ResearchPad - free-energy https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[How global DNA unwinding causes non-uniform stress distribution and melting of DNA]]> https://www.researchpad.co/article/elastic_article_14712 DNA unwinding is an important process that controls binding of proteins, gene expression and melting of double-stranded DNA. In a series of all-atom MD simulations on two DNA molecules containing a transcription start TATA-box sequence we demonstrate that application of a global restraint on the DNA twisting dramatically changes the coupling between helical parameters and the distribution of deformation energy along the sequence. Whereas only short range nearest-neighbor coupling is observed in the relaxed case, long-range coupling is induced in the globally restrained case. With increased overall unwinding the elastic deformation energy is strongly non-uniformly distributed resulting ultimately in a local melting transition of only the TATA box segment during the simulations. The deformation energy tends to be stored more in cytidine/guanine rich regions associated with a change in conformational substate distribution. Upon TATA box melting the deformation energy is largely absorbed by the melting bubble with the rest of the sequences relaxing back to near B-form. The simulations allow us to characterize the structural changes and the propagation of the elastic energy but also to calculate the associated free energy change upon DNA unwinding up to DNA melting. Finally, we design an Ising model for predicting the local melting transition based on empirical parameters. The direct comparison with the atomistic MD simulations indicates a remarkably good agreement for the predicted necessary torsional stress to induce a melting transition, for the position and length of the melted region and for the calculated associated free energy change between both approaches.

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<![CDATA[Conservation laws by virtue of scale symmetries in neural systems]]> https://www.researchpad.co/article/elastic_article_14657 Considerations of the way in which a dynamical system changes under transformation of scale offer insight into its operational principles. Scale freeness is a paradigm that has been observed in a variety of physical and biological phenomena and describes a situation in which appropriately scaling the space and time coordinates of any evolution of the system yields another possible evolution. In the brain, scale freeness has drawn considerable attention, as it has been associated with optimal information transmission capabilities. Scale symmetry describes a special case of scale freeness, in which a system is perfectly unchanged under transformation of scale. Noether’s theorem tells us that in a system that possesses such a symmetry, an associated conservation law must also exist. Here we show that scale symmetry can be identified, and the related conserved quantities measured, in both simulations and real-world data. We achieve this by deriving a generalised equation of motion that leaves the action invariant under spatiotemporal scale transformations and using a modified version of Noether’s theorem to write the associated family of conservation laws. Our contribution allows for the first such statistical characterisation of the quantity that is conserved purely by virtue of scale symmetry.

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<![CDATA[Chemical profile of Lippia thymoides, evaluation of the acetylcholinesterase inhibitory activity of its essential oil, and molecular docking and molecular dynamics simulations]]> https://www.researchpad.co/article/5c8c194fd5eed0c484b4d3c7

The essential oils of the fresh and dry flowers, leaves, branches, and roots of Lippia thymoides were obtained by hydrodistillation and analyzed using gas chromatography (GC) and GC–mass spectrometry (MS). The acetylcholinesterase inhibitory activity of the essential oil of fresh leaves was investigated on silica gel plates. The interactions of the key compounds with acetylcholinesterase were simulated by molecular docking and molecular dynamics studies. In total, 75 compounds were identified, and oxygenated monoterpenes were the dominant components of all the plant parts, ranging from 19.48% to 84.99%. In the roots, the main compounds were saturated and unsaturated fatty acids, having contents varying from 39.5% to 32.17%, respectively. In the evaluation of the anticholinesterase activity, the essential oils (detection limit (DL) = 0.1 ng/spot) were found to be about ten times less active than that of physostigmine (DL = 0.01ng/spot), whereas thymol and thymol acetate presented DL values each of 0.01 ng/spot, equivalent to that of the positive control. Based on the docking and molecular dynamics studies, thymol and thymol acetate interact with the catalytic residues Ser203 and His447 of the active site of acetylcholinesterase. The binding free energies (ΔGbind) for these ligands were -18.49 and -26.88 kcal/mol, demonstrating that the ligands are able to interact with the protein and inhibit their catalytic activity.

