Hongxing Lei

Folding free-energy landscape of villin headpiece subdomain from molecular dynamics simulations

High-accuracy ab initio folding has remained an elusive objective despite decades of effort. To explore the folding landscape of villin headpiece subdomain HP35, we conducted two sets of replica exchange molecular dynamics for 200 ns each and three sets of conventional microsecond-long molecular dynamics simulations, using AMBER FF03 force field and a generalized-Born solvation model. The protein folded consistently to the native state; the lowest Cα-rmsd from the x-ray structure was 0.46 Å, and the Cα- rmsd of the center of the most populated cluster was 1.78 Å at 300 K. ab initio simulations have previously not reached this level. The folding landscape of HP35 can be partitioned into the native, denatured, and two intermediate-state regions. The native state is separated from the major folding intermediate state by a small barrier, whereas a large barrier exists between the major folding intermediate and the denatured states. The melting temperature Tm = 339 K extracted from the heat-capacity profile was in close agreement with the experimentally derived Tm = 342 K. A comprehensive picture of the kinetics and thermodynamics of HP35 folding emerges when the results from replica exchange and conventional molecular dynamics simulations are combined.

Strike a Balance: Optimization of Backbone Torsion Parameters of AMBER Polarizable Force Field for Simulations of Proteins and Peptides

Based on the AMBER polarizable model (ff02), we have reoptimized the parameters related to the main‐chain (Φ, Ψ) torsion angles by fitting to the Boltzmann‐weighted average quantum mechanical (QM) energies of the important regions (i.e., β, PII, αR, and αL regions). Following the naming convention of the AMBER force field series, this release will be called ff02pol.rl The force field has been assessed both by energetic comparison against the QM data and by the replica exchange molecular dynamics simulations of short alanine peptides in water. For Ace‐Ala‐Nme, the simulated populations in the β, PII and αR regions were approximately 30, 43, and 26%, respectively. For Ace‐(Ala)7‐Nme, the populations in these three regions were approximately 24, 49, and 26%. Both were in qualitative agreement with the NMR and CD experimental conclusions. In comparison with the previous force field, ff02pol.rl demonstrated good balance among these three important regions. The optimized torsion parameters, together with those in ff02, allow us to carry out simulations on proteins and peptides with the consideration of polarization.

Development of Polarizable Models for Molecular Mechanical Calculations II: Induced Dipole Models Significantly Improve Accuracy of Intermolecular Interaction Energies

In the companion paper, we presented a set of induced dipole interaction models using four types of screening functions, which include the Applequist (no screening), the Thole linear, the Thole exponential model, and the Thole Tinker-like (another form of exponential screening function) functions. In this work, we evaluate the performance of polarizability models using a large set of amino acid analog pairs in conformations that are frequently observed in protein structures as a benchmark. For each amino acid pair, we calculated quantum mechanical interaction energies at the MP2/aug-cc-pVTZ//MP2/6-311++G(d,p) level with the basis set superposition error (BSSE) correction and compared them with molecular mechanics results. Encouragingly, all polarizable models significantly outperform the additive F94 and F03 models (mimicking AMBER ff94/ff99 and ff03 force fields, respectively) in reproducing the BSSE-corrected quantum mechanical interaction energies. In particular, the root-mean-square errors (RMSEs) for three Thole models in Set A (where the 1-2 and 1-3 interactions are turned off and all 1-4 interactions are included) are 1.456, 1.417, and 1.406 kcal/mol for model AL (Thole Linear), model AE (Thole exponential), and model AT (Thole Tinker-like), respectively. In contrast, the RMSEs are 3.729 and 3.433 kcal/mol for F94 and F03 models, respectively. A similar trend was observed for the average unsigned errors (AUEs), which are 1.057, 1.025, 1.011, 2.219, and 2.070 kcal/mol for AL, AE, AT, F94/ff99, and F03, respectively. Analyses based on the trend line slopes indicate that the two fixed charge models substantially underestimate the relative strengths of noncharge-charge interactions by 24 (F03) and 35% (F94), respectively, whereas the four polarizable models overestimate the relative strengths by 5 (AT), 3 (AL, AE), and 13% (AA), respectively. Agreement was further improved by adjusting the van der Waals parameters. Judging from the notably improved accuracy in comparison with the fixed charge models, the polarizable models are expected to form the foundation for the development of high quality polarizable force fields for protein and nucleic acid simulations.

