Conformational Sampling Method Research Articles

Assessing small molecule conformational sampling methods in molecular docking.

Small molecule conformational sampling plays a pivotal role in molecular docking. Recent advancements have led to the emergence of various conformational sampling methods, each employing distinct algorithms. This study investigates the impact of different small molecule conformational sampling methods in molecular docking using UCSF DOCK 3.7. Specifically, six traditional sampling methods (Omega, BCL::Conf, CCDC Conformer Generator, ConfGenX, Conformator, RDKit ETKDGv3) and a deep learning-based model (Torsional Diffusion) for generating conformational ensembles are evaluated. These ensembles are subsequently docked against the Platinum Diverse Dataset, the PoseBusters dataset and the DUDE-Z dataset to assess binding pose reproducibility and screening power. Notably, different sampling methods exhibit varying performance due to their unique preferences, such as dihedral angle sampling ranges on rotatable bonds. Combining complementary methods may lead to further improvements in docking performance.

Structural Basis for Voltage Gating and Dalfampridine Binding in the Shaker Potassium Channel.

The generation and propagation of action potentials in neurons depend on the coordinated activation of voltage-dependent sodium and potassium channels. Potassium channels of the Shaker family regulate neuronal excitability through voltage-dependent opening and closing of their ion conduction pore. This family of channels is an important therapeutic target, particularly in multiple sclerosis where the inhibitor dalfampridine (4-aminopyridine) is used to improve nerve conduction. The molecular details of how the voltage sensor domain drives opening of the pore domain has been limited by the lack of closed-state structures, also impairing the search for novel drugs. Using AlphaFold2-based conformational sampling methods we identify a structural model for the closed Shaker potassium channel where movement of the voltage sensor drives the opening trough interactions between the S4-S5 linker and S6 helix. We show experimentally that breakage of a backbone hydrogen bond is a critical part of the activation pathway. Through docking we identify a hydrophobic cavity formed by the pore domain helices that binds dalfampridine in the closed state. Our results demonstrate how voltage sensor movement drives pore opening and provide a structural framework for developing new therapeutic agents targeting the closed state. We anticipate this work will enable structure-based drug design efforts focused on state-dependent modulation of voltage-gated ion channels for the treatment of neurological disorders.

Identification of novel inhibitors targeting KRAS-SOS1 interactions by structure-based drug design.

The Kristen Rat Sarcoma (KRAS) protein, encoded by the KRAS gene, is a signal transducer that plays a crucial role in regulating cell proliferation. KRAS mutations have been known to cause lung, colorectal, and pancreatic cancers. Previously, KRAS was considered an "undruggable" target. However, with a better understanding of the protein's biology paired with advanced new technologies, the FDA approved the first KRAS inhibitor (sotorasib) for lung cancer patients with the KRASG12C mutation in 2021, expressing the recent interest of targeted drugs for KRAS. Oncogenic KRAS requires activation by the guanine nucleotide exchange factor (GEF) Son of Sevenless 1 (SOS1). The goal of this study is to develop novel pan-KRAS inhibitors by targeting the KRAS-SOS1 interactions through computational modeling. To start, we applied Gaussian accelerated molecular dynamics (GaMD) simulation, an advanced conformational sampling method, to collect the nature of the KRAS protein motion in solution. Then, the clustering analysis method was used to assemble KRAS conformational structures into ten groups. Finally, virtual screening and docking simulations are performed using the ChemBridge molecule database to identify potential KRAS inhibitors and their binding locations. We have addressed 60 compounds that show a good binding score to KRAS for a later experimental assessment of their (1) ability to disrupt the KRAS-SOS1 interactions and (2) cytotoxicity in KRAS mutation-bearing cell lines. The work provides insights into the drug efficacy of KRAS inhibitors and gives rise to a novel set of KRAS candidates to be used in oncogenic clinical treatments.

Molecular Simulation to Investigate Open-Close Motion of a Flagellar Export Apparatus Protein FlhAC.