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<![CDATA[Metal based donepezil analogues designed to inhibit human acetylcholinesterase for Alzheimer’s disease]]> https://www.researchpad.co/article/5c76fe06d5eed0c484e5b2cd

Among neurodegenerative disorders, Alzheimer’s disease (AD) is one of the most common disorders showing slow progressive cognitive decline. Targeting acetylcholinesterase (AChE) is one of the major strategies for AD therapeutics, as cholinergic pathways in the cerebral cortex and basal forebrain are compromised. Herein, we report the design of some copper and other metal based donepezil derivatives, employing density functional theory (DFT). All designed compounds are optimized at the B3LYP/SDD level of theory. Dipole moments, electronic energie, enthalpies, Gibbs free energies, and HOMO-LUMO gaps of these modified compounds are also investigated in the subsequent analysis. The molecules were then subjected to molecular docking analysis with AChE to study the molecular interactions broadly. Ensemble based docking and molecular dynamics (MD) simulations of the best candidates were also performed. Docking and MD simulation reveal that modified drugs are more potent than unmodified donepezil, where Trp86, Tyr337, Phe330 residues play some important roles in drug-receptor interactions. According to ensemble based docking, D9 shows greater binding affinity compared to the parent in most conformations obtained from protein data bank and MD simulation. In addition, it is observed that the π- π stacking with the residues of Trp86, Tyr337, Tyr341, Tyr124 and Trp286 may be required for strong ligand binding. Moreover, ADME/T analysis suggests that modified derivatives are less toxic and have improved pharmacokinetic properties than those of the parent drug. These results further confirm the ability of metal-directed drugs to bind simultaneously to the active sites of AChE and support them as potential candidates for the future treatment of Alzheimer’s disease.

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<![CDATA[Predicting change: Approximate inference under explicit representation of temporal structure in changing environments]]> https://www.researchpad.co/article/5c5ca27ed5eed0c48441e4cc

In our daily lives timing of our actions plays an essential role when we navigate the complex everyday environment. It is an open question though how the representations of the temporal structure of the world influence our behavior. Here we propose a probabilistic model with an explicit representation of state durations which may provide novel insights in how the brain predicts upcoming changes. We illustrate several properties of the behavioral model using a standard reversal learning design and compare its task performance to standard reinforcement learning models. Furthermore, using experimental data, we demonstrate how the model can be applied to identify participants’ beliefs about the latent temporal task structure. We found that roughly one quarter of participants seem to have learned the latent temporal structure and used it to anticipate changes, whereas the remaining participants’ behavior did not show signs of anticipatory responses, suggesting a lack of precise temporal expectations. We expect that the introduced behavioral model will allow, in future studies, for a systematic investigation of how participants learn the underlying temporal structure of task environments and how these representations shape behavior.

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<![CDATA[Kinetic and thermodynamic insights into sodium ion translocation through the μ-opioid receptor from molecular dynamics and machine learning analysis]]> https://www.researchpad.co/article/5c536a92d5eed0c484a47639

The differential modulation of agonist and antagonist binding to opioid receptors (ORs) by sodium (Na+) has been known for decades. To shed light on the molecular determinants, thermodynamics, and kinetics of Na+ translocation through the μ-OR (MOR), we used a multi-ensemble Markov model framework combining equilibrium and non-equilibrium atomistic molecular dynamics simulations of Na+ binding to MOR active or inactive crystal structures embedded in an explicit lipid bilayer. We identify an energetically favorable, continuous ion pathway through the MOR active conformation only, and provide, for the first time: i) estimates of the energy differences and required timescales of Na+ translocation in inactive and active MORs, ii) estimates of Na+-induced changes to agonist binding validated by radioligand measurements, and iii) testable hypotheses of molecular determinants and correlated motions involved in this translocation, which are likely to play a key role in MOR signaling.

