Molecular modeling methods. Basic techniques and challenging problems

Exploring space-energy matching via quantum-molecular mechanics modeling and breakage dynamics-energy dissipation via microhydrodynamic modeling to improve the screening efficiency of nanosuspension prepared by wet media milling

Introduction: The preparation of nanosuspensions by wet media milling is a promising technique that increases the bioavailability of insoluble drugs. The nanosuspension is thermodynamically unstable, where its stability might be influenced by the interaction energy between the stabilizers and the drugs after milling at a specific collision energy. However, it is difficult to screen the stabilizers and the parameters of milling accurately and quickly by using traditional analysis methods. Quantum-molecular mechanics and microhydrodynamic modeling can be applied to improve screening efficiency.Areas covered: Quantum-molecular mechanics model, which includes molecular docking, molecular dynamics simulations, and data on binding energy, provides insights into screening stabilizers based on their molecular behavior at the atomic level. The microhydrodynamic model explores the mechanical processes and energy dissipation in nanomilling, and even combines information on the mechanical modulus and an energy vector diagram for the milling parameters screening of drug crystals.Expert opinion: These modeling methods improve screening efficiency and support screening theories based on thermodynamics and physical dynamics. However, how to reasonably combine different modeling methods with their theoretical characteristics and further multidimensional and cross-scale simulations of nanosuspension formation remain challenges.

Exploring Covalent Docking Mechanisms of Boron-Based Inhibitors to Class A, C and D β-Lactamases Using Time-dependent Hybrid QM/MM Simulations

Recently, molecular covalent docking has been extensively developed to design new classes of inhibitors that form chemical bonds with their biological targets. This strategy for the design of such inhibitors, in particular boron-based inhibitors, holds great promise for the vast family of β-lactamases produced, inter alia, by Gram-negative antibiotic-resistant bacteria. However, the description of covalent docking processes requires a quantum-mechanical approach, and so far, only a few studies of this type have been presented. This study accurately describes the covalent docking process between two model inhibitors - representing two large families of inhibitors based on boronic-acid and bicyclic boronate scaffolds, and three β-lactamases which belong to the A, C, and D classes. Molecular fragments containing boron can be converted from a neutral, trigonal, planar state with sp2 hybridization to the anionic, tetrahedral sp3 state in a process sometimes referred to as morphing. This study applies multi-scale modeling methods, in particular, the hybrid QM/MM approach which has predictive power reaching well beyond conventional molecular modeling. Time-dependent QM/MM simulations indicated several structural changes and geometric preferences, ultimately leading to covalent docking processes. With current computing technologies, this approach is not computationally expensive, can be used in standard molecular modeling and molecular design works, and can effectively support experimental research which should allow for a detailed understanding of complex processes important to molecular medicine. In particular, it can support the rational design of covalent boron-based inhibitors for β-lactamases as well as for many other enzyme systems of clinical relevance, including SARS-CoV-2 proteins.

Computational Simulations to Guide Enzyme-Mediated Prodrug Activation

Prodrugs are designed to improve pharmaceutical/biopharmaceutical characteristics, pharmacokinetic/pharmacodynamic properties, site-specificity, and more. A crucial step in successful prodrug is its activation, which releases the active parent drug, exerting a therapeutic effect. Prodrug activation can be based on oxidation/reduction processes, or through enzyme-mediated hydrolysis, from oxidoreductases (i.e., Cytochrome P450) to hydrolytic enzymes (i.e., carboxylesterase). This study provides an overview of the novel in silico methods for the optimization of enzyme-mediated prodrug activation. Computational methods simulating enzyme-substrate binding can be simpler like molecular docking, or more complex, such as quantum mechanics (QM), molecular mechanics (MM), and free energy perturbation (FEP) methods such as molecular dynamics (MD). Examples for MD simulations used for elucidating the mechanism of prodrug (losartan, paclitaxel derivatives) metabolism via CYP450 enzyme are presented, as well as an MD simulation for optimizing linker length in phospholipid-based prodrugs. Molecular docking investigating quinazolinone prodrugs as substrates for alkaline phosphatase is also presented, as well as QM and MD simulations used for optimal fit of different prodrugs within the human carboxylesterase 1 catalytical site. Overall, high quality computational simulations may show good agreement with experimental results, and should be used early in the prodrug development process.

Dynamics theory for molecular liquids based on an interaction site model

Dynamics theories for molecular liquids based on an interaction site model have been developed over the past few decades and proved to be powerful tools to investigate various dynamical phenomena.

Water-membrane partition thermodynamics of an amphiphilic lipopeptide: an enthalpy-driven hydrophobic effect

To shed light on the driving force for the hydrophobic effect that partitions amphiphilic lipoproteins between water and membrane, we carried out an atomically detailed thermodynamic analysis of a triply lipid modified H-ras heptapeptide anchor (ANCH) in water and in a DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) bilayer. Combining molecular mechanical and continuum solvent approaches with an improved technique for solute entropy calculation, we obtained an overall transfer free energy of approximately -13 kcal mol(-1). This value is in qualitative agreement with free energy changes derived from a potential of mean force calculation and indirect experimental observations. Changes in free energies of solvation and ANCH conformational reorganization are unfavorable, whereas ANCH-DMPC interactions-especially van der Waals-favor insertion. These results are consistent with an enthalpy-driven hydrophobic effect, in accord with earlier calorimetric data on the membrane partition of other amphiphiles. Furthermore, structural and entropic analysis of molecular dynamics-generated ensembles suggests that conformational selection may play a hitherto unappreciated role in membrane insertion of lipid-modified peptides and proteins.

