Improved Peptide and Protein Torsional Energetics with the OPLSAA Force Field

Effect of conjugated (EK)10 peptide on structural and dynamic properties of ubiquitin protein: a molecular dynamics simulation study

Peptide conjugation modulates the stability and biological acitivty of proteins via the allosteric effect.

Influence of thermostatting on nonequilibrium molecular dynamics simulations of heat conduction in solids

Nonequilibrium molecular dynamics (NEMD) has been extensively used to study thermal transport at various length scales in many materials. In this method, two local thermostats at different temperatures are used to generate a nonequilibrium steady state with a constant heat flux. Conventionally, the thermal conductivity of a finite system is calculated as the ratio between the heat flux and the temperature gradient extracted from the linear part of the temperature profile away from the local thermostats. Here, we show that, with a proper choice of the thermostat, the nonlinear part of the temperature profile should actually not be excluded in thermal transport calculations. We compare NEMD results against those from the atomistic Green's function method in the ballistic regime and those from the homogeneous nonequilibrium molecular dynamics method in the ballistic-to-diffusive regime. These comparisons suggest that in all the transport regimes, one should directly calculate the thermal conductance from the temperature difference between the heat source and sink and, if needed, convert it into the thermal conductivity by multiplying it with the system length. Furthermore, we find that the Langevin thermostat outperforms the Nosé-Hoover (chain) thermostat in NEMD simulations because of its stochastic and local nature. We show that this is particularly important for studying asymmetric carbon-based nanostructures, for which the Nosé-Hoover thermostat can produce artifacts leading to unphysical thermal rectification.

A Competition between Dissociation Pathway and Energy Transfer Pathway: Unimolecular Dissociation of a Benzene-Hexafluorobenzene Complex in Nitrogen Bath

The unimolecular dissociation of a benzene-hexafluorobenzene complex at 1000, 1500, and 2000 K is studied inside a bath of 1000 N₂ molecules kept at 300 K using chemical dynamics simulation. Three bath densities of 20, 324, and 750 kg/m³ are considered. The dissociation dynamics of the complex at a 20 kg/m³ bath density is found to be similar to that in the gas phase, whereas the dynamics is drastically different at higher bath densities. The microcanonical/canonical dissociation rate constants for the three bath densities are calculated and fitted to the Arrhenius equation. The activation energies are found to be similar to the gas-phase one. However, the pre-exponential factor is lower and decreases with the increase in bath density. The vibrational degree of freedom of the complex more effectively participates in the collisional energy transfer to the N₂ bath, whereas the translational and rotational degrees of freedom of N₂ receive the transferred energy. The energy transfer efficiency increases with the increase in bath density. The time scale of the energy transfer pathway is more than that of the dissociation pathway, and negligible direct dissociation of the complex is observed from the simulation at the highest bath density.

Towards Rational Computational Engineering of Psychrophilic Enzymes

Cold-adapted enzymes from psychrophilic species achieve their high catalytic efficiency at low temperature by a different partitioning of the activation free energy into its enthalpic and entropic components, compared to orthologous mesophilic enzymes. Their lower activation enthalpy, partly compensated by an increased entropic penalty, has been suggested to originate from changes in flexibility of the protein surface. Multiple sequence alignments of psychrophilic and mesophilic enzymes also show characteristic motifs located in surface loops of the protein. Here, we use computer simulations to examine the effects of a number of designed surface mutations of psychrophilic and mesophilic elastases on the temperature dependence of the catalyzed peptide cleavage reaction. For each of 14 mutant enzyme variants we report calculations of their thermodynamic activation parameters. The results show that substitution of psychrophilic loop residues into the mesophilic enzyme consistently changes both the activation parameters and loop flexibilities towards the former, and vice versa for opposite substitutions.

Do Molecular Dynamics Force Fields Capture Conformational Dynamics of Alanine in Water?

We examine the ability of six molecular dynamics (MD) force fields (Amber ff14SB, Amber ff99SBnmr1, Amber ff03ws, OPLS-AA/L, OPLS-AA/M, and CHARMM36) to reproduce conformational ensembles of the central alanine in GAG and AAA in a way that is consistent with five (GAG) or six (AAA) J coupling constants and amide I' profiles. MD-derived Ramachandran plots for all six force fields under study differ from those obtained by the Gaussian fit to experimental data in three major ways: (i) the polyproline II (pPII) basin in the Ramachandran plot is too concentrated, (ii) the antiparallel β (aβ) basin is overpopulated, and (iii) the transitional β (βt) basin is underpopulated. Amber ff14SB outperforms the other five MD force fields and yields the highest pPII populations of the central alanine residue in GAG (55%) and AAA (63%), in good agreement with the predictions of the Gaussian model (59 and 76%). The analysis of the hydration layer around the central alanine residue reveals considerable reorientation of water molecules and reduction in both the average number of water molecules and the average number of water-water hydrogen bonds when glycines (in GAG) are replaced by alanines (in AAA), elucidating water-mediated nearest neighbor effects on alanine's conformational dynamics.

An exclusive computational insight toward molecular mechanism of MMV007571, a multitarget inhibitor of Plasmodium falciparum

Recently, two Malaria Box molecules namely MMV007571 and MMV020439 well known inhibitors of New Permeability Pathway (NPP) function also showed a secondary phenotype of inhibition of enzyme Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) and cytochrome bc1 complex in metabolic profile assays. Intricacies of their binding at the newly identified targets was need of the hour which motivated us to study their binding using molecular docking and dynamics simulations approach. Interestingly, molecular docking results of both MMV007571 and MMV020439 showed good binding affinity toward the Q_o site of cytochrome bc1 complex while only MMV007571 illustrated notable binding characterstics for PfDHODH. Molecular Dynamics (MD) simulations when carried out for native-PfDHODH, PfDHODH-MMV007571 and PfDHODH-Genz667348 models (100 ns each) demonstrated the role of inhibitors over the N-terminus domain which experienced conformational transition from an open state (22 Å) to closed state (16 Å) in the protein-inhibitor models. Dynamics also indicated that the loop domain near cofactor flavin mononucleotide (FMN) attained more felxibility which further lead to its poor binding and may contribute to inhibition of the oxidation (catalytic) process. Moreover, the pharmacophoric features of MMV007571 was justified and may serve as a template for the design of novel series of more potent multitarget inhibitors against Plasmodium falciparum.AbbreviationsÅAngstromACTsArtemisinin combination therapiescyt bc1cytochrome bc1 complexhhour(s)KKelvinµMmicromolarMMVMedicine for malaria ventureNLucNanoluciferasenMnanomolarNPPNew permeation pathwayPDBProtein data bankPfDHODHPlasmodium falciparum dihydroorotate dehydrogenasePOPC1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholineRBCRed blood corpusclesRMSDRoot-mean-square deviationSPStandard precisionvdWvan der WaalsXPExtra precisionyDHODHYeast dihydroorotate dehydrogenaseCommunicated by Ramaswamy H. Sarma.

