise the interactions of testosterone agonists (TES), dihydrotestosterone (DHT) and tetrahydrogestrinone (THG) in complex with the AR. In addition, we also evaluated the impact of ligand-receptor affinity differences in a mutation model. We apply computational techniques based on density functional theory (DFT) and use, as methodology, Molecular Fractionation with Conjugate Caps (MFCC). The energetic specificities present in the interaction between the analyzed complexes attest that the highest affinity with the AR receptor is found for AR-THG, followed by AR-DHT, AR-TES and AR-T877A-DHT, respectively. Our results also show the differences and equivalences between the different agonists, in addition to evaluating the difference between the DHT ligand in complex with the wild-type and mutant receptor, presenting the main amino acid residues that involve the interaction with the ligands. The computational methodology used proves to be an operative and sophisticated choice to help in the search for pharmacological agents for various therapies that have androgen as a target.

A simple and consistent quantum-chemical fragmentation scheme for proteins that includes two-body contributions.

The Molecular Fractionation with Conjugate Caps (MFCC) method is a popular fragmentation method for the quantum-chemical treatment of proteins. However, it does not account for interactions between the amino acid fragments, such as intramolecular hydrogen bonding. Here, we present a combination of the MFCC fragmentation scheme with a second-order many-body expansion (MBE) that consistently accounts for all fragment-fragment, fragment-cap, and cap-cap interactions, while retaining the overall simplicity of the MFCC scheme with its chemically meaningful fragments. We show that with the resulting MFCC-MBE(2) scheme, the errors in the total energies of selected polypeptides and proteins can be reduced by up to one order of magnitude and relative energies of different protein conformers can be predicted accurately.

Systematic Partitioning of Proteins for Quantum-Chemical Fragmentation Methods Using Graph Algorithms

Quantum-chemical fragmentation methods offer an efficient approach for the treatment of large proteins, in particular if local target quantities such as protein-ligand interaction energies, enzymatic reaction energies, or spectroscopic properties of embedded chromophores are sought. However, the accuracy that is achievable for such local target quantities intricately depends on how the protein is partitioned into smaller fragments. While the commonly employed naı̈ve approach of using fragments with a fixed size is widely used, it can result in large and unpredictable errors when varying the fragment size. Here, we present a systematic partitioning scheme that aims at minimizing the fragmentation error of a local target quantity for a given maximum fragment size. To this end, we construct a weighted graph representation of the protein, in which the amino acids constitute the nodes. These nodes are connected by edges weighted with an estimate for the fragmentation error that is expected when cutting this edge. This allows us to employ graph partitioning algorithms provided by computer science to determine near-optimal partitions of the protein. We apply this scheme to a test set of six proteins representing various prototypical applications of quantum-chemical fragmentation methods using a simplified molecular fractionation with conjugate caps (MFCC) approach with hydrogen caps. We show that our graph-based scheme consistently improves upon the naı̈ve approach.

Blockade of the checkpoint PD-1 by its ligand PD-L1 and the immuno-oncological drugs pembrolizumab and nivolumab.

We investigate the interaction between the programmed cell death protein 1 (PD-1) and the programmed cell death ligand 1 (PD-L1), as well as the immuno-oncological drugs pembrolizumab (PEM), and nivolumab (NIV), through quantum chemistry methods based on the Density Functional Theory (DFT) and the molecular fractionation with conjugate caps (MFCC) scheme, in order to map their hot-spot regions. Our results showed that the total interaction energy order of the three complexes is in good agreement with the experimental binding affinity order: PD-1/PEM > PD-1/NIV > PD-1/PD-L1. Besides, a detailed investigation revealed the energetically most relevant residue-residue pairs-interaction for each complex. Our computational results give a better understanding of the interaction mechanism between the protein PD-1 and its ligands (natural and inhibitors), unleashing the immune surveillance to destroy the cancer cells by decreasing their immune evasion. They are also an efficient alternative towards the development of new small-molecules and antibody-based drugs, pointing out to new treatments for cancer therapy.

Polarizable Density Embedding for Large Biomolecular Systems.

We present an efficient and robust fragment-based quantum-classical embedding model capable of accurately capturing effects from complex environments such as proteins and nucleic acids. This is realized by combining the molecular fractionation with conjugate caps (MFCC) procedure with the polarizable density embedding (PDE) model at the level of Fock matrix construction. The PDE contributions to the Fock matrix of the core region are constructed using the local molecular basis of the individual fragments rather than the supermolecular basis of the entire system. Thereby, we avoid complications associated with the application of the MFCC procedure on environment quantities such as electronic densities and molecular-orbital energies. Moreover, the computational cost associated with solving self-consistent field (SCF) equations of the core region remains unchanged from that of purely classical polarized embedding models. We analyze the performance of the resulting model in terms of the reproduction of the electrostatic potential of an insulin monomer protein and further in the context of solving problems related to electron spill-out. Finally, we showcase the model for the calculation of one- and two-photon properties of the Nile red molecule in a protein environment. Based on our analyses, we find that the combination of the MFCC approach with the PDE model is an efficient, yet accurate approach for calculating molecular properties of molecules embedded in structured biomolecular environments.