Refinement of X-ray data on dual cosubstrate specificity of CK2 kinase by free energy calculations based on molecular dynamics simulation

Free energy differences of binding of adenosine triphosphate (ATP) and guanine triphosphate (GTP) to the protein kinase CK2 (casein kinase 2) were calculated, using molecular dynamics (MD) simulations and the thermodynamic cycle approach. Good agreement with experimental data was obtained. Simulations confirm observations based on crystallographic data that specifically interacting water molecules in the binding site region of CK2 kinase play a key role in its ability to use ATP or GTP as equally efficient phosphate donors. We point out that to obtain quantitatively reasonable results, it was necessary to modify original X-ray data by assuming the presence of an additional water molecule in the CK2 binding site structure with GTP.

Finite element solution of the steady-state Smoluchowski equation for rate constant calculations

This article describes the development and implementation of algorithms to study diffusion in biomolecular systems using continuum mechanics equations. Specifically, finite element methods have been developed to solve the steady-state Smoluchowski equation to calculate ligand binding rate constants for large biomolecules. The resulting software has been validated and applied to mouse acetylcholinesterase. Rates for inhibitor binding to mAChE were calculated at various ionic strengths with several different reaction criteria. The calculated rates were compared with experimental data and show very good agreement when the correct reaction criterion is used. Additionally, these finite element methods require significantly less computational resources than existing particle-based Brownian dynamics methods.

9-[(Hydroxymethyl)phenyl]adenines: new aryladenine substrates of adenosine deaminase

New phenyl adenine compounds 5-7 were synthesized as analogues of adenosine and studied for their adenosine deaminase (ADA) substrate activity. The 9-[(o-hydroxymethyl)phenyl]methyl]adenine 5 and 9-[(m-hydroxymethyl)phenyl]adenine 7 were deaminated by ADA, and 9-[(o-hydroxyethyl)phenyl]adenine 6 was not deaminated up to 7 days. The ADA substrates 5 and 7 were deaminated quantitatively to their inosine analogues in 10 and 6h, respectively.

A mezoscopic model of nucleic acids. Part 1. Lagrangian and quaternion molecular dynamics

This study presents a model for mezoscopic molecular dynamics simulations with objects of different scale and properties e.e. atoms, pseudoatoms, rigid and pseudo-elastic bodies, described by the external coordinates and internal degrees of freedom. The Lagrangian approach is used to derive equations of motion and a quaternion representation is used for the description of the dynamics of rigid and pseudo-elastic molecular elements. Stability of the LQMD algorithm was tested for a 10-base pair deoxynucleotide. The total energy, momentum and angular momentum are conserved for time-steps up to 20 fs.

How and why phosphotyrosine-containing peptides bind to the SH2 and PTB domains

BACKGROUND

Specific recognition of phosphotyrosine-containing protein segments by Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains plays an important role in intracellular signal transduction. Although many SH2/PTB-domain-containing receptor-peptide complex structures have been solved, little has been done to study the problem computationally. Prediction of the binding geometry and the binding constant of any peptide-protein pair is an extremely important problem.

RESULTS

A procedure to predict binding energies of phosphotyrosine-containing peptides with SH2/PTB domains was developed. The average deviation between experimentally measured binding energies and theoretical evaluations was 1.8 kcal/mol. Binding states of unphosphorylated peptides were also predicted reasonably well. Ab initio predictions of binding geometry of fully flexible peptides correctly identified conformations of two pentapeptides and a hexapeptide complexed with a v-Src SH2 domain receptor with root mean square deviations (rmsds) of 0.3 A, 1.2 A and 1.5 A, respectively.

CONCLUSIONS

The binding energies of phosphotyrosine-containing complexes can be effectively predicted using the procedure developed here. It was also possible to predict the bound conformations of flexible short peptides correctly from random starting conformations.

New approaches in molecular structure prediction

In the past years, much effort has been put on the development of new methodologies and algorithms for the prediction of protein secondary and tertiary structures from (sequence) data; this is reviewed in detail. New approaches for these predictions such as neural network methods, genetic algorithms, machine learning, and graph theoretical methods are discussed. Secondary structure prediction algorithms were improved mostly by considering families of related proteins; however, for the reliable tertiary structure modeling of proteins, knowledge-based techniques are still preferred. Methods and examples with more or less successful results are described. Also, programs and parameterizations for energy minimisations, molecular dynamics, and electrostatic interactions have been improved, especially with respect to their former limits of applicability. Other topics discussed in this review include the use of traditional and on-line databases, the docking problem and surface properties of biomolecules, packing of protein cores, de novo design and protein engineering, prediction of membrane protein structures, the verification and reliability of model structures, and progress made with currently available software and computer hardware. In summary, the prediction of the structure, function, and other properties of a protein is still possible only within limits, but these limits continue to be moved.

Ligand-protein docking and rational drug design

Over the past year there have been some interesting and significant advances in computer-based ligand-protein docking techniques and related rational drug-design tools, including flexible ligand docking and better estimation of binding free energies and solvation energies. As a result, the successful use of computational tools to help generate interesting new guide (lead) compounds for targeted receptors is becoming more commonplace.