Accurate Biomolecular Simulations Account for Electronic Polarization

In this perspective, we discuss where and how accounting for electronic many-body polarization affects the accuracy of classical molecular dynamics simulations of biomolecules. While the effects of electronic polarization are highly pronounced for molecules with an opposite total charge, they are also non-negligible for interactions with overall neutral molecules. For instance, neglecting these effects in important biomolecules like amino acids and phospholipids affects the structure of proteins and membranes having a large impact on interpreting experimental data as well as building coarse grained models. With the combined advances in theory, algorithms and computational power it is currently realistic to perform simulations with explicit polarizable dipoles on systems with relevant sizes and complexity. Alternatively, the effects of electronic polarization can also be included at zero additional computational cost compared to standard fixed-charge force fields using the electronic continuum correction, as was recently demonstrated for several classes of biomolecules.

Determination and evaluation of the nonadditivity in wetting of molecularly heterogeneous surfaces

Every folded protein presents an interface with water that is composed of domains of varying hydrophilicity/-phobicity. Many simulation studies have highlighted the nonadditivity in the wetting of such nanostructured surfaces in contrast with the accepted theoretical formula that is additive. We present here an experimental study on surfaces of identical composition but different organization of hydrophobic and hydrophilic domains. We prove that the interfacial energy of such surfaces differs by ∼20% and that a significant difference in the interfacial water H-bonding structure can be measured. As a result, in combination with molecular-dynamics simulations, we propose a model that captures the wetting of molecularly heterogeneous surfaces, showing the importance of local structure (first-nearest neighbors) in determining the wetting properties.

The interface between water and folded proteins is very complex. Proteins have “patchy” solvent-accessible areas composed of domains of varying hydrophobicity. The textbook understanding is that these domains contribute additively to interfacial properties (Cassie’s equation, CE). An ever-growing number of modeling papers question the validity of CE at molecular length scales, but there is no conclusive experiment to support this and no proposed new theoretical framework. Here, we study the wetting of model compounds with patchy surfaces differing solely in patchiness but not in composition. Were CE to be correct, these materials would have had the same solid–liquid work of adhesion (W_SL) and time-averaged structure of interfacial water. We find considerable differences in W_SL, and sum-frequency generation measurements of the interfacial water structure show distinctively different spectral features. Molecular-dynamics simulations of water on patchy surfaces capture the observed behaviors and point toward significant nonadditivity in water density and average orientation. They show that a description of the molecular arrangement on the surface is needed to predict its wetting properties. We propose a predictive model that considers, for every molecule, the contributions of its first-nearest neighbors as a descriptor to determine the wetting properties of the surface. The model is validated by measurements of W_SL in multiple solvents, where large differences are observed for solvents whose effective diameter is smaller than ∼6 Å. The experiments and theoretical model proposed here provide a starting point to develop a comprehensive understanding of complex biological interfaces as well as for the engineering of synthetic ones.

Novel multi-epitope protein containing conserved epitopes from different Leishmania species as potential vaccine candidate: Integrated immunoinformatics and molecular dynamics approach

Leishmaniosis, caused by intracellular parasites of the genus Leishmania, has become a serious public health problem around the world, and for which there are currently extensive limitations. In this work, a theoretical model was proposed for the development of a multi-epitope vaccine. The protein GP63 of the parasite was selected for epitopes prediction, due to its important biological role for the infection process and abundance. IEDB tools were used to determine epitopes B and T in Leishmania braziliensis; besides, other conserved epitopes in three species were selected. To improve immunogenicity, 50S ribosomal protein L7 / L12 (ID: P9WHE3) was used as a domain of adjuvant in the assembly process. The folding arrangement of the vaccine was obtained through homologous modeling multi-template with MODELLER v9.21, and a Ramachandran plot analysis was done. Furthermore, physicochemical properties were described with the ProtParam tool and secondary structure prediction combining GOR-IV and SOPMA tools. Finally, a molecular dynamics simulation (50 ns) was performed to establish flexibility and conformational changes. The analysis of the results indicates high conservancy in the epitopes predicted among the four species. Moreover, Ramachandran plot, physicochemical parameters, and secondary structure prediction suggest a stable conformation of the vaccine, after a minimum conformational change that was evaluated with the free energy landscape. The conformational change does not drive any substantial change for epitope exposition on the surface. The vaccine proposed could be tested experimentally to guide new approaches in the development of pan-vaccines; vaccines with regions conserved in multiple species.

Path Integral Calculation of the Hydrogen/Deuterium Kinetic Isotope Effect in Monoamine Oxidase A-Catalyzed Decomposition of Benzylamine

Monoamine oxidase A (MAO A) is a well-known enzyme responsible for the oxidative deamination of several important monoaminergic neurotransmitters. The rate-limiting step of amine decomposition is hydride anion transfer from the substrate α–CH2 group to the N5 atom of the flavin cofactor moiety. In this work, we focus on MAO A-catalyzed benzylamine decomposition in order to elucidate nuclear quantum effects through the calculation of the hydrogen/deuterium (H/D) kinetic isotope effect. The rate-limiting step of the reaction was simulated using a multiscale approach at the empirical valence bond (EVB) level. We applied path integral quantization using the quantum classical path method (QCP) for the substrate benzylamine as well as the MAO cofactor flavin adenine dinucleotide. The calculated H/D kinetic isotope effect of 6.5 ± 1.4 is in reasonable agreement with the available experimental values.