Exploring the Binding Mechanism of GABAB Receptor Agonists and Antagonists through in Silico Simulations.

GABAB is a G protein-coupled receptor that functions as a constitutive heterodimer composed of the GABAB1a/b and GABAB2 subunits. It mediates slow and prolonged inhibitory neurotransmission in the nervous system, representing an attractive target for the treatment of various disorders. However, the molecular mechanism of the GABAB receptor is not thoroughly understood. Therefore, a better description of the binding of existing agonists and antagonists to this receptor is crucial to improve our knowledge about G protein-coupled receptor structure as well as for helping the development of new potent and more selective therapeutic agents. In this work, we used the recent X-ray cocrystallization data of agonists (GABA and baclofen) and antagonists (2-hydroxysaclofen, SCH50911, and CGP54626) bound to the GABAB orthosteric site together with quantum biochemistry and the molecular fractionation with conjugate caps (MFCC) scheme to describe the individual contribution of each amino acid residue involved in the GABAB-ligand interaction, pointing out differences and similarities among the compounds. Our quantum biochemical computational results show that the total binding energy of the ligands to the GABAB ligand pocket, with radius varying from 2.0 to 9.0 Å, is well-correlated with the experimental binding affinity. In addition, we found that the binding site is very similar for agonists or antagonists, showing small differences in the importance of the most significant amino acids. Finally, we predict the energetic relevance of the regions of the five ligands as well as the influence of each protein lobe on GABAB-ligand binding. These results provide important new information on the binding mechanism of the GABAB receptor and should facilitate the development of new chemicals targeting this receptor.

MOLECULAR FRACTIONATION WITH CONJUGATE CAPS STUDY OF THE INTERACTION OF THE ANACARDIC ACID WITH THE ACTIVE SITE OF TRYPANOSOMA CRUZI GAPDH ENZYME: A QUANTUM INVESTIGATION

Objective: The objective of this study was to use the molecular fractionation with conjugate caps (MFCC) method to elucidate the possible interaction mechanism of anacardic acid (AA) with the saturated alkyl chain (AA0) in the Trypanosoma cruzi glyceraldehyde-3-phosphate dehydrogenase (TcGAPHD) enzyme.
 Methods: Initially, the geometry optimization of the AA three-dimensional structure (with the pentadecyl chain) was performed using density functional theory (B3LYP) calculations. With the AA0 optimization data, it was possible to plot the molecular electrostatic potential (MESP) surface. Molecular docking simulation was performed using automated coupling with the AutoDock Vina program. The best-fit conformation in the docking simulation of AA0 is the binding site used for the construction of the TcGAPHD-AA0 complex. Interaction energies between the AA0 molecule and the amino acid residues of the TcGAPHD enzyme were estimated using the MFCC strategy.
 Results: To obtain more reliable quantitative information on the interaction of AA with the active site of the TcGAPHD enzyme, the fragmentation method was combined with conjugated layers (MFCC) and molecular docking. It can be observed that the AA0 molecule occupies a region near the active site of the chalepin molecule in the TcGAPHD enzyme, and the Ile13 residue has the strongest binding energy of approximately 25 kcal/mol with AA0, through a strong Van der Waals interaction.
 Conclusion: The paper presents an improved quantitative analysis approach for assessing the contribution of individual amino acids to the free energy of interaction between AA and TcGAPHD. Specifically, the paper illustrates the advantageous approach of combining molecular docking with the MFCC method.

Ribosomal RNA-Aminoglycoside Hygromycin B Interaction Energy Calculation within a Density Functional Theory Framework.

We intend to investigate the drug-binding energy of each nucleotide inside the aminoglycoside hygromycin B (hygB) binding site of 30S ribosomal RNA (rRNA) subunit by using the molecular fractionation with conjugate caps (MFCC) strategy based on the density functional theory (DFT), considering the functional LDA/PWC, OBS, and the dielectric constant parametrization. Aminoglycosides are bactericidal antibiotics that have high affinity to the prokaryotic rRNA, inhibiting the synthesis of proteins by acting on the main stages of the translation mechanism, whereas binding to rRNA 16S, a component of the 30S ribosomal subunit in prokaryotes. The identification of the nucleotides presenting the most negative binding energies allows us to stabilize hygB in a suitable binding pocket of the 30S ribosomal subunit. In addition, it should be highlighted that mutations in these residues may probably lead to resistance to ribosome-targeting antibiotics. Quantum calculations of aminoglycoside hygromycin B-ribosome complex might contribute to further quantum studies with antibiotics like macrolides and other aminoglycosides.