Molecular dynamics (MD) simulation and parallel cascade selection molecular dynamics (PaCS-MD) are widely used to investigate large-amplitude motions of proteins. PaCS-MD is an enhanced conformational sampling method consisting of cycles of parallel unbiased MD simulations combined with a selection of MD snapshots as the initial structures for the next cycle. In addition, free energy calculation can be achieved by the combination of PaCS-MD and the Markov state model (MSM). In this chapter, the protocols to investigate the open-close motion of a flagellar export apparatus protein, FlhAC, by MD and the combination of PaCS-MD and MSM are described.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs.

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.

Accelerating optical reporting for conformation of tyrosine kinase inhibitors in solutions

AbstractThe present study has been developing a robust quantum mechanical (QM) conformational sampling method (PrefQMCon) for optical reporting of 4‐anilinoquinazoline derivatives based epidermal growth factor receptor (EGFR) tyrosine kinases inhibitors. We use AG‐1478 to demonstrate how PrefQMCon helps QM determination of 22 target drug conformer clusters and their properties and UV–vis spectra. In this method, the preferred conformers of AG‐1478 are obtained by density functional theory (DFT) optimization from conformational local minimum sampling around the identified rotatable bonds, followed by clustering analysis and time‐dependent (TD) DFT calculations for the UV–vis spectra in solvents. Such obtained preferred conformers agree well with earlier experimental measurements where the conformer dependent UV–Vis spectral shift of AG‐1478 is as large as ~15 nm. We are further developing this PrefQMCon to study and design other 4‐anilinoquinazoline derivatives of EGFR TKIs.

Titr-DMD-A Rapid, Coarse-Grained Quasi-All-Atom Constant pH Molecular Dynamics Framework.

The pH-dependence of enzyme fold stability and catalytic activity is a fundamentally dynamic, structural property which is difficult to study. The challenges and expense of investigating dynamic, atomic scale behavior experimentally means that computational methods, particularly constant pH molecular dynamics (CpHMD), are well situated tools for this. However, these methods often struggle with affordable sampling of sufficiently long time scales while also obtaining accurate pKa prediction and verifying the structures they generate. We introduce Titr-DMD, an affordable CpHMD method that combines the quasi-all-atom coarse-grained discrete molecular dynamics (DMD) method for conformational sampling with Propka for pKa prediction, to circumvent these issues. The combination enables rapid sampling on limited computational resources, while simulations are still performed on the atomic scale. We benchmark the method on a set of proteins with experimentally attested pKa and on the pH triggered conformational change in a staphylococcal nuclease mutant, a rare experimental study of such behavior. Our results show Titr-DMD to be an effective and inexpensive method to study pH-coupled protein dynamics.

Cell Permeability of Isomeric Macrocycles: Predictions and NMR Studies.

Conformation-dependent 3D descriptors have been shown to provide better predictions of the physicochemical properties of macrocycles than 2D descriptors. However, the computational identification of relevant conformations for macrocycles is nontrivial. Herein, we report that the Caco-2 cell permeability difference between a pair of diastereomeric macrocycles correlated with their solvent accessible 3D polar surface area and radius of gyration. The descriptors were calculated from the macrocycles’ solution-phase conformational ensembles and independently from ensembles obtained by conformational sampling. Calculation of the two descriptors for three other stereo- and regioisomeric macrocycles also allowed the correct ranking of their cell permeability. Methods for conformational sampling may thus allow ranking of passive permeability for moderately flexible macrocycles, thereby contributing to the prioritization of macrocycles for synthesis in lead optimization.

Difference of binding modes among three ligands to a receptor mSin3B corresponding to their inhibitory activities

A preceding experiment suggested that a compound, which inhibits binding of the REST/NRSF segment to the cleft of a receptor protein mSin3B, can be a potential drug candidate to ameliorate many neuropathies. We have recently developed an enhanced conformational sampling method, genetic-algorithm-guided multi-dimensional virtual-system-coupled canonical molecular dynamics, and in the present study, applied it to three systems consisting of mSin3B and one of three compounds, sertraline, YN3, and acitretin. Other preceding experiments showed that only sertraline inhibits the binding of REST/NRSF to mSin3B. The current simulation study produced the spatial distribution of the compounds around mSin3B, and showed that sertraline and YN3 bound to the cleft of mSin3B with a high propensity, although acitretin did not. Further analyses of the simulation data indicated that only the sertraline–mSin3B complex produced a hydrophobic core similar to that observed in the molecular interface of the REST/NRSF-mSin3B complex: An aromatic ring of sertraline sunk deeply in the mSin3B’s cleft forming a hydrophobic core contacting to hydrophobic amino-acid residues located at the bottom of the cleft. The present study proposes a step to design a compound that inhibits competitively the binding of a ligand to its receptor.

A Comprehensive Review of Predicting Method of RNA Tertiary Structure

In recent years, great progress has been made in the research of RNA function, and more and more RNA functions have been discovered. The function of RNA is highly dependent on its 3D structure, the RNA tertiary structure includes the RNA 3D structure and RNA tertiary interaction, so the RNA tertiary structure prediction has also attracted extensive attention. There are many RNA tertiary structure prediction algorithms. According to the traditional classification methods, the existing RNA tertiary structure prediction algorithms can be divided into two categories: the RNA tertiary structure prediction algorithm based on knowledge mining and the RNA tertiary structure prediction algorithm based on physics. On this basis, this paper further refines the RNA tertiary structure prediction algorithm based on physics in traditional classification, and proposes a new refinement classification method based on conformational sampling method, namely RNA tertiary structure prediction algorithm based on physical fragment assembly conformational sampling method and RNA tertiary structure prediction algorithm based on Stepwise ansatz conformational sampling method. We make a comparative analysis of RNA tertiary structure prediction algorithms, and put forward some suggestions for improving the energy function in the next step, in order to find an RNA tertiary structure prediction algorithm that can achieve atomic accuracy.

Model Lignin Oligomer Pyrolysis: Coupled Conformational and Thermodynamic Analysis of β-O-4′ Bond Cleavage

The abundance, carbon content, and functionalized nature of lignin make it a promising candidate for targeted valorization to fuels and polymer composites. While lignin modeling by the application of computational chemistry is an active area of research, electronic structure methods have been limited mainly to structures in the dimeric or trimeric range. In this study, we have modeled a lignin structure composed of 10 β-O-4′ linked guaiacyl (G) units, such that this work represents, to the best of our knowledge, the largest structure that has been examined to date using quantum mechanical calculations. As such, this work can provide information on a model, the size of which is more representative of the lignin polymer than has been previously reported. We have calculated bond dissociation enthalpy (BDE) for the homolytic cleavage reaction between each G unit in our model lignin oligomer, which occurs as one of the initial reactions during lignin pyrolysis. The objective of the current work was to determine how or if reactivity within the oligomer changes as a function of bond cleaving position within the chain. The methods used were classical molecular mechanics for conformational sampling and quantum mechanically based density functional theory (DFT) calculations. We have developed a novel and robust method for conformational sampling, which maps the conformational energy landscape efficiently and provides multiple low-energy structures that are then used to determine the BDE values by DFT. Our results for BDE calculations of lignin exhibit significant position dependence along the oligomer chain. To the best of our knowledge, we have reported for the first time the calculated standard thermodynamic properties including enthalpy of formation, heat capacity, entropy, and Gibbs free energy. Despite using a simplified model lignin oligomer structure, our calculated values for standard thermodynamic properties have a remarkable agreement with the experimental values.

Edge expansion parallel cascade selection molecular dynamics simulation for investigating large-amplitude collective motions of proteins.

We propose edge expansion parallel cascade selection molecular dynamics (eePaCS-MD) as an efficient adaptive conformational sampling method to investigate the large-amplitude motions of proteins without prior knowledge of the conformational transitions. In this method, multiple independent MD simulations are iteratively conducted from initial structures randomly selected from the vertices of a multi-dimensional principal component subspace. This subspace is defined by an ensemble of protein conformations sampled during previous cycles of eePaCS-MD. The edges and vertices of the conformational subspace are determined by solving the "convex hull problem." The sampling efficiency of eePaCS-MD is achieved by intensively repeating MD simulations from the vertex structures, which increases the probability of rare event occurrence to explore new large-amplitude collective motions. The conformational sampling efficiency of eePaCS-MD was assessed by investigating the open-close transitions of glutamine binding protein, maltose/maltodextrin binding protein, and adenylate kinase and comparing the results to those obtained using related methods. In all cases, the open-close transitions were simulated in ∼10 ns of simulation time or less, offering 1-3 orders of magnitude shorter simulation time compared to conventional MD. Furthermore, we show that the combination of eePaCS-MD and accelerated MD can further enhance conformational sampling efficiency, which reduced the total computational cost of observing the open-close transitions by at most 36%.

