A Phenomenological Model for Predicting Melting Temperatures of DNA Sequences

We report here a novel method for predicting melting temperatures of DNA sequences based on a molecular-level hypothesis on the phenomena underlying the thermal denaturation of DNA. The model presented here attempts to quantify the energetic components stabilizing the structure of DNA such as base pairing, stacking, and ionic environment which are partially disrupted during the process of thermal denaturation. The model gives a Pearson product-moment correlation coefficient (r) of ∼0.98 between experimental and predicted melting temperatures for over 300 sequences of varying lengths ranging from 15-mers to genomic level and at different salt concentrations. The approach is implemented as a web tool (www.scfbio-iitd.res.in/chemgenome/Tm_predictor.jsp) for the prediction of melting temperatures of DNA sequences

Mechanisms of Loss of Functions of Human Angiogenin Variants Implicated in Amyotrophic Lateral Sclerosis

Background: Mutations in the coding region of angiogenin (ANG) gene have been found in patients suffering from Amyotrophic Lateral Sclerosis (ALS). Neurodegeneration results from the loss of angiogenic ability of ANG (protein coded by ANG). In this work, we performed extensive molecular dynamics (MD) simulations of wild-type ANG and disease associated ANG variants to elucidate the mechanism behind the loss of ribonucleolytic activity and nuclear translocation activity, functions needed for angiogenesis. Methodology/Principal Findings: MD simulations were carried out to study the structural and dynamic differences in the catalytic site and nuclear localization signal residues between WT-ANG (Wild-type ANG) and six mutants. Variants K17I, S28N, P112L and V113I have confirmed association with ALS, while T195C and A238G single nucleotide polymorphisms (SNPs) encoding L35P and K60E mutants respectively, have not been associated with ALS. Our results show that loss of ribonucleolytic activity in K17I is caused by conformational switching of the catalytic residue His114 by 99u. The loss of nuclear translocation activity of S28N and P112L is caused by changes in the folding of the residues 31 RRR 33 that result in the reduction in solvent accessible surface area (SASA). Consequently, we predict that V113I will exhibit loss of angiogenic properties by loss of nuclear translocation activity and L35P by loss of both ribonucleolytic activity and nuclear translocation activity. No functional loss was inferred for K60E. The MD simulation results were supported by hydrogen bond interactio

RASPD+: Fast Protein-Ligand Binding Free Energy Prediction Using Simplified Physicochemical Features

The virtual screening of large numbers of compounds against target protein binding sites has become an integral component of drug discovery workflows. This screening is often done by computationally docking ligands into a protein binding site of interest, but this has the drawback that a large number of poses must be evaluated to obtain accurate estimates of protein-ligand binding affinity. We here introduce a fast prefiltering method for ligand prioritization that is based on a set of machine learning models and uses simple pose-invariant physicochemical descriptors of the ligands and the protein binding pocket. Our method, Rapid Screening with Physicochemical Descriptors + machine learning (RASPD+), is trained on PDBbind data and achieves a regression performance better than for the original RASPD method and comparable to traditional scoring functions on a range of different test sets without the need for generating ligand poses. Additionally, we use RASPD+ to identify molecular features important for binding affinity and assess the ability of RASPD+ to enrich active molecules from decoys

Hydrogen bond interaction network for L35P mutant.

<p>The hydrogen bond interactions between contiguous amino acid residues based on a 3.2 Å cut-off has been presented here. The paths leading from the site of mutation Pro35 to catalytic residue His114 have been shown in blue square boxes. Other hydrogen bond interactions are shown in grey circles. The bond length is given on the edge between the nodes of amino acid residues. One of the path is mediating through Leu115 which plays a role in His114 conformational switching and the other path is mediating through Thr44 similar to that of WT-ANG.</p

Percentage hydrogen bonding occupancy between Thr44-Thr80 and Asp116-Ser118.

<p>Percentage hydrogen bonding occupancy between Thr44-Thr80 and Asp116-Ser118.</p

Comparison of AutoDock and ParDOCK binding energy scores for NCI-65828 complexes with WT-ANG and ANG mutants.

<p>*(ANG in which there is no conformational change of the catalytic residue His114).</p

Changes in folding of residues ³¹RRR³³ for WT-ANG, S28N and L35P mutants.

<p>Comparison of the changes in the folding of the residues R31, R32 and R33 at initial condition and at 50 ns of simulation. The residues are in open conformation for WT-ANG throughout the duration of simulation. For S28N and L35P mutants, a closed conformation is dominant. Figure produced using PyMOL <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032479#pone.0032479-DeLano1" target="_blank">[53]</a>.</p

Conformational switching of catalytic residue His114 in K17I and L35P mutants.

<p>Orientation of the catalytic triad residue His114 at a regular interval of 10 ns during the MD simulations of K17I and L35P mutants. In these figures, T = 0 ns is the start of production phase post-equilibration. Figure produced using PyMOL <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032479#pone.0032479-DeLano1" target="_blank">[53]</a>.</p

Hydrogen bond interaction network for WT-ANG.

<p>The hydrogen bond interactions between contiguous amino acid residues based on a 3.2 Å cut-off has been presented here. All hydrogen bond interaction paths up to catalytic residue His114 have been compared with the hydrogen bond interaction paths of other mutants. These hydrogen bond interactions are shown in blue square boxes. Other hydrogen bond interactions are shown in grey circles. The starting residues through which these paths led to His114 are shown in pink square boxes. The bond length is given on the edge between the nodes of amino acid residues. All the hydrogen bond interaction paths are mediating through Thr44 and there is no conformational switching of His114.</p

Residues interacting through hydrogen bonds from the site of mutation to His114 in K17I variant.

<p>Amino acid residues of K17I variant through which hydrogen bonds exert influence from the site of mutation on the catalytic site His114. The ribbon representation shows the shortest path traced by the contiguous amino acid sequence Ile17-Asp15-Ile46-His13-Leu115-Gln117-Asp116-His114-Ala106-Val113 and the hydrogen bond interactions. Residues have been shown in stick model in marine blue color. Catalytic triad residues have been shown as stick model and represented in green color. Hydrogen bonds between residues have been shown in red dashed-lines. Figure produced using PyMOL <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032479#pone.0032479-DeLano1" target="_blank">[53]</a>.</p