Molecular modelling and quantum biochemistry computations of a naturally occurring bioremediation enzyme: Alkane hydroxylase from Pseudomonas putida P1

Many species of bacteria involved in degradation of n-alkanes have an important constitutional metabolic enzyme, the alkane hydroxylase called AlkB, specialized in the conversion of hydrocarbons molecules that can be used as carbon and/or energy source. This enzyme plays an important role in the microbial degradation of oil, chlorinated hydrocarbons, fuel additives, and many other compounds. A number of these enzymes has been biochemically characterized in detail because the potential of alkane hydroxylases to catalyse high added-value reactions is widely recognized. Nevertheless, the industrial and process bioremediation application of them is restricted, owing to their complex biochemistry, challenging process requirements, and the limited number of their three-dimensional structures. Furthermore, AlkB has great potential as biocatalysts for selective transformation of a wide range of chemically inert unreactive alkanes into reactive chemical precursors that can be used as tools for bioremediation and bioprocesses. Aiming to understand the possible ways the AlkB enzyme Pseudomonas putida P1 interacts with octane, octanol and 1-octyne, we consider its suitable biochemical structure taking into account a 3-D homology modelling. Besides, by using a quantum chemistry computational model based on the density functional theory (DFT), we determine possible protein-substrate interaction regions measured by means of its binding energy simulated throughout the Molecular Fractionation with Conjugated Caps (MFCC) approach.

Quantum mechanical calculation of nanomaterial-ligand interaction energies by molecular fractionation with conjugated caps method

Molecular fractionation with conjugate caps (MFCC) method is introduced for the efficient estimation of quantum mechanical (QM) interaction energies between nanomaterial (carbon nanotube, fullerene, and graphene surface) and ligand (charged and neutral). In the calculations, nanomaterials are partitioned into small fragments and conjugated caps that are properly capped, and the interaction energies can be obtained through the summation of QM calculations of the fragments from which the contribution of the conjugated caps is removed. All the calculations were performed by density functional theory (DFT) and dispersion contributions for the attractive interactions were investigated by dispersion corrected DFT method. The predicted interaction energies by MFCC at each computational level are found to give excellent agreement with full system (FS) calculations with the mean energy deviation just a fractional kcal/mol. The accurate determination of nanomaterial-ligand interaction energies by MFCC suggests that it is an effective method for performing QM calculations on nanomaterial-ligand systems.

A quantum biochemistry model of the interaction between the estrogen receptor and the two antagonists used in breast cancer treatment

In this work we employed quantum biochemistry methods based on the density functional theory (DFT) model and the MFCC (Molecular Fractionation with Conjugate Caps) scheme to unveil the detailed binding energy features of the tissue-selective synthetic agents SERMs (selective estrogen receptor modulators) 4-hydroxytamoxifen (OHT) and raloxifene (RAL), widely used in the breast cancer treatment, co-crystallized with the estrogen receptor α (ERα). Our theoretical/computational results demonstrated that the total binding energies of OHT and RAL to the ERα ligand-pocket correlate with the experimental binding affinity. Besides, we found that SERMs-OHT binds stronger when compared to SERMs-RAL, confirming experimental data, whose main contributions to the total SERMs-ERα binding energy are due to the amino acid residues in decreasing sequence D351>E542>D538>E353>E423, an important information to understand their binding mechanisms.

Modeling environment effects on pigment site energies: Frozen density embedding with fully quantum-chemical protein densities

The recently developed 3-FDE method (Jacob and Visscher, 2008) combines ideas from the Molecular Fractionation with Conjugate Caps (MFCC) method (Zhang and Zhang, 2003) with Frozen Density Embedding (FDE) (Wesołowski and Warshel, 1993) and is thus able to produce fully quantum-chemical electron densities of entire proteins. In contrast to the original FDE method, 3-FDE facilitates a fragmentation into covalently bound subunits. We apply the method for the first time to the calculation of excitation energies, where we use the Fenna–Matthews–Olson (FMO) pigment–protein complex as a test case. Several technical and conceptual parameters for the preparation stages are tested and a robust protocol for this type of embedding is established. We present calculations of excitation energies of the individual pigments (site energies) under the influence of full protein densities obtained with different settings and compare them to the results from a simple point charge model. Our results indicate that 3-FDE is a well-suited method for the description of excitation energies within density-based embedding.

