CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed.

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published.

Systematic Assessment of Deep Learning-Based Predictors of Fragmentation Intensity Profiles.

In recent years, several deep learning-based methods have been proposed for predicting peptide fragment intensities. This study aims to provide a comprehensive assessment of six such methods, namely Prosit, DeepMass:Prism, pDeep3, AlphaPeptDeep, Prosit Transformer, and the method proposed by Guan et al. To this end, we evaluated the accuracy of the predicted intensity profiles for close to 1.

A Simple Method for Robust and Accurate Intrinsic Subtyping of Breast Cancer.

Motivation: The PAM50 signature/method is widely used for intrinsic subtyping of breast cancer samples. However, depending on the number and composition of the samples included in a cohort, the method may assign different subtypes to the same sample. This lack of robustness is mainly due to the fact that PAM50 subtracts a reference profile, which is computed using all samples in the cohort, from each sample before classification.

An 8-Gene Signature for Classifying Major Subtypes of Non-Small-Cell Lung Cancer.

Motivation: The precise diagnosis of the major subtypes, lung adenocarcinoma and lung squamous cell carcinoma, of non-small-cell lung cancer is of practical importance as some treatments are subtype-specific. However, in some cases diagnosis via the commonly-used method, that is staining the specimen using immunohistochemical markers, may be challenging. Hence, having a computational method that complements the diagnosis is desirable.

Exploring induced pluripotency in human fibroblasts via construction, validation, and application of a gene regulatory network.

Reprogramming of somatic cells to induced pluripotent stem cells, by overexpressing certain factors referred to as the reprogramming factors, can revolutionize regenerative medicine. To provide a coherent description of induced pluripotency from the gene regulation perspective, we use 35 microarray datasets to construct a reprogramming gene regulatory network. Comprising 276 nodes and 4471 links, the resulting network is, to the best of our knowledge, the largest gene regulatory network constructed for human fibroblast reprogramming and it is the only one built using a large number of experimental datasets.

Ultra-High-Frequency Reprogramming of Individual Long-Term Hematopoietic Stem Cells Yields Low Somatic Variant Induced Pluripotent Stem Cells.

Efficiency of reprogramming of human cells into induced pluripotent stem cells (iPSCs) has remained low. We report that individual adult human CD49f long-term hematopoietic stem cells (LT-HSCs) can be reprogrammed into iPSCs at close to 50% efficiency using Sendai virus transduction. This exquisite sensitivity to reprogramming is specific to LT-HSCs, since it progressively decreases in committed progenitors.

Mechanism-based disease similarity.

In recent years several methods have been proposed to assign pairwise mechanism- based similarity scores to human diseases. Despite their differences in approach and performance, these methods work in a somewhat similar manner: first a set of biomolecules (genes, proteins, chemicals, etc.) is associated with each disease, and then a measure is defined to calculate the similarity between the sets assigned to a pair of diseases.

Analytical solution and scaling of fluctuations in complex networks traversed by damped, interacting random walkers.

A general model for random walks (RWs) on networks is proposed. It incorporates damping and time-dependent links, and it includes standard (undamped, noninteracting) RWs (SRWs), coalescing RWs, and coalescing-branching RWs as special cases. The exact, time-dependent solutions for the average numbers of visits (w) to nodes and their fluctuations (σ2) are given, and the long-term σ-w relation is studied.

DeCoaD: determining correlations among diseases using protein interaction networks.

Background: Disease-disease similarities can be investigated from multiple perspectives. Identifying similar diseases based on the underlying biomolecular interactions can be especially useful, because it may shed light on the common causes of the diseases and therefore may provide clues for possible treatments. Here we introduce DeCoaD, a web-based program that uses a novel method to assign pair-wise similarity scores, called correlations, to genetic diseases.

Relating diseases by integrating gene associations and information flow through protein interaction network.

Identifying similar diseases could potentially provide deeper understanding of their underlying causes, and may even hint at possible treatments. For this purpose, it is necessary to have a similarity measure that reflects the underpinning molecular interactions and biological pathways. We have thus devised a network-based measure that can partially fulfill this goal.

A method for the inclusion of sphenoidal electrodes in realistic EEG source imaging.

