Ab initio prediction is the challenging attempt to predict protein structures based only on sequence information and without using templates. It is often divided into two distinct sub-problems: (a) the scoring function that can distinguish native, ...

August 10, 2023 - If the test sequence is a whole chromosome or genome, the accuracy is invariably reduced. No current method yields good specificity/sensitivity results over entire chromosomes, where the organisms used for training are not related to the test organisms. To address this challenge, we present a new ab initio ML method that uses a NN to learn patterns of features in labeled DNA to predict DNA coding locations in unlabeled sequences.

August 22, 2025 - Ab initio protein structure prediction aims to determine 3D protein structures from amino acid sequences alone. This method relies on physics and chemistry principles to model protein folding without using existing templates, enhancing our ability to analyze and manipulate protein structures ...

May 20, 2020 - Actually, ab-initio is one of the methods to predict a protein structure, which in case not available in protein data bank (PDB) [1]. There are basically three methods to predict a protein’s structure:

August 16, 2024 - This blog will give you a brief introduction to one of the fundamental methods of Gene Prediction called Ab Initio Method.

Predicting a protein’s structure using only its amino acid sequence is called ab initio structure prediction (ab initio means “from the beginning” in Latin).

April 11, 2002 - The approaches used to predict protein structure range from comparative modeling using a homologous protein that already exists in the structural databases to ab initio folding, which results in a novel fold. In between these two extremes is the technique of threading, a method of fold recognition whereby one attempts to construct a model of the protein using as a template the structure of a protein in the PDB that has little or no obvious sequence relation to the target protein.

There are two components to ab initio prediction: devising a scoring (ie, energy) function that can distinguish between correct (native or native-like) structures from incorrect ones, and a search method to explore the conformational space. In many methods, the two components are coupled together such that a search function drives, and is driven by, the scoring function to find native-like structures.

February 15, 2011 - Background Native structures of proteins are formed essentially due to the combining effects of local and distant (in the sense of sequence) interactions among residues. These interaction information are, explicitly or implicitly, encoded into the scoring function in protein structure prediction approaches—threading approaches usually measure an alignment in the sense that how well a sequence adopts an existing structure; while the energy functions in Ab Initio methods are designed to measure how likely a conformation is near-native.

May 1, 2017 - Traditionally, methods for predicting protein loop structures are divided into two categories, knowledge-based or ab initio, depending on how they generate possible conformations (decoys). Knowledge-based methods rely upon databases of previously observed protein structure fragments.

September 16, 2022 - Depending on whether reliable structural templates are available in the PDB, protein structure prediction methods have been divided into template-based modeling (TBM) and template-free (FM) approaches, the latter of which is also called ab initio modeling [1]. For many years, TBM has been the most reliable method for modeling protein structures; however, its accuracy is essentially determined by the availability of close homologous templates and the quality of the query-template alignments.

✓ Abstraction of homologous (or analogous) structure from protein structure prediction is known as ab initio.

August 18, 2021 - Sequence-based contact prediction has shown considerable promise in assisting non-homologous structure modeling, but it often requires many homologous sequences and a sufficient number of correct contacts to achieve correct folds. Here, we developed a method, C-QUARK, that integrates multiple deep-learning and coevolution-based contact-maps to guide the replica-exchange Monte Carlo fragment assembly simulations.

algorithms and concluded that I-TASSER is about the best method in terms of the · modeling accuracy and CPU cost per target (Helles 2008). Figure 1.3a shows an · example of successful ab initio structure modeling by I-TASSER that constructed a

• Ab initio protein structure prediction methodologies based on genetic algorithms/metaheuristic searching strategies; • Development and implementation of ab initio computational modelling strategies based around specific experimental techniques; • Ab initio modelling methods using low-resolution experimental data; • Methods for (ab initio) bead modelling of proteins • Enhancement of the fragment-based ab initio protein structure assembly through the prediction of low-accuracy contact-map; • Evolutionary computation-based approaches for ab initio protein structure modelling; • Advances on methods for ab initio modelling and folding of small single-domain proteins via iterative TASSER simulations (threading/assembly/refinement); • Integrating DL and coevolution-oriented contact-maps via replica-exchange-based Monte Carlo fragment assembly simulation experiments.

Ab initio protein fold prediction methods are · usually formulated as optimization processes · Distinguished by · • by the representation of a protein and its degrees of freedom · – Restrict or not the possible position of the Ca atoms points on some ·

September 3, 2016 - Ab initio protein structure prediction uses computational methods to predict a protein's 3D structure from its amino acid sequence. It relies on conformational searching to generate structure decoys and selecting native-like models.

If structure homologues (occasionally analogues) do not exist, or exist but cannot be identified, models have to be constructed from scratch. This procedure, called ab initio modelling, is essential for a complete solution to the protein structure prediction problem; it can also help us understand the physicochemical principle of how proteins fold in nature.

January 1, 2009 - In this chapter, we give a review on the field of ab initio modelling. Focus will be put on three key factors of the modelling algorithms: energy function, conformational search, and model selection. Progresses and advances of a variety ... D.J. Rigden (ed.) From Protein Structure to Function with Bioinformatics, 3