Molecular dynamics simulation studies on influenza A virus H5N1 complexed with sialic acid and fluorinated sialic acid

Abbreviations HA Hemagglutinin

MD Molecular Dynamics

MM-PBSA Molecular Mechanics Poisson–Boltzmann Surface Area

NA Neuraminidase

NAMD Nanoscale Molecular Dynamic Simulation

PMEMD Particle Mesh Ewald Molecular Dynamics

RMSD Root-Mean-Square Deviation

RMSF Root-Mean-Square Fluctuation

SIA sialic acid

VMD Visual Molecular Dynamics

Communicated by Ramaswamy H. Sarma     

Rational MD simulations for improvement the affinity of nanobody against PlGF (placenta growth factor): mutagenesis based on electrostatic interactions

Abbreviations COM center of mass distance

MD molecular dynamics

MM-PBSA Molecular Mechanics Poisson–Boltzmann Surface Area

Nb nanobody

PlGF placenta growth factor

Rg radius of gyration

RMSD root mean-square deviation

SASA solvent-accessible surface area

VEGF vascular endothelial growth factor

     

Recognition of selected monosaccharides by Pseudomonas aeruginosa Lectin II analyzed by molecular dynamics and free energy calculations

In this study, interactions of selected monosaccharides with the Pseudomonas aeruginosa Lectin II (PA-IIL) are analyzed in detail. An interesting feature of the PA-IIL binding is that the monosaccharide is interacting via two calcium ions and the binding is unusually strong for protein-saccharide interaction. We have used Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) and normal mode analysis to calculate the free energy of binding. The impact of intramolecular hydrogen bond network for the lectin/monosaccharide interaction is also analyzed.     

Molecular dynamics simulation of interleukin-2 and its complex and determination of the binding free energy

Interleukin-2 (IL-2) protein belongs to the signal modulator cytokine's family and therefore it is prevalent for immunological responses. It has been identified as a centrally important potential drug target for the inhibition of protein-protein interactions; so as to suppress the immunological responses associated with autoimmune, inflammatory and immunological diseases, and cancer. In the present work, we have performed two independent 100?ns of molecular dynamics (MD) simulations on the apo IL-2 protein and its ligand-bound complex (with a potent inhibitor FRG), to study the effect of inhibitor binding on the dynamics and stability of the protein. The calculation of binding free energy via post-processing end state method of Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA) and Molecular Mechanics Generalised Born Surface Area (MM-GBSA) has inferred a good correlation in accordance with the already reported experimental data, demonstrating that the free energy of binding calculated by the two methods has no significant difference. The investigation of individual components of free energy revealed that the association of IL-2 protein with FRG ligand is primarily driven by the van der Waals energy contribution that represents the non-polar/hydrophobic energy contribution as dominant in this case of ligand binding.     

The relaxed complex method: Accommodating receptor flexibility for drug design with an improved scoring scheme

An extension of the new computational methodology for drug design, the "relaxed complex" method (J.-H. Lin, A. L. Perryman, J. R. Schames, and J. A. McCammon, Journal of the American Chemical Society, 2002, vol. 24, pp. 5632-5633), which accommodates receptor flexibility, is described. This relaxed complex method recognizes that ligand may bind to conformations that occur only rarely in the dynamics of the receptor. We have shown that the ligand-enzyme binding modes are very sensitive to the enzyme conformations, and our approach is capable of finding the best ligand enzyme complexes. Rapid docking serves as an efficient initial filtering method to screen a myriad of docking modes to a limited set, and it is then followed by more accurate scoring with the MM/PBSA (Molecular Mechanics/Poisson Boltzmann Surface Area) approach to find the best ligand-receptor complexes. The MM/PBSA scorings consistently indicate that the calculated binding modes that are most similar to those observed in the x-ray crystallographic complexes are the ones with the lowest free energies.     

A systematic computational analysis of human matrix metalloproteinase 13 (MMP-13) crystal structures and structure-based identification of prospective drug candidates as MMP-13 inhibitors repurposable for osteoarthritis

Abstract

Osteoarthritis (OA) is the most common form of arthritis with no available disease-modifying treatments, and is a major cause of disability. Matrix metalloproteinase 13 (MMP-13) is vital for OA progression and thus, inhibition of MMP-13 is an effective strategy to treat OA. Since the past few decades, drug repurposing has gained substantial popularity worldwide as a time- and cost-effective approach to find new indications for the existing drugs. Therefore, more than 40 X-ray co-crystal structures of the human MMP-13 with bound inhibitors are investigated to gain the structural insights such as conserved direct interactions with binding site residues, namely Ala-238, Thr-245 and Thr-247. Afterwards, enrichment study using active and decoy set of ligands revealed three MMP-13 structures (PDB-IDs: 1XUC, 3WV1 and 5BPA) with optimal enrichment performance. Docking-based screening of existing drugs against the three crystal structures followed by binding free-energy calculation suggested drugs namely eltrombopag, cilostazol and domperidone as potential MMP-13 inhibitors that need further experimental validation. These insights may serve as a potential starting point of further experimental validation and structure-based drug design/repurposing of MMP-13 inhibitors for the treatment of OA. Abbreviations 2D two-dimensional

