A Molecular Dynamics Simulation of the Human Lysozyme – Camelid VHH HL6 Antibody System

Amyloid diseases such as Alzheimer’s and thrombosis are characterized by an aberrant assembly of specific proteins or protein fragments into fibrils and plaques that are deposited in various tissues and organs. The single-domain fragment of a camelid antibody was reported to be able to combat against wild-type human lysozyme for inhibiting in-vitro aggregations of the amyloidogenic variant (D67H). The present study is aimed at elucidating the unbinding mechanics between the D67H lysozyme and VHH HL6 antibody fragment by using steered molecular dynamics (SMD) simulations on a nanosecond scale with different pulling velocities. The results of the simulation indicated that stretching forces of more than two nano Newton (nN) were required to dissociate the proteinantibody system, and the hydrogen bond dissociation pathways were computed

Gene Cloning, Characterization, and Molecular Simulations of a Novel Recombinant Chitinase from Chitinibacter Tainanensis CT01 Appropriate for Chitin Enzymatic Hydrolysis

Chitin, a polymer of N-acetyl-d-glucosamine (GlcNAc), can be degraded by chitinase, which is produced by higher plants, vertebrates, and bacteria. Chitinases are characterized by the ability to hydrolyze the beta-1,4-linkages in the chitin chain by either an endolytic or an exolytic mechanism. Chitinase 1198 is a novel endochitinase from the genome sequence of Chitinibacter tainanensis CT01. Herein, we report the findings of molecular simulations and bioassays for chitinase 1198. Our experimental results suggest that chitinase 1198 can recognize the nonreducing end of chitin and cleave the second or third glycosidic linkage from the nonreducing end of chitin oligomers. Furthermore, our simulations results revealed that chitinase 1198 is more likely to bind chitin oligomers with the main hydrogen bonds of the Asp440, the second GlcNAc unit of chitin oligomers, and degrade chitin oligomers to (GlcNAc)2 molecules. Moreover, chitinase 1198 is less likely to bind chitin oligomers with the main hydrogen bonds of the Asp440, the third GlcNAc unit of chitin oligomers, and degrade chitin oligomers to (GlcNAc)3 molecules. Lastly, chitinase 1198 can bind (GlcNAc)3 molecules with the main hydrogen bonds of the Asp440, the second GlcNAc of the (GlcNAc)3 molecules, and degrade chitin oligomers to GlcNAc and (GlcNAc)2 molecules

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes

Anti-TNF Alpha Antibody Humira with pH-dependent Binding Characteristics: A constant-pH Molecular Dynamics, Gaussian Accelerated Molecular Dynamics, and In Vitro Study

Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira–TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira–TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pKa of histidine side chains (6.0–6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design

An evaluation of multi-probe locality sensitive hashing for computing similarities over web-scale query logs

Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of complex objects. Due to the very large scale of data involved (e.g., users’ queries from commercial search engines), computing such near or nearest neighbors is a non-trivial task, as the computational cost grows significantly with the number of items. To address this challenge, we adopt Locality Sensitive Hashing (a.k.a, LSH) methods and evaluate four variants in a distributed computing environment (specifically, Hadoop). We identify several optimizations which improve performance, suitable for deployment in very large scale settings. The experimental results demonstrate our variants of LSH achieve the robust performance with better recall compared with “vanilla” LSH, even when using the same amount of space.Graham Cormode;Anirban Dasgupta;Amit Goyal;Chi Hoon Le