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<![CDATA[Thioguanine-based DENV-2 NS2B/NS3 protease inhibitors: Virtual screening, synthesis, biological evaluation and molecular modelling]]> https://www.researchpad.co/article/5c536b8fd5eed0c484a48cc8

Dengue virus Type 2 (DENV-2) is predominant serotype causing major dengue epidemics. There are a number of studies carried out to find its effective antiviral, however to date, there is still no molecule either from peptide or small molecules released as a drug. The present study aims to identify small molecules inhibitor from National Cancer Institute database through virtual screening. One of the hits, D0713 (IC50 = 62 μM) bearing thioguanine scaffold was derivatised into 21 compounds and evaluated for DENV-2 NS2B/NS3 protease inhibitory activity. Compounds 18 and 21 demonstrated the most potent activity with IC50 of 0.38 μM and 16 μM, respectively. Molecular dynamics and MM/PBSA free energy of binding calculation were conducted to study the interaction mechanism of these compounds with the protease. The free energy of binding of 18 calculated by MM/PBSA is -16.10 kcal/mol compared to the known inhibitor, panduratin A (-11.27 kcal/mol), which corroborates well with the experimental observation. Results from molecular dynamics simulations also showed that both 18 and 21 bind in the active site and stabilised by the formation of hydrogen bonds with Asn174.

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<![CDATA[Locus Coeruleus tracking of prediction errors optimises cognitive flexibility: An Active Inference model]]> https://www.researchpad.co/article/5c390b8dd5eed0c48491d307

The locus coeruleus (LC) in the pons is the major source of noradrenaline (NA) in the brain. Two modes of LC firing have been associated with distinct cognitive states: changes in tonic rates of firing are correlated with global levels of arousal and behavioural flexibility, whilst phasic LC responses are evoked by salient stimuli. Here, we unify these two modes of firing by modelling the response of the LC as a correlate of a prediction error when inferring states for action planning under Active Inference (AI). We simulate a classic Go/No-go reward learning task and a three-arm ‘explore/exploit’ task and show that, if LC activity is considered to reflect the magnitude of high level ‘state-action’ prediction errors, then both tonic and phasic modes of firing are emergent features of belief updating. We also demonstrate that when contingencies change, AI agents can update their internal models more quickly by feeding back this state-action prediction error–reflected in LC firing and noradrenaline release–to optimise learning rate, enabling large adjustments over short timescales. We propose that such prediction errors are mediated by cortico-LC connections, whilst ascending input from LC to cortex modulates belief updating in anterior cingulate cortex (ACC). In short, we characterise the LC/ NA system within a general theory of brain function. In doing so, we show that contrasting, behaviour-dependent firing patterns are an emergent property of the LC that translates state-action prediction errors into an optimal balance between plasticity and stability.

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<![CDATA[Energy landscape for the insertion of amphiphilic nanoparticles into lipid membranes: A computational study]]> https://www.researchpad.co/article/5c3fa610d5eed0c484cabadc

Amphiphilic, monolayer-protected gold nanoparticles (NPs) have been shown to enter cells via a non-endocytic, non-disruptive pathway that could be valuable for biomedical applications. The same NPs were also found to insert into a series of model cell membranes as a precursor to cellular uptake, but the insertion mechanism remains unclear. Previous simulations have demonstrated that an amphiphilic NP can insert into a single leaflet of a planar lipid bilayer, but in this configuration all charged end groups are localized to one side of the bilayer and it is unknown if further insertion is thermodynamically favorable. Here, we use atomistic molecular dynamics simulations to show that an amphiphilic NP can reach the bilayer midplane non-disruptively if charged ligands iteratively “flip” across the bilayer. Ligand flipping is a favorable process that relaxes bilayer curvature, decreases the nonpolar solvent-accessible surface area of the NP monolayer, and increases attractive ligand-lipid electrostatic interactions. Analysis of end group hydration further indicates that iterative ligand flipping can occur on experimentally relevant timescales. Supported by these results, we present a complete energy landscape for the non-disruptive insertion of amphiphilic NPs into lipid bilayers. These findings will help guide the design of NPs to enhance bilayer insertion and non-endocytic cellular uptake, and also provide physical insight into a possible pathway for the translocation of charged biomacromolecules.