3D three-dimensional

FDA Food and Drug Administration

MM-GBSA Molecular Mechanics Generalized Born Surface Area

MMPs matrix metalloproteinases

MMP-13 matrix metalloproteinase 13

NMR nuclear magnetic resonance

OA osteoarthritis

PDB Protein Data Bank

PDB-ID Protein Data Bank ID

PLIP protein–ligand interaction profiler

ROC receiver operating characteristic,

RMSD root mean square deviation

Communicated by Ramaswamy H. Sarma     

Structure-based virtual screening for insect ecdysone receptor ligands using MM/PBSA

The ecdysone receptor (EcR) is an insect nuclear receptor that is activated by the molting hormone, 20-hydroxyecdysone. Because synthetic EcR ligands disrupt the normal growth of insects, they are attractive candidates for new insecticides. In this study, the Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method was used to predict the binding activity of EcR ligands. Validity analyses using 40 known EcR ligands showed that the binding activity was satisfactorily predicted when the ligand conformational free energy term was introduced. Subsequently, this MM/PBSA method was applied to structure-based hierarchical virtual screening, and 12 candidate compounds were selected from a database of 3.8 million compounds. Five of these compounds were active in a cell-based competitive binding assay. The most potent compound is a simple proline derivative with low micromolar binding activity, representing a valuable lead compound for further structural optimization.     

Novel insights into the dynamics behavior of glucagon-like peptide-1 receptor with its small molecule agonists

Abstract

The glucagon-like peptide-1 receptor (GLP-1R) is a well-known target of therapeutics industries for the treatment of various metabolic diseases like type 2 diabetes and obesity. The structural–functional relationships of small molecule agonists and GLP-1R are yet to be understood. Therefore, an attempt was made on structurally known GLP-1R agonists (Compound 1, Compound 2, Compound A, Compound B, and (S)-8) to study their interaction with the extracellular domain of GLP-1R. In this study, we explored the dynamics, intrinsic stability, and binding mechanisms of these molecules through computational modeling, docking, molecular dynamics (MD) simulations and molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) binding free energy estimation. Molecular docking study depicted that hydrophobic interaction (pi–pi stacking) plays a crucial role in maintaining the stability of the complex, which was also supported by intermolecular analysis from MD simulation study. Principal component analysis suggested that the terminal ends along with the turns/loops connecting adjacent helix and strands exhibit a comparatively higher movement of main chain atoms in most of the complexes. MM/PBSA binding free energy study revealed that non-polar solvation (van der Waals and electrostatic) energy subsidizes significantly to the total binding energy, and the polar solvation energy opposes the binding agonists to GLP-1R. Overall, we provide structural features information about GLP-1R complexes that would be conducive for the discovery of new GLP-1R agonists in the future for the treatment of various metabolic diseases.

Communicated by Ramaswamy H. Sarma     

Recruiting monomer for dimer formation: resolving the antagonistic mechanisms of novel immune check point inhibitors against Programmed Death Ligand-1 in cancer immunotherapy

The design of small molecule antagonists against Programmed Death Ligand-1 (PD-L1) has been the recent highlight of the immune checkpoint blockade therapy. This interventive approach has been potentiated by the development of BMS compounds; BMS-1001 and BMS-1166, which exert their therapeutic activities by inducing dimerisation of PD-L1; a molecular mechanism that has remained unclear. For the first time, we resolve the dynamical events that underlie the antagonistic mechanisms of BMS-1001 and BMS-1166 when bound to PD-L1 using an all-atom molecular dynamics (MD) simulations approach and free binding energy Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) calculations. Time-scale dynamical findings revealed that upon binding a PD-L1 monomer, the BMS-compounds gradually facilitated the ‘inbound’ motion of another PD-L1 monomer in the same conformational phase space up till dimer formation. Moreover, the non-liganded PD-L1 monomer exhibited the highest structural flexibility and atomistic motions relative to the BMS-liganded monomer as revealed by post-MD trajectory analyses using root mean square deviation (RMSD) and root mean square fluctuations (RMSF) parameters. Trajectory investigations into ligand motions also revealed that the BMS compounds exhibited mechanistic transitions from the monomeric binding site (monomer A) where they were initially bound, to the second monomeric site (monomer B) where they were strongly bound, followed by eventual high-affinity interactions at the tunnel-like binding cleft formed upon the dimerisation of both PD-L1 monomers. These findings present a model that describes the mechanism by which the BMS compounds induce PD-L1 dimerisation and could further enhance the design of highly selective and novel monomeric recruiters of PD-L1 in cancer immunotherapy.     