Absolute Free Energy of Binding Calculations for Macrophage Migration Inhibitory Factor in Complex with a Druglike Inhibitor

Calculation of the absolute free energy of binding (ΔG_bind) for a complex in solution is challenging owing to the need for adequate configurational sampling and an accurate energetic description, typically with a force field (FF). In this study, Monte Carlo (MC) simulations with improved side-chain and backbone sampling are used to assess ΔG_bind for the complex of a druglike inhibitor (MIF180) with the protein macrophage migration inhibitory factor (MIF) using free energy perturbation (FEP) calculations. For comparison, molecular dynamics (MD) simulations were employed as an alternative sampling method for the same system. With the OPLS-AA/M FF and CM5 atomic charges for the inhibitor, the ΔG_bind results from the MC/FEP and MD/FEP simulations, -8.80 ± 0.74 and -8.46 ± 0.85 kcal/mol, agree well with each other and with the experimental value of -8.98 ± 0.28 kcal/mol. The convergence of the results and analysis of the trajectories indicate that sufficient sampling was achieved for both approaches. Repeating the MD/FEP calculations using current versions of the CHARMM and AMBER FFs led to a 6 kcal/mol range of computed ΔG_bind. These results show that calculation of accurate ΔG_bind for large ligands is both feasible and numerically equivalent, within error limits, using either methodology.

Structural Analysis of PfSec62-Autophagy Interacting Motifs (AIM) and PfAtg8 Interactions for Its Implications in RecovER-phagy in Plasmodium falciparum

Autophagy is a degradative pathway associated with many pathological and physiological processes crucial for cell survival. During ER stress, while selective autophagy occurs via ER-phagy, the re-establishment of physiologic ER homeostasis upon resolution of a transient ER stress is mediated by recovER-phagy. Recent studies demonstrated that recovER-phagy is governed via association of Sec62 as an ER-resident autophagy receptor through its autophagy interacting motifs (AIM)/LC3-interacting region (LIR) toAtg8/LC3. Atg8 is an autophagy protein, which is central to autophagosome formation and maturation. Plasmodium falciparum Atg8 (PfAtg8) has both autophagic and non-autophagic functions critical for parasite survival. Since Plasmodium also has Sec62 in the ER membrane and is prone to ER stress due to drastic transformation during their complex intraerythrocytic cycle; hence, we initiated the studies to check whether recovER-phagy occurs in the parasite. To achieve this, a comprehensive study based on the computational approaches was carried out. This study embarks upon identification of AIM sequences in PfSec62 by carrying out peptide-protein docking simulations and comparing the interactions of these AIMs with PfAtg8, based on the molecular dynamic simulations. Detailed analysis is based on electrostatic surface complementarity, peptide-protein interaction strength, mapping of non-covalent bond interactions and rupture force calculated from steered MD simulations. Potential mean forces and unbinding free energies (ΔG_dissociation) using Jarzynski's equality were also computed for the AIM/LIR motif complexes with PfAtg8/HsLC3 autophagy proteins to understand their dissociation free energy profiles and thereby their binding affinities and stability of the peptide-protein complexes. Through this study, we predict Sec62 mediated recovER-phagy in Plasmodium falciparum, which might open new avenues to explore novel drug targets for antimalarial drug discovery.

Comparing water-mediated hydrogen-bonding in different polyelectrolyte complexes

All-atom molecular dynamics simulations are used to investigate the polyelectrolyte-specific influence of hydration and temperature on water diffusion in hydrated polyelectrolyte complexes (PECs). Two model PECs were compared: poly(allylamine hydrochloride) (PAH)-poly(sodium 4-styrenesulfonate) (PSS) and poly(diallyldimethylammonium) (PDADMA)-poly(acrylic acid) (PAA). The findings show that the strength of the hydrogen bonding i.e. polyelectrolyte water interaction has enormous influence on the water mobility, which has implications for PEC structure and properties. A 10-fold difference in the average water diffusion coefficient between PAH-PSS and PDADMA-PAA PECs at the same hydration level is observed. The vast majority of the water molecules hydrating the PDADMA-PAA PECs, for hydrations in the range of 26-38 wt%, are effectively immobilized, whereas for PAH-PSS PECs the amount of immobilized water decreases with hydration. This points to the polyelectrolyte-specific character of the PE-water hydrogen bonding relationship with temperature. PAA-water hydrogen bonds are found to be significantly less sensitive to temperature than for PSS-water. The polyelectrolyte-water interactions, investigated via radial distribution function, hydrogen bond distance and angle distributions, are connected with resulting structure of the PECs. The PDADMA-PAA and PAH-PSS PECs are prepared experimentally and the states of water at different hydration levels is determined using differential scanning calorimetry (DSC). Experiments confirm the differences between PDADMA-PAA and PAH-PSS PECs observed in the theoretical modelling. The results suggest that the initial predictions of the PEC's bonding with water can be based on simple molecular-level considerations.

Blinded prediction of protein-ligand binding affinity using Amber thermodynamic integration for the 2018 D3R grand challenge 4

In the framework of the 2018 Drug Design Data Resource grand challenge 4, blinded predictions on relative binding free energy were performed for a set of 39 ligands of the Cathepsin S protein. We leveraged the GPU-accelerated thermodynamic integration of Amber 18 to advance our computational prediction. When our entry was compared to experimental results, a good correlation was observed (Kendall's τ: 0.62, Spearman's ρ: 0.80 and Pearson's R: 0.82). We designed a parallelized transformation map that placed ligands into several groups based on common alchemical substructures; TI transformations were carried out for each ligand to the relevant substructure, and between substructures. Our calculations were all conducted using the linear potential scaling scheme in Amber TI because we believe the softcore potential/dual-topology approach as implemented in current Amber TI is highly fault-prone for some transformations. The issue is illustrated by using two examples in which typical preparation for the dual-topology approach of Amber TI fails. Overall, the high accuracy of our prediction is a result of recent advances in force fields (ff14SB and GAFF), as well as rapid calculation of ensemble averages enabled by the GPU implementation of Amber. The success shown here in a blinded prediction strongly suggests that alchemical free energy calculation in Amber is a promising tool for future commercial drug design.

Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation

Intrinsically disordered proteins (IDPs) are abundant in eukaryotic proteomes, play a major role in cell signaling, and are associated with human diseases. To understand IDP function it is critical to determine their configurational ensemble, i.e., the collection of 3-dimensional structures they adopt, and this remains an immense challenge in structural biology. Attempts to determine this ensemble computationally have been hitherto hampered by the necessity of reweighting molecular dynamics (MD) results or biasing simulation in order to match ensemble-averaged experimental observables, operations that reduce the precision of the generated model because different structural ensembles may yield the same experimental observable. Here, by employing enhanced sampling MD we reproduce the experimental small-angle neutron and X-ray scattering profiles and the NMR chemical shifts of the disordered N terminal (SH4UD) of c-Src kinase without reweighting or constraining the simulations. The unbiased simulation results reveal a weakly funneled and rugged free energy landscape of SH4UD, which gives rise to a heterogeneous ensemble of structures that cannot be described by simple polymer theory. SH4UD adopts transient helices, which are found away from known phosphorylation sites and could play a key role in the stabilization of structural regions necessary for phosphorylation. Our findings indicate that adequately sampled molecular simulations can be performed to provide accurate physical models of flexible biosystems, thus rationalizing their biological function.