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<![CDATA[Trajectory-based training enables protein simulations with accurate folding and Boltzmann ensembles in cpu-hours]]> https://www.researchpad.co/article/5c2e7fdbd5eed0c48451bc2f

An ongoing challenge in protein chemistry is to identify the underlying interaction energies that capture protein dynamics. The traditional trade-off in biomolecular simulation between accuracy and computational efficiency is predicated on the assumption that detailed force fields are typically well-parameterized, obtaining a significant fraction of possible accuracy. We re-examine this trade-off in the more realistic regime in which parameterization is a greater source of error than the level of detail in the force field. To address parameterization of coarse-grained force fields, we use the contrastive divergence technique from machine learning to train from simulations of 450 proteins. In our procedure, the computational efficiency of the model enables high accuracy through the precise tuning of the Boltzmann ensemble. This method is applied to our recently developed Upside model, where the free energy for side chains is rapidly calculated at every time-step, allowing for a smooth energy landscape without steric rattling of the side chains. After this contrastive divergence training, the model is able to de novo fold proteins up to 100 residues on a single core in days. This improved Upside model provides a starting point both for investigation of folding dynamics and as an inexpensive Bayesian prior for protein physics that can be integrated with additional experimental or bioinformatic data.

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<![CDATA[Enzymatic and non-enzymatic pathways of kynurenines' dimerization: the molecular factors for oxidative stress development]]> https://www.researchpad.co/article/5c181389d5eed0c484775320

Kynurenines, the products of tryptophan oxidative degradation, are involved in multiple neuropathologies, such as Huntington's chorea, Parkinson's disease, senile dementia, etc. The major cause for hydroxykynurenines's neurotoxicity is the oxidative stress induced by the reactive oxygen species (ROS), the by-products of L-3-hydroxykynurenine (L-3HOK) and 3-hydroxyanthranilic acid (3HAA) oxidative self-dimerization. 2-aminophenol (2AP), a structural precursor of L-3HOK and 3HAA, undergoes the oxidative conjugation to form 2-aminophenoxazinone. There are several modes of 2AP dimerization, including both enzymatic and non-enzymatic stages. In this study, the free energies for 2AP, L-3HOK and 3HAA dimerization stages have been calculated at B3LYP/6-311G(d,p)//6-311+(O)+G(d) level, both in the gas phase and in heptane or water solution. For the intermediates, ionization potentials and electron affinities were calculated, as well as free energy and kinetics of molecular oxygen interaction with several non-enzymatically formed dimers. H-atom donating power of the intermediates increases upon the progress of the oxidation, making possible generation of hydroperoxyl radical or hydrogen peroxide from O2 at the last stages. Among the dimerization intermediates, 2-aminophenoxazinole derivatives have the lowest ionization potential and can reduce O2 to superoxide anion. The rate for O-H homolytic bond dissociation is significantly higher than that for C-H bond in non-enzymatic quinoneimine conjugate. However, the last reaction passes irreversibly, reducing O2 to hydroperoxyl radical. The inorganic ferrous iron and the heme group of Drosophila phenoxazinone synthase significantly reduce the energy cost of 2AP H-atom abstraction by O2. We have also shown experimentally that total antioxidant capacity decreases in Drosophila mutant cardinal with L-3HOK excess relative to the wild type Canton-S, and lipid peroxidation decreases in aged cardinal. Taken together, our data supports the conception of hydroxykynurenines' dual role in neurotoxicity: serving as antioxidants themselves, blocking lipid peroxidation by H-atom donation, they also can easily generate ROS upon dimerization, leading to the oxidative stress development.

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<![CDATA[A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins]]> https://www.researchpad.co/article/5c0ed755d5eed0c484f13f37

Intrinsically disordered proteins/regions (IDPs/IDRs) are prevalent in allosteric regulation. It was previously thought that intrinsic disorder is favorable for maximizing the allosteric coupling. Here, we propose a comprehensive ensemble model to compare the roles of both order-order transition and disorder-order transition in allosteric effect. It is revealed that the MWC pathway (order-order transition) has a higher probability than the EAM pathway (disorder-order transition) in allostery, suggesting a complicated role of IDPs/IDRs in regulatory proteins. In addition, an analytic formula for the maximal allosteric coupling response is obtained, which shows that too stable or too unstable state is unfavorable to endow allostery, and is thus helpful for rational design of allosteric drugs.