A simulation investigation on interaction mechanism between Ebola nucleoprotein and VP35 peptide

Ebola viruses (EBOV) will induce acute hemorrhagic fever, which is fatal to humans and nonhuman primates. The combination of EBOV VP35 peptide with nucleoprotein N-terminal (NPNTD) is proposed based on static crystal structures in recent studies, but VP35 binding mechanism and conformational dynamics are still unclear. This investigation, using Molecular Dynamic (MD) simulation and Molecular Mechanics Generalized Born Surface Area (MM-GB/SA) energy calculation, more convincingly proves the greater roles of the protein binding mechanisms than do hints from the static crystal structure observations. Conformational analysis of the systems demonstrate that combination with VP35 may lead to the conformational transition of NPNTD from “open” to “closed” state. According to the analyses of binding free energies and their decomposition, VP35 residue R37 plays a crucial role in wild type as well as mutant systems. Mutations of I29 and L33 to aspartate as well as M34 to proline affect binding affinity mainly through influencing electrostatic interaction, which is closely related to H-bonds formation. In addition, mutations mainly affect β-hairpin and loop regions, among which, M34P may have the greatest influence to the binding. This study may provide specific binding mechanisms between VP35 peptide and NPNTD, especially some important residues concerning binding.     

Identifying potential GluN2B subunit containing N-Methyl-D-aspartate receptor inhibitors: an integrative in silico and molecular modeling approach

Abstract

N-methyl-D-aspartate receptors (NMDARs), a class of ligand-gated ion channels, are involved in non-selective cation transport across the membrane. These are contained in glutamatergic synapse and produce excitatory effects leading to synaptic plasticity and memory function. GluN1-GluN2B, a subtype of NMDAR(s), has significant role in neurodegeneration, amyloid β (Aβ) induced synaptic dysfunction and loss. Thus, targeting and inhibiting GluN1-GluN2B may be effective in the management of neurodegenerative diseases including Alzheimer’s disease. In the present study, ligand and structure-based approaches were tried to identify the inhibitors. The pharmacophore, developed from co-crystallised ifenprodil, afforded virtual hits, which were further subjected through drug likeliness and PAINS filters to remove interfering compounds. Further comprehensive docking studies, free energy calculations and ADMET studies resulted in two virtual leads. The leads, ZINC257261614 and ZINC95977857 displayed good docking scores of ?12.90 and ?12.20?Kcal/mol and free binding energies of ?60.83 and ?61.83?Kcal/mol, respectively. The compounds were having acceptable predicted ADMET profiles and were subjected to molecular dynamic (MD) studies. The MD simulation produced stable complexes of these ligands with GluN1-GluN2B subunit having protein and ligand RMSD in acceptable limit. Abbreviations AD Alzheimer's disease

ADME Absorption distribution metabolism and excretion

ATD Amino terminal domain

BBB Blood-brain barrier

CNS Central nervous system

CREB cAMP response element binding protein

CTD Carboxy-terminal domain

Glu Glutamate

GMQE Global model quality estimation

HTVS High throughput virtual screening

HIA Human intestinal absorption

LGA Lamarckian genetic algorithm

MD Molecular dynamics

MM-GBSA Molecular mechanics, the Generalised Born model for Solvent Accessibility

NMDAR N-methyl-D-aspartate receptors

PAINS Pan assay interference compounds

RMSD Root-mean square deviation

RMSF Root-mean-square fluctuation

SMARTS SMILES arbitrary target specification

SP standard precision

XP extra precision

Communicated by Ramaswamy H. Sarma     

Molecular insights into Aβ42 protofibril destabilization with a fluorinated compound D744: A molecular dynamics simulation study