Development and Validation of the Quantum Mechanical Bespoke Protein Force Field

Molecular mechanics force field parameters for macromolecules, such as proteins, are traditionally fit to reproduce experimental properties of small molecules, and thus, they neglect system-specific polarization. In this paper, we introduce a complete protein force field that is designed to be compatible with the quantum mechanical bespoke (QUBE) force field by deriving nonbonded parameters directly from the electron density of the specific protein under study. The main backbone and sidechain protein torsional parameters are rederived in this work by fitting to quantum mechanical dihedral scans for compatibility with QUBE nonbonded parameters. Software is provided for the preparation of QUBE input files. The accuracy of the new force field, and the derived torsional parameters, is tested by comparing the conformational preferences of a range of peptides and proteins with experimental measurements. Accurate backbone and sidechain conformations are obtained in molecular dynamics simulations of dipeptides, with NMR J coupling errors comparable to the widely used OPLS force field. In simulations of five folded proteins, the secondary structure is generally retained, and the NMR J coupling errors are similar to standard transferable force fields, although some loss of the experimental structure is observed in certain regions of the proteins. With several avenues for further development, the use of system-specific nonbonded force field parameters is a promising approach for next-generation simulations of biological molecules.

Refinement of Peptide Conformational Ensembles by 2D IR Spectroscopy: Application to Ala‒Ala‒Ala

Characterizing ensembles of intrinsically disordered proteins is experimentally challenging because of the ill-conditioned nature of ensemble determination with limited data and the intrinsic fast dynamics of the conformational ensemble. Amide I two-dimensional infrared (2D IR) spectroscopy has picosecond time resolution to freeze structural ensembles as needed for probing disordered-protein ensembles and conformational dynamics. Also, developments in amide I computational spectroscopy now allow a quantitative and direct prediction of amide I spectra based on conformational distributions drawn from molecular dynamics simulations, providing a route to ensemble refinement against experimental spectra. We performed a Bayesian ensemble refinement method on Ala-Ala-Ala against isotope-edited Fourier-transform infrared spectroscopy and 2D IR spectroscopy and tested potential factors affecting the quality of ensemble refinements. We found that isotope-edited 2D IR spectroscopy provides a stringent constraint on Ala-Ala-Ala conformations and returns consistent conformational ensembles with the dominant ppII conformer across varying prior distributions from many molecular dynamics force fields and water models. The dominant factor influencing ensemble refinements is the systematic frequency uncertainty from spectroscopic maps. However, the uncertainty of conformer populations can be significantly reduced by incorporating 2D IR spectra in addition to traditional Fourier-transform infrared spectra. Bayesian ensemble refinement against isotope-edited 2D IR spectroscopy thus provides a route to probe equilibrium-complex protein ensembles and potentially nonequilibrium conformational dynamics.

Overcoming Challenging Substituent Perturbations with Multisite λ-Dynamics: A Case Study Targeting β-Secretase 1

Alchemical free energy calculations have made a dramatic impact upon the field of structure-based drug design by allowing functional group modifications to be explored computationally prior to experimental synthesis and assay evaluation, thereby informing and directing synthetic strategies. In furthering the advancement of this area, a series of 21 β-secretase 1 (BACE1) inhibitors developed by Janssen Pharmaceuticals were examined to evaluate the ability to explore large substituent perturbations, some of which contain scaffold modifications, with multisite λ-dynamics (MSλD), an innovative alchemical free energy framework. Our findings indicate that MSλD is able to efficiently explore all structurally diverse ligand end-states simultaneously within a single MD simulation with a high degree of precision and with reduced computational costs compared to the widely used approach TI/MBAR. Furthermore, computational predictions were shown to be accurate to within 0.5-0.8 kcal/mol when CM1A partial atomic charges were combined with CHARMM or OPLS-AA-based force fields, demonstrating that MSλD is force field independent and a viable alternative to FEP or TI approaches for drug design.

Parameterization of Molybdenum Disulfide Interacting with Water Using the Free Energy Perturbation Method

Water contact angles (WCA) are often used to parametrize force field parameters of novel 2D nanomaterials, such as molybdenum disulfide (MoS₂), which has emerged as a promising nanomaterial in many biomedical applications due to its unique and impressive properties. However, there is a wide range of water-MoS₂ contact angles in the literature depending on the aging process on the surface of a MoS₂ nanosheet and/or substrate material. In this study, we revisit and optimize existing parameters for the basal plane of MoS₂ with two popular water models, TIP3P and SPC/E, using the wide range of WCAs from various experiments. We develop and deploy the free energy perturbation method for parametrizing MoS₂ with experimentally determined WCAs for both fresh and aged surfaces. Energy decomposition analysis on the simulation trajectories reveals that MoS₂-water interaction is dominated by van der Waals interaction, which mainly comes from the top layer of MoS₂. We conclude that to describe both fresh and aged MoS₂ surfaces it is convenient to only adjust the Lennard-Jones parameter ε_S (the depth of the potential well of a sulfur atom), which displays a surprisingly linear correlation with WCAs.

Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins

Compared with rapid accumulation of protein sequences from high-throughput DNA sequencing, obtaining experimental 3D structures of proteins is still much more difficult, making protein structure prediction (PSP) potentially very useful. Currently, a vast majority of PSP efforts are based on data mining of known sequences, structures and their relationships (informatics-based). However, if closely related template is not available, these methods are usually much less reliable than experiments. They may also be problematic in predicting the structures of naturally occurring or designed peptides. On the other hand, physics-based methods including molecular dynamics (MD) can utilize our understanding of detailed atomic interactions determining biomolecular structures. In this mini-review, we show that all-atom MD can predict structures of cyclic peptides and other peptide foldamers with accuracy similar to experiments. Then, some notable successes in reproducing experimental 3D structures of small proteins through MD simulations (some with replica-exchange) of the folding were summarized. We also describe advancements of MD-based refinement of structure models, and the integration of limited experimental or bioinformatics data into MD-based structure modeling.