Although EEG source imaging (ESI) has become more popular over the last few years, sphenoidal electrodes (SPE) have never been incorporated in ESI using realistic head models. This is in part because of the true locations of these electrodes are not exactly known. In this study, we demonstrate the feasibility of determining the true locations of SPE and incorporating this information into realistic ESI.

Automated removal of EKG artifact from EEG data using independent component analysis and continuous wavelet transformation.

The electrical potential produced by the cardiac activity sometimes contaminates electroencephalogram (EEG) recordings, resulting in spiky activities that are referred to as electrocardiographic (EKG) artifact. For a variety of reasons it is often desirable to automatically detect and remove these artifacts. Especially, for accurate source localization of epileptic spikes in an EEG recording from a patient with epilepsy, it is of great importance to remove any concurrent artifact.

EEG source imaging in epilepsy--practicalities and pitfalls.

EEG source imaging (ESI) is a model-based imaging technique that integrates temporal and spatial components of EEG to identify the generating source of electrical potentials recorded on the scalp. Recent advances in computer technologies have made the analysis of ESI data less time-consuming, and have rekindled interest in this technique as a clinical diagnostic tool. On the basis of the available body of evidence, ESI seems to be a promising tool for epilepsy evaluation; however, the precise clinical value of ESI in presurgical evaluation of epilepsy and in localization of eloquent cortex remains to be investigated.

Sphenoidal electrodes significantly change the results of source localization of interictal spikes for a large percentage of patients with temporal lobe epilepsy.

Although scalp EEG is a very useful tool for presurgical evaluation in epilepsy, the 10-20 system of electrodes in many cases fails to accurately localize the source of the epileptic seizures. One suggested solution to this problem is to use additional electrodes. Sphenoidal electrodes especially have been suggested to be helpful in identifying the irritative and seizure onset zones in patients with temporal lobe epilepsy.

A direct coupling between global and internal motions in a single domain protein? MD investigation of extreme scenarios.

Proteins are not rigid molecules, but exhibit internal motions on timescales ranging from femto- to milliseconds and beyond. In solution, proteins also experience global translational and rotational motions, sometimes on timescales comparable to those of the internal fluctuations. The possibility that internal and global motions may be directly coupled has intriguing implications, given that enzymes and cell signaling proteins typically associate with binding partners and cellular scaffolds.

Structure and function of the intracellular region of the plexin-b1 transmembrane receptor.

Members of the plexin family are unique transmembrane receptors in that they interact directly with Rho family small GTPases; moreover, they contain a GTPase-activating protein (GAP) domain for R-Ras, which is crucial for plexin-mediated regulation of cell motility. However, the functional role and structural basis of the interactions between the different intracellular domains of plexins remained unclear. Here we present the 2.

Refinement of the primary hydration shell model for molecular dynamics simulations of large proteins.

A realistic representation of water molecules is important in molecular dynamics simulation of proteins. However, the standard method of solvating biomolecules, that is, immersing them in a box of water with periodic boundary conditions, is computationally expensive. The primary hydration shell (PHS) method, developed more than a decade ago and implemented in CHARMM, uses only a thin shell of water around the system of interest, and so greatly reduces the computational cost of simulations.

Tripping a switch: PDZRhoGEF rgRGS-bound Galpha13.

Ras superfamily guanine nucleotide-binding proteins, such as G-proteins and small GTPases, are a paradigm for two-state molecular switches in cell signaling. Recent experimental and theoretical studies question this simple model. Now Chen et al.

Insights into oncogenic mutations of plexin-B1 based on the solution structure of the Rho GTPase binding domain.

The plexin family of transmembrane receptors are important for axon guidance, angiogenesis, but also in cancer. Recently, plexin-B1 somatic missense mutations were found in both primary tumors and metastases of breast and prostate cancers, with several mutations mapping to the Rho GTPase binding domain (RBD) in the cytoplasmic region of the receptor. Here we present the NMR solution structure of this domain, confirming that the protein has both a ubiquitin-like fold and surface features.

Acceptable protein and solvent behavior in primary hydration shell simulations of hen lysozyme.

The "primary hydration shell" method in molecular dynamics simulations uses a two- to three-layer thick shell of explicitly represented water molecules as the solvent around the protein of interest. We show that despite its simplicity, this computationally cheap model is capable of predicting acceptable water and protein behavior using the CHARMM22/CMAP potential function. For protein dynamics, comparisons are made with Lipari-Szabo order parameters.