Concerted perturbation observed in a hub network in Alzheimer's disease.

Alzheimer’s disease (AD) is a progressive neurodegenerative disease involving the alteration of gene expression at the whole genome level. Genome-wide transcriptional profiling of AD has been conducted by many groups on several relevant brain regions. However, identifying the most critical dys-regulated genes has been challenging. In this work, we addressed this issue by deriving critical genes from perturbed subnetworks. Using a recent microarray dataset on six brain regions, we applied a heaviest induced subgraph algorithm with a modular scoring function to reveal the significantly perturbed subnetwork in each brain region. These perturbed subnetworks were found to be significantly overlapped with each other. Furthermore, the hub genes from these perturbed subnetworks formed a connected hub network consisting of 136 genes. Comparison between AD and several related diseases demonstrated that the hub network was robustly and specifically perturbed in AD. In addition, strong correlation between the expression level of these hub genes and indicators of AD severity suggested that this hub network can partially reflect AD progression. More importantly, this hub network reflected the adaptation of neurons to the AD-specific microenvironment through a variety of adjustments, including reduction of neuronal and synaptic activities and alteration of survival signaling. Therefore, it is potentially useful for the development of biomarkers and network medicine for AD.

GSA: Genome Sequence Archive*

With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for managing huge sequence data, here we present Genome Sequence Archive (GSA; http://bigd.big.ac.cn/gsa or http://gsa.big.ac.cn), a data repository for archiving raw sequence data. In compliance with data standards and structures of the International Nucleotide Sequence Database Collaboration (INSDC), GSA adopts four data objects (BioProject, BioSample, Experiment, and Run) for data organization, accepts raw sequence reads produced by a variety of sequencing platforms, stores both sequence reads and metadata submitted from all over the world, and makes all these data publicly available to worldwide scientific communities. In the era of big data, GSA is not only an important complement to existing INSDC members by alleviating the increasing burdens of handling sequence data deluge, but also takes the significant responsibility for global big data archive and provides free unrestricted access to all publicly available data in support of research activities throughout the world.

Down-Regulation of Energy Metabolism in Alzheimer's Disease is a Protective Response of Neurons to the Microenvironment

A central issue in the field of Alzheimers disease (AD) is to separate the cause from the consequence among many observed pathological features, which may be resolved by studying the time evolution of these features at distinctive stages. In this work, comprehensive analyses on transcriptome studies of human postmortem brain tissues from AD patients at distinctive stages revealed stepwise breakdown of the cellular machinery during the progression of AD. At the early stage of AD, the accumulation of amyloid-β oligomers and amyloid plaques leads to the down-regulation of biosynthesis and energy metabolism. At the intermediate stage, the progression of the disease leads to enhanced signal transduction, while the late stage is characterized by elevated apoptosis. The down-regulation of energy metabolism in AD has been considered by many as a consequence of mitochondrion damage due to oxidative stress. However, the non-existence of enhanced response to oxidative stress and the revelation of intriguing down-regulation patterns of the electron-transport chain at different stages suggest otherwise. In contrast to the damage-themed hypothesis, we propose that the down-regulation of energy metabolism in AD is a protective response of the neurons to the reduced level of nutrient and oxygen supply in the microenvironment. The elevated apoptosis at the late stage of AD is triggered by the conflict between the low level of energy metabolism and high level of regulatory and repair burden. This new hypothesis has significant implication for pharmaceutical intervention of Alzheimers disease.

Folding processes of the B domain of protein A to the native state observed in all-atom ab initio folding simulations.