Free-Energy Calculations for Bioisosteric Modifications of A3 Adenosine Receptor Antagonists

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A₃ adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

Residual Structures and Transient Long-Range Interactions of p53 Transactivation Domain: Assessment of Explicit Solvent Protein Force Fields

Molecular dynamics simulations using physics-based atomistic force fields have been increasingly used to characterize the heterogeneous structural ensembles of intrinsically disordered proteins (IDPs). To evaluate the accuracy of the latest atomistic explicit-solvent force fields in modeling larger IDPs with nontrivial structural features, we focus on the 61-residue N-terminal transactivation domain (TAD) of tumor suppressor p53, an important protein in cancer biology that has been extensively studied, and abundant experimental data is available for evaluation of simulated ensembles. We performed extensive replica exchange with solute tempering simulations, in excess of 1.0 μs/replica, to generate disordered structural ensembles of p53-TAD using six latest explicit solvent protein force fields. Multiple local and long-range structural properties, including chain dimension, residual secondary structures, and transient long-range contacts, were analyzed and compared against available experimental data. The results show that IDPs such as p53-TAD remain highly challenging for atomistic simulations due to conformational complexity and difficulty in achieving adequate convergence. Structural ensembles of p53-TAD generated using various force fields differ significantly from each other. The a99SB-disp force field demonstrates the best agreement with experimental data at all levels and proves to be suitable for simulating unbound p53-TAD and how its conformational properties may be modulated by phosphorylation and other cellular signals or cancer-associated mutations. Feasibility of such detailed structural characterization is a key step toward establishing the sequence-disordered ensemble-function-disease relationship of p53 and other biologically important IDPs.

Interdependent Electronic Structure, Protonation, and Solvatization of Aqueous 2-Thiopyridone

2-Thiopyridone (2-TP), a common model system for excited-state proton transfer, has been simulated in aqueous solution with ab initio molecular dynamics. The interplay of electronic structure, protonation, and solvatization is investigated by comparison of three differently protonated molecular forms and between the lowest singlet and triplet electronic states. An interdependence clearly manifests in the mixed-character T₁ state for the 2-TP form, systematic structural distortions of the 2-mercaptopyridine (2-MP) form, and photobase protolysis of the 2-TP^- form, in the aqueous phase. In comparison, simplified continuum models for the solvatization are found to be significantly inaccurate for several of the species. To facilitate future computational studies, we therefore present a minimal representative solvatization complex for each stable form and electronic state. Our findings demonstrate the importance of explicit solvatization of the compound and sets the stage for including it also in future studies.

Computational and Experimental Studies of Inhibitor Design for Aldolase A

Glycolytic enzyme fructose-bisphosphate aldolase A is an emerging therapeutic target in cancer. Recently, we have solved the crystal structure of murine aldolase in complex with naphthalene-2,6-diyl bisphosphate (ND1) that served as a template of the design of bisphosphate-based inhibitors. In this work, a series of ND1 analogues containing difluoromethylene (-CF₂), methylene (-CH₂), or aldehyde substitutions were designed. All designed compounds were studied using molecular dynamics (MD) simulations with the AMOEBA force field. Both energetics and structural analyses have been done to understand the calculated binding free energies. The average distances between ligand and protein atoms for ND1 were very similar to those for the ND1 crystal structure, which indicates that our MD simulation is sampling the correct conformation well. CF₂ insertion lowers the binding free energy by 10-15 kcal/mol, while CF₂ substitution slightly increases the binding free energy, which matches the experimental measurement. In addition, we found that NDB with two CF₂ insertions, the strongest binder, is entropically driven, while others including NDA with one CF₂ insertion are all enthalpically driven. This work provides insights into the mechanisms underlying protein-phosphate binding and enhances the capability of applying computational and theoretical frameworks to model, predict, and design diagnostic strategies targeting cancer.

Computation of protein-ligand binding free energies using quantum mechanical bespoke force fields

A quantum mechanical bespoke molecular mechanics force field is derived for the L99A mutant of T4 lysozyme and used to compute absolute binding free energies of six benzene analogs to the protein. Promising agreement between theory and experiment highlights the potential for future use of system-specific force fields in computer-aided drug design.

Assessment of molecular dynamics simulations for amorphous poly(3-hexylthiophene) using neutron and X-ray scattering experiments

The molecular morphology and dynamics of conjugated polymers in the bulk solid state play a significant role in determining macroscopic charge transport properties. To understand this relationship, molecular dynamics (MD) simulations and quantum mechanical calculations are used to evaluate local electronic properties. In this work, we investigate the importance of system and simulation parameters, such as force fields and equilibration methods, when simulating amorphous poly(3-hexylthiophene) (P3HT), a model semiconducting polymer. An assessment of MD simulations for five different published P3HT force fields is made by comparing results to experimental wide-angle X-ray scattering (WAXS) and to a broad range of quasi-elastic neutron scattering (QENS) data. Moreover, an in silico analysis of force field parameters reveals that atomic partial charges and torsion potentials along the backbone and side chains have the greatest impact on structure and dynamics related to charge transport mechanisms in P3HT.

PyRod: Tracing Water Molecules in Molecular Dynamics Simulations

Ligands entering a protein binding pocket essentially compete with water molecules for binding to the protein. Hence, the location and thermodynamic properties of water molecules in protein structures have gained increased attention in the drug design community. Including corresponding data into 3D pharmacophore modeling is essential for efficient high throughput virtual screening. Here, we present PyRod, a free and open-source Python software that allows for visualization of pharmacophoric binding pocket characteristics, identification of hot spots for ligand binding, and subsequent generation of pharmacophore features for virtual screening. The implemented routines analyze the protein environment of water molecules in molecular dynamics (MD) simulations and can differentiate between hydrogen bonded waters as well as waters in a protein environment of hydrophobic, charged, or aromatic atom groups. The gathered information is further processed to generate dynamic molecular interaction fields (dMIFs) for visualization and pharmacophoric features for virtual screening. The described software was applied to 5 therapeutically relevant drug targets, and generated pharmacophores were evaluated using DUD-E benchmarking sets. The best performing pharmacophore was found for the HIV1 protease with an early enrichment factor of 54.6. PyRod adds a new perspective to structure-based screening campaigns by providing easy-to-interpret dMIFs and purely protein-based pharmacophores that are solely based on tracing water molecules in MD simulations. Since structural information about cocrystallized ligands is not needed, screening campaigns can be followed, for which less or no ligand information is available. PyRod is freely available at https://github.com/schallerdavid/pyrod .

Chemical Dynamics Simulations on Association and Ensuing Dissociation of a Benzene-Hexafluorobenzene Molecular System

Chemical dynamics simulations are performed to study the association of benzene (Bz) and hexafluorobenzene (HFB) followed by the ensuing dissociation of the Bz-HFB complex. The calculations are done for 1000, 1500, and 2000 K with an impact parameter ( b) range of 0-10 Å at each temperature. Almost no complexes are observed to form at b = 8 and 10 Å. Following three different methods of calculation of the temperature-dependent association rate constant k_asso( T), the values obtained are 1.67 × 10^-10, 1.86 × 10^-10, and 2.05 × 10^-10 cm³/molecule·s with a standard deviation of approximately 0.1 × 10^-10 cm³/molecule·s for T = 1500 K. Among those values of k_asso( T), the middle one is obtained by considering a relative translational energy of 3 RT/2 at T = 1500 K, and the same is followed to calculate k_asso( T) at 1000 and 2000 K. The Arrhenius parameters, using the k_asso( T) values at three temperatures, are 0.203 × 10^-10 cm³/molecule·s for the pre-exponential factor and -5.79 kcal/mol for the activation energy. The absolute value of the latter is similar to the Bz + HFB association energy of 5.93 kcal/mol. The ensuing dissociation dynamics of the complex is significantly different from the unimolecular dissociation dynamics, and an exponential function fits the N( t - t₀)/ N( t₀) curves comparatively well. The ensuing dissociation is also observed to be independent of time for a statistically large sample size.

New scaling relations to compute atom-in-material polarizabilities and dispersion coefficients: part 1. Theory and accuracy

Polarizabilities and London dispersion forces are important to many chemical processes. Force fields for classical atomistic simulations can be constructed using atom-in-material polarizabilities and C n (n = 6, 8, 9, 10…) dispersion coefficients. This article addresses the key question of how to efficiently assign these parameters to constituent atoms in a material so that properties of the whole material are better reproduced. We develop a new set of scaling laws and computational algorithms (called MCLF) to do this in an accurate and computationally efficient manner across diverse material types. We introduce a conduction limit upper bound and m-scaling to describe the different behaviors of surface and buried atoms. We validate MCLF by comparing results to high-level benchmarks for isolated neutral and charged atoms, diverse diatomic molecules, various polyatomic molecules (e.g., polyacenes, fullerenes, and small organic and inorganic molecules), and dense solids (including metallic, covalent, and ionic). We also present results for the HIV reverse transcriptase enzyme complexed with an inhibitor molecule. MCLF provides the non-directionally screened polarizabilities required to construct force fields, the directionally-screened static polarizability tensor components and eigenvalues, and environmentally screened C6 coefficients. Overall, MCLF has improved accuracy compared to the TS-SCS method. For TS-SCS, we compared charge partitioning methods and show DDEC6 partitioning yields more accurate results than Hirshfeld partitioning. MCLF also gives approximations for C8, C9, and C10 dispersion coefficients and quantum Drude oscillator parameters. This method should find widespread applications to parameterize classical force fields and density functional theory (DFT) + dispersion methods.

LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands

The accurate calculation of protein/nucleic acid–ligand interactions or condensed phase properties by force field-based methods require a precise description of the energetics of intermolecular interactions. Despite the progress made in force fields, small molecule parameterization remains an open problem due to the magnitude of the chemical space; the most critical issue is the estimation of a balanced set of atomic charges with the ability to reproduce experimental properties. The LigParGen web server provides an intuitive interface for generating OPLS-AA/1.14*CM1A(-LBCC) force field parameters for organic ligands, in the formats of commonly used molecular dynamics and Monte Carlo simulation packages. This server has high value for researchers interested in studying any phenomena based on intermolecular interactions with ligands via molecular mechanics simulations. It is free and open to all at jorgensenresearch.com/ligpargen, and has no login requirements.

Methods for the Refinement of Protein Structure 3D Models

The refinement of predicted 3D protein models is crucial in bringing them closer towards experimental accuracy for further computational studies. Refinement approaches can be divided into two main stages: The sampling and scoring stages. Sampling strategies, such as the popular Molecular Dynamics (MD)-based protocols, aim to generate improved 3D models. However, generating 3D models that are closer to the native structure than the initial model remains challenging, as structural deviations from the native basin can be encountered due to force-field inaccuracies. Therefore, different restraint strategies have been applied in order to avoid deviations away from the native structure. For example, the accurate prediction of local errors and/or contacts in the initial models can be used to guide restraints. MD-based protocols, using physics-based force fields and smart restraints, have made significant progress towards a more consistent refinement of 3D models. The scoring stage, including energy functions and Model Quality Assessment Programs (MQAPs) are also used to discriminate near-native conformations from non-native conformations. Nevertheless, there are often very small differences among generated 3D models in refinement pipelines, which makes model discrimination and selection problematic. For this reason, the identification of the most native-like conformations remains a major challenge.

Evolution of All-Atom Protein Force Fields to Improve Local and Global Properties

Experimental studies on intrinsically disordered and unfolded proteins have shown that in isolation they typically have low populations of secondary structure and exhibit distance scalings suggesting that they are at near-theta-solvent conditions. Until recently, however, all-atom force fields failed to reproduce these fundamental properties of intrinsically disordered proteins (IDPs). Recent improvements by refining against ensemble-averaged experimental observables for polypeptides in aqueous solution have addressed deficiencies including secondary structure bias, global conformational properties, and thermodynamic parameters of biophysical reactions such as folding and collapse. To date, studies utilizing these improved all-atom force fields have mostly been limited to a small set of unfolded or disordered proteins. Here, we present data generated for a diverse library of unfolded or disordered proteins using three progressively improved generations of Amber03 force fields, and we explore how global and local properties are affected by each successive change in the force field. We find that the most recent force field refinements significantly improve the agreement of the global properties such as radii of gyration and end-to-end distances with experimental estimates. However, these global properties are largely independent of the local secondary structure propensity. This result stresses the need to validate force fields with reference to a combination of experimental data providing information about both local and global structure formation.

