Tools

    Brief summary of tools developed by us: 
    All tools are developed at SciWhyLab or by its members prior to setting up SciWhyLab.


    Highlight Tools: 

    GIGEASA: Gentle Integration of Gene Expression And Structural Attributes

    This tool gives Human, Mouse and Arabidopsis Thaliana predictions of DNA-binding proteins based on the integration of gene expression and sequence analysis 

    DynaSeq: Conformational dynamics (shape dynamics) dictionary for genome-wide applications

    This tool a large number of DNA sequence fragments (6 bases) and predicts a corresponding shape/ conformational ensemble described by 13 DNA conformational parameters such as Twist, Minor groove width, Slide, Roll etc. 


    Binding site prediction and interaction analysis tools:

    DBS-Pred: DNA binding site prediction from single sequences.

    This is our old legacy tool to predict DNA-binding sites from single sequences. For most purposes, we recommend use of SDCPred for the purpose.

    DBS-PSSM: DNA-binding site prediction from protein sequences.

    This tool predicts DNA-binding sites in proteins from protein by computing their PSSM first. 

    SDCPred: Dinucleotide specific binding site prediction from protein sequences.

    This tool predicts DNA-binding sites for each dinucleotide separately in proteins from protein by computing their PSSM first. 

    SRCPred: RNA-binding site prediction from protein sequences.

    This tool predicts dinucleotide specific RNA-binding sites in proteins from protein by computing their PSSM first. 

    PPiPP: Pair-wise Protein-protein binding site prediction from a pair of protein sequences.

    This tool predicts protein-protein binding sites by evaluating all possible residue pairs between two proteins. 

    CBS-Pred: Carbohydrate binding site prediction from protein sequences.

    This tool predicts carbohydrate binding sites in proteins, both from protein single sequences directly or by computing their PSSM. 

    GPolate: Predicts expected impact of mutation in protein-DNA complex.

    This tool estimates the average expected change upon point mutations in a protein-DNA complex. Mutated and wild type residue identity and secondary structures are the only inputs. 


    DNA shape or indirect readout prediction Tools:

    DynaSeq: Conformational dynamics (shape dynamics) dictionary for genome-wide applications

    This tool a large number of DNA sequence fragments (6 bases) and predicts a corresponding shape/ conformational ensemble described by 13 DNA conformational parameters such as Twist, Minor groove width, Slide, Roll etc. 

    ReadOut: Sequence and shape energy specificities from a base-amino acid and DNA shape perspective.

    This server computes sequence and DNA shape preferences of a DNA-binding protein using a given protein-DNA complex as a reference. Based on a statistical force field derived from known protein-DNA complexes. 



    Solvent accessibility and general structural analysis tools:

    ASAView: Computing normalized solvent accessibility and its graphical representation from protein structures.

    This server takes uploaded coordinates or a PDB identifier to compute and visualize relative solvent accessibility distribution in a protein. 

    HOA: Computing normalized solvent accessibility using context dependent reference states for normalizing.

    Standalone tools for normalization with highest observed ASA are provided. 

    NETASA Predicts solvent accessibility states (buried/exposed) for residues from a protein sequence.

    This is our legacy tool to predict ASA from sequence. The other tool on ASA prediction "RVP-Net" may be seen to supersede it. 

    RVP-Net Predicts relative solvent accessibility (analog values) for residues from a protein sequence.

    This tool is used for real-valued relative ASA prediction from sequence. Relative values are also converted to their two class values as buried/exposed. 

    CCRXP: Computing and visualizing clusters of conserved residues specially for DNA-binding proteins.

    Conserved residues occurring in clusters are computed and shown together with target DNA, where possible. Computation of packing density, ASA and other residue wise properties are also provided. 

    HTMOne: Prediction and analysis of several structural properties of transmembrane helical proteins.

    This tool uses either a helical membrane protein sequence or structure and predicts its multiple structural properties. For known structures, predicted data is compared with directly computed data to assess the divergence from expected values. 

    TMBetaNet: Predict TM regions in beta-barrel TM proteins.

    This tool predicts Transmembrane strands in beta barrel membrane proteins from sequence inputs. 

    © Prof Shandar Ahmad Research Group. | Developed by Sudhir Patwal