Quantum analysis/improvement of antipsychotic's docking results

Research support: CNPq‐BrazilHuman dopamine receptors are important targets in treatment of Parkinson's disease and Schizophrenia. Thus, the understanding of the binding mechanisms involving selective ligand agents and dopamine receptors D2 and D3 may contribute to pharmacologic strategies. Recently, we have applied quantum mechanics methods to calculate the contribution of each amino acid residue in the binding pocket of D3 receptor in complex with eticlopride (Zanatta, G et al, 2012). In this study, to understand the mechanism of haloperidol interaction, we employed the Molecular Fractionation with Conjugated Caps (MFCC) followed by quantum calculations to analyze the structure of haloperidol docked in D3 receptor using Autodock 4.0 (Fig 1).It was not possible to obtain the stabilization in total binding energy for a radius of 16 Å (Fig. 2), suggesting that this pose is not yet in the best binding conformation. In order to improve the results, we are performing a series of energy minimization steps using quantum mechanics/molecular mechanics (QM/MM). The establishment of a protocol to improve docking results is important to obtain representative structures of selective ligands to D2 and D3 receptors.

Quantum biochemistry study of the T3-785 tropocollagen triple-helical structure

We estimate the residue–monomer and residue–residue interaction energies of the collagen-like peptide T3-785, whose triple helix structure is the sequence X–Y-glycine (X, Y are often the imino acids proline and hydroxyproline), considering its full X-ray diffraction crystal structure, including a hydratation layer of 111 water molecules. The computations are performed within the density functional theory (DFT) scope together with a Molecular Fractionation with Conjugate Caps (MFCC) approach. We found that the hydroxyproline and proline residues play a very important role in the stabilization of the T3-785 structure, with the arginine residue in a given peptide chain exhibiting the strongest residue–strand interaction.

Fully ab initio protein‐ligand interaction energies with dispersion corrected density functional theory

Dispersion corrected density functional theory (DFT-D3) is used for fully ab initio protein-ligand (PL) interaction energy calculation via molecular fractionation with conjugated caps (MFCC) and applied to PL complexes from the PDB comprising 3680, 1798, and 1060 atoms. Molecular fragments with n amino acids instead of one in the original MFCC approach are considered, thereby allowing for estimating the three-body and higher many-body terms. n > 1 is recommended both in terms of accuracy and efficiency of MFCC. For neutral protein side-chains, the computed PL interaction energy is visibly independent of the fragment length n. The MFCC fractionation error is determined by comparison to a full-system calculation for the 1060 atoms containing PL complex. For charged amino acid side-chains, the variation of the MFCC result with n is increased. For these systems, using a continuum solvation model with a dielectricity constant typical for protein environments (ϵ = 4) reduces both the variation with n and improves the stability of the DFT calculations considerably. The PL interaction energies for two typical complexes obtained ab initio for the first time are found to be rather large (-30 and -54 kcal/mol).

Divide and Conquer Hartree−Fock Calculations on Proteins

The ability to perform ab initio electronic structure calculations that scales linearly with the system size is one of the central aims in theoretical chemistry. In this study, the implementation of the divide-and-conquer (DC) algorithm, an algorithm with the potential to aid the achievement of true linear scaling within Hartree-Fock (HF) theory is revisited. Standard HF calculations solve the Roothaan-Hall equations for the whole system; in the DC-HF approach, the diagonalization of the Fock matrix is carried out on smaller subsystems. The DC algorithm for HF calculations was validated on polyglycines, polyalanines and eleven real three-dimensional proteins of up to 608 atoms in this work. We also found that a fragment-based initial guess using molecular fractionation with conjugated caps (MFCC) method significantly reduces the number of SCF cycles and even is capable of achieving convergence for some globular proteins where the simple superposition of atomic densities (SAD) initial guess fails.

Quantum study of HIV-1 protease-bridge water interaction

We present a fully quantum mechanical calculation for binding interaction between HIV-1 protease (PR) and the water molecule W301 which bridges the flaps of the protease with the inhibitors of PR. The quantum calculation is made possible by applying a recently developed molecular fractionation with conjugate caps (MFCC) method which divides a protein molecule into capped amino acid-based fragments and their conjugate caps. These individual fragments are properly treated to preserve the chemical property of bonds that are cut. Ab initio methods at HF, B3LYP, and MP2 levels with a fixed basis set 6-31+G* have been employed in the present calculation. The MFCC calculation produces a quantum mechanical interaction "map" representing interactions between individual residues of PR and W301. This enables a detailed quantitative analysis on binding of W301 to specific residues of PR at quantum mechanical level.