Reaching the native states of small proteins, a necessary step towards a comprehensive understanding of the folding mechanisms, has remained a tremendous challenge to ab initio protein folding simulations despite the extensive effort. In this work, the folding process of the B domain of protein A (BdpA) has been simulated by both conventional and replica exchange molecular dynamics using AMBER FF03 all-atom force field. Started from an extended chain, a total of 40 conventional (each to 1.0 micros) and two sets of replica exchange (each to 200.0 ns per replica) molecular dynamics simulations were performed with different generalized-Born solvation models and temperature control schemes. The improvements in both the force field and solvent model allowed successful simulations of the folding process to the native state as demonstrated by the 0.80 A C(alpha) root mean square deviation (RMSD) of the best folded structure. The most populated conformation was the native folded structure with a high population. This was a significant improvement over the 2.8 A C(alpha) RMSD of the best nativelike structures from previous ab initio folding studies on BdpA. To the best of our knowledge, our results demonstrate, for the first time, that ab initio simulations can reach the native state of BdpA. Consistent with experimental observations, including Phi-value analyses, formation of helix II/III hairpin was a crucial step that provides a template upon which helix I could form and the folding process could complete. Early formation of helix III was observed which is consistent with the experimental results of higher residual helical content of isolated helix III among the three helices. The calculated temperature-dependent profile and the melting temperature were in close agreement with the experimental results. The simulations further revealed that phenylalanine 31 may play critical to achieve the correct packing of the three helices which is consistent with the experimental observation. In addition to the mechanistic studies, an ab initio structure prediction was also conducted based on both the physical energy and a statistical potential. Based on the lowest physical energy, the predicted structure was 2.0 A C(alpha) RMSD away from the experimentally determined structure.

Early stage intercalation of doxorubicin to DNA fragments observed in molecular dynamics binding simulations

The intercalation mode between doxorubicin (an anticancer drug) and two 6-base-pair DNA model fragments (d(CGATCG)₂ and d(CGTACG)₂) has been well studied by X-ray crystallography and NMR experimental methods. Yet, the detailed intercalation pathway at molecular level remains elusive. In this study, we conducted molecular dynamics binding simulations of these two systems using AMBER DNA (parmbsc0) and drug (GAFF) force fields starting from the unbound state. We observed outside binding (minor groove binding or end-binding) in all six independent binding simulations (three for each DNA fragment), followed by the complete intercalation of a drug molecule in two simulations (one for each DNA fragment). First, our data directly supported that the minor groove binding is the dominant pre-intercalation step. Second, we observed that the opening and flipping of a local base pair (A3-T10 for d(CGATCG)₂ and C1-G12 for d(CGTACG)₂) in the two intercalation trajectories. This locally cooperative flipping-intercalation mechanism was different from the previously proposed rise-insertion mechanism by which the distance between two neighboring intact base pairs increases to create a space for the drug insertion. Third, our simulations provided the first set of data to support the applicability of the AMBER DNA and drug force fields in drug-DNA atomistic binding simulations. Implications on the kinetics pathway and drug action are also discussed.

Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward.

Characteristic Transformation of Blood Transcriptome in Alzheimer's Disease

Blood transcriptome has emerged as a potential resource for the discovery of biomarkers for Alzheimers disease (AD). However, the validity of blood transcriptome in the early diagnosis of AD has yet to be extensively tested. In this work, we analyzed published data on AD blood transcriptome and revealed the characteristic perturbation of cellular functional units, including upregulation of environmental responses (immune response, survival/death signaling, and cellular recycling) and down-regulation of core metabolism (energy metabolism and translation/splicing). This characteristic perturbation was unique to AD based on the comparison with blood transcriptome from other neurological disorders and complex diseases. More importantly, similar perturbation was observed in both AD and mild cognitive impairment (MCI) groups. This perturbation pattern was further validated in our independent microarray experiment in a small Chinese cohort. In addition, the potential effect of aging and lifestyle on blood transcriptome was discussed. Based on the analyses, we propose that the transformation of the blood transcriptome in AD is an integrated part of the disease mechanism and has potential to serve as a reliable biomarker for assisting the early diagnosis as well as monitoring purpose. Therefore, more independent studies on blood transcriptome of AD and MCI with larger sample size are warranted.