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<![CDATA[Binding of the general anesthetic sevoflurane to ion channels]]> https://www.researchpad.co/article/5c059df1d5eed0c4849c981e

The direct-site hypothesis assumes general anesthetics bind ion channels to impact protein equilibrium and function, inducing anesthesia. Despite advancements in the field, a first principle all-atom demonstration of this structure-function premise is still missing. We focus on the clinically used sevoflurane interaction to anesthetic-sensitive Kv1.2 mammalian channel to resolve if sevoflurane binds protein’s well-characterized open and closed structures in a conformation-dependent manner to shift channel equilibrium. We employ an innovative approach relying on extensive docking calculations and free-energy perturbation of all potential binding sites revealed by the latter, and find sevoflurane binds open and closed structures at multiple sites under complex saturation and concentration effects. Results point to a non-trivial interplay of site and conformation-dependent modes of action involving distinct binding sites that increase channel open-probability at diluted ligand concentrations. Given the challenge in exploring more complex processes potentially impacting channel-anesthetic interaction, the result is revealing as it demonstrates the process of multiple anesthetic binding events alone may account for open-probability shifts recorded in measurements.

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<![CDATA[Towards a molecular basis of ubiquitin signaling: A dual-scale simulation study of ubiquitin dimers]]> https://www.researchpad.co/article/5bf86f60d5eed0c48405a957

Covalent modification of proteins by ubiquitin or ubiquitin chains is one of the most prevalent post-translational modifications in eukaryotes. Different types of ubiquitin chains are assumed to selectively signal respectively modified proteins for different fates. In support of this hypothesis, structural studies have shown that the eight possible ubiquitin dimers adopt different conformations. However, at least in some cases, these structures cannot sufficiently explain the molecular basis of the selective signaling mechanisms. This indicates that the available structures represent only a few distinct conformations within the entire conformational space adopted by a ubiquitin dimer. Here, molecular simulations on different levels of resolution can complement the structural information. We have combined exhaustive coarse grained and atomistic simulations of all eight possible ubiquitin dimers with a suitable dimensionality reduction technique and a new method to characterize protein-protein interfaces and the conformational landscape of protein conjugates. We found that ubiquitin dimers exhibit characteristic linkage type-dependent properties in solution, such as interface stability and the character of contacts between the subunits, which can be directly correlated with experimentally observed linkage-specific properties.

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<![CDATA[Allosteric binding sites in Rab11 for potential drug candidates]]> https://www.researchpad.co/article/5b28b6fa463d7e13c14ded96

Rab11 is an important protein subfamily in the RabGTPase family. These proteins physiologically function as key regulators of intracellular membrane trafficking processes. Pathologically, Rab11 proteins are implicated in many diseases including cancers, neurodegenerative diseases and type 2 diabetes. Although they are medically important, no previous study has found Rab11 allosteric binding sites where potential drug candidates can bind to. In this study, by employing multiple clustering approaches integrating principal component analysis, independent component analysis and locally linear embedding, we performed structural analyses of Rab11 and identified eight representative structures. Using these representatives to perform binding site mapping and virtual screening, we identified two novel binding sites in Rab11 and small molecules that can preferentially bind to different conformations of these sites with high affinities. After identifying the binding sites and the residue interaction networks in the representatives, we computationally showed that these binding sites may allosterically regulate Rab11, as these sites communicate with switch 2 region that binds to GTP/GDP. These two allosteric binding sites in Rab11 are also similar to two allosteric pockets in Ras that we discovered previously.

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<![CDATA[Structural Determinants of Misfolding in Multidomain Proteins]]> https://www.researchpad.co/article/5989da7aab0ee8fa60b980a6