The characterization of Thermotoga maritima Arginine Binding Protein variants demonstrates that minimal local strains have an important impact on protein stability

The Ramachandran plot is a versatile and valuable tool that provides fundamental information for protein structure determination, prediction, and validation. The structural/thermodynamic effects produced by forcing a residue to adopt a conformation predicted to be forbidden were here explored using Thermotoga maritima Arginine Binding Protein (TmArgBP) as model. Specifically, we mutated TmArgBP Gly52 that assumes a conformation believed to be strictly disallowed for non-Gly residues. Surprisingly, the crystallographic characterization of Gly52Ala TmArgBP indicates that the structural context forces the residue to adopt a non-canonical conformation never observed in any of the high-medium resolution PDB structures. Interestingly, the inspection of this high resolution structure demonstrates that only minor alterations occur. Nevertheless, experiments indicate that Gly52 replacements in TmArgBP produce destabilizations comparable to those observed upon protein truncation or dissection in domains. Notably, we show that force-fields commonly used in computational biology do not reproduce this non-canonical state. Using TmArgBP as model system we here demonstrate that the structural context may force residues to adopt conformations believed to be strictly forbidden and that barely detectable alterations produce major destabilizations. Present findings highlight the role of subtle strains in governing protein stability. A full understanding of these phenomena is essential for an exhaustive comprehension of the factors regulating protein structures.

Mechanism of Trehalose-Induced Protein Stabilization from Neutron Scattering and Modeling

The sugar molecule trehalose has been proven to be an excellent stabilizing cosolute for the preservation of biological materials. However, the stabilizing mechanism of trehalose has been much debated during the previous decades, and it is still not fully understood, partly because it has not been completely established how trehalose molecules structure around proteins. Here, we present a molecular model of a protein-water-trehalose system, based on neutron scattering results obtained from neutron diffraction, quasielastic neutron scattering, and different computer modeling techniques. The structural data clearly show how the proteins are preferentially hydrated, and analysis of the dynamical properties show that the protein residues are slowed down because of reduced dynamics of the protein hydration shell, rather than because of direct trehalose-protein interactions. These findings, thereby, strongly support previous models related to the preferential hydration model and contradict other models based on water replacement at the protein surface. Furthermore, the results are important for understanding the specific role of trehalose in biological stabilization and, more generally, for providing a likely mechanism of how cosolutes affect the dynamics of proteins.

Development and Testing of the OPLS-AA/M Force Field for RNA

Significant improvements have been made to the OPLS-AA force field for modeling RNA. New torsional potentials were optimized based on density functional theory (DFT) scans at the ωB97X-D/6-311++G(d,p) level for potential energy surfaces of the backbone α and γ dihedral angles. In combination with previously reported improvements for the sugar puckering and glycosidic torsion terms, the new force field was validated through diverse molecular dynamics simulations for RNAs in aqueous solution. Results for dinucleotides and tetranucleotides revealed both accurate reproduction of 3 J couplings from NMR and the avoidance of several unphysical states observed with other force fields. Simulations of larger systems with noncanonical motifs showed significant structural improvements over the previous OPLS-AA parameters. The new force field, OPLS-AA/M, is expected to perform competitively with other recent RNA force fields and to be compatible with OPLS-AA models for proteins and small molecules.

Free Energy Calculations Based on Coupling Proximal Distribution Functions and Thermodynamic Cycles

Techniques to calculate the free energy changes of a system are very useful in the study of biophysical and biochemical properties. In practice, free energy changes can be described with thermodynamic cycles, and the free energy change of an individual process can be computed by sufficiently sampling the corresponding configurations. However, this is still time-consuming especially for large biomolecular systems. Previously, we have shown that by utilizing precomputed solute-solvent correlations, so-called proximal distribution functions (pDF), we are capable of reconstructing the solvent environment near solute atoms, thus estimating the solute-solvent interactions and solvation free energies of molecules. In this contribution, we apply the technique of pDF-reconstructions to calculate chemical potentials and use this information in thermodynamic cycles. This illustrates how free energy changes of nontrivial chemical processes in aqueous solution systems can be rapidly estimated.

A Better Understanding of the Unimolecular Dissociation Dynamics of Weakly Bound Aromatic Compounds at High Temperature: A Study on C6H6-C6F6 and Comparison with C6H6 Dimer

Chemical dynamics simulations are performed to study the unimolecular dissociation of the benzene (Bz)-hexafluorobenzene (HFB) complex at five different temperatures ranging from 1000 to 2000 K, and the results are compared with that of the Bz dimer at common simulation temperatures. Bz-HFB, in comparison with Bz dimer, possesses a much attractive intermolecular interaction, a very different equilibrium geometry, and a lower average quantum vibrational excitation energy at a given temperature. Six low-frequency modes of Bz-HFB are formed by Bz + HFB association which are weakly coupled with the vibrational modes of Bz and HFB. However, this coupling is found much stronger in Bz-HFB compared to the same in the Bz dimer. The simulations are done with very good potential energy parameters taken from the literature. Considering the canonical (TST) model, the unimolecular dissociation rate constant at each temperature is calculated and fitted to the Arrhenius equation. An activation energy of 5.0 kcal/mol and a pre-exponential factor of 2.39 × 10¹² s^-1 are obtained, which are of expected magnitudes. The responsible vibrational mode for dissociation is identified by performing normal-mode analysis. Simulations with random excitations of high-frequency Bz and HFB modes and low-frequency inter-Bz-HFB vibrational modes of the Bz-HFB complex are also performed. The intramolecular vibrational energy redistribution (IVR) time and the unimolecular dissociation rate constants are calculated from these simulations. The latter shows good agreement with the same obtained from simulation with random excitation of all vibrational modes.

