Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Bong Hyun Kim is active.

Publication


Featured researches published by Bong Hyun Kim.


Nucleic Acids Research | 2008

PROMALS3D: A tool for multiple protein sequence and structure alignments

Jimin Pei; Bong Hyun Kim; Nick V. Grishin

Although multiple sequence alignments (MSAs) are essential for a wide range of applications from structure modeling to prediction of functional sites, construction of accurate MSAs for distantly related proteins remains a largely unsolved problem. The rapidly increasing database of spatial structures is a valuable source to improve alignment quality. We explore the use of 3D structural information to guide sequence alignments constructed by our MSA program PROMALS. The resulting tool, PROMALS3D, automatically identifies homologs with known 3D structures for the input sequences, derives structural constraints through structure-based alignments and combines them with sequence constraints to construct consistency-based multiple sequence alignments. The output is a consensus alignment that brings together sequence and structural information about input proteins and their homologs. PROMALS3D can also align sequences of multiple input structures, with the output representing a multiple structure-based alignment refined in combination with sequence constraints. The advantage of PROMALS3D is that it gives researchers an easy way to produce high-quality alignments consistent with both sequences and structures of proteins. PROMALS3D outperforms a number of existing methods for constructing multiple sequence or structural alignments using both reference-dependent and reference-independent evaluation methods.


Proteins | 2009

Structure prediction for CASP8 with all-atom refinement using Rosetta

Srivatsan Raman; Robert B. Vernon; James Thompson; Michael D. Tyka; Ruslan I. Sadreyev; Jimin Pei; David E. Kim; Elizabeth H. Kellogg; Frank DiMaio; Oliver F. Lange; Lisa N. Kinch; Will Sheffler; Bong Hyun Kim; Rhiju Das; Nick V. Grishin; David Baker

We describe predictions made using the Rosetta structure prediction methodology for the Eighth Critical Assessment of Techniques for Protein Structure Prediction. Aggressive sampling and all‐atom refinement were carried out for nearly all targets. A combination of alignment methodologies was used to generate starting models from a range of templates, and the models were then subjected to Rosetta all atom refinement. For the 64 domains with readily identified templates, the best submitted model was better than the best alignment to the best template in the Protein Data Bank for 24 cases, and improved over the best starting model for 43 cases. For 13 targets where only very distant sequence relationships to proteins of known structure were detected, models were generated using the Rosetta de novo structure prediction methodology followed by all‐atom refinement; in several cases the submitted models were better than those based on the available templates. Of the 12 refinement challenges, the best submitted model improved on the starting model in seven cases. These improvements over the starting template‐based models and refinement tests demonstrate the power of Rosetta structure refinement in improving model accuracy. Proteins 2009.


PLOS Computational Biology | 2014

ECOD: an evolutionary classification of protein domains.

Hua Cheng; R. Dustin Schaeffer; Yuxing Liao; Lisa N. Kinch; Jimin Pei; Shuoyong Shi; Bong Hyun Kim; Nick V. Grishin

Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or “fold”). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.


Current Opinion in Structural Biology | 2009

Discrete-continuous duality of protein structure space

Ruslan I. Sadreyev; Bong Hyun Kim; Nick V. Grishin

Recently, the nature of protein structure space has been widely discussed in the literature. The traditional discrete view of protein universe as a set of separate folds has been criticized in the light of growing evidence that almost any arrangement of secondary structures is possible and the whole protein space can be traversed through a path of similar structures. Here we argue that the discrete and continuous descriptions are not mutually exclusive, but complementary: the space is largely discrete in evolutionary sense, but continuous geometrically when purely structural similarities are quantified. Evolutionary connections are mainly confined to separate structural prototypes corresponding to folds as islands of structural stability, with few remaining traceable links between the islands. However, for a geometric similarity measure, it is usually possible to find a reasonable cutoff that yields paths connecting any two structures through intermediates.


Molecular Endocrinology | 2009

Expression profiling of nuclear receptors in human and mouse embryonic stem cells

Chang Qing Xie; Yangsik Jeong; Mingui Fu; Angie L. Bookout; Minerva T. Garcia-Barrio; Tingwan Sun; Bong Hyun Kim; Yang Xie; Sierra Root; Jifeng Zhang; Ren-He Xu; Y. Eugene Chen; David J. Mangelsdorf

Nuclear receptors (NRs) regulate gene expression in essential biological processes including differentiation and development. Here we report the systematic profiling of NRs in human and mouse embryonic stem cell (ESC) lines and during their early differentiation into embryoid bodies. Expression of the 48 human and mouse NRs was assessed by quantitative real-time PCR. In general, expression of NRs between the two human cell lines was highly concordant, whereas in contrast, expression of NRs between human and mouse ESCs differed significantly. In particular, a number of NRs that have been implicated previously as crucial regulators of mouse ESC biology, including ERRbeta, DAX-1, and LRH-1, exhibited diametric patterns of expression, suggesting they may have distinct species-specific functions. Taken together, these results highlight the complexity of the transcriptional hierarchy that exists between species and governs early development. These data should provide a unique resource for further exploration of the species-specific roles of NRs in ESC self-renewal and differentiation.