GA-guided mD-VcMD: A genetic-algorithm-guided method for multi-dimensional virtual-system coupled molecular dynamics

We introduced a conformational sampling method in an earlier report: The multi-dimensional virtual-system coupled molecular dynamics (mD-VcMD) enhances conformational sampling of a biomolecular system by computer simulations. Herein, new sampling method, a subzone-based mD-VcMD, is presented as an extension of mD-VcMD. Then, the subzone-based method is extended further using a genetic algorithm (GA) named the GA-guided mD-VcMD. In these methods, iterative simulation runs are performed to increase the sampled region gradually. The new methods have the following benefits: (1) They are free from a production run: i.e., all snapshots from all iterations are useful for analyses. (2) They are free from fine tuning of a weight function (probability distribution function or potential of mean force). (3) A canonical ensemble (i.e., a thermally equilibrated ensemble) is generated from a simple procedure. A thermodynamic weight is assigned to each snapshot. (4) Selective sampling can be performed for particularly addressing a poorly sampled region without breaking the proportion of the canonical ensemble if the poorly sampled conformational region emerges in sampling. By applying the methods to a simple system that involves an energy barrier between potential-energy minima, we demonstrated that the new methods have considerably higher sampling efficiency than the original mD-VcMD does.

Replica-Exchange Umbrella Sampling Combined with Gaussian Accelerated Molecular Dynamics for Free-Energy Calculation of Biomolecules.

We have developed an enhanced conformational sampling method combining replica-exchange umbrella sampling (REUS) with Gaussian accelerated molecular dynamics (GaMD). REUS enhances the sampling along predefined reaction coordinates, while GaMD accelerates the conformational dynamics by adding a boost potential to the system energy. The method, which we call GaREUS (Gaussian accelerated replica-exchange umbrella sampling), enhances the sampling more efficiently than REUS or GaMD, while the computational resource for GaREUS is the same as that required for REUS. The two-step reweighting procedure using the multistate Bennett acceptance ratio method and the cumulant expansion for the exponential average is applied to the simulation trajectories for obtaining the unbiased free-energy landscapes. We apply GaREUS to the calculations of free-energy landscapes for three different cases: conformational equilibria of N-glycan, folding of chignolin, and conformational change of adenyl kinase. We show that GaREUS speeds up the convergences of free-energy calculations using the same amount of computational resources as REUS. The free-energy landscapes reweighted from the trajectories of GaREUS agree with previously reported ones. GaREUS is applicable to free-energy calculations of various biomolecular dynamics and functions with reasonable computational costs.

Selection Rules for Outliers in Outlier Flooding Method Regulate Its Conformational Sampling Efficiency

The outlier flooding method (OFLOOD) has been proposed as an enhanced conformational sampling method of proteins. In OFLOOD, rarely occurring states of proteins are detected as sparse conformational distributions (outliers) with a clustering algorithm. The detected outliers are intensively resampled with short-time molecular dynamics (MD) simulations. As a set of cycles, OFLOOD repeats selections of outliers and their conformational resampling. Herein, as an essential issue to be tackled to perform OFLOOD efficiently, a selection rule for outliers should be carefully specified. Generally, many outliers are detected from distributions on conformational subspaces with the clustering. Judging from its computational costs, it is unreasonable to select all the detected outliers upon the conformational resampling. Therefore, it is important to consider which outliers should be selected from the sparse distributions when restarting their short-time MD simulations with limited computational costs. In this sense, we investigated the conformational sampling efficiency of OFLOOD by changing the selection rules for outliers. To address the conformational sampling efficiency of OFLOOD depending on its selection rules, outliers to be resampled were selected by focusing their probability occurrences (populations of outliers). As a comparison, a random selection rule for outliers was also considered. Through the present assessment, the random selection of outliers showed the most efficient conformational sampling efficiency compared to the other OFLOOD trials using the biased selection rules, indicating that a variety of outliers should be selected and resampled during the OFLOOD cycles. In conclusion, the random outlier selection rule is the best strategy to perform OFLOOD efficiently.

Nontargeted Parallel Cascade Selection Molecular Dynamics Using Time-Localized Prediction of Conformational Transitions in Protein Dynamics

Nontargeted parallel cascade selection molecular dynamics (nt-PaCS-MD) is an enhanced conformational sampling method of proteins, which does not rely on knowledge of the target structure. It makes use of cyclic resampling from some relevant initial structures to expand the searched conformational subspace. The efficiency of nt-PaCS-MD depends on the selections of these initial structures. They are usually stochastically occurring perturbed structures at which larger conformation transitions are about to happen. Reliable identification of these is the key to using nt-PaCS-MD. Two new parameters, the moving root-mean-square deviation (mRMSD) and the inner products of the backbone dihedral angles Φ and Ψ, are introduced as indicators of conformational outliers in MD trajectories. Both are based on the analysis of a time-localized set of coordinates, overcoming the need for a target structure while still capturing the complexity of the conformational transition. The reference to which the mRMSD relates is the close surrounding of the i-th conformation, often the (i-1)st one. Hence the name "time-localized" analysis. In this work, we focus on its interplay with nt-PaCS-MD and show that it increases its effectiveness compared to older versions. The target system is the midsized protein T4 lysozyme (in explicit water) on which we demonstrate the open-closed transition without referring to any target configuration. Additionally, we show that the short MD trajectories can be used for the construction of a free energy landscape of the conformational transition based on the Markov state model.

Development of Enhanced Conformational Sampling Methods for GPCRs

G protein‐coupled receptors (GPCRs) are known to possess multiple active conformational states in nature, however, studying these conformations is extremely challenging as majority of the functionally important conformations have high energy compared to the lowest energy conformation. We are developing a method called Enhanced Conformational Markov‐state Sampling in Membrane BiLayer Environment (EnCoMSeMBLE) that would enhance our search of the conformational landscape of GPCRs and that can be applied to a‐helical transmembrane proteins in general. It enables a level of conformational sampling not achievable by classical or accelerated molecular dynamics (MD) simulations or Markov‐State Models (MSM). This method combines brute force conformational sampling of helix‐helix interactions in the membrane with MD simulations and Markov‐State modeling to identify functionally important conformations. This method is being tested by application to the Glucagon Like peptide‐1 receptor (GLP1‐R), a class B GPCR, and the muscarinic acetylcholine M2 receptor, a class A GPCR, both of which have been crystallized in inactive as well as active conformations. The comparison of the activation landscapes of class A and class B GPCRs is beginning to provide key similarities and differences in activation across these very distinct GPCRs. This detailed understanding of the GPCR activation, enabled by our method, complements major structural biology efforts underway targeting GPCRs, where it is very challenging to map out the structural landscape and activation pathways of GPCRs.Support or Funding InformationBUILD PODER is supported through a grant from the National Institutes of General Medical Sciences (NIGMS), grants # # 8TL4GM11897This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Temperature-pressure shuffling outlier flooding method enhances the conformational sampling of proteins.

Outlier flooding method (OFLOOD) is an efficient conformational sampling method developed by the authors. In the present study, to further enhance the conformational sampling efficiency, a set of parameters (temperatures and pressures) specified as inputs in the original OFLOOD were shuffled before restarting the short-time molecular dynamics (MD) simulations. Because of the diversity of these parameters, it was confirmed that the extended OFLOOD becomes superior to the original one in finding the folding pathways of Trp-cage. © 2019 Wiley Periodicals, Inc.

Computational Structural Biology: Successes, Future Directions, and Challenges.

Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous ‘big data’ integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells’ actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions.

Protein structure predictions by enhanced conformational sampling methods.

In this Special Festschrift Issue for the celebration of Professor Nobuhiro Gō’s 80th birthday, we review enhanced conformational sampling methods for protein structure predictions. We present several generalized-ensemble algorithms such as multicanonical algorithm, replica-exchange method, etc. and parallel Monte Carlo or molecular dynamics method with genetic crossover. Examples of the results of these methods applied to the predictions of protein tertiary structures are also presented.