Recent single molecule experiments, using either atomic force microscopy (AFM) or Förster resonance energy transfer (FRET) have shown that multidomain proteins containing tandem repeats may form stable misfolded structures. Topology-based simulation models have been used successfully to generate models for these structures with domain-swapped features, fully consistent with the available data. However, it is also known that some multidomain protein folds exhibit no evidence for misfolding, even when adjacent domains have identical sequences. Here we pose the question: what factors influence the propensity of a given fold to undergo domain-swapped misfolding? Using a coarse-grained simulation model, we can reproduce the known propensities of multidomain proteins to form domain-swapped misfolds, where data is available. Contrary to what might be naively expected based on the previously described misfolding mechanism, we find that the extent of misfolding is not determined by the relative folding rates or barrier heights for forming the domains present in the initial intermediates leading to folded or misfolded structures. Instead, it appears that the propensity is more closely related to the relative stability of the domains present in folded and misfolded intermediates. We show that these findings can be rationalized if the folded and misfolded domains are part of the same folding funnel, with commitment to one structure or the other occurring only at a relatively late stage of folding. Nonetheless, the results are still fully consistent with the kinetic models previously proposed to explain misfolding, with a specific interpretation of the observed rate coefficients. Finally, we investigate the relation between interdomain linker length and misfolding, and propose a simple alchemical model to predict the propensity for domain-swapped misfolding of multidomain proteins.

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<![CDATA[The structural basis of a high affinity ATP binding ε subunit from a bacterial ATP synthase]]> https://www.researchpad.co/article/5989db5cab0ee8fa60bdfe83

The ε subunit from bacterial ATP synthases functions as an ATP sensor, preventing ATPase activity when the ATP concentration in bacterial cells crosses a certain threshold. The R103A/R115A double mutant of the ε subunit from thermophilic Bacillus PS3 has been shown to bind ATP two orders of magnitude stronger than the wild type protein. We use molecular dynamics simulations and free energy calculations to derive the structural basis of the high affinity ATP binding to the R103A/R115A double mutant. Our results suggest that the double mutant is stabilized by an enhanced hydrogen-bond network and fewer repulsive contacts in the ligand binding site. The inferred structural basis of the high affinity mutant may help to design novel nucleotide sensors based on the ε subunit from bacterial ATP synthases.

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<![CDATA[Accelerated flexible protein-ligand docking using Hamiltonian replica exchange with a repulsive biasing potential]]> https://www.researchpad.co/article/5989db51ab0ee8fa60bdc4dc

A molecular dynamics replica exchange based method has been developed that allows rapid identification of putative ligand binding sites on the surface of biomolecules. The approach employs a set of ambiguity restraints in replica simulations between receptor and ligand that allow close contacts in the reference replica but promotes transient dissociation in higher replicas. This avoids long-lived trapping of the ligand or partner proteins at nonspecific, sticky, sites on the receptor molecule and results in accelerated exploration of the possible binding regions. In contrast to common docking methods that require knowledge of the binding site, exclude solvent and often keep parts of receptor and ligand rigid the approach allows for full flexibility of binding partners. Application to peptide-protein, protein-protein and a drug-receptor system indicate rapid sampling of near-native binding regions even in case of starting far away from the native binding site outperforming continuous MD simulations. An application on a DNA minor groove binding ligand in complex with DNA demonstrates that it can also be used in explicit solvent simulations.

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<![CDATA[Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication]]> https://www.researchpad.co/article/5989da09ab0ee8fa60b76e4a

Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design.

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<![CDATA[Effect of set up protocols on the accuracy of alchemical free energy calculation over a set of ACK1 inhibitors]]> https://www.researchpad.co/article/5c915fc1d5eed0c48420af01

Hit-to-lead virtual screening frequently relies on a cascade of computational methods that starts with rapid calculations applied to a large number of compounds and ends with more expensive computations restricted to a subset of compounds that passed initial filters. This work focuses on set up protocols for alchemical free energy (AFE) scoring in the context of a Docking–MM/PBSA–AFE cascade. A dataset of 15 congeneric inhibitors of the ACK1 protein was used to evaluate the performance of AFE set up protocols that varied in the steps taken to prepare input files (using previously docked and best scored poses, manual selection of poses, manual placement of binding site water molecules). The main finding is that use of knowledge derived from X-ray structures to model binding modes, together with the manual placement of a bridging water molecule, improves the R2 from 0.45 ± 0.06 to 0.76 ± 0.02 and decreases the mean unsigned error from 2.11 ± 0.08 to 1.24 ± 0.04 kcal mol-1. By contrast a brute force automated protocol that increased the sampling time ten-fold lead to little improvements in accuracy. Besides, it is shown that for the present dataset hysteresis can be used to flag poses that need further attention even without prior knowledge of experimental binding affinities.

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