Nucleic Acids Research | 2007

PROMALS web server for accurate multiple protein sequence alignments

Jimin Pei; Bong Hyun Kim; Ming Tang; Nick V. Grishin

Multiple sequence alignments are essential in homology inference, structure modeling, functional prediction and phylogenetic analysis. We developed a web server that constructs multiple protein sequence alignments using PROMALS, a progressive method that improves alignment quality by using additional homologs from PSI-BLAST searches and secondary structure predictions from PSIPRED. PROMALS shows higher alignment accuracy than other advanced methods, such as MUMMALS, ProbCons, MAFFT and SPEM. The PROMALS web server takes FASTA format protein sequences as input. The output includes a colored alignment augmented with information about sequence grouping, predicted secondary structures and positional conservation. The PROMALS web server is available at: http://prodata.swmed.edu/promals/


Database | 2009

Analysis of CASP8 targets, predictions and assessment methods

Shuoyong Shi; Jimin Pei; Ruslan I. Sadreyev; Lisa N. Kinch; Indraneel Majumdar; Jing Tong; Hua Cheng; Bong Hyun Kim; Nick V. Grishin

Results of the recent Critical Assessment of Techniques for Protein Structure Prediction, CASP8, present several valuable sources of information. First, CASP targets comprise a realistic sample of currently solved protein structures and exemplify the corresponding challenges for predictors. Second, the plethora of predictions by all possible methods provides an unusually rich material for evolutionary analysis of target proteins. Third, CASP results show the current state of the field and highlight specific problems in both predicting and assessing. Finally, these data can serve as grounds to develop and analyze methods for assessing prediction quality. Here we present results of our analysis in these areas. Our objective is not to duplicate CASP assessment, but to use our unique experience as former CASP5 assessors and CASP8 predictors to (i) offer more insights into CASP targets and predictions based on expert analysis, including invaluable analysis prior to target structure release; and (ii) develop an assessment methodology tailored towards current challenges in the field. Specifically, we discuss preparing target structures for assessment, parsing protein domains, balancing evaluations based on domains and on whole chains, dividing targets into categories and developing new evaluation scores. We also present evolutionary analysis of the most interesting and challenging targets. Database URL: Our results are available as a comprehensive database of targets and predictions at http://prodata.swmed.edu/CASP8.


Nucleic Acids Research | 2007

COMPASS server for remote homology inference

Ruslan I. Sadreyev; Ming Tang; Bong Hyun Kim; Nick V. Grishin

COMPASS is a method for homology detection and local alignment construction based on the comparison of multiple sequence alignments (MSAs). The method derives numerical profiles from given MSAs, constructs local profile-profile alignments and analytically estimates E-values for the detected similarities. Until now, COMPASS was only available for download and local installation. Here, we present a new web server featuring the latest version of COMPASS, which provides (i) increased sensitivity and selectivity of homology detection; (ii) longer, more complete alignments; and (iii) faster computational speed. After submission of the query MSA or single sequence, the server performs searches versus a user-specified database. The server includes detailed and intuitive control of the search parameters. A flexible output format, structured similarly to BLAST and PSI-BLAST, provides an easy way to read and analyze the detected profile similarities. Brief help sections are available for all input parameters and output options, along with detailed documentation. To illustrate the value of this tool for protein structure-functional prediction, we present two examples of detecting distant homologs for uncharacterized protein families. Available at http://prodata.swmed.edu/compass


Nucleic Acids Research | 2009

COMPASS server for homology detection: improved statistical accuracy, speed and functionality

Ruslan I. Sadreyev; Ming Tang; Bong Hyun Kim; Nick V. Grishin

COMPASS is a profile-based method for the detection of remote sequence similarity and the prediction of protein structure. Here we describe a recently improved public web server of COMPASS, http://prodata.swmed.edu/compass. The server features three major developments: (i) improved statistical accuracy; (ii) increased speed from parallel implementation; and (iii) new functional features facilitating structure prediction. These features include visualization tools that allow the user to quickly and effectively analyze specific local structural region predictions suggested by COMPASS alignments. As an application example, we describe the structural, evolutionary and functional analysis of a protein with unknown function that served as a target in the recent CASP8 (Critical Assessment of Techniques for Protein Structure Prediction round 8). URL: http://prodata.swmed.edu/compass


Nucleic Acids Research | 2007

MALISAM: a database of structurally analogous motifs in proteins

Hua Cheng; Bong Hyun Kim; Nick V. Grishin

MALISAM (manual alignments for structurally analogous motifs) represents the first database containing pairs of structural analogs and their alignments. To find reliable analogs, we developed an approach based on three ideas. First, an insertion together with a part of the evolutionary core of one domain family (a hybrid motif) is analogous to a similar motif contained within the core of another domain family. Second, a motif at an interface, formed by secondary structural elements (SSEs) contributed by two or more domains or subunits contacting along that interface, is analogous to a similar motif present in the core of a single domain. Third, an artificial protein obtained through selection from random peptides or in sequence design experiments not biased by sequences of a particular homologous family, is analogous to a structurally similar natural protein. Each analogous pair is superimposed and aligned manually, as well as by several commonly used programs. Applications of this database may range from protein evolution studies, e.g. development of remote homology inference tools and discriminators between homologs and analogs, to protein-folding research, since in the absence of evolutionary reasons, similarity between proteins is caused by structural and folding constraints. The database is publicly available at http://prodata.swmed.edu/malisam.

Collaboration


Dive into the Bong Hyun Kim's collaboration.

Top Co-Authors

Avatar

Nick V. Grishin

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar

Hua Cheng

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Jimin Pei

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar

Lisa N. Kinch

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar

Ming Tang

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar

Qian Cong

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar

Shuoyong Shi

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar

Angie L. Bookout

University of Texas Southwestern Medical Center

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge