Biomolecules

It is well known that Drug Design is often a costly process both in terms of time and economic effort. While good Quantitative Structure-Activity Relationship models (QSAR) can help predicting molecular properties without the need to…

Drug development is time-consuming and expensive. Repurposing existing drugs for new therapies is an attractive solution that accelerates drug development at reduced experimental costs, specifically for Coronavirus Disease 2019 (COVID-19),…

The potential of virtual reality (VR) to contribute to drug design and development has been recognised for many years. Hardware and software developments now mean that this potential is beginning to be realised, and VR methods are being…

Monte Carlo (MC) methods are important computational tools for molecular structure optimizations and predictions. When solvent effects are explicitly considered, MC methods become very expensive due to the large degree of freedom associated…

Surface assays such as ELISA are pervasive in clinics and research and predominantly standardized in microtiter plates (MTP). MTPs provide many advantages but are often detrimental to surface assay efficiency due to inherent mass transport…

Background:Typically, proteins perform key biological functions by interacting with each other. As a consequence, predicting which protein pairs interact is a fundamental problem. Experimental methods are slow, expensive, and may be error…

Motivation: Predicting the drug-target interaction is crucial for drug discovery as well as drug repurposing. Machine learning is commonly used in drug-target affinity (DTA) problem. However, machine learning model faces the cold-start…

We investigate possible shapes of the electric field, which oscillating dipoles in a certain region of biological tissue can produce in a neighboring region, or outside the tissue boundaries. We find that a wide range of shapes, including…

When considering large sets of molecules, it is helpful to place them in the context of a "chemical space" - a multidimensional space defined by a set of descriptors that can be used to visualize and analyze compound grouping as well as…

Antibodies are versatile proteins that bind to pathogens like viruses and stimulate the adaptive immune system. The specificity of antibody binding is determined by complementarity-determining regions (CDRs) at the tips of these Y-shaped…

Post-translational modifications (PTMs) in proteins occur after the process of translation. PTMs account for many cellular processes such as deoxyribonucleic acid (DNA) repair, cell signaling and cell death. One of the recent PTMs is…

During their evolution, proteins explore sequence space via an interplay between random mutations and phenotypic selection. Here we build upon recent progress in reconstructing data-driven fitness landscapes for families of homologous…

The tetanus neurotoxin (TeNT) is one of the most toxic proteins known to man, which prior to the use of the vaccine against the TeNT producing bacteria Clostridium tetani, resulted in a 20 % mortality rate upon infection. The clinical…

Drug-target interaction (DTI) prediction plays a crucial role in drug discovery, and deep learning approaches have achieved state-of-the-art performance in this field. We introduce an ensemble of deep learning models (EnsembleDLM) for DTI…

Accurate knowledge of RNA hybridization is essential for understanding RNA structure and function. Here we mechanically unzip and rezip a 2-kbp RNA hairpin and derive the 10 nearest-neighbor base pair (NNBP) RNA free energies in sodium and…

The assembly of functional biomolecular condensates often involves liquid-liquid phase separation (LLPS) of proteins with multiple modular domains, which can be folded or conformationally disordered to various degrees. To understand the…

The estrogen receptor is a nuclear hormone receptor activated by the natural steroid hormone 17$\beta$-estradiol (E2). Fragment molecular orbital (FMO) calculations were performed which allowed us to obtain the interaction energy…

Liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is a major undergirding factor in the regulated formation of membraneless organelles in the cell. The phase behavior of an IDP is sensitive to its amino acid…

In this paper, we utilized generative models, and reformulate it for problems in molecular dynamics (MD) simulation, by introducing an MD potential energy component to our generative model. By incorporating potential energy as calculated…

Predicting a structure of an antibody from its sequence is important since it allows for a better design process of synthetic antibodies that play a vital role in the health industry. Most of the structure of an antibody is conservative.…