QligFEP: an automated workflow for small molecule free energy calculations in Q

The process of ligand binding to a biological target can be represented as the equilibrium between the relevant solvated and bound states of the ligand. This which is the basis of structure-based, rigorous methods such as the estimation of relative binding affinities by free energy perturbation (FEP). Despite the growing capacity of computing power and the development of more accurate force fields, a high throughput application of FEP is currently hampered due to the need, in the current schemes, of an expert user definition of the "alchemical" transformations between molecules in the series explored. Here, we present QligFEP, a solution to this problem using an automated workflow for FEP calculations based on a dual topology approach. In this scheme, the starting poses of each of the two ligands, for which the relative affinity is to be calculated, are explicitly present in the MD simulations associated with the (dual topology) FEP transformation, making the perturbation pathway between the two ligands univocal. We show that this generalized method can be applied to accurately estimate solvation free energies for amino acid sidechain mimics, as well as the binding affinity shifts due to the chemical changes typical of lead optimization processes. This is illustrated in a number of protein systems extracted from other FEP studies in the literature: inhibitors of CDK2 kinase and a series of A2A adenosine G protein-coupled receptor antagonists, where the results obtained with QligFEP are in excellent agreement with experimental data. In addition, our protocol allows for scaffold hopping perturbations to identify the binding affinities between different core scaffolds, which we illustrate with a series of Chk1 kinase inhibitors. QligFEP is implemented in the open-source MD package Q, and works with the most common family of force fields: OPLS, CHARMM and AMBER.

Adsorption of amino acids on graphene: assessment of current force fields

We compare the free energies of adsorption (ΔAads) and the structural preferences of amino acids on graphene obtained using the non-polarizable force fields-Amberff99SB-ILDN/TIP3P, CHARMM36/modified-TIP3P, OPLS-AA/M/TIP3P, and Amber03w/TIP4P/2005. The amino acid-graphene interactions are favorable irrespective of the force field. While the magnitudes of ΔAads differ between the force fields, the relative free energy of adsorption across amino acids is similar for the studied force fields. ΔAads positively correlates with amino acid-graphene and negatively correlates with graphene-water interaction energies. Using a combination of principal component analysis and density-based clustering technique, we grouped the structures observed in the graphene adsorbed state. The resulting population of clusters, and the conformation in each cluster indicate that the structures of the amino acid in the graphene adsorbed state vary across force fields. The differences in the conformations of amino acids are more severe in the graphene adsorbed state compared to the bulk state for all the force fields. Our findings suggest that the force fields studied will give qualitatively consistent relative strength of adsorption across proteins but different structural preferences in the graphene adsorbed state.

A study of CCD8 genes/proteins in seven monocots and eight dicots

In plants, the enzyme CCD8 (carotenoid cleavage dioxygenase 8) is involved in the synthesis of an important hormone, strigolactone, and therefore, plays an important role in controlling growth and development. Using cDNA and protein sequence derived from the gene ZmCCD8 from maize, we identified putative orthologs of the gene encoding CCD8 in six other monocots and eight dicots; the sequence similarity ranged from 52–75.9% at the gene level and 60.9–93.7% at the protein level. The average length of the gene was ~3.3 kb (range: 2.08 to 3.98 kb), although the number of introns within the genes differed (4 or 5 in dicots and 3 or 4 in monocots, except in T. urartu with 6 introns). Several cis-acting regulatory elements were identified in the promoters of CCD8 genes, which are known to respond to biotic and abiotic stresses. The N-terminal end (up to ~70 amino acids) of CCD8 proteins was highly variable due to insertions, deletions and mismatches. The variation in genes and proteins were particularly conspicuous in T. urartu and Ae. tauschii among the monocots and A. thaliana and P. persica among the dicots. In CCD8 proteins, 12 motifs were also identified, of which 6 were novel; 4 of these novel motifs occurred in all the 15 species. The 3D structures of proteins had the characteristic features of the related enzyme apocarotenoid oxygenase (ACO) of Synechocystis (a representative of cyanobacteria). The results of qRT-PCR in wheat revealed that under phosphorous (P)-starved condition (relative to expression under optimum P used as control), the expression of TaCCD8 genes increased ~37 fold in root tissue of the cultivar C306 and ~33 fold in shoot tissue of the cultivar HUW468 (the two cultivars differed in their P-use efficiency). This suggested that expression of TaCCD8 genes is genotype-dependent and tissue-specific and is regulated under different levels of P supply.

Deriving Force-Field Parameters from First Principles Using a Polarizable and Higher Order Dispersion Model

In this work we propose a strategy based on quantum mechanical (QM) calculations to parametrize a polarizable force field for use in molecular dynamics (MD) simulations. We investigate the use of multiple atoms-in-molecules (AIM) strategies to partition QM determined molecular electron densities into atomic subregions. The partitioned atomic densities are subsequently used to compute atomic dispersion coefficients from effective exchange-hole-dipole moment (XDM) calculations. In order to derive values for the repulsive van der Waals parameters from first principles, we use a simple volume relation to scale effective atomic radii. Explicit inclusion of higher order dispersion coefficients was tested for a series of alkanes, and we show that combining C6 and C8 attractive terms together with a C11 repulsive potential yields satisfying models when used in combination with our van der Waals parameters and electrostatic and bonded parameters as directly obtained from quantum calculations as well. This result highlights that explicit inclusion of higher order dispersion terms could be viable in simulation, and it suggests that currently available QM analysis methods allow for first-principles parametrization of molecular mechanics models.

Computational and In-Vitro Validation of Natural Molecules as Potential Acetylcholinesterase Inhibitors and Neuroprotective Agents

Background:

Cholinesterase inhibitors are the first line of therapy for the management of Alzheimer’s disease (AD), however, it is now established that they provide only temporary and symptomatic relief, besides, having several inherited side-effects. Therefore, an alternative drug discovery method is used to identify new and safer ‘disease-modifying drugs’.

Methods:

Herein, we screened 646 small molecules of natural origin having reported pharmacological and functional values through in-silico docking studies to predict safer neuromodulatory molecules with potential to modulate acetylcholine metabolism. Further, the potential of the predicted molecules to inhibit acetylcholinesterase (AChE) activity and their ability to protect neurons from degeneration was determined through in-vitro assays.

Results:

Based on in-silico AChE interaction studies, we predicted quercetin, caffeine, ascorbic acid and gallic acid to be potential AChE inhibitors. We confirmed the AChE inhibitory potential of these molecules through in-vitro AChE inhibition assay and compared results with donepezil and begacestat. Herbal molecules significantly inhibited enzyme activity and inhibition for quercetin and caffeine did not show any significant difference from donepezil. Further, the tested molecules did not show any neurotoxicity against primary (E18) hippocampal neurons. We observed that quercetin and caffeine significantly improved neuronal survival and efficiently protected hippocampal neurons from HgCl2 induced neurodegeneration, which other molecules, including donepezil and begacestat, failed to do.

Conclusion:

Quercetin and caffeine have the potential as “disease-modifying drugs” and may find application in the management of neurological disorders such as AD.