The aggregation of amyloid β‐peptide (Aβ₄₂) into toxic oligomers, fibrils, has been identified as a key process in Alzheimer's disease (AD) progression. The role of halogen‐substituted compounds have been highlighted in the disassembly of Aβ protofibril. However, the underlying inhibitory mechanism of Aβ₄₂ protofibril destabilization remains elusive. In this regard, a combined molecular docking and molecular dynamics (MD) simulations were performed to elucidate the inhibitory mechanism of a fluorinated compound, D744 , which has been reported previously for potential in vitro and in vivo inhibitory activity against Aβ₄₂ aggregation and reduction in the Aβ‐induced cytotoxicity. The molecular docking analysis highlights that D744 binds and interacts with chain A of the protofibril structure with hydrophobic contacts and orthogonal multipolar interaction. MD simulations reveal destabilization of the protofibril structure in the presence of D744 due to the decrease in β‐sheet content and a concomitant increase of coil and bend structures, increase in the interchain D23‐K28 salt bridge distance, decrease in the number of backbone hydrogen bonds, increase in the average distance between Cα atoms, and decrease in the binding affinity between chains A and B of the protofibril structure. The binding free‐energy analysis between D744 and the protofibril structure with Molecular Mechanics Poisson‐Boltzmann Surface Area (MM‐PBSA) reveal that residues Leu17, Val18, Phe19, Phe20, Ala21, Glu22, Asp23, Leu34, Val36, Gly37, and Gly38 of chain A of the protofibril structure contribute maximum towards binding free energy (ΔG _binding  = −44.87 kcal/mol). The insights into the underlying inhibitory mechanism of small molecules that show potential in vitro anti‐aggregation activity against Aβ₄₂ will be beneficial for the current and future AD therapeutic studies.     

Binding free energies for nicotine analogs inhibiting cytochrome P450 2A6 by a combined use of molecular dynamics simulations and QM/MM-PBSA calculations

Molecular dynamics (MD) simulations and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations have been performed to explore the dynamic behaviors of cytochrome P450 2A6 (CYP2A6) binding with nicotine analogs (that are typical inhibitors) and to calculate their binding free energies in combination with Poisson–Boltzmann surface area (PBSA) calculations. The combined MD simulations and QM/MM-PBSA calculations reveal that the most important structural parameters affecting the CYP2A6-inhibitor binding affinity are two crucial internuclear distances, that is, the distance between the heme iron atom of CYP2A6 and the coordinating atom of the inhibitor, and the hydrogen-bonding distance between the N297 side chain of CYP2A6 and the pyridine nitrogen of the inhibitor. The combined MD simulations and QM/MM-PBSA calculations have led to dynamic CYP2A6-inhibitor binding structures that are consistent with the observed dynamic behaviors and structural features of CYP2A6-inhibitor binding, and led to the binding free energies that are in good agreement with the experimentally-derived binding free energies. The agreement between the calculated binding free energies and the experimentally-derived binding free energies suggests that the combined MD and QM/MM-PBSA approach may be used as a valuable tool to accurately predict the CYP2A6-inhibitor binding affinities in future computational design of new, potent and selective CYP2A6 inhibitors.     

Probing binding mechanism of interleukin-6 and olokizumab: in silico design of potential lead antibodies for autoimmune and inflammatory diseases

Computer-aided antibody engineering has been successful in the design of new biologics for disease diagnosis and therapeutic interventions. Interleukin-6 (IL-6), a well-recognized drug target for various autoimmune and inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, and psoriasis, was investigated in silico to design potential lead antibodies. Here, crystal structure of IL-6 along with monoclonal antibody olokizumab was explored to predict antigen–antibody (Ag???Ab)-interacting residues using DiscoTope, Paratome, and PyMOL. Tyr56, Tyr103 in heavy chain and Gly30, Ile31 in light chain of olokizumab were mutated with residues Ser, Thr, Tyr, Trp, and Phe. A set of 899 mutant macromolecules were designed, and binding affinity of these macromolecules to IL-6 was evaluated through Ag???Ab docking (ZDOCK, ClusPro, and Rosetta server), binding free-energy calculations using Molecular Mechanics/Poisson Boltzman Surface Area (MM/PBSA) method, and interaction energy estimation. In comparison to olokizumab, eight newly designed theoretical antibodies demonstrated better result in all assessments. Therefore, these newly designed macromolecules were proposed as potential lead antibodies to serve as a therapeutics option for IL-6-mediated diseases.     

Revisiting Free Energy Calculations: A Theoretical Connection to MM/PBSA and Direct Calculation of the Association Free Energy

The prediction of absolute ligand-receptor binding affinities is essential in a wide range of biophysical queries, from the study of protein-protein interactions to structure-based drug design. End-point free energy methods, such as the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) model, have received much attention and widespread application in recent literature. These methods benefit from computational efficiency as only the initial and final states of the system are evaluated, yet there remains a need for strengthening their theoretical foundation. Here a clear connection between statistical thermodynamics and end-point free energy models is presented. The importance of the association free energy, arising from one molecule's loss of translational and rotational freedom from the standard state concentration, is addressed. A novel method for calculating this quantity directly from a molecular dynamics simulation is described. The challenges of accounting for changes in the protein conformation and its fluctuations from separate simulations are discussed. A simple first-order approximation of the configuration integral is presented to lay the groundwork for future efforts. This model has been applied to FKBP12, a small immunophilin that has been widely studied in the drug industry for its potential immunosuppressive and neuroregenerative effects.