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Search · four archives
16 papers · ranked by Valyu relevance
Authors not listed
The Protein Data Bank (PDB) is one of the richest open‑source repositories in biology, housing over 277,000 macromolecular structural models alongside much of the experimental data that underpins these models. By systematically collecting, validating, and indexing these models, the PDB has accelerated structural…
Authors not listed
Proteochemometric models (PCM) are used in computational drug discovery to leverage both protein and ligand representations for bioactivity prediction. While machine learning (ML) and deep learning (DL) have come to dominate PCMs, often serving as scoring functions, rigorous evaluation standards have not always been…
Arun Shanker, Divya Bhanu, Anjani Alluri, Samriddhi Gupta
The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike…
Joseph Redshaw, Darren Ting, Alex Brown, Jonathan Hirst + 1 more
Antimicrobial peptides (AMPs) represent a potential solution to the growing problem of antimicrobial resistance, yet their identification through wet-lab experiments is a costly and timeconsuming process. Accurate computational predictions would allow rapid in silico screening of candidate AMPs, thereby accelerating…
Lim Heo, Collin Arbour, Michael Feig
Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict…
Authors not listed
Generative deep-learning models have demonstrated significant potential in designing drug-like molecules. However, medicinal chemistry typically requires generating analogues that combine structural similarity with scaffold hopping—the replacement of molecular scaffolds while retaining biological relevance. To address…
Arun Shanker, Divya Bhanu, Anajani Alluri
The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the Novel COVID-19 has emerged in China. Characterization of spike…
Babu Bassa
In this communication the author describes a software tool named "ChameleonSort". The software program, developed by the present author is useful in the sorting of biological sequence variants like those accumulating mutations while diverging from the common ancestors. Examples include viral protein variants, protein…
Victor Daniel Aldas-Bulos, Fabien Plisson
Machine learning models provide an informed and efficient strategy to create novel peptide and protein sequences with the desired profiles. Nevertheless, they are primarily trained on sequences where the tridimensional structures of peptides and proteins are often overlooked. We need a fast and reliable approach to…
Authors not listed
Pose prediction of ligands to proteins remains a central challenge of structure-based drug design. Although data leakage and generalizability concerns remain, data-driven methods for pose prediction (i.e. based on deep learning and diffusion) now routinely outperform traditional techniques such as molecular docking. In…
Theresa Ramelot, Roberto Tejero, Gaetano Montelione
Biomolecules exhibit dynamic behavior that single-state models of their structures cannot fully capture. We review some recent advances for investigating multiple conformations of biomolecules, including experimental methods, molecular dynamics simulations, and machine learning. We also address the challenges…
Authors not listed
Sequence is the critical determinant of macromolecular function, yet current polymer design approaches often optimize monomer composition and ratios while ignoring sequence. This creates poorly defined design spaces for active learning that miss the vast combinatorial landscape of sequence possibilities. We introduce…
Jérôme Eberhardt, Markus Lill, Torsten Schwede
This study introduces a novel Bayesian Optimization (BO) method to support the design and optimization of bioactive peptide sequences in the context of a fully automated closed-loop Design-Make-Test (DMT) pipeline. Using the major histocompatibility complex class I receptor system as test case, we showed that BO is…
Dominique Sydow, Eva Aßmann, Albert J. Kooistra, Friedrich Rippmann + 1 more
Protein kinases are among the most important drug targets because their dysregulation can cause cancer, inflammatory, and degenerative diseases. Developing selective inhibitors is challenging due to the highly conserved binding sites across the roughly 500 human kinases. Thus, detecting subtle similarities on a…
Authors not listed
RNA molecules fold into complex three-dimensional structures that determine their function. A wide range of mathematical frameworks, such as chord diagrams, fatgraphs, and context-free grammars, have been used to represent these structures; however, these models have largely been developed from mathematical motivations…
Judah Evangelista, Michael S. Kay
Chemical protein synthesis (CPS), in which custom peptide segments of ~20-60 aa are produced by solid-phase peptide synthesis and then stitched together through sequential ligation reactions, is an increasingly popular technique. The workflow of CPS is often depicted with a “bracket” style diagram detailing the…